Multi-information fusion tunnel advanced geological forecast water disaster hidden danger judgment method

Abstract

The invention discloses a multi-information fusion tunnel advanced geological forecast water disaster hidden danger judgment method, relates to the technical field of advanced geological forecast, and can collect various tunnel advanced geological forecast method information when implementing advanced geological forecast work. An information fusion scheme formula is realized based on a dynamic weighted average method, various information weight scores are quantified, the weighted average method is to endow each parameter or index with a weight, and then the value of each parameter or index is subjected to weighted average to obtain a comprehensive value; the problems of scattered reference information, much man-made interference, inaccurate judgment and the like of water disaster hidden danger judgment in tunnel advanced geological forecast work by means of geophysical prospecting, drilling and the like are solved, and spatial position characteristics of water-rich region hidden dangers such as karst caves and fractures in front of a tunnel face can be more accurately judged. And the development probability of the water disaster hidden danger in front of the tunnel is quantified, reference is provided for tunnel excavation construction, and the safety risk hidden danger of tunnel excavation construction is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of advanced geological prediction, and particularly to a method for identifying hidden dangers of water disasters in advanced geological prediction of tunnels with multi-information fusion. Background Art

[0002] The advanced geological prediction work can detect the spatial position of hidden dangers of water disasters in front of the tunnel heading face and speculate on the types of hidden dangers.

[0003] The methods commonly used in the advanced geological prediction work of tunnels are mainly divided into the advanced drilling method and geophysical prospecting methods (including seismic wave method, ground penetrating radar method, transient electromagnetic method, direct current method, etc.). Since each type of geophysical prospecting method is based on the difference in a certain property of the geological medium (such as elastic property, conductive property, water content property, etc.), by detecting the physical property differences of the geological medium in front, the development of geological disasters in front is speculated. Therefore, each type of technology has its own scope of application, sensitive characteristics and identification of hidden dangers of water disasters. The advanced drilling method has the advantages of directness and reliability, and can directly reveal the geological conditions in front of the tunnel excavation, but it only has a limited view and cannot comprehensively judge the geological conditions in front and the distribution of water body occurrence positions. The seismic wave method in geophysical prospecting methods has more advantages in identifying the integrity of rock masses, and the detection distance is relatively long, generally reaching 100m, but its ability to identify the development of water bodies is poor; the ground penetrating radar method has good effects on geological disasters such as faults, fracture zones, karst cavities, and groundwater in the surrounding rock in front, but the detection distance is short, generally not exceeding 30m, and it is easily interfered and causes the results to be distorted; the detection distance of the transient electromagnetic method generally does not exceed 80m, and it is sensitive to low-resistivity geological bodies such as water bodies in the surrounding rock in front, but it is more easily interfered; the direct current method has relatively strong anti-interference ability and can identify hidden dangers such as fracture zones and water-rich areas, but the detection distance is short, generally not exceeding 18m. Generally speaking, the advanced drilling method is stable and reliable but obtains less information, and the geophysical prospecting methods obtain rich information, but the on-site data collection process is easily interfered, and in addition, the geophysical prospecting results have multiple solutions, which restricts the accuracy of its results. Thus, the idea of the present invention is introduced, that is, to use a variety of methods for comprehensive analysis, obtain multi-element information and perform fusion and quantification to improve the accuracy of identifying hidden dangers of water disasters in the advanced geological prediction work of tunnels.

[0004] At present, the advanced geological prediction work of tunnels often uses multiple methods simultaneously, mainly geophysical prospecting methods supplemented by the advanced drilling method. However, there is no suitable scheme for fusing and quantifying the multiple information obtained by these methods. Regarding the development of hidden dangers of water disasters in front, it depends on technical staff to collect and analyze various information based on experience to give conclusions. This means that the accuracy of geological prediction is largely restricted by how much information the engineering and technical personnel collect and analyze and their personal experience, which will lead to a large problem of human interference factors in the advanced geological prediction work.

