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中文摘要：
机电设备的复合故障往往同时或级联出现，其振动信号常表现为多故障特征的相互耦合。基于波形匹配的思想，兼备优良性质的多小波拥有多个尺度函数和小波函数，可以很好地匹配复合故障的各种特征波形，从而实现复合故障耦合特征的一次性分离与提取。基于提升框架的多小波构造方法不依赖于傅里叶变换，具有算法简单，运行速度快等优点。研究类似二代小波变换的多小波提升框架分解和重构算法。基于Hermite样条插值，构造了紧支、双正交、对称和4阶逼近阶的多小波，并给出其相应的前处理算法。针对机电设备复合故障问题，改进了多小波后处理流程，使得解耦的特征信息能够清晰地呈现于多小波分析结果的不同通道中。将提出的方法应用于轴承试验台和电力机车走行部复合故障诊断中，结果显示该方法可以有效地实现试验台轴承内圈故障和转轴不规则弯曲故障的分离和提取，并成功解耦出机车轴承外圈和滚动体损伤复合故障。
英文摘要：
Compound faults of electromechanical equipment always occur simultaneously and in a cascading way. Based on signal matching, multiwavelets with good properties have several scaling functions and wavelet functions. Therefore, they could better match various features of compound faults, and separate and extract compound features at one time. The construction of multiwavelets based on lift frame does not depend on the Fourier transform, and the algorithm is simple and fast. Hence, multiwavelet transforms via lift frame like the second wavelet transforms are studied. Based on Hermite spline interpolation, the new multiwavelets with short support, biorthogonality, symmetry and fourth approximate order are designed, and the corresponding preprocessing algorithm is given. Aimed at the problem of compound faults, posttreatment procedure is modified and decoupled features are clearly presented in different channels of analysis results of multiwavelets. The proposed method is applied to compound faults diagnosis for beating test bench and traveling unit of electric locomotive. The results show that this method can effectively separate and extract the features of bearing inner-race fault and shaft anomalous bending, and successfully decouple the bearing outer-race defect and roller defect of the locomotive.
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