System and method for intelligent decision-making and remote linkage based on mine ventilation system

Abstract

The present application relates to a system and method for intelligent decision-making and remote linkage based on a mine ventilation system, including: a ventilation parameter acquisition and data communication module, a ventilation parameter comprehensive perception and measurement module, a ventilation network solution module, a ventilation intelligent decision module and a ventilation intelligent remote linkage module. By acquiring the ventilation parameters to be tested, comprehensive perception and measurement of the ventilation parameters are performed, a ventilation network solution model is constructed, ventilation network solution is performed, decision-making and design processing is performed on the mine ventilation system, and based on the results of the ventilation network solution and the results of the decision-making and design processing of the mine ventilation system, remote linkage of automatic dampers, wind windows and intelligent control of ventilators is performed. The present application realizes functions such as intelligent decision-making for air volume regulation in mines, automatic identification of hidden dangers and remote linkage of ventilation equipment and facilities.

Description

Technical Field

[0001] The present application relates to the field of ventilation technology for underground coal mines and non-coal mines, and in particular to a system and method for intelligent decision-making and remote linkage based on a mine ventilation system. Background Art

[0002] With the in-depth development of smart mines and intelligent coal mines, ventilation systems are an important part of coal mine safety production guarantee. It is imperative to realize the full automation and intelligent control of mine ventilation systems. At present, my country's research on intelligent ventilation in mines is still in its infancy. In terms of intelligent solution software, there are mainly VentAnaly mine ventilation intelligent analysis system of Coal Research Institute and MVSS mine ventilation simulation system of Liaoning University of Engineering and Technology. The algorithm is mainly based on the traditional Scott-Hensley method, Newton method, Pingsong method, etc. Although it has been continuously improved and has a good convergence speed and accuracy, in actual application, the high requirements for basic ventilation data and unsatisfactory intelligent decision-making effect are still common problems.

[0003] In terms of ventilation control, the Coal Science and Technology Research Institute Co., Ltd. developed the KJ980 mine ventilation monitoring and facility control system, China University of Mining and Technology studied the remote control of mine fire wind flow and sprinkler fire extinguishing equipment, Hunan Ping An Electric and Shanxi Julong developed local fan control systems, Jinan Jiahong and Jinkexing developed automatic dampers, etc. Although remote control technology is constantly developing and improving, the lack of intelligent decision-making means for wind control solutions leads to low efficiency and poor accuracy of manual adjustment, the fan has not achieved automatic adjustment on demand, the wind window has not achieved remote automatic control, and the system lacks effective means for adaptive wind adjustment of the fan and wind window linkage.

[0004] In view of the current situation that mine ventilation systems mainly rely on manual experience to adjust air volume and are unable to realize on-demand air supply according to the actual production layout of the mine and the distribution of wind resistance in the tunnel, this paper proposes environmental parameter monitoring based on the mine ventilation system to realize intelligent decision-making of mine air volume adjustment, automatic identification of hidden dangers and remote linkage of ventilation equipment and facilities. Summary of the invention

[0005] In order to at least to some extent overcome the problem in the relevant technology that the current mine ventilation system mainly relies on manual experience to adjust the air volume and cannot realize on-demand air supply according to the actual production layout of the mine and the wind resistance distribution of the tunnel, the present application provides a system and method based on intelligent decision-making and remote linkage of the mine ventilation system.

[0006] The scheme of this application is as follows:

[0007] The system is based on intelligent decision-making and remote linkage of mine ventilation system, including:

[0008] Ventilation parameter collection and data communication module, used to collect ventilation parameters to be tested and establish a communication ring network;

[0009] A ventilation parameter comprehensive perception measurement module is used to perform comprehensive perception measurement of the ventilation parameters based on the ventilation parameters and the communication ring network, and obtain ventilation route resistance monitoring parameters, ventilation structure pressure difference and excess air volume monitoring parameters, and full-section accurate wind measurement parameters;

[0010] A ventilation network solution module is used to construct a ventilation network solution model and perform ventilation network solution based on the ventilation route resistance monitoring parameters, ventilation structure pressure difference and air volume monitoring parameters, and full-section accurate wind measurement parameters;

[0011] A ventilation intelligent decision-making module is used to make decisions and design processing on the mine ventilation system based on the results of the ventilation network solution;

[0012] The intelligent remote linkage module for ventilation is used to perform remote linkage of intelligent control of automatic dampers, wind windows and ventilators based on the results of the ventilation network solution and the results of the decision-making design processing of the mine ventilation system.

