Research on Engraving Recognition Method of Nodular Cast Iron Pipe Bearing End Based on Improved YOLOX

This study proposes a method for recognizing the engravings on the spigot ends of ductile iron pipes based on an improved YOLOX model. Ductile iron pipes, known for their excellent mechanical properties and corrosion resistance, are widely used in critical fields such as municipal water supply, drainage, and gas transportation. To ensure product quality and achieve traceability, identification information is typically engraved on the spigot ends of ductile iron pipes during production. However, traditional manual recognition methods are inefficient and prone to human error. To address this issue, this paper proposes an automated engraving recognition system based on an improved YOLOX model. By integrating techniques such as Depthwise Separable Convolutions, a multi-scale feature extraction network, and an adaptive attention mechanism, the YOLOX model structure is further optimized to enhance recognition accuracy and robustness in complex industrial environments. Experimental results demonstrate that the improved YOLOX model surpasses traditional models in both recognition accuracy and computational efficiency, proving its effectiveness and reliability for industrial production applications.