CN108518221A - A kind of automation coal mining system and method based on various dimensions positioning and deep learning - Google Patents
A kind of automation coal mining system and method based on various dimensions positioning and deep learning Download PDFInfo
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- CN108518221A CN108518221A CN201810441497.9A CN201810441497A CN108518221A CN 108518221 A CN108518221 A CN 108518221A CN 201810441497 A CN201810441497 A CN 201810441497A CN 108518221 A CN108518221 A CN 108518221A
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- 239000003245 coal Substances 0.000 title claims abstract description 67
- 238000005065 mining Methods 0.000 title claims abstract description 33
- 238000013135 deep learning Methods 0.000 title claims abstract description 24
- 238000000034 method Methods 0.000 title claims description 17
- 230000005540 biological transmission Effects 0.000 claims abstract description 4
- NJPPVKZQTLUDBO-UHFFFAOYSA-N novaluron Chemical compound C1=C(Cl)C(OC(F)(F)C(OC(F)(F)F)F)=CC=C1NC(=O)NC(=O)C1=C(F)C=CC=C1F NJPPVKZQTLUDBO-UHFFFAOYSA-N 0.000 claims description 16
- 238000005520 cutting process Methods 0.000 claims description 8
- 238000012544 monitoring process Methods 0.000 claims description 8
- 238000013136 deep learning model Methods 0.000 claims description 7
- 238000009434 installation Methods 0.000 claims description 7
- 238000000605 extraction Methods 0.000 claims description 4
- 230000002269 spontaneous effect Effects 0.000 claims description 3
- 239000007788 liquid Substances 0.000 claims description 2
- 210000005036 nerve Anatomy 0.000 claims 1
- 238000010586 diagram Methods 0.000 description 4
- 238000009826 distribution Methods 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 238000005259 measurement Methods 0.000 description 2
- 210000002569 neuron Anatomy 0.000 description 2
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 description 1
- 230000006399 behavior Effects 0.000 description 1
- 229910052799 carbon Inorganic materials 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
Classifications
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- E—FIXED CONSTRUCTIONS
- E21—EARTH OR ROCK DRILLING; MINING
- E21C—MINING OR QUARRYING
- E21C35/00—Details of, or accessories for, machines for slitting or completely freeing the mineral from the seam, not provided for in groups E21C25/00 - E21C33/00, E21C37/00 or E21C39/00
- E21C35/24—Remote control specially adapted for machines for slitting or completely freeing the mineral
-
- E—FIXED CONSTRUCTIONS
- E21—EARTH OR ROCK DRILLING; MINING
- E21D—SHAFTS; TUNNELS; GALLERIES; LARGE UNDERGROUND CHAMBERS
- E21D23/00—Mine roof supports for step- by- step movement, e.g. in combination with provisions for shifting of conveyors, mining machines, or guides therefor
- E21D23/12—Control, e.g. using remote control
-
- E—FIXED CONSTRUCTIONS
- E21—EARTH OR ROCK DRILLING; MINING
- E21F—SAFETY DEVICES, TRANSPORT, FILLING-UP, RESCUE, VENTILATION, OR DRAINING IN OR OF MINES OR TUNNELS
- E21F17/00—Methods or devices for use in mines or tunnels, not covered elsewhere
- E21F17/18—Special adaptations of signalling or alarm devices
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
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- Engineering & Computer Science (AREA)
- Mining & Mineral Resources (AREA)
- Life Sciences & Earth Sciences (AREA)
- General Life Sciences & Earth Sciences (AREA)
- Geochemistry & Mineralogy (AREA)
- Geology (AREA)
- Mechanical Engineering (AREA)
- Length Measuring Devices By Optical Means (AREA)
Abstract
A kind of automation coal mining system based on various dimensions positioning and deep learning, including system host (1) are formed with several Monitor Sub-Station of Less (2)；Monitor Sub-Station of Less is arranged in below each set cap (3) and above bracket base (4)；Each Monitor Sub-Station of Less (2) includes double-shaft tilt angle sensor (5) and laser orientation system (6)；Between system host (1) and Monitor Sub-Station of Less (2) or Monitor Sub-Station of Less (2) realizes data transmission by wirelessly or non-wirelessly mode between each other.The present invention can realize that working face automation is mined.
