CN105319050A - Test measuring system of riverbank lateral erosion collapse rate and measuring method thereof - Google Patents
Test measuring system of riverbank lateral erosion collapse rate and measuring method thereof Download PDFInfo
- Publication number
- CN105319050A CN105319050A CN201510575400.XA CN201510575400A CN105319050A CN 105319050 A CN105319050 A CN 105319050A CN 201510575400 A CN201510575400 A CN 201510575400A CN 105319050 A CN105319050 A CN 105319050A
- Authority
- CN
- China
- Prior art keywords
- riverbank
- lateral erosion
- image
- grid
- avalanche
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Abstract
The invention provides a test measuring system of a riverbank lateral erosion collapse rate. The test measuring system comprises a tracing grid on a riverbank model, a shooting device and an image processing system. The shooting range of the shooting device covers the tracing grid on the riverbank model. The shooting device is connected with an image processing system. The method comprises the steps of: carrying out uniform grid marking on an upstream face bank slope of a riverbank lateral erosion collapse model, and forming an equal-interval tracing grid; in the test process, carrying out image collection through a high-precision camera; by means of binary image segmentation and digital image processing, extracting position coordinates of grid nodes of a newest bank line after lateral erosion collapse of a riverbank; carrying out coordinate conversion, comparing the position coordinates of the newest bank line with position coordinates of an initial bank line, and calculating a riverbank lateral erosion collapse distance; and then dividing the riverbank lateral erosion collapse distance by a time interval, and obtaining the riverbank lateral erosion collapse rate. According to the invention, measured data is accurate, and a technical support is effectively provided for deep research of a riverbank lateral erosion collapse mechanical mechanism and a forecasting method thereof.
Description
Technical field
The present invention relates to testing & measuring system and the method for measurement thereof of a kind of riverbank lateral erosion avalanche speed in the basic test research of hydraulic engineering river dynamics field.
Background technology
Riverbank lateral erosion avalanche phenomenon is distributed widely among each large rivers in the world, and lateral erosion avalanche phenomenon in riverbank also often can occur in the river such as the Changjiang river, the Yellow River of China, especially shows the most outstanding after flood season and flood, is the disaster that a kind of harm is very large.Riverbank lateral erosion avalanche often leads to great dangerous situation, and the safety of life and property of people across the Straits in serious threat.In addition, riverbank lateral erosion avalanche can cause river course to produce transversely deforming toward contact, causes river gesture acute variation, all causes great adverse effect to the aspects such as flood control, navigation channel, harbour, also brings many difficulties to river controlling projects, and the example of this respect is lifted and is unequal to number.As can be seen here, riverbank lateral erosion avalanche problem is one of problem the most serious in flood control and river regulation, and be an important and urgent problem by the process of experimental study riverbank lateral erosion avalanche and mechanical mechanism thereof, the prediction that can be riverbank lateral erosion avalanche provides technical support.
The river-bed deformation of great rivers comprises transversely deforming two aspect of vertical erosion and deposition and effluent bank lateral erosion avalanche initiation.At present, the achievement in research of being out of shape about vertical change in bed level is more also more ripe, the research of the riverbed transversely deforming caused about riverbank lateral erosion avalanche is then relatively less, comprises the understanding of riverbank lateral erosion avalanche Changing Pattern, mathematical description mode and simulation test research and all lags behind the change of vertical change in bed level.From present stage situation, though riverbank lateral erosion avalanche belongs to the problem received much attention in river engineering field, but experimental study means and method for measurement are all inadequate, the surveying instrument spininess that adopts of the experimental study of change in bed level change is in the past to the vertical Scour and Accretion of bed configuration under water, then be short of very much for the surveying instrument easily and effectively of riverbank lateral erosion avalanche and method for measurement thereof, this becomes a large technical bottleneck of research riverbank lateral erosion avalanche mechanical mechanism gradually.
Summary of the invention
For this problem, the present invention will propose a kind of testing & measuring system and method for measurement thereof can measuring riverbank lateral erosion avalanche speed easily and effectively, thus provide technical support for the further investigation of riverbank lateral erosion avalanche mechanical mechanism and forecasting procedure thereof.
