Digital image correlation-assisted phase-sensitive optical coherence tomography.

In this Letter, we introduce a digital image correlation-assisted (DIC-assisted) method to tackle the challenges of phase decorrelation and the inability to measure lateral displacement in phase-sensitive optical coherence tomography (PhS-OCT). This DIC-assisted PhS-OCT (DIC-PhS-OCT) first employs DIC to track displacements from the measured amplitude spectra and subsequently uses these tracked displacements to correct supra-pixel displacement offsets in the measured phase spectra. As a result, it effectively mitigates phase decorrelation resulting from both axial and lateral displacements while enabling the acquisition of sub-pixel-level lateral displacements during the DIC computation. Our experiments demonstrate the effectiveness of DIC-PhS-OCT in addressing these challenges while retaining the ultrahigh sensitivity of conventional PhS-OCT.

Dual-convolutional neural network-enhanced strain estimation method for optical coherence elastography.

Strain estimation is vital in phase-sensitive optical coherence elastography (PhS-OCE). In this Letter, we introduce a novel, to the best of our knowledge, method to improve strain estimation by using a dual-convolutional neural network (Dual-CNN). This approach requires two sets of PhS-OCE systems: a high-resolution system for high-quality training data and a cost-effective standard-resolution system for practical measurements. During training, high-resolution strain results acquired from the former system and the pre-existing strain estimation CNN serve as label data, while the narrowed light source-acquired standard-resolution phase results act as input data. By training a new network with this data, high-quality strain results can be estimated from standard-resolution PhS-OCE phase results. Comparison experiments show that the proposed Dual-CNN can preserve the strain quality even when the light source bandwidth is reduced by over 80%.

High-resolution optical coherence tomography using gapped spectrum and real-valued iterative adaptive approach.

Optical coherence tomography (OCT) is a powerful imaging technique that is capable of imaging cross-sectional structures with micrometer resolution. After combining with phase-sensitive detection, it can sense small changes in the physical quantities inside an object. In OCT, axial resolution is generally improved by expanding the bandwidth of the light source. However, when the bandwidth is expanded discontinuously, the wavelength gap induces abnormal sidelobes when estimating OCT signals in the depth domain. This problem can lead to poor axial resolution. Herein, we present a method based on a real-valued iterative adaptive approach (RIAA) to achieve a high axial resolution under a discontinuous bandwidth condition. The method uses a weighted matrix to suppress the abnormal sidelobes caused by the wavelength gap and, therefore, can realize high-resolution measurements. A single-reflector OCT spectrum was first measured for validation, and its amplitude in the depth domain was estimated using different methods. The results indicate that the RIAA had the best capability of suppressing abnormal sidelobes, thereby achieving a high axial resolution. In addition, cross-sectional images and phase-difference maps of three different samples were measured. A comparison of the results validated the practical value of this method.

Deep learning-based method for non-uniform motion-induced error reduction in dynamic microscopic 3D shape measurement.

The non-uniform motion-induced error reduction in dynamic fringe projection profilometry is complex and challenging. Recently, deep learning (DL) has been successfully applied to many complex optical problems with strong nonlinearity and exhibits excellent performance. Inspired by this, a deep learning-based method is developed for non-uniform motion-induced error reduction by taking advantage of the powerful ability of nonlinear fitting. First, a specially designed dataset of motion-induced error reduction is generated for network training by incorporating complex nonlinearity. Then, the corresponding DL-based architecture is proposed and it contains two parts: in the first part, a fringe compensation module is developed as network pre-processing to reduce the phase error caused by fringe discontinuity; in the second part, a deep neural network is employed to extract the high-level features of error distribution and establish a pixel-wise hidden nonlinear mapping between the phase with motion-induced error and the ideal one. Both simulations and real experiments demonstrate the feasibility of the proposed method in dynamic macroscopic measurement.

Generic saturation-induced phase error correction for structured light 3D shape measurement.

