基于光截图像测量技术的轮对在线检测中，面阵CCD 摄像机拍摄的轮对光截曲线畸变严重，摄像机标定方法和标定精度直接影响轮对检测精度。本文根据非线性畸变成像模型，提出了一种基于移动平面标定板的Tsai异面标定算法。根据径向约束条件和一阶径向畸变公式，利用最小二乘法和Levenberg-Marquardt 优化算法标定出摄像机内、外部参数。并根据现场安装位置要求和光截曲线关键点区域分布情况，设计了标定板及其三个安装位置，实现了图像特征点提取和摄像机参数的标定。实验结果表明，Tsai 异面标定算法标定精度在0.1 mm 以内，满足轮对在线检测对标定精度的要求。

In wheel set online detection based on structured light projection image technique, the wheel set light-section curves acquired by CCD are heavily distorted. The camera calibration method and calibration precision will directly affect the wheel set online detection precision. According to the nonlinear distortion imaging model, Tsai non-coplanar calibration algorithm based on a moving planar calibration plate was proposed. According to the radial alignment constraint and first-order radial distortion formula, the least square method and Levenberg-Marquardt optimization algorithm were used to calibrate the internal and external parameters of camera. The calibration plate and its three installation location were designed, on the basis of the requirements of on-site installation position and the key point regional distribution of the light-section curves. The extraction of image feature points and the calibration of camera parameters were realized. The experimental results show that the calibration precision of Tsai non-coplanar calibration algorithm was less than 0.1 mm. The calibration precision meets the demands of wheel set online detection.