Finite difference-embedded UNet for solving transcranial ultrasound frequency-domain wavefield.

Transcranial ultrasound imaging assumes a growing significance in the detection and monitoring of intracranial lesions and cerebral blood flow. Accurate solution of partial differential equation (PDE) is one of the prerequisites for obtaining transcranial ultrasound wavefields. Grid-based numerical solvers such as finite difference (FD) and finite element methods have limitations including high computational costs and discretization errors. Purely data-driven methods have relatively high demands on training datasets. The fact that physics-informed neural network can only target the same model limits its application. In addition, compared to time-domain approaches, frequency-domain solutions offer advantages of reducing computational complexity and enabling stable and accurate inversions. Therefore, we introduce a framework called FD-embedded UNet (FEUNet) for solving frequency-domain transcranial ultrasound wavefields. The PDE error is calculated using the optimal 9-point FD operator, and it is integrated with the data-driven error to jointly guide the network iterations. We showcase the effectiveness of this approach through experiments involving idealized skull and brain models. FEUNet demonstrates versatility in handling various input scenarios and excels in enhancing prediction accuracy, especially with limited datasets and noisy information. Finally, we provide an overview of the advantages, limitations, and potential avenues for future research in this study.

Physics-informed neural networks for transcranial ultrasound wave propagation.

Transcranial ultrasound imaging has been playing an increasingly important role in the non-invasive treatment of brain disorders. However, the conventional mesh-based numerical wave solvers, which are an integral part of imaging algorithms, suffer from limitations such as high computational cost and discretization error in predicting the wavefield passing through the skull. In this paper, we explore the use of physics-informed neural networks (PINNs) for predicting the transcranial ultrasound wave propagation. The wave equation, two sets of time snapshots data and a boundary condition (BC) are embedded as physical constraints in the loss function during training. The proposed approach has been validated by solving the two-dimensional (2D) acoustic wave equation under three increasingly complex spatially varying velocity models. Our cases demonstrate that due to the meshless nature of PINNs, they can be flexibly applied to different wave equations and types of BCs. By adding physics constraints to the loss function, PINNs can predict wavefields far outside the training data, providing ideas for improving the generalization capability of existing deep learning methods. The proposed approach offers exciting perspectives because of the powerful framework and simple implementation. We conclude with a summary of the strengths, limitations and further research directions of this work.

On acoustic fields of complex scatters based on physics-informed neural networks.

This paper proposes a modeling method for scattered acoustic fields under complex structures based on Physics-informed Neural Networks (PINNs), with particular attention to the acquisition of training sets and the embedding of physical governing equations. First, using acoustic simulation softwares to obtain the scattered acoustic field under various models, and select the scattered acoustic field data at several moments as the training sets. Then, according to the characteristics of the simulated model, the corresponding physical equations have been embedded in the loss function of the network. We tested the method by predicting the propagation of ultrasonic waves and the scattering of acoustic fields with various simple scatterers. Furthermore, we also use PINN to simulate the scattered acoustic field of the real complex damaged structure. The results show that the mean square error (MSE) between prediction and ground truth is in the order of 10-4, which illustrate PINN can effectively simulate the propagation and reflection of ultrasonic waves, and can also simulate the scattered acoustic field of complex structures accurately. The meshless and accurate characteristics of PINN provide a reliable alternative for the theoretical prediction of complex and continuous scattered acoustic fields.

Dual-biprism-based coaxial fringe projection system.

Fringe projection profilometry (FPP) has been widely used for three-dimensional shape measurement because of its simple hardware and high measurement accuracy. However, the use of most FPP systems to measure complex surfaces such as stepped height objects can result in severe occlusion and shadow. To alleviate this problem, a coaxial measurement method based on dual biprisms is presented in this paper. The system is low-cost and easy to implement, and does not require the introduction of mechanical moving parts. Only dual biprisms are introduced into the coaxial system to provide the geometric constraints required for reconstruction. Experimental results on the reconstruction of a surface with significant height changes demonstrate that the proposed method can achieve shadow-free measurements.

