Structural Health Monitoring on the SARISTU Full Scale Door Surround Structure

2017 ◽  
pp. 463-473
Author(s):  
M. Moix-Bonet ◽  
D. Schmidt ◽  
P. Wierach
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Full Scale ◽  
Structural Health

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 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.

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

Development and full-scale validation of high-fidelity data acquisition on a next-generation wireless smart sensor platform

2019 ◽  
Vol 22 (16) ◽  
pp. 3512-3533 ◽  
Author(s):  
Yuguang Fu ◽  
Kirill Mechitov ◽  
Tu Hoang ◽  
Jong R Kim ◽  
Deuck Hang Lee ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Data Acquisition ◽  
Health Monitoring ◽  
Full Scale ◽  
Smart Sensors ◽  
Smart Sensor ◽  
Structural Health ◽  
Sensor Platforms ◽  
Sensor Platform ◽  
Wireless Smart Sensors

Although wireless smart sensor platforms have been available over a decade, only a limited number of full-scale wireless smart sensor–based structural health monitoring implementations have been realized. Most wireless smart sensor platforms that are validated in full-scale implementations have now become obsolete and are no longer commercially available. While wireless sensing capabilities have grown, presenting significant opportunities, obstacles to wide application of wireless smart sensor for structural health monitoring exist both in terms of hardware and software. This article assesses the efficacy of the Xnode, a new wireless platform whose development has been driven by structural health monitoring requirements, as well as lessons learned from several full-scale wireless smart sensor deployments. The capabilities of the platform are evaluated in comparison with other commercial wireless smart sensors, in terms of hardware, software, and mechanical design. Extensive laboratory and field testing is employed to validate its performance on three aspects: fidelity of data acquisition, reliability of wireless communication, and efficiency of power management. Test results demonstrate the capabilities of the Xnode to support full-scale, high-fidelity data acquisition for civil infrastructure. In addition, the new sensor platform provides several significant benefits to extend the use of wireless smart sensors to a broader class of structural health monitoring applications, such as sudden event monitoring and real-time and control applications.

Autonomous smart sensor network for full-scale structural health monitoring

2010 ◽  
Author(s):  
Jennifer A. Rice ◽  
Kirill A. Mechitov ◽  
B. F. Spencer, Jr. ◽  
Gul A. Agha
Keyword(s):  
Structural Health Monitoring ◽  
Sensor Network ◽  
Health Monitoring ◽  
Full Scale ◽  
Smart Sensor ◽  
Structural Health

Damage Detection for SMC Benchmark Problem: A Subspace-Based Approach

2016 ◽  
Vol 16 (04) ◽  
pp. 1640025 ◽  
Author(s):  
Wensong Zhou ◽  
Shunlong Li ◽  
Hui Li
Keyword(s):  
Structural Health Monitoring ◽  
Damage Detection ◽  
Health Monitoring ◽  
Full Scale ◽  
Detection Methods ◽  
Benchmark Problems ◽  
Small Scale ◽  
Benchmark Problem ◽  
Monitoring And Control ◽  
Structural Health

A full-scale bridge benchmark problem was issued by the Center of Structural Monitoring and Control at the Harbin Institute of Technology. The data used in this problem were collected by an in situ structural health monitoring system implemented into a full-scale cable-stayed bridge before and after the bridge was damaged, which is very rare in structural health monitoring field. This benchmark problem will help to verify and/or make comparison of the condition assessment and the damage detection methods, which are usually validated by numerical simulation and/or laboratory testing of small-scale structures with assumed deterioration models and artificial damage. With respect to damage detection of girder, one of the benchmark problems, using the monitored and field testing acceleration data, this paper describes a damage detection method, based on a residual generated from a subspace-based covariance-driven identification method, to detect the damage, and give relative quantitative damage indexes. This method was applied on both two parts of the given benchmark problem, and then detailed discussions and results on this problem are reported in this paper.

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