Nondestructive Testing System Research Articles

The Study on Nondestructive Detection Methods for Internal Quality of Korla Fragrant Pears Based on Near-Infrared Spectroscopy and Machine Learning.

Quality control and grading of Korla fragrant pears significantly impact their commercial value. Rapid and non-destructive detection of soluble solids content (SSC) and firmness is crucial to improving this. This study proposes a method combining near-infrared spectroscopy (NIRS) with machine learning for the rapid, non-destructive detection of SSC and firmness in Korla pears. By analyzing absorbance in the 900-1800 nm range, six preprocessing methods-Savitzky-Golay derivative (SGD), standard normal variate (SNV), multiplicative scatter correction (MSC), Savitzky-Golay smoothing (SGS), vector normalization (VN), and min-max normalization (MMN)-were applied to the raw spectral data. uninformative variable elimination (UVE) and successive projections algorithm (SPA) were then used to extract effective wavelengths. Partial least squares regression (PLSR) models were developed for SSC and firmness based on the extracted data. The results showed that all preprocessing and wavelength-extraction methods improved model accuracy. The optimal SSC prediction model was MSC-SPA-PLSR (R = 0.93, RMSE = 0.195), and the best hardness prediction model was MSC-UVE-PLSR (R = 0.83, RMSE = 0.249). This research aids in establishing a non-destructive testing system, offering producers a rapid and accurate quality assessment tool, and provides the food industry with better production control measures to enhance standardization and market competitiveness of Korla pears.

Design and implementation of a nondestructive testing system for magnetic field imaging based on machine learning

This study presents the design of a nondestructive testing (NDT) system for detecting metal defects using a magnetic field sensor array. The system integrates a hardware-software detection framework that includes parallel computation and processing cores, along with multiple anisotropic magnetoresistance (AMR) sensors. These AMR sensors capture subtle variations in the magnetic field, which serve as the foundation for defect identification. The system enables synchronized data acquisition from multiple AMR sensors, achieving multi-axis data fusion and parallel signal processing. Furthermore, the detection system gathers defect features to train an NDT system based on machine learning (ML). Subsequently, ML-generated defect imaging features are processed through an imaging framework, producing magnetic field imaging (MFI) for precise defect localization. The study tested six different metal samples with various defect sizes and types to validate the system. The results demonstrate the system’s ability to accurately detect and identify different defects, highlighting the high precision of magnetic field detection and the overall effectiveness of the proposed system for NDT.

Development of an Open-Source Robotic NDT Solution for Automated Composite Repair Testing

Abstract Non-destructive testing (NDT) plays an important role in aircraft maintenance and repair processes, ensuring the structural integrity necessary for safe operation. The paper presents the design and evaluation of an animated, low-cost robotic NDT system tailored for inspecting composite bonding agents. The system integrates commercially available components, including a three-degree-of-freedom robotic arm and a Raspberry Pi 4B, managed by custom Python software with a user-friendly graphical interface. Mechanical Impedance Analysis (MIA) and Eddy Current Testing (ET) methods were employed to assess the system’s performance on representative test specimens. Results indicate that the system delivers reliable and accurate measurements comparable to commercial tools like the MAUS V, while offering simplicity and modularity. Limitations such as scanning speed and handling of complex geometries are acknowledged, with potential solutions proposed for future enhancement. The system provides an affordable and customizable alternative for NDT automation in the aerospace industry.

An integrated multichannel system for air-coupled CMUT array imaging and guided wave detection applications

Abstract Capacitive micromachined ultrasonic transducers (CMUTs) made by MEMS process have become a new choice for air-coupled ultrasonic transducers due to their high sensitivity, low acoustic impedance and easy arraying. At present, in the air coupling application of CMUT transducer, due to the weak signal strength of single element, the CMUT array usually works in a whole piece, limiting the advantage of the array. Therefore, a multi-channel air-coupled CMUT imaging system with high-voltage DC bias and low-noise high-gain current signal amplification is designed to realize the electronic scanning of our CMUT arrays. The imaging system has 16 transmit and receive channels, and each channel consists of pulse transmitting circuit, AC/DC coupling circuit, impedance matching circuit, low-noise transimpedance amplification circuit, controllable gain amplification circuit and AD circuit. The imaging chain and element control method of our CMUT array were developed to realize the electronic scanning imaging of air-coupled ultrasound. The feasibility of the system for non-destructive testing was also verified via the Lamb wave detection in a metal plate.…

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

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

Numerical simulation and experimental studies of rotational eddy current detection of cracks around rivet holes

Multi-layered aeronautical structures, such as fuselage panels and wings, are composed of several layers of materials such as metal and composites. These structures are prone to damage such as corrosion, cracks and delamination between layers, which can compromise their structural integrity. Eddy current sensors are an essential tool for the inspection and preventive maintenance of multi-layered aeronautical structures, contributing to the safety and reliability of these crucial components. Differential-mode eddy current sensors are particularly well-suited for the inspection of multi-layer aerospace structures around dished-head rivets. The differential measurement improves the detection and characterization of defects in these complex geometries, which are prone to fatigue, corrosion, and other types of damage. The advantages of differential mode are improved sensitivity to small defects, elimination of lift-off variations (distance between the sensor and the surface), reduced electromagnetic interference and detection of defects around rivets, which are critical and difficult to access areas. This work deals with a study of the rotational differential sensor signal according to geometrical parameters of fastener holes defect. It is carried out by an eddy current nondestructive testing system implemented under COMSOL Multiphysics. Indeed, despite its rapidity, the results have shown that the sensor is sensitive to the hole defects when the distances Sensor/Rivet and Lift-off are reduced. As predicted, the experimental results have shown the presence of unsuitable signals caused by the additional Lift-off and the distance Sensor/Rivet. As a solution, these tow parameters should be reduced and kept constant in order to get a better defect signal.

