Infrared Camera Geometric Calibration: A Review and a Precise Thermal Radiation Checkerboard Target.

Different infrared (IR) planar geometric calibration targets have been developed over the years that exploit a well-established and flexible optical camera geometric calibration procedure following the pinhole approximation. This geometric calibration is typically neglected in IR cameras, due to the relatively low resolution of thermal images and the complex IR targets needed for the geometric calibration in comparison to the optical targets. In this study, a thorough literature review of numerous IR camera geometric calibration targets, along with their respective outcomes, were summarized and leveraged to deliver a practical checkerboard target for less experienced end users, while offering the lowest reprojection errors. It was concluded that the fabrication of high emissivity contrast and precise square points of intersection within a checkerboard pattern extends the accuracy of capturing these control points in a thermal image for an optimized IR camera geometric calibration. Accordingly, two simple planar checkerboard targets were fabricated using laser engraving and ultraviolet (UV) printing technologies on a polished stainless steel (SS304) plate. The UV-printed checkerboard target on a polished metallic alloy delivered the lowest mean reprojection error (MRE) of 0.057 pixels and the lowest root mean square error (RMSE) of reprojection of 0.063 pixels, with a standard deviation lower than 0.003 pixels. The UV-printed design offers better accuracy than any other checkerboard calibration target, and comparable results to the best prominent circular pattern results reported in the literature.

Wheel-Rail Contact-Induced Impact Vibration Analysis for Switch Rails Based on the VMD-SS Method.

When trains pass through damaged switch rails, rail head damage will change wheel-rail contact states from rolling frictions to unsteady contacts, which will result in impact vibrations and threaten structural safeties. In addition, under approaching and moving away rolling contact excitations and complex wheel-rail contacts, the non-stationary vibrations make it difficult to extract and analyze impact vibrations. In view of the above problems, this paper proposes a variational-mode-decomposition (VMD)-spectral-subtraction (SS)-based impact vibration extraction method. Firstly, the time domain feature analysis method is applied to calculate the time moments that the wheels pass joints, and to correct vehicle velocities. This can help estimate and confine impact vibration distribution ranges. Then, the stationary intrinsic mode function (IMF) components of the impact vibration are decomposed and analyzed with the VMD method. Finally, impact vibrations are further filtered with the SS method. For rail head damage with different dimensions, under different velocity experiments, the frequency and amplitude features of the impact vibrations are analyzed. Experimental results show that, in low-velocity scenarios, the proposed VMD-SS-based method can extract impact vibrations, the frequency features are mainly concentrated in 3500-5000 Hz, and the frequency and peak-to-peak features increase with the increase in excitation velocities.

Comparison of Repeatability and Stability of Residual Magnetic Field for Stress Characterization in Elastic and Plastic Ranges of Silicon Steels.

Deep insights into microstructures and domain wall behaviors in the evaluation of different material statuses under elastic and plastic stress ranges have essential implications for magnetic sensing and nondestructive testing and evaluation (NDT&E). This paper investigates the repeatability and stability of residual magnetic field (RMF) signals using a magneto-optical Kerr effect microscope for the stress characterization of silicon steel sheets beyond their elastic limit. Real-time domain motion is used for RMF characterization, while both the repeatability under plastic ranges after the cyclic stress rounds and stability during relaxation time are studied in detail. The distinction between elastic and plastic materials is discussed in terms of their spatio-temporal properties for further residual stress measurement since both ranges are mixed. During the relaxation time, the RMF of the plastic material shows a two-stage change with apparent recovery, which is contrasted with the one-stage change in the elastic material. Results show that the grain boundary affects the temporal recovery of the RMF. These findings concerning the spatio-temporal properties of different RMFs in plastic and elastic materials can be applied to the design and development of magnetic NDT&E for (residual) stress measurement and material status estimation.

Research on the Time Drift Stability of Differential Inductive Displacement Sensors with Frequency Output.

