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Proceedings Papers

Recurrent Neural Networks for Fault Diagnosis and Severity Assessment of a Screw Compressor

C. James Li, Yimin Fan

Proc. ASME. IMECE97, Dynamic Systems and Control, 257-264, November 16–21, 1997

Paper No: IMECE1997-0404

DOI: https://doi.org/10.1115/IMECE1997-0404

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Topics: Artificial neural networks, Compressors, Fault diagnosis, Screws, Feedforward control, Friction, Neural network models, Wear

Proceedings Papers

Dimensional Fault Diagnosis for Compliant Beam Structure Assemblies

Q. Rong, D. Ceglarek, J. Shi

Proc. ASME. IMECE98, Manufacturing Science and Engineering, 93-101, November 15–20, 1998

Paper No: IMECE1998-1019

DOI: https://doi.org/10.1115/IMECE1998-1019

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Topics: Fault diagnosis, Manufacturing, Aerospace industry, Engineering simulation, Errors, Pattern recognition, Principal component analysis, Simulation, Stiffness

Proceedings Papers

Fault Diagnosing of Large Rotating Machinery Using Evolutionary Spectrum

Minping Jia, R. Du

Proc. ASME. IMECE98, Manufacturing Science and Engineering, 103-111, November 15–20, 1998

Paper No: IMECE1998-1020

DOI: https://doi.org/10.1115/IMECE1998-1020

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Topics: Machinery, Emission spectroscopy, Fault diagnosis, Rotors, Signals, Spectroscopy, Computer simulation, Stiffness, Vibration, Wavelet transforms

Proceedings Papers

Distributed Sensor Optimization for Fault Diagnosis in Multi-Fixture Assembly Systems

Ashraf Khan, Dariusz Ceglarek

Proc. ASME. IMECE98, Manufacturing Science and Engineering, 315-324, November 15–20, 1998

Paper No: IMECE1998-1042

DOI: https://doi.org/10.1115/IMECE1998-1042

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Topics: Fault diagnosis, Manufacturing, Optimization, Sensors, Computer-aided design, Sheet metal, System architecture

Proceedings Papers

Diagnosability and Measurement Configurations for Automotive Body Assembly

Yufeng Long, S. Jack Hu

Proc. ASME. IMECE98, Manufacturing Science and Engineering, 305-313, November 15–20, 1998

Paper No: IMECE1998-1041

DOI: https://doi.org/10.1115/IMECE1998-1041

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Topics: Manufacturing, Design, Automobiles, Complex systems, Doors, Fault diagnosis, Machinery, Measurement systems, Sheet metal

Proceedings Papers

Machine Fault Diagnosis Through a Recursive Optimal Pairwise Linear Discriminant Function Method

Shuxin Gu, Jun Ni, Jingxia Yuan, Jay Lee

Proc. ASME. IMECE98, Manufacturing Science and Engineering, 547-554, November 15–20, 1998

Paper No: IMECE1998-1068

DOI: https://doi.org/10.1115/IMECE1998-1068

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Topics: Fault diagnosis, Machinery, Pattern recognition, Artificial neural networks, Failure, Feedforward control

Proceedings Papers

Fault Diagnosis With Deep Learning for Standard and Asymmetric Involute Spur Gears

Fatih Karpat, Ahmet Emir Dirik, Onur Can Kalay, Celalettin Yüce, Oğuz Doğan, Burak Korcuklu

Proc. ASME. IMECE2021, Volume 13: Safety Engineering, Risk, and Reliability Analysis; Research Posters, V013T14A029, November 1–5, 2021

Paper No: IMECE2021-73702

DOI: https://doi.org/10.1115/IMECE2021-73702

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Topics: Fault diagnosis, Gears, Spur gears

Proceedings Papers

Spindle Bearings Fault Diagnosis Technique Based on Integration of Zero Resonator Frequency Filter and Discrete Wavelet Packet Transform

Avitus Titus Mwelinde, Hongyu Jin, Jamal Banzi, Hongya Fu, Zhenyu Han

Proc. ASME. IMECE2021, Volume 13: Safety Engineering, Risk, and Reliability Analysis; Research Posters, V013T14A004, November 1–5, 2021

