The objective of this study is to demonstrate the application of two different system identification methods on the
structural health monitoring of a bridge. The numerical simulation of bridge-vehicle interaction with road surface
roughness is considered in this study for system identification. To identify the bridge dynamic characteristics
Covariance-driven Stochastic Subspace Identification method (SSI-COV) in cooperated with Wavelet Packet Transform
(WPT) decomposition are used to extract the natural frequencies and mode shapes of the system. For comparison, a
popular blind source separation technique called Second Order Blind Identification (SOBI) is also used. Comparison
between these two different identification methods is discussed. It was demonstrated that the bridge natural frequencies
can be identified by the proposed two system identification techniques. Besides, the SOBI algorithm can avoid the
difficulty of determining of parameters by using SSI-COV algorithm, such as system order, row of Hankel matrix, etc.
Finally, a damage scenario of the bridge structure is provided and damage detection algorithms are also proposed to
quantify and locate the damage.