CN115480241A - Tunnel face advanced geological prediction robot system and method - Google Patents
Tunnel face advanced geological prediction robot system and method Download PDFInfo
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- CN115480241A CN115480241A CN202211053693.1A CN202211053693A CN115480241A CN 115480241 A CN115480241 A CN 115480241A CN 202211053693 A CN202211053693 A CN 202211053693A CN 115480241 A CN115480241 A CN 115480241A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/86—Combinations of radar systems with non-radar systems, e.g. sonar, direction finder
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- E—FIXED CONSTRUCTIONS
- E21—EARTH OR ROCK DRILLING; MINING
- E21F—SAFETY DEVICES, TRANSPORT, FILLING-UP, RESCUE, VENTILATION, OR DRAINING IN OR OF MINES OR TUNNELS
- E21F17/00—Methods or devices for use in mines or tunnels, not covered elsewhere
- E21F17/18—Special adaptations of signalling or alarm devices
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- E—FIXED CONSTRUCTIONS
- E21—EARTH OR ROCK DRILLING; MINING
- E21F—SAFETY DEVICES, TRANSPORT, FILLING-UP, RESCUE, VENTILATION, OR DRAINING IN OR OF MINES OR TUNNELS
- E21F17/00—Methods or devices for use in mines or tunnels, not covered elsewhere
- E21F17/18—Special adaptations of signalling or alarm devices
- E21F17/185—Rock-pressure control devices with or without alarm devices; Alarm devices in case of roof subsidence
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/885—Radar or analogous systems specially adapted for specific applications for ground probing
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Abstract
The invention discloses a tunnel face advanced geology forecasting robot system and a method, which comprises the following steps: the robot carrying module is provided with a collapse monitoring module and a radar detection module; the collapse monitoring module is used for carrying out rock image acquisition and laser vibration measurement on the face and carrying out stability monitoring on the face; the radar detection module comprises a geological radar detection arm clamped with a geological radar, a vertical detection arm driving the geological radar detection arm to vertically move and a transverse detection arm driving the geological radar detection arm to transversely move; on horizontal exploration arm was located to the one end of vertical exploration arm, the other end of vertical exploration arm was equipped with geological radar exploration arm, according to the exploration mode, when face stability monitoring is as an exception, control geological radar exploration arm and drive geological radar and carry out face advance geology forecast. Under the premise of ensuring the safety of the tunnel face, unmanned construction of advanced geological forecast is realized, and the problems of difficult manual operation, limited survey line layout, surrounding rock collapse and other risks in the traditional geological radar forecast are solved.
Description
Technical Field
The invention relates to the technical field of advanced geological forecast and disaster monitoring and early warning of geotechnical engineering, in particular to a robot system and a method for advanced geological forecast of a tunnel face.
Background
The statements in this section merely provide background information related to the present disclosure and may not constitute prior art.
The advanced geological forecast technology is necessary work for tunnel construction in unfavorable geological regions, and the geological radar is widely applied to advanced geological forecast as a convenient and rapid nondestructive short-range geophysical prospecting method.
However, in actual operation, the conventional artificial geological radar forecast has the following problems:
(1) The equipment is heavy, the operation of personnel is difficult, and time and labor are wasted;
(2) The layout of the survey line is limited, and unfavorable geological disasters cannot be effectively detected;
(3) The danger of block falling, collapse and the like on the tunnel face easily causes injury to operators and damages equipment; especially, the current tunnel engineering generally passes through extreme geological conditions and extreme construction environments, the risk of sudden disasters is increased, constructors are in extreme operation environments, and the major geological disaster intelligent active prevention and control and unmanned intelligent construction are the mainstream development trend of the current tunnel construction.
Disclosure of Invention
In order to solve the problems, the invention provides a tunnel face advanced geological prediction robot system and a tunnel face advanced geological prediction robot method. The problems that the traditional geological radar forecast is difficult to operate manually, the layout of measuring lines is limited, and risks such as collapse of surrounding rocks exist are solved.
