CN115482648A - Visual intelligent monitoring and early warning method and system for safety of wind power deep foundation pit - Google Patents
Visual intelligent monitoring and early warning method and system for safety of wind power deep foundation pit Download PDFInfo
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Abstract
The invention discloses a visual intelligent monitoring and early warning method and system for wind power deep foundation pit safety, which comprises the following steps: performing multi-stage compression on the BIM foundation pit support model to obtain a lightweight BIM model; monitoring each collection point of the foundation pit and the overall state of the foundation pit to obtain a plurality of laser point cloud models; splicing the laser point cloud models, and obtaining a lightweight point cloud model by adopting a point cloud model obtained by dense splicing by a space sampling method; respectively carrying out coordinate transformation on the light weight BIM model and the light weight point cloud model, converting the light weight BIM model and the light weight point cloud model into an engineering actual coordinate system to obtain data of a virtual scene and a real scene, and then synthesizing the data of the virtual scene and the data of the real scene through coordinate unification to construct a three-dimensional deep foundation pit model; and judging whether each associated part has a fault according to the safety state of each associated part in the three-dimensional deep foundation pit model, and finishing the visual intelligent monitoring and early warning of the safety of the wind power deep foundation pit.
Description
Technical Field
The invention belongs to the technical field of wind power infrastructure management, and relates to a safety visual intelligent monitoring and early warning method and system for a wind power deep foundation pit.
Background
Wind power generation as a renewable clean energy source is rapidly developed in China, and the installed capacity of wind power is gradually increased. As a high-rise building, a deep foundation pit needs to be excavated during foundation construction, and the deep foundation pit construction is often a stage with larger risk in the whole engineering construction. In addition, fans are extremely sensitive to pitch, which can easily lead to fan failure when pitch occurs. Therefore, the requirements for the construction of the wind power deep foundation pit are higher, and various emergency situations need to be dealt with and timely treated. The foundation pit is intelligently monitored in real time in the construction process, effective matching among construction units and safe and smooth implementation of engineering are facilitated, and related technologies are not provided in the prior art.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a visual intelligent monitoring and early warning method and system for the safety of a wind power deep foundation pit.
In order to achieve the purpose, the visual intelligent monitoring and early warning method for the safety of the wind power deep foundation pit comprises the following steps:
performing multi-stage compression on the BIM foundation pit support model to obtain a lightweight BIM model;
monitoring each collection point of the foundation pit and the overall state of the foundation pit to obtain a plurality of laser point cloud models;
splicing the laser point cloud models, and then adopting a space sampling method
Obtaining a point cloud model after sparse splicing to obtain a lightweight point cloud model;
respectively carrying out coordinate transformation on the light weight BIM model and the light weight point cloud model, converting the light weight BIM model and the light weight point cloud model into an engineering actual coordinate system to obtain data of a virtual scene and a real scene, and then synthesizing the data of the virtual scene and the data of the real scene through coordinate unification to construct a three-dimensional deep foundation pit model;
and judging whether each associated part has a fault according to the safety state of each associated part in the three-dimensional deep foundation pit model, and finishing the safe visual intelligent monitoring and early warning of the wind power deep foundation pit.
And performing multi-stage compression on the BIM foundation pit supporting model by adopting a SynLZ algorithm or a QuickLZ algorithm to obtain a lightweight BIM model.
Further comprising: and displaying the lightweight BIM model.
Further comprising: and storing the information obtained by monitoring.
By pitch sampling
And (4) reducing the number of the point clouds by about 100 times by using the sparse point cloud model to obtain a lightweight point cloud model.
The specific process of carrying out the visual intelligent monitoring and early warning on the safety of the wind power deep foundation pit according to the safety state of each associated part in the three-dimensional deep foundation pit model comprises the following steps:
displaying the safety state of each associated part in the three-dimensional deep foundation pit model in real time through color change, wherein the normal state is green, the state is yellow when exceeding the early warning limit, and the state is red when exceeding the emergency limit;
the dangerous situation is early warned through the set upper and lower working limits of the sensor, when the BIM real-time display module is yellow, a reminding notice is sent, when the BIM real-time display module is red, an alarm mechanism is triggered to send an alarm, and the position of the sensor is rapidly positioned through the BIM model.
