CN115178400A - Intelligent guniting robot, guniting system and method - Google Patents
Intelligent guniting robot, guniting system and method Download PDFInfo
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- CN115178400A CN115178400A CN202210917608.5A CN202210917608A CN115178400A CN 115178400 A CN115178400 A CN 115178400A CN 202210917608 A CN202210917608 A CN 202210917608A CN 115178400 A CN115178400 A CN 115178400A
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- 238000000034 method Methods 0.000 title claims abstract description 39
- 230000007246 mechanism Effects 0.000 claims abstract description 213
- 239000007921 spray Substances 0.000 claims abstract description 37
- 238000005507 spraying Methods 0.000 claims abstract description 37
- 230000033001 locomotion Effects 0.000 claims description 42
- 238000002347 injection Methods 0.000 claims description 37
- 239000007924 injection Substances 0.000 claims description 37
- 238000012545 processing Methods 0.000 claims description 17
- 238000013441 quality evaluation Methods 0.000 claims description 17
- 238000004458 analytical method Methods 0.000 claims description 12
- 230000002159 abnormal effect Effects 0.000 claims description 11
- 230000001681 protective effect Effects 0.000 claims description 10
- 238000001514 detection method Methods 0.000 claims description 9
- 239000000284 extract Substances 0.000 claims description 4
- 238000009499 grossing Methods 0.000 claims description 3
- 230000011218 segmentation Effects 0.000 claims description 3
- 230000006978 adaptation Effects 0.000 claims 1
- 230000001133 acceleration Effects 0.000 abstract description 3
- 238000013136 deep learning model Methods 0.000 description 10
- 238000010276 construction Methods 0.000 description 6
- 238000013135 deep learning Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 238000005065 mining Methods 0.000 description 3
- 239000002002 slurry Substances 0.000 description 3
- 238000012549 training Methods 0.000 description 3
- 238000009412 basement excavation Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000007613 environmental effect Effects 0.000 description 2
- 238000004886 process control Methods 0.000 description 2
- 238000005070 sampling Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 229910052500 inorganic mineral Inorganic materials 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 239000011707 mineral Substances 0.000 description 1
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- 230000002787 reinforcement Effects 0.000 description 1
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B05—SPRAYING OR ATOMISING IN GENERAL; APPLYING FLUENT MATERIALS TO SURFACES, IN GENERAL
- B05B—SPRAYING APPARATUS; ATOMISING APPARATUS; NOZZLES
- B05B13/00—Machines or plants for applying liquids or other fluent materials to surfaces of objects or other work by spraying, not covered by groups B05B1/00 - B05B11/00
- B05B13/005—Machines or plants for applying liquids or other fluent materials to surfaces of objects or other work by spraying, not covered by groups B05B1/00 - B05B11/00 mounted on vehicles or designed to apply a liquid on a very large surface, e.g. on the road, on the surface of large containers
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B05—SPRAYING OR ATOMISING IN GENERAL; APPLYING FLUENT MATERIALS TO SURFACES, IN GENERAL
- B05B—SPRAYING APPARATUS; ATOMISING APPARATUS; NOZZLES
- B05B12/00—Arrangements for controlling delivery; Arrangements for controlling the spray area
- B05B12/08—Arrangements for controlling delivery; Arrangements for controlling the spray area responsive to condition of liquid or other fluent material to be discharged, of ambient medium or of target ; responsive to condition of spray devices or of supply means, e.g. pipes, pumps or their drive means
- B05B12/12—Arrangements for controlling delivery; Arrangements for controlling the spray area responsive to condition of liquid or other fluent material to be discharged, of ambient medium or of target ; responsive to condition of spray devices or of supply means, e.g. pipes, pumps or their drive means responsive to conditions of ambient medium or target, e.g. humidity, temperature position or movement of the target relative to the spray apparatus
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B05—SPRAYING OR ATOMISING IN GENERAL; APPLYING FLUENT MATERIALS TO SURFACES, IN GENERAL
- B05B—SPRAYING APPARATUS; ATOMISING APPARATUS; NOZZLES
- B05B13/00—Machines or plants for applying liquids or other fluent materials to surfaces of objects or other work by spraying, not covered by groups B05B1/00 - B05B11/00
- B05B13/02—Means for supporting work; Arrangement or mounting of spray heads; Adaptation or arrangement of means for feeding work
- B05B13/04—Means for supporting work; Arrangement or mounting of spray heads; Adaptation or arrangement of means for feeding work the spray heads being moved during spraying operation
- B05B13/0431—Means for supporting work; Arrangement or mounting of spray heads; Adaptation or arrangement of means for feeding work the spray heads being moved during spraying operation with spray heads moved by robots or articulated arms, e.g. for applying liquid or other fluent material to 3D-surfaces
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- E—FIXED CONSTRUCTIONS
- E21—EARTH OR ROCK DRILLING; MINING
- E21D—SHAFTS; TUNNELS; GALLERIES; LARGE UNDERGROUND CHAMBERS
- E21D11/00—Lining tunnels, galleries or other underground cavities, e.g. large underground chambers; Linings therefor; Making such linings in situ, e.g. by assembling
- E21D11/04—Lining with building materials
- E21D11/10—Lining with building materials with concrete cast in situ; Shuttering also lost shutterings, e.g. made of blocks, of metal plates or other equipment adapted therefor
- E21D11/105—Transport or application of concrete specially adapted for the lining of tunnels or galleries ; Backfilling the space between main building element and the surrounding rock, e.g. with concrete
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- General Life Sciences & Earth Sciences (AREA)
- Geochemistry & Mineralogy (AREA)
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- Robotics (AREA)
- Spray Control Apparatus (AREA)
Abstract
The invention discloses an intelligent guniting robot, a guniting system and a method, wherein the robot comprises a chassis with a walking mechanism, a mechanical arm is arranged on the chassis, a spray gun is arranged at the front end of the mechanical arm, the spray gun is provided with a spraying switch for controlling the opening and closing of the spray gun, and the mechanical arm is arranged on the chassis through an action mechanism; the mechanical arm comprises at least two sections of arm units and a joint mechanism, the joint mechanism comprises a rotating mechanism, an angle adjusting mechanism, a telescopic mechanism and a circle drawing mechanism, and all the arm units and the joint mechanism are connected to form the mechanical arm; each action mechanism and each joint mechanism are respectively provided with a driving device; and a three-dimensional scanning device is arranged on the chassis. The intelligent guniting system can realize intelligent guniting operation, improve the operation efficiency, reduce the impact generated by the mechanical arm in the acceleration and deceleration process and monitor the state of the guniting system in the whole process.