Description
Technical field
The present invention relates to it is a kind of based on various dimensions positioning and deep learning automation coal mining system and method.
Background technology
Production efficiency and the rate of extraction can be improved in fully-mechanized mining, ensures safety in production, improves utilization rate of equipment and installations and coal
Carbon yield and reduction equipment failure rate, or even can further cancel the work posts such as coalcutter driver and timberer, all other behaviour
Make and control is all completed on crossheading console.On this basis, automatically working face is also gradually emerged in large numbers.But domestic institute at present
" the automatically working face " of meaning, is mostly the automation using electrohydraulic control system as core, i.e., working face uses electrohydraulic control system
Holder try to stop people from fighting each other with machine, pushing and sliding, receives face guard, but coalcutter still uses manual operation coal cutting, but passes through electrichydraulic control system
That there is also precision is not high enough for system operation holder, and working face is not straight enough, it is still necessary to which worker frequently adjusts the drawbacks such as frame.
Invention content
In order to solve the automation issues of comprehensive mechanization working face, the present invention provides one kind to be positioned based on various dimensions
And the automation coal mining system and method for deep learning.
The technical solution adopted by the present invention is：
A kind of automation coal mining system based on various dimensions positioning and deep learning, including system host and several prisons
Survey substation composition；Monitor Sub-Station of Less is arranged in below each set cap and above bracket base；Each Monitor Sub-Station of Less includes
Double-shaft tilt angle sensor and laser orientation system；Between system host and Monitor Sub-Station of Less or Monitor Sub-Station of Less passes through nothing between each other
Line or wired mode realize data transmission；The double-shaft tilt angle sensor is located in Monitor Sub-Station of Less, to obtain working face coal seam
The pitching rake angle variation characteristic and advance of the face direction top of support of the angular distribution feature and monitoring coal seam of inclined direction
The inclination angle of beam and bracket base calculates obtain the bowing of each holder, looking up position state accordingly；The laser orientation system is located at
In Monitor Sub-Station of Less, including two or more laser emission elements and a laser pick-off unit, the same monitoring point
It is spaced apart between the laser emission element stood.
A kind of automation coal-mining method based on various dimensions positioning and deep learning, is positioned using above-mentioned based on various dimensions
And the automation coal mining system of deep learning is controlled, and is included the following steps：
(a) the positioning criterion of laser orientation system is established；
(b) using the Monitor Sub-Station of Less position coordinates above first bracket base of working face lower end as origin, first is determined
Monitor Sub-Station of Less position coordinates below a set cap determine the then using Monitor Sub-Station of Less below first set cap as basic point
Monitor Sub-Station of Less position coordinates above two bracket bases, until determining position at each Monitor Sub-Station of Less of working face all hydraulic holder
The relative coordinate set；
(c) by system host by each hydraulic support top beam and pedestal Monitor Sub-Station of Less position coordinates and double-shaft tilt angle data
It is handled, is obtained using Monitor Sub-Station of Less position above first bracket base as coordinate origin, including entire working face hydraulic pressure branch
Bowing on frame top beam, the inclination angle and direction of propulsion of the relative coordinate of position base and bracket base and top beam in an inclined direction
Dip angle, at the same show on system host screen working surface hydraulic support on alter or glide and advanced or lag feelings
Condition；
(d) according to the thickness a of hydraulic support Monitor Sub-Station of Less installation site top beam, the thickness b of pedestal, top beam and pedestal edge
The inclination angle theta 1 and θ 2 in advance of the face direction, it is h=a+ that corresponding coal seam thickness or mining height at corresponding hydraulic support, which is calculated,
B+ (z1-z2) tan (θ 1- θ 2), wherein two Monitor Sub-Station of Less are respectively z1, z2 along the coordinate in the i.e. mining height direction of Z axis is adopted；
(e) it is basic point to be based on first hydraulic support foundation Monitor Sub-Station of Less installation site, by double-shaft tilt angle sensor and
Laser orientation system, which measures, obtains the top beam of working face all hydraulic holder, the position coordinates of pedestal and across pitch and tendency
Angle, including the supporting height of each holder and front coal seam thickness further calculate and obtain coal body top bottom in front of each holder
The multidimensional coordinate system (x, y, z, φ, θ) of plate detail parameters, wherein x, y, z are using first bracket base as the work of basic point
