Non-destructive Testing Process Research Articles

Non-destructive ultrasonic testing for identifying concealed weapons and analyzing internal chemical substances

The management of unknown weapons obtained from warfare, military operations, and terrorist situations requires a series of nondestructive testing processes. This management process, which is aimed at collecting information on the nature of the weapons, encompasses identification, processing, transportation, and storage of the obtained weapons. A lack of identification marks in acquired ammunition may indicate the potential presence of a chemical weapon. Therefore, nondestructive evaluation methods have been employed to identify unknown weapons. However, these methods rely on neutron- and radiation-based analyses, which require radiation-handling experts and specific protective facilities. Consequently, their application in this field is challenging. Herein, a nondestructive ultrasonic testing method, which can identify substances inside unknown weapons and optimize the verifiability of the state of the ammunition, was employed as an alternative method to overcome these limitations. The experimental system enabled quantitative and qualitative analyses of the internal chemicals by analyzing the time difference in acquiring the signals, particularly when the results indicate that the internal substance is a liquid. The results of this study can serve as a basis for advancing the application of ultrasonic testing as a viable and efficient approach for managing unknown weapons.

Debonding of piezoelectric transducers for residue-free ultrasonic non-destructive testing

ABSTRACT Components made of fibre-reinforced polymers (FRP) are prone to different types of damages such as delamination or matrix cracks, which can be critical for a component’s functionality. In classical ultrasonic nondestructive testing (NDT), lamb waves (LW) are frequently used to detect imperfections due to their favourable propagation characteristics over long distances. The LW are often excited by piezoelectric transducers, which are either bonded onto the component’s surface using comparatively stiff adhesives so to ensure loss-free LW coupling into the component or laminated directly into the FRP. In both cases the a priori nonseparable connection between the transducer and the substrate may itself be considered a defect when the component is put into service. In addition, laminating the transducers directly into the matrix is accompanied by both additional production effort and corresponding effects on thermomechanical component properties. To provide a cost-effective solution for NDT applications, the study focused on the development of a residue-free bonding concept for piezoelectric transducers. To this end, a total of three application approaches involving 14 commercially available adhesives and one dilatant material were investigated in different rounds of experimental testing. During the scientific campaign, the authors finally identified an adhesive that guarantees both lossless ultrasonic coupling and residue-free bonding, paving the way for much more process control and reusage of tested components for future NDT processes.

Non-destructive investigation of thermophysical properties on the China's space station: In-orbit experiment measurements and analysis

This paper discusses the current state of non-destructive research on the density, surface tension and viscosity of molten samples using the electrostatic levitation furnace (ELF) aboard the China Space Station (CSS). To address the challenges posed by the microgravity environment during the non-destructive testing process of containerless technology, we have developed several solutions. These include a temperature correction for infrared temperature measurement, a dual-camera position correction technique for density testing, a double electrode synchronous excitation, semi-frequency excitation and fine-sweeping approach for surface tension testing, and a signal demodulation method for viscosity testing. The uncertainties of the three thermophysical properties were 0.51 %, 3.10 %, and 9.78 %, respectively. This study highlights the feasibility and accuracy of measurements conducted in the ELF on the CSS, offering valuable insights into the behavior of molten materials under microgravity conditions. The findings from this study significantly contribute to our understanding of the thermophysical properties of molten materials.

Efficient Autonomous Path Planning for Ultrasonic Non-Destructive Testing: A Graph Theory and K-Dimensional Tree Optimisation Approach

