A component map tuning method for performance prediction and diagnostics of gas turbine compressors
A component map tuning method for performance prediction and diagnostics of gas turbine compressors
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DOI：
10.1016/j.apenergy.2014.08.115
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发表时间：
2014-12-15
期刊：
影响因子：
11.2
通讯作者：
Khorasani, Khashayar
中科院分区：
文献类型：
--
作者：
Tsoutsanis, Elias;Meskin, Nader;Khorasani, Khashayar
本文提出了一种新的压气机MAP整定方法，其主要目的是提高用于性能预测和诊断的燃气轮机模型的准确性和保真度。介绍了一种新的压缩图拟合和建模方法，可同时确定一组压缩图数据的最佳椭圆曲线。通过多目标优化方案对决定压气机性能曲线形状的系数进行分析和调整，以便同时匹配多组发动机性能测量。在面向对象的MatLab Simulink环境下开发的部件图整定方法在动态燃气轮机模型上实现，并在变工况、过渡工况和退化工况下进行了试验。所提供的结果证明和说明了我们所提出的方法能够将现有的发动机性能模型改进为不同的燃气轮机运行模式。此外，喷油量与发动机模型预测退化之间的良好一致性表明了所提出的方法在燃气轮机诊断中的潜力。所提出的方法可以与基于性能的工具相集成，以改进燃气轮机发电厂的状态监测和诊断。(C)2014爱思唯尔有限公司。保留所有权利。
In this paper, a novel compressor map tuning method is developed with the primary objective of improving the accuracy and fidelity of gas turbine engine models for performance prediction and diagnostics. A new compressor map fitting and modeling method is introduced to simultaneously determine the best elliptical curves to a set of compressor map data. The coefficients that determine the shape of the compressor map curves are analyzed and tuned through a multi-objective optimization scheme in order to simultaneously match multiple sets of engine performance measurements. The component map tuning method, that is developed in the object oriented Matlab Simulink environment, is implemented in a dynamic gas turbine engine model and tested in off-design steady state and transient as well as degraded operating conditions. The results provided demonstrate and illustrate the capabilities of our proposed method in refining existing engine performance models to different modes of the gas turbine operation. In addition, the excellent agreement between the injected and the predicted degradation of the engine model demonstrates the potential of the proposed methodology for gas turbine diagnostics. The proposed method can be integrated with the performance-based tools for improved condition monitoring and diagnostics of gas turbine power plants. (C) 2014 Elsevier Ltd. All rights reserved.