CN115773723A - Roadbed section goaf deformation monitoring method and system based on BIM - Google Patents
Roadbed section goaf deformation monitoring method and system based on BIM Download PDFInfo
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- CN115773723A CN115773723A CN202211512920.2A CN202211512920A CN115773723A CN 115773723 A CN115773723 A CN 115773723A CN 202211512920 A CN202211512920 A CN 202211512920A CN 115773723 A CN115773723 A CN 115773723A
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Abstract
The invention belongs to the technical field of data processing, and discloses a BIM-based roadbed section goaf deformation monitoring method and system. The method comprises the following steps: acquiring three-dimensional data and image data of a roadbed section goaf; updating the BIM of the roadbed section goaf according to the three-dimensional data and the image data; and judging whether the roadbed section gob has deformation danger or not according to the BIM of the roadbed section gob. By the mode, deformation of the roadbed section goaf can be predicted from two dimensions of the three-dimensional model and the two-dimensional image based on the BIM, so that whether danger is generated due to deformation in the goaf can be judged, early warning can be given in advance, and the safety of engineering is improved.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a deformation monitoring method and system for a roadbed section gob based on BIM.
Background
The goaf is a common unfavorable geological phenomenon in engineering, has the characteristics of strong concealment, irregular spatial distribution, difficulty in prediction and the like, brings serious potential safety hazards to the road basic body structure and later-stage operation, usually, deformation of the goaf is observed manually, but manual observation is inaccurate and has certain subjectivity, so that deformation of the goaf cannot be predicted accurately.
The above is only for the purpose of assisting understanding of the technical aspects of the present invention, and does not represent an admission that the above is prior art.
Disclosure of Invention
The invention mainly aims to provide a BIM-based roadbed section goaf deformation monitoring method and system, and aims to solve the technical problem that the safety of construction in a roadbed section goaf cannot be accurately judged in the prior art.
In order to achieve the aim, the invention provides a BIM-based roadbed section goaf deformation monitoring method, which comprises the following steps:
acquiring three-dimensional data and image data of a roadbed section goaf;
updating the BIM of the roadbed section goaf according to the three-dimensional data and the image data;
and judging whether the roadbed section gob has deformation danger or not according to the BIM of the roadbed section gob.
Optionally, the determining, according to the BIM of the subgrade section goaf, whether there is a deformation risk in the subgrade section goaf includes:
extracting the shape characteristics of the BIM of the roadbed section gob;
extracting the image characteristics of the BIM of the roadbed section goaf;
determining the deformation trend of the roadbed section goaf according to the shape characteristics and the image characteristics;
and judging whether the roadbed section gob has deformation danger or not according to the deformation trend.
Optionally, the extracting the shape feature of the BIM of the roadbed section gob includes:
determining a plurality of target point pairs on the BIM of the roadbed section goaf;
calculating the Euclidean distance before each target point pair;
obtaining a shape distribution curve according to the Euclidean distance;
and determining shape characteristics according to the shape distribution curve.
Optionally, the extracting the image features of the BIM of the roadbed section goaf includes:
acquiring a BIM image of the roadbed section goaf;
carrying out image enhancement on the image to obtain an enhanced image;
performing down-sampling processing on the enhanced image to obtain a down-sampled image;
calculating gradient values of the down-sampling images to obtain gradient images;
carrying out binarization processing on the gradient image to obtain a binarized image;
and determining the image characteristics of the BIM of the roadbed section goaf according to the binary image.
Optionally, the determining a deformation trend of the subgrade section goaf according to the shape feature and the image feature includes:
inputting the historical shape characteristics and the shape characteristics into a first preset model to obtain a shape deformation trend;
inputting the historical image characteristics and the image characteristics into a second preset model to obtain an image deformation trend;
and determining the deformation trend of the roadbed section goaf according to the shape deformation trend and the image deformation trend.
Optionally, the determining whether there is a deformation risk in the roadbed section gob according to the deformation trend includes:
determining a deformation rate and a crack growth rate according to the deformation trend;
and judging whether the roadbed section gob has deformation danger or not according to the deformation rate and the crack growth rate.
Optionally, after determining whether there is a deformation risk in the roadbed section goaf according to the BIM of the roadbed section goaf, the method further includes:
and when the roadbed section gob is determined to have deformation danger, sending early warning information to target equipment, and giving an alarm when a worker approaches a deformation danger area.
