Purpose Induction motors (IMs) are considered one of the most important elements of the industrial process. However, in this environment, these machines are subject to electrical and mechanical faults, which may cause significant financial losses. Thus, the purpose of this paper is to propose an optimal identification of inter-turn insulation faults present in the random wound IM. Design/methodology/approach The design approach deals with a simple technique, using the effect of the inter-turn fault in modifying the high-frequency components of the applied pulse-width-modulated voltage. Findings The change in insulation strength between the turns affects the capacitive component of the stator line current. Resulting changes in wave shapes of the applied voltage have been studied with respect to both the distance of inter-turn faults from line end and reduction in the insulation strength, and hence in the insulation resistance value. Originality/value Studies have been conducted by using computer simulation and validated by experiments. There is ample evidence that an impending and progressing inter-turn fault can be identified in adjustable speed drives driven by frequency converters by studying line-end coil-voltage waveforms.

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This project presents the anoptimization method for harmonic elimination in a cascaded multilevel inverter and energy balance in photovoltaic cells. The main objective in selective harmonic elimination pulse width modulation strategy is eliminating low-order harmonics by solving nonlinear equations, while the fundamental component is satisfied.In this paper, the Energy balance algorithm (EB) is applied to a 7-level inverter for solving the equations. The algorithm is based on the cooling of a high temperature metal behavior under fast cooling constraint. This method has higher precision and probability of convergence than the genetic algorithm (BA).MATLAB software is used for optimization and comparison of BA and EB. Simulation results are expected to show superiority of EB over BA in attaining accurate global minima and higher convergence rate. Also, its performance is almost 10 times lesser time for running.

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