Analysis of Bridge Vibration Extraction Based on Parameters Optimization Variational Modal Decomposition

The bridge vibration data collected by accelerometer contains the event and intensity of the bridge vibration as well as the information of the inherent frequency of the bridge, and the problem of feature extraction of the vibration signal is a prerequisite for the safety monitoring of the bridge. For the problem that the number of modal decompositions and penalty term coefficients affect the extraction of vibration features in the variational modal decomposition, a multi-objective optimization method is proposed, and the optimized algorithm is combined with HHT to extract vibration features. Firstly, the mean envelope entropy and center frequency are used to establish the objective function, determine the number of modal decompositions and penalty coefficients, then the vibration data are processed using the optimized variational modal decomposition method to obtain several individual components, and finally, the vibration event time-frequency map is obtained using HHT. Variational Modal Decomposition (VMD) can accurately extract each component of the simulated signal and outperforms the Empirical Modal Decomposition (EMD) algorithm in terms of anti-mode aliasing. In the vibration information processing of the bridge, the acceleration data processed by VMD-HHT can obtain the individual vibration event time-frequency information, and the bridge vibration frequencies identified by using VMD-HHT differ from the third-order intrinsic frequencies of the bridge by 0.022 Hz, 0.091 Hz, and 0.231 Hz, respectively, indicating that this method has certain reliability.