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Fault detection and isolation system for boiler-turbine unit of a thermal power plant

机译:火力发电厂汽轮机故障检测与隔离系统

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摘要

In this study, a sensor fault detection and isolation (FDI) system is presented for a boiler-turbine unit of a thermal power plant in Mexico. The FDI system is based on a Luenberger-like observer for residual generation. An adaptive threshold for residual evaluation is considered to avoid false alarms. The observer is based on a quasi-linear parameter variant (quasi-LPV) model of the boiler-turbine unit parameterized with real data of the plant in a wide range of operations, namely, at low, medium, and high loads. The quasi-LPV model adequately represents the dynamics of more critical variables including first stage turbine pressure, superheated steam pressure, drum pressure, and electric power. The performance of the FDI system is evaluated in a practical scenario by using real data from the thermoelectric plant. The main contribution of this study involves proposing a reliable fault diagnosis system to detect sensor faults in a wide operational range of the process based on the quasi-LPV framework. (C) 2017 Elsevier B.V. All rights reserved.
机译:在这项研究中,提出了一种针对墨西哥火力发电厂的汽轮机机组的传感器故障检测与隔离(FDI)系统。 FDI系统基于类似Luenberger的观察器来生成残差。残差评估的自适应阈值被认为可以避免误报。该观察器基于锅炉涡轮机单元的准线性参数变量(quasi-LPV)模型,该模型使用电厂的实际数据在各种操作(即低,中和高负荷)下进行参数化。准LPV模型可以充分代表更关键的变量的动力学,包括第一级涡轮压力,过热蒸汽压力,汽包压力和电力。在实际情况下,通过使用来自热电厂的真实数据来评估FDI系统的性能。这项研究的主要贡献在于,提出一种可靠的故障诊断系统,以基于准LPV框架在过程的广泛操作范围内检测传感器故障。 (C)2017 Elsevier B.V.保留所有权利。

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