Automatic rule learning using decision tree for fuzzy classifier in fault diagnosis of roller bearing-Reference-Cited by-同舟云学术

Automatic rule learning using decision tree for fuzzy classifier in fault diagnosis of roller bearing

Published:2007-07 Issue:5 Volume:21 Page:2237-2247
ISSN:0888-3270
Container-title:Mechanical Systems and Signal Processing
language:en
Short-container-title:Mechanical Systems and Signal Processing

Author:

Sugumaran V.,Ramachandran K.I.

Publisher

Elsevier BV

Subject

Computer Science Applications,Mechanical Engineering,Aerospace Engineering,Civil and Structural Engineering,Signal Processing,Control and Systems Engineering

Reference19 articles.

1. S.S. Wang, Artificial intelligence and expert systems for diagnostics, Proceedings of the Institute of International Conference Machining and Diagnostics and Exhibition, Las Vegas, Neveda, 1989. pp. 516–512.

2. Bearing Damage Analysis,1976

3. Online detection of localised defects in bearing by pattern recognition analysis;James Li;ASME Journal of Engineering Industry,1989

4. A.K. Nandi, Advanced digital vibration signal processing for condition monitoring, Proceedings of COMADEM2000, Houston, TX, USA, 2000. pp. 129–143.

5. Artificial neural network based fault diagnostics of rolling element bearings using time domain features;Samanta;Mechanical Systems and Signal Processing,2003

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