Description
Technical Field
The invention belongs to the technical field of spraying equipment, and particularly relates to an intelligent guniting robot, a guniting system and a method.
Background
In the underground construction environment, some channels need to be subjected to guniting reinforcement during construction, such as tunnel excavation construction or mine roadway construction. Taking mine operation as an example, the most important thing in the mining, utilizing and transporting process is the excavation and construction work of the roadway. Therefore, the efficiency of tunneling and guniting of the roadway becomes a key technical problem which restricts the underground mining efficiency. The traditional manual guniting fully relying on the experience type has the problems that the underground construction environment is poor, the labor intensity is high, the potential safety hazard is high, the whole course of the spray gun is vertical to the sprayed surface, the distance between the spray gun and the sprayed surface is uncertain, the guniting thickness is uneven, the quality is unstable, the production efficiency is low and the like. Moreover, manual guniting cannot realize the automation of guniting, the supervision and control on the guniting process is weak, the inspection standards of the guniting quality are inconsistent, and the mining efficiency of minerals is finally seriously influenced.
Patent documents CN104165064 a and CN102913258 a both provide guniting robots dedicated to roadways, but these guniting robots have insufficient moving capability and flexibility, and are difficult to be applied to complex pavements in the pit and work in spaces with more obstacles; the spraying quality can not be judged after comparing the scanning models before and after spraying the slurry on the sprayed surface, and the slurry can be automatically positioned and sprayed on the part which is not satisfied with the quality. At present, a guniting robot with high intelligent degree, high reaction speed, strong environment adaptability and high efficiency is needed.
Disclosure of Invention
In view of the above, an object of the present invention is to provide an intelligent guniting robot.
The technical scheme is as follows:
an intelligent guniting robot comprises a chassis with a walking mechanism, a mechanical arm is arranged on the chassis, a spray gun is arranged at the front end of the mechanical arm, the spray gun is provided with a spraying switch for controlling the opening and closing of the spray gun, and the intelligent guniting robot is characterized in that,
the mechanical arm is arranged on the chassis through an action mechanism;
the mechanical arm comprises at least two sections of arm units and a joint mechanism, the joint mechanism comprises a rotating mechanism, an angle adjusting mechanism, a telescopic mechanism and a circle drawing mechanism, and all the arm units and the joint mechanism are connected to form the mechanical arm;
each action mechanism and each joint mechanism are respectively provided with a driving device;
and a three-dimensional scanning device is arranged on the chassis.
Preferably, the operating mechanism includes a slide mechanism and a turntable;
the sliding part of the sliding mechanism is respectively provided with the rotary table and the three-dimensional scanning device;
the rotary table is provided with the mechanical arm and is used for driving the mechanical arm to horizontally rotate around the rotation center line of the rotary table.
Preferably, the sliding mechanism comprises a sliding guide rail and a guide rail sliding table, the sliding guide rail is matched with the sliding guide rail, the guide rail sliding table is arranged on the chassis, the guide rail sliding table is arranged on the sliding guide rail in a sliding mode, the revolving table is fixedly arranged on the guide rail sliding table, the three-dimensional scanning device is further arranged on the guide rail sliding table, and the three-dimensional scanning device is located in front of the revolving table.
Preferably, the angle adjusting mechanism includes a small arm swing mechanism and a pitching mechanism, both of which are used for adjusting the joint angle in the vertical direction;
the arm unit comprises a large arm, a small arm and an extension arm, the large arm is vertically arranged on the rotary table, the upper end of the large arm is hinged to the rear end of the small arm, the small arm is driven by the small arm swing mechanism to rotate, the front end of the small arm is connected with the extension arm through the telescopic mechanism, the front end of the extension arm is connected with the rotating mechanism, the rotating portion of the rotating mechanism winds the axis rotation of the extension arm, the rotating portion of the rotating mechanism is connected with the pitching mechanism, and the front end of the pitching mechanism is connected with the spray gun through the circle drawing mechanism.
Preferably, the guide rail sliding table is provided with a protective cover, and the three-dimensional scanning device is arranged in the protective cover;
the three-dimensional scanning device is arranged on the guide rail sliding table through an extension mechanism, and the extension mechanism is used for driving the three-dimensional scanning device to extend forwards or retract back to enter the protective cover.
The second objective of the present invention is to provide a guniting system.
The technical scheme is as follows:
a guniting system comprises the intelligent guniting robot, and is characterized by further comprising a controller and an upper computer, wherein the upper computer comprises a memory, a processor, a point cloud data processing mechanism, a guniting quality evaluation mechanism, a motion planning mechanism and a jet planning mechanism, wherein the point cloud data processing mechanism, the guniting quality evaluation mechanism, the motion planning mechanism and the jet planning mechanism are stored in the memory and can run on the processor;
the three-dimensional scanning device is used for acquiring point cloud data of a surface to be gunited, a scanning data output end of the three-dimensional scanning device is connected with a point cloud data input end of the controller, and a point cloud data output end of the controller is connected with a point cloud input end of the upper computer;
the point cloud data processing mechanism is used for: carrying out splicing, denoising and smoothing on the point cloud input into the upper computer, reconstructing an actual tunnel model and extracting a tunnel method vector;
the guniting quality evaluation mechanism is used for: comparing the actual tunnel model with a standard tunnel model, and identifying pit information of a position to be re-sprayed;
the motion planning mechanism is to: generating a motion planning instruction based on the actual tunnel model and the pit information;
the injection planning mechanism is to: generating an injection instruction based on the tunnel normal vector and the pit information;
the motion planning instruction and the injection instruction are output from an instruction signal output end of the upper computer, an instruction signal output end of the upper computer is connected with an instruction signal input end of the controller, and an action signal output end of the controller is connected with the traveling mechanism, the action mechanisms and the driving devices of the joint mechanisms and the spraying switches.
