An Approach for Optimal Measurements Selection on Gas Turbine Engine Fault Diagnosis

Abstract

Gas path fault diagnosis plays an important role in guaranteeing safe, reliable and cost-effective operation for gas turbine engines. Measurements selection is among the most critical issues for diagnostic method implementation. In this paper, an integration approach for optimal measurements selection, which combines finger print diagrams analysis, health parameters correlation analysis, performance estimation uncertainty index analysis and fault cases validation based on genetic algorithm, has been proposed and applied to assess the health condition of a two-spool split flow turbofan in test bed. First, mathematical description of an engine gas path fault diagnosis process was given and the influence coefficient matrix was also calculated based on a well calibrated nonlinear engine performance simulation model. Second, the number of combination candidates was reduced from 782 to 256 and three measurements were picked out using the finger print diagrams analysis and the health parameters correlation analysis. Then, the number of the combination candidates was further narrowed down to 13 using the performance estimation uncertainty index analysis. A nonlinear genetic algorithm fault diagnosis method was applied to test the diagnostic ability of the remaining measurement candidates. Finally, an optimal measurement combination was worked out which demonstrated the effectiveness of the integration approach. This integration approach for optimal measurements selection is also applicable to other type of gas turbine engines.

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

“…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. However, GPA techniques can diagnose GT faults if, and only if, noise and bias does not exist [93].…”

“…For this purpose, six SCF and 15 DCF classes were considered. A GA based GT fault diagnosis method was used to find an optimal combination of a set of performance parameters and the corresponding set of best match measurement parameters, through a non-linear performance simulation model [108]. A generalized GA based GT fault classification method was proposed by Loboda et al [207] using a thermodynamic model that is applicable to multiple operating point conditions for both steady state and transient cases.…”

A performance degradation evaluation method for a turbocharger in a diesel engine

“…Normally, turbocharger overall health status can be represented by gas-path component health parameters SF (i.e. compressor and turbine flow capacity indices and efficiency indices [18,19]), which represent a shift of the characteristic curves on component maps due to degradation, seen in figure 5. However, this essential performance and health status information cannot be directly measured and thus cannot be easily monitored and diagnosed.…”

“…However, these important performance and health status information cannot be directly measured and therefore are not easily monitored. During turbocharger operations, the deviation of component performance parameters can be indicated by the deviation of gas-path measurement parameters and such deviation of component performance parameters may be due to varying operating conditions or turbocharger performance degradation [18,19]. The thermodynamic relationship between turbocharger gas-path measurement parameters and turbocharger component performance parameters can be expressed with equation (2.36).z=f false(x, ufalse)+v,where z is gas-path measurement parameter vector, z∈RM; x is turbocharger component performance parameter vector; u is ambient and operating condition vector; v is transducer measurement noise vector, v∈RM.…”

Gas turbine gas path diagnostics: A review

“…To tackle this problem he introduced a new system by combining analytical approach and measurement subset concept. More recently, Chen et al [28] proposed an approach that can select the optimal number of engine measurements for diagnostics. However, GPA techniques can diagnose gas turbine faults if and only if noise and bias doesn't exist and they cannot classify clearly the gas path component faults [25].…”