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Defects, such as delamination and debonding, are critical to the performance of carbon fiber-reinforced polymer (CFRP) composites. In recent years, non-destructive testing techniques have been improved for the inspection of these defects among CFRPs. In this study, an all-optical and non-destructive laser ultrasonic technique with an optical microphone detection module has been presented to detect the artificial subsurface defects among the CFRP composites. A finite element simulation based on the thermo-mechanical coupling model was used to study the process of nanosecond pulsed laser excitation of the CFRP laminate to produce ultrasound and the propagation behavior of ultrasound among the CFRP laminate. A series of non-contact laser ultrasonic testing experiments were carried out to study the flat bottom holes of different sizes via a laser ultrasonic detection system. The artificial subsurface defects were reliably identified by the presented all-optical laser ultrasonic system imbedded in the optical microphone using four feature images. [ABSTRACT FROM AUTHOR]

Laser-induced ultrasound scanning imaging is proposed and utilized for the detection of the printed circuit board (PCB) delamination defect in this present study. Initially, based on the principle of laser-induced ultrasound scanning imaging, a three-dimensional mathematical model of the ultrasonic excitation by pulsed laser acting on the surface of PCB is established and analyzed. Furthermore, based on the established laser ultrasonic nondestructive testing system, single-point testing is investigated on the PCB specimen. A-scan experiments were carried out by transmission and reflection approaches, respectively. Moreover, the influence of the signal receiving position on the discrimination of defective signals and the effect of wavelet transform denoising parameters on the signal-to-noise ratio were investigated. Eventually, based on the laser-induced ultrasound scanning imaging inspection system, the defects of simulated debonding flat bottom holes are detected and studied. The different algorithms or parameters (Fast Fourier Transform, variance, extremum, and principal component analysis, etc.) are employed to extract the characteristic information are analyzed. The experimental results are compared with the traditional infrared thermal wave imaging (lock-in thermography). The experimental results indicate that laser-induced ultrasound scanning imaging has the advantages of high-resolution imaging for the defect with a small diameter. Therefore, it is of great significance to study a set of feasible laser-induced ultrasound scanning imaging for PCB delamination defect detection. [ABSTRACT FROM AUTHOR]

This report is on convolution neural network (CNN) fusion lock-in thermography, which can implement the intelligent identification of defects for aviation honeycomb sandwich composites (HSCs). First, HSCs specimens with subsurface delamination defects were fabricated and stimulated by halogen lamps according to sinusoidal modulation, and the defects were reliably inspected using lock-in thermography. The amplitude and phase images (commonly referred to as feature images) were obtained by using a digital lock-in correlation algorithm. Furthermore, these feature images were changed into gray or color-level image formalism datasets, which is pre-processed in ways including contrast enhancement, threshold segmentation as well as mosaic data augmentation. Finally, the four-layer feature pyramid structure and ransformer are combined and introduced to the popular YOLOv5 CNN model, and a YOLOLT CNN model is formed to realize the defect identification. The average precision (AP) in the defect identification of HSCs in complex environments (contains noise and other objects) reached 93.2% and achieved an average recognition speed of 0.6 s/image. [ABSTRACT FROM AUTHOR]

Contact failure as one of primary failures, which occurs between thin film resistance strain gauge (FRSG) and metal measured objective substrate, seriously influences the measurement validity and precision of the strain gauge. In this article, an electrical excitation thermal-wave imaging (EE-TWI) method is proposed for the inspection of contact failure. Equivalent circuits of the contact resistance under an external electrical source are used to identify the location of the contact failure. Long pulse thermography and lock-in thermography (LIT) are experimentally studied on the detection of contact failure. Pulsed phase thermography and principal component thermography in long pulse thermography as well as the amplitude, quadrature component in LIT are desirable to form the EE-TWI feature images, respectively. A graph-based segmentation method is employed to distinguish and localize the contact failure from EE-TWI images. EE-TWI provides a powerful tool for the contact failure evaluation of integrated thin film resistance strain gauge (FRSG) and has a significant potential to ensure the thin FRSG sticking performance and quality with application of mechanical properties measurements. [ABSTRACT FROM AUTHOR]