In addition, in order to achieve the above object, the present invention further provides a system for monitoring deformation of a gob in a roadbed section based on BIM, wherein the system for monitoring deformation of a gob in a roadbed section based on BIM comprises:
the acquisition module is used for acquiring three-dimensional data and image data of the roadbed section goaf;
the updating module is used for updating the BIM of the roadbed section goaf according to the three-dimensional data and the image data;
and the judging module is used for judging whether the roadbed section gob has deformation danger or not according to the BIM of the roadbed section gob.
In addition, in order to achieve the above object, the present invention further provides a device for monitoring deformation of a gob in a roadbed section based on BIM, which comprises: the BIM-based roadbed section goaf deformation monitoring program is configured to realize the steps of the BIM-based roadbed section goaf deformation monitoring method.
In addition, in order to achieve the above object, the present invention further provides a storage medium, where a BIM-based roadbed section goaf deformation monitoring program is stored, and when executed by a processor, the BIM-based roadbed section goaf deformation monitoring program implements the steps of the BIM-based roadbed section goaf deformation monitoring method as described above.
The method comprises the steps of obtaining three-dimensional data and image data of a roadbed section goaf; updating the BIM of the roadbed section goaf according to the three-dimensional data and the image data; and judging whether the roadbed section gob has deformation danger or not according to the BIM of the roadbed section gob. By the mode, deformation of the roadbed section goaf can be predicted from two dimensions of the three-dimensional model and the two-dimensional image based on the BIM, so that whether danger is generated due to deformation in the goaf can be judged, early warning can be given in advance, and the safety of engineering is improved.
Drawings
Fig. 1 is a schematic structural diagram of a BIM-based roadbed section goaf deformation monitoring device in a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a schematic flow diagram of a first embodiment of a BIM-based roadbed section gob deformation monitoring method according to the present invention;
FIG. 3 is a schematic flow chart of a BIM-based roadbed section goaf deformation monitoring method according to a second embodiment of the present invention;
fig. 4 is a structural block diagram of a first embodiment of a BIM-based roadbed section goaf deformation monitoring system.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Referring to fig. 1, fig. 1 is a schematic structural diagram of a BIM-based roadbed section goaf deformation monitoring device in a hardware operating environment according to an embodiment of the present invention.
As shown in fig. 1, the BIM-based roadbed section goaf deformation monitoring device may include: a processor 1001, such as a Central Processing Unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a Wireless interface (e.g., a Wireless-Fidelity (Wi-Fi) interface). The Memory 1005 may be a Random Access Memory (RAM) Memory, or may be a Non-Volatile Memory (NVM), such as a disk Memory. The memory 1005 may alternatively be a storage device separate from the processor 1001.
Those skilled in the art will appreciate that the configuration shown in fig. 1 does not constitute a limitation of the BIM-based subgrade section gob deformation monitoring apparatus and may include more or fewer components than those shown, or some components in combination, or a different arrangement of components.
As shown in fig. 1, a memory 1005, which is a storage medium, may include therein an operating system, a network communication module, a user interface module, and a BIM-based gob deformation monitoring program.
In the BIM-based gob deformation monitoring apparatus of the roadbed section shown in fig. 1, the network interface 1004 is mainly used for data communication with a network server; the user interface 1003 is mainly used for data interaction with a user; the processor 1001 and the memory 1005 of the BIM-based roadbed section goaf deformation monitoring device can be arranged in the BIM-based roadbed section goaf deformation monitoring device, and the BIM-based roadbed section goaf deformation monitoring device calls a BIM-based roadbed section goaf deformation monitoring program stored in the memory 1005 through the processor 1001 and executes the BIM-based roadbed section goaf deformation monitoring method provided by the embodiment of the invention.
An embodiment of the present invention provides a method for monitoring deformation of a gob in a roadbed section based on BIM, and referring to fig. 2, fig. 2 is a schematic flow diagram of a first embodiment of a method for monitoring deformation of a gob in a roadbed section based on BIM according to the present invention.
In this embodiment, the method for monitoring deformation of the gob in the roadbed section based on the BIM includes the following steps:
step S10: and acquiring three-dimensional data and image data of the roadbed section goaf.
