Research On Pattern Recognition Features Of TSP Advanced Detection For Hidden Karst

Tunnel construction has the characteristics of large concealment,many unknown factors,harsh operating environment,and high risk.In recent years,more and more tunnels have been built under the background and rapid pace of China's accelerated infrastructure construction.However,due to the unique factors in the construction of the tunnel,the advance geological forecast of the tunnel becomes indispensable in the construction of the tunnel,so that the life and property safety of the tunnel constructors are properly protected.During the construction of underground tunnels such as tunnels or mining,the problem of hidden karst and the water and sand surge caused by it are also becoming increasingly prominent.From the Malujing Tunnel and the Yesanguan Tunnel of the Yiwan Railway,which opened to traffic at the end of 2010,to the Guanjiao Tunnel,which was announced to be open in 2014,and then to the Yunnan Anshi Tunnel under construction in 2019,the muddy gushing water caused by the hidden karst hidden below the ground in these long tunnels that pass through complex geological conditions such as karst landforms seriously threatens the safety of construction workers.It is urgent to strengthen the exploration of advance geological forecast.With the advancement of advanced geological forecasting technologies such as TSP in China,due to the simple operation method,less time occupation,and less interference with tunnel construction,the TSP method is outstanding in advanced forecasting methods including electrical methods,geological radar detection methods,and infrared water detection technologies.However,TSP and its accompanying exclusive interpretation system TSPwin's interpreted wave velocity diagrams have disadvantages such as difficulty in identifying the features and multi-resolution,etc.In view of this shortcoming,this article deeply researches various types of hidden karsts and establishes related engineering geological models.By referring to its geological models,the relevant geological lithology and genesis are explained and combined with engineering practice.Using specific wave field separation,parameter selection and setting methods,an artificial neural network model test is established,and the model is extracted for identification and prediction,thereby solving the problem that the TSP wave velocity map features are difficult to identify and interpret.It provides ideas for the reinterpretation of the TSP wave velocity map in the future and fills in the blanks in this field.In addition,this paper believes that the ultimate purpose of hidden karst detection and deep interpretation should serve the actual needs of the hidden karst prevention and control project.To this end,this article studies in-depth various types of hidden karst and establishes relevant engineering geological models.By referring to its geological models,this article explains the relevant geological lithology and genesis and combines them with the actual engineering,in order to provide advanced control and prevention preparation measures for karst prevention.