Wind Turbine Generator Bearing Condition Monitoring with NEST Method

摘要：

Condition Monitoring (CM) can greatly reduce the maintenance cost for a wind turbine. In this paper, history data of Supervisory Control and Data Acquisition (SCADA) system is analyzed to detect the incipient failure of wind turbine generator bearing. A new condition monitoring method based on the Nonlinear State Estimate Technique (NSET) is proposed. NSET is used to construct the normal behavior model of the generator bearing temperature. Detail of NSET is introduced. When the generator bearing has an incipient failure, the residuals between NSET model estimates and the measured generator bearing temperature will become significant. When the residual exceeds the predefined thresholds, an incipient failure is flagged. Analysis of a manual drift added on the historical SCADA data for a wind turbine generator bearing demonstrates the effectiveness of this new condition monitoring method.

关键词： condition monitoring Nonlinear State Estimate Technique (NSET) SCADA data residual analysis wind turbine generator bearing.

作者: Peng Guo

作者单位: School of Control and Computer Engineering, North China Electric Power University, Beijing 102206

会议类型: 国际会议

会议名称: The 24th Chinese Control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)

会议地点: 太原

会议语种:英文

页码: 235-239

在线出版日期: 2012-05-23（万方平台首次上网日期，不代表论文的发表时间）