Within the domain of robotic non-destructive testing (NDT) of complex structures, the existing methods typically utilise an offline robot-path-planning strategy. Commonly, for robotic inspection, this will involve full coverage of the component. An NDT probe oriented normal to the component surface is deployed in a raster scan pattern. Here, digital models are used, with the user decomposing complex structures into manageable scan path segments, while carefully avoiding obstacles and other geometric features. This is a manual process that requires a highly skilled robotic operator, often taking several hours or days to refine. This introduces several challenges to NDT, including the need for an accurate model of the component (which, for NDT inspection, is often not available), the requirement of skilled personnel, and careful consideration of both the NDT inspection method and the geometric structure of the component. This paper addresses the specific challenge of scanning complex surfaces by using an automated approach. An algorithm is presented, which is able to learn an efficient scan path by taking into account the dimensional constraints of the footprint of an ultrasonic phased-array probe (a common inspection method for NDT) and the surface geometry. The proposed solution harnesses a digital model of the component, which is decomposed into a series of connected nodes representing the NDT inspection points within the NDT process—this step utilises graph theory. The connections to other nodes are determined using nearest neighbour with KD-Tree optimisation to improve the efficiency of node traversal. This enables a trade-off between simplicity and efficiency. Next, movement restrictions are introduced to allow the robot to navigate the surface of a component in a three-dimensional space, defining obstacles as prohibited areas, explicitly. Our solution entails a two-stage planning process, as follows: a modified three-dimensional flood fill is combined with Dijkstra’s shortest path algorithm. The process is repeated iteratively until the entire surface is covered. The efficiency of this proposed approach is evaluated through simulations. The technique presented in this paper provides an improved and automated method for NDT robotic inspection, reducing the requirement of skilled robotic path-planning personnel while ensuring full component coverage.

Resource Optimisation of Distributed Manufacturing Processes Using Simulation

Non-destructive testing processes in the technological cycle of a wagon repair enterprise largely determine safety of railway transport facilities. The most effective ways to control such processes can only be determined through simulation which makes it possible to assess stability of the production system in a wide range of both external conditions and internal factors.The objective of the work is to create a method for optimising the resources of distributed manufacturing processes for non-destructive testing of a wagon repair depot based on simulation to reduce the likelihood of stopping the production cycle and reducing unreasonable costs of the enterprise.The features of non-destructive testing as a stage of the technological cycle of the enterprise are considered followed by the analysis of information on the qualifications of the specialists of the wagon repair company. The positions of non-destructive testing and controlled details are described and analysed within the framework of the queuing theory. To optimise the non-destructive testing division, simulation modelling is used, while mathematical statistics methods and correlation analysis are used to process the simulation results.A built model of a non-destructive testing unit comprises posts at the units for repair of parts of the automatic coupling devices and the wagon bogie, wheel sets. A production personnel management scheme is proposed, which might be a basis for optimising the organisational structure of the non-destructive testing unit.The simulation resulted in formulating requirements for qualification of non-destructive testing inspectors of the wagon repair depot. It is shown that the optimal strategy for development of a subdivision should be aimed at ensuring the universal qualification of employees, in which they have the necessary competencies to perform work at all testing positions. This will increase the average occupancy rate of NDT inspectors from 0,34 to 0,45 and reduce the average delay time of an item at the post from 650 % to 150 % of the standard time.

Establishing a Prediction Model for Tea Leaf Moisture Content Using the Free-Space Method’s Measured Scattering Coefficient

The rapid and nondestructive detection of tea leaf moisture content (MC) is of great significance to processing tea with an automatic assembly line. This study proposes an MC detection method based on microwave scattering parameters (SPs). Through the established free-space electromagnetic measurement device, 901 different frequency points are taken between 2.45 and 6 GHz using a vector network analyzer (VNA). The SPs of tea leaves with different moisture contents (5.72–55.26%) at different bulk density and different sample thicknesses were measured. The relationship between frequency, S21 amplitude and moisture content, thickness, and bulk density of tea was analyzed using correlation coefficients, significance analysis, and model construction. Back propagation (BP) neural network, decision tree (DT), and random forest (RF) MC prediction models were established with the frequency, amplitude, and phase of the SPs, thickness, and bulk density of the samples as inputs. The results showed that the RF-based model had the best performance, with determination coefficient (R2) = 0.998, mean absolute error (MAE) = 0.242, and root mean square error (RMSE) = 0.614. Compared to other nondestructive testing processes for tea, this method is simpler and more accurate. This study provides a new method for the detection of tea MC, which may have potential applications in tea processing.

