Hybrid Structural Health Monitoring System Using Interstory Drift Angle and Hilbert–Huang Transformation–Based Nonlinearity

A hybrid structural health monitoring (SHM) system is developed by integrating the interstory drift angle method and the Hilbert–Huang transform (HHT) analysis into a comprehensive framework. This approach seeks to provide a comprehensive damage detection capability, seamlessly bridging the assessment of linear behavior under minor excitations with the sensitive detection of nonlinearity and stiffness degradation under severe loads. The proposed SHM system comprises two individual methods: the interstory drift angle method, which mainly focuses on the linear behavior of the structure, and the HHT‐based analysis, which is employed to detect structural nonlinearity. The first part focuses on detecting the displacement of interstory drift in each floor under minor excitation. Data measured by accelerometers installed on the structure are converted into floor displacements, and the drift angles between different floors are calculated, reflecting the health conditions of each floor. The second part utilizes the superior capability of the time–frequency domain of the HHT to analyze the vibration signals measured under external forces. The relationship between structural behavior and nonlinearity is explored by identifying the dynamic parameters of the structure within the time–frequency domain magnification function, thereby defining a damage index (DI). A shaking table test was conducted on a six‐story steel frame model to verify the feasibility of this system. The system achieved more than 97% similarity with measured displacement at low intensities, captured dominant frequency softening from 1.12 to 0.46 Hz, and produced DI values increasing from 0.34 ( healthy ) to 0.79 ( severely damaged ). The results show that interstory drift angles and the HHT‐based nonlinearity can serve as effective cores for SHM, providing an important basis for the safety assessment and maintenance of building structures. By accurately identifying the possible damage of the structures, the developed SHM system can enhance disaster resilience under extreme conditions such as earthquakes.