Nondestructive Inspection Methods Research Articles

Automatic Detection of Concrete Surface Defects Using PRE-TRAINED CNN and Laser Ultrasonic Visualization Testing

In recent years, nondestructive testing for civil engineering structures has become increasingly important. Ultrasonic testing is one of nondestructive inspection methods for civil structures. However, the inspection of civil engineering structures takes much time because of the extensive scope of the inspection. Moreover, in the field of nondestructive testing, there are also concerns about a future shortage of inspectors, so that an innovative effective nondestructive method needs to be developed. This study proposes an automatic defect detection approach using pre-trained convolutional neural network for laser ultrasonic visualization testing. The effectiveness of the proposed method is confirmed by applying it to a concrete structure with a surface defect. Grad-CAM demonstrates that the created CNN model in this study accurately predicts the position of a surface defect of concrete specimens.

Non-Destructive Quantification of In-Plane Depth Distribution of Sub-Surface Damage on 4H-SiC Wafers Using Laser Light Scattering

The development of non-destructive quantitative evaluation techniques for the in-plane depth distribution of sub-surface damage (SSD) layer induced by mechanical processing of chemical mechanical polishing (CMP) finished SiC wafers is essential to reduce the occurrence of crystal defects during epitaxial growth. Until now, no wafer inspection method has been able to nondestructively and quantitatively assess the in-plane depth distribution of the SSD. This study investigates the correlation between the scattered light intensity measured nondestructively by the Laser light scattering (LLS) method and the SSD depth estimated by destructive inspection using the Dynamic AGE-ing® method, a sublimation-controlled etching and growth process, to develop a novel non-destructive SSD inspection method. As a result, it was found that there is an exponential relationship between the scattered light intensity by the LLS method on the bare wafer surface and the depth of the SSD layer that contributes to the formation of in-grown stacking faults (IGSF) during subsequent epitaxial growth. The results show that SiC wafer inspection using the novel LLS method, which introduces this relational equation, enables non-destructive and quantitative evaluation of SSD depth and in-plane distribution.

Non-destructive inspection method for egg freshness evaluation via low-field nuclear magnetic resonance technology

Non-destructive inspection method for egg freshness evaluation via low-field nuclear magnetic resonance technology

Development of a High-Sensitivity Millimeter-Wave Radar Imaging System for Non-Destructive Testing.

There is an urgent need to develop non-destructive testing (NDT) methods for infrastructure facilities and residences, etc., where human lives are at stake, to prevent collapse due to aging or natural disasters such as earthquakes before they occur. In such inspections, it is desirable to develop a remote, non-contact, non-destructive inspection method that can inspect cracks as small as 0.1 mm on the surface of a structure and damage inside and on the surface of the structure that cannot be seen by the human eye with high sensitivity, while ensuring the safety of the engineers inspecting the structure. Based on this perspective, we developed a radar module (absolute gain of the transmitting antenna: 13.5 dB; absolute gain of the receiving antenna: 14.5 dB) with very high directivity and minimal loss in the signal transmission path between the radar chip and the array antenna, using our previously developed technology. A single-input, multiple-output (SIMO) synthetic aperture radar (SAR) imaging system was developed using this module. As a result of various performance evaluations using this system, we were able to demonstrate that this system has a performance that fully satisfies the abovementioned indices. First, the SNR in millimeter-wave (MM-wave) imaging was improved by 5.4 dB compared to the previously constructed imaging system using the IWR1443BOOST EVM, even though the measured distance was 2.66 times longer. As a specific example of the results of measurements on infrastructure facilities, the system successfully observed cracks as small as 0.1 mm in concrete materials hidden under glass fiber-reinforced tape and black acrylic paint. In this case, measurements were also made from a distance of about 3 m to meet the remote observation requirements, but the radar module with its high-directivity and high-gain antenna proved to be more sensitive in detecting crack structures than measurements made from a distance of 780 mm. In order to estimate the penetration length of MM waves into concrete, an experiment was conducted to measure the penetration of MM waves through a thin concrete slab with a thickness of 3.7 mm. As a result, Λexp = 6.0 mm was obtained as the attenuation distance of MM waves in the concrete slab used. In addition, transmission measurement experiments using a composite material consisting of ceramic tiles and fireproof board, which is a component of a house, and experiments using composite plywood, which is used as a general housing construction material in Japan, succeeded in making perspective observations of defects in the internal structure, etc., which are invisible to the human eye.