Laser array scanning thermography (LAsST) was used to detect the subsurface defects of carbon fiber reinforced composite (CFRP). A series of bottom flat hole (BFHs) of CFRP were prepared for LAsST. Truncation pseudo-static matrix reconstruction (TC-PSMR) method was used to reconstruct the thermal response signal. Fast Fourier transform (FFT), principal component analysis (PCA) and partial least squares regression (PLSR) were used to process the thermal response signals, forming FFT image, PCA image, and PLSR image. The signal noise ratios (SNRs) of defects is calculated, and it is used to evaluate the defect detection ability of different post-processing algorithms. The experimental results show that the image based on FFT phase has a higher signal-to-noise ratio with PLSR image, and the FFT amplitude image and PLSR image can accurately represent the defect size. [ABSTRACT FROM AUTHOR]

• Sinusoidal carrier BCTWI for CFRP laminate delamination detection is proposed. • More energy concentration is achieved by cross-correlation matched filtering. • SNR and defect depth resolution are improved by BCTWI. A Barker-coded modulation thermal-wave imaging (BCTWI) with laser as an external stimulus source based on pulse compression technique is reported on carbon fiber reinforced polymer (CFRP) laminates delamination detection. CFRP samples with different size and depth flat bottom holes (FBHs) are prepared for providing simulated defects of CFRP interlayer delamination. Three kinds of thermal wave feature images (phase, delay time and peak) are formed and deeply studied on their capability of detectivity. Experimental results indicate that delay time and phase images are relatively suitable modality for low-power active thermography requirement due to insensitive to the various excitation power. BCTWI significantly improve SNR and defect depth resolution in comparison with linear frequency modulation thermography (LFMT). [ABSTRACT FROM AUTHOR]

Precise and efficient inspection of disband defect in sub-mm layers of composite structures is a big challenge for the non-destructive and testing industry. In this work, 16 artificial disbands (flat bottom holes), with different sizes and depths, in carbon fiber reinforced polymer (CFRP) composites were contactless detected using combined laser thermography and laser ultrasonics with optical microphone. The presented laser ultrasonic technique employed a membrane free optical microphone is a contactless and nondestructive technique and shows high detectability for flat bottom holes with deep depth in this preliminary investigation. Sizes and depths of the flat-bottom holes were determined by the presented laser ultrasonics technique. This investigation combined the high detection efficiency of laser thermography and high detection sensitivity of laser ultrasonics with the optical microphone together for the contactless inspection of artificial disbonds. [ABSTRACT FROM AUTHOR]

A simple theoretical expression is described to demonstrate the thermal response characteristics of the thermal wave field in the frequency domain by means of the Green's function method. The defect detectivity using lock-in thermography (LIT) for a carbon-fiber-reinforced polymer (CFRP) with a subsurface defect is investigated, and theoretical analysis results of the defect depth resolution as well as the detection range determined by the thermal wave phase information have shown good agreement with experimental results. The detectable size of a lamination defect in a CFRP has also been studied using lock-in thermographic imaging. The experimental results indicate that LIT is reliably available for evaluating subsurface defects of a CFRP panel at the appropriate modulation frequency, and the defect diameter-to-depth ratio can be as low as 3.0. [ABSTRACT FROM AUTHOR]

Highlights: [•] LITI measurement is in good agreement with FEM analysis for TSA on MCS. [•] An artificial neural network was proposed to determine the component of MCS. [•] LITI is an attractive tool for stress distribution analysis of MCS. [Copyright &y& Elsevier]

We demonstrate theoretically and experimentally quantitative long-pass filtered lock-in carrierography (LIC) or lock-in photoluminescence (LIP) imaging and perform comparisons with lock-in thermography (LIT) imaging of industrial Si solar cells. Optoelectronic LIP and thermoelectronic LIT imaging modalities are used for non-destructive, non-contact measurements of the electrical parameters of solar cells from images obtained at various external load resistances. It is shown that quantitative surface-averaged pixel brightness statistical distributions derived from near-infrared (NIR) LIP and mid-infrared LIT images can be used to measure, among other parameters, photogeneration current density, diode saturation current density, ideality factor, and maximum power photovoltage of a multi-crystalline Si solar cell. LIP images were found to have superior contrast and spatial resolution to the respective LIT images. The electrical parameter values measured from the images were found to be in very good agreement with each other and with electrical measurements (EM). The theory further allows for the generation of derivative diode saturation current density and ideality factor images. [ABSTRACT FROM AUTHOR]

