scholarly journals Applications of Cement-Based Smart Composites to Civil Structural Health Monitoring: A Review

2021 ◽  
Vol 11 (18) ◽  
pp. 8530
Author(s):  
Paolino Cassese ◽  
Carlo Rainieri ◽  
Antonio Occhiuzzi
Keyword(s):  
Structural Health Monitoring ◽  
Literature Review ◽  
Health Monitoring ◽  
State Of The Art ◽  
Conductive Filler ◽  
Full Scale ◽  
Research Interest ◽  
Structural Health ◽  
Smart Composites ◽  
Open Issues

In recent years, cement-based smart composites (CSCs) doped with conductive filler have attracted increasing research interest because of their high potentiality as self-sensing materials for civil Structural Health Monitoring (SHM) applications. Nevertheless, several issues are still open and need further studies. This paper presents an extensive state-of-the-art in which investigations on CSCs are summarized and critically revised, with the primary aim of outlining the main limits and development points. The literature review first addresses in detail several specific issues related to fabrication and operation as sensing elements of CSC samples. State-of-the-art applications of CSCs to SHM of reduced-, medium- and full-scale structural prototypes are extensively reviewed afterwards, resulting in a database useful to critically revise the main trends and open issues of the research in this field.

The 1st International Project Competition for Structural Health Monitoring (IPC-SHM, 2020): A summary and benchmark problem

2021 ◽  
pp. 147592172110064
Author(s):  
Yuequan Bao ◽  
Jian Li ◽  
Tomonori Nagayama ◽  
Yang Xu ◽  
Billie F Spencer ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Undergraduate Students ◽  
Health Monitoring ◽  
Fatigue Cracks ◽  
Full Scale ◽  
Asia Pacific ◽  
International Project ◽  
Full Time ◽  
Structural Health ◽  
Institute Of Technology

To promote the development of structural health monitoring around the world, the 1st International Project Competition for Structural Health Monitoring (IPC-SHM, 2020) was initiated and organized in 2020 by the Asia-Pacific Network of Centers for Research in Smart Structures Technology, Harbin Institute of Technology, the University of Illinois at Urbana-Champaign, and four leading companies in the application of structural health monitoring technology. The goal of this competition was to attract more young scholars to engage in the study of structural health monitoring, encouraging them to provide creative and effective solutions for full-scale applications. Recognizing the recent advent and importance of artificial intelligence in structural health monitoring, three competition projects were set up with the data from full-scale bridges: (1) image-based identification of fatigue cracks in bridge girders, (2) data anomaly detection for structural health monitoring, and (3) condition assessment of stay cables using cable tension data. Three corresponding data sets were released at http://www.schm.org.cn and http://sstl.cee.illinois.edu/ipc-shm2020 . Participants were required to be full-time undergraduate students, M.S. students, Ph.D. students, or young scholars within 3 years after obtaining their Ph.D. Both individual and teams (each team had no more than five individuals) could compete. Submissions for the competition included a 10- to 15-page technical paper, a 10-min presentation video with PowerPoint slides, and commented code. The organizing committee then conducted the validation, review, and evaluation. A total of 330 participants in 112 teams from 70 universities and institutions in 12 countries registered for the competition, resulting in 75 papers from 56 teams from 57 different affiliations finally being submitted. Of those submitted, 31, 30, and 14 papers were for Projects 1, 2, and 3, respectively. After completion of the review by the organization committee and awards committee, the top 10, 10, and 5 teams were selected as the prize winners for the three competition projects.

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 Prototyping and Validation of MEMS Accelerometers for Structural Health Monitoring—The Case Study of the Pietratagliata Cable-Stayed Bridge

2018 ◽  
Vol 7 (3) ◽  
pp. 30 ◽  
Author(s):  
Chiara Bedon ◽  
Enrico Bergamo ◽  
Matteo Izzi ◽  
Salvatore Noè
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Full Scale ◽  
Shaking Table ◽  
Efficient Design ◽  
Dynamic Identification ◽  
Structural Health ◽  
Cable Stayed Bridge ◽  
Mems Accelerometers

In recent years, thanks to the simple and yet efficient design, Micro Electro-Mechanical Systems (MEMS) accelerometers have proven to offer a suitable solution for Structural Health Monitoring (SHM) in civil engineering applications. Such devices are typically characterised by high portability and durability, as well as limited cost, hence resulting in ideal tools for applications in buildings and infrastructure. In this paper, original self-made MEMS sensor prototypes are presented and validated on the basis of preliminary laboratory tests (shaking table experiments and noise level measurements). Based on the well promising preliminary outcomes, their possible application for the dynamic identification of existing, full-scale structural assemblies is then discussed, giving evidence of their potential via comparative calculations towards past literature results, inclusive of both on-site, Experimental Modal Analysis (EMA) and Finite Element Analytical estimations (FEA). The full-scale experimental validation of MEMS accelerometers, in particular, is performed using, as a case study, the cable-stayed bridge in Pietratagliata (Italy). Dynamic results summarised in the paper demonstrate the high capability of MEMS accelerometers, with evidence of rather stable and reliable predictions, and suggest their feasibility and potential for SHM purposes.

