Detection of surface and subsurface cracks in metallic and non-metallic materials using a complementary split-ring resonator

Design of novel highly sensitive sensors for crack detection in metal surfaces: theoretical foundation and experimental validation

The application of different types of microwave resonators for sensing cracks in metallic structures has been subject of many studies. While most studies have been focused on improving the sensitivity of planar crack sensors, the theoretical foundation of the topic has not been treated in much detail. The major objective of this study is to perform an exhaustive study of the principles and theoretical foundations for crack sensing based on planar microwave resonators, especially defective ground structures (DGS) including complementary split ring resonators (CSRRs). The analysis is carried out from the equivalent circuit model as well as the electromagnetic (EM) field perspectives, and guidelines for the design of crack sensors with high sensitivity are developed. Numerical and experimental validation of the provided theoretical analysis is another aim of this article. With this aim, the developed guidelines are used to design a crack sensor based on a single-ring CSRR. It is shown that the sensitivity of the proposed sensor is almost three times higher than the sensitivity of a conventional double-ring CSRR. Moreover, it is demonstrated that folded dumbbell-shape DGS resonators can be used to achieve even higher sensitivities. The CSRR-based crack sensors presented in this study and other studies available in the literature are only sensitive to cracks with a specific orientation. To address this limitation, a modified version of the DGS is proposed to sense cracks with arbitrary orientations at the cost of lower sensitivity. The performance of all the presented sensors is validated through EM simulation, equivalent circuit model extraction, and measurement of the fabricated prototypes.

Mammography using low-frequency electromagnetic fields with deep learning

In this paper, a novel technique for detecting female breast anomalous tissues is presented and validated through numerical simulations. The technique, to a high degree, resembles X-ray mammography; however, instead of using X-rays for obtaining images of the breast, low-frequency electromagnetic fields are leveraged. To capture breast impressions, a metasurface, which can be thought of as analogous to X-rays film, has been employed. To achieve deep and sufficient penetration within the breast tissues, the source of excitation is a simple narrow-band dipole antenna operating at 200 MHz. The metasurface is designed to operate at the same frequency. The detection mechanism is based on comparing the impressions obtained from the breast under examination to the reference case (healthy breasts) using machine learning techniques. Using this system, not only would it be possible to detect tumors (benign or malignant), but one can also determine the location and size of the tumors. Remarkably, deep learning models were found to achieve very high classification accuracy.

A Highly Sensitive 3D Resonator Sensor for Fluid Measurement

Planar sub-wavelength resonators have been used for sensing applications, but different types of resonators have different advantages and disadvantages. The split ring resonator (SRR) has a smaller sensing region and is suitable for microfluidic applications, but the sensitivity can be limited. Meanwhile, the complementary electric-LC resonator (CELCR) has a larger sensing region and higher sensitivity, but the topology cannot be easily designed to reduce the sensing region. In this work, we propose a new design that combines the advantages of both SRR and CELCR by incorporating metallic bars in a trapezoid-shaped resonator (TSR). The trapezoid shape allows for the sensing region to be reduced, while the metallic bars enhance the electric field in the sensing region, resulting in higher sensitivity. Numerical simulations were used to design and evaluate the sensor. For validation, the sensor was fabricated using PCB technology with aluminum bars and tested on dielectric fluids. The results showed that the proposed sensor provides appreciably enhanced sensitivity in comparison to earlier sensors.