The invention provides following technical scheme:
A testing & measuring system for riverbank lateral erosion avalanche speed, comprising: spike grid, filming apparatus and image processing system on the model of riverbank; The coverage of described filming apparatus covers the spike grid on the model of described riverbank, and described filming apparatus is connected with described image processing system.
Further, the spike grid on the model of described riverbank scribbles whiteness tracer agent.
Further, image processing system comprises: image sampling module, image segmentation module, collapse on the bank point identification module, coordinate extraction module and coordinate transferring;
The image information of filming apparatus shooting described in described image sampling module acquires;
Described image segmentation module, by Image Segmentation Using process, forms binary image;
Described collapse on the bank point identification module carries out the identification of collapse on the bank point to the image after segmentation;
Described coordinate extraction module extracts the up-to-date water front grid node locations coordinate after the lateral erosion avalanche of riverbank;
The up-to-date water front grid node locations coordinate extracted and initial water front position coordinates contrast by described coordinate transferring, calculate riverbank lateral erosion and collapse and move back distance; Then collapse with riverbank lateral erosion and move back distance divided by the time interval, just can obtain riverbank lateral erosion avalanche speed.
A test method for measurement for riverbank lateral erosion avalanche speed, comprises the steps:
S1, test prepare, and accurately produce riverbank lateral erosion avalanche model with the model sasnd that color is darker, lateral erosion avalanche model side, described riverbank is the ladder type with inclination angle, then on upstream face bank slope, uniform grid mark is carried out with whiteness tracer agent, form equidistant spike grid, the water stirring that whiteness tracer agent mixes about 20 ~ 40% by talcum powder forms, then whiteness tracer agent is loaded in plastic bottle, and an aperture is opened with needle point on bottle cap, make whiteness tracer agent can squeeze injection to be as the criterion, uniform grid is marked with fine rule on bank slope by ruler in advance, and then indicate one by one with whiteness tracer agent, thus form equally spaced whiteness tracer grid, wherein longitudinal network ruling is set to vertical flow direction as far as possible, that is be parallel to riverbank lateral erosion and collapse and move back direction, finally, filming apparatus is arranged in above the water surface, and vertical with slope, and adopt less to ensure grid image distortion compared with long focal length lens, and by transmission line, high-definition camera is connected with computer measurement system,
S2, carry out lateral erosion avalanche test, collection model grid gray level image carries out binary conversion treatment; In riverbank lateral erosion avalanche process of the test, by current scour effect, upstream face bank slope constantly collapses and moves back, and the soil body comprising whiteness tracer grid constantly to cave in water and is pulled away, control camera continuous acquisition model meshes gray level image by computing machine, and distortion correction is carried out to image; In order to extract grid image, first need to carry out binary image segmentation by following formula:
G(i,j)≥T(i,j)，G(i,j)＝255
G(i,j)＜T(i,j)，G(i,j)＝0
In above formula, G (i, j) for pixel coordinate in image be the gray-scale value at (i, j) place, intensity value ranges is (0-255), and 0 is black, 255 be white; T (i, j) is for carrying out the threshold value of binarization segmentation; When this threshold value is set, the continuity of grid be ensured, also will remove picture noise simultaneously as far as possible;
S3, search each longitudinal network ruling collapse on the bank point position one by one; By in advance to image calibration, determine the image transverse and longitudinal changes in coordinates scope of every bar mesh lines; Suppose that the horizontal ordinate variation range of kth bar longitudinal network ruling is for (M
1< I
k< M
2), ordinate variation range is (N
1< J
k< N
2); First from (N
1~ N
2) go and carry out longitudinal searching, namely from crossing the bank slope direction search to the inside gradually of water side, to jth row (N
1< j < N
2) pixel, at (M
1< i < M
2) pixel in scope searches for, one by one if meet following condition:
G(i,j)＝255，(M
1＜i＜M
2,N
1＜j＜N
2)
The then avalanche point coordinate X of kth bar longitudinal network ruling
k=i, Y
k=j;
Image coordinate and model coordinate ratio S can measure in advance, identify avalanche point and extract this point coordinate (X
k, Y
k) after, with image and model origin (X
0, Y
0) compare, be just converted to model collapse on the bank point coordinate by following formula:
x
k＝(X
k-X
o)×S
y
k＝(Y
k-Y
o)×S；
S4, calculate riverbank lateral erosion and collapse back speed rate, successively image procossing is carried out to the every bar longitudinal network ruling in model, extract mesh point coordinate after collapse on the bank, and with the corresponding initial water front position of longitudinal network ruling (x
0, y
0) contrast, calculate the riverbank lateral erosion avalanche displacement L of every bar longitudinal network ruling, then divided by time interval Δ t, just can obtain riverbank lateral erosion avalanche speed v, that is:
v＝L/Δt。
The invention has the beneficial effects as follows: measurement data of the present invention is accurate and effective, technical support can be provided for the further investigation of riverbank lateral erosion avalanche mechanical mechanism and forecasting procedure thereof.
