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Wind Turbine Fault Diagnosis and Fault-Tolerant Torque Load Control Against Actuator Faults

机译:针对执行器故障的风力发电机故障诊断和容错转矩负载控制

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摘要

Wind turbines are designed to generate electrical energy as efficiently and reliably as possible. Advanced fault detection, diagnosis, and accommodation schemes are necessary to realize the required levels of reliability and availability in modern wind turbines. This paper presents two novel approaches oriented to the design of fault-tolerant control (FTC) schemes for reliable regulation of generator torque in a wind turbine that can be affected by both model uncertainties and actuator faults in its generator/converter. The first approach is based on fuzzy model reference adaptive control in which a fuzzy inference mechanism is used for parameter adaptation without any explicit knowledge of the potential faults in the system. The second approach exploits fuzzy modeling and identification method to develop an integrated model-based fault detection and diagnosis, and automatic signal correction mechanism to accommodate potential faults in the system based on online diagnostic information. Finally, the effectiveness of the proposed FTC schemes is illustrated and compared by a series of simulations on a well-known large offshore wind turbine benchmark in the presence of wind turbulences, measurement noises, and realistic fault scenarios in the generator/converter torque actuator.
机译:风力涡轮机被设计为尽可能高效和可靠地产生电能。先进的故障检测,诊断和适应方案对于实现现代风力涡轮机所需的可靠性和可用性水平是必不可少的。本文提出了两种新颖的方法,旨在设计用于容错控制(FTC)方案的设计,以可靠地调节风力发电机中的发电机转矩,该转矩可同时受模型不确定性和发电机/变频器中的执行器故障的影响。第一种方法基于模糊模型参考自适应控制,其中模糊推理机制用于参数自适应,而无需任何系统潜在故障的明确知识。第二种方法利用模糊建模和识别方法来开发基于模型的集成故障检测和诊断,以及基于在线诊断信息的自动信号校正机制以适应系统中的潜在故障。最后,在发电机/变矩器扭矩执行器中存在风湍流,测量噪声和实际故障情况的情况下,通过在著名的大型海上风力发电机基准上进行一系列模拟,对提出的FTC方案的有效性进行了说明和比较。

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