Structural Health Monitoring Techniques

Structural health monitoring is the practice of continuously or periodically measuring how buildings, bridges, and other infrastructure respond to loads and environmental conditions in order to detect damage before it becomes dangerous. Sensors—increasingly deployed as low-power wireless networks—record vibrations and other signals that engineers analyze using techniques ranging from classical modal identification and model updating to Bayesian inference and deep learning, each aimed at pinpointing where, how severely, and sometimes why a structure has been compromised. A central challenge is separating genuine damage signatures from the confounding effects of temperature, humidity, and traffic variability, which can mimic or mask structural change. Active research is pushing toward more reliable real-time detection in noisy environments, better ways to quantify uncertainty in damage assessments, and methods that remain valid when structures behave nonlinearly.

Works

127,791

Total citations

1,411,246

Keywords

Vibration-based Damage IdentificationWireless SensorsModal IdentificationStructural Damage DetectionModel UpdatingBayesian System Identification