CN114135337A - Internet of things mine ventilation remote monitoring management system based on LSTM network - Google Patents
Internet of things mine ventilation remote monitoring management system based on LSTM network Download PDFInfo
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- CN114135337A CN114135337A CN202111433139.1A CN202111433139A CN114135337A CN 114135337 A CN114135337 A CN 114135337A CN 202111433139 A CN202111433139 A CN 202111433139A CN 114135337 A CN114135337 A CN 114135337A
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 74
- 238000009423 ventilation Methods 0.000 title claims abstract description 37
- 230000006855 networking Effects 0.000 claims abstract description 3
- 238000001514 detection method Methods 0.000 claims description 61
- 238000007726 management method Methods 0.000 claims description 30
- 239000007789 gas Substances 0.000 claims description 27
- 230000005540 biological transmission Effects 0.000 claims description 17
- 238000012545 processing Methods 0.000 claims description 14
- 230000002457 bidirectional effect Effects 0.000 claims description 13
- 239000000428 dust Substances 0.000 claims description 12
- UGFAIRIUMAVXCW-UHFFFAOYSA-N Carbon monoxide Chemical compound [O+]#[C-] UGFAIRIUMAVXCW-UHFFFAOYSA-N 0.000 claims description 11
- RWSOTUBLDIXVET-UHFFFAOYSA-N Dihydrogen sulfide Chemical compound S RWSOTUBLDIXVET-UHFFFAOYSA-N 0.000 claims description 11
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 claims description 11
- 229910002091 carbon monoxide Inorganic materials 0.000 claims description 11
- 229910000037 hydrogen sulfide Inorganic materials 0.000 claims description 11
- 239000001301 oxygen Substances 0.000 claims description 11
- 229910052760 oxygen Inorganic materials 0.000 claims description 11
- 238000013523 data management Methods 0.000 claims description 8
- 238000005259 measurement Methods 0.000 claims description 7
- 230000010354 integration Effects 0.000 abstract description 7
- 230000007613 environmental effect Effects 0.000 abstract description 5
- 238000011161 development Methods 0.000 abstract description 3
- 238000010801 machine learning Methods 0.000 abstract description 2
- 238000010586 diagram Methods 0.000 description 5
- 238000004519 manufacturing process Methods 0.000 description 5
- 238000004458 analytical method Methods 0.000 description 3
- 238000004891 communication Methods 0.000 description 3
- 230000001105 regulatory effect Effects 0.000 description 3
- 230000002159 abnormal effect Effects 0.000 description 2
- 238000013499 data model Methods 0.000 description 2
- 238000012423 maintenance Methods 0.000 description 2
- 230000006996 mental state Effects 0.000 description 2
- 238000000034 method Methods 0.000 description 2
- 238000003860 storage Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000001276 controlling effect Effects 0.000 description 1
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- 238000005516 engineering process Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 238000007689 inspection Methods 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 238000005065 mining Methods 0.000 description 1
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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
- 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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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
- F04D—NON-POSITIVE-DISPLACEMENT PUMPS
- F04D27/00—Control, e.g. regulation, of pumps, pumping installations or pumping systems specially adapted for elastic fluids
- F04D27/001—Testing thereof; Determination or simulation of flow characteristics; Stall or surge detection, e.g. condition monitoring
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
- F04D—NON-POSITIVE-DISPLACEMENT PUMPS
- F04D27/00—Control, e.g. regulation, of pumps, pumping installations or pumping systems specially adapted for elastic fluids
- F04D27/008—Stop safety or alarm devices, e.g. stop-and-go control; Disposition of check-valves
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
- F05D—INDEXING SCHEME FOR ASPECTS RELATING TO NON-POSITIVE-DISPLACEMENT MACHINES OR ENGINES, GAS-TURBINES OR JET-PROPULSION PLANTS
- F05D2270/00—Control
- F05D2270/70—Type of control algorithm
- F05D2270/709—Type of control algorithm with neural networks
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- Engineering & Computer Science (AREA)
- Mining & Mineral Resources (AREA)
- Mechanical Engineering (AREA)
- General Engineering & Computer Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- General Life Sciences & Earth Sciences (AREA)
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Abstract
The invention relates to the field of mine operation, and discloses an Internet of things mine ventilation remote monitoring management system based on an LSTM network. This thing networking mine ventilation remote monitoring management system based on LSTM network has realized remote control and automatic control to the fan, from monitoring the collection, uploading high in the clouds to environmental data, to integrating data, through intelligent speed governing module, intervene in real time and regulate and control the fan operation to improve the ventilation condition in the mine, three integration subsystem synergism makes efficiency maximize. The machine learning method is used for improving the current ventilation system in the mine, so that the working efficiency of related workers is improved, and the intelligent development of the field of mine ventilation is facilitated.
