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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".

Deadline for manuscript submissions: closed (30 May 2020) | Viewed by 46108

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Prof. Dr. Bo Han

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Guest Editor

School of Civil Engineering, Shandong University, Jinan 250061, China
Interests: offshore “fluid - wind turbine - seabed” integrated analysis; offsore geotechnical engineering; intelligent health diagnosis
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Seunghee Park

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Guest Editor

School of Civil, Architectural, and Environmental Engineering, Sungkyunkwan University, 2066, Seoburo, Jangangu, Suwon, Gyeonggido 16419, Republic of Korea
Interests: structural health monitoring; non-destructive evaluation; smart sensors; smart structures; damage detection
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Non-destructive evaluation (NDE) is an engineering approach for examining the properties of a structure or system, without causing damage. Non-destructive evaluation techniques, such as optical, electromagnetics, ultrasonic, radiography, and thermal methods have contributed to ground-breaking improvements in safety in many industrial areas.
In order to develop successful NDE technology, various integrated technologies, such as advanced sensors, data measurement technology, signal processing method, and statistical decision making algorithms have been studied in combination, in order to evaluate the condition of the structures and machinery.
Meanwhile, over the last decades, there has been a growing number of new NDE solutions that provide artificial intelligence (AI) and machine learning (ML) based techniques for automated decision making. In addition, Internet of things (IoT) technologies are also undergoing great expansion and development, and the convergence of both AI and IoT are now realities that are going to change the paradigm of NDE technology.
We invite you to submit original research papers or technical or review articles to this Special Collection, with emphasis on novel and emerging technologies for a wide range of non-destructive evaluation techniques, including AI and ML combined techniques.

Potential topics include, but are not limited to, the following:

non-destructive evaluation
real-time monitoring
structural health monitoring

Data mining methods, algorithms, and applications
Data analysis for non-destructive evaluation
Advanced signal processing, data mining, and data fusion
Pattern recognition applications
Artificial intelligence and machine learning application for NDE
Computer vision-based NDE
Industry 4.0, sensors, and AI

Prof. Dr. Seunghee Park
Prof. Dr. Bo Han
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

non-destructive evaluation;
structural health monitoring;
artificial intelligence;
machine learning;
Internet of things;
intelligent health diagnosis

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Published Papers (13 papers)

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Research

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21 pages, 4134 KiB

Open AccessArticle

Mechanical Properties and Fracture Behavior of Crumb Rubber Basalt Fiber Concrete Based on Acoustic Emission Technology

by Hanbing Liu, Wenjun Li, Guobao Luo, Shiqi Liu and Xiang Lyu

Sensors 2020, 20(12), 3513; https://doi.org/10.3390/s20123513 - 21 Jun 2020

Cited by 8 | Viewed by 2553

Abstract

Basalt fiber and crumb rubber, as excellent road material modifiers, have great advantages in improving the mechanical properties and fracture behavior of concrete. Acoustic emission (AE) is a nondestructive testing and real-time monitoring technique used to characterize the fracture behavior of concrete specimens. The object of this paper is to investigate the effects of crumb rubber replacement rate, basalt fiber content and water–binder ratio on the mechanical properties and fracture behavior of crumb rubber basalt fiber concrete (CRBFC) based on orthogonal test. The fracture behavior of a CRBFC specimen under three-point flexural conditions was monitored by AE technology and the relative cumulative hit (RCH) was defined to characterize the internal damage degree of CRBFC. The experimental results showed that, considering the mechanical strength and fracture damage behavior of CRBFC, the optimal crumb rubber replacement rate, basalt fiber content and water–binder ratio are 10%, 2 kg/m³ and 0.46, respectively. In addition, it was found that AE parameters can effectively characterize the fracture behavior of CRBFC. The fracture stages of CRBFC can be divided according to the cumulative AE hits and counts. AE amplitude value can be used as an early warning of CRBFC specimen fracture. Moreover, the fracture mode can be identified by RA and average frequency (AF) values variation during the loading process. Full article

(This article belongs to the Special Issue Sensors for Nondestructive Testing and Evaluation)

