A certain type of eddy current displacement sensor was taken as an example, and three calibration testing experiments were conducted, in order to increase the accuracy of thickness measurement for insulating coating on curved surface. The 9th-degree polynomial, 7th-order Fourier series, Gaussian multi-peak function, and radial basis function neural network were used for fitting. The squared sum of errors, root mean square, coefficient of determination and single-point operation time were compared and analyzed in terms of measurement accuracy and operation rate, for reference on how to choose the calibration method in different applications. Aiming at the requirements of thickness measurement of polyurethane foam on the outer surface of the fuel tank, chose the method based on radial basis function neural network for verification test. Results show that the measurement error can be controlled between ?0.15 mm to 0.15 mm by optimizing the calibration method.