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.
Infrared Imagery Nondestructive Testing Lie Group Machine Learning Classifier of Symplectic Group Image Registration
Yunlin Luo Zhanxiao Yan Kun Wang Li Wang
Civil Aviation University of China,Aeronautical Automation College,Tianjin 300300
国际会议
长沙
英文
2104-2108
2014-05-31（万方平台首次上网日期，不代表论文的发表时间）