Features of Wear of Gears of Agricultural Machinery
References
- BAEK, S. M. – BAEK, S. Y. – JEON, H. H. – KIM, W. S. – KIM, Y. S. – KIM, N. H. – SIM, T. – KIM, H. – KIM, Y. J. 2022. Improvement of gear durability for an 86 kW class agricultural tractor transmission by material selection. In Agriculture, vol. 12, no. 2, article no. 123. DOI: https://doi.org/10.3390/agriculture12020123
- CHANG, H. – BORGHESANI, P. – SMITH, W.A. – PENG, Z. 2019. Application of surface replication combined with image analysis to investigate wear evolution on gear teeth – A case study. In Wear, vol. 430–431, pp. 355–368. DOI: https://doi.org/10.1016/j.wear.2019.05.024
- EBERSBACH, S. 2007. Artificial intelligent system for integrated wear debris and vibration analysis in machine condition monitoring. PhD thesis. North Queensland : James Cook University.
- FÜRSTENZELLER, A. – TÓTH, F. – KADNÁR, M. – RUSNÁK, J. – BOŠANSKÝ, M. 2019. Comparison of PVD coatings Nacro4 and TIALN + DLC deposited on high contact ratio gearing interacting with conventional and ecological lubricants. In Acta Technologica Agriculturae, vol. 22, no. 2, pp. 48–55. DOI: https://doi.org/10.2478/ata-2019-0009
- GONZALEZ-ARIAS, C. – VIAFARA, C. C. – CORONADO, J. J. – MARTINEZ, F. 2019. Automatic classification of severe and mild wear in worn surface images using histograms of oriented gradients as descriptor. In Wear, vol. 426–427, part B, pp. 1702–1711. DOI: https://doi.org/10.1016/j.wear.2018.11.028
- KANGALOV, P. – NIKOLOV, M. – TODOROV, I. 2022. Abrasion resistance of restorative coatings for crankshafts and bearings in agricultural machinery. In Acta Technologica Agriculturae, vol. 25, no. 1, pp. 27–32. DOI: https://doi.org/10.2478/ata-2022-0005
- KOBELEVA, K. V. – TYKTAMISHEV, V. R. 2017. Methods of increasing the loadability on aeronautical gear transmissions. In Bulletin of the Perm National Research Polytechnic University. Aerospace Engineering, vol. 50, pp. 128–138.
- KULESHKOV, Y. V. – RUDENKO, T. V. – KRASOTA, M. V. – BOŠANSKÝ, M. – TÓTH, F. 2021. Performance features of tooth gearing in gear hydraulic machines. In Acta Technologica Agriculturae, vol. 24, no. 2, pp. 84–91. DOI: https://doi.org/10.2478/ata-2021-0014
- LEI, Y. – LIN, J. – ZUO, M. J. – HE, Z. 2014. Condition monitoring and fault diagnosis of planetary gearboxes: A review. In Measurement, vol. 48, pp. 292–305. DOI: https://doi.org/10.1016/j.measurement.2013.11.012
- MBA, D. – RAO, R. B. K. N. 2006. Development of acoustic emission technology for condition monitoring and diagnosis of rotating machines; Bearings, pumps, gearboxes, engines and rotating structures. In The Shock and Vibration Digest, vol. 38, no. 1, pp. 3–16.
