Nonlinear bridge deflection monitoring and prediction system based on network communication - Lei Yanli; Li Zhiqiang (Nonlinear Engineering, 2023)
In order to study the bridge deflection monitoring and prediction system based on network communication, first, the development status of the bridge deflection monitoring system, overall demand of the system, hardware composition of the system, realization of the system software, and the timely processing and analysis of monitoring data are discussed. Then, the dynamic prediction of the change trend of the external load and the decay information of the structural resistance contained in the deflection monitoring data is carried out, and the prediction function of the external effect of the structure is established at the same time. Finally, a rapid monitoring system specially designed to deal with accidental bridge disasters was developed, and it was installed and applied in the engineering experiment of Chongqing Gaojia Garden Bridge. The deflection data analysis of Gaojia Huayuan Bridge was carried out, and suggestions for the operation and maintenance of the bridge were put forward, and the safety status assessment of the bridge was realized. The results show that the system has strong practicability, real-time monitoring and accuracy. It provides a convenient and accurate way for bridge managers to supervise bridges and formulate specific bridge maintenance plans in a timely manner. During the radio frequency modulation of communication data, harmonic oscillations occur due to the nonlinear characteristics of oscillating data, so it is difficult to improve the wireless ability to modulate and demodulate transmitted data in communications. The traditional method uses neural network fuzzy control distribution estimation harmonic balance algorithm and nonlinear rolling. The performance of dynamic predictive control is poor in quality, harmonic balance, and stability control. An improved harmonic-based communication network is proposed to balance the stability control model of nonlinear communication system, construct nonlinear communication system model, and extract signal and channel characteristics of the communication system. The channel model is designed and the communication network control method is adopted to improve the control algorithm. The simulation results show that the proposed algorithm can be used to improve the stability of nonlinear communication system, reduce the bit error rate, overcome the interference of coherent component in sidelobe, and autocorrelated the impulse response of receiver. The stability of the cumulative output is good, which can overcome the communication error caused by the harmonic oscillation due to the nonlinear characteristics of the oscillating data, and improve the communication quality.