Control of the Railroad Bed by the Degree of Reliability of Operational State and the Degree of Hazard of Non-operational State
DOI:
https://doi.org/10.47839/ijc.24.2.4009Keywords:
railroad bed, vibration noisy signal, useful signal, noise, reliability degree, hazard degree, operational state, non-operational stateAbstract
The railroad bed is subject to various destructive processes. Therefore, constant monitoring and control of the technical condition of railroad tracks is required. The existing literature examines a method, according to which special equipment is installed in one of the cars of the rolling stock, and an intelligent system is created to identify the railroad track sections that require extraordinary control. In this system, using a controller, the characteristics of the noise of the noisy vibration signal resulting from ground vibration are calculated, which are used as diagnostic informative attributes of the occurrence of malfunction on the railroad track in the initial latent period of inception, and a knowledge base of the technical condition is created. As a result of the analysis, a decision is made on the necessity or omission of off-schedule inspection of railroad tracks. In this paper, we propose to include new and more important diagnostic attributes into this knowledge base, which are estimates of the degree of reliability of operational and the degree of hazard of non-operational states of the railroad bed. To calculate these attributes, algorithms are proposed for calculating the probability of the useful component and the noise falling within given bounding intervals. Taking into account that the algorithms are rather complicated, the calculation of characteristics should be performed in the control center, where the noisy vibration signal is transmitted. As a result, a new final improved knowledge base is formed. The application of the proposed algorithms increases the reliability and adequacy of the control of the railroad bed.
References
M. Zhang, “Decision support approach for integrated maintenance program of urban rail transit,” International Journal of Computing, vol. 16, issue 3, pp. 143-151, 2017. https://doi.org/10.47839/ijc.16.3.897.
C. Bantin, J. Siu, “Designing a secure data communications system for automatic train control,” Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, vol. 225, no 4, pp. 395-402, 2011. https://doi.org/10.1243/09544097JRRT390.
Zujun Yu, Hongwei Wang and Feng Chen, “Security of railway control systems: A survey, research issues and challenges,” High-speed Railway, vol. 1, issue 1, pp. 6-17, 2023. https://doi.org/10.1016/j.hspr.2022.12.001.
A. L. Manakov, A. D. Abramov, A. S. Ilinykh, S. A. Bekher, A. A. Igumnov, S. A. Kolarz, “The stabilization control of the railroad track,” Transportation Research Procedia, vol. 61, pp. 681-690, 2022. https://doi.org/10.1016/j.trpro.2022.01.108.
A. Ilinykh, A. Manakov, A. Abramov and S. Kolarzh, “Quality assurance and control system for railway track tamping,” Proceedings of the X International Scientific and Technical Conference “Polytransport Systems”, MATEC Web Conference, Tomsk, November 15-16, 2018, vol. 216. https://doi.org/10.1051/matecconf/201821603004.
E. Dincel, H. Nak, Ş. Akkaya, M. Canevi, İ. Mutlu, M. Turan Söylemez, “Robust control of railway traction system,” IFAC-PapersOnLine, vol. 51, issue 25, pp. 171-177, 2018. https://doi.org/10.1016/j.ifacol.2018.11.100.
L. Liudvinavičius, S. Dailydka, A. Sładkowski, “New possibilities of railway traffic control systems,” Transport Problems, vol. 11, issue 2, pp. 133-142, 2016. https://doi.org/10.20858/tp.2016.11.2.13.
Om Prakash Yadav, G. L. Pahuja, "Bearing Health Assessment Using Time Domain Analysis of Vibration Signal", International Journal of Image, Graphics and Signal Processing (IJIGSP), vol.12, no.3, pp. 27-40, 2020. https://doi.org/10.5815/ijigsp.2020.03.04.
M. Metin and R. Guclu, “Rail vehicle vibrations control using parameters adaptive PID controller,” Mathematical Problems in Engineering, Hindawi, vol. 2014, 728946, 10 pages, 2014. https://doi.org/10.1155/2014/728946.
T. A. Aliev, T. A. Babayev, N. F. Musaeva, R. M. Gadimov, A. I. Mammadova, “An intelligent system for identifying track hauls requiring out-of-turn control of the railroad bed,” Mechatronics, Automation, Control, vol. 25, issue 5, pp. 223-230, 2024. https://doi.org/10.17587/mau.25.223-230.
