CN115807543A - Concrete pouring method based on image recognition and laser radar data fusion - Google Patents
Concrete pouring method based on image recognition and laser radar data fusion Download PDFInfo
- Publication number
- CN115807543A CN115807543A CN202211577232.4A CN202211577232A CN115807543A CN 115807543 A CN115807543 A CN 115807543A CN 202211577232 A CN202211577232 A CN 202211577232A CN 115807543 A CN115807543 A CN 115807543A
- Authority
- CN
- China
- Prior art keywords
- pouring
- area
- concrete
- poured
- construction
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Abstract
The invention discloses a concrete pouring method based on image recognition and laser radar data fusion, which comprises the following steps: the method comprises the following steps: acquiring path planning data of a structured building structure to be poured, and planning a pouring path according to the method; step two: further planning the track of the movement of the tail end of the mechanical arm of the distributing machine according to the planned pouring information in the first step; step three: calculating the amount to be poured in the area by fusing image recognition and laser radar data; step four: and judging whether the pouring water overflows or not, and installing a flowmeter device for measuring the actual pouring amount. According to the automatic concrete pouring metering method based on image recognition and laser radar data fusion, automatic pouring of an automatic distributing machine is achieved, concrete pouring operation of various complex structures is facilitated, pouring amount of each pouring structure is calculated, concrete is more uniformly accumulated, a formwork cannot overflow, full-automatic pouring construction is achieved, and construction quality and efficiency are improved.
Description
Technical Field
The invention relates to the technical field of intelligent construction in the construction industry, in particular to a concrete pouring method based on image recognition and laser radar data fusion.
Background
At present, most of the constructions of highway bridges, airport ports, building structures and the like adopt a concrete pouring construction mode, and in the current construction process, the concrete is mainly conveyed in a pumping mode, namely, the concrete is regarded as fluid with certain concentration, and the concrete is conveyed by means of plunger thrust of a concrete conveying pump and a pipeline. At the end of the transfer pipe, a concrete spreader is connected, which receives the transferred concrete and then, with the cooperation of workers, pours the concrete into the space between the mesh reinforcement and the formwork, thereby forming a corresponding engineering structure.
The concrete spreader is mainly divided into a manual type and an automatic type. The manual type cloth machine's operation mode is around revolving the support rotation and two sections arm supports folding removal under the rope is pulled to the manpower to realize that the discharge gate removes and waits to pour regional concreting. The operation mode of the automatic distributing machine is a wired remote control mode, and hydraulic drive is adopted to control the Z-shaped folding arm support to move to a region to be poured so as to realize concrete pouring.
In the final pouring link of the concrete spreader, constructors move by holding hoses to pour concrete delivered by a pump into templates at different positions in a to-be-poured area, predict the pouring amount and visually inspect the actual pouring amount according to experience, manually level the bins, scrape the bars and vibrate by the constructors to ensure that the concrete poured in the templates is compactly leveled, and then the concrete is matched with operators of the spreader to reach different areas of a spreader discharge port in a coverage area so as to complete the pouring task of the coverage area of the spreader,
however, the traditional concrete pouring mainly depends on a large amount of manual work, and is matched with mechanical devices such as a concrete spreader, a concrete delivery pump and the like, the whole technology is relatively backward, in addition, the concrete pouring mainly predicts the pouring amount by field construction personnel by experience, the pouring amount is visually observed in the construction process, the pouring state and the next to-be-poured area are fed back to an operator of the spreader, the operator of the spreader controls an outlet of the spreader to move to a corresponding area, the manual feedback mode cannot keep the coordination, the moving time of the spreader can be advanced or lagged, so that concrete overflows a template, and the concrete is wasted; meanwhile, the metering of each area is not accurate enough and the pouring is not uniform easily, so that a concrete pouring method based on image recognition and laser radar data fusion is provided.
Disclosure of Invention
The invention aims to provide a concrete pouring method based on image recognition and laser radar data fusion, and solves the problems in the background art.
