Non-destructive Inspection Technology Research Articles

Evaluation of Fatigue Limit Improvement and Harmless Crack Size of Maraging Steel Using Shot Peening

The fatigue strength of maraging steel, which is an ultra-high-strength steel, is relatively low, compared to that of conventional high-strength steel. The fatigue life of a structure is highly dependent on the surface conditions, because fatigue cracks generally start at the surface of the material. In particular, surface cracks considerably degrade the fatigue limit. To expand the application range of maraging steel, it is necessary to improve the fatigue limit, and render the surface cracks harmless. This study aims to investigate the effect of shot peening (SP) on the fatigue strength of maraging steel with surface cracks. The SP application introduced a compressive residual stress from the specimen surface to a depth of 170 μm, and increased the fatigue limit by 77 %. The estimated crack size that can be rendered harmless, based on fracture mechanics, is (0.170 − 0.202) μm in the range As = (1.0 − 0.1). The intersections of the harmless crack sizes were determined at depth. A semicircular surface crack below this value is harmless in terms of fatigue limit. The usefulness of non-destructive inspection (NDI) and non-damaging technology was evaluated in relation to ahml, aNDI, a25,50, and As. Thus, the SP process can improve the reliability of the maraging steel. Compressive residual stress is the dominant factor to improve fatigue strength and render the surface crack harmless.

Non-destructive inspection technologies for repair assessment in materials and structures

Aging infrastructure globally faces degradation, posing risks and requiring substantial repair investment. Strategic maintenance practices are crucial for evaluating structural conditions and ensuring sustainability. The growing demands on modern materials and structures necessitate enhanced health monitoring approaches. Shifting from reactive to proactive maintenance methodologies is paramount, due to lower investment while keeping the structural performance at acceptable standards. However, quantitative assurance of repair/reinforcement/retrofit programs or self-healing effect in structures is similarly crucial for the operation of the infrastructure. Non-destructive testing (NDT) techniques, such as ultrasound, acoustic emission, and optical methods, play a vital role in assessing structural health. Through real-world case studies, the effectiveness of repair in addition to damage assessment are evaluated, encouraging a more systematic approach to monitoring structural repair efficacy. The paper intends to address the research gap in monitoring the repair effectiveness in civil structures and materials and provides valuable insights to enhance repair strategies in civil engineering.

Surface defect detection of CFRP materials based on infrared thermography and Attention U-Net algorithm

ABSTRACT Carbon fiber reinforced polymer (CFRP) materials have been widely used in aerospace and other fields because of their excellent properties such as high temperature resistance and corrosion resistance, so the nondestructive inspection technology for CFRP materials has become a hot research topic. In this paper, we propose a method based on infrared thermography and Attention U-Net algorithm to characterize the defect shape of CFRP material surface. Firstly, the CFRP surface is scanned by a line laser and the trend of its temperature distribution is recorded using an infrared thermography camera. Subsequently, temperature analysis and entropy value of image information are calculated for individual defect image blocks in order to select images with clear defect contours. Next, the Attention U-Net is used to segment the defect in the image blocks, and the defect shape is characterization. By calculating the evaluation indexes of image segmentation, the method in this paper can achieve 99.57% accuracy, 97.06% recall, 96.63% precision, and the processing time for a single image is 0.13s. Finally, the algorithm of this paper is compared with other algorithms to verify the advantages of this research in the task of detecting surface defects in CFRP materials with fast and high accuracy.

X-ray Imaging Assessment of Internal Seed Morphology as a Nondestructive Viability Prediction for Triploid Watermelon Seeds

Highlights X-ray imaging techniques were used to assess the internal morphology of triploid watermelon seeds. Structural integrity of triploid watermelon seed was quantified through image-processing and analyzed according to multiple viability classes. Integrity and CNN-based viability prediction models were developed and evaluated for multiple viability criteria. In the integrity analysis and modeling results, there were differences in the correlation between internal seed morphology and viability depending on the condition of the seed lot. Abstract. Watermelon (Citrullus lanatus) is a tropical fruit consumed worldwide in various forms. Triploid watermelons—or seedless watermelons—have remained popular for decades because of the absence of hard seeds and their flavor. However, triploid watermelon seeds have lower viability than diploid watermelon seeds because of their thick seed coats, underdeveloped embryos, and larger internal cavity spaces. This poor viability characteristic of triploid watermelon seed leads to low crop productivity. Therefore, a nondestructive inspection technology is deemed necessary for sorting triploid watermelon seeds. In this study, we assessed the internal morphology of triploid watermelon seeds by applying the X-ray imaging technique to predict seed viability. More specifically, we analyzed the association between the structural integrity and viability of the seeds by X-ray image processing. Furthermore, prediction models based on integrity and convolutional neural networks (CNN) were developed and evaluated for multiple viability criteria and seed lots. As a result, first-grade class seeds were shown to significantly differ from the rest of the classes in terms of integrity. Similarly, the performance of classifying the first-grade class from other classes was the highest among classification criteria in prediction models. Although the CNN model showed better performances than the integrity-based model, seed integrity was considered to be the most important feature even in the CNN model. The CNN model in this study showed accuracies of 73.64%–90.63% depending on the seed lot, suggesting that the correlation between seed internal structure and viability may differ depending on the conditions of the seed lot. Keywords: Deep learning, Seed, Seed integrity, Triploid watermelon, Viability, X-ray.

