Nondestructive Testing and Imaging Based on Electromagnetic Fields and Waves

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Optics and Lasers".

Deadline for manuscript submissions: closed (31 July 2019) | Viewed by 84680

Special Issue Editor


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Guest Editor
Department of Electrical and Electronic Engineering, University of Manchester, Manchester M60 1QD, UK
Interests: EM sensing; instruments; NDT; tomography
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Electromagnetic Fields and Waves can be used to interrogate an object non-destructively for the purpose of object characterization, defect detection, structural health monitoring, process monitoring, remote sensing, and imaging. In recent years, there have been new developments of this field in various aspects such as sensor design, instrument development, new algorithms, and applications. This special issue of Applied Sciences on “Non-destructive Testing and Imaging Based on Electromagnetic Fields and Waves” welcomes contributions from the following topics:

  • Novel EM sensing principle
  • EM Sensor modelling
  • EM Sensor design and optimisation
  • EM sensing system developments such as those based on FPGA, DSP, etc.
  • Materials characterization
  • Defect detection
  • Process sensing and imaging
  • Signal and imaging processing
  • Subsurface mapping and imaging of maritime targets

Dr. Wuliang Yin
Guest Editor

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Keywords

  • Nondestructive Testing (NDT)
  • Eddy current
  • Microwave
  • Electrical Tomography
  • Electromagnetic Sensing
  • Electromagnetic imaging

Published Papers (12 papers)

