FEATURES OF THE IMPLEMENTATION OF COMPUTER VISION IN THE PROBLEMS OF AUTOMATED PRODUCT QUALITY CONTROL
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Abstract
The article analyzes the fields of application of machine vision. Special attention is focused on the application of Machine Vision in intelligent technological systems for product quality control. An important aspect is a quick and effective analysis of product quality directly at the stage of the technological process with high accuracy in determining product defects. The appropriateness and perspective of using the mathematical apparatus of artificial neural networks for the development of an intelligent technological system for monitoring the geometric state of products have been demonstrated. The purpose of this study is focused on the identification and classification of reed tuber quality parameters. For this purpose, new methods of identification and classification of quality control of various types of defects using computer vision and machine learning algorithms were proposed.
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References
Desmond K. et al.: A machine vision algorithm for quality control inspection of gears. The International Journal of Advanced Manufacturing Technology 106(1-2), 2020, 105–120. DOI: https://doi.org/10.1007/s00170-019-04426-2
Domel A. et al.: Autonomous pick and place operations in industrial production. 12th Intern. Conf. on Ubiquitous Robots and Ambient Intelligence (URAI 2015), Kintex, Goyang, Korea, 356. DOI: https://doi.org/10.1109/URAI.2015.7358978
Dyatlov E. I.: Machine vision (analytical review). Mathematical machines and systems 2, 2013, 32–40.
Guo Y. et al.: Rotational projection statistics for 3D local surface description and object recognition. International journal of computer vision 105(1), 2013, 63–86. DOI: https://doi.org/10.1007/s11263-013-0627-y
Industrial Machine Vision Market by Component (Hardware (Camera, Frame Grabber, Optics, Processor), and Software (Deep Learning, and Application Specific)), Product (PC-based, and Smart Camerabased), Application, End-User. Global Forecast to 2023 [https://www.researchandmarkets.com/research/k6lrbk/global_industrial?w=5].
Johnson A. E.: Spin-images: a representation for 3-D surface matching: Diss. Andrew Edie Johnson – Pittsburgh, Pennsylvania, 1997.
Lisovsky A. L.: Application of neural network technologies for management development of systems. Strategic decisions and risk management 11(4), 2020, 378–389. DOI: https://doi.org/10.17747/2618-947X-923
Mastenko I. et al.: Vision yak nevidyemna chastyna intelektual’nykh tekhnolohichnykh system. Tekhnichni Nauky Ta Tekhnolohiyi 4(26), 2021, 58–65 [http://doi.org/10.25140/2411-5363-2021-4(26)-58-66]. DOI: https://doi.org/10.25140/2411-5363-2021-4(26)-58-66
Mastenko І. V., Stelmakh N. V.: Generative design of a frame type construction. KPI Science News 2, 2021, 81–89. DOI: https://doi.org/10.20535/kpisn.2021.2.236954
Sahoo S. K. et al.: A Dynamic Bottle Inspection Structure. Computational Intelligence in Data Mining 711, 2019, 873–884. DOI: https://doi.org/10.1007/978-981-10-8055-5_77
Stelmakh N.: Software module for accelerated technological preparation of assembly small-scale production of devices. Visn. NTUU "KPI". Eng. 54, 2009, 12–17.
Tymchyshyn R. M. et al.: Modern approaches to solving computer vision problems. Control systems and machines 6, 2018, 46–73.
Zhong Y., Fengyu X., Yue W.: Analysis and experiment of workpiece quality detection based on industrial robot. 23rd Intern. Conf. on Mechatronics and Machine Vision in Practice (M2VIP), 2016, 1–6. DOI: https://doi.org/10.1109/M2VIP.2016.7827291
Zuxiang W., Lei Z., Junpeng F.: Design of safety capacitors quality inspection robot based on machine vision. 1st Intern. Conf. on Electronics Instrumentation Information Systems (EIIS), 2017, 1–4. DOI: https://doi.org/10.1109/EIIS.2017.8298545
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