CN109268072A - Mine floor water bursting disaster intelligence, the big data cloud platform of real-time prediction and warning - Google Patents
Mine floor water bursting disaster intelligence, the big data cloud platform of real-time prediction and warning Download PDFInfo
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- CN109268072A CN109268072A CN201811365704.3A CN201811365704A CN109268072A CN 109268072 A CN109268072 A CN 109268072A CN 201811365704 A CN201811365704 A CN 201811365704A CN 109268072 A CN109268072 A CN 109268072A
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- 238000004422 calculation algorithm Methods 0.000 claims abstract description 10
- 230000005540 biological transmission Effects 0.000 claims abstract description 7
- 238000003860 storage Methods 0.000 claims abstract description 6
- 239000003245 coal Substances 0.000 claims description 21
- 238000005553 drilling Methods 0.000 claims description 16
- 238000012545 processing Methods 0.000 claims description 13
- 238000004457 water analysis Methods 0.000 claims description 13
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- 239000011083 cement mortar Substances 0.000 claims description 8
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- 238000013528 artificial neural network Methods 0.000 claims description 6
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- 238000007621 cluster analysis Methods 0.000 claims description 4
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- SVPXDRXYRYOSEX-UHFFFAOYSA-N bentoquatam Chemical compound O.O=[Si]=O.O=[Al]O[Al]=O SVPXDRXYRYOSEX-UHFFFAOYSA-N 0.000 claims description 3
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- 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
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Abstract
The invention belongs to intelligent predicting fields, are related to mine floor water bursting disaster intelligence, the big data cloud platform of real-time prediction and warning, and the big data cloud platform realizes its platform by modes such as Ali's cloud, oneself establishment cloud platforms.The distributed storage designed using Hadoop programming model packet.The distributed storage of data using a high reliability, high-performance, towards column, telescopic distributed data base HBase.Clustering, prediction and warning algorithm are realized using computing engines Spark.The real-time display and transmission of the realization prediction result that message system is realized are subscribed to using a kind of distributed post of high-throughput.The data that early warning floor undulation mine floor to be predicted monitoring Internet of things system monitors and floor undulation gushing water situation are stored to history mine floor and monitor Internet of Things monitor database by the present invention.Mine floor water bursting disaster intelligence, real-time prediction model and early warning threshold values are modified on this basis.
Description
Technical field
The invention belongs to intelligent predicting fields, are related to mine floor water bursting disaster intelligence, the big data of real-time prediction and warning
Cloud platform.
Background technique
China's superficial part coal resources are petered out, and deep water bursting disaster takes place frequently, and there is an urgent need to mine water inrush calamities for safety in production
The relevant risk recognition of evil and prediction and warning method and big data application system.The present invention passes through the research big number of coal mine water bursting disaster
According to intelligent predicting early warning key technology, it will thus provide a kind of relevant prediction and warning side of mine water inrush diaster prevention and control based on cloud platform
Method and big data application system promote mine water inrush risk recognition and early warning precision, guarantee safe production.Rely on prior art clothes
Business market value basis can be applicable in the mine that national mine water inrush threatens, and provide mine water inrush damage control for service mine
The value-added services such as big data mining analysis provide water-inrush prevention decision support for responsible departments of the government such as Supervisor Bureau of Coal.
Summary of the invention
The present invention provides a kind of big data cloud platform of mine floor water bursting disaster prediction and warning, using the calculating of big data
Method determines type belonging to mine floor according to coal mine work area bottom plate engineering geological condition to be predicted, then according to work face
Monitoring data realize mine floor water bursting disaster intelligence, real-time prediction and warning, to prevent the generation of mine floor water bursting disaster.
Technical scheme is as follows:
Mine floor water bursting disaster intelligence, the big data cloud platform of real-time prediction and warning by Ali's cloud, oneself set up cloud
The modes such as platform realize its platform.Using the distributed storage of Hadoop programming model packet design and implementation data.Point of data
Cloth is stored using a high reliability, high-performance, towards column, telescopic distributed data base HBase.Using calculating
Engine Spark realizes clustering, prediction and warning algorithm.Message system is subscribed to using a kind of distributed post of high-throughput
(Kafka) real-time display and transmission for the realization prediction result realized.
