Dynamic Scanning Electromagnetic Infrared Thermographic Analysis Based on Blind Source Separation for Industrial Metallic Damage Evaluation
In order to solve the problems of low efficiency and small area of existing eddy current thermography industrial nondestructive testing, this work realizes in field of view (FOV) dynamic scanning eddy current pulsed thermography (DSECPT) with the help of blind source separation (BSS) algorithms for continuous detection of large scaled industrial components. The principle of FOV DSECPT, including finite length inductive heating of mobile coil, the reconstruction of transient temperature response, and feature extraction, is investigated. The original thermal images cannot be used for depth analysis; thus, new data reconstruction method with good adaptivity for manual movement was proposed. The emerging BSS algorithms, including independent component analysis and nonnegative matrix factorization, are employed to process the reconstructed data. Through experimental studies, images using various features from classical and BSS algorithms were compared. The proposed FOV DSECPT could provide a visualized and effective means for quality control and inspection of large scaled key components in both manufacturing and service processes.
IEEE Transactions on Industrial Informatics