Ultrasonic Phased Array Imaging Research Articles

Ultrasonic diffuse bulk wave passive array imaging of internal defects in a complex structure

Ultrasonic bulk wave inspection of defects in safety–critical components with complex external geometries, such as turbine blades is challenging. While ultrasonic phased array imaging can yield high-resolution subsurface images, a commercial phased array probe can hardly be mounted on irregular external boundaries to perform in-situ imaging. In fact, a component with irregular shapes, as a highly reverberant body, is capable of generating elastic random diffuse or coda wavefields. The diffuse wavefields can be utilized to reconstruct Green’s functions between any two passive receiving points. In this paper, an ultrasonic passive array imaging method using the diffuse reverberation resulting from complex boundaries is implemented to image internal defects. The method involves the utilization of active piezoelectric actuators to excite elastic diffuse waves within the component, which are received by a laser vibrometer scanning at multiple points. A passive full matrix capture (FMC) of array signals is extracted for defect imaging using the total focusing method. The proposed method is evaluated by the numerical simulations, and the effects of centre frequency, bandwidth, and source excitation methods on the imaging performance are investigated. An experiment using a turbine blade-like structure is conducted to further evaluate the imaging method.

Ultrasonic phased array imaging of multi-layered structures using full-matrix migration and normalized cross-correlation matching technique

Multi-layered structures play a critical role in aerospace, automotive and electrical industries, so the non-destructive evaluation and maintenance of such structures must be accurate and rapid. The application of conventional ultrasonic phased array imaging methods is limited due to computational complexity, image quality and image size. In this paper, we proposed a cost-effective, high-quality imaging method that uses full-matrix migration total focus method (FM-TFM) and produces large-area scanned image with the aid of normalized cross-correlation (NCC) template matching technique. The FM-TFM method eliminated the need for iterative refraction point calculations by using full matrix migration extrapolation, and the optimization of NCC was also investigated in the study. The verification was divided into two parts, fixed transducer experiment and manual scanned experiment, to demonstrate the advantages of FM-TFM with improved SNR (22 % or greater) and one order of magnitude reduction in computational time when compared to ray tracing total focus method (RT-TFM) and NCC matching accuracy of multilayer specimen, respectively. The proposed method can help eliminate the need for costly scanning equipment and shows great potential for extension to other TFM-based approaches.

Large rectangular cross-section tunnel undercrossing urban road by micro pipe jacking and joint assembly structure (MPJ & JAS) method in soft soils

With the continuous construction of urban traffic roads, more and more new roads are cut off by existing roads to form “dead end roads”. There is an urgent need for a trenchless method suitable for urban ultra-shallow overburden to build the undercrossing tunnel. To solve this problem, this paper proposed the micro pipe jacking and joint assembly structure (MPJ & JAS) method, which has the characteristics of shallow burial depth, low cost, short construction time, flexible cross-section setting and high space utilization. The MPJ & JAS method construct a large cross-section tunnel through assembling small cross-section elements, quite different from traditional methods. Therefore, this paper designed a CT-shaped integrated joint, the mechanical performance of which was verified and clarified by tensile test. The bending test and finite element (FE) analysis proved the reliability of MPJ & JAS tunnel structure, and confirmed the structure performances such as the failure models, crack behaviors, load–deflection response and stress–strain distribution. Moreover, the influences of the steel plate thickness, concrete strength and shear connector spacing were determined by the FE analysis. On the basis of test results and reasonable assumptions, a theoretical design method considering the influence of the CT-shaped integrated joint was proposed, which can effectively predict the bending strength of the MPJ & JAS tunnel structure with an error of less than 10%. Finally, in view of the characteristics of the MPJ & JAS method, the suitable micro pipe jacking machine, soil reinforcement measure, hydraulic traction construction technology, high-precision guidance system and concrete construction quality detection method based on the phased array ultrasonic imaging technology were developed, supporting the accurate and efficient construction of the MPJ & JAS tunnel.

Ultrasonic Phased Array Imaging for Defects in Angle Blind Spots Based on the Solid Directivity Function

Ultrasonic Phased Array Imaging for Defects in Angle Blind Spots Based on the Solid Directivity Function

Single-Bit Reception with Coded Excitation for Lightweight Advanced Ultrasonic Imaging Systems.