Analysis on power flow of Lamb waves generated by laser illumination in carbon fiber reinforced plastic laminates

Abstract The laser ultrasonics using guided waves excited by laser irradiation has attracted attention as an efficient non-destructive inspection method for carbon fiber reinforced plastic (CFRP) composite laminates. In this paper, to clarify the properties of laser-excited Lamb waves, we investigate the power flow of Lamb waves in an anisotropic CFRP laminate. The temperature rising caused by laser absorption is analytically calculated, and the derived thermal force is input to a finite element model to simulate the generation of Lamb waves. It is found that the power flow has an obvious directivity in a quasi-isotropic CFRP laminate. The power flow is smaller in the direction parallel to the carbon fibers of the surface layer and is larger in the perpendicular direction, but the maximum is in slightly different direction; this result was validated by an experiment. Such directivity pattern is determined by two factors: the distribution of thermal force and the stacking sequence of CFRP laminates. Moreover, we investigate the different simulation models (metal-coated CFRP and cross-ply CFRP) to discuss the influence of each factor on the distribution of power flow separately.

Non-Destructive Inspection Method Using Elastic Waves for Quality Management in the Bending Process Region of BFRTP

In order to establish a sustainable infrastructure, structures must maintain their minimum required performance for an extended period. Typically, existing concrete structures are reinforced with steel, but the susceptibility of steel reinforcements to corrosion, attributed to factors such as carbonation and chlorides, can lead to performance degradation, rendering the specified requirements unmet. As a remedy, there has been a growing interest in using lightweight and corrosion-resistant fiber-reinforced polymer (FRP) bars as an alternative to traditional steel reinforcement in concrete structures. Particularly noteworthy is the use of FRP bars manufactured with thermoplastic resins (FRTP) due to their ease of processing and convenient applicability on construction sites. This study delves into the mechanical behavior evaluation by examining the propagation characteristics of elastic waves in the curved section of basalt FRTP (BFRTP). Multiple BFRTP bars underwent a 180-degree bending process, subject to various conditions, including heat and twist variations. Subsequent measurements focused on the propagation characteristics of elastic waves in the curved sections, emphasizing wave attenuation, frequency features, and propagation velocity. Additionally, bending tensile tests were conducted on the curved bars, and a comparative analysis was performed between the tensile strength and the aforementioned elastic wave propagation characteristics. The results affirm a consistent correlation between the propagation characteristics of elastic waves (amplitude ratio, centroid frequency, velocity) during the traversal of the curved BFRTP section and its tensile strength. Notably, both centroid frequency and velocity exhibited correlation coefficients exceeding 0.7, suggesting their potential efficacy as reliable indicators for estimating tensile strength.

Hybrid Inspection Method using Three Dimensional Scanning, Lock-in Thermography and Laser Shearography

The proportion of composite materials (such as CFRP) to the metal used on the modern aircrafts is rising, imposing different kind of failure modes. Since the composite structures are known to be sensitive to the impact loading, there is need for means to assess the sub-surface damage in the structure rapidly. Royal Netherlands Aerospace Centre NLR has an extensive track record on contactless non-destructive inspection (NDI) methods based on optical sensors, such as 3D surface scanning, lock-in thermography and laser shearography. The combination of these methods (multi-domain inspection) enables us to assess the structural integrity of an aircraft outer surface in a short time, reducing inspection costs and the “down time” of the aircraft. Recently, NLR is working towards a 3D oriented mesh environment of an object, enhanced with NDI data, providing sub-surface damage information. By automatically stitching the 3D object images, it is possible to expand this method for a complete scan of an aircraft surface. Furthermore, the thermographic and shearography imaging information has been integrated into the 3D surface accounting for the image distortion from the different measurement angles. In this paper, the results from the various studies will be presented involving integration of the 2D measurements with the 3D scan mesh. Keywords: Thermography, Shearography, 3D scanning, Data fusion

Improving defect detection capability of pulse and pulse phase thermography method for CFRP plates by enhancing rear surface heat transfer coefficient

Infrared pulse thermography (PT) is a noncontact and convenient nondestructive inspection method, and its application to various objects has been reported in many papers. However, conventional PT is not suitable for detecting deep- or near-rear-surface defects. This study focuses on PT inspections of CFRP plates and improvements in their defect detection capabilities. To improve the capability of detecting near-rear-surface defects, a method for enhancing the heat transfer coefficient (HTC) of the rear surface during PT inspection was examined in this study; this would increase the temperature difference in the defective areas observed in thermal images. To investigate the effectiveness of the proposed method, experiments were conducted on CFRP specimens with artificial defects. The CFRP specimens were inspected using the PT method, during which water was brought into contact with the rear surfaces of the specimens to enhance the HTC. The experimental results showed that the capability of detecting near-rear-surface defects improved when the rear surfaces were in contact with water with forced convection. In addition, obtaining phase images by applying a Fourier transform to the experimentally obtained temperature data (that is, pulse phase thermography: PPT) was examined. Consequently, the combination of the enhancement of the rear-surface HTC and the use of phase images was significantly effective in improving the defect detection capability.

