Vibration Fault Diagnosis of Rotating Machine Based on the Principle of Entropy Increase

Chen Yu; Jian Lan Li; Shu Hong Huang

doi:10.4028/www.scientific.net/AMR.530.109

Paper Titles

Experiment Study on Mechanical Performance of Shale Lightweight Aggregate Concrete
p.80

Study for the Reason of Chromium Coating Seepage on Piston Rods and the Anti-Seepage by Using Ultrasonic Elliptical Vibration Burnishing Process
p.85

Friction and Wear Mechanism between Rubber and Nickel for Water Lubricated Bearings
p.91

Study on the Deposition and Characterization of Nanocrystalline Diamond Composite Films
p.95

An Identification Method of Physical Parameters for nR Serial Robots
p.103

Vibration Fault Diagnosis of Rotating Machine Based on the Principle of Entropy Increase
p.109

Study on Damage Mechanism for Foundation Pile of Girder Bridge under Seismic Influence
p.115

Study on Numerical Simulation for Failure Process of Girder Bridge under Seismic Influence
p.122

Analysis of Vane Hydraulic Damp Dynamic Seal Mechanism and Performance Influencing Factors
p.130

HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 530Vibration Fault Diagnosis of Rotating Machine...

Vibration Fault Diagnosis of Rotating Machine Based on the Principle of Entropy Increase

Abstract:

Information fusion is the main method to improve diagnosis accuracy. In this paper, fusion information entropy is defined by fusing speed with three kinds of information entropy that are singular spectrum entropy in time domain, power spectrum entropy in frequency domain and wavelet energy spectrum entropy in time-frequency domain from multiple perspectives to describes vibration fault characteristics. According to the principle of entropy increase, condition information entropy increase of vibration fault are defined and used as new criterion for fault diagnosis, and the grey correlation between sample fault and typical fault is defined to realize the vibration fault diagnosis. Finally, the method’s effectiveness is verified by vibration simulation data from vibration fault simulator. The result shows that this method can identify 6 typical vibration faults correctly.

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Periodical:

Advanced Materials Research (Volume 530)

Pages:

109-114

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.530.109

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Online since:

June 2012

Authors:

Chen Yu, Jian Lan Li, Shu Hong Huang

Keywords:

Entropy Increase, Fusion Information Entropy, Rotating Machine, Vibration Fault Diagnosis

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