[0013] Preferably, the ventilation parameter comprehensive perception and measurement module includes:

[0014] A ventilation structure pressure difference excess air volume monitoring unit, which is used to monitor through a pressure difference sensor based on the ventilation parameters and the communication ring network, calculate the local wind resistance, perform correction through numerical simulation based on the calculation result of the local wind resistance, obtain the ventilation structure wind resistance value, and obtain the ventilation structure excess air volume monitoring parameter based on the inversion of the ventilation structure wind resistance value;

[0015] The full-section accurate wind measurement parameter measurement unit is used to install ultrasonic and transmitting sensors in the wind measurement tunnel for synchronous measurement based on the ventilation parameters and the communication ring network through the ultrasonic time difference method and decoupling algorithm to obtain the full-section accurate wind measurement parameters.

[0016] Preferably, the ventilation network solution module includes:

[0017] The ventilation network solution data preprocessing unit is used to obtain ventilation route resistance monitoring parameters, ventilation structure pressure difference and excess air volume monitoring parameters, and full-section precise wind measurement parameters by measuring the obtained ventilation parameters, and perform data preprocessing on the ventilation route resistance monitoring parameters, ventilation structure pressure difference and excess air volume monitoring parameters, and full-section precise wind measurement parameters through a thermal flow coupling algorithm and numerical simulation;

[0018] A ventilation network solution data processing unit, which is used to realize fast reading of heterogeneous monitoring data through database snapshot technology and file exchange technology based on the result of the data preprocessing;

[0019] The ventilation network solution data filtering unit is used to effectively filter the heterogeneous monitoring data through a time series analysis method, eliminate the conflict of monitoring data inside the ventilation network, and realize ventilation network solution.

[0020] Preferably, the intelligent ventilation decision module includes:

[0021] A regulation scheme auxiliary decision unit, used to calculate the required air volume and provide a power consumption regulation scheme for a specified air demand point based on the result of the ventilation network solution;

[0022] The ventilation dynamic performance curve library building unit is used to establish the relationship model between the individual characteristic curve and the speed, blade angle and frequency based on the fan performance test, and obtain the fan performance data;

[0023] A main fan air volume adjustment auxiliary decision unit, used for assisting in deciding the main fan operating frequency or blade angle based on the calculation of the required air volume and the fan performance data;

[0024] The local ventilator air volume adjustment auxiliary decision unit is used to assist in deciding the local ventilator operating frequency based on the calculation of the required air volume and the ventilator performance data.

[0025] Preferably, the intelligent ventilation remote linkage module includes:

[0026] An automated damper and window remote linkage unit, for switching the damper system supporting remote control, and adjusting the opening of the adjustable dampers and windows supporting remote control, based on the results of the ventilation network solution and the results of the decision-making design processing of the mine ventilation system;

[0027] The remote linkage unit for adjusting the air volume of the ventilator is used to dynamically adjust the air volume by changing the motor frequency or the angle of the fan blades through remote linkage based on the results of the ventilation network solution and the results of the decision-making design processing of the mine ventilation system.

[0028] The present application also provides a method for intelligent decision-making and remote linkage based on a mine ventilation system, including: collecting ventilation parameters to be tested and establishing a communication ring network;

[0029] Based on the ventilation parameters and the communication ring network, a comprehensive sensing measurement of the ventilation parameters is performed to obtain ventilation route resistance monitoring parameters, ventilation structure pressure difference excess air volume monitoring parameters and full-section precise wind measurement parameters;

[0030] Based on the ventilation route resistance monitoring parameters, ventilation structure pressure difference and excess air volume monitoring parameters and full-section precise wind measurement parameters, a ventilation network solution model is constructed to perform ventilation network solution;

[0031] Based on the results of the ventilation network solution, decision-making and design processing are performed on the mine ventilation system;

[0032] Based on the results of the ventilation network solution and the results of the decision-making design processing of the mine ventilation system, remote linkage of automatic dampers, wind window intelligent control and ventilator intelligent control is carried out.

[0033] Preferably, the measurement of the ventilation structure pressure difference and excess air volume monitoring parameters includes:

[0034] Based on the ventilation parameters and the communication ring network, the local wind resistance is calculated by monitoring through a pressure difference sensor, and based on the calculation result of the local wind resistance, correction is performed through numerical simulation to obtain the wind resistance value of the ventilation structure, and based on the inversion of the wind resistance value of the ventilation structure, the air volume of the ventilation structure is obtained;

[0035] Preferably, the measurement of the full-section accurate wind measurement parameters includes:

[0036] Based on the ventilation parameters and the communication ring network, ultrasonic time difference method and decoupling algorithm are used to install ultrasonic and transmitting sensors in the wind measurement tunnel for synchronous measurement to obtain accurate wind measurement parameters of the entire section.

