CN112258648A - A-SFM three-dimensional reconstruction algorithm-based soft rock foundation surface deformation monitoring method - Google Patents
A-SFM three-dimensional reconstruction algorithm-based soft rock foundation surface deformation monitoring method Download PDFInfo
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Abstract
The invention relates to a soft rock foundation surface deformation monitoring method based on an A-SFM three-dimensional reconstruction algorithm, belonging to the technical field of foundation deformation monitoring. The A-SFM is a three-dimensional reconstruction algorithm obtained by optimizing the traditional SFM-MVS method by AKAZE which shows the best performance in image processing. The soft rock foundation surface deformation A-SFM three-dimensional reconstruction algorithm comprises earth control point acquisition, foundation surface image acquisition, feature point extraction and feature point description, feature vector matching, sparse reconstruction and dense reconstruction. The soft rock foundation surface deformation monitoring device comprises a total station assembly, a supporting assembly, a beam assembly, a camera assembly and a displacement meter assembly. The invention provides a soft rock foundation surface deformation monitoring method based on an A-SFM three-dimensional reconstruction algorithm by improving the traditional SFM-MVS three-dimensional reconstruction algorithm, and realizes the real-time monitoring of soft rock foundation deformation.
Description
Technical Field
The invention relates to a method for three-dimensional reconstruction and deformation monitoring of a soft rock foundation surface, in particular discloses a foundation surface A-SFM three-dimensional reconstruction algorithm and a foundation surface deformation monitoring device, and belongs to the field of foundation deformation monitoring.
Background
Soft rock is widely distributed in multiple areas such as the middle part and the southwest part of China. With the rapid development of national economic construction, more and more super high-rise buildings use soft rock as a foundation. At present, the most authoritative method for determining the bearing capacity of the foundation is a rock foundation load test, but the method can only determine the bearing capacity, cannot obtain the surface dynamic deformation condition of the foundation in the test process, and cannot obtain the failure mode and the failure range of the foundation. The rock mass surface is subjected to three-dimensional reconstruction in the process of the rock base load test, so that the deformation condition of the rock mass surface can be obtained, and the failure mode and the failure range of the rock mass can be obtained. However, the related rock foundation surface three-dimensional reconstruction equipment facilities are relatively rare at present.
The existing relatively accurate measuring method for monitoring the rock mass surface deformation is three-dimensional laser scanning, but the three-dimensional laser scanning technology has high hardware cost and labor-intensive data acquisition and cannot be effectively applied to a rock base load test. In consideration of the limitations of the size of a test site, the technical level of operators and the like, an intelligent, efficient and convenient-to-install method is urgently needed to realize dynamic monitoring of rock mass surface deformation in the process of a rock foundation load test.
With the development of machine vision measurement technology, a soft rock foundation surface deformation monitoring method based on an A-SFM three-dimensional reconstruction algorithm is developed conditionally aiming at soft rock foundation deformation monitoring, and an efficient and convenient monitoring method is provided for determining a foundation damage mode and a damage range in the building industry.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides a soft rock foundation surface deformation monitoring method based on an A-SFM three-dimensional reconstruction algorithm.
In order to achieve the purpose, the invention provides a soft rock foundation surface deformation monitoring method based on an A-SFM three-dimensional reconstruction algorithm. The monitoring method provides a three-dimensional reconstruction algorithm of the A-SFM, which is suitable for soft rock foundation load test site conditions. The method comprises the steps of obtaining geodetic control point coordinate information of a region to be tested by adopting a total station, then extracting soft rock foundation surface images in the loading process in real time by using camera equipment, and obtaining specific position information of the foundation surface at different moments by reconstructing three-dimensional images of the soft rock foundation surface, so as to obtain the specific deformation condition of the soft rock foundation surface in the loading process.
According to an embodiment of the invention, the A-SFM is a three-dimensional reconstruction algorithm obtained by optimizing the traditional SFM-MVS method by AKAZE which performs best in image processing.
The monitoring method comprises six steps of earth control point acquisition, foundation surface image acquisition, feature point extraction and feature point description, feature vector matching, sparse reconstruction and dense reconstruction, and the main method comprises the following steps:
the method comprises the following steps: and acquiring a ground control point. Coordinate information of eight control points of a foundation load test field is collected through a total station, so that the horizontal position and the elevation position of a monitoring area are unified.
