Search Results (99)

Railway infrastructures necessitate the inspection of various elements to ensure operational safety. This study concentrates on five key components: rail, sleepers and ballast, track geometry, and catenary. The operational principles of the primary defect measurement sensors are elaborated, emphasizing the use of ultrasound, eddy currents, active and passive optical elements, accelerometers, and ground penetrating radar. Each sensor type is evaluated in terms of its advantages and limitations. Examples of mobile inspection platforms are provided, ranging from laboratory trains to draisines and track trolleys. The authors foresee future trends in railway inspection, including the implementation of IoT sensors, autonomous robots, and geospatial intelligence technologies. It is anticipated that the integration of sensors within both infrastructure and rolling stock will enhance maintenance and safety, with an increased utilization of autonomous robotic systems for hazardous and hard-to-reach areas. Full article

The eddy current testing (ECT) technique enables efficient and non-destructive conductivity measurement. However, conventional ECT is significantly influenced by the thickness of the material, often resulting in the arbitrary selection of excitation frequency. In addition, complex inverse calculations in the eddy current analytical model pose challenges for practical application. This paper proposes a method for measuring the conductivity of non-ferromagnetic materials based on a simplified analytical model. Firstly, the classical Dodd–Deeds analytical model is simplified based on the electromagnetic properties of materials under high-frequency conditions, resulting in a simplified model that directly relates the coil impedance phase to the material’s conductivity. Furthermore, in combination with a finite element method (FEM) analysis, a frequency selection criterion is proposed, and a corresponding measurement method is developed. This method enables direct conductivity calculation by substituting the measured coil impedance phase into the simplified model. Finally, experiments were conducted to verify the effectiveness of the proposed method. The results demonstrate that the proposed method accurately measures the conductivity of non-ferromagnetic materials over a range of 0.5–58.5 MS/m, achieving absolute and relative errors less than 1.05 MS/m and 1.83%, respectively, without requiring complex inversion calculations or multiple calibrations. This advancement in measurement principles provides a new theoretical foundation and technical pathway for developing online inspection systems and portable instrumentation. Full article

In power inspection fields, snake-like robots are often used for transmission line inspection tasks, requiring accurate identification of various power fittings. However, traditional visual sensors perform poorly under varying light intensity and complex background conditions. This paper proposes a non-visual perception method for the high-precision classification of different power fittings (e.g., vibration dampers, suspension clamps, and tension clamps) in snake-like robot transmission line inspection for high-voltage lines. This method, unaffected by light intensity changes, uses machine learning to classify the magnetic induction electromotive force signals around the fittings. First, the Dodd–Deeds eddy current model is used to analyse the magnetic field changes around the transmission line fittings and determine the induction coil distribution. Then, the concept of condition number and singular value decomposition (SVD) are introduced to analyse the impact of detection position on classification accuracy, with optimal detection positions found using the particle swarm optimization algorithm. Finally, a BP neural network optimised by a genetic algorithm is used for power fitting identification. Experiments show that this method successfully identifies vibration dampers, tension clamps, suspension clamps, and transmission lines at detection distances of 5 cm, 10 cm, 15 cm, and 20 cm, with accuracies of 99.8%, 97.5%, 95.1%, and 92.5%, respectively. Full article

This paper presents a discrete Fourier transform (DFT)-based signal processing framework for eddy current non-destructive testing (NDT), aiming to enhance signal quality for precise defect characterization in critical nuclear components. By enforcing strict periodicity matching between sampling points and signal frequencies, the proposed approach mitigates DFT spectrum leakage, validated via phase linearity analysis with errors of ≤0.07° across the 20 Hz–1 MHz frequency range. A high-resolution 24-bit analog-to-digital converter (ADC) hardware architecture eliminates complex analog balancing circuits, reducing system-wide noise by overcoming the limitations of traditional 16-bit ADCs. A 6 × 6 mm application-specific integrated circuit (ASIC) for array sensors enables three-dimensional (3D) defect visualization, complemented by Gaussian filtering to suppress vibration-induced noise. Our experimental results demonstrate that the digital method yields smoother signal waveforms and superior 3D defect imaging for nuclear power plant tubes, enhancing result interpretability. Field tests confirm stable performance, showcasing clear 3D defect distributions and improved inspection performance compared to conventional techniques. By integrating DFT signal processing, hardware optimization, and array sensing, this study introduces a robust framework for precise defect localization and characterization in nuclear components, addressing key challenges in eddy current NDT through systematic signal integrity enhancement and hardware innovation. Full article

