Gas path fault diagnosis for gas turbine engines with fully operating regions using mode identification and model matching

Abstract

Gas path fault diagnosis is key to improving the reliability and safety of gas turbine engines. Flexible operating conditions bring obstacles to performing accurate gas path performance analysis. Most of the existing methods are developed for specific operating conditions, which are difficult to adapt to fully operating regions. The operating mode identification and targeted diagnostic model matching are effective technologies to solve the gas path fault diagnosis under fully operating regions, which improves diagnostic accuracy and efficiency. The fully operating regions are classified into four typical operating modes, and the targeted diagnostic models are matched according to the mode features. For the typical start-stop state and high dynamic state, the small deviation diagnostic model and transient diagnostic model are established and verified by real fault cases. The small deviation diagnostic model based on boundary parameters reduces the influences of operating conditions on diagnostic results, it accurately monitors the health states. The transient diagnostic model driven by the dynamic model and a designed hybrid solution algorithm markedly improves diagnostic accuracy and efficiency. It shows better performance for the mixed gas path fault modes, more stable diagnostic results, and higher diagnostic efficiency. The proposed technical framework provides an effective way for the fault diagnosis of gas turbine engines under fully operating regions.

Determining Steady-State Operation Criteria Using Transient Performance Modelling and Steady-State Diagnostics

“…The importance of identifying the steady-state operation of engineering systems in general has been recognized, and efforts towards developing algorithms that are able to identify such operation have been presented for many years (for example, [9]) using statistical concepts. The features of the problem of determining whether an operating condition can be characterized as steady-state, for the particular case of gas turbines, is also well known, and methods for its solution have been presented in the literature until very recently [10][11][12][13][14][15][16][17][18]. The motivation of exploiting test data for the purpose of engine condition monitoring was the driver of earlier methods [10,12].…”

“…In [16], for example, measurement data from operation are statistically processed in order to derive the relevant criteria. In [18], test data are used to identify clusters that are indicative of the mode of operation, with steady state being one of the modes of interest. Although the underlying physical principles are understood regarding the reasons why steady-state diagnostic methods using data from transient operation do not produce accurate information on the condition of the components, no quantification of such effects has been presented; neither has a procedure of a general nature been presented for tackling this problem in gas turbines.…”