Step two: and acquiring images of the surface of the foundation. Acquiring images of the surface of the foundation by a camera to obtain focal length information and realize self-calibration of the camera;
step three: extracting characteristic points and describing the characteristic points. Extracting and describing feature points by using an AKAZE feature detection algorithm;
step four: and matching the feature vectors. After the feature points extracted by the features are obtained, establishing a matching neighborhood by using an initial matching pair, searching all matching points, screening the feature point pairs by mainly using Euclidean distance, and removing the feature points if a result which does not meet a threshold distance appears;
step five: and (5) sparse reconstruction. The selected image pair is used for initializing the whole light beam adjustment process, firstly, the light beam adjustment is carried out on the two initially selected images for the first time, then, new images are added in a circulating mode for carrying out new light beam adjustment, the light beam adjustment is an iterative process, and all effective images need to be continuously calculated until iteration is finished. Obtaining camera estimation parameters and scene geometric information, namely sparse 3D point cloud;
step six: and (5) dense reconstruction. And calculating the point cloud data again on the basis of sparse reconstruction by using the basic data to obtain denser point cloud data, and unifying the three-dimensional data of the foundation surface obtained in different time domains to the same coordinate system by using the obtained coordinate information of the geodetic control point.
Compared with the traditional SFM algorithm, the improved A-SFM three-dimensional reconstruction algorithm not only accelerates the three-dimensional reconstruction speed, but also increases the measurement accuracy to a certain extent.
On the basis of the A-SFM three-dimensional reconstruction algorithm provided by the invention, the monitoring method provides a monitoring device. The device comprises a total station assembly, a support assembly, a beam assembly, a camera assembly and a displacement meter assembly. The total station assembly comprises a total station, a mark point and a mark point bracket. The support assembly comprises a stable support and a telescopic vertical support beam. The beam assembly comprises a main beam, a secondary beam and a ring beam. The camera assembly comprises a camera, a connecting bearing and a rolling pulley. The displacement meter assembly comprises a displacement meter, a displacement meter bracket and a displacement meter data line.
According to one embodiment of the invention, the stabilizing supports are connected with the telescopic supporting beams through bolts and are arranged at four corners of a test field. The main beam is connected with the telescopic bracket by bolts. The auxiliary beam is connected with the main beam through bolts, and the position of the auxiliary beam on the main beam can be freely adjusted according to test requirements. The annular beam is arranged on the auxiliary beam, and connecting devices for connecting the camera assemblies are arranged on two sides of the annular beam. The camera assembly is free to move on the ring beam. The mark point bracket is arranged on the annular beam and used for fixing the mark point. The displacement meter bracket is arranged on the auxiliary beam and used for fixing the displacement meter.
According to one embodiment of the invention, the telescopic supporting beam is a hollow round steel beam, the height of the hollow round steel beam is 50cm, and the telescopic range of the hollow round steel beam is 20 cm; a horizontal connecting device expanded towards two sides is welded at the top of the telescopic bracket, a screw hole for bolt connection is formed in the horizontal connecting device, and the length of the horizontal connecting device is 10 cm; screw holes for bolt connection are formed in two sides of the bottom of the telescopic supporting beam, and the length of the screw holes is 10 cm. The stabilizing support is divided into two parts, the upper structure is a hollow round steel beam with a screw hole, and the length of the stabilizing support is 10 cm; the substructure is a bottom plate crossed in a cross manner, the bottom plate is connected with the circular steel beam in a welding manner, and the length of the bottom plate is 40 cm.
According to an embodiment of the invention, the main beam with the hollowed middle part has the total length of 300cm, the width of 10cm, the bottom surfaces of the two ends of the main beam with the hollowed strip parts, the length of 10cm and the length of 100cm, and the main beam with the hollowed strip parts is used for fixedly connecting a bolt and a telescopic supporting beam, and the two sides of the middle part of the main beam with the hollowed strip parts are used for fixedly connecting a bolt and a secondary beam. The total length of the girder without the hollow parts in the middle part is 130cm, the width of the girder is 10cm, the bottom surfaces of the two ends of the girder are provided with strip-shaped hollow parts, and the length of the girder is 10cm, so that the girder is used for fixedly connecting a bolt and a telescopic supporting beam.
