CN113267128A - Binocular vision automatic side slope displacement monitoring method - Google Patents
Binocular vision automatic side slope displacement monitoring method Download PDFInfo
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- G01B11/00—Measuring arrangements characterised by the use of optical techniques
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Abstract
The invention relates to a binocular vision automatic slope displacement monitoring method in the technical field of slope displacement monitoring, which comprises the following steps: firstly, monitoring the slope of a monitored object slope in real time; secondly, calculating the real displacement value of the whole slope in real time by using a binocular vision technology and a machine vision means; and finally, evaluating the real-time displacement value of the alarm through the alarm value set in advance, if the real-time displacement value exceeds the alarm value set in advance, triggering an alarm, and simultaneously displaying the alarm on a screen to inform a manager. The method of combining the binocular vision technology and the machine vision technology is adopted, and the safety state early warning system for slope displacement in slope engineering is constructed through automatic extraction of information in the shot images, so that the operation is simple, the efficiency and timeliness of safety monitoring are improved, and the probability of safety accidents is greatly reduced.
Description
Technical Field
The invention relates to the technical field of slope displacement monitoring, in particular to a binocular vision automatic slope displacement monitoring method.
Background
China is a country with complex geographic conditions, and particularly, the terrain in the middle and western regions mainly takes complex mountains and hills as the main part. In the process of advancing modern construction, how to deal with complex problems such as mountain engineering represented by slope engineering and the like has become a central importance. Wherein, whether the side slope is stable or not directly influences the safety situation of the side slope, and further influences national economy and engineering safety. The stability of the side slope can be directly reflected on displacement deformation generally, and how to accurately control the displacement deformation information of the side slope has great significance for judging the safety situation of the side slope.
At present, most of the traditional methods such as geodetic observation, GPS measurement, instrument monitoring and the like are adopted for slope displacement monitoring. Some methods may cause great human error, and some methods may rely on special monitoring equipment or have high learning cost for workers. The existing other slope displacement monitoring methods have low automation degree, rely on manual operation, and have complex operation and expensive instrument cost.
Disclosure of Invention
The technical problem solved by the invention is as follows: aiming at the defects of the prior art, the high-precision binocular vision real-time slope displacement monitoring method based on simple equipment, simple and clear structure, low cost and high automation degree is provided. The technical scheme comprises the following steps:
step 1: and acquiring the slope surface image of the slope in real time through image acquisition equipment.
Step 2: the image processing device is used for denoising and distortion correction of the image, and then dynamic identification of the image characteristic points is carried out.
And step 3: utilizing an image processing device to automatically extract three-dimensional space coordinate information of the feature points in the image in real time; firstly, completing automatic calibration of a binocular vision camera; secondly, two-dimensional coordinates of image feature points in the left camera and the right camera are identified at the same time, and left-right corresponding matching is carried out; finally, automatically generating two-dimensional coordinates X of feature points in the left camera and the right camerai,YiConverted into three-dimensional space coordinate Xi,Yi,Zi。
And 4, step 4: a displacement threshold is set in the alert evaluation device.
And 5: data (X)i，Yi，Zi) And inputting the data into a warning evaluation device to judge the safety state of the side slope.
Step 6: triggering an alarm system, sending a signal, and displaying the slope displacement value at the moment in a display for an operator to view.
Furthermore, a camera and an illuminating lamp are arranged on the image data acquisition equipment; the camera adopts a binocular camera, acquires image data of the slope surface of the side slope at an overlooking angle, adopts a clamping frame and a telescopic rod to fix the camera, and is connected with a warning evaluation system through a supporting structure; the illuminating lamp is used for night illumination.
Furthermore, the central processing unit is used for beautifying images and extracting features, adopts a Gaussian filtering and MASK-RCNN recognition algorithm, and is connected with a lower warning evaluation system through a transmission line.
Further, the warning value in the warning evaluation device is set to be 3mm, when the displacement value is detected to exceed the set warning value, the environment is more dangerous, otherwise, the safety is higher, and finally, the displacement value of the side slope is displayed on the screen and triggers the alarm.
Further, the siren divide into bee calling organ and warning light, if the slope displacement value is greater than warning value 3mm on the same day, start bee calling organ and warning light, its value is less, and bee calling organ sound is bigger, and warning light flicker frequency is faster.
The basic principle of the invention is as follows:
by researching the relation between the two-dimensional coordinate and the three-dimensional coordinate of the slope displacement plane and introducing a means of a machine vision technology, the whole system program is developed by adopting MATLAB 2014a and Visual Studio 2013C + + mixed programming language, and dynamic real-time slope displacement evaluation is realized.