Description
Technical Field
The invention relates to the field of mine operation, in particular to an Internet of things mine ventilation remote monitoring management system based on an LSTM network.
Background
The mining industry is the basic industry for producing raw materials and plays an important role in national economic development. In the environment with complex production risk of mines, mine enterprises with higher risk coefficient of underground operation face sudden equipment failure and natural disasters. Aiming at the current situation of mine enterprises in China, measures for improving the safe production level of mines are required to be taken, and the research on mine safe production monitoring technology and method is strengthened. From the practical point of view, scholars at home and abroad put forward the concept of 'intelligent mine'.
In recent years, with the gradual increase of mine energy and the gradual expansion of underground operation range, the underground ventilation problem becomes a difficult problem to be solved urgently for underground safe production. Because the fan number of the small ventilation system of the multistage engine is mostly larger in the underground distribution area. The ventilation technical department and the load ventilation operation class thereof are not only responsible for the installation and maintenance of the whole mine ventilator, but also have great difficulty in the inspection, management control and management of all ventilators in the whole mine. The specific method of manual monitoring is to arrange monitoring equipment such as a thermometer, an air volume measuring instrument, a dust concentration sensor and the like at key parts of the system, so that workers who regularly patrol can read and record data. Once the system finds an anomaly, a command room wait indication is reported. Specifically, the manual observation and reading mode is greatly restricted by various subjective factors such as the responsibility and mental state of the staff, and the monitoring result is directly influenced. Once the monitoring personnel mistakenly report or fail to report the data, the result can cause serious consequences, in addition, the scheduling room can not obtain the system information at the first time, the timely scheduling at the critical moment is not facilitated, and the storage and reading of a large amount of data are not facilitated for the generation of a data chart. On the basis of the original intelligent mine ventilation building monitoring system, various state information of the ventilator can be checked in real time, production operation can be carried out, various execution of parameters such as dust concentration, wind speed, working voltage and current of the ventilator in a mine can be controlled remotely, various data can be collected, various remote control commands can be executed, and the like. Therefore, an Internet of things mine ventilation remote monitoring management system based on an LSTM network is designed.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides an LSTM network-based Internet of things mine ventilation remote monitoring management system, which solves the problem that the manual meter-reading observation mode is greatly limited by various subjective factors such as the responsibility and mental state of staff, and the monitoring result is directly influenced. Once the monitoring personnel mistakenly report or fail to report the data, the result can cause serious consequences, in addition, the scheduling room can not obtain the system information in the first time, the timely scheduling at the critical moment is not facilitated, and the generation of a data chart is not facilitated by the storage and reading of a large amount of data.
In order to achieve the purpose, the invention adopts the technical scheme that:
the mine ventilation remote monitoring and management system based on the Internet of things comprises a gas concentration monitoring subsystem, a ventilator running state monitoring subsystem, a data transmission subsystem, a ground monitoring and management subsystem, a switch, a database, a processing module and a control terminal, wherein the control terminal is in bidirectional signal connection with the switch, and the gas concentration monitoring subsystem, the ventilator running state monitoring subsystem, the data transmission subsystem and the ground monitoring and management subsystem are in bidirectional signal connection with the switch.
The gas concentration monitoring subsystem comprises a gas concentration detection module, an oxygen concentration detection module, a dust concentration detection module, a hydrogen sulfide concentration detection module and a carbon monoxide detection module, wherein the output ends of the gas concentration detection module, the oxygen concentration detection module, the dust concentration detection module, the hydrogen sulfide concentration detection module and the carbon monoxide detection module are electrically connected with the input end of the processing module, the database is electrically connected with the processing module in a two-way mode, and the processing module is connected with the switch in a two-way signal mode.
