An Lpv Modelling And Fault Diagnosis In Wind Turbine Benchmark System
INTERNATIONAL JOURNAL OF MODELLING IDENTIFICATION AND CONTROL(2017)
摘要
In order to keep away wind turbines from catastrophic conditions due to sudden breakdowns, it is important to detect faults as soon as possible. For diagnosis, a model-based approach is chosen. There are many works that use this fault detection design, but the majority of them consider this system as a linear time invariant (LTI) model. The objective of this paper is, first, to find an LPV model of the system using the subspace identification technique of linear parameter-varying (LPV). Second, we focus on fault diagnosis based on residual generation which is obtained as a comparison between the measured variable and the estimated one using this LPV model. In this work, a benchmark of a wind turbine case is proposed with six predefined faults (three sensor fault scenarios, two actuator fault scenarios and a system fault scenario).
更多查看译文
关键词
model-based fault diagnosis, wind turbine, LPV modelling, subspace identification, residue
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要