It should be noted that the execution main body of this embodiment is a BIM-based roadbed section goaf deformation monitoring device, and the BIM-based roadbed section goaf deformation monitoring device may be a device with a computing function, such as a smart phone, a tablet computer, a notebook computer, a server, and an embedded device.
It can be understood that when a road is constructed, a roadbed is firstly constructed, which mainly has the functions of providing necessary conditions for track or road surface laying and train or train operation, bearing static load and dynamic load of track and locomotive vehicle or road surface and traffic load, and transmitting and diffusing the load to the deep part of the foundation. The goaf is a common unfavorable geological phenomenon in engineering, has the characteristics of strong concealment, irregular spatial distribution, difficulty in prediction and the like, and brings serious potential safety hazards to the road basic body structure and later-stage operation.
In a specific implementation, when three-dimensional data and image data are acquired, a three-dimensional scanner can be used for acquiring, the three-dimensional scanner can simultaneously acquire the three-dimensional data and the image data of the roadbed section goaf, the three-dimensional data is acquired by acquiring point cloud data of the surface geometry of the goaf, and the image data is acquired by a camera in the three-dimensional scanner. The three-dimensional scanner can be arranged on the unmanned aerial vehicle, and the unmanned aerial vehicle automatically cruises the roadbed section goaf at regular intervals, and the three-dimensional scanner collects data once.
Step S20: and updating the BIM of the roadbed section goaf according to the three-dimensional data and the image data.
It should be noted that the Building Information Modeling (Building Information model) can help to realize the integration of Building Information, and various Information is always integrated in a three-dimensional model Information database from the design, construction and operation of a Building to the end of the whole life cycle of the Building, so that personnel of a design team, a construction unit, a facility operation department, an owner and the like can perform cooperative work based on the Building, thereby effectively improving the working efficiency, saving resources, reducing the cost and realizing sustainable development. The core of BIM is to provide a complete building engineering information base consistent with the actual situation for a virtual building engineering three-dimensional model by establishing the model and utilizing the digital technology. The information base not only contains geometrical information, professional attributes and state information describing building components, but also contains state information of non-component objects (such as space and motion behaviors). By means of the three-dimensional model containing the construction engineering information, the information integration degree of the construction engineering is greatly improved, and therefore a platform for engineering information exchange and sharing is provided for related interest parties of the construction engineering project.
It can be understood that, the three-dimensional data and the image data acquired each time are recorded in the BIM of the roadbed section goaf, and the three-dimensional data and the image data acquired last time are taken as the current building information model data, so that an engineer can manage the project according to the current building information model data. Thereby promoting the construction efficiency of the project.
Step S30: and judging whether the roadbed section gob has deformation danger or not according to the BIM of the roadbed section gob.
In specific implementation, because the BIM records data of the roadbed section goaf at a plurality of moments, whether the roadbed section goaf deforms or not can be determined according to BIM analysis, and whether dangers such as collapse and the like can be generated due to overlarge deformation or not can be analyzed.
In the embodiment, three-dimensional data and image data of a roadbed section goaf are obtained; updating the BIM of the roadbed section goaf according to the three-dimensional data and the image data; and judging whether the roadbed section gob has deformation danger or not according to the BIM of the roadbed section gob. By the mode, deformation of the roadbed section goaf can be predicted from two dimensions of the three-dimensional model and the two-dimensional image based on the BIM, so that whether danger is generated due to deformation in the goaf can be judged, early warning can be given in advance, and the safety of engineering is improved.
Referring to fig. 3, fig. 3 is a schematic flow chart of a second embodiment of a method for monitoring deformation of a gob in a roadbed section based on BIM according to the present invention.
Based on the first embodiment, in step S30, the method for monitoring deformation of a gob in a roadbed section based on BIM in this embodiment includes:
step S31: and extracting the BIM shape characteristics of the roadbed section goaf.
It should be noted that, in order to be able to determine in advance whether the subgrade section gob is dangerous due to deformation, further analysis needs to be performed according to the BIM, and first, the shape feature of the BIM of the subgrade section gob is extracted.
Further, the extracting the shape characteristics of the BIM of the roadbed section gob includes: determining a plurality of target point pairs on the BIM of the roadbed section goaf; calculating the Euclidean distance before each target point pair; obtaining a shape distribution curve according to the Euclidean distance; and determining shape characteristics according to the shape distribution curve.
