微特电机 ›› 2025, Vol. 53 ›› Issue (4): 39-42.

• 设计分析 • 上一篇    下一篇

基于正余弦麻雀搜索与峭度解卷积的发电机故障诊断


  

  1. 运达能源科技集团股份有限公司,杭州 310000
  • 收稿日期:2025-01-17 出版日期:2025-04-28 发布日期:2025-04-28

Fault Diagnosis of Generator Based on SCSSA-MCKD

  1. Windey Energy Technology Group Co., Ltd.,Hangzhou 310000, China
  • Received:2025-01-17 Online:2025-04-28 Published:2025-04-28

摘要: 提出了一种基于结合正余弦麻雀搜索算法和最大相关峭度解卷积的风电机组发电机故障诊断方法。
该方法通过正余弦麻雀搜索算法优化最大相关峭度解卷积算法的参数,有效提取故障信号中的微弱特征。 实验结
果表明,该方法能够在复杂噪声环境下准确识别发电机的早期故障特征,为风电机组的故障预警和维护提供了有力
的技术支持。

关键词: 发电机, 故障诊断, 正余弦, 麻雀搜索算法, 最大相关峭度解卷积, 风电机组

Abstract: This article proposed a fault diagnosis method for wind turbine generators based on the sine-cosine and
sparrow search algorithm( SCSSA) , and maximum correlation kurtosis deconvolution ( MCKD) . This method optimized the
parameters of the MCKD algorithm through SCSSA, effectively extracting weak features from fault signals. The experimental
results showed that this method can accurately identify the early fault characteristics of generators in complex noise
environments, providing strong technical support for fault warning and maintenance of wind turbines.

Key words: generators, fault diagnosis, sine-cosine transformation, sparrow search algorithm, maximum correlation
kurtosis deconvolution( MCKD),
wind turbine unit