In order to achieve the purpose, the invention provides the following technical scheme: a concrete pouring method based on image recognition and laser radar data fusion is characterized by comprising the following steps: the method comprises the following steps:
the method comprises the following steps: acquiring path planning data of a structured building structure to be poured, and performing pouring path planning according to the method to acquire planning data of the structured building structure to be poured;
step two: and planning a motion track according to the path planning data, and further planning the motion track of the tail end of the mechanical arm of the material distributing machine according to the pouring information planned in the step one, wherein the motion track is used as a precondition for the automatic motion of a material distributing port of the material distributing machine in the pouring process.
Step three: the method includes the steps that image recognition and laser radar data are fused to calculate the amount of to-be-poured in an area, firstly, images of walls, plates, beams, columns and the like in a construction process and images of to-be-poured areas, pouring overflow and the like under corresponding attribute information in a large number of building projects are collected through a high-definition camera to manufacture data sets with labels, then the data sets are used as training samples, and the data sets are classified through a deep learning algorithm through continuous training, so that feature information corresponding to each image is extracted, a priori knowledge base is formed, and the priori knowledge base is used in the to-be-poured process.
In this embodiment, according to the motion trajectory data obtained by planning in the second step, the tail end of the mechanical arm is controlled to move to a corresponding cloth opening pouring construction point location, then according to the attribute information of the current building point location obtained in the first step, that is, the current point location is attribute information of a wall, a beam, a column, a plate and the like, and the information of the area to be poured and the pouring amount information of the pouring point location are calculated and judged in real time through image recognition and laser radar fusion data;
step four: and judging whether the pouring of the current pouring area is finished or not and whether the pouring is overflowed or not, and installing a flowmeter device at a discharge port for measuring the actual pouring amount of the current area. And after the discharge port at the tail end of the mechanical arm moves to a specified point according to the planned track, the discharge port can continuously output the concrete from the conveying pipeline to a pouring area corresponding to the point. And calculating and updating the pouring amount required by the current area in real time according to the step three, and matching the pouring amount with the flow counted by the tail end flowmeter, thereby judging the completion condition of the current pouring area. And if the pouring task in the current area is judged to be finished, automatically controlling the material distribution port to move to the next pouring point position according to the movement track planned in the step two, and repeating the process of the step three.
According to the result obtained by the neural network training in the third step, identifying and judging the concrete overflow condition of the current pouring area in real time in the continuous pouring process;
step five: and judging the pouring completion condition of the construction area of the mechanical arm material distributing machine at the current construction position, finishing the pouring areas corresponding to all pouring points of the area to be poured covered by the machine at the current construction position according to the second, third and fourth steps, scanning the construction area at the current construction position through a high-definition camera and a laser radar, and identifying and judging whether areas corresponding to missed pouring or unqualified pouring points exist or not through a method in the third step of the process.
As a preferred embodiment of the present invention, the method in the first step is "concrete automatic distributing mechanical arm pouring path planning method", and the structured data includes attribute information of walls, columns, beams, plates, and the like, information of a construction position and a construction area of the mechanical arm distributing machine, and information of a pouring construction point position, an order, an area, and a pouring amount of the building structure corresponding to the construction position.
As a preferred embodiment of the present invention, the motion trajectory in the second step is: based on the construction process requirement of concrete pouring in the building engineering, the tail end of the mechanical arm of the distributing machine needs to be kept at a certain height in the pouring process and linearly moves in a plane. Combining the pouring sequence planned in the step one and the construction process requirements of concrete pouring in the building engineering, planning a Cartesian space linear motion track at the tail end of a mechanical arm of the distributing machine by using a linear function method with parabolic transition for a planned path so as to ensure that a material distribution port can stably make linear motion on a region to be poured in the pouring process, further ensuring that concrete can be accurately poured into the region to be poured, obtaining the linear motion track of the tail end of the mechanical arm of the distributing machine in the Cartesian space by planning the linear motion track of the tail end of the mechanical arm in the Cartesian space, and then mapping the linear motion track of the Cartesian space to the motion track of each joint in the joint space by using an inverse kinematics solving method of the mechanical arm. Then, each joint is controlled to move to a corresponding angle according to the same period through a control system, so that the tail end of a mechanical arm of the distributing machine is guaranteed to do linear motion in a Cartesian space, and full-automatic control pouring is achieved.
