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Remote operation and monitoring of a micro aero gas turbine

Part of: ISABE 2017

Published online by Cambridge University Press:  21 June 2017

M. Diakostefanis*
Affiliation:
Cranfield University, SATM, Propulsion Enginnering Centre, Cranfield, United Kingdom
T. Nikolaidis
Affiliation:
Cranfield University, SATM, Propulsion Enginnering Centre, Cranfield, United Kingdom
S. Sampath
Affiliation:
Cranfield University, SATM, Propulsion Enginnering Centre, Cranfield, United Kingdom
T. Triantafyllou
Affiliation:
Cranfield University, SATM, Propulsion Enginnering Centre, Cranfield, United Kingdom

Abstract

Internet applications have been extended to various aspects of everyday life and offer services of high reliability and security at relatively low cost. This project presents the design of a reliable, safe and secure software system for real-time remote operation and monitoring of an aero gas turbine with utilisation of existing internet technology, whilst the gas turbine is installed in a remote test facility

This project introduces a capability that allows remote and flexible operation of an aero gas turbine throughout the whole operational envelope, as required by the user at low cost, by exploiting the available Internet technology. Remote operation of the gas turbine can be combined with other remote Internet applications to provide very powerful gas-turbine performance-simulation experimental platforms and real-time performance monitoring tools, whilst keeping the implementation cost at low levels.

The gas turbine used in this experiment is an AMT Netherlands Olympus micro gas turbine and a spiral model approach was applied for the software. The whole process was driven by risk mitigation.

The outcome is a fully functional software application that enables remote operation of the micro gas turbine whilst constantly monitors the performance of the engine according to basic gas turbine control theory. The application is very flexible, as it runs with no local installation requirements and includes provisions for expansion and collaboration with other online performance simulation and diagnostic tools.

Type
Research Article
Copyright
Copyright © Royal Aeronautical Society 2017 

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Footnotes

This paper will be presented at the ISABE 2017 Conference, 3-8 September 2017, Manchester, UK.

