Nondestructive Testing System Research Articles

Development of an energy-autonomous eddy current sensor system for in-situ component monitoring

Energy-autonomous non-destructive testing (NDT) systems provide new opportunities for structural health monitoring. An NDT system that is energy-autonomous and transmits the recorded data wirelessly can be used in places that are not easily accessible for inspection. In addition, it can provide for continuous monitoring, which can improve the operational safety of various components and structures. This study presents a concept that enables energy-autonomous and wireless structural health monitoring using a splined shaft as a demonstrator. To monitor mechanical overloads, a material sensor is applied to critical areas of these components by a laser heat treatment. The structural change that occurs as a result of an overload can be monitored by the developed smart sensor system. This system consists of a material sensor, a low-cost eddy current sensor, an energy-efficient evaluation unit with an ultra-low-power microcontroller unit (MCU) and a Long-Range Wide Area Network (LoRaWAN) data transmission unit. Wireless data transmission via LoRaWAN provides access to the Industrial Internet of Things network, enabling the collection of NDT data from multiple smart sensors in a cloud and the processing of these data to assess the condition of the component from any location. It is shown that the MCU-based eddy current testing system is able to generate a similar signal quality for material characterisation compared to an industrial eddy current testing system, despite a much more compact design and a significantly higher energy efficiency. The energy autonomy of the smart sensor system is achieved by an energy harvesting system integrated into the splined shaft. In addition, three different testing scenarios are presented, which differ mainly in the scope of data processing and evaluation on the MCU, and thus also in the energy required.

Development of an in-service NDT system for storage tanks

The large storage tank is one of the major infrastructures. Once a leak occurs, it often causes environmental pollution and even catastrophic accidents. In the early years, the method of emptying tanks and cutting plates for defects inspection was adopted to avoid leakage. However, there exist some deficiencies such as large blindness, long downtime and high cost. Since there are many problems in the traditional testing, inspection without emptying the tank and without stopping production is an indispensable technical means to ensure the safe operation of the tank. An in-service non-destructive testing (NDT) system for storage tanks without emptying is developed in this paper, which mainly includes sensors, the signal processing module, the testing crawler, the winding and releasing mechanism and control module et. al. The sensors, signal processing module and testing crawler need to be placed into the tank from the roof man-hole by the crane, while the control module is located outside the tank. The sensor can realize the combined inspection of magnetic field leakage (MFL) and electromagnetic acoustic transducer (EMAT). The laboratory experiments indicate that the system can realize in-service inspection of the corrosion defects on the bottom and works well in water. The new testing system will overcome the shortage of off-line service inspection methods that emptying and cleaning tanks are needed before inspection and environmental risks are involved. These research works guarantee the safe operation of storage tanks and provide an alternative NDT system for storages related industrial projects.

Impact-Echo for Crack Detection in Concrete with Artificial Intelligence based on Supervised Deep Learning

Aging concrete infrastructure such as bridges and tunnels need to be appropriately maintained in their service life because these structures must be employed with ensured safety level. Inspection and maintenance with reasonable measures are typically operated for the reinforced concrete before severe damage and failure are developed. Especially, the crack propagation in concrete can significantly affect the structural integrity, durability and overall performance of structural elements. Effective maintenance strategies are required for material and structural assessment with detection and repair of cracks to prevent further deterioration. Identification of cracks in concrete is effectively operated to extend the service life of structures for mitigating the potential safety hazards and minimize the repair costs. In order to detect the cracks in the concrete structure member, non-destructive testing (NDT) system can be often introduced to satisfy the technical issues in terms of damage evaluation and estimation of repair condition. Currently, various NDT methods have been utilized for quantitative analysis of internal damage/defects using elastic wave method such as impact-echo method, focusing on reflection of P-wave in concrete as wave propagation behavior. In experimental laboratory tests, concrete specimens are usually prepared with interior damages (cracks) which are simulated as embedded plastic plate or styrofoam. In this study, starch- type polysaccharide sheet is used to form the simulated cracks in concrete specimen. This study aims at applying impact-echo method with AI (Artificial Intelligence) to identify the internal crack information based on the waveform characteristics obtained from the elastic wave propagation behavior. The waveform results are converted to frequency spectrum by FFT analysis. Consequently, it is found in this study that AI, which is employed by supervised deep learning models, successfully evaluates the data and displays the probability of crack existence in concrete. Since FFT is a powerful algorithm that quickly converts a signal from the time domain to the frequency domain, it gives efficient analysis to the impact echo method for crack detection with the application of AI system.

