During the past decades, significant efforts have been dedicated to develop reliable methods in structural health monitoring. The health assessment for the target structure of interest is achieved through the interpretation of collected data. At the beginning of the 21st century, the rapid advances in sensor technologies and data acquisition platforms have led to the new era of Big Data, where a huge amount of heterogeneous data are collected by a variety of sensors. The increasing accessibility and diversity of the data resources provide new opportunities for structural health monitoring, while the aggregation of information obtained from multiple sensors to make robust decisions remains a challenging problem. This article presents a comprehensive review of the recent data fusion applications in structural health monitoring. State-of-the-art theoretical concepts and applications of data fusion in structural health monitoring are presented. Challenges for data fusion in structural health monitoring are discussed, and a roadmap is provided for future research in this area.

中文翻译：

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结构健康监测和系统识别的数据融合方法：过去、现在和未来

在过去的几十年中，人们致力于开发可靠的结构健康监测方法。对感兴趣的目标结构的健康评估是通过对收集到的数据的解释来实现的。21世纪初，传感器技术和数据采集平台的飞速发展，催生了大数据的新时代，海量的异构数据由各种传感器采集。数据资源的可访问性和多样性的增加为结构健康监测提供了新的机会，而从多个传感器获得的信息聚合以做出稳健的决策仍然是一个具有挑战性的问题。本文全面回顾了最近在结构健康监测中的数据融合应用。介绍了数据融合在结构健康监测中的最新理论概念和应用。讨论了结构健康监测中数据融合的挑战，并为该领域的未来研究提供了路线图。