Split-Ring Resonator Based Sensor for the Detection of Amino Acids in Liquids

Amino acids belong to the most important compounds for life. They are structural components of proteins and required for growth and maintenance of cells. Essential amino acids cannot be produced by the organism and must be ingested through the nutrition. Therefore, the detection of amino acids is of great interest when analyzing cell culture media and nutrition. In this work, we present a split-ring resonator as a simple but sensitive detector for amino acids. Split-ring resonators are RLC resonant circuits with a split capacitance and thus a resonance frequency that depends on the electromagnetic properties of a liquid sample at the split capacitance. Here, the split capacitance is an interdigital structure for highest sensitivity and covered with a fluidic channel for flow through experiments. First measurements with a vector network analyzer show detection limits in the range from 105 µM for glutamic acid to 1564 µM for isoleucine, depending on the electromagnetic properties of the tested amino acids. With an envelope detector for continuous recording of the resonance frequency, the split-ring resonator can be used in ion chromatography. At a flow rate of 0.5 mL/min, it reaches limits of detection of 485 µM for aspartic acid and 956 µM for lysine.

A Novel Coupling Mechanism for CSRRs as Near-Field Dielectric Sensors

This work proposes a novel coupling mechanism for a complementary split-ring resonator as a planar near-field microwave sensor for dielectric materials. The resonator is etched into the ground plane of a microstrip line. This mechanism is based on the inductive coupling synthesized by utilizing a via that connects the power plane of the microstrip line to the central island of the resonator. The proposed coupling makes the coupling capacitance between the transmission line and the resonator relatively small and insignificant compared to the capacitance of the resonator, making it more sensitive to changes in the dielectric constant of the materials under test. In addition, the coupling is no longer dependent solely on the capacitive coupling, which significantly reduces the coupling degradation caused by loading the resonator with dielectric materials, so the inductive coupling plays an important role in the proposed design. Therefore, the proposed coupling mechanism improves the sensitivity and enhances the coupling between the transmission line and the resonator. The sensor is evaluated for sensitivity, normalized resonance shift, and coupling factor using a full-wave numerical simulation. The sensitivity of the proposed sensor is 12% and 5.6% when detecting dielectric constants of 2 and 10, respectively. Compared to recent studies, the sensitivity improvement when detecting similar permittivity is 20% (1.32 times) and 9.8% (1.1 times). For verification, the proposed sensor is manufactured using PCB technology and is used to detect the presence of two dielectric laminates.

Review of advances in microwave and millimetre-wave NDT&E: principles and applications

Microwave and millimetre-wave non-destructive testing and evaluation (NDT&E) has a long history dating back to the late 1950s (Bahr 1982 Microwave non-destructive testing methods ; Zoughi 2000 Microwave Non-destructive testing and evaluation principles ; Feinstein 1967 Surface crack detection by microwave methods ; Ash 1973 In 3rd European Microwave Conference ; Auld 1981 Phys. Technol. 12, 149-154; Case 2017 Mater. Eval. 75). However, sustained activities in this field date back to the early 1980s (Zoughi 1995 Res. Nondestr. Eval. 7, 71-74; Zoughi 2018 Mater. Eval. 76, 1051-1057; Kharkovsky 2007 IEEE Instrumentation & Measurement Magazine 10, 26-38). Owing to various limitations associated with using microwaves and millimetre waves for NDT&E, these techniques did not see much utility in the early days. However, with the advent and prevalence of composite materials and structures, in a wide range of applications, and technological advances in high-frequency component design and availability, these techniques are no longer considered as 'emerging techniques' (Zoughi 2018 Mater. Eval. 76, 1051-1057; Schull 2002 Nondestructive evaluation: theory, techniques, and applications ). Currently, microwave and millimetre-wave NDT&E is a rapidly growing field and has been more widely acknowledged and accepted by practitioners over the last 25+ years (Case 2017 Mater. Eval. 75; Bakhtiari 1994 IEEE Trans. Microwave Theory Tech . 42, 389-395; Bakhtiari 1993 Mater. Eval. 51, 740-743; Bakhtiari 1993 IEEE Trans. Instrum. Meas. 42, 19-24; Ganchev 1995 IEEE Trans. Instrum. Meas. 44, 326-328; Bois 1999 IEEE Trans. Instrum. Meas. 48, 1131-1140; Ghasr 2009 IEEE Trans. Instrum. Meas. 58, 1505-1513). Microwave non-destructive testing was recently recognized and designated by the American Society for Nondestructive Testing (ASNT) as a 'Method' on its own (Case 2017 Mater. Eval. 75). These techniques are well suited for materials characterization; layered composite inspection for thickness, disbond, delamination and corrosion under coatings; surface-breaking crack detection and evaluation; and cure-state monitoring in concrete and resin-rich composites, to name a few. This work reviews recent advances in four major areas of microwave and millimetre-wave NDT&E, namely materials characterization, surface crack detection, imaging and sensors. The techniques, principles and some of the applications in each of these areas are discussed. This article is part of the theme issue 'Advanced electromagnetic non-destructive evaluation and smart monitoring'.

