Infrared and Laser Engineering, Volume. 53, Issue 7, 20240144(2024)
Research progress of laser thermography non-destructive testing (invited)
Figures & Tables(17)
Fig. 3. Schematic diagram of laser-line scanning thermography system
Fig. 4. Schematic diagram of laser array spot thermography system[17]
Fig. 7. Schematic diagram of laser pulse phase thermography detection
Fig. 8. Schematic diagram of fiber-coupled beam homogenization system[24]
Fig. 9. Schematic diagram of pulsed compression enhanced laser infrared thermal imaging[25]
Fig. 10. Experimental measurement results of pulsed compression enhanced laser infrared thermal imaging for test specimen with 3 mm desticking defect[25]
Fig. 11. Deconvolution reconstruction method based on Lucy-Richardson algorithm[41]
Table 1. Comparison of different heating modes in laser thermal imaging
View tableView in ArticleTable 1. Comparison of different heating modes in laser thermal imaging
Heating mode Advantages Limitations LPT Simple High energy Long detection time Sensitive to noises Heating unevenly LLT High sensitivity Low noise Low efficiency LPPT High efficiency Well distributed Comparatively complex Need appropriate sampling intervals
Table 2. Imaging data processing methods
View tableView in ArticleTable 2. Imaging data processing methods
Ref. Method Processing result [40] Otsu adaptive threshold segmentation method and a derivative analysis method Can control the quantification accuracy of defect size within 25% and the depth quantification accuracy of tiny defects within 7% [41] Deconvolution reconstruction method based on Lucy-Richardson algorithm The defect detection diameter-to-depth ratio reached 1.5, while the defect detection rate of the test specimens can approach 90% [42] Signal enhancement of the scanning laser line source (SLLS) method SLLS peak for signal enhancement can effectively respond to the crack depth within a limited scope [43] An active 3-D thermography system uses only one thermal camera for moving objects The error is calibrated within 0.25 mm in the range of 1 to 150 mm and evidenced the capability for subsurface defects detection [44] Laplacian calculations Extremely small perturbations can be efficiently extracted from lock-in thermography signals [45] Absolute thermal contrast, thermographic signal reconstruction, phase Fourier analysis and principal component analysis PCA applied to long pulse thermography provides accurate imaging results over traditional pulsed thermography and step heating thermography [46] Construct and subtract an oriented carrier temperature field Blind holes with diameters of 1, 2, and 3 mm and artificial disbonds with diameters of 2 and 3 mm are detected with high efficiency [47] Partial least squares regression (PLSR) and Independent component analysis (ICA) The 1 st independent component has a better detection effect for defect depth and diameter [48] Reconstruction method based on 1 D heat conduction model Solve the dilemma between the inspection speed and the inspection capacity, get higher temporal resolution and spatial resolution of thermal images [49] Non-orthogonal reconstructed space for line scanning thermography The temporal alignment error is controlled within one pixel [50] Data parameterization (curve fitting) for infrared sequences Reduction of output data size and faster real time processing [51] Sequence differential processing Effectively reduces the influence of uneven laser energy distribution on detection efficiency and enhances internal defect information [52] A contrast enhancement method by homomorphic technology The composite material defects with a depth of less than 4 mm can be detected and that with a depth of less than 3 mm can be evaluated quantitatively with a small error less than 10%
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Yunze HE, Qi CHEN, Hongjin WANG, Baoyuan DENG, Ruizhen YANG, Yaonan WANG. Research progress of laser thermography non-destructive testing (invited)[J]. Infrared and Laser Engineering, 2024, 53(7): 20240144
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Received: Apr. 1, 2024
Accepted: --
Published Online: Aug. 9, 2024
The Author Email: WANG Hongjin (hjwang_2018@hnu.edu.cn)
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