[1]刘景艳,李玉东,杨晓邦..遗传神经网络在齿轮故障诊断中的应用[J].郑州大学学报(工学版),2012,33(03):36-39.[doi:10.3969/j.issn.1671-6833.2012.03.009]
　LIU Jingyan,LI Yudong,YANG Xiaobang.Application of Genetic Neural Network to Gear Fault Diagnosis[J].Journal of Zhengzhou University (Engineering Science),2012,33(03):36-39.[doi:10.3969/j.issn.1671-6833.2012.03.009]
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遗传神经网络在齿轮故障诊断中的应用()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
33
期数:
2012年03期
页码:
36-39
栏目:
出版日期:
2012-05-10

文章信息/Info

Title:
Application of Genetic Neural Network to Gear Fault Diagnosis
作者:
刘景艳; 李玉东; 杨晓邦.
河南理工大学 电气工程与自动化学院,河南焦作,454000, 河南理工大学 电气工程与自动化学院,河南焦作,454000, 河南理工大学 电气工程与自动化学院,河南焦作,454000
Author(s):
LIU Jingyan;  LI Yudong; YANG Xiaobang
School of Electricity & Automation Engineering, Henan Poiytechnic Univerity, Jiaozuo 454000, China
关键词:
齿轮;  故障诊断;  神经网络;  遗传算法
Keywords:
gear; fault diagnosis; neural network ; genetic algorithm
分类号:
TP183
DOI:
10.3969/j.issn.1671-6833.2012.03.009
摘要:
由于齿轮故障征兆与故障之间具有非线性和耦合性等特点,采用BP神经网络对齿轮进行故障诊断存在着收敛速度慢和可靠性差等缺点,提出了一种基于遗传算法的BP神经网络齿轮故障诊断方法,即在利用BP神经网络对齿轮进行故障诊断的基础上,利用遗传算法对神经网络的权值和阈值进行修正,得到全局的最优值.仿真结果表明,该诊断策略具有故障诊断能力强和诊断效率高的特点,改善了齿轮故障诊断的精度和速度.
Abstract:
Because gear faults have characteristics of being nonlinear and coupling between fault symptoms andfault, BP neural network gear fault diagnosis has slow convergence speed and poor reliability, The BP neuralnetwork gear fault diagnosis method based on genelic algorithm is put forward. Namely, the BP neural networkis used in gear fault diagnosis, and genetic algorithm is applied to optimize the weights and thresholds of thenetwork. So the global optimal value is obtained, The simulation results show that the diagnosis strategy hasthe characteristic of strong diagnosis ability and high diagnosis effciency and improves the gear fault diagnosisprecision and speed.

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更新日期/Last Update: 1900-01-01