| Abstract: |
In recent years, damage to structures resulting from deterioration over time has become a major social issue. With regard to structural inspections, it is common for people to conduct inspections visually or by means of a hammering method, but the development of IT has led to the expansion of structural health monitoring using smart sensing and sensor networks. Structural health monitoring utilizes, for example, sensors embedded in smartphones, drones, images from cameras that utilize advanced signal processing, and the like. The object of such systems is not to investigate narrow areas in a concentrated manner, but to efficiently investigate wide areas.
Structural health monitoring is a technology in which sensors are installed in structures to sense the physical quantity of vibrations and the like, and various signal processing methods are employed to dynamically diagnose accumulated damage and the locations and severity of the deterioration, whereby the future progression of damage is predicted. One such method is a method in which sensors are installed to diagnose structural performance from response waveforms generated due to minor earthquakes, microtremors, and the like. This performance information makes it possible to conduct preventative maintenance by identifying the locations where damage could occur in the event of a major earthquake, a typhoon, or the like.
In this study, we investigated the implementation of an efficient, wide-area structural health monitoring system by using optical fibers over existing communication cables. Thus, we investigated processing using edge computing and conducted vibration measurements using existing optical fibers for communication, thereby testing the effectiveness in the case of earthquake vibrations. By distributively measuring the expansion and contraction of optical fibers from 0 to 20 Hz during an earthquake, we were able to visualize the ease of shaking of the ground and the structures. |