The demand for an efficient and reliable ultrasonic phased array imaging system is not unique to a single industry. Today's imaging systems can be enhanced in a number of areas including; improving scanning and processing times, reducing data storage requirements, simplifying hardware and prolonging probe lifespan. In this work, it is shown that by combining the use of Coded Excitation with single-bit data capture, a number of these areas can be improved. Despite using single-bit receive data, resolution can be recovered through the coded excitation pulse compression process, and shown to produce high Signal-to-Noise Ratio (SNR) images of Phase Coherence Imaging (PCI) and Total Focusing Method (TFM) of tip diffraction in a carbon steel sample. Comparison with conventional single-cycle transmission pulses has shown that little imaging performance degradation is seen despite a significant reduction in data resolution and size. This has also been shown to be effective at low excitation voltages with gain compensation due to the obsolescence of signal saturation concerns when considering single-bit receive data. The ability to compute high-resolution ultrasonic images from low-resolution input data at low transmission voltages has important implications for data compression, acquisition & imaging performance, operator safety and hardware simplification for ultrasonic imaging systems across industrial and medical fields.

Discretized tensor-based model of total focusing method: A sparse regularization approach for enhanced ultrasonic phased array imaging

The total focusing method (TFM) is considered as the standard in ultrasonic phased array imaging and plays a vital role in industrial non-destructive testing (NDT). By utilizing the full matrix capture (FMC) dataset, the TFM can focus on every point within the specified imaging region, and is more accurate than the traditional ultrasonic phased array imaging methods. However, the TFM is essentially a delay and sum technique that often operates linearly on the time-domain signals and takes no prior information into account, so its image quality remains inadequate when dealing with defects in close proximity or scattering materials. To address this problem, this paper formulates the imaging principle of the TFM as a Boolean matrix and establishes the discretized tensor-based model. Subsequently, the model is addressed by employing the sparse regularization strategy, taking into some characteristics of industrial NDT. Regarding the solution algorithm, due to the generation of negative values by the fast iterative shrinkage threshold algorithm (FISTA), this paper introduces the rectified linear unit (ReLU) function as a non-negative constraint and presents a dedicated solution algorithm (ReLU-FISTA) for acquiring detection results. Through verification of simulation and experiment, the proposed approach exhibits superior capabilities of defect characterization and noise suppression when compared to the TFM, leading to substantial enhancements in image quality.

Automated quantification of small defects in ultrasonic phased array imaging using AWGA-gcForest algorithm

ABSTRACT The imaging quality of ultrasonic phased array technology significantly affects the quantification of small defects inside metals. Moreover, traditional manual evaluation methods require a substantial amount of manpower and time, and they are easily influenced by subjective factors. To mitigate the impact of imaging quality on the automated quantification of defects, this study proposes an improved gcForest algorithm (AWGA-gcForest, Adaptive window genetic algorithm- gcForest). Firstly, the acquired ultrasonic full matrix data from the phased array is processed using full focusing A-scan technique. Additionally, a window averaging weighting method is introduced for ultrasound signal processing to eliminate the interference from incident waves and backwall echoes. Subsequently, a multi-scale adaptive sliding window adjustment strategy based on Mean Absolute Deviation (MAD) is employed to reduce the computational time complexity of the gcForest algorithm. Furthermore, a weighted approach optimised with a genetic algorithm is utilised in the cascade forest to improve the classification accuracy and generalisation capability. Experimental results demonstrate that the proposed method achieves an accuracy of 97.50%, precision of 97.26%, recall rate of 96.63%, and F1 score of 96.92, exhibiting higher detection accuracy compared to other models while also reducing time costs.

A multiscale residual U-net architecture for super-resolution ultrasonic phased array imaging from full matrix capture data.

Ultrasonic phased array imaging using full-matrix capture (FMC) has raised great interest among various communities, including the nondestructive testing community, as it makes full use of the echo space to provide preferable visualization performance of inhomogeneities. The conventional way of FMC data postprocessing for imaging is through beamforming approaches, such as delay-and-sum, which suffers from limited imaging resolution and contrast-to-noise ratio. To tackle these difficulties, we propose a deep learning (DL)-based image forming approach, termed FMC-Net, to reconstruct high-quality ultrasonic images directly from FMC data. Benefitting from the remarkable capability of DL to approximate nonlinear mapping, the developed FMC-Net automatically models the underlying nonlinear wave-matter interactions; thus, it is trained end-to-end to link the FMC data to the spatial distribution of the acoustic scattering coefficient of the inspected object. Specifically, the FMC-Net is an encoder-decoder architecture composed of multiscale residual modules that make local perception at different scales for the transmitter-receiver pair combinations in the FMC data. We numerically and experimentally compared the DL imaging results to the total focusing method and wavenumber algorithm and demonstrated that the proposed FMC-Net remarkably outperforms conventional methods in terms of exceeding resolution limit and visualizing subwavelength defects. It is expected that the proposed DL approach can benefit a variety of ultrasonic array imaging applications.