An edge displacement sensor is one of the key technologies for building large segmented mirror astronomical optical telescopes. A digital interface is one novel approach for sensor technologies, digital transformation and the Internet of Things (IoT) in particular. Frequency output sensors and inductance-to-digital converter (LDC) demonstrated significant advantages in comparison with conventional sensors with analog-to-digital converter (ADC) interfaces. In order for the differential inductive frequency output displacement (DIFOD) sensor to meet the high-stability requirements of segmented mirror astronomical telescopes, it is important to understand the factors for time drift of the sensor. This paper focuses on the investigation of key factors of sensor structure and material, signal conditioning and interface, and fixtures for time drift to permanently installed applications. First, the measurement principle and probe structural characteristics of the sensor are analyzed. Then, two kinds of signal conditioning and digitalization methods using resonance circuits and LDC chips are implemented and compared. Finally, the time drift stability experiments are performed on the sensors with different signal conditioning methods and fixtures under controlled temperature. Experimental results show that the magnetic shield ring effectively improves the sensitivity and quality factor of the sensors, the time drift stability of the sensor using the signal conditioning based on resonance circuits is better than that of the sensors using LDC chips, and the root mean square (RMS) of the sensor time drift meets the requirement of 0.01 µm/24 h. This study will help further development of high-stability of frequency output sensors and IoT-based systems for scaled-up applications in the future.

An Amorphous-Crystalline Nanosheet Arrays Structure for Ultrahigh Electrochemical Performance Supercapattery.

Hybrid supercapacitors (HSCs), also called supercapattery, which can substitute for low power density batteries have attracted extensive interest. However, when HSCs comes to commercial applications, there is still space for improvement in energy density. It seems that designing of electrode with high capacity is an effective measure. Herein, amorphous-crystalline MoO3 -Ni3 S2 /NF-0.5 nanosheet arrays are developed as battery-type electrodes. Specifically, the sheet-like structure of crystalline Ni3 S2 can achieve rich structural nanocrystallization, improving the redox reaction efficiency. Meanwhile, the disordered structure and irregular surface of the amorphous MoO3 are conducive to maximize the contact between the electrode and electrolyte, slowing down the volume change caused by the continuous charge-discharge process. As a result, it displays an ultrahigh areal specific capacity of 8.52 C cm-2 at 5 mA cm-2 , and superior lifespan up to 7500 cycles with 90.0% retention. Further, when assembled into HSCs, the specific capacity reaches 1.47 C cm-2 , corresponding to an energy density of 4.18 mWh cm-2 at a power density of 0.34 mW cm-2 . Totally, the design of the unique structure displays a valuable measure for rational development of high energy density hybrid energy storage devices that are not limited to supercapacitors.

Magnetic Barkhausen Noise Transient Analysis for Microstructure Evolution Characterization with Tensile Stress in Elastic and Plastic Status.

Stress affects the microstructure of the material to influence the durability and service life of the components. However, the previous work of stress measurement lacks quantification of the different variations in time and spatial features of micromagnetic properties affected by stress in elastic and plastic ranges, as well as the evolution of microstructure. In this paper, microstructure evolution under stress in elastic and plastic ranges is evaluated by magnetic Barkhausen noise (MBN) transient analysis. Based on a J-A model, the duration and the intensity are the eigenvalues for MBN transient analysis to quantify transient size and number of Barkhausen events under stress. With the observation of domain wall (DW) distribution and microstructure, the correlation between material microstructure and MBN transient eigenvalues is investigated to verify the ability of material status evaluation on the microscopic scale of the method. The results show that the duration and the intensity have different change trends in elastic and plastic ranges. The eigenvalue fusion of the duration and intensity distinguishes the change in microstructure under the stress in elastic and plastic deformation. The appearance of grain boundary (GB) migration and dislocation under the stress in the plastic range makes the duration and the intensity higher on the GB than those inside the grain. Besides, the reproducibility of the proposed method is investigated by evaluating microstructure evolution for silicon steel sheet and Q235 steel sheet. The proposed method investigates the correlation between the microstructure and transient micromagnetic properties, which has the potential for stress evaluation in elastic and plastic ranges for industrial materials.

