Thermal Wave Radar Imaging Research Articles

Comparative analysis of single- and multiple-frequency thermal wave radar imaging inspection of glass fiber reinforced polymer (GFRP)

Active infrared thermography has gained increasing popularity for nondestructive testing and evaluation in various industrial fields, especially for composite structures. In this regard, thermal wave radar (TWR) imaging is recognized as the next-generation active thermography technology to obtain great resolution and depth range over the inspected objects. A critical aspect concerns the optimal test parameter selection to guarantee reliable quality assurance required for industrial products. In this work, single- and multiple-frequency TWR was investigated in a quantitative manner with the goal of optimizing the detection parameters in terms of probing range and lateral and depth resolution. The effects of test parameters, including sampling frequency, modulation frequency, chirp duration, chirp bandwidth, etc, were investigated in detail through experiments on a glass fiber reinforced polymer specimen with multi-scale diameter-to-depth ratio defects. This paper aims to help yield a better understanding of the physical mechanism behind TWR and propose a workable scheme for testing parameter selection in practical applications.

Accurate identification and detection of occlusal/smooth early caries using thermal-wave radar imaging (TWRI) technique under low temperature rising condition

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.

Vibro-Thermal Wave Radar: Application of Barker Coded Amplitude Modulation for Enhanced Low-Power Vibrothermographic Inspection of Composites.

This paper proposes an efficient non-destructive testing technique for composite materials. The proposed vibro-thermal wave radar (VTWR) technique couples the thermal wave radar imaging approach to low-power vibrothermography. The VTWR is implemented by means of a binary phase modulation of the vibrational excitation, using a 5 bit Barker coded waveform, followed by matched filtering of the thermal response. A 1D analytical formulation framework demonstrates the high depth resolvability and increased sensitivity of the VTWR. The obtained results reveal that the proposed VTWR technique outperforms the widely used classical lock-in vibrothermography. Furthermore, the VTWR technique is experimentally demonstrated on a 5.5 mm thick carbon fiber reinforced polymer coupon with barely visible impact damage. A local defect resonance frequency of a backside delamination is selected as the vibrational carrier frequency. This allows for implementing VTWR in the low-power regime (input power < 1 W). It is experimentally shown that the Barker coded amplitude modulation and the resultant pulse compression efficiency lead to an increased probing depth, and can fully resolve the deep backside delamination.

Study on cracks defect inspection for GFRP laminates using laser excitation chirp pulsed photothermal radar imaging (CP-PRI)

Laser excitation chirp pulsed photothermal radar imaging (CP-PRI), as a novel nondestructive testing and evaluation (NDT&E) approach, is employed to recognize the surface crack at glass fiber reinforced polymer (GFRP) composite materials. The mechanism of crack detection has been demonstrated in detail by a photothermal method and the principle of CP-PRI. A GFRP specimen with artificial surface crack is prepared for NDT&E by CP-PRI. First-order differential processing was employed to enhance edge sharpening of the amplitude image. The effects of the laser power, excitation pulsed width, reference pulsed width, delay time and chirp frequency on the signal-noise-ratio (SNR) of cracks are completely investigated. The results illustrated that the SNR of the crack is increased with the increase of laser power, the opening width of crack and excitation pulse width. The reference pulse width has few implications for the SNRs of the smaller opening width cracks (~100 μm). However, the reference initial delay time and chirp frequency had a significant influence on the SNRs of cracks. The comparison experiments between thermal wave radar imaging (TWRI) and CP-PRI has been carried out, its results indicated that the CP-PRI has the higher SNRs of cracks than that of TWRI. Consequently, CP-PRI is available for the detection of GFRP surface cracks as a result of its high detectability.

Multi-characteristic combination based reliability enhancement of optical bidirectional thermal wave radar imaging for GFRP laminates with subsurface defects

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 (r90/95) at 90% POD with 95% confidence level and detection rates (DRs). The comparison results show that the MCC method exhibits enhanced reliability with smaller r90/95 and higher DRs at a series of determination thresholds compared with CLI, HTM, and CC algorithms.

