To improve the accuracy of the single CCD dual light path laser triangulation dynamic online thickness measurement system,a method that fitting the relationship between the position of spots on CCD target surface and the thickness of the measured object based on RBF neural network was proposed.After theoretical analysis,the experiments with two methods were carried out and compared,the one is that fitting the relationship between the position of two spots on CCD target surface and the thickness of the measured object based on RBF neural network,the another is that the existing least squares fitting method of three polynomial models,and the two methods get a network and an approximate mathematical model respectively.Experiments are done in different locations through using ten standard thickness gauges,and it is found that the first method is better than the second method obviously.The results show that the method that fitting the relationship between two spots and the thickness of the measured object based on RBF neural network can improve the accuracy of existing system,and it has strong robustness and meets the requirements of time complexity.