|本期目录/Table of Contents|

[1]陈汉新,刘岑,杨诗琪.检测与诊断齿轮裂纹故障的一种方法[J].武汉工程大学学报,2014,(09):53-58.[doi:103969/jissn16742869201409011]
　CHEN Han xin,LIU Cen,YANG Shi qi.Gearbox fault diagnosis of sequential probability ratio based on radial basis function optimized particle filter[J].Journal of Wuhan Institute of Technology,2014,(09):53-58.[doi:103969/jissn16742869201409011]
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检测与诊断齿轮裂纹故障的一种方法(/HTML)
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《武汉工程大学学报》[ISSN:1674-2869/CN:42-1779/TQ]

卷:
期数:
2014年09期
页码:
53-58
栏目:
机电与信息工程
出版日期:
2014-09-30

文章信息/Info

Title:
Gearbox fault diagnosis of sequential probability ratio based on radial basis function optimized particle filter
文章编号:
16742869(2014)09005306
作者:
陈汉新; 刘岑; 杨诗琪
武汉工程大学机电工程学院，湖北 武汉430205
Author(s):
CHEN Hanxin;  LIU Cen;  YANG Shiqi
School of Mechanical and Engineering, Wuhan Institute of Technology, Wuhan 430205, China
关键词:
粒子滤波; 序贯概率比检验; 齿轮箱; 故障诊断
Keywords:
sequential probability ratio test;  gearbox;  fault diagnosis
分类号:
TH165+.O3;212.3
DOI:
103969/jissn16742869201409011
文献标志码:
A
摘要:
基于径向基函数 (RBF)网络优化的粒子滤波降噪与序贯概率比检验相结合的原理，提出了一种检测与诊断齿轮裂纹故障的方法，并采集一种无裂纹与另外两种存在差异裂纹齿轮的水平方向振动信号，对该方法进行验证.首先，运用RBF网络优化的粒子滤波程序对原始振动信号进行降噪预处理，将振动真实值从中提出；然后，利用时域分析法提取振动真实值的特征参数（峭度值）序列；最后，将特征值序列输入序贯概率比检验程序，根据结果图综合分析对不同齿轮故障进行区分.结果表明建立的优化粒子滤波程序对原始振动信号降噪处理效果良好，获得了细致、准确和稳定的振动信号；序贯概率比检验能比较与区分齿轮不同的故障，改进了齿轮箱故障检测与诊断效果.
Abstract:
A method for the detection and diagnosis of gear crack was put forward based on the principles of radial basis function (RBF) network optimized particle filter and sequential probability ratio test. The horizontal vibration signals of a crackfree and two different crack gears were collected to verify the method. Firstly, the true vibration value was extracted from the original signals after the RBF optimized particle filter operating. Then, the time domain analysis was used to extract characteristic parameter sequence (kurtosis value). Finally, failure mode was determined according to the result map of which the kurtosis value sequence was put into the sequential probability ratio test procedures. The results show that the established procedure for optimized particle filter has a good effect on noise reduction with detailed, accurate and stable vibration signals; gears’ different failures can be compared and distinguished by sequential probability ratio test, which improves the effect of gearbox fault detection and diagnosis.

参考文献/References:

［1］GORDON N J, SALMOND D J, SMITH A F M . A novel approach to nonlinear/nonGaussian Bayesian state estimation［J］. IEE Proceedings on Radar and Signal Processing, 1993, 140(2): 107113.［2］MERWE R V, DOUCET A, FREITAS N D,et al. The unscented particle filter［R］. Technical Report CUED/FINPENG/TR 380, Cambridge University Engineering Department, 2000.［3］CHEN Hanxin, TU Ling, SUN Kui, et al. Noise reduction method based on RBF network optimized particle filter［C］//Key Engineering Materials Vols,(589590)2014:629633.［4］WALD A. Sequential Analysis［M］. New York: Wiley,1947.［5］ WALD A. Sequential tests of statistical hypotheses［J］. Ann. Math. Statist. 1945, 16(2): 117186.［6］ STANDER C J, HEYNS P S, SCHOOMBIE W. Using vibration monitoring for local fault detection on gears operating under fluctuating local conditions［J］. Mechanical Systems and Signal Processing. 2002, 16(6):10051024.［7］FAKHFAKH T, CHAARI F, HADDER M. Numerical and Experimental Analysis of a Gear System with Teeth Defects［J］. International Journal of Advanced Manufacturing Technology, 2005, 25(56):542550.［8］YU Chenggang, SU Bingjing, A nonparametric sequential ranksum probability ratio test method for binary hypothesis testing［J］. Signal Processing, 2004(84): 12671272.

相似文献/References:

[1]尚云飞,陈汉新,孙魁.面向齿轮箱故障诊断的序贯概率比检验理论和方法[J].武汉工程大学学报,2011,(12):65.
　SHANG Yun fei,CHEN Han xin,SUN Kui.Theories and methods of gearbox fault diagnosis oriented sequentialprobability ratio test[J].Journal of Wuhan Institute of Technology,2011,(09):65.
[2]黄文健,黄瑾珉,曹承昊,等.基于PCA与SPRT的机械故障诊断方法研究[J].武汉工程大学学报,2018,40(06):678.[doi:10. 3969/j. issn. 16742869. 2018. 06. 019]
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[3]方　璐,范东亮,张光宇,等.一种带变异算子的粒子群优化粒子滤波降噪算法[J].武汉工程大学学报,2019,(04):392.[doi:10. 3969/j. issn. 1674?2869. 2019. 04. 017]
　FANG Lu,FAN Dongliang,ZHANG Guangyu,et al.Particle Filter Algorithm Based on Particle Swarm Optimization with Mutation Operator for Noise Reduction[J].Journal of Wuhan Institute of Technology,2019,(09):392.[doi:10. 3969/j. issn. 1674?2869. 2019. 04. 017]

备注/Memo

备注/Memo:
收稿日期：20140717基金项目：国家自然科学基金（61273176）;教育部新世纪优秀人才支持计划（201010621237）;湖北省教育厅科学技术研究重大项目(Z20101501)；教育部留学回国人员科研启动基金（20091001）作者简介：陈汉新（1969），男，湖北武汉人.教授，博士.研究方向：机械故障诊断及控制.
更新日期/Last Update: 2014-10-10