Accompanying drawing explanation
Accompanying drawing is used to provide a further understanding of the present invention, and forms a part for instructions, together with embodiments of the present invention for explaining the present invention, is not construed as limiting the invention.In the accompanying drawings:
Fig. 1 is present system preferred embodiment model side view;
Fig. 2 is the vertical view of Fig. 1;
Fig. 3 is typical grid bianry image in riverbank lateral erosion avalanche process of the test.
Embodiment
In the present embodiment, testing & measuring system composition as shown in Figure 1 and Figure 2, mainly comprises: the spike grid on the model of riverbank, high-definition camera, image processing system.
Measuring principle: adopt the whiteness tracer agent with dark model sasnd color contrast distinctness, carry out uniform grid mark on model upstream face bank slope is caved in riverbank lateral erosion, form equidistant spike grid; Image acquisition is carried out by high-precision camera, and split and Digital Image Processing by binary image, extract the up-to-date water front grid node locations coordinate after the lateral erosion avalanche of riverbank, and contrasted with initial (or arbitrarily upper moment) water front position coordinates, calculate riverbank lateral erosion and collapse and move back distance; Then collapse with riverbank lateral erosion and move back distance divided by the time interval, just can obtain riverbank lateral erosion avalanche speed.
Concrete measuring process is as follows:
(1) riverbank lateral erosion avalanche model and measuring system are installed and are prepared.The first step, first accurately produce riverbank lateral erosion avalanche model with the model sasnd that color is darker, as shown in Figure 1, this model side is the ladder type with certain inclination angle, second step, then on upstream face bank slope, uniform grid mark is carried out with whiteness tracer agent, form equidistant spike grid, as shown in Figure 2, the water stirring that wherein whiteness tracer agent mixes about 20 ~ 40% by talcum powder forms, make it have certain toughness to be as the criterion, then loaded (mineral water bottle) in plastic bottle, and an aperture is opened with needle point on bottle cap, make whiteness tracer agent can squeeze injection to be as the criterion, uniform grid is marked with fine rule on bank slope by ruler in advance, and then indicate one by one with whiteness tracer agent, thus form equally spaced whiteness tracer grid, wherein longitudinal network ruling is set to vertical flow direction as far as possible, that is be parallel to riverbank lateral erosion and collapse and move back direction, finally, high-definition camera is arranged in above the water surface, and vertical with slope, and adopt less to ensure grid image distortion compared with long focal length lens, and by transmission line, high-definition camera is connected with computer measurement system.
(2) carry out lateral erosion avalanche test, collection model grid gray level image carries out binary conversion treatment.In riverbank lateral erosion avalanche process of the test, by current scour effect, upstream face bank slope constantly collapses and moves back, and the soil body comprising whiteness tracer grid constantly to cave in water and is pulled away, control camera continuous acquisition model meshes gray level image by computing machine, and distortion correction is carried out to image.In order to extract grid image, first need to carry out binary image segmentation by following formula:
G(i,j)≥T(i,j)，G(i,j)＝255
G(i,j)＜T(i,j)，G(i,j)＝0
In above formula, G (i, j) for pixel coordinate in image be the gray-scale value at (i, j) place, intensity value ranges is (0-255), and 0 is black, 255 be white.T (i, j) is for carrying out the threshold value of binarization segmentation.When this threshold value is set, the continuity of grid be ensured, also will remove picture noise simultaneously as far as possible.In riverbank lateral erosion avalanche process of the test, typical binaryzation grid image as shown in Figure 3, is only made up of (note: text display needs is black mesh lines and white background in Fig. 3) white mesh lines and black background.
