Based On GA Innovation Kalman Filter Application In Deformation Monitoring For Subway

At present countrywide each district lifted the upsurge of construction of the subway,with reasonable monitoring method and monitoring method of data processing ofdeformation body changes a trend to make anticipation, for decision-making offer toprovide strong evidence to support the safety of subway operation, it is very important to.In order to understand the deformation regularity, it is necessary to establish accurate dataprocessing model. According to the characteristics of subway tunnel monitoring, theintroduction of Kalman filtering model, and was used to improve the model, the model isapplied to subway tunnel monitoring data processing for the study of. The main contentsare as follows:The Kalman filter in data processing of deformation monitoring for subway feasibilityanalysis. Because of the common Kalman filter can effectively resist gross errors andfiltering the initial value can usually only be given according to the experience, and thegross error and noise variance is directly related to the filtering accuracy. The article fromthe two aspects of general Kalman filter is improved, based on GA innovation model ofKalman filter. The experiments prove that the model can effectively identify gross errorlocation, to resist gross errors, while the model based on adaptive estimation of noisevariance of state, can avoid the filter divergence.In combination with a subway monitoring data, to establish a common Kalman filterand Kalman filter based on GA innovation dynamic model, the comparison of two kinds ofmodel filtering results, two kinds of model and the measured value trend consistency,describe the deformation trend and the improved model is more close to the measuredvalues of the filtering results.The above studies show that, based on GA innovation of Kalman filter for subwaytunnel deformation monitoring data processing is feasible, and has good practical value.