CN112965136B - Multi-means advanced detection method for water-rich karst tunnel - Google Patents
Multi-means advanced detection method for water-rich karst tunnel Download PDFInfo
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Abstract
The invention relates to a multi-means advanced detection method for a water-rich karst tunnel, which comprises the following steps: obtaining structural topography in a tunnel region, predicting bad geological structures and engineering tunnel conditions; geometric modeling is carried out, and a three-dimensional tunnel geological generalized model is determined; determining corresponding layout parameters, and carrying out advanced drilling layout on tunnel face; performing cross-hole CT scanning, in-hole geological radar detection and induced polarization method detection on the tunnel face with complete arrangement, and respectively determining wave velocity distribution images between two advanced drilling holes, wave velocity maps in the advanced drilling holes and geological electricity data; determining a position interval range of a predicted poor geological structure according to the wave velocity distribution image, the wave velocity map in the drill hole and the data consistency of geological electricity data in multiple directions; and detecting according to the range of the position interval, and planning a construction scheme. The invention adopts multi-means advanced geological detection, combines three information of earthquake waves, electromagnetic waves and an electric method, effectively reduces the risk of tunnel construction and ensures safe construction.
Description
Technical Field
The invention relates to the technical field of tunnel detection, in particular to a multi-means advanced detection method for a water-rich karst tunnel.
Background
At present, china obtains remarkable construction results, the material demand of each region is increased continuously, and the problems of insufficient highway transportation capacity and transportation cost can prevent the regional economy from developing. In southwest areas of China, the topography is complex, and in order to reduce the cost while protecting the environment, tunnels are adopted for mountain area construction, so tunnel engineering becomes an indispensable key item in engineering construction.
In the construction process of tunnel engineering, various complex geology conditions exist, and along with the occurrence of more and more water burst mud geological structures, the construction safety of the tunnel is strictly clamped. The time for finishing the tunnel has a vital control effect on the traffic time of the highway, the construction progress is sought once, the construction specification is violated, geological disasters such as collapse of the tunnel or mud bursting and water rushing can be caused when serious, the construction progress is affected, and the personal safety is threatened when serious. Therefore, before the tunnel is constructed, the tunnel is subjected to preconditions such as surveying and hydrologic investigation, however, due to the variability and complexity of geological structures, obvious differences exist between a surveying structure and an actual structure, the actual situation is not reflected, and effective conclusions are difficult to obtain through surveying on the geological problems existing in the construction engineering. While the uncertain geological conditions are often invisible "bombs" in construction, there is a high probability that significant damage will be caused to the project. Not only can the construction period be influenced, but also the engineering investment is improved; the equipment is more likely to be damaged, and the safety of constructors is threatened. Therefore, for tunnel construction, the geological forecast of the tunnel is controlled, and the geological condition in front of the tunnel is obtained through an effective detection means.
Specifically, in a complicated surrounding rock geological structure area in a mountain area, under the action of crustal movement, surrounding rock weathering, underground water and the like, the surrounding rock is easy to produce a gushing water geological disaster due to the structural characteristics of the surrounding rock. In the prior art, a highway tunnel is subjected to large-scale blind scanning or geological analysis by combining geology, but due to movement of the crust and flowing of groundwater, geological structures are complicated, so that a single detection mode is often incapable of obtaining more accurate geological information, along with the promotion of construction, the originally unstable surrounding rock structure is unstable due to disturbance of the surrounding rock structure in the construction process by adding manpower, thus a gushing water geological disaster occurs, loss or damage occurs to people, materials, machines and the like in a construction site, and the promotion of engineering construction period is caused, so that the passively reinforced engineering quantity of tunnel engineering is increased, and the risk of instability of the surrounding rock structure is caused. Therefore, the method for quickly, simply, conveniently and accurately detecting the advanced poor geological structure of the tunnel is particularly urgent.
Disclosure of Invention
In view of the foregoing, it is necessary to provide a multi-means advanced detection method for a water-rich karst tunnel, so as to solve the problem of how to realize rapid, simple and accurate advanced detection of poor geological structures of the tunnel.
