Application of Multiple Handle Gas Path Analysis on a Singlespool Turbofan Engine

2001 ◽  
Vol 18 (4) ◽  
Author(s):  
Eftychios Kleinakis ◽  
Pericles Pilidis ◽  
Petros Kotsiopoulos
Keyword(s):  
Path Analysis ◽  
Turbofan Engine

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 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.

Evolutionary Algorithm for Enhanced Gas Path Analysis in Turbofan Engines

2021 ◽  
Author(s):  
T. O. Rootliep ◽  
W. P. J. Visser ◽  
M. Nollet
Keyword(s):  
Path Analysis ◽  
Evolutionary Algorithm ◽  
Operating Point ◽  
Turbofan Engine ◽  
Turbofan Engines ◽  
Novel Approach ◽  
Multiple Data Sets ◽  
Engine Maintenance ◽  
Operating Points ◽  
Health Parameters

Abstract Adaptive modelling (AM) based Gas Path Analysis (GPA) is a powerful diagnostic and prognostic technique for turbofan engine maintenance. This involves the assessment of turbofan component condition using thermodynamic models that can iteratively adapt to measurements values in the gas path by changing component condition parameters. The problem with this approach is that newer turbofan engines such as the General Electric GEnx-1B have fewer gas path sensors installed causing the AM equation systems to become underdetermined. To overcome this problem, a novel approach has been developed that combines the AM model with an Evolutionary Algorithm (EA) optimization scheme and applies it to multiple operating points. Additionally, these newer turbofan engines provide performance data continuously during flight. Information on variable geometry and bleed valve position, active clearance control state and power off-take is included and can be accounted for to further enhance AM model accuracy. A procedure is proposed where the selection of operating points is based on steady-state stability requirements, cycle model operating point uncertainty and parameter outlier filtering. The Gas turbine Simulation Program (GSP) is used as the non-linear GPA modelling environment. A Multiple Operating Point Analysis (MOPA) is chosen to overcome the problem of underdetermination by utilizing multiple data sets at different operating points. The EA finds the best fit of health parameter deviations by minimizing the multi-point objective function using the GSP AM model. A sub-form of the EA class named Differential Evolution (DE) has been chosen as the optimizer. Like all EAs, DE is a parallel direct search method in which a population of parameter vectors evolves following genetic operations towards an optimum output candidate. The resulting hybrid GPA tool has been verified by solving for different simulated deterioration cases of a GSP model. The tool can identify the direction and magnitude of condition deviation of 10 health parameters using 6 gas path sensors. It has subsequently been validated using historical in-flight data of the GEnx-1B engine. It has demonstrated successful tracking of engine component condition for all 10 health parameters and identification of events such as turbine blade failure and water washes. The authors conclude that the tool has proven significant potential to enhance turbofan engine condition monitoring accuracy for minimizing maintenance costs and increasing safety and reliability.

An Input–Process–Output Model of Pilot Core Competencies

2017 ◽  
Vol 7 (2) ◽  
pp. 78-85 ◽  
Author(s):  
Heikki Mansikka ◽  
Don Harris ◽  
Kai Virtanen
Keyword(s):  
Path Analysis ◽  
Team Performance ◽  
Core Competencies ◽  
Core Competency ◽  
Principal Component ◽  
Analysis Model ◽  
Input Process ◽  
The Core ◽  
Performance Framework ◽  
Process Output

Abstract. The aim of this study was to investigate the relationship between the flight-related core competencies for professional airline pilots and to structuralize them as components in a team performance framework. To achieve this, the core competency scores from a total of 2,560 OPC (Operator Proficiency Check) missions were analyzed. A principal component analysis (PCA) of pilots’ performance scores across the different competencies was conducted. Four principal components were extracted and a path analysis model was constructed on the basis of these factors. The path analysis utilizing the core competencies extracted adopted an input–process–output’ (IPO) model of team performance related directly to the activities on the flight deck. The results of the PCA and the path analysis strongly supported the proposed IPO model.

