Welcome to the Industrial Automation website!

NameDescriptionContent
XING-Automation
E-mail  
Password  
  
Forgot password?
  Register
当前位置:

The basic connotation, core problem and key technology of smart mine

F: | Au:佚名 | DA:2023-12-21 | 652 Br: | 🔊 点击朗读正文 ❚❚ | Share:

1. Basic connotation of smart mine

To grasp the basic connotation of smart mine, it is necessary to clarify the connection and difference between smart mine, digital mine and unmanned mine: digital mine is the basis of smart mine, without the digitization of mine, the wisdom of mine is out of the question; The unmanned mine is the advanced stage and the ultimate goal of the intelligent mine. Unmanned mines must be built on the basis of highly intelligent mines to achieve.

(1) Digital mine is the basis and support of smart mine. The core of digital mining is to obtain massive, heterogeneous, heterogeneous, multidimensional and dynamic mine information through different means such as three-dimensional visualization and expression under a unified time-reference and spatial framework, and conduct scientific and orderly organization, management and maintenance of it, so as to establish a distributed sharing, collaboration and utilization mechanism of mine information [4]. It can be seen that the core goal of digital mine is the digital representation, storage and sharing of all kinds of information related to mine. This information is the fundamental basis for intelligent decision making.

(2) The core meaning of smart mines is "wisdom". Digital mining has realized the centralized collection, storage and display of production, safety and management data, but it has not considered the in-depth mining of data value, and lacks the comprehensive utilization ability of data and the ability to provide decision support for the fine management of coal mines [5]. The smart mine emphasizes the deep utilization of data, with the help of big data, artificial intelligence and other technologies, from data to "wisdom", so that the entire mine has the ability of self-analysis and decision-making, to provide strong decision support for coal mine safety production and management, so that the mine "man, machine, environment, pipe" in a highly coordinated unity of operation.

(3) Unmanned mines are the advanced stage and ultimate goal of smart mines. With the further improvement of the intelligent level of mines, the dependence of various kinds of decisions such as mining, mining, transportation, safety and management on people is further reduced, and the goal of unmanned mines is finally realized with the help of robots and other technologies. Unmanned mine is the fundamental guarantee of mine safety. There is no need for manual work underground. Instead, robots work. A small number of high-quality practitioners are mainly working in the mine dispatching command center.

On the basis of the original digital construction, the smart mine closely combines the perception technology, transmission technology, information processing, intelligent computing, etc., with modern mining technology to achieve a comprehensive perception of the real coal mine, and forms a network of people, people and things, and things and things in the coal mine [6-7], which dynamically and in detail describes and controls the whole process of coal mine safety production and operation. Realize the intelligent operation of the whole process of mine development, mining, transportation, washing, safety guarantee, ecological protection, production management, etc. [8], and finally realize the few people or even unmanned mines. Smart mine is the inevitable choice to solve mine safety problems, management problems and efficiency problems, and is a frontier research field of interdisciplinary integration [3], which has broad development prospects.

2 Core issues of smart mine construction

Starting from the basic connotation of smart mine, it is helpful to focus on the core issues of smart mine construction. The "wisdom" of the smart mine includes the ability of active perception, automatic analysis and fast processing of the mine. Taking the mining face as an example, it is necessary to actively perceive the changes of coal rock strata and the changes of the support force, automatically analyze whether the support strength is up to the standard, and give the adjustment strategy of the support scheme in real time. Starting from the active perception ability, automatic analysis ability and rapid processing ability, the construction of smart mines needs to focus on solving the following three core problems.

(1) Mine state depth perception. At the digital mining stage, part of the perception capability has been developed, such as the deployment of some sensors sensing environmental parameters [9-10], but the overall perception capability is not sufficient. The first ability of smart mine is the active perception ability, and only on the basis of perception can automatic analysis and rapid processing be carried out. This perception should be a more comprehensive and in-depth perception, involving the dynamic changes of the parameters of personnel, equipment, environment, management and other aspects of the mine. At the same time, this kind of perception should be more accurate and can confirm the specific part of the change, such as the specific location of the roadway deformation.

