Simulation of Incipient Fault Detection, Confirmation and Diagnosis Using Kalman Filter

Motor plays a important role in many household and industry applications for example, in robots, printers, etc wherever it is necessary to convert the electrical energy to a mechanical energy. In this paper a model based fault diagnosis, detection and fault confirmation in DC motor is presented. A comparison is made by building a healthy and faulty DC motor. The Kalman filter and its iterations are mathematically modeled and is used for fault diagnosis of DC motor. The performance is evaluated from the estimated states of the Kalman filter. For incipient fault as a Guassian noise, a fault model is developed and difference between healthy and faulty output of DC motor is obtained. Simulink (Matlab) is the simulation tool used to model the DC motor and Kalman filter. Computer simulation and modeling tools have been widely used to support and enhance the working and operation of electro mechanical devices.