[0005] Therefore, it is urgently necessary to establish a method to collect various types of quantitative geological information as much as possible, analyze these multiple information parameters using information fusion methods, calculate the risk coefficient of the development of water disaster hazards ahead, obtain the probability of the development of water disaster hazards ahead based on this risk coefficient, reduce the interference of some human factors, improve the accuracy of advanced geological forecasting, and achieve the effect of 1 + 1 > 2 in the working method of advanced geological forecasting. Summary of the Invention

[0006] In order to solve the technical problems of advanced geological forecasting in tunnels, the present invention provides a method for discriminating water disaster hazards in advanced geological forecasting of tunnels with multi-information fusion. The following technical solutions are adopted: A method for discriminating water disaster hazards in advanced geological forecasting of tunnels with multi-information fusion includes the following steps: Step 1, collect information from various advanced geological forecasting methods for tunnels; Step 2, extract key information parameters from the information of various advanced geological forecasting methods for tunnels. The key information parameters include the value of intact rock mass, the value at the hazard location, the distance value from the midpoint of the hazard to the tunnel face, and the maximum detection distance value; Step 3, when it is judged that the difference in the distance from the midpoint of the water disaster hazard obtained by any two advanced geological forecasting methods for tunnels to the tunnel face is less than or equal to the set difference threshold, calculate the distance coefficient; Step 4, for each advanced geological forecasting method for tunnels, calculate the probability coefficient of type A hazard, the probability coefficient of type B hazard, and the comprehensive anomaly probability coefficient respectively; Step 5, calculate the weight coefficient of each advanced geological forecasting method for tunnels according to the probability coefficient of type A hazard, the probability coefficient of type B hazard, and the distance coefficient of each advanced geological forecasting method for tunnels; Step 6, use the comprehensive anomaly probability coefficient and weight coefficient of each advanced geological forecasting method for tunnels, and based on the dynamic weighted average method, implement the information fusion method to calculate the risk coefficient of the development of water disaster hazards ahead; Step 7, judge the development probability of the water disaster hazard ahead according to the value of the risk coefficient of the development of the water disaster hazard ahead.

[0007] By adopting the above technical solutions, when implementing the advanced geological prediction work, information on various tunnel advanced geological prediction methods can be collected (such as advanced drilling information, advanced geological prediction information, and surface geophysical exploration information along the tunnel longitudinal axis, etc.). Based on the dynamic weighted average method to implement the information fusion scheme formula, the weight scores of various information are quantified, and the calculated values are substituted into the formula to obtain the development risk coefficient of potential water disasters ahead. The information fusion method formula implemented by the dynamic weighted average method is as follows: The weighted average method assigns a weight to each parameter or index, and then performs a weighted average on the values of each parameter or index to obtain a comprehensive value. The dynamic weighted average method applied in this method dynamically adjusts the weight values based on the on-site geological condition information and the information on the implemented advanced geological prediction methods; It solves the problems of scattered discriminant reference information for potential water disasters, many human interferences, and inaccurate judgments encountered in tunnel advanced geological prediction work using geophysical exploration and drilling and other means, helps to more accurately identify the spatial location characteristics of potential hazards in water-rich areas such as karst caves and fractures in front of the tunnel face, quantifies the development probability of potential water disasters ahead of the tunnel, provides a reference for tunnel excavation construction, and reduces the potential safety risks in tunnel excavation construction.

[0008] Optionally, the information on various tunnel advanced geological prediction methods includes advanced drilling information, information on various geophysical exploration methods, and surface geophysical exploration information along the tunnel longitudinal axis; The information on various tunnel advanced geological prediction methods is specifically as follows: Advanced drilling method: Assign a value of 1 to the complete rock mass section, 0.5 to the potential water disaster section, the distance from the midpoint of the potential water disaster to the tunnel face , the maximum drilling distance ; Direct current resistivity method: The average apparent resistivity value of the complete rock mass , the average resistivity value at the potential water disaster location , the distance from the midpoint of the potential water disaster to the tunnel face , the maximum effective detection distance ; Ground penetrating radar method: The average frequency spectrum characteristic value of the complete rock mass , , the average frequency spectrum characteristic value at the potential water disaster location , , the distance from the midpoint of the potential water disaster to the tunnel face , the maximum effective detection distance ; Transient electromagnetic method: The average apparent resistivity value of the complete rock mass , the average resistivity value at the potential water disaster location , the distance from the midpoint of the potential water disaster to the tunnel face , the maximum effective detection distance ; Seismic wave method: average wave velocity value of intact rock mass , average wave velocity value at potential water hazard location , distance from the midpoint of potential water hazard to the tunnel face , maximum effective detection distance ; For the nth advanced geological prediction method, average wave velocity value of intact rock mass , average wave velocity value at potential water hazard location , distance from the midpoint of potential water hazard to the tunnel face , maximum effective detection distance ; Surface geophysical exploration method: average parameter value of intact rock mass , average parameter value at potential water hazard location , distance from the midpoint of potential water hazard to the tunnel face , maximum effective detection distance in the implementation of advanced detection method .