(3) each longitudinal network ruling collapse on the bank point position is searched one by one.In riverbank lateral erosion avalanche process of the test, typical binaryzation grid image as shown in Figure 3, is only made up of (note: text display needs is black mesh lines and white background in Fig. 3) white mesh lines and black background.By in advance to image calibration, determine the image transverse and longitudinal changes in coordinates scope of every bar mesh lines.Suppose that the horizontal ordinate variation range of kth bar longitudinal network ruling is for (M
1< I
k< M
2), ordinate variation range is (N
1< J
k< N
2), as shown in Figure 3.First from (N
1~ N
2) go and carry out longitudinal searching, namely from crossing the bank slope direction search to the inside gradually of water side, to jth row (N
1< j < N
2) pixel, at (M
1< i < M
2) pixel in scope searches for, one by one if meet following condition:
G(i,j)＝255，(M
1＜i＜M
2,N
1＜j＜N
2)
The then avalanche point coordinate X of kth bar longitudinal network ruling
k=i, Y
k=j.
Image coordinate and model coordinate ratio S can measure in advance, identify avalanche point and extract this point coordinate (X
k, Y
k) after, with image and model origin (X
0, Y
0) compare, be just converted to model collapse on the bank point coordinate by following formula:
x
k＝(X
k-X
o)×S
y
k＝(Y
k-Y
o)×S
(4) calculate riverbank lateral erosion and collapse back speed rate.Successively above-mentioned image procossing is carried out to the every bar longitudinal network ruling in model, extract mesh point coordinate after collapse on the bank, and initial with corresponding longitudinal network ruling (or arbitrarily upper moment) water front position (x
0, y
0) contrast, calculate the riverbank lateral erosion avalanche displacement L of every bar longitudinal network ruling, then divided by time interval Δ t, just can obtain riverbank lateral erosion avalanche speed v, that is:
v＝L/Δt
The foregoing is only the preferred embodiments of the present invention, be not limited to the present invention, although with reference to previous embodiment to invention has been detailed description, for a person skilled in the art, it still can be modified to the technical scheme described in foregoing embodiments, or carries out equivalent replacement to wherein portion of techniques feature.Within the spirit and principles in the present invention all, any amendment done, equivalent replacement, improvement etc., all should be included within protection scope of the present invention.
Claims (5)
1. a testing & measuring system for riverbank lateral erosion avalanche speed, is characterized in that, comprising: spike grid, filming apparatus and image processing system on the model of riverbank; The coverage of described filming apparatus covers the spike grid on the model of described riverbank, and described filming apparatus is connected with described image processing system.
2. the testing & measuring system of lateral erosion avalanche speed in riverbank according to claim 1, is characterized in that, the spike grid on the model of described riverbank scribbles whiteness tracer agent.
3. the testing & measuring system of the riverbank lateral erosion avalanche speed according to any one in claim 1-2, it is characterized in that, image processing system comprises: image sampling module, image segmentation module, collapse on the bank point identification module, coordinate extraction module and coordinate transferring;
The image information of filming apparatus shooting described in described image sampling module acquires;
Described image segmentation module, by Image Segmentation Using process, forms binary image;
Described collapse on the bank point identification module carries out the identification of collapse on the bank point to the image after segmentation;
Described coordinate extraction module extracts the up-to-date water front grid node locations coordinate after the lateral erosion avalanche of riverbank;
The up-to-date water front grid node locations coordinate extracted and initial water front position coordinates contrast by described coordinate transferring, calculate riverbank lateral erosion and collapse and move back distance; Then collapse with riverbank lateral erosion and move back distance divided by the time interval, just can obtain riverbank lateral erosion avalanche speed.
