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22 May 2023 Automatic detection method of conveyor belt deviation based on DeepLabv3+
Zhen Wang, Jiacheng Li, Xiaohui Yang, Honglei Wang, Liang Wang
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Proceedings Volume 12640, International Conference on Internet of Things and Machine Learning (IoTML 2022); 1264019 (2023) https://doi.org/10.1117/12.2673718
Event: International Conference on Internet of Things and Machine Learning (IoTML 2022), 2022, Harbin, China
Abstract
Conveyor is one of the main equipment for coal production and transportation. Due to impact fatigue, uneven surface stress of conveyor belt and other external factors, deviation will occur, leading to material overflow and damage to transportation equipment. Therefore, it is of great significance to detect the deviation status of the conveyor belt quickly and timely to ensure the safe and efficient operation of the transportation system. This paper presents an automatic detection method of belt deviation based on DeeplabV3+, which can detect the deviation of any position of belt conveyor. We have established a new belt edge dataset under real working conditions. In order to improve the deviation detection accuracy, we expand and erode the image after feature extraction, extract the centerline, and finally detect the deviation distance through the deviation detection module. Experiments show that this method can well balance the detection accuracy and detection speed. The processing speed of a single image is 0.32 s, and the conveyor belt edge detection error is less than 6mm, this method has good real-time performance and high precision, and can be applied to the production scene of underground coal mine.
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Zhen Wang, Jiacheng Li, Xiaohui Yang, Honglei Wang, and Liang Wang "Automatic detection method of conveyor belt deviation based on DeepLabv3+", Proc. SPIE 12640, International Conference on Internet of Things and Machine Learning (IoTML 2022), 1264019 (22 May 2023); https://doi.org/10.1117/12.2673718
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KEYWORDS
Edge detection
Image segmentation
Image processing
Detection and tracking algorithms
Feature extraction
Education and training
Distance measurement
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