2018 Vol.1 Aug No.4

• Title: System intelligent fault diagnosis method combining fault tree and BAM neural network
• Name: Vivian Yvonne
• Company: Dickinson State University, America
• Abstract:

  Aiming at the problems of low effectiveness and long time of fault diagnosis in artillery system, an intelligent fault diagnosis method based on fault tree and BAM neural network is proposed. The fault tree structure function and the minimum partition set are determined by analyzing the characteristics of network diagnosis, and the fault tree theory fusion based on BAM neural network is completed. On this basis, through the qualitative diagnosis and quantitative diagnosis of common faults of artillery system, the importance of fault tree is determined, and the new diagnosis method can run smoothly. The experimental results show that the intelligent fault diagnosis method combined with fault tree and BAM neural network is used to diagnose the fault. The effectiveness was increased by 40 and the diagnostic time was shortened by 20 s.

• Keyword: fault tree; BAM neural network; intelligent fault diagnosis; structure function; minimum cut set; qualitative analysis; quantita
• DOI: 10.12250/jpciams2018040113
• Citation form: Vivian Yvonne.System intelligent fault diagnosis method combining fault tree and BAM neural network[J]. Computer Informatization and Mechanical System, 2018, vol. 1, pp. 33-38.

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