Preferably, the guniting system further comprises a sensor module and an early warning module;
the sensor module is used for collecting the running state data of the robot, the detection signal output end of the sensor module is connected with the detection signal input end of the controller, and the detection signal output end of the controller is connected with the state signal input end of the upper computer;
the memory further has stored thereon an early warning analysis mechanism operable on the processor to: analyzing the state signal input by the controller, identifying an abnormal state, and generating an early warning instruction according to the abnormal state;
the early warning instruction output end of the upper computer is connected with the early warning instruction input end of the controller, and the early warning signal output end of the controller is connected with the early warning signal receiving end of the early warning module.
The invention also aims to provide a guniting method.
The technical scheme is as follows:
the guniting method is based on the guniting system and is characterized by comprising the following steps:
s1, identifying and modeling a surface to be gunited: the three-dimensional scanning device scans and collects tunnel point clouds and transmits the tunnel point clouds to the upper computer through the controller, and the point cloud data processing mechanism processes the tunnel point clouds, reconstructs an actual tunnel model and extracts a tunnel method vector;
step S2, primary guniting: the motion planning mechanism generates a motion planning instruction based on the actual tunnel model, meanwhile, the injection planning mechanism generates an injection instruction based on the tunnel normal vector and transmits the injection instruction to the controller, and the controller generates an action signal and transmits the action signal to the action mechanism and the driving device and the spraying switch of the joint mechanism, so that the intelligent guniting robot controls the gunjet to move at a constant speed and guniting along the tunnel normal vector direction;
s3, carrying out guniting quality evaluation, and identifying a position to be sprayed again: the three-dimensional scanning device scans local areas of the sprayed tunnel inner wall again and collects tunnel point clouds, the point cloud data processing mechanism reconstructs an actual tunnel model again and extracts a tunnel method vector, and the guniting quality comparison mechanism compares the reconstructed actual tunnel model with a standard tunnel model and identifies pit information of a position to be re-sprayed;
step S4, re-spraying: the motion planning mechanism and the injection planning mechanism generate a motion planning instruction and an injection instruction based on the pit information and the tunnel normal vector in the S3 and transmit the motion planning instruction and the injection instruction to the controller, and the controller generates an action signal and transmits the action signal to the action mechanism and the driving device of the joint mechanism and the spraying switch, so that the intelligent guniting robot controls the spray gun to carry out guniting again on the position to be subjected to re-spraying;
and S5, circularly repeating the steps S3 and S4 until the guniting is finished.
Preferably, in step S3, the guniting quality evaluation mechanism operates based on a guniting quality evaluation identification algorithm, the guniting quality evaluation identification algorithm calculates the point cloud thickness based on a tetrahedral segmentation method, and determines the guniting quality and identifies the hole information of the position to be re-sprayed by comparing the actual tunnel model with the standard tunnel model.
Preferably, in the steps S2 to S5, the sensor module and the early warning analysis mechanism continuously work, monitor the operation state data of the driving devices of the traveling mechanism, the action mechanism and the joint mechanism, recognize an abnormal state and generate an early warning signal, and then transmit the early warning signal to the controller, the controller generates an early warning instruction and transmits the early warning instruction to the early warning module, and the early warning module sends an early warning prompt.
Compared with the prior art, the invention has the beneficial effects that:
(1) The multi-joint robot can flexibly adjust the pose, and intelligent guniting operation can be realized by using a three-dimensional scanning and point cloud technology and an intelligent control technology;
(2) By planning the motion path and the track of the robot, the obstacle can be automatically avoided, the operation efficiency of the guniting robot is improved, and the impact generated by the mechanical arm in the acceleration and deceleration process is reduced;
(3) Automatic spraying is guided through intelligent spraying quality evaluation and defect identification;
(4) The invention reconstructs different pit hole appearances and calculates the volumes of the pit hole appearances through point cloud data, and intelligently adjusts the spraying angle, the distance and the spraying flow of a spray gun through a deep learning algorithm;
(5) The guniting robot is provided with sensors at multiple positions, collects, uploads and stores operation data, monitors the operation state in real time through big data and deep learning algorithm training, and can predict and alarm faults through a monitoring system.
Drawings
Fig. 1 is a schematic structural diagram of a guniting robot according to a first embodiment of the invention;
FIG. 2 is a schematic diagram of a guniting system according to a second embodiment of the invention;
FIG. 3 is a flow chart of a guniting quality rating and identification algorithm according to a second embodiment of the invention;
FIG. 4 is a flowchart of a deep learning algorithm according to a second embodiment of the present invention;
FIG. 5 is a schematic process control diagram of a third embodiment of the present invention;
fig. 6 is a flow chart of a guniting method according to a third embodiment of the invention.
Detailed Description
The present invention will be further described with reference to the following examples and the accompanying drawings.
Example one
Referring to fig. 1, an intelligent guniting robot includes a chassis 100 having a traveling mechanism 101, a robot arm 300 mounted on the chassis 100, and a spray gun provided with a spray switch for controlling the opening and closing of the spray gun, the spray gun being mounted at a front end of the robot arm 300. The mechanical arm 300 is mounted on the chassis 100 through a motion mechanism; the robot arm 300 includes at least two sections of arm units and joint mechanisms, each of which includes a rotation mechanism 360, an angle adjustment mechanism, a telescoping mechanism 340, and a circle drawing mechanism 380, and all the arm units and the joint mechanisms are connected to form the robot arm 300. And each action mechanism and each joint mechanism are respectively provided with a driving device.