The spatial triaxial coordinate of face roof or bottom plate, φ and θ are respectively the tendency and angle of strike of roof or bottom plate；
(f) during working face extraction, deep learning model is established by system host, the input layer in model with
The x, y, z of top plate and bottom plate in front of each hydraulic support, φ, θ parameters are input pointer, and output layer is to wait adopting not in front of coal wall
Know the coal seam fold form in region, including three-dimensional coordinate, coal seam thickness, roof and floor angle of inclination and pitching rake angle, hidden layer
Neuron number determines according to actual needs；
(g) index for exporting deep learning model, including coal seam each position prediction roof and floor three-dimensional coordinate, coal
Layer thickness, roof and floor angle of inclination and pitching rake angle are transferred to coalcutter, guide coalcutter coal cutting roller with coal seam fold shape
The variation of state adjusts in real time, realizes that automation coal cutting, simultaneity factor host are monitored working face various dimensions parameter, including
It alters or glides on hydraulic support, advanced or lag, bow or come back, by sending instructions to electrohydraulic control system to hydraulic pressure
Holder is adjusted.
The positioning criterion of above-mentioned laser orientation system is：In plane XY coordinate systems, a laser orientation system is determined
Distance is d between interior two laser emission elements A and B, and coordinate is respectively A (0,0) and B (d, 0), each spontaneous emission laser beam
Angle with line between 2 points of A, B is respectively α, β, then the space of another laser orientation system (6) interior laser pick-off unit
Relative coordinate is that C (xc, yc) is CDetermine that some hydraulic support top beam (or pedestal) is supervised
The position coordinates at substation are surveyed, the opposite position of adjacent hydraulic support foundation (or top beam) is then measured by laser orientation system
Set coordinate；If above-mentioned coordinate system is adjusted to three-dimensional XYZ coordinate system by plane XY coordinate systems, position equally applicable.
The above-mentioned technical proposal of the present invention has the advantages that compared with the prior art：
(1) automation coal mining system and method provided by the invention based on various dimensions positioning and deep learning, due to making
It is realized to coal cutting height and set cap, pedestal coordinate and position state with double-shaft sensor and laser precise positioning measurement
Precisely monitoring, therefore, the present invention can realize that working surface hydraulic support alters or glided in appearance, advanced or lag, bows and face upward
It is adjusted in time when head undesirable condition.
(2) automation coal mining system and method provided by the invention based on various dimensions positioning and deep learning, due to energy
The enough accurate measurement to Seam Roof And Floor position coordinates and bearing and tendency angle shows the complete fold of coal wall
Form and accurate position coordinates, therefore, the present invention can realize that coal mining machine roller rises and falls and thickness change adjust automatically with coal seam
Highly.
(3) automation coal mining system and method provided by the invention based on various dimensions positioning and deep learning, due to building
It has found deep learning model, and with the three-dimensional coordinate of roof in front of each hydraulic support of actual monitoring and bottom plate and has walked
To being input pointer with tendency angle, in front of the coal wall in the form of the coal seam fold of zone of ignorance, including three-dimensional coordinate, coal seam are thick
Degree, roof and floor angle of inclination and pitching rake angle, therefore, the present invention are capable of providing working face automation coal mining control.
Description of the drawings
In order to make the content of the present invention more clearly understood, it below according to specific embodiments of the present invention and ties
Attached drawing is closed, the present invention is described in further detail, wherein：
Fig. 1 is that a kind of automation coal mining system and method work based on various dimensions positioning and deep learning of the present invention is former
Manage schematic diagram；
Fig. 2 is that the present invention a kind of automation coal mining system and method scene based on various dimensions positioning and deep learning are answered
Use schematic diagram；
Fig. 3 is monitored in the present invention a kind of automation coal mining system and method based on various dimensions positioning and deep learning
Substation schematic view of the mounting position；
Fig. 4 is monitored in the present invention a kind of automation coal mining system and method based on various dimensions positioning and deep learning
Substation structure and positioning principle schematic diagram；
Fig. 5 is the present invention a kind of automation coal mining system and method various dimensions based on various dimensions positioning and deep learning
Parameter information schematic diagram；
Reference numeral is expressed as in figure：1- system hosts；2- Monitor Sub-Station of Less；3- set caps；4- bracket bases；5- is bis-
Axial rake sensor；6- laser orientation systems；7- laser emission elements；8- laser pick-off units.
