基于CMSATE和DTCAE的风电机组偏航轴承服役状态评估

王晓龙; 杨秀彬; 陆志鹏; 金韩微; 张博文; 陶振哲; 韩会龙

doi:10.19805/j.cnki.jcspe.2026.240649

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基于CMSATE和DTCAE的风电机组偏航轴承服役状态评估

数字化与智能化 | 更新时间：2026-10-10

- 基于CMSATE和DTCAE的风电机组偏航轴承服役状态评估
- Service Status Evaluation of Wind Turbine Yaw Bearing Based on CMSATE and DTCAE
- 动力工程学报 2026年46卷第1期页码：138-147
- 作者机构：
  
  华北电力大学机械工程系,河北,保定,071000
- 作者简介：
  
  王晓龙(1989—),男,黑龙江大庆人,副教授,博士,研究方向为故障诊断及状态监测
  韩会龙(通信作者),男,高级工程师,硕士,E-mail:hanhuilongncepu@163.com
- 基金信息：
  
  国家自然科学基金资助项目(52005180);河北省自然科学基金资助项目(E2025502001);中央高校基本科研业务费专项资金资助项目(2025MS133);国创计划资助项目(S202410079079)
- DOI：10.19805/j.cnki.jcspe.2026.240649
  中图分类号：
- 网络首发：2026-01-15，
  
  纸质出版：2026-01-15
- 稿件说明：
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王晓龙,杨秀彬,陆志鹏,金韩微,张博文,陶振哲,韩会龙. 基于CMSATE和DTCAE的风电机组偏航轴承服役状态评估动力工程学报, 2026, 46(1): 138-147 https://doi.

org/10.19805/j.cnki.jcspe.2026.240649
王晓龙,杨秀彬,陆志鹏,金韩微,张博文,陶振哲,韩会龙. 基于CMSATE和DTCAE的风电机组偏航轴承服役状态评估动力工程学报, 2026, 46(1): 138-147 https://doi. DOI： 10.19805/j.cnki.jcspe.2026.240649.

org/10.19805/j.cnki.jcspe.2026.240649 DOI：

摘要

针对难以准确检测风电机组偏航轴承早期退化时刻的问题

提出了一种基于复合多尺度符号注意熵和趋势约束自编码器的服役状态评估模型。首先利用复合多尺度符号注意熵方法从偏航轴承原始振动信号中提取多尺度退化特征

然后利用趋势约束自编码器将多尺度退化特征进行压缩降维

构造出能够准确反映偏航轴承服役状态的健康指标

最后结合切比雪夫不等式的自适应健康阈值策略实现偏航轴承服役状态评估。结果表明:该模型能够准确跟踪偏航轴承的运行状态

及时捕捉到初始退化时刻

实现偏航轴承服役状态的准确评估。

Abstract

In response to the problem of difficulty in accurately detecting early degradation of wind turbine yaw bearings

a service status evaluation model based on composite multiscale symbolic attention entropy and trend constrained autoencoder was proposed. Firstly

multiscale degradation features were extracted from the original vibration signals of yaw bearings by the composite multiscale symbolic attention entropy method. Secondly

the trend constrained autoencoder was used to compress and reduce the dimensionality of multiscale degradation features

to construct a health index that can accurately reflect the service status of yaw bearings. Finally

yaw bearing performance degradation was evaluated using adaptive health threshold strategy based on Chebyshev's inequality. Results show that the proposed model can accurately track the operational state of yaw bearings

promptly capture the initial degradation moment

and provide an accurate assessment of the service status of yaw bearings.

关键词

Keywords

references

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