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[1]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):678-684.[doi:10. 3969/j. issn. 16742869. 2018. 06. 019]
 HUANG Wenjian,HUANG Jinmin,CAO Chenghao,et al.Mechanic Fault Diagnosis Based on PCA and SPRT[J].Journal of Wuhan Institute of Technology,2018,40(06):678-684.[doi:10. 3969/j. issn. 16742869. 2018. 06. 019]
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基于PCA与SPRT的机械故障诊断方法研究(/HTML)
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《武汉工程大学学报》[ISSN:1674-2869/CN:42-1779/TQ]

卷:
40
期数:
2018年06期
页码:
678-684
栏目:
机电与信息工程
出版日期:
2018-12-28

文章信息/Info

Title:
Mechanic Fault Diagnosis Based on PCA and SPRT
文章编号:
20180619
作者:
黄文健黄瑾珉曹承昊陈汉新*
武汉工程大学机电工程学院,湖北 武汉 430205
Author(s):
HUANG Wenjian HUANG Jinmin CAO Chenghao CHEN Hanxin*
School of Mechanical and Electrical Engineering, Wuhan Institute of Technology, Wuhan 430205, China
关键词:
故障诊断主元分析法序贯概率比检验齿轮箱齿轮裂纹
Keywords:
fault diagnosis principal component analysis sequential probability ratio test gear casegear crack
分类号:
TH165+.3
DOI:
10. 3969/j. issn. 16742869. 2018. 06. 019
文献标志码:
A
摘要:
提出了一种基于主元分析法(PCA)和序贯概率比检验(SPRT)的齿轮箱故障诊断新方法。选用正常的和有裂纹的齿轮建立实验模型,采用小波包变换对齿轮箱实验系统采集的振动信号进行预处理。采用时域信号分析方法提取振动信号的特征参数,并运用PCA对数据进行降维。选取降维后贡献率最大的主元作为测试参数,验证了所提出的SPRT算法和均方根误差,并检测了该方法的诊断能力。结果表明,该方法对于齿轮箱的齿轮状况识别是有效且实用的。
Abstract:
The experimental model was established using the normal gears and the gears with cracks, where the collected vibration signals were preprocessed using wavelet transform, and then the characteristic parameters of the vibration signals were extracted using the time domain signal analysis, and the dimension of which was reduced by the principal component analysis method. After that, the principal components with the largest contribution rate were selected as the testing parameters to verify the proposed algorithm for sequential probability ratio test (SPRT) and the root mean square error(RMSE) and to test the diagnostic ability of the proposed method. The experimental results show that the proposed method is effective and practical to identify the gear conditions in gearbox.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2018-06-29基金项目:国家自然科学基金(51775390);湖北省科技厅重大专项项目(2016AAA056)作者简介:黄文健,硕士研究生。E-mail:799851115@qq.com*通讯作者:陈汉新,教授,博士。E-mail:pg01074057@163.com引文格式: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(6):678-684.
更新日期/Last Update: 2018-12-22