Fault Diagnosis for Diesel Engines Based on Discrete Hidden Markov Model

摘要：

Fault diagnosis based on Principal Component Analysis (PCA) and Discrete Hidden Markov Model (DHMM) for engine are studied. First, the vibration signal feature extraction from the diesel engine is realized by PCA; next, the vibration signal feature extraction algorithm is designed; then DHMM is applied for fault diagnosis; furthermore, a fault classifier based on DHMM with diagnostic databases is developed; and, finally, the fault diagnosis strategies of diesal vibration signal is conceived. The practical application results showed that the method proposed in this paper is feasible for diesel engine fault diagnosis that can be achieved with highly accuracy.

关键词： Principal Component Analysis Discrete Hidden Markov Model Fault diagnosis Diesel Engines Construction machinery

作者: Jia-shan Huang Ping-jun Zhang

作者单位: Electronic and Electric Engineering Department Fujian University of Technology Fu Zhou, P.R.China

会议类型: 国际会议

会议名称: 2009 Second International Conference on Intelligent Computation Technology and Automation(2009 第二届IEEE智能计算与自动化国际会议 ICICTA 2009)

会议地点: 长沙

会议语种:英文

页码: 1465-1468

在线出版日期: 2009-10-10（万方平台首次上网日期，不代表论文的发表时间）