ABSTRACT A prognostic approach based on a MISO (multiple inputs and single output) fuzzy logic model was introduced to estimate the pressure difference across a gas turbine (GT) filter house in a heavy-duty power generation system. For modelling and simulation of clogging of the GT filter house, nine real-time process variables (ambient temperature, humidity, ambient pressure, GT produced load, inlet guide vane position, airflow rate, wind speed, wind direction and PM10 dust concentration) were fuzzified using a graphical user interface within the framework of an artificial intelligence-based methodology. The results revealed that the proposed fuzzy logic model produced very small deviations and showed a superior predictive performance than the conventional multiple regression methodology, with a very high determination coefficient of 0.974. A complicated dynamic process, such as clogging phenomenonin heavy-duty GT system, was successfully modelled due to high capability of the fuzzy logic-based prognostic approach in capturing the nonlinear interactions.

中文翻译：

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模拟重型发电系统中燃气轮机过滤室的堵塞情况

摘要引入了基于 MISO（多输入单输出）模糊逻辑模型的预测方法来估计重型发电系统中燃气轮机 (GT) 过滤室的压差。为了对 GT 过滤室的堵塞进行建模和模拟，九个实时过程变量（环境温度、湿度、环境压力、GT 产生的负载、入口导叶位置、气流速率、风速、风向和 PM10 粉尘浓度）是在基于人工智能的方法的框架内使用图形用户界面进行模糊化。结果表明，所提出的模糊逻辑模型产生的偏差非常小，并且比传统的多元回归方法具有更好的预测性能，确定系数非常高，为 0.974。