Microwave Nondestructive Testing Techniques Research Articles

Fast VGG: An Advanced Pre-Trained Deep Learning Framework for Multi-Layered Composite NDE via Multifrequency Near-Field Microwave Imaging

ABSTRACT Microwave nondestructive testing (NDT) techniques show promise for composite inspection due to microwave signals’ ability to penetrate and interact with internal structures. However, current microwave imaging approaches have poor spatial resolution, struggling to distinguish defects from defect-free regions. This limits reliable subsurface analysis and widespread adoption. This paper introduces a novel multi-frequency microwave imaging fusion method using an open-ended waveguide and deep learning to enhance defect detection accuracy in carbon fiber-reinforced polymer (CFRP) composites. The proposed technique employs an optimized feature extraction strategy to improve differentiation between defective and sound areas for superior subsurface visualization. The method leverages VGG-19 for efficient feature extraction and parallel processing to merge information from multi-frequency images. Our method significantly improved detection accuracy and F1 score, surpassing non-deep learning image fusion techniques by at least 50%. The optimized fusion strategy enables clear visualization of various defect types across multiple subsurface layers. Our approach also reduces computation time versus standard VGG implementation by 3–4×, showing scalability. The results demonstrate the proposed method’s potential to overcome existing constraints and provide rapid, accurate subsurface analysis of complex CFRP structures through an optimized deep learning framework, holding significance for expanding microwave NDE applications.

Inspection of thick composites: a comparative study between microwaves, X-ray computed tomography and ultrasonic testing

ABSTRACT Inspection of thick and low-density multilayer composite structures is of paramount importance. X-ray computed tomography (CT) and phased array ultrasonic testing (PAUT) are widely employed modalities for non-destructive testing (NDT) of these composites. Owing to low density of constituent materials typically utilised to construct composites and rich wave scattering within their structures, inspecting them using X-ray CT and PAUT does not always yield acceptable flaw detection results. On the other hand, microwave NDT techniques have shown to be particularly suitable for inspecting thick multilayer non-carbon-based composites. However, the relative performance of emerging microwave NDT techniques and the widely accepted X-ray CT and PAUT is yet to be established. This paper provides first-of-its-kind experimental comparison between microwave, X-ray CT, and PAUT on a comprehensive set of thick composite samples with different defect types. It is demonstrated herein that microwave NDT performed on par with X-ray CT in terms of defect detection capability (qualitatively and quantitatively), and in many cases outperformed PAUT. A detailed summary overviewing the performance, advantages and shortcomings of each method for particualr defect types is included which disseminates new knowledge to benefit practitioners and researchers alike.

Detection of surface cracks on slanted surfaces and through thick irregular insulation layers using polarimetric microwave imaging

Reliable detection of cracks on slanted metal surfaces and through irregular insulation/coating is critical in many inspection applications. Microwave non-destructive testing (NDT) techniques have proven to be effective for crack detection and characterization. However, the utility of conventional microwave NDT techniques for challenging inspection scenarios which involve cracks on slanted surfaces, or cracks under relatively thick, and possibly, irregular insulation has been limited. In this paper, a polarimetric microwave imaging approach is employed for the detection of cracks in such inspection cases. The detection concept using interrogation with dual polarized wave to suppress the background is presented. It is established herein that the cross-polarization measurement is independent to irregular surfaces, and therefore, it constitutes an effective mean for reliable crack detection even if the background is not uniform or if the metal surface is slanted. This fact is further corroborated by numerical electromagnetic simulations and measurements. The efficacy of the proposed method is demonstrated using imaging results of various samples spanning the abovementioned scenarios.