• A new depth-resolved tomography approach titled laser induced chirp-pulsed radar photothermal tomography (CR-PT) is introduced. • The accuracy of the shape, position, and depth of the defects detected by CR-PT. • CR-PT technique can achieve high-quality 3D geometric reconstruction of CFRP delamination defect. In this paper, a new depth-resolved tomography approach titled laser induced chirp-pulsed radar photothermal tomography (CR-PT) is introduced, and it is employed for the 3D visualization detection for carbon fiber reinforced polymer (CFRP). Initially, the time delay correlation dual orthogonal demodulation (DOD) algorithm is applied to extract the time/frequency-domain characteristic sequence of the chirp-pulsed radar signal, and the applicability of CR-PT is analyzed by COMSOL simulation environment. Subsequently, the correctness of the simulation analysis is verified by the experiment of detecting CFRP with the flat bottom holes by CR-PT. Meanwhile, the accuracy of the shape, position, and depth of the defects detected by CR-PT is determined. Finally, the immersion ultrasonic C-scan imaging and CR-PT are employed to compare and analyze the delamination defect of CFRP composites, which proved the superiority of CR-PT. The experimental results illustrated that CR-PT technique can achieve high-quality 3D geometric reconstruction of CFRP delamination defect, which provides a new attempt and method for quantitative non-destructive evaluation and tomography of CFRP composites. [ABSTRACT FROM AUTHOR]

[Display omitted] • The multimodal optical excitation pulsed thermography can enhance the depth-resolution dynamic range for debonding defects of the solid propellant rocket motor. • Multiple feature extraction algorithms were proposed and applied to extract characteristic parameters. • Pulse thermography optimized by PLSR and ICA can achieve better detection of interface debonding defects. We demonstrated the multimodal optical excitation pulsed thermography, and this technique can enhance the defect detectability and the depth-resolution dynamic range for the propellant /cladding layer interface debonding defects of the solid propellant rocket motor. Firstly, three-dimensional (3D) thermal-wave model which stimulated by a pulse excitation thermal source was built. The temperature field distribution and the thermal-wave diffusion behavior were analyzed. Subsequently, multiple feature extraction algorithms were proposed and applied to extract characteristic images. The experimental set-up was developed and utilized to detect cladding layers with artificial defects. The results demonstrate that pulse thermography optimized by PLSR and ICA can achieve better detection of interface debonding defects. The characteristic profiles were analyzed to evaluate the ability of feature images to characterize the defect diameter and depth. The results depict that the 1st independent component has a better detection effect for defect depth and diameter. [ABSTRACT FROM AUTHOR]

Abstract: The pulsed thermographic technique was used to detect flat-bottomed hole defects in SiC coated high-temperature alloy plates. Temperature–time Logarithm Fitting Method (TtLFM), Principal Component Analysis (PCA) and Pulsed Phase Thermography (PPT) were used to extract the characteristic information of the thermal wave signal generated by thermal pulse. It is found that PCA algorithm is available for analyzing the thermal wave signal generated by thermal pulse due to higher signal–noise ratio. Experiments were performed to investigate the effect on the thermal contrast by the pulse intensity, frame rate and analysis moment, respectively. Experimental results show that larger pulse intensity and frame rate are benefit to get larger thermal contrast thermogram, and optimal analysis moment selected is helpful to detect the defects of SiC coated high-temperature alloy plates using pulsed thermographic technique. [Copyright &y& Elsevier]

Abstract: The ultrasound lock-in thermographic technique was developed to detect interfacial defects and cracks in a metal plate. Discrete correlation method (DCM), Fourier transformation method (FTM), Short Time Fourier transformation (STF) and Discrete Wavelet Transformation (DWT) algorithms were used to extract the characteristic information of the thermal wave signal generated by ultrasonic wave modulated. It is found that STF and DWT algorithms are available for analyzing the thermal wave signal generated by ultrasonic wave modulated due to higher signal–noise ratio. Experiments were performed to investigate the effect on the amplitude contrast and phase angle contrast by the ultrasound transducer position, initial sonotrode action force and modulation frequency, respectively. Experimental results show that transducer position closed to the defect, higher initial sonotrode action force loaded and optimal modulation frequency selected are help to detect the defects of metal plate using ultrasound lock-in thermographic technique. [Copyright &y& Elsevier]