An improved hybrid solar cell defect detection approach using Generative Adversarial Networks and weighted classification

Quality control has a vital role in manufacturing processes. Electroluminescence (EL) imaging is one of the main non-destructive inspection methods for quality assessment in the Photovoltaic (PV) module production industry. EL test reveals PV cell defects such as micro cracks, broken cells, finger interruptions and provides detailed information about production quality. In recent years, automated detection and classification systems using deep neural networks for PV module inspection have gained increasing attention. However, deep learning-based systems usually require large amount of labeled data and high computational power. In this work, we proposed a compact classification framework based on hybrid data augmentation and deep learning models for detection of the defective solar cells. In the proposed method, the limited and imbalanced EL datasets were augmented through various Generative Adversarial Networks (GAN), and defect detection was achieved by customized pre-trained Convolutional Neural Networks (CNN). A novel hybrid EL dataset for training was formed by combining public ELPV dataset, our custom real-world dataset and synthetic images created with different GAN architectures such as GAN, cGAN and WGAN-GP. The datasets were classified through proposed customized VGG-16 and other state-of-the-art CNN models. The best results obtained by the proposed CNN model with WGAN-GP augmented dataset are 94.11% mean accuracy in the ELPV test dataset and 93.08% mean accuracy in the custom real-world test dataset. Therefore, the proposed detection system achieved superior performance with lesser resource usage and limited data.

Terahertz time-domain spectroscopy for the inspection of dry fibre preforms

Liquid moulded polymer matrix composites (LM-PMCs) are increasingly used in aerospace, automotive and other industrial applications. Liquid moulding processes featuring dry fibre preforms provide flexibility and enable cost reductions for secondary load-bearing structures. However, preform variability and manufacturing reproducibility remain major obstacles to wider use in primary structures. The open literature records only marginal use of non-destructive inspection (NDI) methods for dry multilayer preforms due to technological limitations and cost of NDI methods. In this work, terahertz time-domain spectroscopy (THz-TDS) is used for inspecting three dry multilayer glass fibre preforms featuring different defects, for the first time. A novel time-domain enhancement method is compared with classical image processing methods, aiming at improving image contrast and detecting potential defects. Furthermore, THz B-Scan is used for verifying the accuracy of interply defect detection. Finite difference time domain is simulated for analyzing THz magnitude variation in time-domain. Finally, quantitative evaluation is applied to further illustrate the significant potential of THz-TDS for the inspection of dry fibre preforms. The results show that the errors on defects lengths, widths, angles, and diameters for THz-TDS are in the ranges 8.2 %–34.3 %, 18.67 %–75 %, 0.29 %–6.67 %, and 1.33 %–10 % respectively.

Ultrasonic non-destructive inspection method for glass fibre reinforcement polymer (GFRP) hull plates considering design and construction characteristics

The design and construction characteristics, including glass fibre weight fraction ( Gc), number of single-ply layers, fabric combination, and fabrication quality, of glass fibre reinforcement polymer (GFRP) hull plates affect ultrasound propagation characteristics, such as ultrasonic velocity and attenuation, thereby influencing the accuracy of ultrasonic non-destructive test results. Therefore, this study is to propose a method to decrease the ultrasonic test errors of GFRP hull plate by using statistical method. The GFRP specimens with Gc of approximately 30–50 wt%, thicknesses of approximately 5–20 mm, and different fabric combinations were prepared using the hand lay-up method, considering the general design–construction characteristics. Further, an ultrasonic velocity decision method for ultrasonic inspection was proposed considering the GFRP hull design-construction characteristics, such as Gc and number of single-ply layers of hull plate by multiple linear regression method. The results show that the proposed method can reduce the thickness measurement error from approximately 20%–30% to 1%–2%, compared to an existing ultrasonic inspection method, only considering the Gc effect on ultrasonic velocity, which indicates that the proposed test method is suitable for practical applications.

