To address the issues of insufficient accuracy and susceptibility to multiple factors in the detection of weld defects in steel structure bridges, and to ensure the structural safety and service life of bridges, this paper systematically analyzes the classification and formation mechanisms of weld defects, as well as the core principles of detection technology. It dissects the factors influencing accuracy from four dimensions: equipment, parameters, environmental structure, personnel operation, and data processing. Based on this analysis, a multi-dimensional accuracy improvement plan is designed, encompassing equipment optimization, anti-interference technology, algorithm upgrades, and process standardization. Verification experiments are conducted through the establishment of a simulated test platform. The results indicate that the optimized detection plan enhances the identification accuracy of typical defects such as porosity, slag inclusions, and incomplete penetration to 96.3%, with detection errors controlled within ± 0.12mm. This represents a 21.7% improvement in accuracy compared to traditional methods, providing technical support for the precise detection of weld defects in steel structure bridges.