计算机与现代化Issue(10)：57-61,71,6.DOI:10.3969/j.issn.1006-2475.2017.10.012
基于D-S证据融合的风力发电机组的故障预测
Fault Prediction of Wind Turbine Based on D-S Evidence Fusion
摘要
Abstract
Aiming at the mechanical and electrical faults of wind turbine generator,this paper presents a D-S fusion model based on electrical feature vector and vibrational feature vector.We construct two parameter-optimized support vector machines,as two evidences to predict the final fault pattern.Compared with the traditional fault diagnosis of generator for mechanical fault and electrical fault with vibration sensor and current sensor to distinguish different faults by spectrum characteristics,evidence fusion method can make current signal used for mechanical fault diagnosis,also vibration signal can be used for electric fault.Through a large number of experimental data analysis,fusion model compared with only a single signal structure has higher classification accuracy.关键词
风力发电机/故障诊断/小波包分解/D-S证据理论/支持向量机Key words
wind power generator/fault diagnosis/wavelet packet/D-S evidence theory/SVM分类
信息技术与安全科学引用本文复制引用
田艳丰,刘石磊,井艳军,杨轶..基于D-S证据融合的风力发电机组的故障预测[J].计算机与现代化,2017,(10):57-61,71,6.基金项目
辽宁省自然科学基金资助项目(201404105) （201404105）
