Quantitative Nondestructive Testing Research Articles

Application of quantitative non-destructive determination of protein in wheat based on pretreatment combined with parallel convolutional neural network

With the increasing demand for wheat, the detection of wheat quality has become imperative. Protein content is an important indicator for wheat quality. Near infrared spectroscopy (NIRS) quantitative non-destructive testing technology has gained widespread application in agricultural field with the development of science and chemometrics technology. In this study, NIRS system was employed to measure the spectra of wheat, and the original spectra were pretreated using Savitzky-Golay smoothing (SG) pretreatment method. Subsequently, the NIRS prediction model of protein in wheat that using SG combined with parallel convolutional neural network (PaBATunNet) was established. PaBATunNet was composed of a one-dimensional convolutional layer, a parallel convolution module (Module), a flattening layer, four fully connected layers and a parameter regulator (PR). Module was made up of five submodules and a Concatenate function. The multidimensional features of the spectra were extracted by five submodules and spliced by Concatenate function. SG pretreatment combined with PaBATunNet (SG-PaBATunNet) was compared with commonly modeling methods, such as SG-partial least squares (SG-PLS), SG-principal component regression (SG-PCR), SG-support vector machine (SG-SVM) and SG-back propagation neural network (SG-BP). The results demonstrated that the modeling accuracy and prediction accuracy of SG-PaBATunNet were improved by 26.7%, 23.9%, 45.6%, 44.2%, and 38.4%, 39.6%, 60.1%, 58.0%, when compared with SG-PLS, SG-PCR, SG-SVM and SG-BP. The problems of low prediction accuracy and poor generalization ability with commonly modeling methods were effectively addressed by SG-PaBATunNet. This study provides an essential theoretical foundation for developing a fast, nondestructive and high-precision NIRS quantitative analysis model of protein in wheat.

3D Hybrid Modeling for the Ultrasonic Phased Array Inspection of Porosity in Heavy Plates: Simulation and Experimental Validation

Quantitative non-destructive testing (NDT) modelling and simulation tools are important in design and fabrication of ultrasonic phased array (UTPA) sensors with optimum characteristics and reduce the number of experimental efforts and development time. In order to achieve high accuracy with a low computational time in the simulation, the modeling tools require not only the high-frequency approximation of the ultrasonic wave propagation but also the high-precision electro-acoustic coupling model. In this work, an application specific 4 MHz, 32-element linear phased array probe with an optimized angle beam wedge for the inspection of porosity in heavy plates was developed based on the new 3D hybrid modeling approach. As a first step, we performed the FEA modeling of an UTPA sensor, which includes the full 1-3 piezo-composite design with the arrangement of array elements, conducting electrodes, multi-phase damping material, acoustical matching layer and the electrical circuit of a 50 Ω coaxial cable. In addition, the real excitation pulse of an industrial UT equipment was included in the current modelling to achieve the high accuracy in the simulated result. In the second step, the FEA simulated pulse-echo characteristics of an array element were further used as the reference signal in the CIVA-UT Software to simulate the imaging of porosity in heavy plates, quantitatively. Furthermore, the 3D wedge-geometry of the array sensor was modeled and optimized to suppress the unwanted wedge-boundary reflected echoes and to improve the signal-to-noise ratio (SNR) in the detected signals. The 3D hybrid model simulated Time Corrected Gain (TCG) curves for the 3 mm SDH at different depths in the reference steel plate were compared with the real experiments and a good quantitative agreement was achieved.

Quantitative Visualization of Buried Defects in GFRP via Microwave Reflectometry.

Glass fiber-reinforced polymer (GFRP) is widely used in engineering fields involving aerospace, energy, transportation, etc. If internal buried defects occur due to hostile environments during fabrication and practical service, the structural integrity and safety of GFRP structures would be severely undermined. Therefore, it is indispensable to carry out effective quantitative nondestructive testing (NDT) of internal defects buried within GFRP structures. Along with the development of composite materials, microwave NDT is promising in non-intrusive inspection of defects in GFRPs. In this paper, quantitative screening of the subsurface impact damage and air void in a unidirectional GFRP via microwave reflectometry was intensively investigated. The influence of the microwave polarization direction with respect to the GFRP fiber direction on the reflection coefficient was investigated by using the equivalent relative permittivity calculated with theoretical analysis. Following this, a microwave NDT system was built up for further investigation regarding the imaging and quantitative evaluation of buried defects in GFRPs. A direct-wave suppression method based on singular-value decomposition was proposed to obtain high-quality defect images. The defect in-plane area was subsequently assessed via a proposed defect-edge identification method. The simulation and experimental results revealed that (1) the testing sensitivity to buried defects was the highest when the electric-field polarization direction is parallel to the GFRP fiber direction; and (2) the averaged evaluation accuracy regarding the in-plane area of the buried defect reached approximately 90% by applying the microwave reflectometry together with the proposed processing methods.