According to one embodiment of the invention, the length of the secondary beam is 130cm, the width of the secondary beam is 10cm, the bottom of the secondary beam is provided with a strip-shaped hollow, the width of the hollow is 0.5cm, and two ends of the hollow are provided with screw holes for connecting the main beam. The width of the annular beam is 5cm, the height of the annular beam is 5cm, and the annular beam is divided into an inner annular beam and an outer annular beam. The diameter of the inner ring beam is 50cm and the diameter of the outer ring beam is 100 cm. The top of annular roof beam is equipped with the bar fretwork, and one side that is close to the jack is equipped with the bar fretwork and is used for connecting the camera subassembly, and the equidistant 8 screws that are equipped with in bottom are used for connecting the mark point bracket.
According to an embodiment of the invention, the connecting bearing has a width of 3cm, and the camera can rotate 360 degrees. The length of the rolling pulley is 5cm, and the 360-degree surrounding of the ring-shaped beam can be realized.
According to one embodiment of the invention, the total length of the marker support is 50cm and the width is 3 cm. The top of the mark point bracket is provided with a screw hole, the bottom of the mark point bracket is provided with a horizontal extension for placing a mark point, and the extension length is 5 cm.
According to one embodiment of the invention, the displacement meter bracket has a total length of 50cm and a width of 3 cm. The amesdial bracket top is equipped with the screw, and the bottom is equipped with the horizontal extension of placing the amesdial, and extension length is 5 cm.
In conclusion, the invention provides a monitoring method based on an A-SFM three-dimensional reconstruction algorithm for monitoring the real-time deformation of the soft rock foundation. According to the monitoring method, intelligent real-time monitoring can be achieved only by setting initial environment parameters, and the monitoring requirements of different types of soft rock foundations can be met.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
Fig. 1 is a flow chart for monitoring deformation of a soft rock foundation surface based on an a-SFM three-dimensional reconstruction algorithm according to an embodiment of the present invention.
Fig. 2 is a plan view of a soft rock foundation surface deformation monitoring device based on an a-SFM three-dimensional reconstruction algorithm according to an embodiment of the present invention.
Fig. 3 is an elevation view of a soft rock foundation surface deformation monitoring device based on an a-SFM three-dimensional reconstruction algorithm according to an embodiment of the present invention.
Detailed Description
As shown in fig. 1, the three-dimensional reconstruction algorithm of the a-SFM provided by this embodiment includes geodetic control point acquisition, image acquisition, and three-dimensional reconstruction. The earth control point acquisition mode is as follows: equally dividing the periphery of the pressure bearing plate into 4 fan-shaped areas, and placing 8 marking points in the fan-shaped areas; and acquiring the position information of the 8 mark points by using the total station. The implementation process comprises the following steps: attaching all the mark points to the mark point brackets, obtaining specific position information of each mark point by using a total station, loading, collecting shooting area images every 180s by using 4 cameras, obtaining the images, and performing three-dimensional reconstruction by using an algorithm to obtain the deformation condition.
As shown in fig. 1, in this embodiment, the monitoring steps of the a-SFM three-dimensional reconstruction algorithm are as follows:
step 1: and acquiring a ground control point. Collecting coordinate information of 8 geodetic control points of a region to be tested of a foundation load test field through a total station;
step 2: and acquiring images of the surface of the foundation. Acquiring images of the surface of the foundation by a camera to obtain focal length information and realize self-calibration of the camera;
and step 3: extracting characteristic points and describing the characteristic points. Extracting and describing feature points by using an AKAZE feature detection algorithm;
and 4, step 4: and matching the feature vectors. After the feature points extracted by the features are obtained, establishing a matching neighborhood by using an initial matching pair, searching all matching points, screening the feature point pairs by mainly using Euclidean distance, and removing the feature points if a result which does not meet a threshold distance appears;
and 5: and (5) sparse reconstruction. Obtaining camera estimation parameters and scene geometric information, namely sparse 3D point cloud;
step 6: and (5) dense reconstruction. And calculating the point cloud data again by using the basic data on the basis of sparse reconstruction to obtain denser point cloud data, and unifying the three-dimensional coordinate information of the surface of the foundation by using the obtained geodetic control point coordinate information.
As shown in FIG. 2, in the present embodiment, the diameter of the mark point in the sector area is 3-5 cm. However, the present invention is not limited thereto.
As shown in fig. 2 to 3, the device for monitoring the deformation of the surface of the soft rock foundation based on the a-SFM three-dimensional reconstruction algorithm provided by the present embodiment includes a total station component (including a total station 01, a mark point 02, and a mark point bracket 03), a support component (including a stable support 11 and a retractable vertical support beam 12), a beam component (including a hollow main beam 21 in the middle, a hollow main beam 22 in the middle, a secondary beam 23, an inner ring beam 24, and an outer ring beam 25), a camera component (a camera 31, a connecting bearing 32, a rolling pulley 33), and a displacement meter component (a displacement meter 41, a displacement meter bracket 42, and a displacement meter data line 43).
