Advances in Non-Destructive Testing Methods

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Energies energies	3.0	6.2	2008	16.8 Days	CHF 2600
Applied Sciences applsci	2.5	5.3	2011	18.4 Days	CHF 2400
Sensors sensors	3.4	7.3	2001	18.6 Days	CHF 2600
Materials materials	3.1	5.8	2008	13.9 Days	CHF 2600
Designs designs	-	3.9	2017	21.7 Days	CHF 1600

5 pages, 332 KiB

Open AccessEditorial

Advances in Non-Destructive Testing Methods

by Grzegorz Peruń

Materials 2024, 17(3), 554; https://doi.org/10.3390/ma17030554 - 24 Jan 2024

Cited by 4 | Viewed by 2482

Non-destructive testing (NDT) methods are a group of tests allowing one to detect external (surface) as well as internal defects of a structure [...] Full article

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18 pages, 6491 KiB

Open AccessArticle

A Transformer-Optimized Deep Learning Network for Road Damage Detection and Tracking

by Niannian Wang, Lihang Shang and Xiaotian Song

Sensors 2023, 23(17), 7395; https://doi.org/10.3390/s23177395 - 24 Aug 2023

Cited by 10 | Viewed by 3144

Abstract

To solve the problems of low accuracy and false counts of existing models in road damage object detection and tracking, in this paper, we propose Road-TransTrack, a tracking model based on transformer optimization. First, using the classification network based on YOLOv5, the collected [...] Read more.

To solve the problems of low accuracy and false counts of existing models in road damage object detection and tracking, in this paper, we propose Road-TransTrack, a tracking model based on transformer optimization. First, using the classification network based on YOLOv5, the collected road damage images are classified into two categories, potholes and cracks, and made into a road damage dataset. Then, the proposed tracking model is improved with a transformer and a self-attention mechanism. Finally, the trained model is used to detect actual road videos to verify its effectiveness. The proposed tracking network shows a good detection performance with an accuracy of 91.60% and 98.59% for road cracks and potholes, respectively, and an F1 score of 0.9417 and 0.9847. The experimental results show that Road-TransTrack outperforms current conventional convolutional neural networks in terms of the detection accuracy and counting accuracy in road damage object detection and tracking tasks. Full article

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21 pages, 13385 KiB

Open AccessArticle

Exploration of Damage Identification Method for a Large-Span Timber Lattice Shell Structure in Taiyuan Botanical Garden based on Structural Health Monitoring

by Guoqing Wang, Chenjia Xu, Shujia Zhang, Zichun Zhou, Liang Zhang, Bin Qiu, Jia Wan and Honggang Lei

Sensors 2023, 23(15), 6710; https://doi.org/10.3390/s23156710 - 27 Jul 2023

Cited by 2 | Viewed by 1603

Abstract

Large-span spatial lattice structures generally have characteristics such as incomplete modal information, high modal density, and high degrees of freedom. To address the problem of misjudgment in the damage detection of large-span spatial structures caused by these characteristics, this paper proposed a damage [...] Read more.

Large-span spatial lattice structures generally have characteristics such as incomplete modal information, high modal density, and high degrees of freedom. To address the problem of misjudgment in the damage detection of large-span spatial structures caused by these characteristics, this paper proposed a damage identification method based on time series models. Firstly, the order of the autoregressive moving average (ARMA) model was selected based on the Akaike information criterion (AIC). Then, the long autoregressive method was used to estimate the parameters of the ARMA model and extract the residual sequence of the autocorrelation part of the model. Furthermore, principal component analysis (PCA) was introduced to reduce the dimensionality of the model while retaining the characteristic values. Finally, the Mahalanobis distance (MD) was used to construct the damage sensitive feature (DSF). The dome of Taiyuan Botanical Garden in China is one of the largest non-triangular timber lattice shells worldwide. Relying on the structural health monitoring (SHM) project of this structure, this paper verified the effectiveness of the damage identification model through numerical simulation and determined the damage degree of the dome structure through SHM measurement data. The results demonstrated that the proposed damage identification method can effectively identify the damage of large-span timber lattice structures, locate the damage position, and estimate the degree of damage. The constructed DSF had relatively strong robustness to small damage and environmental noise and has practical application value for SHM in engineering. Full article

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15 pages, 6221 KiB

Open AccessArticle

Design and Experimental Research of Intelligent Inspection and Classification System for Yuba Skin Quality

by Yanhu Tao, Yinjie Shen, Liangyuan Xu, Qiansheng Tang and Haibo Yang

Appl. Sci. 2023, 13(12), 7070; https://doi.org/10.3390/app13127070 - 13 Jun 2023

Viewed by 1375

Abstract

At present, the surface quality of Yuba skin is determined by sensory methods. In order to realize the intelligent classification detection of Yuba skin quality, this study designed a system that automatically determines the quality of Yuba skin surfaces based on image processing [...] Read more.

At present, the surface quality of Yuba skin is determined by sensory methods. In order to realize the intelligent classification detection of Yuba skin quality, this study designed a system that automatically determines the quality of Yuba skin surfaces based on image processing and support vector machine (SVM) approaches. Specifically, the system uses image preprocessing to extract the grayscale eigenvalues, gray level co-occurrence matrix (GLCM) eigenvalues, and gray level run length matrix (GLRLM) eigenvalues of the sample image and uses them as input values for a quality grading system. Through model evaluation of three classification models, the SVM classification model was selected according to the evaluation results, and different kernel functions were used in the model for sample training. Based on Matlab, the quality grading software of Yuba skin was developed and designed. Intelligent detection and grading were realized through the radial basis kernel function support vector machine (RBF-SVM) grading model. The best penalty factor (c = 3.50) and kernel parameter value (g = 0.98) were obtained through cross-validation. The accuracy of the model was 95.31% and 94.16% for the training and test sets, respectively. The grading accuracy of the RBF-SVM grading system was 93.56%, and the error was less than 5% compared with the traditional sensory method of grading; thus, the quality classification method based on the SVM classification system for Yuba skin is feasible and can be used for quality detection. Full article

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17 pages, 12375 KiB

Open AccessArticle

Learning from Projection to Reconstruction: A Deep Learning Reconstruction Framework for Sparse-View Phase Contrast Computed Tomography via Dual-Domain Enhancement

by Changsheng Zhang, Jian Fu and Gang Zhao

Appl. Sci. 2023, 13(10), 6051; https://doi.org/10.3390/app13106051 - 15 May 2023

Cited by 3 | Viewed by 1951

Abstract

Phase contrast computed tomography (PCCT) provides an effective non-destructive testing tool for weak absorption objects. Limited by the phase stepping principle and radiation dose requirement, sparse-view sampling is usually performed in PCCT, introducing severe artifacts in reconstruction. In this paper, we report a [...] Read more.