References

REFERENCES

1. Lufthansa Technik. manage/m Technical Operations Suite, 2016. Available at: www.manage-m.com/managem_page_about.Google Scholar
2. Siemens The Benchmark in Controls – Technical Highlights Siemens Power Plant Automation™ – SPPA-T3000, 2016. Available at: www.energy.siemens.com/hq/pool/hq/automation/automation-control-pg/sppa-t3000/T3-B-ContrSys-us-V11.pdf.Google Scholar
3. Ko, C.C., Chen, B.M., Jianping, C., Zhuang, Y. and Chen, T. K. Development of a web-based laboratory for control experiments on a coupled tank apparatus, IEEE Transactions on Education, 2001, 44, (1), pp 7686.CrossRefGoogle Scholar
4. Okajima, H.S.S., Ledel, L.C. Fragnito, H.L. and Rocha, H.V. WebLab development using a Java and Labview integrated solution for Kyatera network, 3rd TIDIA Fapesp Workshop, 15–17 November 2006, Sao Paolo, Brasil, pp 204.Google Scholar
5. Apostolidis, A., Sampath, S., Laskaridis, P. and Singh, R. WebEngine - A web-based gas turbine performance simulation tool, Proceedings of ASME Turbo Expo 2013 GT2013, Vol. 4, June 3–7, 2013, ASME, New York, New York, US, pp. V004T08A007.Google Scholar
6. AMT Netherlands. Olympus AMT Netherlands gas turbine, 2014. Available at: http://www.amtjets.com/index.php.Google Scholar
7. AMT Netherlands, Olympus Manual, Geldrop, 2001, Netherlands.Google Scholar
8. Sommerville, I. Software Engineering, 8th ed., 2006, Pearson Education, GB.Google Scholar
9. Boehm, B.W. A spiral model of software development and enhancement, Computer, 1988, 21, (5), pp 6172.CrossRefGoogle Scholar
10. Gallina, B. and Guelfi, N. A template for requirement elicitation of dependable product lines, Sawyer, P., Paech, B. and Heymans, P. (Eds.) Requirements Engineering: Foundation for Software Quality, 2007, Springer, Berlin, Germany, pp 6377.Google Scholar
11. Broy, M. Seamless model driven systems engineering based on formal models. In Proceedings of the 11th International Conference on Formal Engineering Methods: Formal Methods and Software Engineering (ICFEM '09), Breitman, K. and Cavalcanti, A. (Eds.). 2009. Springer-Verlag, Berlin, Heidelberg, pp 1–19. doi:http://dx.doi.org/10.1007/978-3-642-10373-5_1.Google Scholar
12. Hayhurst, K.J., Veerhusen, D.S., Chilenski, J.J. and Rierson, L.K. NASA/TM-2001-210 - A Practical Tutorial on Modified Condition/Decision Coverage, 2001, NASA, Hampton, Virginia, US.Google Scholar
13. Hilderman, V. and Baghi, T. Avionics certification: a complete guide to DO-178 (software), DO-254 (hardware), 2007, Avionics Communications, Leesburg, Virginia, US.Google Scholar
14. Ameur, Y.A., Boniol, F. and Wiels, V. Toward a wider use of formal methods for aerospace systems design and verification, Int J Software Tools for Technology Transfer, 2010, 12, (1), pp 17.Google Scholar
15. Berard, B., Bidoit, M., Finkel, A., Laroussinie, F., Petit, A., Petrucci, L. and Schnoebelen, P. Systems and Software Verification: Model-Checking Techniques and Tools, 1st ed, 2010, Springer Publishing Company, Incorporated, New York, US.Google Scholar
16. Li, W. Risk Assessment of Power Systems: Models, Methods, and Applications, 2005, Wiley, Hoboken, New Jersey, US.Google Scholar
17. Gokhale, S. S. and Trivedi, K.S. Reliability prediction and sensitivity analysis based on software architecture, Software Reliability Engineering, 2002. ISSRE 2003. Proceedings. 13th International Symposium on, 2002, pp 64.Google Scholar
18. Clarke, P.J., Power, J.F., Babich, D. and King, T.M., A testing strategy for abstract classes, Software Testing, Verification and Reliability, 2012, 22, (3), pp 147169.Google Scholar
19. British Standards Institution, (2007), BS EN 61025:2007 - Fault Tree Analysis (FTA), British Standards Online. Available at: https://bsol.bsigroup.com/Bibliographic/BibliographicInfoData/000000000030101041. Accessed May 2017.Google Scholar
20. British Standards Institution, (2001), BS IEC 61882:2001 - Hazard and operability studies (HAZOP studies). Application guide, British Standards Online. Available at: https://bsol.bsigroup.com/Bibliographic/BibliographicInfoData/000000000030031511. Accessed May 2017.Google Scholar
21. Fullwood, R. Probabilistic Safety Assessment in the Chemical and Nuclear Industries, 1999, Butterworth-Heinemann, UK.Google Scholar
22. Hignett, K.C. Practical Safety and Reliability Assessment, 1996, E & FN Spon, London.Google Scholar
23. Stamatelatos, M. Fault Tree Handbook with Aerospace Applications, 2002, NASA, Washington DC, US. http://www.hq.nasa.gov/office/codeq/doctree/fthb.pdf ed.Google Scholar
24. British Standards Institution, (2006), BS EN 60812:2006 - Analysis techniques for system reliability. Procedure for failure mode and effects analysis (FMEA), British Standards Online. Available at: https://bsol.bsigroup.com/Bibliographic/BibliographicInfoData/000000000030101028. Accessed May 2017.Google Scholar
25. Jaw, L.C. and Mattingly, J.D. Aircraft engine controls: design, system analysis, and health monitoring, 2009, American Institute of Aeronautics and Astronautics, Reston, US.Google Scholar
26. The Apache Software Foundation. mod_proxy - Apache HTTP Server, 2016. Available at: http://httpd.apache.org/docs/2.2/mod/mod_proxy.html.Google Scholar
27. Heffelfinger, D. Java EE 6 Development with NetBeans 7, 2011, Packt Publishing, Great Britain.Google Scholar
28. Trivedi, K.S. Probability and Statistics with Reliability, Queuing, and Computer Science Applications, 1982, Prentice-Hall, Englewood Cliffs, New Jersey, US.Google Scholar