In this embodiment, the total length of the mark point bracket 03 is 50cm, the width thereof is 3cm, the top thereof is provided with a screw hole, the bottom thereof is provided with a horizontal extension for placing the mark point, and the extension length is 5 cm. The length of the upper hollow steel pipe structure of the stabilizing support 11 is 10cm, and the length of the lower cross support is 40 cm. The length of the horizontal connecting device at the upper part of the telescopic supporting beam 12 is 10 cm. The total length of the main beam 21 is 300cm, the width of the main beam is 10cm, the bottom surfaces of the two ends of the main beam are provided with strip-shaped hollows, the length of each hollow is 10cm, the main beam is used for fixedly connecting the bolt with the telescopic supporting beam, the strip-shaped hollows are arranged on the two sides of the middle of the main beam, and the length of each hollow is 100cm and used for fixedly connecting the bolt with the auxiliary beam. The main beam 22 without the hollow parts in the middle part has the total length of 130cm, the width of 10cm, the bottom surfaces of the two ends of the main beam are provided with strip-shaped hollow parts, and the length of 10cm is used for fixedly connecting the bolts with the telescopic supporting beam. The length of the auxiliary beam 23 is 130cm, the width is 10cm, the bottom of the auxiliary beam is provided with a strip-shaped hollow, the width of the hollow is 0.5cm, and screw holes for connecting the main beam are arranged at two ends of the hollow. The inner ring beam 24 and the outer ring beam 25 are spliced by two semicircular ring beams, the width is 5cm, the height is 5cm, the diameter of the inner ring beam is 50cm, the diameter of the outer ring beam is 100cm, the top of each ring beam is provided with a strip-shaped hollow, one side of each ring beam is provided with a strip-shaped hollow, and the bottom of each ring beam is provided with 8 screw holes at equal intervals. The width of the connecting bearing 32 is 3cm, and the camera can rotate 360 degrees. The length of the rolling pulley 33 is 5cm, and 360-degree surrounding of the ring-shaped beam can be realized. The total length of the displacement meter bracket 41 is 50cm, the width is 3cm, a screw hole is formed in the top of the displacement meter bracket, a horizontal extension for placing a dial indicator is arranged at the bottom of the displacement meter bracket, and the extension length is 5 cm. However, the present invention is not limited thereto. In other embodiments, the above value is adjusted to 5cm to 10cm as appropriate according to the actual situation in consideration of the actual situation of loading.
The installation of the A-SFM three-dimensional reconstruction algorithm-based soft rock foundation surface deformation monitoring device provided by the embodiment is operated according to the following steps.
The method comprises the following steps: firstly, inserting the lower part of a telescopic vertical supporting beam 12 into an upper steel pipe of a stable support 11, and fixing the lower part by using bolts; then, placing the two ends of the middle hollow main beam 21 and the middle main beam 22 without hollow on the upper part of the vertical supporting beam 12, and reinforcing by using bolts; then, searching a proper position, and performing bolt reinforcement on the two ends of the auxiliary beam 23 and the middle part of the middle hollow main beam 21; finally, 4 rolling pulleys 33 are placed in the annular beam, proper positions are found, the two semicircular inner annular beams 24, the outer annular beams 25 and the auxiliary beams are respectively connected through bolts, and finally the annular beam is assembled into an integral annular beam.
Step two: the rolling pulley 33 and the connecting bearing 32 are connected with the camera 31, and the camera is fixed on the ring beam by adjusting the position and the angle of the camera, so that the fan-shaped area can be shot by 360 degrees and the whole fan-shaped area can be shot in the visual field.
Step three: and the displacement meter bracket 42 is connected with the displacement meter 41 and is arranged at a proper position on the auxiliary beam 23, and the displacement meter bracket is connected with a displacement meter data wire 43, so that the reading returns to zero.
Step four: the landmark brackets 03 are first mounted in place on the outer ring beam and the landmarks are then attached to the horizontal extensions of the landmark brackets.
