Vibrational analysis using neural network classifier for motor fault detection

摘要

Early detection and diagnosis of induction machine incipient faults are desirable for increasing machinery availability, reducing consequential damage, and improving operational efficiency. However, fault detection using analytical method is not always possible because it requires perfect knowledge of a process model. A neural network based expert system was proposed for diagnostic problems of the induction motors using vibration analysis. The short-time Fourier transform (STFT) was used to process the quasi-steady vibration signals, and the neural network was trained and tested using the vibration spectra. The efficiency of the developed neural network expert system was evaluated. The obtained results lead to a conclusion that neural network expert system can be developed based on vibration measurements acquired online from the machine.