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A Method to Predict Compressor Stall in the TF34-100 Turbofan Engine Utilizing Real-Time Performance Data Shuxiang A

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A Method to Predict Compressor Stall in the TF34-100 Turbofan Engine Utilizing Real-Time Performance Data Shuxiang A Air Force Institute of Technology AFIT Scholar Theses and Dissertations Student Graduate Works 6-18-2015 A Method to Predict Compressor Stall in the TF34-100 Turbofan Engine Utilizing Real-Time Performance Data Shuxiang A. Li Trevor G. Jones Follow this and additional works at: https://scholar.afit.edu/etd Part of the Operations Research, Systems Engineering and Industrial Engineering Commons Recommended Citation Li, Shuxiang A. and Jones, Trevor G., "A Method to Predict Compressor Stall in the TF34-100 Turbofan Engine Utilizing Real-Time Performance Data" (2015). Theses and Dissertations. 197. https://scholar.afit.edu/etd/197 This Thesis is brought to you for free and open access by the Student Graduate Works at AFIT Scholar. It has been accepted for inclusion in Theses and Dissertations by an authorized administrator of AFIT Scholar. For more information, please contact [email protected]. A METHOD TO PREDICT COMPRESSOR STALL IN THE TF34-100 TURBOFAN ENGINE UTILIZING REAL-TIME PERFORMANCE DATA THESIS June 2015 Shuxiang ‘Albert’ Li, Civ, USAF G Trevor Jones, Civ, USAF AFIT-ENV-MS-15-J-036 DEPARTMENT OF THE AIR FORCE AIR UNIVERSITY AIR FORCE INSTITUTE OF TECHNOLOGY Wright-Patterson Air Force Base, Ohio DISTRIBUTION STATEMENT A. APPROVED FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED. AFIT-ENV-MS-15-J-036 The views expressed in this thesis are those of the author and do not reflect the official policy or position of the United States Air Force, Department of Defense, or the United States Government. This material is declared a work of the U.S. Government and is not subject to copyright protection in the United States. AFIT-ENV-MS-15-J-036 A METHOD TO PREDICT COMPRESSOR STALL IN THE TF34-100 TURBOFAN ENGINE UTILIZING REAL-TIME PERFORMANCE DATA THESIS Presented to the Faculty Department of Systems Engineering and Management Graduate School of Engineering and Management Air Force Institute of Technology Air University Air Education and Training Command In Partial Fulfillment of the Requirements for the Degree of Master of Science in Systems Engineering Shuxiang ‘Albert’ Li, BS Civilian, USAF G. Trevor Jones, BS, MBA Civilian, USAF June 2015 DISTRIBUTION STATEMENT A. APPROVED FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED. AFIT-ENV-MS-15-J-036 A METHOD TO PREDICT COMPRESSOR STALL IN THE TF34-100 TURBOFAN ENGINE UTILIZING REAL-TIME PERFORMANCE DATA Shuxiang ‘Albert’ Li, BS Civilian, USAF G. Trevor Jones, BS, MBA Civilian, USAF Committee Membership: Maj. Jason Freels, PhD Chair Dr. David Jacques Member Maj. Vhance Valencia, PhD Member AFIT-ENV-MS-15-J-036 ABSTRACT Air Force current operations continue to undergo significant changes compelled by decreasing fiscal appropriations, aging aircraft, and personnel drawdown. The Air Force must effectively improve current maintenance operations in part to deal with these challenges. This study will explore the area of the A-10 aircraft fleet’s TF34-100 high- pass turbo–fan engine sensor data to seek its deterioration modelling and prognostics capability. In futurity this will allow for achievement of greater confidence in predicting the compressor stall which leads to engine performance deterioration and a costly repair in maintenance. By utilizing an innovative method to forecast the probability of compressor stall, according to individual engine sensor data which has recently become available, it will be possible to achieve significant benefits in both maintenance planning and mission scheduling (which will greatly reduce the associated costs of maintenance servicing). iv Acknowledgments We would like to express our sincere appreciation to our faculty advisor, Major Jason Freels, for his guidance and support throughout the course of this thesis effort. The insight and experience are certainly appreciated. We would, also, like to thank Mr. Jeff Hanson of Air Force Engineering and Technical Services (AFETS), Mr. Robert Bowels and Mr. Kenneth Hurst of Southwest Research Institute (SwRI) for their insight and tutorial assistance in developing this research. Shuxiang ‘Albert’ Li G. Trevor Jones . v TABLE OF CONTENTS Page Abstract .............................................................................................................................. iv Table of Contents ............................................................................................................... vi List of Figures .................................................................................................................. viii I. Introduction .....................................................................................................................1 General Issue ................................................................................................................1 Problem Statement........................................................................................................3 Investigative Questions ................................................................................................9 Methodology.................................................................................................................9 Assumptions/Limitations ............................................................................................12 Implications ................................................................................................................12 Preview .......................................................................................................................13 II. Research and Development Process ..............................................................................14 Overview ....................................................................................................................14 Processing the RTED Data .........................................................................................15 Check the ACF and PACF of VG Data ......................................................................23 Performance Summary for arima(p,0,q) over Various Combined Flights Data.........35 Model Adequacy Check for arima(20,0,6) Model .....................................................42 Model Adequacy Check for Probability Model of Compressor Stall Fault Event .....50 Relevant Research – Application of Weight Filter for Times Series Data .................59 III. Methodology ...............................................................................................................69 Overview ....................................................................................................................69 Test Subjects ...............................................................................................................69 vi Summary.....................................................................................................................71 IV. Analysis and Results ....................................................................................................72 Results of arima(p,0,q) Model ....................................................................................72 Results of Linear Regression Model (LRM) ..............................................................73 Investigative Questions Answered .............................................................................78 V. Conclusions and Recommendations ............................................................................79 Conclusions of Research ............................................................................................79 Significance of Research ............................................................................................79 Recommendations for Future Actions ........................................................................79 Recommendations for Future Research......................................................................79 Summary.....................................................................................................................80 Bibliography ......................................................................................................................81 Appendix ............................................................................................................................82 Appendix A. The formula to calculate Variable Geometry (VG)Error! Bookmark not defined. Vita ....................................................................................................................................83 vii LIST OF FIGURES Page Figure 1: Locations illustrated for three interested sensors (T2C, NG and IGV). .............. 5 Figure 2: Physical location of the engine sensor Compressor Inlet Temperature (T2C). ... 6 Figure 3: Physical location of engine sensor PLA. ............................................................. 7 Figure 4: Physical location of the engine sensor IGV. ....................................................... 7 Figure 5: Physical location of the engine sensor PT5 and PS3........................................... 8 Figure 6: Physical location of the engine sensor for Front Frame Accelerometer. ............ 8 Figure 7: Screenshot of ASIST opening RTED data file. ................................................. 15 Figure 8: Sample the RTED data files from all available flight data - Nellis hard disk and JRAMS website. ......................................................................................................... 16 Figure 9: Percentage of “good” data points over number of combined flights. ..............
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