The majority of bridge condition assessment methods from acceleration data incorporate the use of the Fourier Transform (FT) to obtain or assess damage sensitive features, however the accuracy of the FT’s output for non-linear and non-stationary signals can causes a problem for real-world structural applica-tions. The Hilbert–Huang Transform (HHT) has long been cited as a potential alternative to the FT for non-linear, non-stationary signals and has gathered popularity in the condition assessment of rotating machinery due to its time-frequency-energy representation. On the other hand, instances of the HHT being applied to bridge structures has been less common, predominantly due to the inconsistency of the required Empirical Mode Decomposition (EMD) phase of the methodology. The present paper utilises recent advancements in EMD methodology through the application of Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN), which considerably reduces the undesirable decomposition effects of signal noise contamination. A novel damage parameter is proposed that utilizes the HHT’s instantaneous out-puts to successfully achieve damage identification in a real bridge structure subjected to a progress damage test under single vehicle excitation.