[0009] By adopting the above technical solutions, assuming that n methods are implemented at the same tunnel face mileage in the advanced geological prediction work, including advanced drilling method, seismic wave method, ground penetrating radar method, transient electromagnetic method, direct current method, etc., and the surface geophysical exploration method (commonly magnetotelluric method) is also implemented in the tunnel investigation and design stage, the variation characteristics of physical property parameters of the tunnel longitudinal axis are obtained. These n + 1 methods obtain n + 1 groups of geological information corresponding to the detection range in front of the tunnel face. According to the numerical distribution characteristics of the geophysical exploration results, information parameters such as the numerical size of the possible potential hazard point location corresponding to each method, the numerical size of the intact rock mass, the distance from the midpoint of the hazard to the tunnel face, and the maximum detection distance can be extracted. The above information parameter settings are used to provide parameters for subsequent calculations.

[0010] Optionally, set the difference threshold to 20%. When it is judged that the distance from the midpoint of potential water hazard obtained by any two tunnel advanced geological prediction methods has a difference less than or equal to 20%, calculate the distance coefficient.

[0011] By adopting the above technical solutions, the difference threshold of 20% is an empirical value. If it is too large, it will cause the fusion of multiple abnormal ranges, resulting in inaccurate positioning of geological hazards. If it is too small, it will cause the fusion effect of multiple methods to deteriorate and weaken the probability of development of each geological hazard.

[0012] Optionally, the distance coefficient is calculated using the following formula: ; where is the distance coefficient.

[0013] Optionally, in step 4 set the probability coefficient of type A hazard to : ; Set the probability coefficient of hidden danger of type B : ; Set the comprehensive anomaly probability coefficient : , where Az and Bz take values of 2 and 3 respectively.

[0014] By adopting the above technical solution, the hidden danger coefficient of type A reflects the relationship between the abnormally developed section and the detection distance of this geophysical exploration method. In view of the fact that the resolution, accuracy and detection distance of the geophysical exploration method are related, the hidden danger coefficient of type A is based on this relationship to evaluate the possibility of the development of abnormal hidden dangers.

[0015] The hidden danger coefficient of type B reflects the relationship between the abnormal value and the normal value. Generally speaking, the greater the difference between the abnormal value and the normal value, the greater the probability of the development of hidden dangers.

[0016] Optionally, in the case of using multiple geophysical exploration methods for construction, a given weight coefficient is used to fuse the results of multiple tunnel advanced geological prediction methods, and the weight coefficient of the corresponding geophysical exploration method is calculated The formula is:

[0017] where: the independent variable a is the probability coefficient of hidden danger of type A, the independent variable b is the probability coefficient of hidden danger of type B, c is the ratio of the distance from the midpoint of the detected water disaster hidden danger to the tunnel face to the actual maximum detection distance of the corresponding geophysical exploration method, and f(a, b, c) is the weight function.

[0018] Optionally, in step 7, based on the comprehensive anomaly probability coefficient of a single geophysical exploration method and the weight coefficient of the corresponding geophysical exploration method, a comprehensive discrimination is carried out to obtain the development risk coefficient Q of the water disaster hidden danger in front, and the discrimination formula is as follows: .

[0019] By adopting the above technical solution, the information fusion method formula is realized by the dynamic weighted average method: the weighted average method is to assign a weight to each parameter or index, and then perform a weighted average on the values of each parameter or index to obtain a comprehensive value.

[0020] It helps to more accurately identify the spatial position characteristics of hidden dangers in water-rich areas such as karst caves and fractures in front of the tunnel face, quantify the development probability of water disaster hidden dangers in front of the tunnel, provide a reference for tunnel excavation construction, and reduce the potential safety risks of tunnel excavation construction.

[0021] Optionally, when the distances from the midpoints of multiple obtained water disaster hidden dangers to the tunnel face When the difference is greater than 20%, assuming that there are multiple abnormal points in the front, the average parameter values of the corresponding abnormal positions are taken according to the geophysical exploration results, the distance coefficient and the comprehensive abnormal probability coefficient are obtained for the abnormal points at different positions, and finally the development risk coefficient Q of the hidden danger of water disasters at the positions of the corresponding multiple abnormal points is calculated respectively.

[0022] By adopting the above technical solution, the multi-source data fusion of the tunnel advanced geological prediction based on the dynamic weighted average method is realized through the above steps, and a quantitative index is obtained.

[0023] Optionally, the value range of the risk coefficient Q is [0, 1]. When its value is 0, it means that there is no development of hidden danger of water disasters within the detected range in the front. When its value is 1, it means that there is development of hidden danger of water disasters within the detected range in the front. When the value is between 0 and 1, it means that there may be development of hidden danger of water disasters in the front. The magnitude of the value of Q is the magnitude of the possibility of the existence of the hidden danger.