Theoretical and experimental investigation of circumferential guided waves in orthotropic annuli.

The fiber composite materials fabricated by stacking the lamina structure obtain increasing attention in the industry, and at the same time, damage analysis is essential for safe operation. A proposed way to detect defects such as debonding and delamination is to induce circumferential guided waves. Accurate determination of the dispersion characteristics and wave fields is a prerequisite for using acoustic guided waves. The aim of this work is to provide such an accurate dispersion results in an arbitrarily thick cylindrically orthotropic homogeneous cylindrical shell of uniform thickness. Compared with the traditional SAFE method, the proposed method, which combines the two numerical methods, namely Floquet Boundary Condition (Floquet BC) Method and Sweeping Frequency Finite Element Modeling (SFFEM) method has obvious advantages. Through Floquet BC method, a theoretical result can be easily obtained without tedious code writing. Then SFFEM helps to verify the theoretical result in an experimental way. Besides, the slight gap between the theoretical and experimental results works as a basis for calibrating the elastic constants of composite materials provided in the manual. Simulations in COMSOL Multiphysics FE software supported by both methods and experiments by the latter have been carried out in this work. The calculated phase velocity dispersion curves demonstrated the efficiency of those two methods. The developed method can be adapted to other complex pipeline structures to extract circumferential guided wave dispersion characteristics by both simulation and experimental measurements.

Fast computational depth segmentation using orthogonal fringe patterns without pattern sequence changing.

The recently proposed omnidirectional depth segmentation method (ODSM) has advantages over traditional depth segmentation in terms of robustness and computational costs. However, this method uses at least six fringe patterns and changes their sequences multiple times to perform depth segmentation, which limits its segmentation speed and increases computational complexity. This paper proposes a fast computational depth segmentation (FCDS) method in which only five patterns are used for object segmentation at different depths into isolated regions without the requirement of pattern sequence changing. Phase singularity points are fully utilized due to their significance as depth segmentation markers to extract segmenting lines used for depth determination. Meanwhile, a modified Fourier transform algorithm (MFTA) is introduced to calculate the wrapped phase sequences, which uses two groups of orthogonal phase-shifting fringe patterns and a DC component pattern (five in total). The segmenting lines along orthogonal directions can be extracted with the FCDS method without changing the fringe sequences, which not only solves the problem of phase insensitivity but reduces the calculation costs. Besides, the problem of mis-segmentation is solved with an optimization algorithm for depth segmenting lines and successfully segments objects with abrupt depth changes. The simulation results demonstrate the effectiveness and precision of the proposed method. The experimental results prove the success of the proposed method for segmenting objects of similar color with a segmentation speed that is up to a 120% increase relative to previous methods.

Efficient intensity-based fringe projection profilometry method resistant to global illumination.

Intensity-based fringe projection profilometry (IBFPP) is used widely because of its simple structure, high robustness, and noise resilience. Most IBFPP methods assume that any scene point is illuminated by direct illumination only, but global illumination effects introduce strong biases in the reconstruction result for many real-world scenes. To solve this problem, this paper describes an efficient IBFPP method for reconstructing three-dimensional geometry in the presence of global illumination. First, the average intensity of two sinusoidal patterns is used as a pixel-wise threshold to binarize the codeword patterns. The binarized template pattern is then used to convert other binarized fringe patterns into traditional Gray-code patterns. A proprietary compensation algorithm is then applied to eliminate fringe errors caused by environmental noise and lens defocusing. Finally, simple, efficient, and robust phase unwrapping can be achieved despite the effects of subsurface scattering and interreflection. Experimental results obtained in different environments show that the proposed method can obtain three-dimensional information reliably when influenced by global illumination.

An Impact Location Algorithm for Spacecraft Stiffened Structure Based on Posterior Possibility Correlation.

