Ultrasonic Testing Research Articles

LNG storage tanks 9% Ni steel weld inspection via phased-coherent TFM and SVD enhancement

ABSTRACT 9% Ni steel is commonly utilised in liquefied natural gas storage tanks due to its strong resistance to corrosion and oxidation. However, the welds in these tanks are prone to serious defects, necessitating thorough non-destructive testing. Unfortunately, when inspecting nickel-based alloy welds using phased array ultrasonic testing (PAUT) technology the ultrasonic waves are scattered and attenuated because of the coarse columnar grains. To address this challenge, this paper introduces a based on SVD enhancement directivity corrected circular coherence factor weighted TFM imaging algorithm (SVD-DC-CCF). Initially, the CCF matrix is corrected by the directivity and energy attenuation compensation factors, then weighted with the TFM pixel point amplitude. Subsequently, the weighted amplitude matrix undergoes singular value decomposition (SVD), followed by the establishment of an enhancement factor to reconstruct the amplitude matrix. The proposed algorithm is evaluated through experiments on three types of defects in a 30.0 mm thick 9% Ni steel T-shaped fillet weld test block. Results demonstrate superior signal-to-noise ratio (SNR) and enhanced image resolution. Compared to TFM results, the SNR increases by 4.97 dB, 4.25 dB, and 4.96 dB, respectively, while the array performance index (API) decreases by 9.80%, 34.39%, and 22.22%, respectively.

Focused Electromagnetic Acoustic Transducers for Lamb Wave Inspection

Abstract Ultrasonic inspection of conductive samples can be performed using electromagnetic acoustic transducers (EMATs). These allow generation of guided waves, such as Lamb waves, in thin plates. Lamb waves are used for defect screening as they can travel long distances with relatively little attenuation. However, large wavelengths are used, which results in poor sensitivity to subwavelength sized defects. This work presents methods for using Lamb waves to detect smaller defects. Curved, geometrically focused EMATs were used to generate and detect Lamb waves in a 1 mm thick aluminum plate. The focal spot of these EMATs is investigated and the dependence of the focal spot dimensions and locations on the wavelength of the generation signal are presented. An array of geometrically focused detection EMATs was used to measure a 10×10×0.5mm square machined defect, simulating wall thinning. Perturbations in the pulse transmission in the region of the defect were detected, along with reflections, with each detector in the array sensitive to different defect features. B-scans and C-scans are presented utilizing these perturbations and reflections to locate, size, and image the machined defect. Analysis of data from the B-scan is shown to accurately size the defect width to within ±0.73mm. Very good agreement is shown between the C-scan images and the known location and orientation of the defect. Data fusion techniques are presented to combine data sets from different receiver EMATs and increase the defect detection capability, accuracy, and precision, with the potential for full defect sizing demonstrated.

Study on ultrasonic lamb wave testing technology of honeycomb sandwich structures

Abstract Honeycomb sandwich composite panels have complex structures, large sizes, many types of defects, and significant sound attenuation, which lead to low efficiency and poor sensitivity of ultrasonic non-destructive testing. In the study, a non-linear ultrasonic lamb wave testing technique for honeycomb sandwich composite panels is proposed. Firstly, the anisotropic propagation characteristics and modal structure of lamb waves in honeycomb sandwich composite panels are analyzed, and the lamb wave modes with non-linear ultrasonic accumulation are excited. Secondly, the data extraction method and imaging algorithm of non-linear ultrasonic lamb wave imaging testing are proposed. Finally, an enhanced imaging algorithm is proposed to improve image quality based on the sliding window algorithm. Based on the comparative analysis of air-coupled ultrasonic testing images and metallographic tests, it can be seen that non-linear ultrasonic lamb wave testing signals can be used to characterize the damage distribution characteristics of honeycomb sandwich composite panels, display debonding and weak debonding defects, and have the advantages of being able to perform on the same side testing and high efficiency, which can be used for non-destructive testing of honeycomb sandwich composite panels.

Influence of polyethylene pipe butt fusion welding in ultrasonic non-destructive testing

Abstract Butt fusion welding is a commonly used manufacturing method for polyethylene pipes. To investigate the influence of butt fusion welding on oblique ultrasonic wave in ultrasonic non-destructive testing, a numerical simulation model was established for polyethylene pipe with welding joints. Wave propagation in the polyethylene pipe was analysed, which showed that there exist longitudinal and shear waves propagating and their mode conversion. Detection signals of pipes with different defects and different acoustic attenuations were calculated. The special structure of welding joint was then modelled. Results show that the signal response declines with acoustic attenuation coefficient. Butt welding joints, especially the inner joints, would affect waves propagation. Finally, the welding process of polyethylene pipes was also simulated. The influence of cooling time was discussed, which indicated that insufficient cooling time would cause thermal residual stress and then alter the ultrasonic signal.

