Research On GPR Data Processing Visualization And Disease Risk Assessment Methods

The safety hazards of urban roads and underground spaces pose a serious threat to urban public safety.At present,Ground Penetrating Radar(GPR)has been widely used in the field of urban road and underground space safety detection due to its fast,nondestructive,and efficient advantages.Due to the low level of visualization of conventional GPR 2D profiles,coupled with the lack of unified management,low informatization,and poor sharing of resulting data,this technology is no longer able to meet the requirements of smart cities for road and underground space safety informatization.In response to the above issues,the work carried out in this article is as follows:(1)An improved wavelet threshold de-noising algorithm based on PSO optimization is proposed.The Particle swarm optimization algorithm is used to optimize the selection of wavelet threshold.Through the simulation de-noising experiment on the "bumps" signal,the results show that the signal-to-noise ratio of the de-noising algorithm is 26.1% higher than the soft threshold function and 8.87% higher than the hard threshold function.(2)A Kriging interpolation algorithm based on Particle swarm optimization is proposed.The 3D visualization of the detection data is realized by interpolating the 2D data.Four variogram functions are used to interpolate and fit the simulation data of the ground penetrating radar,which has lower Mean squared error and better interpolation effect than the conventional Kriging interpolation algorithm.(3)Analyzed the inducing factors of road diseases,and based on the Analytic Hierarchy Process(AHP)and fuzzy comprehensive evaluation methods,proposed a risk level assessment method for urban road diseases based on AHP fuzzy comprehensive evaluation,and established a fuzzy comprehensive evaluation model to achieve the assessment of urban road disease risk.(4)Designed and implemented a GPR data processing visualization and disease risk assessment platform,established a disease information database and detection database,achieved data sharing and retrieval,data denoising and visualization,disease risk assessment,and disease localization and data linkage analysis functions.The research results of this article provide effective technical support for the safety of urban roads and underground spaces,and provide monitoring and prediction for the comprehensive management of urban safety,intelligent city management,and other fields.