CN115438920A

CN115438920A - CPS intelligent mine modeling system and management method

Info

Publication number: CN115438920A
Application number: CN202210983420.0A
Authority: CN
Inventors: 陶伟忠; 杨娟利; 王妙云; 胡小刚; 任雷平; 刘朝; 张云泰; 贺海波
Original assignee: China Coal Industry Group Information Technology Co ltd
Current assignee: China Coal Industry Group Information Technology Co ltd
Priority date: 2022-08-16
Filing date: 2022-08-16
Publication date: 2022-12-06

Abstract

The utility model discloses a CPS intelligent mine modeling system and a management method, wherein a data processing device in the system collects mine global data, extracts the mine global data, and establishes a class, an object and a connection relation based on the class and the object; the modeling device is used for constructing a digital twin model of the intelligent mine by combining material flow, information flow, energy flow and an equilibrium equation based on mine global data and a connection relation, wherein the digital twin model comprises a material flow model, an information flow model and an energy flow model; the control device acquires the management demand information, generates an application model by using the digital twin model according to the management demand information, acquires real-time mine data corresponding to the management demand information, inputs the real-time mine data into the application model, and outputs a response result aiming at the management demand information so as to realize the management of the mine. According to the system disclosed by the invention, the mine can be comprehensively managed.

Description

CPS intelligent mine modeling system and management method

Technical Field

The disclosure relates to the field of coal mine digital mine construction, in particular to a CPS intelligent mine modeling system and a management method.

Background

With the development of mining industry development, intelligent mines are gradually paid attention by research and development personnel of coal enterprises in order to better perform mine management, efficient mining, safe production and the like. The intelligent mine can improve the industrial level, the innovation capability and the quality benefit, is a necessary way for the development of coal enterprises, and promotes the mine construction of China to move forward to the safe, efficient, economic, green and sustainable development directions. Currently, in the key period of development and construction of intelligent mines, a modeling technology of an intelligent mine capable of reflecting real mine scenes more comprehensively, accurately and efficiently is urgently needed.

Disclosure of Invention

The present disclosure is directed to solving, at least in part, one of the technical problems in the related art. Therefore, one purpose of the present disclosure is to provide a CPS intelligent mine modeling system, which mainly aims to realize the comprehensive management of the mine.

The second purpose of the disclosure is to provide a CPS intelligent mine management method.

In order to achieve the above object, an embodiment of a first aspect of the present disclosure provides a CPS intelligent mine modeling system, including a data processing device, a modeling device, and a control device;

the data processing device is used for acquiring mine global data, extracting the mine global data and establishing a class, an object and a connection relation based on the class and the object;

the modeling device is used for constructing a digital twin model of the intelligent mine by combining material flow, information flow, energy flow and a balance equation based on the mine global data and the connection relation, and the digital twin model comprises a material flow model, an information flow model and an energy flow model;

the control device is used for acquiring management demand information, generating an application model by using the digital twin model according to the management demand information, acquiring real-time mine data corresponding to the management demand information, inputting the real-time mine data into the application model, and outputting a response result aiming at the management demand information so as to realize management of the mine.

In one embodiment of the present disclosure, the mine global data includes personnel data, equipment data, process data, production data, consumption data, safety data, operational data, and environmental data involved under a minefield, a strip mine, a coal preparation plant; the classes comprise personnel classes, equipment classes and environment classes; the class is the collection of the objects, and the connection relationship comprises the connection relationship between the classes and the connection relationship between the objects.

In an embodiment of the present disclosure, the data processing apparatus is specifically configured to: extracting the mine global data, dividing the mine global data into different classes, and further obtaining objects in each class; for each class, combining one direction of material flow, information flow and energy flow to obtain the attribute of the class and the time-space function of each object; and determining the connection relation between the classes and the connection relation between the objects based on the attributes of the classes.