Accurately measuring the thickness of the oxide film that accumulates on nuclear fuel assemblies is critical for maintaining nuclear power plant safety. Oxide film thickness typically ranges from a few micrometers to several tens of micrometers, necessitating a high-precision measurement system. Eddy current testing (ECT) is commonly employed during poolside inspections due to its simplicity and ease of on-site implementation. The use of swept frequency technology can mitigate the impact of interference parameters and improve the measurement accuracy of ECT. However, as the nuclear assembly is placed in a pool for inspection, a cable several dozen meters in length is used to connect the ECT probe to the instrument. The measurement is affected by the transmission line and its effect is a function of the operating frequencies, resulting in errors for swept frequency measurements. This paper proposes a method for precisely measuring oxide film thickness based on the swept frequency technique and long transmission line impedance correction. The signals are calibrated based on a transmission line model of the cable, effectively eliminating the influence of the transmission cable. A swept frequency signal-processing algorithm is developed to separate the parameters and calculate oxide film thickness. To verify the feasibility of the method, measurements are conducted on fuel cladding samples with varying conductivities. It is found that the method can accurately assess oxide film thickness with varying conductivity. The maximum error is 3.42 μm, while the average error is 1.82 μm. The impedance correction reduces the error by 66%. The experimental results indicate that this method can eliminate the impact of long transmission cables, and the algorithm can mitigate the influence of material conductivity. This method can be utilized to measure oxide film thickness in nuclear power maintenance inspections following extensive testing and engineering optimization. Full article

Pole tower grounding bodies are part of the normal structure of the power system, providing relief from fault currents and equalizing overvoltage channels. They are important devices; however, in the harsh environment of the soil, they are prone to corrosion or even fracture, which in turn affects the normal utilization of the transmission line, so accurately assessing the condition of grounding bodies of the power grid is critical. To assess the operational status of a grounding body in a timely manner, this paper proposes a multi-parameter pulsed eddy current (PEC) time-domain characteristic signal corrosion classification method for the detection of the state of a pole tower grounding body. The method firstly theoretically analysed the influence of multi-parameter changes on the PEC response time-domain feature signal caused by grounding body corrosion and extracts the decay time constant (DTC), and the decay time constant stabilization value (DTCSV) and time to stabilization (TTS) were obtained based on the DTC time domain characteristics for describing the corrosion of the grounding body. Subsequently, DTCSV and TTS were used as inputs to a support vector machine (SVM) to classify the corrosion of the grounding body. A simulation model was constructed to investigate the effect of multiparameter time on the DTCSV and TTS of the tower grounding body based on the single-variable method, and the multiparameter time-domain characterization method used for corrosion assessment was validated. Four defects with different corrosion levels were classified using the optimized SVM model, with an accuracy rate of 95%. Finally, a PEC inspection system platform was built to conduct classification tests on steel bars with different degrees of corrosion, and the results show that the SVM classification model based on DTCSV and TTS has a better discriminatory ability for different corrosive grounders and can be used to classify corrosion in the grounders of poles towers to improve the stability of power transmission. Full article

