CN107764192A - One kind landslide multi-point displacement intelligent monitoring device and monitoring method - Google Patents

One kind landslide multi-point displacement intelligent monitoring device and monitoring method Download PDF

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Publication number
CN107764192A
CN107764192A CN201711239416.9A CN201711239416A CN107764192A CN 107764192 A CN107764192 A CN 107764192A CN 201711239416 A CN201711239416 A CN 201711239416A CN 107764192 A CN107764192 A CN 107764192A
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mrow
module
landslide
point
monitoring
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殷跃平
郭伟
王晨辉
曹修定
潘书华
王洪磊
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Center for Hydrogeology and Environmental Geology CGS
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Center for Hydrogeology and Environmental Geology CGS
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    • GPHYSICS
    • G01MEASURING; TESTING
    • G01BMEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00Measuring arrangements characterised by the use of optical techniques
    • G01B11/02Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness
    • G01B11/026Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness by measuring distance between sensor and object

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  • General Physics & Mathematics (AREA)
  • Alarm Systems (AREA)

Abstract

The invention discloses one kind landslide multi-point displacement intelligent monitoring device, including intelligent control module, intelligent control module is connected to landslide multi-point displacement monitoring modular, storage display module, data communication module and power supply module, and intelligent control module gathers the data of landslide target monitoring point by the multi-point displacement monitoring modular that comes down and sends result to distant early warning platform by data communication module.The invention also discloses a kind of monitoring method of supporting above-mentioned landslide multi-point displacement intelligent monitoring device, the present invention can improve existing landslide monitoring early warning technology, device realizes intelligentized control method, compact, easy for installation, simple to operate, precision is high, data visualization, the monitoring to landslide entirety or local deformation trend can be achieved, send warning information in time.

Description

One kind landslide multi-point displacement intelligent monitoring device and monitoring method
Technical field
The present invention relates to monitoring technology for geological hazards field, especially a kind of landslide multi-point displacement intelligent monitoring device and prison Survey method.
Background technology
Landslide is the sliding geological phenomenon that slope Rock And Soil is occurred along logical shear breakage is used to.The mechanism on landslide is Caused by shear stress has exceeded the shearing strength in the face on a certain slide surface.Industrial and agricultural production and people's life wealth are usually given in landslide Production brings about great losses, the even destructive disaster of some.
Landslide harm most important to rural area is to destroy farmland, room, injury people and animals, deforestation, road and agricultural Mechanical facility and water conservancy and hydropower facility etc., even cause crushing disaster to rural area sometimes.Usually pound and bury positioned at the landslide in cities and towns House, factory, school, institutional settings etc. are destroyed, and damage various facilities, caused to have a power failure, cut off the water, stop work, even destroyed sometimes Whole cities and towns.Occur on the landslide of industrial and mining area, mine facility can be destroyed, injures and deaths worker, factory building is damaged, make mine stop work and production, Often result in heavy losses.
Landslide is had by sliding speed division:Creep landslide, usual people can only pass through with being visually difficult to see its motion Instrument observation could be found;Come down at a slow speed, slide several centimeters daily to several tens cm, people can observe directly landslide with naked eyes Activity;Middling speed comes down, and slides the landslide of several tens cm to several meters per hour;HIGH-SPEED LANDSLIDE, it is per second to slide several meters to tens of rice Landslide.
Except wriggling comes down, people can have found to come down and withdraw early danger zone early.Come down for wriggling, It is disguised stronger, and harmfulness is bigger, and people are difficult to find, even if being unable to estimate it because its slip is slower after finding Liveness, difficulty is brought to people's disaster prevention and danger avoidance.China is the multiple area of geological disaster, and all parts of the country landslide is ten hundreds of, generally Belong to wriggling landslide, the safety of life and property of this people group of serious threat.
The existing geological disaster landslide monitoring method in China has mass presdiction and disaster prevention and professional monitoring two ways at present.