As a preferred embodiment of the present invention, in the concrete pouring amount formula in the third step, n is the number of stacked cones or approximate cones formed by scanning with the laser radar, in general, a cone with a wave shape formed by stacking is generated according to the structure of a steel bar formwork and the characteristics of cement concrete in the building engineering, and if other irregular patterns are generated, cone approximation processing is performed, and real-time calculation and correction are performed in the later pouring process, so as to ensure the accuracy of calculation. Meanwhile, in the pouring process, manual vibration is occasionally added to level the accumulated concrete.
As a preferred embodiment of the present invention, in the fourth step, if concrete overflows during the pouring process, the position of the discharge port is appropriately corrected, so that the concrete can be accurately poured into the area to be poured; and if the concrete overflows after the current pouring task is finished, stopping the concrete conveying pump, controlling the material distribution port to move to the next pouring point position according to the movement track planned in the step two, and repeating the process in the step three.
As a preferred embodiment of the present invention, in the fifth step, if there is a region corresponding to the point location where the casting is missed or the casting does not reach the standard, a motion trajectory from the current point location to the point location is automatically planned, the discharge port is automatically controlled to reach the designated position, and the casting task is completed. And repeatedly confirming the pouring completion condition of the construction area at the current construction position until all pouring in the area is completed and reaches the standard, moving the machine to the next construction position, and repeating all the processes.
Compared with the prior art, the invention has the following beneficial effects:
according to the automatic concrete pouring metering method based on image recognition and laser radar data fusion, automatic pouring within a mechanical arm pouring range of an automatic distributing machine is achieved, concrete pouring operation of various complex structures such as a plate surface, a wall body, a beam and a column in building engineering is conveniently achieved, the pouring amount of each pouring structure is accurately calculated, concrete is more uniformly accumulated, a template cannot overflow, meanwhile, manual field operation and monitoring feedback are not needed, and full-automatic pouring construction is achieved according to planned path data and fusion calculation of the image recognition and the laser radar data. Effectively reduce the cost of labor, improve construction quality and efficiency.
Drawings
Other features, objects and advantages of the invention will become more apparent upon reading of the detailed description of non-limiting embodiments with reference to the following drawings:
FIG. 1: a general structure construction drawing;
FIG. 2: the construction drawing of the plate surface, the wall body, the beam and the column body is poured;
FIG. 3: mechanical structure and relationship diagram;
FIG. 4: a concrete pouring shape schematic diagram;
FIG. 5: calculating a pouring amount flow chart by image recognition and laser radar fusion data;
FIG. 6: and (3) a concrete automatic pouring method flow chart based on image recognition and laser radar data fusion.
Detailed Description
In order to make the technical means, the creation characteristics, the achievement purposes and the effects of the invention easy to understand, the invention is further described with the specific embodiments.
