Blade fault diagnosis using Mahalanobis distance

The fault diagnosis of a rotating multi-blade system has been conducted using the vibration characteristics of the system. For the fault diagnosis, multi-dimensional features related to the system vibration characteristics were extracted and used for monitoring the system health condition in most of previous studies. Recently, blade tip timing (BTT) method becomes increasingly popular to measure the vibration signals of rotating multi-blade systems. Due to the under-sampling characteristics of the method, relatively low frequency components of the vibration signal can be only collected with the BTT method. In this study, a statistical index called the Mahalanobis distance is defined and employed for the fault diagnosis of a rotating multi-blade system having a crack. The effects of crack existence and signal to noise ratio on the reliability of the proposed method using BTT signals obtained with a simulation model are investigated in this study.