基于融合信息熵距的转子裂纹-碰摩耦合故障诊断方法

针对转子系统的裂纹-碰摩耦合故障,提出了一种基于融合信息熵距的转子振动故障诊断方法.利用转子实验台模拟转子系统裂纹故障、碰摩故障及裂纹-碰摩耦合故障,并采集三种典型故障的振动加速度信号.利用时域的奇异谱熵、频域的功率谱熵、时-频域的小波能谱熵以及小波空间特征谱熵,计算融合信息熵距实现故障诊断.实例研究表明:这四种信息熵形成了综合评价转子振动状态的特征指标,多测点、多转速下的信息熵距曲线较好地区分了单一故障和耦合故障,有效地提高了转子振动故障诊断的准确性.测试信号与其对应的振动故障之间的信息熵距最小,信息熵距曲线位于坐标轴的最下方,达到了诊断单一故障和耦合故障的目的.

Diagnosis method for crack-rubbing coupled fault in rotor system based on integration of information entropy distance

For the crack-rubbing coupled fault in rotor system, a fault diagnosis method was proposed. Firstly, the rubbing fault, crack fault and crack-rubbing coupled fault were simulated on rotor test rig. The acceleration signals of each fault were collected. The integration of information entropy distance was calculated for fault diagnosis using singular spectrum entropy in time-domain, power spectrum entropy in frequency domain, wavelet energy entropy and wavelet spatial characteristics spectral entropy in frequency-time domain. The case study showed that these four information entropies could evaluate rotor vibration state comprehensively. Information entropy distance curves in multiple points and multiple speeds can effectively improve the accuracy and distinguish single and coupled faults. The information entropy distance between the test signal and its corresponding fault is the least and the information entropy distance curve is located in the bottom of the axis, so its fault category can be diagnosed.