scholarly journals Sol–Gel Waveguide-Based Sensor for Structural Health Monitoring on Large Surfaces in Aerospace Domain

Aerospace ◽  
2021 ◽  
Vol 8 (4) ◽  
pp. 109
Author(s):  
Maxime Royon ◽  
Damien Jamon ◽  
Thomas Blanchet ◽  
François Royer ◽  
Francis Vocanson ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Optical Sensors ◽  
Low Cost ◽  
Sol Gel ◽  
Matrix Structure ◽  
Structural Health ◽  
Photonic Sensor ◽  
Promising Tool ◽  
Direct Laser

The potential of sol–gel-based optical sensors is investigated for applications in the aerospace domain. To this aim, a low-cost and non-intrusive sol–gel sensor based on waveguides, arranged as a 2D matrix structure, is fabricated by UV photolithography for delamination and damage detection. Two different organic–inorganic sol–gels were selected to fabricate the photonic device: TiO2–SiO2 and ZrO2–SiO2, acting as the waveguide core and the cladding, respectively. A systematic study was performed to determine the manufacturing parameters controlling their properties. The results show that large surfaces can be functionalized via sol–gel methods using the direct laser-writing approach. The structures are characterized in terms of refractive index, and the guiding properties were investigated through simulations and experiments, indicating an excellent behavior regarding the light guidance in a straight waveguide or in the 2D matrix structure grid. Additionally, preliminary tests show that the presence of impact can be easily detected after damage through the induced optical losses on large surfaces. This proof of concept sensor is a promising tool for structural health monitoring. To achieve the ultimate goal, the integration of this photonic sensor will be later performed on aircraft wings.

scholarly journals Data-Driven Structural Health Monitoring and Damage Detection through Deep Learning: State-of-the-Art Review

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2778 ◽  
Author(s):  
Mohsen Azimi ◽  
Armin Eslamlou ◽  
Gokhan Pekcan
Keyword(s):  
Deep Learning ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
High Speed ◽  
Deep Neural Networks ◽  
State Of The Art ◽  
Data Driven ◽  
Structural Health ◽  
Promising Tool ◽  
Significant Attention

Data-driven methods in structural health monitoring (SHM) is gaining popularity due to recent technological advancements in sensors, as well as high-speed internet and cloud-based computation. Since the introduction of deep learning (DL) in civil engineering, particularly in SHM, this emerging and promising tool has attracted significant attention among researchers. The main goal of this paper is to review the latest publications in SHM using emerging DL-based methods and provide readers with an overall understanding of various SHM applications. After a brief introduction, an overview of various DL methods (e.g., deep neural networks, transfer learning, etc.) is presented. The procedure and application of vibration-based, vision-based monitoring, along with some of the recent technologies used for SHM, such as sensors, unmanned aerial vehicles (UAVs), etc. are discussed. The review concludes with prospects and potential limitations of DL-based methods in SHM applications.

scholarly journals Advances in the Structural Health Monitoring of Bridges Using Piezoelectric Transducers

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4312 ◽  
Author(s):  
Yunzhu Chen ◽  
Xingwei Xue
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Piezoelectric Materials ◽  
Low Cost ◽  
Rapid Development ◽  
Concrete Strength ◽  
Steel Corrosion ◽  
Fast Response ◽  
Future Application ◽  
Structural Health

With the rapid development of the world’s transportation infrastructure, many long-span bridges were constructed in recent years, especially in China. However, these bridges are easily subjected to various damages due to dynamic loads (such as wind-, earthquake-, and vehicle-induced vibration) or environmental factors (such as corrosion). Therefore, structural health monitoring (SHM) is vital to guarantee the safety of bridges in their service lives. With its wide frequency response range, fast response, simple preparation process, ease of processing, low cost, and other advantages, the piezoelectric transducer is commonly employed for the SHM of bridges. This paper summarizes the application of piezoelectric materials for the SHM of bridges, including the monitoring of the concrete strength, bolt looseness, steel corrosion, and grouting density. For each problem, the application of piezoelectric materials in different research methods is described. The related data processing methods for four types of bridge detection are briefly summarized, and the principles of each method in practical application are listed. Finally, issues to be studied when using piezoelectric materials for monitoring are discussed, and future application prospects and development directions are presented.