In an embodiment of the present disclosure, the modeling apparatus is specifically configured to: taking an object of a device class as a node or an object of a personnel class as a node, and combining a connection relation, an information flow, a time-space function of each node and a balance equation to construct an information flow model; taking an object of the equipment class as a node, and constructing a mass flow model by combining a connection relation, a material flow, a time-space function and a balance equation of each node; taking an object of the equipment class as a node, and combining a connection relation, the energy flow, a time-space function of each node and a balance equation to construct an energy flow model; and inputting the data of the corresponding class in the mine global data into a material flow model, an information flow model and an energy flow model for model parameter optimization, thereby obtaining a digital twin model meeting the requirements.

In an embodiment of the present disclosure, the modeling apparatus is further configured to: the digital twin model further comprises a three-dimensional geographic environment model, the environment data comprises geographic environment and production environment data, and the three-dimensional geographic environment model is constructed and obtained based on well working conditions, open mines and geographic environment and production environment data of a coal preparation plant.

In one embodiment of the present disclosure, the management requirement information includes at least one requirement of virtual-real synchronization, event prediction and early warning, comprehensive scanning, data validation, reason tracing, data deduction, and collaborative analysis.

In an embodiment of the present disclosure, the control device is specifically configured to: the management requirement information comprises virtual and real synchronization requirements, and the application model comprises a synchronization application model; and according to the virtual-real synchronization requirements, generating the synchronization application model by using the material flow model, the information flow model, the energy flow model and the three-dimensional geographic environment model, acquiring all real-time mine data, inputting the real-time mine data into the synchronization application model, and outputting action and position change results of all equipment and personnel so as to realize three-dimensional synchronization monitoring of mine operation.

In order to achieve the above object, a second aspect embodiment of the present disclosure further provides a CPS intelligent mine management method based on the CPS intelligent mine modeling system in any one of the above embodiments, including:

collecting mine global data, extracting the mine global data, and establishing a class, an object and a connection relation based on the class and the object;

constructing a digital twin model of the intelligent mine by combining material flow, information flow, energy flow and a balance equation based on the mine global data and the connection relation, wherein the digital twin model comprises a material flow model, an information flow model and an energy flow model;

acquiring management demand information, generating an application model by using the digital twin model according to the management demand information, acquiring real-time mine data corresponding to the management demand information, inputting the real-time mine data into the application model, and outputting a response result aiming at the management demand information so as to realize management of mines.

In an embodiment of the present disclosure, the extracting the mine global data, and establishing a class, an object, and a connection relationship based on the class and the object includes: extracting the mine global data, dividing the mine global data into different classes, and further obtaining objects in each class; aiming at each class, combining one direction of material flow, information flow and energy flow to obtain the attribute of the class and the time-space function of each object; and determining the connection relation between the classes and the connection relation between the objects based on the attributes of the classes.

In one embodiment of the present disclosure, the digital twin model further comprises a three-dimensional geographic environment model; and constructing and obtaining the three-dimensional geographic environment model based on the well working condition, the open pit mine, the geographic environment of the coal preparation plant and the production environment data.

In one or more embodiments of the disclosure, the CPS intelligent mine modeling system comprises a data processing device, a modeling device and a control device, wherein the data processing device acquires mine global data, extracts the mine global data, and establishes a class, an object and a connection relation based on the class and the object; the modeling device is used for constructing a digital twin model of the intelligent mine by combining material flow, information flow, energy flow and a balance equation based on mine global data and a connection relation, wherein the digital twin model comprises a material flow model, an information flow model and an energy flow model; the control device acquires the management demand information, generates an application model by using the digital twin model according to the management demand information, acquires real-time mine data corresponding to the management demand information, inputs the real-time mine data into the application model, and outputs a response result aiming at the management demand information so as to realize management of the mine. Under the condition, the mine global data, the connection relation based on the class and the object, the material flow, the information flow, the energy flow and the balance equation are comprehensively utilized to obtain a digital twin model of the intelligent mine, then the real-time mine data and the application model are obtained according to the management demand information, and the real-time mine data are input into the application model to obtain a response result aiming at the management demand information, so that the comprehensive management of the mine can be realized.