An open database for benchmarking guided waves structural health monitoring algorithms on a composite full-scale outer wing demonstrator

2019 ◽  
Vol 19 (5) ◽  
pp. 1524-1541 ◽  
Author(s):  
Alessandro Marzani ◽  
Nicola Testoni ◽  
Luca De Marchi ◽  
Marco Messina ◽  
Ernesto Monaco ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Damage Detection ◽  
Monitoring System ◽  
Health Monitoring ◽  
Guided Wave ◽  
Full Scale ◽  
Composite Panel ◽  
Health Monitoring System ◽  
Electromechanical Impedance ◽  
Structural Health

This article reports on the creation of an open database of piezo-actuated and piezo-received guided wave signals propagating in a composite panel of a full-scale aeronautical structure. The composite panel closes the bottom part of a wingbox that, along with the leading edge, the trailing edge, and the wingtip, forms an outer wing demonstrator approximately 4.5 m long and from 1.2 to 2.3 m wide. To create the database, a structural health monitoring system, composed of a software/hardware central unit capable of controlling a network of 160 piezoelectric transducers secondarily bonded on the composite panel, has been realized. The structural health monitoring system has been designed to (1) perform electromechanical impedance measurement at each transducer, in order to check for their reliability and bonding strength, and (2) to operate an active guided wave screening for damage detection in the composite panel. Electromechanical impedance and guided wave measurements were performed at four different testing stages: before loading, before fatigue, before impacts, and after impacts. The database, freely available at http://shm.ing.unibo.it/ , can thus be used to benchmarking, on real-scale structural data, guided wave algorithms for loading, fatigue, as well as damage detection, characterization, and sizing. As an example, in this work, a delay and sum algorithm is applied on the post-impact data to illustrate how the database can be exploited.

scholarly journals Piezoelectric Sensing Techniques in Structural Health Monitoring: A State-of-the-Art Review

Sensors ◽  
2020 ◽  
Vol 20 (13) ◽  
pp. 3730 ◽  
Author(s):  
Pengcheng Jiao ◽  
King-James I. Egbe ◽  
Yiwei Xie ◽  
Ali Matin Nazar ◽  
Amir H. Alavi
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Smart Materials ◽  
State Of The Art ◽  
Piezoelectric Materials ◽  
Great Promise ◽  
Monitoring Systems ◽  
Electromechanical Impedance ◽  
Structural Health ◽  
Health Monitoring Systems

Recently, there has been a growing interest in deploying smart materials as sensing components of structural health monitoring systems. In this arena, piezoelectric materials offer great promise for researchers to rapidly expand their many potential applications. The main goal of this study is to review the state-of-the-art piezoelectric-based sensing techniques that are currently used in the structural health monitoring area. These techniques range from piezoelectric electromechanical impedance and ultrasonic Lamb wave methods to a class of cutting-edge self-powered sensing systems. We present the principle of the piezoelectric effect and the underlying mechanisms used by the piezoelectric sensing methods to detect the structural response. Furthermore, the pros and cons of the current methodologies are discussed. In the end, we envision a role of the piezoelectric-based techniques in developing the next-generation self-monitoring and self-powering health monitoring systems.

Foundation structural health monitoring of an offshore wind turbine—a full-scale case study

2016 ◽  
Vol 15 (4) ◽  
pp. 389-402 ◽  
Author(s):  
Wout Weijtjens ◽  
Tim Verbelen ◽  
Gert De Sitter ◽  
Christof Devriendt
Keyword(s):  
Structural Health Monitoring ◽  
Wind Turbine ◽  
Health Monitoring ◽  
Full Scale ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Structural Health

Design of Structural Health Monitoring System Based on WSNs

2014 ◽  
Vol 681 ◽  
pp. 47-50
Author(s):  
Yue Zhou ◽  
Shuai Liu ◽  
Li Xin Zhang
Keyword(s):  
Structural Health Monitoring ◽  
Monitoring System ◽  
Health Monitoring ◽  
Large Scale ◽  
State Of The Art ◽  
Health Monitoring System ◽  
Structural Health ◽  
Structural Health Monitoring System ◽  
Large Scale Networks ◽  
Monitoring Application

The structural health monitoring technology has been one of the most important issues. In this paper, the design of wireless sensor network for structural health monitoring application is studied. The basic concept, significance, state of the art of structural health monitoring, the architecture and the principle of the wireless structural health monitoring system are described. The hardware and software of the overall system are designed and built. The WLANonSAN architecture network is particularly proposed as a solution for the large-scale networks.

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