In order to ensure the safety of spacecrafts in orbit, impact location is an important part of structural health monitoring systems. In this paper, an impact location algorithm based on posterior probability correlation is proposed to solve the problem, that is, the impact point in the stiffened structure of a spacecraft is difficult to locate. The algorithm combines the Gaussian cross-correlation possibility weight method and the Bayesian posterior probability method. The cross-correlation possibility weight superposition based on grids was used to reduce the dependence of the accuracy of time difference extraction. Gaussian and normalized fitting were used to compensate the reflection, modal transformation, and amplitude attenuation of a stiffened plate. The location result was further optimized by the posterior probability. The proposed algorithm can be applied to the impact source localization of complex stiffened plate structures. The experiment results showed that the average location error can be 2.57 cm with proper sensor network schemes.

Resolution verification sensing device for a stereo digital image correlation system based on dual-frequency laser interference.

Digital image correlation (DIC) is widely used in materials mechanics, nondestructive testing, and other fields due to its advantages of noncontact, full-field measurement, and simple experimental setup. As an optical measurement method to measure the three-dimensional shape and deformation of an object, measurement accuracy is one of the most important technical indicators of DIC. If DIC is made into a measuring instrument, the resolution is an important parameter that must be provided. In general, the higher the measurement accuracy of the instrument, the higher the resolution of the instrument. At present, the research on DIC focuses on the analysis of factors affecting measurement accuracy, the noise reduction of measurement results, and the improvement of correlation algorithms. There are few reports on the verification of the resolution of DIC measurement instruments. However, accuracy analysis and resolution verification of the measurement instrument is a vital technical task to ensure the credibility of the measurement data. In this paper, a high-precision dual-frequency laser interferometer principle is used to design a sensing device to verify the measurement resolution of the DIC instrument. The accuracy and resolution of the self-made stereo DIC instrument were tested and evaluated using this sensing device.

A Random-displacement Measurement by Combining a Magnetic Scale and Two Fiber Bragg Gratings.

Long-distance displacement measurements using optical fibers have always been a challenge in both basic research and industrial production. We developed and characterized a temperature-independent fiber Bragg grating (FBG)-based random-displacement sensor that adopts a magnetic scale as a novel transferring mechanism. By detecting shifts of two FBG center wavelengths, a full-range measurement can be obtained with a magnetic scale. For identification of the clockwise and counterclockwise rotation direction of the motor (in fact, the direction of movement of the object to be tested), there is a sinusoidal relationship between the displacement and the center wavelength shift of the FBG; as the anticlockwise rotation alternates, the center wavelength shift of the second FBG detector shows a leading phase difference of around 90° (+90°). As the clockwise rotation alternates, the center wavelength shift of the second FBG displays a lagging phase difference of around 90° (-90°). At the same time, the two FBG-based sensors are temperature independent. If there is some need for a remote monitor without any electromagnetic interference, this striking approach makes them a useful tool for determining the random displacement. This methodology is appropriate for industrial production. As the structure of the whole system is relatively simple, this displacement sensor can be used in commercial production. In addition to it being a displacement sensor, it can be used to measure other parameters, such as velocity and acceleration.

Hyper-Heuristic Capacitance Array Method for Multi-Metal Wear Debris Detection.

Online detection of fatigued wear debris in the lubricants of aero-engines can provide warning of engine failure during flight, thus having great economic and social benefits. In this paper, we propose a capacitance array sensor and a hyper-heuristic partial differential equation (PDE) inversion method for detecting multiple micro-scale metal debris, combined with self-adaptive cellular genetic (SA-CGA) and morphological algorithms. Firstly, different from the traditional methods, which are limited in multi-induction-Dirac-boundary-inversion, a mathematical model with non-local boundary conditions is established. Furthermore, a hyper-heuristic method based on prior knowledge is also proposed to extract the wear character. Moreover, a 12-plate array circulating sensor and corresponding detection system are designed. The experimental results were compared with the optical microscopy. The results show that under the conditions of 1~3 wear debris with diameters of between 250⁻900 µm, the accuracy of the proposed method is 10⁻38% higher than those of the traditional methods. The recognition error of the wear debris counts decreases to 0.

Characterization of pulsed ultrasound using optical detection in Raman-Nath regime.