Compared with the related art, the invention has the advantages that:
the binocular vision technology and the machine vision technology are introduced, information identification and extraction are more accurate, and the whole slope displacement monitoring and early warning system is more intelligent and automatic. The structure is simple and clear, the learning cost and the instrument cost of workers are reduced, and the working efficiency is improved. Can be competent in the long-time monitoring process of side slope, can in time carry out the early warning, remind the workman.
Drawings
FIG. 1 is a block flow diagram of the method of the present invention;
FIG. 2 is a schematic diagram of a binocular vision automated slope displacement monitoring method;
FIG. 3 is a schematic diagram of a central processing unit;
in the figure: 1-an image acquisition device; 2-a rotatable hinge; 3-a telescopic frame rod; 4, a support; 5, a support; 6-a central processing unit; 7-a display; 8-an alarm; 9-crawler walking mechanism; 10-lighting lamp; 11-a binocular camera; 12-slope surface; 13-image receiving means; 14-an image processing apparatus; 15-a data storage device; 16-alert evaluation means; 17-a transmission line; 18-power switch
Step 1: the monitoring image of the slope scene 12 is acquired by the image acquisition device 1.
Step 2: the image receiving device 13 in the central processing unit 6 is used for receiving the image from the image acquisition equipment through the transmission line 17, and denoising and distortion correction are carried out on the image, so that the image is beautified and is easy to identify. And finally transmitted to the image processing device 14 through the transmission line 17.
And step 3: and (4) utilizing an image processing device 14 in the central processing unit 6 to automatically extract the three-dimensional space coordinate information of the feature points in the image in real time. First, the image processing device 14 processes the beautified image from the image receiving device 13 to recognize the feature points of the left and right cameras. And simultaneously, matching two-dimensional coordinates of image feature points in the left camera and the right camera in a left-right corresponding mode. The image processing device 14 automatically generates two-dimensional coordinates X of feature points in the left and right camerasi,YiConverted into three-dimensional space coordinate Xi,Yi,ZiAnd transmitted to the data storage module 15 through the transmission line 17.
And 4, step 4: a displacement threshold of 3mm is set in the warning evaluation device 16.
And 5: the data storage module 15 stores the data (X)i，Yi，Zi) And the data is input into an alarm evaluation device 16 through a transmission line 17 to judge the safety state of the slope.
Step 6: the alarm 8 is triggered, a signal is sent out, and the slope displacement value at the moment is displayed in the display 7 for the operator to view.
The image acquisition equipment 1 is provided with a camera 11 and an illuminating lamp 10; the camera 11 adopts a binocular camera to acquire monitoring image data of the slope surface at an overlooking angle; the illuminating lamp 10 is used for night illumination; the image acquisition equipment 1 is connected with a telescopic frame rod 3 through a rotatable hinge 2 and is fixed on a crawler traveling mechanism 9 by using a support 4; the slope surface 12 of the side slope is in a natural state.
The central processor 6 is fixed on the crawler traveling mechanism 9 through the support 5, and the display 7 and the alarm 8 are fixed on the central processor 6 in a sticking way; the cpu 6 includes an image receiving device 13, an image processing device 14, a data storage device 15, an alarm evaluation device 16, a transmission line 17 and a power switch 18.
The image receiving device 13 is used for receiving and beautifying the image, and is connected with the image processing device 14 through a transmission line 17 by adopting a Gaussian filter algorithm.
The image processing device 14 is used for identifying the characteristic points in the image and measuring the three-dimensional space coordinates of the characteristic points, and is connected with the data storage device 15 through a transmission line 17 by adopting a MASK-RCNN algorithm.
The data storage device 15 stores data (X) from the image processing device 14 through the transmission line 17i，Yi，Zi) And transmitted to the warning evaluation device 16 through the transmission line 17.
The warning evaluation device 16 can set a warning value to be 3 mm/day in advance, and if the slope displacement value of the day exceeds 3mm, the alarm 8 is triggered and the value is displayed in the display 7 in real time.
The alarm 8, when the displacement value is greater than the warning value 3mm, start bee calling organ and warning light, its value is less, and bee calling organ sound is bigger, and the warning light flicker frequency is faster.
The invention discloses a binocular vision automatic slope displacement monitoring method which adopts a means of combining a binocular vision technology and machine vision. Firstly, monitoring the slope of a monitored object slope in real time; secondly, calculating the real displacement value of the whole slope in real time by using a binocular vision technology and a machine vision means; and finally, evaluating the real-time displacement value of the alarm through the alarm value set in advance, if the real-time displacement value exceeds the alarm value set in advance, triggering an alarm, and simultaneously displaying the alarm on a screen to inform a manager. The method improves the accuracy and efficiency of information acquisition, identification and processing, can reflect the safety state of the slope site in real time, and realizes automatic monitoring of the whole slope site. The technical means disclosed in the invention scheme are not limited to the technical means disclosed in the above embodiments, but also include the technical scheme formed by any combination of the above technical features.