The invention provides a multi-means advanced detection method for a water-rich karst tunnel, which comprises the following steps:
obtaining structural topography in a tunnel region, predicting bad geological structures and engineering tunnel conditions;
geometric modeling is carried out according to the structural terrain, the predicted poor geological structure and the engineering tunnel condition, and a three-dimensional tunnel geological generalized model is determined;
determining layout parameters corresponding to the three-dimensional tunnel geological generalized model, and carrying out advanced drilling layout on tunnel faces according to the layout parameters to determine the fully laid tunnel faces;
performing cross-hole CT scanning, in-hole geological radar detection and induced polarization method detection on the tunnel face with the complete arrangement, and respectively determining wave velocity distribution images between two advanced drilling holes, wave velocity maps in the advanced drilling holes and geological electricity data;
determining a position interval range of the predicted poor geological structure according to the wave velocity distribution image, the wave velocity map in the drill hole and the data consistency of the geological electricity data in a plurality of directions;
and detecting according to the position interval range, determining an actual poor geological structure, and planning a construction scheme through the actual poor geological structure.
Further, the layout parameters include at least one of a size of the tunnel face, a drilling position, a number of drilling holes, a drilling hole depth, a drilling angle, and a hole pitch.
Further, the determining the layout parameters corresponding to the three-dimensional tunnel geological generalized model includes: and setting the layout parameters according to the boundary data and the detection requirements of the three-dimensional tunnel geological generalized model so as to lay out a plurality of advanced drilling holes.
Further, the boundary data includes a three-dimensional spatial dimension of the three-dimensional tunnel geological generalized model, an arrangement spatial structure test layout, and a spatial relationship of each test instrument with respect to each other.
Further, performing cross-hole CT scanning, in-hole geological radar detection and induced polarization detection on the tunnel face with complete layout, and determining a wave velocity distribution image between two advanced drilling holes, a wave velocity map in the advanced drilling holes and geological electricity data respectively includes:
exciting seismic waves to perform cross-hole CT between every two advanced drilling holes of the tunnel face;
and determining the wave velocity distribution image between every two advanced drilling holes according to the first arrival travel time information of the seismic waves.
Further, performing cross-hole CT scanning, in-hole geological radar detection and induced polarization detection on the tunnel face with complete layout, and determining a wave velocity distribution image between two advanced drilling holes, a wave velocity map in the advanced drilling holes and geological electricity data respectively includes:
transmitting a pulse electromagnetic wave signal to the front of the tunnel face, wherein when the pulse electromagnetic wave signal meets a detection target, a corresponding reflection signal is generated;
and determining the wave velocity diagram in the advanced drilling corresponding to the advanced drilling according to the reflected signal.
Further, performing cross-hole CT scanning, in-hole geological radar detection and induced polarization detection on the tunnel face with complete layout, and determining a wave velocity distribution image between two advanced drilling holes, a wave velocity map in the advanced drilling holes and geological electricity data respectively includes: and sequentially detecting the advanced drilling holes of the tunnel face by using an induced polarization method, and determining the corresponding geological electricity data.
Further, the determining the location interval range of the predicted poor geological structure according to the wave velocity distribution image, the intra-borehole wave velocity map and the data consistency of the geological electrical data in a plurality of directions comprises:
forming corresponding positioning information according to the wave velocity distribution image and the geological electricity data;
and combining the positioning information, performing geological reverse reasoning in front of the tunnel face by a numerical reverse calculation mode, and determining the range of the position interval.
Further, the determining the location interval range of the predicted poor geological structure according to the wave velocity distribution image, the intra-borehole wave velocity map and the data consistency of the geological electrical data in a plurality of directions further comprises:
and combining the wave velocity distribution image and the wave velocity diagram in the drilling hole, and performing verification analysis on the vertical plane and the horizontal plane.
