Diagnosis of Inter-turn Short-circuit Fault in Stator Windings of DFIG Based on Mechanical and Electrical Signal Fusion

Dongyue WANG; Huaiguang GU; Shurong WEI; Rui WU; Yang FU

doi:10.7500/AEPS20190913001

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Diagnosis of Inter-turn Short-circuit Fault in Stator Windings of DFIG Based on Mechanical and Electrical Signal Fusion

Application Research | 更新时间：2025-06-16

- Diagnosis of Inter-turn Short-circuit Fault in Stator Windings of DFIG Based on Mechanical and Electrical Signal Fusion
- Automation of Electric Power Systems Vol. 44, Issue 9, Pages: 171-178(2020)
- 作者机构：
  
  1.上海电力大学电气工程学院，上海市200090
  2.全球能源互联网研究院有限公司，北京市102209
  3.国网安徽省电力有限公司六安供电公司，安徽省六安市 237006
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China;National Key R&D Program of China;Shanghai Science and Technology Innovation Action Plan
- DOI：10.7500/AEPS20190913001
  CLC：
- Received：13 September 2019，
  
  Revised：2019-12-30，
  
  Published Online：01 April 2020，
  
  Published：10 May 2020
- 稿件说明：
移动端阅览
王栋悦,谷怀广,魏书荣等.基于机电信号融合的DFIG定子绕组匝间短路故障诊断[J].电力系统自动化,2020,44(9):171-178.

WANG Dongyue,GU Huaiguang,WEI Shurong,et al.Diagnosis of Inter-turn Short-circuit Fault in Stator Windings of DFIG Based on Mechanical and Electrical Signal Fusion[J].Automation of Electric Power Systems,2020,44(9):171-178.
王栋悦,谷怀广,魏书荣等.基于机电信号融合的DFIG定子绕组匝间短路故障诊断[J].电力系统自动化,2020,44(9):171-178. DOI： 10.7500/AEPS20190913001.

WANG Dongyue,GU Huaiguang,WEI Shurong,et al.Diagnosis of Inter-turn Short-circuit Fault in Stator Windings of DFIG Based on Mechanical and Electrical Signal Fusion[J].Automation of Electric Power Systems,2020,44(9):171-178. DOI： 10.7500/AEPS20190913001.

摘要

定子绕组匝间短路故障是双馈异步发电机(DFIG)常见的故障形式，发生概率高达30%，直接威胁到发电机的安全运行。发电机在复杂多变的环境下运行时，单一故障特征往往难以精准地反映故障，从而易产生误判、漏判的情况。文中提出一种基于电气、机械信号融合的定子绕组匝间短路故障诊断新方法——负序电流差与定子径向振动信号的二倍频分量联合诊断。首先利用支持向量机分别计算单一故障特征下的匝间短路故障概率；然后将其作为D-S证据理论的基本概率分配，依托证据组合规则，得出定子绕组匝间短路的最终诊断结果。实验结果表明：与基于单一信号的故障诊断方法相比，该方法能够更有效地诊断定子绕组匝间短路故障并可靠识别短路匝数，提高故障诊断的精确度，可推广应用至海上风电等对故障识别精度要求更高的领域。

Abstract

The stator winding inter-turn short-circuit fault is a common fault form of the doubly-fed induction generator (DFIG) and the occurrence probability is up to 30%

which directly threatens the safe operation of the generator. When a generator operates in a complex and variable environment

it is often difficult to diagnosis inter-turn short-circuit fault accurately by a single fault feature

which can easily lead to misjudgments and missed diagnosis. Therefore

a new fault diagnosis method for stator winding inter-turn short-circuit fault is proposed based on electrical and mechanical signal fusion

that is the joint diagnosis of negative sequence current difference and double frequency component of stator radial vibration signal. Firstly

support vector machine (SVM) is used to calculate the probability of the inter-turn short-circuit fault with the single fault feature

and then the probability is taken as the basic probability assignment of D-S evidence theory. The final diagnosis result is obtained relying on the evidence combination rule. The experimental results indicate that compared with the fault diagnosis method based on single fault feature

this method can diagnose the inter-turn short circuit faults in stator winding more effectively and identify the number of short-circuit turns reliably

so as to improve the accuracy of fault diagnosis

and can be applied to the other fields requiring higher fault identification accuracy

such as offshore wind power.

关键词

Keywords

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