Splicing the laser point cloud models, performing point cloud analysis, deleting point cloud data, noise point cloud and suspension point cloud which do not express ground information, and then adopting a space sampling method
And (5) obtaining a lightweight point cloud model by using the sparse point cloud model. And monitoring each acquisition point of the foundation pit and the overall state of the foundation pit by adopting the combination of a wireless sensor and a 3D laser scanning technology to obtain a plurality of laser point cloud models.
The invention relates to a visual intelligent monitoring and early warning system for safety of a wind power deep foundation pit, which comprises:
the collecting box is used for monitoring each collecting point of the foundation pit and the overall state of the foundation pit to obtain a plurality of laser point cloud models;
the data processing module is used for carrying out multi-stage compression on the BIM foundation pit supporting model to obtain a lightweight BIM model; splicing the laser point cloud models, and then adopting a space sampling method
Obtaining a point cloud model after sparse splicing to obtain a lightweight point cloud model; respectively carrying out coordinate transformation on the light weight BIM model and the light weight point cloud model, converting the light weight BIM model and the light weight point cloud model into an engineering actual coordinate system to obtain data of a virtual scene and a real scene, and then synthesizing the data of the virtual scene and the data of the real scene through coordinate unification to construct a three-dimensional deep foundation pit model; and judging whether each associated part has a fault according to the safety state of each associated part in the three-dimensional deep foundation pit model, and finishing the visual intelligent monitoring and early warning of the safety of the wind power deep foundation pit.
The invention has the following beneficial effects:
according to the wind power deep foundation pit safety visualized intelligent monitoring and early warning method and system, during specific operation, the combined space display is carried out on the safety state of the deep foundation pit based on the BIM model and the point cloud model, so that the monitoring data can be visualized in a three-dimensional space in real time, whether faults occur at each related part is judged according to the safety state of each related part in the three-dimensional deep foundation pit model, the wind power deep foundation pit safety visualized intelligent monitoring and early warning is completed, and compared with a traditional point measurement mode, the whole deformation of the foundation pit can be reflected more objectively.
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FIG. 1 is a system block diagram of the present invention.
Detailed Description
In order to make those skilled in the art better understand the technical solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, not all of the embodiments, and do not limit the scope of the disclosure of the present invention. Moreover, in the following description, descriptions of well-known structures and techniques are omitted so as to not unnecessarily obscure the concepts of the present disclosure. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
There is shown in the drawings a schematic block diagram of a disclosed embodiment in accordance with the invention. The figures are not drawn to scale, wherein certain details are exaggerated and possibly omitted for clarity of presentation. The shapes of the various regions, layers and their relative sizes, positional relationships are shown in the drawings as examples only, and in practice deviations due to manufacturing tolerances or technical limitations are possible, and a person skilled in the art may additionally design regions/layers with different shapes, sizes, relative positions, according to the actual needs.
Example one
The invention relates to a visual intelligent monitoring and early warning method for safety of a wind power deep foundation pit, which comprises the following steps:
performing multi-stage compression on the BIM foundation pit support model to obtain a lightweight BIM model;
monitoring each collection point of the foundation pit and the overall state of the foundation pit to obtain a plurality of laser point cloud models;
splicing the laser point cloud models, and then adopting a space sampling method
Obtaining a lightweight point cloud model by using a point cloud model obtained after sparse splicing;
respectively carrying out coordinate transformation on the light weight BIM model and the light weight point cloud model, converting the light weight BIM model and the light weight point cloud model into an engineering actual coordinate system to obtain data of a virtual scene and a real scene, and then synthesizing the data of the virtual scene and the data of the real scene through coordinate unification to construct a three-dimensional deep foundation pit model;
and judging whether each associated part has a fault according to the safety state of each associated part in the three-dimensional deep foundation pit model, and finishing the visual intelligent monitoring and early warning of the safety of the wind power deep foundation pit.
Specifically, a SynLZ algorithm or a QuickLZ algorithm is adopted to carry out multi-stage compression on the BIM foundation pit supporting model, and the lightweight BIM model is obtained.
The invention also includes: displaying the lightweight BIM model; and storing the information obtained by monitoring.
In particular, a pitch sampling method is adopted
And (4) reducing the number of the point clouds by about 100 times by using the sparse point cloud model to obtain a lightweight point cloud model.