[0037] Preferably, the step of constructing a ventilation network solution model includes:

[0038] S1. Based on the measurement of the obtained ventilation parameters, three parameters are obtained, namely, ventilation route resistance monitoring, ventilation structure pressure difference over-air volume monitoring, and full-section accurate wind measurement. The parameters are preprocessed by heat-flow coupling algorithm and numerical simulation;

[0039] S2. Based on the results of the data preprocessing, fast reading of heterogeneous monitoring data is achieved through database snapshot technology and file exchange technology;

[0040] S3. Effectively filter the heterogeneous monitoring data through time series analysis method, eliminate the conflict of monitoring data inside the ventilation network, and realize ventilation network solution.

[0041] Preferably, the decision design process includes:

[0042] Auxiliary decision-making for adjustment scheme, building database of ventilation dynamic performance curve, auxiliary decision-making for main fan air volume adjustment, auxiliary decision-making for local fan air volume adjustment;

[0043] The adjustment scheme assists decision making, and is used to calculate the required air volume and provide a power consumption adjustment scheme for a specified air demand point based on the result of the ventilation network solution;

[0044] The ventilation dynamic performance curve database is used to establish a relationship model between individual characteristic curves and rotation speed, blade angle and frequency based on the ventilator performance test, and obtain a ventilator performance database;

[0045] The main fan air volume adjustment auxiliary decision is used to assist in deciding the main fan operating frequency or blade angle based on the calculation of the required air volume and the fan performance database;

[0046] The local ventilator air volume adjustment auxiliary decision is used to assist in deciding the local ventilator operating frequency based on the calculation of the required air volume and the ventilator performance database.

[0047] The technical solution provided by the present application may include the following beneficial effects: through comprehensive perception and measurement of ventilation parameters, construction of a ventilation network solution model, ventilation network solution, and remote linkage of automated dampers, intelligent control of wind windows, and intelligent control of ventilators, the present application solves the current situation where air volume adjustment mainly relies on manual experience and cannot achieve on-demand air supply based on the actual production layout of the mine and the distribution of wind resistance in the tunnel, and realizes functions such as intelligent decision-making for air volume adjustment in mines, automatic identification of hidden dangers, and remote linkage of ventilation equipment and facilities.

[0048] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0050] Figure 1 This is a schematic diagram of the structure composition of intelligent decision-making and remote linkage based on a mine ventilation system provided by an embodiment of the present application;

[0051] Figure 2 This is a flow chart of a method for intelligent decision-making and remote linkage based on a mine ventilation system provided by another embodiment of the present application;

[0052] Figure 3 It is a schematic diagram of a method for measuring ventilation resistance in a mine according to another embodiment of the present application. DETAILED DESCRIPTION

[0053] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0054] Embodiment 1

[0055] Figure 1 This is a schematic diagram of the structure of intelligent decision-making and remote linkage based on a mine ventilation system provided by an embodiment of the present application. Figure 1 This embodiment provides a system for intelligent decision-making and remote linkage based on a mine ventilation system, including:

[0056] The ventilation parameter acquisition and data communication module 11 is used to acquire the ventilation parameters to be tested, establish a stable and reliable communication ring network, and exchange data with the field equipment controller;

[0057] In this embodiment, establishing a communication ring network includes the following contents:

[0058] Smooth and stable communication is the basis for realizing intelligent decision-making and remote linkage operation of ventilation system. The system uses two high-performance servers as the computing and processing core of intelligent ventilation system. The server runs the intelligent analysis and decision platform software of mine. By networking with the field equipment controller, it can monitor the working status of various ventilators, dampers and other equipment in the mine, collect the design data of communication ring network of various instruments, and analyze and process the data in real time after entering the computing and processing core, so as to realize the online monitoring, remote control, fault diagnosis, alarm and other functions of mine ventilation system. The intelligent ventilation comprehensive monitoring platform controls the main ventilator, local ventilator, damper, wind window and other related equipment and facilities in the mine, and remotely regulates the ventilation system of the mine to achieve the purpose of supplying air on demand, avoiding wind flow disorder, insufficient air volume, over-ventilation, wind flow adjustment during disasters and reasonably selecting disaster avoidance routes. At the same time, it can also diagnose the faults of the main fan, local ventilator, damper and wind window, and remotely dispatch and monitor the wind flow in the ventilation area of ​​the mine.

[0059] The ring network that has been built in the coal mine is used to realize the network interconnection between the monitoring center and the on-site equipment. The number of mine-level network access nodes is large and the situation is complicated. Although it is a ring network, IP address conflicts, power failures of major nodes and other events that affect stability occasionally occur; the core processor running on the workstation is a general-purpose CPU, and the operating system is not specially designed for industrial application scenarios. The workstation has powerful computing power, but its stability and security are a shortcoming. In view of the above reasons, the intelligent ventilation control system has designed a field equipment safety assurance program, which checks the network communication status and the data status of the server. When an abnormality is found, the emergency preset program is started to make the equipment process a preset and relatively safe state, thereby improving the safety of the system after centralized control.