On the application of an optimized Frequency-Phase Modulated waveform for enhanced infrared thermal wave radar imaging of composites

Thermal Wave Radar (TWR) imaging employs the concept of pulse compression in order to obtain an increased probing depth and depth resolution in infrared thermographic testing of materials. The efficiency of the TWR imaging is highly dependent on the nature of the employed excitation signal. Most studies exploit the use of an excitation signal with an analogue frequency modulation (e.g. sweep signal) or a discrete phase modulation (e.g. Barker coded signal). Recently, a novel frequency-phase modulated (FPM) waveform was introduced, and computationally verified by the current authors, which couples the concept of frequency- and phase modulation to each other in view of obtaining an optimized excitation signal for improved TWR imaging.This paper experimentally investigates the performance of the novel optimized FPM waveform for the inspection of glass and carbon fiber reinforced polymer (GFRP and CFRP) composites, using an optical infrared thermography set-up in reflection mode. The response of the halogen lamps to the FPM waveform is measured, and further the influence of the electro-thermal latency of excitation lamps on the applicability of the novel FPM excitation signal is analytically investigated. Then, the performance of the FPM waveform is experimentally investigated for both glass- and carbon fiber reinforced polymers with defects of different depths and sizes. A comparative analysis is performed with amplitude modulated (classical lock-in), frequency modulated (sweep) and phase modulated (Barker coded) excitation, each with the same time duration as the FPM waveform. The novel FPM waveform outperforms these existing waveforms in terms of defect detectability and contrast-to-noise ratio, especially for the deeper defects. Different central frequencies are examined and the improved performance of the FPM waveform in TWR imaging is demonstrated in all cases.

A study on the SNR performance analysis of laser-generated bidirectional thermal wave radar imaging inspection for hybrid C/GFRP laminate defects

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.

Fourier-Laplace Spectral Theory for Non-Steady-State Thermal Fields with Applications to Problems in Steady-State Photothermal Linear Frequency Modulation

The spectral theory of thermal fields subject to arbitrary boundary surface flux conditions developed in this work establishes a universal approach to non-steady-state (photo)thermal responses of solids under transient or modulated thermal excitation through a combined Fourier-Laplace formalism. The self-consistent evolution from the nonsteady state to the steady state under single frequency or arbitrary pulsed or multifrequency thermal-wave excitation waveforms allows for defining experimental criteria in terms of excitation waveform repetition periods to attain steady state in frequency-modulated photothermal (and other general experimental) systems. This approach is crucial for ensuring accurate material property measurements using lock-in or correlation and spectral analysis demodulation of thermal waves, especially under linear frequency modulation (LFM) when the modulated steady state is time dependent. The theory is validated using experimental photothermal radiometry LFM responses from black anodized aluminum. We also define the associated thermal diffusion length in terms of linear superpositions of partial thermal waves (wavelets), which are shown to result in improved depth, lateral, and axial resolution in thermal-wave radar imaging applications compared with sequential single-modulation frequency detection.

Research on Modulated Thermal Wave Radar Imaging Technique for Photothermal Properties of Semi-transparent Materials

The photothermal characteristics of semi-transparent medium are the basis for describing the transmission process of photothermal radiation. Therefore, the related measurement researches have important application value for the non-destructive testing of high-tech module. In the present work, an infrared thermal wave radar imaging (TWRI) technique combined with sequential quadratic programming (SQP) algorithm was proposed for simultaneous reconstruction of the photothermal property distributions in 2D semi-transparent materials containing defects. The Fourier transform, Hilbert transform, and the Chirp lock-in correlation algorithm were applied and the results of the amplitude and phase information of the temperature signals were compared, so as to identify the position of internal defects, which reduced the number of parameters needed to reconstruct. Then, the SQP algorithm was introduced to simultaneously reconstruct the absorption coefficient and thermal conductivity coefficient distributions in the medium. The TWRI-SQP technique absorbs the advantages of fast identification of defects by TWRI technique and the accurate reconstruction of the photothermal properties of the semi-transparent materials by SQP algorithm. The number of internal defects, geometric dimensioning, shape, and photothermal properties can be reconstructed accurately. The results show that this method is practical and robust to detect the photothermal properties of 2D semi-transparent materials with defects.

