Mechanical faults detection in induction machine using recursive PCA with weighted distance

An original method for multi-fault detection in synchronous machine is proposed in this paper. This method aims to answer two questions: how to detect a fault when only the normal functioning is known? How to differentiate two different faults from one fault with two severities? The proposed method relies on the use of a recursive Principal Components Analysis (PCA), which is updated each time a new fault is detected. The detection is based on a weighted distance criteria that takes into account the contribution of the different components. A geometrical criteria is also proposed to differentiate new faults from existing ones. The method has been successfully tested on a simulation database of motor currents with different levels of unbalance and eccentricity. It is then tested on real data from a 5.5 kW synchronous machine with three different levels of unbalance.