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23 pages, 9613 KiB

Open AccessArticle

Structural Operativity Evaluation of Strategic Buildings through Finite Element (FE) Models Validated by Operational Modal Analysis (OMA)

by Dora Foti, Nicola Ivan Giannoccaro, Vitantonio Vacca and Michela Lerna

Sensors 2020, 20(11), 3252; https://doi.org/10.3390/s20113252 - 7 Jun 2020

Cited by 17 | Viewed by 3475

Abstract

In this paper, a non-destructive technique based on the monitoring of the environmental vibrations of two strategic buildings by positioning accelerometers in well-defined points was used for fixing their dynamic behavior. The accelerometers measurements were elaborated through Operational Modal Analysis (OMA) techniques, in order to identify natural frequencies, damping coefficients, and modal shapes of the structure. Once these parameters have been determined, a numerical model calibrated on the identified frequencies and verified on the corresponding mode shapes was created for each building. The structural operational efficiency index of the buildings was determined by using the Seismic Model Ambient Vibration (SMAV) methodology, which allows us to evaluate their seismic vulnerability. The results obtained from the experimental analysis (on three different tests for each analyzed building) concern the frequencies and the modal shapes of the structure. They have been compared to the results of the finite element model, with a very small error, indicating a good quality of the analysis and also the possibility of using directly well-tuned models for verifying the structural operating indices. Full article

(This article belongs to the Special Issue Sensors for Nondestructive Testing and Evaluation)

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17 pages, 8837 KiB

Open AccessArticle

A New Approach to Explore the Surface Profile of Clay Soil Using White Light Interferometry

by Suchun Yang, Junwei Liu, Longfei Xu, Mingyi Zhang and Dong-Sheng Jeng

Sensors 2020, 20(11), 3009; https://doi.org/10.3390/s20113009 - 26 May 2020

Cited by 11 | Viewed by 3007

Abstract

In order to have a better understanding of the real contact area of granular materials, the white light interference method is applied to explore the real surface morphology of clay soils under high stress. Analysis of the surface profile indicates that there exists a support point height z₀ with the highest distribution frequency. A concept of a real contact region (from z₀ to z₀ + d₉₀; d₉₀ represents the particle size corresponding to 90% of the volume fraction) is proposed by combining a surface profile with the particle size distribution of clay soil. It was found that under the compressive stress of 106 MPa–529 MPa, the actual contact area ratio of clay soil varies between 0.375 and 0.431. This demonstrates an increasing trend with the rise of stress. On the contrary, the apparent porosity decreases with an increasing stress, varying between 0.554 and 0.525. In addition, as the compressive stress increases, the cumulative frequency of apparent profile height (from z₀ − d₉₀ to z₀ + d₉₀) has a concentrated tendency with a limited value of 0.9. Full article

(This article belongs to the Special Issue Sensors for Nondestructive Testing and Evaluation)

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13 pages, 3992 KiB

Open AccessArticle

Field Test of Excess Pore Water Pressure at Pile–Soil Interface Caused by PHC Pipe Pile Penetration Based on Silicon Piezoresistive Sensor

by Yonghong Wang, Xueying Liu, Mingyi Zhang, Suchun Yang and Songkui Sang

Sensors 2020, 20(10), 2829; https://doi.org/10.3390/s20102829 - 16 May 2020

Cited by 9 | Viewed by 2856

Abstract

Prestressed high-strength concrete (PHC) pipe pile with the static press-in method has been widely used in recent years. The generation and dissipation of excess pore water pressure at the pile–soil interface during pile jacking have an important influence on the pile’s mechanical characteristics and bearing capacity. In addition, this can cause uncontrolled concrete damage. Monitoring the change in excess pore water pressure at the pile–soil interface during pile jacking is a plan that many researchers hope to implement. In this paper, field tests of two full-footjacked piles were carried out in a viscous soil foundation, the laws of generation and dissipation of excess pore water pressure at the pile–soil interface during pile jacking were monitored in real time, and the laws of variation in excess pore water pressure at the pile–soil interface with the burial depth and time were analyzed. As can be seen from the test results, the excess pore water pressure at the pile–soil interface increased to the peak and then began to decline, but the excess pore water pressure after the decline was still relatively large. Test pile S1 decreased from 201.4 to 86.3 kPa, while test pile S2 decreased from 374.1 to 114.3 kPa after pile jacking. The excess pore water pressure at the pile–soil interface rose first at the initial stage of consolidation and dissipated only after the hydraulic gradient between the pile–soil interface and the soil surrounding the pile disappeared. The dissipation degree of excess pore water pressure reached about 75–85%. The excess pore water pressure at the pile–soil interface increased with the increase in buried depth and finally tended to stabilize. Full article