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Research

Jump to: Review

10 pages, 4335 KiB  
Article
Measurement System of Metal Magnetic Memory Method Signals around Rectangular Defects of a Ferromagnetic Pipe
by J. Jesús Villegas-Saucillo, José Javier Díaz-Carmona, Carlos A. Cerón-Álvarez, Raúl Juárez-Aguirre, Saúl M. Domínguez-Nicolás, Francisco López-Huerta and Agustín L. Herrera-May
Appl. Sci. 2019, 9(13), 2695; https://doi.org/10.3390/app9132695 - 02 Jul 2019
Cited by 11 | Viewed by 2890
Abstract
Oil and gas pipeline networks require the periodic inspection of their infrastructure, which can cause gas and oil leakage with several damages to the environment and human health. For this, non-destructive testing (NDT) techniques of low-cost and easy implementation are required. An option [...] Read more.
Oil and gas pipeline networks require the periodic inspection of their infrastructure, which can cause gas and oil leakage with several damages to the environment and human health. For this, non-destructive testing (NDT) techniques of low-cost and easy implementation are required. An option is the metal magnetic memory (MMM) method, which could be used for real-time monitoring defects of ferromagnetic structures based on the analysis of self-magnetic leakage fields distribution around each defect. This method only requires magnetic sensors with high resolution and a data processing system. We present a measurement system of tangential and normal MMM signals of three rectangular defects of an ASTM A-36 steel pipe. This system is formed by a magnetoresistive sensor, an Arduino nano and a virtual instrumentation. The measured magnetic signals have non-uniform distributions around the rectangular defects, which have small differences with respect to the results obtained of a 2D magnetic dipole model. The size of each rectangular defect is related to the amplitude and shape of its tangential and normal MMM signals. The proposed system could be used for real-time monitoring of the size and location of rectangular defects of ferromagnetic pipes. This system does not require expensive equipment, operators with high skill level or a special treatment of the ferromagnetic samples. Full article
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15 pages, 4652 KiB  
Article
Data Interpretation Technology of GPR Survey Based on Variational Mode Decomposition
by Juncai Xu and Bangjun Lei
Appl. Sci. 2019, 9(10), 2017; https://doi.org/10.3390/app9102017 - 16 May 2019
Cited by 15 | Viewed by 3663
Abstract
Data interpretation is the crucial scientific component that influences the inspection accuracy of ground penetrating radar (GPR). Developing algorithms for interpreting GPR data is a research focus of increasing interest. The problem of algorithms for interpreting GPR data is unresolved. To this end, [...] Read more.
Data interpretation is the crucial scientific component that influences the inspection accuracy of ground penetrating radar (GPR). Developing algorithms for interpreting GPR data is a research focus of increasing interest. The problem of algorithms for interpreting GPR data is unresolved. To this end, this study proposes a sophisticated algorithm for interpreting GPR data with the aim of improving the inspection resolution. The algorithm is formulated by integrating variational mode decomposition (VMD) and Hilbert–Huang transform techniques. With this method, the intrinsic mode function of the GPR data is first produced using the VMD of the data, followed by obtaining the instantaneous frequency by using the Hilbert–Huang transform to analyze the intrinsic mode functions. The instantaneous frequency data can be decomposed into three frequency attributes, including frequency division section, time-frequency section, and space frequency section, which constitute a platform to gain insight into the nature of the GPR data, such that the inspected media components can be examined. The effectiveness of the proposed method on a synthetic signal from a GPR forward model was studied, with the multi-resolution performance being tested. Inspecting the media of a highroad by analyzing the GPR data, with the abnormal characteristics being designated, validated the applicability of the proposed method. Full article
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29 pages, 12213 KiB  
Article
Nondestructive Testing with 3MA—An Overview of Principles and Applications
by Bernd Wolter, Yasmine Gabi and Christian Conrad
Appl. Sci. 2019, 9(6), 1068; https://doi.org/10.3390/app9061068 - 14 Mar 2019
Cited by 70 | Viewed by 6929
Abstract
More than three decades ago, at Fraunhofer IZFP, research activities that were related to the application of micromagnetic methods for nondestructive testing (NDT) of the microstructure and the properties of ferrous materials commenced. Soon, it was observed that it is beneficial to combine [...] Read more.
More than three decades ago, at Fraunhofer IZFP, research activities that were related to the application of micromagnetic methods for nondestructive testing (NDT) of the microstructure and the properties of ferrous materials commenced. Soon, it was observed that it is beneficial to combine the measuring information from several micromagnetic methods and measuring parameters. This was the birth of 3MA—the micromagnetic multi-parametric microstructure and stress analysis. Since then, 3MA has undergone a remarkable development. It has proven to be one of the most valuable testing techniques for the nondestructive characterization of metallic materials. Nowadays, 3MA is well accepted in industrial production and material research. Over the years, several equipment variants and a wide range of probe heads have been developed, ranging from magnetic microscopes with µm resolution up to large inspection systems for in-line strip steel inspection. 3MA is extremely versatile, as proved by a huge amount of reported applications, such as the quantitative determination of hardness, hardening depth, residual stress, and other material parameters. Today, specialized 3MA systems are available for manual or automated testing of various materials, semi-finished goods, and final products that are made of steel, cast iron, or other ferromagnetic materials. This paper will provide an overview of the historical development, the basic principles, and the main applications of 3MA. Full article
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11 pages, 1804 KiB  
Article
Mode Separation for Multimodal Ultrasonic Lamb Waves Using Dispersion Compensation and Independent Component Analysis of Forth-Order Cumulant
by Xiao Chen and Dandan Ma
Appl. Sci. 2019, 9(3), 555; https://doi.org/10.3390/app9030555 - 07 Feb 2019
Cited by 12 | Viewed by 3454
Abstract
Ultrasonic Lamb wave testing has been successfully applied in nondestructive testing. However, because of Lamb wave multimodal and dispersion characteristics, the received signals are often multimodal and overlapping, which makes them very complicated. This paper proposes a mode separation method by combining dispersion [...] Read more.
