Fault Characteristic Extracting Based on PSO

The fault symptoms of the gearbox can be indicated by different characteristic parameters. In the working process of gearbox, because the responding signal is very complex, it is difficult to extract its sensitive fault attributive information. The sensitivity of the fault degree, fault position and fault type is very different, so the characteristic parameter set constructed by the traditional characteristic extraction and analysis method is voluminous. Therefore, how to define the reliable and effective fault characteristic parameter set and how to optimize the parameter set by the sensitivity are problems should be solved to realize real time and online fault diagnosis. In this paper, the characteristic extractive method base on PSO is presented for fault characteristic selection of gearbox. Then the technology is applied to analyze and process the vibration responding signal of gearbox, extract and optimize the fault characteristic parameter set. Finally the parameter set osculating related to the gearbox´s fault is constructed and it is used to the fault diagnosis. It proves the diagnosis result that PSO algorithm has good effectiveness, higher diagnosis precision and fast optimal speed than the traditional genetic algorithm.