Referring to fig. 1, the present invention provides a technical solution: a concrete pouring method based on image recognition and laser radar data fusion comprises the following steps: the method comprises the following steps: acquiring path planning data of a structured building structure to be poured, and performing pouring path planning according to the method to acquire planning data of the structured building structure to be poured; step two: planning a motion track according to the path planning data, further planning the track of the motion of the tail end of the mechanical arm of the material distributing machine according to the pouring information planned in the step one, and taking the planned track as a precondition for the automatic motion of a material distributing port of the material distributing machine in the pouring process, and performing the step three: the method includes the steps that image recognition and laser radar data are fused to calculate the amount of pouring to be performed in a region, firstly, images of walls, plates, beams, columns and the like in the construction process and images of the areas to be poured, poured areas, pouring overflow and the like under corresponding attribute information in a large number of building projects are collected through a high-definition camera to form a labeled data set, then the data set is used as a training sample, the data set is classified through a deep learning algorithm through continuous training, and accordingly, characteristic information corresponding to the images is extracted to form a priori knowledge base to be used in the pouring process, according to motion trajectory data obtained through planning in the second step, the tail end of a mechanical arm is controlled to move to a corresponding material distribution opening pouring construction point, then according to the attribute information of the current building point obtained in the first step, namely the current building point is the attribute information of the walls, the beams, the columns, the points and the like, the information of the regions to be poured and the pouring amount information, the pouring amount of the pouring of the regions where the current point is located is calculated in real time through the image recognition and the laser radar fused data, and the fourth step: judging the pouring completion condition and whether the concrete in the current pouring area overflows, installing a flowmeter device at a discharge port for measuring the actual pouring amount of the current area, continuously outputting the concrete from a conveying pipeline to a pouring area corresponding to the point after a discharge port at the tail end of a mechanical arm moves to an appointed point according to a planned track, calculating and updating the pouring amount required by the current area in real time according to the step three, and matching the calculated flow with the flow counted by the tail end flowmeter, so as to judge the completion condition of the current pouring area, if the pouring task of the current area is judged to be completed, automatically controlling a material distribution port to move to the next pouring point according to the planned motion track in the step two, repeating the step three processes, and identifying and judging the concrete overflow condition of the current pouring area in real time in the continuous pouring process according to the result obtained by neural network training in the step three processes; step five: and judging the pouring completion condition of the construction area of the mechanical arm distributing machine at the current construction position according to the second step and the third step. After the pouring areas corresponding to all pouring point positions of the area to be poured covered by the machine at the current construction position are finished in the fourth process, the construction area at the current construction position is scanned through a high-definition camera and a laser radar, and whether areas corresponding to the point positions which are missed to pour or do not reach the standard to pour exist or not is identified and judged by the method in the third process step.
Example one
Firstly, planning a motion track according to path planning data, further planning the motion of the tail end of a mechanical arm of a distributing machine according to the planned pouring information in the first step, automatically moving the mechanical arm as a material distributing port of the distributing machine in the pouring process, secondly, calculating the quantity of to-be-poured areas of areas by fusing image recognition and laser radar data, firstly, collecting a large number of images of walls, plates, beams, columns and the like in the construction process through a high-definition camera, manufacturing a labeled data set by corresponding images of the to-be-poured areas, poured overflow and the like in attribute information, judging whether the pouring completion condition of the current pouring area and the overflow are available, installing a flowmeter device at a discharge port, measuring the actual pouring quantity of the current area, then judging the pouring completion condition of the construction area of the mechanical arm at the current construction position, and scanning the construction area at the current construction position through the camera and the laser radar according to the second, third and fourth steps, and judging whether the pouring missing points of the corresponding pouring areas which are covered by the mechanical arm at the current construction station exist or not exist.
Comparison example 1
Firstly, a concrete spreader, a concrete delivery pump and other mechanical devices are manually matched, pouring is carried out by controlling the movement of the tail end of a mechanical arm of the spreader, concrete is discharged and poured through the concrete delivery pump, the pouring amount is predicted by field constructors by experience, the pouring amount is visually observed in the construction process, the pouring state and the next to-be-poured area are fed back to an operator of the spreader, and then the operator of the spreader controls an outlet of the spreader to move to the corresponding area, so that semi-automatic pouring operation is realized.
The automatic concrete pouring metering method based on image recognition and laser radar data fusion realizes automatic pouring within the pouring range of the mechanical arm of the automatic distributing machine, achieves the purposes of accurately calculating the pouring amount of each pouring structure, enabling concrete to be more uniformly accumulated and not to overflow a template, does not need manual field operation and monitoring feedback, and realizes full-automatic pouring construction according to planned path data and fusion calculation by the image recognition and the laser radar data. Effectively reduce the cost of labor, improve construction quality and efficiency.
While there have been shown and described what are at present considered the fundamental principles and essential features of the invention and its advantages, it will be apparent to those skilled in the art that the invention is not limited to the details of the foregoing exemplary embodiments, but is capable of other specific forms without departing from the spirit or essential characteristics thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Furthermore, it should be understood that although the present description refers to embodiments, not every embodiment may contain only a single embodiment, and such description is for clarity only, and those skilled in the art should integrate the description, and the embodiments may be combined as appropriate to form other embodiments understood by those skilled in the art.