In order to achieve the purpose, the invention adopts the following technical scheme:
in a first aspect, the present invention provides a tunnel face advanced geological prediction robot system, including: the system comprises a robot carrying module, a collapse monitoring module and a radar detection module;
the robot carrying module is provided with a collapse monitoring module and a radar detection module;
the collapse monitoring module is used for carrying out rock image acquisition and laser vibration measurement on the face so as to carry out stability monitoring on the face;
the radar detection module comprises a geological radar detection arm clamped with a geological radar, a vertical detection arm driving the geological radar detection arm to vertically move and a transverse detection arm driving the geological radar detection arm to transversely move; the geological radar detection arm is controlled to drive the geological radar to forecast the face advance geology when the face stability monitoring is abnormal according to a set detection mode.
As an alternative embodiment, the collapse monitoring module comprises an image monitoring system and a laser vibration measurement monitoring system; the image monitoring system is used for acquiring information of a face rock structural plane, positioning and identifying a block and monitoring rockfall in real time, and the laser vibration measurement monitoring system is used for monitoring the displacement, the speed and the change of the natural vibration frequency of a face region.
As an alternative embodiment, the bottom end of the vertical detection arm is arranged on the horizontal detection arm through a sliding base, and a movable support is arranged on the base, so that when radar detection is not performed, the bottom end of the vertical detection arm rotates by 90 degrees around the movable support as an axis and is carried on the top of the robot carrying module.
As an alternative embodiment, the top end of the robot carrying module is provided with a groove matched with the vertical detection arm, and when the robot carrying module reaches a specified position for radar detection, the vertical detection arm rotates by 90 degrees around the movable support to work.
As an alternative embodiment, a movable support is arranged at the joint of the vertical detection arm and the geological radar detection arm, and when the vertical detection arm is carried on the top of the robot carrying module, the geological radar detection arm is folded.
As an alternative embodiment, the front end of the robot carrying module is connected to the middle position of a transverse detection arm through a bracket, the transverse detection arm comprises a first track and a second track, the first track comprises a first transverse mechanical arm in parallel, the second track comprises a second transverse mechanical arm in parallel, and both ends of the first transverse mechanical arm are connected with the second transverse mechanical arm;
the two ends of the first transverse mechanical arm on one side are movably connected with the corresponding second transverse mechanical arm, and the two ends of the first transverse mechanical arm on the other side are detachably connected with the corresponding second transverse mechanical arm; when radar detection is not carried out, the second transverse mechanical arm is arranged on two sides of the robot carrying module, and the first transverse mechanical arm is arranged at the front end of the robot carrying module.
As an alternative embodiment, when the radar detection is performed when the radar detection reaches a specified position, the second horizontal mechanical arms on two sides extend to the same horizontal position as the first horizontal mechanical arm in front, and the detachably connected parts are clamped to form a horizontal detection arm which drives the vertical detection arm to move horizontally, so that the radar detection of the tunnel face is performed.
In an alternative embodiment, active obstacle crossing devices are mounted on both sides of the geological radar, and the retraction amount of the geological radar is controlled by pressure sensors.
As an alternative embodiment, the detection mode of the radar detection module includes: a continuous measurement mode for flat tunnel faces, a point measurement mode for uneven tunnel faces, and a wheel track measurement mode for abnormal body position detection.
In a second aspect, the present invention provides a working method of a tunnel face advance geology prediction robot system, where the tunnel face advance geology prediction robot system of the first aspect is adopted, and includes:
the robot carrying module is used for driving the robot carrying module to run below the primary support, so that the collapse monitoring module is used for carrying out stability monitoring on the tunnel face through rock image acquisition and laser vibration measurement on the tunnel face;
when the face stability monitoring is abnormal, carry the module drive through the robot and move to face below, the horizontal arm of second of control horizontal gauge arm extends to the same horizontal position with first horizontal arm to stretch out the bearing spike, vertical gauge arm of simultaneous control erects, makes vertical gauge arm along horizontal gauge arm lateral shifting, according to the detection mode of setting for, control geological radar gauge arm drives geological radar and carries out face advance geological forecast.
Compared with the prior art, the invention has the beneficial effects that:
the invention provides a tunnel face advanced geological prediction robot system and method based on intelligent monitoring, aiming at the difficult problems of difficult manual operation, limited survey line layout, surrounding rock collapse and other risks of traditional geological radar prediction, in the tunnel construction process, a collapse monitoring module is adopted to carry out tunnel face stability monitoring and collapse early warning, after a robot carrying module is driven to a specified position, a radar detection module is remotely controlled to carry out geological prediction automatic construction, and the remote unmanned construction of advanced geological prediction is realized on the premise of ensuring the safety of a tunnel face area.
