Research

10 pages, 2828 KiB

Open AccessCommunication

Multiple Damage Detection in PZT Sensor Using Dual Point Contact Method

by Sayantani Bhattacharya, Nitin Yadav, Azeem Ahmad, Frank Melandsø and Anowarul Habib

Sensors 2022, 22(23), 9161; https://0-doi-org.brum.beds.ac.uk/10.3390/s22239161 - 25 Nov 2022

Cited by 1 | Viewed by 1616

Lead Zirconate Titanate (PZT) is used to make ultrasound transducers, sensors, and actuators due to its large piezoelectric coefficient. Several micro-defects develop in the PZT sensor due to delamination, corrosion, huge temperature fluctuation, etc., causing a decline in its performance. It is thus [...] Read more.

Lead Zirconate Titanate (PZT) is used to make ultrasound transducers, sensors, and actuators due to its large piezoelectric coefficient. Several micro-defects develop in the PZT sensor due to delamination, corrosion, huge temperature fluctuation, etc., causing a decline in its performance. It is thus necessary to identify, locate, and quantify the defects. Non-Destructive Structural Health Monitoring (SHM) is the most optimal and economical evaluation method. Traditional ultrasound SHM techniques have a huge impedance mismatch between air and solid material, and most of the popular signal processing methods define time series signals in only one domain, which provides sub-optimal results for non-stationary signals. Thus, to improve the accuracy of detection, the point contact excitation and detection method is implemented to determine the interaction of ultrasonic waves with micro-scale defects in the PZT. The signal generated from this method being non-stationary in nature, it requires signal processing with changeable resolutions at different times and frequencies. The Haar Discrete Wavelet Transformation (DWT) is applied to the time series data obtained from the coulomb coupling setup. Using the above process, defects up to 100 μm in diameter could be successfully distinguished. Full article

(This article belongs to the Special Issue Smart Materials for Structural Health Monitoring and Damage Detection)

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18 pages, 664 KiB

Open AccessArticle

Dependence of Piezoelectric Discs Electrical Impedance on Mechanical Loading Condition

by Niharika Gogoi, Jie Chen, Jens Kirchner and Georg Fischer

Sensors 2022, 22(5), 1710; https://0-doi-org.brum.beds.ac.uk/10.3390/s22051710 - 22 Feb 2022

Cited by 3 | Viewed by 2971

Abstract

The piezoelectric effect, along with its associated materials, fascinated researchers in all areas of basic sciences and engineering due to its interesting properties and promising potentials. Sensing, actuation, and energy harvesting are major implementations of piezoelectric structures in structural health monitoring, wearable devices, [...] Read more.

The piezoelectric effect, along with its associated materials, fascinated researchers in all areas of basic sciences and engineering due to its interesting properties and promising potentials. Sensing, actuation, and energy harvesting are major implementations of piezoelectric structures in structural health monitoring, wearable devices, and self-powered systems, to name only a few. The electrical or mechanical impedance of its structure plays an important role in deriving its equivalent model, which in turn helps to predict its behavior for any system-level application, such as with respect to the rectifiers containing diodes and switches, which represent a nonlinear electrical load. In this paper, we study the electrical impedance response of different sizes of commercial piezoelectric discs for a wide range of frequencies (without and with mechanical load for 0.1–1000

kHz

with resolution 20

Hz

). It shows significant changes in the position of resonant frequency and amplitude of resonant peaks for different diameters of discs and under varying mechanical load conditions, implying variations in the mechanical boundary conditions on the structure. The highlight of our work is the proposed electrical equivalent circuit model for varying mechanically loaded conditions with the help of impedance technique. Our approach is simple and reliable, such that it is suitable for any structure whose accurate material properties and dimensions are unknown. Full article

(This article belongs to the Special Issue Smart Materials for Structural Health Monitoring and Damage Detection)

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16 pages, 17226 KiB

Open AccessArticle

ConcrEITS: An Electrical Impedance Interrogator for Concrete Damage Detection Using Self-Sensing Repairs

by Jack McAlorum, Marcus Perry, Andrew C. Ward and Christos Vlachakis

Sensors 2021, 21(21), 7081; https://0-doi-org.brum.beds.ac.uk/10.3390/s21217081 - 26 Oct 2021

Cited by 10 | Viewed by 1677

Abstract

Concrete infrastructure requires continuous monitoring to ensure any new damage or repair failures are detected promptly. A cost-effective combination of monitoring and maintenance would be highly beneficial in the rehabilitation of existing infrastructure. Alkali-activated materials have been used as concrete repairs and as [...] Read more.