Abstract: Lock-in thermography, an active IR thermography technique for NDT, is based on propagation and reflection of thermal waves which are launched from the surface into the inspected component by absorption of modulated radiation. In this paper, thermal wave image sequences were sampled by a Cedip JADE MWIR 550 FPA infrared camera. Thermal wave signal processing algorithms are investigated to obtain information on subsurface defects. The Fourier transform, four-point correlation, and digital lock-in correlation algorithms are applied to extract the amplitude and phase of thermal wave’s harmonic component. A novel method called the time constant method (TCM) is proposed to analyze subsurface defects by using lock-in thermography. The experimental results confirm the thermal wave signal processing algorithms’ efficiency on subsurface defect detection. [Copyright &y& Elsevier]

• 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. 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. [ABSTRACT FROM AUTHOR]

In this paper, the detection reliability of optical bidirectional thermal wave radar imaging (BTWRI) for glass fiber reinforced polymer (GFRP) laminates with subsurface defects using various imaging algorithms was quantitatively investigated. A set of GFRP laminates with artificial defects were prepared and inspected. Three frequently-used imaging algorithms (cross-correlation, CC; chirp lock-in, CLI; and Hilbert transform mean, HTM) were applied to construct characteristic images. An analysis for probability of detection (POD) was carried out based on the hit/miss data obtained by comparing the defect contrasts and noise thresholds of characteristic images. A multi-characteristic combination (MCC) method integrating the advantages of each algorithm was proposed. The reliability assessment of optical BTWRI for inspecting GFRP laminate defects was compared by the defect diameter-to-depth ratio (r 90/95) at 90% POD with 95% confidence level and detection rates (DRs). The comparison results show that the MCC method exhibits enhanced reliability with smaller r 90/95 and higher DRs at a series of determination thresholds compared with CLI, HTM, and CC algorithms. [ABSTRACT FROM AUTHOR]

In this paper, a Barker-coded thermal wave imaging approach is reported on the detection of carbon fiber reinforced polymer (CFRP) laminate with subsurface defects, using an integrated Barker code sequence and sinusoidal carrier-modulated laser as the excitation source. Artificial flat bottom holes as subsurface defects are prepared for the experimental investigation. Cross-correlation (CC) algorithm is applied for extracting characteristics of thermal wave signal and forming the corresponding peak delay time and phase images. The effects of Barker code sequence length and carrier-modulated frequency are investigated, which are both most important factors on the detectability of BC-TWI method. The results of the experiments show 5-bit Barker code and 0.1 Hz carrier frequency are the most suitable selection for enhancing inspection capability and obtaining the highest image SNR for a given CFRP laminate material. Furthermore, a comparative experiment is carried out between BC-TWI and lock-in thermography (LIT) method by taking the defect contrast and SNR into account. The results indicate that the BC-TWI CC phase image has higher contrast and SNR than the LIT phase image. [ABSTRACT FROM AUTHOR]

In this paper, truncated-correlation photothermal coherence tomography (TC-PCT) was used as a nondestructive inspection technique to evaluate glass-fiber reinforced polymer (GFRP) composite surface cracks. Chirped-pulsed signal that combines linear frequency modulation and pulse excitation was proposed as an excitation signal to detect GFRP composite surface cracks. The basic principle of TC-PCT and extraction algorithm of the thermal wave signal feature was described. The comparison experiments between lock-in thermography, thermal wave radar imaging and chirped-pulsed photothermal radar for detecting GFRP artificial surface cracks were carried out. Experimental results illustrated that chirped-pulsed photothermal radar has the merits of high signal-to-noise ratio in detecting GFRP composite surface cracks. TC-PCT as a depth-resolved photothermal imaging modality was employed to enable three-dimensional visualization of GFRP composite surface cracks. The results showed that TC-PCT can effectively evaluate the cracks depth of GFRP composite. [ABSTRACT FROM AUTHOR]