Intensity saturation is a challenging problem in structured light 3D shape measurement. Most of the existing methods achieve high dynamic range (HDR) measurement by sacrificing measurement speed, making them limited in high-speed dynamic applications. This Letter proposes a generic efficient saturation-induced phase error correction method for HDR measurement without increasing any fringe patterns. We first theoretically analyze the saturated signal model and deduce the periodic characteristic of saturation-induced phase error. Based on this, we specially design a saturation-induced phase error correction method by joint Fourier analysis and Hilbert transform. Furthermore, the relationship among phase error, saturation degree, and number of phase-shifting steps is established by numerical simulation. Since the proposed method requires no extra captured images or complicated intensity calibration, it is extremely convenient in implementation and is applicable to performing high-speed 3D shape measurements. Simulations and experiments verify the feasibility of the proposed method.

Deep-learning-based approach for strain estimation in phase-sensitive optical coherence elastography.

In this Letter, a deep-learning-based approach is proposed for estimating the strain field distributions in phase-sensitive optical coherence elastography. The method first uses the simulated wrapped phase maps and corresponding phase-gradient maps to train the strain estimation convolution neural network (CNN) and then employs the trained CNN to calculate the strain fields from measured phase-difference maps. Two specimens with different deformations, one with homogeneous and the other with heterogeneous, were measured for validation. The strain field distributions of the specimens estimated by different approaches were compared. The results indicate that the proposed deep-learning-based approach features much better performance than the popular vector method, enhancing the SNR of the strain results by 21.6 dB.

Adaptive incremental method for strain estimation in phase-sensitive optical coherence elastography.

We proposed an adaptive incremental method for the cumulative strain estimation in phase-sensitive optical coherence elastography. The method firstly counts the amount of phase noise points by mapping a binary noise map. After the noise threshold value is preset, the interframe interval is adaptively adjusted in terms of the phase noise ratio. Finally, the efficient estimation of cumulative strain is implemented by reducing the cumulative number. Since the level of phase noise is related to the different strain rates in accordance with the speckle decorrelation, the proposed method can estimate the large strains with high computation efficiency as well as signal-to-noise ratio (SNR) enhancement in nonlinear change of sample deformations. Real experiments of visualizing polymerization shrinkage with nonlinear change of deformations were performed to prove the superiority of adaptive incremental method in estimating the large strains. The proposed method expands the practicability of the incremental method in more complex scenes.

An Investigation of Softening Laws and Fracture Toughness of Slag-Based Geopolymer Concrete and Mortar.

This paper aimed to determine the softening laws and fracture toughness of slag-based geopolymer (SG) concrete and mortar (SGC and SGM) as compared to those of Portland cement (PC) concrete and mortar (PCC and PCM). Using three-point bending (TPB) tests, the load vs. mid-span displacement, crack mouth opening displacement, and crack tip opening displacement curves (P-d, P-CMOD, and P-CTOD curves) were all recorded. Bilinear softening laws of the PC and SG series were determined by inverse analysis. Furthermore, the cohesive toughness was predicted using an analytical fracture model. The cohesive toughness obtained by experimental study was consistent with that predicted by analytical method, proving the correctness of the tension softening law obtained from inverse analysis. In addition, both initial and unstable fracture toughness values of SG mortar were lower than those of PC mortar given the same compressive strength. Moreover, the initial fracture toughness of SG concrete was generally lower than that of PC concrete, whereas the unstable fracture toughness exhibited an opposite trend.

Super-resolution reconstruction of speckle phase in depth-resolved wavelength scanning interference using the total least-squares analysis.

Depth-resolved wavelength scanning interferometry (DRWSI) is a tomographic imaging tool that employs phase measurement to visualize micro-displacement inside a sample. It is well known that the depth resolution of DRWSI is restricted by a wavelength scanning range. Recently, a nonlinear least-squares analysis (NLS) algorithm was proposed to overcome the limitation of the wavelength scanning range to achieve super-resolution; however, the NLS failed to measure speckle surfaces owing to the sensibility of initial values. To the best of our knowledge, the improvement of depth resolution on measuring a speckle surface remains an open issue for DRWSI. For this study, we redesigned the signal processing algorithm for DRWSI to refine the depth resolution when considering the case of speckle phase measurement. It is mathematically shown that the DRWSI's signal is derived as a model of total least-squares analysis (TLSA). Subsequently, a super-resolution of the speckle phase map was obtained using a singular value decomposition. Further, a numerical simulation to measure the micro-displacements for speckle surfaces was performed to validate the TLSA, and the results show that it can precisely reconstruct the displacements of layers whose depth distance is 5 µm. This study thus provides an opportunity to improve the DRWSI's depth resolution.