Ultrasonic phased array imaging of gas evolution in a lithium-ion battery

Ultrasonic phased array imaging of gas evolution in a lithium-ion battery

Ultrasonic defect detection of high-density polyethylene pipe materials using FIR filtering and block-wise singular value decomposition

Condition monitoring of high-density polyethylene (HDPE) pipes used for fluid and gas transfer is important for the safety of energy conservation and the environment. Ultrasonic phased array imaging methods provide a solution to detect and assess defects in HDPE pipes. However, ultrasonic bulk waves propagating in these viscoelastic media are strongly attenuated, resulting in reduced signal amplitude. In this study, a linear-phase Finite Impulse Response (FIR) filter is used to remove unwanted frequency components from the measured ultrasonic signals to improve the signal-to-noise ratio before applying the imaging algorithm of the total focusing method (TFM). Building upon this, a block-wise singular value decomposition (SVD) technique, which can adaptively determine the singular value cutoff threshold based on each block in the whole TFM image, is used to enhance the obtained TFM image quality. The performance of the combination of FIR filtering and block-wise SVD technique is validated by experimental data of HDPE pipe materials. Results demonstrate that the proposed approach generates good images to provide the detection and characterization of side-drilled holes in HDPE pipe materials.

Anisotropy Corrected FMC/TFM Based Phased Array Ultrasonic Imaging in an Austenitic Buttering Layer

For the narrow gap dissimilar weld between a ferritic steel and a nickel base superalloy, a nickel base alloy buttering layer is deposited on the ferritic steel side as an intermediate layer. The bonding between the buttering layer and the ferritic steel is required to be inspected from the buttering layer side. The buttering layer exhibits very high elastic anisotropy due to elongated columnar grains with preferred orientations. In this paper, the effect of elastic anisotropy on the phased array ultrasonic imaging of defects in the buttering layer is demonstrated for data acquired in full matrix capture (FMC) mode and reconstructed with the total focusing method (TFM). The anisotropy in the buttering layer leads to distorted flaw images, which limits the lateral resolution and defect detection sensitivity. Angle-dependent ultrasonic velocity measured in through-transmission FMC mode has been used for processing the FMC data to obtain high-resolution TFM images with improved sensitivity. The velocity values used are in line with the grain orientations observed by electron-backscatter diffraction (EBSD) studies. Further, an alternate approach is also proposed to obtain a TFM image with improved resolution using a suitable isotropic velocity. The approach can be implemented in any commercial phased array ultrasonic system having the FMC-TFM feature.

Research Progress in Nonlinear Ultrasonic Testing for Early Damage in Metal Materials

There are some limitations when conventional ultrasonic testing methods are used for testing early damage in metal parts. With the continuous development of acoustics and materials science, nonlinear ultrasonic nondestructive testing technology has been used for testing of early damage in metal materials. In order to better understand the basic theory and research progress of the nonlinear ultrasonic testing technology, the classical nonlinear ultrasonic theoretical models, including the dislocation monopole model, dislocation dipole model, precipitate-dislocation pinning model, and contact nonlinear ultrasonic theory-microcrack model, are analyzed in depth. This paper introduces the application and research progress of nonlinear ultrasonic detection technology, which is derived from different acoustic nonlinear effects, such as higher harmonic, wave mixing and modulation, sub-harmonic, resonance frequency spectrum analysis, and non-linear ultrasonic phased array imaging. The key technologies and problems are summarized to provide a reference for the further development and promotion of nonlinear ultrasonic non-destructive testing technology.

Ultrasonic Phased Array Imaging Approach Using Omni-Directional Velocity Correction for Quantitative Evaluation of Delamination in Composite Structure.

The ultrasonic detectability of buried defects within composite materials is dependent on the anisotropy of the composite material by which the propagation property of acoustic wave in each direction is variably affected. In this study, the characteristics of acoustic waves propagating in different directions for composite materials are explored based on the full matrix capture (FMC) data using an ultrasonic phased array. The elastic constant of multidirectional carbon fiber reinforced plastic (CFRP) laminate is first derived based on the genetic algorithm. The characteristics of transmitted and reflected waves in higher angles are predicted by implementing the Christoffel equation, and the focal law used in post-processing of FMC data can be optimized accordingly. The imaging results of the total focusing method (TFM) using the improved focal law are compared with the results of the conventional TFM. The results suggest that the optimized TFM can effectively characterize the defect by reducing the background noise. Furthermore, since it is impractical to theoretically correct angle-dependent velocity for in situ inspection, a linear extrapolation method based on the experimentally measurable velocity at low angles is proposed to estimate the velocity profile at higher angles. The imaging results using the fast extrapolated velocity profile is then compared with the theoretical, and it has been demonstrated that while the difference between the images using the theoretical focal law and the linearly extrapolated one is barely visible, the later one is overwhelmingly advantageous to be realiszd for engineering practices.

Secondary Interface Echoes Suppression for Immersion Ultrasonic Imaging Based on Phase Circular Statistics Vector.

Immersion ultrasonic phased array imaging technology offers great advantages, particularly in coupling and automatic detection of industrial non-destructive testing (NDT). To suppress the influence of secondary interface echoes in the immersion ultrasonic phased array imaging, a novel phase circular statistics vector (PCSV) weighting method is proposed in this paper. Firstly, the PCSV factor matrix is established according to the phase consistency of the echo signals. Secondly, due to the higher phase coherence of the defect echo, the PCSV factor matrix is used to weight the TFM image to suppress the secondary interface echo. The result shows the secondary interface echoes are effectively suppressed in the total focusing method (TFM) image on a 0~40 dB scale. It is also shown that PCSV weighting could not only suppress the secondary interface echoes but also improved the image quality in terms of SNR and lateral resolution by comparing with traditional TFM.

High signal-to-noise-ratio ultrasonic imaging of crack defects in particles filled composite explosives

<sec>Polymer bonded explosive (PBX) is a kind of composite material with highly filled molding explosive particles (normally more than 95%) and a small quantity of binders (less than 5%). The effective detection of internal cracks in PBX is of great significance in evaluating structural integrity and safety reliability.</sec><sec>Ultrasonic phased array detection and imaging methods show great advantages and potential in detecting crack defects. But acoustic test results indicate that the PBX has unique characteristics with low longitudinal wave velocity (～3000 m·s<sup>–1</sup>) and strong attenuation (attenuation coefficient ～400 dB·m<sup>–1</sup> for 2.5 MHz ultrasound). When the defect is imaged by traditional ultrasonic total focusing method (TFM), the structural noises at the boundaries between particles lead to low signal-to-noise ratio (SNR) in the FMC signals and strong background noise in reconstructed image, which will disturb the detection of cracks.</sec><sec>To realize the high SNR imaging of crack defects in PBX, an ultrasonic imaging algorithm based on baseband nonlinear synthetic focusing (BB-NSF) is proposed. By utilizing the spatial coherence of the received signals in full matrix capture (FMC) data, the pixel intensity at defect position can be enhanced while the background noise can be drastically weakened. The delay rule of the algorithm is modified according to the characteristics of PBX surface configuration. In this way, the high SNR imaging of crack defects with different orientations of PBX surface configuration is realized, and the quality of the reconstructed images is compared and evaluated quantitatively. Meanwhile, the base band transformation in calculation process optimization could significantly reduce calculation burden and increase imaging efficiency.</sec><sec>Experimental results show that the proposed algorithm can effectively suppress background noise and significantly improve the ability to detect the PBX cracks. The effective suppression to background noise makes the defect more highlighting and distinguished easily. For the BB-NSF algorithm, spatial coherence coefficient <i>p</i> is a crucial parameter used for dynamically regulating the SNR of reconstructed image. When <i>p</i> value is more than 2.0, the SNR of the ultrasonic reconstructed image of PBX crack defect is improved by more than 10 dB compared with that of the traditional linear synthetic focusing imaging. With the increase of <i>p</i> value, the SNR is further improved, while the calculation efficiency for a single image is almost kept stable. Moreover, the increase of SNR to some extent will improve the far-field detect capability.</sec><sec>Besides, with the BB-NSF algorithm, flexible transducer inhibits different imaging characteristics of for cracks with different orientations and depths in curved PBX specimens. For defects with large orientation angle and buried depth, the tip, root and shape of cracks can be completely present. For defects with small orientation angle and buried depth, part of shape and contour features will be lost.</sec><sec>In conclusion, the BB-NSF algorithm shows the advantage of high SNR and calculation efficiency in imaging PBX cracks, and exhibits great application prospect in imaging internal defects of other strongly attenuated composites.</sec>

Phased array ultrasonic imaging and characterization of adhesive bonding between thermoplastic composites aided by machine learning

ABSTRACT The testing and evaluation of adhesive bonding quality between thermoplastics are crucial for structural integrity. This article presents the use of phased array ultrasonic testing (PAUT) method to characterise the adhesive interface between thermoplastic composites. Samples with three different bond conditions: control, bad and mid-level were fabricated and tested using PAUT. A damage index (DI) based classification framework aided by machine learning (ML) algorithm is proposed to classify different adhesion conditions. A set of 18 physics-based damage indices were extracted from each PAUT image for quantitative characterisation. ML algorithms were developed to build a non-linear mapping that correlates the input DIs with the output sample types to address the classification problem. The experimental results show that support vector machine (SVM) performs better than other ML algorithms with classification accuracy greater than 95%, and the defined DIs can differentiate among bad, mid-level, and control samples.

