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Mechatronics Research Lab Publications
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2020
20.
Kevin Vanslette; Abdullatif Al Alsheikh; Kamal Youcef-Toumi
Why simple quadrature is just as good as Monte Carlo Journal Article
In: Monte Carlo Methods and Applications, vol. 26, no. 1, pp. 1–16, 2020, ISSN: 1569-3961.
Abstract | Links | BibTeX | Tags: Computational Intelligence, Control Theory, Experimentation, intelligent systems, Modeling; sizing and control for smart grids, Simulation
@article{MRL_AFM_Quadrature_Monte_Carlo,
title = {Why simple quadrature is just as good as Monte Carlo},
author = {Kevin Vanslette and Abdullatif Al Alsheikh and Kamal Youcef-Toumi},
url = {http://dx.doi.org/10.1515/mcma-2020-2055},
doi = {10.1515/mcma-2020-2055},
issn = {1569-3961},
year = {2020},
date = {2020-03-01},
journal = {Monte Carlo Methods and Applications},
volume = {26},
number = {1},
pages = {1–16},
publisher = {Walter de Gruyter GmbH},
abstract = {We motive and calculate Newton–Cotes quadrature integration variance and compare it directly with Monte Carlo (MC) integration variance. We find an equivalence between deterministic quadrature sampling and random MC sampling by noting that MC random sampling is statistically indistinguishable from a method that uses deterministic sampling on a randomly shuffled (permuted) function. We use this statistical equivalence to regularize the form of permissible Bayesian quadrature integration priors such that they are guaranteed to be objectively comparable with MC. This leads to the proof that simple quadrature methods have expected variances that are less than or equal to their corresponding theoretical MC integration variances. Separately, using Bayesian probability theory, we find that the theoretical standard deviations of the unbiased errors of simple Newton–Cotes composite quadrature integrations improve over their worst case errors by an extra dimension independent factor ∝ N−1/2 This dimension independent factor is validated in our simulations.},
keywords = {Computational Intelligence, Control Theory, Experimentation, intelligent systems, Modeling; sizing and control for smart grids, Simulation},
pubstate = {published},
tppubtype = {article}
}
We motive and calculate Newton–Cotes quadrature integration variance and compare it directly with Monte Carlo (MC) integration variance. We find an equivalence between deterministic quadrature sampling and random MC sampling by noting that MC random sampling is statistically indistinguishable from a method that uses deterministic sampling on a randomly shuffled (permuted) function. We use this statistical equivalence to regularize the form of permissible Bayesian quadrature integration priors such that they are guaranteed to be objectively comparable with MC. This leads to the proof that simple quadrature methods have expected variances that are less than or equal to their corresponding theoretical MC integration variances. Separately, using Bayesian probability theory, we find that the theoretical standard deviations of the unbiased errors of simple Newton–Cotes composite quadrature integrations improve over their worst case errors by an extra dimension independent factor ∝ N−1/2 This dimension independent factor is validated in our simulations.
2019
19.
Juan Heredia; Jonathan Tirado; Vladislav Panov; Miguel Altamirano Cabrera; Kamal Youcef-Toumi; Dzmitry Tsetserukou
RecyGlide: A Forearm-Worn Multi-Modal Haptic Display Aimed to Improve User VR Immersion Submission Proceedings Article
In: 25th ACM Symposium on Virtual Reality Software and Technology, pp. 1-2, Association for Computing Machinery, 2019, ISBN: 9781450370011.
Abstract | Links | BibTeX | Tags: Computational Intelligence, Control Theory, Data-driven learning for intelligent machine maintenance, Experimentation, intelligent systems, Mechatronic Design, Simulation, Visualization
@inproceedings{MRL_AFM_VR_Multi_Modal_Display,
title = {RecyGlide: A Forearm-Worn Multi-Modal Haptic Display Aimed to Improve User VR Immersion Submission},
author = {Juan Heredia and Jonathan Tirado and Vladislav Panov and Miguel Altamirano Cabrera and Kamal Youcef-Toumi and Dzmitry Tsetserukou},
url = {https://doi.org/10.1145/3359996.3364759},
doi = {10.1145/3359996.3364759},
isbn = {9781450370011},
year = {2019},
date = {2019-11-01},
booktitle = {25th ACM Symposium on Virtual Reality Software and Technology},
pages = {1-2},
publisher = {Association for Computing Machinery},
abstract = {Haptic devices have been employed to immerse users in VR environments. In particular, hand and finger haptic devices have been deeply developed. However, this type of devices occludes hand detection for some tracking systems, or, for some other tracking systems, it is uncomfortable for the users to wear two different devices (haptic and tracking device) on both hands. We introduce RecyGlide, a novel wearable multimodal display located at the forearm. The RecyGlide is composed of inverted five-bar linkages with 2 degrees of freedom (DoF) and vibration motors (see Fig. 1.(a). The device provides multimodal tactile feedback such as slippage, force vector, pressure, and vibration. We tested the discrimination ability of monomodal and multimodal stimuli patterns on the forearm and confirmed that the multimodal patterns have higher recognition rate. This haptic device was used in VR applications, and we proved that it enhances VR experience and makes it more interactive.},
keywords = {Computational Intelligence, Control Theory, Data-driven learning for intelligent machine maintenance, Experimentation, intelligent systems, Mechatronic Design, Simulation, Visualization},
pubstate = {published},
tppubtype = {inproceedings}
}
Haptic devices have been employed to immerse users in VR environments. In particular, hand and finger haptic devices have been deeply developed. However, this type of devices occludes hand detection for some tracking systems, or, for some other tracking systems, it is uncomfortable for the users to wear two different devices (haptic and tracking device) on both hands. We introduce RecyGlide, a novel wearable multimodal display located at the forearm. The RecyGlide is composed of inverted five-bar linkages with 2 degrees of freedom (DoF) and vibration motors (see Fig. 1.(a). The device provides multimodal tactile feedback such as slippage, force vector, pressure, and vibration. We tested the discrimination ability of monomodal and multimodal stimuli patterns on the forearm and confirmed that the multimodal patterns have higher recognition rate. This haptic device was used in VR applications, and we proved that it enhances VR experience and makes it more interactive.
18.
Kevin Vanslette; Tony Tohme; Kamal Youcef-Toumi
A general model validation and testing tool Journal Article
In: Reliability Engineering & System Safety, vol. 195, pp. 106684, 2019, ISSN: 0951-8320.
Abstract | Links | BibTeX | Tags: Algorithms, Computational Intelligence, Control Theory, Experimentation, intelligent systems, Probabilistic neural networks for robust machine learning, Simulation
@article{MRL_Model_Validation_Testing,
title = {A general model validation and testing tool},
author = {Kevin Vanslette and Tony Tohme and Kamal Youcef-Toumi},
url = {https://www.sciencedirect.com/science/article/pii/S0951832019302571},
doi = {https://doi.org/10.1016/j.ress.2019.106684},
issn = {0951-8320},
year = {2019},
date = {2019-10-28},
journal = {Reliability Engineering & System Safety},
volume = {195},
pages = {106684},
publisher = {Elsevier BV},
abstract = {We construct and propose the “Bayesian Validation Metric” (BVM) as a general model validation and testing tool. We find the BVM to be capable of representing all of the standard validation metrics (square error, reliability, probability of agreement, frequentist, area, probability density comparison, statistical hypothesis testing, and Bayesian model testing) as special cases and find that it can be used to improve, generalize, or further quantify their uncertainties. Thus, the BVM allows us to assess the similarities and differences between existing validation metrics in a new light. The BVM has the capacity to allow users to invent and select models according to novel validation requirements. We formulate and test a few novel compound validation metrics that improve upon other validation metrics in the literature. Further, we construct the BVM Ratio for the purpose of quantifying model selection under user defined definitions of agreement in the presence or absence of uncertainty. This construction generalizes the Bayesian model testing framework.},
keywords = {Algorithms, Computational Intelligence, Control Theory, Experimentation, intelligent systems, Probabilistic neural networks for robust machine learning, Simulation},
pubstate = {published},
tppubtype = {article}
}
We construct and propose the “Bayesian Validation Metric” (BVM) as a general model validation and testing tool. We find the BVM to be capable of representing all of the standard validation metrics (square error, reliability, probability of agreement, frequentist, area, probability density comparison, statistical hypothesis testing, and Bayesian model testing) as special cases and find that it can be used to improve, generalize, or further quantify their uncertainties. Thus, the BVM allows us to assess the similarities and differences between existing validation metrics in a new light. The BVM has the capacity to allow users to invent and select models according to novel validation requirements. We formulate and test a few novel compound validation metrics that improve upon other validation metrics in the literature. Further, we construct the BVM Ratio for the purpose of quantifying model selection under user defined definitions of agreement in the presence or absence of uncertainty. This construction generalizes the Bayesian model testing framework.