Quantitative Measurement and Evaluation of High-Resolution Ultrasonic Sound Fields using a Novel Automated Ultrasonic Immersion Scanner

Ultrasonic probes are an integral part of the automated ultrasonic non-destructive testing and evaluation (NDT&E) systems to detect and size the defects in a wide range of structural materials in production lines. A complete quantitative assessment of the performance characteristics of an application-specific UT probe is needed to be evaluated on the basis of the international standard DIN EN ISO 22232-2. This requirement of full assessment not only improves the quality assurance of the manufactured probes by evaluating the acceptance criteria but also provides the useful technical information to the end-user to optimize the automated ultrasonic testing on-site. In addition, the evaluation of probe characteristics should be carried periodically throughout their service life. In this work, we developed a novel high-precision ultrasonic immersion scanner to evaluate the full ultrasonic probe characteristics which include the squint angle measurement in three different reference planes (XY, XZ, and YZ), RF-signal and its frequency spectrum at water-steel interface, focal distance, focal range, focal width, focal length and also the angle of beam divergence in different planes of the sound field distribution. In the newly developed UT immersion scanner, for the first time, we successfully integrated the high-precision Hexapod with six axes to achieve a few micrometer (~15 µm) spatial-resolution in the measured sound field patterns and a good angular resolution (~0.05°) in the squint angle measurement. In addition, we used a verified UT instrument in accordance with the standard DIN EN ISO 22232-1 to obtain more accurate amplitude values (±0.5 dB) while scanning a test block. The automated scanning, data acquisition, evaluation, visualization and the automated test report generation are carried based on the standard DIN EN ISO 22232-2. The measured sound beam characteristics of both focused and non-focused application-specific ultrasonic probes with center frequencies ranging from 0.2 - 15 MHz using the pulse-echo technique on a 3 mm half-ball steel reflector are presented. In addition, the measured sound beams of an application-specific 5 MHz multi-element transmit-receive (TR) probe using the 3 mm flat-bottomed-hole (FBH) reflector in a steel reference plate are discussed. Finally, the quantitative analysis of the measured sound field results and the acceptance criteria in accordance with DIN EN ISO 22232-2 are discussed.

Continuous Wave Ultrasound Testing Techniques

Currently, the primary method employed for ultrasound inspection is based on sending and detecting ultrasound pulses. Typically, pulse-based methods are essentially time-domain back-reflection methods, and the time-of-flight is the main measured parameter. Recently, continuous-wave methods have been developed in the radar and the fiber-optics fields, which demonstrate significantly better spatial resolution, higher signal-to-noise ratio, and ability to detect reflecting objects at very short distances. It is proposed to use the same approach to develop continuous-wave ultrasound inspection systems. The two main differences between the proposed continuous-wave ultrasonic testing and the classical pulsed ultrasound inspection method are: (i) in the continuous-wave ultrasonic testing method, the transmitted and received signals overlap in the time domain, while in the pulsed ultrasound inspection method the transmitted and received signals are separated in the time; and (ii) in the pulsed ultrasound inspection method the most important parameter is the time delay between the transmitted and received signals, while in the continuous-wave ultrasonic testing method the most informative parameters are the frequency and phase changes in the received signal in respect to modulated transmitted signal. This allows for additional flexibility in the continuous-wave ultrasonic measurements, through control of the frequency modulation. Also, the continuous-wave ultrasonic method potentially offers improved detection range and resolution; improved signal-to-noise ratio due to better energy efficiency and easier filtering; and reduced requirements on the voltage applied to the transducer, which in turn allows the use of simplified low-cost electronics. The theoretical basis of several continuous-wave ultrasound inspection technique is explained, and their advantages and limitations are discussed. Implementation of several prototype continuous-wave ultrasound testing systems is presented. Examples of the use of the systems for non-destructive testing are described.

