Simulation for Automotive Engine Fault Diagnosis Method

Abstract:

For engine fault diagnosis problem, an engine fault diagnosis method based on particle swarm optimization algorithm is proposed. The velocity and spatial position of all the particles in the particle swarm are updated, in order to provide accurate data basis for the engine fault diagnosis. Particle swarm optimization method is utilized to process iteration for all particles, so as to determine whether failure exists in components of engine. Experimental results show that with the proposed algorithm to diagnose engine fault can effectively improve the accuracy of fault diagnosis, and achieved the desired results.

• Periodical: Applied Mechanics and Materials (Volumes 687-691)
• Pages: 882-885
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.687-691.882
• Online since: November 2014
• Authors: Huan Xue Liu, Guang Dong Zhang, Zhen Zhong Zhang
• Keywords: Fault Diagnosis, Particle Swarm, Pre-Failure

References

[1] Xie Kefu, Luo AN. Fuzzy diagnosis system optimized with genetic algorithm for power transformer [J]. ELECTRIC POWER AUTOMATION EQUIPMENT, 2005, 25(4): 55-58.

[2] Gu Zhenyu. Single-phase ground fault detection and treatment about the 10kV distribution line [J]. MANAGEMENT & TECHNOLOGY OF SME, 2011. 1: 292-293.

[3] Qiu Chidong, Tan Yue, Ren Guang. A detection method for bearing faults of marine motors based on multi-taper technique [J]. Journal of Dalian maritime university, 2008. 4: 135-139.

[4] Lv Jingxiu, Ma Qinglin, Wang Xin. Fault Diagnosis of Asynchronous Induction Motor Based on Fuzzy Neural Network [J]. Colliery mechanical & electrical technology，2009，4：4-7.

[5] Chen Ke, Li Ye, Chen Lan. Ensemble empirical mode decomposition for power quality detection applications [J]. Computer simulation, 2010. 3: 263-266.