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Proceedings Papers

Temperature Field Monitoring in Fused Filament Fabrication Process Based on Physics-Constrained Dictionary Learning

Yanglong Lu, Yan Wang

Proc. ASME. IAM2022, 2022 International Additive Manufacturing Conference, V001T03A003, October 19–20, 2022

Paper No: IAM2022-93987

DOI: https://doi.org/10.1115/IAM2022-93987

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Topics: Manufacturing, Physics, Temperature, Sensors, Additive manufacturing, Compression, Imaging, Process monitoring, Resolution (Optics), Sensor placement

Proceedings Papers

Research on Condition Monitoring Technology of Automobile Parts Intelligent Production Line Based on Cyber Physical System

Yifei Wang, Zhiwen Xia, Kexin Yang, Lijun Jin

Proc. ASME. MSEC2022, Volume 2: Manufacturing Processes; Manufacturing Systems, V002T06A031, June 27–July 1, 2022

Paper No: MSEC2022-87425

DOI: https://doi.org/10.1115/MSEC2022-87425

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Topics: Assembly lines, Automobiles, Condition monitoring, Cyber-physical systems, Signals

Proceedings Papers

Pass-Wise Tool Wear Prediction in Turning Based on Long-Short Term Memory Algorithm Using Current Signals

Benvolence Chinomona, Chunhui Chung, Po-Chieh Wang

Proc. ASME. MSEC2022, Volume 2: Manufacturing Processes; Manufacturing Systems, V002T05A031, June 27–July 1, 2022

Paper No: MSEC2022-85339

DOI: https://doi.org/10.1115/MSEC2022-85339

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Topics: Algorithms, Signals, Turning, Wear

Proceedings Papers

Estimating Milling Forces From Vibration Measurements

Manish Joddar, Keivan Ahmadi

Proc. ASME. MSEC2022, Volume 1: Additive Manufacturing; Biomanufacturing; Life Cycle Engineering; Manufacturing Equipment and Automation; Nano/Micro/Meso Manufacturing, V001T04A001, June 27–July 1, 2022

Paper No: MSEC2022-85157

DOI: https://doi.org/10.1115/MSEC2022-85157

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Topics: Milling, Vibration measurement, Machining, Vibration, Kalman filters, Process monitoring, Signals, Accelerometers, Cutting, Force sensors

Proceedings Papers

Thin-Film Nitrate Sensor Performance Prediction Based on Image Analysis and Credibility Data to Enable a Certify As Built Framework

Xihui Wang, Ajanta Saha, Ye Mi, Ali Shakouri, Muhammad Ashraful Alam, George T. C. Chiu, Jan P. Allebach

Proc. ASME. MSEC2022, Volume 2: Manufacturing Processes; Manufacturing Systems, V002T06A021, June 27–July 1, 2022

Paper No: MSEC2022-85638

DOI: https://doi.org/10.1115/MSEC2022-85638

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Topics: Sensors, Thin films, Machine learning, Testing, Data collection, Errors, Manufacturing, Membranes, Noise (Sound), Pipelines

Proceedings Papers

Prediction of Weld Defects in Underwater Friction Stir Welding of Dissimilar Materials

Raju Prasad Mahto, Ananta Dutta, Debasish Mishra

Proc. ASME. MSEC2022, Volume 2: Manufacturing Processes; Manufacturing Systems, V002T05A047, June 27–July 1, 2022

Paper No: MSEC2022-85574

DOI: https://doi.org/10.1115/MSEC2022-85574

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Topics: Friction, Welding, Signal processing, Signals, Torque, Aluminum, Filters, Flow (Dynamics), Intermetallic compounds, Shear strength

Proceedings Papers

Multistream Sensor Fusion-Based Prognostics Model for Systems Under Multiple Operational Conditions

Xin Li, Xiaolei Fang

Proc. ASME. MSEC2021, Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T09A003, June 21–25, 2021

Paper No: MSEC2021-62348

DOI: https://doi.org/10.1115/MSEC2021-62348

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Topics: Sensors, Signals, Failure, Engineering systems and industry applications, Aircraft, Data fusion, Engines, NASA, Switches, Turbofans

Proceedings Papers

Multiple Sound Sensors And Fusion In Modern CNN-Based Machine State Prediction

Eunseob Kim, Huitaek Yun, Martin Byung-Guk Jun, Kyunghyun Kim, Suk Won Cha

Proc. ASME. MSEC2021, Volume 1: Additive Manufacturing; Advanced Materials Manufacturing; Biomanufacturing; Life Cycle Engineering; Manufacturing Equipment and Automation, V001T05A017, June 21–25, 2021

