Applications of Smart Materials in Structural Health Monitoring

Author(s):  
Hui-Ru Shih ◽  
Wei Zheng ◽  
Wilbur L. Walters

Structural Health Monitoring (SHM) is an emerging technology devoted to monitoring and assessing of structural health. SHM emerged from the wide field of smart structures and laterally encompasses disciplines such as structural dynamics, materials and structures, non-destructive testing, sensors and actuators, data acquisition, signal processing and possibly much more. To stimulate students’ desire for pursing advanced technologies and prepare them well for their future careers, engineering and technology educators need to dedicate their efforts to educate the students with this emerging technology. At Jackson State University (JSU), three course modules (Smart Materials and Structures, Signals & Data Acquisition Systems, and Lamb Waves Generation & Detection) have been added to the existing courses to help undergraduate students develop hands-on experience for understanding this technology. The course modules do not assume prior knowledge of software and hardware, and they all follow an applied, hands-on approach. These three course modules allow students to gain insight into the SHM as well as to become knowledgeable users of the instrumentation.

2010 ◽  
Vol 2010 ◽  
pp. 1-13 ◽  
Author(s):  
M. Sun ◽  
W. J. Staszewski ◽  
R. N. Swamy

Structural Health Monitoring (SHM) aims to develop automated systems for the continuous monitoring, inspection, and damage detection of structures with minimum labour involvement. The first step to set up a SHM system is to incorporate a level of structural sensing capability that is reliable and possesses long term stability. Smart sensing technologies including the applications of fibre optic sensors, piezoelectric sensors, magnetostrictive sensors and self-diagnosing fibre reinforced composites, possess very important capabilities of monitoring various physical or chemical parameters related to the health and therefore, durable service life of structures. In particular, piezoelectric sensors and magnetorestrictive sensors can serve as both sensors and actuators, which make SHM to be an active monitoring system. Thus, smart sensing technologies are now currently available, and can be utilized to the SHM of civil engineering structures. In this paper, the application of smart materials/sensors for the SHM of civil engineering structures is critically reviewed. The major focus is on the evaluations of laboratory and field studies of smart materials/sensors in civil engineering structures.


Author(s):  
Hui-Ru Shih ◽  
Albert C. McIntyre

Structural Health Monitoring (SHM) is the process of monitoring and assessing the state of health for aerospace, civil, and mechanical engineering infrastructure. SHM offers the opportunity to reduce inspection efforts and optimize maintenance and mission planning. SHM is a highly emerging field of technology. It brings together a variety of disciplines. To stimulate students’ desire for pursuing advanced study in science, technology, engineering, and mathematics (STEM) and well prepare them for their future careers, STEM educators need to dedicate their efforts to educate the students with this emerging technology. SHM is a field that requires a significant amount of background knowledge to build upon. At Jackson State University (JSU), four course modules (Smart Materials, Data Acquisition Systems, Lamb Waves, and Wavelet Analysis) have been developed and integrated into an existing course to help undergraduate students gain practical experience and have a firm grasp on this emerging vital tool. After taking the class, several students were selected to participate in a research activity sponsored by the Center for Undergraduate Research (CUR) at JSU. This paper describes the content covered in the modules as well as summarizes student perceptions of their learning and research experiences.


Actuators ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 101
Author(s):  
Abdul Aabid ◽  
Bisma Parveez ◽  
Md Abdul Raheman ◽  
Yasser E. Ibrahim ◽  
Asraar Anjum ◽  
...  

With the breadth of applications and analysis performed over the last few decades, it would not be an exaggeration to call piezoelectric materials “the top of the crop” of smart materials. Piezoelectric materials have emerged as the most researched materials for practical applications among the numerous smart materials. They owe it to a few main reasons, including low cost, high bandwidth of service, availability in a variety of formats, and ease of handling and execution. Several authors have used piezoelectric materials as sensors and actuators to effectively control structural vibrations, noise, and active control, as well as for structural health monitoring, over the last three decades. These studies cover a wide range of engineering disciplines, from vast space systems to aerospace, automotive, civil, and biomedical engineering. Therefore, in this review, a study has been reported on piezoelectric materials and their advantages in engineering fields with fundamental modeling and applications. Next, the new approaches and hypotheses suggested by different scholars are also explored for control/repair methods and the structural health monitoring of engineering structures. Lastly, the challenges and opportunities has been discussed based on the exhaustive literature studies for future work. As a result, this review can serve as a guideline for the researchers who want to use piezoelectric materials for engineering structures.


2021 ◽  
pp. 147592172110064
Author(s):  
Yuequan Bao ◽  
Jian Li ◽  
Tomonori Nagayama ◽  
Yang Xu ◽  
Billie F Spencer ◽  
...  

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.


Author(s):  
Milton Muñoz ◽  
Remigio Guevara ◽  
Santiago González ◽  
Juan Carlos Jiménez

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.


Author(s):  
Esraa Elhariri ◽  
Nashwa El-Bendary ◽  
Shereen A. Taie

Feature engineering is a key component contributing to the performance of the computer vision pipeline. It is fundamental to several computer vision tasks such as object recognition, image retrieval, and image segmentation. On the other hand, the emerging technology of structural health monitoring (SHM) paved the way for spotting continuous tracking of structural damage. Damage detection and severity recognition in the structural buildings and constructions are issues of great importance as the various types of damages represent an essential indicator of building and construction durability. In this chapter, the authors connect the feature engineering with SHM processes through illustrating the concept of SHM from a computational perspective, with a focus on various types of data and feature engineering methods as well as applications and open venues for further research. Challenges to be addressed and future directions of research are presented and an extensive survey of state-of-the-art studies is also included.


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