In recent years, with the increasing construction mileage of oil and gas pipelines (OGPs), the aging problem of OGPs has become increasingly prominent, so, ensuring the safety of OGPs is of great significance. In addition, the safety of OGP transportation is also an important component of pipeline integrity. Therefore, to ensure the safety of OGP transportation, regular OGP inspections should be carried out. During this process, defects in the OGP and measured wall thickness information should be recorded to provide a basis for subsequent pipeline repair or replacement. This study analyzes the literature on pipeline testing and reviews approximately eighty articles. Based on these articles, we summarize the types of common OGP defects and review the basic principles of various non-destructive testing methods for pipelines, including electromagnetic acoustic transducer inspection, magnetic flux leakage testing, ultrasonic testing, and eddy current testing. We also provide a detailed introduction to the applications and innovative testing methods based on the above OGP inspection methods. Finally, an analysis and outlook on the future research focus of OGP inspection technology are presented. This research suggests that different detection methods should be used for different types of defects, such as using the magnetic leakage method for the internal detection of natural gas pipelines. Full article

Multi-layer conductive structures, especially those with features like bolt holes, are vulnerable to hidden corrosion and cracking, posing a serious threat to equipment integrity. Early defect detection is vital for implementing effective maintenance strategies. However, the subtle signals produced by these defects necessitate highly sensitive non-destructive testing (NDT) techniques. Analytical modeling plays a critical role in both enhancing defect-detection capabilities and guiding the design of highly sensitive sensors for these complex structures. Compared to the finite element method (FEM), analytical approaches offer advantages, such as faster computation and high accuracy, enabling a comprehensive analysis of how sensor and material parameters influence defect detection outcomes. This paper introduces a novel T-core eddy current sensor featuring a central air gap. Utilizing the vector magnetic potential method and a truncated region eigenfunction expansion (TREE) method, an analytical model was developed to investigate the sensor’s interaction with multi-layer conductive materials containing a hidden hole. The model yielded closed-form expressions for the induced eddy current density and coil impedance. A comparative study, implemented in Matlab, analyzed the eddy current distribution generated by T-core, E-core, I-core, and air core sensors under identical conditions. Furthermore, the study examined how the impedance of the T-core sensor changed at different excitation frequencies between 100 Hz and 10 kHz when positioned over a multi-layer conductor with a hidden air hole. These findings were then compared to those obtained from E-core, I-core, and air-core sensors. The analytical results were validated through finite element simulations and experimental measurements, exhibiting excellent agreement. The study further explored the influence of T-core design parameters, including the air gap radius, dome radius, core column height, and relative permeability of the T-core material, on the inspection sensitivity. Finally, the proposed T-core sensor was used to evaluate crack and hole defects in conductors, demonstrating its superior sensitivity compared to I-core and air core sensors. Although slightly less sensitive than the E-core sensor, the T-core sensor offers advantages, including a more compact design and reduced material requirements, making it well-suited for inspecting intricate and confined surfaces of the target object. This analytical model provides a valuable tool for designing advanced eddy current sensors, particularly for applications like detecting bolt hole defects or measuring the thickness of non-conductive coatings in multi-layer conductor structures. Full article

Zr-2.5%Nb pressure tubes (PTs) house uranium fuel bundles in the fuel channels of CANDU^® nuclear reactors. Preventing a failure mode caused by contact of the PT with an outer calandria tube (CT) is performed by inspection using eddy current (EC) testing and ultrasonic testing (UT) to measure the PT-CT gap. EC gap measurements are particularly sensitive to circumferential variation of the PT’s electrical resistivity due to microstructural variations. A full-factorial experiment was performed to examine the statistical significance of variations in the EC test parameters and manufacturing conditions on the average circumferential electrical resistivity of as-manufactured PTs. It was found that 79% of the variance in the data could be attributed to variations caused by any of the test factors or combinations of test factors. The parameters that accounted for the majority of the variance were: (1) heat treatment (HT); (2) HT and EC frequency; (3) probe inner or outer surface placement; and (4) EC frequency. Measurements of circumferential resistivity showed up to ±2.3% variation from the average of either surface. HT caused the average PT resistivity to decrease at a rate of $1.53\pm 0.08 {\displaystyle \frac{\mathsf{\mu }\mathsf{\Omega }·\mathrm{c}\mathrm{m}}{\log \left(\mathrm{h}\mathrm{r}\right)}}$ and $1.1\pm 0.4{\displaystyle \frac{\mathsf{\mu }\mathsf{\Omega }·\mathrm{c}\mathrm{m}}{\log \left(\mathrm{h}\mathrm{r}\right)}}$ for inner and outer PT surfaces, respectively. The results are correlated with differences reported in the literature in the average ${\beta }_{Zr}$ ribbon thickness in the axial-transverse cross-section between inner and outer PT surfaces. The results demonstrate potential for EC-based resistivity measurements to characterize variations and changes in the microstructure of Zr-2.5%Nb PT material. Full article