Ultrasonic Lamb wave testing has been successfully applied in nondestructive testing. However, because of Lamb wave multimodal and dispersion characteristics, the received signals are often multimodal and overlapping, which makes them very complicated. This paper proposes a mode separation method by combining dispersion compensation with the independent component analysis of fourth-order cumulant. Taking two-mode overlapped signals as an example, the single-mode dispersion compensation is performed according to the measured distance difference between the two sets of signals. The two sets of signals are returned to the same distance. The fourth-order cumulant independent component analysis method is further used to process the Lamb wave signals of different superposition situations at the same distance. The corresponding mode signal contained in the two sets of signals is separated through the joint diagonalization of the whitened fourth-order cumulant matrix. The different modes are compensated and separated successively, achieving the multimodal signal separation. Experimental results in steel plates show that the presented method can accurately achieve mode separation for the multimodal overlapping Lamb waves. This is helpful for the signal processing of multimodal Lamb waves. Full article
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12 pages, 5107 KiB  
Article
Multi-Channel Electrical Impedance-Based Crack Localization of Fiber-Reinforced Cementitious Composites under Bending Conditions
by Man-Sung Kang, Hanju Lee, Hong Jae Yim, Yun-Kyu An and Dong Joo Kim
Appl. Sci. 2018, 8(12), 2582; https://doi.org/10.3390/app8122582 - 12 Dec 2018
Cited by 7 | Viewed by 2482
Abstract
This study proposes a multi-channel electrical impedance-based crack localization technique of fiber-reinforced cementitious composites (FRCCs) under bending conditions. FRCCs have a self-sensing capability by adding conductive steel fibers into nonconductive cementitious composites, making it possible to measure electrical impedance without sensor installation. Moreover, [...] Read more.
This study proposes a multi-channel electrical impedance-based crack localization technique of fiber-reinforced cementitious composites (FRCCs) under bending conditions. FRCCs have a self-sensing capability by adding conductive steel fibers into nonconductive cementitious composites, making it possible to measure electrical impedance without sensor installation. Moreover, FRCCs materials can be used as a structural member thanks to its own enhanced structural ductility as well as stiffness. In a structural health monitoring point of view, these characteristics make FRCCs suitable for monitoring structural hot spots, particularly where the crack is most likely to be initiated. Since the electrical impedance obtained from FRCCs is typically sensitive to environmental and operational conditions, false alarms are often triggered. The proposed technique can minimize the false alarms by using currently measured multi-path data as well as localize a crack within the sensing range. To examine the feasibility of crack localization in FRCCs, an instantaneous multi-channel electrical impedance acquisition system and a crack localization algorithm are developed. Subsequently, three-point bending tests are carried out under various temperature conditions. The validation test results reveal that cracks are successfully identified and localized even under varying temperature conditions. Full article
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19 pages, 6715 KiB  
Article
An Improved Skewness Decision Tree SVM Algorithm for the Classification of Steel Cord Conveyor Belt Defects
by Qinghua Mao, Hongwei Ma, Xuhui Zhang and Guangming Zhang
Appl. Sci. 2018, 8(12), 2574; https://doi.org/10.3390/app8122574 - 11 Dec 2018
Cited by 9 | Viewed by 3268
Abstract
Skewness Decision Tree Support Vector Machine (SDTSVM) algorithm is widely known as a supervised learning model for multi-class classification problems. However, the classification accuracy of the SDTSVM algorithm depends on the perfect selection of its parameters and the classification order. Therefore, an improved [...] Read more.
Skewness Decision Tree Support Vector Machine (SDTSVM) algorithm is widely known as a supervised learning model for multi-class classification problems. However, the classification accuracy of the SDTSVM algorithm depends on the perfect selection of its parameters and the classification order. Therefore, an improved SDTSVM (ISDTSVM) algorithm is proposed in order to improve the classification accuracy of steel cord conveyor belt defects. In the proposed model, the classification order is determined by the sum of the Euclidean distances between multi-class sample centers and the parameters are optimized by the inertia weight Particle Swarm Optimization (PSO) algorithm. In order to verify the effectiveness of the ISDTSVM algorithm with different feature space, experiments were conducted on multiple UCI (University of California Irvine) data sets and steel cord conveyor belt defects using the proposed ISDTSVM algorithm and the conventional SDTSVM algorithm respectively. The average classification accuracies of five-fold cross-validation were obtained, based on two kinds of kernel functions respectively. For the Vowel, Zoo, and Wine data sets of the UCI data sets, as well as the steel cord conveyor belt defects, the ISDTSVM algorithm improved the classification accuracy by 3%, 3%, 1% and 4% respectively, compared to the SDTSVM algorithm. The classification accuracy of the radial basis function kernel were higher than the polynomial kernel. The results indicated that the proposed ISDTSVM algorithm improved the classification accuracy significantly, compared to the conventional SDTSVM algorithm. Full article
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15 pages, 5740 KiB  
Article
Further Investigations into the Capacitive Imaging Technique Using a Multi-Electrode Sensor
by Zhen Li, Guoming Chen, Yue Gu, Kefan Wang, Wei Li and Xiaokang Yin
Appl. Sci. 2018, 8(11), 2296; https://doi.org/10.3390/app8112296 - 19 Nov 2018
Cited by 7 | Viewed by 2680
Abstract
As a novel non-destructive testing technique, capacitive imaging (CI) has been used to detect defects within the insulation layer and metal surface of an insulated metallic structure, that is, pipe or vessel. Due to the non-linearity of the probing field, the defects at [...] Read more.
As a novel non-destructive testing technique, capacitive imaging (CI) has been used to detect defects within the insulation layer and metal surface of an insulated metallic structure, that is, pipe or vessel. Due to the non-linearity of the probing field, the defects at different depths in the insulation layer are difficult to compare accurately using the conventional CI sensor with a single pair of electrodes. In addition, the conventional CI sensor cannot provide adequate information to discriminate the defects in the insulation layer and metal surface. In order to solve the above-mentioned problems, the multi-electrode sensor is introduced. The multi-electrode sensor uses multiple quasi-static fringing electric fields generated by an array of coplanar electrodes to obtain extra information about the defects in the specimen. In this work, the feasibility of multiple quasi-static electric fields detecting the defects was demonstrated and the Measurement Sensitivity Distributions (MSDs) of the multi-electrode sensor detecting the defects were acquired using the FEM models. The simulation and experimental results show that the Dynamic Change Rates (DCRs) of the measured values obtained at the center of the defects in the insulator layer and metal surface present different variation patterns, which can be used to discriminate these two different kinds of defects. The reasons for the different variation patterns of DCRs were explained by the changing trends of MSDs with increased electrode separation. In addition, it was demonstrated that the different depths of the defects in the insulator layer can be compared accurately by comprehensive analysis of the detection results from all the electrode pairs. Full article
