应用EEMD与广义维数优化逼近的自动机故障诊断

摘要

考虑到自动机的高速运动过程及其振动信号的非线性、短时、瞬态、冲击特性，对自动机的故障机理进行了分析，找到了故障的易发生位置；根据枪械的现实使用状况和理论分析的结果，运用机械加工的手段设置了三种典型故障，并设计实验采集和记录了自动机的振动响应信号。提出使用聚合经验模态分解( EEMD)结合相关系数法对自动机故障信号进行预处理。然后，运用覆盖法求各工况自动机振动信号的广义分形维数。最后，根据序列单值优化逼近法实现自动机故障的识别。%Considering the high-speed automaton movement process and its nonlinear vibration signal, short time, transient, impact properties, in this paper, the fault mechanism are analyzed, and finds the prone to fault location;According to the reality of gun usage and the results of the theoretical analysis to set up three kinds of typical faults with machining means, and design the experiment to collect and record the vibration response signal of the automaton. A method which is proposed to preprocess the fault signals by applying the Ensemble Empirical Mode Decomposition ( EEMD) with correlation coefficient method, and then using the covering method to calculate the generalized fractal dimension of the automaton vibration signals in the vari-ous states. Finally, realizing automaton fault diagnosis according to sequence of single value judging optimal approximation method.