scholarly journals Reliable Data Acquisition System for a Low-Cost Accelerograph Applied to Structural Health Monitoring

2020 ◽  
Vol 3 (2) ◽  
pp. 181-194
Author(s):  
Milton Muñoz ◽  
Remigio Guevara ◽  
Santiago González ◽  
Juan Carlos Jiménez
Keyword(s):  
Structural Health Monitoring ◽  
Data Acquisition ◽  
Health Monitoring ◽  
Seismic Event ◽  
Low Cost ◽  
Recording System ◽  
Continuous Recording ◽  
Remote Communication ◽  
Structural Health ◽  
Hydroelectric Dam

This paper presents and evaluates a continuous recording system designed for a low-cost seismic station. The architecture has three main blocks. An accelerometer sensor based on MEMS technology (Microelectromechanical Systems), an SBC platform (Single Board Computer) with embedded Linux and a microcontroller device. In particular, the microcontroller represents the central component which operates as an intermediate agent to manage the communication between the accelerometer and the SBC block. This strategy allows the system for data acquisition in real time. On the other hand, the SBC platform is used for storing and processing data as well as in order to configure the remote communication with the station. This proposal is intended as a robust solution for structural health monitoring (i.e. in order to characterize the response of an infrastructure before, during and after a seismic event). The paper details the communication scheme between the system components, which has been minutely designed to ensure the samples are collected without information loss. Furthermore, for the experimental evaluation the station was located in the facilities on a relevant infrastructure, specifically a hydroelectric dam. The system operation was compared and verified with respect to a certified accelerograph station. Results prove that the continuous recording system operates successfully and allows for detecting seismic events according to requirements of structural health applications (i.e. detects events with a frequency of vibration less than 100 Hz). Specifically, through the system implemented it was possible to characterize the effect of a seismic event of 4 MD reported by the regional seismology network and with epicenter located about 30 Km of the hydroelectric dam. Particularly, the vibration frequencies detected on the infrastructure are in the range of 13 Hz and 29 Hz. Regarding the station performance, results from experiments reveals an average CPU load of 51%, consequently the processes configured on the SBC platform do not involve an overload. Finally, the average energy consumption of the station is close to 2.4 W, therefore autonomy provided by the backup system is aroud of 10 hours.

scholarly journals Structural reliability assessment based on optical monitoring system: case study

2016 ◽  
Vol 9 (2) ◽  
pp. 297-305 ◽  
Author(s):  
E. Mesquita ◽  
P. Antunes ◽  
A. A. Henriques ◽  
A. Arêde ◽  
P. S. André ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Structural Reliability ◽  
Extreme Values ◽  
Low Cost ◽  
Reliability Assessment ◽  
Water Reservoir ◽  
Optical Systems ◽  
Structural Health

ABSTRACT Optical systems are recognized to be an important tool for structural health monitoring, especially for real time safety assessment, due to simplified system configuration and low cost when compared to regular systems, namely electrical systems. This work aims to present a case study on structural health monitoring focused on reliability assessment and applying data collected by a simplified optical sensing system. This way, an elevated reinforced concrete water reservoir was instrumented with a bi-axial optical accelerometer and monitored since January 2014. Taking into account acceleration data, the natural frequencies and relative displacements were estimated. The reliability analysis was performed based on generalized extreme values distribution (GEV) and the results were employed to build a forecast of the reliability of the water elevated reservoir for the next 100 years. The results showed that the optical system combined with GEV analysis, implemented in this experimental work, can provide adequate data for structural reliability assessment.

