Quantum-behaved Particle Swarm Optimization, as a development of Particle Swarm Optimization, is an optimization algorithm based on Swarm Intelligence. Thank to its advantages of less parameter, simple programming, easy to convergence and fast convergence, Quantum-behaved Particle Swarm Optimization received much concern. The minimization of difference between theoretical and test value of frequency response function, the former is a formula including modal parameters, and the later is calculated based on the input and output data of structure, will be adopted as an objection function of optimization issue. The optimal objective value can be gained through searching reasonable modal parameters. Then, the issue of structural modal identification is converted to an optimization issue. During the optimization procedure, Quantum-behaved Particle Swarm Optimization is adopted and the modal parameters are identified. Finally, the modal parameter identification method based on Quantum-behaved Particle Swarm Optimization presented herein will be verified by a numerical simulation of six-story frame structure. The calculation results show that the method can effectively identify the structural modal parameters.