Phase contrast computed tomography (PCCT) provides an effective non-destructive testing tool for weak absorption objects. Limited by the phase stepping principle and radiation dose requirement, sparse-view sampling is usually performed in PCCT, introducing severe artifacts in reconstruction. In this paper, we report a dual-domain (i.e., the projection sinogram domain and image domain) enhancement framework based on deep learning (DL) for PCCT with sparse-view projections. It consists of two convolutional neural networks (CNN) in dual domains and the phase contrast Radon inversion layer (PCRIL) to connect them. PCRIL can achieve PCCT reconstruction, and it allows the gradients to backpropagate from the image domain to the projection sinogram domain while training. Therefore, parameters of CNNs in dual domains are updated simultaneously. It could overcome the limitations that the enhancement in the image domain causes blurred images and the enhancement in the projection sinogram domain introduces unpredictable artifacts. Considering the grating-based PCCT as an example, the proposed framework is validated and demonstrated with experiments of the simulated datasets and experimental datasets. This work can generate high-quality PCCT images with given incomplete projections and has the potential to push the applications of PCCT techniques in the field of composite imaging and biomedical imaging. Full article

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12 pages, 4820 KiB

Open AccessArticle

A Technique for Multi-Parameter Signal Processing of an Eddy-Current Probe for Measuring the Thickness of Non-Conductive Coatings on Non-Magnetic Electrically Conductive Base Metals

by Michael Syasko, Pavel Solomenchuk, Igor’ Soloviev and Natalia Ampilova

Appl. Sci. 2023, 13(8), 5144; https://doi.org/10.3390/app13085144 - 20 Apr 2023

Cited by 4 | Viewed by 1634

Abstract

The known amplitude-sensitive eddy-current method for measuring the thickness of non-conductive coatings on conductive non-magnetic base metals does not satisfy the accuracy requirements. A primary consideration is the significant influence of a change in the specific electrical conductivity of the base metals on [...] Read more.

The known amplitude-sensitive eddy-current method for measuring the thickness of non-conductive coatings on conductive non-magnetic base metals does not satisfy the accuracy requirements. A primary consideration is the significant influence of a change in the specific electrical conductivity of the base metals on results of measurements. In this study, we developed a technique for measuring the thickness of non-conductive coatings on non-magnetic conductive base metals by using the eddy-current amplitude-phase method and implemented algorithms to process obtained information. Our method considered the influence of the specific electrical conductivity of the base metals by forming a two-dimensional graduation characteristic of the thickness gauge by using several base metals with different specific electrical conductivity. The algorithm for point-in-polygon determination was applied, which allowed us to measure the thickness of the coatings and the specific electrical conductivity of the base metals as independent values. The equipment necessary to construct the two-dimensional graduation characteristic and the algorithm for calculation of the thickness are described in detail. Full article

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16 pages, 5754 KiB

Open AccessArticle

An Approach to the Automated Characterization of Out-of-Plane and In-Plane Local Defect Resonances

by Paweł Zdziebko, Mateusz Krzemiński, Maciej Okoń, Gabriela Loi, Francesco Aymerich, Łukasz Pieczonka and Andrzej Klepka

Materials 2023, 16(8), 3084; https://doi.org/10.3390/ma16083084 - 13 Apr 2023

Cited by 4 | Viewed by 1415

Abstract

The paper presents an approach to efficiently detect local defect resonances (LDRs) in solids with localized defects. The 3D scanning laser Doppler vibrometry (3D SLDV) technique is applied to acquire vibration responses on the surface of a test sample due to a broadband [...] Read more.

The paper presents an approach to efficiently detect local defect resonances (LDRs) in solids with localized defects. The 3D scanning laser Doppler vibrometry (3D SLDV) technique is applied to acquire vibration responses on the surface of a test sample due to a broadband vibration excitation applied by a piezoceramic transducer and modal shaker. Based on the response signals and known excitation, the frequency characteristics for individual response points are determined. The proposed algorithm then processes these characteristics to extract both out-of-plane and in-plane LDRs. Identification is based on calculating the ratio between local vibration levels and the mean vibration level of the structure as a background. The proposed procedure is verified on simulated data obtained from finite element (FE) simulations and validated experimentally for an equivalent test scenario. The obtained results confirmed the effectiveness of the method in identifying in-plane and out-of-plane LDRs for both numerical and experimental data. The results of this study are important for damage detection techniques utilizing LDRs to enhance the efficiency of detection. Full article

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14 pages, 4182 KiB

Open AccessArticle

Possibilities of Detecting Damage Due to Osmosis of GFRP Composites Used in Marine Applications

by Waldemar Swiderski and Martyna Strag

Appl. Sci. 2023, 13(7), 4171; https://doi.org/10.3390/app13074171 - 24 Mar 2023

Cited by 5 | Viewed by 2154

Abstract

The marine composites market is driven by the increasing demand for lightweight, corrosion-resistant, and impact-resistant boats. Polymer matrix composites are currently the most popular composite material in marine applications. Fiberglass composites are practically the main type of fiber composites that are used extensively [...] Read more.