Additional aspects and advantages of the disclosure will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the disclosure.

Drawings

The foregoing and/or additional aspects and advantages of the present disclosure will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:

FIG. 1 illustrates a block diagram of a CPS intelligent mine modeling system provided by an embodiment of the present disclosure;

FIG. 2 is a schematic diagram illustrating a part of a coal preparation plant personnel organization architecture provided by an embodiment of the disclosure;

FIG. 3 is a schematic diagram illustrating a partial device architecture provided by an embodiment of the present disclosure;

FIG. 4 illustrates a schematic diagram of a partial coal flow model provided by an embodiment of the present disclosure;

FIG. 5 illustrates a partial current model schematic provided by an embodiment of the present disclosure;

FIG. 6 illustrates a schematic diagram of a partial three-dimensional digital twin model provided by an embodiment of the present disclosure;

fig. 7 shows a flow chart of a CPS intelligent mine management method provided by the embodiment of the disclosure.

Detailed Description

Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the exemplary embodiments below are not intended to represent all implementations consistent with embodiments of the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the disclosed embodiments, as detailed in the appended claims.

In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present disclosure. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Moreover, various embodiments or examples and features of various embodiments or examples described in this specification can be combined and combined by one skilled in the art without being mutually inconsistent.

Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the feature. In the description of the present disclosure, "a plurality" means at least two, e.g., two, three, etc., unless explicitly specifically limited otherwise. It should also be understood that the term "and/or" as used in this disclosure refers to and encompasses any and all possible combinations of one or more of the associated listed items.

Reference will now be made in detail to the embodiments of the present disclosure, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the drawings are exemplary and intended to be illustrative of the present disclosure, and should not be construed as limiting the present disclosure.

The invention relates to a CPS intelligent mine modeling system and a management method, and mainly aims to realize comprehensive management of a mine.

In a first embodiment, fig. 1 shows a block diagram of a CPS intelligent mine modeling system provided by an embodiment of the disclosure. As shown in fig. 1, the CPS intelligent mine modeling system 10 includes a data processing device 11, a modeling device 12, and a control device 13.

In this embodiment, the data processing device 11 is configured to collect mine global data, extract the mine global data, and establish a class, an object, and a connection relationship based on the class and the object. The environmental data includes geographic environment and production environment data.

In this embodiment, the mine global data includes personnel data, equipment data, process data, production data, consumption data, safety data, operation data and environmental data related to the mine, open-pit mine and coal preparation plant; the classes comprise personnel classes, equipment classes and environment classes; a class is a collection of objects, and a connection relationship (i.e., a relation) includes a connection relationship between classes, and a connection relationship between objects and objects.

In the embodiment, the data processing device 11 performs extraction, storage and structure governance on the mine global data by adopting an object-oriented idea mode, wherein the data structure governance establishes classes, objects and relations according to the object-oriented idea. Specifically, the data processing device 11 is specifically configured to: extracting the mine global data, dividing the mine global data into different classes, and further obtaining objects in each class; aiming at each class, combining one direction of material flow, information flow and energy flow to obtain the attribute of the class and the time-space function of each object; and determining the connection relation between the classes and the connection relation between the objects based on the attributes of the classes. The object-oriented idea is adopted when the mine global data is extracted.

In this embodiment, the classes are sets of objects having the same features and functions, and the objects are entity objects established on the basis of establishing entity information extraction classes in a mine, an open pit mine and a coal preparation plant. Contacts are connections between classes/objects. The connection relationship is mainly based on material flow, information flow and energy flow (such as coal flow, water flow, wind flow, electric current, control flow, personnel organization flow and the like) under a well industrial mine, an open pit mine, a coal preparation plant and the like, and the connection relationship between the classes/objects is established.