Mass presdiction and disaster prevention monitoring mode typically has artificial monitoring stake and landslide pantograph, and wherein personal monitoring's stake is in slip mass The staking out of two edge-on two, crack, by the relative displacement of two monitoring stakes of tape measure, and makes a record, for observing crack Tension degree;The pantograph that comes down is a kind of follow-on personal monitoring's stake, and tape measure and electronic component are integrated together, and increases Warning device is added, its equipment one end is arranged on the stable side in slip mass crack, and drawstring one end unstable side of fixing crack is sliding Slope pantograph inbuilt displacement threshold switch, after displacement reaches early warning value, landslide pantograph triggers external alarm equipment alarm, reminds Resident prevents and reduces natural disasters.
Professional monitoring mode has drawstring displacement monitor, earth's surface GNSS monitors, deep soils instrument, ground laser thunder Monitored up to scanner and InSAR.Its medium pulling rope displacement monitor is installed to slip mass crack both sides, monitors the relative of crack both sides Displacement, and Monitoring Data is transferred to distant early warning center by GPRS network, realize field unattended automatic data collection work( Energy.Its precision reaches 1mm levels, and systematic comparison is stable;Earth's surface GNSS monitors using satellite fix and algorithm with realizing slip mass The three-dimensional absolute displacement monitoring of table (X, Y, Z), precision reaches 5mm levels, overall to hold slip mass variation tendency for simulation modeling There is absolute predominance;Deep soils instrument is to calculate landslide using the inclination angle in borehole inclinometer measurement drilling at slip band Relative shift, for wriggling landslide monitoring positive effect;It is sharp that ground laser radar scanner is that profit is computerizedd control Optical radar is quickly scanned to slip mass entire surface, and scanning result and history scan data are contrasted, and calculates slip mass Deformation tendency;InSAR monitorings are to obtain slip mass influence figure using spaceborne or airborne Interference radar, and each of which pixel both included The radar raster-displaying strength information of ground resolution element, the phase information relevant with oblique distance is also included, areal will be covered The phase value of two width radar image respective pixels subtracts each other an available phase difference figure, and these phase signals can reflect place's earth's surface Deformation extent.
Inventor has found that prior art has following defect and deficiency during the present invention is realized:
1st, drawstring displacement monitor can not monitor the variation tendency of whole slip mass, if it is desired to monitoring whole slip mass change Trend causes great in constructing amount, it is necessary to lay multiple devices, and cost is high;
2nd, earth's surface GNSS monitors power consumption is larger, and cost is higher, and computing speed is slow, and is had a great influence by electromagnetism and environment, Have a strong impact on precision;
3rd, deep soils instrument does not possess drilling because it is in drilling for overwhelming majority landslide, Installation deep soils instrument needs to drill, and its workload and cost increase are many;
4th, its shortcoming of ground laser radar scanner is can not to filter out vegetation, the southeast and southwest ground for dense vegetation Area, its monitoring effect are bad.
The content of the invention
The technical problem to be solved in the present invention is to provide one kind landslide multi-point displacement intelligent monitoring device and monitoring method, energy Enough solve the deficiencies in the prior art, realize intelligentized control method, compact, easy for installation, simple to operate, precision is high, data can Depending on change, the monitoring to landslide entirety or local deformation trend can be achieved, send warning information in time.
In order to solve the above technical problems, the technical solution used in the present invention is as follows.
One kind landslide multi-point displacement intelligent monitoring device, including,
Intelligent control module, for IMAQ in the multi-point displacement monitoring modular that comes down, image recognition, gesture stability, swash Coordination, the data depth processing of each module of ligh-ranging, data storage show that data communication mode selection and power supply mode select;
Come down multi-point displacement monitoring modular, including image capture module, picture recognition module, gesture stability module and laser Range finder module, wherein image capture module are used for the view data for gathering landslide target monitoring point, and picture recognition module is used for will The image information of image capture module collection carries out target identification, and gesture stability module controls image to adopt according to image recognition result Collect module both horizontally and vertically, reach the purpose of the identification landslide each monitoring point of target monitoring point, laser ranging module will Each monitoring point of identification carries out range measurement;
Display module is stored, at by the result data for multi-point displacement monitoring modular collection of coming down through intelligent control module Store after reason and intuitively show;
Data communication module, including LoRa modules, NB-IOT modules, GPRS module and big dipper module, wherein LoRa modules Realize that short-middle-range networks and data transfer, GPRS communication modules and Beidou communication module are used to send out data with NB-IOT modules It is sent to distant early warning platform;
Power supply module, for being powered to intelligent control module and landslide multi-point displacement monitoring modular;
Come down target monitoring point, is the collection position of land slide data;
Distant early warning platform, for receiving gathered data and result.