17.
You Wu; Elizabeth Mittmann; Crystal Winston; Kamal Youcef-Toumi
A Practical Minimalism Approach to In-pipe Robot Localization Proceedings Article
In: 2019 American Control Conference (ACC), pp. 3180-3187, IEEE IEEE, 2019, ISBN: 978-1-5386-7926-5.
Abstract | Links | BibTeX | Tags: Algorithms, Computational Intelligence, Inspection; repair and intelligence for water distribution pipes, Physical System Modeling, Robotics & Automation, Simulation, Visualization
@inproceedings{MRL_WDP_Pipe_Robot_Localization,
title = {A Practical Minimalism Approach to In-pipe Robot Localization},
author = {You Wu and Elizabeth Mittmann and Crystal Winston and Kamal Youcef-Toumi},
url = {https://ieeexplore.ieee.org/document/8814648},
doi = {10.23919/ACC.2019.8814648},
isbn = {978-1-5386-7926-5},
year = {2019},
date = {2019-08-19},
booktitle = {2019 American Control Conference (ACC)},
pages = {3180-3187},
publisher = {IEEE},
organization = {IEEE},
abstract = {Water pipe leakage is a common and significant problem around the world. In recent years, an increasing amount of effort has been put into developing effective leak detection solutions for water pipes. Among them, the pressure gradient based method developed at the Massachusetts Institute of Technology excels for its sensitivity in low pressure, small diameter pipes. It can also work in both plastic and metallic pipes. However, in order for leaks detected to be fixed, one must also know the locations of the leaks. In addition, sensing the robot's location via GPS or remote sensors requires greater power and relies on certain ground properties. Thus this paper sets out to localize the robot using only the on board sensors which are an IMU, gyro, and the leak sensors. Through pipe joint measurement and the extended Kalman filter simulations show the tracking error is about 0.5% of the total distance of the robotic inspection. With a minimal number of additional leak sensors added, a complementary method was developed to function in more heavily tuberculated pipes.},
keywords = {Algorithms, Computational Intelligence, Inspection; repair and intelligence for water distribution pipes, Physical System Modeling, Robotics & Automation, Simulation, Visualization},
pubstate = {published},
tppubtype = {inproceedings}
}
Water pipe leakage is a common and significant problem around the world. In recent years, an increasing amount of effort has been put into developing effective leak detection solutions for water pipes. Among them, the pressure gradient based method developed at the Massachusetts Institute of Technology excels for its sensitivity in low pressure, small diameter pipes. It can also work in both plastic and metallic pipes. However, in order for leaks detected to be fixed, one must also know the locations of the leaks. In addition, sensing the robot's location via GPS or remote sensors requires greater power and relies on certain ground properties. Thus this paper sets out to localize the robot using only the on board sensors which are an IMU, gyro, and the leak sensors. Through pipe joint measurement and the extended Kalman filter simulations show the tracking error is about 0.5% of the total distance of the robotic inspection. With a minimal number of additional leak sensors added, a complementary method was developed to function in more heavily tuberculated pipes.
16.
Ishara Paranawithana; Zhong Hoo Chau; Liangjing Yang; Zhong Chen; Kamal Youcef-Toumi; U-Xuan Tan
Automatic Targeting of Plant Cells via Cell Segmentation and Robust Scene-Adaptive Tracking Proceedings Article
In: 2019 International Conference on Robotics and Automation (ICRA), pp. 7116-7122, IEEE IEEE, 2019, ISBN: 978-1-5386-6027-0.
Abstract | Links | BibTeX | Tags: Algorithms, Biological device for cancer cell characterization, Computational Intelligence, Experimentation, Mechatronic Design, Nanotechnology, Visualization
@inproceedings{MRL_AFM_Cell_Segment_Targeting,
title = {Automatic Targeting of Plant Cells via Cell Segmentation and Robust Scene-Adaptive Tracking},
author = {Ishara Paranawithana and Zhong Hoo Chau and Liangjing Yang and Zhong Chen and Kamal Youcef-Toumi and U-Xuan Tan},
url = {https://ieeexplore.ieee.org/document/8793944},
doi = {10.1109/ICRA.2019.8793944},
isbn = {978-1-5386-6027-0},
year = {2019},
date = {2019-08-12},
booktitle = {2019 International Conference on Robotics and Automation (ICRA)},
pages = {7116-7122},
publisher = {IEEE},
organization = {IEEE},
abstract = {Automatic targeting of plant cells to perform tasks like extraction of chloroplast is often desired in the study of plant biology. Hence, this paper proposes an improved cell segmentation method combined with a robust tracking algorithm for vision-guided micromanipulation in plant cells. The objective of this work is to develop an automatic plant cell detection and localization technique to complete the automated workflow for plant cell manipulation. The complex structural properties of plant cells make both segmentation of cells and visual tracking of the microneedle immensely challenging, unlike single animal cell applications. Thus, an improved version of watershed segmentation with adaptive thresholding is proposed to detect the plant cells without the need for staining of the cells or additional tedious preparations. To manipulate the needle to reach the identified centroid of the cells, tracking of the needle tip is required. Visual and motion information from two data sources namely, template tracking and projected manipulator trajectory are combined using score-based normalized weighted averaging to continuously track the microneedle. The selection of trackers is influenced by their complementary nature as the former and latter are individually robust against physical and visual uncertainties, respectively. Experimental results validate the effectiveness of the proposed method by detecting plant cell centroids accurately, tracking the microneedle constantly and reaching the plant cell of interest despite the presence of visual disturbances.},
keywords = {Algorithms, Biological device for cancer cell characterization, Computational Intelligence, Experimentation, Mechatronic Design, Nanotechnology, Visualization},
pubstate = {published},
tppubtype = {inproceedings}
}
Automatic targeting of plant cells to perform tasks like extraction of chloroplast is often desired in the study of plant biology. Hence, this paper proposes an improved cell segmentation method combined with a robust tracking algorithm for vision-guided micromanipulation in plant cells. The objective of this work is to develop an automatic plant cell detection and localization technique to complete the automated workflow for plant cell manipulation. The complex structural properties of plant cells make both segmentation of cells and visual tracking of the microneedle immensely challenging, unlike single animal cell applications. Thus, an improved version of watershed segmentation with adaptive thresholding is proposed to detect the plant cells without the need for staining of the cells or additional tedious preparations. To manipulate the needle to reach the identified centroid of the cells, tracking of the needle tip is required. Visual and motion information from two data sources namely, template tracking and projected manipulator trajectory are combined using score-based normalized weighted averaging to continuously track the microneedle. The selection of trackers is influenced by their complementary nature as the former and latter are individually robust against physical and visual uncertainties, respectively. Experimental results validate the effectiveness of the proposed method by detecting plant cell centroids accurately, tracking the microneedle constantly and reaching the plant cell of interest despite the presence of visual disturbances.
15.
Kevin Vanslette; Arwa Alanqari; Zeyad Al-awwad; Kamal Youcef-Toumi
Vectorized Uncertainty Propagation and Input Probability Sensitivity Analysis Journal Article
In: 2019.
Abstract | Links | BibTeX | Tags: Algorithms, Computational Intelligence, Experimentation, Uncertainty estimation and calibration for modeling
@article{MRL_AFM_Vectorized_Uncertainty_Input_Probability,
title = {Vectorized Uncertainty Propagation and Input Probability Sensitivity Analysis},
author = {Kevin Vanslette and Arwa Alanqari and Zeyad Al-awwad and Kamal Youcef-Toumi},
url = {https://arxiv.org/abs/1908.11246},
doi = {1908.11246v1},
year = {2019},
date = {2019-06-04},
publisher = {King Abdulaziz City for Science and Technology},
abstract = {In this article we construct a theoretical and computational process for assessing Input Probability Sensitivity Analysis (IPSA) using a Graphics Processing Unit (GPU) enabled technique called Vectorized Uncertainty
Propagation (VUP). VUP propagates probability distributions through
a parametric computational model in a way that’s computational time
complexity grows sublinearly in the number of distinct propagated input probability distributions. VUP can therefore be used to efficiently
implement IPSA, which estimates a model’s probabilistic sensitivity to
measurement and parametric uncertainty over each relevant measurement
location. Theory and simulation illustrate the effectiveness of these methods.},
keywords = {Algorithms, Computational Intelligence, Experimentation, Uncertainty estimation and calibration for modeling},
pubstate = {published},
tppubtype = {article}
}
In this article we construct a theoretical and computational process for assessing Input Probability Sensitivity Analysis (IPSA) using a Graphics Processing Unit (GPU) enabled technique called Vectorized Uncertainty
Propagation (VUP). VUP propagates probability distributions through
a parametric computational model in a way that’s computational time
complexity grows sublinearly in the number of distinct propagated input probability distributions. VUP can therefore be used to efficiently
implement IPSA, which estimates a model’s probabilistic sensitivity to
measurement and parametric uncertainty over each relevant measurement
location. Theory and simulation illustrate the effectiveness of these methods.