[0060] For newly added equipment underground, PLC control is used to directly connect to the ring network switch through the Ethernet interface. The PLC control program includes a safety assurance program module; for underground equipment with an existing control system, a new PLC is added as the running carrier of the safety assurance program. At the same time, if the original equipment control system does not support Ethernet, the new PLC can also be used as a communication gateway to connect the original equipment to the ring network. For newly added measuring instruments, the field control center is used to collect data and access the network through the Ethernet interface.

[0061] The ventilation parameter comprehensive perception and measurement module 12 is used to perform comprehensive perception and measurement of ventilation parameters based on ventilation parameters, and obtain three parameters: ventilation route resistance monitoring, ventilation structure pressure difference and air volume monitoring, and full-section accurate wind measurement;

[0062] The ventilation network solution module 13 is used to construct a ventilation network solution model based on the parameters and perform ventilation network solution;

[0063] The ventilation intelligent decision module 14 is used to make decision and design processing on the mine ventilation system based on the results of the ventilation network solution;

[0064] The intelligent ventilation remote linkage module 15 is used to perform remote linkage of the intelligent control of automatic dampers, wind windows and ventilators based on the results of ventilation network solution and the results of decision-making design processing of the mine ventilation system.

[0065] In this embodiment, the ventilation parameter comprehensive sensing and measuring module 12 includes:

[0066] The ventilation structure pressure difference excess air volume monitoring unit is used to calculate the local wind resistance based on the pressure difference monitoring data, and to obtain the ventilation structure wind resistance value by performing correction through numerical simulation based on the calculation result of the local wind resistance, and to obtain the ventilation structure excess air volume based on the inversion of the ventilation structure wind resistance value;

[0067] The full-section accurate wind measurement parameter measurement unit is used to obtain the full-section accurate wind measurement parameters based on ventilation parameters, through ultrasonic time difference method and decoupling algorithm, by installing ultrasonic and transmitting sensors in the wind measurement tunnel for synchronous measurement.

[0068] In this embodiment, the ventilation network solution module includes 13:

[0069] The ventilation network solution data preprocessing unit is used to obtain three parameters based on the measurement of the ventilation parameters, namely, ventilation route resistance monitoring, ventilation structure pressure difference and air volume monitoring, and full-section accurate wind measurement. The parameters are preprocessed through the thermal flow coupling algorithm and numerical simulation.

[0070] The ventilation network solution data processing unit is used to realize fast reading of heterogeneous monitoring data based on the results of data preprocessing through database snapshot technology and file exchange technology;

[0071] The ventilation network solution data filtering unit is used to effectively filter heterogeneous monitoring data through time series analysis, eliminate the conflict of monitoring data inside the ventilation network, and realize ventilation network solution.

[0072] In this embodiment, the intelligent ventilation decision module 14 includes:

[0073] The adjustment scheme auxiliary decision unit is used to calculate the required air volume and provide the power consumption adjustment scheme for the specified air demand point based on the results of the ventilation network solution;

[0074] The ventilation dynamic performance curve database building unit is used to establish the relationship model between the individual characteristic curve and the speed, blade angle and frequency based on the fan performance test, and obtain the fan performance database;

[0075] The main fan air volume adjustment auxiliary decision unit is used to assist in deciding the main fan operating frequency or blade angle based on the required air volume calculation and the fan performance database;

[0076] The local fan air volume adjustment auxiliary decision unit is used to assist in deciding the local fan operating frequency based on the required air volume calculation and the fan performance database.

[0077] In this embodiment, the ventilation intelligent remote linkage module 15 includes:

[0078] The automatic damper and wind window remote linkage unit is used to switch the damper system supporting remote control and adjust the opening of the adjustable damper and wind window supporting remote control based on the results of the ventilation network solution and the results of the decision-making design processing of the mine ventilation system;

[0079] The remote linkage unit for fan air volume regulation is used to dynamically adjust the air volume by changing the motor frequency or the fan blade angle through remote linkage based on the results of ventilation network solution and the results of decision-making design processing of the mine ventilation system.

[0080] Embodiment 2

[0081] Figure 2 This is a flow chart of a method for intelligent decision-making and remote linkage based on a mine ventilation system provided by an embodiment of the present application. Figure 2 This embodiment provides a method for intelligent decision-making and remote linkage based on a mine ventilation system, including:

[0082] S1. Collect the ventilation parameters to be tested and establish a communication ring network;

[0083] S2. Based on the ventilation parameters and the communication ring network, a comprehensive sensing measurement of the ventilation parameters is performed to obtain ventilation route resistance monitoring parameters, ventilation structure pressure difference over-air volume monitoring parameters and full-section accurate wind measurement parameters;

[0084] In this embodiment, the quality of the mine ventilation system is related to the safety of the mine. To realize the intelligent management of the mine ventilation system, accurate measurement of ventilation parameters is necessary. The ventilation sensing system mainly includes three key links: key ventilation route resistance monitoring, ventilation structure pressure difference excess air volume monitoring, and accurate wind measurement of the entire section of the main tunnel.