Claims (6)
1. A binocular vision automatic slope displacement monitoring method is characterized by comprising the following steps:
step 1: acquiring a slope surface image in real time through image acquisition equipment;
step 2: carrying out denoising and distortion correction on an image by an image processing device, and then carrying out dynamic identification on image characteristic points;
and step 3: the method comprises the steps of utilizing an image processing device to automatically extract three-dimensional space coordinate information of feature points in images in real time, firstly completing automatic calibration of a binocular vision camera, secondly identifying two-dimensional coordinates of image feature points in left and right cameras simultaneously and carrying out left and right corresponding matching, and finally automatically generating two-dimensional coordinates X of the feature points in the left and right camerasi,YiConverted into three-dimensional space coordinate Xi,Yi,Zi；
And 4, step 4: setting a displacement threshold in the alert evaluation device;
and 5: data (X)i，Yi，Zi) Inputting the slope safety state into a warning evaluation device to judge the slope safety state;
step 6: triggering an alarm system, sending a signal, and displaying the slope displacement value at the moment in a display for an operator to view.
2. The binocular vision automatic slope displacement monitoring method according to claim 1, wherein a camera and an illuminating lamp are arranged on the image acquisition equipment. The camera adopts a binocular camera, acquires the monitoring image data of the slope surface of the side slope at an overlooking angle, is connected with the telescopic frame rod through the rotatable hinge, and is fixed on the crawler traveling mechanism by using the support; the illuminating lamp is used for night illumination; the slope surface of the side slope is in a natural state.
3. The binocular vision automatic slope displacement monitoring method as claimed in claim 1, wherein the image receiving device is used for receiving images and beautifying the images, and is connected with the image processing device through a transmission line by adopting a Gaussian filter algorithm.
4. The real-time early warning method based on the safety states of construction workers and dynamic dangerous sources as claimed in claim 1, wherein the image processing device is used for identifying the feature points in the image and measuring the three-dimensional space coordinates of the feature points, and is connected with the data storage device through a transmission line by adopting a MASK-RCNN algorithm.
5. The real-time early warning method based on safety states of construction workers and dynamic hazard sources as claimed in claim 1, wherein the data storage device stores data (X) from the image processing device through a transmission linei，Yi，Zi) And transmitting the alarm signal to the alarm evaluation device through a transmission line.
6. The real-time early warning method based on the safety states of construction workers and dynamic hazard sources as claimed in claim 1, wherein the warning assessment device can set the warning value to 3 mm/day in advance, and if the slope displacement value of the day exceeds 3mm, an alarm is triggered and the value is displayed in the display in real time.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114648575A (en) * | 2022-04-01 | 2022-06-21 | 合肥学院 | Track slope displacement binocular vision detection method and system based on ORB algorithm |
| CN114663501A (en) * | 2022-05-17 | 2022-06-24 | 深圳市华世智能科技有限公司 | Geological disaster early warning method based on feature code image pose detection |
Citations (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2002031529A (en) * | 2000-07-17 | 2002-01-31 | Kansai Koji Sokuryo Kk | Automated position measuring system and method therefor |
| CN102721370A (en) * | 2012-06-18 | 2012-10-10 | 南昌航空大学 | Real-time mountain landslide monitoring method based on computer vision |
| CN104501735A (en) * | 2014-12-23 | 2015-04-08 | 大连理工大学 | Method for observing three-dimensional deformation of side slope by utilizing circular marking points |
| CN104690709A (en) * | 2015-02-16 | 2015-06-10 | 溧阳市超强链条制造有限公司 | Wheel-track composite moving detection robot |