The marine composites market is driven by the increasing demand for lightweight, corrosion-resistant, and impact-resistant boats. Polymer matrix composites are currently the most popular composite material in marine applications. Fiberglass composites are practically the main type of fiber composites that are used extensively in marine applications. Due to the aggressive sea environment, composite structural elements of ships are exposed to damage due to the phenomenon of osmosis. This damage is also favored by defects that result from impacts and technological errors during the production of these elements. Non-destructive testing methods are necessary to detect damage in the internal structure of the composite. The paper presents a numerical analysis of the possibility of using vibrothermography in the detection of defects in glass–fiber reinforced laminates in marine applications. Numerical simulations have shown that the most favorable method for detecting defects will be acoustic waves. This is an unusual application because, as a rule, the range of ultrasonic waves is used in vibrothermography. In our further works, it is planned to verify numerical calculations through experimental research. The applicability of the terahertz technique was also assessed. During the experimental testing, all defects in the test sample of the glass–fiber reinforced composite were detected using this technique. The presented results indicate the applicability of the presented methods for the detection of defects in composites used in marine applications. Full article

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24 pages, 15622 KiB

Open AccessArticle

Historical Silk: A Novel Method to Evaluate Degumming with Non-Invasive Infrared Spectroscopy and Spectral Deconvolution

by Ludovico Geminiani, Francesco Paolo Campione, Carmen Canevali, Cristina Corti, Barbara Giussani, Giulia Gorla, Moira Luraschi, Sandro Recchia and Laura Rampazzi

Materials 2023, 16(5), 1819; https://doi.org/10.3390/ma16051819 - 22 Feb 2023

Cited by 11 | Viewed by 4088

Abstract

To correctly manage a collection of historical silks, it is important to detect if the yarn has been originally subjected to degumming. This process is generally applied to eliminate sericin; the obtained fiber is named soft silk, in contrast with hard silk which [...] Read more.

To correctly manage a collection of historical silks, it is important to detect if the yarn has been originally subjected to degumming. This process is generally applied to eliminate sericin; the obtained fiber is named soft silk, in contrast with hard silk which is unprocessed. The distinction between hard and soft silk gives both historical information and useful indications for informed conservation. With this aim, 32 samples of silk textiles from traditional Japanese samurai armors (15th–20th century) were characterized in a non-invasive way. ATR-FTIR spectroscopy has been previously used to detect hard silk, but data interpretation is challenging. To overcome this difficulty, an innovative analytical protocol based on external reflection FTIR (ER-FTIR) spectroscopy was employed, coupled with spectral deconvolution and multivariate data analysis. The ER-FTIR technique is rapid, portable, and widely employed in the cultural heritage field, but rarely applied to the study of textiles. The ER-FTIR band assignment for silk was discussed for the first time. Then, the evaluation of the OH stretching signals allowed for a reliable distinction between hard and soft silk. Such an innovative point of view, which exploits a “weakness” of FTIR spectroscopy—the strong absorption from water molecules—to indirectly obtain the results, can have industrial applications too. Full article

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17 pages, 14981 KiB

Open AccessArticle

The Signal Characteristics of Oil and Gas Pipeline Leakage Detection Based on Magneto-Mechanical Effects

by Bin Liu, Qian Ge, Zihan Wu, Zheng Lian, Lijian Yang and Hao Geng

Sensors 2023, 23(4), 1857; https://doi.org/10.3390/s23041857 - 7 Feb 2023

Cited by 6 | Viewed by 2196

Abstract

In order to solve the problem of the quantification of detection signals in the magnetic flux leakage (MFL) of defective in-service oil and gas pipelines, a non-uniform magnetic charge model was established based on magnetic effects. The distribution patterns of magnetic charges under [...] Read more.

In order to solve the problem of the quantification of detection signals in the magnetic flux leakage (MFL) of defective in-service oil and gas pipelines, a non-uniform magnetic charge model was established based on magnetic effects. The distribution patterns of magnetic charges under different stresses were analyzed. The influences of the elastic load and plastic deformation on the characteristic values of MFL signals were quantitatively assessed. The experimental results showed that the magnetic charge density was large at the edges of the defect and small at the center, and approximately decreased linearly with increasing stress. The eigenvalues of the axial and radial components of the MFL signals were compared, and it was found that the eigenvalues of the radial component exhibited a larger decline rate and were more sensitive to stress. With the increase in the plastic deformation, the characteristic values of the MFL signals initially decreased and then increased, and there was an inflection point. The location of the inflection point was associated with the magnetostriction coefficient. Compared with the uniform magnetic charge model, the accuracy of the axial and radial components of the MFL signals in the elastic stage of the improved magnetic charge model rose by 17% and 16%, respectively. The accuracy of the axial and radial components of the MFL signals were elevated by 9.15% and 9%, respectively, in the plastic stage. Full article

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18 pages, 9444 KiB

Open AccessArticle

An Inversion Algorithm for the Dynamic Modulus of Concrete Pavement Structures Based on a Convolutional Neural Network

by Gongfa Chen, Xuedi Chen, Linqing Yang, Zejun Han and David Bassir

Appl. Sci. 2023, 13(2), 1192; https://doi.org/10.3390/app13021192 - 16 Jan 2023

Cited by 5 | Viewed by 2263

Abstract

Based on the spectral element method (SEM) and a convolutional neural network (CNN), an inversion algorithm for the dynamic modulus of concrete pavement structures is proposed in this paper. In order to evaluate the service performance of pavement structures more systematically and accurately [...] Read more.

Based on the spectral element method (SEM) and a convolutional neural network (CNN), an inversion algorithm for the dynamic modulus of concrete pavement structures is proposed in this paper. In order to evaluate the service performance of pavement structures more systematically and accurately via the existing testing techniques using a falling weight deflectometer (FWD), it is necessary to obtain accurate dynamic modulus parameters of the structures. In this work, an inversion algorithm for predicting the dynamic modulus is established by using a CNN which is trained with the dynamic response samples of a multi-layered concrete pavement structure obtained through SEM. The gradient descent method is used to adjust the weight parameters in the network layer by layer in reverse. As a result, the accuracy of the CNN can be improved via iterative training. With the proposed algorithm, more accurate results of the dynamic modulus of pavement structures are obtained. The accuracy and numerical stability of the proposed algorithm are verified by several numerical examples. The dynamic modulus and thickness of concrete pavement structure layers can be accurately predicted by the CNN trained with a certain number of training samples based on the displacement curve of the deflection basin from the falling weight deflectometer. The proposed method can provide a reliable testing tool for the FWD technique of pavement structures. Full article

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14 pages, 4052 KiB

Open AccessArticle

Comparison of Measurement Possibilities by Non-Invasive Reflectometric Sensors and Invasive Probes

by Magdalena Paśnikowska-Łukaszuk, Magda Wlazło-Ćwiklińska, Jarosław Zubrzycki and Zbigniew Suchorab

Appl. Sci. 2023, 13(1), 665; https://doi.org/10.3390/app13010665 - 3 Jan 2023

Cited by 8 | Viewed by 2031

Abstract

The measurement of the moisture content of building materials is of key importance both in the process of building structures and in their subsequent operation. In engineering practice, indirect techniques of moisture measurement, mainly, resistance and capacitive, are the most popular. The main [...] Read more.