(2) Deep mining of mine data. The original perception data reflects the characteristics of large quantity and low value density, so it is necessary to obtain the judgment of equipment and environment status, the monitoring of abnormal events and the early warning of potential dangers through data analysis and mining. There are many types of mine data [11], such as data reflecting the working status of various equipment, environmental parameters such as temperature, gas concentration and pressure, data reflecting the stress of working face support and the state of coal and rock formations, data reflecting the geographical location of workers and other information. Therefore, the deep mining of mine data must have the ability to mine multi-source data. In addition, the deep mining of mine data should pay special attention to the mining of the relationship between different data.

(3) Mine safety production and management decision support. On the basis of condition judgment, abnormal monitoring and danger early warning, reasonable decisions must be made automatically in combination with mine professional knowledge to realize the adjustment and control of personnel, equipment and environment, so as to ensure the efficiency and safety of production.

3. Key technologies of smart mine

Corresponding to the three core issues of smart mine, the key technologies of smart mine include coal mine Internet of things technology, coal mine big data technology and coal mine intelligent decision support technology.

(1) Coal mine Internet of Things technology. Coal mine Internet of Things technology mainly solves the problem of mine state depth perception, and the core is to obtain more comprehensive data and provide a source for the generation of "wisdom". The sources of mine data are complex, including geology, mining, surveying and mapping, production, machinery and equipment, personnel, finance, etc. The data types include images, graphics, text, tables, etc. [12], and the data changes dynamically in the process of mining. On the basis of expanding network, storage and other facilities, the Internet of Things in coal mines should use intelligent sensors, intelligent cameras, RFID readers, three-dimensional laser scanners [13] and other devices to further broaden the orientation of data acquisition. With the help of coal mine Internet of Things technology, the depth and dynamic perception of all aspects of the state of the mine can be realized, and finally the mass data can be gathered.

(2) Coal mine big data technology. To rise from data to "wisdom", it is necessary to rely on coal mine big data technology, which is mainly used to predict the change of geological environment, detect the abnormal working state of equipment and predict the possible dangerous events in the environment [14-16]. The coal mine big data technology should focus on the comprehensiveness of the analyzed data, and based on this requirement, design an analysis platform that can accommodate both structured and unstructured data, and combine sensor data, monitoring video stream, audio stream and artificially generated data to participate in the big data analysis platform [5,17]. Different big data analysis applications can share computing resources in the same cluster but are logically isolated from each other, ensuring the normal running of heterogeneous services. Big data technology can be used to analyze the change trend of mine geological environment, detect the abnormal state of production equipment, predict the occurrence of dangerous events in the environment, etc., which is conducive to more scientific production safety management [18].

(3) Coal mine intelligent decision support technology. After capturing the changing trend of the environment, the abnormal state of equipment and the occurrence of dangerous events, the smart mine must automatically and quickly handle and respond, such as the automatic alarm of the dangerous area of coal and gas outburst, the automatic fault diagnosis of equipment, lines and ventilation system, and the automatic generation and dynamic update of emergency plans and rescue plans. These need to rely on coal mine intelligent decision support technology. The technology specifically includes three aspects: (1) With the experience of coal mine experts, various expert knowledge bases such as mine safety, production, washing, equipment maintenance, operation and management are built [19] to form an automatic diagnosis and response system for coal mine to ensure the reliability of smart mine decision-making; (2) Through virtual reality and augmented reality technology, the excavation process, gas extraction process, emergency rescue and personnel evacuation are simulated, so as to accumulate new experience and constantly expand the knowledge base; (3) By identifying the ontology of the coal mine field and extracting the relationship between the ontology [20], the knowledge map of the coal mine field is constructed, which is conducive to the construction of a more perfect expert system and provides strong support for coal mine safety production and management.


