Adaptive Stochastic Resonance Method Based on Quantum Genetic Algorithm and its Application in Dynamic Characteristic Identification of Bridge GNSS Monitoring Data

Abstract

Bridge dynamic monitoring based on GNSS has become an important means of monitoring bridge structure. GNSS dynamic monitoring signals are often overwhelmed by strong noises and multipath errors. Thus the conventional data processing methods such as Fourier transform, wavelet analysis, and others have poor denoising effect or obtain unconspicuous dynamic characteristics from weak vibration signals. To solve this problem, the present study proposes a new adaptive stochastic resonance method based on quantum genetic algorithm with known frequency as optimal parameter. Analyzing the simulation signals not only verifies the validity and scientificity of the method, but also analyzes its frequency extraction effect in the approximate error range of target frequency with different noise intensity. A notable bridge vibration frequency is obtained when the new method is applied to analyze the bridge dynamic monitoring data based on GNSS.