Ultrasonic evaluation of wire arc additively manufactured parts with heterogeneous microstructure

Abstract In Wire Arc Additive Manufacturing (WAAM) components manufactured by gas metal arc welding strategy, periodically alternating patterns of fine- and coarse-grained microstructures develop along the building direction, depending on the temperature evolution. Ultrasonic non-destructive evaluation relies on the scattering of waves from defects. In the material microstructure, ultrasound waves are also scattered at the grain boundaries as grain noise. The work presents a study on the influence of heterogeneous microstructure in WAAM on defect detectability during ultrasonic inspections. The study used a 2D finite element model to simulate ultrasound wave propagation in the material microstructure represented by a surface element from electron backscatter diffraction scans. Side-drilled holes were introduced in the material as defects. Phased array was used to perform full matrix capture and obtain ultrasound image through total focusing method, with dynamic focusing capability to inspect the heterogeneous microstructure. The study analysed the defect echoes and noises using the signal-to-noise ratio (SNR) to assess its defect detectability. While defects were well detected, the SNR values differ by 10% for defects at various positions along the building and transverse directions in the heterogeneous microstructure.

Signal de-noising based on ICEEMDAN for delamination detection by phased array ultrasonic testing

Abstract Aiming at the problem of clutter noise of inter-layer reflections that occurs in multilayer heterogeneous medium such as hybrid fibre composites during ultrasonic inspection, a signal de-noising method based on the improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) is proposed in this paper. In the method, the cross-correlation coefficient is utilized to identify the intrinsic mode function (IMF) that is related to raw ultrasonic signal. Particularly, the root mean square error (RMSE), as selection criterions, are employed conjunctively to sift the optimal IMF among selected decomposition signals. Hilbert transform is used to extract the envelope of the signal after removing the interlayer reflection noise. Experimental results show that, the proposed method can adaptively decompose the non-stationary ultrasonic signal into several IMFs with different spectrum so as to dealing with clutter noises. For delaminate detection by phased array ultrasonic testing for hybrid fibre composites, structural noises are significantly suppressed in the reconstructed signal that retains the distinct echo characteristics of a delaminated defect.

Ultrasonic imaging assisted by Phase Coherence and Synthetic Aperture Focusing Technology

Abstract B-Scan is widely applied in ultrasonic testing. However, the imaging quality is affected by noise and acoustic diffusion. This paper proposed a method combining synthetic aperture focusing technology (SAFT) and phase-coherent imaging (PCI) technology to improve image quality. In SAFT, a transducer at different positions is utilized to form an array, which represents a large aperture transducer to obtain high resolution. By constructing a weight matrix based on the phase of signals, PCI is used to modify the SAFT imaging, thus the signal-to-noise ratio is significantly improved. In this paper, finite element models were built and the corresponding simulations were carried out first. Then, the Hilbert transform was implemented to all the simulated echoes with artificial white noise. The amplitudes and phases were extracted, whilst the amplitudes were used to construct SAFT images. The phases were used to construct a coherent weight matrix. Finally, images of SAFT modified by phase-coherent matrix were reconstructed and compared with SAFT images and B-scan. It verifies that the SAFT-PCI method can improve the image effectively.

SM-GMVAE: an intelligent model for defect quantification evaluation based on few ultrasonic signals

The conventional defect quantification evaluation approaches based on machine learning requires massive amounts of labelled defect signals, which is expensive and time-consuming works. This paper proposed a novel Similarity Metric Gaussian Mixture Variational Auto-Encoder (SM-GMVAE) model, which enables quantify defect with few labelled defect signals. The SM-GMVAE model is designed based on few-shot learning, which includes two modules: feature extraction (FE) module and similarity metric (SM) module. The FE module is designed to extract the feature of defect signal via the Variational Auto-Encoder (VAE). The SM module is used to measure the similarity of two defect signals based on the Gaussian Mixture Model (GMM). Moreover, sparse filtering techniques are used to enhance the sparsity of the features in the SM module. To validate proposed model, some specimens with four various depth defects are designed and fabricated for ultrasonic non-destructive testing experiments. A dataset with defects of different depths is established to compare proposed model with other methods. Our method obtains state-of-the-art experimental results with few labelled defect signals. Different from many published papers, our model is trained with few labelled data, which is more close to engineering practical application than other evaluation model trained using large numbers of labelled data. In other words, the developed approach can realize more complex defect evaluation tasks (such as: size, location, shapes, etc) at very low data labelling cost.