On the premise of real-time assessment of the tunnel face stable state, the invention provides an automatic construction permission mechanism for advanced geological forecast, which is 'tunnel face stability monitoring → tunnel face collapse early warning → automatic construction of geological forecast → automatic interpretation of forecast data', and reforms the geological forecast process. Compared with the existing research, the robot is adopted to forecast the tunnel face geology, so that the damage of personnel and equipment can be effectively avoided, the speed and the precision of the tunnel face geology forecast are improved, and the safety construction of tunnel engineering is guaranteed.
The tunnel face advanced geological prediction robot system and method based on intelligent monitoring provided by the invention replace the traditional manual tunnel face geological prediction, realize remote unmanned fine detection of poor geological bodies in front of the tunnel face in a complex environment and avoid personnel and equipment loss caused by the collapse of the tunnel face.
The tunnel face advanced geological prediction robot system and method based on intelligent monitoring can carry out more reasonable and uniform survey line arrangement, set a detection mode according to the face condition, realize stable and uniform continuous measurement and effectively improve the precision and efficiency of advanced geological prediction. The whole face can be monitored even in an environment where a plurality of operators work, and the rapid, real-time and intelligent face stable monitoring is realized.
Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the invention and together with the description serve to explain the invention and not to limit the invention.
Fig. 1 is a schematic structural diagram of a tunnel face advanced geological prediction robot system according to embodiment 1 of the present invention during radar detection;
fig. 2 is a schematic structural diagram of a tunnel face advanced geological prediction robot system provided in embodiment 1 of the present invention during traveling;
wherein, 1, the robot carries the module; 2. a collapse monitoring module; 3. a radar detection module; 4. a geological radar detection arm; 5. a vertical probe arm; 6. a lateral probing arm; 7. an active obstacle crossing device; 8. a geological radar; 9. a pressure sensor; 10. a load-bearing arm brace; 11. a first transverse robotic arm; 12. a second lateral robotic arm.
Detailed Description
The invention is further explained by the following embodiments in conjunction with the drawings.
It is to be understood that the following detailed description is exemplary and is intended to provide further explanation of the invention as claimed. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the invention. As used herein, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise, and it should be understood that the terms "comprises" and "comprising", and any variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The embodiments and features of the embodiments of the invention may be combined with each other without conflict.
Example 1
The embodiment provides a tunnel face advance geology forecast robot system based on intelligent monitoring, includes: the system comprises a robot carrying module, a collapse monitoring module and a radar detection module; aiming at the difficult problems of difficult manual operation, limited survey line arrangement, surrounding rock collapse and other risks of the traditional geological radar prediction, a collapse monitoring module is adopted to carry out tunnel face stability monitoring and collapse early warning in the tunnel construction process, when the tunnel face stability monitoring is abnormal, a robot carrying module is remotely controlled to run to a specified position, a radar detection module is remotely controlled to carry out geological prediction automatic construction, and the remote unmanned construction of advanced geological prediction is realized on the premise of ensuring the safety of a tunnel face area.
As shown in fig. 1, the method specifically includes:
the robot carrying module is provided with a collapse monitoring module and a radar detection module;
the collapse monitoring module is used for performing rock image acquisition and laser vibration measurement on the face so as to perform stability monitoring on the face;
the radar detection module comprises a geological radar detection arm clamped with a geological radar, a vertical detection arm driving the geological radar detection arm to vertically move and a transverse detection arm driving the geological radar detection arm to transversely move; wherein, on horizontal exploration arm was located to the one end of vertical exploration arm, the other end of vertical exploration arm was equipped with geological radar exploration arm, according to the detection mode of setting for, when face stability monitoring is as an exception, control geological radar exploration arm and drive geological radar and carry out face advance geology forecast.
In the embodiment, the robot carrying module 1 is driven by electric power, the service quality is less than or equal to 0.5t, the cruising ability is greater than or equal to 5 hours, the traveling speed is greater than or equal to 5 kilometers per hour, the maximum obstacle crossing height is 220mm, the obstacle crossing width is 600mm, and the robot carrying module has stable passing ability of complex road conditions such as wading and is suitable for severe tunnel environments.