Further, the determining the location interval range of the predicted poor geological structure according to the wave velocity distribution image, the intra-borehole wave velocity map and the data consistency of the geological electrical data in a plurality of directions further comprises:
and according to the geological electricity data, carrying out verification analysis on the wave velocity distribution image and the wave velocity diagram in the drilling.
Compared with the prior art, the invention has the beneficial effects that: firstly, effectively acquiring structural topography, predicting bad geological structures and engineering tunnel conditions; then, combining multiple factors to build a three-dimensional tunnel geological generalization model so as to reflect the basic characteristics of the tunnel; furthermore, based on a three-dimensional tunnel geological generalization model, setting layout parameters, and primarily determining advanced drilling layout of a tunnel face; then, on the tunnel face with the drilled holes, multi-means advanced geological detection is carried out, and by utilizing a plurality of detection methods and combining seismic wave information, radar information and electromagnetic information, mutual verification of data is realized, more accurate geological features are obtained, and therefore accurate prediction of the position interval range of the poor geological structure is realized; and finally, detecting according to the range of the position interval, and determining the actual bad geological structure, so that the whole construction scheme is planned, and the tunnel excavation stability meets the engineering requirement. In summary, the invention considers the physical and mechanical parameter changes of rock and soil before and after engineering excavation, performs geological exploration on a tunnel construction area before excavation, fully analyzes the structure of the initial state of the rock and soil in the area, avoids the great reduction of the rock and soil strength caused by deformation and softening of surrounding rock of the tunnel after excavation, adopts multi-means advanced geological detection, combines three information of earthquake waves, electromagnetic waves and an electric method, effectively reduces the tunnel construction risk, analyzes surrounding rock geological strips at multiple angles, avoids sudden geological disasters in the tunnel excavation, endangers safety, and reduces construction risk and loss.
Drawings
FIG. 1 is a schematic flow chart of a multi-means advanced detection method for a water-rich karst tunnel provided by the invention;
FIG. 2 is a flow chart of the seismic wave detection method provided by the invention;
FIG. 3 is a side view of a vertical plane CT unit provided by the present invention;
FIG. 4 is a schematic flow chart of a radar detection method according to the present invention;
FIG. 5 is a schematic layout diagram of tunnel face provided by the present invention;
FIG. 6 is a schematic diagram of the present invention for providing an in-hole address radar;
FIG. 7 is a schematic flow chart of an electromagnetic detection method provided by the invention;
FIG. 8 is a schematic diagram of the induced polarization phenomenon according to the present invention;
fig. 9 is a schematic flow chart of determining a location interval range provided by the present invention.
Detailed Description
Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form a part hereof, and together with the description serve to explain the principles of the invention, and are not intended to limit the scope of the invention.
Example 1
The embodiment of the invention provides a multi-means advanced detection method for a water-rich karst tunnel, and in combination with fig. 1, fig. 1 is a flow schematic diagram of the multi-means advanced detection method for the water-rich karst tunnel, where the multi-means advanced detection method for the water-rich karst tunnel includes steps S1 to S6:
in step S1, obtaining structural topography in a tunnel region, predicting bad geological structures and engineering tunnel conditions;
in step S2, geometric modeling is carried out according to structural terrain, predicted bad geological structures and engineering tunnel conditions, and a three-dimensional tunnel geological generalized model is determined;
in step S3, determining layout parameters corresponding to the three-dimensional tunnel geological generalized model, and carrying out advanced drilling layout on tunnel faces according to the layout parameters to determine the fully laid tunnel faces;
in step S4, cross-hole CT scanning, in-hole geological radar detection and induced polarization method detection are carried out on the tunnel face with complete arrangement, and a wave velocity distribution image, an in-hole wave velocity image and geological electricity data between two advanced drilling holes are respectively determined;
in step S5, determining a position interval range of the predicted poor geological structure according to the wave velocity distribution image, the wave velocity diagram in the drilling hole and the data consistency of the geological electricity data in a plurality of directions;
in step S6, detection is performed according to the range of the location interval, an actual poor geological structure is determined, and a construction scheme is planned through the actual poor geological structure.