The maintenance of the surface of steel structures is crucial for ensuring the quality of shipbuilding cranes. Various types of wall-climbing robots have been proposed for inspecting diverse structures, including ships and offshore installations. Given that these robots often operate in outdoor environments, their performance is significantly influenced by wind conditions. Consequently, understanding the impact of wind loads on these robots is essential for developing structurally sound designs. In this study, SolidWorks software was utilized to model both the wall-climbing robot and crane, while numerical simulations were conducted to investigate the aerodynamic performance of the magnetic wall-climbing inspection robot under wind load. Subsequently, a MATLAB program was developed to simulate both the time history and spectrum of wind speed affecting the wall-climbing inspection robot. The resulting wind speed time-history curve was analyzed using a time-history analysis method to simulate wind pressure effects. Finally, modal analysis was performed to determine the natural frequency and vibration modes of the frame in order to ensure dynamic stability for the robot. The analysis revealed that wind pressure predominantly concentrates on the front section of the vehicle body, with significant eddy currents observed on its windward side, leeward side, and top surface. Following optimization efforts on the robot’s structure resulted in a reduction in vortex formation; consequently, compared to pre-optimization conditions during pulsating wind simulations, there was a 99.19% decrease in induced vibration displacement within the optimized inspection robot body. Modal analysis indicated substantial differences between the first six non-rigid natural frequencies of this vehicle body and those associated with its servo motor frequencies—indicating no risk of resonance occurring. This study employs finite element analysis techniques to assess stability under varying wind loads while verifying structural safety for this wall-climbing inspection robot. Full article

The robotization of the non-destructive inspection of aircraft is essential for improving the accuracy and duration of performed inspections, being an integral part of inspection and data management systems within the currently developed NDT 4.0 concept. In this paper, the authors presented the design and testing of a universal mobile platform with interchangeable sensing systems for the non-destructive inspection of aircraft structures with various angles of inclination. As a result of the performed studies, a low-cost approach of automation of existing measurement devices used for inspection was proposed. The constructed prototype of the mobile platform was equipped with eddy current testing probe and successfully passed both laboratory and environmental tests, demonstrating its performance in various conditions. The presented approach confirms the effectiveness of the automation of the inspection process using climbing robots and defining the directions of possible development of automation in non-destructive testing in aviation. Full article

Complex multiphase flow in oil and gas pipelines raises safety risks. Magnetic flux leakage (MFL) detection effectively identifies pipeline defects. However, the high-speed movement of MFL inspection tools induces motion-induced eddy currents (MIECs), complicating defect recognition and quantification. Most prior research has primarily focused on rectangular defects, leaving a gap in understanding the impact of MIECs on weld defects. This paper proposes the amplitude and shape deformation coefficients to analyze the influence of velocity on various weld defects, including internal reinforcement, lack of penetration, crack, external corrosion, internal corrosion, porosity, and lack of fusion. Utilizing these coefficients, this study examines the influence of the defect size and magnetizer configuration on these velocity-induced effects. The results show that the shape deformation coefficients range from 2.75 to 3.57 for Bx and from −0.13 to −0.3 for By, indicating a significant change in the MFL signal shape at 10 m/s compared to 0 m/s. The amplitude deformation coefficients for lack of penetration, internal corrosion, and porosity range from −0.01 to 0.1 for Bx, and from 0.86 to 0.98 for By, suggesting a decrease in peak-to-peak values. In contrast, other defects exhibit an increase in peak-to-peak values, indicating that the velocity effect may enhance the MFL signal. Also, the defect size and magnetizer configuration can affect the velocity effect on signals. These findings provide essential guidance for quantifying defect sizes and a solid foundation for designing more effective magnetization devices. Full article

