Measurement Selections for Multicomponent Gas Path Diagnostics Using Analytical Approach and Measurement Subset Concept

Abstract

Gas path analysis (GPA) is a powerful tool to predict gas turbine degradations based on measurement parameters of gas turbine engines. Accordingly, prudent measurement selections are crucial to ensure accurate GPA predictions. This paper is intended to investigate the infiuence of measurement parameter selection toward the effectiveness of GPA algorithm. An analytical methodology for measurement selection, combined with measurement subset concept, is developed to properly select measurements for multiple component fault diagnosis. The effectiveness of GPA using the measurement sets selected with the introduced measurement selection method are then compared with the results of using standard measurements installed on existing gas turbine engines. A case study applying the new measurement selection method to GPA diagnostic analysis is demonstrated on a three-shaft aeroderivative industrial gas turbine model based on similar unit in.'italled onboard an offshore platform operated by PETRONAS. The engine is modeled and simulated using PYTHIA, a gas turbine performance and diagnostics analysis tool developed by Cranfieid University. To validate the findings, nonlinear GPA prediction errors are evaluated in various cases of single and multiconiponents faults. As a result, the selected measurements have successfully produced much superior diagnostics accuracies in the fault cases when compared with the standard measurements. These findings proved that proper measurement selection for better GPA diagnostic analysis can be achieved by using the proposed analytical methods. Several engine sensor enhancements are also discussed to accommodate the unique sensor requirements for health diagnostics using GPA.

A Review on Gas Turbine Gas-Path Diagnostics: State-of-the-Art Methods, Challenges and Opportunities

“…GT engines are packed with different sensors for different purposes such as process control, health monitoring, and diagnostics. Measurement parameters which are essential for engine performance analysis are known as standard measurements [80]. For instance, these include pressure, temperature, fuel flow rate, and spool speed.…”

“…Larsson [107] developed a systematic design procedure to construct non-linear MB fault diagnosis method for industrial GTs. In another study, Jasmani et al [80], devised a new measurement parameter selection scheme by combining analytical approach and measurement subset concept. Likewise, Chen et al [108] proposed an approach that can select the optimal number of engine measurements for engine GPA purpose.…”

Gas turbine gas path diagnostics: A review

“…Also, Emil Larsson [26] developed a systematic design procedure to construct non-linear model based fault diagnosis method for industrial gas turbines. Jasmani [27], mentioned that effective measurement parameter selection is a very critical issue for GPA based engine diagnostics. To tackle this problem he introduced a new system by combining analytical approach and measurement subset concept.…”

Three-spool turbofan pass-off test data analysis using an optimization-based diagnostic technique

“…Several studies have been reported in the literature where different techniques are used for optimal measurement selection. 22,23 The present measurement subset is considered representative for today's turbofan engines undergoing a pass-off test and hence, will be used as a reference subset in this paper. Table 1(a) and (b) presents a standard set of measured data during pass-off testing.…”