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基于集成包络谱的滚动轴承早期故障检测指标 被引量:4

Early fault detection index of rolling bearing based on integrated envelope spectrum
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摘要 针对常规统计指标对滚动轴承早期故障不敏感的问题,该研究基于集成包络谱(integrated envelope spectrum,IES)提出一种滚动轴承早期故障检测指标——集成包络谱谱峰因子(integrated envelope spectrum peak factor,IESPF),应用于轴承早期故障检测。首先,对信号进行快速谱相干(fast spectral coherence,Fast-SCoh)计算;然后,根据循环频率与谱频率的映射关系确定包含故障信息丰富的频带,并对该频带积分获得IES;最后,计算IES的最大值与其均方根值的比值,从而获得该研究所提指标IESPF,应用于轴承外圈故障检测。通过分析滚动轴承外圈模拟故障试验数据和疲劳试验数据表明,该研究所提指标对轴承外圈早期故障较敏感,适用于早期故障检测。 Aiming at the problem that conventional statistical index is not sensitive to the early fault of bearing,an early fault detection indicator of rolling bearings,integrated envelope spectrum peak factor(IESPF),was proposed based on integrated envelope spectrum(IES),which was applied to bearing degradation assessment.Firstly,the signal was calculated by the algorithm of fast spectral coherence(Fast-SCoh).Then the frequency band with rich fault information was determined according to the mapping relationship between cycle frequency and carrier frequency,and the frequency band was integrated to obtain the IES for bearing fault detection.Finally,the ratio of the maximum value in IES to the root mean square value of IES was calculated to obtain the IESPF proposed in this paper,and the degree of bearing fault was evaluated according to its value.The analysis of the experimental data and fatigue test data of artificial rolling bearing faults shows that the indexes proposed in this paper are sensitive to early faults and suitable for detection.
作者 杨新敏 郭瑜 田田 朱云贵 YANG Xinmin;GUO Yu;TIAN Tian;ZHU Yungui(Faculty of Mechanical and Electrical Engineering,Kunming University of Science and Technology,Kunming 650500,China)
出处 《振动与冲击》 EI CSCD 北大核心 2023年第10期67-73,共7页 Journal of Vibration and Shock
基金 国家自然科学基金(52165067) 云南省重大科技专项计划(202002AC080001) 昆明理工大学分析测试基金(2022P20193103005)。
关键词 滚动轴承 快速谱相干 集成包络谱(IES) 集成包络谱谱峰因子(IESPF) 早期故障检测 rolling element bearing fast spectral coherence integrated envelope spectrum(IES) integrated envelope spectrum peak factor(IESPF) early fault detection
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