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Proceedings Papers

Assessment of State of Charge Estimation Methods Based on Neural Networks and Support Vector Machine for Lithium-Ion Batteries Used in Vehicular Applications

Sara Luciani, Stefano Feraco, Mario Silvagni, Angelo Bonfitto, Nicola Amati, Andrea Tonoli

Proc. ASME. IDETC-CIE2022, Volume 1: 24th International Conference on Advanced Vehicle Technologies (AVT), V001T01A014, August 14–17, 2022

Paper No: DETC2022-89454

DOI: https://doi.org/10.1115/DETC2022-89454

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Topics: Artificial intelligence, Artificial neural networks, Lithium-ion batteries, Support vector machines

Proceedings Papers

A Constraint-Handling Technique for Parametric Optimization and Control Co-Design

Ying-Kuan Tsai, Richard J. Malak, Jr.

Proc. ASME. IDETC-CIE2022, Volume 3A: 48th Design Automation Conference (DAC), V03AT03A009, August 14–17, 2022

Paper No: DETC2022-89957

DOI: https://doi.org/10.1115/DETC2022-89957

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Topics: Design, Optimization, Genetic algorithms, Pendulums, Support vector machines, Algorithms, Control equipment, Control systems, Dynamics (Mechanics), Machine learning

Proceedings Papers

A Study of Machine Learning Framework for Enabling Early Defect Detection in Wire Arc Additive Manufacturing Processes

Nowrin Akter Surovi, Shaista Hussain, Gim Song Soh

Proc. ASME. IDETC-CIE2022, Volume 3A: 48th Design Automation Conference (DAC), V03AT03A002, August 14–17, 2022

Paper No: DETC2022-89164

DOI: https://doi.org/10.1115/DETC2022-89164

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Topics: Additive manufacturing, Flaw detection, Machine learning, Wire, Acoustics, Printing, Support vector machines, Pressure

Proceedings Papers

A Multi-Fidelity Approach for Reliability Assessment Based on the Probability of Model Inconsistency

Bharath Pidaparthi, Samy Missoum

Proc. ASME. IDETC-CIE2022, Volume 3B: 48th Design Automation Conference (DAC), V03BT03A030, August 14–17, 2022

Paper No: DETC2022-90115

DOI: https://doi.org/10.1115/DETC2022-90115

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Topics: Failure, Heat exchangers, Probability, Reliability, Support vector machines

Proceedings Papers

Gait Prediction and Mechanism Design for 1-DOF Lower Limb Rehabilitation Devices Based on Machine Learning

Wanbing Song, Yating Zhang, Zhaojie Ge, Ping Zhao

Proc. ASME. IDETC-CIE2021, Volume 8A: 45th Mechanisms and Robotics Conference (MR), V08AT08A045, August 17–19, 2021

Paper No: DETC2021-70009

DOI: https://doi.org/10.1115/DETC2021-70009

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Topics: Design, Machine learning, Patient rehabilitation, Rehabilitation devices, Trajectories (Physics), Algorithms, Machinery, Shapes, Support vector machines, Trains

Proceedings Papers

Towards Transparent Motion Planning of Wearable Rehabilitation Exoskeletons via Model-Based Estimation

Jiamin Wang, David Blankenship, Oumar Barry

Proc. ASME. IDETC-CIE2021, Volume 9: 17th International Conference on Multibody Systems, Nonlinear Dynamics, and Control (MSNDC), V009T09A030, August 17–19, 2021

Paper No: DETC2021-70011

DOI: https://doi.org/10.1115/DETC2021-70011

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Topics: Exoskeleton devices, Path planning, Transparency, Algorithms, Delays, Optimization, Signals, Stress, Control equipment, Design

Proceedings Papers

Dimensional Prediction for FDM Machines Using Artificial Neural Network and Support Vector Regression

Jiaqi Lyu, Souran Manoochehri

Proc. ASME. IDETC-CIE2019, Volume 1: 39th Computers and Information in Engineering Conference, V001T02A033, August 18–21, 2019

Paper No: DETC2019-97963

DOI: https://doi.org/10.1115/DETC2019-97963

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Topics: Artificial neural networks, Machinery, Modeling, Support vector machines

Proceedings Papers

Exploiting Multi-Modal Sensing for Increased Detection Fidelity of Pipeline Leakage

Apeksha Lanjile, Mohamed Younis, Seung-Jun Kim, Soobum Lee

Proc. ASME. IDETC-CIE2019, Volume 2B: 45th Design Automation Conference, V02BT03A017, August 18–21, 2019

Paper No: DETC2019-97553

DOI: https://doi.org/10.1115/DETC2019-97553

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Topics: Leakage, Pipelines, Acoustics, Pipes, Sensors, Accelerometers, Corrosion, Cracking (Materials), Damage, Fluids

Proceedings Papers

Human Computer Interface Using Electroencephalography for Driver Behavior Classification

Vamsi K. Manchala, Alvaro V. Clara, Susheelkumar C. Subramanian, Sangram Redkar, Thomas Sugar

Proc. ASME. IDETC-CIE2019, Volume 3: 21st International Conference on Advanced Vehicle Technologies; 16th International Conference on Design Education, V003T01A014, August 18–21, 2019

Paper No: DETC2019-97540

DOI: https://doi.org/10.1115/DETC2019-97540

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Topics: Electroencephalography, User interfaces, Vehicles, Artificial neural networks, Machine learning, Support vector machines, Brain, Computers

Proceedings Papers

Predicting Multi-Disciplinary Design Performance Utilizing Automated Topic Discovery

Zachary Ball, Kemper Lewis

Proc. ASME. IDETC-CIE2019, Volume 7: 31st International Conference on Design Theory and Methodology, V007T06A053, August 18–21, 2019

Paper No: DETC2019-97189

DOI: https://doi.org/10.1115/DETC2019-97189

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Topics: Design, Algorithms, Engineering design, Collaboration, Competencies, Engineering design processes, Engineering disciplines, Students, Support vector machines, Teams

Proceedings Papers

A Multi-Objective Robust Optimization Approach Under Interval Uncertainty Based on Kriging and Support Vector Machine

Tingli Xie, Ping Jiang, Qi Zhou, Leshi Shu, Yang Yang

Proc. ASME. IDETC-CIE2018, Volume 2B: 44th Design Automation Conference, V02BT03A036, August 26–29, 2018

Paper No: DETC2018-86237

DOI: https://doi.org/10.1115/DETC2018-86237

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Topics: Optimization, Support vector machines, Uncertainty, Design, Engineering design, Engineering simulation, Simulation, Vehicles

Proceedings Papers

Automatic Postprocessing of Topology Optimization Solutions by Using Support Vector Machines

Niclas Strömberg

Proc. ASME. IDETC-CIE2018, Volume 2B: 44th Design Automation Conference, V02BT03A001, August 26–29, 2018

Paper No: DETC2018-85051

DOI: https://doi.org/10.1115/DETC2018-85051

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Topics: Optimization, Support vector machines, Topology, Computer-aided design, Density, Computer software, Design, Engineers, Filters, Modeling

Proceedings Papers

Comparing Machine Learning Regression Techniques for Transmission-Related Storm Outages

Caitlyn E. Clark, Bryony DuPont

Proc. ASME. IDETC-CIE2018, Volume 2A: 44th Design Automation Conference, V02AT03A024, August 26–29, 2018

Paper No: DETC2018-85127

DOI: https://doi.org/10.1115/DETC2018-85127

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Topics: Machine learning, Storms, Polynomials, Cost benefit analysis, Probability, Risk, Shorelines, Support vector machines

Proceedings Papers

Short-Term Load Forecasting With Different Aggregation Strategies

Cong Feng, Jie Zhang

Proc. ASME. IDETC-CIE2018, Volume 2A: 44th Design Automation Conference, V02AT03A019, August 26–29, 2018

Paper No: DETC2018-86084

DOI: https://doi.org/10.1115/DETC2018-86084

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Topics: Load forecasting, Stress, Algorithms, Artificial neural networks, Machine learning, Machinery, Power systems (Machinery), Robustness, Structures, Support vector machines

Proceedings Papers

High Degree of Freedom Hand Pose Tracking Using Limited Strain Sensing and Optical Training

Wentai Zhang, Jonelle Z. Yu, Fangcheng Zhu, Yifang Zhu, Nurcan Gecer Ulu, Batuhan Arisoy, Levent Burak Kara

Proc. ASME. IDETC-CIE2018, Volume 1B: 38th Computers and Information in Engineering Conference, V01BT02A019, August 26–29, 2018

Paper No: DETC2018-85870

DOI: https://doi.org/10.1115/DETC2018-85870

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Topics: Artificial neural networks, Control equipment, Degrees of freedom, Feedforward control, Manufacturing, Optimization, Sensors, Strain gages, Strain sensors, Support vector machines

Proceedings Papers

From Mining Affective States to Mining Facial Keypoint Data: The Quest Towards Personalized Feedback

Christian E. Lopez, Conrad S. Tucker

Proc. ASME. IDETC-CIE2017, Volume 1: 37th Computers and Information in Engineering Conference, V001T02A039, August 6–9, 2017

Paper No: DETC2017-67340

DOI: https://doi.org/10.1115/DETC2017-67340

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Topics: Feedback, Mining, Machine learning, Support vector machines, Workshops (Work spaces)

Proceedings Papers

3D Machined Surface Topography Forecasting With Space-Time Multioutput Support Vector Regression Using High Definition Metrology

Yiping Shao, Shichang Du, Lifeng Xi

Proc. ASME. IDETC-CIE2017, Volume 1: 37th Computers and Information in Engineering Conference, V001T02A069, August 6–9, 2017

Paper No: DETC2017-67155

DOI: https://doi.org/10.1115/DETC2017-67155

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Topics: Metrology, Spacetime, Support vector machines, Engine cylinders, Manufacturing, Milling

Proceedings Papers

Application of Audible Sound Signals for Tool Wear Monitoring and Workpiece Hardness Identification in Gear Milling Using Machine Learning Techniques

Achyuth Kothuru, Sai Prasad Nooka, Patricia Iglesias Victoria, Rui Liu

Proc. ASME. IDETC-CIE2017, Volume 10: 2017 ASME International Power Transmission and Gearing Conference, V010T11A030, August 6–9, 2017

Paper No: DETC2017-68067

DOI: https://doi.org/10.1115/DETC2017-68067

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Topics: Gears, Machine learning, Milling, Signals, Wear, Cutting, Cutting tools, Machining, Support vector machines, Algorithms

Proceedings Papers

Wind Turbine Blade Damage Detection Using Various Machine Learning Algorithms

Taylor Regan, Rukiye Canturk, Elizabeth Slavkovsky, Christopher Niezrecki, Murat Inalpolat

Proc. ASME. IDETC-CIE2016, Volume 8: 28th Conference on Mechanical Vibration and Noise, V008T10A040, August 21–24, 2016

Paper No: DETC2016-59686

DOI: https://doi.org/10.1115/DETC2016-59686

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Topics: Algorithms, Blades, Damage, Machine learning, Wind turbines, Acoustics, Cavities, Composite materials, Microphones, Support vector machines

Proceedings Papers

Product “In-Use” Context Identification Using Feature Learning Methods

Dipanjan D. Ghosh, Andrew Olewnik, Kemper Lewis

Proc. ASME. IDETC-CIE2016, Volume 1B: 36th Computers and Information in Engineering Conference, V01BT02A020, August 21–24, 2016

Paper No: DETC2016-59645

DOI: https://doi.org/10.1115/DETC2016-59645

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Topics: Accelerometers, Algorithms, Artificial neural networks, Dimensions, Fatigue, Internet of things, Machine learning, Mining, Product design, Support vector machines

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NARROW

Assessment of State of Charge Estimation Methods Based on Neural Networks and Support Vector Machine for Lithium-Ion Batteries Used in Vehicular Applications

A Constraint-Handling Technique for Parametric Optimization and Control Co-Design

A Study of Machine Learning Framework for Enabling Early Defect Detection in Wire Arc Additive Manufacturing Processes

A Multi-Fidelity Approach for Reliability Assessment Based on the Probability of Model Inconsistency

Gait Prediction and Mechanism Design for 1-DOF Lower Limb Rehabilitation Devices Based on Machine Learning

Towards Transparent Motion Planning of Wearable Rehabilitation Exoskeletons via Model-Based Estimation

Dimensional Prediction for FDM Machines Using Artificial Neural Network and Support Vector Regression

Exploiting Multi-Modal Sensing for Increased Detection Fidelity of Pipeline Leakage

Human Computer Interface Using Electroencephalography for Driver Behavior Classification

Predicting Multi-Disciplinary Design Performance Utilizing Automated Topic Discovery

A Multi-Objective Robust Optimization Approach Under Interval Uncertainty Based on Kriging and Support Vector Machine

Automatic Postprocessing of Topology Optimization Solutions by Using Support Vector Machines

Comparing Machine Learning Regression Techniques for Transmission-Related Storm Outages

Short-Term Load Forecasting With Different Aggregation Strategies

High Degree of Freedom Hand Pose Tracking Using Limited Strain Sensing and Optical Training

From Mining Affective States to Mining Facial Keypoint Data: The Quest Towards Personalized Feedback

3D Machined Surface Topography Forecasting With Space-Time Multioutput Support Vector Regression Using High Definition Metrology

Application of Audible Sound Signals for Tool Wear Monitoring and Workpiece Hardness Identification in Gear Milling Using Machine Learning Techniques

Wind Turbine Blade Damage Detection Using Various Machine Learning Algorithms

Product “In-Use” Context Identification Using Feature Learning Methods

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