Sleeve Bearing Oil Whirl Fault Diagnosis In Three Phase Induction Motor using Hilbert - Huang Transform

Induction motors play an indispensable role in setting up the industry’s wheel and production cycle. Therefore, much research is being done to improve their construction and production and to monitor their condition. This paper aims to study and investigate a common fault related to these motors, i.e. the oil whirl fault within their sleeve bearing, and try to provide a useful and effective solution in order to diagnose this fault. For this purpose, firstly, an induction motor that has one of its bearings with oil whirl fault, is modeled and simulated by appropriate definition of the air gap function and using the modified winding function approach. Then, the stator current is obtained under both the healthy and faulty conditions to detect an effective and non-invasive method for the fault diagnosis. The stator current signal is processed using a combination of the empirical mode decomposition and Hilbert transform, called Hilbert-Huang transform and a suitable index for detecting oil whirl fault is proposed. Then, the efficiency of the proposed index is evaluated by applying it to the stator current signal obtained from the practical induction motor and its efficiency is proved in practice.