CN109870105A - A kind of biscuit method and biscuit system - Google Patents
A kind of biscuit method and biscuit system Download PDFInfo
- Publication number
- CN109870105A CN109870105A CN201711268656.1A CN201711268656A CN109870105A CN 109870105 A CN109870105 A CN 109870105A CN 201711268656 A CN201711268656 A CN 201711268656A CN 109870105 A CN109870105 A CN 109870105A
- Authority
- CN
- China
- Prior art keywords
- biscuit
- material heap
- vision imaging
- track
- image
- 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.)
- Pending
Links
Landscapes
- Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)
Abstract
The invention discloses a kind of biscuit method and biscuit system, method includes: the vision imaging that S1. obtains material heap;S2. the threedimensional model of material heap is established according to the vision imaging;S3. the volume that material heap is calculated according to the threedimensional model, the material of preset vol is taken by biscuit device disk.With no measurement dead area, Neosinocalamus affinis can be accurately established, the advantages that biscuit precision is high, high degree of automation.
Description
Technical field
The present invention relates to sampling biscuit technical field more particularly to a kind of biscuit methods and biscuit system, are particularly suitable for
To the biscuit of coal charge in coal sample detection.
Background technique
Existing disk coal instrument is largely fixed on bucket wheel machine cantilever front end, needs to walk with bucket wheel machine, rotary disk coal;Also
A little disk coal instrument are fixed on disk coal on riding track, depend on cloud platform rotation disk coal.Disk coal mode mostly uses greatly laser scanner, using sharp
The principle measurement scanner of ligh-ranging is then convert into the 3 d space coordinate of target to the distance of target object.It is general fixed
On bucket wheel machine or on the holder in coal ceiling portion, coal yard scanning is realized in the movement dependent on bucket wheel machine or holder.Using this method
Disk coal is limited by the performance of scanner and installation site limits, the limited amount using point of laser scanning, and most of feelings
There can be the case where laser is blocked by dump under condition, measurement accuracy is not high.Wherein, there is blind area with bucket wheel machine revolution mobile disk coal,
There are blind areas for dump two sides, and rely on that bucket wheel machine sport efficiency is not high, and accuracy cannot be guaranteed;Being fixed on disk coal on riding track needs
Multiple laser scanners are used, need to install multiple probes, it is at high cost, and can equally be blocked by dump cannot be complete for laser
All risk insurance demonstrate,proves no blind area.
Summary of the invention
The technical problem to be solved in the present invention is that, for technical problem of the existing technology, the present invention provides one
Kind no measurement dead area can accurately establish Neosinocalamus affinis, and biscuit precision is high, the biscuit method of high degree of automation and biscuit system
System.
In order to solve the above technical problems, technical solution proposed by the present invention are as follows: a kind of biscuit method,
S1. the vision imaging of material heap is obtained;
S2. the threedimensional model of material heap is established according to the vision imaging;
S3. the volume that material heap is calculated according to the threedimensional model, the material of preset vol is taken by biscuit device disk.
Further, the specific steps of the step S1 include: to the material heap by vision imaging sensor according to pre-
If track is continuously taken pictures, the image photo to the material heap all standing is obtained, and the image photo is sent to image
Processing server;The degree of overlapping of adjacent two image photos is greater than preset threshold value.
Further, the preset track passes through the track being arranged in above material heap and is determined, the vision imaging passes
Sensor moves on the track, takes pictures to the material heap;The track is preferably " u "-shaped or " V " shape;
Or: the preset track determines that the vision imaging sensor setting exists according to the pre-set flight track of unmanned plane
On unmanned plane, take pictures to the material heap.
Further, at least one end of the track is provided with charging unit, in the vision imaging sensor in track
On when moving to charging unit position, can charge automatically.
Further, it in the step S2, is obtained by image processing server according to the image photo, is carried out at image
Reason, establishes the threedimensional model of material heap.
A kind of biscuit system, including vision imaging obtain module, modeling control module and biscuit device;The vision imaging
The vision imaging that module is used to obtain material heap is obtained, and vision imaging is supplied to modeling control module;
The modeling control module is used to establish the threedimensional model of material heap according to the vision imaging, according to the threedimensional model meter
The volume of material heap is calculated, and controls the material that biscuit device disk takes preset vol;
The biscuit device is used to carry out biscuit operation under the control of the modeling control module.