Highlights • The different camera system calibration and matching are simultaneously achieved. • The fusion of 3D digital model to 2D IR image reaches up to sub-pixel accuracy. • Integration active thermography and 3D optical imaging is used for the 3D visualization of defects. Abstract In this paper, a combination active thermography and three-dimensional (3D) structural optical imaging is reported on the nondestructive inspection of curved clad composites with subsurface defects. Artificial points are marked on the background of test objective and helpful to obtain the mapping matrix from two-dimensional (2D) thermal wave characteristic imaging data to 3D spatial coordinate's digital model. The 3D digital model is transformed into a new coordinate system and then reprojected onto the thermal-wave feature image exactly. The fusion of 2D thermal-wave characteristic data and the 3D digital model is achieved by bilinear interpolation. Specimens of carbon fiber reinforced polymer (CFRP) skin-honeycomb sandwich (CFRP-SHS) and High silicon oxygen phenolic resin (HSOPR) sheet with artificial defects are prepared for the experimental investigation. Experimental results indicate that the proposed method can reliably inspect the defects and accurately locate defect positions on the curved surface of CFRP-SHS and HSOPR laminate test sample, and it has a significantly potential for the use of aerospace and aircraft manufacturing and application. [ABSTRACT FROM AUTHOR]

Quantitative detection of debonding defects’ diameter and depth in TBCs has been carried out using pulsed infrared thermography technology. By combining principal component analysis with neural network theory, the Markov–PCA–BP algorithm was proposed. The principle and realization process of the proposed algorithm was described. In the prediction model, the principal components which can reflect most characteristics of the thermal wave signal were set as the input, and the defect depth and diameter was set as the output. The experimental data from pulsed infrared thermography tests of TBCs with flat bottom hole defects was selected as the training and testing sample. Markov–PCA–BP predictive system was arrived, based on which both the defect depth and diameter were identified accurately, which proved the effectiveness of the proposed method for quantitative detection of debonding defects in TBCs. [ABSTRACT FROM AUTHOR]

• C/GFRP specimens are tested using bidirectional thermal wave radar imaging. • Multiple imaging algorithms are used for subsurface defect detection and compared by SNR performance. • A modified correlation phase algorithm (Analytical chirp correlation, ACC) is presented for calculation load reduction. • The optimal image of ACC algorithm has a significant improvement on SNR performance. In this paper, the detection capability of laser-generated bidirectional thermal wave radar imaging (BTWRI) inspection for carbon/glass fiber reinforced polymer (C/GFRP) defects was quantitatively evaluated by signal-to-noise ratio (SNR) analysis of characteristic images. A low-power experimental system was devised, and the C/GFRP specimens with multi-scale diameter-to-depth ratio were tested. An improved imaging algorithm (analytical chirp correlation, ACC) was presented by applying analytical bidirectional chirp signal to extract the correlation phase and amplitude of thermal wave radar signal corresponding to the expected delay time. The optimal ACC detection image is obtained by the SNR comparison of characteristic images frame by frame. The conventional imaging inspection results of using cross-correlation (CC), cross-correlation phase (CCP), chirp lock-in (CLI), and Hilbert transform mean (HTM) algorithms were performed for SNR comparison. Experimental results indicate that the ACC algorithm displays almost the same detection capability as the traditional CCP algorithm by a simpler calculation process, and the optimal ACC detection image has a significant enhancement on SNR performance for C/GFRP subsurface defects compared with conventional imaging algorithms. [ABSTRACT FROM AUTHOR]

Laser arrays scan thermography (LAsST) as a nondestructive testing and evaluation (NDT&E) tool is presented to detect the subsurface delamination or abnormally of carbon fiber reinforced polymer (CFRP) composite. A series of woven CFRP specimens with artificial bottom flat holes (BFHs) are prepared for NDT&E by LAsST. The thermal response signal was reconstructed and in turn appeared the analogous thermal responsible behavior similar to pulsed thermography (PT). The thermal response signal was processed by using of Fast Fourier transform (FFT) and principal component analysis (PCA), and FFT amplitude and phase images, PCA image were formed. The signal noise ratios (SNRs) of defects were calculated and employed to evaluate the defect detectability of different post processing algorithms. A likeness optical flow (LOF) approach was proposed to reduce the interruption of lateral thermal diffusion and improve the defect detectability. The experimental results indicate that FFT phase based image shows a relatively high SNR, and the LOF method effectively enlarged the SNRs of defects. [ABSTRACT FROM AUTHOR]