4. a test method for measurement for riverbank lateral erosion avalanche speed, is characterized in that, comprise the steps:
S1, test prepare, and accurately produce riverbank lateral erosion avalanche model with the model sasnd that color is darker, lateral erosion avalanche model side, described riverbank is the ladder type with inclination angle; Then on upstream face bank slope, uniform grid mark is carried out with whiteness tracer agent, form equidistant spike grid, then whiteness tracer agent is loaded in plastic bottle, and an aperture is opened with needle point on bottle cap, make whiteness tracer agent can squeeze injection to be as the criterion, uniform grid is marked with fine rule on bank slope by ruler in advance, and then indicate one by one with whiteness tracer agent, thus form equally spaced whiteness tracer grid, wherein longitudinal network ruling is set to vertical flow direction as far as possible, that is is parallel to riverbank lateral erosion and collapses and move back direction; Finally, filming apparatus is arranged in above the water surface, and vertical with slope, and adopt less to ensure grid image distortion compared with long focal length lens, and by transmission line, high-definition camera is connected with computer measurement system;
S2, carry out lateral erosion avalanche test, collection model grid gray level image carries out binary conversion treatment; In riverbank lateral erosion avalanche process of the test, by current scour effect, upstream face bank slope constantly collapses and moves back, and the soil body comprising whiteness tracer grid constantly to cave in water and is pulled away, control camera continuous acquisition model meshes gray level image by computing machine, and distortion correction is carried out to image; In order to extract grid image, first need to carry out binary image segmentation by following formula:
G(i,j)≥T(i,j)，G(i,j)＝255
G(i,j)＜T(i,j)，G(i,j)＝0
In above formula, G (i, j) for pixel coordinate in image be the gray-scale value at (i, j) place, intensity value ranges is (0-255), and 0 is black, 255 be white; T (i, j) is for carrying out the threshold value of binarization segmentation; When this threshold value is set, the continuity of grid be ensured, also will remove picture noise simultaneously as far as possible;
S3, search each longitudinal network ruling collapse on the bank point position one by one; By in advance to image calibration, determine the image transverse and longitudinal changes in coordinates scope of every bar mesh lines; Suppose that the horizontal ordinate variation range of kth bar longitudinal network ruling is for (M
1< I
k< M
2), ordinate variation range is (N
1< J
k< N
2); First from (N
1~ N
2) go and carry out longitudinal searching, namely from crossing the bank slope direction search to the inside gradually of water side, to jth row (N
1< j < N
2) pixel, at (M
1< i < M
2) pixel in scope searches for, one by one if meet following condition:
G(i,j)＝255，(M
1＜i＜M
2,N
1＜j＜N
2)
The then avalanche point coordinate X of kth bar longitudinal network ruling
k=i, Y
k=j;
Image coordinate and model coordinate ratio S can measure in advance, identify avalanche point and extract this point coordinate (X
k, Y
k) after, with image and model origin (X
0, Y
0) compare, be just converted to model collapse on the bank point coordinate by following formula:
x
k＝(X
k-X
o)×S
y
k＝(Y
k-Y
o)×S；
S4, calculate riverbank lateral erosion and collapse back speed rate, successively image procossing is carried out to the every bar longitudinal network ruling in model, extract mesh point coordinate after collapse on the bank, and with the corresponding initial water front position of longitudinal network ruling (x
0, y
0) contrast, calculate the riverbank lateral erosion avalanche displacement L of every bar longitudinal network ruling, then divided by time interval Δ t, just can obtain riverbank lateral erosion avalanche speed v, that is:
v＝L/Δt。
