Fault Diagnosis Mechanism Based on FTA and Bayesian for Large-Scale CNC Equipments

Abstract:

In view of the disadvantage of current FAT-based fault diagnosis method in large-scale complicated system, fault diagnosis method of heavy NC machine based on FTA and Bayesian is discussed. Firstly, building fault trees with the help of reachability matrix, and to set the determinate conditions at every node of fault tree combining FTA with rule reasoning, the minimum cut set of fault reasons are determined as a result of step by step screening fault tree from top-down; Secondly, Bayesian method is integrated into the fault tree diagnostic method to calculate the posterior probability triggered by each fault tree in order to locate the fault tree where the fault had occurred and ensure high efficiency of fault diagnosis; Finally, B/S based intelligent fault diagnosis system for large-scale CNC equipments is developed, and the feasibility and efficiency of this method are proved in an example of fault diagnosis of Φ 160 NC boring and milling machine.

• Periodical: Applied Mechanics and Materials (Volumes 236-237)
• Pages: 474-479
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.236-237.474
• Online since: November 2012
• Authors: Jin Fei Liu, Ming Chen, Ying Lei Li
• Keywords: Bayesian Algorithm, FAT, Fault Diagnosis System, Fault Tree, Reachability Matrix

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