Further, it includes track, moving trolley and vision imaging sensor that the vision imaging, which obtains module,;
The moving trolley can move in orbit;The vision imaging sensor is arranged on the trolley, exists with trolley
It moves on track, is continuously taken pictures to material heap, obtain the image photo to the material heap all standing, and by the image photo
It is sent to modeling control module.
Further, the top of the material heap is arranged in the track, and the track is preferably " u "-shaped or " V " shape.
Further, it is provided with charging unit on the track, for being the moving trolley and the vision imaging
Sensor charging;The charging unit is at least one, is preferably provided at the end of the track.
Further, it includes unmanned plane and vision imaging sensor that the vision imaging, which obtains module,;The unmanned plane exists
Preset airline operation is pressed above the material heap, the vision imaging sensor is arranged on unmanned plane, carries out to material heap continuous
It takes pictures, obtains the image photo to the material heap all standing, and the image photo is sent to modeling control module.
Further, the degree of overlapping of adjacent two image photos be greater than preset threshold value, the threshold value be preferably greater than etc.
In 60%.
Compared with the prior art, the advantages of the present invention are as follows:
1, the present invention continuously take pictures to material heap by visual sensor obtains the vision imaging of material heap, and adjacent image shines
There is certain degree of overlapping between piece, can be without the truth of the embodiment material heap at dead angle, no measurement dead area, then pass through vision shadow
Picture is come the threedimensional model for constructing material heap, and model accuracy is high, to guarantee high-precision biscuit.
2, the present invention claps material heap on the track preset by computer controlled automatic vision imaging sensor
According to, and server is sent by image photo automatically, material heap is established according to image photo by the computing capability for servicing powerful
Threedimensional model, and the volume of material heap is calculated, then control biscuit device and carry out biscuit, high degree of automation.
3, the present invention establishes the threedimensional model of material heap by vision imaging photo, and modeling algorithm is mature, and modeling efficiency is high;
For vision imaging sensor relative to scanning laser sensor, cost is lower.
Detailed description of the invention
Fig. 1 is specific embodiment of the invention flow diagram.
Fig. 2 is specific embodiment of the invention structural schematic diagram.
Fig. 3 is specific embodiment of the invention trade shape schematic diagram.
Specific embodiment
Below in conjunction with Figure of description and specific preferred embodiment, the invention will be further described, but not therefore and
It limits the scope of the invention.
As shown in Figure 1, the biscuit method of the present embodiment, S1. obtains the vision imaging of material heap;S2. according to vision imaging
Establish the threedimensional model of material heap;S3. the volume that material heap is calculated according to threedimensional model, takes preset vol by biscuit device disk
Material.
In the present embodiment, the specific steps of step S1 include: to material heap by vision imaging sensor according to default rail
Mark is continuously taken pictures, and obtains the image photo to material heap all standing, and image photo is sent to image processing server;Phase
The degree of overlapping of adjacent two image photos is greater than preset threshold value.Preset track passes through the track institute being arranged in above material heap really
Fixed, vision imaging sensor moves in orbit, takes pictures to material heap;Track is preferably " u "-shaped or " V " shape;
Or: the preset track determines that the vision imaging sensor setting exists according to the pre-set flight track of unmanned plane
On unmanned plane, take pictures to the material heap.At least one end of track is provided with charging unit, in-orbit in vision imaging sensor
When moving to charging unit position on road, it can charge automatically.
In this example, in step s 2, it is obtained by image processing server according to image photo, carries out image procossing, build
The threedimensional model of vertical material heap.
As shown in Fig. 2, the biscuit system of the present embodiment, including vision imaging obtain module, modeling control module and biscuit
Device;Vision imaging obtains the vision imaging that module is used to obtain material heap, and vision imaging is supplied to modeling control module;It builds
Mould control module is used to establish the threedimensional model of material heap according to vision imaging, and the volume of material heap is calculated according to threedimensional model, and controls
Biscuit device disk processed takes the material of preset vol;Biscuit device is used to carry out biscuit operation under the control of modeling control module.