A kind of monitoring method of above-mentioned landslide multi-point displacement intelligent monitoring device, comprises the following steps:
A, system electrification, equipment are initialized;The multi-point displacement monitoring modular that comes down clicks through line number to landslide target monitoring According to gathering and transferring data to intelligent control module, intelligent control module will be communicated after data progress advanced treating by data Module is sent to distant early warning platform, while treated data are stored and shown by storing display module;
B, intelligent control module control image capture module carries out image information collecting to landslide target monitoring point;
C, image information and characteristic target dot image information progress of the intelligent control module to the target monitoring point of collection With with identification;
D, the focal length of intelligent control module control adjustment image capture module and posture are so as to each landslide mesh to identification Mark monitoring point is relocated;
E, intelligent control module controls the laser ranging module measurement image for being in parallel axle center with image capture module to adopt Collect module to the distance of each landslide target monitoring point;
F, intelligent control module carries out validity processing to step E acquired results;
G, intelligent control module carries out data analysis to step F acquired results;
H, intelligent control module is sent to distant early warning platform to step G acquired results by data communication module, simultaneously Data storage and display are carried out by storing display module.
Preferably, in step B, image capture module carries out IMAQ to landslide target monitoring point, and image is believed Breath is converted into digital information.
Preferably, in step C, multiple monitoring points in the image of collection are identified including following picture recognition module Step:
C1, image preprocessing, the Color Bitmap of collection is subjected to gray processing processing,
I=0.299 × Red+0.587 × Green+0.114 × Blue
Wherein, I represents gray value, Red, Green, and Blue is the rgb value of each pixel;Suitable threshold value is set, it is real Existing image binaryzation, the gray value of all pixels in wicket centered on certain point (X, Y), is arranged by order from small to large Row, the gray value using median as (X, Y) place, so as to remove the noise introduced from actual environment;
C2, characteristics extraction, after C1 steps, the shape facility of monitoring point in image can be described with matrix, then monitoring point R (i, j) rank be
The point (x, y) that computing is participated in formula is all point or boundary point in the R of monitoring point;
C3, template matches, by multiple known template characteristic target dot matrix parameters and the monitoring point feature of C2 steps extraction Value carry out matching primitives obtain image in whether information and coordinate containing the template, represented with similarity D
After at its normalization, the coefficient correlation of template matches is obtained
When template and just the same identification target, coefficient R (i, j)=1.
Preferably, in step E, the laser ranging module for being in parallel axle center with image capture module is controlled to measure image Acquisition module to identification landslide target monitoring point distance, duplicate measurements n times, 1 < n≤100.
Preferably, in step F, processing is filtered to n range data of step E collections, rejecting abnormalities value, retained Average value, B-F steps are repeated, until simultaneously filtering process is completed in the landslide target monitoring point ranging of identification.
Preferably, in step G, the range data of gained landslide target monitoring point in F-step is stored with System History Corresponding point data be compared analysis, the change in displacement trend and overall landslide for calculating each monitoring point change X-Y scheme.
It is using beneficial effect caused by above-mentioned technical proposal:The present invention can realize intelligentized control method, small volume Ingeniously, it is easy for installation, simple to operate, precision is high, data visualization, can be achieved to landslide entirety or local deformation trend monitoring, Send warning information in time.
Brief description of the drawings
Fig. 1 is the hardware structure diagram of an embodiment of the invention.
Fig. 2 is the monitoring method schematic diagram of an embodiment of the invention.
Fig. 3 is the monitoring device installation diagram of an embodiment of the invention.