[0024] In summary, the present invention includes at least one of the following beneficial technical effects: The present invention can provide a method for discriminating hidden dangers of water disasters in tunnel advanced geological prediction with multi-information fusion. When implementing the advanced geological prediction work, information of various tunnel advanced geological prediction methods is collected, an information fusion scheme formula is realized based on the dynamic weighted average method, the weight scores of various information are quantified, and the development risk coefficient of the hidden danger of water disasters in the front is obtained by substituting into the formula for calculation.

[0025] The weighted average method is to assign a weight to each parameter or index, and then perform a weighted average on the values of each parameter or index to obtain a comprehensive value. The dynamic weighted average method applied in this method is to dynamically adjust the weight value based on the on-site geological condition information and the information of the implemented advanced geological prediction method on the basis of the weighted average; It solves the problems of scattered reference information for discriminating hidden dangers of water disasters, many human interferences, inaccurate judgment, etc. encountered in the tunnel advanced geological prediction work by means of geophysical exploration and drilling, etc., helps to more accurately discriminate the spatial position characteristics of hidden dangers in water-rich areas such as karst caves and faults in front of the tunnel face, quantifies the development probability of hidden dangers of water disasters in front of the tunnel, provides a reference for tunnel excavation construction, and reduces the potential safety risks in tunnel excavation construction. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 is a schematic flow chart of a method for discriminating hidden dangers of water disasters in tunnel advanced geological prediction with multi-information fusion of the present invention; Figure 2 is a schematic diagram of the magnetotelluric sounding result and the schematic diagram of the corresponding implemented advanced geological prediction range in a specific embodiment of the present invention; Figure 3 is a schematic diagram of the advanced geological prediction result of the transient electromagnetic method in a specific embodiment of the present invention; Figure 4 It is a schematic diagram of the TSP result in a specific embodiment of the present invention. Specific Embodiment

[0027] The present invention will be further described in detail below with reference to the accompanying drawings.

[0028] An embodiment of the present invention discloses a method for discriminating hidden dangers of water disasters in advanced geological prediction of tunnels with multi-information fusion.

[0029] Refer to Figures 1-4 , a method for discriminating hidden dangers of water disasters in advanced geological prediction of tunnels with multi-information fusion, includes the following steps: Step 1, collect information of various advanced geological prediction methods for tunnels; Step 2, extract key information parameters from the information of various advanced geological prediction methods for tunnels respectively. The key information parameters include the value of intact rock mass, the value at the hidden danger location, the distance value from the midpoint of the hidden danger to the tunnel face, and the maximum detection distance value; Step 3, when it is judged that the difference in the distance from the midpoint of the water disaster hidden danger obtained by any two advanced geological prediction methods for tunnels to the tunnel face is less than or equal to the set difference threshold, calculate the distance coefficient; Step 4, for each advanced geological prediction method for tunnels, calculate the probability coefficient of type A hidden danger, the probability coefficient of type B hidden danger, and the comprehensive anomaly probability coefficient respectively; Step 5, according to the probability coefficient of type A hidden danger, the probability coefficient of type B hidden danger, and the distance coefficient of each advanced geological prediction method for tunnels, calculate the weight coefficient of each advanced geological prediction method for tunnels; Step 6, use the comprehensive anomaly probability coefficient and weight coefficient of each advanced geological prediction method for tunnels, and based on the dynamic weighted average method, implement the information fusion method to calculate the development risk coefficient of the water disaster hidden danger ahead; Step 7, according to the value of the development risk coefficient of the water disaster hidden danger ahead, judge the development probability of the water disaster hidden danger ahead.

[0030] When implementing the advanced geological prediction work, information of various advanced geological prediction methods for tunnels (such as advanced drilling information, advanced geological prediction information, and ground geophysical exploration information along the tunnel longitudinal axis, etc.) can be collected. Based on the dynamic weighted average method, the information fusion scheme formula is implemented to quantify the weight scores of various information, and then substitute them into the formula for calculation to obtain the development risk coefficient of the water disaster hidden danger ahead. The information fusion method formula is implemented by the dynamic weighted average method: the weighted average method is to assign a weight to each parameter or index, and then perform a weighted average on the values of each parameter or index to obtain a comprehensive value. The dynamic weighted average method applied in this method is to dynamically adjust the weight value based on the on-site geological condition information and the information of the implemented advanced geological prediction method on the basis of the weighted average.

