Over the past two decades, extensive research has been conducted on the application of fiber-optic sensors (FOSs) in structural health monitoring (SHM). In Volume 1 of this book a long-gauge sensing technique for incorporating a proposed areawise sensing, developed by the authors, was introduced. High precision and good durability of the long-gauge sensors were also demonstrated via technical improvements that further enable the applications of optical fiber sensors and carbon fiber sensors. In Volume 2, based on the merits of the long-gauge sensors, the methods that have been developed for processing areawise distributed monitoring data for structural identification are introduced. A discussion follows on how those methods are capable of performing a rich recognition of local and global structural parameters including structural deflections, dynamic characteristics, damages, and loads. Also presented is a three-level method of structural performance evaluation that utilizes monitoring data and identified results.
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Mohammad Noori, a recognized researcher in AI techniques for structural health monitoring, and random vibrations, is an ASME Fellow and professor of mechanical engineering, at California Polytechnic State University. He has also been a distinguished visiting professor at Southeast University, in China and a recipient of Japan Society for Promotion of Science fellowship.
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