Research Article

Developing an Approach for Fault Detection and Diagnosis of Angular Velocity Sensors

Volume: 02 Number: 01 June 27, 2021
EN

Developing an Approach for Fault Detection and Diagnosis of Angular Velocity Sensors

Abstract

Angular velocity sensor detection and diagnosis become increasingly essential for the improvement of reliability, safety, and efficiency of the control system on aircraft. The classical methods for fault detection and diagnosis are limit or trend checking of some measurable output variables. Due to they do not give a deeper insight and usually do not allow a fault diagnosis, model-based methods of fault detection and diagnosis were developed by using input and output signals and applying dynamic process models. These approaches are based on parameter estimation, parity equations, or state observers. This paper presents an improvement method to build algorithm fault diagnosis for angular velocity sensors on aircraft. Based on proposed method, results of paper can be used in designed intelligent systems that can automatically fault detection on aircraft.

Keywords

References

  1. Xue, W., Guo, Y.Q. and Zhang, X.D., 2007, September. A bank of Kalman filters and a robust Kalman filter applied in fault diagnosis of aircraft engine sensor/actuator. In Second International Conference on Innovative Computing, Informatio and Control (ICICIC 2007) (pp. 10-10). IEEE.
  2. He, Q., Zhang, W., Lu, P. and Liu, J., 2020, Performance comparison of representative model-based fault reconstruction algorithms for aircraft sensor fault detection and diagnosis. Aerospace Science and Technology, 98, p.105649.
  3. Chen, J. and Patton, R.J., 2012, Robust model-based fault diagnosis for dynamic systems (Vol. 3). Springer Science & Business Media. Isermann, R., 2005. Model-based fault-detection and diagnosis–status and applications. Annual Reviews in control, 29(1), pp.71-85.
  4. Lu, P., Van Eykeren, L., Van Kampen, E., De Visser, C.C. and Chu, Q.P., 2016, Adaptive three-step kalman filter for air data sensor fault detection and diagnosis. Journal of Guidance, Control, and Dynamics, 39(3), pp.590-604.
  5. Lu, P., Van Eykeren, L., van Kampen, E.J., de Visser, C. and Chu, Q., 2015, Double-model adaptive fault detection and diagnosis applied to real flight data. Control Engineering Practice, 36, pp.39-57.
  6. Kim, S., Choi, J. and Kim, Y., 2008, Fault detection and diagnosis of aircraft actuators using fuzzy-tuning IMM filter. IEEE Transactions on Aerospace and Electronic Systems, 44(3), pp.940-952.
  7. Xue, W., Guo, Y.Q. and Zhang, X.D., 2007, September. A bank of Kalman filters and a robust Kalman filter applied in fault diagnosis of aircraft engine sensor/actuator. In Second International Conference on Innovative Computing, Information and Control (ICICIC 2007) (pp. 10-10). IEEE.
  8. Baskaya, E., Bronz, M. and Delahaye, D., 2017, September. Fault detection & diagnosis for small UAVs via machine learning. In 2017 IEEE/AIAA 36th Digital Avionics Systems Conference (DASC) (pp. 1-6). IEEE.

Details

Primary Language

English

Subjects

Aerospace Engineering

Journal Section

Research Article

Publication Date

June 27, 2021

Submission Date

March 25, 2021

Acceptance Date

June 8, 2021

Published in Issue

Year 2021 Volume: 02 Number: 01

APA
Tran, H. S., Tran, T. T., Nguyen, D.- dung, Dang Quoc, D., & Nguyen, H. T. (2021). Developing an Approach for Fault Detection and Diagnosis of Angular Velocity Sensors. International Journal of Aviation Science and Technology, 02(01), 15-21. https://doi.org/10.23890/IJAST.vm02is01.0102
AMA
1.Tran HS, Tran TT, Nguyen D dung, Dang Quoc D, Nguyen HT. Developing an Approach for Fault Detection and Diagnosis of Angular Velocity Sensors. IJAST. 2021;02(01):15-21. doi:10.23890/IJAST.vm02is01.0102
Chicago
Tran, Hong Son, Thi Thuy Tran, Dinh-dung Nguyen, Dat Dang Quoc, and Hong Tien Nguyen. 2021. “Developing an Approach for Fault Detection and Diagnosis of Angular Velocity Sensors”. International Journal of Aviation Science and Technology 02 (01): 15-21. https://doi.org/10.23890/IJAST.vm02is01.0102.
EndNote
Tran HS, Tran TT, Nguyen D- dung, Dang Quoc D, Nguyen HT (June 1, 2021) Developing an Approach for Fault Detection and Diagnosis of Angular Velocity Sensors. International Journal of Aviation Science and Technology 02 01 15–21.
IEEE
[1]H. S. Tran, T. T. Tran, D.- dung Nguyen, D. Dang Quoc, and H. T. Nguyen, “Developing an Approach for Fault Detection and Diagnosis of Angular Velocity Sensors”, IJAST, vol. 02, no. 01, pp. 15–21, June 2021, doi: 10.23890/IJAST.vm02is01.0102.
ISNAD
Tran, Hong Son - Tran, Thi Thuy - Nguyen, Dinh-dung - Dang Quoc, Dat - Nguyen, Hong Tien. “Developing an Approach for Fault Detection and Diagnosis of Angular Velocity Sensors”. International Journal of Aviation Science and Technology 02/01 (June 1, 2021): 15-21. https://doi.org/10.23890/IJAST.vm02is01.0102.
JAMA
1.Tran HS, Tran TT, Nguyen D- dung, Dang Quoc D, Nguyen HT. Developing an Approach for Fault Detection and Diagnosis of Angular Velocity Sensors. IJAST. 2021;02:15–21.
MLA
Tran, Hong Son, et al. “Developing an Approach for Fault Detection and Diagnosis of Angular Velocity Sensors”. International Journal of Aviation Science and Technology, vol. 02, no. 01, June 2021, pp. 15-21, doi:10.23890/IJAST.vm02is01.0102.
Vancouver
1.Hong Son Tran, Thi Thuy Tran, Dinh-dung Nguyen, Dat Dang Quoc, Hong Tien Nguyen. Developing an Approach for Fault Detection and Diagnosis of Angular Velocity Sensors. IJAST. 2021 Jun. 1;02(01):15-21. doi:10.23890/IJAST.vm02is01.0102

Please find the article preperation and structure guides in author guidelines section.
Please do not hasitate to contact with us in here.