A Simple High-resolution Near-field Probe for Microwave Non-Destructive Test and Imaging

Non-destructive tests working at lower microwave frequencies have large advantages of dielectric material penetrability, lower equipment cost, and lower implementation complexity. However, the resolution will become worse as the work frequencies become lower. Relying on designing the structure of high field confinement, this study realizes a simple complementary spiral resonators (CSRs)-based near-field probe for microwave non-destructive testing (NDT) and imaging around 390 MHz (λ = 769 mm) whereby very high resolution (λ/308, 2.5 mm) is achieved. By applying an ingenious structure where a short microstrip is connected to a microstrip ring to feed the CSR, the probe, that is a single-port microwave planar circuit, does not need any extra matching circuits, which has more application potential in sensor arraying compared with other microwave probes. The variation of the electric field distribution with the standoff distance (SOD) between the material under test and the probe are analyzed to reveal the operation mechanisms behind the improved sensitivity and resolution of the proposed probe. Besides, the detection abilities of the tiny defects in metal and non-metal materials are demonstrated by the related experiments. The smallest detectable crack and via in the non-metal materials and the metal materials are of a λ/1538 (0.5 mm) width, a λ/513 (1.5 mm) diameter, a λ/3846 (0.2 mm) width and a λ/513 (1.5 mm) diameter, respectively. Moreover, to further evaluate the performance of the proposed probe, the defects under skin layer in the multilayer composite materials and the defects under corrosion in the carbon steel are inspected and imaged. Due to lower work frequency, high resolution, outstanding detection abilities of tiny defects, and large potentials in sensor arraying, the proposed probe would be a good candidate for microwave NDT and imaging.

Novel Electromagnetic Sensors Embedded in Reinforced Concrete Beams for Crack Detection

This paper investigates the possibility of applying novel microwave sensors for crack detection in reinforced concrete structures. Initially, a microstrip patch antenna with a split ring resonator (SRR) structure was designed, simulated and fabricated. To evaluate the sensor’s performance, a series of structural tests were carried out and the sensor responses were monitored. Four reinforced concrete (RC) beam specimens, designed according to the European Standards, were tested under three-point bending. The load was applied incrementally to the beams and the static responses were monitored via the use of a load cell, displacement transducers and crack width gauges (Demec studs). In parallel, signal readings from the microwave sensors, which were employed prior to the casting of the concrete and located along the neutral axis at the mid-span of the beam, were recorded at various load increments. The microwave measurements were analysed and compared with those from crack width gauges. A strong linear relationship between the crack propagation and the electromagnetic signal across the full captured spectrum was found, demonstrating the technique’s capability and its potential for further research, offering a reliable, low-cost option for structural health monitoring (SHM).

A Pixelated Microwave Near-Field Sensor for Precise Characterization of Dielectric Materials

A highly sensitive microwave near-field sensor based on electrically-small planar resonators is proposed for highly accurate characterization of dielectric materials. The proposed sensor was developed in a robust complete-cycle topology optimization procedure wherein first the sensing area was pixelated. By maximizing the sensitivity as our goal, a binary particle swarm optimization algorithm was applied to determine whether each pixel is metalized or not. The outcome of the optimization is a pixelated pattern of the resonator yielding the maximum possible sensitivity. A curve fitting method was applied to the full-wave simulation results to derive a closed form expression for extracting the dielectric constant of a chemical material from the shift in the resonance frequency of the sensor. As a proof of concept, the sensor was fabricated and used to measure the permittivity of two known liquids (cyclohexane and chloroform) and their mixtures with different volume ratios. The experimentally extracted dielectric constants were in an excellent agreement with the reference data (for pure cyclohexane and chloroform) or those obtained by mixture formulas.