[0085] S2.1 Measurement of pressure difference and air volume monitoring parameters of ventilation structures, including:

[0086] Based on the ventilation parameters and the communication ring network, the local wind resistance is calculated by monitoring through a pressure difference sensor, and based on the calculation result of the local wind resistance, correction is performed through numerical simulation to obtain the wind resistance value of the ventilation structure, and based on the inversion of the wind resistance value of the ventilation structure, the air volume of the ventilation structure is obtained;

[0087] S2.2 Measurement of full-section accurate wind measurement parameters, including:

[0088] Based on a stable communication environment, ultrasonic time difference method and decoupling algorithm are used to install ultrasonic and transmitting sensors in the wind measurement tunnel for synchronous measurement to obtain accurate wind measurement parameters of the entire section.

[0089] Specifically, the current wind sensors used in mines measure wind speed at a point, cannot accurately measure the amount of air passing through, have poor measurement accuracy, and are prone to failure after a disaster. Intelligent ventilation systems need to establish stable and accurate wind measurement devices, and should focus on installing full-section automatic wind measurement devices in the main air intake tunnels, mining working faces, return air tunnels in mining areas, stone gates, and total return air tunnels in the mine to form a fully automatic and efficient wind measurement system, and complete automatic wind measurement of the entire mine in a short period of time.

[0090] Wind speed measurement mainly uses the ultrasonic time difference method. By using a digital conversion chip (TDC) that can accurately time and a turbulent disturbance suppression decoupling algorithm, ultrasonic receiving and transmitting sensors are bidirectionally installed in the wind measurement tunnel to realize large-span ultrasonic bidirectional synchronous measurement. This method can effectively overcome the sensor scale effect and wind turbulence fluctuations during point wind speed measurement, making the wind speed error accuracy less than 0.1m / s, meeting the accuracy requirements of the air volume for real-time calculation of the mine ventilation network.

[0091] S2.3 Ventilation route resistance monitoring specifically includes the following steps:

[0092] S2.3.1 Ventilation resistance monitoring

[0093] like Figure 3 As shown, when the wind flows from point 1 to point 2, the Bernoli equation (also called the ventilation energy equation) is used to represent the ventilation resistance between the two points.

[0094]

[0095] Where:

[0096] P 1 , P 2 It represents the static pressure energy of the airflow in the shaft and tunnel at the two sections at points 1 and 2, Pa;

[0097]

[0098] Therefore, as long as the decision pressure, air density, temperature and humidity, and air flow speed of points 1 and 2 are monitored in real time, the ventilation resistance between points 1 and 2 can be accurately monitored. Select the key ventilation routes and arrange multi-parameter sensors at each node. Measuring range: temperature 0-50℃, humidity 0-100RH%, atmospheric pressure 700hPa-1200hPa; measurement error: temperature ≤±2.5% (FS), humidity ≤±8.0% (FS), atmospheric pressure ≤30Pa) Monitor the tunnel resistance section by section to realize online monitoring of ventilation resistance.

[0099] Select the key ventilation routes of the mine, arrange multi-parameter sensors at each node, monitor the air pressure, temperature, and humidity at the beginning and end of each tunnel of the key route of the mine in real time, calculate the air density of the node, monitor the tunnel resistance section by section, and realize online monitoring of ventilation resistance; accumulate the ventilation resistance of all tunnels on the key ventilation routes of the mine to obtain the total resistance of the mine; monitor the fluctuation of natural wind pressure in the mine in real time; grasp the changes of wind resistance in the main tunnels, correct the wind resistance in the tunnels in real time, and improve the accuracy of real-time solution and wind control decision-making. The total ventilation resistance of the mine and the resistance distribution of the three zones of air intake area-air use area-return air area can be grasped in real time, providing basic data for ventilation system status evaluation and air volume control. At the same time, the natural wind pressure of the mine can be controlled to provide data support for the green energy-saving adjustment of the main fan.

[0100] S3. Based on the parameters, a ventilation network solution model is constructed to perform ventilation network solution;

[0101] In this embodiment, accurate parameters such as the air volume and wind resistance of the tunnel are obtained through S2. The air volume of other tunnels can be quickly iterated and calculated within one inspection cycle of the monitoring system, thereby eliminating the blind spot of the air volume monitoring of the monitoring system, which has important guiding significance for the safe production of coal mines.

