Multi-fault diagnosis of gear based on sequential fuzzy inference

Abstract

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.