Blind image separation for the debonding defects recognition of the solid propellant rocket motor cladding layer using pulse thermography. (April 2021) - Wang, Fei; Liu, Junyan; Dong, Boyuan; Gong, Jinlong; Peng, Wei; Wang, Yang; Chen, Mingjun; Liu, Guobin
Highlights: The noise reduction ability of Haar and db1 wavelet is stronger. The number of WT decomposition levels should be selected as 2 or 3. Full half-width method can accurately detect the defect size. The debonding defects can be recognized with high precision. Abstract: Blind image separation based on wavelet transform (WT) enhancement algorithm for the pulse thermography was introduced as a novel modality to recognize the debonding defects of the solid propellant rocket motor cladding layer. Experimental research on the pulse thermography detection of the cladding layer debonding defects was carried out. The main noise sources and the characteristics associated with pulse thermography were analyzed. Subsequently, the traditional image enhancement algorithm and WT enhancement algorithm were compared and investigated. The influence of wavelet parameters on the enhancement of noise reduction ability of WT blind separation is studied. The half-width method is used to detect the defect size, and the results showed that the debonding defects of the solid propellant rocket motor cladding layer can be recognized with high precision by blind image separation based on WT enhancement algorithm.