Research On Static Load Detection Of Steel Plate Structure Based On FBG Sensor Array

Unfavorable static load causes serious damage to large-scale engineering structures.Therefore,it is of great significance to test the static load for structural engineering.In order to solve the problem of static load detection in the process of structural service,a high-precision mathematical model for geostatic load prediction is established in this paper.Based on the sensor array constructed by FBG,the mathematical prediction model is studied by using large-scale structural common 304 steel mechanical modeling and optical signal preprocessing methods.The mapping relationship of model is established by the shift of the central wavelength of the reflection spectrum and the variation of the characteristic parameters of the structural state.The prediction algorithm for static load detection of FBG sensor arrays is also studied in this paper.Firstly,the FBG multiplexing technology is briefly explained,and the research status at home and abroad based on FBG sensor array detection technology is introduced.The sensing mechanism of the grating is analyzed,and the influence mechanism of temperature and stress on the FBG is introduced.Secondly,the number of gratings in the FBG sensor array is calculated.Integrated with the mechanical properties of the steel plate structure,the optimal configuration of the grating is located.The surface mount technology is used for grating packaging,and an optical fiber array testing platform is set up.At the same time,the experimental information data of static load positioning and static load detection of each measuring point are preprocessed to construct a sample set.Third,combining particle swarm optimization with least squares support vector machine algorithm,the PSO algorithm is used to optimize the key parameters of the LSSVM model,which improves global search capability of the LSSVM algorithm and overcome the deficiencies of its easy to fall into a local optimal solution.It is applied to static load location detection to establish a mathematical prediction model for static load location detection,and to evaluate and analyze the predictive stability and predictability of the model.Finally,based on the FBG sensor array detection system,compared with thePSO-LSSVM prediction model constructed under the same conditions,the artificial bee colony algorithm is combined with the LSSVM algorithm.By using the characteristics of low ABC control parameters and strong global optimization ability,the prediction algorithm seeks the optimal parameters of the LSSVM in a short time,effectively improving the prediction accuracy of the LSSVM to the global optimum state.The hybrid prediction algorithm,that the LSSVM algorithm is optimized by the artificial bee colony algorithm,is applied to the static load size detection prediction model,and the prediction accuracy of the prediction model is validated and evaluated.