Wherein for class-to-class connection relationships: the classes and the relations among the classes mainly comprise inheritance, implementation, dependency, association, aggregation and combination. Inheritance means that one class inherits the function of another class and can add its own new function capability; dependency means that one class a is used to another class b, and the usage relationship is accidental, temporary and very weak, but the change of the class b can affect the class a; association refers to a strong dependency relationship at the semantic level between two classes; aggregation is a special case of associative relations, which is embodied by the whole and partial relations. The whole and the part are separable at this time, they can have their own life cycles, and the part can belong to a plurality of whole objects or can be shared by a plurality of whole objects. For example, the motors of the respective devices can be described by adopting a polymerization relation; combinations are also a special case of associative relationships that are stronger than aggregations, also known as strong aggregations. The whole life cycle is ended, namely the end of the partial life cycle. Such as the human and brain.

Wherein for a connection relationship between objects: the connection relation between the objects mainly comprises a dependency relation, an association relation, an aggregation relation, a combination relation, a generalization relation and an implementation relation. The dependency between objects describes a temporary relationship, such as person and device; the relationship between objects describes a relatively fixed relationship, such as the relationship between the downstream tape machines of the scraper machines; an object aggregation relationship describes a relationship of whole and part, emphasizing that part can exist apart from whole; the object combination describes a relationship of whole and part, and the emphasized part can not exist separately from the whole; the objects are generalized, solid line hollow triangle arrows, describing a special and general relationship, such as human being and scientist, which is one of human being; an object implementation describes a relationship, such as a tape machine having transport capabilities.

In some embodiments, corresponding flows or architectural relationships of the coal flows, water flows, wind flows, electrical currents, control flows, personnel organization flows, etc. under the well mines, strip mines, coal preparation plants are stored in the data processing device 11.

In some embodiments, the personnel, equipment, and environment classes may be established in conjunction with entity information and personnel organizational structure relationships within a well mine, a strip mine, a coal preparation plant, and the like. Wherein the entity information and the human organizational structure relationship are stored in the data processing device 11. The entity information comprises personnel entity information, equipment entity information and environment entity information.

In some embodiments, the personnel class, the equipment class and the environment class are all large classes, and the personnel class, the equipment class and the environment class can be further classified. For example, for personnel, the personnel can be classified into production personnel, overhaul personnel, management personnel and the like according to different working properties of the personnel. Wherein, the classification can be continued after different classes are classified according to the working property of the personnel. For example, the manager classes can be further divided according to the personnel organization and architecture relationship and the personnel role of the mine, the open pit mine and the coal preparation plant.

In some embodiments, fig. 2 shows a schematic diagram of a part of coal preparation plant personnel organizational structure provided by an embodiment of the present disclosure, as shown in fig. 2, the personnel entity information includes a plant leader, an electromechanical manager, a production manager, a security manager, a service person, an electromechanical person, a production person, a scheduling person, and an assistant person, and a personnel organizational structure relationship is that a subordinate level of the plant leader is the electromechanical manager, the production manager, and the security manager; the lower level of the electromechanical manager is maintainers and electromechanical personnel; the lower level of the production manager is production personnel and scheduling personnel; the subordinate level of the security manager is an assistant. It should be noted that the human entity information and human organizational architecture relationship shown in fig. 2 are only examples.

Taking a person class as an example, a method for obtaining attributes of the person class and the person class (i.e. a time-space function of each object) by combining one direction of a material flow, an information flow and an energy flow for the person class specifically includes:

the producer can establish producer attributes and methods according to producers related to the process of circulating production flow of coal in miners, strip mines and coal preparation plants, wherein the attributes of the producer include name, gender, on-duty time, personnel's academic calendar, job level, professional skill certificate and personnel position information; a method for establishing a time-space function as a producer class;

the maintainers can establish maintainer attributes and methods according to maintainers involved in maintenance work of a mine, a strip mine and a coal preparation plant, wherein the maintainer attributes comprise names, sexes, on-duty time, staff academic records, job grades, professional skill certificates, maintenance capacity, maintenance quality and staff position information; establishing a time-space function as a method for maintainers;

the manager class can construct manager class attributes and methods according to managers supported in production, overhaul, process and factories, wherein the manager class attributes comprise names, sexes, on-duty time, personnel academic records, job levels, professional skill certificates, management capacity and personnel position information; establishing a time-space function as a method for managing personnel;

the producer class can establish producer class attributes and methods according to producers involved in the industrial and mining, open-pit mines and coal preparation plant coal circulation production flow process. The maintainer class establishes maintainer class attributes and methods according to maintainers involved in overhaul work of a mine industrial mine, a strip mine and a coal preparation plant.

