TY  - JOUR
T1  - Integrated AI-Based Vision System for Quality Inspection of Welded Structures in Agricultural Machinery Manufacturing
A1  - Bekmyrza Zhumash
A1  - Bulat Salykov
A1  - Seitbek Kuanyshbayev
A1  - Olga Salykova
A1  - Bolat Makhmutov
A1  - Aliya Yskak
A1  - Gulnaz Yermoldina
A1  - Vladimir Fominov
A1  - Denis Komarov
A1  - Zhanibek Nauyrzbayev
A1  - Zayna Zhussupbekova
JF  - World Journal of Environmental Biosciences
JO  - World J Environ Biosci
SN  - 2277-8047
Y1  - 2026
VL  - 15
IS  - 2
DO  - 10.51847/prbBFDZLzE
SP  - 106
EP  - 112
N2  - The quality of welded joints is a critical factor affecting the reliability and service life of agricultural machinery, while conventional inspection methods remain dependent on operator experience and are difficult to automate in serial production. This study aimed to develop and experimentally evaluate an integrated intelligent system for automated weld defect detection using machine vision and a convolutional neural network. The proposed system combines an industrial camera, controlled lighting, an industrial computer, image preprocessing algorithms, and a ResNet-18-based classifier. A dataset of 3,000 weld seam images obtained under production conditions was divided into training, validation, and test subsets using a stratified 70/15/15 ratio. The images were classified as defective or non-defective, and data augmentation and class-weighting procedures were applied during model training. Evaluation on the independent test subset yielded an accuracy of 0.88, precision of 0.88, recall of 0.93, and F1-score of 0.90. The results demonstrate that the developed system can reliably distinguish defective from normal weld areas while providing automated inspection and digital recording of classification results. The proposed approach can be integrated into agricultural machinery manufacturing processes and provides a basis for scalable, data-driven weld quality control within modern digital production systems.
UR  - https://environmentaljournals.org/article/integrated-ai-based-vision-system-for-quality-inspection-of-welded-structures-in-agricultural-machin-hriz2poys07kflf
ER  -