Automated Defect Recognition for Additive Manufactured Parts Using Machine Perception and Visual Saliency.

Metal additive manufacturing (AM) is known to produce internal defects that can impact performance. As the technology becomes more mainstream, there is a growing need to establish nondestructive inspection technologies that can assess and quantify build quality with high confidence. This article presents a complete, three-dimensional (3D) solution for automated defect recognition in AM parts using X-ray computed tomography (CT) scans. The algorithm uses a machine perception framework to automatically separate visually salient regions, that is, anomalous voxels, from the CT background. Compared with supervised approaches, the proposed concept relies solely on visual cues in 3D similar to those used by human operators in two-dimensional (2D) assuming no a priori information about defect appearance, size, and/or shape. To ingest any arbitrary part geometry, a binary mask is generated using statistical measures that separate lighter, material voxels from darker, background voxels. Therefore, no additional part or scan information, such as CAD files, STL models, or laser scan vector data, is needed. Visual saliency is established using multiscale, symmetric, and separable 3D convolution kernels. Separability of the convolution kernels is paramount when processing CT scans with potentially billions of voxels because it allows for parallel processing and thus faster execution of the convolution operation in single dimensions. Based on the CT scan resolution, kernel sizes may be adjusted to identify defects of different sizes. All adjacent anomalous voxels are subsequently merged to form defect clusters, which in turn reveals additional information regarding defect size, morphology, and orientation to the user, information that may be linked to mechanical properties, such as fatigue response. The algorithm was implemented in MATLAB™ using hardware acceleration, that is, graphics processing unit support, and tested on CT scans of AM components available at the Center for Innovative Materials Processing through Direct Digital Deposition (CIMP-3D) at Penn State's Applied Research Laboratory. Initial results show adequate processing times of just a few minutes and very low false-positive rates, especially when addressing highly salient and larger defects. All developed analytic tools can be simplified to accommodate 2D images.

A Specular Highlight Removal Algorithm for Quality Inspection of Fresh Fruits

Nondestructive inspection technology based on machine vision can effectively improve the efficiency of fresh fruit quality inspection. However, fruits with smooth skin and less texture are easily affected by specular highlights during the image acquisition, resulting in light spots appearing on the surface of fruits, which severely affects the subsequent quality inspection. Aiming at this issue, we propose a new specular highlight removal algorithm based on multi-band polarization imaging. First of all, we realize real-time image acquisition by designing a new multi-band polarization imager, which can acquire all the spectral and polarization information through single image capture. Then we propose a joint multi-band-polarization characteristic vector constraint to realize the detection of specular highlight, and next we put forward a Max-Min multi-band-polarization differencing scheme combined with an ergodic least-squares separation for specular highlight removal, and finally, the chromaticity consistency regularization is used to compensate the missing details. Experimental results demonstrate that the proposed algorithm can effectively and stably remove the specular highlight and provide more accurate information for subsequent fruit quality inspection. Besides, the comparison of algorithm speed further shows that our proposed algorithm has a good tradeoff between accuracy and complexity.

