基于共振解调波束形成的滚动轴承故障定位方法研究  被引量:3

Fault localization method based on resonance demodulation beamforming for rolling bearings

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作  者:江文涛 郭永杰 伍星[1,3] 柳小勤 JIANG Wentao;GUO Yongjie;WU Xing;LIU Xiaoqin(Faculty of Mechanical and Electrical Engineering,Kunming University of Science and Technology,Kunming 650500;Inner Mongolia First Machinery Group Co.,Ltd.,Baotou 014032;School of Mechanical Engineering,Yunnan Vocational College of Mechanical and Electrical Technology,Kunming 650203)

机构地区:[1]昆明理工大学机电工程学院,云南昆明650500 [2]内蒙古第一机械集团有限公司,内蒙古包头014032 [3]云南机电职业技术学院机械工程学院,云南昆明650203

出  处:《机械设计》2024年第4期42-48,共7页Journal of Machine Design

基  金:国家自然科学基金(51875272);云南省科技重大专项资助项目(202002AC80001)。

摘  要:针对传统分析方法识别高频滚动轴承故障位置存在的定位混叠及精度问题,文中提出了基于共振解调波束形成的滚动轴承故障定位方法。该方法通过对轴承故障信号进行共振解调,从高频载波中提取含有故障信息的低频信号,然后选择含有故障信息的频率段采用近场波束形成算法进行定位,实现了在较大传声器间距下对高频轴承故障冲击信号进行定位同时也有效地解决了传统定位方法的不足。通过轴承故障试验台的定位试验验证了该方法的准确性,结果表明:该方法定位精度保持在95%以上,且能识别轴承的状态及其故障类型。The traditional analytical method suffers such problems as confusing localization and poor accuracy,when the location of the rolling bearings’high-frequency faults is identified.In this article,a fault-localization method is proposed,based on resonance demodulation beamforming,which is specially designed for rolling bearings.Efforts are made to extract the low-frequency signals with the fault information from the high-frequency carrier wave through resonant demodulation of the bearing-fault signals;then,the frequency band with the fault information for localization is selected,with the help of the near-field beamforming algorithm.It realizes the localization of the high-frequency bearing-fault impact signal with larger microphone spacing and effectively overcomes the traditional localization method’s shortcomings.Through the experiments on the bearing-fault test bench,it is verified that this method is accurate.The results show that this method’s accuracy in localization remains above 95%and both the state of the bearing and its fault type can be identified.

关 键 词:故障定位 滚动轴承 共振解调 波束形成 

分 类 号:TB532[理学—物理]

 

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