| Title |
Fault Diagnosis of 3 Phase Induction Motor Drive Systems Using Clustering |
| Authors |
Jang-Hwan Park ; Sung-Suk Kim ; Dae-Jong Lee ; Myung-Geun Chun |
| Keywords |
fault diagnosis ; induction motor drive system ; inverter ; ANFIS |
| Abstract |
In many industrial applications, an unexpected fault of induction motor drive systems can cause serious troubles such as downtime of the overall system, heavy loss, and etc. As one of methods to solve such problems, this paper investigates the fault diagnosis for open-switch damages in a voltage-fed PWM inverter for induction motor drive. For the feature extraction of a fault, we transform the current signals to the d-q axis and calculate mean current vectors. And then, for diagnosis of different fault patterns, we propose a clustering based diagnosis algorithm. The proposed diagnostic technique is a modified ANFIS(Adaptive Neuro-Fuzzy Inference System) which uses a clustering method on the premise of general ANFIS’s. Therefore, it has a small calculation and good performance. Finally, we implement the method for the diagnosis module of the inverter with MATLAB and show its usefulness. |