Fracture Properties and Softening Curves of Steel Fiber-Reinforced Slag-Based Geopolymer Mortar and Concrete.

Adding short steel fibers into slag-based geopolymer mortar and concrete is an effective method to enhance their mechanical properties. The fracture properties of steel fiber-reinforced slag-based geopolymer concrete/mortar (SGC/SGM) and unreinforced control samples were compared through three-point bending (TPB) tests. The influences of steel fiber volume contents (1.0%, 1.5% and 2.0%) on the fracture properties of SGC and SGM were studied. Load-midspan deflection (P-δ) curves and load-crack mouth opening displacement (P-CMOD) curves of the tested beams were recorded. The compressive and splitting tensile strengths were also tested. The fracture energy, flexural strength parameters, and fracture toughness of steel fiber-reinforced SGC and SGM were calculated and analyzed. The softening curves of steel fiber-reinforced SGC and SGM were determined using inverse analysis. The experimental results show that the splitting tensile strength, fracture energy, and fracture toughness are significantly enhanced with fiber incorporation. A strong correlation between the equivalent and residual flexural strengths is also observed. In addition, the trilinear strain-softening curves obtained by inverse analysis predict well of the load-displacement curves recorded from TPB tests.

Wavenumber synthesis approach to high-resolution wavenumber scanning interference using a mode-hoped laser.

A new method for the synthesis of wavenumber series before and after mode hopping is proposed for depth-resolved wavenumber scanning interferometry. The classical Fourier transform is not suitable for mode hopping; consequently, the wavenumber scanning range of diode lasers is rather narrow, reducing the depth resolution and measurement accuracy. We show that the discontinuity in wavenumber domain interferograms caused by mode hopping can be removed by introducing the phase compensation of the interference spectrum. Thus, the wavenumber series before and after mode hopping can be synthesized. Experiments and numerical simulations validate the proposed method, and the measurement error is within 5nm.

Finite Element Modeling for Debonding of FRP-to-Concrete Interfaces Subjected to Mixed-Mode Loading.

This paper presents finite element (FE) modeling of the debonding behavior of fiber reinforced polymer (FRP)-to-concrete interfaces subject to mixed-mode loading, which is realized through a peeling test of FRP composites externally bonded onto a concrete substrate. A cohesive zone model (CZM) is implemented into the FE model to represent the behavior of the FRP-to-concrete interface. Two element schemes (orthotropic plane stress element and beam element) were employed to simulate the behavior of FRP composite plate in the peeling test. The orthotropic plane stress element scheme, bearing a clear physical background and with an easy definition of the material property parameters following the composite mechanics, is found to be superior to the beam element scheme, and thus is utilized to conduct parametric studies. The influences of the peeling angle, the interfacial parameters (i.e., the configuration of the cohesive zone models, the interfacial damage initiation law (DIL), the interfacial damage evolution law (DEL), the coupling of mode-I and mode-II components), on the mixed-mode failure of the FRP-concrete-interface are carefully investigated. The results showed that the mode I component plays a critical role in the debonding failure of FRP-to-concrete interfaces even when the peeling angle is very small. The failure of FRP-to-concrete interface transits promptly from a mode II-dominated one to a mode I-dominated one when the peeling angle increases to a relatively small value (e.g., 4 degree) and subsequently the peeling force (i.e., the debonding strength of FRP) decreases dramatically. Such mixity of the mode I and mode II components should be appropriately considered for refining the analysis of FRP-strengthened RC beams and the FRP debonding strength design, for which a pure mode II interfacial failure was usually assumed.