(This article belongs to the Special Issue Sensors for Nondestructive Testing and Evaluation)

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21 pages, 45267 KiB

Open AccessArticle

Beam Deflection Monitoring Based on a Genetic Algorithm Using Lidar Data

by Michael Bekele Maru, Donghwan Lee, Gichun Cha and Seunghee Park

Sensors 2020, 20(7), 2144; https://doi.org/10.3390/s20072144 - 10 Apr 2020

Cited by 18 | Viewed by 5692

Abstract

The Light Detection And Ranging (LiDAR) system has become a prominent tool in structural health monitoring. Among such systems, Terrestrial Laser Scanning (TLS) is a potential technology for the acquisition of three-dimensional (3D) information to assess structural health conditions. This paper enhances the application of TLS to damage detection and shape change analysis for structural element specimens. Specifically, estimating the deflection of a structural element with the aid of a Lidar system is introduced in this study. The proposed approach was validated by an indoor experiment by inducing artificial deflection on a simply supported beam. A robust genetic algorithm method is utilized to enhance the accuracy level of measuring deflection using lidar data. The proposed research primarily covers robust optimization of a genetic algorithm control parameter using the Taguchi experiment design. Once the acquired data is defined in terms of plane, which has minimum error, using a genetic algorithm and the deflection of the specimen can be extracted from the shape change analysis. Full article

(This article belongs to the Special Issue Sensors for Nondestructive Testing and Evaluation)

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13 pages, 8881 KiB

Open AccessArticle

Test and Study of Pipe Pile Penetration in Cohesive Soil Using FBG Sensing Technology

by Yonghong Wang, Xueying Liu, Mingyi Zhang, Songkui Sang and Xiaoyu Bai

Sensors 2020, 20(7), 1934; https://doi.org/10.3390/s20071934 - 30 Mar 2020

Cited by 6 | Viewed by 3152

Abstract

In order to examine the applicability of Fiber Bragg Grating (FBG) sensing technology in the static penetration of pipe piles, static penetration tests in clay were conducted using double-wall open and closed model pipe piles. The strain was measured using FBG sensors, and the plug height was measured using a cable displacement sensor. Using one open pile and two closed piles, the difference in pipe pile penetration was compared and analyzed. Based on FBG sensing technology and the strain data, the penetration characteristics of the pipe pile, such as axial force, lateral friction, and driving resistance were examined. Results showed that FBG sensing technology has superior testing performance for the pipe pile penetration process, can accurately reflect the strain time history of pipe piles, and can clearly reflect the penetration process of pipe piles with increasing penetration depth. In addition, the variation law of the characteristics of the jacked pile pile–soil interface was obtained. This test has significance for model tests and the engineering design of pipe piles. Full article

(This article belongs to the Special Issue Sensors for Nondestructive Testing and Evaluation)

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13 pages, 4466 KiB

Open AccessArticle

A One-Stage Approach for Surface Anomaly Detection with Background Suppression Strategies

by Gaokai Liu, Ning Yang, Lei Guo, Shiping Guo and Zhi Chen

Sensors 2020, 20(7), 1829; https://doi.org/10.3390/s20071829 - 25 Mar 2020

Cited by 17 | Viewed by 3376

Abstract

We explore a one-stage method for surface anomaly detection in industrial scenarios. On one side, encoder-decoder segmentation network is constructed to capture small targets as much as possible, and then dual background suppression mechanisms are designed to reduce noise patterns in coarse and fine manners. On the other hand, a classification module without learning parameters is built to reduce information loss in small targets due to the inexistence of successive down-sampling processes. Experimental results demonstrate that our one-stage detector achieves state-of-the-art performance in terms of precision, recall and f-score. Full article

(This article belongs to the Special Issue Sensors for Nondestructive Testing and Evaluation)

