CN111598955A - Mobile terminal intelligent foundation pit monitoring system and method based on photogrammetry - Google Patents
Mobile terminal intelligent foundation pit monitoring system and method based on photogrammetry Download PDFInfo
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Abstract
The invention belongs to the field of foundation pit monitoring, and particularly relates to a mobile terminal intelligent foundation pit monitoring system and method based on photogrammetry. The monitoring system is based on mobile terminal, includes: the data input and storage module: the system is used for inputting data, downloading the data from the cloud and uploading the data; the camera calibration module: the system is used for obtaining the internal and external orientation elements of the camera and adjusting the shooting attribute of the camera; the picture screening and processing module comprises: the method is used for processing the gray scale, the size and the light sensation of the photo, extracting the features of the photo, matching the features and splicing the photo; the picture analysis module: the method is used for data calculation, obtaining internal and external orientation elements and coordinates of a target point, and judging the rationality of a result; a database: for storing and providing data; cloud artificial intelligence technology module: the system is used for being linked with a client database and providing cloud information and artificial intelligence analysis data. The invention can realize the function of rapidly monitoring the safety of the foundation pit, effectively save the monitoring time of the foundation pit, save the management cost, improve the monitoring effect and ensure the construction safety of the foundation pit.
Description
Technical Field
The invention belongs to the field of foundation pit monitoring, and particularly relates to a mobile terminal intelligent foundation pit monitoring system and method based on photogrammetry.
Background
With the rapid development of economy in China, the number of engineering construction projects is increasing, and the construction scale is also increasing. Therefore, engineers need to design various different schemes to protect the foundation pit, so as to avoid the situation that the side slope is unstable, collapses and slips to threaten the life and property safety of people and cause national economic loss.
In recent years, with the rapid development of close-range photogrammetry technology, it is becoming a new type of non-contact measurement means. Compared with the traditional monitoring method, the close-range photogrammetry technology has the advantages of instantly acquiring the geometric and physical information of the measured object, having less field work and the like. However, the dedicated measuring camera is expensive, complex to operate and poor in portability, so that the conventional close-range photogrammetry device has more restrictions on the use environment and poor popularity, and the development and application of the close-range photogrammetry technology in the field of foundation pit monitoring are limited. In addition, the existing close-range photogrammetry configuration is generally an independent measuring device or a linkage system of a computer and the measuring device, and has limited computing capability, lacks a cloud database, lacks cloud intelligent dynamic analysis capability based on big data, and cannot realize dynamic early warning and dynamic management of the big data.
Disclosure of Invention
The invention aims to provide a mobile terminal intelligent foundation pit monitoring system and method based on photogrammetry.
The technical solution for realizing the purpose of the invention is as follows: the utility model provides a mobile terminal intelligence foundation ditch monitoring system based on photogrammetry, monitoring system is based on mobile terminal, includes:
the data input and storage module: the system is used for inputting data, downloading the data from the cloud and uploading the data;
the camera calibration module: the system is used for obtaining the internal and external orientation elements of the camera and adjusting the shooting attribute of the camera;
the picture screening and processing module comprises: the method is used for processing the gray scale, the size and the light sensation of the photo, extracting the features of the photo, matching the features and splicing the photo;
the picture analysis module: the method is used for data calculation, obtaining internal and external orientation elements and coordinates of a target point, and judging the rationality of a result;
a database: for storing data and providing data;
cloud artificial intelligence technology module: the system is used for being linked with a client database and providing cloud information and artificial intelligence analysis data.
A method for monitoring a foundation pit by using the detection system comprises the following steps:
step (1): performing self-checking on a camera of the mobile terminal through a camera checking module;
step (2): inputting field basic data through a data input and storage module;
and (3): analyzing the field data through a camera calibration module, and adjusting various parameters of a camera of the mobile terminal;
and (4): acquiring a live photo based on the functions of a camera and an album of the mobile terminal;
and (5): primarily processing the photos through a picture screening and processing module to synthesize a state to be analyzed;
and (6): analyzing the photos processed by the picture screening and processing module through a picture analysis module to obtain data;
and (7): the cloud artificial intelligence technology module is combined with the database to dynamically compare and analyze the data obtained by the picture analysis module;
and (8): the cloud artificial intelligence technology module judges whether early warning is needed or not;
and (9): and storing the data in a database and uploading the data to the cloud.
Further, the self-calibration in the step (1) obtains the optical distortion parameters of the camera by using a vanishing point method or a DLT method.
Further, in the step (3), the focal length and the zooming characteristic of the camera are automatically adjusted according to the self-checking in the step (1) and the basic data input in the step (2).
Further, in the step (5), the images are spliced and synthesized through a mobile terminal image size processing function and an SIFT feature matching algorithm.
Further, the steps of extracting the SIFT feature vectors in the SIFT feature matching algorithm are as follows
Step (5-1): gaussian filtering is carried out to construct an image scale space;
step (5-2): detecting an extreme value of the scale space;
step (5-3): refining extreme value feature vectors;
step (5-4): removing unstable points and edge points;
step (5-5): the main direction of the extreme point gradient;
step (5-6): and (4) describing the characteristics of the extreme point region.