The Curriculum in NDT Training Have to Include Basics Information Technology to Accomplish Reliability of Automated NDT Result's

Automation in Non-Destructive Testing (NDT) is a reality of modern manufacturing and quality assurance. Information technology applications are simultaneously developed and applied to different fields of NDT methods. The future of doing reliability checks using automated system is inevitable. The results are important to make a variety of decisions regarding the quality of a product and/or service, hence affecting safety and reliability. Depending on artificial intelligence and quantum device development, various NDT training schemes have to adopt a new curriculum to address the issue of the basic knowledge of information technology and automation in NDT. NDT operators are basically dependent on the end results of software, in which the software developer uses a set of algorithms. These are obtained in three categories; 1) Real time database; 2) Synthetic database and 3) Hybrid or combination of them. The developers should know how the NDT systems run and NDT operators in the other hand know the mechanism of the program, so that appropriate action can be taken, in case there is a missed detection, or a detected indication is not very much detrimental to the reliability of the part (Over sizing or wrongly evaluated). For example, a set of algorithms are used to create the focal laws in a phased array ultrasonic test software in space of 1˚ beam steering. Each has a limit of maximum up to 2nd Critical angle. Operators try to copy the same algorithm and set up to 89˚ refraction angle, which will just create creep wave with unreliable results to detect effective size the reflector. Programming knowledge of the operator can effectively eliminate this type of unreliability. In various Schemes of NDT Syllabus which are in common place to employ and train plus certify operators does not have it; actually, the operators do the scope of work which does includes application of Artificial Intelligence (AI) and Software. With the development of Q coupler (Quantum Computing) system, it is obvious to adopt the upcoming technology into the application of NDT industry. Training needs to update the curriculum accordingly. The current topic has intended to focus on the training gap and to address related kind of unreliability.

Development of an Infrared Marker based Encoder System as a Non-Contact Positioning System for Ultrasonic Probes

The digitalization of testing procedures is one of the challenges in the development of modern non-destructive testing systems. In order to guarantee a high level of inspection reliability, the assignment of measurement data to the measurement position plays an important role as well as the optimal inspection hardware. In a cooperative research and development project, an optical tracking system has been developed with which it is possible to determine the positions of different ultrasonic probes in space without contact. Thus, the position of the measurement is linked to the measurement results directly. Infrared LED markers attached to the ultrasonic probes are used for this purpose. The position of the markers are tracked in space with a camera. By linking several cameras and trackers, a positional accuracy of a few millimeters can be achieved for a camera specimen distance of 2 m. The more cameras are used the bigger the investigated part can be. For the tracking system, an existing optical camera system is coupled with a conventional of the shelve ultrasonic phased array device by means of a newly developed universal encoder. Different single transducer probes or phased array probes can be used. The costly and time consuming use of mechanical encoders is thus eliminated. This combination enables the further digitalization of hand-guided ultrasonic testing precisely in those areas where robot-based testing is not feasible. Additionally, a much easier way of documentation is possible. Due to the exact position determination a better evaluation of the measurement data can be carried out via a subsequent 3D display of the ultrasound data.

Magnetic characterisation of ferromagnetic material

In magnetic and electromagnetic non-destructive testing, the physical properties of the material are often not well known or completely unknown. The design of the non-destructive testing systems that provide the magnetisation is often oversized in order to get enough magnetic saturation (e.g. in magnetic flux leakage method or in magnetoscopy method). An improvement of the device performances, expressed usually by the signal to noise ratio, can be obtained only when the designer of the device well knows the material characteristic in terms of magnetic curve, the curve that links the magnetic field strengths to the magnetic flux density. A good device must be able to saturate the material sample under test but not to overcame determinate values. In fact, when the magnetisation is low, the leakage of the flux is negligible, while when the magnetisation is too strong the material tends to be like air and the leakage flux is negligible too. The experimental characterisation is derived from the technique adopted for the testing of soft magnetic material adopted in electrical machines or electromechanical actuators. In the present paper will be presented some material characterisation useful for the non-destructive testing of railway track, metallic ropes or reinforcement iron.

