The Research On Motor Control System Fault Diagnosis Based On Wavelet Transformation

With the development of the electronic technology, great progress has been made in the research on motor control system fault diagnosis. Nowadays wavelet analysis has been one of the hottest areas of the research on motor control system fault diagnosis. Based on the research and development of the project,"The control and fault diagnosis system for 154t motor dump trucks", some new ideas on motor control system fault diagnosis from the theory are proposed in the paper.In the first part of the paper, the development of motor control system fault diagnosis theory is summarized. On the basis of the analysis of the characteristics of wavelet, the theory is discussed and the definition of the singularity is given. Because of the localization property of wavelet transform, wavelet analysis can be used to detect the characteristics of the singularity from the signal and intermittence fault problems lying in the motor under test. For real world implementation of wavelet theory, the selection of suitable wavelet bases and related algorithms is mainly focused on.Then the application in signal de-noising with wavelet transform is investigated. Due to the specialties of fault signals in motor control system fault diagnosis, a novel de-noising method applying wavelet analysis scale space filter by using the properties of the signal and noise modulus maxima across scales is proposed. This de-noising method can reduce noise to a high degree while preserving most of the important features of the signal such as edges and other singularities. This algorithm applied to real system produces a good result.Finally our investigations on real 154t motor dump trucks fault diagnosis system was applied, and achieve a success. Our research is proved to be important for improving efficiency on 154t motor dump trucks fault diagnosis.