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INVERSE METHODOLOGIES FOR ACTUAL STATUS RECOGNITION OF GAS TURBINE COMPONENTS

机译:燃气轮机组件实际状态识别的逆方法

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摘要

A general methodology has been established to set up GT based plant simulators to perform analysis and to identify inverse model parameters. The attention is focused on three categories of inverse problems faced in setting up the plant simulator: ⅰ) sizing of components; ⅱ) calibration on the basis of test acceptance data; ⅲ) actual status recognition from data collected by the plant monitoring system. Due to the different nature and requirements of the above problems different solution approaches have been adopted: hybrid stochastic- deterministic algorithms for model calibration and neural techniques for status recognition. An application to a real plant shows the capabilities of the proposed methodology.
机译:已经建立了一种通用的方法来设置基于GT的工厂模拟器来执行分析和识别逆模型参数。注意力集中在安装工厂模拟器时面临的三类逆问题上:ⅰ)组件的尺寸确定; ⅱ)根据测试验收数据进行校准; ⅲ)从工厂监控系统收集的数据中识别出实际状态。由于上述问题的性质和要求不同,因此采用了不同的解决方法:用于模型校准的混合随机确定性算法和用于状态识别的神经技术。实际工厂中的应用程序显示了所提出方法的功能。

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