A kind of big data cloud platform of intelligent, the real-time prediction and warning of mine floor water bursting disaster, includes mine floor geology
Categorizing system, mine floor monitoring Internet of things system and real-time display, Early-Warning System.
Mine floor monitors Internet of things system and collected information is transferred to mine floor geological classes system, by number
After processing, mine floor geological classes system passes data to real-time display, Early-Warning System.
The mine floor geological classes system includes acquisition module, the mine floor geology of mine floor geological information
Information quantification processing module, mine floor geological information database and mine floor geology Cluster Analysis module.
The acquisition module of mine floor geological information realizes the engineering geology and hydrogeological information for collecting the bottom plate of coal mine,
Information includes spatial distribution containing mine floor, aquifer water well, water-bearing layer head pressure and thickness of water barrier etc..
Mine floor geological information quantification processing module, realization collect the acquisition module of mine floor geological information
Information be handled as follows:
(1) to aquifer water well X1Judgement classification: the watery in seat earth water-bearing layer is the material base of gushing water,
Degree of water-rich and nourishment condition determine that can the water size of Water Inrush and projective water point lasting water burst.Influence watery because
Element mainly has specific capacity and infiltration coefficient, watery in water-bearing layer is divided into five grades, i.e.,
(2) to water-bearing layer head pressure X2Judged: the head pressure that floor water-bearing rock has is that gushing water occurs for bottom plate
Precondition, in the identical situation of seat earth geological conditions, artesian water hydraulic pressure is higher, easier gushing water.
(3) to the thickness X of water barrier3Judged: when other geological conditions are identical, impermeable layer thickness is bigger, impedance water
Ability is stronger.
(4) to fault transmissibility X4Be classified: it is disconnected to be divided into watery fault, water guide by its hydrogeological feature for fracture
Split, water storage fracture, anhydrous fracture and 5 seed type of shield function, the transmissibility of fracture successively reduce, to the contribution of Water Inrush according to
Secondary reduction.
(5) seat earth lithology combination X is pressed5Be classified: different lithology has different mechanical strengths, impedance outlet capacity
Also different, mine floor rock mass lithology combination is divided as follows:
The mine floor geological information database is the high reliability designed based on Hadoop programming model packet, Gao Xing
Can, towards column and telescopic distributed data base, by mine floor geological information quantification processing module quantification processing after
Data be stored in the distributed data base.
The mine floor geology Cluster Analysis module uses the cluster algorithm realized based on computing engines Spark,
The data of mine floor geological information database are analyzed, mine floor is divided into four kinds of backplane types: easily being occurred prominent
Water disaster bottom plate is easier to that water bursting disaster bottom plate, more difficult water bursting disaster bottom plate and extremely difficult generation water bursting disaster bottom plate occurs.
The mine floor monitors Internet of things system, including Internet of Things monitoring device, data transmission module and mine floor
Monitor Internet of Things monitor database.
Internet of Things monitoring device includes microseismic sensors, hydraulic pressure sensor, borehole stressmeter, water flow sensor and water
Matter analyte sensors etc., according to field demand and engineering construction condition, further supplement or screening.
The sensing is provided that
1. microseismic sensors: firstly, being purged using air pressure gun to remaining water in drilling and cinder.Then, peace is utilized
Holding tool send sensor to the bottom of drilling, couples sensor base sufficiently with palisades, pastes jail.And it is poured into drilling backward
Appropriate cement mortar, and mud lid is made to cross sensor.Finally, extract sensor installation tool out when cement mortar starts solidification,
And drilling is filled real with cement mortar.