The chassis 100 is mounted with a three-dimensional scanning apparatus 200.
The walking mechanism 101 is used for the overall movement of the robot, the action mechanism is used for the movement and adjustment of the mechanical arm 300 on the chassis 100, the joint mechanism on the mechanical arm 300 is used for the posture adjustment in the three-dimensional space thereof, so that the spray gun can be positioned at a proper position and the surface to be sprayed is sprayed at a proper angle, and the local area is uniformly sprayed by means of the circle drawing mechanism. The three-dimensional scanning device 200 is used to acquire environmental information in front of the robot, thereby guiding the robot to work.
The running gear 101 may be a crawler belt.
In one embodiment, the motion mechanism includes a slide mechanism 110 and a turntable 120. The rotary table 120 and the three-dimensional scanning device 200 are respectively mounted on the sliding part of the sliding mechanism 110; the rotary table 120 is provided with the mechanical arm 300, and the rotary table 120 is used for driving the mechanical arm 300 to horizontally rotate around the rotation center line of the rotary table 120. When the traveling mechanism 101 is stopped, the turn table 120 is moved on the base plate 100 by means of the slide mechanism to adjust the position, and the turn table 120 facilitates the overall horizontal direction rotation of the robot arm 300.
The sliding mechanism 110 includes a sliding guide rail 111 and a guide rail sliding table 112, the sliding guide rail 111 is fixedly mounted on the chassis 100, the sliding guide rail 111 is slidably provided with the guide rail sliding table 112, the guide rail sliding table 112 is fixedly mounted with the rotary table 120, the guide rail sliding table 112 is further provided with the three-dimensional scanning device 200, and the three-dimensional scanning device 200 is located in front of the rotary table 120. In this way, the three-dimensional scanning device 200 can always acquire environmental information of the area in front of the robot arm 300. In this embodiment, the angle adjustment mechanism includes the arm swing mechanism 330 and the pitch mechanism 370, both of which are used to adjust the joint angle in the vertical direction. The arm unit comprises a large arm 310, a small arm 320 and an elongated arm 350, wherein the large arm 310 is vertically arranged on the rotary table 120, and the mechanical arm 300 rotates around the axis of the large arm 310 along with the rotary table 120. The upper end of the large arm 310 is hinged to the rear end of the small arm 320 and driven by the small arm swing mechanism 330 to rotate the small arm 320, the front end of the small arm 320 is connected with the lengthening arm 350 through the telescopic mechanism 340, the front end of the lengthening arm 350 is connected with the rotating mechanism 360, the rotating part of the rotating mechanism 360 rotates around the axis of the lengthening arm 350, the rotating part of the rotating mechanism 360 is connected with the pitching mechanism 370, and the front end of the pitching mechanism 370 is connected with the spray gun through the circle drawing mechanism 380.
Through the adjustment of a plurality of joints, the mechanical arm 300 has strong flexibility and can cover the spraying range of 0-2.6 m.
The guide rail sliding table 112 is provided with a protective cover 220, and the three-dimensional scanning device 200 is arranged in the protective cover 220. The three-dimensional scanning device 200 may be a three-dimensional laser scanner.
The three-dimensional scanning apparatus 200 is mounted on the rail slide table 112 by an extension mechanism 210. The extending mechanism 210 may be a telescopic cylinder, and the extending mechanism 210 is used to drive the three-dimensional scanning device 200 to extend forward or retract into the protective cover 220, so as to protect the three-dimensional scanning device 200 and extend out of the protective cover 220 only during scanning.
Example two
As shown in fig. 2, a guniting system comprises the intelligent guniting robot, a controller 600 and an upper computer 700, wherein the upper computer 700 comprises a memory 710, a processor 720, a point cloud data processing mechanism 711, a guniting quality evaluation mechanism 712, a motion planning mechanism 713 and an injection planning mechanism 714, which are stored in the memory 710 and can run on the processor 720. The running mechanism 101, the action mechanism, the joint mechanism and the spraying switch of the guniting robot together form an execution module of the guniting system, and the controller 600 and the upper computer 700 form a control module of the system. The controller 600 and the upper computer 700 are provided with an input terminal group and an output terminal group of signals or commands, respectively.
The three-dimensional scanning device 200 is used for acquiring point cloud data of a surface to be gunited, the scanning data output end of the three-dimensional scanning device 200 is connected with the point cloud data input end of the controller 600, and the point cloud data output end of the controller 600 is connected with the point cloud input end of the upper computer 700. When scanning, a reference position is calibrated, for example, a ground center position of a tunnel entrance or a certain section of a tunnel is selected as a reference position, and a three-dimensional coordinate system is established by taking the reference position as a coordinate origin.
In addition, the three-dimensional scanning device 200 can also acquire point cloud data of an obstacle in front of the robot, and the point cloud data is transmitted to the upper computer 700 through the controller 600 to reconstruct an obstacle model, so that the robot is guided to move to avoid the obstacle.
The point cloud data processing unit 711 is configured to: and performing splicing, denoising and smoothing on the point cloud input into the upper computer 700, reconstructing an actual tunnel model and extracting a tunnel method vector.
The point cloud data processing mechanism 711 operates based on a three-dimensional reconstruction algorithm of a PCL library to reconstruct a tunnel model, establish a spraying model, and display the spraying model on the upper computer 700 in real time as required.
The guniting quality evaluation mechanism 712 is configured to: and comparing the actual tunnel model with a standard tunnel model, and identifying the pit information of the position to be re-sprayed. The standard tunnel model is a tunnel design model, point cloud data of the standard tunnel model is provided by a tunnel designer, and the point cloud data of the standard tunnel model is stored in the upper computer 700 in advance.
Specifically, the guniting quality rating mechanism 712 operates based on a guniting quality rating identification algorithm, the guniting quality rating identification algorithm calculates the point cloud thickness based on a tetrahedral segmentation method, the guniting quality is judged through comparison of an actual tunnel model and a standard tunnel model, and pit information of a position to be re-sprayed is identified. And then, automatically positioning and re-spraying the part of which the spraying thickness does not meet the requirement, and realizing the automatic control of the spraying quality.
