Abstract

This paper describes a new diagnosis approach, the Root-Multiple Signal Classification (MUSIC) (RM) method, for identification of the progressive cracking in the bearing of induction motors. This approach has several advantages compared with the stator current spectral analysis using the conventional Periodogram method. Indeed, the main advantage of this approach is its very good frequency resolution for a very short acquisition time, something impossible to achieve with the conventional method. However, in order to reduce the computation time, which is the main drawback of the RM method, this method will be applied to only a specified frequency band; one that carries information about the sought fault. Experimental results show the effectiveness of the RM method on the reliability of the incipient bearing fault detection.

INTRODUCTION

The induction motor is the most common electric machine in the industry. Its main advantage is the absence of sliding electrical contacts, which leads to a simple and robust structure easy to build with low cost. However, various faults can appear on the induction motor making the fault detection procedure necessary to prevent the interruption of the industrial process. Several reliability studies conducted on a large number of induction motors, show that the bearing faults account for 52% of all failures. For that, early detection of bearing faults increases the life of the motors and thus avoids unnecessary financial losses [1-3].