In the present embodiment, it includes track, moving trolley and vision imaging sensor that vision imaging, which obtains module,;Movement is small
Vehicle can move in orbit;Vision imaging sensor is arranged on trolley, moves with trolley, connects in orbit to material heap
It is continuous to take pictures, the image photo to material heap all standing is obtained, and image photo is sent to modeling control module.As shown in figure 3, rail
The top of material heap is arranged in road, and track is preferably " u "-shaped or " V " shape.It should be noted that with the actual size according to material heap, track
Can according to the actual situation by one or multiphase " u "-shaped or " V " shape structure composition, in Fig. 3, the shape of track by 3 " u "-shapeds or
" V " shape head and the tail are formed by connecting.It is provided with charging unit in orbit, for charging for moving trolley and vision imaging sensor;
Charging unit is at least one, is preferably provided at the end of track.The degree of overlapping of adjacent two image photos is greater than preset threshold
Value, threshold value are preferably greater than to be equal to 60%.Charging unit can setting track one end, can also respectively be set at the both ends of track
Set a charging unit.
In the present embodiment, it includes unmanned plane and vision imaging sensor that the vision imaging, which obtains module,;It is described nobody
Machine presses preset airline operation above the material heap, and the vision imaging sensor is arranged on unmanned plane, carries out to material heap
It continuously takes pictures, obtains the image photo to the material heap all standing, and the image photo is sent to modeling control module.?
Carrier of the unmanned plane as vision imaging sensor can be used, vision imaging sensor is carried above material heap by unmanned plane
Flight, takes pictures to material heap.
In the present embodiment, it is illustrated so that is once had carries out biscuit process to coal charge as an example.Track is arranged in material heap
Top is provided with moving trolley on track, vision imaging sensor (such as camera) is provided in moving trolley.In initial shape
State, moving trolley are parked in one end of track, which is provided with charging unit, and moving trolley and vision imaging sensor can be by filling
Electric installation charges.When starting disk coal, first start moving trolley, moving trolley is moved in orbit with vision imaging sensor
It is dynamic, the frequency of taking pictures of vision imaging sensor is set according to the movement speed of moving trolley, coal charge heap is carried out continuously and is taken pictures, and
And guarantee that the shooting area for two image photos being continuously shot has 60% or more degree of overlapping.It is in orbit by moving trolley
Movement, primary complete shooting is carried out to coal charge heap, obtains the complete image picture for covering entire coal charge heap, and will shooting
Obtained image photo is sent to modeling control module by wireless network, includes the location information of photo in image photo.
After completing shooting, moving trolley returns to initial position, is that moving trolley and vision imaging sensor charge by charging unit.
Modeling control module in the present embodiment is a server, is responsible for the movement of control moving trolley, vision imaging sensor
It takes pictures, and three-dimensional modeling is carried out according to image photo, generate the three-dimensional module of coal charge heap, and coal charge is calculated according to three-dimensional module
The volume of heap controls coal charge of the biscuit device from respective volume under coal charge heap mid-game further according to the biscuit amount pre-set.?
In the present embodiment, the modeling algorithm for generating threedimensional model by image photo is mature, and modeling efficiency is high.Meanwhile relative to laser
Scanning means is limited by scanning number of threads, can only scan the scan data for obtaining limited thread, image photo can be complete
Ground is truly reflected the case where coal charge heap, and the threedimensional model of foundation is more accurate.And this vision imaging sensor cost is lower,
Requirement to working environment is lower, also easily facilitates maintenance and management.
Above-mentioned only presently preferred embodiments of the present invention, is not intended to limit the present invention in any form.Although of the invention
It has been disclosed in a preferred embodiment above, however, it is not intended to limit the invention.Therefore, all without departing from technical solution of the present invention
Content, technical spirit any simple modifications, equivalents, and modifications made to the above embodiment, should all fall according to the present invention
In the range of technical solution of the present invention protection.
Claims (11)
1. a kind of biscuit method, it is characterised in that:
S1. the vision imaging of material heap is obtained;
S2. the threedimensional model of material heap is established according to the vision imaging;
S3. the volume that material heap is calculated according to the threedimensional model, the material of preset vol is taken by biscuit device disk.
2. biscuit method according to claim 1, it is characterised in that: the specific steps of the step S1 include: to pass through view
Feel that image sensor continuously takes pictures to the material heap according to desired guiding trajectory, obtains shining the image of the material heap all standing
Piece, and the image photo is sent to image processing server;The degree of overlapping of adjacent two image photos is greater than default
Threshold value.
3. biscuit method according to claim 2, it is characterised in that: the preset track is by being arranged above material heap
Track determined that the vision imaging sensor moves on the track, take pictures to the material heap;The track is excellent
It is selected as " u "-shaped or " V " shape;
Or: the preset track determines that the vision imaging sensor setting exists according to the pre-set flight track of unmanned plane
On unmanned plane, take pictures to the material heap.