Propagation (VUP). VUP propagates probability distributions through
a parametric computational model in a way that’s computational time
complexity grows sublinearly in the number of distinct propagated input probability distributions. VUP can therefore be used to efficiently
implement IPSA, which estimates a model’s probabilistic sensitivity to
measurement and parametric uncertainty over each relevant measurement
location. Theory and simulation illustrate the effectiveness of these methods.
14.
Ali Jahanian; Quang H Le; Kamal Youcef-Toumi; Dzmitry Tsetserukou
See the E-Waste! Training Visual Intelligence to See Dense Circuit Boards for Recycling Proceedings Article
In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2019.
Abstract | Links | BibTeX | Tags: Algorithms, Automated cellphone recycling, Computational Intelligence, Experimentation, Mechatronic Design, Robotics & Automation, Visualization
@inproceedings{MRL_AFM_Training_CB_Recycling,
title = {See the E-Waste! Training Visual Intelligence to See Dense Circuit Boards for Recycling},
author = {Ali Jahanian and Quang H Le and Kamal Youcef-Toumi and Dzmitry Tsetserukou},
url = {https://openaccess.thecvf.com/content_CVPRW_2019/html/cv4gc/Jahanian_See_the_E-Waste_Training_Visual_Intelligence_to_See_Dense_Circuit_CVPRW_2019_paper.html},
year = {2019},
date = {2019-06-01},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
abstract = {The state-of-the-art semantic segmentation and object detection deep learning models are taking the leap to generalize and leverage automation, but have yet to be useful in real-world tasks such as those in dense circuit board robotic manipulation. Consider a cellphone circuit board that because of small components and a couple of hundred microns gaps between them challenges any manipulation task. For effective automation and robotics usage in manufacturing, we tackle this problem by building a convolutional neural networks optimized for multi-task learning of instance semantic segmentation and detection while accounting for crisp boundaries of small components inside dense boards. We explore the feature learning mechanism, and add the auxiliary task of boundary detection to encourage the network to learn the objects' geometric properties along with the other objectives. We examine the performance of the networks in the visual tasks (separately and all together), and the extent of generalization on the recycling phone dataset. Our network outperformed the state-of-the-art in the visual tasks while maintaining the high speed of computation. To facilitate this globally concerning topic, we provide a benchmark for Ewaste visual tasks research, and publicize our collected dataset and code, as well as demos on our in-lab robot at https://github.com/MIT-MRL/recybot. pubstate = published},
keywords = {Algorithms, Automated cellphone recycling, Computational Intelligence, Experimentation, Mechatronic Design, Robotics & Automation, Visualization},
pubstate = {published},
tppubtype = {inproceedings}
}
The state-of-the-art semantic segmentation and object detection deep learning models are taking the leap to generalize and leverage automation, but have yet to be useful in real-world tasks such as those in dense circuit board robotic manipulation. Consider a cellphone circuit board that because of small components and a couple of hundred microns gaps between them challenges any manipulation task. For effective automation and robotics usage in manufacturing, we tackle this problem by building a convolutional neural networks optimized for multi-task learning of instance semantic segmentation and detection while accounting for crisp boundaries of small components inside dense boards. We explore the feature learning mechanism, and add the auxiliary task of boundary detection to encourage the network to learn the objects' geometric properties along with the other objectives. We examine the performance of the networks in the visual tasks (separately and all together), and the extent of generalization on the recycling phone dataset. Our network outperformed the state-of-the-art in the visual tasks while maintaining the high speed of computation. To facilitate this globally concerning topic, we provide a benchmark for Ewaste visual tasks research, and publicize our collected dataset and code, as well as demos on our in-lab robot at https://github.com/MIT-MRL/recybot. pubstate = published
13.
Kai Meng; Bo Jiang; Christos D Samolis; Mohamad Alrished; Kamal Youcef-Toumi
Unevenly spaced continuous measurement approach for dual rotating--retarder Mueller matrix ellipsometry Journal Article
In: Opt. Express, vol. 27, no. 10, pp. 14736–14753, 2019, ISSN: 1094-4087.
Abstract | Links | BibTeX | Tags: Algorithms, Computational Intelligence, Intelligent optical characterization for nano-manufacturing, Nanotechnology, Physical System Modeling
@article{MRL_AFM_Dual_Rotating_Retarder_Mueller,
title = {Unevenly spaced continuous measurement approach for dual rotating--retarder Mueller matrix ellipsometry},
author = {Kai Meng and Bo Jiang and Christos D Samolis and Mohamad Alrished and Kamal Youcef-Toumi},
url = {http://www.opticsexpress.org/abstract.cfm?URI=oe-27-10-14736},
doi = {10.1364/OE.27.014736},
issn = {1094-4087},
year = {2019},
date = {2019-05-01},
journal = {Opt. Express},
volume = {27},
number = {10},
pages = {14736--14753},
publisher = {OSA},
abstract = {In order to efficiently extract the sample Mueller matrix by dual rotating–retarder ellipsometry, it is critical for the data reduction technique to achieve a minimal data processing burden while considering the ease of retarder control. In this paper, we propose an unevenly spaced sampling strategy to reach a globally optimal measurement matrix with minimum sampling points for continuous measurements. Taking into account the robustness to both systematic errors and detection noise, we develop multi-objective optimization models to identify the optimal unevenly spaced sampling points. A combined global search algorithm based on the multi-objective genetic algorithm is subsequently designed to solve our model. Finally, simulations and experiments are conducted to validate our approach as well as to provide near-optimal schemes for different design scenarios. The results demonstrate that significant improvement on error immunity performance can be achieved by applying an unevenly sampled measurement strategy compared to an evenly sampled one for our ellipsometer scenario.},
keywords = {Algorithms, Computational Intelligence, Intelligent optical characterization for nano-manufacturing, Nanotechnology, Physical System Modeling},
pubstate = {published},
tppubtype = {article}
}
In order to efficiently extract the sample Mueller matrix by dual rotating–retarder ellipsometry, it is critical for the data reduction technique to achieve a minimal data processing burden while considering the ease of retarder control. In this paper, we propose an unevenly spaced sampling strategy to reach a globally optimal measurement matrix with minimum sampling points for continuous measurements. Taking into account the robustness to both systematic errors and detection noise, we develop multi-objective optimization models to identify the optimal unevenly spaced sampling points. A combined global search algorithm based on the multi-objective genetic algorithm is subsequently designed to solve our model. Finally, simulations and experiments are conducted to validate our approach as well as to provide near-optimal schemes for different design scenarios. The results demonstrate that significant improvement on error immunity performance can be achieved by applying an unevenly sampled measurement strategy compared to an evenly sampled one for our ellipsometer scenario.
2018
12.
Lina Altoaimy; Arwa Alromih; Shiroq Al-Megren; Ghada Al-Hudhud; Heba Kurdi; Kamal Youcef-Toumi
Context-Aware Gossip-Based Protocol for Internet of Things Applications Journal Article
In: Sensors, vol. 18, no. 7, 2018, ISSN: 1424-8220.
