Health condition monitoring of rotating shaft based on electrical signature

Abstract

Fatigue loading is among the most common fault occurring in rotating shafts. This could result in large downtimes and financial losses. Therefore, it is desirable to be able to detect such failures in an early stage. Thus, significant research effort has been placed on fault detection techniques for rotating shafts. This project develops an alternative method to trace the health condition of a particular shaft by analysing the current of the electric machine. The benefit of this approach is that it does not require any special sensors and does not interfere with the normal operation of the system. The project starts by developing a mathematical model of a two-mass system accounting for a cracked shaft connecting a motor and generator. According to existing literature, a cracked shaft exhibits a breathing effect phenomenon which makes its stiffness vary with time. Through the model, the current produced by generator could be measured and subsequently, Fast Fourier Transform is applied to the response to enable analysis on frequency domain. The simulation result shows that the cracked shaft affects the current of the electric machines and there are increment of peak appears once in every mechanical speed. The simulation results were afterwards experimentally verified. It is proven that with the existence of crack, there are increments in the fundamental frequency of the system as well as in the higher harmonics. Thus, this project provides an alternative technique to monitor the health condition of a rotating shaft only by analysing the current of the electric machines connected to it. However, more work is required to fully mature this method of analysing the electric current signature to detect shaft faults before it can be practically applied to rotating machines.