Non-destructive characterization of resistance projection welded joints by ultrasonic and passive magnetic flux density testing

The weld of resistance projection welded joints is not visible from outside. Therefore, visual evaluation is restricted, and visual inspection is not possible at all. So far, the parameters of the welding process are monitored and controlled. In addition, the welds are periodically tested destructively to determine the quality of the welds. No industrial standard has yet been established in the field of non-destructive testing (NDT) for projection welded joints. This study focuses on NDT of projection welds using two different ultrasonic imaging inspection systems and the passive magnetic ux density testing (pMFT) method. The ultrasonic inspection systems commercially available and established in the field of NDT of spot welds. Both systems are originally designed for the NDT of spot welds and not for projection welds. Unlike the ultrasonic systems, the pMFT is still in laboratory status. The method has originally been developed to evaluate spot welds and is also used in this study to evaluate projection welds. The applicability of the investigated systems to projection welding is investigated in order to derive mandatory development steps to achieve reliable results. The pMFT method shows also good results for NDT of spot welds In this contribution, the measurement and evaluation concept of the three NDT systems for projection welded joints is presented. The NDT results are discussed in the context of the corresponding destructive results in terms of tensile forces and fracture areas. Advises for further development of all investigated systems are given.

Three-dimensional reconstruction method for layered structures based on a frequency modulated continuous wave terahertz radar.

The feasibility of employing a continuous-wave terahertz detection system for non-contact and non-destructive testing (NDT) in multi-layered bonding structures is assessed in this study. The paper introduces the detection principle of terahertz frequency modulated continuous wave (FMCW) radar and outlines the two-dimensional (2D) scanning platform, which integrates optical lenses, three linear actuators, a control platform, and data acquisition units. Experimental results on two types of insulation with prefabricated defects demonstrate the capability of terahertz waves for transparent inspection imaging. These results confirm the viability of terahertz FMCW detection technology as an advanced NDT tool for multi-layered bonding structures. However, the inherent limitations of terahertz wavelength and hardware systems pose challenges in discriminating reflection peaks on upper and lower surfaces. To address this issue, a local adaptive empirical wavelet coefficient modal decomposition (LAEWCMD) method is proposed to enhance the longitudinal discrimination ability of terahertz detection. The proposed method involves segmenting the 2D terahertz detection image into regions to differentiate between defective and non-defective areas. Continuous wavelet transforms (CWT) are then applied to the range signals of each region to derive continuous wavelet coefficients (CWCs). Subsequently, empirical mode decomposition (EMD) is performed on the CWCs to decompose them into intrinsic mode functions (IMFs) and residual signals. The 1st IMF is utilized for three-dimensional (3D) reconstruction, and the regions are fused to generate the final output. The effectiveness of the proposed method is validated on aircraft thermal protection structures (TPS), achieving high-precision 3D reconstruction. This offers a novel approach for the application of terahertz computed tomography imaging and NDT.

Design of Ultrasonic Guided Wave Pipeline Non-Destructive Testing System Based on Adaptive Wavelet Threshold Denoising

Design of Ultrasonic Guided Wave Pipeline Non-Destructive Testing System Based on Adaptive Wavelet Threshold Denoising

Designing and fabricating a stationary magnetic particle system for Non-destructive testing

The bench unit, also known as the stationary magnetic particle system or the wet horizontal system, has been designed and fabricated to incorporate both circular and longitudinal magnetization techniques. Its primary purpose is to test machine parts commonly used in various industries, including aviation, automotive, and railway. The system comprises several key components: a transformer, a current control unit, a parameter display and adjustment circuit, a head shot, a coil, and wet magnetic irrigation device. This system is in compliance with international standards and is ready for implementation in companies that require it

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.

Development of an Algorithm of Displacing the Measuring Module of an Automated Nondestructive Testing System

Development of an Algorithm of Displacing the Measuring Module of an Automated Nondestructive Testing System

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.

Efficient MAPoD via Least Angle Regression based Polynomial Chaos Expansion Metamodel for Eddy Current NDT

In this article, a metamodeling approach based on non-intrusive polynomial chaos expansion (PCE) with least angle regression (LAR) method is used in boundary element analysis for a model-assisted probability of detection (MAPoD) study of eddy current nondestructive testing (NDT) systems. The LAR-PCE metamodel represents the NDT system model responses by a set of coefficients with the polynomial basis functions in lieu of pure kernel degeneration accelerated boundary element method (KD-BEM) based physical model. Both the computational accuracy and efficiency of the LAR-PCE metamodel over the ordinary least squares (OLS) based PCE metamodel are demonstrated by testing the 3D eddy current NDT benchmarks with different system setups, flaw lengths and widths. The simulation results show two digits accuracy of the PoD metrics compared with the ones achieved by the KD-BEM based physical model as the benchmark. The LAR-PCE metamodel has remarkable improvements in computational efficiency over the OLS-PCE metamodel and accelerates the MAPoD study.