Time-Response-Histogram-Based Feature of Magnetic Barkhausen Noise for Material Characterization Considering Influences of Grain and Grain Boundary under In Situ Tensile Test.

Stress is the crucial factor of ferromagnetic material failure origin. However, the nondestructive test methods to analyze the ferromagnetic material properties' inhomogeneity on the microscopic scale with stress have not been obtained so far. In this study, magnetic Barkhausen noise (MBN) signals on different silicon steel sheet locations under in situ tensile tests were detected by a high-spatial-resolution magnetic probe. The domain-wall (DW) motion, grain, and grain boundary were detected using a magneto-optical Kerr (MOKE) image. The time characteristic of DW motion and MBN signals on different locations was varied during elastic deformation. Therefore, a time-response histogram is proposed in this work to show different DW motions inside the grain and around the grain boundary under low tensile stress. In order to separate the variation of magnetic properties affected by the grain and grain boundary under low tensile stress corresponding to MBN excitation, time-division was carried out to extract the root-mean-square (RMS), mean, and peak in the optimized time interval. The time-response histogram of MBN evaluated the silicon steel sheet's inhomogeneous material properties, and provided a theoretical and experimental reference for ferromagnetic material properties under stress.

Pipeline In-Line Inspection Method, Instrumentation and Data Management.

Pipelines play an important role in the national/international transportation of natural gas, petroleum products, and other energy resources. Pipelines are set up in different environments and consequently suffer various damage challenges, such as environmental electrochemical reaction, welding defects, and external force damage, etc. Defects like metal loss, pitting, and cracks destroy the pipeline's integrity and cause serious safety issues. This should be prevented before it occurs to ensure the safe operation of the pipeline. In recent years, different non-destructive testing (NDT) methods have been developed for in-line pipeline inspection. These are magnetic flux leakage (MFL) testing, ultrasonic testing (UT), electromagnetic acoustic technology (EMAT), eddy current testing (EC). Single modality or different kinds of integrated NDT system named Pipeline Inspection Gauge (PIG) or un-piggable robotic inspection systems have been developed. Moreover, data management in conjunction with historic data for condition-based pipeline maintenance becomes important as well. In this study, various inspection methods in association with non-destructive testing are investigated. The state of the art of PIGs, un-piggable robots, as well as instrumental applications, are systematically compared. Furthermore, data models and management are utilized for defect quantification, classification, failure prediction and maintenance. Finally, the challenges, problems, and development trends of pipeline inspection as well as data management are derived and discussed.

Wireless power transfer-based eddy current non-destructive testing using a flexible printed coil array.

Eddy current testing (ECT) has been employed as a traditional non-destructive testing and evaluation (NDT&E) tool for many years. It has developed from single frequency to multiple frequencies, and eventually to pulsed and swept-frequency excitation. Recent progression of wireless power transfer (WPT) and flexible printed devices open opportunities to address challenges of defect detection and reconstruction under complex geometric situations. In this paper, a transmitter-receiver (Tx-Rx) flexible printed coil (FPC) array that uses the WPT approach featuring dual resonance responses for the first time has been proposed. The dual resonance responses can provide multiple parameters of samples, such as defect characteristics, lift-offs and material properties, while the flexible coil array allows area mapping of complex structures. To validate the proposed approach, experimental investigations of a single excitation coil with multiple receiving coils using the WPT principle were conducted on a curved pipe surface with a natural dent defect. The FPC array has one single excitation coil and 16 receiving (Rx) coils, which are used to measure the dent by using 21 C-scan points on the dedicated dent sample. The experimental data were then used for training and evaluation of dual resonance responses in terms of multiple feature extraction, selection and fusion for quantitative NDE. Four features, which include resonant magnitudes and principal components of the two resonant areas, were investigated for mapping and reconstructing the defective dent through correlation analysis for feature selection and feature fusion by deep learning. It shows that deep learning-based multiple feature fusion has outstanding performance for 3D defect reconstruction of WPT-based FPC-ECT. This article is part of the theme issue 'Advanced electromagnetic non-destructive evaluation and smart monitoring'.