In the embodiment of the invention, firstly, structural topography, predicted bad geological structure and engineering tunnel conditions are effectively obtained; then, combining multiple factors to build a three-dimensional tunnel geological generalization model so as to reflect the basic characteristics of the tunnel; furthermore, based on a three-dimensional tunnel geological generalization model, setting layout parameters, and primarily determining advanced drilling layout of a tunnel face; then, on the tunnel face with the drilled holes, multi-means advanced geological detection is carried out, and by utilizing a plurality of detection methods and combining seismic wave information, radar information and electromagnetic information, mutual verification of data is realized, more accurate geological features are obtained, and therefore accurate prediction of the position interval range of the poor geological structure is realized; and finally, detecting according to the range of the position interval, and determining the actual bad geological structure, so that the whole construction scheme is planned, and the tunnel excavation stability meets the engineering requirement.
It should be noted that, taking advanced detection of the front of the face of the water burst section of the entrance of the nine-roof mountain tunnel as an example, the structural topography is judged as follows: carrying out geological investigation of a tunnel construction area and summarizing lithology analysis of water burst sections (ZK281+850-ZK281+975, KK281+860-KK282+160) of the tunnel of the Jiuding mountain: the surrounding rock grade of the area is V1 grade. The rock is mainly an invading rock consisting of gray limestone, and is broken and corroded by multiple weathered limestone, and is penetrated with full weathered granite, and the rock mass is in a broken and loose structure; therefore, the stability of the surrounding rock of the structure of the tunnel is extremely poor when the tunnel is excavated, collapse or softening of the structural contact zone occurs frequently along with construction, so that when the underground water rises sharply in a rainy season, larger water gushes and collapse of the tunnel can be caused, and the water enrichment of the surrounding rock structure is better due to development of surrounding rock cracks, so that the construction risk in the rainy season is extremely high. The ground water in the (ground water) tunnel area is fourth series pore water type and bedrock fissure water and carbonate karst water type, the fourth series pore water is mostly reserved in the fourth series loose soil body, mostly appears in a diving form, and the water quantity is very small; the carbonate karst water and the bedrock fracture water are reserved in the polar karst fracture of the joint fracture of the rock stratum, and the water quantity is not large. Groundwater is mainly supplemented by atmospheric precipitation and infiltration of surrounding surface water, and is collected and excreted in the valley low-lying areas in the manner of underground runoff. (surface water) groundwater was exposed in a spring point type in a pit of 2800m altitude below the highest mountain top of a nine-roof mountain tunnel and 2600m altitude below the high mountain top.
Preferably, before step S1, geological investigation is performed on the surrounding rock structure in the tunnel site selection area before tunnel excavation, and summary analysis is performed on the lithology in the area, so as to obtain relevant physical performance parameters of the surrounding rock structure in the tunnel area, including: physical and mechanical parameters of the rock and soil in an initial state and physical and mechanical parameters of the rock and soil after deformation and softening, wherein the physical and mechanical parameters comprise volume weight, cohesive force, internal friction angle, tensile strength, elastic modulus and poisson ratio. If a surrounding rock structure in the area has a geological structure with larger hidden trouble, if a surrounding rock structure breaking belt, a structure water-rich area, a weak surrounding rock and other bad geological structures appear, the multi-means advanced detection method for the water-rich karst tunnel provided by the invention is adopted to continue detection, and if the surrounding rock structure does not exist, the conventional method is adopted to detect.
Preferably, in step S1, the predicting the poor geological structure predicts the rock-soil sample of the tunnel with the potential poor geological structure to obtain the rock-soil physical and mechanical parameters, wherein the experiment includes at least one of a ring cutter experiment, a triaxial experiment, a direct shear experiment, a brazilian split experiment and a uniaxial compression experiment. As a specific embodiment, the embodiment of the invention firstly pre-judges the whole tunnel area and preliminarily obtains the predicted poor geological structure.
