Introduction

This chapter explores the foundational principles of structural health monitoring, emphasizing the critical role of system identification techniques in understanding structural behavior from monitoring data. The challenges associated with achieving controlled input and measuring input signals have driven the development of innovative structural health monitoring methodologies. Central to this discussion is the transmissibility functions, a mathematical framework that characterizes output-to-output relationships. They offer advantages over conventional approaches, including the elimination of input measurement requirements, the avoidance of idealized input assumptions, the operation without controlled or artificial excitation, and the facilitation of non-intrusive monitoring. Furthermore, this chapter presents a structured overview of the book, outlining the thematic progression that spans the theoretical foundations of the transmissibility function and its practical applications in structural health monitoring.