Principles of Gas Path Analysis

1. Auflage 2025
ISBN: 978-1-041-09267-4
Verlag: CRC Press

Buch, Englisch, 408 Seiten, Format (B × H): 156 mm x 234 mm

Principles of Gas Path Analysis offers a self-contained reference of the concept and theory of Gas Path Analysis (GPA), as both a diagnostic and prognostic methodology for gas turbine engines. It provides a chronological account of the methodology as it evolved over the past 50 years.

Before expanding into specific GPA concepts, the book begins by covering the basics generic to diagnostics and prognostics and discusses Engine Health Management (EHM) and how GPA can contribute to this strategy. The text further introduces essential parameter corrections important for understanding the foundational principles of GPA. Additionally, advanced topics such as information fusion and ambiguity resolution are explored to highlight potential future advancements in the field. A comprehensive set of appendices provides detailed treatment of the mathematical derivations and statistics behind GPA as well as specialized constructs for relevant methods such as Neural Networks and Fuzzy Logic.

The book is intended for professional engineers engaged in the gas turbine industry and engine health management, including aircraft operators and maintainers. It will also benefit researchers studying gas turbine engine diagnostics and prognostics.

Zielgruppe

Postgraduate and Professional Reference

Autoren/Hrsg.

Volponi, Allan J

Tang, Liang

Fachgebiete

• Technische Wissenschaften Technik Allgemein Technische Instrumentierung
• Technische Wissenschaften Technik Allgemein Mess- und Automatisierungstechnik
• Technische Wissenschaften Sonstige Technologien | Angewandte Technik Signalverarbeitung, Bildverarbeitung, Scanning
• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Signalverarbeitung
• Technische Wissenschaften Technik Allgemein Systems Engineering
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Technische Wissenschaften Maschinenbau | Werkstoffkunde Maschinenbau
• Technische Wissenschaften Verkehrstechnik | Transportgewerbe Luft- und Raumfahrttechnik, Luftverkehr
• Naturwissenschaften Physik Thermodynamik

Inhaltsverzeichnis

1. Engine Health Management. 2. Diagnostics and Prognostics. 3. Parameter Corrections. 4. Gas Path Analysis Fundamentals. 5. Discrete Time Gas Path Analysis. 6. Transient Modeling. 7. Extending Beyond Steady-State Gas Path Analysis. 8. Information Fusion. 9. Ambiguity Resolution. 10. Prognostics and Future Trends. Addendum to Introduction. Chapter 2 Addendums. Chapter 3 Addendums. Chapter 4 Addendums. Chapter 5 Addendums. Chapter 6 Addendums. Chapter 7 Addendums. Chapter 8 Addendums. Chapter 9 Addendums.

Über Autor(innen)

Dr. Allan J Volponi is a retired Senior Fellow from the Controls & Diagnostic Systems organization at Pratt & Whitney in East Hartford, CT. He received his B.S. and M.S. degrees from Pratt Institute (1971-2), and Ph.D. from the Adelphi University (1977), all in mathematics. He spent 40 years with United Technologies, initially with the Hamilton Sundstrand Division as a Senior Principal Engineer in the engine controls group before transferring to P&W in 2000. His interests are in propulsion health management where he has been active in the development of engine performance diagnostic systems. Dr. Volponi has been the recipient of numerous awards including the 1992 Manly Memorial Medal by the SAE, the 2006 Aircraft Engine Technology Award by ASME, the Silver Specialist and Sir Roy Fedden Awards from the Royal Aeronautical Society, and the 2013 Scholar Award from ASME/IGTI. Dr. Volponi has been an active member of the International Gas Turbine Institute (IGTI) and a past Chairman of its Controls, Diagnostics and Instrumentation Committee and is an ASME Fellow. He holds 17 patents, has 2 pending, and he is the author of numerous technical papers on gas turbine diagnostics and prognostics health management.

Dr. Liang Tang is an expert in jet engine health management, controls, and the application of artificial intelligence (AI) and machine learning in aerospace. He currently serves as a Principal Scientist at General Electric Aerospace Research in Niskayuna, NY. In this role, he focuses on AI applications, including engine health monitoring, automated part inspection, and process improvements. Before joining GE, Dr. Tang worked at Pratt & Whitney in East Hartford, CT, from 2012 to 2022. During his tenure, he held several technical leadership roles in the diagnostics, prognostics, and health management group, developing models and GPA analytics for commercial engines across multiple product lines. Earlier in his career, Dr. Tang spent eight years at Impact Technologies, a Sikorsky Company, managing several government-funded research programs as Principal Investigator. Dr. Tang has published over sixty papers and holds multiple patents related to engine health management. He is actively involved in technical committees and standards organizations such as the SAE and the ASME, where he has held several leadership positions, including chairing technical committees over the past decade.