Antifriction Bearings Damage Analysis Using Experimental Data Based Models

Abstract

Diagnosis of antifriction bearings is usually performed by means of vibration signals measured by accelerometers placed in the proximity of the bearing under investigation. The aim is to monitor the integrity of the bearing components, in order to avoid catastrophic failures, or to implement condition based maintenance strategies. In particular, the trend in this field is to combine in a simple theory the different signal-enhancement and signal-analysis techniques. The experimental data based model (EDBM) has been pointed out as a key tool that is able to highlight the effect of possible damage in one of the bearing components within the vibration signal. This paper presents the application of the EDBM technique to signals collected on a test-rig, and be able to test damaged fibrizer roller bearings in different working conditions. The effectiveness of the technique has been tested by comparing the results of one undamaged bearing with three bearings artificially damaged in different locations, namely on the inner race, outer race, and rollers. Since EDBM performances are dependent on the filter length, the most suitable value of this parameter is defined on the basis of both the application and measured signals. This paper represents an original contribution of the paper.