Frequency Based Model Mixing for Machine Condition Monitoring

Conference Proceedings of the Society for Experimental Mechanics Series - Dynamic Substructures, Volume 4 ◽

10.1007/978-3-030-47630-4_15 ◽

2020 ◽

pp. 157-161

Author(s):

Samuel Krügel ◽

Daniel J. Rixen

Keyword(s):

Condition Monitoring ◽

Machine Condition ◽

Machine Condition Monitoring ◽

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Induction machine condition monitoring with higher order spectra

IEEE Transactions on Industrial Electronics ◽

10.1109/41.873211 ◽

2000 ◽

Vol 47 (5) ◽

pp. 1031-1041 ◽

Author(s):

N. Arthur ◽

J. Penman

Keyword(s):

Condition Monitoring ◽

Induction Machine ◽

Higher Order ◽

Machine Condition ◽

Machine Condition Monitoring ◽

Higher Order Spectra

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Induction machine condition monitoring with higher order spectra. II. Variable frequency operation and automated diagnosis

IECON '98. Proceedings of the 24th Annual Conference of the IEEE Industrial Electronics Society (Cat. No.98CH36200) ◽

10.1109/iecon.1998.723031 ◽

2002 ◽

Author(s):

N. Arthur ◽

J. Penman ◽

A. McLean ◽

A. Parsons

Keyword(s):

Condition Monitoring ◽

Induction Machine ◽

Higher Order ◽

Variable Frequency ◽

Machine Condition ◽

Automated Diagnosis ◽

Machine Condition Monitoring ◽

Higher Order Spectra

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An Illustration of New Methods in Machine Condition Monitoring, Part II: Adaptive outlier detection

Journal of Physics Conference Series ◽

10.1088/1742-6596/842/1/012059 ◽

2017 ◽

Vol 842 ◽

pp. 012059

Author(s):

I. Antoniadou ◽

K. Worden ◽

S. Marchesiello ◽

C. Mba ◽

L. Garibaldi

Keyword(s):

Outlier Detection ◽

Condition Monitoring ◽

Machine Condition ◽

New Methods ◽

Machine Condition Monitoring

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Machine Condition Monitoring with Industrial Wireless Sensor Networks

Industrial Wireless Sensor Networks ◽

10.1201/b14072-2 ◽

2017 ◽

pp. 23-45 ◽

Author(s):

Neil W. Bergmann ◽

Liqun Hou

Keyword(s):

Wireless Sensor Networks ◽

Sensor Networks ◽

Condition Monitoring ◽

Wireless Sensor ◽

Machine Condition ◽

Industrial Wireless Sensor Networks ◽

Machine Condition Monitoring

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Prism signal processing for machine condition monitoring II: Experimental data and fault detection

2018 IEEE Industrial Cyber-Physical Systems (ICPS) ◽

10.1109/icphys.2018.8390748 ◽

2018 ◽

Author(s):

Manus Henry ◽

Vladimir V Sinitsin

Keyword(s):

Experimental Data ◽

Signal Processing ◽

Fault Detection ◽

Condition Monitoring ◽

Machine Condition ◽

Machine Condition Monitoring

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Smart Phone Based Machine Condition Monitoring System

Neural Information Processing - Lecture Notes in Computer Science ◽

10.1007/978-3-642-34500-5_58 ◽

2012 ◽

pp. 488-497 ◽

Author(s):

Iqbal Gondal ◽

Muhammad Farrukh Yaqub ◽

Xueliang Hua

Keyword(s):

Monitoring System ◽

Condition Monitoring ◽

Smart Phone ◽

Machine Condition ◽

Machine Condition Monitoring ◽

Condition Monitoring System

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ALADDIN: Event Recognition & Fault Diagnosis for Process & Machine Condition Monitoring

Power Systems - Power Plant Surveillance and Diagnostics ◽

10.1007/978-3-662-04945-7_22 ◽

2002 ◽

pp. 335-354

Author(s):

Davide Roverso

Keyword(s):

Fault Diagnosis ◽

Condition Monitoring ◽

Event Recognition ◽

Machine Condition ◽

Machine Condition Monitoring

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Computer image analysis of wear debris for machine condition monitoring and fault diagnosis

Wear ◽

10.1016/0043-1648(94)07071-7 ◽

1995 ◽

Vol 181-183 ◽

pp. 717-722 ◽

Author(s):

T Kirk

Keyword(s):

Image Analysis ◽

Fault Diagnosis ◽

Condition Monitoring ◽

Computer Image ◽

Wear Debris ◽

Machine Condition ◽

Computer Image Analysis ◽

Machine Condition Monitoring

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Artificial Intelligence Application in Machine Condition Monitoring and Fault Diagnosis

Artificial Intelligence - Emerging Trends and Applications ◽

10.5772/intechopen.74932 ◽

2018 ◽

Author(s):

Yasir Hassan Ali

Keyword(s):

Artificial Intelligence ◽

Fault Diagnosis ◽

Condition Monitoring ◽

Machine Condition ◽

Machine Condition Monitoring ◽

Artificial Intelligence Application ◽

Intelligence Application

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Machine Condition Monitoring and Remaining Life Prediction Using Integrated Approach

Advanced Tribology ◽

10.1007/978-3-642-03653-8_324 ◽

2009 ◽

pp. 949-956

Author(s):

S. Ebersbach ◽

Zhongxiao Peng ◽

Chengqing Yuan ◽

Xinping Yan

Keyword(s):

Condition Monitoring ◽

Life Prediction ◽

Integrated Approach ◽

Machine Condition ◽

Remaining Life ◽

Machine Condition Monitoring

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