[0031] Solving the problems encountered in tunnel advanced geological prediction work by means of geophysical prospecting and drilling, such as scattered reference information for judging water disaster hidden dangers, many human interferences, and inaccurate judgments, helps to more accurately judge the spatial position characteristics of hidden dangers in water-rich areas such as karst caves and faults in front of the tunnel face, quantify the development probability of water disaster hidden dangers in front of the tunnel, and provide a reference for tunnel excavation construction to reduce the hidden dangers of safety risks in tunnel excavation construction.

[0032] The information of various tunnel advanced geological prediction methods includes advanced drilling information, information of various geophysical prospecting methods, and ground geophysical prospecting information of the tunnel longitudinal axis; The information of various tunnel advanced geological prediction methods is specifically: Advanced drilling method: Assign a value of 1 to the complete rock mass section, 0.5 to the water disaster hidden danger section, the distance from the midpoint of the water disaster hidden danger to the tunnel face and the maximum drilling distance ; DC resistivity method: The average apparent resistivity value of the complete rock mass , the average resistivity value at the water disaster hidden danger , the distance from the midpoint of the water disaster hidden danger to the tunnel face and the maximum effective detection distance ; Ground penetrating radar method: The average frequency spectrum characteristic value of the complete rock mass , , the average frequency spectrum characteristic value at the water disaster hidden danger , , the distance from the midpoint of the water disaster hidden danger to the tunnel face and the maximum effective detection distance ; Transient electromagnetic method: The average apparent resistivity value of the complete rock mass , the average resistivity value at the water disaster hidden danger , the distance from the midpoint of the water disaster hidden danger to the tunnel face and the maximum effective detection distance ; Seismic wave method: The average wave velocity value of the complete rock mass , the average wave velocity value at the water disaster hidden danger , the distance from the midpoint of the water disaster hidden danger to the tunnel face and the maximum effective detection distance ; The nth advanced geological prediction method, the average wave velocity value of the complete rock mass , the average wave velocity value at the water disaster hidden danger , the distance from the midpoint of the water disaster hidden danger to the tunnel face and the maximum effective detection distance ; Ground geophysical prospecting method: The average parameter value of the complete rock mass , Average parameter value at potential water disaster locations , Distance from the midpoint of potential water disaster to the tunnel face , Maximum effective detection distance in the advanced detection method .

[0033] Assume that n methods are implemented at the same tunnel face mileage in the advanced geological prediction work, including advanced drilling method, seismic wave method, geological radar method, transient electromagnetic method, direct current method, etc. And in the tunnel investigation and design stage, surface geophysical exploration method (commonly magnetotelluric method) is also implemented to obtain the variation characteristics of physical property parameters of the tunnel longitudinal axis. These n + 1 methods obtain n + 1 groups of geological information corresponding to the detection range in front of the tunnel face. According to the numerical distribution characteristics of the geophysical exploration results, information parameters such as the numerical size of the possible potential hazard point corresponding to each method, the numerical size of the intact rock mass, the distance from the midpoint of the potential hazard to the tunnel face, and the maximum detection distance can be extracted. Using the above information parameter settings provides parameters for subsequent calculations.

[0034] Let the difference threshold be 20%. When it is judged that the distance from the midpoint of potential water disaster obtained by any two tunnel advanced geological prediction methods to the tunnel face has a difference less than or equal to 20%, calculate the distance coefficient.

[0035] The difference threshold of 20% is an empirical value. If it is too large, it will cause the fusion of multiple abnormal ranges, resulting in inaccurate positioning of geological hazards. If it is too small, it will cause the deterioration of the fusion effect of multiple methods and weaken the probability of the development of each geological hazard.

[0036] The distance coefficient is calculated using the following formula: ; where is the distance coefficient.

[0037] In step 4 Let the probability coefficient of type A potential hazard be : ; Let the probability coefficient of type B potential hazard : ; Let the comprehensive anomaly probability coefficient : , where Az and Bz take values of 2 and 3 respectively.

[0038] The type A potential hazard coefficient reflects the relationship between the abnormal development section and the detection distance of this geophysical exploration method. Considering that the resolution, accuracy of the geophysical exploration method are related to the detection distance, the type A potential hazard coefficient is based on this relationship to evaluate the possibility of abnormal potential hazard development.

[0039] The hidden danger coefficient of type B reflects the relationship between the abnormal value and the normal value. Generally, it is considered that the greater the difference between the abnormal value and the normal value, the greater the probability of hidden danger development.

[0040] In the case of using multiple geophysical prospecting methods for construction, a given weight coefficient is used to fuse the results of multiple advanced geological prediction methods for tunnels, and the weight coefficient of the corresponding geophysical prospecting method is calculated. The formula is: .

