Abstract: Objective To support quality control and process optimization in multi-layer multi-pass welding, this study employs line laser sensing which aims to detect weld geometric features across the pre-weld, interpass and post-weld stages. Methods Surface point of the weld cloud data are acquired, combining slope analysis and inflection point detection, forming three core modules including groove detection, interpass detection and post-weld detection. Groove key points are identified by groove feature detection based on slope analysis. Inflection point detection extracts the deposited weld bead and its geometric features. Reinforcement height and cross-section area are computed after welding. Results In multi-layer multi-pass welding tests, the method effectively identifies key geometric features including groove depth, weld width, reinforcement height and cross-sectional area. The method exhibits high detection accuracy under the tested conditions. The positional consistency of the detected features verified by contrasting macro-morphology of cross-section. Conclusion The line laser geometric feature detection provides an integrated workflow for the pre-weld, interpass and post-weld stages, demonstrating engineering applicability value and offering technical support for quality control, process optimization and automation in multi-layer multi-pass welding.