Although the present invention has been described with reference to the preferred embodiments, it should be understood that various changes and modifications can be made therein by those skilled in the art without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (8)
1. A soft rock foundation surface deformation monitoring method based on an A-SFM three-dimensional reconstruction algorithm is characterized by comprising the following steps:
A-SFM three-dimensional reconstruction algorithm for soft rock foundation surface deformation monitoring comprises the steps of acquiring a ground control point, acquiring a foundation surface image, extracting and describing a characteristic point, matching a characteristic vector, performing sparse reconstruction and performing dense reconstruction;
a soft rock foundation surface deformation monitoring device comprises a total station assembly, a supporting assembly, a beam assembly, a camera assembly and a displacement meter assembly.
2. The A-SFM three-dimensional reconstruction algorithm of claim 1, characterized in that the A-SFM three-dimensional reconstruction algorithm is optimized to the traditional SFM-MVS method by the AKAZE algorithm which has the best performance in image processing.
3. The a-SFM three-dimensional reconstruction algorithm as claimed in claim 1, wherein the a-SFM three-dimensional reconstruction algorithm mainly comprises 6 steps: step one, acquiring a ground control point: obtaining coordinate information of three geodetic control points of a region to be measured through a total station; step two, acquiring images of the surface of the foundation: acquiring image information of the surface of the foundation through a camera to realize self-calibration of the camera; step three, feature point extraction and feature point description: extracting and describing feature points by using an AKAZE feature detection algorithm; step four, matching the feature vectors: establishing a matching pair by utilizing the initial matching pair, and screening the characteristic point pair by utilizing the Euclidean distance; step five, sparse reconstruction: performing beam adjustment iteration on the picture to obtain camera estimation parameters and scene geometric information; step six, dense reconstruction: and calculating the point cloud data again on the basis of sparse reconstruction by using the basic data to obtain denser point cloud data, and unifying the three-dimensional data of the foundation surface to the same coordinate system by using the coordinate information of the geodetic control points.
4. The deformation monitoring device of claim 1, wherein the support assembly comprises a stable support base and a telescoping vertical support beam.
5. A total station assembly according to claim 1, including said total station, a marker point carrier.
6. The beam assembly of claim 1, including said primary, secondary and ring beams.
7. The camera assembly of claim 1, comprising the camera, a connecting bearing, and a rolling pulley.
8. The displacement gauge assembly of claim 1, comprising the displacement gauge, a displacement gauge carrier, and a displacement gauge data wire.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104807975A (en) * | 2015-04-28 | 2015-07-29 | 西南石油大学 | Talus slope freezing and thawing circulating action deformation physical model experiment apparatus and experimental method |
| CN107037195A (en) * | 2016-10-31 | 2017-08-11 | 中国地质大学（武汉） | Water-level fluctuation influences experimental rig and method to lower sleeping ice sheet talus slope stability |
| CN209231683U (en) * | 2019-02-20 | 2019-08-09 | 周玥 | A kind of e-commerce camera |
| JP2019178953A (en) * | 2018-03-30 | 2019-10-17 | 株式会社フジタ | Inspection object state evaluating device |
-
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Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104807975A (en) * | 2015-04-28 | 2015-07-29 | 西南石油大学 | Talus slope freezing and thawing circulating action deformation physical model experiment apparatus and experimental method |
| CN107037195A (en) * | 2016-10-31 | 2017-08-11 | 中国地质大学（武汉） | Water-level fluctuation influences experimental rig and method to lower sleeping ice sheet talus slope stability |
| JP2019178953A (en) * | 2018-03-30 | 2019-10-17 | 株式会社フジタ | Inspection object state evaluating device |
| CN209231683U (en) * | 2019-02-20 | 2019-08-09 | 周玥 | A kind of e-commerce camera |
Non-Patent Citations (3)
| Title |
|---|
| QIJUN HU等: "A Rapid Method of the Rock Mass Surface Reconstruction for Surface Deformation Detection at Close Range", SENSORS, vol. 20, no. 18, 19 September 2020 (2020-09-19), pages 1 - 18 * |
| YONGKANG LU等: "An error analysis and optimization method for combined measurement with binocular vision", CHINESE JOURNAL OF AERONAUTICS, vol. 34, no. 10, 22 July 2020 (2020-07-22), pages 282 - 292, XP086750265, DOI: 10.1016/j.cja.2020.07.002 * |
| 欧阳一博: "基于DIC的采场覆岩变形检测试验研究", 中国优秀硕士学位论文全文数据库 工程科技Ⅰ辑, no. 01, 15 January 2020 (2020-01-15), pages 021 - 266 * |
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