DESIGN OF COMBINED SCALAR INDICATORS FOR FAULT DETECTION OF ROTATING MACHINES

The machine health monitoring becomes crucial for any company using rotating machines. A rotating machine is subject to developments that induce changes in its vibration behaviour. These changes can be due either to a change in its parameters (load or speed), or to degradations, or to defects affecting its intrinsic characteristics and behaviour. Several maintenance methods are currently used to detect defects in rotating machines. Time-domain analysis is one of the methods for detecting defects that use well-known scalar indicators such as Root Mean Square (RMS), Kurtosis, peak-to-peak value, crest factor etc. However, these indicators may have limitations when it comes to detecting multiple defects in machines. In this article, we propose new innovations in the field of the monitoring of rotating machine by vibration analysis, specifically in time-domain analysis. We propose new indicators for detecting defects by linear combination of scalar indicators We evaluate these indicators in order to assess their capacity to detect a single or multiple defects, their capacity to assess the severity of a defect, and their capacity to detect a healthy gear or a defective gear in different configurations of defects created on the gear and on the bearing mounted on an experimental test bench.