A Misfire Fault Diagnosis System Based on Improved Neural Network

被引：0
|
作者：
Zhang, Kaiyu [1 ]
Deng, Jiwen [1 ]
Lu, Di [1 ]
机构：
[1] Harbin Univ Sci & Technol, Coll Elect & Elect Engn, Harbin, Peoples R China
来源：
MANUFACTURING SCIENCE AND TECHNOLOGY, PTS 1-8 | 2012年 / 383-390卷
关键词：
misfiring fault diagnosis; fuzzy theory; neural network; genetic algorithm;
D O I：
10.4028/www.scientific.net/AMR.383-390.1549
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Misfiring fault is one of the common faults of automobile engines. This paper presents an algorithm based improved neural network which is used for misfiring fault. It calculates the memberships of inputs and initializes the weights and thresholds of the neural network by genetic algorithm firstly, and then trains the improved neural network and uses it for diagnosis. By applying GUI function of MATLAB, a new man-machine interaction interface was designed. The results of experiment indicate that this algorithm can effectively carry out misfiring fault diagnosis.
引用
收藏
页码：1549 / 1554
页数：6
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