湖南大学学报（自然科学版）2026，Vol.53Issue(6)：131-143,13.DOI:10.16339/j.cnki.hdxbzkb.2026278
基于联邦学习和可变形卷积网络的风机集群多故障诊断方法
Multi-fault diagnosis of wind turbine clusters based on federated learning and deformable convolutional networks
摘要
Abstract
To solve the problem of"data islands"generated by different turbines in a wind turbine cluster,which affects the accuracy of multi-fault diagnosis,the FedLVA-WTDCN method is proposed,which achieves cross-equipment and cross-region data co-training,and at the same time guarantees the generalisation ability of the model,which improves the comprehensiveness and reliability of fault diagnosis.In this paper,the aggregation algorithm of federated learning is improved,and an aggregation method based on the joint weighting of loss inverse and variance(FedLVA)is proposed to replace the traditional FedAvg algorithm.In addition,combining with the background of wind turbine fault diagnosis,the latest deformable convolutional network(DCN)is used to the federated learning local model,and WTDCN(wind turbine deformable convolutional network)is proposed,which makes full use of its self-adaptive feature extraction capability to further improve the diagnostic accuracy.Comparison between centralised training and federated learning through open-source wind turbine datasets demonstrates the effectiveness of federated learning in solving the wind turbine cluster fault diagnosis problem;comparison through different aggregation algorithms proves the stability and reliability of the proposed FedLVA algorithm;and the use of different local learning models illustrates that the proposed WTDCN method can be better applied to wind turbine cluster data.关键词
风电机组/故障诊断/联邦学习/可变形卷积网络Key words
wind turbines/fault diagnosis/federated learning/deformable convolutional network分类
信息技术与安全科学引用本文复制引用
火久元,张沣琦,孟昱煜,常琛..基于联邦学习和可变形卷积网络的风机集群多故障诊断方法[J].湖南大学学报（自然科学版）,2026,53(6):131-143,13.基金项目
甘肃省重点研发计划-工业领域(25YFGA045),Gansu Provincial Key R&D Program-Industrial Field(25YFGA045) （25YFGA045）
国家自然科学基金资助项目(62262038),National Natural Science Foundation of China(62262038) （62262038）
