Real-time structural damage detection using wireless sensing and monitoring system

Abstract

A wireless sensing system is designed for application to structural monitoring and damage detection applications. Embedded in the wireless monitoring module is a two-tier prediction model, the auto-regressive (AR) and the autoregressive model with exogenous inputs (ARX), used to obtain damage sensitive features of a structure. To validate the performance of the proposed wireless monitoring and damage detection system, two near full scale single-story RC-frames, with and without brick wall system, are instrumented with the wireless monitoring system for real time damage detection during shaking table tests. White noise and seismic ground motion records are applied to the base of the structure using a shaking table. Pattern classification methods are then adopted to classify the structure as damaged or undamaged using time series coefficients as entities of a damage-sensitive feature vector. The demonstration of the damage detection methodology is shown to be capable of identifying damage using a wireless structural monitoring system. The accuracy and sensitivity of the MEMS-based wireless sensors employed are also verified through comparison to data recorded using a traditional wired monitoring system.

A damage detection algorithm integrated with a wireless sensing system

“…After the host computer receives the selected frequency spectrum segments from all the WSUs, the FRF segments are estimated. The variations of elemental stiffness matrices Δκ can be calculated using these FRF segments by equation (15). Since the necessary information for FRFCM to detect damage of the structure could be accessed automatically right after a ground excitation, i.e.…”

“…This prototype was applied to structural health monitoring successfully [15]. Figure 1 shows the overall hardware design of the prototype wireless sensing unit with an optional off-board auxiliary module for conditioning analog sensor signals.…”

“…The energy efficiency gained from local data interrogation is also explored in detail. The same damage detection algorithm is later successfully applied to detect damage of nearly full-scale single-story reinforcement-concrete frames [15]. Gao et al [16] apply a flexibilitybased damage detection method to assess local health condition of a truss-structure.…”

“…After the variations of elemental stiffness components in equation (13) k is not known analytically if no FE model is constructed, here the components in the identified stiffness matrix using equation (11) can be utilized to calculate the stiffness reduction ratio. In summary, the FRFs of the system prior and posterior to damage as well as the system matrices including the mass matrix, damping matrix and stiffness matrix of the undamaged structure are required to solve equation (15). However, to obtain all the well-estimated or well-updated system matrices individually is not an easy task.…”

Multiscale Acceleration-Dynamic Strain-Impedance Sensor System for Structural Health Monitoring

“…The development of wireless sensor nodes as much as the selection of embedding SHM algorithms are important topics for the autonomous SHM [11][12][13][14][15]. To date, many damage monitoring algorithms have been developed for detecting the location and the severity of damage in structures [16][17][18][19][20].…”