过程功率谱熵在转子振动定量诊断中的应用

Application of Process Power Spectrum Entropy in Rotor Vibration Quantitative Diagnosis

针对旋转机械振动过程的复杂性和振动故障产生的随机性,提出了1种以信息熵理论为基础,通过多测点、多转速下的功率谱信息熵(功率谱熵)差矩阵来描述旋转机械振动过程变化规律的故障定量诊断方法。采用在转子试验台模拟转子振动的4种典型故障,得到4个测点多转速下的振动故障数据;对这些故障数据进行分析和处理,求其功率谱熵矩阵。结果表明:通过对转子振动故障信号进行实例计算和分析,该方法在转子振动故障分类和故障严重程度判断方面效果良好。

Aiming at the complexity of rotating machinery vibration process and the randomcity of vibration fault, a fault quantitative diagnosis method which described the change disciplinarian of rotor vibration by power spectrum information entropy （power spectrum entropy） difference matrix under more measurement points and multi-speed based on the information entropy theory was presented. Four typical failures of rotor vibration were simulated based on rotor experiment and vibration fault data under more points and multi-speed were collected, and then the power spectrum entropy matrix was calculated through analyzing and processing the data. The resuh show that the validity of the method between distinguishing the rotor fault types and determining the fault severity is proved to be effective by example calculation and analysis of rotor vibration fault signals.