Applications of THz Spectral Imaging in the Detection of Agricultural Products

Agricultural products need to be inspected for quality and safety, and the issue of safety of agricultural products caused by quality is frequently investigated. Safety testing should be carried out before agricultural products are consumed. The existing technologies for inspecting agricultural products are time-consuming and require complex operation, and there is motivation to develop a rapid, safe, and non-destructive inspection technology. In recent years, with the continuous progress of THz technology, THz spectral imaging, with the advantages of its unique characteristics, such as low energies, superior spatial resolution, and high sensitivity to water, has been recognized as an efficient and feasible identification tool, which has been widely used for the qualitative and quantitative analyses of agricultural production. In this paper, the current main performance achievements of the use of THz images are presented. In addition, recent advances in the application of THz spectral imaging technology for inspection of agricultural products are reviewed, including internal component detection, seed classification, pesticide residues detection, and foreign body and packaging inspection. Furthermore, machine learning methods applied in THz spectral imaging are discussed. Finally, the existing problems of THz spectral imaging technology are analyzed, and future research directions for THz spectral imaging technology are proposed. Recent rapid development of THz spectral imaging has demonstrated the advantages of THz radiation and its potential application in agricultural products. The rapid development of THz spectroscopic imaging combined with deep learning can be expected to have great potential for widespread application in the fields of agriculture and food engineering.

Non-contact imaging of subsurface defects using a scanning laser source

The quality of additive manufacturing (AM) components must be guaranteed to ensure wide applicability, and a nondestructive inspection technology is required in this regard. Therefore, this study examined a method for detecting subsurface defects using ultrasonic waves excited by a laser. Fundamental experiments showed that wideband ultrasonic waves can be excited with a suitable signal-to-noise ratio using high-repetition laser pulses. Images of subsurface defects were appropriately obtained using a scanning laser source (SLS) with broadband waves for an aluminum alloy flat plate with artificial defects. The imaging experiments showed that the acquisition condition depends on the local defect resonant (LDR) frequency in the defective part. The imaging technique also enabled to detect subsurface circular defects created by AM with the diameter below 1.0 mm that were undetectably small in our previous study using the SLS. Based on results of these experiments and a finite element analysis, the following guideline is proposed: the LDR frequencies of targeted defects must be included in the tested frequency range.

Hyper‐reduced direct numerical simulation of voids in welded joints via image‐based modeling

SummaryDefects such as gas pores can be formed and trapped in the fusion zone during laser welding. These defects can significantly affect the mechanical reliability of the welded joint. Current nondestructive inspection technologies are able to detect micro‐voids in a mass production context. Finite element analysis can therefore be used to assess the lifetime of an observed component via image‐based modeling. Unfortunately, running a simulation per component entails a huge and generally unaffordable computational cost. In addition, voids do not admit a parametric modeling. In this paper, a numerical method is proposed to study the impact of defects on the mechanical response of a welded joint. It is based on model order reduction techniques that decrease the computational cost of each simulation related to an image‐based modeling. To tackle the reduction of nonparametric defects, a multiscale construction of the reduced basis is proposed, although no scale separation is assumed when computing the mechanical response of the structure. Some empirical modes are representing the structure behavior and other empirical modes are related to the defect‐induced local fluctuations. They are then assembled to simulate a defective joint. Assets and limitations of the proposed method are explored through a simplified two‐dimensional (2D) problem. For the sake of reproducibility, this 2D problem is fully parametric. Finally, a realistic three‐dimensional (3D) industrial case is presented, where voids geometries have been measured via computed tomography. This 3D problem being nonparametric, fluctuation modes must be computed on the fly, once the computed tomography has been performed.

Non-destructive Inspection Technology for Electronic Parts Using Scanning Acoustic Tomography and Its Detectability Improvement

Non-destructive Inspection Technology for Electronic Parts Using Scanning Acoustic Tomography and Its Detectability Improvement

Destructive accidents / incidents and non-destructive inspection technologies

Destructive accidents / incidents and non-destructive inspection technologies

Exploiting Acoustic Anisotropy to Detect Recrystallization in a Ni Single Crystal Using Ultrasonic Nondestructive Inspection

Ultrasonic inspection was used to detect regions of recrystallization (RX) within a single crystal of Ni. RX can produce polycrystalline regions within single-crystal (SX) materials. Because RX regions act as initiator sites for failure by fatigue-crack growth in otherwise SX Ni-based superalloys, RX is an issue of direct concern for the service life of high-performance turbine blades. Detection and discrimination of RX regions in single-crystal materials are significant challenges for current nondestructive inspection technologies. The present study leverages the elastic anisotropy of single crystals, which produces acoustic anisotropy, to ultrasonically detect and characterize RX regions produced within single-crystal specimens. Single crystals of pure Ni were processed to create controlled regions of RX. These specimens were ultrasonically examined in an immersion tank using a high-resolution, polyvinylidene fluoride transducer to detect acoustic impedance changes across the boundaries between different crystals (i.e., grains) within the RX region. Data from time-of-flight and absolute peak amplitude measurements were used to create acoustic images that were compared against electron microscope images of the RX regions. The ultrasonic inspection technique described here successfully detected not only the locations of RX regions, but also the approximate sizes and shapes of the RX regions.

Strain

The aim of this special issue of Strain is to highlight current methods for the non- and minimally invasive evaluation of works of art. The trend of upgrading the inspection tools for artwork conservation has increased significantly in recent years, and most conservation laboratories as well as conservation organisations show an increased interest in new and effective tools that can solve everyday problems in the conservation field. In this issue, the focus on the non- or minimum invasivity of the methods is due to the ethical constraints set by the conservation scientists out of respect for the precious cultural heritage. It is commonly accepted that objects of fine arts such as paintings, sculptures, books, and historic buildings belong to the most important and valuable contribution of humanity tracing our identity, evolution, and progress. Therefore, their preservation deserves special attention across generations. An issue of main importance that a conservator has to consider prior to any restoration is the assessment of the structural and mechanical conditions of the artwork. To overcome conventional approaches such as the nail test and subjective visual monitoring, there have been great efforts in recent years to investigate and to implement efficient technologies to assist the restorers work and to objectify the assessment of the state of an artwork. An increasing need exists for non-invasive methods. Therefore, the significance of non-destructive and contactless inspection technologies dominates the discussions among experts in recent years. Many of the new instruments for both structural and analytical investigations are usually located in academic research institutes since they are usually invented there and require very specific expertise. Therefore, they are often far from being used by museums and cultural heritage researchers since the art pieces and monuments cannot easily moved to the location of the instruments. The implementation of portable instruments is therefore a further important challenge for all researchers and equipment manufacturers. Suitable experimental methods which were applied and tested explicitly in laboratory and in-situ are presented in this special issue. The eleven contributions from various countries and research institutions cover a broad range of inspection problems, technologies, instruments, and approaches. To them belong NMR techniques for depth profiling, Raman spectroscopy and chemometrics for investigating ageing effects on terpenoid resins, a coherent and low-coherence digital holographic interferometry set-up for structural diagnostics with example on a marquetry sample, digital shearography for the detection of sub-surface defects by applying a combination of FEM-simulation and measurement to support the process of fault classification, the investigation of Mediterranean wall paintings by its optical infrared emission, the development of a portable digital holographic speckle pattern interferometry system for remote-access monitoring in art conservation, photoacoustic imaging for uncovering the hidden content of layered documents, THz-technologies for time domain imaging of immovable cultural heritage materials, optical coherence microscopy for the evaluation of art objects made by marquetry technique, the use of digital image correlation for strain measurement in historic tapestries, and of the discrete Fourier transform to control strain in art objects by processing relative humidity data. Thus, this special issue is a snapshot of current activities in the field of minimally invasive artwork inspection and shows the wide bandwidth of modern technologies, approaches, and measurement objectives. The editors hope that these articles will contribute to the ongoing progress of optical inspection methods and will stimulate the cooperation between research groups and conservators to solve significant challenges in artwork protection and conservation. Stuttgart and Heraklion, February 2019 Wolfgang Osten and Vivi Tornari

Terahertz Spectrum Measurement of Corrosion Products on Coated Steel Sheet Surface

Our research group has developed a terahertz light source with high luminance and broadband, and is developing research on non-destructive inspection technology. As a nondestructive inspection technology for hot-dip galvanized steel sheets, we have built a terahertz spectrum database for corrosion products that may exist there. In this research, we aim to newly obtain spectral data of β-FeOOH. Absorption Spectrum is shown in Figure.1. Optical system is shown in Figure.2. The terahertz wave was generated by difference frequency mixing using a GaP crystal which is a nonlinear optical crystal. The standard powder sample was diluted with polyethylene powder and pelletized, and it was measured at room temperature by a permeation method. As a result of spectroscopic measurement, an absorption peak was obtained around 3.06 THz. On the day of the presentation, in addition to discussions on attribution of peaks, report together with ATR-FTIR results. Figure 1

Development of Non-destructive Inspection Technology and Structural Analysis System for Main Parts of Hydro-Turbine

Development of Non-destructive Inspection Technology and Structural Analysis System for Main Parts of Hydro-Turbine

Terahertz Application for Non-Destructive Inspection of Coated Al Electrical Conductive Wires

At present, one of the main inspection methods of electric wires is visual inspection. The development of a novel non-destructive inspection technology is required because of various problems, such as water invasion by the removal of insulators. Since terahertz (THz) waves have high transparency to nonpolar substances such as coatings of conductive wire, electric conductive wires are extremely suitable for THz non-destructive inspection. In this research, in order to investigate the quantitative possibility of detecting the defects on aluminum electric wire, THz wave reflection imaging measurement was performed for artificially disconnected wires. It is shown that quantitative detection is possible for the disconnect status of the aluminum electric wire by using THz waves.

