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赵劲松,王梓齐,刘长良. 基于Bagging集成策略和多元状态估计的风电机组齿轮箱状态监测[J]. 科学技术与工程, 2020, 20(20): 8180-8186.
zhaojinsong,wangziqi.Wind Turbine Gearbox Condition Monitoring based on Bagging Ensemble Strategy and MSET[J].Science Technology and Engineering,2020,20(20):8180-8186.
基于Bagging集成策略和多元状态估计的风电机组齿轮箱状态监测
Wind Turbine Gearbox Condition Monitoring based on Bagging Ensemble Strategy and MSET
投稿时间:2019-09-17  修订日期:2020-04-17
DOI:
中文关键词:  Bagging 集成学习  多元状态估计 风电机组齿轮箱  状态监测
英文关键词:Bagging  ensemble learning  multivariate state  estimation technique  wind turbine  gearbox condition  monitoring
基金项目:北京市自然科学基金(4182061)
        
作者单位
赵劲松 华北电力大学控制与计算机工程学院
王梓齐 华北电力大学控制与计算机工程学院
刘长良 新能源电力系统国家重点实验室(华北电力大学)
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中文摘要:
      风电机组齿轮箱的故障率和维护成本相对较高,有必要对其运行状态进行实时监测。多元状态估计(MSET)是一种常用的状态监测方法,但在记忆矩阵规模较大时,MSET在线计算的实时性较差。为此,提出了一种基于Bagging集成策略和MSET的新方法:首先基于Bagging集成策略,对训练数据进行多次随机抽样,构造多个记忆矩阵规模较小的MSET子模型,最终将子模型的结果平均后作为集成模型的输出。以某2 MW风电机组的运行数据为算例,对集成MSET的性能进行了对比实验,结果表明:在精度相当的前提下,集成方法的计算时间仅为常规方法的60%;结合统计过程控制(SPC)技术设计了预警阈值和滑动窗口异常率,并对集成MSET的故障预警能力进行验证,结果表明:集成方法能够提前约10天预警齿轮箱的实际故障。
英文摘要:
      The failure rate and maintenance cost of wind turbine gearbox are relatively high, it is necessary to monitor its operation condition in real-time. Multivariate state estimation technique (MSET) is a commonly used condition monitoring method, he real-time performance of MSET online computing is poor when the memory matrix is large. To this end, a novel method based on Bagging ensemble strategy and MSET was proposed. Firstly, the training data are sampled randomly for several times based on Bagging ensemble strategy, and a subset of MSET with smaller memory matrix is constructed. Finally, the results of the subset are averaged as the output of the ensemble model. Taking the operational data of a 2 MW wind turbine as an example, the performance of ensemble MSET was compared. The results show that the calculation time of ensemble method is only 60% of conventional method under the premise of the same accuracy. The warning threshold and sliding window exception rate were designed based on statistical process control (SPC), and the fault warning ability of ensemble MSET was verified. The results show that the ensemble method can warn the actual faults of gearbox about 10 days in advance.
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