Resonant frequency tracking mode on eddy current pulsed thermography non-destructive testing.

Eddy current pulsed thermography (ECPT) has been widely used in the field of non-destructive testing due to its safety, non-contact detection, high spatial resolution and intuitive results. Inductive excitation source is an important component of ECPT and provides high-frequency alternating current to drive the excitation coil. However, a resonant frequency distortion phenomenon exists in the excitation source during the detection process, which seriously affects the output power of the excitation source and the sample detection effect. This paper presents a fast resonant frequency tracking loop for full bridge series resonant inverter which is used to search the resonance frequency in real time through direct digital synthesizer (DDS) and all-digital phase-locked loop. Theoretical analysis and simulation are presented to explain the working principle of the loop. Then, an experimental prototype is manufactured which serves as an excitation source for the ECPT experimental system. Compared with traditional excitation sources, the prototype does not need a water-cooled device and the tracking speed can be adjusted by modifying the parameters of DDS. Finally, experiments have been conducted on both artificial slot of 45# steel and natural cracks of rail and stainless steel to investigate the influence of resonant frequency tracking speed on the crack detection. The results revealed that reducing the resonant frequency tracking time can efficiently improve defect detectability and the manufactured prototype showed more application potential. This article is part of the theme issue 'Advanced electromagnetic non-destructive evaluation and smart monitoring'.

Study on a New Electromagnetic Flow Measurement Technology Based on Differential Correlation Detection.

Under the conditions of low flow rate and strong noise, the current electromagnetic flowmeter (EMF) cannot satisfy the requirement for measurement or separate the actual flow signal and interference signal accurately. Correlation detection technology can reduce the bandwidth and suppress noise effectively using the periodic transmission of signal and noise randomness. As for the problem that the current anti-interference technology cannot suppress noise effectively, the noise and interference of the electromagnetic flowmeter were analyzed in this paper, and a design of the electromagnetic flowmeter based on differential correlation detection was proposed. Then, in order to verify the feasibility of the electromagnetic flow measurement system based on differential correlation, an experimental platform for the comparison between standard flow and measured flow was established and a verification experiment was carried out under special conditions and with flow calibration measurements. Finally, the data obtained in the experiment were analyzed. The research result showed that an electromagnetic flowmeter based on differential correlation detection satisfies the need for measurement completely. The lower limit of the flow rate of the electromagnetic flowmeter based on the differential correlation principle could reach 0.084 m/s. Under strong external interferences, the electromagnetic flowmeter based on differential correlation had a fluctuation range in output value of only 10 mV. This shows that the electromagnetic flowmeter based on the differential correlation principle has unique advantages in measurements taken under the conditions of strong noise, slurry flow, and low flow rate.

Enhanced Infrared Sparse Pattern Extraction and Usage for Impact Evaluation of Basalt-Carbon Hybrid Composites by Pulsed Thermography.

Nowadays, infrared thermography, as a widely used non-destructive testing method, is increasingly studied for impact evaluation of composite structures. Sparse pattern extraction is attracting increasing attention as an advanced post-processing method. In this paper, an enhanced sparse pattern extraction framework is presented for thermographic sequence processing and defect detection. This framework adapts cropping operator and typical component extraction as a preprocessing step to reduce the dimensions of raw data and applies sparse pattern extraction algorithms to enhance the contrast on the defect area. Different cases are studied involving several defects in four basalt-carbon hybrid fiber-reinforced polymer composite laminates. Finally, comparative analysis with intensity distribution is carried out to verify the effectiveness of contrast enhancement using this framework.

A Review of Microwave Thermography Nondestructive Testing and Evaluation.