Defect Recognition and Classification Using Ultrasonic Scattered Signals Based on Convolutional Neural Network

Abstract Carbon Fiber Reinforced Polymer (CFRP) is widely used in the aerospace, aircraft, and railway industries because of its remarkable advantages, such as its lightweight and high strength. Detecting and identifying defects in CFRP is crucial for ensuring its secure and efficient use. Ultrasonic non-destructive testing is one of the most practical and effective methods for defect detection and identification. The ultrasonic scattered signals of defects, which contain abundant defect feature information, are advantageous for defect recognition and classification. However, the anisotropy and inhomogeneity of CFRP, which lead to a low signal-to-noise ratio and poor image quality, pose challenges in flaw recognition. To address the issue, this paper proposes using Convolutional Neural Networks (CNN) methods for defect classification, which can adequately extract information from ultrasonic scattered signals directly. The scattering signals from various types of defects in CFRP, including the different sizes of holes and folds, were selected as inputs for CNN models. Different network models combining Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) with 1D-CNN were employed to classify and identify defect signals. To generate sufficient input sample signals, the data sets were further enlarged by incorporating noise into the original signals. The experimental results showed that using the 1D-LSTM-CNN and 1D-GRU-CNN network models can reduce computational resources while ensuring the accuracy of defect recognition.

Application of optical fiber distributed acoustic sensing system in ultrasonic detection

Abstract The optical fiber distributed acoustic sensing system can continuously detect acoustic signals along the optical fiber, with the characteristics of wide response frequency band, large capacity, anti-electromagnetic interference and so on. An ultra-sensitive distributed optical fiber acoustic sensing system (uDAS) was produced with a high response frequency up to 100 kHz and thousands of sensing points. The arrayed ultrasonic detection can be realized by the distributed characteristics of the system. For verifying its ultrasonic detection ability, it is applied to ultrasonic nondestructive testing of structural defects. 20 optical fiber ultrasonic detection units were constructed. Each one is a fiber ring with a diameter of about 1.5 cm and a length of 2 meters. Two cubic cement structures with a side length of 30 cm were manufactured for experiment, one of which had an artificial internal defect. The optical fiber array was attached to the surface of the cement structure, and the ultrasonic signal with a frequency of 40 kHz was excited at a single point on the opposite side. The ultrasonic propagation speed changes on account of the defects such as holes and loose texture in the propagation path. The defects in the structure are identified and located by analyzing the difference of arrival time of waves. It is expected that such sensing system could found important applications in structure defect detection.

Phased Array Ultrasonic Inspection of Composite Fuselage Panel

Abstract The composite fuselage panel is a crucial component in large civil aircraft, necessitating higher detection rates and efficiency. Phased array ultrasonic testing can enhance the efficiency and defect detection rate; however, it is essential to consider the structural characteristics of the fuselage to ensure reliable identification of design defects. Based on the material properties, structural features, and defect detection requirements of composite fuselage panels, a test block reflecting their characteristics was designed and fabricated with various prefabricated defects. Ultrasonic phased array method was employed for a series of testing parameter optimization experiments and defect detectability analysis. The detected flaws were quantitatively analyzed and compared with those obtained using conventional ultrasonic automatic scanning techniques to validate the effectiveness of the developed ultrasonic phased array method. The feasibility of utilizing phased array ultrasonics for nondestructive evaluation of wide-body airliner composite fuselage panels is confirmed.

Mechanical properties and damage characterization of 310S steel using laser ultrasonic inspection under extreme temperature condition

Abstract To evaluate the mechanical properties of 310S stainless steel under extreme working conditions, and realize the damage characterization function, in this study, the longitudinal wave and Rayleigh wave of materials are measured by the method of coaxial inspection on reverse surface and ipsilateral ectopic inspection, respectively, and surface cracks and internal voids are detected by the scanning laser source technology and transmission scanning detection, respectively. The detection methods are designed based on the energy distribution characteristics of Rayleigh wave and longitudinal waves in laser ultrasound. The laser ultrasonic detection systems coupled with a temperature loading device (high temperature: vacuum chamber; low temperature: refrigerating chamber) developed by the laboratory enable on-site monitoring of laser ultrasonic technology in harsh environments. Experimental results demonstrate that the error in mechanical properties (elastic modulus, shear modulus, Poisson ratio) is less than 5% over a wide temperature range (-180-1000°C). At 1000°C, surface cracks wider than 0.5mm and deeper than 1.9mm as well as internal hole defects larger than 1.0mm can be detected with an error rate below 5%.

