DYNAMIC MODELING AND SURFACE INTEGRITY OPTIMIZATION OF LOW-FREQUENCY HYDRAULIC IMPULSE SYSTEMS

DYNAMIC MODELING AND SURFACE INTEGRITY OPTIMIZATION OF LOW-FREQUENCY HYDRAULIC IMPULSE SYSTEMS

Authors

DOI:

https://doi.org/10.31489/2025N2/113-120

Keywords:

Hydraulic impulse system, mechanical processing, surface roughness, dynamic load, mathematical modeling, system stability.

Abstract

This study investigates the dynamic behavior and surface integrity optimization of low-frequency hydraulic impulse systems operating under cyclic loading conditions. Particular attention is paid to the performance of the hydraulic module rod, which is subjected to repeated dynamic impacts during system operation. The influence of surface roughness, residual stresses, and microhardness on vibration stability and durability of friction pairs is analyzed. A dynamic mathematical model describing pressure variation, piston motion, and energy transfer within the hydraulic impulse chamber is developed. The model is implemented in the MATLAB/Simulink simulation environment for numerical analysis of transient processes. Experimental studies were conducted on cylindrical rod-type specimens made of 30KhGSA alloy steel processed using rotary multi-blade turning technology. The experimental results demonstrate that optimization of machining parameters significantly improves surface quality and reduces vibration amplitude of the hydraulic impulse system. The proposed modeling approach enables prediction of system dynamic behavior and provides a basis for improving operational stability. The obtained results confirm that the integration of advanced machining technologies with digital modeling tools can increase the reliability and efficiency of hydraulic impulse systems used in industrial applications.

References

1 Smirnov Y.M., Uraimov M., Smakova N.S. (2019) Mathematical model of hydraulic manipulators of impulse machines. Proceedings of the University, (1), 18–22 Available at: http://tu.kstu.kz/archive/issue/11 [in Russian]

2 Glotov, B.N., Kokenova, A.T., Smagina, V.S. (2015) Classification of hydraulic hand hammers. Applied Research Journal, (5), 385–388. Available at: https://s.applied-research.ru/pdf/2015/2015_05_3.pdf [in Russian]

3 Sherov K. T., Sikhimbayev M. R., Donenbayev B. S. (2017) Experimental research of rotational-and-frictional boring of big holes in large parts. Journal of Theoretical and Applied Mechanics, 47, 2, 67–74. https://doi.org/10.1515/jtam-2017-0018 DOI: https://doi.org/10.1515/jtam-2017-0018

4 Grieves M., Vickers J. (2017) Digital twin: Mitigating unpredictable, undesirable emergent behavior in complex systems. Springer https://doi.org/10.1007/978-3-319-38756-7_8 DOI: https://doi.org/10.1007/978-3-319-38756-7_4

5 Lee J., Davari H., Singh J., Pandhare V. (2020) Industrial AI and digital twins for smart manufacturing. Robotics and Computer-Integrated Manufacturing, 61. https://doi.org/10.1016/j.rcim.2020.102095 DOI: https://doi.org/10.1016/B978-0-12-820027-8.00008-3

6 Saruev, L.A., Ziyakaev, G.R., & Pashkov, E.N. (2011) Mathematical modeling of the hydro-impulse mechanism of drilling machines. Mining Informational and Analytical Bulletin. https://cyberleninka.ru/article/n/matematicheskoe-modelirovanie-gidroimpulsnogo-mehanizma-burilnyh-mashin [in Russian]

7 Gorodilov L.V. (2013) Analysis of the dynamics of two-way hydropercussion systems. II. Influence of design factors and their interaction with rocks. Journal of Mining Science, 49(3), 465–474. https://doi.org/10.1134/S1062739149030143 DOI: https://doi.org/10.1134/S1062739149030143

8 Shcherbakov, V.S., & Galdin, V.N. (2010) Modeling of hydraulic impulse systems. Bulletin of VSTU. Available at: https://cyberleninka.ru/article/n/modelirovanie-gidravlicheskih-impulsnyh-sistem [in Russian]

9 Galdin N.S., Galdin V.N., & Egorova N.N. (2013) Optimization synthesis of main parameters of hydraulic impulse systems of construction machines. Bulletin of SibADI. Available at: https://cyberleninka.ru/article/n/ optimizatsionnyy-sintez-osnovnyh-parametrov-gidravlicheskih-impulsnyh-sistem-stroitelnyh-mashin [in Russian]

10 Skiba, V.Yu. (2021) Improving the efficiency of machine part processing by integrating abrasive grinding and induction hardening. NSTUJ. Available at: https://journals.nstu.ru/files/articles/ flash/27364/2/ [in Russian]

11 Skeeba V., Pushnin V., Erohin I. (2015) Numerical modeling of steel surface hardening by high-frequency currents. Applied Mechanics and Materials, 698, 288–292. https://doi.org/10.4028/www.scientific.net/AMM.698.288 DOI: https://doi.org/10.4028/www.scientific.net/AMM.698.288