[0102] In this embodiment, the heat-flow coupling theory is used in combination with numerical simulation to reveal the formation mechanism of thermal variable wind resistance, derive the energy dissipation equation of the thermal variable wind resistance of the tunnel, and establish a heat-flow dynamic coupling real-time network solution model. Based on database snapshot technology and file exchange technology, fast reading of heterogeneous monitoring data is achieved, and time series analysis is used to effectively filter disturbance and abnormal air volume monitoring data, eliminate the conflict of monitoring data within the ventilation network, and improve the accuracy of real-time network solution. The ventilation network is simplified, the series branches are eliminated, the total air volume and total wind pressure are quickly determined, the node full hierarchical method is used to speed up the search speed of all paths in the entire wind network, and dynamic sorting is performed based on branch variable weights.

[0103] S4. Based on the results of ventilation network solution, make decision and design for the mine ventilation system;

[0104] In this embodiment, after the ventilation network solution model is established using S3, the ventilation system is subjected to decision-making and design processing, which mainly includes:

[0105] Adjustment scheme assists decision-making: For a given air volume at a required air point and the position of the adjustment point, the adjustment scheme that minimizes power consumption or maximizes the required air volume can be calculated for reference by ventilation managers. After authorization and confirmation by the manager, the system can also directly send adjustment instructions to the on-site equipment and remotely control the on-site equipment;

[0106] Ventilation dynamic performance curve database construction: Based on the fan performance test, the relationship model between individual characteristic curves and speed, blade angle and frequency is established to establish the fan performance database.

[0107] Auxiliary decision-making for main fan air volume adjustment: Based on the calculation of required air volume and the main fan performance database, auxiliary decision-making on the main fan operating frequency or blade angle is made to determine the optimal operating point for reference by ventilation managers. After authorization and confirmation by the manager, the system can also directly send adjustment instructions to the on-site equipment to remotely control the fan's operating angle or operating frequency.

[0108] Auxiliary decision-making for local fan air volume adjustment: Based on the calculation of required air volume and the local fan performance database, the system assists in making decisions on the operating frequency of the local fan and determines the optimal operating point for reference by ventilation managers. After authorization and confirmation by the manager, the system can also directly send adjustment instructions to the on-site equipment to remotely control the operating frequency of the fan.

[0109] S5. Based on the results of ventilation network solution and the results of decision-making design processing of mine ventilation system, remote linkage of automatic damper, wind window intelligent control and ventilator intelligent control is carried out.

[0110] In this embodiment, the system integrates the main damper control system and the regulating damper control system into the intelligent ventilation control platform by connecting with the existing equipment. According to the adjustment instructions issued by the S3 mediation scheme, the damper systems supporting remote control are switched on and off at various locations; and the opening of the regulating dampers and windows supporting remote control is adjusted.

[0111] In this embodiment, the basic principle of intelligent fan control is: first, a characteristic curve database of each blade installation angle of fans of different models is constructed, and the optimal motor frequency is selected according to the actual resistance and required air volume of the mine. According to the purpose of air regulation, it can be divided into emergency frequency regulation and power consumption frequency regulation. The main purpose of emergency frequency regulation is to quickly isolate the disaster under disaster conditions such as underground fire and gas outburst. The purpose of power consumption frequency regulation is to adjust the frequency to maintain the optimal power consumption of the ventilation system according to the mining deployment and required air volume.

[0112] Through the adjustment instructions issued by the auxiliary decision-making of the main fan air volume adjustment in S3, the main fan can change the motor frequency or the fan blade angle to achieve dynamic adjustment of the air volume. The main fan automation control system includes the main fan monitoring system and control system.

[0113] The main fan online monitoring system uses two sets of control cabinets with built-in S7-1500 PLC as the control core. The two systems each control one fan and serve as backup for each other. The two systems use Ethernet for data exchange and coordinated scheduling to achieve control of the two fans.

[0114] Through the adjustment instructions issued by the S3 local fan air volume adjustment auxiliary decision, the local fan can change the motor frequency to achieve dynamic adjustment of the air volume.

[0115] The local ventilator unattended and fault diagnosis system mainly solves the problems of centralized remote control of local ventilators, remote power supply of a single group of local ventilators, power system monitoring, environmental parameter detection, leakage, locking, reverse machine experiment, fault diagnosis, etc. The system includes the mine intelligent ventilation remote centralized control system, network transmission equipment, local ventilator controller, mine intrinsically safe branch line device, supporting cable tools, main local fan and inverter, switch, etc.

[0116] In this embodiment, the local fan system structure is:

[0117] (1) A control master station is set up at the ground command center. Two high-performance industrial computers are used in the control master station to collect and monitor the relevant status parameters of the local ventilators at the underground excavation working face. The equipment mainly includes industrial control host, sound and light alarm, etc. The host system is equipped with corresponding configuration software, which can collect the status parameters and monitoring information of the local ventilators and display them on the industrial screen.