As shown in fig. 3, the operation process of the guniting quality evaluation identification algorithm is that after the standard tunnel point cloud and the actual tunnel point cloud are preprocessed, the four corner surfaces on the standard tunnel point cloud are used as the bottom, the normal vector pointing to the outside is the growth direction, and the operation is stopped when the actual point cloud grows to the outside to form the quadrangular frustum pyramid. Setting sampling distances, counting the sum of the volumes of the quadrangular frustum in the local area at intervals of the sampling distances to obtain the local volume to be gunned of the tunnel, and dividing the local volume to be gunned of the tunnel by the bottom area of the quadrangular frustum to obtain the local thickness to be gunned. And if the thickness of the local area to be gunited is larger than 0, recording the point coordinate in the database. And if the thickness of the local area to be sprayed is equal to 0, skipping the local area and detecting and identifying the next adjacent local area. And obtaining the appearance of the pit according to the local thickness to be sprayed with the slurry. The identified pit information of the position to be repeatedly sprayed comprises coordinates, morphology and volume.
The motion planning mechanism 713 is configured to: and generating a motion planning instruction based on the actual tunnel model and the pit information. Referring to the prior art, for example, patent document CN109358500a discloses a control method for a tunnel intelligent concrete guniting robot, which uses mechanical arm kinematics calculation in combination with a tunnel three-dimensional scanning modeling technique to solve an optimal spraying trajectory, where the generated motion planning instruction is an action signal for controlling each action mechanism or a driving device of the action mechanism. The motion planning comprises two aspects of planning of a motion path of the robot and planning of a motion track of the spray gun, so that the operation stroke and the action of the robot are optimized, the efficiency of guniting operation is improved, and the impact generated by the mechanical arm in the acceleration and deceleration process is reduced. The motion planning mechanism 713 may also reconstruct an obstacle model according to the obstacle point cloud data input to the upper computer 700 when performing motion planning, and may also cause the motion path of the robot to avoid an obstacle.
The injection planning mechanism 714 is configured to: and generating an injection instruction based on the tunnel normal vector and the pit information.
The motion planning instruction and the injection instruction are output from an instruction signal output end of the upper computer 700, an instruction signal output end of the upper computer 700 is connected with an instruction signal input end of the controller 600, and an action signal output end of the controller 600 is connected with the walking mechanism 101, driving devices of the action mechanisms and the joint mechanisms and the spraying switch.
During the spraying operation, the spraying command is further combined with the normal vector of the tunnel, and each joint mechanism of the robot 300 is adjusted by the controller 600 so that the spray gun is perpendicular to the spraying surface during spraying. Referring to the prior art, this method for adjusting the attitude of the spray gun is disclosed in patent document CN110653137a, for example, a spray method for keeping a spray head perpendicular to a spray surface.
In order to maintain the robot working normally, the guniting system further comprises a sensor module 400 and an early warning module 500.
The memory 710 further has stored thereon an alert analysis mechanism 715 operable on the processor 720, the alert analysis mechanism 715 to: analyzing the state signal input by the controller 600, identifying an abnormal state, and generating an early warning instruction according to the abnormal state;
the early warning instruction output end of the upper computer 700 is connected with the early warning instruction input end of the controller 600, and the early warning signal output end of the controller 600 is connected with the early warning signal receiving end of the early warning module 500.
The injection planning mechanism 714 and the early warning analysis mechanism 715 respectively generate an injection instruction and an early warning instruction based on the deep learning model, and the model training process is shown in fig. 4.
The injection planning mechanism 714 is based on a deep learning model 1, and the building process of the model is as follows: taking the pit information such as different pit morphology and volume data in the database as the input of the deep learning model 1, and taking the spray angle, distance and spray flow of the spray gun as the model output to train the deep learning model 1. Specifically, the morphology and the volume of the pot hole are input into the deep learning model 1 to calculate and predict the spray angle, the distance and the spray flow of the spray gun, and the data are stored as the next round of training data; according to the data calculated and predicted each time, generating an injection instruction, and controlling the mechanical arm 300 to adjust the injection angle and the injection flow rate to perform injection; and after the spraying is finished, carrying out guniting quality evaluation, identifying the pit information of the position to be subjected to repeated spraying, and inputting the deep learning model 1 again until the thickness of the guniting to be carried out in the local area is equal to 0. The injection flow and angle are manually set at the time of initial injection.
The early warning analysis mechanism 715 is based on a deep learning model 2, and the building process of the model is as follows: the model 2 is trained by using data such as current and temperature of the motors of the driving devices of the motion mechanism and the joint mechanism in different states as input of the model 2 and using operation state data corresponding to the motors as output of the model 2. Specifically, the sensor module 400 includes at least two sensors, each of which collects the current and temperature of the motor during operation in real time as the input of the deep learning model 2, and the deep learning model 2 outputs the operation state data of the motor; and comparing the running state data with the reference data according to the set running state data as a reference, judging that the running state is normal or abnormal, and outputting an early warning signal by an early warning analysis mechanism 715 in the abnormal state. Through the deep learning model 2, the early warning analysis mechanism 715 can monitor the running state of the guniting robot in real time, and carry out fault prediction and alarm.
The various data processing mechanisms on memory 710 are stored in the form of control software. The guniting system is provided with a necessary signal receiving feedback device and a remote controller, and the guniting robot can be manually operated through the remote controller or can automatically run to carry out guniting.
The robot can be powered by a hydraulic system, can stably and automatically adjust the traction speed in a given range, and can realize stepless speed regulation; the reversing is easy, the operation and control are simple and convenient, and the automation degree is high; overload protection is easy to realize; the anti-interference performance is strong.
