Fault diagnosis of rotating machinery using the Mahalanobis distance

A diagnostic system for the predictive maintenance of production facilities is highly recommended due to the need for higher reliability and accuracy to detect incipient faults. This paper presents the results of a study on the application of vibration signals to diagnose faults in rotating machinery using the Mahalanobis Distance. The root mean square (RMS), crest factor and kurtosis are statistical parameters of the Mahalanobis distance and were used, along with spectrum analysis, to diagnose these faults