2. hydraulic pressure sensor: the present invention uses pore pressure gauge, bores under 1.5m depth to hole, using plunging by hole
Water pressure gauge is sent to projected depth, and 1 meter of backfill or more bentonite mud ball, last sealing of hole, specific installation requirement are produced according to sensor
Product require to make the appropriate adjustments.
3. borehole stressmeter: using diameter to bore for the drill bit of 55mm, vertical coal wall direction drilling depth is 8m circular hole, will be drilled
Stress meter is placed in hole.
4. water flow sensor: water flow sensor is arranged in service drain, needs after being installed individually to it
Coordinate measures.
5. water analysis sensor: water analysis sensor is installed in service drain, needs list after being installed
Solely its coordinate is measured.
Internet of Things monitoring device and mine floor are monitored Internet of Things monitoring data using cable by the data transmission module
Library is connected, and concrete mode is as follows:
A to lay cable carry out casing protection, casing select material be 2.0MPa PPR pipe, tubing with a thickness of
3.5mm is reinforced between spool and spool using bidirectional joint；
B carries out landfill protection to cable is laid, and the cable after casing is put into the wire casing of 30cm, is filled out using cinder
Pile things on protects cable in fact.
Mine floor monitoring Internet of Things monitor database be the high reliability designed based on Hadoop programming model packet,
High-performance, towards column, telescopic distributed data base.The microseismic event that mine floor monitoring Internet of things system monitors is sat
Real-time Monitoring Datas and the work such as mark and related focal shock parameter, water pressure data, water flow data, stress data and water analysis data
Make space of planes distribution, microseismic sensors, borehole stressmeter, hydraulic pressure sensor, water flow sensor and water analysis sensor
The information data storings such as space coordinate are in the distributed data base.
The real-time display, Early-Warning System include history mine floor monitoring Internet of Things monitor database, predict in advance
Alert algoritic module and real-time display module.
The prediction and warning algoritic module carries out the data in history mine floor monitoring Internet of Things monitor database
Analysis, and shown by real-time display module.
The history mine floor monitoring Internet of Things monitor database is that the height designed based on Hadoop programming model packet can
By property, high-performance, towards column and telescopic distributed data base.
There are two types of the data stored in history mine floor monitoring Internet of Things monitor database: the first, mine floor
The mine floor monitoring data of collection in qualitative classification system, the partial data include microseismic event coordinate and related focus ginseng
Number, water pressure data, water flow data, stress data, the Real-time Monitoring Data of water analysis data and microseismic sensors, hydraulic pressure pass
The letter such as sensor, water flow sensor, strain gauge, the space coordinate of water analysis sensor, floor undulation gushing water situation
Breath.Second, exploited the installation of completion mine floor monitoring Internet of things system mine floor monitoring data and working face
Water Inrush situation.
The prediction and warning algoritic module is the deep neural network algorithm realized based on computing engines Spark.Pass through coal
Data in the history mine floor monitoring Internet of Things monitor database of four kinds of backplane types of mine bottom plate, are drawn using based on calculating
The corresponding mine floor water bursting disaster of deep neural network algorithm four kinds of backplane types of training for holding up Spark realization is intelligent, real-time
Prediction model and early warning threshold values.To obtain the corresponding mine floor water bursting disaster intelligence of different bottom plate geological types, pre- in real time
Survey Early-warning Model.
Beneficial effects of the present invention:
(1) a large amount of to collect domestic mine floor spatial distribution, aquifer water well, water-bearing layer head pressure, water barrier
Thickness and the engineering geology of the thickness of water barrier etc. and hydrogeological information and microseismic event coordinate and related focal shock parameter, hydraulic pressure
The Real-time Monitoring Datas such as data, water flow data, stress data, water analysis data and microseismic sensors, hydraulic pressure sensor, water
The information such as space coordinate, the floor undulation gushing water situation of flow sensor, strain gauge, water analysis sensor etc., build
Vertical mine floor geological information database and history mine floor monitor Internet of Things monitor database.