Optical excitation fractional Fourier transform (FrFT) based enhanced thermal-wave radar imaging (TWRI)

In this paper, we demonstrated a novel thermal-wave radar imaging approach with use of a dual-directional (down then up) chirp (or linear frequency modulation, LFM) modulated laser as an external excitation source and signal processing by Fractional Fourier transform (FrFT), which can enhance the defect detectability and extend the depth-resolution dynamic range. The thermal-wave signal was reconstructed by use of dimensionless normalization scaling (DNS) method, and furthermore, it explored the centralized feature of energy spectral density in FrFT domain. The amplitude and phase angle at the peak energy density in FrFT domain were extracted to form the corresponding image and used for the defect detection and identification. The experiments were carried over a carbon fiber reinforced polymer (CFRP) specimen with the artificial flat bottom holes (FBHs) to validate the defect detection capability using FrFT based enhanced TWRI compared to the FFT based TWRI or conventional lock-in thermography (LIT) by taking the defect signal to noise ratio (SNR) into account.

Research on Debonding Defects in Thermal Barrier Coatings Structure by Thermal-Wave Radar Imaging (TWRI)

In this paper, thermal-wave radar imaging (TWRI) is introduced to detect debonding defects in SiC-coated Ni-based superalloy plates. Linear frequency modulation signal (chirp) is used as the excitation signal which has a large time–bandwidth product. Artificial debonding defects in SiC coating are excited by the laser beam with the light intensity modulated by a chirp signal. Cross-correlation algorithm and chirp lock-in algorithm are introduced to extract the thermal-wave signal characteristic. The comparative experiment between TWRI reflection mode and transmission mode was carried out. Experiments are conducted to investigate the influence of laser power density, chirp period, and excitation frequency. Experimental results illustrate that chirp lock-in phase has a better detection capability than other characteristic parameters. TWRI can effectively detect simulated debonding defects of SiC-coated Ni-based superalloy plates.

Single frequency thermal wave radar: A next-generation dynamic thermography for quantitative non-destructive imaging over wide modulation frequency ranges.

Single-Frequency Thermal Wave Radar Imaging (SF-TWRI) was introduced and used to obtain quantitative thickness images of coatings on an aluminum block and on polyetherketone, and to image blind subsurface holes in a steel block. In SF-TWR, the starting and ending frequencies of a linear frequency modulation sweep are chosen to coincide. Using the highest available camera frame rate, SF-TWRI leads to a higher number of sampled points along the modulation waveform than conventional lock-in thermography imaging because it is not limited by conventional undersampling at high frequencies due to camera frame-rate limitations. This property leads to large reduction in measurement time, better quality of images, and higher signal-noise-ratio across wide frequency ranges. For quantitative thin-coating imaging applications, a two-layer photothermal model with lumped parameters was used to reconstruct the layer thickness from multi-frequency SF-TWR images. SF-TWRI represents a next-generation thermography method with superior features for imaging important classes of thin layers, materials, and components that require high-frequency thermal-wave probing well above today's available infrared camera technology frame rates.

Experimental Study on GFRP Surface Cracks Detection Using Truncated-Correlation Photothermal Coherence Tomography

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.