Paper No: IMECE2021-73194

DOI: https://doi.org/10.1115/IMECE2021-73194

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Topics: Bearings, Fault diagnosis, Filters, Flaw detection, Wavelets

Proceedings Papers

An Empirical Study of Machine Learning and Deep Learning Algorithms on Bearing Fault Diagnosis Benchmarks

Behnoush Rezaeianjouybari, Yi Shang

Proc. ASME. IMECE2021, Volume 7A: Dynamics, Vibration, and Control, V07AT07A050, November 1–5, 2021

Paper No: IMECE2021-69994

DOI: https://doi.org/10.1115/IMECE2021-69994

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Topics: Algorithms, Bearings, Fault diagnosis, Machine learning

Proceedings Papers

Diagnosis of Multiple Simultaneous Faults in Manufacturing Systems

Wei Li, S. Jack Hu, Jun Ni

Proc. ASME. IMECE99, Manufacturing Science and Engineering, 581-588, November 14–19, 1999

Paper No: IMECE1999-0718

DOI: https://doi.org/10.1115/IMECE1999-0718

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Topics: Manufacturing systems, Fault diagnosis, Modeling, Simulation, Welding

Proceedings Papers

Multiple Fault Diagnosis as Applied to Automated Vehicle Control

Adam S. Howell, J. Karl Hedrick

Proc. ASME. IMECE99, Dynamic Systems and Control, 615-621, November 14–19, 1999

Paper No: IMECE1999-0083

DOI: https://doi.org/10.1115/IMECE1999-0083

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Topics: Autonomous vehicles, Fault diagnosis, Control systems, Fuzzy logic

Proceedings Papers

Fault Diagnosis of an Internal Combustion Engine With Embedded Radial Basis Function Modules

Chengyu Gan, Kourosh Danai, Giorgio Rizzoni

Proc. ASME. IMECE2000, Dynamic Systems and Control: Volume 1, 399-406, November 5–10, 2000

Paper No: IMECE2000-2328

DOI: https://doi.org/10.1115/IMECE2000-2328

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Topics: Fault diagnosis, Internal combustion engines, Automotive engines, Kalman filters, Modeling, Sensors, State estimation

Proceedings Papers

Fault Diagnosis With a Model-Based Recurrent Neural Network

Chengyu Gan, Kourosh Danai

Proc. ASME. IMECE2000, Dynamic Systems and Control: Volume 1, 391-397, November 5–10, 2000

Paper No: IMECE2000-2327

DOI: https://doi.org/10.1115/IMECE2000-2327

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Topics: Artificial neural networks, Fault diagnosis, Generators, Flaw detection

Proceedings Papers

Bayesian Belief Network Modeling and Diagnosis of Xerographic Systems

Chunhui Zhong, Perry Y. Li

Proc. ASME. IMECE2000, Dynamic Systems and Control: Volume 1, 195-202, November 5–10, 2000

Paper No: IMECE2000-2302

DOI: https://doi.org/10.1115/IMECE2000-2302

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Topics: Modeling, Printing, Computer software, Entropy, Fault diagnosis, Physics, Statistical distributions

Proceedings Papers

Model Based Diagnostics for Vehicle Systems

Pierluigi Pisu, Giorgio Rizzoni, Ahmed Soliman, Sanket Amberkar, Brian Murray, Laci Jalics

Proc. ASME. IMECE2000, Dynamic Systems and Control: Volume 1, 543-550, November 5–10, 2000

Paper No: IMECE2000-2346

DOI: https://doi.org/10.1115/IMECE2000-2346

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Topics: Vehicles, Flaw detection, Control equipment, Control systems, Design, Fault diagnosis, Reliability, Safety

Proceedings Papers

Vibration-Based Early Crack Diagnosis With Machine Learning for Spur Gears

Fatih Karpat, Ahmet Emir Dirik, Onur Can Kalay, Oğuz Doğan, Burak Korcuklu

Proc. ASME. IMECE2020, Volume 7B: Dynamics, Vibration, and Control, V07BT07A004, November 16–19, 2020

Paper No: IMECE2020-24006

DOI: https://doi.org/10.1115/IMECE2020-24006

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Topics: Fault diagnosis, Fracture (Materials), Gears, Machine learning, Spur gears, Vibration