The contribution of numerical models to Lamb-wave-driven NDT processes – part II: experimental design and numerical studies

During production or service life, lightweight components made of fibre-reinforced polymers (FRP) may suffer from different types of defects such as cracks or delamination, which may be detected, amongst others, with the help of ultrasonic lamb waves (LW). The study intends to illustrate the potentials of numerical models to assist the design of LW-based non-destructive testing (NDT) processes. For that, the complete NDT chain of an LW driven inspection system was supported by a Finite Element Analysis (FEA) using stringer-stiffened C FRP panels as an exemplary component. The study was divided in two publications: The first part focused on the description of the numerical model, illustration of its functionalities and – most importantly – the determination of LW related effects that were needed to design the inspection system (dispersion characteristics, excitation frequency, propagating modes etc.). In this part, the FEA driven design approach was first validated with self measured experimental data as well as experiments provided in literature. In the second step, the numerical model was applied for the performance of parameter studies in order to identify component specific aspects that proved important for the NDT process. Finally, general advices and FEA related working steps were derived from all findings to assist practitioners in the implementation of the technique.

Machine Learning for Parametrical Analysis of Friction Stir Welded Aluminum Metal Matrix Composites

The research focuses on the behaviour and process parametric influence on friction stir welded Al metal matrix composites reinforced with varied percentages of SiC, B4C, and Mg. The experimentation involves fabrication of Al metal matrix composites followed by friction stir welding and, subsequently, evaluation of the joint properties in terms of mechanical strength, microstructural integrity, and quality. In comparison to other joints with varied base material compositions, the weld exhibits refined grains and uniform distribution of hybrid particles in the joint region, resulting in increased strength. Higher SiC composition adds to greater strength, better wear characteristics, and harness, whereas B4C percentage is linked to hardness. The maximum ultimate tensile stress for a particular sample was determined to be around 160MPa, while the maximum percentage elongation was found to be around 165 for 10% SiC and 3% B4C. As the amount of SiC declines and that of B4C rises, the percentage elongation decreases. In samples with a B4C weight percentage of 10%, the greatest hardness measured was around 103Hv. For a load of 30N, the wear rate was as high as 12gm/s with a SiC weight percentage of 10. For lower load values and a higher percentage of B4C, the wear rate often decreased. Chemical properties are barely changed. Therefore, the materials keep their original qualities after welding. During the non-destructive testing process, no large cracks, pores, or clusters of pores are found, indicating that the weld is of good quality. To achieve a satisfactory weld, optimal ranges based on analysis using machine learning of rotary tool speed, tool linear velocity, transverse speed are maintained. Linear Regression algorithm, Random Forest algorithm and Lasso Regression algorithms are being used and the results are also compared. This work covers a wide range of topics, and the results are found to have improved significantly in most cases and is in good agreement with data previously presented in the literatures.

The contribution of numerical models to Lamb wave driven NDT processes – part I: model building

Components made of fibre-reinforced polymers (FRP) may suffer from various types of damages, such as cracks or delamination. In order to monitor the structures’ material condition, non destructive testing (NDT) methods have emerged – among them, the use of ultrasonic waves. Inter alia, research focused on Lamb waves (LW), which offer promising conditions for NDT processes. However, prior implementation in a specific production environment, practitioners are faced with many open questions such as excitation frequencies to be used or which mode to select for defect identification. Therefore, the study aimed at demonstrating how a finite element analysis (FEA) can assist the experimental design of an LW driven NDT process. For that, a numerical model was developed, capable of computing LW propagations in an exemplary component: Stringer-stiffened C-FRP panels. The study was divided into two parts: In this part, all information regarding the model building is presented and principal functionality demonstrated. In the second part, the FEA is validated and then used to perform parameter studies, highlighting important conditions for practical application. The results of the present paper showed that stiffeners provoke varying interactions with LW modes – effects that increase wave field complexity but do not limit defect identification within or behind the stringer.

Performance inspection and defect cause analysis of girth weld of high steel grade pipeline

Abstract The suspected circumferential weld defects found in the pipeline inspection process were tested and studied. It was found that there was slag inclusion in the girth weld at 9 o’clock, which had not been found in the early stage or in the laboratory nondestructive testing process. The defects are most likely due to incomplete slag removal between layers and low welding wire energy. There was a root crack at the 6 o’clock position of the weld, and the crack length was 10 mm, which was close to the original film and the detection result of excavation. The misjudgment of the field rebeat and the laboratory test results may be caused by the pits in the weld cover and the bottom weld. The crack is caused by the crystal crack formed along the middle of the columnar crystal during the solidification process of backing welding due to the increase of residual stress caused by the reduction of welding layers and the group stress caused by the steel tube.