Abstract | Links | BibTeX | Tags: Algorithms, Computational Intelligence, Data-driven learning for intelligent machine maintenance, intelligent systems
@article{MRL_AFM_Gossip_Protocal_Internet_App,
title = {Context-Aware Gossip-Based Protocol for Internet of Things Applications},
author = {Lina Altoaimy and Arwa Alromih and Shiroq Al-Megren and Ghada Al-Hudhud and Heba Kurdi and Kamal Youcef-Toumi},
url = {https://www.mdpi.com/1424-8220/18/7/2233},
doi = {10.3390/s18072233},
issn = {1424-8220},
year = {2018},
date = {2018-07-11},
journal = {Sensors},
volume = {18},
number = {7},
publisher = {MDPI},
abstract = {This paper proposes a gossip-based protocol that utilises a multi-factor weighting function (MFWF) that takes several parameters into account: residual energy, Chebyshev distances to neighbouring nodes and the sink node, node density, and message priority. The effects of these parameters were examined to guide the customization of the weight function to effectively disseminate data to three types of IoT applications: critical, bandwidth-intensive, and energy-efficient applications. The performances of the three resulting MFWFs were assessed in comparison with the performances of the traditional gossiping protocol and the Fair Efficient Location-based Gossiping (FELGossiping) protocol in terms of end-to-end delay, network lifetime, rebroadcast nodes, and saved rebroadcasts. The experimental results demonstrated the proposed protocol’s ability to achieve a much shorter delay for critical IoT applications. For bandwidth-intensive IoT application, the proposed protocol was able to achieve a smaller percentage of rebroadcast nodes and an increased percentage of saved rebroadcasts, i.e., better bandwidth utilisation. The adapted MFWF for energy-efficient IoT application was able to improve the network lifetime compared to that of gossiping and FELGossiping. These results demonstrate the high level of flexibility of the proposed protocol with respect to network context and message priority.},
keywords = {Algorithms, Computational Intelligence, Data-driven learning for intelligent machine maintenance, intelligent systems},
pubstate = {published},
tppubtype = {article}
}
This paper proposes a gossip-based protocol that utilises a multi-factor weighting function (MFWF) that takes several parameters into account: residual energy, Chebyshev distances to neighbouring nodes and the sink node, node density, and message priority. The effects of these parameters were examined to guide the customization of the weight function to effectively disseminate data to three types of IoT applications: critical, bandwidth-intensive, and energy-efficient applications. The performances of the three resulting MFWFs were assessed in comparison with the performances of the traditional gossiping protocol and the Fair Efficient Location-based Gossiping (FELGossiping) protocol in terms of end-to-end delay, network lifetime, rebroadcast nodes, and saved rebroadcasts. The experimental results demonstrated the proposed protocol’s ability to achieve a much shorter delay for critical IoT applications. For bandwidth-intensive IoT application, the proposed protocol was able to achieve a smaller percentage of rebroadcast nodes and an increased percentage of saved rebroadcasts, i.e., better bandwidth utilisation. The adapted MFWF for energy-efficient IoT application was able to improve the network lifetime compared to that of gossiping and FELGossiping. These results demonstrate the high level of flexibility of the proposed protocol with respect to network context and message priority.
11.
H Kurdi; F Ezzat; L Altoaimy; S H Ahmed; K Youcef-Toumi
MultiCuckoo: Multi-Cloud Service Composition Using a Cuckoo-Inspired Algorithm for the Internet of Things Applications Journal Article
In: IEEE Access, vol. 6, pp. 56737-56749, 2018, ISSN: 2169-3536.
Abstract | Links | BibTeX | Tags: Algorithms, Computational Intelligence, Data-driven learning for intelligent machine maintenance, intelligent systems, Mechatronic Design, Simulation
@article{MRL_AFM_MultiCuckoo,
title = {MultiCuckoo: Multi-Cloud Service Composition Using a Cuckoo-Inspired Algorithm for the Internet of Things Applications},
author = {H Kurdi and F Ezzat and L Altoaimy and S H Ahmed and K Youcef-Toumi},
url = {https://ieeexplore.ieee.org/document/8476294?denied=},
doi = {10.1109/ACCESS.2018.2872744},
issn = {2169-3536},
year = {2018},
date = {2018-01-01},
journal = {IEEE Access},
volume = {6},
pages = {56737-56749},
publisher = {IEEE},
abstract = {Internet of things (IoT) applications aim to provide access to widespread interconnected networks of smart devices, services, and information. This can be achieved by integrating IoT and cloud computing (CC). By using cloud computing service composition (SC), multiple services from various providers can be combined to meet users' requirements. However, SC is known for its complexity and is classified as an NP-hard problem; such problems are usually approached using heuristics, such as bioinspired algorithms. This paper aims at developing a bio-inspired algorithm that mimics the behavior of cuckoo birds (which examine the nests of other birds to find eggs similar to their own) to find a composite service that fulfills a user's request in a multi-cloud environment (MCE). Previous work on cuckoo-inspired algorithms has generally utilized metaheuristics, which try to fit a “good”solution to a general optimization problem. In contrast, we propose a problem-dependent heuristic that considers the SC problem and its particularities in MCE. The proposed algorithm, MultiCuckoo, was thoroughly evaluated based on a well-controlled experimental framework that benchmarks the performance of the new algorithm to other outstanding SC algorithms, including the all clouds combination algorithm, base cloud combination algorithm, and combinatorial optimization algorithm for multiple cloud service Composition. The results show that our algorithm is more efficient in terms of decreasing the number of examined services, the composed clouds, and the running time in comparison to the benchmark algorithms.},
keywords = {Algorithms, Computational Intelligence, Data-driven learning for intelligent machine maintenance, intelligent systems, Mechatronic Design, Simulation},
pubstate = {published},
tppubtype = {article}
}
Internet of things (IoT) applications aim to provide access to widespread interconnected networks of smart devices, services, and information. This can be achieved by integrating IoT and cloud computing (CC). By using cloud computing service composition (SC), multiple services from various providers can be combined to meet users' requirements. However, SC is known for its complexity and is classified as an NP-hard problem; such problems are usually approached using heuristics, such as bioinspired algorithms. This paper aims at developing a bio-inspired algorithm that mimics the behavior of cuckoo birds (which examine the nests of other birds to find eggs similar to their own) to find a composite service that fulfills a user's request in a multi-cloud environment (MCE). Previous work on cuckoo-inspired algorithms has generally utilized metaheuristics, which try to fit a “good”solution to a general optimization problem. In contrast, we propose a problem-dependent heuristic that considers the SC problem and its particularities in MCE. The proposed algorithm, MultiCuckoo, was thoroughly evaluated based on a well-controlled experimental framework that benchmarks the performance of the new algorithm to other outstanding SC algorithms, including the all clouds combination algorithm, base cloud combination algorithm, and combinatorial optimization algorithm for multiple cloud service Composition. The results show that our algorithm is more efficient in terms of decreasing the number of examined services, the composed clouds, and the running time in comparison to the benchmark algorithms.
2017
10.
Sabrina Titri; Cherif Larbes; Kamal Youcef Toumi; Karima Benatchba
A new MPPT controller based on the Ant colony optimization algorithm for Photovoltaic systems under partial shading conditions Journal Article
In: Applied Soft Computing, vol. 58, pp. 465-479, 2017, ISSN: 1568-4946.