The measurement of the moisture content of building materials is of key importance both in the process of building structures and in their subsequent operation. In engineering practice, indirect techniques of moisture measurement, mainly, resistance and capacitive, are the most popular. The main objective of this research work was to compare the classic TDR measurement technique to the non-invasive, surface TDR sensors. Moisture measurements were carried out on samples made of cellular concrete with density class of 400 and 600. These samples were moist to various degrees, from 0 to 69% (400 c.c.) and from 0 to 55 (600 c.c.). For each sample, five measurements were carried out. Both the RMSE and the expanded uncertainty values were more favorable for the TDR FP/mts probe and were consistent with the literature data. Compared to them, the measurement result for the 400 c.c. samples with the S1 probe was 154.6%, and that with the S2 probe was 87.03% of the values obtained with the invasive probe. When measuring the 600 c.c. samples, we found values of 122.16% for S1 and of 120.1% for S2 of those obtained with the invasive probe. The use of surface TDR sensors provided an easy and quick measurement without damaging the surface and structure of the tested material, as there was no need to introduce the probe actuators inside the tested material. Full article

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14 pages, 2207 KiB

Open AccessArticle

Late Shelf Life Saturation of Golden Delicious Apple Parameters: TSS, Weight, and Colorimetry

by Salma Kassebi, Csaba Farkas, László Székely, Attila Géczy and Péter Korzenszky

Appl. Sci. 2023, 13(1), 159; https://doi.org/10.3390/app13010159 - 23 Dec 2022

Cited by 6 | Viewed by 3133

Abstract

This work aims to estimate the shelf life of Golden Delicious apple fruit stored at room temperature by determining the changing trend in color every week using a non-destructive measurement method. Moreover, the study will measure the changes in weight loss (Δm) and [...] Read more.

This work aims to estimate the shelf life of Golden Delicious apple fruit stored at room temperature by determining the changing trend in color every week using a non-destructive measurement method. Moreover, the study will measure the changes in weight loss (Δm) and the total soluble solids (TSS) contained in the apple. The research focuses on the last stage of ripening and the effect of shelf life affecting consumer behavior; therefore, the examined fruits were picked at the end of the season and were stored at an ambient temperature and in controlled laboratory conditions for six weeks, at 24 °C under 60% RH relative. Color measurements were performed with a portable color sensor, which provided a simple and effective examination method in the case of an appropriate number of fruit samples. The findings showed a significant increase in TSS and weight loss over time. Color varying (ΔE) and chroma (C*) parameters increased with prolonged storage duration, meaning that the color of the apples became darker and more color-saturated at the end of storage. While weight loss and TSS follow a linear tendency in the given storage period, the color changes in deteriorating fruits were characterized by exponential asymptotic regression. It was found that although the moisture content reaches its limit value during the drying process of apples, the saturation of color coordinates allows for determination of the limit parameters of consumption in the linear stage of weight loss. The saturation limits (70.97; 12.77; 56.34 CIELAB L*; a*; b*), the dominant color part (b*), and the growth rate of the saturation curves allow an accurate characterization of ripening from the visual aspect, thus determining the limit parameters of shelf life and improving the critical analysis factors affecting the life of fruits after harvest. By assessing color characteristics using a non-destructive technology, customers may quickly evaluate the quality of apples and make better decisions during their purchase. Full article

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20 pages, 6654 KiB

Open AccessArticle

Non-Destructive Evaluation of the Quality of Adhesive Joints Using Ultrasound, X-ray, and Feature-Based Data Fusion

by Elena Jasiūnienė, Bengisu Yilmaz, Damira Smagulova, Gawher Ahmad Bhat, Vaidotas Cicėnas, Egidijus Žukauskas and Liudas Mažeika

Appl. Sci. 2022, 12(24), 12930; https://doi.org/10.3390/app122412930 - 16 Dec 2022

Cited by 11 | Viewed by 3096

Abstract

The aim of this work is to achieve reliable nondestructive evaluation (NDE) of adhesively bonded aerospace components by developing novel multidimensional data fusion techniques, which would combine the information obtained by ultrasonic and X-ray NDE methods. Separately, both NDE techniques have their advantages [...] Read more.

The aim of this work is to achieve reliable nondestructive evaluation (NDE) of adhesively bonded aerospace components by developing novel multidimensional data fusion techniques, which would combine the information obtained by ultrasonic and X-ray NDE methods. Separately, both NDE techniques have their advantages and limitations. The integration of data obtained from pulse echo immersion ultrasound testing and radiography holds immense potential to help improve the reliability of non-destructive evaluation. In this study, distinctive features obtained from single techniques, traditional ultrasonic pulse echo testing, and radiography, as well as fused images, were investigated and the suitability of these distinctive features and fusion techniques for improving the probability of defect detection was evaluated. For this purpose, aluminum single lap joints with brass inclusions were analyzed using ultrasound pulse echo and radiography techniques. The distinctive features were extracted from the data obtained, and images of features obtained by both techniques were fused together. Different combinations of features and fusion algorithms were investigated, considering the desire to automate data evaluation in the future. Full article

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12 pages, 9439 KiB

Open AccessArticle

Effect of Temperature on Ultrasonic Nonlinear Parameters of Carbonated Concrete

by Jinzhong Zhao, Jin Wu, Xuejun Chen and Ruifu Zeng

Materials 2022, 15(24), 8797; https://doi.org/10.3390/ma15248797 - 9 Dec 2022

Cited by 4 | Viewed by 1464

Abstract

In order to explore the monitoring technique of concrete carbonation in various temperatures, longitudinal ultrasonic nonlinear parameters of carbonated concrete are measured by using an embedded composite piezoelectric transducer (ECPT) and a surface-mounted transducer. The effect of temperature from −20

^{\circ}

C to [...] Read more.