Automatic Defect Identification Method for Magnetic Particle Inspection of Bearing Rings Based on Visual Characteristics and High-Level Features

Fluorescent magnetic particle inspection (MPI) is a conventional non-destructive testing process for railway bearing rings that still needs to be completed manually. Due to the complexity of bearing ring surfaces in inspection, automatic detection for bearing rings based on image processing is difficult to apply. Therefore, we proposed a bearing ring defect identification method based on visual characteristics and high-level features. Inspired by the mechanism of human visual perception, defects can be identified from the complex background conveniently by human eyes. According to the linear structure characteristics and greyscale distribution characteristics of cracks in the acquired images, we introduce the centerline extraction and Gaussian similarity measure to reduce background noise and obtain the crack candidate regions. Then, an improved MobileNetV3 is used to extract high-level features of the candidate regions and determine whether they are defective, which uses a new attention module, Coordinate Attention (CA), to substitute the Squeeze-and-Excitation (SE) attention to improve the performance. The experimental results show that the detection accuracy rate of the proposed method is 96.5%. Compared with traditional methods, the proposed method can efficiently extract crack defects in a complex textured background and shows high-quality performance in recall and precision.

Возможности использования математических моделей для теплового контроля дефектов многослойных биметаллических пластин

There is an actual task of delamination detection in multilayer bimetallic materials. Various methods of nondestructive testing (NDT) are used to solve it, including the method of transient thermal NDT. This method consists in remote registration, visualization and analysis of thermal (temperature) fields, which depend on thermophysical and geometric characteristics, thermal effect capacity and internal structure features of the object. The internal structure defects cause the appearance of abnormal temperature zones on the object surface. Their analysis allows us to judge the presence of changes in the material as a whole or in individual areas. It is possible to understand whether there is a defect under the anomalous site, and what its parameters are, if there is an adequate mathematical model that theoretically describes the dependence of the measuring results on the properties of the object and the selected technological modes. This model is a significant component of thermal NDT systems. For the same object or process, a certain set of mathematical models can be compiled, differing in the number of factors taken into account, the assumptions made, the completeness and accuracy of the description of the state of the object or the conditions of the process. The set of factors is determined by the purpose of the study, and in order to unambiguously determine the model of the thermal state, it is necessary to describe the characteristics of the object (geometric shape and thermophysical characteristics of the material) and the heat exchange process (characteristics of heat sources, initial and boundary conditions). Aim. To analyze the existing mathematical models for the research object – a multilayer bimetallic plate with delaminations between the outer and inner layers, and to identify common approaches to modeling the processes of thermal NDT of multilayer objects. Materials and methods. The structure of the mathematical model of the thermal state of the object is determined. An analytical review of mathematical models of thermal NDT of multilayer objects is performed. Results. The requirements, assumptions and limitations for a mathematical model of thermal NDT of a multilayer bimetallic plate with delamination defects are formulated. Conclusion. On the basis of the considered approaches to the mathematical modeling of the thermal state of multilayer objects with ideal layers contact and delamination defects, the necessary factors for the development of a model for the transient thermal NDT processes of the studied objects are determined.

Empower parameterized generative adversarial networks using a novel particle swarm optimizer: algorithms and applications

In this paper, a novel parameterized generative adversarial network (GAN) is proposed where the parameters are introduced to enhance the performance of image segmentation. The developed algorithm is applied to the image-based crack detection problem on the thermal data obtained through the non-destructive testing process. A new regularization term, which contains three tunable hyperparameters, embedded into the objective function of the GAN in order to improve the contrast ratio of certain areas of the image so as to benefit the crack detection process. To automate the selection of the optimal hyperparameters of the GAN, a new particle swarm optimization (PSO) algorithm is put forward where a neighborhood-based velocity updating strategy is developed for the purpose of thoroughly exploring the problem space. The proposed PSO-based GAN algorithm is shown to 1) work well in detecting cracks on the thermal data generated by the eddy current pulsed thermography technique; and 2) outperforms other conventional GAN algorithms.

