ACOUSTIC EMISSION-BASED DAMAGE DETECTION IN STEEL FRAMED STRUCTURE- A REVIEW

Q4 Engineering
Mr. Anupam Kumar Biswas, Dr. Aloke Kumar Datta, Dr. Pijush Topdar, Dr. Sanjay Sengupta
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引用次数: 0

Abstract

Steel structures are commonly utilized in vast areas in industries, and also now a days they are used in residential settings as well. Structures made of steel is a better alternative as their constructions have high strength, light weight and quick compared to other construction materials. Steel structure degradation is frequently related to an engineering system's underperformance and leads to collapse. Therefore, it is essential to identify the problem and take remedial steps to make sure that structures function as intended throughout their design lives. Among the best non-destructive assessment methods for finding problems is acoustic emission (AE). The current study evaluates the available literature on this method in a few major areas and discusses historical advances in each category. The pros and cons of each approach are discussed, and future study directions are suggested. This review examines the fundamental Acoustic Emission techniques and contemporary research to identify damage in different types of steel structures using various localization approaches. This research aims to find the ideal placement for a real-time sensor to detect deterioration in a steel-framed construction. Finally, the artificial intelligence techniques used to identify deterioration in the steel frame construction are discussed.
基于声发射的钢框架结构损伤检测研究进展
钢结构在工业中广泛应用,现在也被用于住宅环境中。钢结构是一个更好的选择,因为与其他建筑材料相比,它们的结构强度高,重量轻,速度快。钢结构的退化往往与工程系统性能不佳有关,并导致其倒塌。因此,必须确定问题并采取补救措施,以确保结构在其设计寿命期间按预期功能运行。声发射(AE)是发现问题的最佳无损评估方法之一。目前的研究在几个主要领域评估了关于这种方法的现有文献,并讨论了每个类别的历史进展。讨论了每种方法的优缺点,并提出了未来的研究方向。本文综述了基本声发射技术和当前研究,以识别不同类型的钢结构损伤,使用各种定位方法。这项研究的目的是找到一个实时传感器的理想位置,以检测钢框架结构的恶化。最后,讨论了用于识别钢架结构劣化的人工智能技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
0.80
自引率
0.00%
发文量
43
审稿时长
4 weeks
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