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Smart Structures and Systems Volume 29, Number 2, February 2022 , pages 361-374 DOI: https://doi.org/10.12989/sss.2022.29.2.361 |
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Capturing research trends in structural health monitoring using bibliometric analysis |
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Jaesun Yeom, Seunghoo Jeong, Han-Gyun Woo and Sung-Han Sim
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| Abstract | ||
| As civil infrastructure has continued to age worldwide, its structural integrity has been threatened owing to material deteriorations and continual loadings from the external environment. Structural Health Monitoring (SHM) has emerged as a cost-efficient method for ensuring structural safety and durability. As SHM research has gradually addressed an increasing number of structure-related problems, it has become difficult to understand the changing research topic trends. Although previous review papers have analyzed research trends on specific SHM topics, these studies have faced challenges in providing (1) consistent insights regarding macroscopic SHM research trends, (2) empirical evidence for research topic changes in overall SHM fields, and (3) methodological validations for the insights. To overcome these challenges, this study proposes a framework tailored to capturing the trends of research topics in SHM through a bibliometric and network analysis. The framework is applied to track SHM research topics over 15 years by identifying both quantitative and relational changes in the author keywords provided from representative SHM journals. The results of this study confirm that overall SHM research has become diversified and multi-disciplinary. Especially, the rapidly growing research topics are tightly related to applying machine learning and computer vision techniques to solve SHM-related issues. In addition, the research topic network indicates that damage detection and vibration control have been both steadily and actively studied in SHM research. | ||
| Key Words | ||
| bibliometric analysis; centrality index; network analysis; research trend; structural health monitoring | ||
| Address | ||
| (1) Jaesun Yeom, Han-Gyun Woo: School of Business Administration, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea; (2) Seunghoo Jeong: Advanced Railroad Civil Engineering Division, Korea Railroad Research Institute, Uiwang 16105, Republic of Korea; (3) Sung-Han Sim: School of Civil, Architectural Engineering, and Landscape Architecture, Sungkyunkwan University, Suwon 16419, Republic of Korea. | ||