Share:


Efficiency of operational data processing for radio electronic equipment

    Oleksandr Solomentsev   Affiliation
    ; Maksym Zaliskyi   Affiliation
    ; Tetyana Herasymenko Affiliation
    ; Olena Kozhokhina   Affiliation
    ; Yuliia Petrova   Affiliation

Abstract

The paper deals with the statistical data processing algorithms in operation system of radio electronic equipment. The main purpose is analysis of data processing algorithm efficiency according to the analytical calculations and simulation results. During radio electronic equipment operation failures are possible. These failures affect on the equipment’s technical condition that can deteriorate. In case of condition-based maintenance, it is necessary to detect the time moment of deterioration beginning. Therefore, in this paper the deterioration detection algorithm was developed according to Neyman-Pearson criterion with a fixed sample size. The initial data are times between failures of radio electronic equipment, and these data can be identified by the exponential probability density function. The step-function model was chosen for failure rate change description. To estimate efficiency the operating characteristic was calculated. The simulation based on Monte-Carlo method confirmed the correctness of theoretical calculations.


First published online 22 January 2020

Keyword : efficiency, statistical data processing, operation system, radio electronic equipment, changepoint, detection

How to Cite
Solomentsev, O., Zaliskyi, M., Herasymenko, T., Kozhokhina, O., & Petrova, Y. (2019). Efficiency of operational data processing for radio electronic equipment. Aviation, 23(3), 71-77. https://doi.org/10.3846/aviation.2019.11849
Published in Issue
Dec 31, 2019
Abstract Views
1316
PDF Downloads
575
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Barlow, R. E., & Proschan, F. (1965). Mathematical theory of reliability (256 p.). New York: John Wiley and Sons.

Dhillon, B. S. (2006). Maintainability, maintenance, and reliability for engineers. New York: Taylor & Francis Group. https://doi.org/10.1201/9781420006780

Galar, D., Sandborn, P., & Kumar, U. (2017). Maintenance costs and life cycle cost analysis (492 p.). Boca Raton: CRC Press. https://doi.org/10.1201/9781315154183

Gertsbakh, I. (2005). Reliability theory: with applications to preventive maintenance (219 p.). New York: Springer. https://doi.org/10.1007/978-3-662-04236-6

Goncharenko, A. (2017). Aircraft operation depending upon the uncertainty of maintenance alternatives. Aviation, 21(4), 126–131. https://doi.org/10.3846/16487788.2017.1415227

Goncharenko, A. V. (2018, 20–24 February). Multi-optional hybrid effectiveness functions optimality doctrine for maintenance purposes. In 14th International Conference on Advanced Trends in Radioelecrtronics, Telecommunications and Computer Engineering (TCSET) Proceedings (pp. 771–775). Lviv-Slavske, Ukraine. https://doi.org/10.1109/TCSET.2018.8336313

Hryshchenko, Y. V. (2016, 18–20 October). Reliability problem of ergatic control systems in aviation. In IEEE 4th International Conference on Methods and Systems of Navigation and Motion Control (MSNMC) Proceedings (pp. 126–129). Kyiv, Ukraine. https://doi.org/10.1109/MSNMC.2016.7783123

Jones, M. T. (2009). Artificial intelligence: a systems approach (498 p.). Hingham: Jones & Bartlett Learning.

Kuzmenko, N. S., Ostroumov, I. V., & Marais, K. (2018, 16–18 October). An accuracy and availability estimation of aircraft positioning by navigational aids. In IEEE International Conference on Methods and Systems of Navigation and Motion Control (MSNMC) Proceedings (pp. 36–40). Kyiv, Ukraine. https://doi.org/10.1109/MSNMC.2018.8576276

Levin, B. R. (1978). Theory of reliability of radio engineering systems (274 p.). Moscow: Radio (in Russian).

Mironov, A., Doronkin, P., Priklonsky, A., & Kabashkin, I. (2016). Structural health monitoring of rotating blades on helicopters. Aviation, 20(3), 110–122. https://doi.org/10.3846/16487788.2016.1227554

Rausand, M. (2004). System reliability theory: models, statistical methods and applications (458 p.). New York: John Wiley & Sons, Inc.

Silkov, V., & Delas, M. (2015). Approximate assessment of the operational performances of an unmanned aerial vehicle according to its flight data. Aviation, 19(4), 187–193. https://doi.org/10.3846/16487788.2015.1136024

Smith, D. J. (2005). Reliability, maintainability and risk. Practical methods for engineers (365 p.). London: Elsevier.

Solomentsev, O., Zaliskyi, M., & Zuiev, O. (2013, 5–7 June). Radioelectronic equipment availability factor models. In Signal Processing Symposium 2013 (SPS 2013) Proceedings (pp. 1–4). Jachranka Village, Poland. https://doi.org/10.1109/SPS.2013.6623616

Solomentsev, O. V., Melkumyan, V. H., Zaliskyi, M. Yu., & Asanov, M. M. (2015, 13–15 October). UAV operation system designing. IEEE 3rd International Conference on Actual Problems of Unmanned Air Vehicles Developments (APUAVD) Proceedings (pp. 95–98). Kyiv, Ukraine. https://doi.org/10.1109/APUAVD.2015.7346570

Solomentsev, O., Zaliskyi, M., & Zuiev, O. (2016). Estimation of quality parameters in the radio flight support operational system. Aviation, 20(3), 123–128. https://doi.org/10.3846/16487788.2016.1227541

Solomentsev, O., Zaliskyi, M., Kozhokhina, O., & Herasymenko, T. (2017, 12–14 September). Reliability parameters estimation for radioelectronic equipment in case of change-point. In Signal Processing Symposium 2017 (SPSympo 2017) Proceedings (pp. 1–4). Jachranka Village, Poland. https://doi.org/10.1109/SPS.2017.8053676

Taranenko, A. G., Gabrousenko, Ye. I., Holubnychyi, A. G., & Slipukhina, I. A. (2018, 16–18 October). Estimation of redundant radionavigation system reliability. IEEE 5th International Conference on Methods and Systems of Navigation and Motion Control (MSNMC) Proceedings (pp. 28–31). Kyiv, Ukraine. https://doi.org/10.1109/MSNMC.2018.8576282

Tartakovsky, A., Nikiforov, I., & Basseville, M. (2015). Sequential analysis. Hypothesis testing and changepoint detection (580 p.). New York: Taylor & Francis Group. https://doi.org/10.1201/b17279

Wang, W., Zhou, Y., Li, C., Wang, H., & Zhang, Y. (2018). Dynamic reliability analysis of a cantilever beam during a deterioration process. Mechanics Based Design of Structures and Machines, 47(1). https://doi.org/10.1080/15397734.2018.1525992

Zaliskyi, M., & Solomentsev, O. (2014, 14–17 October). Method of sequential estimation of statistical distribution parameters. In IEEE 3rd International Conference Methods and Systems of Navigation and Motion Control (MSNMC) Proceedings (pp. 135–138). Kyiv, Ukraine. https://doi.org/10.1109/MSNMC.2014.6979752

Zhyhlyavskyi, А. А., & Kraskovskyi, A. E. (1988). Changepoint detection of random processes in problems of radio engineering (224 p.). St. Petersburg: LU Publishing (in Russian).