Slope State Detection And Stability Analysis Of Mountain Substation

Yunnan Province,an average elevation of more than 2000 meters,due to the overall high terrain,limited by the more unfavorable terrain and landform conditions,many substations to be built in the mountains,a large number of filling the composition of substation slope.The instability of mountain substation will bring great influence to Yunnan power system,so it is necessary to analyze and monitor the stability of substation slope.At present,in the civil engineering in the use of a lot of techniques and methods to complete the slope structure of the safety monitoring,and continue to improve and optimize the previous most of the monitoring examples are using artificial observation or use a single point of monitoring equipment To complete,and now with the progress of science and technology,the use of more accurate,more reasonable model analysis and automated monitoring to achieve.Based on the above requirements,this paper has carried on the research on slope condition detection and stability analysis of mountain substation.The research content mainly includes the following aspects:(1)GeoStudio Slope/w module was used to establish the simulation analysis model,and the critical slip surface was obtained by searching the sliding surface of the slope,and the critical slip surface was obtained on the critical slip surface.According to the simulation results,the slope of the slope is determined to be 2?6m below the secondary step.(2)According to the applicability of the limit equilibrium method,the Fellenius method,Bishop method and Janbu method are used to analyze the state of the slope structure.The minimum safety factor is 1.304,It is concluded that the monitoring of the sensor is mainly aimed at the location of the subgrade of the backfill soil and the establishment of the slope monitoring model of the mountain substation.(3)According to the actual strain monitoring data of the slope of the mountain substation,the stability of the slope is analyzed.The maximum actual strain value is 110??,and the strain value is within the safe range,and the slope is determined to be stable.Based on RBF neural network algorithm,an analytical model with predictive ability is designed.The comparison between slope prediction value and monitoring value is made.The results show that the pressure variation curve is high and the relative error value is less than 0.1,Change the value is more stable,so as to determine the slope in a stable state.