  • Siemens 6SN1123-1AB00-0AA2 LT Module
  • A100005506 Compair Delcos 3100 Control Panel
  • Omron ZFV-CA40 Smart Sensor Amplifier
  • Fanuc A16B-2200-0660 I O Board
  • Omron CJ1W-NC471 Position Control Unit
  • Siemens 6SN1112-1AA00-0AA0 Simodrive PWM Module
  • Mitsubishi GT2708 HMI Touch Panel
  • Siemens 3TK2834-1BB40 Safety Switch
  • INSYS EBW-E100 Industrial Ethernet Router
  • Schneider LC1F400 Contactor TeSys F
  • Mitsui RYP-51 PCB Control Board
  • Tamagawa TS2620N941E172 Encoder
  • Pilz PZE 9 Safety Relay
  • Omron C1000H-CPU01-V1 PLC
  • Siemens 6SL3210-1KE21-3UP1 Frequency Converter
  • Allen-Bradley 440E-L22BNSM Rope Pull Switch
  • ABB CI868K01 Interface Module
  • Stein Sohn E 083.1 PLC Rack
  • Mitsubishi GT2508-VTBD GT2508-VTBA HMI
  • ABB 3BSE018161R1 Module
  • CAREL ASD100 PGD1AY0I00 Operation Panel
  • ABB EK370-40-11 Contactor 220-230V
  • Eaton 9PX1500IRTM UPS 1500VA
  • NCV-20NGNMP Programmable Controller
  • Mitsubishi LE-40MTA-E Tension Controller
  • Fanuc A16B-3200-0429 Control Board
  • Mitsubishi GT2310-VTBA HMI Touch Screen
  • 3A99184G 1C31170G PCB Module Rev 10
  • Schneider 140NOM25200 Modicon Quantum Adapter
  • Mitsubishi NV400-SW 400A Circuit Breaker
  • Applied Materials 0190-51102 Heater Controller
  • Omron C200H-DA003 Analog Output Module
  • Yaskawa JANCD-YCP21-E DX200 CPU Board
  • IAI 12G2-60-250-P-L-C1-SP Intelligent Actuator
  • NLT NL8060BC21-11 8.4 LCD Screen
  • Omron NX502-1300 Controller Unit
  • ABB RVT-6 Power Factor Controller
  • Schneider TM258LF66DT4L PLC Controller
  • NLT NL6448BC26-27D 8.4 LCD Panel
  • NLT NL8060BC21-09 8.4 LCD Screen
  • Keyence XG-8700L Multi-camera Imaging System
  • EPC 50 3183045486 I O Motherboard
  • Nidec Emerson M701-054-00270A CT Drive
  • Therma Wave 18-011040 Controller Assembly
  • Mitsubishi Q03UDECPU PLC CPU Module
  • Allen-Bradley 2002-NX70-MWLINK PLC Module
  • AS-2P-60M-B Industrial PLC Cable
  • Yaskawa JANCD-YCP21-E DX200 CPU Board
  • PASABAN MC-2006 03 CAN PLC Card
  • Mitsubishi RJ71PB91V PROFIBUS DP Module
  • Fanuc A20B-8100-0137 PCB I O Board
  • D0-06DD2-D PLC Module DL06 PLC
  • Kepco BOP100-4M Power Supply Amplifier
  • Allen-Bradley 1785-L60B PLC-5 60 Module
  • Siemens 7MH4900-3AA01 Weighing Module
  • Pilz 773100 PNOZ m1p Safety Controller
  • Omron NS12-TS00B-V2 Graphic Operation Panel
  • EC20-4040BTA Programmable Controller PLC
  • Fanuc A16B-1212-0100-01 Power Unit CNC
  • Siemens 6ES7151-3BB23-0AB0 ET200S Interface Module
  • ATTO Control DU-01 PLC Display System
  • Keyence KV-RC8BXR Programmable Controller
  • Lenze GST04-1GVCK-063C22 Servo Motor
  • CKD AX9000GH AX9210H Control Unit
  • ABB PG6310 DC Trigger Control Board
  • Cutler Hammer 10316H621C Type L Device
  • TAIYO AA-277 EM CY TRIP PCB Card
