## 1 Introduction  
The belt conveyor is the most widely used piece of equipment in coal mine undergrounds and surface production systems with continuous transportation capacities. Due to the complicated force conditions of the conveyor belt, it is very prone to failures such as tearing, deviation, and surface damage, which poses serious threats to the safe and efficient production of enterprises. When a conveyor belt failure occurs, it usually results in a conveyor running resistance increases, the speed of wear and tear increases, and even leads to downtime. A deviation accident is the most common failure during the operation of the belt conveyor [1], which accounts for 70\(\sim\)80% of the total accidents. It is generally defined as the distance between the centerline of the belt surface and the centerline of the rack exceeding 5% of the bandwidth length. Deviation is a kind of extremely harmful belt conveyor failure, and its failure usually manifests itself as follows: the edges of the belt are worn, the actual width of the belt used to carry the conveying material becomes smaller, and the friction of the roller frame causes the belt to tear, or directly increases the running resistance of the conveyor, causing slippage, which in turn causes a series of other safety accidents. Conveyor belt running deviation is caused by a variety of factors. Reference [2] put forward the reasons and solutions from the aspects of strength, installation accuracy and maintenance quality of conveyor parts. Reference [3] combined with the specific situation of the coal mines in the Huaibei area of China, from the aspects of equipment selection and installation, analyzed the causes of conveyor belt deviation, and specific solutions were given. It has been recognized for a long time that it is very necessary to establish a conveyor state detection system. Radio frequency identification (RFID) technology [4], Embedded conductive detection (ECD) technology [5], and an X-ray testing model [6] were proposed one after another. However, due to the technical conditions and the use cost, these technologies have not been successfully practiced in the field. Specifically for the problem of conveyor belt deviation, the methods to detect the deviation of conveyor belt mainly include manual detection, mechanical deviation correction and photoelectric deviation correction [7] at present. However, they also have a variety of problems, such as the poor accuracy of mechanical deviation correction equipment, high cost of photoelectric deviation correction equipment, and that they cannot achieve the visualization of deviation data. With the development of computer vision technology, its application in fault detection of conveyors is becoming more and more extensive. A multispectral visual detection method for conveyor belt longitudinal tear was proposed in [8] to solve the drawbacks of the existing conveyor belt longitudinal tear detection technology, and its reliability and real-time were verified to meet the requirements in the industrial field. Reference [9] presented a mathematical model for measuring bulk material flow on the conveyor belt using laser scanning technology, providing a basis for intelligent speed regulation of conveyor. A non-contact monitoring method was proposed based on image processing and pattern recognition in Reference [10], which provided new ideas for real-time and non-blind zone conveyor belt monitoring. In Reference [11], an algorithm combined wavelet packet decomposition with the Canny operator was proposed, and this algorithm was also proved in laboratory experiments not only can ensure the validity and reliability of extracting line but also to reduce the calculation to improve the real-time performance of the system. An online visual belt inspection system was developed in Reference [12] used for detecting longitudinal rip and belt deviation from binary belt images.