EXAMPLE III
A guniting method is based on the guniting system of the second embodiment, the process control is shown in fig. 5, the guniting process is shown in fig. 6, and the concrete steps are as follows:
s1, identifying and modeling a surface to be gunited: calibrating a reference position and establishing a coordinate system, scanning and acquiring tunnel point cloud by the three-dimensional scanning device 200, transmitting the tunnel point cloud to the upper computer 700 through the controller 600, processing the tunnel point cloud by the point cloud data processing mechanism 711, reconstructing an actual tunnel model and extracting a tunnel method vector;
step S2, primary guniting: the motion planning mechanism 713 generates a motion planning instruction based on the actual tunnel model, the injection planning mechanism 714 generates an injection instruction based on the tunnel normal vector and transmits the injection instruction to the controller 600, and the controller 600 generates an action signal and transmits the action signal to the actuating mechanism and the driving device of the joint mechanism and the spraying switch, so that the intelligent guniting robot controls the spray gun to move at a constant speed and guniting along the direction of the tunnel normal vector;
s3, carrying out guniting quality evaluation, and identifying a position to be sprayed again: the three-dimensional scanning device 200 scans the local area of the sprayed tunnel inner wall again and collects the point cloud of the tunnel, the point cloud data processing mechanism 711 reconstructs an actual tunnel model again and extracts a tunnel method vector, and the guniting quality comparing mechanism 712 compares the reconstructed actual tunnel model with a standard tunnel model and identifies the pit information of the position to be sprayed again;
step S4, re-spraying: the motion planning mechanism 713 and the injection planning mechanism 714 generate a motion planning instruction and an injection instruction based on the pit information and the tunnel normal vector in the step S3 and transmit the motion planning instruction and the injection instruction to the controller 600, and the controller 600 generates an action signal and transmits the action signal to the actuating mechanism and the driving device of the joint mechanism and the spraying switch, so that the intelligent guniting robot controls the gunjet to guniting the position to be re-gunned again;
and S5, circularly repeating the steps S3 and S4 until the guniting is finished.
In the steps S2 to S5, the sensor module 400 and the early warning analysis mechanism 715 continuously operate to monitor the operation state data of the driving devices of the traveling mechanism 101, the action mechanism, and the joint mechanism, identify an abnormal state and generate an early warning signal, and then transmit the early warning signal to the controller 600, the controller 600 generates an early warning instruction and transmits the early warning instruction to the early warning module 500, and the early warning module 500 sends an early warning prompt.
The guniting system and the guniting method can realize intelligent automatic guniting operation.
Finally, it should be noted that the above-mentioned description is only a preferred embodiment of the present invention, and those skilled in the art can make various similar representations without departing from the spirit and scope of the present invention.
Claims (10)
1. The utility model provides an intelligence whitewashing robot, is including chassis (100) that have running gear (101), installs arm (300) on this chassis (100), and the spray gun is installed to the front end of this arm (300), the spray gun is provided with the spraying switch that is used for controlling its switching, its characterized in that:
the mechanical arm (300) is arranged on the chassis (100) through an action mechanism;
the mechanical arm (300) comprises at least two sections of arm units and joint mechanisms, each joint mechanism comprises a rotating mechanism (360), an angle adjusting mechanism, a telescopic mechanism (340) and a circle drawing mechanism (380), and all the arm units and the joint mechanisms are connected to form the mechanical arm (300);
each action mechanism and each joint mechanism are respectively provided with a driving device;
the chassis (100) is provided with a three-dimensional scanning device (200).
2. The intelligent guniting robot according to claim 1, wherein: the action mechanism comprises a sliding mechanism (110) and a rotary table (120);
the rotary table (120) and the three-dimensional scanning device (200) are respectively arranged on the sliding part of the sliding mechanism (110);
the mechanical arm (300) is mounted on the rotary table (120), and the rotary table (120) is used for driving the mechanical arm (300) to horizontally rotate around the rotation center line of the rotary table (120).
3. The intelligent guniting robot as claimed in claim 2, wherein: slide mechanism (110) include sliding guide (111) of looks adaptation and conduct the guide rail slip table (112) of sliding part, sliding guide (111) fixed mounting be in on chassis (100), sliding guide (111) go up to slide and be provided with guide rail slip table (112), fixed mounting has on guide rail slip table (112) revolving platform (120), still be provided with on guide rail slip table (112) three-dimensional scanning device (200), three-dimensional scanning device (200) are located revolving platform (120) the place ahead.
4. The intelligent guniting robot according to claim 3, wherein: the angle adjusting mechanism comprises a small arm swinging mechanism (330) and a pitching mechanism (370), and the small arm swinging mechanism and the pitching mechanism are used for adjusting the joint angle in the vertical direction;
the arm unit comprises a large arm (310), a small arm (320) and an extension arm (350), wherein the large arm (310) is vertically arranged on the rotary table (120), the upper end of the large arm (310) is hinged with the rear end of the small arm (320) and driven by the small arm swinging mechanism (330) to rotate the small arm (320), the front end of the small arm (320) is connected with the extension arm (350) through the telescopic mechanism (340), the front end of the extension arm (350) is connected with the rotating mechanism (360), the rotating part of the rotating mechanism (360) winds the axis of the extension arm (350) to rotate, the rotating part of the rotating mechanism (360) is connected with the pitching mechanism (370), and the front end of the pitching mechanism (370) is connected with the spray gun through the circle drawing mechanism (380).
5. The intelligent guniting robot according to claim 3 or 4, wherein: a protective cover (220) is arranged on the guide rail sliding table (112), and the three-dimensional scanning device (200) is arranged in the protective cover (220);
the three-dimensional scanning device (200) is arranged on the guide rail sliding table (112) through an extension mechanism (210), and the extension mechanism (210) is used for driving the three-dimensional scanning device (200) to extend forwards or retract back to enter the protective cover (220).
