A sensitive and easy-to-deploy condition monitoring method for main drive chain of large wind turbines

IF 9 1区工程技术 Q1 ENERGY & FUELS

Renewable Energy Pub Date : 2025-06-16 DOI:10.1016/j.renene.2025.123773

Wei Liu , Xian Wang , Qingcan Long , Bing Zeng , Shuai Zhong

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引用次数: 0

Abstract

Effective condition monitoring of the main drive chain of wind turbines is crucial to reducing the operation and maintenance costs of wind farms. Based on the condition monitoring theory of Normal Behavior Model (NBM) of machine learning, this paper proposes a sensitive and easy-to-deploy condition monitoring method for main drive chain of large wind turbines. In order to better characterize the normal state of main drive chain, the process of selecting input and output variables for the NBM considers both the correlations among monitoring data and the working mechanism of main drive chain. The NBM, constructed based on the Informer network using the Transformer architecture, ProbSparse self-attention mechanism, and attention distillation mechanism, provides a better accuracy and requires fewer computing resources than traditional methods. In order to accurately and sensitively reflect the health conditions of main drive chain, the designed condition assessment index adopts a double-variable residual fusion mechanism and a historical memory elimination mechanism. The case studies show that the method is effective for condition monitoring and early warning for fault of main drive chain in an on-site environment. Further studies have found that the proposed method has strong transferability and is expected to be easily deployed at scale.

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大型风力发电机组主传动链状态监测方法研究

对风力发电机主传动链进行有效的状态监测，对于降低风电场的运行和维护成本至关重要。基于机器学习的正常行为模型（NBM）状态监测理论，提出了一种灵敏、易于部署的大型风力发电机组主传动链状态监测方法。为了更好地表征主传动链的正常状态，在选择NBM输入输出变量的过程中，既考虑了监测数据之间的相关性，又考虑了主传动链的工作机理。NBM基于Informer网络，采用Transformer架构、ProbSparse自关注机制和关注蒸馏机制构建而成，与传统方法相比，具有更高的准确率和更少的计算资源。为了准确灵敏地反映主传动链的健康状况，所设计的状态评估指标采用双变量残余融合机制和历史记忆消除机制。实例研究表明，该方法对现场环境下主传动链的状态监测和故障预警是有效的。进一步研究发现，该方法具有较强的可移植性，有望实现规模化部署。

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来源期刊

Renewable Energy 工程技术-能源与燃料

CiteScore

18.40

自引率

9.20%

发文量

1955

审稿时长

6.6 months

期刊介绍： Renewable Energy journal is dedicated to advancing knowledge and disseminating insights on various topics and technologies within renewable energy systems and components. Our mission is to support researchers, engineers, economists, manufacturers, NGOs, associations, and societies in staying updated on new developments in their respective fields and applying alternative energy solutions to current practices. As an international, multidisciplinary journal in renewable energy engineering and research, we strive to be a premier peer-reviewed platform and a trusted source of original research and reviews in the field of renewable energy. Join us in our endeavor to drive innovation and progress in sustainable energy solutions.