TIME-SERIES-BASED DAMAGE ALARMING METHOD AND ITS APPLICATION IN EXPERIMENTAL BENCHMARK STUDIES

A time-series-based damage alarming method is presented to solve the problem of on-line damage diagnosis in structural health monitoring (SHM). Auto-regressive moving-average (ARMA) models were firstly built according to the monitoring data, and then a principal-component matrix was derived from the AR coefficients of these models to establish the Mahalanobis distance criterion functions. After that, a new damage sensitive feature index DSF was proposed. A hypothesis test involving t-test method was carried out to determine if damage alarming is needed by checking whether or not the mean value of DSF had significant changed after damage. At last, the ambient vibration test of the IASC-ASCE Benchmark structure was taken as a case study. Results show that, the time-series-based index DSF is sensitive to structural minor damage, and the proposed method can be applied in the on-line damage alarming in SHM.