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The purpose of the article is developing the locomotive structure of intellectual system of support of decision-making and to find a criterion by which to adequately assess different control action to the train. System of decision support for locomotive crew is seen as a complex structure with complex interactions located at a great distance, on-board locomotive systems. The quality of the organization determines the effectiveness of the system as a whole. To solve the problem of creating the optimal structure of the DSS applies the aggregate-decomposition method that involves two steps: decomposition of the problem into a number of subproblems and aggregating the partial results. To evaluate the quality control of a locomotive used the concept of control strategy with specific indicators. Design is developed and structure of locomotive DSS is obtained, taking into account peculiarities of operation of railway transport. To account for not only quantitative but also qualitative characteristics of activity of the locomotive or intellectual systems of decision support, it is proposed to use methods of fuzzy logic. So were able to deduce and calculate the additive criterion of the quality control activities of the intelligent system. Formal indicator of the quality of the train control process using different strategies is received. In the work theoretically grounded definition of the weighting factors for each partial criterion of the quality of train control. Using the dependencies derived, the nature of the influence of the value of partial criteria on the quality of train control in relation to a strategy. The results of the work allow to more accurately simulate the operations of a locomotive crew, which in the future will serve as the basis for the development of autonomous intelligent systems of locomotive control. The developed method is shown to be three main criteria which values the safety, energy consumption, and execution time schedule. However, for more flexible and accurate model, this approach allows to enter additional criteria, and the simplicity of the calculation provides the necessary speed when implemented on on-board locomotive computers.
Czasopismo
Rocznik
Tom
Strony
47--58
Opis fizyczny
Bibliogr. 24 poz., rys., tab., wykr.
Twórcy
autor
- Department of Traction Rolling Stock of Railways, State University of Infrastructure and Technologies, Kyiv, Ukraine
autor
- Department of Traction Rolling Stock of Railways, State University of Infrastructure and Technologies, Kyiv, Ukraine
Bibliografia
- [1] ANDRONCHEV, I. K., ASABIN, V. V., KOSSOV, E. E., GORDEEV, I. P., TSELIKOVSKAIA, V. S., PLOKHOV, E. M., 2020. The energy performance efficiency of locomotives. Russian Electrical Engineering, 91(3), 175-178. DOI: 10.3103/S106837122003 0049.
- [2] ARUN, N. K., and MOHAN, B. M., 2017. Modeling, stability analysis, and computational aspects of some simplest nonlinear fuzzy two-term controllers derived via center of area/gravity defuzzification. ISA transactions, 70, 16-29.
- [3] ASABIN, V. V., KURMANOVA, L. S., PETUKHOV, S. A., PLOKHOV, E. M., LETYAGIN, P. V., 2020. A Method for Determining the Energy Efficiency of Self-Contained Locomotives with Electric Power Transmission. Russian Electrical Engineering, 91(3), 179-182.
- [4] BAKLANOV, A., 2005. The energy balance of the movement to address the problem of reducing energy consumption for traction. Transport: science, technology, control/VINITI, 6, 32-35.
- [5] BUTKO, T., BABANIN, A., GOROBCHENKO, A., 2015. Rationale for the type of the membership function of fuzzy parameters of locomotive intelligent control systems. Eastern-European Journal of Enterprise Technologies, 1(3), 4-8. DOI: 10.15587/1729-4061.2015. 35996.
- [6] EGAMBERDIEV, B., LEE, K., LEE, J., BURNASHEV, S., 2016. A Study on Life Cycle Cost on Railway Locomotive Systems. International Journal of Railway, 9(1), 10-14.
- [7] GOROBCHENKO, O., FOMIN, O., GRITSUK, I., SARAVAS, V., GRYTSUK, Y., BULGAKOV, M., ZINCHENKO, D., 2018. Intelligent locomotive decision support system structure development and operation quality assessment. Paper presented at the 2018 IEEE 3rd International Conference on Intelligent Energy and Power Systems, IEPS 2018 - Proceedings, 2018-January, 239-243. DOI: 10.1109 /IEPS.2018.8559487.
