Novel Diagnostic Techniques for Rotating Electrical Machines-A Review

被引：41

作者：

Frosini, Lucia ^{[1
]}

机构：

[1] Univ Pavia, Dept Elect Comp & Biomed Engn, Via Ferrata 5, I-27100 Pavia, Italy

来源：

ENERGIES | 2020年 / 13卷 / 19期

关键词：

diagnostics; fault detection; electrical machine; electromagnetic signal; vibration; BAYESIAN HIERARCHICAL-MODELS; ELEMENT BEARING DIAGNOSTICS; INDUCTION MACHINES; FAULT-DETECTION; ROTOR FAULTS; RELIABLE DETECTION; SHORT-CIRCUIT; MOTOR; LOAD; FLUX;

D O I：

10.3390/en13195066

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

This paper aims to update the review of diagnostic techniques for rotating electrical machines of different type and size. Each of the main sections of the paper is focused on a specific component of the machine (stator and rotor windings, magnets, bearings, airgap, load and auxiliaries, stator and rotor laminated core) and divided into subsections when the characteristics of the component are different according to the type or size of the machine. The review considers both the techniques currently applied on field for the diagnostics of the electrical machines and the novel methodologies recently proposed by the researchers in the literature.

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页数：26

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