基于序列模糊推理的齿轮多故障诊断

Z. Luo, Qiangqiang Chen, Peng Chen, Xiong Zhou
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引用次数: 3

摘要

简要分析了齿轮故障的振动机理和齿轮的各种典型信号特征,并将逐次模糊推理引入到齿轮故障诊断中。对于特征参数的选择,我们使用识别指数DI来评价特征参数的识别能力,并选择DI值最大的特征参数。根据可能性理论和统计概率论,将原始特征参数替换为已知分布的特征参数,然后将隶属度函数等价于模糊推理。最后,给出的诊断实例表明,将逐次模糊推理方法应用于齿轮故障诊断是有效可行的。
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Multi-fault diagnosis of gear based on sequential fuzzy inference
The article briefly analyzes the vibration mechanism of the gear fault and kinds of typical signal characteristics of the gears, and introduces successive fuzzy reasoning into the fault diagnosis of the gears. For the selection of characteristic parameters, we used the discrimination index DI to evaluate the identification ability of the characteristic parameters, and select the characteristic parameters of the largest value of DI. According to possibility theory and statistics and probability theory, we replace the original feature parameters into feature parameters of known distributional, and then equate the membership function used in fuzzy reasoning. Finally, the given diagnosis instance indicates that it is effective and feasible to use the method of successive fuzzy reasoning in the fault diagnosis of gears.
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