The Research Of Double Close Loop Self-healing System : Based On The Improved Particle Swarm Optimizer

In recent years, the automation of industrial production improve continually. The motor, as a core dynamic facility of machinery and electronic plant system, has been much more widely used in the industrial production in various fields. In the whole process of industrial production, the failure of the motor will not only cause serious impact to production schedule and quality, but also does great harm to personal safety property of workers. Thus, to ensure the normal working condition of the motor is extremely important. During the working process, the running state of a motor will change because of some transformation of external factors or their own changes, such as the change in working temperature caused by heat production, etc. When temperature rising, the resistance of the load will reduce, which push the current up. If that kind of situation continues for a long period of time, the motor will burn down because of the high working temperature. We call this kind of working state as sub-health state. A large amount of research has been carried out at home and abroad. How to do prevent the fault and make the motor from sub-health state back to the normal state has been a very significance topic.After reading a lot about the fault detection and control methods, the paper puts forward a kind of double-close self-healing control algorithm to deal with the sub-health state of a running motor, which has improved a lot compared with the traditional control and evaluation algorithm. A self-healing ring is added into the traditional control ring, which constitutes a double closed structure. The PID controller is used in the control ring. The particle swarm optimization algorithm is adopted to adjust the parameter of PID controller. Aiming at the disadvantage of easily falling into local optimum, both the inertia weight and the learning factor are improved to raise the effectiveness of the algorithm to get the improved particle swarm optimization. The self-healing ring uses the RMS to transform the three phase current signals and combines the “sub-health” factor with the running state to design the partition function. The concept of heath degree is adopted to divide the health level and makes a decision for the running state of the DC motor. This algorithm is focus on that the motor can do some self-healing control to deal with the incipient fault caused by some transformation of external factors or their own during the running state. It can make the motor judge the health level itself and reduce the load, which can reduce the probability of the incipient fault.The SIMULINK simulation experiment is done in the platform of MATLAB. The brush-less DC motor is used to verify the effectiveness of the algorithm. The experimental result shows that when the motor running condition changes, the motor load can be reduced by the control algorithm itself and escape from the sub-health state.