One of the main challenges for bridge damage identification using monitoring data is to acquire sensitive damage features but insensitive to operational and environmental effects as well as noise. Specifically, the temperature as part of environmental variability can mask structural damages in bridges. Principal Component Analysis (PCA) has been applied here as a well-known and robust technique for removing environmental variability and obtain damage-sensitive indices. As a first aim, PCA is used considering only ambient vibrations and the natural frequencies are considered as damage indicators. As a second objective, PCA in conjunction with Hilbert Huang Transform (HHT) and Variational Mode Decomposition (VMD) are applied to eliminate the environmental influence in transient vibrations due to traffic. The combined methodology is applied to the case of a numerical benchmark by using the ...