The method in the personnel class mainly establishes a spatiotemporal function (namely a spatiotemporal function) for each object according to the position of the geographic information of the personnel so as to realize the establishment of the spatiotemporal function of time, position and state for the entity object. The running tracks of all objects can be displayed in real time in a three-dimensional geographical position space through a space-time function. Taking the shearer driver in the class of people as an example, the shearer driver's spatio-temporal function can be expressed as y1= f (Loc, tim, sta, bas). Where y1 represents the corresponding person class, loc represents the position, tim represents the time, sta represents the status, and Bas represents the basic attribute (which may be simply referred to as an attribute).

Taking the personnel class under the scene of the fully mechanized mining face of the underground mine as an example, the data processing device 11 adopts the object-oriented idea mode to extract, store and structurally treat the mine global data, and specifically comprises:

the production personnel refer to direct production personnel involved in the production process of the fully mechanized mining face, such as coal mining drivers, scaffolding workers, pushing and sliding workers, coal cleaning workers and advanced support workers, and can be specifically divided into coal mining machine drivers, scaffolding workers, post workers and auxiliary workers; attributes of the direct production personnel category include name, gender, on-duty time, personnel's academic history, job level, professional skill certificates, personnel location information. On the basis of direct production personnel, various types of personnel objects are established, such as a coal mining machine driver object, a scaffolding object, a post work object and an auxiliary work object. The attributes of the objects are established, such as the attribute of the shearer driver object inherits the attribute of the direct production personnel class and comprises the attribute of the shearer driver operation efficiency. The property of the scaffolding object directly inherits the property of the personnel and comprises the support efficiency property, such as five protection effect evaluation factors of support effect, top connection effect, bottom lifting effect, whether to fall over and whether to break down. The post work object inherits the attribute of the direct production personnel class and contains the fault handling capability attribute of the post work book. The auxiliary object inherits the attribute of the direct production personnel class;

the maintainers refer to the staff who directly participate in maintenance in the maintenance class and are directly defined as maintainer classes; the service personnel category attributes include name, gender, on-duty time, personnel's academic history, job level, professional skill certificates, service capability, service quality, and personnel location information. The specific maintainer object directly inherits the attribute of the maintainer;

and establishing fully-mechanized coal mining face managers by combining the personnel organization architecture relationship of the underground and mine fully-mechanized coal mining face. The management personnel are personnel for commanding production and maintenance on the fully mechanized coal mining face, and are divided into a production management personnel class and a maintenance management personnel class according to different management contents, and generally comprise a fully mechanized coal mining team production team leader, a production team minor team leader, a technician, a maintenance team leader, a maintenance minor team leader and the like; the manager category attributes comprise name, gender, on-duty time, personnel study, job level, professional skill certificate, production management capability and personnel position information; the maintenance manager type attributes comprise name, gender, on-duty time, personnel study, job level, professional skill card and maintenance management capability;

on the basis of the personnel entity object, the production organization relation and the personnel organization architecture relation are combined, the classes and the objects of a fully mechanized mining face manager-a production manager, a maintenance manager-a producer and a maintenance person are established on a fully mechanized mining face, the class attributes are obtained, and a space-time function is established for each object, so that the operation track of each object can be displayed in real time in a three-dimensional geographic position space in the subsequent implementation.

In some embodiments, the device classes are established in connection with well conditions, surface mines, coal preparation plant device associations, geographic location information, device architectures, and the like. The device architecture is typically stored in the data processing apparatus 11 in a tree-like manner.