Proceedings Papers

An Investigation of Temperature Measurement Granularity Towards Improving Li-Ion Battery Management System Design

Mehrdad Zandigohar, Nima Lotfi

Proc. ASME. IMECE2019, Volume 6: Energy, V006T06A031, November 11–14, 2019

Paper No: IMECE2019-11874

DOI: https://doi.org/10.1115/IMECE2019-11874

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Topics: Design, Lithium-ion batteries, Temperature measurement, Batteries, Bridges (Structures), Electrochemistry, Energy storage, Engineers, Fault diagnosis, Flaw detection

Proceedings Papers

Early Fault Warning of Spindle Based on the Adaptive Weighted Fuzzy Petri Net

Hai Li, Wei Wang, Qingzhao Li, Lei Fan, Pu Huang

Proc. ASME. IMECE2018, Volume 13: Design, Reliability, Safety, and Risk, V013T05A015, November 9–15, 2018

Paper No: IMECE2018-86042

DOI: https://doi.org/10.1115/IMECE2018-86042

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Topics: Design, Engineering simulation, Fault diagnosis, Machine tools, Maintenance, Manufacturing, Simulation, Time series

Proceedings Papers

LTI Filtering- and Multiple Resonance-Based Signal Decomposition for Semi-Quantitative Fault Diagnosis of Rolling Bearings

Hongjian Sun, Wentao Huang, Yunchuan Jiang, Weijie Wang

Proc. ASME. IMECE2017, Volume 13: Acoustics, Vibration and Phononics, V013T01A010, November 3–9, 2017

Paper No: IMECE2017-70293

DOI: https://doi.org/10.1115/IMECE2017-70293

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Topics: Fault diagnosis, Filtration, Resonance, Rolling bearings, Signals, Composite materials, Machinery, Rotation, Separation (Technology), Signal processing

Proceedings Papers

A Novel Information Fusion Model Based on D-S Evidence Theory for Equipment Diagnosis

Dengji Zhou, Tingting Wei, Huisheng Zhang, Meishan Chen, Shixi Ma, Zhenhua Lu

Proc. ASME. IMECE2016, Volume 6A: Energy, V06AT08A017, November 11–17, 2016

Paper No: IMECE2016-65292

DOI: https://doi.org/10.1115/IMECE2016-65292

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Topics: Algorithms, Fault diagnosis, Machinery, Probability, Sensors, Signals, Uncertainty

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NARROW

Recurrent Neural Networks for Fault Diagnosis and Severity Assessment of a Screw Compressor

Dimensional Fault Diagnosis for Compliant Beam Structure Assemblies

Fault Diagnosing of Large Rotating Machinery Using Evolutionary Spectrum

Distributed Sensor Optimization for Fault Diagnosis in Multi-Fixture Assembly Systems

Diagnosability and Measurement Configurations for Automotive Body Assembly

Machine Fault Diagnosis Through a Recursive Optimal Pairwise Linear Discriminant Function Method

Fault Diagnosis With Deep Learning for Standard and Asymmetric Involute Spur Gears

Spindle Bearings Fault Diagnosis Technique Based on Integration of Zero Resonator Frequency Filter and Discrete Wavelet Packet Transform

An Empirical Study of Machine Learning and Deep Learning Algorithms on Bearing Fault Diagnosis Benchmarks

Diagnosis of Multiple Simultaneous Faults in Manufacturing Systems

Multiple Fault Diagnosis as Applied to Automated Vehicle Control

Fault Diagnosis of an Internal Combustion Engine With Embedded Radial Basis Function Modules

Fault Diagnosis With a Model-Based Recurrent Neural Network

Bayesian Belief Network Modeling and Diagnosis of Xerographic Systems

Model Based Diagnostics for Vehicle Systems

Vibration-Based Early Crack Diagnosis With Machine Learning for Spur Gears

An Investigation of Temperature Measurement Granularity Towards Improving Li-Ion Battery Management System Design

Early Fault Warning of Spindle Based on the Adaptive Weighted Fuzzy Petri Net

LTI Filtering- and Multiple Resonance-Based Signal Decomposition for Semi-Quantitative Fault Diagnosis of Rolling Bearings

A Novel Information Fusion Model Based on D-S Evidence Theory for Equipment Diagnosis

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