Discrete wavelet transform-based fault diagnosis for driving system of pipeline detection robot arm

A real-time wavelet multi-resolution analysis (MRA)-based fault detection algorithm is proposed. The first stage detailed MRA signals extracted from the original signals were used as the criteria for fault detection. By measuring sharp variations in the detailed MRA signals, faults in the motor driving system of pipeline detection robot arm could be detected. The fault type was then identified by comparison of the three-phase MRA sharp variations. The effects of the faults were examined. The simulation results show that this algorithm is effective and robust, it is promising for fault detection in a robot's joint driving system. The method is simple, rapid and it can operate in real time.