A New GAN-Based Approach to Data Augmentation and Image Segmentation for Crack Detection in Thermal Imaging Tests

As a popular nondestructive testing (NDT) technique, thermal imaging test demonstrates competitive performance in crack detection, especially for detecting subsurface cracks. In thermal imaging test, the temperature of the crack area is higher than that of the non-crack area during the NDT process. By extracting the features of the thermal image sequences, the temperature curve of each spatial point is employed for crack detection. Nevertheless, the quality of thermal images is influenced by the noises due to the complex thermal environment in NDT. In this paper, a modified generative adversarial network (GAN) is employed to improve the image segmentation performance. To improve the feature extraction ability and alleviate the influence of noises, a penalty term is put forward in the loss function of the conventional GAN. A data preprocessing method is developed where the principle component analysis algorithm is adopted for feature extraction. The data argumentation technique is utilized to guarantee the quantity of the training samples. To validate its effectiveness in thermal imaging NDT, the modified GAN is applied to detect the cracks on the eddy current pulsed thermography NDT dataset.

The effects of undercut geometry on the static stress concentration factor of welds

Undercutting is a welding defect that appears as a groove in the base metal directly along the edges of the weld metal. It is inevitable in fillet and butt joints if improper welding parameters are used in the operation. It is a discontinuity in the welding that produces stress concentration and lowers the strength of the weld. The stress concentration factor of an undercut is due to the reinforcement angle, undercut width, undercut depth and undercut root radius. In this study, 20 mm thick mild steel plates were welded by automatic gas metal arc welding with the carbon dioxide (CO2) shielding gas process. A single-V butt joint was obtained after welding. Before welding, 30° groove angles were obtained by milling on the longitudinal side of each workpiece. Two plates were welded with several passes. After welding, the weldment was tested with a radiographic non-destructive testing process. A defect-free weldment was obtained. Then, standard tensile test samples were machined from the weldment. A groove was drilled in the heat-affected zone, adjacent to the weld metal boundary on every tensile test sample. Each groove resembled an undercut. The length, root radius and depth of grooves were varied. Then, the samples were broken on a tensile test machine. From the test results, the static stress concentration factor of each groove was calculated. The effects of groove geometry on stress concentration factors were determined.

Mechanical and Microstructural Characterization of Friction Stir Welded SiC and B4C Reinforced Aluminium Alloy AA6061 Metal Matrix Composites.

This study focuses on the properties and process parameters dictating behavioural aspects of friction stir welded Aluminium Alloy AA6061 metal matrix composites reinforced with varying percentages of SiC and B4C. The joint properties in terms of mechanical strength, microstructural integrity and quality were examined. The weld reveals grain refinement and uniform distribution of reinforced particles in the joint region leading to improved strength compared to other joints of varying base material compositions. The tensile properties of the friction stir welded Al-MMCs improved after reinforcement with SiC and B4C. The maximum ultimate tensile stress was around 172.8 ± 1.9 MPa for composite with 10% SiC and 3% B4C reinforcement. The percentage elongation decreased as the percentage of SiC decreases and B4C increases. The hardness of the Al-MMCs improved considerably by adding reinforcement and subsequent thermal action during the FSW process, indicating an optimal increase as it eliminates brittleness. It was seen that higher SiC content contributes to higher strength, improved wear properties and hardness. The wear rate was as high as 12 ± 0.9 g/s for 10% SiC reinforcement and 30 N load. The wear rate reduced for lower values of load and increased with B4C reinforcement. The microstructural examination at the joints reveals the flow of plasticized metal from advancing to the retreating side. The formation of onion rings in the weld zone was due to the cylindrical FSW rotating tool material impression during the stirring action. Alterations in chemical properties are negligible, thereby retaining the original characteristics of the materials post welding. No major cracks or pores were observed during the non-destructive testing process that established good quality of the weld. The results are indicated improvement in mechanical and microstructural properties of the weld.