| CN204679861U (en) * | 2015-06-12 | 2015-09-30 | 任天第 | From line delay production car and scenario reduction production car |
| CN205592588U (en) * | 2016-04-26 | 2016-09-21 | 江西服装学院 | 3D scanning device camera adjusting device |
| US20170094144A1 (en) * | 2015-09-24 | 2017-03-30 | Sharp Kabushiki Kaisha | Mobile vehicle |
| KR101833057B1 (en) * | 2017-12-14 | 2018-04-13 | (주)지스페이스코리아 | 3-dimension space image drawing system |
| CN209043242U (en) * | 2018-12-27 | 2019-06-28 | 贵州大学 | One kind is around multi-faceted Rosa roxburghii Tratt detection system |
| CN110297232A (en) * | 2019-05-24 | 2019-10-01 | 合刃科技（深圳）有限公司 | Monocular distance measuring method, device and electronic equipment based on computer vision |
| CN110332894A (en) * | 2019-07-10 | 2019-10-15 | 中国地质大学（武汉） | A kind of untouchable measurement method of dam surface displacement based on binocular vision |
| CN110514126A (en) * | 2019-09-30 | 2019-11-29 | 西南石油大学 | A method of the tunnel tunnel face displacement monitoring based on machine vision |
| CN110599489A (en) * | 2019-08-26 | 2019-12-20 | 华中科技大学 | Target space positioning method |
| CN111679060A (en) * | 2020-06-28 | 2020-09-18 | 河海大学 | Angle-variable slope model test device and method under coupling action of earthquake and rainfall |
| CN212721324U (en) * | 2020-09-25 | 2021-03-16 | 西南石油大学 | Butterfly-shaped mark point soft rock foundation surface deformation monitoring device based on binocular vision |
| KR20210049655A (en) * | 2019-10-25 | 2021-05-06 | 네이버 주식회사 | Apparatus and method for generating feature maps |
-
2021
- 2021-05-31 CN CN202110597490.8A patent/CN113267128A/en active Pending
Patent Citations (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2002031529A (en) * | 2000-07-17 | 2002-01-31 | Kansai Koji Sokuryo Kk | Automated position measuring system and method therefor |
| CN102721370A (en) * | 2012-06-18 | 2012-10-10 | 南昌航空大学 | Real-time mountain landslide monitoring method based on computer vision |
| CN104501735A (en) * | 2014-12-23 | 2015-04-08 | 大连理工大学 | Method for observing three-dimensional deformation of side slope by utilizing circular marking points |
| CN104690709A (en) * | 2015-02-16 | 2015-06-10 | 溧阳市超强链条制造有限公司 | Wheel-track composite moving detection robot |
| CN204679861U (en) * | 2015-06-12 | 2015-09-30 | 任天第 | From line delay production car and scenario reduction production car |
| US20170094144A1 (en) * | 2015-09-24 | 2017-03-30 | Sharp Kabushiki Kaisha | Mobile vehicle |
| CN205592588U (en) * | 2016-04-26 | 2016-09-21 | 江西服装学院 | 3D scanning device camera adjusting device |
| KR101833057B1 (en) * | 2017-12-14 | 2018-04-13 | (주)지스페이스코리아 | 3-dimension space image drawing system |
| CN209043242U (en) * | 2018-12-27 | 2019-06-28 | 贵州大学 | One kind is around multi-faceted Rosa roxburghii Tratt detection system |
| CN110297232A (en) * | 2019-05-24 | 2019-10-01 | 合刃科技（深圳）有限公司 | Monocular distance measuring method, device and electronic equipment based on computer vision |
| CN110332894A (en) * | 2019-07-10 | 2019-10-15 | 中国地质大学（武汉） | A kind of untouchable measurement method of dam surface displacement based on binocular vision |
| CN110599489A (en) * | 2019-08-26 | 2019-12-20 | 华中科技大学 | Target space positioning method |
| CN110514126A (en) * | 2019-09-30 | 2019-11-29 | 西南石油大学 | A method of the tunnel tunnel face displacement monitoring based on machine vision |
| KR20210049655A (en) * | 2019-10-25 | 2021-05-06 | 네이버 주식회사 | Apparatus and method for generating feature maps |
| CN111679060A (en) * | 2020-06-28 | 2020-09-18 | 河海大学 | Angle-variable slope model test device and method under coupling action of earthquake and rainfall |
| CN212721324U (en) * | 2020-09-25 | 2021-03-16 | 西南石油大学 | Butterfly-shaped mark point soft rock foundation surface deformation monitoring device based on binocular vision |
Non-Patent Citations (2)
| Title |
|---|
| 叶子涵 等: "基于视觉和动态运动基元的机械臂抓取轨迹规划", 机器人技术与应用, no. 03, 15 June 2020 (2020-06-15), pages 31 - 36 * |
| 王晓光 等: "地震振动台实验三维全场位移测量的研究", 应用光学, no. 04, 15 July 2016 (2016-07-15), pages 567 - 572 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114648575A (en) * | 2022-04-01 | 2022-06-21 | 合肥学院 | Track slope displacement binocular vision detection method and system based on ORB algorithm |
| CN114663501A (en) * | 2022-05-17 | 2022-06-24 | 深圳市华世智能科技有限公司 | Geological disaster early warning method based on feature code image pose detection |
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