Claims (6)
1. A concrete pouring method based on image recognition and laser radar data fusion is characterized by comprising the following steps: the method comprises the following steps:
the method comprises the following steps: acquiring path planning data of a structured building structure to be poured, and performing pouring path planning according to the method to acquire planning data of the structured building structure to be poured;
step two: planning a motion track according to the path planning data, and further planning the motion track of the tail end of the mechanical arm of the material distributing machine according to the pouring information planned in the step one, wherein the motion track is used as a precondition for automatic motion of a material distributing port of the material distributing machine in the pouring process;
step three: the method comprises the steps of integrating image recognition and laser radar data to calculate the amount of to-be-poured in a region, collecting a large number of images of walls, plates, beams, columns and the like in the construction process in the building engineering through a high-definition camera, and preparing the images of the to-be-poured region, the poured region, pouring overflow and the like under corresponding attribute information into a labeled data set; then, the data set is used as a training sample, and the data set is classified through continuous training by a deep learning algorithm, so that the characteristic information corresponding to each image is extracted, and a priori knowledge base is formed to be used in the casting process;
in this embodiment, according to the motion trajectory data obtained by planning in the second step, the tail end of the mechanical arm is controlled to move to a corresponding cloth opening pouring construction point location, then according to the attribute information of the current building point location obtained in the first step, that is, the current point location is attribute information of a wall, a beam, a column, a plate and the like, and the information of the area to be poured and the pouring amount information of the pouring point location are calculated and judged in real time through image recognition and laser radar fusion data;
the specific method comprises the following steps:
(1) Obtaining image information of an area to be poured
In the pouring process, after the planning point position corresponding to the movement of the tail end of the mechanical arm, a high-definition image of an area to be poured corresponding to the point position is collected through a high-definition camera and is input to a neural network;
(2) Preprocessing the acquired information of the area to be poured
After obtaining an input high-definition unlabelled image of the area to be poured, the neural network preprocesses the image, eliminates irrelevant information in the image of the area to be poured corresponding to the point position in the current image, recovers useful real information in a steel bar template structure in the area to be poured, enhances the detectability of relevant information, and simplifies data with maximum limitation, thereby improving the reliability of matching and identification;
(3) Performing feature extraction and selection on the preprocessed information
Carrying out edge part feature extraction on the preprocessed to-be-poured area by neurons in the neural network, and then further extracting a more complex reinforced concrete structure in the pouring area; in the process, the neural network extracts the basic features according to the color features, the shape features, the texture features and the spatial relationship features of the image of the area to be poured. Then selecting a minimum feature subset capable of effectively identifying the area to be poured from the given features through training;
(4) Making classification decisions on identified objects
For the casting region feature subset obtained by feature extraction and selection, classifying the casting region corresponding to the identified point location and other casting regions through a given category and a known classification rule learned by training data, and determining the area of the region to be cast by the current point location;
(5) Performing laser radar scanning on the decided area to form point cloud data
For the area casting area obtained by the image recognition decision, performing area depth scanning on the steel bar template structure under the area by using a laser radar to form point cloud data of the casting area; if no concrete exists in the area of the area, point cloud data obtained by scanning the area is similar to an empty box; if concrete exists in the area of the area, the point cloud data obtained by scanning the area can present a piled or flat ground shape, but the depth of the point cloud data is smaller than that of the point cloud data when no concrete exists;
as shown in fig. 4, by using a planning data and image recognition method, the plane area of the region to be poured corresponding to the current point location can be obtained, and then the depth of the region to be poured, the depth of the completed pouring highest position and the side length of the shape generated by stacking can be obtained by using the point cloud data formed by scanning the laser radar; and calculating according to the obtained data to obtain the concrete pouring amount required by the area corresponding to the current point position as follows:
step four: judging the pouring completion condition and whether the pouring in the current pouring area is overflowed or not, installing a flowmeter device at a discharge port for measuring the actual pouring amount of the current area, continuously outputting concrete from a conveying pipeline to a pouring area corresponding to the point position by the discharge port after the discharge port at the tail end of the mechanical arm moves to a specified point position according to a planned track, calculating and updating the pouring amount required by the current area in real time according to the step three, and matching the calculated pouring amount with the flow counted by the tail end flowmeter, thereby judging the completion condition of the current pouring area, if the pouring task of the current area is judged to be completed, automatically controlling the material distribution port to move to the next pouring point position according to the planned motion track in the step two, and repeating the three processes;
according to the result obtained by the neural network training in the third step, identifying and judging the concrete overflow condition of the current pouring area in real time in the continuous pouring process;
step five: and judging the pouring completion condition of the construction area of the mechanical arm material distributing machine at the current construction position, finishing the pouring areas corresponding to all pouring points of the area to be poured covered by the machine at the current construction position according to the second, third and fourth steps, scanning the construction area at the current construction position through a high-definition camera and a laser radar, and identifying and judging whether areas corresponding to missed pouring or unqualified pouring points exist or not through a method in the third step of the process.
