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Advanced Sensing Technology in Structural Health Monitoring

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

Deadline for manuscript submissions: 31 March 2025 | Viewed by 5850

Special Issue Editors


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Guest Editor
Department of Industrial and Information Engineering and of Economics, University of L’Aquila, 67100 L’Aquila, Italy
Interests: measuring systems; MEMS accelerometers; sensor integration; uncertainty assessment
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Industrial and Information Engineering and of Economics, University of L’Aquila, 67100 L’Aquila, Italy
Interests: measuring systems; MEMS accelerometers; sensor integration; uncertainty assessment
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Public safety, cultural heritage preservation, and sustainable urban growth are among the most important political and technical concerns in advanced countries. Because of this, assessing the health and functionality of the current infrastructure and buildings represents a crucial need that enables decision-makers to set up the optimal lines of intervention and priorities to enhance patient safety and quality of life.

To develop integrated techniques and procedures investigating geotechnical and structural aspects as well as the diagnostics of buildings, distributed multi-sensor networks are required in order to cover entire structures or groups of structures in wide areas.

The high connectivity and digitalisation of modern cities, the availability of miniaturised and low-cost sensors, and the development of advanced processing algorithms, even based on artificial intelligence, and cloud platforms favour the development of sensor networks and integrated systems for acquisition, processing, transmission, and information storage.

However, numerous factors must be taken into account in order to develop robust and trustworthy techniques for structural health monitoring, as well as to guarantee widespread validity, easy field application, and affordability, including the following:

  • Sensor type, number, and positioning;
  • Uncertainty analysis;
  • Validation of data;
  • Metrological traceability;
  • In field calibration of sensors;
  • Validation of data processing techniques.

Other topics will also be considered if they are coherent with this theme.

Dr. Emanuela Natale
Prof. Dr. Giulio D'Emilia
Guest Editors

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Keywords

  • sensors
  • sensor networks
  • MEMS sensors
  • measuring systems
  • uncertainty evaluation
  • structural monitoring
  • artificial intelligence
  • sensor fusion
  • calibration

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Published Papers (4 papers)