Specific implementation mode
To make the object, technical solutions and advantages of the present invention clearer, below in conjunction with attached drawing to embodiment party of the present invention
Formula is described in further detail.
The present invention a kind of automation coal mining system and side based on various dimensions positioning and deep learning is shown in Fig. 1-5
The preferred embodiment of method.
The automation coal mining system based on various dimensions positioning and deep learning, including system host 1 and several prisons
Substation 2 is surveyed to form；Monitor Sub-Station of Less is arranged in 4 top of 3 lower section of each set cap and bracket base；Each Monitor Sub-Station of Less 2
Including double-shaft tilt angle sensor 5 and laser orientation system 6；Between system host 1 and Monitor Sub-Station of Less 2 or Monitor Sub-Station of Less 2 it is mutual it
Between data transmission realized by wirelessly or non-wirelessly mode；The double-shaft tilt angle sensor 5 is located in Monitor Sub-Station of Less 2, to obtain
The angular distribution feature in working face seam inclination direction and pitching rake angle variation characteristic and the advance of the face in monitoring coal seam
The inclination angle of direction set cap 3 and bracket base 4 calculates obtain the bowing of each holder, looking up position state accordingly；The laser
Positioning system 6 is located in Monitor Sub-Station of Less 2, including two or more laser emission elements 7 and a laser pick-off unit
8, it is spaced apart between the laser emission element 7 of the same Monitor Sub-Station of Less 2.
The automation coal-mining method based on various dimensions positioning and deep learning, is positioned using above-mentioned based on various dimensions
And the automation coal mining system of deep learning is controlled, and is included the following steps：
(a) the positioning criterion of laser orientation system 6 is established；
(b) using 2 position coordinates of Monitor Sub-Station of Less of the top of first bracket base of working face lower end 4 as origin, the is determined
Then one 3 lower section Monitor Sub-Station of Less of set cap, 2 position coordinates is basic point with first 3 lower section Monitor Sub-Station of Less 2 of set cap,
Second 4 top Monitor Sub-Station of Less of bracket base, 2 position coordinates is determined, until determining that working face all hydraulic holder respectively monitors
The relative coordinate of position at substation；
(c) by system host 1 by each hydraulic support top beam and 2 position coordinates of pedestal Monitor Sub-Station of Less and double-shaft tilt angle number
According to being handled, obtain using first 4 top Monitor Sub-Station of Less of bracket base, 2 position as coordinate origin, including entire working face liquid
Press set cap, position base relative coordinate and bracket base and top beam inclination angle and direction of propulsion in an inclined direction on
Pitching rake angle, while show on 1 screen of system host working surface hydraulic support on alter or glide and advanced or stagnant
Situation afterwards；
(d) according to the thickness a of 2 installation site top beam of hydraulic support Monitor Sub-Station of Less, the thickness b of pedestal, top beam and pedestal edge
The inclination angle theta 1 and θ 2 in advance of the face direction, it is h=a+ that corresponding coal seam thickness or mining height at corresponding hydraulic support, which is calculated,
B+z1-z2tan (θ 1- θ 2), wherein two Monitor Sub-Station of Less 2 are respectively z1, z2 along the coordinate in the i.e. mining height direction of Z axis is adopted；
(e) it is basic point to be based on first 2 installation site of hydraulic support foundation Monitor Sub-Station of Less, passes through double-shaft tilt angle sensor 5
The top beam of acquisition working face all hydraulic holder, the position coordinates of pedestal and across pitch and tendency are measured with laser orientation system 6
Angle, including the supporting height of each holder and front coal seam thickness further calculate and obtain coal body top in front of each holder
