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Condition Monitoring and Fault Detection in Wind Turbine Based on DFIG by the Fuzzy Logic

机译:基于模糊逻辑的DFIG风力涡轮机的状态监测与故障检测

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Doubly-fed induction generator is widely used in wind turbine conversion systems. Several research works are being made to efficiently approve existing condition monitoring and fault detection techniques for these systems. The condition monitoring of these systems becomes more and more important, the main obstacle in this task is the lack of an accurate analytical model to describe a faulty DFIG in the majority of the research tasks. In this paper, we present the monitoring strategy of short-circuit fault between turns of the stator windings and open stator phases in doubly-fed induction generator by fuzzy logic technique. The stator condition monitoring is diagnosed based on the root mean square values of current magnitude in addition to the knowledge expressed in rules and membership function. The proposed strategy is verified using simulations performed via the model of Doubly-fed induction generator built in MatLab~R SIMULINK.
机译:双馈诱导发电机广泛用​​于风力涡轮机转换系统。正在进行几种研究工作以有效地批准这些系统的现有状态监测和故障检测技术。这些系统的状态监测变得越来越重要,这项任务中的主要障碍是缺乏准确的分析模型来描述大多数研究任务中的错误DFIG。本文通过模糊逻辑技术,介绍了定子绕组匝数与开放定子阶段的短路故障监测策略。除了规则和隶属函数中表达的知识之外,还基于当前幅度的根均方值诊断定子状态监测。使用通过Matlab〜R Simulink中内置的双馈感应发电机模型进行仿真验证所提出的策略。

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