As an optional implementation manner, the robot carrying module 1 carries an ultrasonic, infrared and laser coupling obstacle avoidance technology, and can realize autonomous walking control and active obstacle avoidance in a tunnel in a terrain environment.
In this embodiment, the collapse monitoring module 2 includes an image monitoring system and a laser vibration measurement monitoring system, wherein the image monitoring system is used for collecting information of a face rock mass structural plane, positioning and identifying a block, and monitoring falling rocks in real time to determine whether a face area is safe;
the laser vibration measurement monitoring system is used for monitoring the displacement, the speed and the change of the natural vibration frequency of the whole tunnel face and the peripheral area;
the collapse monitoring module realizes quick identification of the stability of the tunnel face through image monitoring and laser vibration measurement monitoring; if the displacement, speed, natural vibration frequency and the like of the face do not change obviously, the face is stable at the moment, and advanced geological prediction can be carried out; if the displacement, the natural vibration frequency and the like of the face and the dangerous block body are obviously changed, the face is not stable at the moment, and advanced geological prediction work is carried out after measures such as mechanical elimination, local reinforcement and the like are taken on the face.
In this embodiment, the radar detection module 3 comprises a vertical detection arm 5, a horizontal detection arm 6 and a geological radar detection arm 4; wherein, vertical exploration arm 5 is used for controlling reciprocating of geological radar exploration arm 4, and horizontal exploration arm 6 is used for controlling moving about geological radar exploration arm 4, and the centre gripping has geological radar 8 on the geological radar exploration arm 4 for control geological radar 8 carries out advance geological forecast.
As an alternative embodiment, the bottom end of the vertical detection arm 5 is arranged on the transverse detection arm 6 through a sliding base, so that the vertical detection arm 5 moves transversely along the transverse detection arm 6;
the base is provided with a movable support to control the bottom end of the vertical detection arm 5 to rotate 90 degrees by taking the movable support as an axis, so that the vertical detection arm 5 is carried on the top of the robot carrying module 1 when radar detection is not carried out.
Furthermore, the top end of the robot carrying module 1 is provided with a groove matched with the vertical detection arm 5, the vertical detection arm 5 is horizontally arranged in the groove in the advancing geological prediction robot traveling process of the tunnel face, and when the specified position is reached for radar detection, the vertical detection arm 5 rotates for 90 degrees by taking the movable support as an axis and is erected for prediction work.
Furthermore, the junction of vertical search arm 5 and geological radar search arm 4 is equipped with movable support equally, and when vertical search arm 5 was arranged in the recess, geological radar search arm 4 was also folded up equally.
As an alternative embodiment, the front end of the robot carrier module 1 in the traveling direction is connected to the middle position of the transverse detection arm 6 through a bracket;
the transverse detection arm 6 comprises a first rail and a second rail, the first rail comprises a first transverse mechanical arm 11 which is parallel to the first rail, the second rail comprises a second transverse mechanical arm 12 which is parallel to the second rail, and two ends of the first transverse mechanical arm 11 are connected with the second transverse mechanical arm 12;
wherein, two ends of the first transverse mechanical arm 11 at one side are movably connected with the corresponding second transverse mechanical arm 12; the two ends of the first transverse mechanical arm 11 on the other side are detachably connected with the corresponding second transverse mechanical arm 12;
in the process of advancing, through the movable connection of one side and the detachable connection of the other side, the second transverse mechanical arm 12 is arranged on the two sides of the robot carrying module 1, and the first transverse mechanical arm 11 is arranged at the front end of the advancing direction of the robot carrying module 1.
As can be seen in fig. 2, during the travel, the transverse feeler arms 6 are placed in a "concave" shape in front of and on both sides of the robotic carrier module 1; namely, the second transverse mechanical arm 12 is arranged at two sides of the robot carrying module 1, and the first transverse mechanical arm 11 is arranged at the front end of the robot carrying module 1 in the advancing direction;
when the specific position is reached for detection, the second transverse mechanical arms 12 on the two sides extend to the same horizontal position as the first transverse mechanical arm 11 in front, and then the detachably connected parts are clamped to form the transverse detection arm 6 capable of driving the vertical detection arm 5 to transversely move, so that the whole tunnel face is detected.
