Bayesian network based on a fault tree and its application in diesel engine fault diagnosis

Gang Qian; Shengguo Zheng; Longhan Cao

doi:10.1117/12.664626

2 May 2006 Bayesian network based on a fault tree and its application in diesel engine fault diagnosis

Gang Qian, Shengguo Zheng, Longhan Cao

Proceedings Volume 6042, ICMIT 2005: Control Systems and Robotics; 60421P (2006) https://doi.org/10.1117/12.664626
Event: ICMIT 2005: Merchatronics, MEMS, and Smart Materials, 2005, Chongqing, China

Abstract

This paper discusses the faults diagnosis of diesel engine systems. This research aims at the optimization of the diagnosis results. Inspired by Bayesian Network (BN) possessing good performance in solving uncertainty problems, a new method was proposed for establishing a BN of diesel engine faults quickly, and diagnosing faults exactly. This method consisted of two stages,namely the establishment of a BN model, and a faults diagnosis of the diesel engine system using that BN mode. For the purpose of establishing the BN, a new algorithm, which can establish a BN quickly and easily, is presented. The Fault Tree (FT) diagnosis model of the diesel engine system was established first. Then it was transformed it into a BN by using our algorithm. Finally, the BN was used to diagnose the faults of a diesel engine system. Experimental results show that the diagnosis speed is increased and the accuracy is improved.

Citation Download Citation

Gang Qian, Shengguo Zheng, and Longhan Cao "Bayesian network based on a fault tree and its application in diesel engine fault diagnosis", Proc. SPIE 6042, ICMIT 2005: Control Systems and Robotics, 60421P (2 May 2006); https://doi.org/10.1117/12.664626

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