(2) pass through the aquifer water well, water-bearing layer head pressure to mine floor in mine floor geological information database
Mine floor is divided into and water bursting disaster bottom plate easily occurs, is easier to send out by the information such as the thickness of power, the thickness of water barrier and water barrier
Raw water bursting disaster bottom plate, more difficult water bursting disaster bottom plate and extremely difficult generation water bursting disaster bottom plate, and establish corresponding classification method.
(3) data in Internet of Things monitor database are monitored by the history mine floor of four kinds of backplane types, using base
In the corresponding mine floor water bursting disaster intelligence of deep neural network algorithm four kinds of backplane types of training that computing engines Spark is realized
Energy, real-time prediction model and early warning threshold values.To obtain the corresponding mine floor water bursting disaster intelligence of different bottom plate geological types,
Real-time prediction and warning model.
(4) the bottom plate geological conditions of early warning working face to be predicted, acquisition, coal mine bottom to mine floor geological information are analyzed
Plate geological information carries out quantification processing and determines that early warning to be predicted works by the cluster algorithm that computing engines Spark is realized
Geological type belonging to the bottom plate in face.
(5) mine floor monitoring Internet of things system is established in the bottom plate of early warning working face to be predicted, carries out real-time prison to it
It surveys, and is stored in mine floor monitoring Internet of Things monitor database.
(6) suitable model is selected, based on the data in mine floor monitoring Internet of Things monitor database, using suitable
Mine floor water bursting disaster intelligence, real-time prediction model and early warning threshold values, carry out real-time prediction and warning to working face disaster, and right
Monitoring result, prediction and warning result carry out real-time display and publication.
(7) it after the completion of early warning working face mining to be predicted, is stored after early warning working face to be predicted is carried out quantification processing
To mine floor geological information database.Early warning floor undulation mine floor to be predicted monitoring Internet of things system is monitored
Data and floor undulation gushing water situation store to history mine floor and monitor Internet of Things monitor database.On this basis to coal
Mine water inrush from floor intelligence, real-time prediction model and early warning threshold values are modified.
Detailed description of the invention
Fig. 1 is the content schematic diagram that mine floor geological information includes.
Fig. 2 is gushing water big data platform data warehouse schema schematic diagram.
Fig. 3 is gushing water big data on-line analytical processing framework schematic diagram.
Specific embodiment
It is next with reference to the accompanying drawings of the specification that the present invention is further described.
Step 1: adopting coal mine work area backplane mine floor monitoring Internet of things system to be predicted.
The mine floor monitors Internet of things system, including microseismic sensors, hydraulic pressure sensor, water flow sensor, answers
Force snesor, signal cable and mine data acquire center.
Microseismic sensors, hydraulic pressure sensor, water flow sensor and strain gauge are passed through into signal cable and mine respectively
The connection of mountain data acquisition center, mine data acquisition center is for monitoring the microseism to be predicted adopted in coal mine work area recovery process
Signal, variation in water pressure, changes in flow rate, change of water quality and stress variation.
The monitoring Internet of things system establishes mode, and steps are as follows:
The setting of 1.1 sensors
Because the laying of microseism, hydraulic pressure, water flow, water quality and strain gauge has difference to bore position, depth, inclination angle
It is required that being measured to each drilling orifice, bottom hole coordinate by mine geology and survey department, and calculating sensor coordinates, report is formed.
1.1.1 microseismic sensors are installed: firstly, being purged using air pressure gun to remaining water in drilling and cinder.Then,
Microseismic sensors are sent to the bottom of drilling, microseismic sensors bottom is coupled sufficiently with palisades, pastes jail.Then, into drilling
It is poured slowly into appropriate cement mortar, and mud lid is made to cross microseismic sensors, drilling is filled real with cement mortar.
1.1.2 hydraulic pressure sensor is installed: hydraulic pressure sensor uses pore pressure gauge, bores under 1.5m depth to hole, uses
Plunging send pore pressure gauge to lower into hole, 1 meter of backfill or more bentonite mud ball, last sealing of hole.
