Aiming at the problem of serious vibration interference effect in checkweigher measurement process, a new anti-vibration method of checkweigher using dynamic neural network system identification based on nonlinear auto regressive with exogenous inputs (NARX) model is proposed. The vibration characteristics of the checkweigher system is estimated through the redundant distribution of acceleration sensors. Then, combined with the weighing sensor error caused by the vibration interference in the case of no-load transmission, the dynamic neural network is used to automatically identify the vibration interference signal, and the vibration signal analysis model is established, which is used to match and eliminate the vibration interference in the dynamic weight detection signal. In resonance state, the proposed method is compared with traditional anti-vibration methods such as moving-average filter and adaptive notch filter methods in simulation and experimental. The result proves that the dynamic weighing anti-vibration performance of the multiacceleration sensors is superior. Finally, the operation speeds of 2 m/ s and maximum weighing of 200. 0 g are achieved, which meets the requirements of establishing the national standard “GB/ T 27739- 2011 Automatic Catchweighing Instruments” category XIII scale.