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Nondestructive Technologies for Complex Engineering Structure Health Monitoring and State...
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Nondestructive Technologies for Complex Engineering Structure Health Monitoring and State Prediction

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

Deadline for manuscript submissions: closed (20 January 2024) | Viewed by 3896

Special Issue Editors

Dr. Nan Li

E-Mail Website
Guest Editor
School of Automation, Northwestern Polytechnical University, Xi’an 710129, China
Interests: nondestructive testing and evaluation; sensor design and optimization
Prof. Dr. Yunze He

E-Mail Website
Guest Editor
College of Electrical and Information Engineering, Hunan University, Changsha 410082, China
Interests: intelligent sensing; NDT
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Qi Wang

E-Mail Website
Guest Editor
School of Electrics & Information Engineering, Tiangong University, Tianjin 300387, China
Interests: intelligent information processing and process tomography
Dr. Yujue Wang

E-Mail Website
Guest Editor
Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China
Interests: electromagnetic nondestructive evaluation

Special Issue Information

Dear Colleagues,

The health status and state prediction of key engineering structures, which generally have complex geometries, are vital to the safety of important equipment. The ongoing development of nondestructive sensing technologies (including magnetic sensors, optical sensors, and vibrational sensors) and state prediction technologies (such as AI algorithms) help realize the monitoring and evaluation of health structures. With the emergence of new materials (e.g., composite and flexible materials), new manufacturing technologies (e.g., additive manufacturing), and new applications (e.g., deformable structures and multi-scale structures), the research of related technologies has become a hot spot.

This Special Issue seeks to gather the latest developments in nondestructive health monitoring technologies and new processing methods for the state prediction of the complex engineering structure. This Special Issue will cover, but not be limited to, the following areas:

  • Quality evaluation of ferromagnetic material additive manufacturing;
  • Quality and health evaluation of ferromagnetic alloyed weld;
  • AI algorithms in structural health monitoring and state prediction;
  • Digital twin technologies;
  • Advanced system design and signal processing;
  • Robot carried automated NDT system;
  • Structural health monitoring of carbon fiber reinforced polymer (CFRP);
  • Visualization and interpretation of structural health monitoring data.

Dr. Nan Li
Prof. Dr. Yunze He
Prof. Dr. Qi Wang
Dr. Yujue Wang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

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.

Published Papers (3 papers)