1.1.3 strain gauge is installed: strain gauge is arranged using the vertical coal wall direction of borehole stressmeter in depth 8m
Hole in.
1.1.4 water flow sensor is installed: water flow sensor is fixed in service drain, is individually surveyed to its coordinate
Amount.
1.2 signal cables are laid with
To ensure that the signal between mine data acquisition center and sensor is unimpeded, cable is protected using following measure
Shield:
1.2.1 casing protection is carried out to arranging signal cable, the material that casing is selected is the PPR pipe of 2.0MPa, tubing
With a thickness of 3.5mm, reinforced between spool and spool using bidirectional joint；
1.2.2 landfill protection is carried out to arranging signal cable, the cable after casing is put into the wire casing of 30~32cm, benefit
Landfill compacting protection cable is carried out with cinder.
Step 2: data are analyzed
Collected mine floor geological information is subjected to quantification processing, forms mine floor geological information data bins
Library.Mine floor geological information data warehouse is analyzed using the calculation method of big data, determines mine floor geology
Classification.
The calculation method of the big data uses clustering method；
The mine floor geological information quantification processing method is as follows:
(1) aquifer water well: the watery in seat earth water-bearing layer is the material base of gushing water, degree of water-rich and benefit
It can lasting water burst to the water size and projective water point of conditional decision Water Inrush.The factor for influencing watery mainly has unit
Watery in water-bearing layer is divided into five grades, i.e., by water yield and infiltration coefficient
(2) water-bearing layer head pressure: the head pressure that floor water-bearing rock has is the precondition that gushing water occurs for bottom plate,
In the similar situation of seat earth geological conditions, artesian water hydraulic pressure is higher, easier gushing water.
(3) thickness of water barrier: when other geological conditions are similar, impermeable layer thickness is bigger, and impedance outlet capacity is stronger.
(4) fault transmissibility: fracture can be divided into watery fault, water guide is broken, water storage is disconnected by its hydrogeological feature
Split, anhydrous fracture, 5 seed types, the transmissibility of fracture such as shield function successively reduce, the contribution of Water Inrush is successively reduced.
(5) seat earth lithology combination: different lithology has different mechanical strengths, and impedance outlet capacity is also different,
Coal mine common base plate rock mass lithology combination is divided as follows:
Step 3: collected data information is adopted coal mine work area bottom plate geological conditions according to be predicted, using big number
According to calculation method --- pattern-recognition, determine and to be predicted adopt coal mine work area bottom plate geological type.Utilize identical coal mine working
The monitoring data of face bottom plate geological type form mine floor monitoring information data warehouse.
The mine floor monitoring information Construction of Data Warehouse method are as follows: supervise stress, hydraulic pressure, water, water quality, microseism etc.
Measured data arranges monitoring data for different Data Marts according to different analysis themes, in Hadoop big data platform
Underground water gushing water data warehouse is constructed, sees Fig. 2, realizes the underground water gushing water data log to different data fairground, different themes
Analysis processing, such as Fig. 3.
Step 4: using the calculation method of big data --- deep neural network is carried out to mine floor monitoring information data
Warehouse is learnt, the corresponding mine floor water bursting disaster intelligence of the training bottom plate geological type, real-time prediction and warning model.From
And obtain the corresponding mine floor water bursting disaster intelligence of different bottom plate geological types, real-time prediction and warning model.