A Microwave Time Domain Reflectometry Technique Combining the Wavelet Decomposition Analysis and Artificial Neural Network for Detection of Defects in Dielectric Structures

The microwave nondestructive testing (MNDT) technique is an attractive candidate for defect detection in the dielectric structures as microwave signals can penetrate inside and interact with the insides of the dielectric material. In this research, a novel MNDT technique is presented for defect detection combining the time domain reflectometry (TDR) technique, the wavelet decomposition analysis (WDA) technique, and an artificial neural network (ANN), which has good generality and can be applied to various dielectric materials with different thicknesses. This method is based on scanning the dielectric material with an open-ended rectangular waveguide (OERW) operating from 18 to 26.5 GHz with 201 frequency points and analyzing its reflections using the proposed algorithm. The method was validated by simulation and experiments successfully. In the simulations, two typical kinds of dielectric materials were used to verify the generality and accuracy of this proposed method. The accuracies of these two dielectric materials were 96% and 90%, respectively. A 2-D image of detection can be constructed by performing repetition of the process with a certain step on the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">xy</i> plane of a material, which is illustrated by simulations. Meanwhile, the sensitivity analysis was performed by studying the similarity quantified using the Pearson’s coefficient correlation. Eventually, some FR4 samples were machined to demonstrate the feasibility of this method. The acceptable accuracy is 86% of the experimental result.

Prospect of Using Machine Learning-Based Microwave Nondestructive Testing Technique for Corrosion Under Insulation: A Review

Corrosion under insulations is described as localized corrosion that forms because of moisture penetration through the insulation materials or due to contaminants&#x2019; presence within the insulation material. The traditional non-destructive inspection techniques operating at a low frequency require removing insulation material to enable inspection, due to poor signal penetration. Several high-frequency inspection techniques such as the microwave technique have shown successful inspection in detecting the defect under insulations, without removing the insulations. However, the microwave technique faces several challenges such as poor spatial imaging, large errors in terms of defect size and depth owing to stand-off distance variations, optimal frequency point selection, and the presence of the outlier in microwave measurement data. The microwave technique in conjunction with machine learning approaches has tremendous potential and viability for assessing corrosion under insulation. Machine learning is highly possible to improve the efficiency of microwave techniques because its impact has been demonstrated in various conventional non-destructive techniques. This paper provides an in-depth review of non-destructive techniques for assessing corrosion under insulation, as well as the possibility of using machine learning approaches in microwave techniques in comparison to other conventional techniques.

A Past, Present, and Prospective Review on Microwave Nondestructive Evaluation of Composite Coatings

Recent years have witnessed an increase in the use of composite coatings for numerous applications, including aerospace, aircraft, and maritime vessels. These materials owe this popularity surge to the superior strength, weight, stiffness, and electrical insulation they exhibit over conventional substances, such as metals. The growing demand for such materials is accompanied by the inevitable need for fast, accurate, and affordable nondestructive testing techniques to reveal any possible defects within the coatings or any defects under coating. However, typical nondestructive testing (NDT) techniques such as ultrasonic testing (UT), infrared thermography (IRT), eddy current testing (ECT), and laser shearography (LS) have failed to provide successful results when inspecting composite coatings. Consequently, microwave NDT techniques have emerged to compensate for the shortcomings of traditional NDT approaches. Numerous microwave NDT methods have been reported for composite coatings inspection. Although existing microwave NDT methods have shown successful inspection of composite coatings, they often face several challenges, such as low spatial image quality and extensive data interpretation. Nevertheless, many of these limitations can be addressed by utilizing microwave NDT techniques with modern technologies such as soft computing. Artificially intelligent techniques have greatly enhanced the reliability and accuracy of microwave NDT techniques. This paper reviews various traditional NDT techniques and their limitations in inspecting composite coatings. In addition, the article includes a detailed review of several microwave NDT techniques and their benefits in evaluating composite coatings. The paper also highlights the advantages of using the recently reported microwave NDT approaches employing artificial intelligence approaches. This review demonstrates that microwave NDT techniques in conjunction with artificial intelligence approaches have excellent prospects for further enhancing composite coatings inspection and assessment efficiency. The review aimed to provide the reader with a comprehensive overview of most NDT techniques used for composite materials alongside their most salient features.

