The Study Of Bridge Pre-camber Prediction And Elevation Control Based On Adaptive Filtering

With the rapid development of transportation, continues progress of bridgeengineering technology, bridge construction is expanding in scale. In order to ensurethe construction quality and safety of bridge, and make the geometry and stress statemeet the design requirements, construction monitoring and control of bridge isrequired. Because of the inevitable error of theoretical analysis and practicalconstruction, the core task of the bridge construction monitoring is to predict thefuture state of the structure after the error processing and analysis.In this thesis, the construction monitoring project of the bridge across DeTianrailway is used as an example of engineering practice. The method of pre-camberprediction based on improved adaptive Kalman filtering theory is analyzed to achievethe goal of elevation control.First part of this thesis consists of the necessity of construction monitoring andcontrol, an overview of the continuous beam bridge by cantilever casting and a briefintroduction of the Kalman filter theory.Subsequently, the discrete linear system based basic Kalman filter formula isderived. General characteristics of Kalman filter and the corresponding solutions forthe reasons leading to filter divergence are summarized and analyzed. On this basis,the Sage-Husa adaptive Kalman filter algorithm and the virtual noise compensationtechnology are elaborated. Adaptive filtering algorithm is improved out ofconsideration for the actual situation in bridge monitoring of this thesis.Finally, based on the basic construction control theory of continuous beam bridgeby cantilever casting, the construction monitoring and control program of the bridgeacross DeTian railway is designed and implemented. Stress monitoring of key sectionsduring the construction process ensures construction safety; Deflection monitoring ofeach beam is done to investigate the deformation law, and provide the data base forstate prediction of fellow-up beam. From the geometry control perspective, thepre-camber prediction model is established, improved adaptive Kalman filteralgorithm on the status prediction of the follow-up beam is applied to adjustmentpre-camber and direct the construction, in order to achieve geometry control purposeand ensure closure successful and bridge geometry smooth.Elevation control results in the bottom of the box girder of the construction phase show that the improved adaptive Kalman filter algorithm is effective, steady, and easyfor engineering implementation. It could be popularized.