Abstract: Finite element analysis combined with back propagation(BP) neural network were applied to the active heating infrared nondestructive testing for determing the influencing factors on defect quantitation. Finite element analysis software Ansys, was used to calculate the temperature field of the plates with back sinking hole defects of different depth and diameter under constant heating condition, and surface temperature cloudy map and temperature rise were obtained. The data obtained were used as the sample to train the BP neural network for quantitative evaluation of defects. It was showed by testing that neural network was very effective in predicting the depth of defects. The signal processing method was valuable for engineering application to infrared nondestructive testing.