[0041] Among them: the independent variable a is the hidden danger probability coefficient of type A, the independent variable b is the hidden danger probability coefficient of type B, c is the ratio of the distance from the midpoint of the detected water disaster hidden danger to the tunnel face to the actual maximum detection distance of the corresponding geophysical prospecting method. During specific calculation , f(a, b, c) is the weight function.

[0042] In step 7, based on the comprehensive abnormal probability coefficient of a single geophysical prospecting method and the weight coefficient of the corresponding geophysical prospecting method, a comprehensive discrimination is carried out to obtain the development risk coefficient Q of the water disaster hidden danger in the front. The discrimination formula is as follows: .

[0043] The information fusion method formula is implemented by the dynamic weighted average method: the weighted average method is to assign a weight to each parameter or index, and then perform a weighted average on the values of each parameter or index to obtain a comprehensive value.

[0044] It helps to more accurately identify the spatial position characteristics of hidden dangers in water-rich areas such as karst caves and fractures in front of the tunnel face, quantify the development probability of water disaster hidden dangers in front of the tunnel, provide a reference for tunnel excavation construction, and reduce the safety risk hidden dangers of tunnel excavation construction.

[0045] When the difference in the distance from the midpoint of the water disaster hidden danger obtained by multiple methods to the tunnel face is greater than 20%, assuming that there are multiple abnormal points in the front, according to the geophysical prospecting results, the average parameter values of the corresponding abnormal positions are taken, the distance coefficient and the comprehensive abnormal probability coefficient are obtained for the abnormal points at different positions, and finally the development risk coefficient Q of the water disaster hidden danger at the positions of the corresponding multiple abnormal points is calculated respectively.

[0046] Through the above steps, the multi-source data fusion of the advanced geological prediction of the tunnel based on the dynamic weighted average method is realized, and a quantitative index is obtained.

[0047] The value range of the risk coefficient Q is [0, 1]. When its value is 0, it means that there is no development of water disaster hidden danger within the detected range in the front. When its value is 1, it means that there is water disaster hidden danger development within the detected range in the front. When the value is between 0 and 1, it means that there is a possibility of water disaster hidden danger development in the front. The magnitude of the value of Q is the magnitude of the possibility of the hidden danger existing.

[0048] The following uses specific embodiments to illustrate the implementation principle of a method for discriminating hidden dangers of water disasters in advanced geological prediction of tunnels with multi-information fusion of the present invention: Taking a limestone tunnel in southwestern Hubei as an example: During the exploration and design stage of the tunnel, ground geophysical exploration was carried out using the magnetotelluric method, and the apparent resistivity distribution of the longitudinal section of the tunnel axis was obtained. At the same time, during the construction stage, the transient electromagnetic method for advanced geological prediction and the TSP advanced seismic wave detection method were implemented, and the apparent resistivity distribution information within 80 m in front of the heading face and the longitudinal and transverse wave velocity information within 80 m in front of the heading face were obtained respectively. The specific result diagrams are shown in Figures 2-4 ; The distance values of the midpoints of hidden dangers from the heading face are divided into two types, one is the hidden dangers discovered by geophysical exploration and the other is the hidden dangers discovered by drilling.

[0049] The hidden dangers discovered by geophysical exploration are the abnormal range areas obtained from the detection results. For example, the low resistivity abnormal area within the generally high resistivity range, or the low velocity abnormal area within the generally high wave velocity range. These abnormal areas are often the locations where geological hidden dangers develop, and most of these abnormal areas are a certain range. Then the midpoint of this range is the distance value of the midpoint of the hidden danger discovered by geophysical exploration from the heading face. For example, Figure 2 the length of the midpoint of section (a) from the heading face, Figure 3 the water disaster hidden danger development section circled by the right box.

[0050] The hidden dangers discovered by drilling are mainly manifested as abnormal sections such as fragmentation, water inrush, karst caves, and muddy interlayers within the intact rock mass section. The distance from the center point range of this section to the heading face is the "distance value of the midpoint of the hidden danger discovered by drilling from the heading face".

