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TECHNICAL PAPERS

Pattern Recognition for Automatic Machinery Fault Diagnosis

[+] Author and Article Information
Qiao Sun, Ping Chen, Dajun Zhang

Dept of Mechanical and Manufacturing Engineering, University of Calgary, Calgary, Alberta, Canada T2N 1N4

Fengfeng Xi

Dept of Mechanical, Aerospace, and Industrial Eng., Ryerson University, Toronto, Ontario, Canada M5B 2K3e-mail: fengxi@ryerson.ca

J. Vib. Acoust 126(2), 307-316 (May 04, 2004) (10 pages) doi:10.1115/1.1687391 History: Received December 01, 2002; Revised April 01, 2003; Online May 04, 2004
Copyright © 2004 by ASME
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References

Figures

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Pattern recognition method for machinery fault diagnosis
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(a) Vibration signal from bearing with inner race defect (b) Segmented vibration signal in one inner race rotation
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Schematic of rolling element bearing
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(a) Vibration signal of bearing with roller defect (b) Segmented vibration signal within one cage rotation
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(a) Vibration signal of bearing with outer race defect (b) Segmented vibration signal within one cage rotation
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A fully connected three layered neural network
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(a) Mapping from feature space to classification space (b) Piecewise linear boundaries
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Diagnosis on the classification space

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