Failure evaluation of composite concrete using an acoustic emissions technique

One major problem with concrete is high brittleness with low tensile strength and strain capacity, which can cause sudden failure. Structural Health Monitoring (SHM) is thus very important to detect cracks in initial stages to avoid catastrophic failure. In this research, an acoustic emissions (AE) technique was applied to enable SHM to detect cracks and predict the failure of composite concrete. This physical non-destructive testing process utilises transient elastic waves caused by the rapid release of energy from a localised source within a structure. A low-frequency acoustic emission system was thus tested for economical monitoring of the damage to reinforced composite cubic concrete under compression. Specimens of standard size (150 x 150 x 150 mm) were produced without and with polyamide reinforcement bars. The compression strength of the cubic concrete was then tested according to BS EN 12390-1. Prior to testing, a low-cost single piezoelectric wafer active sensor was applied to the centre of one side of each specimen, which was then connected to a PC’s sound card. Data was successfully recorded using sensors and the real-time of the applied load was recorded using a separate data logger. Traditional AE signal parameters were extracted and used for damage evaluation. The results indicated that the AE system was capable of detecting cracks in representative structures to final failure. Signal amplitude with load versus time showed an increase in AE activity and energy approaching the end of the test, while commutative hits could be used to distinguish between stable and unstable loading stages. The system also detected the initiation of the final failure stage at 72.6% and 83% of the failure load of specimens without and with polyamide reinforcement bars, respectively.

Robotic device for automation of the control of the status of cables in the mining industry

In this work, we propose a design of a robotic device designed to automate the process of nondestructive testing of wire rope equipment. A schematic hydraulic diagram of a robotic device with a description of the logic of work of the system is given. A mathematical model of the dynamics of the system is obtained using the Lagrange formalism. An algorithm for evaluating the control moments necessary for the implementation of programmed motion has been developed. Numerical simulation of the motion corresponding to the mode of approaching the magnetic flaw detector heads to the steel rope has been carried out. The graphs of the traction-speed characteristics and load diagrams of the drives providing the programmed movement of the links of the pantograph mechanism are presented. The results presented in this paper can be used to calculate the parameters of the power section of the electro-hydraulic drives included in the robotic device.

IFFT-Based Microwave Non-Destructive Testing for Delamination Detection and Thickness Estimation

Microwave Non-Destructive Testing (NDT) techniques for dielectric coatings are vital processes in many industrial applications due to their superior defect detection capabilities over traditional NDT methods. However, the limited bandwidth and post-processing complexities of these techniques cause them to fall short of accurately estimating the delamination thickness in such structures. In this paper, a novel low-complexity signal processing method is proposed to estimate the delamination thickness in metal-backed dielectric coatings using bandwidth-limited Open-Ended Rectangular Waveguide (OERW) probes. Here, Inverse Fast Fourier Transform (IFFT) process is used to convert the measured complex reflection coefficients at the surface of the coating to the time domain. Next, the amplitude of a specific time step is used to accurately estimate the delamination thickness without extra time-consuming processing. Using a 3 mm-thick macor samples with machined defects, the proposed technique is validated by correctly estimating delamination thickness down to 0.4 mm using an OERW probe with 13.5 GHz bandwidth. Hence, this technique overcomes the challenge of the OERW's limited bandwidth, which highly affects the possibility of tracking shifting in the peak reflection in the time domain. Moreover, the proposed method does not add to the complexity of the NDT process, which makes it suitable for in-situ real time applications. Hence, following this approach would be of great importance to numerous industries, where accurate thickness estimation of minute delamination in coatings is essential to avoid system failure.

Information Support Methods and Algorithms for Non-destructive Control System Management

The article considers the possibility of using software in conjunction with statistical methods of analysis for continuous monitoring of the activities of non-destructive testing divisions and assessing their condition and effectiveness. Using the developed software allows increasing the efficiency of management and decision-making on the elimination of discrepancies in the structural units of the car repair complex. An assessment of the level of risk associated with the technical condition of non-destructive testing means was carried out. Based on the results of the analysis of normative and technical documentation for the organization of the non-destructive testing process, a system of criteria has been developed that describes the state of equipment with control means. Units having inconsistencies with the requirements for the minimum required amount of equipment and control means were identified. Statistical data on the results of rejection of the brake shoe suspension and the pendulum suspension of freight cars in the structural units of the car repair complex are examined in detail. The kind and numerical characteristics of statistical models of data distribution for each type of part are determined. Structural units were found that significantly exceeded the average frequency of rejection. It is shown that the use of software and statistical analysis methods can improve the efficiency of non-destructive testing units in structural unit management of the car repair complex.