Claims (3)
1. mine floor water bursting disaster intelligence, the big data cloud platform of real-time prediction and warning, which is characterized in that include mine floor
Geological classes system, mine floor monitoring Internet of things system and real-time display, Early-Warning System；
Collected information is transferred to mine floor geological classes system by the mine floor monitoring Internet of things system, is passed through
After data processing, mine floor geological classes system passes data to real-time display, Early-Warning System；
Mine floor geological classes system includes acquisition module, the mine floor geological information quantification of mine floor geological information
Processing module, mine floor geological information database and mine floor geology Cluster Analysis module；
The acquisition module of mine floor geological information realizes the engineering geology and hydrogeological information for collecting the bottom plate of coal mine, information
Including spatial distribution containing mine floor, aquifer water well, water-bearing layer head pressure and water barrier thickness；
Mine floor geological information quantification processing module realizes the collected letter of acquisition module to mine floor geological information
Breath is handled as follows:
A is to aquifer water well X1Judgement classification: the watery in seat earth water-bearing layer is the material base of gushing water, by water-bearing layer
Middle watery is divided into five grades, i.e.,
B is to water-bearing layer head pressure X2Judged: the head pressure that floor water-bearing rock has is the premise item that gushing water occurs for bottom plate
Part, in the identical situation of seat earth geological conditions, artesian water hydraulic pressure is higher, easier gushing water；
Thickness X of the c to water barrier3Judged: when other geological conditions are identical, impermeable layer thickness is bigger, and impedance outlet capacity is got over
By force；
D is to fault transmissibility X4Be classified: by its hydrogeological feature, be divided into watery fault, water guide fracture, water storage fracture,
Anhydrous fracture and five seed type of shield function, the transmissibility of fracture are successively reduced, are successively reduced to the contribution of Water Inrush；
E presses seat earth lithology combination X5It is classified: mine floor rock mass lithology combination is divided as follows:
The mine floor geological information database is the distributed data base designed based on Hadoop programming model packet, by coal mine
Treated that data are stored in the distributed data base for bottom plate geological information quantification processing module quantification；
The mine floor geology Cluster Analysis module uses the cluster algorithm realized based on computing engines Spark, to coal
The data of mine bottom plate geological information database are analyzed, and mine floor is divided into four kinds of backplane types: easily generation gushing water calamity
Evil bottom plate is easier to that water bursting disaster bottom plate, more difficult water bursting disaster bottom plate and extremely difficult generation water bursting disaster bottom plate occurs；
The mine floor monitors Internet of things system, including Internet of Things monitoring device, data transmission module and mine floor monitoring
Internet of Things monitor database；
Internet of Things monitoring device includes microseismic sensors, hydraulic pressure sensor, borehole stressmeter, water flow sensor and water quality point
Analyse sensor；Internet of Things monitoring device and mine floor are monitored Internet of Things monitoring data using cable by the data transmission module
Library is connected；
The mine floor monitoring Internet of Things monitor database is the distributed data base designed based on Hadoop programming model packet；
The Real-time Monitoring Data that mine floor monitoring Internet of things system is monitored and working face spatial distribution, microseismic sensors, drilling
Stress meter, hydraulic pressure sensor, water flow sensor and water analysis sensor spatial coordinated information data be stored in the distribution
Formula database；
The real-time display, Early-Warning System include history mine floor monitoring Internet of Things monitor database, prediction and warning calculation
Method module and real-time display module；
The prediction and warning algoritic module analyzes the data in history mine floor monitoring Internet of Things monitor database,
And it is shown by real-time display module；
The history mine floor monitoring Internet of Things monitor database is the distributed number designed based on Hadoop programming model packet
According to library；
There are two types of the data stored in history mine floor monitoring Internet of Things monitor database: the first, mine floor geology point
The mine floor monitoring data of collection in class system, the data include microseismic event coordinate and related focal shock parameter, hydraulic pressure number
According to, water flow data, stress data, the Real-time Monitoring Data of water analysis data and microseismic sensors, hydraulic pressure sensor, water flow
Quantity sensor, strain gauge, the space coordinate of water analysis sensor, floor undulation gushing water situation information；Second,
Exploit complete installation mine floor monitoring Internet of things system mine floor monitoring data and floor undulation gushing water situation；
The prediction and warning algoritic module is the deep neural network algorithm realized based on computing engines Spark；Pass through coal mine bottom
Data in the history mine floor monitoring Internet of Things monitor database of four kinds of backplane types of plate, using based on computing engines
The corresponding mine floor water bursting disaster of deep neural network algorithm four kinds of backplane types of training that Spark is realized is intelligent, pre- in real time
Survey model and early warning threshold values；To obtain different bottom plate geological types corresponding mine floor water bursting disaster intelligence, in real time prediction
Early-warning Model.