In order to explore the monitoring technique of concrete carbonation in various temperatures, longitudinal ultrasonic nonlinear parameters of carbonated concrete are measured by using an embedded composite piezoelectric transducer (ECPT) and a surface-mounted transducer. The effect of temperature from −20

^{\circ}

C to 40

^{\circ}

C with a temperature interval of 5

^{\circ}

C and water–cement ratio on the measurements of ultrasonic parameters for carbonated concrete is investigated. The ultrasonic transmission detection method and the second harmonic generation (SHG) technique for longitudinal waves are used in the study. Results of the experiment demonstrate that ECPT is effective in the monitoring of the changes in ultrasonic parameters of carbonated concrete. At the temperature ranging from 15

^{\circ}

C to 40

^{\circ}

C, the increasing temperature slightly increases the relative nonlinear parameters of carbonated concrete. It decreases significantly that the relative nonlinear parameters of carbonated concrete measured at 0

^{\circ}

C compared with that at 10

^{\circ}

C. The configuration in this measurement is also appropriate for the assessment of carbonated concrete during carbonation time in low-temperature environments (below 0

^{\circ}

C). In the same carbonation time, the relative nonlinear parameters also increase slightly when the temperature is at −20

^{\circ}

C to 0

^{\circ}

C, but it does not change too much. Furthermore, there is a more significant variation of the nonlinear parameters in the same carbonation time for the specimens with a high water–cement ratio than that with a low one. Full article

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23 pages, 7536 KiB

Open AccessArticle

Three-Dimensional Localization of Buried Polyethylene Pipes Using Acoustic Method

by William Xerri, Gineth Saracco, Alessandra Ribodetti, Laurent Zomero and Philippe Picon

Sensors 2022, 22(23), 9433; https://doi.org/10.3390/s22239433 - 2 Dec 2022

Cited by 2 | Viewed by 1590

Abstract

Localization of buried polyethylene pipes is an important issue for network managers. This study focuses on an acoustic method, which consists of vibrating the pipe and observing the signal with a receiver placed on the ground surface. This method provides an estimate of [...] Read more.

Localization of buried polyethylene pipes is an important issue for network managers. This study focuses on an acoustic method, which consists of vibrating the pipe and observing the signal with a receiver placed on the ground surface. This method provides an estimate of the path of the pipe but gives no information on the depth. We developed a multi-sensor method based on the principle of vibrating the pipe, which allows estimating the depth while being non-invasive and non-destructive and without a priori information on the propagation medium. These sensors are positioned perpendicular to the pipe. We developed a new estimator to estimate the depth and the propagation velocity in the medium, which is an important variable in our problem. This estimator is based on the MUSIC algorithm and is adapted to our choice of modeling. In this paper, two models of travel times in typical situations are presented. The first one represents the case where all sensors can be placed inside the trench (on the ground surface) in which the pipe is buried. The second one represents the case where sensors are placed inside and outside the trench. These travel time models aim to provide a fast result to allow the method to be used by field agents. They are compared with a full wavefield modeling by finite differences. Full article

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15 pages, 3265 KiB

Open AccessArticle

Ship Trajectory Generator under the Interference of Wind, Current and Waves

by Xian Ding, Hongwei Bian, Heng Ma and Rongying Wang

Sensors 2022, 22(23), 9395; https://doi.org/10.3390/s22239395 - 1 Dec 2022

Cited by 3 | Viewed by 2567

Abstract

In view of the low accuracy of the motion parameters generated by the typical ship trajectory generator, and the fact that the problem of wind, current and wave interference is not considered, this paper establishes a new ship trajectory generator by analyzing the [...] Read more.

In view of the low accuracy of the motion parameters generated by the typical ship trajectory generator, and the fact that the problem of wind, current and wave interference is not considered, this paper establishes a new ship trajectory generator by analyzing the changes in the ship’s attitude and speed under different motion states. Through simulation, the accuracy of the main motion parameters is significantly improved compared with the typical trajectory generator; the time-varying non-uniform wind, current and wave fields are constructed, and the interference effect of wind, current and waves on ship motion is analyzed by combining the empirical formulas of force and moment; an adaptive neuro fuzzy inference system (ANFIS) based on wind, current and wave interference is designed, and the fuzzy rules of the fuzzy system are determined by training and testing the measured data; the motion parameters of superimposed wind, current and wave interference are compared with the measured data, and the accuracy is further improved after superimposing wind, current and wave interference. Full article

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15 pages, 5662 KiB

Open AccessArticle

Identification and Classification of Defects in PE Gas Pipelines Based on VGG16

by Yang Wang, Qiankun Fu, Nan Lin, Huiqing Lan, Hao Zhang and Toktonur Ergesh

Appl. Sci. 2022, 12(22), 11697; https://doi.org/10.3390/app122211697 - 17 Nov 2022

Cited by 9 | Viewed by 2731

Abstract

For the problem of classification and identification of defects in polyethylene (PE) gas pipelines, this paper firstly performs preliminary screening of the acquired images and acquisition efficiency of defective image acquisition was improved. Images of defective PE gas pipelines were pre-processed. Then, edge [...] Read more.

For the problem of classification and identification of defects in polyethylene (PE) gas pipelines, this paper firstly performs preliminary screening of the acquired images and acquisition efficiency of defective image acquisition was improved. Images of defective PE gas pipelines were pre-processed. Then, edge detection of the defective images was performed using the improved Sobel algorithm and an adaptive threshold segmentation method was applied to segment the defects in the pipeline images. Finally, the defect images were morphologically processed to obtain binary images. The obtained binary images were applied with VGG16 to complete the training of the defect classifier. The experimental findings show that in the TensorFlow API environment, the test set’s highest accuracy reached 97%, which can achieve the identification of defect types of underground PE gas transmission pipelines. Full article

(This article belongs to the Topic Advances in Non-Destructive Testing Methods)

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17 pages, 8026 KiB

Open AccessArticle

SF₆ High-Voltage Circuit Breaker Contact Status Detection at Different Currents

by Ze Guo, Linjing Li, Weimeng Han and Zixuan Guo

Sensors 2022, 22(21), 8490; https://doi.org/10.3390/s22218490 - 4 Nov 2022

Cited by 5 | Viewed by 3948

Abstract

Currently, the online non-destructive testing (NDT) methods to measure the contact states of high-voltage circuit breakers (HVCBs) with SF₆ gas as a quenching medium are lacking. This paper aims to put forward a novel method to detect the contact state of an [...] Read more.