Paper No: MSEC2021-64036

DOI: https://doi.org/10.1115/MSEC2021-64036

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Topics: Artificial neural networks, Machine tools, Machinery, Sensors, Signals, Internet of things, Manufacturing, Acoustics, Bridges (Structures), Conveyor systems

Proceedings Papers

A Flexible Similarity Based Algorithm for Tool Condition Monitoring

Ben Stuhr, Rui Liu

Proc. ASME. MSEC2021, Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T06A012, June 21–25, 2021

Paper No: MSEC2021-62021

DOI: https://doi.org/10.1115/MSEC2021-62021

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Topics: Algorithms, Condition monitoring, Manufacturing, Signals

Proceedings Papers

Analysis of Vibration Signals in Monitoring Titanium End Milling Process Using Triaxial Accelerometer

John Henry Navarro-Devia, Dzung Viet Dao, Yun Chen, Huaizhong Li

Paper No: MSEC2021-64688

DOI: https://doi.org/10.1115/MSEC2021-64688

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Topics: Accelerometers, Machining, Milling, Signals, Titanium, Vibration

Proceedings Papers

Expulsion Intensity Monitoring and Modeling in Resistance Spot Welding Based on Electrode Displacement Signals

Yu-Jun Xia, Yan Shen, Lang Zhou, Yong-Bing Li

Proc. ASME. MSEC2020, Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T06A012, September 3, 2020

Paper No: MSEC2020-8256

DOI: https://doi.org/10.1115/MSEC2020-8256

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Topics: Displacement, Electrodes, Modeling, Signals, Welding

Proceedings Papers

Semiconductor Aspects of the Oxyfuel Cutting Torch Preheat Flame: Part I — Measurements Between Torch and Work

Christopher R. Martin, Teresa Pond, Jacob Tomas, Jenna Schmit, Erikson Miguel, Alex Untaroiu, Kemu Xu

Proc. ASME. MSEC2020, Volume 1: Additive Manufacturing; Advanced Materials Manufacturing; Biomanufacturing; Life Cycle Engineering; Manufacturing Equipment and Automation, V001T05A011, September 3, 2020

Paper No: MSEC2020-8258

DOI: https://doi.org/10.1115/MSEC2020-8258

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Topics: Cutting, Flames, Semiconductors (Materials), Signals, Currents, Ions, Uncertainty

Proceedings Papers

On Transfer Learning of Traditional Frequency and Time Domain Features in Turning

Melih C. Yesilli, Firas A. Khasawneh

Proc. ASME. MSEC2020, Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T07A027, September 3, 2020

Paper No: MSEC2020-8274

DOI: https://doi.org/10.1115/MSEC2020-8274

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Topics: Accelerometers, Algorithms, Chatter, Cutting, Fast Fourier transforms, Machine learning, Manufacturing, Signal processing, Signals, Spectral energy distribution

Proceedings Papers

Fault Diagnosis of Timed Event Systems: An Exploration of Machine Learning Methods

Joseph Cohen, Baoyang Jiang, Jun Ni

Proc. ASME. MSEC2020, Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T07A029, September 3, 2020

Paper No: MSEC2020-8360

DOI: https://doi.org/10.1115/MSEC2020-8360

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Topics: Fault diagnosis, Machine learning, Principal component analysis, Programmable controllers, Algorithms, Signals, Artificial neural networks, Failure, Integrated circuit fabrication, Manufacturing

Proceedings Papers

Improved Local Mean Decomposition for Vibration-Based Machinery Fault Diagnosis

Lingyan Wang, Hong Lu, Yu Qiao, Wan Wu, Le Li, Qiong Liu, Shaojun Wang

Proc. ASME. MSEC2020, Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T09A006, September 3, 2020

Paper No: MSEC2020-8236

DOI: https://doi.org/10.1115/MSEC2020-8236

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Topics: Fault diagnosis, Machinery, Rotors, Signals, Time-frequency analysis, Vibration

Proceedings Papers

Simultaneous Material Microstructure Classification and Discovery via Hidden Markov Modeling of Acoustic Emission Signals

Xinyu Zhao, Ashif Iquebal, Huifeng Sun, Hao Yan

Proc. ASME. MSEC2020, Volume 2: Manufacturing Processes; Manufacturing Systems; Nano/Micro/Meso Manufacturing; Quality and Reliability, V002T07A035, September 3, 2020