2. The concrete pouring method based on image recognition and laser radar data fusion as claimed in claim 1, wherein: the method in the first step is a concrete automatic distributing mechanical arm pouring path planning method, and the structured data of the method comprises attribute information of walls, columns, beams, plates and the like, construction position and construction area information of a mechanical arm distributing machine, and pouring construction point position, sequence, area and pouring amount information of a building structure corresponding to the construction position.
3. The concrete pouring method based on image recognition and lidar data fusion as recited in claim 1, wherein: the motion trail in the second step is as follows: based on the construction process requirements of concrete pouring in construction engineering, the tail end of a mechanical arm of the distributing machine needs to be kept at a certain height and move linearly in a plane in the pouring process, a linear function method with parabolic transition is used for planning a Cartesian space linear motion track at the tail end of the mechanical arm of the distributing machine according to the pouring sequence planned in the step one and the construction process requirements of the concrete pouring in the construction engineering, so that the material distributing port can stably move linearly in a region to be poured in the pouring process, concrete can be accurately poured into the region to be poured, the rectilinear motion track of the tail end of the mechanical arm of the distributing machine in the Cartesian space is planned through the Cartesian space linear motion track at the tail end of the mechanical arm, then the rectilinear motion track of the Cartesian space is mapped to the motion track of each joint in the joint space through an inverse kinematics solving method of the mechanical arm, each joint is controlled to move to the corresponding angle in the same cycle through a control system, and the tail end of the distributing machine is guaranteed to move linearly in the Cartesian space, and full automation control is achieved.
4. The concrete pouring method based on image recognition and laser radar data fusion as claimed in claim 1, wherein: in the concrete pouring quantity formula in the third step, n is the number of cones or approximate cone shapes formed by stacking scanned by the laser radar, under general conditions, the cones with wave shapes formed by stacking are generated according to the structure of the reinforced formwork in the building engineering and the characteristics of cement concrete, if other irregular figures are generated, cone approximation processing is carried out, and real-time calculation and correction are carried out in the later pouring process, so that the calculation accuracy is ensured, meanwhile, in the pouring process, manual vibration is occasionally added, and the stacked concrete is vibrated and leveled.
5. The concrete pouring method based on image recognition and laser radar data fusion as claimed in claim 1, wherein: in the fourth step, if concrete overflows in the pouring process, the position of the discharge port is properly corrected, so that the concrete can be accurately poured into the area to be poured; and if the concrete overflows after the current pouring task is finished, stopping the concrete conveying pump, controlling the material distribution port to move to the next pouring point position according to the movement track planned in the step two, and repeating the process in the step three.