Concrete infrastructure requires continuous monitoring to ensure any new damage or repair failures are detected promptly. A cost-effective combination of monitoring and maintenance would be highly beneficial in the rehabilitation of existing infrastructure. Alkali-activated materials have been used as concrete repairs and as sensing elements for temperature, moisture, and chlorides. However, damage detection using self-sensing repairs has yet to be demonstrated, and commercial interrogation solutions are expensive. Here, we present the design of a low-cost tomographic impedance interrogator, denoted the “ConcrEITS”, capable of crack detection and location in concrete using conductive repair patches. Results show that for pure material blocks ConcrEITS is capable of measuring 4-probe impedance with a root mean square error of ±5.4% when compared to a commercially available device. For tomographic measurements, ConcrEITS is able to detect and locate cracks in patches adhered to small concrete beam samples undergoing 4-point bending. In all six samples tested, crack locations were clearly identified by the contour images gained from tomographic reconstruction. Overall, this system shows promise as a cost-effective combined solution for monitoring and maintenance of concrete infrastructure. We believe further up-scaled testing should follow this research before implementing the technology in a field trial. Full article

(This article belongs to the Special Issue Smart Materials for Structural Health Monitoring and Damage Detection)

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20 pages, 7936 KiB

Open AccessArticle

A Crack Size Quantification Method Using High-Resolution Lamb Waves

by Xianjun Li, Jinsong Yang and Guangdong Zhang

Sensors 2021, 21(20), 6941; https://0-doi-org.brum.beds.ac.uk/10.3390/s21206941 - 19 Oct 2021

Cited by 2 | Viewed by 1821

Abstract

Traditional tone burst excitation cannot attain a high output resolution, due to the time duration. The received signal is much longer than that of excitation during the propagation, which can increase the difficulty of signal processing, and reduce the resolution. Therefore, it is [...] Read more.

Traditional tone burst excitation cannot attain a high output resolution, due to the time duration. The received signal is much longer than that of excitation during the propagation, which can increase the difficulty of signal processing, and reduce the resolution. Therefore, it is of significant interest to develop a general methodology for crack quantification through the optimal design of the excitation waveform and signal-processing methods. This paper presents a new crack size quantification method based on high-resolution Lamb waves. The linear chirp (L-Chirp) signal and Golay complementary code (GCC) signal are used as Lamb wave excitation signals. After dispersion removal, these excitation waveforms, based on pulse compression, can effectively improve the inspection resolution in plate-like structures. A series of simulations of both healthy plates and plates with different crack sizes are performed by Abaqus CAE, using different excitation waveforms. The first wave package of the S₀ mode after pulse compression is chosen to extract the damage features. A multivariate regression model is proposed to correlate the damage features to the crack size. The effectiveness of the proposed crack size quantification method is verified by a comparison with tone burst excitation, and the accuracy of the crack size quantification method is verified by validation experiments. Full article

(This article belongs to the Special Issue Smart Materials for Structural Health Monitoring and Damage Detection)

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12 pages, 8875 KiB

Open AccessCommunication

Monitoring of Large Diameter Sewage Collector Strengthened with Glass-Fiber Reinforced Plastic (GRP) Panels by Means of Distributed Fiber Optic Sensors (DFOS)

by Paweł Popielski, Bartosz Bednarz, Rafał Sieńko, Tomasz Howiacki, Łukasz Bednarski and Bartosz Zaborski

Sensors 2021, 21(19), 6607; https://0-doi-org.brum.beds.ac.uk/10.3390/s21196607 - 03 Oct 2021

Cited by 4 | Viewed by 2041

Abstract

Diagnostics and assessment of the structural performance of collectors and tunnels require multi-criteria as well as comprehensive analyses for improving the safety based on acquired measurement data. This paper presents the basic goals for a structural health monitoring system designed based on distributed [...] Read more.

Diagnostics and assessment of the structural performance of collectors and tunnels require multi-criteria as well as comprehensive analyses for improving the safety based on acquired measurement data. This paper presents the basic goals for a structural health monitoring system designed based on distributed fiber optic sensors (DFOS). The issue of selecting appropriate sensors enabling correct strain transfer is discussed hereafter, indicating both limitations of layered cables and advantages of sensors with monolithic cross-section design in terms of reliable measurements. The sensor’s design determines the operation of the entire monitoring system and the usefulness of the acquired data for the engineering interpretation. The measurements and results obtained due to monolithic DFOS sensors are described hereafter on the example of real engineering structure—the Burakowski concrete collector in Warsaw during its strengthening with glass-fiber reinforced plastic (GRP) panels. Full article

(This article belongs to the Special Issue Smart Materials for Structural Health Monitoring and Damage Detection)

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19 pages, 12825 KiB

Open AccessArticle

A Multichannel Strain Measurement Technique for Nanomodified Smart Cement-Based Sensors in Reinforced Concrete Structures

by Andrea Meoni, Antonella D’Alessandro, Massimo Mancinelli and Filippo Ubertini

Sensors 2021, 21(16), 5633; https://0-doi-org.brum.beds.ac.uk/10.3390/s21165633 - 21 Aug 2021

Cited by 23 | Viewed by 2449

Abstract

Nanomodified smart cement-based sensors are an emerging self-sensing technology for the structural health monitoring (SHM) of reinforced concrete (RC) structures. To date, several literature works demonstrated their strain-sensing capabilities, which make them suited for damage detection and localization. Despite the most recent technological [...] Read more.