Abstract | Links | BibTeX | Tags: Algorithms, Computational Intelligence, intelligent systems, Mechatronic Design, Probabilistic neural networks for robust machine learning, Simulation
@article{MRL_AFM_MPPT_Controller_Ants,
title = {A new MPPT controller based on the Ant colony optimization algorithm for Photovoltaic systems under partial shading conditions},
author = {Sabrina Titri and Cherif Larbes and Kamal Youcef Toumi and Karima Benatchba},
url = {https://www.sciencedirect.com/science/article/pii/S1568494617302703},
doi = {https://doi.org/10.1016/j.asoc.2017.05.017},
issn = {1568-4946},
year = {2017},
date = {2017-09-01},
journal = {Applied Soft Computing},
volume = {58},
pages = {465-479},
abstract = {The Maximum Power Point Tracking controller (MPPT) is a key element in Photovoltaic systems (PV). It is used to maintain the PV operating point at its maximum under different temperatures and sunlight irradiations. The goal of a MPPT controller is to satisfy the following performances criteria: accuracy, precision, speed, robustness and handling the partial shading problem when climatic changes variations occur. To achieve this goal, several techniques have been proposed ranging from conventional methods to artificial intelligence and bio-inspired methods. Each technique has its own advantage and disadvantage. In this context, we propose in this paper, a new Bio- inspired MPPT controller based on the Ant colony Optimization algorithm with a New Pheromone Updating strategy (ACO_NPU MPPT) that saves the computation time and performs an excellent tracking capability with high accuracy, zero oscillations and high robustness. First, the different steps of the design of the proposed ACO_NPU MPPT controller are developed. Then, several tests are performed under standard conditions for the selection of the appropriate ACO_NPU parameters (number of ants, coefficients of evaporation, archive size, etc.). To evaluate the performances of the obtained ACO_NPU MPPT, in terms of its tracking speed, accuracy, stability and robustness, tests are carried out under slow and rapid variations of weather conditions (Irradiance and Temperature) and under different partial shading patterns. Moreover, to demonstrate the superiority and robustness of the proposed ACO_NPU_MPPT controller, the obtained results are analyzed and compared with others obtained from the Conventional Methods (P&O_MPPT) and the Soft Computing Methods with Artificial intelligence (ANN_MPPT, FLC_MPPT, ANFIS_MPPT, FL_GA_MPPT) and with the Bio Inspired methods (PSO) and (ACO) from the literature. The obtained results show that the proposed ACO_NPU MPPT controller gives the best performances under variables atmospheric conditions. In addition, it can easily track the global maximum power point (GMPP) under partial shading conditions.},
keywords = {Algorithms, Computational Intelligence, intelligent systems, Mechatronic Design, Probabilistic neural networks for robust machine learning, Simulation},
pubstate = {published},
tppubtype = {article}
}
The Maximum Power Point Tracking controller (MPPT) is a key element in Photovoltaic systems (PV). It is used to maintain the PV operating point at its maximum under different temperatures and sunlight irradiations. The goal of a MPPT controller is to satisfy the following performances criteria: accuracy, precision, speed, robustness and handling the partial shading problem when climatic changes variations occur. To achieve this goal, several techniques have been proposed ranging from conventional methods to artificial intelligence and bio-inspired methods. Each technique has its own advantage and disadvantage. In this context, we propose in this paper, a new Bio- inspired MPPT controller based on the Ant colony Optimization algorithm with a New Pheromone Updating strategy (ACO_NPU MPPT) that saves the computation time and performs an excellent tracking capability with high accuracy, zero oscillations and high robustness. First, the different steps of the design of the proposed ACO_NPU MPPT controller are developed. Then, several tests are performed under standard conditions for the selection of the appropriate ACO_NPU parameters (number of ants, coefficients of evaporation, archive size, etc.). To evaluate the performances of the obtained ACO_NPU MPPT, in terms of its tracking speed, accuracy, stability and robustness, tests are carried out under slow and rapid variations of weather conditions (Irradiance and Temperature) and under different partial shading patterns. Moreover, to demonstrate the superiority and robustness of the proposed ACO_NPU_MPPT controller, the obtained results are analyzed and compared with others obtained from the Conventional Methods (P&O_MPPT) and the Soft Computing Methods with Artificial intelligence (ANN_MPPT, FLC_MPPT, ANFIS_MPPT, FL_GA_MPPT) and with the Bio Inspired methods (PSO) and (ACO) from the literature. The obtained results show that the proposed ACO_NPU MPPT controller gives the best performances under variables atmospheric conditions. In addition, it can easily track the global maximum power point (GMPP) under partial shading conditions.
2015
9.
Amith Somanath; Sertac Karaman; Kamal Youcef-Toumi
Controlling stochastic growth processes on lattices: Wildfire management with robotic fire extinguishers Proceedings Article
In: 53rd IEEE Conference on Decision and Control, pp. 1432-1437, IEEE IEEE, 2015, ISBN: 978-1-4673-6090-6.
Abstract | Links | BibTeX | Tags: Algorithms, Computational Intelligence, Computer vision for autonomous vehicle sensing, intelligent systems, Physical System Modeling, Simulation
@inproceedings{MRL_AVS_Robotic_Wildfire_Control,
title = {Controlling stochastic growth processes on lattices: Wildfire management with robotic fire extinguishers},
author = {Amith Somanath and Sertac Karaman and Kamal Youcef-Toumi},
url = {https://ieeexplore.ieee.org/document/7039602},
doi = {10.1109/CDC.2014.7039602},
isbn = {978-1-4673-6090-6},
year = {2015},
date = {2015-02-15},
booktitle = {53rd IEEE Conference on Decision and Control},
pages = {1432-1437},
publisher = {IEEE},
organization = {IEEE},
abstract = {Forest fires continue to cause considerable social and economic damage. Fortunately, the emergence of new robotics technologies, including capable autonomous unmanned aerial vehicles, may help improve wildfire management in the near future. In this paper, we characterize the number of vehicles required to combat wildfires, using a percolation-theoretic analysis that originated in the mathematical physics community. We model the wildfire as a stochastic growth process on a square lattice, where the local growth probabilities depend on the presence of robotic fire-extinguishing vehicles. We develop two control policies: First treats only a fraction of burning nodes at a given time, and the second treats burning nodes only at finite time intervals. We characterize the conditions under which these policies can stabilize a wildfire, i.e., ensure the fire stops eventually almost surely. We also provide computational results which demonstrate our theoretical analysis.},
keywords = {Algorithms, Computational Intelligence, Computer vision for autonomous vehicle sensing, intelligent systems, Physical System Modeling, Simulation},
pubstate = {published},
tppubtype = {inproceedings}
}
Forest fires continue to cause considerable social and economic damage. Fortunately, the emergence of new robotics technologies, including capable autonomous unmanned aerial vehicles, may help improve wildfire management in the near future. In this paper, we characterize the number of vehicles required to combat wildfires, using a percolation-theoretic analysis that originated in the mathematical physics community. We model the wildfire as a stochastic growth process on a square lattice, where the local growth probabilities depend on the presence of robotic fire-extinguishing vehicles. We develop two control policies: First treats only a fraction of burning nodes at a given time, and the second treats burning nodes only at finite time intervals. We characterize the conditions under which these policies can stabilize a wildfire, i.e., ensure the fire stops eventually almost surely. We also provide computational results which demonstrate our theoretical analysis.
2014
8.
Apoorva Santhosh; Amro Farid; Kamal Youcef-Toumi
Real-time economic dispatch for the supply side of the energy-water nexus Journal Article
In: Applied Energy, vol. 122, pp. 42–52, 2014.
Abstract | Links | BibTeX | Tags: Algorithms, Computational Intelligence, Control Theory, Data-driven learning for intelligent machine maintenance, intelligent systems, Simulation
@article{MRL_AFM_Economic_Energy_Water_Nexus,
title = {Real-time economic dispatch for the supply side of the energy-water nexus},
author = {Apoorva Santhosh and Amro Farid and Kamal Youcef-Toumi},
doi = {10.1016/j.apenergy.2014.01.062},
year = {2014},
date = {2014-06-01},
journal = {Applied Energy},
volume = {122},
pages = {42–52},
publisher = {researchgate},
abstract = {Clean energy and water are two essential resources that any society must securely deliver. Their usage raises sustainability issues and questions of nations’ resilience in face of global changes and mega-trends such as population growth, global climate change, and economic growth. Traditionally, the infrastructure systems that deliver these precious commodities, the water distribution and power transmission networks are thought of as separate, uncoupled systems. However, in reality, they are very much coupled in what is commonly known as the energy-water nexus. Although this subject has recently caught the attention of numerous policy and regulatory agencies, rarely is it holistically addressed in terms of an integrated engineering system for its management, planning, and regulation as an interdisciplinary concern. This work specifically fills this gap by addressing the supply side of this integrated engineering system. Specifically, it develops the multi-plant real-time simultaneous economic dispatch of power and water. While significant background literature has addressed traditional power dispatch, and the emerging co-dispatch of power and heat, as of now there does not exist a parameterized model for the optimized dispatch of power and water for multiple power, water, and coproduction facilities. The work presents such a model where production costs are minimized subject to capacity, demand and process constraints. It is demonstrated on an illustrative example of modest size. Interesting results were observed suggesting that the coproduction minimum capacity limits and process constraints can lead to scenarios where cheaper single product plants can be crowded out of the dispatch. The program provides a systematic method of achieving optimal results and can serve as a basis for set-points upon which individual plants can implement their optimal control. In so doing, it makes a supply-side contribution to the ongoing grand-challenge of improving the sustainability of the energy-water nexus.},
keywords = {Algorithms, Computational Intelligence, Control Theory, Data-driven learning for intelligent machine maintenance, intelligent systems, Simulation},
pubstate = {published},
tppubtype = {article}
}
Clean energy and water are two essential resources that any society must securely deliver. Their usage raises sustainability issues and questions of nations’ resilience in face of global changes and mega-trends such as population growth, global climate change, and economic growth. Traditionally, the infrastructure systems that deliver these precious commodities, the water distribution and power transmission networks are thought of as separate, uncoupled systems. However, in reality, they are very much coupled in what is commonly known as the energy-water nexus. Although this subject has recently caught the attention of numerous policy and regulatory agencies, rarely is it holistically addressed in terms of an integrated engineering system for its management, planning, and regulation as an interdisciplinary concern. This work specifically fills this gap by addressing the supply side of this integrated engineering system. Specifically, it develops the multi-plant real-time simultaneous economic dispatch of power and water. While significant background literature has addressed traditional power dispatch, and the emerging co-dispatch of power and heat, as of now there does not exist a parameterized model for the optimized dispatch of power and water for multiple power, water, and coproduction facilities. The work presents such a model where production costs are minimized subject to capacity, demand and process constraints. It is demonstrated on an illustrative example of modest size. Interesting results were observed suggesting that the coproduction minimum capacity limits and process constraints can lead to scenarios where cheaper single product plants can be crowded out of the dispatch. The program provides a systematic method of achieving optimal results and can serve as a basis for set-points upon which individual plants can implement their optimal control. In so doing, it makes a supply-side contribution to the ongoing grand-challenge of improving the sustainability of the energy-water nexus.