6. A guniting system comprising the intelligent guniting robot according to any one of claims 1 to 5, wherein: the system is characterized by further comprising a controller (600) and an upper computer (700), wherein the upper computer (700) comprises a memory (710), a processor (720), a point cloud data processing mechanism (711), a guniting quality evaluation mechanism (712), a motion planning mechanism (713) and a spray planning mechanism (714), wherein the point cloud data processing mechanism (711), the guniting quality evaluation mechanism, the motion planning mechanism (713) and the spray planning mechanism are stored in the memory (710) and can run on the processor (720);
the three-dimensional scanning device (200) is used for acquiring point cloud data of a surface to be gunited, the scanning data output end of the three-dimensional scanning device (200) is connected with the point cloud data input end of the controller (600), and the point cloud data output end of the controller (600) is connected with the point cloud input end of the upper computer (700);
the point cloud data processing means (711) is configured to: carrying out splicing, denoising and smoothing treatment on the point cloud input into the upper computer (700), reconstructing an actual tunnel model and extracting a tunnel method vector;
the guniting quality evaluation mechanism (712) is used for: comparing the actual tunnel model with a standard tunnel model, and identifying pit information of a position to be re-sprayed;
the motion planning mechanism (713) is configured to: generating a motion planning instruction based on the actual tunnel model and the pit information;
the injection planning mechanism (714) is configured to: generating an injection instruction based on the tunnel normal vector and the pit information;
the motion planning instruction and the injection instruction are output from the instruction signal output end of the upper computer (700), the instruction signal output end of the upper computer (700) is connected with the instruction signal input end of the controller (600), and the action signal output end of the controller (600) is connected with the traveling mechanism (101), the traveling mechanism and the joint mechanism, and the driving device and the spraying switch of the action mechanism and the joint mechanism.
7. The guniting system according to claim 6, wherein: the system also comprises a sensor module (400) and an early warning module (500);
the sensor module (400) is used for collecting the running state data of the robot, the detection signal output end of the sensor module (400) is connected with the detection signal input end of the controller (600), and the detection signal output end of the controller (600) is connected with the state signal input end of the upper computer (700);
the memory (710) further has stored thereon a warning analysis mechanism (715) operable on the processor (720), the warning analysis mechanism (715) for: analyzing the state signal input by the controller (600), identifying an abnormal state, and generating an early warning instruction according to the abnormal state;
the early warning instruction output end of the upper computer (700) is connected with the early warning instruction input end of the controller (600), and the early warning signal output end of the controller (600) is connected with the early warning signal receiving end of the early warning module (500).
8. A guniting method based on the guniting system according to claim 7, characterized by comprising the steps of:
s1, identifying and modeling a surface to be gunited: the three-dimensional scanning device (200) scans and collects tunnel point clouds, the tunnel point clouds are transmitted to the upper computer (700) through the controller (600), the tunnel point clouds are processed by the point cloud data processing mechanism (711), an actual tunnel model is reconstructed, and a tunnel normal vector is extracted;
step S2, primary guniting: the motion planning mechanism (713) generates a motion planning instruction based on the actual tunnel model, meanwhile, the injection planning mechanism (714) generates an injection instruction based on the tunnel normal vector and transmits the injection instruction to the controller (600), and the controller (600) generates an action signal and transmits the action signal to the action mechanism and a driving device and a spraying switch of a joint mechanism, so that the intelligent guniting robot controls the spray gun to move at a constant speed and guniting along the direction of the tunnel normal vector;
s3, evaluating the quality of the guniting, and identifying the position to be subjected to repeated guniting: the three-dimensional scanning device (200) scans local areas of the sprayed tunnel inner wall again and collects tunnel point cloud, the point cloud data processing mechanism (711) reconstructs an actual tunnel model again and extracts a tunnel method vector, and the guniting quality evaluation mechanism (712) compares the reconstructed actual tunnel model with a standard tunnel model to identify pit information of a position to be sprayed again;
step S4, re-spraying: the motion planning mechanism (713) and the injection planning mechanism (714) generate a motion planning instruction and an injection instruction and transmit the motion planning instruction and the injection instruction to the controller (600) based on the pit hole information and the tunnel normal vector in the S3, and the controller (600) generates an action signal and transmits the action signal to the actuating mechanism and the driving device and the spraying switch of the joint mechanism, so that the intelligent guniting robot controls the spray gun to carry out guniting again on the position to be re-sprayed;
and S5, circularly repeating the steps S3 and S4 until the guniting is finished.
9. The guniting method according to claim 8, wherein: in the step S3, the guniting quality scale identifying mechanism (712) operates based on a guniting quality scale identifying algorithm, the guniting quality scale identifying algorithm calculates the point cloud thickness based on a tetrahedral segmentation method, and by comparing an actual tunnel model with a standard tunnel model, the guniting quality is determined, and the hole information of the position to be re-sprayed is identified.