CFRP层板缺陷红外热波雷达成像检测概率研究

CFRP层板缺陷红外热波雷达成像检测概率研究

Non-destructive thermal-wave-radar imaging of manufactured green powder metallurgy compact flaws (cracks)

Thermal wave radar imaging (TWRI) was developed to detect manufacturing cracks in automotive powder metallurgy components (transmission sprockets) in their green (unsintered) state. The crack detection capability of the TWRI phase was validated by two sets of cracked/crack-free green and sintered sprockets which were sectioned after TWRI measurements. An automatic defect recognition (ADR) TWR image processing method was also developed to differentiate cracks from local defects. Measurement results demonstrated that TWRI is superior to conventional lock-in thermography imaging (LITI) in both flaw detection resolution and speed, and thus is a viable green-sprocket manufacturing flaw imaging technology.

Research on the fiber lay-up orientation detection of unidirectional CFRP laminates composite using thermal-wave radar imaging

A depth dynamic-resolution thermal-wave radar imaging (TWRI) was used to detect fiber lay-up orientations in the unidirectional CFRP laminate composite. A phase characteristic of thermal wave radar (TWR) signal was proposed and calculated by discrete fractional Fourier transform (DFrFT). The DFrFT phase distribution contour line was approximated as an ellipse and fitted by a non-standard elliptic equation. The ellipse ration angle dependent on the DFrFT phase (defined as Ellipse Angle Curve, EAC) was found to be sensitive to the fiber lay-up orientations of CFRP composite. An inverse methodology was developed to quantitatively characterize the fiber lay-up orientation angle through reconstructing DFrFT phase distribution. A cost function that minimized the square of DFrFT phase difference between TWRI inspection and numerical calculations was constructed, and a hybrid algorithm that combined the simulation annealing (SA) with Nelder–Mead simplex research (NM) method was employed to solve the cost function and find the global optimal solution of the fiber layer-up orientation angle. Experimental investigation of a 7-layer CFRP laminates [0°/45°/90°/0°]s validated the feasibility of estimating carbon fiber layer-up orientations by TWRI.

Detection of Fiber Layer-Up Lamination Order of CFRP Composite Using Thermal-Wave Radar Imaging

In this paper, thermal-wave radar imaging (TWRI) is used as a nondestructive inspection method to evaluate carbon-fiber-reinforced-polymer (CFRP) composite. An inverse methodology that combines TWRI with numerical optimization technique is proposed to determine the fiber layer-up lamination sequences of anisotropic CFRP composite. A 7-layer CFRP laminate $$[0{^{\circ }}/45{^{\circ }}/90{^{\circ }}/0{^{\circ }}]_{\mathrm{{s}}}$$ is heated by a chirp-modulated Gaussian laser beam, and then finite element method (FEM) is employed to calculate the temperature field of CFRP laminates. The phase based on lock-in correlation between reference chirp signal and the thermal-wave signal is performed to obtain the phase image of TWRI, and the least square method is applied to reconstruct the cost function that minimizes the square of the difference between the phase of TWRI inspection and numerical calculation. A hybrid algorithm that combines the simulation annealing with Nelder–Mead simplex research method is employed to solve the reconstructed cost function and find the global optimal solution of the layer-up sequences of CFRP composite. The result shows the feasibility of estimating the fiber layer-up lamination sequences of CFRP composite with optimal discrete and constraint conditions.

Investigation of carbon fiber reinforced polymer (CFRP) sheet with subsurface defects inspection using thermal-wave radar imaging (TWRI) based on the multi-transform technique

A combined theoretical and experimental approach is reported using thermal-wave radar imaging (TRWI) for carbon fiber reinforced polymer (CFRP) with subsurface defects inspection. The multi-transform technique (Fourier transform, FT; Hilbert transform, HT; and cross-correlation, CC) is applied to extract the characteristics of thermal-wave signal. Experimental results indicate that the multi-transform technique of thermal-wave signal is available for detecting the subsurface defect. For the shallow defect (defect depth ≤1mm), the delay time image of CC exhibits high contrast, and the phase image of FT has high SNR at the right frequency component. For the deep defect (defect depth 2.0mm), the phase images of HT have both high contrast and large SNR value.