Preferably, the layout parameters include at least one of a size of tunnel face, a drilling position, a number of drilling holes, a drilling hole depth, a drilling angle, and a hole pitch. As a specific embodiment, the layout parameters are set so that subsequent drilling holes can be laid out. It can be appreciated that the layout parameters also include, but are not limited to, the dimensions of the three-dimensional tunnel geological generalization model, the tunnel face dimensions, and the locations of the holes drilled on the tunnel face of the tunnel model, so that the effective hole drilling layout can be performed in combination with the tunnel face.
Preferably, step S3 specifically includes: and setting layout parameters according to boundary data and detection requirements of the three-dimensional tunnel geological generalized model so as to lay out a plurality of advanced drilling holes. As a specific embodiment, the embodiment of the invention effectively lays out the advanced drilling holes according to the boundary conditions and detection requirements of the three-dimensional tunnel geological generalized model.
Preferably, the boundary data includes a three-dimensional spatial dimension of the three-dimensional tunnel geological generalized model, an arrangement spatial structure test layout, and a spatial relationship of the test instruments to each other. As a specific embodiment, the method and the device for determining the distribution position range of the tunnel face in the three-dimensional tunnel are combined with boundary data of a three-dimensional tunnel geological generalized model.
Preferably, as seen in conjunction with fig. 2, fig. 2 is a schematic flow chart of the seismic wave detection method provided by the present invention, and step S4 includes steps S41 to S42, wherein:
in step S41, exciting seismic waves to perform cross-hole CT between every two advanced drilling holes of the tunnel face;
in step S42, a wave velocity distribution image between each two advanced boreholes is determined according to the first arrival travel time information of the seismic waves.
As a specific embodiment, the embodiment of the invention acquires the geological information between two measuring holes on the face by exciting the form of the seismic wave and combining the characteristics of the seismic wave, and develops multi-means advanced geological detection.
It should be noted that the on-site seismic wave detection system comprises two parts, namely hardware and software. The system hardware comprises a ZDF-3 type electric spark seismic source, an integrated high-sensitivity detector, a 24-bit computer, 8 independent channel portable computers and the like. The software comprises two parts of CT tomography and geology expert. Referring to fig. 3, fig. 3 is a schematic diagram of a vertical plane CT unit according to the present invention, a cross-hole CT is performed in a hole measurement of a face, a cross-hole CT test is performed in both sides of the face, geological information between two holes of the face is obtained by exciting a form of seismic waves according to characteristics of the geological information that can be carried by the seismic waves, the seismic waves CT invert substances by seismic wave data, obtain geological information between two holes of the face according to characteristics of the geological information that can be carried by the seismic waves by exciting a form of seismic waves, and perform a hierarchical analysis to draw a geological formation image, and a structure of the stratum is further estimated according to the obtained distribution map. In the detection process, firstly, the time file of the seismic wave in the structure between two measuring holes is obtained through HSP detection, and the first arrival time t of the seismic wave is read through software interpretation i Then solving a matrix equation to form a wave velocity distribution image of the seismic waves in the geologic body between two holes, and clearly observing the wave velocity distribution situation between the measuring holes according to the image.
Preferably, as seen in fig. 4, fig. 4 is a schematic flow chart of the radar detection method provided by the present invention, and step S4 includes steps S43 to S44, wherein:
in step S43, a pulse electromagnetic wave signal is emitted to the front of the tunnel face, wherein when the pulse electromagnetic wave signal encounters the detection target, a corresponding reflected signal is generated;
in step S44, a wave velocity map in the advanced borehole corresponding to the advanced borehole is determined according to the reflected signal.
As a specific embodiment, the embodiment of the invention acquires the geological information in the hole on the face by combining the characteristics of radar signals through a radar detection method so as to develop multi-means advanced geological detection.
