To address the challenges of aligning dual holes during installation of large mining equipment pins—such as difficulty in alignment and non-intuitive adjustment—this solution precisely quantifies the relative positional deviation between the two holes, providing intuitive control parameters for assembly robots. A pose measurement method based on 3D fitting and Euler angle decomposition is proposed. A rotatable laser ranging device is used to collect multi-depth circumferential data, and the geometric parameters of the axis are extracted by fitting a sequence of circle centers using the least squares method. Based on Z-Y-X order Euler angle decomposition, spatial deviations are converted into executable three-axis translation and rotation compensation values in the robotic arm coordinate system. The method was experimentally validated on a 220-ton mining truck pin hole, with results compared against those from a high-precision measuring instrument. Experimental results show that the relative coaxiality error ranges between 4% and 7%. Parameter analysis indicates that computational error decreases as the number of measurement layers (m) and circumferential points (n) increases; accuracy saturates when n≥36 and m>2, making 36 the optimal number of sampling points. The influence of initial angular deviation α on accuracy increases nonlinearly, and large inclination angles cause cross-sectional projection distortion into ellipses, thereby amplifying axis decomposition errors. This method requires no visual hardware and demonstrates strong robustness against dust and occlusion. Its system accuracy meets the requirements for assembly of large-scale mining machinery, and the output pose compensation values can be seamlessly integrated with control commands for heavy-duty robotic arms, significantly improving the assembly efficiency of transmission components and providing a new technical pathway for automated operation and maintenance of large equipment.