4. biscuit method according to claim 3, it is characterised in that: at least one end of the track is provided with charging dress
It sets, when the vision imaging sensor moves to charging unit position in orbit, can charge automatically.
5. according to the described in any item biscuit methods of claim 2 to 4, it is characterised in that: in the step S2, by image
Reason server is obtained according to the image photo, is carried out image procossing, is established the threedimensional model of material heap.
6. a kind of biscuit system, it is characterised in that: obtain module, modeling control module and biscuit device including vision imaging;Institute
It states vision imaging and obtains the vision imaging that module is used to obtain material heap, and vision imaging is supplied to modeling control module;
The modeling control module is used to establish the threedimensional model of material heap according to the vision imaging, according to the threedimensional model meter
The volume of material heap is calculated, and controls the material that biscuit device disk takes preset vol;
The biscuit device is used to carry out biscuit operation under the control of the modeling control module.
7. biscuit system according to claim 6, it is characterised in that: the vision imaging obtains module and includes track, moves
Dynamic trolley and vision imaging sensor;
The moving trolley can move in orbit;The vision imaging sensor is arranged on the trolley, exists with trolley
It moves on track, is continuously taken pictures to material heap, obtain the image photo to the material heap all standing, and by the image photo
It is sent to modeling control module.
8. biscuit system according to claim 7, it is characterised in that: the top of the material heap is arranged in the track, described
Track is preferably " u "-shaped or " V " shape.
9. biscuit system according to claim 8, it is characterised in that: be provided with charging unit on the track, be used for
It charges for the moving trolley and the vision imaging sensor;The charging unit is at least one, is preferably provided at described
The end of track.
10. biscuit system according to claim 6, it is characterised in that: the vision imaging obtain module include unmanned plane and
Vision imaging sensor;The unmanned plane presses preset airline operation above the material heap, and the vision imaging sensor is set
It sets on unmanned plane, is continuously taken pictures to material heap, obtain the image photo to the material heap all standing, and the image is shone
Piece is sent to modeling control module.
11. according to the described in any item biscuit systems of claim 7 to 10, it is characterised in that: the weight of adjacent two image photos
Folded degree is greater than preset threshold value, and the threshold value is preferably greater than to be equal to 60%.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201711268656.1A CN109870105A (en) | 2017-12-05 | 2017-12-05 | A kind of biscuit method and biscuit system |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201711268656.1A CN109870105A (en) | 2017-12-05 | 2017-12-05 | A kind of biscuit method and biscuit system |
Publications (1)
Publication Number | Publication Date |
---|---|
CN109870105A true CN109870105A (en) | 2019-06-11 |
Family
ID=66916449
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201711268656.1A Pending CN109870105A (en) | 2017-12-05 | 2017-12-05 | A kind of biscuit method and biscuit system |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN109870105A (en) |
Citations (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5480354A (en) * | 1994-11-03 | 1996-01-02 | Loral Corporation | Smart crop yield monitor |
CN103090791A (en) * | 2013-01-08 | 2013-05-08 | 中联重科股份有限公司 | Measuring system, method and device for bulk materials and material piling and taking control system |
CN202988295U (en) * | 2012-11-12 | 2013-06-12 | 中联重科物料输送设备有限公司 | Material pile detecting device and material yard |
CN203177804U (en) * | 2013-03-22 | 2013-09-04 | 中国计量学院 | Information acquisition support mechanism carrying out coal estimating by employing mesh surface structured light |
CN104006743A (en) * | 2014-05-30 | 2014-08-27 | 朱云佳 | Piled stock measurement system and method based on digital photo three-dimensional reconstructed stock pile model |
CN104154861A (en) * | 2014-03-10 | 2014-11-19 | 上海大学 | Circling measurement device and method for volume of large stacked material |
CN104880149A (en) * | 2014-02-28 | 2015-09-02 | 江苏永钢集团有限公司 | Large-size bulk material pile volume measurement method based on stereo image analysis, and equipment thereof |
CN105352438A (en) * | 2015-11-18 | 2016-02-24 | 长沙开元仪器股份有限公司 | Coal inventory system and data collection apparatus |