7.
Sergio Rivera; Amro M Farid; Kamal Youcef-Toumi
A multi-agent system transient stability platform for resilient self-healing operation of multiple microgrids Proceedings Article
In: ISGT 2014, pp. 1-5, IEEE IEEE, 2014, ISBN: 978-1-4799-3653-3.
Abstract | Links | BibTeX | Tags: Computational Intelligence, intelligent systems, Modeling; Systems and Control of Smart Grids, Physical System Modeling, Simulation, Visualization
@inproceedings{MRL_SG_Multi_Agent_Micro_Grid,
title = {A multi-agent system transient stability platform for resilient self-healing operation of multiple microgrids},
author = {Sergio Rivera and Amro M Farid and Kamal Youcef-Toumi},
url = {https://ieeexplore.ieee.org/document/6816377},
doi = {10.1109/ISGT.2014.6816377},
isbn = {978-1-4799-3653-3},
year = {2014},
date = {2014-05-19},
booktitle = {ISGT 2014},
pages = {1-5},
publisher = {IEEE},
organization = {IEEE},
abstract = {This paper proposes a multi-agent transient stability platform for the study of self-operation of multiple microgrids. This platform combines a MATLAB-based time domain simulation of the grid's transient stability with a JAVA-JADE (JAVA Agent DEvelopment Framework) which supports the development of multi-agent systems that utilize distributed artificial intelligence techniques that support simultaneous, geographically-distributed, and coordinated decision-making techniques. This hybrid platform leverages the numerical strengths of MATLAB with JAVA's multi-threaded decision-making capability. To that effect, the platform was tested on two complementary test cases: one to demonstrate a dynamic reconfiguration capability and another to demonstrate the decentralized dispatch of multiple microgrids. The work presents many opportunities for future developments in the domain of resilient self-healing operation of power grids.},
keywords = {Computational Intelligence, intelligent systems, Modeling; Systems and Control of Smart Grids, Physical System Modeling, Simulation, Visualization},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper proposes a multi-agent transient stability platform for the study of self-operation of multiple microgrids. This platform combines a MATLAB-based time domain simulation of the grid's transient stability with a JAVA-JADE (JAVA Agent DEvelopment Framework) which supports the development of multi-agent systems that utilize distributed artificial intelligence techniques that support simultaneous, geographically-distributed, and coordinated decision-making techniques. This hybrid platform leverages the numerical strengths of MATLAB with JAVA's multi-threaded decision-making capability. To that effect, the platform was tested on two complementary test cases: one to demonstrate a dynamic reconfiguration capability and another to demonstrate the decentralized dispatch of multiple microgrids. The work presents many opportunities for future developments in the domain of resilient self-healing operation of power grids.
2013
6.
Apoorva Santhosh; Amro M Farid; Kamal Youcef-Toumi
Design and Evaluation of an In-Pipe Leak Detection Sensing Technique Based on Force Transduction Proceedings Article
In: ASME 2012 International Mechanical Engineering Congress and Exposition, IEEE IEEE, 2013, ISBN: 978-0-7918-4520-2.
Abstract | Links | BibTeX | Tags: Algorithms, Computational Intelligence, Inspection; repair and intelligence for water distribution pipes, Physical System Modeling, Robotics & Automation, Simulation, Visualization
@inproceedings{MRL_WDP_Force_Transduction_Leaking,
title = {Design and Evaluation of an In-Pipe Leak Detection Sensing Technique Based on Force Transduction},
author = {Apoorva Santhosh and Amro M Farid and Kamal Youcef-Toumi},
url = {https://asmedigitalcollection.asme.org/IMECE/proceedings/IMECE2012/45202/489/254570},
doi = {10.1115/IMECE2012-87493},
isbn = {978-0-7918-4520-2},
year = {2013},
date = {2013-10-08},
booktitle = {ASME 2012 International Mechanical Engineering Congress and Exposition},
publisher = {IEEE},
organization = {IEEE},
abstract = {Leakage is the major factor for unaccounted fluid losses in almost every pipe network. In most cases the deleterious effects associated with the occurrence of leaks may present serious economical and health problems and therefore, leaks must be quickly detected, located and repaired. The problem of leakage becomes even more serious when it is concerned with the vital supply of fresh water to the community. Leaking water pipelines can develop large health threats to people mostly because of the infiltration of contaminants into the water network. Such possibilities of environmental health disasters have spurred research into the development of methods for pipeline leakage detection. Most state of the art leak detection techniques have limited applicability, while some of them are not reliable enough and sometimes depend on user experience. Our goal in this work is to design and develop a reliable leak detection sensing system. The proposed technology utilizes the highly localized pressure gradient in the vicinity of a small opening due to leakage in a pressurized pipeline. In this paper we study this local phenomenon in detail and try to understand it with the help of numerical simulations in leaking pipelines (CFD studies). Finally a new system for leak detection is presented. The proposed system is designed in order to reduce the number of sensing elements required for detection. The main concept and detailed design are laid out. A prototype is fabricated and presented as a proof of concept. The prototype is tested in a simple experimental setup with artificial leakages for experimental evaluation. The sensing technique discussed in this work can be deployed in water, oil and gas pipelines without significant changes in the design, since the concepts remain the same in all cases.},
keywords = {Algorithms, Computational Intelligence, Inspection; repair and intelligence for water distribution pipes, Physical System Modeling, Robotics & Automation, Simulation, Visualization},
pubstate = {published},
tppubtype = {inproceedings}
}
Leakage is the major factor for unaccounted fluid losses in almost every pipe network. In most cases the deleterious effects associated with the occurrence of leaks may present serious economical and health problems and therefore, leaks must be quickly detected, located and repaired. The problem of leakage becomes even more serious when it is concerned with the vital supply of fresh water to the community. Leaking water pipelines can develop large health threats to people mostly because of the infiltration of contaminants into the water network. Such possibilities of environmental health disasters have spurred research into the development of methods for pipeline leakage detection. Most state of the art leak detection techniques have limited applicability, while some of them are not reliable enough and sometimes depend on user experience. Our goal in this work is to design and develop a reliable leak detection sensing system. The proposed technology utilizes the highly localized pressure gradient in the vicinity of a small opening due to leakage in a pressurized pipeline. In this paper we study this local phenomenon in detail and try to understand it with the help of numerical simulations in leaking pipelines (CFD studies). Finally a new system for leak detection is presented. The proposed system is designed in order to reduce the number of sensing elements required for detection. The main concept and detailed design are laid out. A prototype is fabricated and presented as a proof of concept. The prototype is tested in a simple experimental setup with artificial leakages for experimental evaluation. The sensing technique discussed in this work can be deployed in water, oil and gas pipelines without significant changes in the design, since the concepts remain the same in all cases.
2012
5.
Atia E Khalifa; Rached Ben-Mansour; Kamal Youcef-Toumi; Changrak Choi
Characterization of In-Pipe Acoustic Wave for Water Leak Detection Proceedings Article
In: ASME 2011 International Mechanical Engineering Congress and Exposition, pp. 995-1000, ACC ACC, 2012, ISBN: 978-0-7918-5494-5.