Nanomodified smart cement-based sensors are an emerging self-sensing technology for the structural health monitoring (SHM) of reinforced concrete (RC) structures. To date, several literature works demonstrated their strain-sensing capabilities, which make them suited for damage detection and localization. Despite the most recent technological improvements, a tailored measurement technique allowing feasible field implementations of smart cement-based sensors to concrete structures is still missing. In this regard, this paper proposes a multichannel measurement technique for retrieving strains from smart cement-based sensors embedded in RC structures using a distributed biphasic input. The experiments performed for its validation include the investigation on an RC beam with seven embedded sensors subjected to different types of static loading and a long-term monitoring application on an RC plate. Results demonstrate that the proposed technique is effective for retrieving time-stable simultaneous strain measurements from smart cement-based sensors, as well as for aiding the identification of the changes in their electrical outputs due to the influence of environmental effects variable over time. Accordingly, the proposed multichannel strain measurement technique represents a promising approach for performing feasible field implementations of smart cement-based sensors to concrete structures. Full article

(This article belongs to the Special Issue Smart Materials for Structural Health Monitoring and Damage Detection)

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18 pages, 4356 KiB

Open AccessArticle

The Artificial Intelligence of Things Sensing System of Real-Time Bridge Scour Monitoring for Early Warning during Floods

by Yung-Bin Lin, Fong-Zuo Lee, Kuo-Chun Chang, Jihn-Sung Lai, Shi-Wei Lo, Jyh-Horng Wu and Tzu-Kang Lin

Sensors 2021, 21(14), 4942; https://0-doi-org.brum.beds.ac.uk/10.3390/s21144942 - 20 Jul 2021

Cited by 12 | Viewed by 4243

Abstract

Scour around bridge piers remains the leading cause of bridge failure induced in flood. Floods and torrential rains erode riverbeds and damage cross-river structures, causing bridge collapse and a severe threat to property and life. Reductions in bridge-safety capacity need to be monitored [...] Read more.

Scour around bridge piers remains the leading cause of bridge failure induced in flood. Floods and torrential rains erode riverbeds and damage cross-river structures, causing bridge collapse and a severe threat to property and life. Reductions in bridge-safety capacity need to be monitored during flood periods to protect the traveling public. In the present study, a scour monitoring system designed with vibration-based arrayed sensors consisting of a combination of Internet of Things (IoT) and artificial intelligence (AI) is developed and implemented to obtain real-time scour depth measurements. These vibration-based micro-electro-mechanical systems (MEMS) sensors are packaged in a waterproof stainless steel ball within a rebar cage to resist a harsh environment in floods. The floodwater-level changes around the bridge pier are performed using real-time CCTV images by the Mask R-CNN deep learning model. The scour-depth evolution is simulated using the hydrodynamic model with the selected local scour formulas and the sediment transport equation. The laboratory and field measurement results demonstrated the success of the early warning system for monitoring the real-time bridge scour-depth evolution. Full article

(This article belongs to the Special Issue Smart Materials for Structural Health Monitoring and Damage Detection)

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18 pages, 6298 KiB

Open AccessArticle

Baseline-Free Structural Damage Identification for Beam-Like Structures Using Curvature Waveforms of Propagating Flexural Waves

by Y. F. Xu and J. S. Kim

Sensors 2021, 21(7), 2453; https://0-doi-org.brum.beds.ac.uk/10.3390/s21072453 - 02 Apr 2021

Cited by 4 | Viewed by 1721

Abstract

Curvatures in mode shapes and operating deflection shapes have been extensively studied for vibration-based structural damage identification in recent decades. Curvatures of mode shapes and operating deflection shapes have proved capable of localizing and manifesting local effects of damage on mode shapes and [...] Read more.

Curvatures in mode shapes and operating deflection shapes have been extensively studied for vibration-based structural damage identification in recent decades. Curvatures of mode shapes and operating deflection shapes have proved capable of localizing and manifesting local effects of damage on mode shapes and operating deflection shapes in forms of local anomalies. The damage can be inversely identified in the neighborhoods of the anomalies that exist in the curvatures. Meanwhile, propagating flexural waves have also been extensively studied for structural damage identification and proved to be effective, thanks to their high damage-sensitivity and long range of propagation. In this work, a baseline-free structural damage identification method is developed for beam-like structures using curvature waveforms of propagating flexural waves. A multi-resolution local-regression temporal-spatial curvature damage index (TSCDI) is defined in a pointwise manner. A two-dimensional auxiliary TSCDI and a one-dimensional auxiliary damage index are developed to further assist the identification. Two major advantages of the proposed method are: (1) curvature waveforms of propagating flexural waves have relatively high signal-to-noise ratios due to the use of a multi-resolution central finite difference scheme, so that the local effects of the damage can be manifested, and (2) the proposed method does not require quantitative knowledge of a pristine structure associated with a structure to be examined, such as its material properties, waveforms of propagating flexural waves and boundary conditions. Numerical and experimental investigations of the proposed method are conducted on damaged beam-like structures, and the effectiveness of the proposed method is verified by the results of the investigations. Full article

(This article belongs to the Special Issue Smart Materials for Structural Health Monitoring and Damage Detection)

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