An intelligent fault diagnosis system for newly assembled transmission

被引：20

作者：

Shang, Wenli ^{[1
]}

Zhou, Xiaofeng ^{[1
]}

Yuan, Jie ^{[2
]}

机构：

[1] Chinese Acad Sci, Shenyang Inst Automat, Ind Control Network & Syst Lab, Shenyang 110016, Peoples R China

[2] Xinjiang Univ, Coll Elect Engn, Xinjiang 830021, Peoples R China

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2014年 / 41卷 / 09期

基金：

中国国家自然科学基金;

关键词：

Vibratory signal; Feature extraction; Fault classification; Order spectrum analysis; Genetic search algorithm; BP neural network; HILBERT-HUANG TRANSFORM; WAVELET TRANSFORM; GEAR; IDENTIFICATION; CLASSIFICATION; DECOMPOSITION; SPECTRUM;

D O I：

10.1016/j.eswa.2013.12.045

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Newly assembled automobile transmission has its particular failure characteristic, strict quality testing working procedure on the assembly line is important for quality of automobile transmission. In this paper, we introduce a new automatic fault detection method for automobile transmission. A fault diagnosis expert system for newly assembled transmission is presented, related method of knowledge representation, feature extraction and fault classification is given. Order spectrum analysis method is used to analyze vibratory signal of automobile transmission. After initial feature vectors set are obtained, improved genetic search strategy is used to select fault features, so as to reduce the dimension of feature vector set. Selected feature vector sets are inputted into the BP neural network for fault identification and classification of the newly assembled automobile transmission. A large number of data are collected from industrial site and analyzed, proposed algorithm is verified to be effective and exact. (C) 2014 Elsevier Ltd. All rights reserved.

引用

页码：4060 / 4072

页数：13

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