一种旋转机械系统耦合故障诊断的新方法

In rotating machinery systems, the nonlinear crack opening/closing behavior related to the rotor vibration response, as well as defects or faults such as transient rubbing contact between dynamic and static parts or gear meshing impact, and loose base, etc., can all excite nonlinear vibrations. Moreover, different fault excitation sources interact with each other, resulting in complex fault coupling forms and increasing the difficulty of fault diagnosis. For this reason, a coupled fault diagnosis method for rotating machinery systems based on eigenmode function energy moment - grey relational analysis is proposed. Using the energy moment measure, features are respectively extracted from the eigenmode functions of the empirical mode decomposition of the vibration response signal, and then the grey relational analysis is further utilized to quantitatively evaluate the correlation characteristics of the coupled faults, thus realizing the recognition of complex coupled fault patterns. The results of simulation and experimental studies verify the effectiveness of the method. Moreover, using this method, the severity of faults can be ranked, which can strongly support the formulation of reasonable maintenance decisions.

旋转机械系统中，与转子振动响应相关的裂纹非线性开/合行为以及动-静件瞬态碰摩接触或齿轮啮合冲击、机座松动等缺陷或故障均会激起非线性振动，且不同的故障激励源相互作用，导致复杂的故障耦合形态，增加了故障诊断的难度。为此提出一种基于本征模函数能量矩-灰色关联分析的旋转机械系统耦合故障诊断方法。应用能量矩测度，从振动响应信号的经验模态分解本征模函数中分别抽取特征，然后进一步利用灰色关联分析对耦合故障的关联特性进行定量评价，从而实现复杂耦合故障模式的识别。仿真与实验研究结果验证了方法的有效性。而且，利用本方法可以对故障的严重程度进行排序，可以有力地支持合理的维修决策的制定。