In a specific implementation, for two points (i.e., a target point pair) randomly sampled from the surface of the three-dimensional model, the euclidean distance (D2 distance) between them can be obtained, and further, by counting the euclidean distances obtained by the above method, the shape distribution curve of the three-dimensional model can be obtained.
It will be appreciated that the slope is taken at a plurality of points on the shape profile to obtain the BIM shape characteristics of the gob in the subgrade section.
Step S32: and extracting the BIM image characteristics of the roadbed section goaf.
Further, the extracting the image features of the BIM of the gob of the roadbed section includes: acquiring a BIM image of the roadbed section goaf; carrying out image enhancement on the image to obtain an enhanced image; performing down-sampling processing on the enhanced image to obtain a down-sampled image; calculating gradient values of the down-sampling images to obtain gradient images; carrying out binarization processing on the gradient image to obtain a binarized image; and determining the image characteristics of the BIM of the roadbed section goaf according to the binary image.
It is understood that after the binarized image is obtained, histogram features of the binarized image, i.e., image features, are calculated.
Step S33: and determining the deformation trend of the subgrade section goaf according to the shape features and the image features.
Further, the determining the deformation trend of the roadbed section goaf according to the shape feature and the image feature comprises: inputting the historical shape characteristics and the shape characteristics into a first preset model to obtain a shape deformation trend; inputting the historical image characteristics and the image characteristics into a second preset model to obtain an image deformation trend; and determining the deformation trend of the subgrade section goaf according to the shape deformation trend and the image deformation trend.
It should be noted that the first preset model and the second preset model are trained time-series-based neural network models, and can predict the deformation trend of the roadbed section goaf. The roadbed section goaf is predicted based on the three-dimensional model and the two dimensions of the two-dimensional image, so that the deformation possibly generated by the roadbed section goaf can be predicted more accurately, and whether cracks on the roadbed section goaf continuously grow to cause collapse danger can be predicted based on the prediction of the image.
Step S34: and judging whether the roadbed section gob has deformation danger or not according to the deformation trend.
Further, the determining whether the roadbed section gob has a deformation risk according to the deformation trend includes: determining a deformation rate and a crack growth rate according to the deformation trend; and judging whether the roadbed section gob has deformation danger or not according to the deformation rate and the crack growth rate.
It can be understood that the deformation of the gob of the roadbed section needs to consider factors in time and space, and when the deformation of the gob of the roadbed section is too large in the first certain time, a danger may be generated, so that whether the deformation is dangerous can be judged according to the deformation rate. The prediction trend obtained by the model calculation comprises a deformation model of the roadbed section goaf at a future time point, the predicted BIM is compared with the current BIM for calculation, so that the deformation rate can be obtained, the crack variation trend on the roadbed section goaf can be calculated based on the image trend obtained by the same image characteristic calculation, and when the crack variation trend exceeds a certain value, the early warning can be carried out in advance to cause danger.
Further, after judging whether the roadbed section gob has a deformation risk according to the BIM of the roadbed section gob, the method further includes:
and when the roadbed section gob is determined to have deformation danger, sending early warning information to target equipment, and giving an alarm when a worker approaches a deformation danger area.
It should be noted that, during the construction operation, the staff all is furnished with the locator on one's body, and the locator is connected with equipment, can acquire staff's position in real time, when detecting that the staff is deforming danger area, then sends out the warning to avoid the staff to meet danger.
The method comprises the steps of extracting the shape characteristics of the BIM of the roadbed section goaf; extracting the image characteristics of the BIM of the roadbed section goaf; determining the deformation trend of the roadbed section goaf according to the shape characteristics and the image characteristics; and judging whether the roadbed section gob has deformation danger or not according to the deformation trend. Through the method, the BIM three-dimensional shape characteristic and the BIM two-dimensional image characteristic are extracted, and the deformation trend of the roadbed paragraph goaf is predicted based on the time sequence neural network model, so that the deformation risk can be predicted more accurately.
In addition, an embodiment of the present invention further provides a storage medium, where a BIM-based roadbed section goaf deformation monitoring program is stored on the storage medium, and when being executed by a processor, the BIM-based roadbed section goaf deformation monitoring program implements the steps of the BIM-based roadbed section goaf deformation monitoring method described above.