Embodiment
Reference picture 1-3, an embodiment of the invention include,
Intelligent control module 1, for IMAQ in the multi-point displacement monitoring modular 2 that comes down, image recognition, gesture stability, Coordination, the data depth processing of each module of laser ranging, data storage show that data communication mode selection and power supply mode are selected Select;
Come down multi-point displacement monitoring modular 2, including image capture module, picture recognition module, gesture stability module and swashs Ligh-ranging module, wherein image capture module are used for the view data for gathering landslide target monitoring point 6, and picture recognition module is used for The image information of image capture module collection is subjected to target identification, gesture stability module controls image according to image recognition result Acquisition module both horizontally and vertically, reaches the purpose of 6 each monitoring point of identification landslide target monitoring point, laser ranging module Each monitoring point of identification is subjected to range measurement;
Display module 3 is stored, for the result data that gathers of multi-point displacement monitoring modular 2 that will come down through intelligent control module Store after 1 processing and intuitively show;
Data communication module 4, including LoRa modules, NB-IOT modules, GPRS module and big dipper module, wherein LoRa modules Realize that short-middle-range networks and data transfer, GPRS communication modules and Beidou communication module are used to send out data with NB-IOT modules It is sent to distant early warning platform 7;
Power supply module 5, for being powered to intelligent control module 1 and landslide multi-point displacement monitoring modular 2;
Come down target monitoring point 6, is the collection position of land slide data;
Distant early warning platform 7, for receiving gathered data and result.
A kind of monitoring method of above-mentioned landslide multi-point displacement intelligent monitoring device, comprises the following steps:
A, system electrification, equipment are initialized;Landslide multi-point displacement monitoring modular 2 is carried out to landslide target monitoring point 6 Data acquisition simultaneously transfers data to intelligent control module 1, and intelligent control module 1 passes through data after data are carried out into advanced treating Communication module 4 is sent to distant early warning platform, while treated data are stored and shown by storing display module 3 Show;
B, intelligent control module 1 controls image capture module to carry out image information collecting to landslide target monitoring point 6;
C, image information and characteristic target dot image information progress of the intelligent control module 1 to the target monitoring point of collection With with identification;
D, the focal length of the control of intelligent control module 1 adjustment image capture module and posture are so as to each landslide mesh to identification Mark monitoring point 6 is relocated;
E, intelligent control module 1 controls the laser ranging module measurement image for being in parallel axle center with image capture module to adopt Collect module to the distance of each landslide target monitoring point 6;
F, intelligent control module 1 carries out validity processing to step E acquired results;
G, intelligent control module 1 carries out data analysis to step F acquired results;
H, intelligent control module 1 is sent to distant early warning platform 7 to step G acquired results by data communication module 4, together When by storing display module 3 carry out data storage and display.
In step B, image capture module carries out IMAQ to landslide target monitoring point 6, and converts image information into Digital information.
In step C, multiple monitoring points in the image of collection are identified picture recognition module comprises the following steps:
C1, image preprocessing, the Color Bitmap of collection is subjected to gray processing processing,
I=0.299 × Red+0.587 × Green+0.114 × Blue
Wherein, I represents gray value, Red, Green, and Blue is the rgb value of each pixel;Suitable threshold value is set, it is real Existing image binaryzation, the gray value of all pixels in wicket centered on certain point (X, Y), is arranged by order from small to large Row, the gray value using median as (X, Y) place, so as to remove the noise introduced from actual environment;
C2, characteristics extraction, after C1 steps, the shape facility of monitoring point in image can be described with matrix, then monitoring point R (i, j) rank be
The point (x, y) that computing is participated in formula is all point or boundary point in the R of monitoring point;
C3, template matches, by multiple known template characteristic target dot matrix parameters and the monitoring point feature of C2 steps extraction Value carry out matching primitives obtain image in whether information and coordinate containing the template, represented with similarity D
After at its normalization, the coefficient correlation of template matches is obtained
When template and just the same identification target, coefficient R (i, j)=1.