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Research

16 pages, 7856 KiB  
Article
An Experimental Study of the Flexural Bearing Capacity of Reinforced Concrete Beams Damaged by Explosions Using Piezoelectric Smart Aggregates
by Kai Xu, Shilong Sheng, Ronghui Jiang and Qian Feng
Sensors 2024, 24(24), 7944; https://doi.org/10.3390/s24247944 - 12 Dec 2024
Viewed by 468
Abstract
Two identically sized RC beams were fabricated to investigate the effects of explosive loads on the flexural behaviour of Reinforced Concrete (RC) beams. One of the beams was subjected to an explosive load to induce post-explosion damage, and subsequently, both beams underwent flexural [...] Read more.
Two identically sized RC beams were fabricated to investigate the effects of explosive loads on the flexural behaviour of Reinforced Concrete (RC) beams. One of the beams was subjected to an explosive load to induce post-explosion damage, and subsequently, both beams underwent flexural capacity testing. Integrating piezoelectric smart aggregates (SAas) within the beams facilitated continuous observation of the damage conditions, allowing for the assessment of internal concrete deterioration from explosive impacts to bending failures. The internal crack development index R was established using the Wavelet Packet Energy Analysis method. Combined with the structure’s residual capacity-based damage assessment criterion, the relationship between R and component damage was found. This allowed us to identify the change in the bending capacity of RC beams after explosion damage and the quantitative damage assessment of the beam to be realised, providing valuable insights for structural engineers and researchers. Comparing the flexural test results between the explosively pre-damaged beam and the undamaged test beam, it was observed that the neutral axis of the damaged beam was significantly elevated, accompanied by a notable reduction in flexural capacity. By examining the variation curve of the internal crack development index R, it was noted that during the initial stage of the bending flexural test, due to bending deformation, cracks in the core region of the pre-damaged beam gradually healed, leading to a pseudo-decrease in the damage index. After reaching a minimum point, the damage progressed faster until failure occurred. Full article
(This article belongs to the Special Issue Advanced Sensing Technology in Structural Health Monitoring)
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25 pages, 6085 KiB  
Article
SHM System for Composite Material Based on Lamb Waves and Using Machine Learning on Hardware
by Gracieth Cavalcanti Batista, Carl-Mikael Zetterling, Johnny Öberg and Osamu Saotome
Sensors 2024, 24(23), 7817; https://doi.org/10.3390/s24237817 - 6 Dec 2024
Viewed by 672
Abstract
There is extensive use of nondestructive test (NDT) inspections on aircraft, and many techniques nowadays exist to inspect failures and cracks in their structures. Moreover, NDT inspections are part of a more general structural health monitoring (SHM) system, where cutting-edge technologies are needed [...] Read more.
There is extensive use of nondestructive test (NDT) inspections on aircraft, and many techniques nowadays exist to inspect failures and cracks in their structures. Moreover, NDT inspections are part of a more general structural health monitoring (SHM) system, where cutting-edge technologies are needed as powerful resources to achieve high performance. The high-performance aspects of SHM systems are response time, power consumption, and usability, which are difficult to achieve because of the system’s complexity. Then, it is even more challenging to develop a real-time low-power SHM system. Today, the ideal process is for structural health information extraction to be completed on the flight; however, the defects and damage are quantitatively made offline and on the ground, and sometimes, the respective procedure test is applied later on the ground, after the flight. For this reason, the present paper introduces an FPGA-based intelligent SHM system that processes Lamb wave signals using piezoelectric sensors to detect, classify, and locate damage in composite structures. The system employs machine learning (ML), specifically support vector machines (SVM), to classify damage while addressing outlier challenges with the Mahalanobis distance during the classification phase. To process the complex Lamb wave signals, the system incorporates well-known signal processing (DSP) techniques, including power spectrum density (PSD), wavelet transform, and Principal Component Analysis (PCA), for noise reduction, feature extraction, and data compression. These techniques enable the system to handle material anisotropy and mitigate the effects of edge reflections and mode conversions. Damage is quantitatively evaluated with classification accuracies of 96.25% for internal defects and 97.5% for external defects, with localization achieved by associating receiver positions with damage occurrence. This robust system is validated through experiments and demonstrates its potential for real-time applications in aerospace composite structures, addressing challenges related to material complexity, outliers, and scalable hardware implementation for larger sensor networks. Full article
(This article belongs to the Special Issue Advanced Sensing Technology in Structural Health Monitoring)
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15 pages, 7201 KiB  
Article
Using Light Polarization to Identify Fiber Orientation in Carbon Fiber Components: Metrological Analysis
by Luciano Chiominto, Giulio D’Emilia and Emanuela Natale
Sensors 2024, 24(17), 5685; https://doi.org/10.3390/s24175685 - 31 Aug 2024
Viewed by 961
Abstract
In this work, a method for measuring tow angles in carbon fiber components, based on the use of a polarized camera, is analyzed from a metrological point of view. Carbon fibers alter the direction of the reflected light’s electrical field, so that in [...] Read more.
In this work, a method for measuring tow angles in carbon fiber components, based on the use of a polarized camera, is analyzed from a metrological point of view. Carbon fibers alter the direction of the reflected light’s electrical field, so that in each point of the surface of a composite piece, the angle of polarization of reflected light matches the fiber orientation. A statistical analysis of the angle of linear polarization (AoLP) in each pixel of each examined area allows to evaluate the average winding angle. An evaluation of the measurement uncertainty of the method on a cylinder obtained by a filament winding process is carried out, and the result appears adequate for the study of the distribution of angles along the surface of the piece, in order to optimize the process. Full article
(This article belongs to the Special Issue Advanced Sensing Technology in Structural Health Monitoring)
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20 pages, 7735 KiB  
Article
Directivity and Excitability of Ultrasonic Shear Waves Using Piezoceramic Transducers—Numerical Modeling and Experimental Investigations
by Emil Aleksiewicz-Drab, Aleksandra Ziaja-Sujdak, Rafał Radecki and Wiesław J. Staszewski
Sensors 2024, 24(11), 3462; https://doi.org/10.3390/s24113462 - 27 May 2024
Viewed by 709
Abstract
In this paper, piezoceramic-based excitation of shear horizontal waves is investigated. A thickness-shear d15 piezoceramic transducer is modeled using the finite-element method. The major focus is on the directivity and excitability of the shear horizontal fundamental mode with respect to the maximization [...] Read more.
In this paper, piezoceramic-based excitation of shear horizontal waves is investigated. A thickness-shear d15 piezoceramic transducer is modeled using the finite-element method. The major focus is on the directivity and excitability of the shear horizontal fundamental mode with respect to the maximization of excited shear and minimization of Lamb wave modes. The results show that the geometry of the transducer has more effect on the directivity than on the excitability of the analyzed actuator. Numerically simulated results are validated experimentally. The experimental results show that transducer bonding significantly affects the directivity and amplitude of the excited modes. In conclusion, when the selected actuator is used for shear excitation, the best solution is to tailor the transducer in such a way that at the resonant frequency the desired directivity is achieved. Full article
(This article belongs to the Special Issue Advanced Sensing Technology in Structural Health Monitoring)
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