In this paper, we describe an optical detection method for the characterization of pulsed ultrasound based on acousto-optic interaction. We deduce the relationship between the ultrasound and the diffracted light from the principle of acousto-optic diffraction in the Raman-Nath regime, which is verified experimentally. Five ultrasonic transducers with different central frequencies and different focusing types are measured to show the method's performance regarding linearity, sound pressure measurement, phase measurement, frequency response, and spatial resolution. The experimental results show a good agreement with simulation data by CIVA (ultrasonic simulation software, M2M NDT, Inc.) and the pulse-echo method.

Ultrasonic Phased Array Compressive Imaging in Time and Frequency Domain: Simulation, Experimental Verification and Real Application.

Embracing the fact that one can recover certain signals and images from far fewer measurements than traditional methods use, compressive sensing (CS) provides solutions to huge amounts of data collection in phased array-based material characterization. This article describes how a CS framework can be utilized to effectively compress ultrasonic phased array images in time and frequency domains. By projecting the image onto its Discrete Cosine transform domain, a novel scheme was implemented to verify the potentiality of CS for data reduction, as well as to explore its reconstruction accuracy. The results from CIVA simulations indicate that both time and frequency domain CS can accurately reconstruct array images using samples less than the minimum requirements of the Nyquist theorem. For experimental verification of three types of artificial flaws, although a considerable data reduction can be achieved with defects clearly preserved, it is currently impossible to break Nyquist limitation in the time domain. Fortunately, qualified recovery in the frequency domain makes it happen, meaning a real breakthrough for phased array image reconstruction. As a case study, the proposed CS procedure is applied to the inspection of an engine cylinder cavity containing different pit defects and the results show that orthogonal matching pursuit (OMP)-based CS guarantees the performance for real application.

Phase-sensitive optical time domain reflectometer with ultrafast data processing based on GPU parallel computation.

The sensing performance of a phase-sensitive optical time domain reflectometer (ϕ-OTDR) has been sufficiently improved, thanks to plenty of valuable research in recent years. However, in the literature, there is hardly any attention aimed at enhancing the data processing capability of the system, the necessity and significance of which are undisputed. This paper, for the first time to the best of our knowledge, analyzed the intrinsic superiority of employing GPU parallel computation in ϕ-OTDR for improving the data processing capability and presented a comprehensive performance evaluation. Three typical, frequently implemented algorithms in ϕ-OTDR-moving average, batch fast Fourier transform, and batch correlation dimension computation-are carried out where CPU-based programs and counterpart GPU-based programs are, respectively, developed. Their time-consuming performances in different data scales are experimentally tested and compared. The experiment results show that in each case, employing GPU parallel computation can significantly enhance the system's data processing capacity, thus providing a feasible and efficient way of guaranteeing real-time operation with the growing data scale.

Non-contact temperature-independent random-displacement sensor using two fiber Bragg gratings.

We present a full-range displacement sensor system using two fiber Bragg gratings (FBGs). The magnetic-scale-combined FBGs allow the exploration of random position. The sinusoidal function variations are displayed by two detectors with a phase difference of 90 deg, and the optimal magnetic gap is explored through numerical simulations. The feasibility of the method is demonstrated in experiments that show the sinusoidal relation between center wavelength shifts with the linear displacement. Results showed that the amplitudes of the tensile-compressive load were 446.1 µÏµ and 434.7 µÏµ, respectively, with linearity of 0.998 and 0.999 at 1.5 mm between the detector and the magnetic scale. These results demonstrate that the sensors can realize non-contact, temperature-independent and full-range measurement.

Phase demodulation method in phase-sensitive OTDR without coherent detection.

A phase demodulation method specially developed for direct detection φ-OTDR is proposed and demonstrated. It is the only method to date that can be used for phase demodulation based on pure direct detection system. As a result, this method greatly simplifies the system configuration and lowers the cost. It works by firstly deriving a pair of orthogonal signals from the single-channel intensity and then realizing phase demodulation by means of IQ demodulation. Different forms of PZT induced vibration are applied to the fiber and the phase is correctly demodulated in each case. The experiment results show that this method can effectively perform phase demodulation with extremely simple system configuration.

