# A Fast Recognition Method for Dynamic Blasting Fragmentation Based on YOLOv8 and Binocular Vision
## 2 Materials and Methods  
### Samples and Equipment  
Blasting is a highly efficient technique employed in open-pit mining and underground tunnel construction [20, 21]. The purpose of blasting is to break intact rock into smaller fragments to facilitate resource extraction and engineering construction [22]. If the fragmentation size after blasting does not meet the requirements, secondary breakage is needed, which affects ore transportation efficiency, increases engineering costs, and reduces production efficiency. Blast fragmentation refers to the volume and size of rock fragments after the blasting operation. Blast fragmentation is a key indicator for evaluating blasting effectiveness, reflecting the degree of rock breakage during the operation. Rock fragments are considered to meet blasting requirements when their size ranges from 0 to 0.5 m. If the fragment size reaches 1.0-1.2 m, it is classified as large rock, and fragments exceeding 1.2 m require secondary breakage. Rapid assessment of blast fragmentation is crucial for optimizing blasting design, evaluating blasting performance, and reducing construction costs. Figure 1 shows an on-site photograph taken during blasting at the Husab open-pit uranium mine in Namibia. Existing rock blast fragmentation evaluation techniques are mainly divided into traditional measurement methods and image analysis techniques. In traditional methods, the sieving method and the large-block measurement method are two typical objective measurement approaches. However, their application suffers from low operational efficiency, long cycles, limited sample coverage, high resource consumption, and cost pressure. The sieving method requires transporting blasted rock fragments to a fixed location for mechanical grading, involving extensive material handling and classification operations, making rapid detection in large-scale projects difficult and time-consuming. Although the large-block measurement method conducts a preliminary assessment by manually counting large rock fragments on the surface, it has a limited sample collection range and relies on subjective judgment, making the overall efficiency susceptible to human factors. Traditionally, manual methods involve outlining rock fragments in blast photos by hand and calculating the number of grid squares used to determine fragment sizes. Nowadays, computer-aided methods using image recognition to calculate fragment sizes save significant time and provide valuable and efficient data support for engineering projects. Computer vision-based methods overcome the drawbacks of traditional measurement techniques and have become a research hotspot in intelligent blasting and smart mining production in recent years. This study proposes using digital photography technology to extract rock fragmentation images for accurate size identification and analysis. The primary equipment used  
Figure 1: On-site blast fragmentation data: (**a**) blasting site; (**b**) fragmentation distribution. includes the OAK-D-W-PoE binocular camera and an industrial computer. The OAK-D-W-PoE binocular camera is a smart network IP camera with depth vision, primarily responsible for capturing images. The OAK-D-W-PoE features three onboard cameras (one 4 K/30 fps color camera and two black-and-white binocular cameras) and an inertial measurement unit (IMU), with an IP65 industrial-grade waterproof rating, suitable for indoor and outdoor use. Additionally, it features a PoE interface (802.3 af power over Ethernet and Gigabit Ethernet). The camera's specifications are shown in Table 1.  
The industrial computer is responsible for recognizing and processing images captured on-site, enabling intelligent analysis of post-blast rock fragmentation. The industrial computer is equipped with a powerful CPU and GPU module and features shockproof, dustproof, and waterproof designs, making it suitable for prolonged operation in harsh environments such as mines and open-pit sites.