The parameter model of a binocular structured light three-dimensional (3D) measurement system based on the multi-frequency heterodyne method exhibits strong nonlinearity,making it difficult for traditional approaches to accurately evaluate measurement uncertainty.To address this issue,a Monte Carlo method (MCM) is proposed for uncertainty evaluation in such systems.First,a 3D measurement model is established by combining coordinate system transformations and the multi-frequency heterodyne principle,and the influence of key error sources on measurement results is analyzed. Next,probability density functions of uncertainty components are constructed to characterize the distribution of each parameter.Finally,an MCM-based model linking system parameters and measured surface parameters is developed,enabling uncertainty evaluation through large-scale random numerical simulations.Experiments using standard spheres and gauge blocks validate the effectiveness of the proposed method.Measurement results confirm that the intervals derived via MCM consistently encompass the nominal values of the standard artifacts,demonstrating the accuracy of the evaluation.