Since the storage medium adopts all technical solutions of all the embodiments, at least all the beneficial effects brought by the technical solutions of the embodiments are achieved, and no further description is given here.
Referring to fig. 4, fig. 4 is a structural block diagram of a first embodiment of a BIM-based roadbed section goaf deformation monitoring system.
As shown in fig. 4, a system for monitoring deformation of a gob of a roadbed section based on BIM according to an embodiment of the present invention includes:
the acquisition module 10 is used for acquiring three-dimensional data and image data of a roadbed section goaf;
an updating module 20, configured to update the BIM of the gob in the roadbed section according to the three-dimensional data and the image data;
and the judging module 30 is used for judging whether the roadbed section goaf has deformation danger according to the BIM of the roadbed section goaf.
In an embodiment, the determining module 30 is further configured to extract a shape feature of the BIM of the gob in the roadbed section;
extracting the image characteristics of the BIM of the roadbed section goaf;
determining the deformation trend of the roadbed section goaf according to the shape characteristics and the image characteristics;
and judging whether the roadbed section gob has deformation danger or not according to the deformation trend.
In an embodiment, the determining module 30 is further configured to determine a plurality of target point pairs on the BIM of the gob in the roadbed section;
calculating the Euclidean distance before each target point pair;
obtaining a shape distribution curve according to the Euclidean distance;
and determining shape characteristics according to the shape distribution curve.
In an embodiment, the determining module 30 is further configured to obtain a BIM image of the gob in the roadbed section;
carrying out image enhancement on the image to obtain an enhanced image;
performing down-sampling processing on the enhanced image to obtain a down-sampled image;
calculating gradient values of the down-sampling images to obtain gradient images;
carrying out binarization processing on the gradient image to obtain a binarized image;
and determining the BIM image characteristics of the roadbed section goaf according to the binary image.
In an embodiment, the determining module 30 is further configured to input the historical shape features and the shape features into a first preset model to obtain a shape deformation trend;
inputting the historical image characteristics and the image characteristics into a second preset model to obtain an image deformation trend;
and determining the deformation trend of the roadbed section goaf according to the shape deformation trend and the image deformation trend.
In an embodiment, the determining module 30 is further configured to determine a deformation rate and a crack growth rate according to the deformation trend;
and judging whether the roadbed section gob has deformation danger or not according to the deformation rate and the crack growth rate.
In an embodiment, the determining module 30 is further configured to send warning information to a target device when it is determined that there is a deformation risk in the roadbed section goaf, and send an alarm when a worker approaches a deformation risk area.
It should be understood that the above is only an example, and the technical solution of the present invention is not limited in any way, and in a specific application, a person skilled in the art may set the technical solution as needed, and the present invention is not limited thereto.
In the embodiment, three-dimensional data and image data of a roadbed section goaf are obtained; updating the BIM of the roadbed section goaf according to the three-dimensional data and the image data; and judging whether the roadbed section gob has deformation danger or not according to the BIM of the roadbed section gob. By the mode, deformation of the roadbed section goaf can be predicted from two dimensions of the three-dimensional model and the two-dimensional image based on BIM, so that whether danger is generated in the goaf due to deformation can be judged, early warning can be performed in advance, and the safety of engineering is improved.
It should be noted that the above-mentioned work flows are only illustrative and do not limit the scope of the present invention, and in practical applications, those skilled in the art may select some or all of them according to actual needs to implement the purpose of the solution of the present embodiment, and the present invention is not limited herein.
In addition, the technical details that are not described in detail in this embodiment may be referred to a method for monitoring deformation of a gob of a roadbed section based on BIM provided in any embodiment of the present invention, and are not described herein again.
Furthermore, it should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising a … …" does not exclude the presence of another identical element in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solution of the present invention or portions thereof that contribute to the prior art may be embodied in the form of a software product, where the computer software product is stored in a storage medium (e.g. Read Only Memory (ROM)/RAM, magnetic disk, optical disk), and includes several instructions for enabling a terminal device (e.g. a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. A BIM-based roadbed section gob deformation monitoring method is characterized by comprising the following steps:
acquiring three-dimensional data and image data of a roadbed section goaf;
updating the BIM of the roadbed section goaf according to the three-dimensional data and the image data;
and judging whether the roadbed section gob has deformation danger or not according to the BIM of the roadbed section gob.