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14 pages, 3472 KiB

Open AccessArticle

A Model Test for the Influence of Lateral Pressure on Vertical Bearing Characteristics in Pile Jacking Process Based on Optical Sensors

by Yonghong Wang, Xueying Liu, Songkui Sang, Mingyi Zhang and Peng Wang

Sensors 2020, 20(6), 1733; https://doi.org/10.3390/s20061733 - 20 Mar 2020

Cited by 5 | Viewed by 2914

Abstract

Photoelectric integrated testing technology was used to study precast piles during pile jacking at the pile–soil interface considering the influence of the earth and pore water pressures on its vertical bearing performance. The low temperature sensitive fiber Bragg grating (FBG) strain sensors and miniature silicon piezoresistive sensors were implanted in the model pile to test the changes of earth pressure, pore water pressure and pile axial force of the jacked pile at the pile–soil interface, and the influence of lateral pressure on pile axial force was studied. The test results showed that the nylon rod is feasible as a model pile. The FBG strain sensor had a stable performance and monitored changes in the axial force of the model pile in real time. The miniature earth and pore water pressure sensors were small enough to avoid size effects and accurately measured changes in the earth and pore water pressures during the pile jacking process. During pile jacking, the lateral earth pressure increased gradually in depth, and the lateral earth pressure at the same depth tended to decrease at greater depths. Lateral pressures caused the axial force of the pile to increases by a factor of 1–2, where the maximum was 2.7. Therefore, the influence of the lateral pressure must be considered when studying the residual pile stress. Full article

(This article belongs to the Special Issue Sensors for Nondestructive Testing and Evaluation)

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16 pages, 5866 KiB

Open AccessArticle

A Rapid and Nondestructive Approach for the Classification of Different-Age Citri Reticulatae Pericarpium Using Portable Near Infrared Spectroscopy

by Pao Li, Xinxin Zhang, Shangke Li, Guorong Du, Liwen Jiang, Xia Liu, Shenghua Ding and Yang Shan

Sensors 2020, 20(6), 1586; https://doi.org/10.3390/s20061586 - 12 Mar 2020

Cited by 27 | Viewed by 3590

Abstract

Citri Reticulatae Pericarpium (CRP), has been used in China for hundreds of years as a functional food and medicine. However, some short-age CRPs are disguised as long-age CRPs by unscrupulous businessmen in order to obtain higher profits. In this paper, a rapid and nondestructive method for the classification of different-age CRPs was established using portable near infrared spectroscopy (NIRS) in diffuse reflectance mode combination with appropriate chemometric methods. The spectra of outer skin and inner capsule of CRPs at different storage ages were obtained directly without destroying the samples. Principal component analysis (PCA) with single and combined spectral pretreatment methods was used for the classification of different-age CRPs. Furthermore, the data were pretreated with the PCA method, and Fisher linear discriminant analysis (FLD) with optimized pretreatment methods was discussed for improving the accuracy of classification. Data pretreatment methods can be used to eliminate the noise and background interference. The classification accuracy of inner capsule is better than that of outer skin data. Furthermore, the best results with 100% prediction accuracy can be obtained with FLD method, even without pretreatment. Full article

(This article belongs to the Special Issue Sensors for Nondestructive Testing and Evaluation)

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19 pages, 1055 KiB

Open AccessArticle

Genetic Improvement of Sawn-Board Stiffness and Strength in Scots Pine (Pinus sylvestris L.)

by Irena Fundova, Henrik R. Hallingbäck, Gunnar Jansson and Harry X. Wu

Sensors 2020, 20(4), 1129; https://doi.org/10.3390/s20041129 - 19 Feb 2020

Cited by 5 | Viewed by 3017

Abstract

Given an overall aim of improving Scots pine structural wood quality by selective tree breeding, we investigated the potential of non-destructive acoustic sensing tools to accurately predict wood stiffness (modulus of elasticity, MOE) and strength (modulus of rupture, MOR) of sawn boards. Non-destructive measurements of wood density (DEN), acoustic velocity (VEL) and MOE were carried out at different stages of wood processing chain (standing trees, felled logs and sawn boards), whilst destructively measured stiffness and strength served as benchmark traits. All acoustic based MOE and VEL estimates proved to be good proxies (r_A > 0.65) for sawn-board stiffness while MOE_TREE, VEL_HIT and resistograph wood density (DEN_RES) measured on standing trees and MOE_LOG and VEL_FAK measured on felled logs well reflected board strength. Individual-tree narrow-sense heritability (

h_{i}^{2}

) for VEL, MOE and MOR were weak (0.05–0.26) but were substantially stronger for wood density (0.34–0.40). Moreover, additive genetic coefficients of variation for MOE and MOR were in the range from 5.4% to 9.1%, offering potential targets for exploitation by selective breeding. Consequently, selective breeding based on MOE_TREE, DEN_RES or stem straightness (STR) could improve several structural wood traits simultaneously. Full article

(This article belongs to the Special Issue Sensors for Nondestructive Testing and Evaluation)