Abstract | Links | BibTeX | Tags: Algorithms, Computational Intelligence, Inspection; repair and intelligence for water distribution pipes, Physical System Modeling, Robotics & Automation, Simulation, Visualization
@inproceedings{MRL_WDP_Acoustic_Wave_Pipe_Leakage,
title = {Characterization of In-Pipe Acoustic Wave for Water Leak Detection},
author = {Atia E Khalifa and Rached Ben-Mansour and Kamal Youcef-Toumi and Changrak Choi},
url = {https://asmedigitalcollection.asme.org/IMECE/proceedings/IMECE2011/54945/995/355499},
doi = {10.1115/IMECE2011-62333},
isbn = {978-0-7918-5494-5},
year = {2012},
date = {2012-08-01},
booktitle = {ASME 2011 International Mechanical Engineering Congress and Exposition},
pages = {995-1000},
publisher = {ACC},
organization = {ACC},
abstract = {This paper presents experimental observations on the characteristics of the acoustic signal propagation and attenuation inside water-filled pipes. An acoustic source (exciter) is mounted on the internal pipe wall, at a fixed location, and produces a tonal sound to simulate a leak noise with controlled frequency and amplitude, under different flow conditions. A hydrophone is aligned with the pipe centerline and can be re-positioned to capture the acoustic signal at different locations. Results showed that the wave attenuation depends on the source frequency and the line pressure. High frequency signals get attenuated more with increasing distance from the source. The optimum location to place the hydrophone for capturing the acoustic signal is not at the vicinity of source location. The optimum location also depends on the frequency and line pressure. It was also observed that the attenuation of the acoustic waves is higher in more flexible pipes like PVC ones.},
keywords = {Algorithms, Computational Intelligence, Inspection; repair and intelligence for water distribution pipes, Physical System Modeling, Robotics & Automation, Simulation, Visualization},
pubstate = {published},
tppubtype = {inproceedings}
}
This paper presents experimental observations on the characteristics of the acoustic signal propagation and attenuation inside water-filled pipes. An acoustic source (exciter) is mounted on the internal pipe wall, at a fixed location, and produces a tonal sound to simulate a leak noise with controlled frequency and amplitude, under different flow conditions. A hydrophone is aligned with the pipe centerline and can be re-positioned to capture the acoustic signal at different locations. Results showed that the wave attenuation depends on the source frequency and the line pressure. High frequency signals get attenuated more with increasing distance from the source. The optimum location to place the hydrophone for capturing the acoustic signal is not at the vicinity of source location. The optimum location also depends on the frequency and line pressure. It was also observed that the attenuation of the acoustic waves is higher in more flexible pipes like PVC ones.
4.
Dimitris M Chatzigeorgiou; Atia E Khalifa; Kamal Youcef-Toumi; Rached Ben-Mansour
An In-Pipe Leak Detection Sensor: Sensing Capabilities and Evaluation Proceedings Article
In: ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, pp. 481-489, ACC ACC, 2012, ISBN: 978-0-7918-5480-8.
Abstract | Links | BibTeX | Tags: Algorithms, Computational Intelligence, Inspection; repair and intelligence for water distribution pipes, Physical System Modeling, Robotics & Automation, Simulation, Visualization
@inproceedings{MRL_WDP_Leak_Capability_Sensor,
title = {An In-Pipe Leak Detection Sensor: Sensing Capabilities and Evaluation},
author = {Dimitris M Chatzigeorgiou and Atia E Khalifa and Kamal Youcef-Toumi and Rached Ben-Mansour},
url = {https://asmedigitalcollection.asme.org/IDETC-CIE/proceedings/IDETC-CIE2011/54808/481/351961},
doi = {10.1115/DETC2011-48411},
isbn = {978-0-7918-5480-8},
year = {2012},
date = {2012-06-12},
booktitle = {ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference},
pages = {481-489},
publisher = {ACC},
organization = {ACC},
abstract = {In most cases the deleterious effects associated with the occurrence of leak may present serious problems and therefore leaks must be quickly detected, located and repaired. The problem of leakage becomes even more serious when it is concerned with the vital supply of fresh water to the community. In addition to waste of resources, contaminants may infiltrate into the water supply. The possibility of environmental health disasters due to delay in detection of water pipeline leaks has spurred research into the development of methods for pipeline leak and contamination detection. Leaks in water pipes create acoustic emissions, which can be sensed to identify and localize leaks. Leak noise correlators and listening devices have been reported in the literature as successful approaches to leak detection but they have practical limitations in terms of cost, sensitivity, reliability and scalability. To overcome those limitations the development of an in-pipe traveling leak detection system is proposed. The development of such a system requires a clear understanding of acoustic signals generated from leaks and the study of the variation of those signals with different pipe loading conditions, leak sizes and surrounding media. This paper discusses those signals and evaluates the merits of an in-pipe-floating sensor.},
keywords = {Algorithms, Computational Intelligence, Inspection; repair and intelligence for water distribution pipes, Physical System Modeling, Robotics & Automation, Simulation, Visualization},
pubstate = {published},
tppubtype = {inproceedings}
}
In most cases the deleterious effects associated with the occurrence of leak may present serious problems and therefore leaks must be quickly detected, located and repaired. The problem of leakage becomes even more serious when it is concerned with the vital supply of fresh water to the community. In addition to waste of resources, contaminants may infiltrate into the water supply. The possibility of environmental health disasters due to delay in detection of water pipeline leaks has spurred research into the development of methods for pipeline leak and contamination detection. Leaks in water pipes create acoustic emissions, which can be sensed to identify and localize leaks. Leak noise correlators and listening devices have been reported in the literature as successful approaches to leak detection but they have practical limitations in terms of cost, sensitivity, reliability and scalability. To overcome those limitations the development of an in-pipe traveling leak detection system is proposed. The development of such a system requires a clear understanding of acoustic signals generated from leaks and the study of the variation of those signals with different pipe loading conditions, leak sizes and surrounding media. This paper discusses those signals and evaluates the merits of an in-pipe-floating sensor.
3.
Dimitris M Chatzigeorgiou; Kamal Youcef-Toumi; Atia E Khalifa; Rached Ben-Mansour
Analysis and Design of an In-Pipe System for Water Leak Detection Proceedings Article
In: ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, pp. 1007-1016, ASME ASME, 2012, ISBN: 978-0-7918-5482-2.
Abstract | Links | BibTeX | Tags: Algorithms, Computational Intelligence, Inspection; repair and intelligence for water distribution pipes, Physical System Modeling, Robotics & Automation, Simulation, Visualization
@inproceedings{MRL_WDP_Design_Water_Leak_Detection,
title = {Analysis and Design of an In-Pipe System for Water Leak Detection},
author = {Dimitris M Chatzigeorgiou and Kamal Youcef-Toumi and Atia E Khalifa and Rached Ben-Mansour},
url = {https://asmedigitalcollection.asme.org/IDETC-CIE/proceedings/IDETC-CIE2011/54822/1007/353866},
doi = {10.1115/DETC2011-48395},
isbn = {978-0-7918-5482-2},
year = {2012},
date = {2012-06-12},
booktitle = {ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference},
pages = {1007-1016},
publisher = {ASME},
organization = {ASME},
abstract = {In most cases the deleterious effects associated with the occurrence of leaks may present serious problems and therefore, leaks must be quickly detected, located and repaired. The problem of leakage becomes even more serious when it is concerned with the vital supply of fresh water to the community. In addition to waste of resources, contaminants may infiltrate into the water supply. The possibility of environmental health disasters due to delay in detection of water pipeline leaks has spurred research into the development of methods for pipeline leak and contamination detection. Leaking in water networks has been a very significant problem worldwide, especially in developing countries, where water is sparse. Many different techniques have been developed to detect leaks, either from the inside or from the outside of the pipe; each one of them with their advantages, complexities but also limitations. To overcome those limitations we focus our work on the development of an in-pipe-floating sensor. The present paper discusses the design considerations of a novel autonomous system for in-pipe water leak detection. The system is carefully designed to be minimally invasive to the flow within the pipe and thus not to affect the delicate leak signal. One of its characteristics is the controllable motion inside the pipe. The system is capable of pinpointing leaks in pipes while operating in real network conditions, i.e. pressurized pipes and high water flow rates, which are major challenges.},
keywords = {Algorithms, Computational Intelligence, Inspection; repair and intelligence for water distribution pipes, Physical System Modeling, Robotics & Automation, Simulation, Visualization},
pubstate = {published},
tppubtype = {inproceedings}
}
In most cases the deleterious effects associated with the occurrence of leaks may present serious problems and therefore, leaks must be quickly detected, located and repaired. The problem of leakage becomes even more serious when it is concerned with the vital supply of fresh water to the community. In addition to waste of resources, contaminants may infiltrate into the water supply. The possibility of environmental health disasters due to delay in detection of water pipeline leaks has spurred research into the development of methods for pipeline leak and contamination detection. Leaking in water networks has been a very significant problem worldwide, especially in developing countries, where water is sparse. Many different techniques have been developed to detect leaks, either from the inside or from the outside of the pipe; each one of them with their advantages, complexities but also limitations. To overcome those limitations we focus our work on the development of an in-pipe-floating sensor. The present paper discusses the design considerations of a novel autonomous system for in-pipe water leak detection. The system is carefully designed to be minimally invasive to the flow within the pipe and thus not to affect the delicate leak signal. One of its characteristics is the controllable motion inside the pipe. The system is capable of pinpointing leaks in pipes while operating in real network conditions, i.e. pressurized pipes and high water flow rates, which are major challenges.