Further, resolving each parameter by adopting a DLT algorithm in photogrammetry in the step (6) and obtaining the measured data;
the original formula is:
the original formula is converted into:
in the formula: (x ', y') -coordinate measurements of the image points in the frame coordinate system;
(x, y) -image plane rectangular coordinates of the image point;
(XA,YA,ZA) -object space coordinates of ground points corresponding to the image points;
(XS,YS,ZS) The object space coordinates of the photographic center are also the exterior orientation linear element of the image;
ai,bi,ci-exterior orientation angle element of image
9 direction cosines consisting of omega and kappa;
x0,y0f is the internal orientation element of the image;
li is eleven coefficients, which are a function of the extrinsic orientation element, the principal distance.
When the object space coordinates of more than 6 control points and the coordinate system coordinates of corresponding image points are known, the numerical values of eleven parameters can be solved by a computer according to the principle of least square method, and if eleven parameters and the coordinate system coordinates of the undetermined point are known, the object space coordinates (X, Y, Z) of the undetermined point can be solved by the method.
Compared with the prior art, the invention has the remarkable advantages that:
the invention provides a mobile client intelligent foundation pit monitoring system based on a photogrammetry technology, which realizes the function of quickly monitoring a foundation pit, further effectively shortens and saves the foundation pit monitoring time, saves the management cost, improves the monitoring effect and ensures the construction safety of the foundation pit; in addition, the early warning and the subsequent use of related personnel can be conveniently and timely carried out through data sharing and dynamic analysis.
Drawings
FIG. 1 is a schematic diagram of the working process of the detection system of the present invention.
Detailed Description
The present invention is described in further detail below with reference to the attached drawing figures.
A mobile client intelligent foundation pit monitoring system based on photogrammetry technology comprises: visualizing an operation interface of the mobile client; a data input and storage module; a camera calibration module; the picture screening and processing module; a picture analysis module; a cloud artificial intelligence technology module; a database.
Visual mobile client operation interface: for operational process streamlining and visualization;
the data input and storage module: the system is used for manually inputting data, downloading the data from the cloud and uploading the data;
camera calibration module (including camera self-calibration): the system is used for obtaining the internal and external orientation elements of the camera and adjusting the shooting attribute of the camera;
the picture screening and processing module comprises: the method is used for processing the gray scale, the size and the light sensation of the photo, extracting the features of the photo, matching the features and splicing the photo;
the picture analysis module: the method is used for data calculation, obtaining internal and external orientation elements and coordinates of a target point, and judging the rationality of a result;
cloud artificial intelligence technology module: the system is used for linking with a client database, providing cloud information and analyzing data by artificial intelligence;
a database: for storing data and for providing data.
A method for monitoring a foundation pit by using the detection system is characterized by comprising the following steps:
step (1): performing self-checking on a camera of the mobile terminal through a camera checking module; step 1, selecting a vanishing point method or a DLT method to obtain optical distortion parameters of a camera according to user requirements;
step (2): inputting field basic data through a data input and storage module;
and (3): analyzing the field data through a camera calibration module, and adjusting various parameters of a camera of the mobile terminal; and (3) automatically adjusting the focal length and the zooming characteristic of the camera according to the self-checking in the step (1) and the basic data input in the step (2).
And (4): acquiring a live photo based on the functions of a camera and an album of the mobile terminal;
and (5): primarily processing the photos through a picture screening and processing module to synthesize a state to be analyzed; and splicing and synthesizing the images through a mobile terminal image size processing function and an SIFT feature matching algorithm. The SIFT feature vector in the SIFT feature matching algorithm is extracted as follows
Gaussian filtering is carried out to construct an image scale space;
detecting an extreme value of the scale space;
refining extreme value feature vectors;
removing unstable points and edge points;
the main direction of the extreme point gradient;
and (4) describing the characteristics of the extreme point region.
And (6): analyzing the photos processed by the picture screening and processing module through a picture analysis module to obtain data;
resolving each parameter by adopting a DLT algorithm in photogrammetry, and obtaining measured data;
the original formula is:
the original formula is converted into:
in the formula: (x ', y') -coordinate measurements of the image points in the frame coordinate system;
(x, y) -image plane rectangular coordinates of the image point;
(XA,YA,ZA) -object space coordinates of ground points corresponding to the image points;
(XS,YS,ZS) The object space coordinates of the photographic center are also the exterior orientation linear element of the image;
ai-exterior orientation angle element of image
9 direction cosines consisting of omega and kappa;
x0,y0f is the internal orientation element of the image;
li is eleven coefficients, which are a function of the extrinsic orientation element, the principal distance.
When the object space coordinates of more than 6 control points and the coordinate system coordinates of corresponding image points are known, the numerical values of eleven parameters can be solved by a computer according to the principle of least square method, and if eleven parameters and the coordinate system coordinates of the undetermined point are known, the object space coordinates (X, Y, Z) of the undetermined point can be solved by the method.