2. mine floor water bursting disaster intelligence as described in claim 1, the big data cloud platform of real-time prediction and warning, feature
It is, the Internet of Things monitoring device is provided that
1. microseismic sensors: being purged using air pressure gun to remaining water in drilling and cinder；Using installation tool by sensor
It send to the bottom of drilling, couples sensor base with palisades；And cement mortar is poured into drilling backward, and mud lid is made to cross biography
Sensor；When cement mortar solidifies, sensor installation tool is extracted out, and drilling is filled real with cement mortar；
2. hydraulic pressure sensor: using pore pressure gauge, bore under 1.5m depth to hole, sent pore pressure gauge using plunging
To projected depth, 1 meter of backfill or more bentonite mud ball, last sealing of hole；
3. borehole stressmeter: using diameter for the drill bit of 55mm, vertical coal wall direction drilling depth is 8m circular hole, by borehole stressmeter
It is placed in hole；
4. water flow sensor: water flow sensor is arranged in service drain, needs after being installed individually to its coordinate
It measures；
5. water analysis sensor: water analysis sensor is installed in service drain, and it is individually right to need after being installed
Its coordinate measures.
3. mine floor water bursting disaster intelligence as claimed in claim 1 or 2, the big data cloud platform of real-time prediction and warning,
It is characterized in that, Internet of Things monitoring device and mine floor are monitored Internet of Things monitoring data using cable by the data transmission module
Library is connected, and concrete mode is as follows:
A carries out casing protection to laying cable, and the material that casing is selected is the PPR pipe of 2.0MPa, tubing with a thickness of 3.5mm,
It is reinforced between spool and spool using bidirectional joint；
B carries out landfill protection to cable is laid, and the cable after casing is put into the wire casing of 30cm, carries out landfill pressure using cinder
Real protection cable.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811365704.3A CN109268072B (en) | 2018-11-16 | 2018-11-16 | Big data cloud platform for intelligent and real-time prediction and early warning of water inrush disaster of coal mine floor |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811365704.3A CN109268072B (en) | 2018-11-16 | 2018-11-16 | Big data cloud platform for intelligent and real-time prediction and early warning of water inrush disaster of coal mine floor |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109268072A true CN109268072A (en) | 2019-01-25 |
| CN109268072B CN109268072B (en) | 2020-04-07 |
Family
ID=65189078
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811365704.3A Active CN109268072B (en) | 2018-11-16 | 2018-11-16 | Big data cloud platform for intelligent and real-time prediction and early warning of water inrush disaster of coal mine floor |
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| CN110552741A (en) * | 2019-09-09 | 2019-12-10 | 中煤科工集团西安研究院有限公司 | coal face bottom plate water inrush comprehensive monitoring and early warning system and method |
| CN110847974A (en) * | 2019-12-06 | 2020-02-28 | 西安科技大学 | Auxiliary method for coal mine water inrush disaster early warning based on neural network |
| CN111287747A (en) * | 2020-02-05 | 2020-06-16 | 天地科技股份有限公司 | Water-controlled coal mining method on pressure-bearing water body |
| CN114087022A (en) * | 2021-10-28 | 2022-02-25 | 山东科技大学 | Coal seam floor variable parameter water inrush channel early warning system and water inrush danger judgment method |
| CN114251124A (en) * | 2021-11-18 | 2022-03-29 | 煤炭科学技术研究院有限公司 | Intelligent early warning method and device for mine water damage |
| CN117689208A (en) * | 2023-12-26 | 2024-03-12 | 山东金软科技股份有限公司 | Metal mine risk dynamic monitoring and intelligent grading early warning system |
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| CN117689208A (en) * | 2023-12-26 | 2024-03-12 | 山东金软科技股份有限公司 | Metal mine risk dynamic monitoring and intelligent grading early warning system |
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