Gas Path Analysis on KLM In-Flight Engine Data

2011 ◽  
Author(s):  
Michel L. Verbist ◽  
Wilfried P. J. Visser ◽  
Jos P. van Buijtenen ◽  
Rob Duivis
Keyword(s):  
Path Analysis ◽  
Gas Turbine ◽  
Diagnostic Techniques ◽  
Operating Conditions ◽  
Performance Data ◽  
Analysis Tool ◽  
Incorrect Diagnosis ◽  
Wing Performance ◽  
Cell Data ◽  
Acceptance Tests

Gas-path-analysis (GPA) based diagnostic techniques enable health estimation of individual gas turbine components without the need for engine disassembly. Currently, the Gas turbine Simulation Program (GSP) gas path analysis tool is used at KLM Engine Services to assess component conditions of the CF6-50, CF6-80 and CFM56-7B engine families during post-overhaul performance acceptance tests. The engine condition can be much more closely followed if on-wing (i.e., in-flight) performance data are analyzed also. By reducing unnecessary maintenance due to incorrect diagnosis, maintenance costs can be reduced, safety improved and engine availability increased. Gas path analysis of on-wing performance data is different in comparison to gas path analysis with test cell data. Generally fewer performance parameters are recorded on-wing and the available data are more affected by measurement uncertainty including sensor noise, sensor bias and varying operating conditions. Consequently, this reduces the potential and validity of the diagnostic results. In collaboration with KLM Engine Services, the feasibility of gas path analysis with on-wing performance data is assessed. In this paper the results of the feasibility study are presented, together with some applications and case studies of preliminary GPA results with on-wing data.

Component Map Tuning Procedure Using Adaptive Modeling

2012 ◽  
Author(s):  
Michel L. Verbist ◽  
Wilfried P. J. Visser ◽  
Rene Pecnik ◽  
Jos P. van Buijtenen
Keyword(s):  
Path Analysis ◽  
Gas Turbine ◽  
Engine Performance ◽  
Diagnostic Techniques ◽  
Reference Points ◽  
Performance Data ◽  
Adaptive Modeling ◽  
Real Component ◽  
Modeling Errors ◽  
Component Map

Performance models are effective tools for analysis of engine condition throughout the life cycle of a gas turbine engine. Component maps necessary for accurate performance modeling are typically not provided by the original equipment manufacturers. To compensate for the missing information, available maps of similar components are scaled to match component performance at one or more reference points. Although scaled maps can provide sufficiently accurate results close to the reference points, modeling errors tend to increase further away from these reference points. For applications such as gas path analysis, the resulting modeling errors can be of the same order of magnitude as the deterioration to be detected. This severely limits the application of such techniques. This article presents a component map tuning procedure that tunes maps with more detail than just scaling. The tuned maps are a closer match to real component performance. The tuning procedure combines the adaptive modeling capability of the Gas turbine Simulation Program (GSP) and on-wing measured engine performance data. On-wing measured engine performance data allows map tuning over a wider range of power settings compared to engine performance data measured in a test cell. Effects of measurement uncertainty and scatter, and effects of compressor bleed flows on the map tuning procedure are analyzed and discussed. The tuned component maps enabled more accurate component condition estimations, mainly characterized by less scatter. By improving the accuracy of gas path analysis with on-wing measured performance data, this work has enabled more effective use of performance diagnostic techniques in the aero-engine maintenance industry.

Experience With Gas Path Analysis for On-Wing Turbofan Condition Monitoring

2013 ◽  
Vol 136 (1) ◽  
Author(s):  
Michel L. Verbist ◽  
Wilfried P. J. Visser ◽  
Jos P. van Buijtenen
Keyword(s):  
Path Analysis ◽  
Condition Monitoring ◽  
Operating Conditions ◽  
Performance Data ◽  
Test Rig ◽  
Substantial Cost ◽  
Substantial Cost Saving ◽  
Turbofan Engine ◽  
Monitoring Information

