Infrared image registration of damage in the aircraft skin based on lie group machine learning

The method of nondestructive testing for aircraft skin composite defects using infrared thermography is very effective. But, against the problem of how to rapidly and accurately identify for the defects of specific types needs to be further study. Based on the analysis of the existed classifier for skin damages, a complex group classifier based on lie group machine learning algorithm is introduced in this paper. According to the damage infrared thermal images obtained by the infrared thermal imager, the feature of internal defects of the skin specific defects is extracted and a discriminant function is established, and then a direct classification for the input image is realized. A simulation result proves that the algorithm given in this paper can satisfy the identification accuracy, and shows the effective of the algorithm.