Multi-index Decision-making Of Service Performance Assessment And Maintenance And Treatment Scheme Of Subgrade Slope

With the continuous development of social economy,China’s highway construction has achieved leapfrog development in the past 30 years.While developing,highway construction inevitably extends to areas with complex geology,resulting in a large number of subgrade slopes.Disturbances caused by different environmental and engineering factors often lead to deformation and destruction of the rock and soil mass of the highway subgrade,which brings many technical challenges to the safe operation of the highway.Therefore,it is very important to reduce casualties and property losses caused by slope disasters.Through a combination of literature research,on-site inspection,theoretical analysis,and comparison of slope monitoring information,the main research results based on inspection data are as follows:(1)Through on-site inspection,the types of slope diseases can be roughly divided into slope surface diseases,slope disasters,protective retaining structure diseases,and water interception and drainage facilities diseases.Summarize the disease characteristics,maintenance and treatment technology,and comprehensive unit price of maintenance and treatment of each disease.Referring to the slope maintenance guidelines and technical specifications,the corresponding weights for diseases of different scales are given based on the occurrence scale of the disease,and the service performance of the slope is evaluated based on the score.(2)A multi index decision-making model for slope maintenance and treatment plans is constructed based on different maintenance and treatment plans for the same disease.The selection principles and establishment methods of the multi indicator system are introduced in detail.Finally,a decision model of 3 factors and 8 indicators is established.The subjective and objective weights of indicators are determined using improved analytic hierarchy process(AHP)and improved entropy weight method,respectively,and the final weights of indicators are determined through combination weighting.Substitute the final weight into the improved analytic hierarchy process decision-making model,and use the hierarchical total ranking method to rank the maintenance and governance plans to select the optimal plan.(3)For slopes that have undergone disasters and completed maintenance and treatment,it is impossible to accurately evaluate the performance of the slope solely through patrol inspection.It is necessary to use high-precision monitoring equipment combined with slope monitoring systems to obtain real-time monitoring data of the slope,thereby completing the performance evaluation of the slope.A monitoring data processing method based on Lagrange interpolation and Kalman filtering is proposed to address the potential for system errors,instrument errors,and data loss or excessive noise in monitoring data.Based on on-site engineering monitoring information,conduct noise reduction experiments based on python to determine the optimal noise reduction method.The basic principles and applicability of four commonly used slope trend prediction and evaluation models are analyzed.The improved grey GM1.1 model is more applicable for obtaining large amounts of irregular and chaotic slope monitoring data from high-precision sensors in engineering.The performance evaluation of the slope after maintenance and treatment is completed based on the monitoring data after noise reduction through Kalman filtering.