Research For Asynchronous Motor Failure Diagnosis Based On Improved Particle Swarm Optimization Algorithm

In the modern industrial and agricultural production process, the motor is the core components of the electric drag system, and the asynchronous motor which having excellent capability is the most important motor equipment, because of the motor failure or the likelihood of its failure will increases as the running time goes, that may eventually cause the entire electric drag system abnormal to run, so there needs a timely and effective way to accurately determine the causes, the type and the severity of the motor failure, then it can improve the security of the motor and its electric drag system.In this paper, through the study of the development trend of the failure diagnosis technology, we considered that the failure diagnosis method based on artificial intelligence technology is its future development trend, so we used a failure diagnosis technology based on artificial neural network to diagnosis the asynchronous motor fault. And through the study of the particle swarm optimization algorithm, we considered that it is an excellent tool for optimization, so we used it to algorithm the BP neural networks, at last we made a design about the system of the asynchronous motor failure diagnosis which it is based on improved particle swarm optimization to algorithm the BP neural networks.In this paper, the main research content is based on improved particle swarm optimization of the asynchronous motor failure diagnosis research. Specifically, it is through the analysis of the slurry pump fans motor’s vibration failure and current failure to establish the appropriate motor failure sample set, making the particle swarm optimization theory and neural network theory applied to the motor failure diagnosis field, combining with the characteristics of motor failure diagnosis based on neural networks to constructed the appropriate use of particle swarm optimization algorithm to the neural networks, then using the MATLAB to program a computer program, and then using the Visual Basic to program the interface of the system, at last we achieve the target of researching the asynchronous motor failure diagnosis systems based on improved particle swarm optimization.