Abstract
Unlike fault diagnosis approaches based on the direct analysis of current and voltage signals, this paper proposes a diagnosis of induction motor faults through monitoring the variations in motor's parameters when it is subjected to an open circuit or short circuit faults. These parameters include stator and rotor resistances, self-inductances, and mutual inductance. The genetic algorithm and the trust-region method are used for the estimation process. Simulation results confirm the efficiency of both the genetic algorithm and the trust-region method in estimating the motor parameters; however, better performance in terms of estimation time is obtained when the trust-region method is adopted. The results also show the possibility of extracting fault signatures from the motor's parameter values because each type of the mentioned faults has a different impact on these parameters. Under a 10% short circuit fault condition, the mutual inductance and rotor resistance deviate by almost 10% from their original values to lower values. While the stator resistance noticeably reduces by up to 20% during the open circuit fault condition.
Highlights
According to a study presented in 2011, the number of electrical machines, which are used around the world, is 16.1 billion
As stator faults have a high percentage of occurrence, many publications are focused on developing strategies for diagnosing them (Garciaguevara et al, 2016), (Guezmil et al, 2019) and (Angelo et al, 2009)
The operating induction motor under this asymmetry has two rotating fields: the forward rotating field created by the positive sequence current and the backward rotating field induced by the negative sequence current, resulting from an unbalanced supply voltage
Summary
According to a study presented in 2011, the number of electrical machines, which are used around the world, is 16.1 billion. Three-phase induction motors represent 60% of the total number; they have a special position in the energy conversion owing to their merits such as robustness, low cost, and high performance (Garcia-guevara et al, 2016). These motors' reliability is mainly affected when a fault occurs; the diagnosis of fault becomes a significant subject in recent years (Rajamany et al, 2019). The worst types of stator faults are phase to ground and phase-to-phase faults These faults generally start with undetectable inter-turn short circuit fault (Khader, Champenois, et al, 2018). This paper adopted the inverse problem theory to study the effects of short circuit and open circuit faults on an induction motor's parameters.
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