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

This study introduces a wave-based Total Focusing Method (TFM) for ultrasonic phased array inspection, incorporating pre-recorded Time-of-Flight (ToF) values from EFIT simulations.By accurately modeling real wave propagation paths, this approach improves spatial resolution and reduces imaging artifacts.Experimental results from aluminum specimens with side-drilled holes (SDHs) demonstrate the method's superiority over conventional geometric-based TFM.

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

An ultrasonic phased array imaging system is provided which includes a normal mode and an adaptive mode of operation. The adaptive mode adjusts the delay associated with each element in the transducer such that the average image brightness of the region of interest is maximized. A motion detector is provided for determining when the transducer has been moved a distance sufficient to render the previous adaptive measurements possibly invalid whereupon the system automatically reenters the normal mode. A method of operating the ultrasonic phased array imaging system is also provided.

Low-frequency ultrasonic array imaging for detecting concrete structural defects in blind zones

Ultrasonic arrays have been widely employed in industrial applications because of their ability to perform quick inspections for detection and characterization of flaws. The total focusing method (TFM) is an advanced ultrasonic imaging technique that utilizes the full matrix capture (FMC) data of the phased array elements to generate a high-resolution image by focusing on every image pixel in both transmission and reception. In this work, the time of flight framework involved for the TFM post-processing is illustrated for an angular wedge configuration. Further, the TFM algorithm is extended for imaging using multiple direct and half-skip wave modes by taking into account the wave mode conversions in the specimen. The implications of the mode conversions on the TFM images are analyzed, and the challenges posed on the TFM, specific to weld inspection, are explained in detail. In this work, experimental studies are performed on weld specimens with five common weld defects using the TFM algorithm. FMC data is acquired from the ultrasonic instrument and is post-processed to get the TFM images. The TFM results of weld defects show high resolution, better defect detectability, and easy visualization of defects compared to phased array sector scan images.KeywordsUltrasonic arraysFull matrix captureTotal focusing methodAngular wedgeWeld inspection

Phased array ultrasonic total focusing method (TFM) imaging has attracted much attention due to its high detection image resolution and large dynamic range. However, due to the small emission energy of its single element, the echo signal is weak and susceptible to noise interference, resulting in a relatively low signal-to-noise ratio (SNR). Especially when detecting high sound attenuation carbon fiber reinforced polymer (CFRP) composites, the signal amplitude can decrease with depth to a level lower than the electronic noise introduced by the signal acquisition system. To solve this problem, a new imaging algorithm was proposed that combines the Golay code excitation using linear frequency modulation (LFM) signal as the carrier with the TFM algorithm (LFM-Golay TFM). Meanwhile, in order to further overcome the disadvantage of the LFM-Golay code encoding excitation method requiring two excitations, an AB code encoding excitation conversion factor was introduced, two sets of echo data were obtained through processing single excitation, TFM imaging based on LFM-Golay code single excitation (IMP-LFM-Golay TFM) is realized. Simulation and experimental studies were conducted to compare the TFM imaging performance of single-pulse excitation (Pulse TFM), Barker coding excitation (Barker TFM), LFM excitation (LFM TFM), and improved LFM-Golay coding excitation. The results show that IMP-LFM-Golay TFM has the best SNR, axial resolution, and depth resolution.

Additive manufacturing (AM) enables the fabrication of complex components with high geometric freedom, but it can introduce near-surface flaws due to rapid solidification, resulting in porosity and lack of fusion. In addition, localized melting and steep thermal gradients favor the formation of micro-cracks. Conventional ultrasonic techniques have shortcomings in detecting such flaws because of front-wall interference, further affected by surface roughness and anisotropy. This study evaluates the effectiveness of the Total Focusing Method (TFM), an advanced ultrasonic imaging technique implemented in Full Matrix Capture (FMC), for near-surface flaw detection in Laser Powder Bed Fusion (LPBF) AM components. To assess TFM performance, subsurface side-drilled holes (SDHs) in AM Ti-5Al-5V-5Mo-3Cr (Ti-5553) material were used as the reference reflectors and compared with Phased Array Ultrasonic Testing (PAUT) under identical conditions. Results showed that TFM achieved higher spatial resolution and more reliable detection of shallow flaws, successfully detecting features as shallow as 0.40 ± 0.05 mm below the surface, whereas PAUT was limited to greater depths. These findings demonstrate TFM as a reliable non-destructive evaluation method for shallow flaws in AM parts, while contributing one of the first systematic comparative datasets of PAUT and TFM for shallow SDHs in LPBF titanium alloys.

