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作 者:朱敏 段志善[1] 郭宝良[1] ZHU Min;DUAN Zhi-shan;GUO Bao-liang(School of Mechanical and Electrical Engineering,Xi’an University of Architecture and Technology,Shaanxi Xi’an710055,China)
机构地区:[1]西安建筑科技大学机电工程学院,陕西西安710055
出 处:《机械设计与制造》2020年第5期63-67,共5页Machinery Design & Manufacture
基 金:国家自然科学基金青年科学基金项目(51105292);教育部博士点基金项目(20126120110009);陕西省科技攻关项目(2013K07-09);陕西省教育厅专项基金项目资助(2013JK1032)。
摘 要:为解决振动机械故障诊断中如何更有效地在复杂信号中提取有用的故障信号的问题,提出了一种优良降噪算法。先将原始信号用小波包降噪,对降噪后的信号进行EEMD分解,然后将分解得到的固有模态分量(IMF)构建不同的带通滤波器,利用算法逼近度指标和相关系数建立优良降噪算法的判断准则,以此来选择最优的滤波器组合。对振动筛轴承信号进行仿真,用新算法处理仿真信号,结果显示,故障信号被保留下来,其他信号均被滤除。同时用该降噪算法分析了实测振动筛轴承信号,所得的结果合理有效。In order to solve the problem of how to more effectively extract fault signals in complex signals in vibration machine fault diagnosis,an excellent noise reduction algorithm is proposed in this paper. First use the wavelet packet to the original signal noise reduction,the denoised signal is decomposed by EEMD,Then,the decomposed intrinsic modal function(IMF)are constructed with different bandpass filters,The criterion of excellent noise reduction algorithm is established by using algorithm approximation degree index and correlation coefficient,so as to select the optimal filter combination. The signal of the vibration screen is simulated,and the simulation signal is processed by the excellent noise reduction algorithm. The result shows that the fault signal is preserved and the other signals are filtered out. At the same time,the signals of the vibration screen bearings are analyzed by the algorithm,and the results are reasonable and effective.
关 键 词:集合经验模态分解(EEMD) 小波包降噪 带通滤波器 优良降噪算法
分 类 号:TH16[机械工程—机械制造及自动化] TH133.33
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