Gas path analysis (GPA) is an effective method for determination of turbofan component condition from measured performance parameters. GPA is widely applied on engine test rig data to isolate components responsible for performance problems, thereby offering substantial cost saving potential. Additional benefits can be obtained from the application of GPA to on-wing engine data. This paper describes the experience with model-based GPA on large volumes of on-wing measured performance data. Critical is the minimization of the GPA results uncertainty in order to maintain reliable diagnostics and condition monitoring information. This is especially challenging given the variable in-flight operating conditions and limited on-wing sensor accuracy. The uncertainty effects can be mitigated by statistical analysis and filtering and postprocessing of the large datasets. By analyzing correlations between measured performance data trends and estimated component condition trends errors can be isolated from the GPA results. The various methods assessed are described and results are demonstrated in a number of case studies on a large turbofan engine fleet.

Experience With GSP as a Gas Path Analysis Tool

2006 ◽  
Author(s):  
W. P. J. Visser ◽  
H. Pieters ◽  
M. Oostveen ◽  
E. van Dorp
Keyword(s):  
Path Analysis ◽  
Gas Turbine ◽  
Reference Model ◽  
Measurement Data ◽  
Engine Performance ◽  
Analysis Data ◽  
Calibration Method ◽  
Analysis Tool ◽  
Operational Environment ◽  
Adaptive Modeling

SKF’s primary tool for gas turbine engine performance analysis is GSP (Gas turbine Simulation Program), a component based modeling environment that is developed at National Aerospace Laboratory NLR and Delft University of Technology, The Netherlands. One of the applications is gas path analysis (GPA) using GSP’s generic adaptive modeling capability. With GSP, gas path analysis has been applied to different aero engines at several maintenance facilities. Additional functionalities have been developed to analyze multiple engine operating points and combine results of different adaptive modeling configurations automatically, resulting in more accurate and reliable GPA results. A ‘multi-point calibration’ method for the reference model was developed providing a significant improvement of GPA accuracy and stability. Also, a method was developed using ‘multiple analysis cycles’ on different condition indicator subsets, which successfully generated values for all condition parameters in cases with fewer measurement parameters than condition indicators and where measurement data are unreliable. The method has been successfully demonstrated on the GEM42 turbo shaft engine. A number of case studies have shown GPA results corresponding to available maintenance notes and inspection data. The extension of the GSP GPA tool with a database system provides a useful tool for analyzing engine history and comparison of analyzed component conditions throughout the fleet. When a large amount of analysis data is stored in the database, statistic analyses, trending and data mining can be performed. Also maintenance work scope effect on engine performance can be predicted. In this paper, the newly developed GSP gas path analysis functionalities are described and experiences and results with the GEM42 engine operational environment are presented.

Validation of a Gas Turbine Thermodynamic Model Without Accurate Component Maps

2017 ◽  
Author(s):  
Anthony Jarrett ◽  
Ying Chen
Keyword(s):  
Gas Turbine ◽  
Thermodynamic Model ◽  
Performance Model ◽  
Test Cell ◽  
Inlet Temperature ◽  
Power Calculation ◽  
Analysis Tool ◽  
Discharge Temperature ◽  
Operating Points ◽  
Cell Data

The authors have developed an engine performance model for use within a physics-based analysis tool to predict gas turbine engine life. The model employs a multivariate optimization method to solve the gas turbine thermodynamic equations, and incorporates a calibration phase to capture the behavior of individual engines without requiring accurate component maps. To validate this approach, a database of test cell data for a turboprop engine has been used. The data consists of approximately 80 engine tests; each one with five operating points. Using a cross-validation method, each engine was uniquely calibrated using four of the operating points, and then validated using parameters from the fifth operating point. To benchmark the calibration process, these analyses were repeated without the calibration stage. The un-calibrated outputs showed a lack of both precision and accuracy, due to imprecision in the component maps, and variation from engine to engine. In contrast, the calibrated outputs of compressor discharge temperature (CDT), compressor discharge pressure (CDP), and turbine inlet temperature (TIT) were predicted within 1% error for more than 95% of all cases. Although most of the key thermodynamic parameters were predicted accurately, we have found that the shaft power calculation demonstrates some significant deviations from the test cell data. This has been attributed to the formulation of the turboprop thermodynamic model, and ongoing work is attempting to mitigate this issue. This understanding of the characteristic engine algorithms will provide valuable guidance in selecting suitable engine parameters as inputs and references.

