A System-Level Failure Propagation Detectability Using ANFIS for an Aircraft Electrical Power System
Source abstract
Abstract
The Electrical Power System (EPS) in an aircraft is designed to interact extensively with other systems. With a growing trend towards more electric aircraft, the complexity of interactions between the EPS and other systems has grown. This has resulted in an increased necessity of implementing health monitoring methods like diagnosis and prognosis of the EPS at the systems level. This paper focuses on developing a diagnostic algorithm for the EPS to detect and isolate faults and their root causes that occur at the Line Replaceable Units (LRUs) connecting with aircraft systems like the engine and the fuel system. This paper aims to achieve this in two steps: (i) developing an EPS digital twin and presenting the simulation results for both healthy and fault scenarios, (ii) developing an Adaptive Neuro-Fuzzy Inference System (ANFIS) monitor to detect faults in the EPS. The results from the ANFIS monitor are processed in two methods: (i) a crisp boundary approach, and (ii) a fuzzy boundary approach. The former approach has a poor misclassification rate; hence the latter method is chosen to combine with causal reasoning for isolating root causes of these interacting faults. The results from both these methods are presented through examples in this paper.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Machine Fault Diagnosis Techniques · Fault Detection and Control Systems · Risk and Safety Analysis
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
IVHM Centre, Cranfield University, Cranfield, MK43 0AL, UK
References (33)
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1. Zumberge, J., Wolff, J., McCarthy, K., O’Connell, T., Walters, E., Russell, G., and Lucas, C. (2010). Integrated Aircraft Electrical Power System Modeling and Simulation Analysis. SAE Techn. Paper Ser.10.4271/2010-01-1804 ↗
2. Moving towards a more electric aircraft10.1109/MAES.2007.340500 ↗
3. Air Accidents Investigation Branch (2020, March 01). AAIB Bulletin: 4/2014 9M-MPL EW/C2012/08/04, Available online: https://www.gov.uk/aaib-reports/boeing-747-4h6-9m-mpl-17-august-2012.
4. Air Accidents Investigation Branch (2020, March 01). Aircraft Accident Report No: 4/2009, Available online: https://assets.publishing.service.gov.uk/media/552659a7e5274a141800000d/Summary_AAR_4-2009_Airbus_A319-111__G-EZAC_09-09.pdf.
5. Ezhilarasu, C.M., Skaf, Z., and Jennions, I.K. (2019, January 21–22). Progress towards a Framework for Aerospace Vehicle Reasoning (FAVER). Proceedings of the Annual Conference of the PHM Society, Scottsdale, AZ, USA.10.36001/phmconf.2019.v11i1.887 ↗
6. Sweet, A. (2020, March 05). Testing HyDE on ADAPT, Available online: https://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/20080017209.pdf.
7. Knox, W.B., and Mengshoel, O.J. (2009, January 2–5). Diagnosis and Reconfiguration using Bayesian Networks: An Electrical Power System Case Study. Proceedings of the IJCAI-09 Workshop on Self-\star and Autonomous Systems (SAS): Reasoning and Integration Challenges, Paris, France.
8. Ricks, B.W., and Mengshoel, O.J. (2009). Methods for Probabilistic Fault Iagnosis: An Electrical Power System Case Study. Annual Conference of the Prognostics and Health Management Society, PHM 2009.
9. McIntire, M.G., Keshavarzi, E., Tumer, I.Y., and Hoyle, C. (2016). Functional Models with Inherent Behavior: Towards a Framework for Safety Analysis Early in the Design of Complex Systems. Adv. Aerosp. Technol., 1–8.10.1115/IMECE2016-67040 ↗
10. Diagnosing Faults in Electrical Power Systems of Spacecraft and Aircraft
11. Cao, Y., Liu, G., and Liu, Z. (2009). Condition Based Maintenance for Aircraft Electrical Systems. SAE Tech. Paper Ser.10.4271/2009-01-3163 ↗
12. Prognostic Health Management of Aircraft Power Generators10.1109/TAES.2009.5089535 ↗
13. Faiz, J., Ghorbanian, V., and Joksimovic, G. (2017, January 24–26). Fault Diagnosis of Induction Motors. Proceedings of the 1st Annual International Interdisciplinary Conference, Azores, Portugal.10.1049/PBPO108E ↗
14. Sekar, B.D., and Dong, M.C. (2009, January 15–17). Bayesian fuzzy inference nets online fault diagnosis of induction motor. Proceedings of the 7th International Conference on Information, ICICS 2009-Conference, Communications and Signal Processing, Aizuwakamatsu, Japan.
