Using an improved LevenbergMarquardt algorithm and based on the experimental data,the BP neural network is trained to study and simulate the damping performance of the particle impact vibration system,and the results are compared with those from conventional calculation methods.It is demonstrated that the LevenbergMarquardt algorithm can greatly speed up the learning process and therefore reduce the training time,and is suitable for real time system identification.The recognized models agree qualitatively well with those in the literatures.