[0051] According to the numerical distribution characteristics of the geophysical exploration results, information parameters such as the numerical size of the possible hidden danger point positions corresponding to each method, the numerical size of the intact rock mass, the distance of the midpoint of the hidden danger from the heading face, and the maximum detection distance are extracted. The information parameters are as follows: Transient electromagnetic method: The average apparent resistivity value of the intact rock mass is 345 Ω·m, the average resistivity value at the water disaster hidden danger is 149.5 Ω·m, the distance of the midpoint of the water disaster hidden danger from the heading face is 65 m, and the maximum effective detection distance is 80 m; TSP advanced seismic wave detection method: The average wave velocity value of the intact rock mass is 5100 m / s, the average wave velocity value at the water disaster hidden danger is 4600 m / s, the distance of the midpoint of the water disaster hidden danger from the heading face is 63 m, and the maximum effective detection distance is 80 m; Ground geophysical exploration method (magnetotelluric method): The average parameter value of the intact rock mass is 962 Ω·m, the average parameter value at the water disaster hidden danger is 696 Ω·m, the distance of the midpoint of the water disaster hidden danger from the heading face is 70 m, and the maximum effective detection distance of the advanced detection method is 80 m.

[0052] The specific steps of the information fusion method implemented by the dynamic weighted average method under this condition are as follows: When the distances of the midpoints of water disaster hidden dangers obtained by multiple methods from the heading face are not very different from each other (less than 10%), the distance coefficient LD = 66 m is obtained.

[0053] Obtain the abnormal probability coefficients of each method: For the transient electromagnetic method, the probability coefficient of type A hidden danger YA1 = 0.93, the probability coefficient of type B hidden danger YB1 = 0.71, and the comprehensive abnormal probability coefficient YZ1 = 0.86; for the TSP advanced seismic wave detection method, the probability coefficient of type A hidden danger YA2 = 0.81, the probability coefficient of type B hidden danger YB2 = 0.13, and the comprehensive abnormal probability coefficient YZ2 = 0.58; for the ground geophysical exploration method (magnetotelluric method), the probability coefficient of type A hidden danger YA3 = 0.77, the probability coefficient of type B hidden danger YB3 = 0.35, and the comprehensive abnormal probability coefficient YZ3 = 0.63.

[0054] Obtain the weight coefficients of each method: For the transient electromagnetic method, the weight coefficient k1 = 0.90 is obtained; for the TSP advanced seismic wave detection method, the weight coefficient k2 = 0.92 is obtained; for the ground geophysical exploration method (magnetotelluric method), the weight coefficient k3 = 0.86 is obtained.

[0055] Based on the comprehensive abnormal probability coefficient of a single geophysical exploration method and the weight coefficient of the corresponding geophysical exploration method for comprehensive discrimination, the development risk coefficient Q of the water disaster hidden danger ahead is obtained as 0.71.

[0056] The water disaster risk coefficient ahead is obtained as 0.71, and it is judged that the probability of a water disaster hidden danger developing at 66 m in front of the heading face is relatively high.

[0057] The above are all preferred embodiments of the present invention, and the protection scope of the present invention is not limited thereby. Therefore, all equivalent changes made according to the structure, shape, and principle of the present invention should be covered within the protection scope of the present invention.

Claims

1. A method for identifying potential water disaster hazards in advanced geological prediction of tunnels with multi-information fusion, characterized in that It includes the following steps: Step 1: Collect information on various tunnel advanced geological prediction methods; Step 2: Extract key information parameters from the information on various tunnel advanced geological prediction methods respectively. The key information parameters include the value of intact rock mass, the value at the potential hazard location, the distance value from the midpoint of the potential hazard to the tunnel face, and the maximum detection distance value; Step 3: When it is judged that the difference in the distance from the midpoint of the water hazard potential detected by any two tunnel advanced geological prediction methods to the tunnel face is less than or equal to the set difference threshold, calculate the distance coefficient; Step 4: For each tunnel advanced geological prediction method, calculate the Class A potential hazard probability coefficient, the Class B potential hazard probability coefficient, and the comprehensive anomaly probability coefficient respectively; Step 5: Calculate the weight coefficient of each tunnel advanced geological prediction method according to the Class A potential hazard probability coefficient, the Class B potential hazard probability coefficient, and the distance coefficient of each tunnel advanced geological prediction method; Step 6: Use the comprehensive anomaly probability coefficient and the weight coefficient of each tunnel advanced geological prediction method, and calculate the development risk coefficient of the water hazard potential ahead based on the dynamic weighted average method to realize the information fusion method; Step 7: Judge the development probability of the water hazard potential ahead according to the value of the development risk coefficient of the water hazard potential ahead; 2. A discriminant method for hidden dangers of water disasters in advanced geological prediction of tunnels with multi-information fusion according to claim 1, characterized in that The information on various tunnel advanced geological prediction methods includes advanced drilling information, information on various geophysical exploration methods, and surface geophysical exploration information along the longitudinal axis of the tunnel; Specifically, the information on various tunnel advanced geological prediction methods is as follows: Advanced drilling method: Assign 1 to the intact rock mass section, 0.5 to the water disaster hidden danger section, the distance from the midpoint of the water disaster hidden danger to the tunnel face , and the maximum drilling distance ; Direct current resistivity method: average apparent resistivity value of intact rock mass , average resistivity value at potential water disaster locations , distance from the midpoint of potential water disaster to the tunnel face , maximum effective detection distance ; Ground Penetrating Radar Method: Average Spectrum Feature Value of Intact Rock Mass and , average spectrum feature value at potential water disaster areas and , distance from the midpoint of potential water disaster areas to the tunnel face and maximum effective detection distance ; Transient electromagnetic method: average apparent resistivity value of intact rock mass , average resistivity value at water disaster hidden danger locations , distance from the midpoint of water disaster hidden danger to the tunnel face , maximum effective detection distance ; Seismic wave method: average wave velocity value of intact rock mass , average wave velocity value at potential water hazard locations , distance from the midpoint of potential water hazard to the tunnel face , maximum effective detection distance ; The nth advanced geological prediction method, the average wave velocity value of the intact rock mass , the average wave velocity value at the hidden danger of water disaster , the distance from the midpoint of the hidden danger of water disaster to the tunnel face , the maximum effective detection distance ; Surface geophysical exploration method: average parameter values of intact rock mass , average parameter values at potential water disaster sites , distance from the midpoint of potential water disaster to the tunnel face , maximum effective detection distance in the advanced detection method .