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11 pages, 3278 KiB  
Article
Vector-Based Eddy-Current Testing Method
by Cheng Li, Runcong Liu, Shangjun Dai, Nianmei Zhang and Xiaodong Wang
Appl. Sci. 2018, 8(11), 2289; https://doi.org/10.3390/app8112289 - 19 Nov 2018
Cited by 3 | Viewed by 6230
Abstract
We present a type of eddy-current testing (ECT) method based on measuring the reaction of the Lorentz force by using a small permanent magnet (PM) as the probe. The means of measuring impedance is superseded by measuring force. By analyzing the variations in [...] Read more.
We present a type of eddy-current testing (ECT) method based on measuring the reaction of the Lorentz force by using a small permanent magnet (PM) as the probe. The means of measuring impedance is superseded by measuring force. By analyzing the variations in different components of the reaction of Lorentz force, the defects characteristics within the measured conductor can be revealed. The results indicate that the vector-based eddy-current testing method obtains good quantitative results and precisely evaluates the lift-off effect during measurement along two orthogonal directions. Numerical simulations are performed to provide supports for the experimental results. The method described in this paper may have great potential for use in industrial nondestructive testing applications. Full article
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15 pages, 2860 KiB  
Article
Shape Mapping Detection of Electric Vehicle Alloy Defects Based on Pulsed Eddy Current Rectangular Sensors
by Kai Zhang, Zhurong Dong, Zhan Yu and Yunze He
Appl. Sci. 2018, 8(11), 2066; https://doi.org/10.3390/app8112066 - 26 Oct 2018
Cited by 2 | Viewed by 2437
Abstract
In this paper, we investigate pulsed eddy current (PEC) testing based on a rectangular sensor for the purpose of defect shape mapping in electric vehicle lightweight alloy material. Different dimensional defects were machined on the 3003 aluminum alloy and detected using the A-scan [...] Read more.
In this paper, we investigate pulsed eddy current (PEC) testing based on a rectangular sensor for the purpose of defect shape mapping in electric vehicle lightweight alloy material. Different dimensional defects were machined on the 3003 aluminum alloy and detected using the A-scan technique and C-scan imaging in two scanning directions. The experiment results indicated that defect plane shape could be preliminarily obtained and length and width could be estimated based upon C-scan contour images. Consequently, the comparison of results between the two directions showed that the C-scan identification in the direction of magnetic flux was better than in the direction of the exciting current. Finally, subsurface defects and irregular defects were detected to verify the performance of shape mapping as a recommended approach. The conclusion drawn indicates that the proposed method, based on PEC rectangular sensors, is an effective approach in reconstructing a defect’s shape. Full article
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19 pages, 5168 KiB  
Article
Detectability of Delamination in Concrete Structure Using Active Infrared Thermography in Terms of Signal-to-Noise Ratio
by Jungwon Huh, Van Ha Mac, Quang Huy Tran, Ki-Yeol Lee, Jong-In Lee and Choonghyun Kang
Appl. Sci. 2018, 8(10), 1986; https://doi.org/10.3390/app8101986 - 19 Oct 2018
Cited by 18 | Viewed by 6153
Abstract
Detecting subsurface delamination is a difficult and vital task to maintain the durability and serviceability of concrete structure for its whole life cycle. The aim of this work was to obtain better knowledge of the effect of depth, heating time, and rebar on [...] Read more.
Detecting subsurface delamination is a difficult and vital task to maintain the durability and serviceability of concrete structure for its whole life cycle. The aim of this work was to obtain better knowledge of the effect of depth, heating time, and rebar on the detectability capacity of delamination. Experimental tests were carried out on a concrete specimen in the laboratory using Long Pulsed Thermography (LPT). Six halogen lamps and a long wavelength infrared camera with a focal plane array of 640 × 480 pixels were used as the heat source and infrared detector, respectively. The study focused on the embedded imitation delaminations with the size of 10 cm × 10 cm × 1 cm, located at depths varying from 1 to 8 cm. The signal-to-noise ratio (SNR) was applied as a criterion to assess the detectability of delamination. The results of this study indicate that as the provided heating time climbed, the SNR increased, and the defect could be identified more clearly. On the other hand, when using the same heating regime, a shallow delamination displayed a higher SNR than a deeper one. The moderate fall of the SNR in the case of imitating defect located below reinforced steel was also observed. The absolute contrast was monitored to determine the observation time, and the nondimensional prefactor k was empirically proposed to predict the depth of delamination. The mean absolute percentage error (MAPE) was used to quantitatively evaluate the difference between forecasted and real depth, which evaluation confirmed the high reliability of the estimated value of the prefactor k. Full article
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13 pages, 5003 KiB  
Article
Accurate Sparse Recovery of Rayleigh Wave Characteristics Using Fast Analysis of Wave Speed (FAWS) Algorithm for Soft Soil Layers
by Zhuoshi Chen, Baofeng Jiang, Jingjing Song and Wentao Wang
Appl. Sci. 2018, 8(7), 1204; https://doi.org/10.3390/app8071204 - 23 Jul 2018
Cited by 2 | Viewed by 3999
Abstract
This paper presents a novel fast analysis of wave speed (FAWS) algorithm from the waveforms recorded by a random-spaced geophone array based on a compressive sensing (CS) platform. Rayleigh-type seismic surface wave testing is excited by a hammer source and conducted to develop [...] Read more.
This paper presents a novel fast analysis of wave speed (FAWS) algorithm from the waveforms recorded by a random-spaced geophone array based on a compressive sensing (CS) platform. Rayleigh-type seismic surface wave testing is excited by a hammer source and conducted to develop the phase velocity characteristics of the subsoil layers in Shenyang Metro line 9. Data are filtered by a bandpass filter bank to pursue the dispersive profiles of phase velocity at various frequencies. The Rayleigh-type surface-wave dispersion curve for the soil layers at each frequency is conducted by the 1-norm minimization algorithm of CS theory. The traditional frequency-wavenumber transform technique and in-site downhole observation are employed as the comparison of the proposed technique. The experimental results indicate the proposed FAWS algorithm has a good agreement with both the results of conventional even-spaced geophone array and the in-site measurements, which provides an effective and efficient way for accurate non-destructive evaluation of the surface wave dispersion curve of the soil. Full article
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Review

