Rolling Bearing Fault Diagnosis Based on Blind Source Separation
Chang Zheng Chen, Qiang Meng, Hao Zhou, Yu Zhang
Abstract
Chang Zheng Chen, Qiang Meng, Hao Zhou, Yu Zhang
Abstract
This document presents fault diagnosis method of rolling bearing based on blind source separation. The algorithm based on fast ICA is improved to separate fault signals according to the rolling bearing’s fault characteristics. Through the experiment it is shown that the algorithm can separate the signals collected from rolling bearing and gearbox effectively, which can provide a new method for fault diagnosis and signal processing of machinery equipment.
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This document presents fault diagnosis method of rolling bearing based on blind source separation. The algorithm based on fast ICA is improved to separate fault signals according to the rolling bearing’s fault characteristics. Through the experiment it is shown that the algorithm can separate the signals collected from rolling bearing and gearbox effectively, which can provide a new method for fault diagnosis and signal processing of machinery equipment.
Key concepts: Bearing (navigation), Fault (geology), Blind signal separation, SIGNAL (programming language), Signal processing, Engineering, Computer science, Pattern recognition (psychology)