The relational expression has the advantages that the expression (2) can be changed into a linear form, so the calculation procedure is simple and the calculation speed is high;
the data analysis process carries out error analysis, and prompts or guides to operate again for obvious unreasonable errors.
And (7): the cloud artificial intelligence technology module is combined with the database to dynamically compare and analyze the data obtained by the picture analysis module; and (4) comparing the result obtained in the step (6) with the specification requirements and cloud data in the database, giving specific prompts to the potential hazards possibly generated by the measured items, and carrying out preliminary analysis on possible reasons of problems.
And (8): the cloud artificial intelligence technology module judges whether early warning is needed or not;
and (9): and storing the data in a database and uploading the data to the cloud.
The invention provides a mobile client intelligent foundation pit monitoring system based on a photogrammetry technology, which realizes the function of quickly monitoring a foundation pit, further effectively shortens and saves the foundation pit monitoring time, saves the management cost, improves the monitoring effect and ensures the construction safety of the foundation pit; in addition, the early warning and the subsequent use of related personnel can be conveniently and timely carried out through data sharing and dynamic analysis.
Claims (7)
1. The utility model provides a mobile terminal intelligence foundation ditch monitoring system based on photogrammetry, a serial communication port, monitoring system is based on mobile terminal, includes:
the data input and storage module: the system is used for inputting data, downloading the data from the cloud and uploading the data;
the camera calibration module: the system is used for obtaining the internal and external orientation elements of the camera and adjusting the shooting attribute of the camera;
the picture screening and processing module comprises: the method is used for processing the gray scale, the size and the light sensation of the photo, extracting the features of the photo, matching the features and splicing the photo;
the picture analysis module: the method is used for data calculation, obtaining internal and external orientation elements and coordinates of a target point, and judging the rationality of a result;
a database: for storing data and providing data;
cloud artificial intelligence technology module: the system is used for being linked with a client database and providing cloud information and artificial intelligence analysis data.
2. A method of pit monitoring using the detection system of claim 1, comprising the steps of:
step (1): performing self-checking on a camera of the mobile terminal through a camera checking module;
step (2): inputting field basic data through a data input and storage module;
and (3): analyzing the field data through a camera calibration module, and adjusting various parameters of a camera of the mobile terminal;
and (4): acquiring a live photo based on the functions of a camera and an album of the mobile terminal;
and (5): primarily processing the photos through a picture screening and processing module to synthesize a state to be analyzed;
and (6): analyzing the photos processed by the picture screening and processing module through a picture analysis module to obtain data;
and (7): the cloud artificial intelligence technology module is combined with the database to dynamically compare and analyze the data obtained by the picture analysis module;
and (8): the cloud artificial intelligence technology module judges whether early warning is needed or not;
and (9): and storing the data in a database and uploading the data to the cloud.
3. The method according to claim 2, wherein the self-calibration in step (1) obtains the optical distortion parameters of the camera by using a vanishing point method or a DLT method.
4. The method according to claim 2, wherein in the step (3), the focal length and zoom characteristics of the camera are automatically adjusted according to the basic data input in the step (1) self-calibration and the step (2).
5. The method according to claim 2, wherein the images are stitched and synthesized in the step (5) through a mobile terminal image size processing function and a SIFT feature matching algorithm.
6. The method of claim 5, wherein the SIFT feature vector in the SIFT feature matching algorithm is extracted as follows
Step (5-1): gaussian filtering is carried out to construct an image scale space;
step (5-2): detecting an extreme value of the scale space;
step (5-3): refining extreme value feature vectors;
step (5-4): removing unstable points and edge points;
step (5-5): the main direction of the extreme point gradient;
step (5-6): and (4) describing the characteristics of the extreme point region.
7. The method according to claim 2, wherein the step (6) adopts DLT algorithm in photogrammetry to solve each parameter and obtain the measured data;
the original formula is:
the original formula is converted into:
in the formula: (x ', y') -coordinate measurements of the image points in the frame coordinate system;
(x, y) -image plane rectangular coordinates of the image point;
(XA,YA,ZA) -object space coordinates of ground points corresponding to the image points;
(XS,YS,ZS) The object space coordinates of the photographic center are also the exterior orientation linear element of the image;
ai-exterior orientation angle element of image
9 direction cosines consisting of omega and kappa;
x0,y0f is the internal orientation element of the image;
li is eleven coefficients, which are a function of the foreign orientation element, principal distance;
when the object space coordinates of more than 6 control points and the coordinate system coordinates of corresponding image points are known, the numerical values of eleven parameters can be solved by a computer according to the principle of least square method, and if eleven parameters and the coordinate system coordinates of the undetermined point are known, the object space coordinates (X, Y, Z) of the undetermined point can be solved by the method.
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| CN112177062A (en) * | 2020-09-26 | 2021-01-05 | 福建省华实建设工程有限公司 | Remote intelligent monitoring system and monitoring method for building foundation pit |
| CN115619849A (en) * | 2022-12-15 | 2023-01-17 | 昆山轩诺电子包装材料有限公司 | Full-automatic processing detection system based on carrier band |
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