Specifically, the specific process of performing the visual intelligent monitoring and early warning on the safety of the wind power deep foundation pit according to the safety state of each associated part in the three-dimensional deep foundation pit model comprises the following steps:
displaying the safety state of each associated part in the three-dimensional deep foundation pit model in real time through color change, wherein the normal state is green, the state is yellow when exceeding the early warning limit, and the state is red when exceeding the emergency limit; the dangerous situation is early warned through the set upper and lower working limits of the sensor, when the BIM real-time display module is yellow, a reminding notice is sent, when the BIM real-time display module is red, an alarm mechanism is triggered to send an alarm, and the position of the sensor is rapidly positioned through the BIM model.
Specifically, the laser point cloud models are spliced, point cloud data, noise point cloud and suspension point cloud which do not express ground information are deleted through point cloud analysis, and then a space sampling method is adopted
And (5) obtaining a light-weight point cloud model by using the sparse point cloud model.
Specifically, a wireless sensor and a 3D laser scanning technology are combined to monitor each collection point of the foundation pit and the overall state of the foundation pit, and a plurality of laser point cloud models are obtained.
Example two
Referring to fig. 1, the visualized intelligent monitoring and early warning system for the safety of the wind power deep foundation pit based on the BIM model comprises:
inputting data and early warning parameters of the BIM foundation pit support model into a data processing module, and performing multi-stage compression on the BIM foundation pit support model by the data processing module through a SynLZ algorithm or a QuickLZ algorithm to obtain a lightweight BIM model, wherein the lightweight BIM model can be browsed in a BIM real-time display module;
the monitoring module monitors each acquisition point of the foundation pit and the overall state of the foundation pit by adopting the combination of a wireless sensor and a 3D laser scanning technology, and sends the detected information to the server for unified storage;
the data processing module calls the data stored in the server from the server, and then displays the working state of the foundation pit in a process curve form through the data curve display module;
meanwhile, the laser point cloud model is spliced, point cloud data, noise point cloud and suspension point cloud which do not express ground information are deleted through point cloud analysis, and a space sampling method is adopted
The method comprises the following steps of (1) reducing the number of point clouds by about 100 times by a sparse point cloud model to obtain a lightweight point cloud model;
the method comprises the steps of respectively carrying out coordinate transformation on data of a lightweight BIM model and a lightweight point cloud model in a BIM real-time display module, converting the data into an engineering actual coordinate system to obtain data of a virtual scene and a real scene, synthesizing the data of the virtual scene and the data of the real scene through coordinate unification to construct a three-dimensional deep foundation pit model, and then displaying the safety state of each associated part in the three-dimensional deep foundation pit model in real time through color change, wherein the normal state is green, the state exceeding the early warning limit is yellow, and the state exceeding the emergency limit is red.
The early warning module carries out the early warning to the dangerous condition through the sensor work bound that sets up, when BIM real-time display module appears yellow, then in time sends and reminds the notice, when BIM real-time display module appears red, then triggers alarm mechanism and sends out the police dispatch newspaper to through the position of BIM model rapid positioning sensor, make things convenient for the quick fixed point of staff to handle.
Claims (9)
1. A visual intelligent monitoring and early warning method for safety of a wind power deep foundation pit is characterized by comprising the following steps:
performing multi-stage compression on the BIM foundation pit support model to obtain a lightweight BIM model;
monitoring each collection point of the foundation pit and the overall state of the foundation pit to obtain a plurality of laser point cloud models;
splicing the laser point cloud models by adopting a space sampling method
Obtaining a lightweight point cloud model by using a point cloud model obtained after sparse splicing;
respectively carrying out coordinate transformation on the light weight BIM model and the light weight point cloud model, converting the light weight BIM model and the light weight point cloud model into an engineering actual coordinate system to obtain data of a virtual scene and a real scene, and synthesizing the data of the virtual scene and the real scene through coordinate unification to construct a three-dimensional deep foundation pit model;
and judging whether each associated part has a fault according to the safety state of each associated part in the three-dimensional deep foundation pit model, and finishing the visual intelligent monitoring and early warning of the safety of the wind power deep foundation pit.
2. The wind power deep foundation pit safety visualization intelligent monitoring and early warning method according to claim 1, characterized in that a SynLZ algorithm or a QuickLZ algorithm is adopted to carry out multistage compression on a BIM foundation pit support model to obtain a lightweight BIM model.
3. The visual intelligent monitoring and early warning method for the safety of the wind power deep foundation pit according to claim 1, further comprising: and displaying the lightweight BIM model.
4. The visual intelligent monitoring and early warning method for the safety of the wind power deep foundation pit according to claim 1, further comprising: and storing the information obtained by monitoring.