A Small Leak Detection Method Based on VMD Adaptive De-Noising and Ambiguity Correlation Classification Intended for Natural Gas Pipelines.

In this study, a small leak detection method based on variational mode decomposition (VMD) and ambiguity correlation classification (ACC) is proposed. The signals acquired from sensors were decomposed using the VMD, and numerous components were obtained. According to the probability density function (PDF), an adaptive de-noising algorithm based on VMD is proposed for noise component processing and de-noised components reconstruction. Furthermore, the ambiguity function image was employed for analysis of the reconstructed signals. Based on the correlation coefficient, ACC is proposed to detect the small leak of pipeline. The analysis of pipeline leakage signals, using 1 mm and 2 mm leaks, has shown that proposed detection method can detect a small leak accurately and effectively. Moreover, the experimental results have shown that the proposed method achieved better performances than support vector machine (SVM) and back propagation neural network (BP) methods.

An Analytical Model for CMUTs with Square Multilayer Membranes Using the Ritz Method.

Capacitive micromachined ultrasonic transducer (CMUT) multilayer membrane plays an important role in the performance metrics including the transmitting efficiency and the receiving sensitivity. However, there are few studies of the multilayer membranes. Some analytical models simplify the multilayer membrane as monolayer, which results in inaccuracies. This paper presents a new analytical model for CMUTs with multilayer membranes, which can rapidly and accurately predict static deflection and response frequency of the multilayer membrane under external pressures. The derivation is based on the Ritz method and Hamilton's principle. The mathematical relationships between the external pressure, static deflection, and response frequency are obtained. Relevant residual stress compensation method is derived. The model has been verified for three-layer and double-layer CMUT membranes by comparing its results with finite element method (FEM) simulations, experimental data, and other monolayer models that treat CMUTs as monolayer plates/membranes. For three-layer CMUT membranes, the relative errors are ranging from 0.71%⁻3.51% for the static deflection profiles, and 0.35%⁻4.96% for the response frequencies, respectively. For the double-layer CMUT membrane, the relative error with residual stress compensation is 4.14% for the central deflection, and -1.17% for the response frequencies, respectively. This proposed analytical model can serve as a reliable reference and an accurate tool for CMUT design and optimization.

A Long Distance Phase-Sensitive Optical Time Domain Reflectometer with Simple Structure and High Locating Accuracy.

A phase-sensitive optical time domain reflectometer (Φ-OTDR) can be used for pipeline security. However, the sensing distance (less than 20 km) of traditional Φ-OTDR is too short for the needs of typical oil and gas pipeline monitoring applications (30-50 km). A simple structure Φ-OTDR system utilizing long pulse, balanced amplified detector and heterodyne detection is proposed in this paper and the sensing range is thereby increased to 60 km. Through analyzing the sensing principle of Φ-OTDR, a novel locating strategy is proposed to maintain the locating accuracy at a few meters when a long pulse (5 µs) is used. The increased pulse width deteriorates the time series of each sensing point seriously. In order to eliminate the deterioration, a data processing technique combining wavelet and empirical mode decomposition is applied in this system. The experiment results show that the sensing distance can be increased to 60 km and the locating accuracy is maintained at 6.8 m.

Recognition of a Phase-Sensitivity OTDR Sensing System Based on Morphologic Feature Extraction.

This paper proposes a novel feature extraction method for intrusion event recognition within a phase-sensitive optical time-domain reflectometer (Φ-OTDR) sensing system. Feature extraction of time domain signals in these systems is time-consuming and may lead to inaccuracies due to noise disturbances. The recognition accuracy and speed of current systems cannot meet the requirements of Φ-OTDR online vibration monitoring systems. In the method proposed in this paper, the time-space domain signal is used for feature extraction instead of the time domain signal. Feature vectors are obtained from morphologic features of time-space domain signals. A scatter matrix is calculated for the feature selection. Experiments show that the feature extraction method proposed in this paper can greatly improve recognition accuracies, with a lower computation time than traditional methods, i.e., a recognition accuracy of 97.8% can be achieved with a recognition time of below 1 s, making it is very suitable for Φ-OTDR system online vibration monitoring.