2010
2.
Dimitris M Chatzigeorgiou; Sumeet Kumar; Atia E Khalifa; Ajay Deshpande; Kamal Youcef-Toumi; Sanjay Sarma; Rached Ben-Mansour
In-pipe Acoustic Characterization of Leak Signals in Plastic Water-filled Pipes Proceedings Article
In: AWWA Annual Conference and Exposition (ACE) 2010, AWWA AWWA, 2010.
Abstract | Links | BibTeX | Tags: Algorithms, Computational Intelligence, Inspection; repair and intelligence for water distribution pipes, Physical System Modeling, Robotics & Automation, Simulation, Visualization
@inproceedings{MRL_WDP_Acoustic_Leak_Signals,
title = {In-pipe Acoustic Characterization of Leak Signals in Plastic Water-filled Pipes},
author = {Dimitris M Chatzigeorgiou and Sumeet Kumar and Atia E Khalifa and Ajay Deshpande and Kamal Youcef-Toumi and Sanjay Sarma and Rached Ben-Mansour},
url = {https://www.researchgate.net/publication/277303127_In-pipe_Acoustic_Characterization_of_Leak_Signals_in_Plastic_Water-filled_Pipes},
year = {2010},
date = {2010-01-01},
booktitle = {AWWA Annual Conference and Exposition (ACE) 2010},
publisher = {AWWA},
organization = {AWWA},
abstract = {Acoustic emissions can be sensed to identify and localize leaks in water pipes. Leak noise correlators and listening devices have been reported in literature as successful approaches to leak detection but they have practical limitations in terms of cost, sensitivity, reliability and scalability. A possible efficient solution is the development of an in-pipe traveling leak detection system. It has been reported that in-pipe sensing is more accurate and efficient since the sensing element can be very close to the sound source. Currently in-pipe approaches are limited to large leaks and larger diameter pipes. Development of such a system requires clear understanding of acoustic signals generated from leaks and their variation with different pipe loading conditions, leak sizes and surrounding media. This paper discusses the acoustic characterization of leak signals in controlled environments. A lab experimental setup was designed and built in which measurements were taken from inside 4 inch PVC water pipes using a hydrophone. Signals were collected for a wide range of conditions: different pressures and leak flow rates to better understand the leak signal signatures. Experiments were conducted with different pipe connecting elements like valves and junctions, and different external conditions such as pipes placed in water, air and soil. Signals were collected at various distances from the leak location (upstream and downstream) to understand the opportunities of spatial cross-correlation techniques in localizing leaks and the effect of sensor position on the signal. Characterizations of different datasets are presented in frequency domain. The implications of acoustic characterization on the design of algorithms for leak detection are discussed and a simple algorithm to decide whether or not a leak is present near the sensor location is proposed, based on signal power calculations. The characterization gives insights, which will pave ways for the development of smart, autonomous pipe-traversing systems capable of detecting and localizing leaks on a city level water distribution network.},
keywords = {Algorithms, Computational Intelligence, Inspection; repair and intelligence for water distribution pipes, Physical System Modeling, Robotics & Automation, Simulation, Visualization},
pubstate = {published},
tppubtype = {inproceedings}
}
Acoustic emissions can be sensed to identify and localize leaks in water pipes. Leak noise correlators and listening devices have been reported in literature as successful approaches to leak detection but they have practical limitations in terms of cost, sensitivity, reliability and scalability. A possible efficient solution is the development of an in-pipe traveling leak detection system. It has been reported that in-pipe sensing is more accurate and efficient since the sensing element can be very close to the sound source. Currently in-pipe approaches are limited to large leaks and larger diameter pipes. Development of such a system requires clear understanding of acoustic signals generated from leaks and their variation with different pipe loading conditions, leak sizes and surrounding media. This paper discusses the acoustic characterization of leak signals in controlled environments. A lab experimental setup was designed and built in which measurements were taken from inside 4 inch PVC water pipes using a hydrophone. Signals were collected for a wide range of conditions: different pressures and leak flow rates to better understand the leak signal signatures. Experiments were conducted with different pipe connecting elements like valves and junctions, and different external conditions such as pipes placed in water, air and soil. Signals were collected at various distances from the leak location (upstream and downstream) to understand the opportunities of spatial cross-correlation techniques in localizing leaks and the effect of sensor position on the signal. Characterizations of different datasets are presented in frequency domain. The implications of acoustic characterization on the design of algorithms for leak detection are discussed and a simple algorithm to decide whether or not a leak is present near the sensor location is proposed, based on signal power calculations. The characterization gives insights, which will pave ways for the development of smart, autonomous pipe-traversing systems capable of detecting and localizing leaks on a city level water distribution network.
1979
1.
Aramazd Muzhikyan; Amro M Farid; Kamal Youcef-Toumi
An a priori analytical method for the determination of operating reserve requirements Journal Article
In: International Journal of Electrical Power & Energy Systems, vol. 86, pp. 1-17, 1979, ISSN: 0142-0615.
Abstract | Links | BibTeX | Tags: Algorithms, Computational Intelligence, intelligent systems, Physical System Modeling, Simulation, Uncertainty estimation and calibration for modeling
@article{MRL_AFM_Priori_Operating_Requirements,
title = {An a priori analytical method for the determination of operating reserve requirements},
author = {Aramazd Muzhikyan and Amro M Farid and Kamal Youcef-Toumi},
url = {https://www.sciencedirect.com/science/article/pii/S0142061515300089},
doi = {https://doi.org/10.1016/j.ijepes.2016.09.005},
issn = {0142-0615},
year = {1979},
date = {1979-04-01},
journal = {International Journal of Electrical Power & Energy Systems},
volume = {86},
pages = {1-17},
publisher = {ScienceDirect},
abstract = {Power balance is one of the key requirements for reliable power system operation. However, factors, such as net load variability and forecast errors, impose practical limitations on matching the scheduled generation and the real-time demand. Normally, potential power imbalances are mitigated by scheduling additional generation capacity called operating reserves. However, reserves are a costly commodity and their requirements should be accurately assessed to avoid unnecessary expense. Currently, the reserve requirements are determined using a posteriori methods based upon operator’s experience and established assumptions. While these assumptions are made out of a level of engineering practicality, they may not be formally true given the numerical evidence. This paper presents a formal mathematical framework for the a priori determination of three types of operating reserve requirements, namely load following, ramping and regulation. Validation of the methodology is performed by a set of extensive simulations that model the power system operations for different scenarios. This methodology is used to study the sensitivity of each type of reserve requirement to the net load and power system parameters.},
keywords = {Algorithms, Computational Intelligence, intelligent systems, Physical System Modeling, Simulation, Uncertainty estimation and calibration for modeling},
pubstate = {published},
tppubtype = {article}
}
Power balance is one of the key requirements for reliable power system operation. However, factors, such as net load variability and forecast errors, impose practical limitations on matching the scheduled generation and the real-time demand. Normally, potential power imbalances are mitigated by scheduling additional generation capacity called operating reserves. However, reserves are a costly commodity and their requirements should be accurately assessed to avoid unnecessary expense. Currently, the reserve requirements are determined using a posteriori methods based upon operator’s experience and established assumptions. While these assumptions are made out of a level of engineering practicality, they may not be formally true given the numerical evidence. This paper presents a formal mathematical framework for the a priori determination of three types of operating reserve requirements, namely load following, ramping and regulation. Validation of the methodology is performed by a set of extensive simulations that model the power system operations for different scenarios. This methodology is used to study the sensitivity of each type of reserve requirement to the net load and power system parameters.