• The principle of multimode infrared thermal-wave imaging is briefly introduced initially. • Several typical infrared thermal-wave imaging modalities are introduced in detail from the aspects of the excitation source, excitation waveform, feature extraction algorithm, and image processing. • The development status and practical application examples of multimode infrared thermal-wave imaging are emphatically introduced, and the problems faced by infrared thermal-wave imaging are analyzed. Multimode infrared thermal-wave imaging has the advantages of intuitive, efficient, large detection area, non-contact, and long-distance detection respectively. It has a wide range of applications in the aerospace, nuclear industry, petrochemical, automobile, and energy fields. In this present investigation, the principle of multimode infrared thermal-wave imaging is briefly introduced initially. Subsequently, several typical infrared thermal-wave imaging modalities, such as pulse thermography, lock-in thermography, line scanning infrared thermography, and infrared radar thermal-wave imaging, are introduced in detail from the aspects of the excitation source, excitation waveform, feature extraction algorithm, and image processing. Multimode infrared thermal-wave imaging based on different heat source triggering modes was also introduced in this paper. The development status and practical application examples of multimode infrared thermal-wave imaging are emphatically introduced, and the problems faced by infrared thermal-wave imaging are analyzed. Finally, the future development trend of multimode infrared thermal-wave imaging is prospected. [ABSTRACT FROM AUTHOR]

• LPBF manufacturing process was monitored by infrared thermography and the processing state was recognized by YOLOV5 model based on convolution neural network. • The network structure was restructured based on Bi-FPN structure to improve the ability of neck network to fuse multi-scale information features. • The results show that the improved YOLOV5 neural network model can effectively identify the LPBF processing state and assist engineers to evaluate the quality of LPBF manufacturing samples. Laser powder bed fusion (LPBF) manufacturing technology is regarded as one of the most promising additive manufacturing technologies. However, the quality and properties of parts manufactured by LPBF are usually affected by different processing states in the LPBF process, which seriously limits the application of this technology. In this present study, an enhanced online processing state monitoring method for LPBF is proposed, which combines convolutional neural network (CNN) and infrared imaging technology. The LPBF process of 316L stainless steel samples with different parameters was recorded by an infrared thermal imager integrated into a commercial LPBF system. An improved YOLOV5 target recognition method for macro defect monitoring in LPBF manufacturing process is proposed. This method has the ability to enhance the small target detection capability by adding a transformer encoder structure and small target monitoring framework in the global scope. Double FPN structure is used to shape the neck network to obtain more effective multi-scale fusion. The CBAM structure block was inserted into the neck network to improve the fuzzy feature recognition capability. The experimental results demonstrated that compared with the original algorithm, the Mean Average Precision (mAP) of the improved model increased from 0.351 to 0.856, indicating that the improved model has a strong ability to recognize the macro processing state in LPBF process. [ABSTRACT FROM AUTHOR]

• The high-power instantaneous xenon lamp-induced chirp-pulsed radar thermography was introduced to detect the surface crack of the silicon/phenolic composite which was widely used in the engine nozzle insulation sleeve. • The chirp-pulsed radar signal was extracted by the time/frequency signal extraction algorithms. • The results demonstrated that the CC peak and DOD amplitude is more sensitive than the phase when detected the surface crack of silica/phenolic composites. In this present study, the high-power instantaneous xenon lamp-induced chirp-pulsed radar thermography was introduced to detect the surface crack of the silicon/phenolic composite which was widely used in the engine nozzle insulation sleeve. Two crack defect specimens were artificially made and detected by chirp-pulsed radar thermography to verify the detection ability of this approach. The cracks of two specimens were made by the diamond scribing process and laser ablation respectively. The differences between them were analyzed by the crack defect detection experiment. The crack defect made by the diamond scratching method is more consistent with the real situation according to the experimental results. The chirp-pulsed radar signal was extracted by the time/frequency signal extraction algorithms [cross-correlation (CC) and dual-orthogonal demodulation algorithms (DOD)]. The influence of parameters such as the power of xenon lamps, excitation frequency, reference pulse width or pulse time, and reference signal delay time on the detection results is mainly investigated by quantitative detection experiments. The results demonstrated that the CC peak and DOD amplitude are more sensitive than the phase when detected the surface crack of silica/phenolic composites. Meanwhile, the reflective phenomenon of the specimen's surface has a great impact on the detection results. The larger the excitation parameters (such as the excitation frequency and the signal pulse width), the larger the contrast of the crack defect and the smaller the signal-to-noise ratio (SNR). The delay time of the reference signal has a small impact on the SNR and contrast of crack detection. In summary, instantaneous high-power xenon lamp-induced chirp-pulsed radar thermography can realize the reliable quantitative detection of surface cracks of silicon/phenolic composite. [ABSTRACT FROM AUTHOR]

