Tula State University (Tula, Russia):

G. V. Seliverstov, Cand. Eng., Associate Prof.
V. Yu. Antsev, Dr. Eng., Prof., Head of Dept. “Lifting and transportation equipment”, e-mail: anzev@yandex.ru
N. V. Antseva, Cand. Eng., Associate Prof., e-mail: n.anzeva@yandex.ru
K. S. Kolomiets, Post-graduate

The modern development of general engineering, including hoisting and transport engineering is characterized by the use of modern steel grades that have good mechanical characteristics while maintaining the necessary requirements for the weldability of metalwork between themselves. However, when working in the cyclic loading mode and when exposed to aggressive media, even new materials tend to accumulate corrosion-fatigue damage, which is the reason for the decrease in their durability. This raises two questions at once. The first question is related to the mathematical description of the accumulation of such damage. The second question is a consequence of the first and involves the development of a new technology for metalwork diagnosis. The article discusses the accumulation of fatigue damage to the structural elements of hoisting machines in the presence and development of pitting damages and the technology for their diagnosis. To build a mathematical model, several joint factors were taken into account that affect the operation of the elements of the supporting metalwork. In addition to cyclic loads, which can conditionally be considered constant in time, there is also a decrease in the mechanical characteristics of the material, an increase in the amplitude of stresses and an increase in the concentration of stresses. A decrease in the strength and yield strengths is associated with the Rehbinder effect, an increase in the amplitude of stresses is caused by a decrease in the cross section of the material, and an increase in stress concentration occurs due to the appearance of pits. At the same time, the pitting depth can be considered a diagnostic parameter, which allows diagnosing the elements of metal structures and predicting the further development of damage, which makes it possible to more fully use the resource of the hoisting machine.
The results of this research are published under fi nancial support of Tula State University within the frameworks of the scientific project No. NIR_2019_1.

1. Neverov А. S., Rodchenko D. А., Tsyrlin М. I. Corrosion and protection of materials: tutorial for universitites. Minsk: Vysheyshaya shkola, 2007. 222 p.
2. Chen S.-T., Cui C.-G., Li Y.-Q., Zhang Y.-H. Research on the damage detection method on existing girder hoisting machine. Journal of Railway Engineering Society. 2015. Vol. 32, Iss. 11. pp. 73–79.
3. Goli-Oglu Е. А. Microalloying of structural low-carbon steel with improved atmospheric corrosion resistance for bridge building. Chernye Metally. 2016. No. 11. pp. 35–40.
4. Seliverstov G. V., Sorokin P. А., Barnikova V. S. The influence of pitting-like defects on development of fatigue damage in elements of crane metal structures. Podyemno-transportnoe delo. 2011. No. 5-6. pp. 30–33.
5. Seliverstov G. V., Danilov А. S. Study of corrosion fatigue of hoisting machines metal structures. Izvestiya Tulskogo gosudarstvennogo universiteta. Seriya: Tekhnicheskie nauki. 2009, Iss. 2. Part 1. pp. 248–253.
6. Seliverstov G. V., Sorokin P. А. Assessment of the theoretical value of the stress concentration coeffi cient during the pitting of crane metal structures. Tyazheloe mashinostroenie. 2013. No. 9. pp. 18–20.
7. GOST 19281–89. Rolled steel with increased strength. General specifications. Introduced: 01.01.1991.
8. GOST 25.502–79. Strength analysis and testing in machine building. Methods of metals mechanical testing. Methods of fatigue testing. Introduced: 01.01.1981.
9. Semenov Yu. Е. Technology for production of metal structures for hoisting machines: tutorial for universities. Tula: Izdatelstvo TulGU, 2006. 153 p.
10. Antsev V. Yu., Seliverstov G. V., Kolomiets K. S. Fatigue calculation of crane metal structures under corrosion effect. Proceedings of the XXI International scientific and technical conference “Interstroymekh 2018”. Edited by S. Ya. Galitskov. 2018. pp. 7–10.
11. Zhang D., Zhang Y., Yu M., Chen Y. Reliability evaluation and component importance measure for manufacturing systems based on failure losses. Journal of Intelligent Manufacturing. 2017. Vol. 28, Iss. 8. pp. 1859–1869.
12. Khatab A. Maintenance optimization in failure-prone systems under imperfect preventive maintenance. Journal of Intelligent Manufacturing. 2018. Vol. 29, Iss. 3. pp. 707–717.
13. Ispiryan R. А. Method for diagnosis of the state of hoisting machines metal structures: Dissertation … of Candidate of Engineering Sciences. Tula: Izdatelstvo TulGU, 2009. 156 p.
14. Pasko N. I., Аntseva N. V. Optimization of the mode for preventive restoration of main processing equipment of a machine-building plant. STIN. 2008. No. 4. pp. 2–6.
15. Aghezzaf E.-H., Khatab A., Tam P. L. Optimizing production and imperfect preventive maintenance planning’s integration in failureprone manufacturing systems. Reliability Engineering and System Safety. 2016. Vol. 145.pp. 190–198.
16. Zhang M., Xie M. An Ameliorated Improvement Factor Model for Imperfect Maintenance and Its Goodness of Fit. Technometrics. 2017. Vol. 59, Iss. 2. pp. 237–246.
17. Inozemtsev А. N., Pasko N. I. Reliability of machine-tools and machine systems: tutorial for universities. Tula: Izdatelstvo TulGU, 2002. 182 p.