Furthermore, the ventilator operation state monitoring subsystem comprises a ventilator operation parameter detection unit, a ventilator operation failure alarm unit and a ventilator operation parameter detection unit, the output ends of the ventilator operation parameter detection unit, the ventilator operation failure alarm unit and the ventilator operation parameter detection unit are all in signal connection with the input end of the switch, and the output ends of the ventilator operation parameter detection unit and the ventilator operation parameter detection unit are all electrically connected with the input end of the ventilator operation failure alarm unit.
Furthermore, the data transmission subsystem comprises an Aliyun terminal and a ground monitoring center, the Aliyun terminal is electrically connected with the ground monitoring center in a bidirectional mode, and the Aliyun terminal and the ground monitoring center are connected with the switch in a bidirectional signal mode.
Furthermore, the ground monitoring management subsystem is composed of a remote measurement module, a remote control module, a remote intelligent speed regulation module, an alarm module and a data management module, wherein the remote measurement module, the remote control module, the remote intelligent speed regulation module, the alarm module and the data management module are all connected with the switch in a bidirectional signal mode.
Furthermore, the ventilator operation parameter detection unit, the ventilator operation failure alarm unit and the ventilator operation parameter detection unit are respectively realized by selecting components such as a gas concentration detector, a hydrogen sulfide concentration detector, an oxygen concentration detector, a carbon monoxide concentration detector, a dust concentration detector and a real-time alarm device which meet the use requirements.
Further, the switch can select a local area network switch or a wide area network switch according to the usage scenario.
The invention has the beneficial effects that:
1. the remote control and the automatic control of the fan are realized, the environment data are monitored, collected and uploaded to the cloud, the data are integrated, and the operation of the fan is intervened and regulated in real time through the intelligent speed regulation module, so that the ventilation condition in a mine is improved. The real-time accurate automatic control of the air quality of the tunnel is realized.
2. Besides meeting the control function requirements, the system can also be effectively compatible with various communication protocols, and has good compatibility and expandability.
3. And the cloud end shares data. Environmental data are comprehensively monitored, collected and uploaded to a cloud end, and data resource sharing is achieved;
4. the data monitoring integration, the data transmission integration and the ground monitoring management integration are realized. The three integrated subsystems act in a synergistic manner, so that the efficiency is maximized. The machine learning method is used for improving the current ventilation system in the mine, so that the working efficiency of related workers is improved, and the intelligent development of the field of mine ventilation is facilitated.
Drawings
FIG. 1 is a schematic view of an overall system of the present invention;
FIG. 2 is a system diagram of a gas concentration monitoring subsystem of the present invention;
FIG. 3 is a system diagram of a ventilator operating condition monitoring subsystem of the present invention;
FIG. 4 is a system diagram of a data transmission subsystem of the present invention;
FIG. 5 is a system diagram of a ground monitoring management subsystem according to the present invention;
FIG. 6 is a system tree diagram of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to FIGS. 1-6: the utility model provides a thing networking mine ventilation remote monitoring management system based on LSTM network, including gas concentration monitoring subsystem, ventilation blower running state monitoring subsystem, data transmission subsystem, ground control management subsystem, the switch, a database, processing module and control terminal, local area network switch or wide area network switch can be selected according to the use scene to the switch, switch data exchange is based on the LSTM network, the minimum 4G network transmission speed that uses of switch simultaneously, control terminal and the two-way signal connection of switch, gas concentration monitoring subsystem, ventilation blower running state monitoring subsystem, data transmission subsystem and ground control management subsystem all with the two-way signal connection of switch.
The gas concentration monitoring subsystem comprises a gas concentration detection module, an oxygen concentration detection module, a dust concentration detection module, a hydrogen sulfide concentration detection module and a carbon monoxide detection module, the gas concentration detection module, the oxygen concentration detection module, the dust concentration detection module, the output ends of the hydrogen sulfide concentration detection module and the carbon monoxide detection module are electrically connected with the input end of the processing module, the database is electrically connected with the processing module in a two-way mode, the processing module is connected with a two-way signal of an exchanger, a ventilator operation parameter detection unit, a ventilator operation failure alarm unit and a ventilator operation parameter detection unit, the ventilator operation failure alarm unit and the ventilator operation parameter detection unit respectively select the gas concentration detector, the hydrogen sulfide concentration detector, the oxygen concentration detector, the carbon monoxide concentration detector and the ventilator operation parameter detection unit which meet the use requirements, The gas concentration monitoring subsystem is implemented by using components such as a gas concentration detector, a hydrogen sulfide concentration detector, an oxygen concentration detector, a carbon monoxide concentration detector, a dust concentration detector, a real-time alarm device and the like, so that full sample monitoring collection and real-time integration are carried out on gas concentration data (gas concentration, hydrogen sulfide concentration, oxygen concentration, carbon monoxide concentration and dust concentration) in a mine, monitored information is transmitted to a processing module for integration, processing and analysis, an analysis result is compared with standard data in a database, and the real-time alarm device gives an alarm when the data exceeds a preset safety value.
