摘要
针对轴承性能时间序列概率信息求取及退化分析问题,对轴承振动、温度、摩擦力矩3种性能时间序列进行了研究,提出了一种基于自助最大熵法的概率密度函数,以及模糊等价关系的退化指标量化方案。利用自助最大熵原理,建立了轴承性能时间序列训练组的概率密度函数;依据验证组落入函数区间的频率证明了模型的准确性;根据模糊集合理论提取了轴承性能信号中的模糊等价关系,结合0.5阈值参数进行了轴承退化特征评估。研究结果表明:轴承振动、温度的区间误报率分别为2%和4%,最小退化系数分别为0.600和0.609,表明概率信息求取较为准确,且轴承的服役状况良好;轴承摩擦力矩区间误报率较高,为66%,最小退化系数为0.477,相对于训练组,验证组的变异显著,说明轴承具有明显的退化迹象。
Aiming at the problem of probability information extraction and degradation analysis of bearing performance time series,three performance time series of bearing vibration,temperature and friction torque were researched,and probability density function and degradation index quantification scheme were proposed based on bootstrap-maximum entropy method and fuzzy equivalent relation.The probability density function of the training group of bearing performance time series was established by using the bootstrap-maximum entropy principle,and the accuracy of above proposed model was proved according to the frequency of the verification group falling into the function interval.Then,the fuzzy equivalence relation of bearing performance signals was extracted by the fuzzy-set theory,and the bearing degradation characteristics was estimated by combining the 0.5 threshold parameter.The results indicate that the interval false positive rate of bearing vibration and temperature is only 2%and 4%,and the minimum degradation coefficient is 0.600 and 0.609 respectively,indicating that the probability information obtained is accurate,and the service condition of bearings is good.The interval false positive rate of bearing friction torque is 66%,and the minimum degradation coefficient is 0.477,indicating that the verification group has occurred significant variation,and the corresponding bearing shows obvious degradation signs.
作者
常振
魏剑波
平晓明
曹茂来
王二化
CHANG Zhen;WEI Jian-bo;PING Xiao-ming;CAO Mao-lai;WANG Er-hua(Hangzhou Bearing Test&Research Center Co.,Ltd,Hangzhou 310022,China;Machinery Industry Bearing Quality Inspection Center(Hangzhou),Hangzhou 310022,China;Department of Intelligent Equipment,Changzhou College of Information Technology,Changzhou 213164,China)
出处
《机电工程》
CAS
北大核心
2021年第1期27-34,共8页
Journal of Mechanical & Electrical Engineering
基金
国家重点研发计划资助项目(2018YFB2000404)
宁波市“科技创新2025”重大专项资助项目(2018B10005)
常州高技术重点实验室资助项目(CM20183004)。
关键词
轴承性能
摩擦力矩
概率密度
退化分析
bearing performance
friction torque
probability density
degradation analysis
