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仿生鳍条姿态测量及其误差分析
引用本文:欧世星,王光明,谭晓朋,郭晓俊. 仿生鳍条姿态测量及其误差分析[J]. 应用声学, 2017, 25(12): 43-45
作者姓名:欧世星  王光明  谭晓朋  郭晓俊
作者单位:轻工过程先进控制教育部重点实验室,轻工过程先进控制教育部重点实验室 江南大学,轻工过程先进控制教育部重点实验室
基金项目:国家自然科学基金资(NSFC 61403167);
摘    要:在复杂环境下齿轮箱信号往往会淹没在噪声信号中,特征向量难以提取。为了有效的进行故障诊断,提出了基于最大相关反褶积(MCKD)总体平均经验模态分解(EEMD)近似熵和双子支持向量机(TWSVM)的齿轮箱故障诊断方法。首先采用MCKD方法对强噪声信号进行滤波处理,在采用EEMD方法对齿轮箱信号进行分解,分解后得到本征模函数(IMF)分量进行近似熵求解,得到齿轮特征向量,最后将其输入到TWSVM分类器中进行故障识别。仿真实验表明,采用MCKD-EEMD方法能够有效的提取原始信号,与其他分类器相比,TWSVM的计算时间短,分类效果好等优点。

关 键 词:最大相关反褶积  总体平均经验模态分解  近似熵  双子支持向量机  齿轮箱故障诊断
收稿时间:2017-02-22
修稿时间:2017-03-14

Attitude Measurement and Error Analysis of Bionic Fin
Ou Shixing,Wang Guangming,Tan Xiaopeng and Guo Xiaojun. Attitude Measurement and Error Analysis of Bionic Fin[J]. Applied Acoustics(China), 2017, 25(12): 43-45
Authors:Ou Shixing  Wang Guangming  Tan Xiaopeng  Guo Xiaojun
Affiliation:Department of Electrical and Mechanical Engineering and Automation,National University of Defense Science and Technology,Department of Electrical and Mechanical Engineering and Automation,National University of Defense Science and Technology,Department of Electrical and Mechanical Engineering and Automation,National University of Defense Science and Technology
Abstract:Gearbox signals always tend to be drowned in the noise at a complex environment, resulting problem in feature vector extraction/which make difficulty for feature vector extraction. In order to effectively diagnose gearbox fault, a method for gearbox is proposed based on maximum correlated kurtosis deconvolution (MCKD) ensemble empirical mode decomposition (EEMD) approximate entropy and twin support vector machine (TWSVM). Firstly, the noise signal is filtered by MCKD method, then EEMD method is used to decompose the signal of gearbox. To get signal eigenvectors, the intrinsic mode functions (IMF) obtained from the decomposition is used to calculate approximate entropy. Finally, signal eigenvectors are input the TWSVM classifier for fault identification. Simulation results show that the MCKD-EEMD method can be used to extract raw signal effectively, and the TWSVM classifier performs a better classification.
Keywords:maximum correlated kurtosis deconvolution   ensemble empirical mode decomposition   approximate entropy    twin support vector machine   Gearbox fault diagnosis
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