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Many traditional methods of damage identification in bridge structures implement numerical models and/or modal parameters as a means of condition assessment. While such techniques can often be effective, they may also succumb to their own intrinsic constraints, such as shortcoming in numerical model calibration to dynamic behaviour and environmental sensitivity of modal parameters. Furthermore, the degree of vibration signal non-stationarity that may be induced due to vehicle excitation can limit the applicability of some common signal processing techniques, such as Fourier transforms. The current study investigates vibration-based approaches to damage identification that circumvent some of these issues. Vibration data obtained from a real bridge structure subjected to a progressive damage test under vehicle induced excitation is used as a test subject. Novel vibration parameters obtained from the raw signals are assessed for their damage detection, localisation and quantification capabilities. Additionally, advanced Empirical Mode Decomposition (EMD) and the Hilbert-Huang Transformation (HHT) is applied to the non-stationary signals for the purpose of damage identification. The investigation shows that damage detection, localisation and quantification is achievable from the vehicle induced vibration signals using the proposed empirical techniques.