中国电力2023，Vol.56Issue(10)：71-79,9.DOI:10.11930/j.issn.1004-9649.202303124
基于DRS与改进Autogram的风电齿轮箱复合故障特征提取
Compound Fault Feature Extraction of Wind Power Gearbox Based on DRS and Improved Autogram
摘要
关键词
风电机组/复合故障/离散随机分离/故障诊断/特征提取Key words
wind turbine/compound fault/discrete random separation/fault diagnosis/feature extraction引用本文复制引用
马海飞,滕伟,彭迪康,柳亦兵,靳涛..基于DRS与改进Autogram的风电齿轮箱复合故障特征提取[J].中国电力,2023,56(10):71-79,9.基金项目
国家自然科学基金资助项目(半监督环境下风电机组群的智能化故障诊断与寿命预测,51775186). This work is supported by National Natural Science Foundation of China(Intelligent Fault Diagnosis and Life Prediction of Wind Turbine Group under Semi-Supervised Environment,No.51775186). （半监督环境下风电机组群的智能化故障诊断与寿命预测,51775186）
