Adaptive Neural Fuzzy Networks Model of Automobile Performance Monitoring

被引:1
|
作者
Kong Lifang [1 ]
Li Dong [1 ]
Zhao Ying [1 ]
机构
[1] AF Logist Acad, Xuzhou 221008, Jiangsu, Peoples R China
关键词
Fault detection; Auto-engine; Performance monitoring; Adaptive neural fuzzy interference system; FAULT-DIAGNOSIS;
D O I
10.1109/IHMSC.2012.113
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
the model for automobile engine performance monitoring and fault detection was proposed based on adaptive neural fuzzy interference system. With recognition mechanism of the adaptive neural fuzzy interference system, according to the properties of entropy, this paper using entropy optimizes the input interface of adaptive neural fuzzy interference system , this model was combined with characteristic performance of automobile engine to attain the degrees of engine performance's abnormal state for monitoring engine performance. The approach can sensitively and accurately reflect the whole performance of the engine. Meanwhile, this method improves the rate of identifying whether the performance of the engine is normal or not, finds out the potential forepart fault of engine and prevents the spread of the fault. The validity of this method is testified by monitoring certain type of cummins engine 6BT5.9.
引用
收藏
页码:72 / 75
页数:4
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