TEMPER—A Gas-Path Analysis Tool for Commercial Jet Engines

1994 ◽  
Vol 116 (1) ◽  
pp. 82-89 ◽  
Author(s):  
D. L. Doel
Keyword(s):  
Path Analysis ◽  
Gas Turbine ◽  
Gas Turbine Engine ◽  
Analysis Tool ◽  
Jet Engines ◽  
Effective Technique ◽  
Turbine Engine ◽  
Scope Definition ◽  
Research Areas ◽  
Improved Algorithm

Almost from the inception of the gas turbine engine, airlines and engine manufacturers have sought an effective technique to determine the health of the gas-path components (fan, compressors, combustor, turbines) based on available gas-path measurements. The potential of such tools to save money by anticipating the need for overhaul and providing help in work scope definition is substantial, provided they produce reliable results. This paper describes a modern gas-path analysis tool (GE’s TEMPER program), discusses the benefits and problems experienced by current TEMPER users, and suggests promising research areas that may lead to an improved algorithm.

scholarly journals TEMPER: A Gas-Path Analysis Tool for Commercial Jet Engines

1992 ◽  
Author(s):  
David L. Doel
Keyword(s):  
Path Analysis ◽  
Gas Turbine ◽  
Gas Turbine Engine ◽  
Analysis Tool ◽  
Jet Engines ◽  
Effective Technique ◽  
Turbine Engine ◽  
Scope Definition ◽  
Research Areas ◽  
Improved Algorithm

Almost from the inception of the gas turbine engine, airlines and engine manufacturers have sought an effective technique to determine the health of the gas-path components (fan, compressors, combustor, turbines) based on available gas-path measurements. The potential of such tools to save money by anticipating the need for overhaul and providing help in work scope definition is substantial, provided they produce reliable results. This paper describes a modern gas-path analysis tool (GE’s TEMPER1 program), discusses the benefits and problems experienced by current TEMPER users, and suggests promising research areas that may lead to an improved algorithm.

Experience With Gas Path Analysis for On-Wing Turbofan Condition Monitoring

2013 ◽  
Author(s):  
Michel L. Verbist ◽  
Wilfried P. J. Visser ◽  
Jos P. van Buijtenen
Keyword(s):  
Path Analysis ◽  
Condition Monitoring ◽  
Operating Conditions ◽  
Performance Data ◽  
Test Rig ◽  
Substantial Cost ◽  
Substantial Cost Saving ◽  
Turbofan Engine ◽  
Monitoring Information

Gas path analysis (GPA) is an effective method for determination of turbofan component condition from measured performance parameters. GPA is widely applied on engine test rig data to isolate components responsible for performance problems, thereby offering substantial cost saving potential. Additional benefits can be obtained from the application of GPA to on-wing engine data. This paper describes the experience with model-based GPA on large volumes of on-wing measured performance data. Critical is the minimization of the GPA results uncertainty in order to maintain reliable diagnostics and condition monitoring information. This is especially challenging giving the variable in-flight operating conditions and limited on-wing sensor accuracy. The uncertainty effects can be mitigated by statistical analysis, and filtering and post-processing of the large datasets. By analyzing correlations between measured performance data trends and estimated component condition trends errors can be isolated from the GPA results. The various methods assessed are described and results are demonstrated in a number of case studies on a large turbofan engine fleet.