In step D, the focal length of image capture module, the image of landslide target monitoring point 6 after amplification identification are adjusted, and adjust Gesture stability module, the image of landslide target monitoring point 6 after identification is set to be among the image capture module visual field.
In step E, the laser ranging module for being in parallel axle center with image capture module is controlled to measure image capture module To the distance of the landslide target monitoring point 6 of identification, duplicate measurements n times, 1 < n≤100.
In step F, processing is filtered to n range data of step E collections, rejecting abnormalities value, retains average value, weight Multiple B-F steps, until simultaneously filtering process is completed in landslide target monitoring point (6) ranging of identification;
The exceptional value of rejecting is stored in buffer area, exceptional value is compared with average value, comparison result is fitted Afterwards, the laser ranging module in step E is modified using fitting result.
In step G, by the range data and the corresponding points of System History storage of gained landslide target monitoring point 6 in F-step Data are compared analysis, and the change in displacement trend and overall landslide for calculating each monitoring point change X-Y scheme;
When resolving overall landslide change X-Y scheme, made according to the displacement data for resolving two closest monitoring points of point To resolve object, the displacement datas of two monitoring points is weighted average, obtains calculation result, weight coefficient with resolve point and Corresponding monitoring point distance it is square directly proportional.
In the description of the invention, it is to be understood that term " longitudinal direction ", " transverse direction ", " on ", " under ", "front", "rear", The orientation or position relationship of the instruction such as "left", "right", " vertical ", " level ", " top ", " bottom ", " interior ", " outer " is based on accompanying drawing institutes The orientation or position relationship shown, the description present invention is for only for ease of, rather than the device or element of instruction or hint meaning must There must be specific orientation, with specific azimuth configuration and operation, therefore be not considered as limiting the invention.
The general principle and principal character and advantages of the present invention of the present invention has been shown and described above.The technology of the industry Personnel are it should be appreciated that the present invention is not limited to the above embodiments, and the simply explanation described in above-described embodiment and specification is originally The principle of invention, without departing from the spirit and scope of the present invention, various changes and modifications of the present invention are possible, these changes Change and improvement all fall within the protetion scope of the claimed invention.The claimed scope of the invention by appended claims and its Equivalent thereof.

Claims (8)

1. one kind landslide multi-point displacement intelligent monitoring device, it is characterised in that:Including,
Intelligent control module (1), for the interior IMAQ of multi-point displacement monitoring modular (2) that comes down, image recognition, gesture stability, Coordination, the data depth processing of each module of laser ranging, data storage show that data communication mode selection and power supply mode are selected Select;
Come down multi-point displacement monitoring modular (2), including image capture module, picture recognition module, gesture stability module and laser Range finder module, wherein image capture module are used for the view data for gathering landslide target monitoring point (6), and picture recognition module is used for The image information of image capture module collection is subjected to target identification, gesture stability module controls image according to image recognition result Acquisition module both horizontally and vertically, reaches the purpose of each monitoring point of identification landslide target monitoring point (6), laser ranging mould Each monitoring point of identification is carried out range measurement by block;
Display module (3) is stored, the result data for multi-point displacement monitoring modular (2) collection that will come down is through intelligent control module (1) store after handling and intuitively show;
Data communication module (4), including LoRa modules, NB-IOT modules, GPRS module and big dipper module, wherein LoRa modules and NB-IOT modules realize that short-middle-range networks and data transfer, GPRS communication modules and Beidou communication module are used to send data To distant early warning platform (7);
Power supply module (5), for being powered to intelligent control module (1) and landslide multi-point displacement monitoring modular (2);
Come down target monitoring point (6), is the collection position of land slide data;
Distant early warning platform (7), for receiving gathered data and result.
