Abstract
To ensure reliable and efficient operation of gas turbines, multiple model (MM) approaches have been extensively studied for online fault detection and isolation (FDI). However, current MM-FDI approaches are difficult to directly apply to gas path FDI, which is one of the common faults in gas turbines and is understood to mainly be due to the high complexity and computation in updating hypothetical gas path faults for online applications. In this paper, a fault contribution matrix (FCM) based MM-FDI approach is proposed to implement gas path FDI over a wide operating range. As the FCM is realized via an additive term of the healthy model set, the hypothetical models for various gas path faults can be easily established and updated online. In addition, a gap metric analysis method for operating points selection is also proposed, which yields the healthy model set from the equal intervals linearized models to approximate the nonlinearity of the gas turbine over a wide range of operating conditions with specified accuracy and computational efficiency. Simulation case studies conducted on a two-shaft marine gas turbine demonstrated the proposed approach is capable of adaptively updating hypothetical model sets to accurately differentiate both single and multiple faults of various gas path faults.
Highlights
With increasing gas turbine complexity, requirements for ensuring reliability and security are growing significantly, and diagnosis of gas path component faults is becoming a major issue [1].The main causes of gas path faults include fouling, erosion, corrosion, and foreign object damage (FOD), which degrade the performance of the gas turbine, further reduce its safety and stability, and lead to decreased fuel economy and increases in operation and maintenance costs [2]
The proposed fault contribution matrix (FCM) based multiple model (MM)-Fault detection and isolation (FDI) approach is applied to a two-shaft marine gas turbine
100 simulations of single gas path faults were performed each time at the operating point, and repeated 10 times for a total of 1000 simulations based on the gas turbine nonlinear model
Summary
With increasing gas turbine complexity, requirements for ensuring reliability and security are growing significantly, and diagnosis of gas path component faults is becoming a major issue [1]. The MM-FDI approach was used to detect and isolate the gas path fault, and a hierarchical architecture was developed that enabled the detection and isolation of both single and multiple faults in the jet engine [24]. According to Equation (2), each gas path fault at the operating point i is matched to a hypothetical fault model, which means that the system matrices corresponding to each gas path fault need to be established separately in advance for applying the MM-FDI approach. A gas path fault contribution matrix (FCM) was introduced to improve the performance of the MM-FDI approach to address the above problem, and a systemic method to select the operating points that form the healthy model set was carried out based on gap metric analysis to achieve MM-FDI over a wide range of operating conditions.
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