- [8] KUKULSKI, J., GOŁĘBIOWSKI, P., PYZA, D., JACHIMOWSKI, R., WYCHOWAŃSKI, W., 2019. Selected aspects of the selection of data sent to the vehicle in automatic rail vehicle driving systems. Zeszyty Naukowe. Transport-Politechnika Śląska, 103, 43-52. DOI: 10.20858/ sjsutst.2019.103.4.
- [9] KULBOVSKYI, I., SAPRONOVA, S., HOLUB, H., TKACHENKO, V., AFANASIEVA, I., SAFRONOV, O., 2019. Development of a model for managing the quality of repair and maintenance of rolling stock in transport infrastructure projects. In Transport Means - Proceedings of the International Conference, 2019-October, 201-205.
- [10] KURIC, I., GOROBCHENKO, O., LITIKOVA, O., GRITSUK, I., MATEICHYK, V., BULGAKOV, M., KLACKOVA, I., 2020. Research of vehicle control informative functioning capacity. OP Conference Series: Materials Science and Engineering, 24th Slovak-Polish International Scientific Conference on Machine Modelling and Simulations - MMS 2019, 3-6 September 2019, 776, 012036.
- [11] LI, G., LIU, Y., HUANG, J., LIU, Y., 2019. Study on train energy-efficient automatic driving from learning human driver patterns. Hunan Daxue Xuebao/Journal of Hunan University Natural Sciences, 46(4), 128-140. DOI: 10.16339/j.cnki.hdxbzkb.2019.04.019.
- [12] MANAFOV, E., 2020. The use of a fuzzy expert system to increase the reliability of diagnostics of axle boxes of rolling stocks. Scientific Journal of Silesian University of Technology. Series Transport, 107, 95-106. DOI: 10.20858/sjsutst.2020.107.7.
- [13] MARCUS S., 2013. Automating knowledge acquisition for expert systems. Springer Science and Business Media.
- [14] NOWAKOWSKI, W., BOJARCZAK, P., ŁUKASIK, Z., 2019. Safety assessment using event tree analysis for railway traffic control systems. Paper presented at the Transport Means - Proceedings of the International Conference, 2019-October, 1387-1391.
- [15] PEDRYCZ, W., 2018. Granular computing: analysis and design of intelligent systems. CRC press.
- [16] RUSSELL, S., NORVIG, P., 2002. Artificial intelligence: a modern approach. Pearson International Content.
- [17] SAPRONOVA, S., TKACHENKO, V., FOMIN, O., HATCHENKO, V., MALIUK, S., 2017. Research on the safety factor against derailment of railway vehicles. Eastern-European Journal of Enterprise Technologies, 6 (7(90)), 19-25. DOI: https://doi.org/10.15587/ 1729-4061.2017.116194.
- [18] SHTOVBA, S. D., 2001. Introduction to the theory of fuzzy sets and fuzzy logic. Ukraine, Vinnitsa, UNIVERSUM-Vinnitsa.
- [19] SOOFASTAEI, A., 2019. Energy-Efficiency Improvement in Mine-Railway Operation Using AI. Journal of Energy and Power Engineering, 13, 333-348.
- [20] SZKODA, M., KACZOR, G., 2016. Reliability and availability assessment of diesel locomotive using fault tree analysis. Archives of Transport, 40, 65-75. DOI: 10.5604/ 08669546.1225470.
- [21] SZKODA, M., SATORA, M., KONIECZEK, Z., 2020. Effectiveness assessment of diesel locomotives operation with the use of mobile maintenance points. Archives of Transport, 54(2), 7-19. DOI: 10.5604/01.3001. 0014.2622.
- [22] TARASOV, V., GERASIMOV, B., LEVIN, I., KORNIYCHUK, V., 2007. Intelligent Decision Support Systems: Theory, Synthesis, Efficiency. Kyiv: International Academy of Computer Science and Systems.
- [23] TARTAKOVSKYI E., GOROBCHENKO O., ANTONOVYCH A., 2016. Improving the process of driving a locomotive through the use of decision support systems. Eastern-European Journal of Enterprise Technologies, 3(83), 4-11.
- [24] TSVIRKUN, A. D., 1982. Fundamentals of structure synthesis of complex systems. Moskow: Nauka.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-10c8614d-767c-439d-8b13-b44c188dea9b