Theoretical research on structural damage alarming of long-span bridges using wavelet packet analysis

The state equation and observation equation of the structural dynamic systems under various analysis scales are derived based on wavelet packet analysis. The time-frequency properties of structural dynamic response under various scales are further formulated. The theoretical analysis results reveal that the wavelet packet energy spectrum （WPES） obtained from wavelet packet decomposition of structural dynamic response will detect the presence of structural damage. The sensitivity analysis of the WPES to structural damage and measurement noise is also performed. The transfer properties of the structural system matrix and the observation noise under various analysis scales are formulated, which verify the damage alarming reliability using the proposed WPES with preferable damage sensitivity and noise robusticity.

Feature extraction and damage alarming using time series analysis

Aiming at the problem of on-line damage diagnosis in structural health monitoring （SHM）, an algorithm of feature extraction and damage alarming based on auto-regressive moving-average （ARMA） time series analysis is presented. The monitoring data were first modeled as ARMA models, while a principalcomponent matrix derived from the AR coefficients of these models was utilized to establish the Mahalanobisdistance criterion functions. Then, a new damage-sensitive feature index DDSF is proposed. A hypothesis test involving the t-test method is further applied to obtain a decision of damage alarming as the mean value of DDSF had significantly changed after damage. The numerical results of a three-span-girder model shows that the defined index is sensitive to subtle structural damage, and the proposed algorithm can be applied to the on-line damage alarming in SHM.

Damage alarming for bridge expansion joints using novelty detection technique based on long-term monitoring data

Damage alarming and safety evaluation using long-term monitoring data is an area of significant research activity for long-span bridges. In order to extend the research in this field, the damage alarming technique for bridge expansion joints based on long-term monitoring data was developed. The effects of environmental factors on the expansion joint displacement were analyzed. Multiple linear regression models were obtained to describe the correlation between displacements and the dominant environmental factors. The damage alarming index was defined based on the multiple regression models. At last, the X-bar control chart was utilized to detect the abnormal change of the displacements. Analysis results reveal that temperature and traffic condition are the dominant environmental factors to influence the displacement. When the confidence level of X-bar control chart is set to be 0.003, the false-positive indications of damage can be avoided. The damage sensitivity analysis shows that the proper X-bar control chart can detect 0.1 cm damage-induced change of the expansion joint displacement. It is reasonably believed that the proposed technique is robust against false-positive indication of damage and suitable to alarm the possible future damage of the expansion joints.

Damage alarming of long-span suspension bridge based on GPS-RTK monitoring

Structure damage identification and alarming of long-span bridge were conducted with three-dimensional dynamic displacement data collected by GPS subsystem of health monitoring system on Runyang Suspension Bridge.First,the effects of temperature on the main girder spatial position coordinates were analyzed from the transverse,longitudinal and vertical directions of bridge,and the correlation regression models were built between temperature and the position coordinates of main girder in the longitudinal and vertical directions;then the alarming indices of coordinate residuals were conducted,and the mean-value control chart was applied to making statistical pattern identification for abnormal changes of girder dynamic coordinates;and finally,the structural damage alarming method of main girder was established.Analysis results show that temperature has remarkable correlation with position coordinates in the longitudinal and vertical directions of bridge,and has weak correlation with the transverse coordinates.The 3%abnormal change of the longitudinal coordinates and 5%abnormal change of the vertical ones caused by structural damage are respectively identified by the mean-value control chart method based on GPS dynamic monitoring data and hence the structural abnormalities state identification and damage alarming for main girder of long-span suspension bridge can be realized in multiple directions.