6. The concrete pouring method based on image recognition and laser radar data fusion as claimed in claim 1, wherein: and fifthly, if an area corresponding to the point location which is missed to be poured or does not reach the standard is poured, automatically planning the motion track from the current point location to the point, automatically controlling the discharge port to reach the designated position, completing the pouring task, repeatedly confirming the pouring completion condition of the construction area at the current construction position until all pouring in the area is completed and reaches the standard, moving the machine to the next construction position, and repeating all the processes.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211577232.4A CN115807543A (en) | 2022-12-05 | 2022-12-05 | Concrete pouring method based on image recognition and laser radar data fusion |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211577232.4A CN115807543A (en) | 2022-12-05 | 2022-12-05 | Concrete pouring method based on image recognition and laser radar data fusion |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115807543A true CN115807543A (en) | 2023-03-17 |
Family
ID=85485520
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211577232.4A Pending CN115807543A (en) | 2022-12-05 | 2022-12-05 | Concrete pouring method based on image recognition and laser radar data fusion |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115807543A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117436184A (en) * | 2023-12-21 | 2024-01-23 | 武汉博雅宏科技有限公司 | Simulation method and system for concrete cast-in-situ distribution |
| CN117901250A (en) * | 2024-03-20 | 2024-04-19 | 徐州市公路工程总公司 | Automatic molding system for concrete prefabricated parts |
| CN117901250B (en) * | 2024-03-20 | 2024-05-10 | 徐州市公路工程总公司 | Automatic molding system for concrete prefabricated parts |
-
2022
- 2022-12-05 CN CN202211577232.4A patent/CN115807543A/en active Pending
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117436184A (en) * | 2023-12-21 | 2024-01-23 | 武汉博雅宏科技有限公司 | Simulation method and system for concrete cast-in-situ distribution |
| CN117436184B (en) * | 2023-12-21 | 2024-03-01 | 武汉博雅宏科技有限公司 | Simulation method and system for concrete cast-in-situ distribution |
| CN117901250A (en) * | 2024-03-20 | 2024-04-19 | 徐州市公路工程总公司 | Automatic molding system for concrete prefabricated parts |
| CN117901250B (en) * | 2024-03-20 | 2024-05-10 | 徐州市公路工程总公司 | Automatic molding system for concrete prefabricated parts |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108312321B (en) | Automatic material distribution method and device of material distributor and automatic material distribution system | |
| CN115807543A (en) | Concrete pouring method based on image recognition and laser radar data fusion | |
| CN108422542B (en) | BIM-based component production method and device and component production system | |
| CN108487641A (en) | Door machine combination GPS positioning technology concreting method | |
| CN112873533B (en) | Concrete self-adaptive intelligent mixing method and device | |
| CN109928223A (en) | A kind of the feeding control method and Related product of coal yard stacker-reclaimer | |
| CN107386660A (en) | Tower crane system in prefabricated concrete structure construction based on BIM technology | |
| CN108425497A (en) | A kind of concrete distributing method and system based on BIM | |
| CN106484977A (en) | High arch dam construction progress self-adapting simulation analysis method | |
| CN106436714A (en) | Bin face regionalization based concrete green layer intelligent identification method | |
| CN104258967A (en) | Stone grading method | |
| Cheng et al. | Vision-based trajectory monitoring for assembly alignment of precast concrete bridge components | |
| CN112959513B (en) | Intelligent self-adaptive mixing system and method in concrete tunnel | |
| CN102581959A (en) | Agitating truck discharge speed control system and method | |
| CN109190206A (en) | It is a kind of for refine calculate steel structure bridge project amount modeling method | |
| Jiang et al. | Scan-VS-BIM for real-time progress monitoring of bridge construction project | |
| CN108894502A (en) | A kind of door machine combination GPS positioning technology concreting method | |
| CN115329589B (en) | Method and device for dynamically simulating casting progress of concrete on bin surface of ultra-high arch dam | |
| CN112904813B (en) | Tunnel lining intelligent control system and method based on 5G and Internet of things | |
| CN114776021B (en) | Intelligent concrete vibrating method | |
| CN115019252B (en) | Concrete quality detection method and device and monitoring equipment | |
| WO2022217949A1 (en) | Ore blending system and ore blending method | |
| Fajarwanto et al. | Managing Mega Project with Digital Construction Technology through Project Management Information System (PMIS) Dashboard: A Case Study of Trans Sumatera Toll Road Project | |
| CN208668918U (en) | A kind of frame body steel pipe that mark scale is known | |
| Chen et al. | Automated Detection for the Reserved Rebars of Bridge Pile Caps Based on Point Cloud Data and BIM |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |