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Proceedings Papers

Physics-Informed Neural Networks (PINNs)-Based Solution of the Lamb Wave Dispersion Equation for Isotropic Plates

Hongye Liu, Rong Wang, Ziqi Huang, Maoxun Sun, Jiali Li, Zhide Wang, Zhenhua Tian
Proc. ASME. SMASIS2024, ASME 2024 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, V001T05A011, September 9–11, 2024
Publisher: American Society of Mechanical Engineers
Paper No: SMASIS2024-141274
https://doi.org/10.1115/SMASIS2024-141274
View Paper titled, Physics-Informed Neural Networks (PINNs)-Based Solution of the Lamb Wave Dispersion Equation for Isotropic Plates
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Topics: Artificial neural networks, Dispersion (Optics), Physics, Plates (structures)
Proceedings Papers

Spectral Analysis of Mechanical Reservoir Computing With ReLU Spring Networks

Daniel Nelson, Steven Kiyabu, Timothy Vincent, Andrew Gillman, Amanda Criner, Philip R. Buskohl
Proc. ASME. SMASIS2024, ASME 2024 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, V001T08A004, September 9–11, 2024
Publisher: American Society of Mechanical Engineers
Paper No: SMASIS2024-141014
https://doi.org/10.1115/SMASIS2024-141014
View Paper titled, Spectral Analysis of Mechanical Reservoir Computing With ReLU Spring Networks
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Topics: Emission spectroscopy, Reservoirs, Spectroscopy, Springs, Nonlinear dynamics, Signals, Artificial neural networks, Computers, Displacement, Dynamics (Mechanics)
Proceedings Papers

Neural Network-Based Sensorless Control of a Shape Memory Alloy Actuator

Krunal Jagdishbhai Koshiya, Gianluca Rizzello, Paul Motzki
Proc. ASME. SMASIS2024, ASME 2024 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, V001T03A001, September 9–11, 2024
Publisher: American Society of Mechanical Engineers
Paper No: SMASIS2024-139592
https://doi.org/10.1115/SMASIS2024-139592
View Paper titled, Neural Network-Based Sensorless Control of a Shape Memory Alloy Actuator
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Topics: Actuators, Artificial neural networks, Control systems, Shape memory alloys
Proceedings Papers

Online Health Monitoring of Electronic Components Subjected to Repeated High-Energy Shock

Joud N. Satme, Daniel Coble, Austin R. J. Downey
Proc. ASME. SMASIS2024, ASME 2024 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, V001T05A002, September 9–11, 2024
Publisher: American Society of Mechanical Engineers
Paper No: SMASIS2024-139950
https://doi.org/10.1115/SMASIS2024-139950
View Paper titled, Online Health Monitoring of Electronic Components Subjected to Repeated High-Energy Shock
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Topics: Electronic components, Shock (Mechanics), Damage, Artificial neural networks, Accelerometers, Electronic packages, Failure, Machine learning, Printed circuit boards, Safety
Proceedings Papers

A Novel Approach for Optimizing Muscle Activation Level and Localization With Vibro-Acoustic DEA Feedback Capability

Tajbeed A. Chowdhury, Sebastian Gratz-Kelly, Eric Wagner, Paul Motzki, Martina Lehser
Proc. ASME. SMASIS2024, ASME 2024 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, V001T04A002, September 9–11, 2024
Publisher: American Society of Mechanical Engineers
Paper No: SMASIS2024-139090
https://doi.org/10.1115/SMASIS2024-139090
View Paper titled, A Novel Approach for Optimizing Muscle Activation Level and Localization With Vibro-Acoustic DEA Feedback Capability
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Topics: Acoustics, Actuators, Dielectric elastomer actuators, Electromyography, Feedback, Muscle, Sensors, Deep learning, Algorithms, Artificial neural networks
Proceedings Papers

An Embedded System for Data-Based Self-Sensing in Shape Memory Alloy Wire Actuators

Krunal Jagdishbhai Koshiya, Gianluca Rizzello, Paul Motzki
Proc. ASME. SMASIS2023, ASME 2023 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, V001T04A002, September 11–13, 2023
Publisher: American Society of Mechanical Engineers
Paper No: SMASIS2023-110385
https://doi.org/10.1115/SMASIS2023-110385
View Paper titled, An Embedded System for Data-Based Self-Sensing in Shape Memory Alloy Wire Actuators
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Topics: Actuators, Artificial neural networks, Embedded systems, Shape memory alloys, Wire
Proceedings Papers

MFC Morphing Aileron Control With Intelligent Sensing

Kevin PT. Haughn, Lawren L. Gamble, Daniel J. Inman
Proc. ASME. SMASIS2022, ASME 2022 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, V001T03A013, September 12–14, 2022
Publisher: American Society of Mechanical Engineers
Paper No: SMASIS2022-92009
https://doi.org/10.1115/SMASIS2022-92009
View Paper titled, MFC Morphing Aileron Control With Intelligent Sensing
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Topics: Actuators, Aerospace industry, Airfoils, Artificial neural networks, Composite materials, Control equipment, Creep, Deflection, Feedback, Fibers
Proceedings Papers

Investigation of Analysis and Gradient-Based Design Optimization Using Neural Networks

Kazuko W. Fuchi, Eric M. Wolf, David S. Makhija, Nathan A. Wukie, Christopher R. Schrock, Philip S. Beran
Proc. ASME. SMASIS2020, ASME 2020 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, V001T08A002, September 15, 2020
Publisher: American Society of Mechanical Engineers
Paper No: SMASIS2020-2241
https://doi.org/10.1115/SMASIS2020-2241
View Paper titled, Investigation of Analysis and Gradient-Based Design Optimization Using Neural Networks
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Topics: Artificial neural networks, Design, Optimization, Boundary-value problems, Differential equations, Errors, Heat, Heat transfer, Meshfree methods, Physics
Proceedings Papers

Sensor-Data Reconstruction for Helicopter Structural-Health Monitoring Using Deep Learning

Andrew D. Harper, Nick Breen, David Alvord, David Pendleton, Teresa Hresko
Proc. ASME. SMASIS2020, ASME 2020 Conference on Smart Materials, Adaptive Structures and Intelligent Systems, V001T08A003, September 15, 2020
Publisher: American Society of Mechanical Engineers
Paper No: SMASIS2020-2311
https://doi.org/10.1115/SMASIS2020-2311
View Paper titled, Sensor-Data Reconstruction for Helicopter Structural-Health Monitoring Using Deep Learning
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Topics: Sensors, Accelerometers, Flight, Maintenance, Vehicles, Artificial neural networks, Damage assessment, Downtime, Failure mechanisms, Machine learning
Proceedings Papers

Deep Learning Based Spectrum Compression Algorithm for Rotating Machinery Condition Monitoring

Gürkan Aydemir
Proc. ASME. SMASIS2018, Volume 1: Development and Characterization of Multifunctional Materials; Modeling, Simulation, and Control of Adaptive Systems; Integrated System Design and Implementation, V001T03A027, September 10–12, 2018
Publisher: American Society of Mechanical Engineers
Paper No: SMASIS2018-8137
https://doi.org/10.1115/SMASIS2018-8137
View Paper titled, Deep Learning Based Spectrum Compression Algorithm for Rotating Machinery Condition Monitoring
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Topics: Algorithms, Compression, Condition monitoring, Machinery, Bearings, Maintenance, Signals, Artificial neural networks, Feature extraction, Flaw detection
Proceedings Papers

Feature Recognition and Detection for Common Maintenance Tools Based on Deep Learning

Chengcheng Liu, Kuan Zhang, Peigang Li, Shengyuan Li, Xuefeng Zhao
Proc. ASME. SMASIS2018, Volume 2: Mechanics and Behavior of Active Materials; Structural Health Monitoring; Bioinspired Smart Materials and Systems; Energy Harvesting; Emerging Technologies, V002T05A016, September 10–12, 2018
Publisher: American Society of Mechanical Engineers
Paper No: SMASIS2018-8266
https://doi.org/10.1115/SMASIS2018-8266
View Paper titled, Feature Recognition and Detection for Common Maintenance Tools Based on Deep Learning
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Topics: Artificial neural networks, Databases, Inspection, Maintenance, Railroads, Rails, Safety, Traffic, Trains
Proceedings Papers

Detection of Component Types and Track Damage for High-Speed Railway Using Region-Based Convolutional Neural Networks

Shengyuan Li, Peigang Li, Yang Zhang, Xuefeng Zhao
Proc. ASME. SMASIS2018, Volume 2: Mechanics and Behavior of Active Materials; Structural Health Monitoring; Bioinspired Smart Materials and Systems; Energy Harvesting; Emerging Technologies, V002T05A012, September 10–12, 2018
Publisher: American Society of Mechanical Engineers
Paper No: SMASIS2018-8223
https://doi.org/10.1115/SMASIS2018-8223
View Paper titled, Detection of Component Types and Track Damage for High-Speed Railway Using Region-Based Convolutional Neural Networks
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Topics: Artificial neural networks, Damage, High speed rail, Databases, Optical quality control, Economics , Safety, Shades and shadows
Proceedings Papers

Real-Time Detection of Ancient Architecture Features Based on Smartphones

Zheng Zou, Niannian Wang, Peng Zhao, Xuefeng Zhao
Proc. ASME. SMASIS2018, Volume 2: Mechanics and Behavior of Active Materials; Structural Health Monitoring; Bioinspired Smart Materials and Systems; Energy Harvesting; Emerging Technologies, V002T05A015, September 10–12, 2018
Publisher: American Society of Mechanical Engineers
Paper No: SMASIS2018-8265
https://doi.org/10.1115/SMASIS2018-8265
View Paper titled, Real-Time Detection of Ancient Architecture Features Based on Smartphones
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Topics: Artificial neural networks, Statistics, Structures, Texture (Materials)
Proceedings Papers

Image-Based Comprehensive Maintenance and Inspection Method for Bridges Using Deep Learning

Xuefeng Zhao, Shengyuan Li, Hongguo Su, Lei Zhou, Kenneth J. Loh
Proc. ASME. SMASIS2018, Volume 2: Mechanics and Behavior of Active Materials; Structural Health Monitoring; Bioinspired Smart Materials and Systems; Energy Harvesting; Emerging Technologies, V002T05A017, September 10–12, 2018
Publisher: American Society of Mechanical Engineers
Paper No: SMASIS2018-8268
https://doi.org/10.1115/SMASIS2018-8268
View Paper titled, Image-Based Comprehensive Maintenance and Inspection Method for Bridges Using Deep Learning
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Topics: Bridges (Structures), Inspection, Maintenance, Optical quality control, Artificial neural networks, Arches, Cable-stayed bridges, Concretes, Crack detection, Fracture (Materials)
Proceedings Papers

Dangerous Scenes Recognition During Hoisting Based on Faster Region-Based Convolutional Neural Network

Hongguo Su, Mingyuan Zhang, Shengyuan Li, Xuefeng Zhao
Proc. ASME. SMASIS2018, Volume 2: Mechanics and Behavior of Active Materials; Structural Health Monitoring; Bioinspired Smart Materials and Systems; Energy Harvesting; Emerging Technologies, V002T05A013, September 10–12, 2018
Publisher: American Society of Mechanical Engineers
Paper No: SMASIS2018-8226
https://doi.org/10.1115/SMASIS2018-8226
View Paper titled, Dangerous Scenes Recognition During Hoisting Based on Faster Region-Based Convolutional Neural Network
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Topics: Artificial neural networks, Accidents, Security, Trains
Proceedings Papers