Ultrasonic testing method for impeller brazing defects with refraction wave perpendicular to brazing surface and angle amplitude compensation

Abstract There are blind areas in ultrasonic brazing defect detection, due to the non-parallel brazing surface and outer surface for many components including impeller. In this paper an oblique incident ultrasonic testing method with a refraction wave perpendicular to brazing surface is proposed. Meanwhile, an incident angle amplitude compensation is implemented to decrease the influence of the defect echo amplitude difference caused by oblique incidence and unify the sensitivity of different scanning positions. The compensation curve based on the theoretical curve of echo energy at different incident angles is optimized with iteration of actual measured defect echo amplitude. In order to prove the need for ultrasonic testing method with a refraction wave perpendicular to brazing surface, bottom surface echo test for conical samples is operated. In addition, with the method proposed in this paper, scanning image of impeller sample with the same detection sensitivity is obtained successfully. Testing results suggest that in relation to old method with incident wave perpendicular to the outer surface, the method proposed in this paper can solve the blind area problem effectively.

Internal Quality Inspection and Characterization of Casting Billets Based on Ultrasonic Microscopy

Abstract For evaluating the internal quality of casting billets, the low-power experimental and metallographic methods have the disadvantages of the complex process, the small detection range and the destructive evaluation. In addition, the internal defects of the casting billet are analyzed by the one-dimensional waveform and two-dimensional image for the traditional ultrasonic testing, which can not describe directly the three-dimensional spatial information. Hence, a new method is proposed based on ultrasonic microscopy to detect and characterize the internal defection of the casting billet. In this paper, 42CrMo casting billet is regarded as objective, five sets of samples are fabricated by adjusting temperature gradient field and the number of presses. The ultrasonic sequence images of the present samples are achieved by using ultrasonic microscopy, and the spatial distributions, number, and sizes are obtained for the defects of the casting billet by reconstructing the three-dimensional appearance of microdefects to characterize the internal mass of the casting billet. Finally, the effective and accuracy of the proposed method are validated by using metallographic method.

Development of Phased Array Ultrasonic Testing System Using Distributed Architecture

Abstract With more rigorous requirements for reliability and safety of structures and materials, high resolution and fast imaging have been urgent needs of Phased Array Ultrasonic Testing (PAUT). In order to improve the detection resolution and efficiency of complex structures and materials such as ultra-thick carbon steel and honeycomb plate, a PAUT system is proposed in this paper. The system uses a distributed architecture, which not only divides hardware resources, improves system performance, but also is scalable. PA, single- and multi-channel conventional UT, and TOFD (Time Of Flight Diffraction) modalities are combined, and PA modality is carried by the fully parallel non-multiplexed 128 PE (Pulse Echo) electronics with independently adjustable emitting and receiving parameters. In addition, the ultrasound analog front-end circuit is designed using discrete devices, providing more powerful analog performance than integrated chips. GTX (Gigabit Transceiver) and PCIe (Peripheral Component Interconnect Express) are applied to high-speed data transmission, providing raw ultrasound data. Characterization and verification results indicate that the system is ideal for challenging inspections in many industries.

Assessment of Weld Microstructure Through Sound Velocity Measurements for Power Plant Applications

This research study employed an immersion-based micro-resolution ultrasonic velocity measurement technique (MUVT) to evaluate Grade 91 (9Cr-1Mo-V) steel welds. This process utilized a 20 MHz focused ultrasonic beam with a spot size of 250 µm, a 6 µm laser vibrometer spot size for detection, and an automated 3-axis raster scanner to accurately collect ultrasonic velocity data from two Grade 91 steel welds fabricated using cold metal transfer (CMT) and flux-cored arc welding (FCAW) processes. By analyzing the MUVT data, the Poisson’s ratio (υ) and modulus of elasticity (E), which are important mechanical properties for weldments, were calculated. The correlation between mechanical properties and ultrasonic velocity was examined. The results indicated that longitudinal ultrasonic velocity could effectively identify base metal, heat-affected zone (HAZ), and weld metal areas, showing a strong correlation with hardness. In particular, the distinctive V-shaped dip in velocity and hardness data across the HAZ areas of both samples highlighted changes in the microstructure of creep strength–enhanced ferritic steel welds. Importantly, the immersion-based MUVT demonstrated high accuracy in small sections of the weld, surpassing the conventional contact ultrasonic testing method in spatial resolution detection.