12 Sherov K. T., Sikhimbayev M. R., Sherov A. K. (2017) Mathematical modeling of thermo-frictional milling using ANSYS Workbench. Journal of Theoretical and Applied Mechanics, 47(3), 34–42. https://doi.org/ 10.1515/jtam 2017-0008 DOI: https://doi.org/10.1515/jtam-2017-0008

13 Khodzhibergenov D.T., Esirkepov A., Sherov K.T. (2015) Rational milling of metals. Russian Engineering Research, 35, 15–19. https://doi.org/10.3103/S1068798X1501013X DOI: https://doi.org/10.3103/S1068798X1501013X

14 Sherov K.T., Nasad T.G., Absadykov B.N. (2020) Reliability of cutting blades for thermo-frictional processing. News of the National Academy of Sciences of the Republic of Kazakhstan. https://doi.org/10.32014/2020.2518-170X.15 [in Russian] DOI: https://doi.org/10.32014/2020.2518-170X.15

15 Smakova N.S., Smirnov Y.M., Kenjin B.M., & Zhurunova M.A. (2020). Optimal control of operating modes of hydraulic impact actuators of mining machines. Mining Informational and Analytical Bulletin, (6), 95–104. https://doi.org/10.25018/0236-1493-2020-6-0-95-104 DOI: https://doi.org/10.25018/0236-1493-2020-6-0-95-104

16 Geng H., Zhao J., Wang J. (2021) Digital twin-based real-time monitoring and fault diagnosis for hydraulic systems. Chinese Journal of Mechanical Engineering, 34. https://doi.org/10.1186/s10033-021-00640-8

17 Zhang Y., Zhou D., Li Z. (2023) Adaptive control of nonlinear hydraulic actuators using neural networks. ISA Transactions, 129, 362–375. https://doi.org/10.1016/j.isatra.2022.08.045

18 Wang X., Li Q., Chen L. (2023) Optimization of hydraulic impulse systems based on machine learning algorithms. Mechanical Systems and Signal Processing, 198.https://doi.org/10.1016/j.ymssp.2023.110520 DOI: https://doi.org/10.1016/j.ymssp.2023.110520

19 Zhang H., Liu Y., Sun C. (2023) Simulation and experimental study of hydraulic impulse energy conversion. Journal of Mechanical Science and Technology, 37, 2, 891–903. https://doi.org/10.1007/s12206-023-0142-2

20 Zhao W., Chen J., Hu Y. (2023) Hybrid modeling and prediction of hydraulic cylinder performance using digital twin framework. Applied Sciences, 13, 4. https://doi.org/10.3390/app13042586 DOI: https://doi.org/10.3390/app13042586

21 Li H., Yu X., Ren J. (2023) Research on energy-saving control of hydraulic systems based on digital twin technology. Sensors, 23, 1. https://doi.org/10.3390/s23010345 DOI: https://doi.org/10.3390/s23010345

22 Liu P., Xie X., Zhang C. (2022) Machine learning-based optimization for hydraulic pump efficiency. Energies, 15, 19. https://doi.org/10.3390/en15197221 DOI: https://doi.org/10.3390/en15228686

23 Xu H., Tian L., Sun W. (2023) Modeling and optimization of hydraulic impulse systems using MATLAB/Simulink. Intern. J. of Dynamics and Control, 11, 1152–1164. https://doi.org/10.1007/s40435-023-01231-8

24 Chen R., Gao D., Wu Z. (2023) Deep learning for fault prediction in hydraulic systems. IEEE Access, 11, 65903–65915. https://doi.org/10.1109/ACCESS.2023.3298765

25 Smakova N.S., Sherov K.T., Tusupova S.O., Buzauova T.M. (2020) The research of micro-hardness of side surfaces of teeth cylindrical wheels processed by “Shaver-Rolling Device”. Journal of Theoretical and Applied Mechanics, 50, 1, 50–56. https://doi.org/10.1515/jtam-2020-0006 DOI: https://doi.org/10.7546/JTAM.50.20.01.05

26 Zhantlesov E.Zh., Gruzin V.V., Togusov A.K., Zhusupbekov T.Kh., Zhantlesov Zh.K. (2024) Scientific and technical substantiation of the parameters of the radiolocation device for the detection of prohibited items. Eurasian phys. tech. j., 21, 3 (49), 93–98. https://doi.org/10.31489/2024No3/93-98 DOI: https://doi.org/10.31489/2024No3/93-98

Downloads

Published online

2026-03-31

How to Cite

Smakova, N., Pankov, S., Baisadykov, B., Zelenkov, V., Toibazarov, D., & Karypov, A. (2026). DYNAMIC MODELING AND SURFACE INTEGRITY OPTIMIZATION OF LOW-FREQUENCY HYDRAULIC IMPULSE SYSTEMS. Eurasian Physical Technical Journal, 23(1 (55), 113–120. https://doi.org/10.31489/2025N2/113-120

Issue

Section

Engineering

Similar Articles

<< < 5 6 7 8 9 10 11 12 13 14 > >> 

You may also start an advanced similarity search for this article.

Loading...