基于改进特征交叉算法的风电机组齿轮箱状态监测

刘长良; 田雯雯; 张书瑶; 尹磊; 刘帅

doi:10.19805/j.cnki.jcspe.2025.240346

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基于改进特征交叉算法的风电机组齿轮箱状态监测

数字化与智能化 | 更新时间：2026-10-10

- 基于改进特征交叉算法的风电机组齿轮箱状态监测
- Condition Monitoring of Wind Turbine Gearbox Based on Improved Feature Crossover Algorithm
- 动力工程学报 2025年45卷第7期页码：1072-1081
- 作者机构：
  
  1. 华北电力大学控制与计算机工程学院,北京,102206
  2. 华北电力大学保定市综合能源系统状态检测与优化调控重点实验室,河北,保定,071003
  3. 华北电力大学自动化系,河北,保定,071003
- 作者简介：
  
  刘长良(1966-),男,河北沧州人,教授,博士,研究方向为发电过程建模仿真,E-mail:13603123513@163.com
- 基金信息：
  
  中央高校基本科研业务费专项资金资助项目(2023JG005、2023JC010);河北省高等学校科学技术研究资助项目(CXY2023001)
- DOI：10.19805/j.cnki.jcspe.2025.240346
  中图分类号：
- 网络首发：2025-07-14，
  
  纸质出版：2025
- 稿件说明：
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刘长良,田雯雯,张书瑶,尹磊,刘帅. 基于改进特征交叉算法的风电机组齿轮箱状态监测动力工程学报, 2025, 45(7): 1072-1081 https://doi.

org/10.19805/j.cnki.jcspe.2025.240346
刘长良,田雯雯,张书瑶,尹磊,刘帅. 基于改进特征交叉算法的风电机组齿轮箱状态监测动力工程学报, 2025, 45(7): 1072-1081 https://doi. DOI： 10.19805/j.cnki.jcspe.2025.240346.

org/10.19805/j.cnki.jcspe.2025.240346 DOI：

摘要

针对风电机组监控与数据采集(SCADA)数据间存在的非线性关联问题

引入特征交叉机制并进行改进

将其应用于风电机组齿轮箱状态监测领域。首先

提出一种两阶段交叉特征选择方法

该方法综合考虑了变量间的因果性、相关性及数据分布差异

以筛选具有强隐藏关联且低冗余度的特征进行交叉;其次

对因子分解机进行改进

仅将交叉特征组内的基准变量与其余变量进行交叉

在生成合理交叉特征的同时显著缩短了生成时间;最后

将改进特征交叉算法用于某风电场齿轮箱状态监测任务中。结果表明:所提方法与五种模型相结合均能取得优异效果

显著提升了模型监测性能。

Abstract

To address the issue of non-linear correlation between SCADA data of wind turbine units

a feature crossover mechanism was introduced and improved

and used for monitoring status of wind turbine gearboxes. Firstly

a two-stage cross feature selection method was proposed

which comprehensively considered the causality

correlation and data distribution differences among variables to screen features with strong hidden associations and low redundancy for cross-selection. Secondly

the factorization machine was improved by crossing only the benchmark variables within the cross feature group with the remaining variables

significantly shortened the generation time while generating reasonable cross features. Finally

the improved feature crossover algorithm was applied to the condition monitoring task of gearboxes in a certain wind farm. The results show that the proposed method

combined with five models

can achieve excellent effects and significantly improve the models' monitoring performance.

关键词

Keywords

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