Paper No: MSEC2020-8454

DOI: https://doi.org/10.1115/MSEC2020-8454

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Topics: Acoustic emissions, Modeling, Signals, Additive manufacturing, Lithography, Materials properties, Probability, Probes, Resolution (Optics)

Proceedings Papers

Degradation Assessment of Reciprocating Seal Using Support Vector Regression

Madhumitha Ramachandran, Jon Keegan, Zahed Siddique

Proc. ASME. MSEC2019, Volume 1: Additive Manufacturing; Manufacturing Equipment and Systems; Bio and Sustainable Manufacturing, V001T02A008, June 10–14, 2019

Paper No: MSEC2019-2820

DOI: https://doi.org/10.1115/MSEC2019-2820

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Topics: Support vector machines, Friction, Machinery, Failure, Leakage, Manufacturing industry, Petroleum industry, Pistons, Principal component analysis, Signals

Proceedings Papers

Singular Vector-Inspired Dictionary Learning for Sparse Decomposition of Vibration Signal

Baoqing Ding, Ruqiang Yan, Shibin Wang, Chaowei Tong, Xuefeng Chen

Proc. ASME. MSEC2019, Volume 1: Additive Manufacturing; Manufacturing Equipment and Systems; Bio and Sustainable Manufacturing, V001T02A013, June 10–14, 2019

Paper No: MSEC2019-2785

DOI: https://doi.org/10.1115/MSEC2019-2785

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Topics: Fault diagnosis, Machinery, Signals, Vibration

Proceedings Papers

Bearing Metrics for Health Monitoring of Machine Tool Linear Axes

Gregory W. Vogl, Brian C. Galfond, N. Jordan Jameson

Proc. ASME. MSEC2019, Volume 1: Additive Manufacturing; Manufacturing Equipment and Systems; Bio and Sustainable Manufacturing, V001T02A015, June 10–14, 2019

Paper No: MSEC2019-2911

DOI: https://doi.org/10.1115/MSEC2019-2911

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Topics: Ball bearings, Bearings, Machine tools, Algorithms, Machinery, Trucks, Damage, Errors, Manufacturing, Measurement units and standards

Proceedings Papers

Forces in Deep-Hole Bone Drilling

JuEun Lee, Zachary Matsumoto, Serena Y. Chu

Proc. ASME. MSEC2019, Volume 1: Additive Manufacturing; Manufacturing Equipment and Systems; Bio and Sustainable Manufacturing, V001T05A010, June 10–14, 2019

Paper No: MSEC2019-2990

DOI: https://doi.org/10.1115/MSEC2019-2990

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Topics: Bone, Drilling, Signals, Bits (Tools), Cutting, Drills (Tools), Surgery

2 3 4 5

NARROW

Temperature Field Monitoring in Fused Filament Fabrication Process Based on Physics-Constrained Dictionary Learning

Research on Condition Monitoring Technology of Automobile Parts Intelligent Production Line Based on Cyber Physical System

Pass-Wise Tool Wear Prediction in Turning Based on Long-Short Term Memory Algorithm Using Current Signals

Estimating Milling Forces From Vibration Measurements

Thin-Film Nitrate Sensor Performance Prediction Based on Image Analysis and Credibility Data to Enable a Certify As Built Framework

Prediction of Weld Defects in Underwater Friction Stir Welding of Dissimilar Materials

Multistream Sensor Fusion-Based Prognostics Model for Systems Under Multiple Operational Conditions

Multiple Sound Sensors And Fusion In Modern CNN-Based Machine State Prediction

A Flexible Similarity Based Algorithm for Tool Condition Monitoring

Analysis of Vibration Signals in Monitoring Titanium End Milling Process Using Triaxial Accelerometer

Expulsion Intensity Monitoring and Modeling in Resistance Spot Welding Based on Electrode Displacement Signals

Semiconductor Aspects of the Oxyfuel Cutting Torch Preheat Flame: Part I — Measurements Between Torch and Work

On Transfer Learning of Traditional Frequency and Time Domain Features in Turning

Fault Diagnosis of Timed Event Systems: An Exploration of Machine Learning Methods

Improved Local Mean Decomposition for Vibration-Based Machinery Fault Diagnosis

Simultaneous Material Microstructure Classification and Discovery via Hidden Markov Modeling of Acoustic Emission Signals

Degradation Assessment of Reciprocating Seal Using Support Vector Regression

Singular Vector-Inspired Dictionary Learning for Sparse Decomposition of Vibration Signal

Bearing Metrics for Health Monitoring of Machine Tool Linear Axes

Forces in Deep-Hole Bone Drilling

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