Microwave Non-Destructive Testing Technique for Material Characterization of Concrete Structures via Electromagnetic Waves with FDTD

Concrete is a nonhomogeneous medium that contains coarse aggregate, sand (fine aggregate), cement powder, water and porosity. Microwave non-destructive testing (NDT) technique is used to simulate three layered media that contains air gap, coarse aggregate and a two layered media that contain rebar and void is modeled as closest to the reality. Interaction of electromagnetic wave and the concrete pile is utilized for numerical simulation. A Finite-Difference Time-Domain (FDTD) method with Perfectly Matched Layer (PML) Absorbing Boundary Condition (ABC) is proposed to simulate electromagnetic wave propagation in FRP tube and composite pile. 2D simulation of a wave generated from a point source at microwave frequencies is obtained by using MATLAB®.

IFFT-Based Microwave Non-Destructive Testing for Delamination Detection and Thickness Estimation

Microwave Non-Destructive Testing (NDT) techniques for dielectric coatings are vital processes in many industrial applications due to their superior defect detection capabilities over traditional NDT methods. However, the limited bandwidth and post-processing complexities of these techniques cause them to fall short of accurately estimating the delamination thickness in such structures. In this paper, a novel low-complexity signal processing method is proposed to estimate the delamination thickness in metal-backed dielectric coatings using bandwidth-limited Open-Ended Rectangular Waveguide (OERW) probes. Here, Inverse Fast Fourier Transform (IFFT) process is used to convert the measured complex reflection coefficients at the surface of the coating to the time domain. Next, the amplitude of a specific time step is used to accurately estimate the delamination thickness without extra time-consuming processing. Using a 3 mm-thick macor samples with machined defects, the proposed technique is validated by correctly estimating delamination thickness down to 0.4 mm using an OERW probe with 13.5 GHz bandwidth. Hence, this technique overcomes the challenge of the OERW's limited bandwidth, which highly affects the possibility of tracking shifting in the peak reflection in the time domain. Moreover, the proposed method does not add to the complexity of the NDT process, which makes it suitable for in-situ real time applications. Hence, following this approach would be of great importance to numerous industries, where accurate thickness estimation of minute delamination in coatings is essential to avoid system failure.

Microwave Nondestructive Testing for Defect Detection in Composites Based on K-Means Clustering Algorithm

Composite such as Glass Fibre Reinforced Polymer (GFRP) is increasingly used as insulation in many industrial applications such as the steel pipelines in the oil and gas industry. Due to ageing and cyclic operation, many hidden defects exist under insulation, such as corrosion and delamination. If these defects are not promptly detected and restored, the growth of defects causes a catastrophic loss. Therefore, an effective inspection technique using non-destructive testing (NDT) to detect the underneath defect is required. The ability of microwave signals to penetrate and interact with the inner structure within composites makes them a promising candidate for composite inspection. In the case of GFRP, the random patterns cause permittivity variations that influence the propagation of the microwave signals, which results in a blurred spatial image making the assessment of the material's state difficult. In this research, a novel microwave NDT technique is presented based on k-means unsupervised machine learning for defect detection in composites. At present, the defect evaluation using an unsupervised machine learning-based microwave NDT technique is not reported elsewhere. The unsupervised machine learning is employed to enhance the imaging efficiency and defect detection in GFRP. The technique is based on scanning the composite material with an open-ended rectangular waveguide operating from 18 to 26.5 GHz with 101 frequency points. The influence of the permittivity variations on the reflected coefficients due to the random patterns of GFRP is mitigated by measuring the mean of a set of the adjacent points at each operating frequency point using a small rectangular window. The measured data is converted to the time domain using a fast inverse Fourier transform (IFFT) to provide significant features and increase the signal resolution to 201-time steps. K-means algorithm is utilized to cluster the given features into the defect and defect-free regions in GFRP. The findings presented in this paper demonstrate the benefits of an unsupervised machine learning to detect a defect down to 1 mm, which is a considerable contribution over any existing defect inspection technique in composites.