Improvement of depth resolution in depth-resolved wavenumber-scanning interferometry using wavenumber-domain least-squares algorithm: comparison and experiment.

It is important to improve the depth resolution in depth-resolved wavenumber-scanning interferometry (DRWSI) owing to the limited range of wavenumber scanning. In this work, a new nonlinear iterative least-squares algorithm called the wavenumber-domain least-squares algorithm (WLSA) is proposed for evaluating the phase of DRWSI. The simulated and experimental results of the Fourier transform (FT), complex-number least-squares algorithm (CNLSA), eigenvalue-decomposition and least-squares algorithm (EDLSA), and WLSA were compared and analyzed. According to the results, the WLSA is less dependent on the initial values, and the depth resolution δz is approximately changed from δz to δz/6. Thus, the WLSA exhibits a better performance than the FT, CNLSA, and EDLSA.

Measurement of depth-resolved thermal deformation distribution using phase-contrast spectral optical coherence tomography.

An updated B-scan method is proposed for measuring the evolution of thermal deformation fields in polymers. In order to measure the distributions of out-of-plane deformation and normal strain field, phase-contrast spectral optical coherence tomography (PC-SOCT) was performed with the depth range and resolution of 4.3 mm and 10.7 µm, respectively, as thermal loads were applied to three different multilayer samples. The relation between temperature and material refractive index was predetermined before the measurement. After accounting for the refractive index, the thermal deformation fields in the polymer were obtained. The measured thermal expansion coefficient of silicone sealant was approximately equal to its reference value. This method allows correctly assessing the mechanical properties in semitransparent polymers.

Eigenvalue decomposition and least squares algorithm for depth resolution of wavenumber-scanning interferometry.

Depth resolution of depth-resolved interferometry evaluated by Fourier transform is limited by the range of phase shifting. A novel algorithm, the eigenvalue decomposition and least squares algorithm (EDLSA), is proposed. Experimental results obtained using depth-resolved wavenumber-scanning interferometry demonstrate that the EDLSA performs better than the Fourier transform and complex number least squares algorithm. Not requiring any a priori information, the algorithm can replace the Fourier transform in depth-resolved interferometry with improved depth resolution.

Improvement of the depth resolution in depth-resolved wavenumber-scanning interferometry using multiple uncorrelated wavenumber bands.

In this article, we provide a method to improve the depth resolution of wide-field depth-resolved wavenumber-scanning interferometry (DRWSI), because its depth resolution is limited by the range of the wavenumber scanning and mode hopping of the light source. An optical wedge is put into the optical path to measure the series of the wavenumber on time using a 2D spatial Fourier transform (FT) of the interferograms. Those uncorrelated multiple bands of the wavenumbers due to mode hopping of the diode laser can be synthesized into one band, to enlarge the range of the wavenumber scanning. A random-sampling FT is put forward to evaluate the distribution of frequencies and phases of the multiple surfaces measured. The benefit is that the depth resolution of the DRWSI is enhanced significantly with a higher signal-to-noise ratio. Because of its simplicity and practicability, this method broadens the way to employing multiple different lasers or lasers with mode hopping as the light sources in the DRWSI.

Processing of fluorescence lifetime image using modified phasor approach: homo-FRET from the acceptor.

As the hardware of FLIM technique becomes mature, the most important criterion for FLIM application is the correct interpretation of its data. In this research, first of all, a more orthogonal phasor approach, called as Modified Phasor Approach (MPA), is put forward. It is a way to calculate the lifetime of the complex fluorescent process, and a rule to measure how much the fluorescence process deviates from single exponential decay. Secondly, MPA is used to analysis the time-resolved fluorescence processes of the transfected CHO-K1 Cell lines expressing adenosine receptor A1R tagged by CYP and YFP, measured in the channel of the acceptor. The image of the fluorescence lifetime and the multiplication of the fluorescence lifetime and deviation from single exponential decay reveal the details of the Homo-FRET. In one word, MPA provides the physical meaning in its whole modified phasor space, and broadens the way for the application of the fluorescence lifetime imaging.