An Interdigital Electrode Probe for Detection, Localization and Evaluation of Surface Notch-Type Damage in Metals

Available microwave notch-type damage detection sensors are typically based on monitoring frequency shift or magnitude changes. However, frequency shift testing needs sweep-frequency data that make scanning detection becomes difficult and time-consuming. This work presents a microwave near-field nondestructive testing sensor for detecting sub-millimeter notch-type damage detection in metallic surfaces. The sensor is loaded with an interdigital electrode element in an open-ended coaxial. It is simple to fabricate and inexpensive, as it is etched on the RC4003 patch by using printed circuit board technology. The detection is achieved by monitoring changes in reflection amplitude, which is caused by perturbing the electromagnetic field around the interdigital structure. The proposed sensor was tested on a metallic plate with different defects, and the experimental results indicated that the interdigital electrode probe can determine the orientation, localization and dimension of surface notch-type damage.

Complementary Split-Ring Resonator-Loaded Microfluidic Ethanol Chemical Sensor

In this paper, a complementary split-ring resonator (CSRR)-loaded patch is proposed as a microfluidic ethanol chemical sensor. The primary objective of this chemical sensor is to detect ethanol’s concentration. First, two tightly coupled concentric CSRRs loaded on a patch are realized on a Rogers RT/Duroid 5870 substrate, and then a microfluidic channel engraved on polydimethylsiloxane (PDMS) is integrated for ethanol chemical sensor applications. The resonant frequency of the structure before loading the microfluidic channel is 4.72 GHz. After loading the microfluidic channel, the 550 MHz shift in the resonant frequency is ascribed to the dielectric perturbation phenomenon when the ethanol concentration is varied from 0% to 100%. In order to assess the sensitivity range of our proposed sensor, various concentrations of ethanol are tested and analyzed. Our proposed sensor exhibits repeatability and successfully detects 10% ethanol as verified by the measurement set-up. It has created headway to a miniaturized, non-contact, low-cost, reliable, reusable, and easily fabricated design using extremely small liquid volumes.

Reducing Sweeping Frequencies in Microwave NDT Employing Machine Learning Feature Selection

Nondestructive Testing (NDT) assessment of materials’ health condition is useful for classifying healthy from unhealthy structures or detecting flaws in metallic or dielectric structures. Performing structural health testing for coated/uncoated metallic or dielectric materials with the same testing equipment requires a testing method that can work on metallics and dielectrics such as microwave testing. Reducing complexity and expenses associated with current diagnostic practices of microwave NDT of structural health requires an effective and intelligent approach based on feature selection and classification techniques of machine learning. Current microwave NDT methods in general based on measuring variation in the S-matrix over the entire operating frequency ranges of the sensors. For instance, assessing the health of metallic structures using a microwave sensor depends on the reflection or/and transmission coefficient measurements as a function of the sweeping frequencies of the operating band. The aim of this work is reducing sweeping frequencies using machine learning feature selection techniques. By treating sweeping frequencies as features, the number of top important features can be identified, then only the most influential features (frequencies) are considered when building the microwave NDT equipment. The proposed method of reducing sweeping frequencies was validated experimentally using a waveguide sensor and a metallic plate with different cracks. Among the investigated feature selection techniques are information gain, gain ratio, relief, chi-squared. The effectiveness of the selected features were validated through performance evaluations of various classification models; namely, Nearest Neighbor, Neural Networks, Random Forest, and Support Vector Machine. Results showed good crack classification accuracy rates after employing feature selection algorithms.