Nondestructive Evaluation of Coatings Delamination Using Microwave Time Domain Reflectometry Technique

Ceramic based coatings such as Thermal Barrier Coatings (TBCs) are widely deposited onto gas turbine engine components to protect their metal substrate against high temperature. However, improper adhesive application, thermal stress and moisture penetration through the insulation materials can cause defects such as delamination to grow between the insulation and the metal surface. Such defects could lead to catastrophic failure if not immediately detected and repaired. Hence, it is imperative to non-destructively inspect these interfaces for delamination to avoid such an event. In this paper, a novel microwave non-destructive testing technique for ceramic-based coatings is proposed. This technique is based on scanning the surface of the coating with an open-ended rectangular waveguide and analyzing the reflections in the time domain. The proposed time-domain technique appears to reveal more about the depth of any existing delamination than any other microwave non-destructive testing (NDT) technique. Here, a ceramic sample with machined delamination is scanned using rectangular waveguides operating from 26.5 to 40 GHz. After applying Fourier analysis to the frequency domain waveguide reflections, time-domain results showed the delamination with significantly better depth resolution compared to frequency domain analysis. The results reported in this paper prove the advantages of the time-domain technique to forecast the relative delamination depth, which is important for many industrial applications. The depth information of delamination can be used in a condition-based predictive maintenance schedule to plan the inspection intervals efficiently, minimize the unnecessary replacements and provide practical guidance for future design.

Review on microwave nondestructive testing techniques and its applications in concrete technology

Abstract Every year, a massive amount of literature is published on many aspects of microwave applications. Over the past few years, the need for progressive methods for assessing different properties of concrete, as well as for maintenance and monitoring of structures, has led to the development of microwave non-destructive testing (MNDT) techniques for preserving the civil infrastructure. MNDT has many advantages, including good penetrability in nonmetallic materials, instantaneous measurements, monochromatic radiation, low power requirements, substantial energy savings, and easy-to-interpret data. Additionally, with the potential to overcome the limits of both conventional testing and non-destructive testing (NDT), MNDT has received much interest. In this paper, a comprehensive review of the most common MNDT techniques for material assessment is conducted based on a detailed literature survey. Furthermore, the basics of MNDT techniques are explored to contribute to its use in the concrete industry. The conventional tests and NDTs on concrete, including the applications of different MNDT methods, are discussed. The outcomes of this review can assist in using the MNDT methods in concrete structures, structural health monitoring, and enhancement of microwave-based techniques. Finally, this work provides a summary of MNDT techniques used in concrete applications, which can lead to advancements in this field.

Prospect of Using Artificial Intelligence for Microwave Nondestructive Testing Technique: A Review

The development in materials technology has produced stronger, lighter, stiffer, and more durable electrically insulating composites which are replacing metals in many applications. These composites require alternative inspection techniques because the conventional nondestructive testing (NDT) techniques such as thermography, eddy currents, ultrasonic, X-ray and magnetic particles have limitations of inspecting them. Microwave NDT technique employing open-ended rectangular waveguides (OERW) has emerged as a promising approach to detect the defects in both metal and composite materials. Despite its promising results over conventional NDT techniques, OERW microwave NDT technique has shown numerous limitations in terms of poor spatial resolution due to the stand-off distance variations, inspection area irregularities and quantitative estimation in imaging the size of defects. Microwave NDT employing OERW in conjunction with robust artificial intelligence approaches have tremendous potential and viability for evaluating composite structures for the purpose mentioned here. Artificial intelligence techniques with signal processing techniques are highly possible to enhance the efficiency and resolution of microwave NDT technique because the impact of artificial intelligence approaches is proven in various conventional NDT techniques. This paper provides a comprehensive review of NDT techniques as well as the prospect of using artificial intelligence approaches in microwave NDT technique with regards to other conventional NDT techniques.

Detection of surface cracks in metals using time‐domain microwave non‐destructive testing technique

This study theoretically investigates the application of ultra-wideband (UWB) signals in crack detection as a microwave non-destructive testing technique which is well developed in frequency domain in recent decades. To analyse UWB signals, with traditional frequency-domain methods, is needed to cover a wide range of separate frequencies. Another approach is to solve the problem with time-domain (TD) techniques in which fields are assumed as general functions of time instead of single frequency harmonics. The advantages of such TD numerical techniques are first, their applicability for arbitrarily wide-frequency range by one-time execution, and second that they give the potential for detection of small changes in the received signal that corresponds to small but sometimes significant defects of specimen. As it will be shown, using UWB pulses is an efficient way for detection of fine cracks which are of practical importance.