[0118] (2) The system utilizes the existing industrial ring network in the mine. The industrial computer establishes communication with the underground through the Ethernet ring network. Each local ventilation fan is equipped with a mine-use flameproof intrinsically safe PLC. The built-in optical terminal uses flame-retardant optical cables to connect to the branch switch. The branch switch uses flame-retardant optical cables to connect to the underground industrial ring network switch and transmits the information to the ground control center through the Gigabit industrial Ethernet ring network.

[0119] (3) The mine flameproof and intrinsically safe programmable control box is responsible for the control of local ventilators, data communication, field sensor collection and data upload. The equipment has the advantages of long transmission distance and convenient maintenance. The mine intrinsically safe network optical terminal equipment that provides 485 optical signal conversion function is integrated into the mine flameproof and intrinsically safe programmable control box to reduce system maintenance nodes.

[0120] It is to be understood that the same or similar parts in the above-mentioned embodiments can refer to each other, and the content not described in detail in some embodiments can refer to the same or similar content in other embodiments. It should be noted that in the description of the present application, the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. In addition, in the description of the present application, unless otherwise specified, the meaning of "multiple" refers to at least two.

[0121] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code that includes one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0122] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0123] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0124] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0125] The storage medium mentioned above can be a read-only memory, a magnetic disk or an optical disk, etc.

[0126] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0127] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in the field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A system based on intelligent decision-making and remote linkage of mine ventilation system, characterized by: include: Ventilation parameter collection and data communication module, used to collect ventilation parameters to be tested and establish a communication ring network; A ventilation parameter comprehensive perception measurement module is used to perform comprehensive perception measurement of the ventilation parameters based on the ventilation parameters and the communication ring network, and obtain ventilation route resistance monitoring parameters, ventilation structure pressure difference and excess air volume monitoring parameters, and full-section accurate wind measurement parameters; A ventilation network solution module is used to construct a ventilation network solution model and perform ventilation network solution based on the ventilation route resistance monitoring parameters, ventilation structure pressure difference and air volume monitoring parameters, and full-section accurate wind measurement parameters; The ventilation network solution module includes: The ventilation network solution data preprocessing unit is used to obtain ventilation route resistance monitoring parameters, ventilation structure pressure difference and excess air volume monitoring parameters, and full-section precise wind measurement parameters by measuring the obtained ventilation parameters, and perform data preprocessing on the ventilation route resistance monitoring parameters, ventilation structure pressure difference and excess air volume monitoring parameters, and full-section precise wind measurement parameters through a thermal flow coupling algorithm and numerical simulation; A ventilation network solution data processing unit, which is used to realize fast reading of heterogeneous monitoring data through database snapshot technology and file exchange technology based on the result of the data preprocessing; A ventilation network solution data filtering unit is used to effectively filter the heterogeneous monitoring data through a time series analysis method, eliminate the conflict of monitoring data within the ventilation network, and realize ventilation network solution; A ventilation intelligent decision-making module is used to make decisions and design processes for the mine ventilation system based on the results of the ventilation network solution; The intelligent ventilation decision module includes: A regulation scheme auxiliary decision unit, used to calculate the required air volume and provide a power consumption regulation scheme for a specified air demand point based on the result of the ventilation network solution; The ventilation dynamic performance curve library building unit is used to establish the relationship model between the individual characteristic curve and the speed, blade angle and frequency based on the fan performance test, and obtain the fan performance data; A main fan air volume adjustment auxiliary decision unit, used for assisting in deciding the main fan operating frequency or blade angle based on the calculation of the required air volume and the fan performance data; A local ventilator air volume adjustment auxiliary decision unit, used for assisting in deciding the local ventilator operating frequency based on the calculation of the required air volume and the ventilator performance data; A ventilation intelligent remote linkage module is used to perform remote linkage of automatic dampers, wind windows and ventilators based on the results of the ventilation network solution and the results of the decision-making design processing of the mine ventilation system; The intelligent ventilation remote linkage module includes: An automated damper and window remote linkage unit, for switching the damper system supporting remote control, and adjusting the opening of the adjustable dampers and windows supporting remote control, based on the results of the ventilation network solution and the results of the decision-making design processing of the mine ventilation system; The remote linkage unit for adjusting the air volume of the ventilator is used to dynamically adjust the air volume by changing the motor frequency or the angle of the fan blades through remote linkage based on the results of the ventilation network solution and the results of the decision-making design processing of the mine ventilation system.

2. The intelligent decision-making and remote linkage system based on mine ventilation system according to claim 1 is characterized in that: The ventilation parameter comprehensive perception and measurement module includes: A ventilation structure pressure difference excess air volume monitoring unit, which is used to monitor through a pressure difference sensor based on the ventilation parameters and the communication ring network, calculate the local wind resistance, perform correction through numerical simulation based on the calculation result of the local wind resistance, obtain the ventilation structure wind resistance value, and obtain the ventilation structure excess air volume monitoring parameter based on the inversion of the ventilation structure wind resistance value; The full-section accurate wind measurement parameter measurement unit is used to install ultrasonic and transmitting sensors in the wind measurement tunnel for synchronous measurement based on the ventilation parameters and the communication ring network through the ultrasonic time difference method and decoupling algorithm to obtain the full-section accurate wind measurement parameters.