3. A discriminant method for hidden dangers of water disasters in advanced geological prediction of tunnels with multi-information fusion according to claim 2, characterized in that: Set the difference threshold to 20%. When judging the distance from the face of the tunnel to the midpoint of the hidden danger of water disaster obtained by any two advanced geological prediction methods of the tunnel If the difference is less than or equal to 20%, calculate the distance coefficient.

4. A method for identifying hidden dangers of water disasters in advanced geological prediction of tunnels with multi-information fusion according to claim 3, characterized in that: The distance coefficient is calculated using the following formula: ； Among them is the distance coefficient.

5. A discriminant method for hidden dangers of water disasters in advanced geological prediction of tunnels with multi-information fusion according to claim 4, characterized in that: In Step 4 Set the hidden danger probability coefficient of type A as :[[]]END]] ； Set the probability coefficient of potential hazards of type B : ； Set the comprehensive anomaly probability coefficient : , Az and Bz are respectively 2 and 3.

6. A discriminant method for hidden dangers of water disasters in advanced geological prediction of tunnels with multi-information fusion according to claim 5, characterized in that: In the case of using multiple geophysical prospecting methods for construction, the results of multiple advanced geological prediction methods for tunnels are fused by using a given weight coefficient, and the weight coefficient of the corresponding geophysical prospecting method is calculated The formula is: ； where: the independent variable a is the Class A potential hazard probability coefficient, the independent variable b is the Class B potential hazard probability coefficient, c is the ratio of the distance from the midpoint of the detected water hazard potential to the tunnel face to the actual maximum detection distance of the corresponding geophysical exploration method, and f(a, b, c) is the weight function; 7. A method for identifying hidden dangers of water disasters in advanced geological prediction of tunnels with multi-information fusion according to claim 6, characterized in that: In Step 7, based on the comprehensive anomaly probability coefficient of a single geophysical exploration method and the weight coefficient of the corresponding geophysical exploration method, a comprehensive discrimination is made to obtain the development risk coefficient Q of the water hazard potential ahead. The discrimination formula is as follows: 。 8. A method for identifying hidden dangers of water disasters in advanced geological prediction of tunnels with multi-information fusion according to claim 7, characterized in that: When the distance from the midpoint of multiple obtained water disaster hazards to the tunnel face differs by more than 20%, it is assumed that there are multiple abnormal points ahead. According to the geophysical exploration results, the average parameter values at the corresponding abnormal positions are taken, and the distance coefficient and comprehensive abnormal probability coefficient are obtained for the abnormal points at different positions. Finally, the development risk coefficients Q of water disaster hazards at the positions of the corresponding multiple abnormal points are calculated respectively.

9. A discriminant method for hidden dangers of water disasters in advanced geological prediction of tunnels with multi-information fusion according to claim 8, characterized in that: The value range of the risk coefficient Q is [0, 1]. When its value is 0, it means that there is no development of water hazard potential within the forward detection range; when its value is 1, it means that there is development of water hazard potential within the forward detection range; when the value is between 0 and 1, it means that there is a possibility of the development of water hazard potential ahead. The magnitude of the value of Q is the magnitude of the possibility of the existence of the potential hazard.

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