Application of Genetic Algorithms and Possibility Theory in Rolling Bearing Compound Fault Diagnosis

The characteristic parameters of mechanical fault are found, on the basis of characteristic component collection according to wavelet transform, through optimizing the commonly-used characteristic parameters reflecting rolling bearing fault by genetic algorithms theory. The relationship between the characteristic fault and the mode of fault is created based on the possibility theory. The article also studies the successive fault diagnosis method of the rolling bearing. The experiment shows the successive fault diagnosis method can be applied well in rolling bearing compound fault diagnosis.