Detection and classification of invisible weld defects by magneto-optical imaging under alternating magnetic field excitation

Aiming at the difficult to detect invisible weld defects, a magneto-optical (MO) imaging non-destructive testing (NDT) system excited by an alternating magnetic field is proposed for feature extraction and detection classification of invisible weld defects. The relationship between the MO image features and the magnetic field intensity is analyzed based on the Faraday MO effect. A magnetic dipole model is proposed to study the magnetic field distribution on weld defect. A three-dimensional finite element model of invisible weld defects (with a width of 0.01mm) is established, and the distribution of leakage magnetic field for different types of invisible defects is analyzed. In order to detect different invisible weld defects under the excitation of alternating magnetic field, MO imaging NDT experiments are carried out. The effectiveness of the finite element model is verified by the experiment. The gray value of the MO image can match the corresponding leakage magnetic field intensity. The Tamura method and gray-level co-occurrence matrix (GLCM) method are used to extract the texture features of natural invisible weld defect’s MO image, and these texture features of MO images are used as input data for the defect classification model established using back propagation (BP) neural network. Experimental results show that the classification accuracy of the GLCM + Tamura-BP model is higher than that of the GLCM-BP model, and its overall classification accuracy reaches 91.1%, indicating that this model can effectively and accurately classify natural invisible weld defects.

Design and Experiment of Non-destructive Testing System for Moisture Content of In-situ Maize Ear Kernels Based on VIS-NIR

To facilitate rapid, non-destructive, cost-effective continuous detection of Moisture Content in corn kernels, a Near-infrared (VIS-NIR) spectroscopy based in-situ maize ear moisture detection device was developed, utilizing machine learning for predictive modeling. Field experiments(30~35℃) assessed three preprocessing algorithms: z-score normalization (ZS), Orthogonal Signal Correction (OSC), and a ZS-OSC combination, with ZS-OSC selected for its superior performance (R2≥0.90, RMSE≤2.12%, RPD＞2.9). Spectral imaging from 410-940nm was used to develop moisture prediction models via Partial Least Squares Regression (PLSR) and Support Vector Machine (SVM), where PLSR is suited for single variety (R2≥0.82, RMSE≤2.62%, RPD≥2.2) and SVM for both single and mixed varieties. Additionally, grain temperature's impact on model performance was analyzed, showing decreased accuracy across temperatures of 30~35℃, 35~40℃, and 40~45℃. The final device and models excelled in 30~35℃ field tests, achieving R2≥0.88, RPD＞2.5, RMSE≤0.901%, with less than 1.82% deviation between predicted and actual values, and all classification indices over 84.38%. The device is proven accurate and effective for corn grain moisture detection, offering valuable insights for in-situ maize moisture content analysis.

基于可见/近红外光谱的鲜枣可溶性固形物在线检测

Soluble solid content (SSC) is one of the important evaluation indexes of the internal quality and taste of fresh jujube. In order to realize the online nondestructive detection of SSC of fresh jujube, this paper took Huping jujube as the research object, adopted self-constructed nondestructive online testing system to collect the spectral information of jujubes (350~2500 nm), and studied the influence of the rotational speed of 4 r/min on the online prediction model of SSC of jujube. Kennard-Stone (KS) algorithm was used to divide the sample into correction set and prediction set. Six commonly used preprocessing methods such as SG smoothing (S-G), multiplicative scatter correction (MSC), standard normal variate (SNV), orthogonal signal correction (OSC), first derivative (FD), and second derivative (SD) were applied to the spectral data, and the regression coefficient (RC) algorithm and the successive projections algorithm (SPA) were utilized to select informative wavelengths, and a quantitative prediction model for the SSC of Huping jujube was established using partial least squares regression (PLSR). The results indicate that the PLSR prediction model established by preprocessing the original spectrum with OSC and combining it with RC algorithm to select characteristic wavelengths was optimal. Therefore, when predicting the SSC of Huping jujube, the optimal model was OSC-RC-PLSR, and the correlation coefficients of the correction set and prediction set were 0.846 and 0.782, respectively, and the corrected root mean square error (RMSEC) and predicted root mean square error (RMSEP) were 1.962 and 2.247, respectively. The results show that non-destructive detection of soluble solid content of jujube can be achieved by combining visible-near-infrared spectroscopy and appropriate regression model, which provides an innovative way for online sorting and identifying fresh jujube.