In some embodiments, fig. 3 illustrates a partial device architecture diagram provided by embodiments of the present disclosure. As shown in fig. 3, the device entity information includes a device I1, a device I2, and a device I3, the environment entity information includes a geographic area I, and fig. 3 divides the device I1, the device I2, and the device I3 at the geographic area I according to a hierarchy of geographic area-device-location-component, each device includes 2 locations (location 1 and portion 2), and each portion includes a corresponding number of components. It should be noted that the geographic area shown in fig. 3 and the number of devices, portions, and components in the geographic area are merely examples.

Taking the device class as an example, the method for obtaining the attribute of the device class and the device class by combining one direction of the material flow, the information flow and the energy flow aiming at the device class specifically comprises the following steps:

dividing the geographic area according to the actual production area by taking the actual geographic position and the field number as the standard;

the equipment layer is mainly used for storing all key equipment in a geographic area I, and defining equipment type attributes and methods according to an object-oriented idea, wherein the attributes comprise equipment ledgers, maintenance history, fault matrixes and dynamic information (specific equipment position information, current, voltage, temperature and the like), and the methods comprise space-time geographic position functions and process operation functions;

the site layer mainly separates the device into different sites, and identifies each site. Attributes and methods are established for each part class. Attributes include site ledgers, maintenance history, fault matrices, dynamic information (current, voltage, temperature, etc.);

the component layer mainly refines the parts to form different components, identifies the components, and establishes component type attributes and methods. Attributes include component ledgers, maintenance history, fault matrices, dynamic information (current, voltage, temperature, etc.);

according to the device architecture relationship, device objects, part objects and component objects are established, comprehensive analysis is carried out according to component types, and parts and components of related devices or similar devices with consistent attributes are analyzed in a unified mode, so that the problem that multiple types of devices on site are modeled respectively can be solved, and the generalization capability of a subsequent model is improved.

On the basis of the device object, the part object, and the component object, a spatio-temporal function is established for a single object, and for example, the spatio-temporal function of the device A1 may be expressed as y2= f (Loc, tim, sta, bas). Where y2 denotes the device A1, loc denotes the location, tim denotes the time, sta denotes the status, and Bas denotes the basic information function (i.e., basic attribute).

Taking the device class as an example, the data processing device 11 adopts an object-oriented idea mode to extract, store and structurally treat the mine global data, and specifically includes:

acquiring geographic position information and a mine-area-equipment-part-component equipment framework, wherein the mine-area is based on the actual geographic position of a mine and the field number, and a mine-area hierarchy is built;

in the equipment layer, according to an object-oriented idea, equipment type attributes are defined, wherein the equipment type attributes comprise equipment accounts, maintenance history, fault matrixes and dynamic information (specific position information, current, voltage, temperature and the like of the equipment), and the equipment type/object is established by combining the moving and reverse characteristics of the coal industry and the uniqueness of the equipment. Taking an equipment layer in a scene of a fully mechanized mining face of an underground mine as an example, a coal cutter class, a scraper belt conveyor class, a crusher class, a reversed loader class, a belt conveyor class, a hydraulic support class and a pump station class are established. The coal mining machine inherits all the attributes of the equipment and contains the coal quantity information attribute. The scraper conveyor class inherits all the attributes of the equipment class, the crusher class inherits all the attributes of the equipment class, the reversed loader class inherits all the attributes of the equipment class, and the belt conveyor class inherits all the attributes of the equipment class, and contains the coal quantity information attribute. The hydraulic support class inherits all the attributes of the equipment class, and the pump station class inherits all the attributes of the equipment class;

at the site level, the device may be divided into different sites and classes/objects may be established for each site. The coal mining machine equipment can be disassembled into a cutting part, a loading part, a traction part, a motor part, an operation control system and an auxiliary device part. The scraper belt conveyor can be divided into a nose, a middle part and a tail part. The crusher equipment can be divided into a crushing part, a transmission part, a sorting part and an automatic control part. The reversed loader equipment can be divided into a main body and a tail part. The belt conveyor equipment consists of a conveying belt part, a carrier roller part, a tensioning mechanism part and a braking mechanism part. The location class attribute may inherit the device class attribute.