It should be noted that, referring to fig. 5 and 6, fig. 5 is a schematic layout diagram of a tunnel face provided by the present invention, and fig. 6 is a schematic diagram of an in-hole address radar provided by the present invention, in which, no. 1 to No. 4 represent different advanced drilling holes, in-hole geological radar detection is sequentially performed in the drilling holes laid on the face, and the geological radar detects underground medium distribution by using ultra-high frequency electromagnetic waves, and its basic principle is that a transmitter transmits pulse electromagnetic wave signals with a center frequency of 12.5M to 1200M and a pulse width of 0.1ns through a transmitting antenna. When this signal encounters a target in the formation, a reflected signal is generated. The direct signal and the reflected signal are input to the receiver through the receiving antenna, amplified and displayed by the oscilloscope. Whether a detected target exists or not can be judged according to whether the oscilloscope has a reflection flood number or not; estimating surrounding rock structures around the measuring hole according to the arrival lag time of the reflected signals and the average reflected wave velocity of the target object and a wave velocity diagram generated by the test; in the detection process of the geological radar in the hole, specific detection parameters are adjusted according to the detection range, wherein the detection range is 20m, the detection rate adopts point measurement, the gain is 35, and the upper limit parameter and the lower limit parameter of the filter are 100-1000MHz; the aperture size of the measuring hole on the face can be a preset value, and the preset value can be 300mm; the depth of the drilled holes on the face is determined according to the space position between the poor geological structure and the face, the drilling direction can be properly adjusted according to the geological region to be detected, the hole spacing comprehensively considers the detection range of the geological radar in the holes, the geological radar detection data on the horizontal plane and the detection data system and analysis of the cross-hole CT in the vertical direction are realized, mutual verification is needed, and mutual complementation and extension are realized.
Preferably, as seen in fig. 7, fig. 7 is a schematic flow chart of the electromagnetic detection method provided by the present invention, and step S4 includes step S45, where:
in step S45, induced polarization detection is sequentially performed on the advanced drilling of the tunnel face, and corresponding geological electrical data is determined.
As a specific embodiment, the embodiment of the invention acquires the geological information in front of the face by detecting through an induced polarization method and combining the characteristics of electromagnetic signals so as to develop multi-means advanced geological detection.
It should be noted that, as shown in fig. 8, fig. 8 is a schematic diagram of induced polarization, where induced polarization detection is performed in a hole for measuring a face, and first, distribution of lithology of surrounding rock and surrounding rock structural band in front of the face is detected; secondly, combining visual geological data and Kong Nakua hole CT to form mutual evidence and extension in the horizontal direction in front of the face; thirdly, analyzing geology from three aspects of electromagnetic wave, earthquake wave and electric method respectively by using the in-hole geological radar, the cross-hole CT and the wave velocity diagram generation.
Preferably, as seen in conjunction with fig. 9, fig. 9 is a schematic flow chart of determining a location interval range provided by the present invention, and step S5 includes steps S51 to S52, wherein:
in step S51, corresponding positioning information is formed according to the wave velocity distribution image and the geological electricity data;
in step S52, in combination with the positioning information, the geological reverse reasoning is performed in front of the tunnel face in a numerical reverse calculation manner, so as to determine the range of the location interval.
As a specific embodiment, the embodiment of the invention combines the wave velocity distribution image and the geological electricity data to mutually supplement and verify so as to determine accurate positioning information and position the range of the position interval.
Preferably, step S5 further comprises: and combining the wave velocity distribution image and the wave velocity diagram in the borehole, and performing verification analysis on the vertical plane and the horizontal plane. As a specific embodiment, the embodiment of the invention combines the cross-hole CT and the in-hole geological radar to detect the bad geological structure in the front vertical direction and the horizontal direction of the face, and if the corresponding data of the detected bad geological structure meets the related requirements of tunnel construction, the construction can be safely carried out; if a bad geological structure endangering tunnel construction is found in the detection process, a corresponding emergency treatment scheme is compiled according to the detection data so as to ensure that the tunnel passes through the section safely.