Quantitative detection of combined cracks based on artificial neural network and eddy current testing signals

Quantitative nondestructive testing with enough precision are the basis for studying crack propagation behaviour and the residual life of structural component. Eddy current testing (ECT) is a fast nondestructive testing technique with many testing objects. As the common effect of each crack in combined cracks on ECT signals, quantitative detection of combined cracks is a challenge. In this paper, quantitative detection of combined cracks using features of ECT signals and an artificial neural network (ANN) method is proposed. Firstly, a model of combined cracks containing a long crack and a short vertical crack is used to approximately calculate two-dimensional ECT signals of crack. Secondly, correlation between the parameters of combined cracks and the features of the two-dimensional ECT signals are investigated by numerical simulation. Finally, the crack parameters are evaluated from the simulation signals of combined cracks and the measured signals of stress corrosion cracking using the proposed strategy. Numerical results verify the effectiveness of the proposed strategy.

X-ray computed tomography of cast metal matrix composites

The development of new cast metal matrix composites and technological processes for their production are inextricably linked with the need to improve the methods of quantitative non-destructive testing. In this work, the features of the spatial structure of cast in-situ metal matrix composites (on example of the Al – Mg2Si system) were studied using X-ray computed microtomography. The parameters of tomographic scanning were optimized to identify structural components with close ranges of radioparency. The rational selection of the scanning parameters of the samples made it possible, during the subsequent computer processing of the slice sets, to clearly identify the structural constituents of the metal matrix composites depending on the gray levels in their comparison with the characteristic morphology of the observed constituents (primary Mg2Si crystals, pseudobinary eutectic, compounds of impurity elements). The total volume of porosity in the studied samples of Al + 15 wt.% Mg2Si composites after melt thermal-rate treatment at 900 °C did not exceed 0.05 mm3, which corresponds to a porosity content in the sample of 0.13 vol.%. The presented results show the significant potential of tomography in the study of the structural and morphological characteristics of composite materials and internal defects in cast products made from them. This research was funded by the Russian Science Foundation (Project № 20-19-00687).

Calculation-experimental procedure for determining welding deformations and stresses based on a digital image correlation method

The object of this study is determining the stressed-strained state (SSS) of a welded article by applying quantitative non-destructive testing. The relevance of the study is associated with the need to devise a universal methodology for the non-destructive quantification of SSS using the simplest approaches and means of provision. To solve this task, an estimation-experimental procedure has been developed. This procedure is based on comparing digital stereo images of the individual sections (spatial primitives) of an article before and after its welding, followed by computer processing. To validate the developed procedure, the SSS of a cylindrical article made of aluminum alloy 7005, at the end of which two flanges were welded laserly with ring seams, was determined. It was established that after performing four diametrically opposed point tacks, the residual deformations of the ends of the article can reach 0.02–0.05 mm, and after performing continuous ring seams – to decrease to 0.01–0.02 mm. The calculation showed that the residual deformations of the end of the article after welding a ring seam are at the level of 0.02 mm, and the residual stresses in the same zone – in the range of 50–60 MPa. The deviation in the coincidence of residual deformations is in the range of 10–20 %, which is a satisfactory result and can be considered as an error in the results of determining SSS in general. Based on the developed methodology for determining SSS, an experimental industrial complex has been created that allows TIG and PAW to perform welding of objects from steels and alloys with the ability to determine the resulting stressed-strained state of these objects. The procedure devised and the equipment designed can be used for to non-destructively determine SSS of spatial structures made of steels and alloys

Quantitative Non-Destructive Testing (NDT) of Submerged Civil Concrete Structures Using Remotely Operated Robotic Drones

