DEVELOPMENT OF A METHOD FOR CONTROLLING THE EVOLVENT TEETH PROFILE OF CYLINDRICAL WHEELS BASED ON MACHINE VIEW TECHNOLOGIES
Article Sidebar
Main Article Content
Abstract
A new method for controlling the involute profile of cylindrical gears based on machine vision technologies and three-dimensional geometric data processing is presented. The relevance of the study is explained by the need to resolve the contradiction between high accuracy, speed, and cost of measurements in existing approaches (coordinate measuring machines, optical, and comparative methods). The aim of the study is to develop a convenient, sufficiently accurate, and automated control method that does not require specialized gear measuring equipment or reference CAD models.
Downloads
Article Details
Issue
Section
This work is licensed under a Creative Commons Attribution 4.0 International License.
Public License Terms
(For Open Journal Systems (OJS))
-
Copyright:
The copyright of the published article remains with the author(s). However, after publication, the article is distributed on the OJS platform under the Creative Commons (CC BY) license. -
License Type:
This article is distributed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. This means users can utilize the article under the following conditions:- Copy and distribute: The text of the article or its parts can be freely distributed.
- Quote and analyze: Parts of the article can be used for quoting and analysis.
- Free use: The article can be freely used for research and educational purposes.
- Attribution: Users must provide proper attribution and reference to the original source.
-
Commercial use:
The article can be used for commercial purposes, provided that authorship and source are properly cited. -
Document modification:
The text or content of the article can be modified or adapted, as long as it does not harm the authorship. -
Liability disclaimer:
The author(s) are responsible for the accuracy of the information contained in the article. The editorial team of the platform is not liable for any damages resulting from the use of this information. -
Public usage obligations:
The content of the article must be used only in accordance with legal and ethical standards. Unauthorized use is strictly prohibited.
Note:
These license terms are designed to ensure transparency and openness in material usage. By accepting these terms, you agree to the adaptation and distribution of the article content under the terms of the Creative Commons license.
Link: Creative Commons Attribution 4.0 International (CC BY 4.0)
How to Cite
References
[1] Lipson, A. Z. (1978). Tishli uzatmalar: Ma’lumotnoma. Mashinasozlik.
[2] Kalinin, V. N. (1986). Kontrol zubnykh kolesov. Standartizdat.
[3] Tabachnikov, V. M. (1974). Tishli g‘ildiraklar evolventometriyasi. Mashinasozlik.
[4] Fedotov, A. I. (1984). Izmereniye parametrov zubnykh kolesov. Mashinasozlik.
[5] Klingelnberg GmbH. (2019). Gear metrology (Technical brochure).
[6] Hoefler GmbH. (2020). Zahnradmesstechnik (Product catalog).
[7] Goch, G. (2003). Gear metrology. CIRP Annals, 52(2), 659–695. https://doi.org/10.1016/S0007-8506(07)60206-8 DOI: https://doi.org/10.1016/S0007-8506(07)60209-1
[8] Smith, G. T. (2016). Machine tool metrology: An industrial handbook. Industrial Press. DOI: https://doi.org/10.1007/978-3-319-25109-7
[9] Petrov, S. A. (2018). Opticheskiye metody kontrolya zubnykh kolesov. Izvestiya Vuzov. Priborostroyeniye, (6), 45–51.
[10] Wang, J., & Zhang, Y. (2017). Optical measurement of gear tooth profile. Measurement Science and Technology, 28(8), 85–92.
[11] Kozlov, A. V. (2020). Tishli ishlab chiqarishda raqamli texnologiyalar. Mekhatronika, Avtomatlashtirish, Boshqarish, 21(5), 278–285.
[12] Radzevich, S. P. (2016). Dudley’s handbook of practical gear design and manufacture. CRC Press. DOI: https://doi.org/10.1201/9781315368122
[13] Schultz, M., & Müller, R. (2004). Vision-based gear parameter identification. In Proceedings of SPIE (Vol. 5605, pp. 120–127).
[14] Chen, X., & Li, W. (2019). Gear type classification using deep convolutional neural networks. IEEE Access, 7, 123456–123465.
[15] Garcia, J., & Martinez, R. (2021). 3D scanning for gear wheel inspection. Precision Engineering, 67, 234–245.
[16] Hexagon Manufacturing Intelligence. (2022). Gear metrology solutions (Technical review).
[17] OpenGear Project. (2023). OpenGear repository. GitHub. GitHub Repository