In another embodiment, the ventilator operation state monitoring subsystem comprises a ventilator operation parameter detection unit, a ventilator operation failure alarm unit and a ventilator operation parameter detection unit, the output ends of the ventilator operation parameter detection unit, the ventilator operation failure alarm unit and the ventilator operation parameter detection unit are all in signal connection with the input end of the switch, the output ends of the ventilator operation parameter detection unit and the ventilator operation parameter detection unit are all electrically connected with the input end of the ventilator operation failure alarm unit, the ventilator operation parameter detection unit and the ventilator operation parameter detection unit in the ventilator operation state monitoring subsystem carry out real-time monitoring on the ventilator operation parameters and the operation state of the mine, intelligent monitoring, alarm management and real-time parameter analysis of each ventilator in the mine are realized, if a failure occurs, the monitored data information is transmitted to the ventilator operation failure alarm unit to alarm and can quickly lock the ventilator operation parameter detection unit The quick-witted trouble reason by for the operation of ventilation blower is more stable and safe, ventilation blower running state monitoring subsystem carries out full sample detection and collection, real-time integration to ventilation blower operating parameter (operating current, operating voltage, the amount of wind etc.), and the unusual thief of parameter can trigger corresponding alarm device, passes through the data transmission subsystem with the whole data of gathering afterwards and passes to the high in the clouds on through wireless 4G communication module, again by the measuring module of ground monitoring management subsystem with data display on the control center screen.
In another embodiment, the data transmission subsystem comprises an Aliyun terminal and a ground monitoring center, the Aliyun terminal is electrically connected with the ground monitoring center in a bidirectional mode, the Aliyun terminal and the ground monitoring center are in bidirectional signal connection with the switch, the data transmission subsystem adopts a tree-shaped graph structure, and all the gas concentration monitoring subsystems and the ventilator operation state monitoring subsystem are connected through existing digital optical fibers. Data are sent to an Ariiyun monitoring center through a 4G wireless module, various information data transmission are collected by the gas concentration monitoring subsystem and the ventilator running state monitoring subsystem through the data transmission mold system, data information is sent to the cloud end through a wireless 4G communication module in real time, data storage is carried out, meanwhile, workers can also display data through mobile terminals such as mobile phones APP, and visual and digital detection of mine ventilation is achieved.
In another embodiment, the ground monitoring management subsystem is composed of a remote measurement module, a remote control module, a remote intelligent speed regulation module, an alarm module and a data management module, wherein the remote measurement module, the remote control module, the remote intelligent speed regulation module, the alarm module and the data management module are all in bidirectional signal connection with the switch, and the remote measurement module is used for displaying data acquired by the gas concentration monitoring subsystem and the ventilator operation state monitoring subsystem in a ground monitoring center.
The remote control module is used for enabling workers to realize fan starting and stopping control, forward and reverse rotation control and the like of the fan monitoring sub-node in the upper computer through monitoring software.
The remote intelligent speed regulation module trains a training data set through an LSTM network algorithm by historical data to obtain a prediction model. The air supply value of the ventilator is intelligently calculated through an LSTM network, and the intelligent regulation and control of the rotating speed of the ventilator are realized.
The alarm module is used for sending a fault early warning signal when detecting that the operation value of the system equipment is abnormal.