Supersonic Ejectors for Hydrocarbon Emissions Capture

2011 ◽  
Author(s):  
Yuri Biba ◽  
H. Allan Kidd ◽  
Stephen Peifer ◽  
Christopher Scott ◽  
Brian Sloof ◽  
...  
Keyword(s):  
Gas Turbine ◽  
Operating Cost ◽  
Operating Conditions ◽  
Hydrocarbon Emissions ◽  
Analysis Tool ◽  
Fuel Gas ◽  
Supersonic Ejector ◽  
Reduce Operating Cost ◽  
Ejector System ◽  
System Operating

Supersonic ejectors can be applied to capture low-pressure leakage gas from the gas seal vents of a centrifugal compressor. This captured gas can be re-injected into the fuel gas line of the gas turbine driver or the captured gas can be used as a fuel for gas fired utility heaters. By capturing the gas that is normally emitted to the atmosphere the operator can reduce operating cost and enjoy a reduction in hydrocarbon foot print. Because the supersonic ejector does not have moving parts, the system operating and maintenance costs are lower than functionally comparable traditional systems. In this study, a prototype of a supersonic ejector system was developed and tested at a pipeline compressor station. The obtained test data were used for developing and tuning a mean-line aerodynamic analysis tool, which predicts the ejector’s operating map. A family of three ejectors was designed to cover a range of operating conditions associated with gas turbine driven pipeline compressors. These ejectors were built, installed on a specially designed panel, described as the ejector system, and tested on inert gas at the original equipment manufacturer’s (OEM’s) facility. A comparison of predicted and as-tested supersonic ejector performance maps is discussed and conclusions are made about the system operating range.

A Generalized Fault Classification for Gas Turbine Diagnostics on Steady States and Transients

2006 ◽  
Author(s):  
Igor Loboda ◽  
Sergey Yepifanov ◽  
Yakov Feldshteyn
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Steady State ◽  
Gas Turbine ◽  
Correct Diagnosis ◽  
Diagnostic Techniques ◽  
Operating Conditions ◽  
Fault Classification ◽  
Diagnostic Process ◽  
Transient Operation

Gas turbine diagnostic techniques are often based on the recognition methods using the deviations between actual and expected thermodynamic performances. The problem is that the deviations depend on real operating conditions. However, our studies show that such a dependency can be reduced. In this paper, we propose the generalized fault classification that is independent of the operating conditions. To prove this idea, the averaged probabilities of the correct diagnosis are computed and compared for two cases: the proposed classification and the traditional one based on the fixed operating conditions. The probabilities are calculated through a stochastic modeling of the diagnostic process, in which a thermodynamic model generates deviations that are induced by the faults. Artificial neural networks recognize these faults. The proposed classification principle has been realized for both, steady state and transient operation of the gas turbine units. The results show that the acceptance of the generalized classification practically does not reduce the diagnosis trustworthiness.

Application of Gas Path Analysis to Compressor Diagnosis of an Industrial Gas Turbine Using Field Data

2014 ◽  
Author(s):  
J. Blinstrub ◽  
Y. G. Li ◽  
M. Newby ◽  
Q. Zhou ◽  
G. Stigant ◽  
...  
Keyword(s):  
Path Analysis ◽  
Gas Turbine ◽  
Field Data ◽  
Measurement Data ◽  
Diagnostic Technique ◽  
Operating Conditions ◽  
Maintenance Cost ◽  
Diagnostic Analysis ◽  
Major Life ◽  
Monitoring And Diagnostics

Maintenance cost is one of the major life cycle costs of gas turbine engines. To reduce the maintenance costs, the maintenance should be changed from preventive (or scheduled) maintenance to predictive (or condition-based) maintenance where condition monitoring and diagnostics become crucially important. This paper represents the application of a gas path diagnostic technique, Gas Path Analysis, to the diagnostic analysis of an aero-derivative gas turbine (GE LM2500+) operated by Manx Electricity Authority in the Isle of Man, UK. In the application, an engine thermodynamic model is created and adapted to the performance of the engine using field data obtained at different operating conditions. Different data pre-processing methods are presented and compared in the diagnostic analysis. The uncertainty of measurement data is analysed and the most suitable measurements are identified in the prediction of key gas path component degradation. A non-linear GPA diagnostic analysis provides promising results for the prediction of compressor degradation and the performance improvement due to a compressor water washing. Such diagnostic information would be very useful for maintenance engineers to optimise their maintenance activities including overhauls and compressor washing.

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