多传感器信息融合的滚动轴承振动性能研究  

Study on Rolling Bearing Vibration Performance by Multi-sensors Information Fusion

作　　者：米月花 霍国涛 MI Yuehua;HUO Guotao(School of Information and Mechatronics Engineering,Zhengzhou Business University,Gongyi 451200,He′nan,China;College of Mechanical Engineering and Applied Electronics Technology,Beijing University of Technology,Beijing 100124,China)

机构地区：[1]郑州商学院信息与机电工程学院,河南巩义451200 [2]北京工业大学机械工程与应用电子技术学院,北京100124

出　　处：《机械科学与技术》2021年第8期1233-1239,共7页Mechanical Science and Technology for Aerospace Engineering

基　　金：国家自然科学基金项目(11572012);教育部产学研协同育人项目(201802108033)。

摘　　要：在变工况和多传感器条件下,分析滚动轴承振动性能的主要影响因素并进行排序。对采集到的数据样本进行均值归一化处理,运用最大熵法计算归一化样本的概率密度函数;基于概率密度函数交集法,求解载荷、转速等数据样本与振动数据样本的概率密度函数的重合面积;融合灰自助法和最大熵法,分析4个工位温度数据样本对轴承振动性能的综合影响度,最终求解出滚动轴承振动性能的主要影响因素。试验研究结果表明,滚动轴承C276909NK2W1在服役过程中,径向载荷、轴向载荷、转速和温度对其振动性能的影响度分别为0.7446、0.2910、0.2903、0.2436,即该轴承的振动性能的主要影响因素为径向载荷,然后依次为轴向载荷、转速和温度。The main influence factors are analyzed and sorted on the vibration performance of rolling bearings under the conditions of variable working condition and multi-sensors.The data samples collected were mean-value-normalized and the probability density functions of the normalized samples were calculated with the maximum entropy method.Based on the probability density function-intersection method,the overlap areas of probability density functions were solved for load,speed and vibration data samples.The grey-bootstrap method and the maximum entropy method were fused to analyze the comprehensive influence degree of 4 temperature data samples on vibration performance of rolling bearing.Finally,the main influence factors were solved for vibration performance of rolling bearing.The experimental results show that the influence degrees of radial load,axial load,speed and temperature are 0.7446,0.2910,0.2903 and 0.2436 respectively on the vibration performance of the rolling bearing C276909NK2W1,which means the main influence factors of the bearing vibration performance is radial load,then the axial load,speed and temperature.

关 键 词：滚动轴承 振动性能 多传感器 最大熵法 概率密度函数交集法 灰自助法 

分 类 号：V233.1[航空宇航科学与技术—航空宇航推进理论与工程] TH133.33[机械工程—机械制造及自动化]