Effect of broken wire on bending fatigue characteristics of wire ropes

The life of damaged wire rope is difficult to judge and the damaged wire rope is prematurely replaced resulting in an enormous economic waste. This paper studies the effect of different distributions of pre-broken wires on bending fatigue behavior of wire ropes using a self-made bending fatigue test facility. The fatigue lives of wire ropes with different distributions of pre-broken wires were studied using both visual inspection and commercial non-destructive inspection technology, combined with electron microscopy. It is found that broken wires on the surface reduce the bending fatigue life of wire ropes. The broken wires increase the stress in the inner wire strands as well as the contact force between the wires. This leads to a concentration of severe wear, which accelerates the density of broken wires locally, leading to short fatigue lives especially in the case with the most concentrated number of pre-broken wires (1×4). After numerous wires fail by wear and fatigue, others fail by tensile overload, as evidenced microscopically by necking and ductile failure. The damage in the rope at failure defined by counting broken wires is nearly 50% smaller than the damage value given by the commercial non-destructive damage value, based on magnetic measurements.

第52回X線材料強度に関する討論会 「企業における非破壊検査の現状と課題および放射光を利用した非破壊材料評価技術の現状と課題」開催報告

第52回X線材料強度に関する討論会 「企業における非破壊検査の現状と課題および放射光を利用した非破壊材料評価技術の現状と課題」開催報告

가변초음파 적외선열화상을 이용한 이종접합용접부의 미세균열 검출 연구

최근 널리 사용되는 모든 비파괴검사 기술 중 적외선열화상 카메라는 점차 적용 범위를 확대하고 있다. 초음파적외선 열화상은 절대온도 0 K 이상의 모든 물체가 방출하는 적외선 에너지를 검출하여 검사자가 볼 수 있는 화상으로 이미지를 만들어 검사하는 기술에 초음파를 접목하여 결함 부위만을 검출하는 방법으로 비접촉으로 넓은 범위를 빠른 시간에 검사할 수 있는 장점이 있는 기술이다. 본 연구에서는 고유주파수를 변화할 수 있는 터패놀-D 소재의 가변초음파 가진검사 방법을 이용하여 결함 검출의 적용가능성을 연구하였다. As a nondestructive inspection technology currently in use, infrared thermography has gradually expanded its application range to industry. The method detects only defect areas by grafting ultrasound on a technique of detecting infrared energy emitted from all objects with absolute temperature of 0 K and converting this energy into thermography for inspection. Ultrasound infrared thermography has merits including the ability to inspect a wide area in a short time without contacting the target object. This study investigated the applicability of the technique for defect detection using variable ultrasound excitation inspection methods on samples of Terfenol-D, a magnetostrictive material with a tunable natural resonant frequency.

Non-Destructive In-Situ Condition Assessment of Plastic Pipe Using Ultrasound

Abstract Pipelines in potable water distribution system are a vital part of modern infrastructure, providing one of the most important services for society. This vital, complex infrastructure is endemic to our urban environments but is ageing, with current average age of around 70 years and with current replacement rates an inferred serviceable asset life of hundreds of years. Hence it is important that we develop technology that will enable pipeline condition assessment without service interruption. Due to environmental and operational stresses acting upon these pipelines, the common structural health problems include stress corrosion, thermal degradation, cracks or even leaks [1] . In particular, it has been suggested that void formation external to buried pipe wall is a crucial factor in pipe breakages due to lack of structural support [1] , [2] . This paper presents the development and laboratory testing of ultrasonic non-destructive inspection technology for the condition assessment of plastic pipes, provide a measure of the structural integrity of the pipe, as well as ‘looking’ through the pipe wall to assess void formation and critical loss of support. Ultrasonic detection results are presented for grooves and cracks with two common plastic pipe materials, HDPE (High-density polyethylene) and PVC (Polyvinyl chloride) in order to simulate material loss in pipe wall. In addition, four voids in the ground external to plastics with varying shapes and dimensions were detected. Tested soils include two particle sized sands and two particle sized gravels. The study demonstrates the feasibility of developing a new technique for condition and health assessing for buried water plastic pipes