The multidimensional coordinate system (x, y, z, φ, θ) of bottom plate detail parameters, wherein x, y, it is basic point that z, which is with first bracket base 4,
The spatial triaxial coordinate of working face roof or bottom plate, φ and θ are respectively the tendency of roof or bottom plate and move towards angle
Degree；
(f) during working face extraction, deep learning model is established by system host 1, the input layer in model with
The x, y, z of top plate and bottom plate in front of each hydraulic support, φ, θ parameters are input pointer, and output layer is to wait adopting not in front of coal wall
Know the coal seam fold form in region, including three-dimensional coordinate, coal seam thickness, roof and floor angle of inclination and pitching rake angle, hidden layer
Neuron number determines according to actual needs；
(g) index for exporting deep learning model, including coal seam each position prediction roof and floor three-dimensional coordinate, coal
Layer thickness, roof and floor angle of inclination and pitching rake angle are transferred to coalcutter, guide coalcutter coal cutting roller with coal seam fold shape
The variation of state adjusts in real time, realizes that automation coal cutting, simultaneity factor host 1 are monitored working face various dimensions parameter, including
It alters or glides on hydraulic support, advanced or lag, bow or come back, by sending instructions to electrohydraulic control system to hydraulic pressure
Holder is adjusted.
The positioning criterion of laser orientation system 6 is：In plane XY coordinate systems, determine in a laser orientation system 6
Distance is d between two laser emission elements A and B, and coordinate is respectively A (0,0) and B (d, 0), each spontaneous emission laser beam and
A, the angle of line is respectively α, β between 2 points of B, then the space of laser pick-off unit is opposite in another laser orientation system 6
Coordinate is that C (xc, yc) is CDetermine the monitoring point of some hydraulic support top beam (or pedestal)
The position coordinates stood at 2, then measure the relative position of adjacent hydraulic support foundation (or top beam) by laser orientation system 6
Coordinate；If above-mentioned coordinate system is adjusted to three-dimensional XYZ coordinate system by plane XY coordinate systems, position equally applicable.
Obviously, the above embodiments are merely examples for clarifying the description, and does not limit the embodiments.
For those of ordinary skill in the art, other various forms of changes can also be made on the basis of the above description
Change or changes.There is no necessity and possibility to exhaust all the enbodiments.And obvious change extended from this
Change or change and is still in the protection scope of this invention.
Claims (3)
1. a kind of automation coal mining system based on various dimensions positioning and deep learning, it is characterised in that：Including system host (1)
It is formed with several Monitor Sub-Station of Less (2)；Monitor Sub-Station of Less is arranged in below each set cap (3) and on bracket base (4)
Side；Each Monitor Sub-Station of Less (2) includes double-shaft tilt angle sensor (5) and laser orientation system (6)；System host (1) and monitoring point
It stands between (2) or Monitor Sub-Station of Less (2) realizes data transmission by wirelessly or non-wirelessly mode between each other；
The double-shaft tilt angle sensor (5) is located in Monitor Sub-Station of Less (2), to obtain the angle point in working face seam inclination direction
Boot is sought peace the pitching rake angle variation characteristic and advance of the face direction set cap (3) and bracket base in monitoring coal seam
(4) inclination angle calculates obtain the bowing of each holder, looking up position state accordingly；
The laser orientation system (6) is located in Monitor Sub-Station of Less (2), including two or more laser emission elements (7)
It is spaced apart between the laser emission element (7) of the same Monitor Sub-Station of Less (2) with a laser pick-off unit (8).
