This paper presents induction machine fault detection possibilities using smartphone recorded audible noise. Different faults of the induction machine, such as various numbers of broken rotor bars and rotor eccentricities are inflicted to the machine. Analysis is performed on audible noise recorded by two different smartphones and compared with mechanical vibrations recorded by sensors. Neural network is composed and probabilities of fault detection using such diagnostic measures are presented. Necessity for further study is pointed out.
Abstract. The paper presents modeling and analysis of a 5-phase induction machine connected to 2-level 5-leg converter in case of openphase failure. A control of the machine is accomplished using the Field Oriented Control with hysteresis current controllers. Moreover, a fault-tolerant algorithm is addressed and simulated.
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