The marriage of welding and Non-Destructive Testing (NDT) processes at the point of manufacture has enabled the detection and correction of defects during the welding process. This has demonstrated clear financial and production benefits by reducing weld rework and ensuring schedule certainty, however this is yet to be demonstrated for use with narrow-groove welding practises. Narrow-groove welds are notoriously difficult to inspect using traditional Phased Array Ultrasonic Testing (PAUT) techniques due to large thicknesses and the vertical nature of Lack-of-Sidewall Fusion (LOSWF) defects. This is further complicated by the presence of partially-filled weld geometries during in-process inspection, which cause geometric reflections which can mask or falsely indicate the presence of a defect. A solution to this is proposed in this work, by adapting a dual-tandem phased array imaging system for the imaging of LOSWF defects in a partial weld geometry. This considers a two array system utilising a phased array probe on each weld side, coupled with an advanced dual-aperture Full Matrix Capture (FMC) acquisition technique. Advanced multi-mode image processing algorithms such as the Total Focusing Method (TFM) and Phase Coherence Imaging (PCI), with adaptive delay law calculation, have shown high sensitivity to LOSWF defects in a mock partial weld geometry. Additionally, an adaptive Probe Centre Spacing (PCS) technique is defined for in-process inspection based on amplitude and phase coherence sensitivity in partial weld geometries, with the effects of partial weld reflections analysed and discussed. These results have demonstrated the effectiveness of a dual-tandem phased array approach to imagine LOSWF defects during the in-process inspection of narrow-gap welds.

The application of total focusing method (TFM) for imaging of Carbon fiber reinforced plastics (CFRP) with ultrasonic phased array is particularly challenging due to the layered structure and anisotropy of CFRP. To improve the TFM imaging performance, the precise knowledge of complex ultrasonic paths in anisotropic CFRP laminates should be obtained for accurate calculation of time of flights (TOFs), which makes the inspection process complicated and time-consuming. In this work, an adaptive TFM is developed for full-matrix imaging of CFRP laminates using ultrasonic phased array. Based on the acquired full matrix data, the elastic constants, including C 11, C 22, C 55, and C 13, can be directly derived using TOFs of A-scan signals. Based on the measured elastic constants, group velocity profiles of quasi-pressure (QP) wave were then calculated for different stacking sequences, from which the TOFs were corrected. To verify the effectiveness of proposed method, simulations and experiments are demonstrated on the CFRP laminates with different stacking sequences. As a representative example, the delamination defects are showcased. Compared with isotropic TFM, the SNR of proposed method is increased by 10.2-18.0 dB. The simulated and experimental results agreed well with each other, indicating that the feasibility of proposed method in full matrix imaging of anisotropic CFRPs.

Plane wave imaging (PWI) is attracting more attention in industrial nondestructive testing and evaluation (NDT&E). To further improve imaging quality and reduce reconstruction time in ultrasonic imaging with a limited active aperture, an optimized PWI algorithm was proposed for rapid ultrasonic inspection, with the comparison of the total focusing method (TFM). The effective area of plane waves and the space weighting factor were defined in order to balance the amplitude of the imaging area. Experiments were carried out to contrast the image quality, with great agreement to the simulation results. Compared with TFM imaging, the space-optimized PWI algorithm demonstrated a wider dynamic detection range and a higher defects amplitude, where the maximum defect amplitude attenuation declined by 6.7 dB and average attenuation on 12 defects decreased by 3.1 dB. In addition, the effects of plane wave numbers on attenuation and reconstruction time were focused on, achieving more than 10 times reduction of reconstruction times over TFM.

Using ultrasonic arrays to detect and evaluate Surface Breaking Cracks (SBCs) is important in the Non-destructive Evaluation (NDE) field. It can provide early stage detection of failure and useful information for component integrity evaluation. The Full Matrix Capture (FMC) can achieve the maxim data from an ultrasonic array and the Total Focusing Method (TFM) is used for imaging. As a powerful method for crack characterisation, machined slots are usually used to examine and assess FMC/TFM methodology. In this paper, real SBCs are fabricated in 3-point bending specimens following ASTM standard E1820 and used to examine the performance of this ultrasonic imaging method. This approach is shown to work well in imaging and sizing of real fatigue cracks.