Evaluation of Atmospheric Corrosion on Coated Steel Using -Band Sweep Frequency Microwave Imaging

This paper investigated a $K$ -band sweep frequency microwave imaging for the evaluation of coated atmospheric corrosion on mild steel. After theory analysis, the experimental system has been built by using a $K$ -band open-ended rectangular waveguide, a vector network analyser, a scanning system, and a signal processing algorithm. Exposed and coated steel samples with different exposure periods (one, six, and ten months) have been prepared by International Paint. The height and roughness of these exposed corrosion samples have been measured by laser profilometry for comparison with microwave results. In experimental studies, the averaged magnitude of sweep frequency microwave signals describing the interaction of microwave signals with a corrosion layer has been used to image and map the corrosion under coating. These results show that the proposed sweep frequency microwave non-destructive testing technique can be used to identify, detect, and evaluate the coated corrosion in different exposure periods without selecting operation frequency, which is a potential solution for remote corrosion evaluation. These results also show that the power function is also suitable for demonstrating the development of short-term stage (in six months) atmospheric corrosion, such as long-term corrosion. With the exposure period increasing, the height of the corrosion layer quickly increases during first six months but has a little decrease at ten months.

Outdoor Insulators Testing Using Artificial Neural Network-Based Near-Field Microwave Technique

This paper presents a novel artificial neural network (ANN)-based near-field microwave nondestructive testing technique for defect detection and classification in nonceramic insulators (NCI). In this paper, distribution class 33-kV NCI samples with no defects, air voids in silicone rubber and fiber glass core, cracks in the fiberglass core, and small metallic inclusion between the fiber core and shank were inspected. The microwave inspection system uses an open-ended rectangular waveguide sensor operating in the near-field at a frequency of 24 GHz. A data acquisition system was used to record the measured data. ANN was trained to classify the different types of defects. The results showed that all defects were detected and classified correctly with high recognition rates.

Concrete dielectric properties investigation using microwave nondestructive techniques

The paper deals with dielectric properties of concrete and the effect of frequency, curing time and water to cement (w/c) ratio, concrete compression strength, steel fibre concrete and moisture content on the dielectric properties. The concrete dielectric properties such as transmission coefficients, reflection coefficients, dielectric constants and loss factors; were investigated using microwave nondestructive testing (MNDT) technique. The MNDT system consists of transmit and receive horn lens antennas, a vector network analyzer, mode transitions, and a printer. The horn lens antennas are used for minimizing diffraction effects due to the edges of the sample. Electromagnetic waves at microwave frequency range 7.0–13.0 GHz using free-space microwave method was used for measuring dielectric properties of concrete. Concrete specimens were prepared using different w/c ratios and different compressive strengths. Concrete dielectric properties were measured and correlated with compressive strength and w/c ratio of concrete, curing time. The experimental results indicate that microwave non-destructive technique has correlated well with to determine the compressive strength and w/c ratios of concrete. The results also show the potential to be used to determine the percentage of fiber. This technique is easy to adapt for in situ measurements.

Detecting defects in outdoor non-ceramic insulators using near-field microwave non-destructive testing

This paper presents a novel near-field microwave nondestructive testing technique for defect detection in non-ceramic insulators (NCI). In this work, distribution class 33 kV NCI samples with no defects, air voids in silicone rubber, cracks in the fiberglass core and small metallic inclusion between the fiber core and shank were inspected. The microwave inspection system utilizes an open-ended rectangular waveguide sensor operating in the near-field at a frequency of 24 GHz. The used inspection system is simple, safe and relatively inexpensive. A data acquisition system was used to record the measured data. The results showed that all defects were repeatedly detected with high sensitivity. Line scans of the samples were obtained revealing the presence of different defects and their location. The technique also demonstrated ability to detect thickness variations in the silicon rubber shank.