2. The method of claim 1, wherein said determining whether the subgrade section gob is in danger of deformation based on the BIM of the subgrade section gob comprises:
extracting the shape characteristics of the BIM of the roadbed section goaf;
extracting the image characteristics of the BIM of the roadbed section goaf;
determining the deformation trend of the roadbed section goaf according to the shape characteristics and the image characteristics;
and judging whether the roadbed section gob has deformation risks or not according to the deformation trend.
3. The method of claim 2, wherein the extracting the shape features of the BIM of the gob of the roadbed section comprises:
determining a plurality of target point pairs on the BIM of the roadbed section goaf;
calculating the Euclidean distance before each target point pair;
obtaining a shape distribution curve according to the Euclidean distance;
and determining shape characteristics according to the shape distribution curve.
4. The method of claim 2, wherein extracting image features of the BIM of the subgrade section gob comprises:
acquiring a BIM image of the roadbed section goaf;
carrying out image enhancement on the image to obtain an enhanced image;
performing down-sampling processing on the enhanced image to obtain a down-sampled image;
calculating gradient values of the down-sampling images to obtain gradient images;
carrying out binarization processing on the gradient image to obtain a binarized image;
and determining the image characteristics of the BIM of the roadbed section goaf according to the binary image.
5. The method of claim 2, wherein determining a deformation trend of the subgrade section gob from the shape features and the image features comprises:
inputting the historical shape characteristics and the shape characteristics into a first preset model to obtain a shape deformation trend;
inputting the historical image characteristics and the image characteristics into a second preset model to obtain an image deformation trend;
and determining the deformation trend of the roadbed section goaf according to the shape deformation trend and the image deformation trend.
6. The method of claim 2, wherein the determining whether the subgrade section goaf is in danger of deformation according to the deformation trend comprises:
determining a deformation rate and a crack growth rate according to the deformation trend;
and judging whether the roadbed section gob has deformation danger or not according to the deformation rate and the crack growth rate.
7. The method of claim 1, wherein after determining whether the subgrade section gob is in danger of deformation based on the BIM of the subgrade section gob, the method further comprises:
and when the roadbed section gob is determined to have deformation danger, sending early warning information to target equipment, and giving an alarm when a worker approaches a deformation danger area.
8. The utility model provides a road bed section goaf deformation monitoring system based on BIM which characterized in that, road bed section goaf deformation monitoring system based on BIM includes:
the acquisition module is used for acquiring three-dimensional data and image data of the roadbed section goaf;
the updating module is used for updating the BIM of the roadbed section goaf according to the three-dimensional data and the image data;
and the judging module is used for judging whether the roadbed section gob has deformation danger or not according to the BIM of the roadbed section gob.
9. The utility model provides a road bed section goaf deformation monitoring facilities based on BIM which characterized in that, equipment includes: a memory, a processor, and a BIM-based subgrade section gob deformation monitoring program stored on the memory and executable on the processor, the BIM-based subgrade section gob deformation monitoring program configured to implement the BIM-based subgrade section gob deformation monitoring method of any one of claims 1 to 7.
10. A storage medium having stored thereon a BIM-based gob deformation monitoring program which, when executed by a processor, implements the BIM-based gob deformation monitoring method according to any one of claims 1 to 7.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116385690A (en) * | 2023-06-05 | 2023-07-04 | 四川云控交通科技有限责任公司 | BIM model-based three-dimensional operation and maintenance management and control platform and management and control method thereof |
| CN116703244A (en) * | 2023-08-02 | 2023-09-05 | 中国矿业大学(北京) | Mining subsidence area treatment effect and comprehensive evaluation method |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116385690A (en) * | 2023-06-05 | 2023-07-04 | 四川云控交通科技有限责任公司 | BIM model-based three-dimensional operation and maintenance management and control platform and management and control method thereof |
| CN116385690B (en) * | 2023-06-05 | 2023-09-26 | 四川云控交通科技有限责任公司 | BIM model-based three-dimensional operation and maintenance management and control platform and management and control method thereof |
| CN116703244A (en) * | 2023-08-02 | 2023-09-05 | 中国矿业大学(北京) | Mining subsidence area treatment effect and comprehensive evaluation method |
| CN116703244B (en) * | 2023-08-02 | 2023-10-20 | 中国矿业大学(北京) | Mining subsidence area treatment effect and comprehensive evaluation method |
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