Ultrasonic phased array has the functions of ultrasonic array, 3D imaging, and defect multi-signal characterization. However, there are problems in current detection such as effective parameter setting and inconsistent identification standards for defect characteristic signals. Based on the principle of ultrasonic phased array imaging, the experimental research on the setting of effective parameters for concrete cavity defect detection is carried out in this paper. The results show that the selection of wave velocity and frequency is the key factor to improve the accuracy of 3D imaging. For 20mm concrete cavity, when the frequency is less than 25kHz, the system cannot detect defects. When the working frequency is increased to 45KHZ, the defect imaging accuracy is gradually improved. When the frequency is increased to 60kHZ, the detection accuracy is reduced. The ultrasonic shear wave velocity is in direct proportion to the detection imaging depth. When the difference between the actual wave velocity and the set wave velocity is 10%, the influence of the detection imaging depth is small. When the difference between the actual wave velocity and the set wave velocity is greater than 20%, the detection imaging depth has a great impact, and the difference between the defect position and the actual value is too large, which may cause the system to be unable to detect the existence of defects.

Real-time imaging, using ultrasound techniques, is a complex task in non-destructive evaluation. In this context, fast and precise control systems require design of specialized parallel architectures. Total focusing method (TFM) for ultrasound imaging has many advantages in terms of flexibility and accuracy in comparison to traditional imaging techniques. However, one major drawback is the high number of data acquisitions and computing requirements for this imaging technique. Due to those constraints, the TFM algorithm was earlier classified in the field of post-processing tasks. This paper describes a multi-FPGA architecture for real-time TFM imaging using the full matrix capture (FMC). In the acquisition process, data are acquired using a phased array and processed with synthetic focusing techniques such as the TFM algorithm. The FMC-TFM architecture consists of a set of interconnected FPGAs integrated on an embedded system. Initially, this imaging system was dedicated to data acquisition using a phased array. The algorithm was reviewed and partitioned to parallelize processing tasks on FPGAs. The architecture was entirely described using VHDL language, synthesized and implemented on a V5FX70T Xilinx FPGA for the control and high-level processing tasks and four V5SX95T Xilinx FPGAs for the acquisition and low-level processing tasks. The designed architecture performs real-time FMC-TFM imaging with a good characterization of defects.

Ultrasonic Non-Destructive Evaluation using Full Matrix Capture (FMC) and Total Focusing Method (TFM) is used for high resolution imaging as every pixel is in optimal focus. FMC excites one element in turn, so operates with lower transmitted energy compared to phased array beamforming. The energy at a reflector is further reduced by the broad directivity pattern of the single element. The large number of Tx/Rx A-scans that contribute to each pixel recover the Signal-to-Noise Ratio (SNR) in the final TFM image. Maintaining this in the presence of attenuating materials is a challenge because relevant information in each A-scan signal is buried in the thermal noise, and the TFM process assumes no quantization effects in the Analogue-to-Digital Converters (ADCs) in each receiver. In-process inspection during Additive Manufacturing (AM) requires ultrasonic array sensors that can tolerate high temperatures, scan over rough surfaces and leave no residue. Dry-coupled wheel probes are a solution, but the tire rubbers are often highly attenuating, causing a problem for FMC+TFM needed to adapt the focus through the rough surface. Common approaches to maintain the SNR are to drop the frequency or to average over multiple transmissions, but these compromise resolution and acquisition rate respectively. In this paper, the application of coded excitation to maintain the SNR in the presence of high signal attenuation is explored.

With the development of ultrasonic technology, ultrasonic wave plays an increasingly important role in the field of nondestructive testing. Among all kinds of ultrasonic nondestructive testing technologie, ultrasonic phased array is widely used because of its high accuracy and flexibility. However, due to the existence of rayleigh limit, ordinary ultrasonic phased array technology cannot recover the space frequency greater than 2K, so it is impossible to achieve the resolution less than half of the wavelength of the super-resolution. In this paper, we introduce a method to realize super resolution imaging in multi-band phased array.In this method, the damage is detected by multiple phased arrays, and the received signals are processed by specific algorithms to obtain super-resolution imaging. The signal is excited by M exciter and then received by N receiver. The total signal can form an M*N matrix. After singular value decomposition of the collected signal matrix,T significant eigenvalues can be obtained. The T significant eigenvalues represent the number of injuries. The singular vector after singular value decomposition contains the information of noise space. The number of eigenvalues in the signal space is the number of damage. Using the randomness of noise subspace, special algorithm can be used to restore the spatial frequency greater than 2K to achieve super-resolution imaging.The more elements in this method, the more accurate and complicated it is. As long as the smallest value of M and N is greater than the number of injuries, each injury can be successfully distinguished under super resolution. Therefore, the appropriate number of matrix elements should be selected for different damages.