Bearings Fault Detection Using Inference Tools

Electric motors are nowadays widely used in all kind of industrial applications due to their robustness and ease of control through inverters. Therefore, any effort, with the aim of improving condition monitoring techniques applied to them, will result in a reduction of overall production costs by means of productive lines stoppage reduction, and increment of the industrial efficiency. In this context, the most used electric machine in the industry is the Induction Motor (IM), due to its simplicity and reduced cost. The analysis of the origin of IMs failures exhibits that the bearings are the major source of fault (Singh et al., 2003), and even a common cause of degradation in other kinds of motors as Permanent Magnet Synchronous Machines. An IM failures percentage distribution, according to previous studies (O’Donell, 1986), is shown in figure 1, in order to highlight the bearings monitoring importance.