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25 pages, 1452 KiB  
Review
Review on the Electrical Resistance/Conductivity of Carbon Fiber Reinforced Polymer
by Qian Zhao, Kai Zhang, Shuang Zhu, Hanyang Xu, Dianguo Cao, Lina Zhao, Ronghua Zhang and Wuliang Yin
Appl. Sci. 2019, 9(11), 2390; https://doi.org/10.3390/app9112390 - 11 Jun 2019
Cited by 98 | Viewed by 39620
Abstract
Carbon fiber reinforced polymer (CFRP) plays an important role in many fields, especially in aviation and civil industries. The electrical conductivity of CFRP is critical for its electrical behavior, such as its lightning strike vulnerability, electromagnetic shielding ability, and potential uses for self-sensing. [...] Read more.
Carbon fiber reinforced polymer (CFRP) plays an important role in many fields, especially in aviation and civil industries. The electrical conductivity of CFRP is critical for its electrical behavior, such as its lightning strike vulnerability, electromagnetic shielding ability, and potential uses for self-sensing. In addition, the electrical conductivity is related to the mechanical integrity. Therefore, electrical properties can be measured as an indication when detecting delamination and other defects in CFRP. This review provides a comprehensive basis for readers to grasp recent research progresses on electrical behaviors of CFRP. Full article
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