- PENG, Y. – WU, T. – WANG, S. – PENG, Z. 2017. Wear state identification using dynamic features of wear debris for on-line purpose. In Wear, vol. 376–377, part B, pp. 1885–1891. DOI: https://doi.org/10.1016/j.wear.2017.01.012
- PENG, Z. 2002. An integrated intelligence system for wear debris analysis. In Wear, vol. 252, no. 9–10, pp. 730–743. DOI: https://doi.org/10.1016/S0043-1648(02)00031-5
- RANDALL, R. B. 2011. Vibration-based Condition Monitoring: Industrial, Aerospace and Automotive Applications. Hoboken : John Wiley and Sons, 308 pp. ISBN 9780470977668. DOI: https://doi.org/10.1002/9780470977668
- STACHOWIAK, G. – BLAU, P. J. 2017. Tribosystem analysis: A practical approach to the diagnosis of wear problems. In Tribology Letters, vol. 65, article no. 136. DOI: https://doi.org/10.1007/s11249-017-0919-4
- STACHOWIAK, G. P. – STACHOWIAK, G. W. – PODSIADLO, P. 2008. Automated classification of wear particles based on their surface texture and shape features. In Tribology International, vol. 41, no. 1, pp. 34–43. DOI: https://doi.org/10.1016/j.triboint.2007.04.004
- STACHOWIAK, G. W. – BATCHELOR, A. W. 2013. Engineering tribology. 4th ed. Oxford : Butterworth-Heinemann, 832 pp. ISBN 9780123977762.
- SUN, S. X. – YAN, M. – BAI, P. – HAN. L. 2010. Gear reliability design using probability finite element method based on response surface. In Applied Mechanics and Materials, vol. 34–35, pp. 7–12. DOI: https://doi.org/10.4028/www.scientific.net/AMM.34-35.7
- SUN, S. X. – YAN, M. – JIA, W. – BAI, P. 2011. Analysis of sensible random factors that influence gear reliability. In Applied Mechanics and Materials, vol, 80–81, pp. 913–916. DOI: https://doi.org/10.4028/www.scientific.net/AMM.80-81.913
- TROYANOVSKAYA, I. – VESELOVSKY, A. – EROFEEV, V. – IGNATIEV, A. 2022. Investigation of Al-V coatings produced by the thermo-reactive diffusion method. In Materials Science and Technology, vol. 38, no. 11, pp. 734–741. DOI: https://doi.org/10.1080/02670836.2022.2063476
- VESELOVSKY, A. A. – EROFEEV, V. V. – TROYANOVSKAYA, I. P. 2022a. Improving the quality of friction surface by applying antifriction materials to them. In IOP Conference Series: Earth and Environmental Science, vol. 949, no. 012133. DOI: https://doi.org/10.1088/1755-1315/949/1/012133
- VESELOVSKY, A. A. – TROYANOVSKAYA, I. P. – EROFEEV, V. V. 2022b. Predicting the thickness of the hardening coating during diffusion metallization of cast iron. In Materials Research Proceedings, vol. 21, pp. 51–55. DOI: https://doi.org/10.21741/9781644901755-9
- WASILEWSKI, M. R. – ALEKSANDROV, V. A. 2021. Study of the dynamic load of the tractor transmission. In AIP Conference Proceedings, vol. 2340, no. 1, article no. 030005. DOI: https://doi.org/10.1063/5.0047252
- WU, H. – KWOK, N. M. – LIU, S. – LI, R. – WU, T. – PENG, Z. 2019. Restoration of defocused ferrograph images using a large kernel convolutional neural network. In Wear, vol. 426–427, part B, pp. 1740–1747. DOI: https://doi.org/10.1016/j.wear.2018.12.089
- YOUNES, M. A. – KHALIL, A. M. – DAMIR, M. 2005. Automatic measurement of spur gear dimensions using laser light. Part 2: Measurement of flank profile. In Optical Engineering, vol. 44, article no. 103603.
- ZHU, X. – ZHONG, C. – ZHE, J. 2017. Lubricating oil conditioning sensors for online machine health monitoring – A review. In Tribology International, vol. 109, pp. 473–484. DOI: https://doi.org/10.1016/j.triboint.2017.01.015
DOI: https://doi.org/10.2478/ata-2023-0028 | Journal eISSN: 1338-5267
Language: English
Page range: 207 - 214
Published on: Nov 14, 2023
Published by: Slovak University of Agriculture in Nitra
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
Related subjects:
© 2023 Aleksandr Veselovsky, Irina Troyanovskaya, Yurii Syromyatnikov, Sergey Voinash, Vladimir Malikov, Ramil Zagidullin, Linar Sabitov, published by Slovak University of Agriculture in Nitra
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.