5. the test method for measurement of lateral erosion avalanche speed in riverbank according to claim 4, is characterized in that, the water stirring that in S1, whiteness tracer agent mixes about 20 ~ 40% by talcum powder forms.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510575400.XA CN105319050B (en) | 2015-09-10 | 2015-09-10 | The testing ＆ measuring system and its method for measurement of riverbank lateral erosion avalanche speed |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510575400.XA CN105319050B (en) | 2015-09-10 | 2015-09-10 | The testing ＆ measuring system and its method for measurement of riverbank lateral erosion avalanche speed |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN105319050A true CN105319050A (en) | 2016-02-10 |
| CN105319050B CN105319050B (en) | 2017-12-15 |
Family
ID=55246922
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510575400.XA Active CN105319050B (en) | 2015-09-10 | 2015-09-10 | The testing ＆ measuring system and its method for measurement of riverbank lateral erosion avalanche speed |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105319050B (en) |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108955999A (en) * | 2018-05-14 | 2018-12-07 | 武汉大学 | A kind of Bank Failure real-time monitoring device based on pressure sensing technology |
| CN109029278A (en) * | 2018-06-29 | 2018-12-18 | 广西大学 | Grid protects the monitoring device and monitoring method of side slope surface stress strain |
| CN111549716A (en) * | 2020-04-26 | 2020-08-18 | 武汉大学 | Method for calculating and describing river bank collapse mode with binary structure |
| CN111896366A (en) * | 2020-08-19 | 2020-11-06 | 黄河水利委员会黄河水利科学研究院 | Method for simulating multi-structure river bank impedance water flow scouring |
| CN111962457A (en) * | 2020-08-19 | 2020-11-20 | 黄河水利委员会黄河水利科学研究院 | Hydraulic model for simulating multi-element structure river bank impedance water flow scouring |
| CN115391904A (en) * | 2022-10-27 | 2022-11-25 | 河海大学 | River bank collapse early warning method and system |
| CN116109869A (en) * | 2023-02-20 | 2023-05-12 | 北京科技大学 | Method and device for identifying reservoir water level fluctuation based on water bank image matching |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101718527A (en) * | 2009-12-17 | 2010-06-02 | 丹东东方测控技术有限公司 | Method for calculating length of dry sand of tailings reservoir based on image recognition |
| CN102288778A (en) * | 2011-05-16 | 2011-12-21 | 西南交通大学 | Method for measuring surface speed of debris flow in real time based on grid object tracking |
| CN103698553A (en) * | 2013-12-26 | 2014-04-02 | 天津大学 | Novel surface flow field velocity measurement system and velocity measurement method on basis of infrared image pickup |
| RU2523737C1 (en) * | 2013-01-24 | 2014-07-20 | Федеральное государственное бюджетное учреждение науки Институт теплофизики им. С.С. Кутателадзе Сибирского отделения Российской академии наук (ИТ СО РАН) | Contactless optical-laser diagnostics of transient hydraulic flow and device to this end |
| CN104776977A (en) * | 2015-04-28 | 2015-07-15 | 中国海洋大学 | Coastal engineering silt physical model test bottom bed dynamic and comprehensive observation method |
-
2015
- 2015-09-10 CN CN201510575400.XA patent/CN105319050B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101718527A (en) * | 2009-12-17 | 2010-06-02 | 丹东东方测控技术有限公司 | Method for calculating length of dry sand of tailings reservoir based on image recognition |
| CN102288778A (en) * | 2011-05-16 | 2011-12-21 | 西南交通大学 | Method for measuring surface speed of debris flow in real time based on grid object tracking |
| RU2523737C1 (en) * | 2013-01-24 | 2014-07-20 | Федеральное государственное бюджетное учреждение науки Институт теплофизики им. С.С. Кутателадзе Сибирского отделения Российской академии наук (ИТ СО РАН) | Contactless optical-laser diagnostics of transient hydraulic flow and device to this end |
| CN103698553A (en) * | 2013-12-26 | 2014-04-02 | 天津大学 | Novel surface flow field velocity measurement system and velocity measurement method on basis of infrared image pickup |
| CN104776977A (en) * | 2015-04-28 | 2015-07-15 | 中国海洋大学 | Coastal engineering silt physical model test bottom bed dynamic and comprehensive observation method |
Non-Patent Citations (2)
| Title |
|---|
| 假冬冬等: "分层岸滩侧蚀坍塌过程及其水动力响应模拟", 《水科学进展》 * |
| 陈明泉等: "Matlab平台下遥感影像的海岸线检测与提取方法", 《湖北工业大学学报》 * |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108955999A (en) * | 2018-05-14 | 2018-12-07 | 武汉大学 | A kind of Bank Failure real-time monitoring device based on pressure sensing technology |
| CN109029278A (en) * | 2018-06-29 | 2018-12-18 | 广西大学 | Grid protects the monitoring device and monitoring method of side slope surface stress strain |