Currently, the online non-destructive testing (NDT) methods to measure the contact states of high-voltage circuit breakers (HVCBs) with SF₆ gas as a quenching medium are lacking. This paper aims to put forward a novel method to detect the contact state of an HVCB based on the vibrational signal. First, for a 40.5-kV SF₆ HVCB prototype, a mechanical vibration detection system along with a high-current generator to provide the test current is designed. Given this, vibration test experiments are carried out, and the vibration signal data under various currents and corresponding contact states are obtained. Afterward, a feature extraction method based on the frequency is designed. The state of the HVCB contacts is then determined using optimized deep neural networks (DNNs) along with the method of adaptive moment estimation (Adam) on the obtained experimental data. Finally, the hyperparameters for the DNNs are tuned using the Bayesian optimization (BO) technique, and a global HVCB contact state recognition model at various currents is proposed. The obtained results clearly depict that the proposed recognition model can accurately identify five various contact states of HVCBs for the currents between 1000 A and 3500 A, and the recognition accuracy rate is above 96%. The designed experimental and theoretical analysis in our study will provide the references for future monitoring and diagnosis of faults in HVCBs. Full article

(This article belongs to the Topic Advances in Non-Destructive Testing Methods)

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14 pages, 4186 KiB

Open AccessArticle

Development of a Dual-Modality Gamma-ray/Fast Neutron Imaging System for Air Cargo Inspection

by Jae Yeon Park, Jungho Mun, Jae Hyun Lee, Yeong-Heum Yeon, Moonsik Chae, Minwoong Lee and Nam-Ho Lee

Appl. Sci. 2022, 12(19), 9775; https://doi.org/10.3390/app12199775 - 28 Sep 2022

Cited by 9 | Viewed by 2457

Abstract

High-energy radiation sources have provided a strong security inspection capability using a non-invasive imaging system. The use of multiple radiation sources in one imaging system can also lead to a more powerful system that can classify various materials compared to using a single [...] Read more.

High-energy radiation sources have provided a strong security inspection capability using a non-invasive imaging system. The use of multiple radiation sources in one imaging system can also lead to a more powerful system that can classify various materials compared to using a single radiation source. The Advanced Radiation Technology Institute of Korea Atomic Energy Research Institute has developed an air cargo inspection system using multiple radiation sources such as fast neutrons and gamma-rays to classify the plastics, metals, and organics among various sample materials. The fast neutron beam with an energy of 14.1 MeV, generated using the D-T neutron generator, and the gamma-ray beam with an energy of 6 MeV, generated by an electron linear accelerator, are projected onto the vertically aligned scintillator-based radiation detectors. The neutron and gamma-ray images of a cargo container moved by a motorized linear translation stage are acquired, and the image data processing shows good material classification results. In this paper, we describe a multi-radiation imaging system for air cargo inspection and investigate its material classification capability using various sample materials. Full article

(This article belongs to the Topic Advances in Non-Destructive Testing Methods)

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15 pages, 3236 KiB

Open AccessArticle

GisaxStudio—An Open Platform for Analysis and Simulation of GISAXS from 3D Nanoparticle Lattices

by Igor Mekterović, Gabrijela Svalina, Senad Isaković and Maja Mičetić

Appl. Sci. 2022, 12(19), 9773; https://doi.org/10.3390/app12199773 - 28 Sep 2022

Cited by 4 | Viewed by 2393

Abstract

Grazing-incidence small-angle X-ray scattering (GISAXS) is a powerful method for the structural analysis of ordered arrays of nanoparticles, quantum dots, or similar objects. However, for the correct interpretation of the measured GISAXS intensity distributions, a proper data analysis, including a suitable model, is [...] Read more.

Grazing-incidence small-angle X-ray scattering (GISAXS) is a powerful method for the structural analysis of ordered arrays of nanoparticles, quantum dots, or similar objects. However, for the correct interpretation of the measured GISAXS intensity distributions, a proper data analysis, including a suitable model, is required. Here, we demonstrate a software platform, GisaxStudio, aimed at the analysis and simulation of 2D GISAXS intensity distributions from ordered lattices of different nanoparticles. It contains several models that satisfactorily describe the GISAXS from 3D lattices or crystals of nanoparticles prepared by the self-assembly processes, pre-pattering, or ion-beam interaction with the material within their tracks. It also supports different shapes of nanoparticles, including core-shell structure with the center of core possibly displaced from the center of the shell. The software is very useful for fast and accurate GISAXS data analysis. Full article

(This article belongs to the Topic Advances in Non-Destructive Testing Methods)

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15 pages, 5838 KiB

Open AccessArticle

Research on Measurement of Tooth Profile Parameters of Synchronous Belt Based on Point Cloud Data

by Zijian Zhang, Mao Pang and Chuanchao Teng

Sensors 2022, 22(17), 6372; https://doi.org/10.3390/s22176372 - 24 Aug 2022

Cited by 2 | Viewed by 2118

Abstract

Accurately detecting the tooth profile parameters of the synchronous belt is crucial for the transmission’s load distribution and service life. However, the existing detection methods have low efficiency, are greatly affected by the manual experience, and cannot realize automatic detection. A measurement method [...] Read more.

Accurately detecting the tooth profile parameters of the synchronous belt is crucial for the transmission’s load distribution and service life. However, the existing detection methods have low efficiency, are greatly affected by the manual experience, and cannot realize automatic detection. A measurement method based on point cloud data is proposed to solve this issue. The surface space points of the synchronous belt are acquired by a line-structured light sensor, and the raw point clouds are preprocessed to remove outliers and reduce the number of points. Then, the point clouds are divided into plane and arc regions, and different methods are used for fitting. Finally, the parameters of each tooth are calculated. The experimental results show that the method has high measurement accuracy and reliable stability and can replace the original detection method to realize automatic detection. Full article

(This article belongs to the Topic Advances in Non-Destructive Testing Methods)

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9 pages, 4232 KiB

Open AccessArticle

MEMS High Aspect Ratio Trench Three-Dimensional Measurement Using Through-Focus Scanning Optical Microscopy and Deep Learning Method

by Guannan Li, Junkai Shi, Chao Gao, Xingjian Jiang, Shuchun Huo, Chengjun Cui, Xiaomei Chen and Weihu Zhou

Appl. Sci. 2022, 12(17), 8396; https://doi.org/10.3390/app12178396 - 23 Aug 2022

Cited by 4 | Viewed by 2513

Abstract

High-aspect-ratio structures have become increasingly important in MEMS devices. In situ, real-time critical dimension and depth measurement for high-aspect-ratio structures is critical for optimizing the deep etching process. Through-focus scanning optical microscopy (TSOM) is a high-throughput and inexpensive optical measurement method for critical [...] Read more.

