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Mohammad Rezazadeh Mehrjou

Researcher at Universiti Putra Malaysia

Publications -  21
Citations -  452

Mohammad Rezazadeh Mehrjou is an academic researcher from Universiti Putra Malaysia. The author has contributed to research in topics: Rotor (electric) & Fault (power engineering). The author has an hindex of 8, co-authored 21 publications receiving 366 citations. Previous affiliations of Mohammad Rezazadeh Mehrjou include Islamic Azad University.

Papers
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Rotor fault condition monitoring techniques for squirrel-cage induction machine—A review

TL;DR: A broad outlook on rotor fault monitoring techniques for the researchers and engineers can be found in this paper, where the authors review and summarize the recent researches and developments performed in condition monitoring of the induction machine with the purpose of rotor faults detection.
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Fault Detection of Broken Rotor Bar in LS-PMSM Using Random Forests

TL;DR: The proposed approach to diagnose broken rotor bar failure in a line start-permanent magnet synchronous motor (LS-PMSM) using random forests can be used in industry for online monitoring and fault diagnostic and can be helpful for the establishment of preventive maintenance plans in factories.
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Broken Rotor Bar Fault Detection and Classification Using Wavelet Packet Signature Analysis Based on Fourier Transform and Multi-Layer Perceptron Neural Network

TL;DR: In this paper, the most appropriate features are extracted from the coefficients of a wavelet packet transform after fast Fourier transform of current signal for rotor bar breakage detection under low load conditions.
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Static Eccentricity Fault Recognition in Three-Phase Line Start Permanent Magnet Synchronous Motor Using Finite Element Method

TL;DR: In this paper, a three-phase LSPMSM with static eccentricity between stator and rotor is analyzed in frequency domain using power spectral density (PSD) and it is demonstrated that static eccentricities generate a series of low frequency harmonic components in the form of sidebands around the fundamental frequency.
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Broken Rotor Bar Detection in LS-PMSM Based on Startup Current Analysis Using Wavelet Entropy Features

TL;DR: In this article, the authors investigated the fault-related feature for broken rotor bar (BRB) faults on LS-PMSMs and proposed a fault detection strategy based on the monitoring of the start-up current signal and discrete wavelet transform.