3. A method for intelligent decision-making and remote linkage based on a mine ventilation system, applied to a system for intelligent decision-making and remote linkage based on a mine ventilation system as described in any one of claims 1-2, characterized in that: include: Collect ventilation parameters to be tested and establish a communication ring network; Based on the ventilation parameters and the communication ring network, a comprehensive sensing measurement of the ventilation parameters is performed to obtain ventilation route resistance monitoring parameters, ventilation structure pressure difference excess air volume monitoring parameters and full-section precise wind measurement parameters; Based on the ventilation route resistance monitoring parameters, ventilation structure pressure difference and excess air volume monitoring parameters and full-section precise wind measurement parameters, a ventilation network solution model is constructed to perform ventilation network solution; The steps of constructing the ventilation network solution model include: S1. Based on the measurement of the obtained ventilation parameters, three parameters are obtained, namely, ventilation route resistance monitoring, ventilation structure pressure difference over-air volume monitoring, and full-section accurate wind measurement. The parameters are preprocessed by heat-flow coupling algorithm and numerical simulation; S2. Based on the results of the data preprocessing, fast reading of heterogeneous monitoring data is achieved through database snapshot technology and file exchange technology; S3. Effectively filter the heterogeneous monitoring data by time series analysis to eliminate conflicts in the internal monitoring data of the ventilation network and realize the ventilation network solution; The decision-making design process includes: Auxiliary decision-making for adjustment scheme, building database of ventilation dynamic performance curve, auxiliary decision-making for main fan air volume adjustment, auxiliary decision-making for local fan air volume adjustment; The adjustment scheme assists decision making, and is used to calculate the required air volume and provide a power consumption adjustment scheme for a specified air demand point based on the result of the ventilation network solution; The ventilation dynamic performance curve database is used to establish a relationship model between individual characteristic curves and rotation speed, blade angle and frequency based on the ventilator performance test, and obtain a ventilator performance database; The main fan air volume adjustment auxiliary decision is used to assist in deciding the main fan operating frequency or blade angle based on the calculation of the required air volume and the fan performance database; The local ventilator air volume adjustment auxiliary decision is used to assist in deciding the local ventilator operating frequency based on the calculation of the required air volume and the ventilator performance database; Based on the results of the ventilation network solution, decision-making and design processing are performed on the mine ventilation system; The decision-making and design processing of the mine ventilation system based on the result of the ventilation network solution includes: Based on the results of the ventilation network solution, the required air volume is calculated and a power consumption adjustment scheme for the specified air demand point is provided; Based on the fan performance test, the relationship model between individual characteristic curve and speed, blade angle and frequency is established to obtain the fan performance data; Based on the calculation of the required air volume and the fan performance data, assist in deciding the operating frequency or blade angle of the main fan; Based on the calculation of the required air volume and the ventilator performance data, assist in deciding the operating frequency of the local ventilator; Based on the results of the ventilation network solution and the results of the decision-making design processing of the mine ventilation system, remote linkage of automatic dampers, wind window intelligent control and ventilator intelligent control is performed; The remote linkage of automatic damper, wind window intelligent control and ventilator intelligent control based on the result of the ventilation network solution and the result of the decision-making design processing of the mine ventilation system includes: Based on the results of the ventilation network solution and the results of the decision-making design processing of the mine ventilation system, the damper system supporting remote control is switched on and off, and the opening of the adjustable damper and wind window supporting remote control is adjusted; Based on the results of the ventilation network solution and the results of the decision-making design processing of the mine ventilation system, dynamic adjustment of the air volume is achieved by remotely linking and changing the motor frequency or the fan blade angle.

4. The method for intelligent decision-making and remote linkage based on mine ventilation system according to claim 3 is characterized in that: The measurement of the ventilation structure pressure difference and air volume monitoring parameters includes: Based on the ventilation parameters and the communication ring network, monitoring is performed through a pressure difference sensor to calculate the local wind resistance. Based on the calculation result of the local wind resistance, correction is performed through numerical simulation to obtain the wind resistance value of the ventilation structure. Based on the inversion of the wind resistance value of the ventilation structure, the airflow rate of the ventilation structure is obtained.

5. The method for intelligent decision-making and remote linkage based on mine ventilation system according to claim 3 is characterized in that: The measurement of the full-section accurate wind measurement parameters includes: Based on the ventilation parameters and the communication ring network, ultrasonic time difference method and decoupling algorithm are used to install ultrasonic and transmitting sensors in the wind measurement tunnel for synchronous measurement to obtain accurate wind measurement parameters of the entire section.

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