High-aspect-ratio structures have become increasingly important in MEMS devices. In situ, real-time critical dimension and depth measurement for high-aspect-ratio structures is critical for optimizing the deep etching process. Through-focus scanning optical microscopy (TSOM) is a high-throughput and inexpensive optical measurement method for critical dimension and depth measurement. Thus far, TSOM has only been used to measure targets with dimension of 1 μm or less, which is far from sufficient for MEMS. Deep learning is a powerful tool that improves the TSOM performance by taking advantage of additional intensity information. In this work, we propose a convolutional neural network model-based TSOM method for measuring individual high-aspect-ratio trenches on silicon with width up to 30 μm and depth up to 440 μm. Experimental demonstrations are conducted and the results show that the proposed method is suitable for measuring the width and depth of high-aspect-ratio trenches with a standard deviation and error of approximately a hundred nanometers or less. The proposed method can be applied to the semiconductor field. Full article

(This article belongs to the Topic Advances in Non-Destructive Testing Methods)

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18 pages, 6130 KiB

Open AccessArticle

A Comparative Study of Parameter Identification Methods for Asymmetric Nonlinear Systems with Quadratic and Cubic Stiffness

by Shibo Wang and Bin Tang

Sensors 2022, 22(15), 5854; https://doi.org/10.3390/s22155854 - 5 Aug 2022

Cited by 4 | Viewed by 2556

Abstract

Understanding the nonlinear dynamic characteristics of engineering structures is challenging, especially for the systems that exhibit asymmetric nonlinear behavior. This paper compared four parameter identification methods for asymmetric nonlinear systems incorporating quadratic and cubic stiffness nonlinearities. Hilbert transform, zero-crossing, direct quadrature, and wavelet [...] Read more.

Understanding the nonlinear dynamic characteristics of engineering structures is challenging, especially for the systems that exhibit asymmetric nonlinear behavior. This paper compared four parameter identification methods for asymmetric nonlinear systems incorporating quadratic and cubic stiffness nonlinearities. Hilbert transform, zero-crossing, direct quadrature, and wavelet transform were used to obtain the backbone, envelope, and restoring force curves from the free vibration time history. A nonlinear curve-fitting method was then applied to estimate the stiffness parameters of the asymmetric systems, and a linear least square fitting approach was utilized to estimate the damping parameters of the asymmetric systems. We used the Helmholtz–Duffing oscillator as a numerical example and a nonlinear vibration absorber with geometric imperfections to verify the feasibility and accuracy of these methods. The advantages and disadvantages of these methods and the deviations in estimated results are discussed. Full article

(This article belongs to the Topic Advances in Non-Destructive Testing Methods)

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14 pages, 5815 KiB

Open AccessArticle

The Restored Premolars Biomechanical Behavior: FEM and Experimental Moiré Analyses

by Jose Luis Valin Rivera, Edison Gonçalves, Paulo Vinicius Soares, Giovana Milito, Jorge Octavio Ricardo Perez, Guillermo Francisco Palacios Roque, Meylí Valin Fernández, Henry Figueredo Losada, Fabrícia Araújo Pereira, Gilberto Garcia del Pino and Alexander Rodriguez Soto

Appl. Sci. 2022, 12(13), 6768; https://doi.org/10.3390/app12136768 - 4 Jul 2022

Cited by 3 | Viewed by 2031

Abstract

This study applied the finite element method (FEM) and the moiré strip projection method to evaluate the biomechanical behavior of healthy and endodontic-treated premolar teeth. The finite element method and the moiré strip projection method were applied to evaluate the influence of restored [...] Read more.

This study applied the finite element method (FEM) and the moiré strip projection method to evaluate the biomechanical behavior of healthy and endodontic-treated premolar teeth. The finite element method and the moiré strip projection method were applied to evaluate the influence of restored materials in association with cervical lesions and were considered as strain estimates for a tooth sample with 21 units, under loads of 25, 50, 75, and 100 N, frontal and oblique applied. The focused cases were: tooth H healthy; tooth A-MOD amalgam; tooth AL-MOD amalgam + lesion; tooth ALR-MOD amalgam + injury restored; tooth R-MOD resin; tooth RL-MOD resin + lesion; tooth RLR-MOD resin + injury restored. The results obtained by FEM simulation can be considered perfectly validated by the results presented by the experimental moiré projection analysis, demonstrating that the FEM numerical analysis can be used to evaluate the biomechanical behavior of healthy and endodontically treated teeth. Developing an alternative protocol to generate FEM three-dimensional models will lead to a ready and inexpensive tool since there is no need for costly equipment for tooth extraction prognosis. Full article

(This article belongs to the Topic Advances in Non-Destructive Testing Methods)

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21 pages, 5787 KiB

Open AccessArticle

Mesoscale Study on Splitting Tensile Damage Characteristics of Concrete Based on X-ray Computed Tomography and Digital Image Correlation Technology

by Hua Zhang, Qi Pan, Kai Zheng, Chuanjun Jin and Luoyu Pan

Materials 2022, 15(13), 4416; https://doi.org/10.3390/ma15134416 - 22 Jun 2022

Cited by 7 | Viewed by 2128

Abstract

In this paper, the mesoscale damage properties of concrete and mortar were studied experimentally under Brazilian disc splitting tensile tests combining X-ray computed tomography (CT) and digital image correlation (DIC) technology. Considering the factors of water/cement ratios and loading rates, the influence of [...] Read more.

