Modelling the clogging of gas turbine filter houses in heavy-duty power generation systems. Issue 2 (3rd March 2020)

• Record Type: Journal Article
• Authors: Abdul-Wahab, Sabah Ahmed; Omer, Abubaker Sayed Mohamed; Yetilmezsoy, Kaan; Bahramian, Majid
• Is Part Of: Mathematical and computer modelling of dynamical systems. Volume 26:Issue 2(2020)
• Page Start: 119
• Page End: 143
• Publication Date: 2020-03-03
• Subjects: Clogging phenomenon -- fuzzy logic model -- heavy-duty power generation system; Engineering -- Mathematical models -- Periodicals; Computer simulation -- Periodicals; 515.39
• DOI: 10.1080/13873954.2020.1713821
• Languages: English
• ISSNs: 1387-3954

Abstract

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.