2. described in a kind of claim 1 landslide multi-point displacement intelligent monitoring device monitoring method, it is characterised in that including with Lower step:
A, system electrification, equipment are initialized;The multi-point displacement monitoring modular (2) that comes down is carried out to landslide target monitoring point (6) Data acquisition simultaneously transfers data to intelligent control module (1), and intelligent control module (1) passes through after data are carried out into advanced treating Data communication module (4) is sent to distant early warning platform, while treated data are deposited by storing display module (3) Storage and display;
B, intelligent control module (1) control image capture module carries out image information collecting to landslide target monitoring point (6);
C, intelligent control module (1) matches to the image information of the target monitoring point of collection with characteristic target dot image information With identification;
D, the focal length of intelligent control module (1) control adjustment image capture module and posture are so as to each landslide target to identification Monitoring point (6) is relocated;
E, intelligent control module (1) control is in the laser ranging module measurement IMAQ in parallel axle center with image capture module Distance of the module to each landslide target monitoring point (6);
F, intelligent control module (1) carries out validity processing to step E acquired results;
G, intelligent control module (1) carries out data analysis to step F acquired results;
H, intelligent control module (1) is sent to distant early warning platform (7) to step G acquired results by data communication module (4), Simultaneously data storage and display are carried out by storing display module (3).
3. the monitoring method of landslide multi-point displacement intelligent monitoring device according to claim 2, it is characterised in that:Step B In, image capture module carries out IMAQ to landslide target monitoring point (6), and converts image information into digital information.
4. the monitoring method of landslide multi-point displacement intelligent monitoring device according to claim 2, it is characterised in that:Step C In, multiple monitoring points in the image of collection are identified picture recognition module comprises the following steps:
C1, image preprocessing, the Color Bitmap of collection is subjected to gray processing processing,
I=0.299 × Red+0.587 × Green+0.114 × Blue
Wherein, I represents gray value, Red, Green, and Blue is the rgb value of each pixel;Suitable threshold value is set, realizes figure As binaryzation, the gray value of all pixels in wicket centered on certain point (X, Y), arranged by order from small to large, Gray value using median as (X, Y) place, so as to remove the noise introduced from actual environment;
C2, characteristics extraction, after C1 steps, the shape facility of monitoring point in image can be described with matrix, then monitoring point R (i, j) rank is
<mrow> <msub> <mi>M</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msub> <mo>=</mo> <munder> <mo>&amp;Sigma;</mo> <mrow> <mi>x</mi> <mo>&amp;Subset;</mo> <mi>R</mi> </mrow> </munder> <munder> <mo>&amp;Sigma;</mo> <mrow> <mi>y</mi> <mo>&amp;Subset;</mo> <mi>R</mi> </mrow> </munder> <msup> <mi>x</mi> <mi>i</mi> </msup> <msup> <mi>y</mi> <mi>j</mi> </msup> </mrow>
The point (x, y) that computing is participated in formula is all point or boundary point in the R of monitoring point;
C3, template matches, the monitoring point characteristic value that multiple known template characteristic target dot matrix parameters are extracted with C2 steps is entered Row matching primitives obtain image in whether information and coordinate containing the template, represented with similarity D
<mrow> <mi>D</mi> <mrow> <mo>(</mo> <mi>i</mi> <mo>,</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>=</mo> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>m</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>M</mi> </munderover> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>n</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>N</mi> </munderover> <msup> <mrow> <mo>&amp;lsqb;</mo> <msup> <mi>S</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msup> <mrow> <mo>(</mo> <mi>m</mi> <mo>,</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>-</mo> <mi>T</mi> <mrow> <mo>(</mo> <mi>m</mi> <mo>,</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>&amp;rsqb;</mo> </mrow> <mn>2</mn> </msup> </mrow>
After at its normalization, the coefficient correlation of template matches is obtained
<mrow> <mi>R</mi> <mrow> <mo>(</mo> <mi>i</mi> <mo>,</mo> <mi>j</mi> <mo>)</mo> </mrow> <mo>=</mo> <mfrac> <mrow> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>m</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>M</mi> </munderover> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>n</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>N</mi> </munderover> <msup> <mi>S</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msup> <mrow> <mo>(</mo> <mi>m</mi> <mo>,</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>&amp;times;</mo> <mi>T</mi> <mrow> <mo>(</mo> <mi>m</mi> <mo>,</mo> <mi>n</mi> <mo>)</mo> </mrow> </mrow> <mrow> <msqrt> <mrow> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>m</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>M</mi> </munderover> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>n</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>N</mi> </munderover> <msup> <mrow> <mo>&amp;lsqb;</mo> <msup> <mi>S</mi> <mrow> <mi>i</mi> <mi>j</mi> </mrow> </msup> <mrow> <mo>(</mo> <mi>m</mi> <mo>,</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>&amp;rsqb;</mo> </mrow> <mn>2</mn> </msup> </mrow> </msqrt> <msqrt> <mrow> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>m</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>M</mi> </munderover> <munderover> <mo>&amp;Sigma;</mo> <mrow> <mi>n</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>N</mi> </munderover> <msup> <mrow> <mo>&amp;lsqb;</mo> <mi>T</mi> <mrow> <mo>(</mo> <mi>m</mi> <mo>,</mo> <mi>n</mi> <mo>)</mo> </mrow> <mo>&amp;rsqb;</mo> </mrow> <mn>2</mn> </msup> </mrow> </msqrt> </mrow> </mfrac> </mrow>
When template and just the same identification target, coefficient R (i, j)=1.