Non-destructive testing of reinforced concrete structures using sub-terahertz reflected waves

Terahertz (THz) and sub-terahertz (sub-THz) waves are unexplored waves between the infrared and microwave ranges. This range features unique characteristics of both light resolution and electromagnetic wave transmission. Sub-THz waves are part of attractive new diagnostic methods for inner objects because they are safer than normal non-destructive inspection methods involving high energy, such as X-rays. In this study, a novel non-contact and non-destructive inspection method for reinforced concrete (RC) structures using sub-THz reflection imaging is proposed to inspect the deterioration of inaccessible damaged RC structures. The results of this study confirmed that the proposed sub-THz imaging method can detect cracks and voids in concrete, as well as in metals inside or behind the concrete, based on differences in reflectance. In addition, the camera-based measurement system makes real-time on-site field measurements possible.

Interface debonding defect detection for CFST columns based on EMI measurements: Experiment, numerical simulation and blind inspection in practice

Concrete-filled steel tube (CFST) members have been widely used in skyscrapers and long-span bridges. Non-uniformly distributed hydration heat during curing, inadequate compaction during construction and unavoidable shrinkage and creep of mass concrete in service most likely lead to interface debonding defects between concrete core and steel tube, which has been a common concern. The development of effective non-destructive inspection methods for interface bonding condition of existing CFST members is critical. In this study, an interface debonding defect detection method based on electromechanical impedance (EMI) measurement using surface-mounted piezoelectric-lead-zirconate-titanate (PZT) sensors is proposed at first. Then, experimental study on the feasibility of the proposed approach is carried out with scaled CFST specimens with artificially mimicked interface debonding defects. EMI of surface-mounted PZT sensors at different frequency bands are measured and compared to verify the detectability of the proposed approach for the mimicked interface debonding defects. Thirdly, a multi-physics CFST-PZT coupling finite element model (FEM) with interface debonding defects is established, and EMI of surface-mounted PZT sensors at different locations is simulated. The influence of interface debonding defects on EMI measurements is illustrated. Finally, a blind inspection on the interface bonding condition of selected CFST columns in an existing skyscraper in service using the proposed approach is carried out. Both bonding and debonding defect in the tested CFST columns are detected correctly and validated with drilling hole observation. Experimental, numerical and engineering application results show the proposed approach is effective for interface debonding detection of CFST members and sensitive to minor debonding defect of 0.3 mm in CFST members.

Research Status and Progress on Non-Destructive Testing Methods for Defect Inspection of Micro-Electronic Packaging

Abstract In a highly competitive and demanding micro-electronics market, non-destructive testing (NDT) technology has been widely applied to defect detection and evaluation of micro-electronic packaging. However, the trend of micro-electronic packaging toward miniaturization, high-density, ultrathin, ultralight, and with small chip footprint, poses an urgent demand for novel NDT methods with high-resolution and large penetration depth, which is utilized for internal defect detection and identification of advanced complicated packages. The conventional NDT methods for micro-electronic packaging mainly include optical visual inspection, X-ray inspection, active infrared thermography, scanning acoustic microscopy (SAM), atomic force microscopy (AFM), laser Doppler vibration measuring technique, scanning SQUID microscopy (SSM), electrical impedance spectroscopy, scanning electron microscope (SEM), and so on. This paper aims to provide a review of addressing their basic principles, advantages, limitations, and application researches in the field of defect inspection of micro-electronic packaging. Moreover, in order to overcome the shortcomings of the existing NDT methods, this paper emphasizes a novel NDT approach, called hybrid ultrasonic-laser digital holographic microscopy (DHM) imaging inspection method, and discusses its basic principle, merits, key techniques, system construction, and experimental results in detail. When some key technical problems can be solved in further research, this method will become a potentially promising technique for defect detection and evaluation of advanced complicated packages.

Evaluation of Pipe Thickness by Magnetic Hammer Test with a Tunnel Magnetoresistive Sensor.

A new nondestructive inspection method, the magnetic hammer test (MHT), which uses a compact and highly sensitive tunnel magnetoresistance (TMR) sensor, is proposed. This method complements the magnetic flux leakage method and eliminates the issues of the hammer test. It can therefore detect weak magnetic fields generated by the natural vibration of a pipe with a high signal-to-noise ratio. In this study, several steel pipes with different wall thicknesses were measured using a TMR sensor to demonstrate the superiority of MHT. The results of the measurement show that wall thickness can be evaluated with the accuracy of several tens of microns from the change in the natural vibration frequency of the specimen pipe. The pipes were also inspected underwater using a waterproofed TMR sensor, which demonstrated an accuracy of less than 100 μm. The validity of these results was by simulating the shielding of magnetic fields and vibration of the pipes with the finite element method (FEM) analysis. The proposed noncontact, fast, and accurate method for thickness testing of long-distance pipes will contribute to unmanned, manpower-saving nondestructive testing (NDT) in the future.

Development of an earthworm-based soft robot for colon sampling.

Colorectal cancer as a major disease that poses a serious threat to human health continues to rise in incidence. And the timely colon examinations are crucial for the prevention, diagnosis, and treatment of this disease. Clinically, gastroscopy is used as a universal means of examination, prevention and diagnosis of this disease, but this detection method is not patient-friendly and can easily cause damage to the intestinal mucosa. Soft robots as an emerging technology offer a promising approach to examining, diagnosing, and treating intestinal diseases due to their high flexibility and patient-friendly interaction. However, existing research on intestinal soft robots mainly focuses on controlled movement and observation within the colon or colon-like environments, lacking additional functionalities such as sample collection from the intestine. Here, we designed and developed an earthworm-like soft robot specifically for colon sampling. It consists of a robot body with an earthworm-like structure for movement in the narrow and soft pipe-environments, and a sampling part with a flexible arm structure resembling an elephant trunk for bidirectional bending sampling. This soft robot is capable of flexible movement and sample collection within an colon-like environment. By successfully demonstrating the feasibility of utilizing soft robots for colon sampling, this work introduces a novel method for non-destructive inspection and sampling in the colon. It represents a significant advancement in the field of medical robotics, offering a potential solution for more efficient and accurate examination and diagnosis of intestinal diseases, specifically for colorectal cancer.

Opportunities for using the thermal imaging method of nondestructive inspection for skin delamination diagnosis in honeycomb structures used in modern aircraft

Opportunities for using the thermal imaging method of nondestructive inspection for skin delamination diagnosis in honeycomb structures used in modern aircraft

Detection of thermo-mechanical damages by in-process Barkhausen Noise Analysis combined with Grinding Power Evaluation

Grinding of workpieces from hardened steel, especially in case of safety relevant components, usually requires a reliable method for the detection of thermo-mechanical surface damages. Compared to the common post-process methods, in-process detection promises saving of detection time and, particularly, a fast reaction to negative influences on the surface integrity. The present work shows the suitability of magnetic Barkhausen noise (BN) for the in-process detection of thermo-mechanically influenced regions during an outer diameter cylindrical grinding process. Different from other non-destructive inspection methods, BN allows the detection of changes of the residual stress state even before the occurrence of visible tempering zones. However, in case of pronounced tempering or rehardening zones, a single BN value does not enable an unambiguous statement about the surface state. Therefore, additionally the specific grinding power Pc” in dependence of the contact time Δt is considered, which allows to exclude grinding burn starting from light tempering zones. A particular focus of this study is the BN analysis during grinding with different types of grinding wheels.

Autonomous detection of steel corrosion spatial variability in reinforced concrete using X-ray technology and deep learning-based semantic segmentation

Correctly determining the spatial distribution of steel corrosion within a structural member is critical for estimating the remaining service life of deteriorating reinforced concrete (RC) structures. While X-ray technology serves as a nondestructive inspection method, existing challenges persist, particularly in semi-automated corrosion boundary detection. This paper describes a deep learning-based semantic segmentation framework to autonomously detect X-ray images associated with RC, facilitating the visualization of nonuniform steel corrosion distribution. X-ray images were collected from a comprehensive experiment using RC specimens with various structural details by two accelerated corrosion methods. Four deep learning models were constructed, trained, and compared based on the database containing the original X-ray images and the corresponding pixel-level labels. The results demonstrate that the proposed autonomous detection method can segment uncorroded steel at a very high level of global accuracy without time-consuming work, outperforming traditional methods in terms of both accuracy and efficiency.

Relationship between non-destructive inspection and heavy-weight floor impact noises in a box-type test building

This study investigated the relationship between floor impact noise performance and non-destructive inspection methods for use in construction quality control prior to installing resilient floor-topping materials. The study measured floor impact noise characteristics using heavy-weight impact sources in a box-type test building with a 180-mm thick bare slab. The study employed impact echo and ultrasonic tomography methods to estimate concrete thickness and other mechanical properties. The results showed that the highest impact noise levels were observed at the central area in the frequency bands of 25 Hz to 50 Hz. However, the frequency bands of 63 Hz to 80 Hz showed different results as a peak characteristic at the middle area in the long direction. The study estimated the average slab thickness as 175 mm and 172 mm, respectively, using the impact echo and ultrasonic tomography methods. The standard deviation of the thickness was up to 9.3 mm and 6.6 mm, respectively, depending on the impact position. Furthermore, the study analyzed the correlation between concrete thickness and impact noise performance by frequency bands and discussed the application directions of the mechanical properties to manage noise performances during construction.