A Correlative Method of Machine Condition Monitoring Based on the Choi-Williams Distribution

Guoan Yang; Zhenhuan Wu; Jin Ji Gao

doi:10.4028/www.scientific.net/KEM.293-294.777

Paper Titles

Local and Global Damages of Quasi-Brittle Material in Uniaxial Compression Based on Gradient-Dependent Plasticity
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Vibration-Based Seismic Damage Identification in Buildings
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Modal Analysis of a Reinforced Concrete Frame in Various States of Damage
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Vibration-Based Condition Monitoring of Smart Prefabricated Concrete Elements
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Detecting Damage of Rolling Bearings Using EMD
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Prediction of the Influence of Vibration on Structural Integrity of Elevator Suspension Ropes
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An Investigation into Scalpel Blade Sharpness Using Cutting Experiments and Finite Element Analysis
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A Correlative Method of Machine Condition Monitoring Based on the Choi-Williams Distribution
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Detection of Stray Current Field Interference on Metal Constructions Using STFT
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HomeKey Engineering MaterialsKey Engineering Materials Vols. 293-294A Correlative Method of Machine Condition...

A Correlative Method of Machine Condition Monitoring Based on the Choi-Williams Distribution

Abstract:

In this paper, a new method for time-varying machine condition monitoring is proposed. By Choi-Williams distribution, the interference terms produced by the bilinear time-frequency transform are reduced and the fault signal is processed by the correlation analysis of the Choi-Williams distribution. For machine fault diagnosis, both the feature extractor and classifier are combined to make a decision. It is particularly suited to those who are not experts in the field. Satisfactory results have been obtained from a real example and the effectiveness of the proposed method is demonstrated.