# Research on the Positioning Method of Steel Belt Anchor Holes Applied in Coal Mine Underground
## 1 Introduction  
Coal production in China is mainly performed via underground mining, which needs a large number of tunnels to be built. To ensure the smooth flow of tunnels and the stability of the surrounding rocks, and to prevent the occurrence of roofing and side wall falling accidents, anchor support for tunnels is needed [1; 2; 3]. The traditional anchor support operations are mainly manual, which have two problems: one is that drilling anchor holes generates high labor costs, and the overall work efficiency is low; the second is that there are high safety hazards in the vicinity of the coal mining and support work surfaces, especially in the unfinished support of tunnels, and the workers' on-site operation is high risk [4; 5]. Domestic coal production is becoming more and more intelligent [6; 7]. Since the mid-20 th century, coal mining has evolved from mechanization, through stages of automation, informatization, and digitalization. Since the realization of mechanized mining, the global mining community has been pursuing the achievement of intelligent mining to liberate miners. Currently, many scholars have optimized the mechanical structure of the anchor drilling rigs used in coal mines for automation control [8; 9; 10]. The optimization of the mechanical structure and the remote control of the anchor drilling rigs can improve work efficiency and reduce the need for manpower. However, these improvements only achieve the automation of the anchor drilling rigs, while the position of the anchor holes still needs to be manually determined [11; 12]. The automation of the whole drilling and anchoring operation is not fully achieved. The automatic identification and positioning of the drilling and anchoring locations (i.e., where the drill rod makes holes and inserts the anchor bolts) are key technologies in enhancing the level of intelligence of anchor drilling machines. After tunneling in the roadway, steel belts are laid and the anchor bolts are anchored through the anchor holes in the steel belts. It is essential to identify and accurately locate the anchor holes on the steel belts because if the positioning is inaccurate, the drill bit will hit the steel belt, which can easily damage the equipment and in severe cases, causesafety accidents. Therefore, the precise identification and location of the anchor holes on the supporting steel belts are of great importance. Current methods for anchor hole positioning predominantly utilize machine vision technology. [PERSON] [13] implemented anchor hole positioning using the YOLOv5 model. However, this method tends to have poor accuracy under conditions of small holes and poor lighting. [PERSON] et al. [14] used an improved SSD-MobileNetV2 model for detecting anchor holes in coal mines. [PERSON] et al. [15] employed a binocular vision technique to locate anchor holes in coal mine tunnels, but the accuracy of these methods can still be impacted by factors such as dust and poor lighting in mine tunnels. To address these issues, it is necessary to select a positioning method that is unaffected by light and dust. Currently, the principle of electromagnetic induction is widely used for detecting cracks and defects in metals like steel plates [16]. [PERSON] et al. [17] applied a DC electromagnetic motion-induced eddy current non-destructive testing technology to detect cracks in bearings and gears, and proposed a quantitative characterization method for crack depth/width. [PERSON] et al. [18] used a magnetic drive array eddy current probe method for detecting defects on the inner walls of long-distance metal pipelines, which effectively identified defects. [PERSON] et al. [19] utilized an array sensor eddy-current detection system to identify abrasions on high-speed railway steel rails, and effectively evaluated the extent and shape of the abrasion damage. As a special form of defect, the anchor holes in the steel plates can also be detected with the principle of electromagnetic induction.