Fault Diagnosis Expert System of Automobile Engine Based on Neural Networks

被引:3
|
作者
Jiang, Lulu [2 ,3 ]
Ni, Yong
Tan, Lihong [2 ,3 ]
He, Yong [1 ]
机构
[1] Zhejiang Univ, Coll Biosyst Engn & Food Sci, Hangzhou 310029, Zhejiang, Peoples R China
[2] Zhejiang Technol Inst Econ, Hangzhou 310018, Zhejiang, Peoples R China
[3] Zhejiang Technol Inst Econ, Hangzhou 310018, Peoples R China
关键词
neural network; engine; fault diagnosis; inspect and measurement;
D O I
10.4028/www.scientific.net/KEM.460-461.605
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
his paper reports a practical approach for detecting and diagnose engine faults in real-time based on both the historical and the real-time engine operation data using a specially design neural networks-based fault diagnosis expert system. This system consisted of multiple sensors for real-time monitoring, an engine database for historic data comparison, and a neural network-bases classifier for detecting faults based on both the real-time and the historic data. This neural network-based engine fault diagnosis system was evaluated in a series of validation tests. The results indicated that the system was capable to detect the predefined faults reliably, and the diagnosis error was less than 5%.
引用
收藏
页码:605 / +
页数:2
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