The data management module consists of a historical control command report, an environmental data report and a fault record log, and the remote speed regulation module intelligently calculates the air supply value of the ventilator by comparing a historical data model with an environmental concentration parameter, so that the intelligent regulation and control of the rotating speed of the fan are realized. Therefore, the aim of intelligently regulating and controlling the ventilator is fulfilled. Meanwhile, the ground monitoring management subsystem is divided into five parallel modules, each independent ventilator can be regulated and controlled, different modules can be started according to different mine running conditions, the data management module is composed of a historical control command report, an environmental data report and a fault recording log, monitoring information sent by the field monitoring subsystem and a control command sent by the ground monitoring management subsystem are stored in a database, a worker can master the historical ventilation condition and the running conditions of the ventilator without entering a mine, and the working efficiency is greatly improved.
In conclusion, when the system is used, all the subsystems related to the mine ventilation remote intelligent monitoring management system based on the internet of things are mutually associated and cooperatively work, and data collected by the mine ventilator monitoring terminal and the gas concentration sensor are transmitted to the cloud and ground monitoring center through the 4G wireless transmission module, so that workers and maintenance personnel can know whether all indexes of the mine ventilation environment are abnormal in real time. And the ground monitoring subsystem receives the data value, establishes a data model by using an LSTM network, predicts the data value and improves the current ventilation state of the mine. The working efficiency is greatly improved, the mine safety is better facilitated, meanwhile, a large amount of labor cost and energy consumption are saved for related energy enterprises, and certain economic benefits are generated.
The above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (6)
1. The utility model provides a thing networking mine ventilation remote monitoring management system based on LSTM network, includes gas concentration monitoring subsystem, ventilation blower running state monitoring subsystem, data transmission subsystem, ground control management subsystem, switch, database, processing module and control terminal, its characterized in that: the control terminal is in bidirectional signal connection with the switch, and the gas concentration monitoring subsystem, the ventilator running state monitoring subsystem, the data transmission subsystem and the ground monitoring management subsystem are in bidirectional signal connection with the switch;
the gas concentration monitoring subsystem comprises a gas concentration detection module, an oxygen concentration detection module, a dust concentration detection module, a hydrogen sulfide concentration detection module and a carbon monoxide detection module, wherein the output ends of the gas concentration detection module, the oxygen concentration detection module, the dust concentration detection module, the hydrogen sulfide concentration detection module and the carbon monoxide detection module are electrically connected with the input end of the processing module, the database is electrically connected with the processing module in a two-way mode, and the processing module is connected with the switch in a two-way signal mode.
2. The Internet of things mine ventilation remote monitoring and management system based on the LSTM network as claimed in claim 1, wherein: the ventilator operation state monitoring subsystem comprises a ventilator operation parameter detection unit, a ventilator operation failure alarm unit and a ventilator operation parameter detection unit, wherein the output ends of the ventilator operation parameter detection unit, the ventilator operation failure alarm unit and the ventilator operation parameter detection unit are all in signal connection with the input end of the switch, and the output ends of the ventilator operation parameter detection unit and the ventilator operation parameter detection unit are all electrically connected with the input end of the ventilator operation failure alarm unit.
3. The Internet of things mine ventilation remote monitoring and management system based on the LSTM network as claimed in claim 1, wherein: the data transmission subsystem comprises an Aliyun terminal and a ground monitoring center, the Aliyun terminal is electrically connected with the ground monitoring center in a bidirectional mode, and the Aliyun terminal and the ground monitoring center are connected with the switch in a bidirectional signal mode.
4. The Internet of things mine ventilation remote monitoring and management system based on the LSTM network as claimed in claim 1, wherein: the ground monitoring management subsystem is composed of a remote measurement module, a remote control module, a remote intelligent speed regulation module, an alarm module and a data management module, wherein the remote measurement module, the remote control module, the remote intelligent speed regulation module, the alarm module and the data management module are all connected with a switch in a bidirectional signal mode.
5. The Internet of things mine ventilation remote monitoring and management system based on the LSTM network as claimed in claim 2, wherein: the ventilator operation parameter detection unit, the ventilator operation failure alarm unit and the ventilator operation parameter detection unit are respectively realized by components such as a gas concentration detector, a hydrogen sulfide concentration detector, an oxygen concentration detector, a carbon monoxide concentration detector, a dust concentration detector and a real-time alarm device which meet the use requirements.
6. The Internet of things mine ventilation remote monitoring and management system based on the LSTM network as claimed in claim 1, wherein: the switch can select a local area network switch or a wide area network switch according to a use scene.
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Application publication date: 20220304 |