A MIRPSA-based criterion to quantify broken rotor bars in induction motors

XU Boqiang; SUN Liling

doi:10.16081/j.issn.1006-6047.2019.03.021

English Version Reader LoginJournal Login

您当前的位置：

首页 >

文章列表页 >

A MIRPSA-based criterion to quantify broken rotor bars in induction motors

更新时间：2025-04-25

- A MIRPSA-based criterion to quantify broken rotor bars in induction motors
- Vol. 39, Issue 3, Pages: 132-136(2019)
- 作者机构：
  
  华北电力大学新能源电力系统国家重点实验室
- 作者简介：
- 基金信息：
- DOI：10.16081/j.issn.1006-6047.2019.03.021
  CLC： TM346
- Published：2019
- 稿件说明：
移动端阅览
[1]许伯强,孙丽玲.基于MIRPSA的感应电动机转子断条数目诊断判据[J].电力自动化设备,2019,39(03):132-136.

XU Boqiang, SUN Liling. A MIRPSA-based criterion to quantify broken rotor bars in induction motors[J]. 2019, 39(3): 132-136.
[1]许伯强,孙丽玲.基于MIRPSA的感应电动机转子断条数目诊断判据[J].电力自动化设备,2019,39(03):132-136. DOI： 10.16081/j.issn.1006-6047.2019.03.021.

XU Boqiang, SUN Liling. A MIRPSA-based criterion to quantify broken rotor bars in induction motors[J]. 2019, 39(3): 132-136. DOI： 10.16081/j.issn.1006-6047.2019.03.021.

摘要

在感应电动机转子断条数目诊断方面

电机定子电流信号分析（MCSA）类方法已经建立明确的解析判据

而电机瞬时无功功率信号分析（MIRPSA）类方法缺乏理论支撑。为此

针对转子断条故障推导了感应电动机瞬时无功功率特征分量的幅值与转子断条数目间的数值对应关系

由此建立了具有解析意义的基于MIRPSA的转子断条数目诊断判据。感应电动机转子断条故障仿真与实验证明了所提判据的有效性。

Abstract

In the diagnosis of broken rotor bars in induction motors

the methods based on MCSA（Motor Current Signal Analysis） have established explicit criterions

while the methods based on MIRPSA（Motor Instantaneous Reactive Power Signal Analysis） lack theoretical support. Therefore

the numerical relationship between the magnitude of the feature component of instantaneous reactive power and the number of broken rotor bars is deduced

based on which

a diagnostic criterion to quantify the broken rotor bars based on MIRPSA is analytically established. The numerical simulation and laboratory experiment verify the effectiveness of the proposed criterion.

关键词

Keywords

references

Views

115

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Fault diagnosis of rotating rectifier in multiphase brushless excitation system based on improved SVDD

Unsupervised open-circuit fault diagnosis strategy of MMC based on sparse autoencoder

Intelligent fault diagnosis of wind turbine unit based on dual-stream generative adversarial network data augmentation

Small sample fault diagnosis of transformer windings based on virtual-real feature fusion and data-mechanism driven

Power transformer fault diagnosis method based on AdaBoost.M2-ISSA-ELM algorithm

Related Author

ZHAO Shuya

HAO Liangliang

CAI Yuang

DUAN Xianwen

LI Huazhong

YANG Xingwu

LU Yuan

WANG Jiang

Related Institution

School of Electrical Engineering，Beijing Jiaotong University

China Nuclear Power Operations Co.，Ltd.

NR Electric Co.，Ltd.

College of Electrical Engineering，Shanghai University of Electric Power

Baoji Power Supply Company，State Grid Shaanxi Electric Power Co.，Ltd.

AI问答

⁰