Given the task of quantifying the PV value of the plane shape of an optical element under atmospheric turbulence. Initially, a model of the Fizeau interferometer under atmospheric turbulence is developed, through which 1,000 interference fringe images are obtained. What’s more, a method of estimating PV value based on convolutional neural network is proposed, leting the interference fringes image as the input of convolutional neural network and extracting the feature information from the image to obtain PV value. Finally, the obtained results are compared with those obtained by ASTM(American Society of Testing Materials) calculation, phase unwrapping and BP(Back Propagation) neural network, and the deviation using the method of convolutional neural network is 2.25×10-4λ, which is more smaller than the results obtained by ASTM,phase unwrapping and BP neural network. The experimental results show that the method has strong interference resistance, high precision and fast operation, and is an effective optical detection method against atmospheric turbulence.