Periodic inspection is of paramount importance to assess structural integrity and safety. Conventional concrete inspection procedures ranging from rebound hammer, to state-of-the-art ground penetrating radar and ultrasonic tomography focus on superstructures. Often, the part of the structure underwater, is subject to significant levels of corrosion. Today, qualitative visual inspection of the submerged surface can be performed by diving teams, wherein internal defects often go undetected. Furthermore, divers are limited to shallow depths and face several risks, especially when visibility is poor and operating in confined spaces. Presently, there are few commercially available quantitative NDT techniques for submerged structures. This paper presents an alternate solution to inspection of submerged concrete structures — using lightweight remotely operated vehicles (ROV) manufactured by Planys Technologies to perform concrete NDT underwater. Rebound hammer and ultrasonic pulse velocity techniques, although elementary, have been redesigned for use on a submersible drone. Several challenges were addressed including long-range communication and data acquisition, marinizing transducers and pulser-receivers, obtaining measurements in water currents and over deformed surfaces. Planys’ ROVs carry payloads including high-definition cameras, lasers, sonar, and underwater positioning systems to improve data-acquisition quality and location tagging of defects. Key results from experimental studies in a laboratory on canonical specimens are presented. Furthermore, the technology has been successfully tested in a port — details of the structure, operational arrangement and sample results from the field trial are also presented. Following calibration procedures, ROV based underwater concrete NDT was used to acquire data from the structure in grids and subsequently, identify zones of potential non-homogeneity. Numerous challenges, including interpretation of the time traces obtained, and correlation of results to structural integrity and to structures above water, are discussed in the paper. This work will be of interest to asset owners in marine, water management and power generation industries.

Quantitative Nondestructive Testing for Wire Rope Based on Multi-Source Information Fusion

Quantitative Nondestructive Testing for Wire Rope Based on Multi-Source Information Fusion

Quantitative Nondestructive Testing of Broken Wires for Wire Rope Based on Multi-Image Fusion

Quantitative Nondestructive Testing of Broken Wires for Wire Rope Based on Multi-Image Fusion

A nonlinear magneto-elastoplastic coupling model based on Jiles–Atherton theory of ferromagnetic materials

As seen in the Jiles–Atherton (J–A) model and its modified form, the linear relationship between the magnetization coefficient and the stress deviates significantly from the experimental results. It is necessary to introduce many parameters that are difficult to obtain or unknown to describe the effect of elastoplastic deformation on magnetization or hysteresis, such as shape coefficient, pinning coefficient, and molecular field coefficient. In this paper, a new nonlinear magneto-elastoplastic model for ferromagnetic materials is established based on the magneto-mechanical coupling effect, and both the sixth-order term of magnetization and the nonlinear equation of the magnetization coefficient are introduced into the magnetostriction equation. In the models established in this paper, the elastoplastic deformation equivalent magnetic field is introduced into the effective magnetic field, and the Frohlich–Kennelly equation is used to describe the anhysteretic magnetization. After comparing the prediction results of different models with the available experimental results, it is observed that the proposed model in this paper exhibits superior prediction ability for magnetostrictive strain, magnetization, and hysteresis phenomena under different stresses. This paper has also analyzed the mechanism of the effect of elasto-plastic loading and residual stress on the hysteresis in different models as well as the differences between them. The determination coefficient of the proposed model in this paper is closer to 1, which is better than the existing models, indicating that it has a better fitting effect and is of great significance to the development of quantitative non-destructive testing technology.

Quantitative Nondestructive Testing of Steel Wire Rope Based on Optimized Support Vector Machine

Quantitative Nondestructive Testing of Steel Wire Rope Based on Optimized Support Vector Machine

An Ultrasonic Laminated Transducer for Viscoelastic Media Detection.

Based on the principle of underwater transducers, an ultrasonic four-laminated transducer with a frequency of 1 MHz was proposed to solve the problem of large energy attenuation when ultrasonic waves propagate in viscoelastic media. First, this study targeted solid rocket propellant as the research object, and the energy attenuation characteristics of ultrasonic waves propagating in viscoelastic media were analyzed through the derivation of the wave equation. Second, the structure of a four-laminated transducer with a frequency of 1 MHz was designed, and the resonance frequency was obtained by a graphical method. The sound field simulation and experimental results showed that the gain of the four-laminated transducer was 15 dB higher than that of the single-wafer transducer. An ultrasonic feature scanning system was built to complete the qualitative and quantitative detection of the smallest artificial hole (2 mm × 10 mm). Finally, two different natural defects were scanned, and the results were compared with those obtained using an industrial computed tomography detection system. The results showed that the ultrasonic method was more accurate in characterizing two natural defects. The primary cause was that the industrial CT was not sensitive to defects parallel to the incident direction of the ray. Therefore, this study not only achieved the qualitative and quantitative nondestructive testing of solid rocket propellants, but also provides an important reference for other viscoelastic components.

