Fault detection in internal combustion engines using wavelet analysis

被引：0

作者：

Chandroth, GO ^{[1
]}

Staszewski, WJ ^{[1
]}

机构：

[1] Univ Sheffield, Dept Comp Sci, Artificial Intelligence Grp, Sheffield S1 4DP, S Yorkshire, England

来源：

COMADEM '99, PROCEEDINGS | 1999年

关键词：

diesel engine; fault detection; signal processing; wavelets;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The analysis of internal combustion processes is an important element in monitoring the performance of engines. These processes are very difficult to model due to their stochastic nature. This paper presents the wavelet analysis to study diesel engine pressure and vibration data for fault diagnostics. The continuous and orthogonal wavelet transforms have been used to reveal the time-frequency nonstationary behaviour of the data. The results show that different engine faults can be properly clustered using wavelet-based feature selection procedure.

引用

页码：7 / 15

页数：9

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