Preferably, step S5 further comprises: and according to the geological electricity data, carrying out verification analysis on the wave velocity distribution image and the wave velocity diagram in the borehole. As a specific embodiment, the embodiment of the invention integrates three detection means comprising a cross-hole CT, an in-hole geological radar and an induced polarization method, wherein the three detection means comprise seismic waves, electromagnetic waves and an electric method, the change of physical and mechanical parameters of rock and soil before and after engineering excavation is considered, and the accuracy of detection data is ensured.
Example 2
The embodiment of the invention provides a multi-means advanced detection device for a water-rich karst tunnel, which comprises a processor and a memory, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the multi-means advanced detection method for the water-rich karst tunnel is realized.
The invention discloses a multi-means advanced detection method of a water-rich karst tunnel, which comprises the steps of firstly, effectively acquiring structural topography, predicted bad geological structure and engineering tunnel conditions; then, combining multiple factors to build a three-dimensional tunnel geological generalization model so as to reflect the basic characteristics of the tunnel; furthermore, based on a three-dimensional tunnel geological generalization model, setting layout parameters, and primarily determining advanced drilling layout of a tunnel face; then, on the tunnel face with the drilled holes, multi-means advanced geological detection is carried out, and by utilizing a plurality of detection methods and combining seismic wave information, radar information and electromagnetic information, mutual verification of data is realized, more accurate geological features are obtained, and therefore accurate prediction of the position interval range of the poor geological structure is realized; and finally, detecting according to the range of the position interval, and determining the actual bad geological structure, so that the whole construction scheme is planned, and the tunnel excavation stability meets the engineering requirement.
According to the technical scheme, the change of physical and mechanical parameters of rock and soil before and after engineering excavation is considered, geological exploration is carried out on a tunnel construction area before the excavation, the structure of the initial state of the rock and soil in the area is fully analyzed, the great reduction of the rock and soil strength caused by deformation and softening of surrounding rock of the tunnel after the excavation is avoided, multi-means advanced geological detection is adopted, three information of earthquake waves, electromagnetic waves and an electric method are combined, the tunnel construction risk is effectively reduced, surrounding rock geological strips are analyzed at multiple angles, sudden geological disasters in the tunnel excavation are avoided, safety is endangered, and construction risk and loss are reduced.
The present invention is not limited to the above-mentioned embodiments, and any changes or substitutions that can be easily understood by those skilled in the art within the technical scope of the present invention are intended to be included in the scope of the present invention.
Claims (6)
1. A multi-means advanced detection method for a water-rich karst tunnel is characterized by comprising the following steps of:
obtaining structural topography in a tunnel region, predicting bad geological structures and engineering tunnel conditions;
geometric modeling is carried out according to the structural terrain, the predicted poor geological structure and the engineering tunnel condition, and a three-dimensional tunnel geological generalized model is determined;
determining layout parameters corresponding to the three-dimensional tunnel geological generalized model, and carrying out advanced drilling layout on tunnel faces according to the layout parameters to determine the fully laid tunnel faces;
performing cross-hole CT scanning, in-hole geological radar detection and induced polarization method detection on the tunnel face with the complete arrangement, and respectively determining wave velocity distribution images between two advanced drilling holes, wave velocity maps in the advanced drilling holes and geological electricity data;
determining a position interval range of the predicted poor geological structure according to the wave velocity distribution image, the wave velocity map in the drill hole and the data consistency of the geological electricity data in a plurality of directions;
detecting according to the position interval range, determining an actual poor geological structure, and planning a construction scheme through the actual poor geological structure;
the determining the location interval range of the predicted poor geological structure according to the wave velocity distribution image, the wave velocity graph in the drilling hole and the data consistency of the geological electricity data in a plurality of directions comprises:
forming corresponding positioning information according to the wave velocity distribution image and the geological electricity data;
combining the positioning information, performing geological reverse reasoning in front of the tunnel face in a numerical reverse calculation mode, and determining the range of the position interval;
combining the wave velocity distribution image and the wave velocity diagram in the drilling hole, and performing verification analysis on the vertical plane and the horizontal plane;
according to the geological electricity data, verifying and analyzing the wave velocity distribution image and the wave velocity diagram in the borehole;
the layout parameters comprise at least one of the size, drilling position, drilling quantity, drilling hole depth, drilling angle and hole spacing of the tunnel face.
