THERMAL SCIENCE
International Scientific Journal
AN ON-LINE DETECTION METHOD FOR CONVEYOR BELT DEVIATION FAULTS
ABSTRACT
The conveyor belt deviation occurs frequently, and it will finally lead to an accident, so its detection has triggered skyrocketing attention from both industry and academia. In this paper, an adaptive segmentation model and a belt offset quantification model are established for continuous online detection of the conveyor belt deviation status. The results show that the degree of the conveyor belt deviation can be quantitatively calculated and its deviation status can be objectively evaluated. This technology has opened the path for a new way to on-line continuously detect the conveyor belt deviation.
KEYWORDS
PAPER SUBMITTED: 2021-12-25
PAPER REVISED: 2022-06-05
PAPER ACCEPTED: 2022-06-15
PUBLISHED ONLINE: 2023-06-11
THERMAL SCIENCE YEAR
2023, VOLUME
27, ISSUE
Issue 3, PAGES [2099 - 2107]
- Li, W. H., et al., Research on Image Recognition Technology of Belt Conveyor in Coal Mine (in Chi-nese), Coal Technology, 39 (2020), 1, pp. 177-179
- Mei, X. Z., et al., On-Line Intelligent Evaluation of the Fatigue State of a Composite Conveyor Belt, Thermal Science, 25 (2021), 3B, pp. 2189-2196
- Yin, Z. M., et al., Study on Deviation of Conveyor Belt Based on Multi-Body Dynamics Characteristics (in Chinese), Journal of Mechanical Engineering, 56 (2020), 1, pp. 37-46
- Fu, T., Design of Belt Conveyor Rectification System Based on Machine Vision (in Chinese), Coal Mine Machinery, 41 (2020), 8, pp. 183-185
- Wang, P., Real-Time Monitoring Technology of Conveyor Belt Deviation State Based on Digital Image Processing (in Chinese), Coal Mine Machinery, 42 (2021), 02, pp. 168-170
- Gao, R., et al., Adaptive Multi-View Image Mosaic Method for Conveyor Belt Surface Fault On-line Detection, Applied Sciences, 11 (2021), 6, pp. 2564-2589
- Zhang, M., et al., A Computer Vision Based Conveyor Deviation Detection System, Applied Sciences, 10 (2020), 7, pp. 2402-2411
- Zeng, C., et al., Real-Time Conveyor Belt Deviation Detection Algorithm Based on Multi-Scale Feature Fusion Network, Algorithms, 12 (2019), 10, pp. 205-216
- Yang, Y., et al., On-Line Conveyor Belts Inspection Based on Machine Vision, Optik, 125 (2014), 19, pp. 5803-5807
- Yang, L. S., et al., On-Line Detection of Conveyor Belt Deviation Fault Based on Image Processing (in Chinese), Coal Engineering, 52 (2020), 10, pp. 116-120
- Han, T., et al., Detection Method of Coal Quantity and Deviation of Belt Conveyor Based on Image Recognition (in Chinese), Industry and Mine Automation, 46 (2020), 4, pp. 20-25
- Wang, S. Q., et al., Prediction of Myelopathic Level in Cervical Spondylotic Myelopathy Using Diffu-sion Tensor Imaging, Journal of Magnetic Resonance Imaging, 41 (2015), 6, pp. 1682-1688
- Yu, W., et al., Morphological Feature Visualization of Alzheimer's Disease via Multidirectional Percep-tion GAN, IEEE Transactions on Neural Networks and Learning Systems, On-line first, doi.org/10.1109/TNNLS.2021.3118369, 2021
- You, S. R., et al., Fine Perceptive Gans for Brain MR Image Super-Resolution In Wavelet Domain, IEEE Transactions on Neural Networks and Learning Systems, On-line first, doi.org/10.1109/TNNLS.2022.3153088, 2022
- Wang, S. Q., et al., Skeletal Maturity Recognition Using a Fully Automated System with Convolutional Neural Networks, IEEE Access, 6 (2018), June, pp. 29979-29993
- Wang, S. Q., et al., An Ensemble-Based Densely-Connected Deep Learning System for Assessment of Skeletal Maturity, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 52 (2020), 1, pp. 426-437
- Hu, S. Y., et al., Cross-Modality Synthesis from MRI to PET Using Adversarial U-Net with Different Normalization, Proceedings, International Conference on Medical Imaging Physics and Engineering, Shenzhen, China, 2019
- Wu, K., et al., 3D convolutional Neural Network for Regional Precipitation Nowcasting, Journal of Im-age and Signal Processing, 7 (2018), 4, pp. 200-212