10. The guniting method according to claim 8, characterized by comprising the steps of: in the steps S2-S5, the sensor module (400) and the early warning analysis mechanism (715) continuously work, the running state data of the driving devices of the walking mechanism (101), the action mechanism and the joint mechanism are monitored, abnormal states are identified, early warning signals are generated and transmitted to the controller (600), the controller (600) generates early warning instructions and transmits the early warning instructions to the early warning module (500), and the early warning module (500) sends out early warning prompts.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116441094A (en) * | 2023-04-20 | 2023-07-18 | 云南途腾智能装备有限公司 | Guniting mechanical arm for concrete wet spraying trolley |
Citations (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201809983U (en) * | 2010-01-19 | 2011-04-27 | 湖南中铁五新重工有限公司 | Wet shotcreting machine |
| CN102913258A (en) * | 2012-10-23 | 2013-02-06 | 游天月 | Special automatic guniting mechanical arm for tunnel |
| CN103775103A (en) * | 2014-02-26 | 2014-05-07 | 徐州徐工施维英机械有限公司 | Grouting manipulator |
| CN104165064A (en) * | 2014-08-15 | 2014-11-26 | 山东科技大学 | Shotcreting mechanical arm with six-foot walking device |
| CN108979668A (en) * | 2018-07-17 | 2018-12-11 | 中铁工程装备集团有限公司 | The information intelligent construction method and system of wet shot trolley |
| CN109015673A (en) * | 2018-07-27 | 2018-12-18 | 江苏省中跃涂装设备有限公司 | A kind of spray robot device |
| CN109471434A (en) * | 2018-11-09 | 2019-03-15 | 江苏大学 | A kind of novel variable rate spray path planning autonomous navigation system and method |
| CN110743735A (en) * | 2019-10-17 | 2020-02-04 | 佛山智能装备技术研究院 | Intelligent spraying system based on robot platform |
| US20200122178A1 (en) * | 2015-08-27 | 2020-04-23 | Forjak Industrial, Inc. | System for treating a surface and components thereof |
| CN111828042A (en) * | 2020-06-23 | 2020-10-27 | 哈尔滨工业大学 | Intelligent guniting support method for wall surface overexcavation tunnel |
| CN112008722A (en) * | 2020-08-20 | 2020-12-01 | 王献 | Control method and control device for construction robot and robot |
| CN113231227A (en) * | 2021-05-06 | 2021-08-10 | 清华大学 | Spraying robot |
| US20210331191A1 (en) * | 2020-04-22 | 2021-10-28 | Nanjing University Of Aeronautics And Astronautics | Method for automatic glue-spraying of stringer and inspection of glue-spraying quality |
| CN114029957A (en) * | 2021-12-10 | 2022-02-11 | 渭南陕煤启辰科技有限公司 | Intelligent control system of guniting robot |
| CN114146850A (en) * | 2021-12-03 | 2022-03-08 | 山东泽明能源科技有限公司 | Intelligent guniting robot |
| CN114444386A (en) * | 2022-01-19 | 2022-05-06 | 中国能源建设集团安徽省电力设计院有限公司 | Fire early warning and post-disaster floor damage prediction method and system based on BIM and deep learning |
| CN114495468A (en) * | 2022-01-10 | 2022-05-13 | 广州高新兴机器人有限公司 | Robot fault state monitoring and early warning method, electronic equipment and storage medium |
-
2022
- 2022-08-01 CN CN202210917608.5A patent/CN115178400A/en active Pending
Patent Citations (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201809983U (en) * | 2010-01-19 | 2011-04-27 | 湖南中铁五新重工有限公司 | Wet shotcreting machine |
| CN102913258A (en) * | 2012-10-23 | 2013-02-06 | 游天月 | Special automatic guniting mechanical arm for tunnel |
| CN103775103A (en) * | 2014-02-26 | 2014-05-07 | 徐州徐工施维英机械有限公司 | Grouting manipulator |
| CN104165064A (en) * | 2014-08-15 | 2014-11-26 | 山东科技大学 | Shotcreting mechanical arm with six-foot walking device |
| US20200122178A1 (en) * | 2015-08-27 | 2020-04-23 | Forjak Industrial, Inc. | System for treating a surface and components thereof |
| CN108979668A (en) * | 2018-07-17 | 2018-12-11 | 中铁工程装备集团有限公司 | The information intelligent construction method and system of wet shot trolley |
| CN109015673A (en) * | 2018-07-27 | 2018-12-18 | 江苏省中跃涂装设备有限公司 | A kind of spray robot device |
| CN109471434A (en) * | 2018-11-09 | 2019-03-15 | 江苏大学 | A kind of novel variable rate spray path planning autonomous navigation system and method |
| CN110743735A (en) * | 2019-10-17 | 2020-02-04 | 佛山智能装备技术研究院 | Intelligent spraying system based on robot platform |
| US20210331191A1 (en) * | 2020-04-22 | 2021-10-28 | Nanjing University Of Aeronautics And Astronautics | Method for automatic glue-spraying of stringer and inspection of glue-spraying quality |
| CN111828042A (en) * | 2020-06-23 | 2020-10-27 | 哈尔滨工业大学 | Intelligent guniting support method for wall surface overexcavation tunnel |
| CN112008722A (en) * | 2020-08-20 | 2020-12-01 | 王献 | Control method and control device for construction robot and robot |
| CN113231227A (en) * | 2021-05-06 | 2021-08-10 | 清华大学 | Spraying robot |
| CN114146850A (en) * | 2021-12-03 | 2022-03-08 | 山东泽明能源科技有限公司 | Intelligent guniting robot |
| CN114029957A (en) * | 2021-12-10 | 2022-02-11 | 渭南陕煤启辰科技有限公司 | Intelligent control system of guniting robot |
| CN114495468A (en) * | 2022-01-10 | 2022-05-13 | 广州高新兴机器人有限公司 | Robot fault state monitoring and early warning method, electronic equipment and storage medium |
| CN114444386A (en) * | 2022-01-19 | 2022-05-06 | 中国能源建设集团安徽省电力设计院有限公司 | Fire early warning and post-disaster floor damage prediction method and system based on BIM and deep learning |
Non-Patent Citations (4)
| Title |
|---|
| 李云江, 樊炳辉, 荣学文, 江浩: "喷浆机器人的研制与开发", 市政技术, no. 01, pages 10 - 14 * |
| 李琼砚等主编: "智能制造概论", vol. 1, 30 April 2021, 机械工业出版社, pages: 74 - 80 * |
| 甘淇匀等: "国内外隧道监控量测技术发展现状综述", 地下空间与工程学报, vol. 15, pages 400 - 415 * |
| 贺勃涛;辛鹏飞;朱栋;李军委;康黎明;: "基于三维激光扫描仪对深基坑实时监测与动态管理", 建筑结构, no. 1, pages 1038 - 1043 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116441094A (en) * | 2023-04-20 | 2023-07-18 | 云南途腾智能装备有限公司 | Guniting mechanical arm for concrete wet spraying trolley |
| CN116441094B (en) * | 2023-04-20 | 2023-12-29 | 云南途腾智能装备有限公司 | Guniting mechanical arm for concrete wet spraying trolley |
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