CN106296816A (en) * | 2016-08-01 | 2017-01-04 | 清华大学深圳研究生院 | Unmanned plane determining method of path and device for reconstructing three-dimensional model |
CN106528592A (en) * | 2016-09-21 | 2017-03-22 | 塞壬智能科技(北京)有限公司 | Mine field inventory method and system |
-
2017
- 2017-12-05 CN CN201711268656.1A patent/CN109870105A/en active Pending
Patent Citations (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5480354A (en) * | 1994-11-03 | 1996-01-02 | Loral Corporation | Smart crop yield monitor |
CN202988295U (en) * | 2012-11-12 | 2013-06-12 | 中联重科物料输送设备有限公司 | Material pile detecting device and material yard |
CN103090791A (en) * | 2013-01-08 | 2013-05-08 | 中联重科股份有限公司 | Measuring system, method and device for bulk materials and material piling and taking control system |
CN203177804U (en) * | 2013-03-22 | 2013-09-04 | 中国计量学院 | Information acquisition support mechanism carrying out coal estimating by employing mesh surface structured light |
CN104880149A (en) * | 2014-02-28 | 2015-09-02 | 江苏永钢集团有限公司 | Large-size bulk material pile volume measurement method based on stereo image analysis, and equipment thereof |
CN104154861A (en) * | 2014-03-10 | 2014-11-19 | 上海大学 | Circling measurement device and method for volume of large stacked material |
CN104006743A (en) * | 2014-05-30 | 2014-08-27 | 朱云佳 | Piled stock measurement system and method based on digital photo three-dimensional reconstructed stock pile model |
CN105352438A (en) * | 2015-11-18 | 2016-02-24 | 长沙开元仪器股份有限公司 | Coal inventory system and data collection apparatus |
CN106296816A (en) * | 2016-08-01 | 2017-01-04 | 清华大学深圳研究生院 | Unmanned plane determining method of path and device for reconstructing three-dimensional model |
CN106528592A (en) * | 2016-09-21 | 2017-03-22 | 塞壬智能科技(北京)有限公司 | Mine field inventory method and system |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN106225678B (en) | Dynamic object positioning based on 3D cameras and volume measuring method | |
CN107514993B (en) | The collecting method and system towards single building modeling based on unmanned plane | |
Khan et al. | Unmanned aerial vehicle–based traffic analysis: Methodological framework for automated multivehicle trajectory extraction | |
CN100486476C (en) | Method and system for automatic generating shoe sole photopolymer coating track based on linear structure optical sensor | |
CN103913116B (en) | Large-scale stacking material volume both sides parallel measuring device and method | |
CN110780305A (en) | Track cone bucket detection and target point tracking method based on multi-line laser radar | |
CN103941748A (en) | Autonomous navigation method and system and map modeling method and system | |
CN203580743U (en) | Vehicle-mounted tunnel measurement system | |
CN104154861A (en) | Circling measurement device and method for volume of large stacked material | |
CN107943064A (en) | A kind of unmanned plane spot hover system and method | |
CN102564335A (en) | Method for measuring deformation of large-scale tunnel | |
CN109282808A (en) | Unmanned plane and Multi-sensor Fusion localization method for the detection of bridge Cut-fill | |
CN105136058A (en) | On-line calibrating device of laser sensing three-dimensional measure system, and calibrating method thereof | |
CN105045276A (en) | Method and apparatus for controlling flight of unmanned plane | |
CN101858730A (en) | Automatic coal pile volume measurement method and special device | |
CN110880202B (en) | Three-dimensional terrain model creating method, device, equipment and storage medium | |
CN111323789A (en) | Ground topography scanning device and method based on unmanned aerial vehicle and solid-state radar | |
CN104570764A (en) | Verification platform for airborne target indicating system | |
CN102155913A (en) | Method and device for automatically measuring coal pile volume based on image and laser | |
CN116050277A (en) | Underground coal mine scene reality capturing sensing and simulating method and equipment | |
Minghui et al. | Deep learning enabled localization for UAV autolanding | |
CN111666876A (en) | Method and device for detecting obstacle, electronic equipment and road side equipment | |
CN111189449B (en) | Robot map construction method | |
CN114113118A (en) | Rapid detection device and detection method for water leakage disease of subway tunnel lining cracks | |
CN110926417B (en) | Vehicle-mounted railway tunnel detection system based on machine vision |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
RJ01 | Rejection of invention patent application after publication |
Application publication date: 20190611 |
|
RJ01 | Rejection of invention patent application after publication |