As an alternative embodiment, a load-bearing brace 10 is provided on the second transverse robotic arm 12 to support the transverse probe arm 6.
As an alternative embodiment, the geological radar detection arm 4 is arranged at the top end of the vertical detection arm 5, the geological radar 8 is clamped at the tail end of the geological radar detection arm 4, the active obstacle crossing devices 7 are carried on the upper side and the lower side of the geological radar 8, the retraction amount of the geological radar 8 is controlled through the pressure sensors 9, so that stable and uniform continuous measurement is realized, and the tunnel faces under different conditions can be stably passed through.
As an alternative embodiment, the geological radar detection arm 4 has a degree of freedom of more than or equal to 120 degrees, a pitching angle of +/-140 degrees, a yawing angle of +/-130 degrees and a compensation range of more than or equal to 45 degrees.
In this embodiment, the detection modes of the radar detection module include three modes, specifically:
(1) Aiming at the relatively flat tunnel face, a continuous measurement mode is adopted, so that the efficiency is high, the speed is high, and convenience and rapidness are realized;
(2) Aiming at the uneven tunnel face, a point measurement mode is adopted, so that the detection depth and the accurate identification are realized, and the effect is good;
(3) Aiming at the accurate detection of the position of an abnormal body, a wheel track measuring mode is adopted, and unmanned remote unfavorable geological detection of tunnel construction in a complex environment is realized.
Example 2
The embodiment provides a working method of a tunnel face advanced geological prediction robot system based on intelligent monitoring, and the tunnel face advanced geological prediction robot system of the embodiment 1 is adopted, and comprises the following steps:
(1) The tunnel face advanced geological prediction robot is remotely controlled to run below a primary support with small vibration and wide visual field, and a collapse monitoring module is adopted to carry out stability monitoring on the whole tunnel face area;
specifically, information acquisition, block positioning identification and real-time rock falling monitoring of a face rock structure face are carried out through an image monitoring system so as to judge whether a face area is safe or not; monitoring the displacement, speed and natural vibration frequency changes of the whole tunnel face and the peripheral area by a laser vibration measurement monitoring system;
(2) After the collapse monitoring module is adopted for monitoring for 15-20 minutes, if the displacement, the inherent vibration frequency and the like of the face do not change obviously, the face is stable at the moment, and advanced geological prediction can be carried out; if the displacement, the natural vibration frequency and the like of the face and the dangerous block body are obviously changed, the face is unstable at the moment, and measures such as mechanical removal, local reinforcement and the like are taken for the face, and then advanced geological prediction is carried out.
(3) After the tunnel face stability monitoring is abnormal, the tunnel face advanced geological forecasting robot is remotely controlled to run to the lower side of the tunnel face, the second transverse mechanical arm of the transverse detection arm is controlled to extend to the same horizontal position as the first transverse mechanical arm and extend out of the bearing supporting foot, and the vertical detection arm is controlled to be erected at the same time, so that the vertical detection arm transversely moves along the transverse detection arm, a corresponding detection mode is selected according to the situation of the tunnel face, and the geological radar detection arm is controlled to carry out tunnel face advanced geological forecasting work.
(4) After the geological radar is adopted to scan the whole tunnel face, the advanced geological forecast data are remotely sent to a data processing system outside the tunnel for intelligent data interpretation, the transverse detection arm and the vertical detection arm are withdrawn, and the advanced geological forecast robot for the tunnel face is remotely controlled to exit the tunnel.
Although the embodiments of the present invention have been described with reference to the accompanying drawings, it is not intended to limit the scope of the present invention, and it should be understood by those skilled in the art that various modifications and variations can be made without inventive efforts by those skilled in the art based on the technical solution of the present invention.
Claims (10)
1. A tunnel face advance geology forecast robot system characterized in that includes: the system comprises a robot carrying module, a collapse monitoring module and a radar detection module;
the robot carrying module is provided with a collapse monitoring module and a radar detection module;
the collapse monitoring module is used for performing rock image acquisition and laser vibration measurement on the face so as to perform stability monitoring on the face;
the radar detection module comprises a geological radar detection arm clamped with a geological radar, a vertical detection arm driving the geological radar detection arm to vertically move and a transverse detection arm driving the geological radar detection arm to transversely move; wherein, on horizontal exploration arm was located to the one end of vertical exploration arm, the other end of vertical exploration arm was equipped with geological radar exploration arm, according to the detection mode of setting for, when face stability monitoring is as an exception, control geological radar exploration arm and drive geological radar and carry out face advance geology forecast.
