Entropy-based Grey Correlation Fault Diagnosis Prediction Model
in order to solve the fault diagnosis problem of automobile engine, the thesis puts forward an entropy-based grey correlation fault diagnosis prediction model. In light of the momentary of oil parameter for automobile engine, entropy-based data fusion can determine the weight of each factor in comprehensive evaluation. Then it makes forecast by grey correlation and evaluation of system oil. The result indicates that, the model is reliable, with strong generalization ability and higher failure recognition rate than that of the single models.
entropy grey correlation oil parameter fault diagnosis
Zhao Ying Kong Lifang He Guoliang
Air Force Logistic Academy Jiangsu Xuzhou 221008, China
国际会议
南昌
英文
448-451
2012-08-26（万方平台首次上网日期，不代表论文的发表时间）