5. The visual intelligent monitoring and early warning method for safety of wind power deep foundation pit according to claim 1, characterized in that a spacing sampling method is adopted
And (4) reducing the number of the point clouds by 100 times by using the rare point cloud model to obtain a lightweight point cloud model.
6. The visualized intelligent monitoring and early warning method for the safety of the wind power deep foundation pit according to claim 1, characterized in that the specific process of performing visualized intelligent monitoring and early warning on the safety of the wind power deep foundation pit according to the safety state of each associated part in the three-dimensional deep foundation pit model comprises the following steps:
displaying the safety state of each associated part in the three-dimensional deep foundation pit model in real time through color change, wherein the normal state is green, the state is yellow when exceeding the early warning limit, and the state is red when exceeding the emergency limit;
the dangerous condition is early warned through the preset upper and lower limits of the working of the sensor, when the BIM real-time display module is yellow, a reminding notice is sent, when the BIM real-time display module is red, an alarm mechanism is triggered to send an alarm, and the position of the sensor is rapidly positioned through the BIM model.
7. The wind power deep foundation pit safety visualization intelligent monitoring and early warning method according to claim 1, characterized in that the laser point cloud models are spliced, point cloud data, noise point cloud and suspension point cloud which do not express ground information are deleted through point cloud analysis, and then a space sampling method is adopted
And (5) obtaining a lightweight point cloud model by using the sparse point cloud model.
8. The visual intelligent monitoring and early warning method for the safety of the wind power deep foundation pit according to claim 1, characterized in that a wireless sensor and a 3D laser scanning technology are combined to monitor each collection point of the foundation pit and the overall state of the foundation pit to obtain a plurality of laser point cloud models.
9. The utility model provides a visual intelligent monitoring early warning system of wind-powered electricity generation deep basal pit safety which characterized in that includes:
the collecting box is used for monitoring each collecting point of the foundation pit and the overall state of the foundation pit to obtain a plurality of laser point cloud models;
the data processing module is used for carrying out multi-stage compression on the BIM foundation pit supporting model to obtain a lightweight BIM model; splicing the laser point cloud models by adopting a space sampling method
Obtaining a point cloud model after sparse splicing to obtain a lightweight point cloud model; respectively carrying out coordinate transformation on the light weight BIM model and the light weight point cloud model, converting the light weight BIM model and the light weight point cloud model into an engineering actual coordinate system to obtain data of a virtual scene and a real scene, and synthesizing the data of the virtual scene and the real scene through coordinate unification to construct a three-dimensional deep foundation pit model; judging whether each associated part has a fault according to the safety state of each associated part in the three-dimensional deep foundation pit model, and finishing the visual intelligent monitoring and early warning of the safety of the wind power deep foundation pit。
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| CN111898052A (en) * | 2020-07-29 | 2020-11-06 | 国网上海市电力公司 | WEB-side online display method of lightweight BIM model |
| WO2021103433A1 (en) * | 2019-11-28 | 2021-06-03 | 中铁十八局集团有限公司 | Method for tunnel measurement and control on basis of combination of 3d laser scanner and bim |
| CN114969912A (en) * | 2022-05-24 | 2022-08-30 | 五凌电力有限公司 | Method and system for analyzing cavern excavation engineering |
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- 2022-09-13 CN CN202211109844.0A patent/CN115482648A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110188505A (en) * | 2019-06-12 | 2019-08-30 | 中国建筑第七工程局有限公司 | Complicated deep based on BIM+3D laser scanner technique monitors system and method |
| CN110765542A (en) * | 2019-11-05 | 2020-02-07 | 中铁二局第一工程有限公司 | Lightweight method of high-precision digital elevation model |
| WO2021103433A1 (en) * | 2019-11-28 | 2021-06-03 | 中铁十八局集团有限公司 | Method for tunnel measurement and control on basis of combination of 3d laser scanner and bim |
| CN111441330A (en) * | 2020-04-24 | 2020-07-24 | 福州大学 | Foundation pit monitoring system and method based on BIM + GIS |
| CN111898052A (en) * | 2020-07-29 | 2020-11-06 | 国网上海市电力公司 | WEB-side online display method of lightweight BIM model |
| CN114969912A (en) * | 2022-05-24 | 2022-08-30 | 五凌电力有限公司 | Method and system for analyzing cavern excavation engineering |
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