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Fault Diagnosis and Accommodation System with a Hybrid Model for Fuel Cell Power Plant

机译:具有燃料电池发电厂混合模型的故障诊断和容纳系统

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As a part of U.S. distributed generation program, the concept of hybrid fuel cell power plants has shown its application potential and is already under commercialization. In the hybrid direct fuel cell and turbine (DFC/T) plant, the control system is an essential component that guarantees reliable and efficient operations. Being an effective complement for the local control scheme, a fault diagnosis and accommodation system based on fuzzy logic is implemented with the help of neural network augmenters, which improve the accuracy of the nominal model of the fuel cell plant. As a quantitative approach, the fuzzy fault diagnosis and accommodation system has considerably lower realization complexities than an analytical and detailed fault regulator. The system structures and design methods are discussed in this paper. Model augmentation and simulation results are presented to verify the performance of the overall system.
机译:作为美国分布式发电计划的一部分,混合动力燃料电池发电厂的概念表明了其应用潜力并且已经在商业化下。在混合直接燃料电池和涡轮机(DFC / T)工厂中,控制系统是保证可靠和有效的操作的必备组件。作为局部控制方案的有效补充,基于模糊逻辑的故障诊断和容纳系统在神经网络增强器的帮助下实现,从而提高了燃料电池厂的标称模型的准确性。作为定量方法,模糊故障诊断和容纳系统的实现复杂性比分析和详细的故障调节器相当较低。本文讨论了系统结构和设计方法。提出了模型增强和仿真结果以验证整个系统的性能。

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