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基于Hilbert边际谱的滚动轴承故障诊断方法 被引量:79

ROLLER BEARING FAULT DIAGNOSIS BASED ON HILBERT MARGINAL SPECTRUM
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摘要 Hilbert Huang变换是一种新的自适应信号处理方法,它适合于处理非线性和非平稳过程。通过对信号进 行Hilbert Huang变换,可以得到信号的Hilbert边际谱,它能精确地反映信号幅值随频率的变化规律。针对滚动轴承故 障振动信号的非平稳特征,提出了一种基于Hilbert边际谱的滚动轴承故障诊断方法。该方法在Hilbert边际谱的基础上 定义了特征能量函数,并以此作为滚动轴承的故障特征向量,建立M距离判别函数来识别滚动轴承的故障类型。对滚 动轴承的内圈、外圈故障信号的分析结果表明本文方法可以有效地提取滚动轴承故障特征。 Hilbert-Huang Transform (HHT) is a new and self-adaptive signal processing method which is suitable for non-linear and non-stationary process. By applying HHT to the signal the Hilbert marginal spectrum which can reflect accurately the signal amplitude changes with the frequency. Aiming at the non-stationary characteristics of bearing fauty signals, a roller bearing fault diagonsis method based on Hilbert marginal spectrum is put forward. The feature energy function based on Hilbert marginal spectrum is introduced, which is served as the fault feature vectors of roller bearings. Meanwhile, M-distance criterion function is established to identify the fault pattern. The analysis results from roller bearing signals with inner - race or out-race faults show that the diagnosis approach could extract fault characteristics effectively.
出处 《振动与冲击》 EI CSCD 北大核心 2005年第1期70-72,共3页 Journal of Vibration and Shock
基金 国家自然科学基金(编号:50275050) 高等学科博士点专项科研基金(编号:20020532024)资助项目
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