In this paper, the mesoscale damage properties of concrete and mortar were studied experimentally under Brazilian disc splitting tensile tests combining X-ray computed tomography (CT) and digital image correlation (DIC) technology. Considering the factors of water/cement ratios and loading rates, the influence of meso components on the macro tensile properties and failure modes of concrete were studied. The experimental results and analysis indicate that the following: (1) the existence of coarse aggregate makes the tensile strength of concrete lower than that of mortar and reduces the sensitivity of tensile strength to the loading rates; (2) the failure modes of mortar and concrete Brazilian discs differ in the crack initiation positions and localization phenomena. Under high loading rates, the local failure plays a critical role in the strength improvement of concrete; (3) for concrete, interface failure and mortar failure are the main failure modes under low loading rates, whereas aggregate failure gradually becomes the main failure mode with increasing loading rates. The decrease in water/cement ratios improves the strength of the mortar matrix and interfacial bonding performance, leading to more serious aggregate damage and higher strength. Full article

(This article belongs to the Topic Advances in Non-Destructive Testing Methods)

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17 pages, 5405 KiB

Open AccessArticle

Damage Detection Using Ultrasonic Techniques in Concrete-Filled Steel Tubes (CFSTs) Columns

by Antonio Callejas, Roberto Palma, David Hernández-Figueirido and Guillermo Rus

Sensors 2022, 22(12), 4400; https://doi.org/10.3390/s22124400 - 10 Jun 2022

Cited by 11 | Viewed by 2751

Abstract

Concrete-filled steel tubes (CFSTs) are structural elements that, as a consequence of an incorrect elaboration, can exhibit internal defects that cannot be visualized, being usually air voids. In this work, the detection of internal damage in CFST samples elaborated with a percentage of [...] Read more.

Concrete-filled steel tubes (CFSTs) are structural elements that, as a consequence of an incorrect elaboration, can exhibit internal defects that cannot be visualized, being usually air voids. In this work, the detection of internal damage in CFST samples elaborated with a percentage of contained air voids in concrete, was carried out by performing a complete ultrasound scan using an immersion tank. The analysis of the ultrasound signals shows the differences presented in the amplitude of the fundamental frequency of the signal, and in the Broadband Ultrasound Attenuation (BUA), in comparison with a sample without defects. The main contribution of this study is the application of the BUA technique in CFST samples for the location of air voids. The results present a linear relationship between BUA averages over the window of the CFSTs and the percentage of air voids contained (Pearson’s correlation coefficient r = 0.9873), the higher percentage of air voids, the higher values of BUA. The BUA algorithm could be applied effectively to distinguish areas with defects inside the CFSTs. Similar to the BUA results, the analysis in the frequency domain using the FFT and the STFT was sensitive in the detection of internal damage (Pearson’s correlation coefficient r = −0.9799, and r = −0.9672, respectively). The results establish an improvement in the evaluation of CFST elements for the detection of internal defects. Full article

(This article belongs to the Topic Advances in Non-Destructive Testing Methods)

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14 pages, 7162 KiB

Open AccessArticle

Utilizing Piezo Acoustic Sensors for the Identification of Surface Roughness and Textures

by Kayra Kurşun, Fatih Güven and Hakan Ersoy

Sensors 2022, 22(12), 4381; https://doi.org/10.3390/s22124381 - 9 Jun 2022

Cited by 5 | Viewed by 2552

Abstract

This study examines surface roughness measurements via piezo acoustic disks and appropriate signal processing. Surface roughness is one characteristic of surface texture that can have various irregularities inherent to manufacturing methods. The surface roughness parameters and corresponding surface profiles are acquired by a [...] Read more.

This study examines surface roughness measurements via piezo acoustic disks and appropriate signal processing. Surface roughness is one characteristic of surface texture that can have various irregularities inherent to manufacturing methods. The surface roughness parameters and corresponding surface profiles are acquired by a stylus profilometer. Simultaneously, elastic waves propagated along metal surfaces caused by the friction of a diamond tip are obtained in the form of raw sound via piezo acoustic disks. Frequency spectrum analysis showed apparent correlations between the traditionally obtained measurement parameters and the piezo acoustic measurement data. Thus, it is concluded that acoustic friction measurement shows promising results as a novel measurement method for the surface roughness states of certain materials. Full article

(This article belongs to the Topic Advances in Non-Destructive Testing Methods)

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13 pages, 1714 KiB

Open AccessTechnical Note

Application of the Differential Evolutionary Algorithm to the Estimation of Pipe Embedding Parameters

by Ping Lu, Shuang Chen, Xiaozhen Sheng and Yan Gao

Sensors 2022, 22(10), 3942; https://doi.org/10.3390/s22103942 - 23 May 2022

Cited by 3 | Viewed by 1648

Abstract

The time-delay estimation (TDE) method is the primary method for predicting leakage locations in buried water distribution pipelines. The accuracy of TDE depends on the acoustic speed and attenuation of the leakage signal propagating along the pipeline. The analytical prediction model is the [...] Read more.

The time-delay estimation (TDE) method is the primary method for predicting leakage locations in buried water distribution pipelines. The accuracy of TDE depends on the acoustic speed and attenuation of the leakage signal propagating along the pipeline. The analytical prediction model is the typical approach for obtaining the propagation speed and attenuation of leakage waves. However, the embedding parameters of the buried pipe in this model must be measured using soil tests, which are very difficult, costly, and time-consuming. These factors restrict the application of the TDE method in pinpointing pipeline leakage. A method for inverse identification of pipe embedding parameters using discrete wavenumbers obtained in field testing is presented in this paper, and the differential evolution algorithm is introduced as an optimization solution. A field experiment is conducted to validate the method, and the test wavenumbers are measured in a cast-iron pipeline. The estimated sensitive parameters in the analytical model using the method are soil elastic modulus, Poisson’s ratio, and pipe–soil contact coefficient, while the conventional soil test is used to measure the soil density due to the character of the optimization algorithm and the soil properties. The application effects show that the estimated parameters are close to those measured from a conventional soil test. The wave speed based on the estimated parameters was an excellent match for the on-site test in the engineering application. This work provides a less costly and more straightforward way to apply the TDE method for leak localization in buried pipelines. Full article

(This article belongs to the Topic Advances in Non-Destructive Testing Methods)

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