作者
Simon Laflamme,Filippo Ubertini,Alberto Di Matteo,Antonina Pirrotta,Marcus Perry,Yue Fu,Jian Li,Hao Wang,Tù Hoang,Branko Glišić,Leonard J. Bond,Mauricio Pereira,Yening Shu,Kenneth J. Loh,Yan Wang,Siqi Ding,Xinyue Wang,Xun Yu,Baoguo Han,Yiska Goldfeld,Donghyeon Ryu,Rebecca Napolitano,Fernando Moreu,Giorgia Giardina,Pietro Milillo
摘要
Abstract Structural health monitoring (SHM) is the automation of the condition assessment process of an engineered system. When applied to geometrically large components or structures, such as those found in civil and aerospace infrastructure and systems, a critical challenge is in designing the sensing solution that could yield actionable information. This is a difficult task to conduct cost-effectively, because of the large surfaces under consideration and the localized nature of typical defects and damages. There have been significant research efforts in empowering conventional measurement technologies for applications to SHM in order to improve performance of the condition assessment process. Yet, the field implementation of these SHM solutions is still in its infancy, attributable to various economic and technical challenges. The objective of this Roadmap publication is to discuss modern measurement technologies that were developed for SHM purposes, along with their associated challenges and opportunities, and to provide a path to research and development efforts that could yield impactful field applications. The Roadmap is organized into four sections: distributed embedded sensing systems, distributed surface sensing systems, multifunctional materials, and remote sensing. Recognizing that many measurement technologies may overlap between sections, we define distributed sensing solutions as those that involve or imply the utilization of numbers of sensors geometrically organized within (embedded) or over (surface) the monitored component or system. Multi-functional materials are sensing solutions that combine multiple capabilities, for example those also serving structural functions. Remote sensing are solutions that are contactless, for example cell phones, drones, and satellites. It also includes the notion of remotely controlled robots.