• Laser-induced thermography was utilized to detect the multiple-type defects of rigid or rigid flexible PCBs. • The thermal-wave diffusion model for four-layer PCBs simulation structure induced by sinusoidal modulation laser was built. • The phase realizes the effective detection of PCBs delamination defects with a depth of 1.2 mm and microporous defects with a depth of 400 μm. Due to the multilayer complex structure characteristics of printed circuit boards (PCBs), multiple types of defects (Such as delamination, debonding, and breakdown damage) are likely to occur during processing and use, which affects the performance of the entire electronic component. In the present study, infrared thermography was employed to detect the multiple-type defects of PCBs. Initially, the thermal-wave diffusion model for a four-layer PCBs simulation structure induced by a sinusoidal modulation laser was built. Meanwhile, the finite element methods were utilized to solve the thermal-wave mathematical model and analyze the behavior of thermal-wave diffusion. Furthermore, a four-layer copper-clad laminate structure with flat bottom holes (FBHs) simulated delaminate defect was designed and manufactured. Finally, laser-induced lock-in thermography was adopted to detect the multiple types of actual defects (breakdown damage, delamination defect, fold defect, and micropore) of rigid or rigid-flexible PCBs. The phase characteristic image realizes the effective detection of PCBs delamination defects with a depth of 1.2 mm and microporous defects with a depth of 400 μm. The experimental results demonstrated that laser-induced thermography is suitable to detect the multiple-type defects of PCBs. [ABSTRACT FROM AUTHOR]

• Laser arrays scanning thermography (LAsST) was introduced to detect the surface and hidden cracks of solid propellant motor charge. • The thermal-wave response signal is reconstructed by truncation pseudo-static matrix reconstruction (TC-PSMR). • The experimental results demonstrated that the defects of the PLSR image and FFT phase image are more obvious. Laser arrays scanning thermography (LAsST) was introduced to detect the surface and hidden cracks of solid propellant motor charge. A series of simulated surface cracks of solid propellant charge was prepared and detected by LAsST. The thermal-wave response signal is reconstructed by truncation pseudo-static matrix reconstruction (TC-PSMR), and then, the thermal image sequence similar to the impulse response is reconstructed. The principle of characteristic extraction algorithms [such as Fast Fourier transform (FFT), principal component analysis (PCA), and partial least squares regression (PLSR)] are introduced and employed to obtain the feature images from the thermal-wave response. The morphological matrix is used to denoise the processed image. The experimental results demonstrated that the defects of the PLSR image and FFT phase image are more obvious, and the image noise after morphological matrix processing is significantly reduced. Meanwhile, the LAsST approach can enable rapid detection for the surface and hidden cracks of solid propellant motor charge. [ABSTRACT FROM AUTHOR]

• Thermal-wave radar imaging (TWRI) technique was utilized to detect dental caries at an early stage in this present study. • The relationship between laser power intensity and dental surface temperature rise has been investigated. • The experimental results illustrated that TWRI approach can be used as an effective method for early caries diagnosis. Dental caries is a worldwide disease, which will cause adverse effects if it is not treated in time. To accurate detect the early caries, a dental caries recognized approach based on infrared thermal diffusion, titled thermal-wave radar imaging (TWRI) technique was utilized to detect dental caries at an early stage in this present study. One-dimensional (1D) thermal-wave model under linear frequency modulation (or -chirp) thermal flux was built and analyzed the chirp thermal-wave diffusion behavior. In addition, simulated caries environment in vitro was designed and proposed for the treatment of artificial dental caries. Four intact tooth tissues were demineralized with this etching agent for different time on the dental occlusal surface. For the safety of the laser application in clinical trials, the relationship between laser power intensity and dental surface temperature rise has been investigated. When the laser power intensity was controlled within 23.3 W under the irradiation area is 2 mm × 2 mm, the surface temperature rise of dental specimen can be dominated within 5 °C. The comparison experiment between TWRI and lock-in thermography was investigated, and TWRI phase represents a high signal-to noise ratio to the early caries. μCT was utilized to 3D tomography for the dental specimen to obtain the actual caries inside the specimen. The experimental results illustrated that TWRI approach can be used as an effective method for early caries diagnosis. [ABSTRACT FROM AUTHOR]