Research on Phased Array Ultrasonic Imaging Method Based on Time Reversal Theory

Abstract With the wide application of additive manufacturing components and composite materials, it is of great significance to detect defects with non-destructive testing methods in the material manufacturing process and in service. Due to the strong attenuation and inhomogeneity characteristics, it is inefficient and poor imaging results to detect its internal defects by conventional ultrasonic testing methods. To improve the detection accuracy, this paper proposes an improved imaging algorithm with time reversal-total focusing method (TR-TFM) imaging technology to improve the defects detection in strongly attenuating materials. The experimental results show that the amplitude of the defect signal is increased by 8.30 dB, and compared with total focusing method (TFM), the diameter of the detected defect with TR-TFM imaging is increased from 1.20 mm to 1.60 mm, which is more adjacent to the accurate size. Meanwhile, with the sparse matrix based on FMC data, TR-TFM could obtain the same image quality with the approximate time of TFM imaging.

Bridging the Gap: Correlating Ultrasonically Quantified BVID with the Compressive Strength of CFRP Composites

ABSTRACT Carbon fiber laminates are susceptible to impact damage due to the lack of fibers in the direction of impact. Often such damage can be difficult to find with visual assessment, prompting the need for detection via nondestructive testing techniques. This study quantifies the ultrasonically characterized impact damage diameters in 22 layered CFRP samples from 16 J, 18 J, 20 J, 22 J, and 24 J impact energies. These energies result in damage often defined as barely visible impact damage. This study utilizes x-ray computed tomography as a baseline to verify the results of the ultrasonic testing. Compression after impact test measurements are used in this study to find the ultimate compressive residual strength of the impacted carbon fiber laminates and to investigate the negative correlation between impact energy and residual mechanical properties of the damaged carbon fiber laminates. Many studies focus on the characterization of impact damage from various impact energies and setups via ultrasonic testing or, separately, the effect of the impact setups on the residual strength of the composite. This study strengthens the bridge between the barely visible impact damage quantified via ultrasonic testing and the residual compressive strength of the affected composite. Overall, this paper offers further insights into the relationship between internal damage size obtained using ultrasonic testing and correlates the characterized internal damage geometry to the resultant compressive strength reduction, providing a path for future studies in predictive modeling of the residual strength after impact.

Influence of aggregate size on relative velocity change of high-frequency ultrasound in progress of concrete curing

Previous research revealed that wave interferometry can be more effective than existing ultrasonic techniques in monitoring the strength development of early-age concrete. To improve its accuracy, this study aims to examine the impact of aggregate size on the relative velocity change of high-frequency ultrasound during the concrete curing process. Concrete cubic specimens with 150 mm sides were prepared using two different maximum aggregate sizes, 4.75 mm and 20 mm. These specimens were subjected to water curing for the first 28 days, followed by air curing until 150 days. Ultrasonic tests employing a 1 MHz frequency were performed throughout the curing process, and the measured signals were analyzed by applying wave interferometry techniques. The test results suggest that the influence of aggregate size was evident in both the initial water curing and the subsequent air curing. During the initial curing, the specimen with larger aggregates exhibited a greater increase in relative velocity change. Thereafter, the velocity change decreased during the subsequent air curing in both specimens. Based on the results, the correlation between relative compressive strength and relative velocity change was proposed considering the maximum aggregate size. The findings offer insights into the use of ultrasonic methods to evaluate the characteristics of early-age concrete.

FalconScan: A hybrid UAV-crawler system for NDT inspection of elevated pipes in industrial plants

Periodic non-destructive testing (NDT) of pipes and tanks is vital in industrial plants, such as Oil & Gas facilities, to proactively detect defects and corrosion before leaks and forced shutdowns occur. This paper presents a hybrid system, consisting of a UAV and a crawler, which enables detailed contact-based inspection of elevated pipes, in pursuit of eliminating the need for dangerous scaffolding and manual inspection to improve safety and reduce cost. Similar to avian animals, the UAV autonomously perches on the pipe to conserve energy. A small inspection crawling robot is carried by the UAV, and is subsequently released onto the pipe’s surface to inspect its health. The crawler uses magnetic wheels for agile mobility and houses an ultrasonic testing (UT) sensor to thoroughly scan the pipe and detect wall thinning, which is a precursor for leaks. Finally, the crawler re-docks with the UAV, which in turn detaches from the pipe to fly back home or inspect another pipe. The multi-robot system is designed for and tested on pipe diameters as small as 8 in.