T. Chu, T. Nguyen, H. Yoo, J. Wang, “A review of vibration analysis and its applications,” Heliyon, vol. 10, issue 5, e26282, 2024. https://doi.org/10.1016/j.heliyon.2024.e26282.
M. A. Khan, K. Akhtar, N. Ahmad, F. Shah, N. Khattak, “Vibration analysis of damaged and undamaged steel structure systems: cantilever column and frame,” Earthquake Engineering and Engineering Vibration, vol. 19, pp. 725–737, 2020. https://doi.org/10.1007/s11803-020-0591-9.
Hu, M., and Li, D. “Noise interference issues in sensor technology and countermeasures,” New Technology & New Process, no. 4, pp. 51–53, 2009. https://doi.org/10.3969/j.issn.1003-5311.2009.04.019.
C. C. Lin, J. F. Wang and B. L. Chen, “Train-induced vibration control of high-speed railway bridges equipped with multiple tuned mass dampers,” Journal of Bridge Engineering, vol. 10, issue 4, pp. 398-414, 2005. https://doi.org/10.1061/(ASCE)1084-0702(2005)10:4(398).
C. Sun and L. Gao, “Medium-to-low-speed freight rail transport induced environmental vibration and analysis of the vibration isolation effect of building slope protection piles,” Journal of Vibroengineering, vol. 19, issue 6, pp. 4531-4549, 2017. https://doi.org/10.21595/jve.2017.18168.
D. Anderson, P. E. Gautier, M. Iida et al., “Noise and vibration mitigation for rail transportation systems,” Proceedings of the 12th International Workshop on Railway Noise, Terrigal, Australia, September 12-16, 2016. https://doi.org/10.1007/978-3-319-73411-8.
E. P. Dudkin, L. A. Andreeva, N. N. Sultanov, “Methods of noise and vibration protection on urban rail transport,” Procedia Engineering, vol. 189, pp. 829-835, 2017. https://doi.org/10.1016/j.proeng.2017.05.129.
Darong, H., Lanyan, K., Bo, M., Ling, Z. and Guoxi, S. “A New Incipient Fault Diagnosis Method Combining Improved RLS and LMD Algorithm for Rolling Bearings with Strong Background Noise,” IEEE Access, no 6, 26001–26010, 2018. https://doi.org/10.1109/ACCESS.2018.2829803.
T. Aliev, Noise Control of the Beginning and Development Dynamics of Accidents, Springer, 2019, 201 p. https://doi.org/10.1007/978-3-030-12512-7.
H. Wang, S. Wang, X. Wang, T. Liu, Y. Wang, “RDTS noise reduction: A fast method study based on signal waveform type,” Optical Fiber Technology, vol. 65, 102594, 2021. https://doi.org/10.1016/j.yofte.2021.102594.
S. V. Vaseghi, Advanced Digital Signal Processing and Noise Reduction, John Wiley & Sons, Ltd. 2008. https://doi.org/10.1002/9780470740156.
T. A. Aliev, N. F. Musaeva, M. T. Suleymanova, B. I. Gazizade, “Technology for calculating the parameters of the density function of the normal distribution of the useful component in a noisy process,” Journal of Automation and Information Sciences, vol. 48, issue 4, pp. 39-55, 2016. https://doi.org/10.1615/JAutomatInfScien.v48.i4.50.
Yohzoh Okumura, Kazuhiro Kuno, “Statistical analysis of field data of railway noise and vibration collected in an urban area,” Applied Acoustics, vol. 33, issue 4, pp. 263-280, 1991. https://doi.org/10.1016/0003-682X(91)90017-9.
O. Iliashov, V. Komarov, “An Approach to Development of a Mathematical Model for Determination of Monitoring Objects Using Informativeness of their Monitoring Indicators,” Cybernetics and Systems Analysis, vol. 56, pp. 766–769, 2020. https://doi.org/10.1007/s10559-020-00297-8.
Chunwei Zhang, Asma A. Mousavi, Sami F. Masri, Gholamreza Gholipour, Kai Yan, Xiuling Li, “Vibration feature extraction using signal processing techniques for structural health monitoring: A review,” Mechanical Systems and Signal Processing, vol. 177, 109175, 2022. https://doi.org/10.1016/j.ymssp.2022.109175.
V. Komarov, O. Iliashov and V. Oleksiiuk, “Methodological Approach to the Identification of Monitoring Objects,” Cybernetics and Systems Analysis, vol. 58, 832–839, 2022. https://doi.org/10.1007/s10559-022-00516-4.
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