Hybrid Algorithm for Structural Health Monitoring of High-Rate Systems

Jonathan Hong, Simon Laflamme, Liang Cao, Bryan Joyce, Jacob Dodson
Proc. ASME. SMASIS2018, Volume 2: Mechanics and Behavior of Active Materials; Structural Health Monitoring; Bioinspired Smart Materials and Systems; Energy Harvesting; Emerging Technologies, V002T05A005, September 10–12, 2018
Publisher: American Society of Mechanical Engineers
Paper No: SMASIS2018-7977
https://doi.org/10.1115/SMASIS2018-7977
View Paper titled, Hybrid Algorithm for Structural Health Monitoring of High-Rate Systems
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Topics: Aircraft, Algorithms, Artificial neural networks, Dampers, Deformation, Degrees of freedom, Engineering simulation, Engineering systems and industry applications, Excitation, Failure
Proceedings Papers

Application of Swarm Intelligence to a Vibration Monitoring System

Takuya Hiura, Shin Morishita
Proc. ASME. SMASIS2017, Volume 2: Modeling, Simulation and Control of Adaptive Systems; Integrated System Design and Implementation; Structural Health Monitoring, V002T03A004, September 18–20, 2017
Publisher: American Society of Mechanical Engineers
Paper No: SMASIS2017-3734
https://doi.org/10.1115/SMASIS2017-3734
View Paper titled, Application of Swarm Intelligence to a Vibration Monitoring System
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Topics: Vibration monitors, Actuators, Sensors, Vibration, Adaptive control, Artificial intelligence, Artificial neural networks, Control systems, Dampers, Damping
Proceedings Papers

Structural Health Monitoring of Pipelines for Environment Pollution Mitigation

Ferdinando Felli, Antonio Paolozzi, Cristian Vendittozzi, Claudio Paris, Hiroshi Asanuma, Gerardo De Canio, Marialuisa Mongelli, Alessandro Colucci
Proc. ASME. SMASIS2015, Volume 2: Integrated System Design and Implementation; Structural Health Monitoring; Bioinspired Smart Materials and Systems; Energy Harvesting, V002T04A009, September 21–23, 2015
Publisher: American Society of Mechanical Engineers
Paper No: SMASIS2015-8922
https://doi.org/10.1115/SMASIS2015-8922
View Paper titled, Structural Health Monitoring of Pipelines for Environment Pollution Mitigation
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Topics: Pipelines, Pollution, Structural health monitoring, Damage, Displacement, Fibers, Leakage, Artificial neural networks, Chain, Corrosion
Proceedings Papers

Aerodynamic Characteristics Prediction via Artificial Hair Sensor and Feedforward Neural Network

Kaman Thapa Magar, Gregory W. Reich, Matthew R. Rickey, Brian M. Smyers, Richard V. Beblo
Proc. ASME. SMASIS2015, Volume 2: Integrated System Design and Implementation; Structural Health Monitoring; Bioinspired Smart Materials and Systems; Energy Harvesting, V002T06A004, September 21–23, 2015
Publisher: American Society of Mechanical Engineers
Paper No: SMASIS2015-8890
https://doi.org/10.1115/SMASIS2015-8890
View Paper titled, Aerodynamic Characteristics Prediction via Artificial Hair Sensor and Feedforward Neural Network
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Topics: Artificial neural networks, Feedforward control, Sensors, Flow (Dynamics), Actuators, Aerodynamics, Airfoils, Control equipment, Design, Manufacturing
Proceedings Papers

PVDF Based Wearable Joystick Using Gesture Recognition via Neural Networks

Kyle R. Van Volkinburg, Gregory N. Washington
Proc. ASME. SMASIS2014, Volume 2: Mechanics and Behavior of Active Materials; Integrated System Design and Implementation; Bioinspired Smart Materials and Systems; Energy Harvesting, V002T04A016, September 8–10, 2014
Publisher: American Society of Mechanical Engineers
Paper No: SMASIS2014-7577
https://doi.org/10.1115/SMASIS2014-7577
View Paper titled, PVDF Based Wearable Joystick Using Gesture Recognition via Neural Networks
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Topics: Artificial neural networks, Feedforward control, Compression, Data acquisition systems