Development and fusion of NDT classifiers for defect detection on underwater structures

Vessel hull inspection is a complex and labor-intensive task, motivating the utilization of data fusion from complementary nondestructive testing (NDT) techniques to boost reliability and reduce detection uncertainties. In this study, an underwater robot equipped with three NDT systems – monocular RGB camera, eddy current (ECT), and ultrasound (UT) – is employed to assess a 12.7 mm thick ASTM-A36 carbon steel plate with artificially induced defects – coating loss, crack, pitting, and generalized corrosion. A classifier is developed for each NDT system for defect classification. Mask R-CNN is used for the camera data, achieving a mean average precision of 67.7% across three defect classes. A multilayer perceptron is used to classify the ECT data into six defect types and the non-defective class, attaining an accuracy of 98.8% on the test set. For UT data, a rule-based classifier based on A-scan-derived features distinguishes four defect classes. Subsequent to spatial synchronization, these classifier outputs are fused at the decision level, where redundancies between the camera and ECT classifiers are eliminated. Their outcomes are concatenated with the UT classifier results, culminating in a comprehensive detection map capable of representing eleven distinct defect classes. The classifiers and fusion are evaluated on a novel plate with unseen artificial defects. The camera and UT classifiers excel in detecting all classes for which they were specifically trained. In contrast, ECT exhibits a more limited capability, detecting only 21% of the specified defect classes. The findings underscore the potential of NDT data fusion to enhance inspection reliability by minimizing redundancies and extending the detection range.

Relevance of monitoring residual stresses and the need to reduce them

The objective of the study is to show the significant impact of taking into account the actual values of residual stresses on the strength and resource of safe operation of nuclear power facilities. Generally accepted approaches of strength physics and fracture mechanics were used to determine strength and service life. The degree of influence of residual stresses on the strength and service life of pipeline elements in the case of a cyclically acting load, under static load, when there is a danger of brittle fracture, and in the case of corrosion is investigated. The objects of the study were pipelines of nuclear power plants. It is noted that the current state of science and technology has made it possible to create a technique for non-destructive testing of mechanical stresses acting in metal structures based on the use of the acoustoelasticity method. Currently, on the basis of this method, a method for measuring residual welding and installation stresses in pipelines has been developed and certified for use in the field of atomic energy use. The measurement technique provides for the determination of membrane and bending stresses in annular sections located on rectilinear sections of pipelines. The values of stresses in the structural elements of pipelines and residual welding stresses in the deposited metal of welded joints are determined using ratios based on the use of the balancing principle. The relevance of introducing into the procedure for monitoring the technical condition of pipelines and equipment of nuclear power plants the procedure for determining the actual level of residual stresses, which significantly increases the reliability of the assessment of their strength and service life, is shown. It is proved that in order to implement the procedure for determining the actual level of residual stresses, it is necessary to use a non-destructive testing system for residual welding and installation stresses using the acoustoelasticity method based on a measurement technique that allows determining the actual values of residual stresses with established error characteristics.

Automated Wall Thickness Evaluation for Turbine Blades Using Robot-Guided Ultrasonic Array Imaging

Abstract Nondestructive testing has become an essential part of the maintenance of modern gas turbine blades and vanes since it provides an increase in both safety against critical failure and efficiency of operation. Targeted repairs of the blade's airfoil require localized wall thickness information. This information, however, is hard to obtain by nondestructive testing due to the complex shapes of surfaces, cavities, and material characteristics. To address this problem, we introduce an automated nondestructive testing system that scans the part using an immersed ultrasonic array probe guided by a robot arm. For imaging, we adopt a two-step, surface-adaptive Total Focusing Method (TFM) approach. For each test position, the TFM allows us to identify the outer surface, followed by calculating an adaptive image of the interior of the part, where the inner surface's position and shape are obtained. To handle the large volumes of data, the surface features are automatically extracted from the TFM images using specialized image processing algorithms. Subsequently, the collection of 2D extracted surface data is merged and smoothed in 3D space to form the outer and inner surfaces, facilitating wall thickness evaluation. With this approach, representative zones on two gas turbine vanes were tested, and the reconstructed wall thickness values were evaluated via comparison with reference data from an optical scan. For the test zones on two turbine vanes, average errors ranging from 0.05 mm to 0.1 mm were identified, with a standard deviation of 0.06–0.16 mm.