  • Schneider BMXCPS2010 PLC Power Supply
  • Schneider TSXMRPC007M PLC PCMCIA Card
  • 101182218 Safety Stop Relay SSW301HV-230V
  • Cutler Hammer 9-1875-3 Size 6 Contactor 480V
  • Nidec UNI3401 Drive Module Control Board
  • Delta AS06XA-A PLC Module Analog Mixed IO
  • Lenze EPL 10201 13408978 Servo Drive 24V DC
  • Sigmatek CCP612-K PLC Module DI DO Module
  • Schneider ATS48D38Q Soft Starter Altistart 48
  • Fanuc A20B-3300-0472 Main CPU Board Series 30i
  • Mitsubishi A171SCPU-S3 Servo CPU Module PLC
  • ABB 1SFL597001R7011 700A 100-250V Soft Starter
  • Yaskawa JANCD-YCP21-E DX200 CPU Control Board
  • Schneider NS630N Circuit Breaker 3P 630A
  • Honeywell DPCB21010002 Rack Slot PCB
  • Mitsubishi RJ71EIP91 PLC Module
  • Siemens 3VL5763-1DC36-0AA0 Circuit Breaker
  • Siemens 6GK7542-1AX00-0XE0 Communication Module
  • Siemens 6SL3130-6AE15-0AB1 Smart Line Module
  • HMS Anybus AB7646-F Gateway
  • Honeywell 621-0020 Analog Input Module
  • Siemens 6ES7212-1HF40-0XB0 PLC Controller
  • MAK 1.00.7-36.21.00-40 PCB Module
  • ABB 3BSE006503R1 PFSA140 Power Supply
  • SAACKE F-GDSA 143303 Burner Controller
  • ABB PFSC230 25m Cable Set
  • GE HYDRAN 201Ci-1 Controller
  • ABB NINT-42C main circuit interface board
  • B&R 3AT660 6 Thermocouple Input Module
  • Honeywell EC7850A1080 Programmable Logic Controller
  • Mitsubishi A2ACPU21 CPU Module MELSEC A Series
  • Mitsubishi R60ADH3FR Analog Input Module iQ R
  • ELMO WLWHIA20 100 Servo Drive Whistle Series
  • Omron CJ1W-MAD42 Analog I O Module PLC
  • Siemens A5E03894525 SINAMICS S120 Power Module
  • Omron K3HB-HTA-DRT1 Temperature Panel Meter
  • Keyence KV-8000SO Programmable Controller CPU Unit
  • Harris 8800-00002-02 PLC Power Control Center
  • Siemens 3TY7480-0A Auxiliary Contact Block
  • Omron 3G3MX2-AB022-ZV1 Inverter
  • ABB ACS380-040S-12A6-4 VFD
  • ATTO controlSYS ATTO-CPU44 PLC System
  • Allen‑Bradley 5069-L330ERMS3 CompactLogix PLC
  • Emerson VE4003S2B2 Terminal Module
  • SND ATS48D38Q Soft Starter
  • Omron CJ1W-MCH71 Motion Control Module
  • Siemens 3TK28060BB4 24VDC Contactor
  • Mitsubishi FR-D740-160-NA Inverter
  • PILZ 312070 PSSuniversal PLC Head Module
  • Omron CJ2M-CPU35 SYSMAC CJ Series PLC CPU
  • KISTLER 4734AWDY2X400S1 Force Displacement Indicator
  • Beckhoff CX2100-0904 Power Supply UPS Module
  • Siemens 6ES7 194-4AD00-0AA0 ET 200PRO IM 154-1 DP Module
  • Siemens 6FC5110-0DB02-0AA2 SINUMERIK MMC CPU Module
  • EDWAR 3-SDDC2CF Dual Circuit Card Control Module
  • ABB CI856K01 S100 I O Communication Module
  • Omron C200HW-PCS01-V2 PC Card Unit Module
  • Pilz 777150 PZE X5P 24VDC Safety Relay
  • Siemens 6SE6430-2AD31-1CA0 Inverter
  • Pilz 774340 Safety Relay
  • Kübler 8.5868.1231.3112 Encoder