2. a kind of automation coal-mining method based on various dimensions positioning and deep learning, it is characterised in that：Using claim 1 institute
The automation coal mining system based on various dimensions positioning and deep learning stated is controlled, and is included the following steps：
(a) the positioning criterion of laser orientation system (6) is established；
(b) using Monitor Sub-Station of Less (2) position coordinates above first bracket base (4) of working face lower end as origin, is determined
Monitor Sub-Station of Less (2) position coordinates below one set cap (3), then with Monitor Sub-Station of Less (2) below first set cap (3)
For basic point, Monitor Sub-Station of Less (2) position coordinates above second bracket base (4) are determined, until determining working face all hydraulic
The relative coordinate of position at each Monitor Sub-Station of Less of holder；
(c) by system host (1) by each hydraulic support top beam and pedestal Monitor Sub-Station of Less (2) position coordinates and double-shaft tilt angle data
It is handled, is obtained using Monitor Sub-Station of Less (2) position above first bracket base (4) as coordinate origin, including entire working face
On hydraulic support top beam, the inclination angle and direction of propulsion of the relative coordinate of position base and bracket base and top beam in an inclined direction
Pitching rake angle, while show on system host (1) screen working surface hydraulic support on alter or glide and it is advanced or
Lag situation；
(d) according to the thickness a of hydraulic support Monitor Sub-Station of Less (2) installation site top beam, the thickness b of pedestal, top beam and pedestal are along work
The inclination angle theta 1 and θ 2 for making face direction of propulsion, it is h=a+b+ that corresponding coal seam thickness or mining height at corresponding hydraulic support, which is calculated,
(z1-z2) tan (θ 1- θ 2), wherein two Monitor Sub-Station of Less (2) are respectively z1, z2 along the coordinate in the i.e. mining height direction of Z axis is adopted；
(e) it is basic point to be based on first hydraulic support foundation Monitor Sub-Station of Less (2) installation site, is passed through double-shaft tilt angle sensor (5)
The top beam of acquisition working face all hydraulic holder, the position coordinates of pedestal and across pitch are measured with laser orientation system (6) and are inclined
To angle, including the supporting height of each holder and front coal seam thickness further calculate and obtain coal body in front of each holder
The multidimensional coordinate system (x, y, z, φ, θ) of roof and floor detail parameters, wherein x, y, z are with first bracket base (4) for basic point
Working face roof or bottom plate spatial triaxial coordinate, φ and θ are respectively the tendency of roof or bottom plate and move towards angle
Degree；
(f) during working face extraction, deep learning model is established by system host (1), the input layer in model is with every
The x, y, z of top plate and bottom plate in front of a hydraulic support, φ, θ parameters are input pointer, and output layer is unknown area to be adopted in front of coal wall
The coal seam fold form in domain, including three-dimensional coordinate, coal seam thickness, roof and floor angle of inclination and pitching rake angle, hidden layer nerve
First number determines according to actual needs；
(g) index for exporting deep learning model, including the roof and floor three-dimensional coordinate of each position prediction in coal seam, coal seam are thick
Degree, roof and floor angle of inclination and pitching rake angle are transferred to coalcutter, guide coalcutter coal cutting roller with coal seam fold form
Variation adjustment in real time, realizes automation coal cutting, simultaneity factor host (1) is monitored working face various dimensions parameter, including liquid
It alters or glides on pressure holder, advanced or lag, bow or come back, by sending instructions to electrohydraulic control system to hydraulic support
It is adjusted.
3. the automation coal-mining method according to claim 2 based on various dimensions positioning and deep learning, it is characterised in that：
The positioning criterion of laser orientation system (6) is：In plane XY coordinate systems, two are determined in a laser orientation system (6)
Distance is d between laser emission element A and B, and coordinate is respectively A (0,0) and B (d, 0), each spontaneous emission laser beam and A, B two
The angle of line is respectively α, β between point, then the space relative coordinate of another laser orientation system (6) interior laser pick-off unit
It is for C (xc, yc)Determine some hydraulic support top beam (or pedestal) Monitor Sub-Station of Less
(2) then the position coordinates at measure the relative position of adjacent hydraulic support foundation (or top beam) by laser orientation system (6)
Coordinate；
If above-mentioned coordinate system is adjusted to three-dimensional XYZ coordinate system by plane XY coordinate systems, position equally applicable.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114263497A (en) * | 2021-12-14 | 2022-04-01 | 中煤科工集团上海研究院有限公司常熟分院 | Device and method for detecting distance between cutting drum of coal mining machine and side protection plate of hydraulic support |
| WO2023151131A1 (en) * | 2022-02-14 | 2023-08-17 | 中煤科工集团沈阳研究院有限公司 | Testing device and testing method for coal mine moving target positioning capability |
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