Automaton Fault Diagnosis Based on Motion Morphology and Information Entropy

Abstract:

Online monitoring and fault diagnosis is an important link of guaranteeing the equipment smooth operation and reliable working, which receives general concern. This subject uses the strategy of combining theoretical research and experimental research, and establishes a set of automaton fault diagnosis theory and method based on motion morphology and information entropy. It solves the following problems, the weak fault signals in the short-time and transient vibration response signals are easy to be drowned in practical application, effective and sensitive characteristic parameters are difficult to be extracted, accurate positioning of fault and real-time diagnosis are difficult to be realized. Use the motion morphology and information entropy to put forward new ideas and methods for the short-time and transient vibration signals analysis processing and feature extraction, and is applied in artillery automaton field, which expands the research scope of mechanical fault diagnosis subject.

• Periodical: Applied Mechanics and Materials (Volumes 121-126)
• Pages: 3175-3179
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.121-126.3175
• Online since: October 2011
• Authors: Ming Zhi Pan, Hong Xia Pan, Run Peng Zhao
• Keywords: Automaton, Fault Diagnosis, Information Entropy, Motion Morphology

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