Microwave thermography (MWT) has many advantages including strong penetrability, selective heating, volumetric heating, significant energy savings, uniform heating, and good thermal efficiency. MWT has received growing interest due to its potential to overcome some of the limitations of microwave nondestructive testing (NDT) and thermal NDT. Moreover, during the last few decades MWT has attracted growing interest in materials assessment. In this paper, a comprehensive review of MWT techniques for materials evaluation is conducted based on a detailed literature survey. First, the basic principles of MWT are described. Different types of MWT, including microwave pulsed thermography, microwave step thermography, microwave pulsed phase thermography, and microwave lock-in thermography are defined and introduced. Then, MWT case studies are discussed. Next, comparisons with other thermography and NDT methods are conducted. Finally, the trends in MWT research are outlined, including new theoretical studies, simulations and modelling, signal processing algorithms, internal properties characterization, automatic separation and inspection systems. This work provides a summary of MWT, which can be utilized for material failures prevention and quality control.

Frequency Optimization for Enhancement of Surface Defect Classification Using the Eddy Current Technique.

Eddy current testing is quite a popular non-contact and cost-effective method for nondestructive evaluation of product quality and structural integrity. Excitation frequency is one of the key performance factors for defect characterization. In the literature, there are many interesting papers dealing with wide spectral content and optimal frequency in terms of detection sensitivity. However, research activity on frequency optimization with respect to characterization performances is lacking. In this paper, an investigation into optimum excitation frequency has been conducted to enhance surface defect classification performance. The influences of excitation frequency for a group of defects were revealed in terms of detection sensitivity, contrast between defect features, and classification accuracy using kernel principal component analysis (KPCA) and a support vector machine (SVM). It is observed that probe signals are the most sensitive on the whole for a group of defects when excitation frequency is set near the frequency at which maximum probe signals are retrieved for the largest defect. After the use of KPCA, the margins between the defect features are optimum from the perspective of the SVM, which adopts optimal hyperplanes for structure risk minimization. As a result, the best classification accuracy is obtained. The main contribution is that the influences of excitation frequency on defect characterization are interpreted, and experiment-based procedures are proposed to determine the optimal excitation frequency for a group of defects rather than a single defect with respect to optimal characterization performances.

A Trajectory-Based Coverage Assessment Approach for Universal Sensor Networks.

To solve the problem of coverage performance assessment, this study proposes an evaluation method based on the trajectory of the target, which is applicable to universal sensor networks, including both heterogeneous and homogeneous sensor networks. Different from the traditional Voronoi algorithm, the proposed Improved Coverage Force Division (ICFD) plans a coverage force division map whichscales the qualitative coverage performancebasedon both covering intensities andlocations of the nodes. Furthermore, the Trajectory-based Evaluating Schedule (TES) is responsible for solving the quantitative coverage evaluationproblem by measuringthe resulting trajectories' Balance Values (BVs). A model of weak-point ranking conjoined in consideration of coverage force and distance can guide future deployment to compensate coverage. Comparative trials using the greedy algorithm, Voronoi algorithm, and the proposed TES verify that TES achieves the approximate results for two-stage and multistage heterogeneous sensor networks with acceptable difference and lower complexity, and it is superior to the Voronoi algorithm in homogeneous sensor networks interms of breaking the four-point circle block.

Research on defects inspection of solder balls based on eddy current pulsed thermography.

In order to solve tiny defect detection for solder balls in high-density flip-chip, this paper proposed feasibility study on the effect of detectability as well as classification based on eddy current pulsed thermography (ECPT). Specifically, numerical analysis of 3D finite element inductive heat model is generated to investigate disturbance on the temperature field for different kind of defects such as cracks, voids, etc. The temperature variation between defective and non-defective solder balls is monitored for defects identification and classification. Finally, experimental study is carried on the diameter 1mm tiny solder balls by using ECPT and verify the efficacy of the technique.

Defect profile estimation from magnetic flux leakage signal via efficient managing particle swarm optimization.