2. The method for multi-means advanced detection of a water-rich karst tunnel according to claim 1, wherein determining layout parameters corresponding to the three-dimensional tunnel geological generalization model comprises: and setting the layout parameters according to the boundary data and the detection requirements of the three-dimensional tunnel geological generalized model so as to lay out a plurality of advanced drilling holes.
3. The method of claim 2, wherein the boundary data comprises three dimensional spatial dimensions of the three dimensional tunnel geological generalized model, a layout of a spatial structure test, and a spatial relationship of the test instruments to each other.
4. The multi-means advanced detection method of a water-rich karst tunnel according to claim 1, wherein the steps of performing cross-hole CT scan, in-hole geological radar detection and induced polarization detection on the fully-laid tunnel face, respectively determining a wave velocity distribution image between two advanced boreholes, an advanced borehole internal wave velocity map and geological electricity data include:
exciting seismic waves to perform cross-hole CT between every two advanced drilling holes of the tunnel face;
and determining the wave velocity distribution image between every two advanced drilling holes according to the first arrival travel time information of the seismic waves.
5. The multi-means advanced detection method of a water-rich karst tunnel according to claim 1, wherein the steps of performing cross-hole CT scan, in-hole geological radar detection and induced polarization detection on the fully-laid tunnel face, respectively determining a wave velocity distribution image between two advanced boreholes, an advanced borehole internal wave velocity map and geological electricity data include:
transmitting a pulse electromagnetic wave signal to the front of the tunnel face, wherein when the pulse electromagnetic wave signal meets a detection target, a corresponding reflection signal is generated;
and determining the wave velocity diagram in the advanced drilling corresponding to the advanced drilling according to the reflected signal.
6. The multi-means advanced detection method of a water-rich karst tunnel according to claim 1, wherein the steps of performing cross-hole CT scan, in-hole geological radar detection and induced polarization detection on the fully-laid tunnel face, respectively determining a wave velocity distribution image between two advanced boreholes, an advanced borehole internal wave velocity map and geological electricity data include:
and sequentially detecting the advanced drilling holes of the tunnel face by using an induced polarization method, and determining the corresponding geological electricity data.
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| CN113805224A (en) * | 2021-08-23 | 2021-12-17 | 中铁二院成都工程检测有限责任公司 | Advanced geological prediction method and system based on cross-advanced horizontal borehole seismic CT |
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| CN114839696B (en) * | 2022-07-04 | 2022-09-13 | 武九铁路客运专线湖北有限责任公司 | Multi-source data fusion sensing three-dimensional tunnel unfavorable geology detection method |
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103744129A (en) * | 2014-01-07 | 2014-04-23 | 山东大学 | Tunnel construction large-scale integrated geophysics advanced detection model test device |
| CN108802824A (en) * | 2018-06-15 | 2018-11-13 | 山东大学 | A kind of physical analog test apparatus and method for geophysical exploration |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
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-
2021
- 2021-02-05 CN CN202110159390.7A patent/CN112965136B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103744129A (en) * | 2014-01-07 | 2014-04-23 | 山东大学 | Tunnel construction large-scale integrated geophysics advanced detection model test device |
| CN108802824A (en) * | 2018-06-15 | 2018-11-13 | 山东大学 | A kind of physical analog test apparatus and method for geophysical exploration |
Non-Patent Citations (3)
| Title |
|---|
| 冯义 ; .综合超前地质预报在岩溶隧道中的应用.筑路机械与施工机械化.2017,(第12期),全文. * |
| 王路,张恒,吴建文.强富水地层隧道含水构造精细预报技术研究.铁道科学与工程学报.2017,第14卷(第12期),第2660-2668页. * |
| 钟明文,汪红武,李武雄,袁从华,陈佳正.综合探测技术在岩溶隧道突水成因判定中的应用与研究.工程勘察.2020,(第12期),全文. * |
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