The accurate detection and quantification of defects is vital for the effectiveness of the eddy current nondestructive testing (ECNDT) of carbon fiber-reinforced plastic (CFRP) materials. This study investigates the identification and measurement of three common CFRP defects—cracks, delamination, and low-velocity impact damage—by employing the You Only Look Once (YOLO) model and an improved Eddy Current YOLO (EDC-YOLO) model. YOLO’s limitations in detecting multi-scale features are addressed through the integration of Transformer-based self-attention mechanisms and deformable convolutional sub-modules, with additional global feature extraction via CBAM. By leveraging the Wise-IoU loss function, the model performance is further enhanced, leading to a 4.4% increase in the mAP50 for defect detection. EDC-YOLO proves to be effective for defect identification and quantification in industrial inspections, providing detailed insights, such as the correlation between the impact damage size and energy levels. Full article

In the field of railroad safety, the effective detection of surface cracks is critical, necessitating reliable, high-speed, non-destructive testing (NDT) methods. This study introduces a hybrid Eddy Current Testing (ECT) probe, specifically engineered for railroad inspection, to address the common issue of “lift-off noise” due to varying distances between the probe and the test material. Unlike traditional ECT methods, this probe integrates transmit and differential receiver (Tx-dRx) coils, aiming to enhance detection sensitivity and minimise the lift-off impact. The study optimises ECT probes employing different transmitter coils, emphasising three main objectives: (a) quantitatively evaluating each probe using signal-to-noise ratio (SNR) and outlining a real-time data-processing algorithm based on SNR methodology; (b) exploring the frequency range proximal to the electrical resonance of the receiver coil; and (c) examining sensitivity variations across varying lift-off distances. The experimental outcomes indicate that the newly designed probe with a figure-8 shaped transmitter coil significantly improves sensitivity in detecting surface cracks on railroads. It achieves an impressive SNR exceeding 100 for defects with minimal dimensions of 1 mm in width and depth. The simulation results closely align with experimental findings, validating the investigation of the optimal operational frequency and lift-off distance for selected probe performance, which are determined to be 0.3 MHz and 1 mm, respectively. The realisation of this project would lead to notable advancements in enhancing railroad safety by improving the efficiency of crack detection. Full article

In this work, a known Eddy Current (EC) model is adapted to characterize subsurface defects in carbon fiber-reinforced polymer (CFRP) plates intended for the civil aerospace industry. The considered defects include delaminations, microcracks, porosity, fiber breakage, and the simultaneous presence of these defects. Each defect is modeled as an additive variation in the material’s electrical conductivity tensor, allowing for a detailed mathematical representation of the defect’s influence on the CFRP’s electromagnetic behavior. The additivity of the variations in the conductivity tensor is justified by the assumption that the defects are not visible to the naked eye, implying that the material does not require non-destructive testing. The adapted EC model admits a unique and stable solution by verifying that all analytical steps are satisfied. To reconstruct 2D maps of the magnetic flux density amplitude, a FEM formulation is adopted, based on the energy functional because it ensures a stable and consistent numerical formulation given its coercivity. Moreover, the numerical approach allows precise and reliable numerical solutions, enhancing the capability to detect and quantify defects. The numerical results show that the obtained 2D maps are entirely superimposable on those highlighting the distribution of mechanical stress states known in the literature, offering a clear advantage in terms of detection costs. This approach provides an effective and economical solution for the non-destructive inspection of CFRP, ensuring accurate and timely defect diagnosis for maintaining structural integrity. Full article