Трещинообразование натуральной и модифицированной прессованием древесины березы повислой (Betula pendula Roth): эффект показателя внутреннего трения под влиянием внешних возмущений

Obtaining information about the presence of cracks in raw materials, blanks and wood products is neces-sary to make a decision on the purposes of its subsequent processing and operation. The method for diagnosing cracks in wood is based on measuring internal friction. For prepared samples of natural and modified wood, sawn from the stem part of drooping birch (Betula pendula Roth) trees growing in Khlevensky Forestry, Lipetsk region. (52.184130, 39.110463, ASL 157m), exposed to radial and tangential directions with ultrasound (frequency 24.5 kHz, exposure 0-20 minutes, step 5 minutes) and pulsed magnetic field (strength - 0.3 T, exposure 0-2 minutes, step 0.5 minutes). Next, the internal friction of the samples was studied on an experimental setup by measuring the logarithmic damping decrement based on free-bending vibrations. The absolute values of the dimensionless coefficient of internal friction Q-1, as the main structural parameter for samples of natural and modified wood, were obtained at a significance level of p=0.95: for humidity, in the presence of one crack, Q-1 decreased by 7.04% (D=0.08), in the presence of two cracks - by 8.4% (D=0.15), in the presence of three cracks - by 9.06% (D=0.15); for ultrasound in the presence of one crack Q-1 decreased by 7.17% (D=0.05), in the presence of two cracks - by 8.46% (D=0.05), in the presence of three cracks - by 9.12% (D=0.09); for a pulsed magnetic field in the presence of one crack Q-1 decreased by 7.14% (D=0.05), in the presence of two cracks - by 8.39% (D=0.09), in the presence of three cracks - by 9.02% (D=0.09). When testing the samples of natural wood and pressure-modified drooping birch (Betula pendula Roth) wood, we obtained an asymptotic equation was obtained for ap-proximating the dependence of the decrease in Q-1 on the number of cracks, with the approximation value R2=0.994. The study of the dependence of internal friction on the process of crack formation in various types of wood provides preparation for the next stage - the construction of a prototype system for non-destructive testing of defects.

APPLICATION OF THE RED PITAYA PLATFORM IN THE TECHNOLOGY OF PROTOTYPING AUTOMATED EDDY CURRENT TESTING SYSTEMS

Automated eddy current non-destructive testing has an important role in the quality inspection system for products made of conductive materials both at the production stage and during their operation. The appearance of novel alloys, the complexity of product geometry and inspection conditions, and the increased requirements for the reliability and accuracy of inspection results stimulate the acceleration process of creating new eddy current inspection tools. The technology of prototyping makes it possible to solve this problem. The purpose of the article is to review the functionality and technical characteristics of Red Pitaya for use in the technology of prototyping eddy current inspection, as well as to create a prototype architecture of an automated eddy current inspection system based on it.The choice of the Red Pitaya platform as a convenient tool for prototyping automated systems was made due to its functionality, reliability, and availability. In general, the article highlights the advantages and prospects of using the Red Pitaya platform in the prototyping of automated eddy current non-destructive testing systems. The aspects of the Red Pitaya hardware and its capabilities for expanding the functionality, which allows to create highly efficient and flexible control systems, are considered in detail. The compatibility of Red Pitaya with other devices and accessories is considered, which significantly increases its versatility and adaptability to various requirements and applications.The article highlights the importance of using the Jupyter Notebook application in combination with Red Pitaya as a convenient tool for software development. This helps to facilitate the process of creating and programmatically implementing complex signal processing algorithms in eddy current control systems, and provides flexibility in creating new software products.Modern trends and prospects for the development of eddy current testing, market needs, and the ability to adapt to different application scenarios are taken into account in the proposed architecture of the prototype automated eddy current testing system.