Adaptive optimisation of multi-aperture ultrasonic phased array imaging for increased inspection speeds of wind turbine blade composite panels

Ultrasonic phased array testing is a commonly used inspection modality in a range of non-destructive testing (NDT) fields. The recent rapid growth in demand for wind turbine installations means that blade manufacturers must address any potential NDT bottlenecks. Multi-aperture (MA) beamforming has previously been shown to increase frame rates, and hence inspection speed, when compared to traditional linear beamforming, in both NDT as well as medical applications.In this work an adaptive MA and spacing concept is presented to autonomously optimise the MA focal laws for the sample in question as well as a critical defect size. For this, full-matrix capture (FMC) data from a calibration sample, designed specifically for the target defect size and spacing, is used to drive the resultant optimised inspection scenario. A 6.7-fold increase in scanning speed with no degradation in resolution or defect sizing accuracy is reported. Three inspection scenarios are presented using firstly linear beamforming at 3.0 mms−1 and 22.0 mms−1 and finally MA beamforming at 22.0 mms−1. Resolutions of 0.8, 5.4 and 0.8 mm in the scan axis are recorded and consequently the optimum scenario, allowing for high resolution at the higher scanning speed, is presented. The concept and process are verified and validated by C-scan inspections of a carbon fibre re-enforced plastic (CFRP) sample, at varying inspection parameters, commonly used in high-power blade construction.

Ultrasonic pseudo-color imaging in strongly attenuating materials with Filtered-Delay Multiply And Sum nonlinear beamforming

To detect flaws in strongly attenuating materials, we propose an ultrasonic phased array imaging method that combines Filtered-Delay Multiply And Sum (F-DMAS) nonlinear beamforming algorithm with pseudo-color technique. Based on the spatial coherence of signals, three filters with different frequency ranges are selected to reconstruct F-DMAS images from the full matrix capture (FMC) data. Then, three channels of F-DMAS images are combined with the RGB color model to obtain the pseudo-color image. Finally, an automatic flaw extraction algorithm is developed using the techniques of color image segmentation, data fusion, and edge detection. Experiments are performed on samples of polymer bonded explosives with side drilled holes. The results show that the proposed method has significant advantages over the linear beamformed Total Focusing Method (TFM) in terms of signal-to-noise ratio, detection ability, and visual presentation of flaws.

Research on Fast Ultrasonic Phased Array Imaging of High-performance Polymer Injection Molded Components

Research on Fast Ultrasonic Phased Array Imaging of High-performance Polymer Injection Molded Components

Development of Low-Frequency Phased Array for Imaging Defects in Concrete Structures.

The nondestructive inspection of concrete structures is indispensable for ensuring the safety and reliability of aging infrastructures. Ultrasonic waves having a frequency of tens of kHz are frequently used to reduce the scattering attenuation due to coarse aggregates. Such low frequencies enable the measurement of the thickness of concrete structures and detection of layer-type defects, such as delamination, whereas it causes a lack of sensitivity to crack-type defects. In this paper, to realize the ultrasonic phased array (PA) imaging of crack-type defects, we fabricated a low-frequency (LF) array transducer with a center frequency of hundreds of kHz. To avoid the crosstalk between piezoelectric elements and dampen the vibration of each element, we adopted soft lead zirconate titanate (soft PZT) with a low mechanical quality factor. Subsequently, we optimized the geometry of each piezoelectric element using a finite element method to generate a short pulse. After validating the design in a fundamental experiment using a single-element transducer, we fabricated a 32-element array transducer with a center frequency of 350 kHz. To show the imaging capability of the LF array transducer, we applied it to a concrete specimen with a delamination. As a result, the PA with the LF array transducer clearly visualized the delamination, which could not be visualized using the PA with a 2.5 MHz array transducer. Furthermore, we applied it to a more challenging defect, a slit, which is sometimes used to simulate crack-type defects. As a result, the PA with the LF array transducer clearly visualized a slit of 1 mm width and 40 mm height in a concrete specimen. Thus, we demonstrated the usefulness of the LF array transducer for inspecting crack-type defects.