5. the monitoring method of landslide multi-point displacement intelligent monitoring device according to claim 2, it is characterised in that:Step D In, the focal length of image capture module is adjusted, amplifies landslide target monitoring point (6) image after identification, and adjust gesture stability mould Block, landslide target monitoring point (6) image after identification is set to be among the image capture module visual field.
6. the monitoring method of landslide multi-point displacement monitoring device according to claim 2, it is characterised in that:In step E, control Make and be in the laser ranging module measurement image capture module in parallel axle center to the landslide target prison of identification with image capture module The distance of measuring point (6), duplicate measurements n times, 1 < n≤100.
7. the monitoring method of landslide multi-point displacement monitoring device according to claim 2, it is characterised in that:It is right in step F N range data of step E collections is filtered processing, rejecting abnormalities value, retains average value, repeats B-F steps, until identification Landslide target monitoring point (6) ranging complete and filtering process.
8. the monitoring method of landslide multi-point displacement monitoring device according to claim 2, it is characterised in that:, will in step G The range data of gained landslide target monitoring point (6) is analyzed compared with the corresponding point data that System History stores in F-step, The change in displacement trend and overall landslide for calculating each monitoring point change X-Y scheme.
CN201711239416.9A 2017-11-30 2017-11-30 One kind landslide multi-point displacement intelligent monitoring device and monitoring method Pending CN107764192A (en)

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CN108416985A (en) * 2018-04-20 2018-08-17 北京航天控制仪器研究所 A kind of Geological Hazards Monitoring early warning system and method for early warning based on image recognition
CN108765557B (en) * 2018-05-29 2022-05-03 桂林电子科技大学 BDS-based geometric method for three-dimensional reconstruction of landslide
CN108765557A (en) * 2018-05-29 2018-11-06 桂林电子科技大学 A kind of method of geometry of the landslide three-dimensional reconstruction based on BDS
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CN112113482A (en) * 2020-09-01 2020-12-22 深圳市瑞芬科技有限公司 Geological landslide monitoring sensor based on NB-IOT network and use method thereof
CN112508861A (en) * 2020-11-19 2021-03-16 安徽理工大学 Coal mining subsidence early warning system based on image processing
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CN112802307A (en) * 2020-12-30 2021-05-14 中国地质调查局成都地质调查中心 Geological monitoring and early warning method and system for geological exploration
CN113033091A (en) * 2021-03-24 2021-06-25 桂林电子科技大学 Landslide displacement prediction method
CN113251913A (en) * 2021-05-08 2021-08-13 中国长江三峡集团有限公司 Comprehensive monitoring method for surface deformation of bank side slope
CN116739183A (en) * 2023-08-02 2023-09-12 长春工程学院 Mine safety risk early warning prediction system
CN116739183B (en) * 2023-08-02 2023-10-20 长春工程学院 Mine safety risk early warning prediction system
CN117549330A (en) * 2024-01-11 2024-02-13 四川省铁路建设有限公司 Construction safety monitoring robot system and control method
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