Linear Array Industrial Computerized Tomography Quantitative Detection Method for Small Defects Based on Coefficients of Variation

A method for accurate and quantitative nondestructive testing of small defects inside metal components has been developed by experimentally investigating the grayscale distribution in computerized tomography (CT) images for a typical 304 stainless-steel material that is extensively used in industrial products. CT scans were performed as a function of the defect pore size. The grayscale level and the noise deviation distribution were measured in each CT image. The localized grayscale features where the defects are located in the CT image were studied using wavelet decomposition. A quantitative correlation between the defect size and the grayscale distribution in the CT images was established based on the coefficient of variation. The experimental findings, when combined with the advantages of an industrial CT detection method, allow for small defects to be characterized, imaged, and presented. The results show that the quantitative accuracy of this method is higher when compared with the traditional full-width at half-maximum method. The measurement process developed herein is simple and highly practicable and, furthermore, represents an effective way to characterize the size of small defects.

Quantitative non-destructive evaluation of drilling defects in SiCf/SiC composites using low-energy X-ray imaging technique

Qualitative and quantitative non-destructive testing and evaluation (QNDT&E) of drilling defects in SiCf/SiC composites are crucial to the manufacture of hot-section components of aero-engines. A new technique for the QNDT&E of drilling defects was established based on grayscale (G) variation caused by attenuation of the relative energy (ΔE) of incident X-rays in SiCf/SiC composites. Specimens with artificial defects and actual SiCf/SiC composite components were used as test specimens. An industrial X-ray imaging system was constructed, the changes in ΔE were analysed, and the G value distribution was studied experimentally. A series of experiments on the detectability and QNDT&E of drilling defects was conducted. The results show that different drilling defects can be detected using the G value distribution and changes in the digital X-ray imaging characteristics of the SiCf/SiC composites. Plane defects, like micro-cracks with opening of 0.1 mm, can be detected. The minimum and maximum absolute deviation between the measured and designed defect sizes was close to 0.0 mm and 0.1 mm, respectively, for a Φ 0.3 mm microdefect.

Non-destructive characterisation and evaluation of manufacturing defects in SiCf/SiC composites using the relative energy attenuation behaviour of X-rays

Silicon carbide fibre/silicon carbide (SiCf/SiC) composites are important for manufacturing the hot-section components of aero engines and supersonic vehicles. Hence, quality control, as well as qualitative and quantitative non-destructive testing and evaluation (NDT&E) are critical. A grey (G) value method for the characterisation and NDT&E of manufacturing defects in SiCf/SiC composites based on the attenuation behaviour of low-energy X-rays was proposed, and a digital X-ray imaging detection system was developed. Specimens with artificial and manufacturing defects were evaluated, thereby revealing that imperfections were induced when the SiCf/SiC composites were formed at the high-temperatures; microcracks (100-μm-wide) and rectangular defects (0.1-mm-deep) were detected with a sensitivity exceeding 100 μm. Our results demonstrated that ‘voids’, ‘microcracks’, ‘porosity’, ‘polymer impregnation inhomogeneity’, ‘fibre-lack’, and ‘gap-delamination’ were the typical manufacturing defects caused during formation of SiCf/SiC composites at high temperatures; the minimum deviation between the detected and designed length of a 10-mm-long microcrack in the 3.0-mm-thick SiCf/SiC composite specimen was ~3%; the manufacturing defects were effectively characterised and evaluated using the distribution behaviours of G values and digital radiographic imaging features.

