Multi-DOFs structural modal parameters identification turns into several SDF structural modal parameters identifications through treating structural output data by Continuous Wavelet Transform. An optimization issue with the objection function of the difference between theoretical formula of wavelet skeleton and the wavelet skeleton calculated from structural output-only data is carried out. The optimal objective value can be gained through searching reasonable modal parameters included in the theoretical formula of wavelet skeleton. And the optimization turns into structural modal parameters identification. Quantum-behaved Particle Swarm Optimization, as a swarm intelligence optimization algorithm, is used in the structural modal parameters identification above to identify the structural modal parameters (frequencies, damp ratios and modal shapes) under ambient excitation just one time. Finally, the modal parameters identification method based on Quantum-behaved Particle Swarm Optimization combined with Continuous Wavelet Transform presented herein is verified by a numerical simulation of a simple-support beam. The results show that methodology herein can effectively identify structural modal parameters under ambient excitation.