Design of submarine pipeline inspection system based on ultrasound

A design of a non-destructive testing system for underwater pipelines based on ultrasound has been proposed, consisting of a three-axis control system and an ultrasonic thickness measurement system. This can achieve full coverage testing and real-time data transmission of pipeline wall thickness through integrated composite rotating mechanisms, travel driving mechanisms, pipeline surface preprocessing mechanisms, data acquisition systems, etc., with high automation and the ability to achieve pipeline based testing. Among them, the pipeline surface pretreatment mechanism includes a polishing mechanism and a circulating immersion system, which are used to improve the coupling effect between the pipeline wall and the ultrasonic probe. This non-destructive testing system can achieve high detection efficiency and testing accuracy, effectively solving the current problems of undersea pipeline leakage and inaccurate positioning of corrosion damage. At present, the problem of global and efficient scanning still needs to be solved, as otherwise it will be difficult to further improve work efficiency. Highlights A design of a non-destructive testing system for underwater pipelines based on ultrasound has been proposed, consisting of a three-axis control system and an ultrasonic thickness measurement system The system can realize scanning detection with high efficiency and automation The system is equipped with an automatic coupling mechanism to ensure the stability and reliability of the work

Non-destructive test system to monitor hydration and strength development of low CO2 concrete

Application of supplementary cementitious materials for production of low CO2 concrete affects the reaction kinetics, which alters the setting time and strength development. The different early-age behavior is of concern for quality control of concrete. Non-destructive test is very useful for monitoring the quality of low CO2 binder systems. This paper presents a new technique to monitor the electrical conductivity and temperature at different depths of hydrating concrete. Indices from monitoring system (conductivity, maturity and formation factor) are compared with data from widely-used methods (ultrasonic pulse velocity, penetration resistance and isothermal calorimetry). Results show that indices from the system can replicate the hydration evolution, setting time and compressive strength of low CO2 concrete. Electrical conductivity of concrete is very sensitive to mineral reactions and it reflects the hydration kinetic consistent with evolution of heat release. Linear correlations are found for penetration resistance in relation to ultrasonic pulse velocity, formation factor and maturity, respectively. The effects of binder type and water-to-binder ratio on hardening are strongly dependent on temperature. The proposed approach enables to include all these factors in characterizing the hardening process of concrete onsite. It is shown that formation factor performs better than ultrasonic pulse velocity on indicating the setting process. Formation factor is also a good parameter for quantitative description of compressive strength development, which is independent of the binder types, mixture proportions and curing ages.

All-fiber photoacoustic system for large-area nondestructive testing

Nondestructive testing (NDT) is of paramount importance in ensuring the safe operation of equipment. Among various NDT techniques, ultrasonic NDT has garnered widespread attention due to its high sensitivity, fast speed, and accurate defect location. Photoacoustic NDT, a burgeoning field in ultrasonic NDT, is particularly attractive due to its immunity to electromagnetic interference. However, existing photoacoustic NDT systems suffer from inadequate excitation intensity and complex ultrasonic signal characteristics, impeding large-area NDT and accurate crack visualization. In this study, we present an all-fiber photoacoustic system for large-area NDT. To address the issues, we have developed a photoacoustic generator unit that can be optimized and controlled to generate stronger ultrasonic signals. Furthermore, we have employed mode decomposition to simplify the detected ultrasonic signals by mitigating the acoustic impedance mismatch-induced mode mixing problem in the system. As a result, the technology allows for large-area crack monitoring of up to 50*50 cm2 with an improved resolution of 1 mm. The present technology paves the way for high-resolution equipment crack monitoring with substantially enhanced accuracy in various environments.

Improved long pulse excitation infrared nondestructive testing evaluation.

In this paper, an improved long-pulse excitation infrared nondestructive testing method is proposed, and a homogeneous pulse thermography (HPT) system is built. Based on the proposed new pulse excitation system, the problem of uneven heating in pulsed infrared non-destructive testing (NDT) has been effectively improved, and the signal-to-noise ratio of thermal images has been improved. Finally, the results of the experimental analysis and discussion show that the improved pulsed infrared NDT system greatly improves the defect detection rate and the reliability of the quantitative analysis of defect depth compared with the traditional pulsed detection system.