Pengaruh Good Corporate Governance Terhadap Nilai Perusahaan Dengan Variabel Intervening Profitabilitas

2017 ◽  
Vol 25 (1) ◽  
pp. 13-39
Author(s):  
Achmad Tjahjono ◽  
Siti Chaeriyah
Keyword(s):  
Corporate Governance ◽  
Path Analysis ◽  
Executive Director ◽  
Audit Committee ◽  
Positive Impact ◽  
Institutional Ownership ◽  
Analysis Tool ◽  
Manufacturing Companies ◽  
Company Value ◽  
Good Corporate Governance

The Company was founded with the goal of increasing the value of the company as well as to provide prosperity for the owners or shareholders. Good Corporate Governance and profitability is an effort to enhance company value. This study aims to determine the influence of good corporate governance to company value with profitability as intervening variable. The population of this research is manufacturing companies listed in Indonesia Stock Exchange in 2010 - 2014. The sample is taken by using purposive sampling method. Under this method, as many as 123 companies were obtained. The analysis tool to test the hypothesis is path analysis with AMOS software version 21. Data analysis method is descriptive analysis, path analysis, and sobeltest. The results of this study indicate that managerial ownership, the audit committee and the profitability have positive impact toward the of the company value, institutional ownership has positive impact but not significant, non-executive director with negative effect tendency on the company value. The results of this study also showed that profitability cannot mediate the effect of good corporate governance mechanisms on company value. It can be suggested to replace the intervening variable with other variables such as quality of earnings instead of profitability since it is declined as an intervening variable. non-executive director and institutional ownership does not contribute any positive and significant effect on company value and profitability. The following research can use another proxy in the measurement process and consider other theories that could explain comprehensively.

PENGARUH KELENTUKAN, KEKUATAN OTOT TUNGKAI DAN KOORDINASI MATA-KAKI TERHADAP KETERAMPILAN SEPAKSILA PADA ATLET SEPAKTAKRAW SULAWESI SELATAN

2018 ◽  
Vol 2 (2) ◽  
Author(s):  
SUHARTIWI SUHARTIWI
Keyword(s):  
Path Analysis

Salah satu faktor terpenting dalam pencapaian prestasi maksimal pada atlet sepaktakraw adalah dengan memiliki kondisi fisik yang dapat menunjang keterampilan khususnya keterampilan sepaksila dalam permainan sepaktakraw. Kelentukan yang baik dapat memudahkan atlet dalam meluweskan lipatan salah satu kaki ke atas saat melakukan keterampilan sepaksila, dibutuhkan kekuatan otot tungkai pada saat salah satu kaki yang menjadi tumpuan berat badan dan koordinasi mata kaki sangat dibutuhkan sebelum sesaat melakukan sepakan dalam permainan sepaksila.Jenis penelitian ini ialah penelitian deskriptif dengan menggunakan teknik analisis jalur (Path Analysis). Populasinya adalah atlet sepaktakraw Sulawesi Selatan yang termasuk dalam pembinaan Sulsel Maju II dan PPLP ( Pusat Pendidikan Latihan Pelajar) yang totalnya berjumlah 24 orang. Teknik penentuan sampelnya adalah sampel jenuh. Teknik anaslisa data yang digunakan adalah analisis statistik deskriptif dan analisis jalur dengan bantuan program computer SPSS 16.Hasil penelitian ini menunjukkan bahwa (1) Atlet sepaktakraw Sulawesi Selatan memiliki kelentukan berpengaruh secara langsung terhadap koordinasi mata kaki sebesar 42,90%.(2) Kekuatan otot tungkai berpengaruh langsung terhadap koordinasi mata kaki sebesar 9,61%. (3) Kelentukan berpengaruh secara langsung dan tidak langsung terhadap keterampilan sepaksila pada permainan sepaktakraw sebesar 20,64%. (4) Kekuatan otot tungkai berpengaruh secara langsung dan tidak langsung terhadap keterampilan sepaksila pada permainan sepaktakraw sebesar 12,27%. (5) Koordinasi mata kaki berpengaruh secara langsung terhadap keterampilan sepaksila pada permainan sepaktakraw sebesar 15,44%.Kata Kunci : Kelentukan, Kekuatan otot tungkai, koordinasi mata kaki, keterampilan sepaksila.

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