Impact Signal Analysis and Fault Diagnosis of High-Speed Automata

Abstract:

Aiming at the early fault diagnosis of the automata of small-caliber antiaircraft guns, a full set of theories and techniques for the early fault diagnosis of the high-speed automata, based on the techniques of the decomposition of motility patterns and the fusion of information entropy, have been established in this article by the strategy of combining of the theoretical research and the experiment study, which can deal with the practical problems of the superposition and interference of successive impulse signals, cope with the difficulties in the effective extraction of the weak signals of early faults in the environment with strong noises and in the determination of sensitive characteristic parameters, and overcome the disadvantages of the traditional methods of fault diagnosis such as its low conversation speed, the weakness in determining the accurate location of faults and the impotence in real time diagnosis. With the techniques of motility pattern decomposition and information entropy fusion, the efficiency and accuracy of the early fault diagnosis of automata will be increased and the study scope of the mechanical fault diagnosis discipline will be extended.

• Periodical: Applied Mechanics and Materials (Volume 108)
• Pages: 95-100
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.108.95
• Online since: October 2011
• Authors: Ming Zhi Pan, Hong Xia Pan, Run Peng Zhao
• Keywords: Fault Diagnosis, High-Speed Automata, Information Entropy, Motion Morphology

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