LIU Zong-hui, LIU Mao-mao, ZHOU Dong, et al. Recognition method of typical anomalies in karst tunnel construction
based on attribute analysis of ground penetrating radar[J]. 2019, 40(8): 3282-3290.
LIU Zong-hui, LIU Mao-mao, ZHOU Dong, et al. Recognition method of typical anomalies in karst tunnel construction
based on attribute analysis of ground penetrating radar[J]. 2019, 40(8): 3282-3290.DOI: 10.16285/j.rsm.2018.0796.
It is difficult to solve the problem of multi-results when using ground penetrating radar (GPR) to forecast geological anomalies of karst tunnel due to numerous factors
such as the field detection environment
the complexity of karst geology and the interpretation technology and so on. Some representative cases from the previous projects were chosen as the studied object
the attribute characteristics of typical geological anomalies in karst tunnel construction were analyzed and summarized. The results of field tests indicated that the attribute characteristics were closely associated with karst geological anomalies. Among them
the center frequencies of GPR reflection waves in cavity karst caves
karst caves filled with dry loose clay and gravel and anhydrous fracture zones attenuated slowly with time
and the distribution ranges were 90-105 MHz
85-100 MHz
and 70-110 MHz respectively. However
the center frequency of radar reflection waves in karst caves filled with soft plastic clay and water-saturated fracture zones decreased rapidly with time
and the distribution ranges were 60-80 MHz and 40-70 MHz respectively. After studying the method of quantitative representation for attribute features
a calculation method of radar wave absorption and attenuation parameter based on generalized S transform and wavelet spectral simulation was proposed. The analysis results of field tests indicated that each of the characteristic properties could reflect the features of the radar reflection wave of karst geological anomalies in some ways. Different geological anomalies in karst tunnel construction could be distinguished after integration of these characteristic parameters
which could enhance the accuracy of GPR interpretation in karst tunnel advanced geology prediction.