近似熵及其在机械设备故障诊断中的应用

APPROXIMATE ENTROPY AND ITS APPLICATIONS IN MECHANICAL FAULT DIAGNOSIS

  • 摘要: 近似熵从衡量时间序列复杂性的角度提供了一种表征信号整体特征的无量纲指标,具有计算所需数据短、抗噪及抗野点能力强、对确定性信号和随机信号都适用等特点.本文介绍了近似熵的概念、性质及其快速算法,并对某汽轮机组轴瓦松动维修前后不同状态下的振动信号进行了分析,结果表明,近似熵在表征信号的复杂性方面具有很强的能力,从而为机械设备状态监测与故障诊断提供了一种行之有效的新方法.

     

    Abstract: Approximate Entropy (ApEn) provides a new dimensionless factor to denote the irregularity of time series from the view of complexity measuring. Only short time-series are needed to calculate the ApEn of random signal or ascertain signals with high anti-interference ability. The conception, nature and a practical fast algorithm are introduced. Successful application has been achieved to analyze the looseness fault in bearing bushing of turbo-generator set. The results show that ApEn has high ability to quantify the complexity of signals, thereby providing an effective technology for condition monitoring and fault diagnosis of mechanical equipment.

     

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