15. Seok, J., Kolmanovsky, I., and Girard, A. (2016, January 12–14). Integrated/coordinated control of aircraft gas turbine engine and electrical power system: Towards large electrical load handling. Proceedings of the 2016 IEEE 55th Conference on Decision and Control (CDC), Las Vegas, NV, USA.10.1109/CDC.2016.7798747 ↗
16. Modelling and simulation of the logical structure of aircraft power distribution systems
17. Boeing (2020, March 03). THE BOEING 737 TECHNICAL SITE. Available online: http://www.b737.org.uk/electrics.htm.
18. Madonna, V., Member, S., Giangrande, P., and Galea, M. (2018). Electrical Power Generation in Aircraft: Review, Challenges and Opportunities. Res. Gate.10.1109/TTE.2018.2834142 ↗
19. Olivier Tremblay L-AD (2020, February 23). Aircraft Electrical Power Generation and Distribution. Available online: https://www.mathworks.com/help/physmod/sps/examples/aircraft-electrical-power-generation-and-distribution.html.
20. Steve, M. (2020, February 23). Aircraft Power Network in Simscape Electrical. Available online: https://www.mathworks.com/matlabcentral/fileexchange/44124-aircraft-power-network-in-simscape-electrical/.
21. Mushiri, T., and Mbohwa, C. (2015, January 1–3). Research on the use of matlab in the modeling of 3-phase power systems. Proceedings of the World Congress on Engineering, London, UK.
22. MathWorks (2020, February 23). Asynchronous Machine. Available online: https://www.mathworks.com/help/physmod/sps/powersys/ref/asynchronousmachine.html.
23. MathWorks (2020, February 23). Simplified Synchronous Machine. Available online: https://www.mathworks.com/help/physmod/sps/powersys/ref/simplifiedsynchronousmachine.html.
24. MathWorks (2020, February 23). Excitation Systems. Available online: https://www.mathworks.com/help/physmod/sps/powersys/ref/excitationsystem.html.
25. OECO (2020, March 05). Transformer Rectifiers. Available online: https://www.oeco.com/wp-content/uploads/2015/07/transformer-rectifier-units.pdf.
26. Eaton (2020, March 05). Fuel Boost Pump Type 20004 and Canister Type 20005. Available online: https://www.eaton.com/Eaton/ProductsServices/Aerospace/Fuel/FuelBoostPumps/index.htm.
27. Aerodynamix Inc. (2020, March 03). Aircraft Instrument Panel Lighting. Available online: https://aerodynamix.com/aircraft-instrument-panel-lighting/.
28. Valcor Aerospace (2020, March 05). 2-Way Normally Open or Normally Closed Shut-Off Solenoid Valve. Available online: https://www.valcor.com/v4700-2-way-shut-solenoid-valve/.
29. Different Methods of Speed Control of Three-Phase Asynchronous Motor
30. ANFIS: Adaptive-Network-Based Fuzzy Inference System10.1109/21.256541 ↗
31. MathWorks (2020, February 23). Fuzzy Logic Toolbox. Available online: https://www.mathworks.com/help/fuzzy/.
32. Bystrov, D., and Westin, J. (2020, February 10). Neuro-Fuzzy Logic Systems. Available online: https://users.du.se/~jwe/fuzzy/NFL/F10.PDF.
33. The application of reasoning to aerospace Integrated Vehicle Health Management (IVHM): Challenges and opportunities10.1016/j.paerosci.2019.01.001 ↗