In this paper, efficient managing particle swarm optimization (EMPSO) for high dimension problem is proposed to estimate defect profile from magnetic flux leakage (MFL) signal. In the proposed EMPSO, in order to strengthen exchange of information among particles, particle pair model was built. For more efficient searching when facing different landscapes of problems, velocity updating scheme including three velocity updating models was also proposed. In addition, for more chances to search optimum solution out, automatic particle selection for re-initialization was implemented. The optimization results of six benchmark functions show EMPSO performs well when optimizing 100-D problems. The defect simulation results demonstrate that the inversing technique based on EMPSO outperforms the one based on self-learning particle swarm optimizer (SLPSO), and the estimated profiles are still close to the desired profiles with the presence of low noise in MFL signal. The results estimated from real MFL signal by EMPSO-based inversing technique also indicate that the algorithm is capable of providing an accurate solution of the defect profile with real signal. Both the simulation results and experiment results show the computing time of the EMPSO-based inversing technique is reduced by 20%-30% than that of the SLPSO-based inversing technique.

Fast estimation of defect profiles from the magnetic flux leakage signal based on a multi-power affine projection algorithm.

Magnetic flux leakage (MFL) inspection is one of the most important and sensitive nondestructive testing approaches. For online MFL inspection of a long-range railway track or oil pipeline, a fast and effective defect profile estimating method based on a multi-power affine projection algorithm (MAPA) is proposed, where the depth of a sampling point is related with not only the MFL signals before it, but also the ones after it, and all of the sampling points related to one point appear as serials or multi-power. Defect profile estimation has two steps: regulating a weight vector in an MAPA filter and estimating a defect profile with the MAPA filter. Both simulation and experimental data are used to test the performance of the proposed method. The results demonstrate that the proposed method exhibits high speed while maintaining the estimated profiles clearly close to the desired ones in a noisy environment, thereby meeting the demand of accurate online inspection.

Compressive sensing of ultrasonic array data with full matrix capture in nozzle welds inspection.

The phased array ultrasonic technique (PAUT) with full matrix capture (FMC) exhibits the advantages of high imaging accuracy and great defect characterization ability, which play important roles in the nondestructive testing of welded structures. To address the problem of a large amount of signal acquisition, storage, and transmission data in nozzle weld defect monitoring, a PAUT with an FMC data compression method based on compressive sensing (CS) was proposed. To accomplish this, the detection of nozzle welds using PAUT with FMC was performed by simulation and experiment, and the obtained FMC data were compressed and reconstructed. A suitable sparse representation was found dedicated to the FMC data of nozzle welds, and the reconstruction performance was compared between the greedy theory-based orthogonal matching pursuit (OMP) algorithm and the convex optimization theory-based basis pursuit (BP). Also, an empirical mode decomposition (EMD)-based intrinsic mode function (IMF) circular matrix was constructed to provide another idea for the construction of the sensing matrix. Although the experimental results were not able to reach the ideal effect in the simulation, the image was restored accurately with a small number of measured values, and flaw identification could be guaranteed, indicating that the CS algorithm can effectively improve the defect detection efficiency of the phased array.

Influence of Varying Tensile Stress on Domain Motion.

Magnetic domain motion has been widely studied in the fields of spintronics, nanowires, and thin films. However, there is a lack of such studies on industrial steels, especially for domain motion under the action of varying stress. Understanding domain motion under stress is helpful for the improvement of evaluation accuracy and the establishment of theoretical models of passive, nondestructive testing technology. This paper presents the influence of varying tensile stresses on the magnetic domain motion of silicon steel sheets. Magnetic domain rotation and domain wall displacement were characterized using magnetic domain images, and their motion mechanisms under elastic and plastic stresses are presented. The results show that the domain rotation under stress involves reversible and irreversible changes. The effect of material rearrangement on domain rotation and domain wall displacement after plastic deformation is discussed. Based on the motion mechanism, a threshold stress value (TSV) required for the complete disappearance of the supplementary domains in the elastic range is proposed, enabling the classification of the elastic stress ranges in which the reversible and irreversible domain rotations occur. In addition, the effect of microstructure on TSV is also discussed, and the results show that the regions far away from the grain boundary need larger stresses to complete an irreversible domain rotation. Additionally, the domain width and orientation also affect the TSV. These findings regarding the domain motion mechanism and TSV can help to explain the sequence of domain rotation under stress and modify the stress assessment under dynamic loads in electromagnetic nondestructive evaluation, especially in the magnetic memory method.