Innovative Near-Field Microwave Nondestructive Testing of Corroded Metallic Structures Utilizing Open-Ended Rectangular Waveguide Probes

An innovative method utilizing microwave nondestructive testing and evaluation (NDT&E) techniques for enhanced detection and evaluation of rust under paint has been developed. The results are promising, and they show that the use of a layer of dielectric material with known properties to replace the standoff layer (air) yields significant improvements in the measurement sensitivity and resolution for some microwave NDT applications. The goals of this investigation were pursued and achieved using theoretical electromagnetic computer programs describing the interaction of microwave signals radiated out of an open-ended rectangular waveguide with any layered medium. One of the computer programs calculates the aperture reflection coefficient (simulating measurements), and the other computer program calculates the field distribution in any layered media. The experimental results were obtained using an inspection system that was built according to the results of the theoretical investigation, and they confirmed the theoretical results.

Microwave non-destructive testing technique for characterization of HPMC-PEG 3000 films

The capacity of microwave non-destructive testing (NDT) technique to characterize the matrix property of binary polymeric films for use as transdermal drug delivery system was investigated. Hydroxypropylmethylcellulose (HPMC) and polyethylene glycol (PEG) 3000 were the choice of polymeric matrix and plasticizer, respectively with loratadine as the model drug. Both blank and drug loaded HPMC-PEG 3000 films were prepared using the solvent-evaporation method. These films were conditioned at the relative humidity of 25, 50 and 75% prior to physicochemical characterization using the established methods of ultra-violet spectrophotometry, differential scanning calorimetry and Fourier transform infrared spectroscopy methods, as well as, novel microwave NDT technique. Blank films exhibited a greater propensity of polymer–polymer interaction at the O–H domain upon storage at a lower level of relative humidity, whereas drug loaded films exhibited a greater propensity of polymer–polymer, polymer–plasticizer and/or drug–polymer interaction via the O–H, C–H and/or aromatic C C functional groups when they were stored at a lower or moderate level of relative humidity. The absorption and transmission characteristics of both blank and drug loaded films for microwave varied with the state of polymer–polymer, polymer–plasticizer, and/or drug–polymer interaction of the matrix. The measurements of microwave NDT test at 8 and 12 GHz were sensitive to the polar fraction of film involving functional group such as O–H moiety and the less polar environment of matrix consisting of functional groups such as C–H and aromatic C C moieties. The state of interaction between polymer, plasticizer and/or drug of a binary polymeric film can be elucidated through its absorption and transmission profiles of microwave.

Non-destructive microwave evaluation of TBC delamination induced by acute angle laser drilling

Laser drilling has been applied to the production of cooling holes of various size and angles in the modern aerospace gas turbine components such as turbine blades, nozzle guide vanes, combustion chambers and afterburner. These parts are usually made of heat resistant nickel superalloys. The superalloy substrate is coated with yttria-stabilized zirconia thermal barrier coatings (TBCs) to protect them from reaching excessive temperatures in hot engine environments. Drilling the parts at acute angles to the surface is complicated because (i) multiple layers are being drilled through, (ii) the melt ejection and heat flow patterns around the hole are non-symmetrical and (iii) the drilling distance is greater than when drilling normal to the surface. In a previous investigation by the authors, delamination of TBC was addressed as a main problem of angled drilling and mechanisms involved were discussed. Characterization of delamination cracks was normally performed via metallographic techniques. It involves sectioning the samples using an abrasive cutting machine, grinding with successively finer silicon carbide paper up to the centre of the hole and polishing to allow optical microscopic analysis of the cracks. However, clamping and sectioning process of thermal-spray-coated workpieces can introduce cracks in brittle coatings due to the drag of the cut-off wheels. Hence, it is not possible to decide if the delamination is caused as a result of post-process sectioning or laser drilling. In this paper, a microwave non-destructive testing (NDT) technique is employed to evaluate the integrity of TBC after acute angle laser drilling. An Agilent 8510 XF network analyser operating over the frequency range of 45 MHz to 110 GHz was used to measure the amplitude and phase variations of scattered waves. The results significantly indicated the existence of delamination of 1–1.5 mm long at the TBC/substrate interface on the leading edge part of an acute-angled hole laser drilled using a 400 W Nd:YAG laser.