Structural Health Monitoring With Piezoelectric Active Sensors

2000 ◽  
Author(s):  
Howard A. Winston ◽  
Fanping Sun ◽  
Balkrishna S. Annigeri
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Structural Damage ◽  
Electromechanical Coupling ◽  
Low Cost ◽  
Piezoelectric Element ◽  
Impedance Spectrum ◽  
Active Sensors ◽  
Electromechanical Impedance ◽  
Structural Health

A technology for non-intrusive real-time structural health monitoring using piezoelectric active sensors is presented. The approach is based on monitoring variations of the coupled electromechanical impedance of piezoelectric patches bonded to metallic structures in high-frequency bands. In each of these applications, a single piezoelectric element is used as both an actuator and a sensor. The resulting electromechanical coupling makes the frequency-dependent electric impedance spectrum of the PZT sensor a good mapping of the underlying structure’s acoustic signature. Moreover, incipient structural damage can be indicated by deviations of this signature from its original baseline pattern. Unique features of this technology include its high sensitivity to structural damage, non-intrusiveness to the host structure, and low cost of implementation. These features have potential for enabling on-board damage monitoring of critical or inaccessible aerospace structures and components, such as aircraft wing joints, and both internal and external jet engine components. Several exploratory applications will be discussed.

Use of low-cost GNSS receivers for Structural Health Monitoring

2018 ◽  
Author(s):  
Nicolas Manzini ◽  
Andre Orcesi ◽  
Antoine Clément ◽  
Miguel Ortiz ◽  
John Dumoulin
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Low Cost ◽  
Structural Health ◽  
Gnss Receivers

Enhancing Vibration-Based Structural Health Monitoring via Edge Computing: A Tiny Machine Learning Perspective

2021 ◽  
Author(s):  
Federica Zonzini ◽  
Francesca Romano ◽  
Antonio Carbone ◽  
Matteo Zauli ◽  
Luca De Marchi
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Network Architecture ◽  
Binary Classification ◽  
Low Cost ◽  
Classification Problems ◽  
Computationally Efficient ◽  
Structural Health

Abstract Despite the outstanding improvements achieved by artificial intelligence in the Structural Health Monitoring (SHM) field, some challenges need to be coped with. Among them, the necessity to reduce the complexity of the models and the data-to-user latency time which are still affecting state-of-the-art solutions. This is due to the continuous forwarding of a huge amount of data to centralized servers, where the inference process is usually executed in a bulky manner. Conversely, the emerging field of Tiny Machine Learning (TinyML), promoted by the recent advancements by the electronic and information engineering community, made sensor-near data inference a tangible, low-cost and computationally efficient alternative. In line with this observation, this work explored the embodiment of the One Class Classifier Neural Network, i.e., a neural network architecture solving binary classification problems for vibration-based SHM scenarios, into a resource-constrained device. To this end, OCCNN has been ported on the Arduino Nano 33 BLE Sense platform and validated with experimental data from the Z24 bridge use case, reaching an average accuracy and precision of 95% and 94%, respectively.

Feasibility of screen-printed PZT microceramics for Structural Health Monitoring piezocomposites applications

2013 ◽  
Vol 2013 (CICMT) ◽  
pp. 000020-000025
Author(s):  
Hélène DEBEDA ◽  
Riadh LAKHMI ◽  
Isabelle FAVRE ◽  
Jonathan ARGILLOS ◽  
Mario MAGLIONE ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Sacrificial Layer ◽  
Low Cost ◽  
Thick Films ◽  
Impedance Analysis ◽  
High Porosity ◽  
Structural Health ◽  
Monitoring Applications ◽  
Screen Printing Technology

Using the association of the low-cost screen-printing technology with the sacrificial layer method, the feasibility of totally released piezoelectric thick-films microceramics of gold electroded PZT type is studied. After the deposition of the sacrificial layer on an alumina substrate and subsequent printing and drying of gold, PZT and gold layers, the final firing is performed at low temperature. This is followed by the releasing step of the Au/PZT/Au in diluted acidic solution. Impedance analysis shows that the electrical properties and electromechanical coefficients of poled PZT thick-films are still lower than those of PZT ceramics. This result is correlated to the high porosity rate of the PZT layer. However these piezoelectric microceramics present a good electromechanical behaviour and can be used as sensors when solicited by vibrations or as actuators to generate vibrations in a structure on which they are bonded. Moreover, the successful fabrication associated to a good electromechanical signature on a metallic test structure suggests Structural Health Monitoring applications.

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