Modern Trends in Approaches to Modelling Technical State of Jet Engines

In presented work, the main approaches of engine technical state assessment are presented with their benefits and limitations. To negotiate constraints of these methods, they should be applied together. However, it is shown, that these methods do not cover present demands of operators and additional methods have to be implemented. Two high-potential methods were observed: model-based diagnostic and AI-based diagnostic. First method is based on thermodynamic model of engine while second one is data-driven approach. Recent works in theses sphere of knowledge have been reviewed and measurement parameters, used for model development, were listed and counted. N2 and N1 speeds, HPC exit pressure and temperature are the most frequently used parameters and they should be considered as main parameters for future research.

• Record URL:
  https://doi.org/10.1007/978-3-030-96196-1
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9783030961954
• Supplemental Notes:
  • © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.
• Corporate Authors:

  Springer International Publishing

  ,    
• Authors:
  • Zhdanov, Vladislav
  • Grakovski, Alexander
• Conference:
  • 21st International Multi-Conference Reliability and Statistics in Transportation and Communication (RelStat 2021)
  • Location: Riga , Latvia
  • Date: 2021-10-14 to 2021-10-15
• Publication Date: 2022-2

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 125-134
• Monograph Title: Reliability and Statistics in Transportation and Communication: Selected Papers from the 21st International Multidisciplinary Conference on Reliability and Statistics in Transportation and Communication, RelStat2021, 14-15 October 2021, Riga, Latvia
• Serial:
  • Lecture Notes in Networks and Systems
  • Volume: 410
  • Publisher: Springer Cham
  • ISSN: 2367-3370
  • Serial URL: https://www.springer.com/series/15179

Subject/Index Terms

• TRT Terms: Condition surveys; Decision support systems; Jet engines; Predictive models; Thermodynamics; Vehicle maintenance
• Subject Areas: Aviation; Maintenance and Preservation; Planning and Forecasting; Vehicles and Equipment;

Filing Info

• Accession Number: 01890795
• Record Type: Publication
• ISBN: 9783030961954
• Files: TRIS
• Created Date: Aug 23 2023 3:24PM