Abstract
In this paper, we describe a new approach to fault diagnosis method of rotating machine by parameter estimation. At first, we derive the moving equations of rotating machine including failure parameters and the observing equation. Next we define the parameter estimation problem to detect symptoms of failure. This parameter estimation problem is devided into two types by terms including failure parameter. In order to apply particle filter to these problems, the moving equations are discretized by Euler-Maruyama method and an approximated parameter estimation problem is defined. Then we conducted numerical simulations, so estimators are effective to detect failure parameters. Moreover log likelihood is comfirmed to decide which failure model is better or not. By using these parameter estimation and model comparison method, we can treat more complex fault diagnosis of rotating machine.