2. The advanced geological prediction robot system of claim 1, wherein the collapse monitoring module comprises an image monitoring system and a laser vibration measurement monitoring system; the image monitoring system is used for acquiring information of a face rock structural plane, positioning and identifying blocks and monitoring falling rocks in real time, and the laser vibration measurement monitoring system is used for monitoring the displacement, the speed and the change of the natural vibration frequency of a face area.
3. The advanced geological prediction robot system for tunnel face as claimed in claim 1, wherein the bottom end of the vertical detection arm is mounted on the horizontal detection arm through a sliding base, and a movable support is provided on the base, so that when radar detection is not performed, the bottom end of the vertical detection arm is mounted on the top of the robot carrying module by rotating 90 degrees around the movable support as an axis.
4. The advanced geological prediction robot system for tunnel face as claimed in claim 3, wherein the top end of the robot carrying module is provided with a groove matched with the vertical detecting arm, and when the robot carrying module reaches a specified position for radar detection, the vertical detecting arm is rotated by 90 degrees around the movable support to be erected for work.
5. The robot system for advanced geological prediction of tunnel face according to claim 3, wherein the joint of the vertical probing arm and the geological radar probing arm is provided with a movable support, and the geological radar probing arm is folded when the vertical probing arm is carried on the top of the robot carrying module.
6. The system as claimed in claim 1, wherein the front end of the robot carrying module is connected to the middle of a transverse probing arm through a bracket, the transverse probing arm comprises a first track and a second track, the first track comprises a first parallel transverse robot, the second track comprises a second parallel transverse robot, and both ends of the first transverse robot are connected to the second transverse robot;
the two ends of the first transverse mechanical arm on one side are movably connected with the corresponding second transverse mechanical arm, and the two ends of the first transverse mechanical arm on the other side are detachably connected with the corresponding second transverse mechanical arm; when radar detection is not carried out, the second transverse mechanical arms are arranged on two sides of the robot carrying module, and the first transverse mechanical arms are arranged at the front end of the robot carrying module.
7. The advanced geological prediction robot system for tunnel face as claimed in claim 6, wherein when radar detection is performed when the tunnel face reaches a designated position, the second transverse mechanical arms at two sides extend to the same horizontal position as the first transverse mechanical arm at the front, and the detachably connected parts are clamped to form the transverse detection arm driving the vertical detection arm to move transversely, so that radar detection of the tunnel face is performed.
8. The robot system for advanced geological prediction of tunnel face as claimed in claim 1, wherein active obstacle-surmounting means are mounted on both sides of the geological radar, and the retraction amount of the geological radar is controlled by pressure sensors.
9. The system of claim 1, wherein the detection mode of the radar detection module comprises: a continuous measurement mode for flat tunnel faces, a point measurement mode for uneven tunnel faces, and a wheel track measurement mode for abnormal body position detection.
10. A working method of a tunnel face advanced geological prediction robot system, which is characterized in that the tunnel face advanced geological prediction robot system of any one of claims 1-9 is adopted, and the working method comprises the following steps:
driving the robot carrying module to run below the primary support, and monitoring the stability of the tunnel face by adopting a collapse monitoring module through rock image acquisition and laser vibration measurement of the tunnel face;
when the face stability monitoring is as good as abnormal, carry the module drive through the robot and move to face below, the horizontal arm of second of control horizontal search arm extends to the same horizontal position with first horizontal arm to stretch out the bearing spike, vertical search arm of simultaneous control erects, makes vertical search arm along horizontal search arm lateral shifting, according to the detection mode of setting for, control geological radar search arm drives geological radar and carries out face advance geology forecast.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115793672A (en) * | 2023-01-09 | 2023-03-14 | 中国地质大学（北京） | Three-dimensional intelligent detection robot and detection method thereof |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115793672A (en) * | 2023-01-09 | 2023-03-14 | 中国地质大学（北京） | Three-dimensional intelligent detection robot and detection method thereof |
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