Quantitative Nondestructive Testing of Broken Wires for Wire Rope Based on Magnetic and Infrared Information

The lifetime of wire rope is crucial in industry manufacturing, mining, and so on. The damage can be detected by using appropriate nondestructive testing techniques or destructive tests by cutting the part. For broken wires classification problems, this work is aimed at improving the recognition accuracy. Facing the defects at the exterior of the rope, a novel method for recognition of broken wires is firstly developed based on magnetic and infrared information fusion. A denoising method, which is adopted for magnetic signal, is proposed for eliminating baseline signal and wave strand. An image segmentation method is employed for parting the defects of infrared images. Characteristic vectors are extracted from magnetic images and infrared images, then kernel extreme learning machine network is applied to implement recognition of broken wires. Experimental results show that the denoising method and image segmentation are effective and the information fusion can improve the classification accuracy, which can provide useful information for estimating the residual lifetime of wire rope.

Application of the total focusing method for quantitative nondestructive testing of anisotropic welds with ultrasound

Abstract In this paper, we report on the application of the ultrasonic Total Focusing Method for quantitative imaging of cracks in austenitic welds. Imaging inspection procedures provide more information than punctual measurements. In addition, an image provides more easy access for most human viewers. In ultrasonic testing, array transducers have played an important role in imaging for many years. The Full Matrix Capture technique in combination with Total Focusing is one of the newer methods with decisive advantages. In combination with fast electronics, computer technology and image processing, it now enables tomographic imaging in real time. The functionality of the method and the technical requirements are explained here. Austenitic weld seams are considered as examples for anisotropic materials, which can be examined with this method. An important requirement for quantitative measurement of defect size in anisotropic materials is the knowledge of the ultrasonic phase and group velocities of the inspected volume. The Gradient Elastic Constant Descent Method can deliver unknown parameters, which are needed to calculate these velocities.

A new quantitative non-destructive testing approach of broken wires for steel wire rope

A new quantitative non-destructive testing approach of broken wires for steel wire rope

Development of a numerical code for laser-induced shock waves applications

The recent development of LAser Shock Adhesion Test (LASAT) as quantitative Non-Destructive Testing (NDT) process for evaluation of structural bonded assemblies brings new challenges. Applicative assemblies composed of complex materials with poor transverse mechanical properties and highly resistant bonded joints require laser parameters optimization and a more accurate control on the whole process. The development of a numerical tool is then necessary to ensure laser parameters specification to evaluate the bond mechanical strength for a given assembly. In this document, the ability of ESTHER code for the description of laser-matter interaction on aluminum and ablation pressure prediction is exposed. The influence of the target initial reflectivity on ablation pressure is investigated. In this paper, validation of the code in both direct (1-500GW/cm2) and water-confined (0,2-7GW/cm2) irradiation regimes is achieved with comparison to suitable sets of experimental data. Experiments were led on two laser facilities: the transportable laser shock generator (GCLT) at the CEA/DAM/DIF and the Hephaïstos facility at the Processes and Engineering in Mechanics and Materials laboratory (PIMM lab). Numerical models developed in this work are compared to previous experimental data and to reference models. Ablation pressures defined by our predictive models can then be coupled to other codes which are able to describe 2D/3D shock propagation, in order to model the entire LASAT process on complex assemblies. Characterization of a 6061 Aluminum/ Epoxy/ 6061 Aluminum assembly is achieved using ESTHER, showing its ability to master the phenomena involved in the LASAT process. For the first time, results open the full numerical design of laser adhesion test with the same code.

Quantitative Nondestructive Testing of Wire Ropes Based on Features Fusion of Magnetic Image and Infrared Image

Magnetic flux leakage (MFL) detection is one of the most widely used and best performing wire rope nondestructive testing (NDT) methods for more than a decade. However, the traditional MFL detection has the disadvantages of single source of information, low precision, easy to miss detection, and false detection. To solve these problems, we propose a method of fusion recognition of magnetic image features and infrared image features. A denoising algorithm based on Hilbert vibration decomposition (HVD) and wavelet transform is proposed to denoise the MFL signal, and the modulus maxima method is used to locate and segment the defect. An infrared image acquisition system was designed to collect the infrared image of the surface of the wire rope. Digital image processing techniques are used to segment infrared defect images. The features of the MFL image and the infrared image are extracted separately for fusion. The fusion feature is input into the nearest neighbor (NN) algorithm for quantitative identification, and the same data are input into the backpropagation (BP) neural network for comparison verification. The experimental results show that the fusion of MFL features and infrared features effectively improves the recognition rate of wire rope defects and reduces the recognition error.