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12 pages, 1687 KiB

Open AccessArticle

A Novel Method of Human Joint Prediction in an Occlusion Scene by Using Low-Cost Motion Capture Technique

by Jianwei Niu, Xiai Wang, Dan Wang and Linghua Ran

Sensors 2020, 20(4), 1119; https://doi.org/10.3390/s20041119 - 18 Feb 2020

Cited by 17 | Viewed by 4023

Abstract

Microsoft Kinect, a low-cost motion capture device, has huge potential in applications that require machine vision, such as human-robot interactions, home-based rehabilitation and clinical assessments. The Kinect sensor can track 25 key three-dimensional (3D) “skeleton” joints on the human body at 30 frames per second, and the skeleton data often have acceptable accuracy. However, the skeleton data obtained from the sensor sometimes exhibit a high level of jitter due to noise and estimation error. This jitter is worse when there is occlusion or a subject moves slightly out of the field of view of the sensor for a short period of time. Therefore, this paper proposed a novel approach to simultaneously handle the noise and error in the skeleton data derived from Kinect. Initially, we adopted classification processing to divide the skeleton data into noise data and erroneous data. Furthermore, we used a Kalman filter to smooth the noise data and correct erroneous data. We performed an occlusion experiment to prove the effectiveness of our algorithm. The proposed method outperforms existing techniques, such as the moving mean filter and traditional Kalman filter. The experimental results show an improvement of accuracy of at least 58.7%, 47.5% and 22.5% compared to the original Kinect data, moving mean filter and traditional Kalman filter, respectively. Our method provides a new perspective for Kinect data processing and a solid data foundation for subsequent research that utilizes Kinect. Full article

(This article belongs to the Special Issue Sensors for Nondestructive Testing and Evaluation)

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14 pages, 5184 KiB

Open AccessArticle

Characteristics Regarding Lift-Off Intersection of Pulse-Modulation Eddy Current Signals for Evaluation of Hidden Thickness Loss in Cladded Conductors

by Yong Li, Yi Wang, Zhengshuai Liu, Ilham Mukriz Zainal Abidin and Zhenmao Chen

Sensors 2019, 19(19), 4102; https://doi.org/10.3390/s19194102 - 23 Sep 2019

Cited by 5 | Viewed by 2743

Abstract

The cladded conductor is broadly utilized in engineering fields, such as aerospace, energy, and petrochemical; however, it is vulnerable to thickness loss occurring in the clad layer and nonconductive protection coating due to abrasive and corrosive environments. Such a flaw severely undermines the integrity and safety of the mechanical structures. Therefore, evaluating the thickness loss hidden inside cladded conductors via reliable nondestructive evaluation techniques is imperative. This paper intensively investigates the pulse-modulation eddy current technique (PMEC) for the assessment of thickness loss in a cladded conductor. An analytical model of the ferrite-cored probe is established for analyzing PMEC signals and characteristics of lift-off intersection (LOI) in testing signals. Experiments are conducted for evaluation of the thickness loss in cladded conductors. An inverse scheme based on LOI for estimation of the thickness-loss depth is proposed and further verified. Through simulations and experiments, it is found that the influences of the thickness loss in the clad layer and protective coating on the PMEC signals can be decoupled in virtue of the LOI characteristics. Based on LOI, the hidden thickness loss can be efficiently evaluated without much of a reduction in accuracy by using the PMEC probe for dedicated inspection of the cladded conductor. Full article

(This article belongs to the Special Issue Sensors for Nondestructive Testing and Evaluation)

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Review

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18 pages, 5432 KiB

Open AccessReview

Application and Algorithm of Ground-Penetrating Radar for Plant Root Detection: A Review

by Hao Liang, Linyin Xing and Jianhui Lin

Sensors 2020, 20(10), 2836; https://doi.org/10.3390/s20102836 - 16 May 2020

Cited by 11 | Viewed by 4944

Abstract

Attention to the natural environment is equivalent to observing the space in which we live. Plant roots, which are important organs of plants, require our close attention. The method of detecting root system without damaging plants has gradually become mainstream. At the same time, machine learning has been achieving good results in recent years; it has helped develop many tools to help us detect the underground environment of plants. Therefore, this article will introduce some existing content related to root detection technology and machine detection algorithms for root detection, proving that machine learning root detection technology has good recognition capabilities. Full article

(This article belongs to the Special Issue Sensors for Nondestructive Testing and Evaluation)

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