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作 者:张山林 陈乃建[1] 李亚辉 任升峰[1,2] 徐玉兴 ZHANG Shan-lin;CHEN Nai-jian;LI Ya-hui;REN Sheng-feng;XU Yu-xing(School of Mechanical Engineering,University of Jinan,Jinan 250022,China;Shandong Linqing Bearing Industry Technology Research Institute,Liaocheng 252600,China;Shandong Zhuogong Precision Bearing Co.Ltd.,Liaocheng 252600,China)
机构地区:[1]济南大学机械工程学院,山东济南250022 [2]山东临清轴承产业技术研究院,山东聊城252600 [3]山东卓工精密轴承有限公司,山东聊城252600
出 处:《山东工业技术》2023年第4期21-27,共7页Journal of Shandong Industrial Technology
基 金:山东省轴承智能制造创新创业共同体资助项目。
摘 要:针对轴承振动与噪声源零件识别与检测问题,利用小波包分解的方法来分析轴承的振动噪声信号:根据待测轴承振动信号特点,确定小波包分解的小波函数及分解层数,得到了轴承振动信号在频域的信息;通过构造小波包能量谱来分析各个频段上振动信号的特征,根据各个小波包空间能量值的大小判断轴承振动的剧烈程度;通过小波包重构算法对轴承振动噪声贡献较大的小波包空间进行重构,得到具有较高信噪比的重构信号,便于进行频谱分析。结果表明,本文的检测方法可以较准确的识别出新出厂轴承中振动噪声的主要来源,对于后期实现轴承静音降噪具有重要意义。In order to detect the main source of vibration and noise in new factory bearings;The method of wavelet packet decomposition is used to analyze the vibration and noise signal of bearing.According to the characteristics of the bearing vibration signal to be measured,the wavelet function and decomposition level of wavelet packet decomposition are determined,and the information of bearing vibration signal in frequency domain is obtained;By constructing wavelet packet energy spectrum,the characteristics of vibration signals in each frequency band are analyzed,and the intensity of bearing vibration is judged according to the spatial energy value of each wavelet packet;Through the wavelet packet recovery algorithm,the wavelet packet space which contributes a lot to the bearing vibration and noise is reconstructed,and the reconstructed signal with high signalto-noise ratio is obtained,which is convenient for spectrum analysis.The results show that the detection method in this paper can accurately identify the main sources of vibration and noise in the new factory bearings,which is of great significance for the later realization of bearing mute and noise reduction.
分 类 号:TP18[自动化与计算机技术—控制理论与控制工程]
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