Detection of Broken Rotor Bars Faults in Inverter-Fed Induction Motors

被引：0

作者：

Godoy, W. F. ^{[1
]}

da Silva, I. N. ^{[2
]}

Goedtel, A. ^{[1
]}

Palacios, R. H. C. ^{[1
]}

Scalassara, P. ^{[1
]}

Morinigo-Sotelo, D. ^{[3
]}

Duque-Perez, O. ^{[3
]}

机构：

[1] Fed Technol Univ Parana UTFPR, Apucarana, Brazil

[2] Univ Sao Paulo, Sao Carlos Sch Engn, Dept Elect Engn, Sao Carlos, SP, Brazil

[3] Univ Valladolid UVA, SElect Engn Dept, Valladolid, Spain

来源：

2018 XIII INTERNATIONAL CONFERENCE ON ELECTRICAL MACHINES (ICEM) | 2018年

基金：

巴西圣保罗研究基金会;

关键词：

Classification; Inverter; Rotor Fault; Three-phase Induction Motor; DIAGNOSIS; MACHINES; DEFECTS;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper proposes a method for classification of broken rotor bars of three-phase induction motors driven with three different models of frequency inverters by using the amplitude of the stator current signal in the time domain. To assess the effectiveness of the method under evaluation in this work, classification accuracy of four different learning machine techniques were compared: Fuzzy ARTMAP network; Support Vector Machine; k-Nearest Neighbour and Multilayer Perceptron Network. Moreover, this paper presents the comparison of an analogue and a digital filter to the line current signal provided by the motor. Results obtained from 2293 experimental tests are presented to validate this comparative study, considering a wide range of speed and load conditions.

引用

页码：1803 / 1808

页数：6

共 35 条

[1] Broken rotor bar fault detection in inverter-fed squirrel cage induction motors using stator current analysis and fuzzy logic [J].