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Research

17 pages, 4745 KiB  
Article
Multi-Parameter Optimization of Rubidium Laser Optically Pumped Magnetometers with Geomagnetic Field Intensity
by Kun Xu, Xiuyan Ren, Yujie Xiang, Mingxu Zhang, Xiang Zhao, Kexin Ma, Yaqi Tian, Dan Wu, Ziqiang Zeng and Guobao Wang
Sensors 2023, 23(21), 8919; https://doi.org/10.3390/s23218919 - 02 Nov 2023
Viewed by 804
Abstract
Rubidium laser optically pumped magnetometers (OPMs) are widely used magnetic sensors based on the Zeeman effect, laser pumping, and magnetic resonance principles. They measure the magnetic field by measuring the magnetic resonance signal passing through a rubidium atomic gas cell. The quality of [...] Read more.
Rubidium laser optically pumped magnetometers (OPMs) are widely used magnetic sensors based on the Zeeman effect, laser pumping, and magnetic resonance principles. They measure the magnetic field by measuring the magnetic resonance signal passing through a rubidium atomic gas cell. The quality of the magnetic resonance signal is a necessary condition for a magnetometer to achieve high sensitivity. In this research, to obtain the best magnetic resonance signal of rubidium laser OPMs in the Earth’s magnetic field intensity, the experiment system of rubidium laser OPMs is built with a rubidium atomic gas cell as the core component. The linewidth and amplitude ratio (LAR) of magnetic resonance signals is utilized as the optimization objective function. The magnetic resonance signals of the magnetometer experiment system are experimentally measured for different laser frequencies, radio frequency (RF) intensities, laser powers, and atomic gas cell temperatures in a background magnetic field of 50,765 nT. The experimental results indicate that optimizing these parameters can reduce the LAR by one order of magnitude. This shows that the optimal parameter combination can effectively improve the sensitivity of the magnetometer. The sensitivity defined using the noise spectral density measured under optimal experimental parameters is 1.5 pT/Hz1/2@1 Hz. This work will provide key technical support for rubidium laser OPMs’ product development. Full article
(This article belongs to the Special Issue Nondestructive Technologies for Complex Engineering Structure Health Monitoring and State Prediction)
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16 pages, 2062 KiB  
Article
A Joint Acoustic Emission Source Localization Method for Composite Materials
by Xiaoran Wang, Fang Yin and Zhishuai Wan
Sensors 2023, 23(12), 5473; https://doi.org/10.3390/s23125473 - 09 Jun 2023
Cited by 1 | Viewed by 861
Abstract
Damage localization methods for composite materials are a popular research topic at present. The time-difference-blind localization method and beamforming localization method are often individually utilized in the localization of the acoustic emission sources of composite materials. Based on the performances of the two [...] Read more.
Damage localization methods for composite materials are a popular research topic at present. The time-difference-blind localization method and beamforming localization method are often individually utilized in the localization of the acoustic emission sources of composite materials. Based on the performances of the two methods, a joint localization method for the acoustic emission sources of composite materials is proposed in this paper. Firstly, the performance of the time-difference-blind localization method and the beamforming localization method were analyzed. Then, with the advantages and disadvantages of these two methods in mind, a joint localization method was proposed. Finally, the performance of the joint localization method was verified using simulations and experiments. The results show that the joint localization method can reduce the localization time by half compared with the beamforming localization method. At the same time, compared with the time-difference-blind localization method, the localization accuracy can be improved. Full article
(This article belongs to the Special Issue Nondestructive Technologies for Complex Engineering Structure Health Monitoring and State Prediction)
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16 pages, 4960 KiB  
Article
Ultrasonic Phased Array Imaging Approach Using Omni-Directional Velocity Correction for Quantitative Evaluation of Delamination in Composite Structure
by Xiangting Xu, Zhichao Fan, Xuedong Chen, Jingwei Cheng and Yangguang Bu
Sensors 2023, 23(4), 1777; https://doi.org/10.3390/s23041777 - 04 Feb 2023
Cited by 1 | Viewed by 1531
Abstract
The ultrasonic detectability of buried defects within composite materials is dependent on the anisotropy of the composite material by which the propagation property of acoustic wave in each direction is variably affected. In this study, the characteristics of acoustic waves propagating in different [...] Read more.
The ultrasonic detectability of buried defects within composite materials is dependent on the anisotropy of the composite material by which the propagation property of acoustic wave in each direction is variably affected. In this study, the characteristics of acoustic waves propagating in different directions for composite materials are explored based on the full matrix capture (FMC) data using an ultrasonic phased array. The elastic constant of multidirectional carbon fiber reinforced plastic (CFRP) laminate is first derived based on the genetic algorithm. The characteristics of transmitted and reflected waves in higher angles are predicted by implementing the Christoffel equation, and the focal law used in post-processing of FMC data can be optimized accordingly. The imaging results of the total focusing method (TFM) using the improved focal law are compared with the results of the conventional TFM. The results suggest that the optimized TFM can effectively characterize the defect by reducing the background noise. Furthermore, since it is impractical to theoretically correct angle-dependent velocity for in situ inspection, a linear extrapolation method based on the experimentally measurable velocity at low angles is proposed to estimate the velocity profile at higher angles. The imaging results using the fast extrapolated velocity profile is then compared with the theoretical, and it has been demonstrated that while the difference between the images using the theoretical focal law and the linearly extrapolated one is barely visible, the later one is overwhelmingly advantageous to be realiszd for engineering practices. Full article
(This article belongs to the Special Issue Nondestructive Technologies for Complex Engineering Structure Health Monitoring and State Prediction)
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