Application of High Order Singular Spectrum Analysis in Deformation Monitoring Data
How to obtain useful information from GNSS time series obtained from monitoring and understand deformation characteristics of deformation monitored objects has become an important research topic in deformation monitoring field. In order to extract bridge de-formation characteristics from GNSS monitoring time series of bridges, and in view of the lack of robustness of singular spectrum analy-sis, this paper proposes to process GNSS monitoring data of long-length steel box girder bridges by using higher-order singularities with better robustness. Quantitative comparison is carried out by two evaluation indexes of information extracted by singular spectrum analysis and high-order singular spectrum analysis. The results show that the time series processed by the higher order singular spec-trum is smoother, the correlation degree with the original time series is higher, and the denoising effect is better. In addition, the standard normal distribution test is carried out on the noise filtered by the high-order singular spectrum analysis. The results show that the noise filtered by the high-order singular spectrum analysis is the standard normal distribution and the bridge deck is stable.
singular spectrum analysishigh order singular spectrum analysisdeformation monitoringdenoisingthe standard normal distribution
万方数据
维普