| CN111549716A (en) * | 2020-04-26 | 2020-08-18 | 武汉大学 | Method for calculating and describing river bank collapse mode with binary structure |
| CN111549716B (en) * | 2020-04-26 | 2021-06-22 | 武汉大学 | Method for calculating and describing river bank collapse mode with binary structure |
| CN111896366A (en) * | 2020-08-19 | 2020-11-06 | 黄河水利委员会黄河水利科学研究院 | Method for simulating multi-structure river bank impedance water flow scouring |
| CN111962457A (en) * | 2020-08-19 | 2020-11-20 | 黄河水利委员会黄河水利科学研究院 | Hydraulic model for simulating multi-element structure river bank impedance water flow scouring |
| CN115391904A (en) * | 2022-10-27 | 2022-11-25 | 河海大学 | River bank collapse early warning method and system |
| CN116109869A (en) * | 2023-02-20 | 2023-05-12 | 北京科技大学 | Method and device for identifying reservoir water level fluctuation based on water bank image matching |
| CN116109869B (en) * | 2023-02-20 | 2024-02-20 | 北京科技大学 | Method and device for identifying reservoir water level fluctuation based on water bank image matching |
Also Published As
| Publication number | Publication date |
|---|---|
| CN105319050B (en) | 2017-12-15 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105319050A (en) | Test measuring system of riverbank lateral erosion collapse rate and measuring method thereof | |
| Moussaid et al. | Using automatic computation to analyze the rate of shoreline change on the Kenitra coast, Morocco | |
| Chen et al. | Temporal and spatial variation of coastline using remote sensing images for Zhoushan archipelago, China | |
| CN106896213B (en) | A kind of rock mass discontinuity intelligent recognition and information extracting method based on point cloud data | |
| US9625611B2 (en) | Method for detecting zonal underground target in mountain land based on ridge heat radiation correction | |
| Xu et al. | Analysis of the characteristics and causes of coastline variation in the Bohai Rim (1980–2010) | |
| CN104652347B (en) | Mountain area non-static water body water level affects population assessed in relation method with flooding | |
| Liu et al. | Automated extraction of tidal creeks from airborne laser altimetry data | |
| CN105387801A (en) | Subway tunnel segment dislocation quantity detection method | |
| Shand et al. | Longshore realignment of shore-parallel sand-bars at Wanganui, New Zealand | |
| CN103914829B (en) | Method for detecting edge of noisy image | |
| Vojtko et al. | Neotectonic evolution of the northern Laborec drainage basin (northeastern part of Slovakia) | |
| Alemi Safaval et al. | Morphological changes in the southern coasts of the Caspian Sea using remote sensing and GIS | |
| CN104596484A (en) | Method of measuring drift ice density in ice flood season of Yellow River | |
| Ye et al. | A novel approach for high-quality drainage network extraction in flat terrains by using a priori knowledge of hydrogeomorphic features to extend DEMs: A case study in the Hoh Xil region of the Qinghai-Tibetan Plateau | |
| Anh et al. | Sand spit morphological evolution at tidal inlets by using satellite images analysis: Two case studies in Vietnam | |
| Medina-Cascales et al. | Tectonic geomorphology of an active slow-moving, intrabasinal fault: The Galera Fault (Guadix-Baza Basin, central Betic Cordillera, southern Spain) | |
| CN104597286A (en) | Yellow River ice run ice floating speed measuring method | |
| Xu et al. | Extraction and spatiotemporal evolution analysis of tidal flats in the Bohai Rim during 1984–2019 based on remote sensing | |
| Wu et al. | Coastal reclamation shaped narrower and steeper tidal flats in Fujian, China: Evidence from time-series satellite data | |
| CN114565657A (en) | Method for extracting river width in remote sensing image based on edge gradient and direction texture | |
| Mahmoodzada et al. | Monitoring of riverbank erosion and shoreline movement at Amu River using remote sensing and GIS: a case study in Jowzjan, Afghanistan | |
| CN103295015B (en) | The local feature point extracting method of partial occlusion target | |
| Scheip | Integrating water-classified returns in DTM generation to increase accuracy of stream delineations and geomorphic analyses | |
| Gopinath et al. | Geomorphological analysis of tropical river basins in southern Kerala using hypsometric indices and neotectonic proxies |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |