Shannon Entropy Index and a Fuzzy Logic System for the Assessment of Stator Winding Short-Circuit Faults in Induction Motors

Arturo Mejia-Barron,J De Santiago-Perez,David Granados-Lieberman,Juan Amezquita-Sanchez,Martin Valtierra-Rodriguez

doi:10.3390/electronics8010090

Arturo Mejia-Barron, J De Santiago-Perez + Show 3 more

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https://doi.org/10.3390/electronics8010090

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Abstract

The induction motor (IM) is one of the most important elements in industry. Although IMs are robust machines, they are susceptible to faults, where the stator winding short-circuit fault is one of the most common ones. In this work, the Shannon entropy (SE) index and a fuzzy logic (FL) system are proposed to diagnose short-circuit faults, considering both different severity levels and different load conditions. In the proposed methodology, a filtering stage based on brick-wall band-pass filters is firstly carried out. After this stage, the SE index is computed to quantify the fault severity and a FL system is applied to diagnose the IM condition in an automatic way. Unlike other works that propose some types of space transformations, the proposal is only based on a filtering stage and a time domain index, requiring low computational resources. The obtained results demonstrate the effectiveness of the proposal, i.e., the SE index quantifies the fault severity, regardless of the mechanical load, and the proposed FL system achieves a positive classification rate of 98%.

Highlights

In recent years, the development of monitoring systems to assess the physical condition of rotatory machinery has been vital to guaranteeing the reliability of industrial processes [1,2,3]
Acquire current signals used and abeen to several generate thea mechanical software, an in which the stator-winding has modified with taps, motor starter,load a general, it consists of: A personal computer (PC) to implement the analysis using MATLAB
Inthe order have a common reference quantifyfor thethe fault severity, After and energy indices were to computed output the results the indices were normalized using thetonumerical valuereference as a normalization for the signalsofgiven by fL and fR

Summary

Introduction

The development of monitoring systems to assess the physical condition of rotatory machinery has been vital to guaranteeing the reliability of industrial processes [1,2,3]. The three-phase induction motor (IM), representing ~85% of the consumed power in the industry, is a default implementation in industrial processes [4] because it offers great benefits, such as low maintenance, low cost, high robustness to aggressive environments and easy control under different load conditions [5,6]. Despite these great benefits, IMs are susceptible to present electrical and mechanical faults during their service-life, which are produced mainly by power quality problems, prolonged activity times and harsh operating conditions, among other factors [1,2,3,5,6]. This fault, even in its incipient/early state, can produce alterations and increments in current consumption, temperature and vibrations, putting at risk the personnel, the production, the machine itself and other machines in the same line of production.

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