In the part layer, a cutting part in coal mining machine equipment comprises a working mechanism and a transmission device thereof, a traction part comprises a traction mechanism and a traction driving device, and two ends of a motor extend out of a shaft and respectively drive the cutting part and the traction part. The coal charging part comprises a coal charging mechanism, a coal charging reduction box and a coal charging motor. The head, the middle part and the tail part of the scraper conveyor equipment mainly comprise a motor, a speed reducer, a hydraulic coupler, a low-speed coupler, a head wheel set, a tail wheel set, a chain, a connecting ring and scraper components. The crushing part, the transmission part, the sorting part and the automatic control part of the crusher equipment mainly comprise a motor, a speed reducer, a hydraulic coupler, a centralized lubricating system, a left gear roller assembly (driving) and a right gear roller assembly (driven) part. The main body and the tail part of the reversed loader mainly comprise a machine head transmission part, a bridge groove, a connecting groove, an adjusting groove, a skylight groove, a discharging skylight groove, a convex groove, a chain stopper and other parts. The belt conveyer includes conveyer belt part, roller part, tension mechanism part and brake mechanism part, and the brake mechanism part consists of motor, speed reducer, hydraulic coupler, low speed coupler, conveyer belt, driving roller, tail roller, head direction changing roller and tail direction changing roller. The hydraulic support equipment components comprise a push rod, a shield beam, a top beam, a telescopic beam, a tail beam, a side guard plate, a front beam, a side guard plate, a plug board, a front connecting rod, a rear connecting rod, a small four-connecting rod, a base and the like. The pump station equipment component comprises a pump device, a valve group, a manifold group, an oil tank and an electric box. The component class property may inherit the site class property.

In some embodiments, an environmental class is established in connection with well conditions, surface mines, coal preparation plant geographical environment, and production environment content. The environment is, for example, a production safety index environment, and the production safety index environment mainly includes safety data indexes in the production environment, which generally include dust, noise, methane, carbon monoxide (CO), and the like. Taking the fully mechanized mining face as an example, the attributes of the production safety environment are GIS geographical position, gas, rock burst, carbon monoxide (CO) and carbon dioxide (CO) ₂ ) Fire, underground water, dust, air quantity, air pressure, temperature, humidity and noise.

In this embodiment, the data processing device 11 may implement high-performance redundant distributed uniform data acquisition according to a uniform data standard system of a data standard, an acquisition standard, a management standard, and the like, and determine the relation of classes/objects in combination with a personnel organization architecture relationship or an equipment architecture, and the like, so as to provide a data basis for the subsequent modeling of the modeling device 12. Under the condition, the data processing device 11 mainly establishes personnel, equipment and environment types according to actual completeness data contents of a mine, a strip mine and a coal preparation plant, establishes a data hierarchical relationship according to class attributes, entity objects and entity relations, and realizes high-performance redundant distributed unified data acquisition and construction by combining a unified data standard system of a data standard, an acquisition standard and a management standard to form a complete-level data set.

In this embodiment, the modeling device 12 is configured to construct a digital twin model of the smart mine by combining the material flow, the information flow, the energy flow and the balance equation based on the mine global data and the connection relationship, where the digital twin model includes the material flow model, the information flow model and the energy flow model.

Specifically, in this embodiment, the modeling apparatus 12 first builds a digital twin model of the intelligent mine by using a connection relationship and combining the material flow, the information flow, the energy flow and the balance equation, and then inputs the mine global data into the built digital twin model to obtain the digital twin model meeting the requirements.

In some embodiments, the modeling apparatus 12 is specifically configured to: the method comprises the steps that an object of a device class is used as a node or an object of a person class is used as a node, and an information flow model is built by combining a connection relation, information flow and a time-space function and a balance equation of each node; taking an object of the equipment class as a node, and constructing a mass flow model by combining a connection relation, a material flow, a time-space function and a balance equation of each node; taking an object of the equipment class as a node, and combining a connection relation, the energy flow, a time-space function of each node and a balance equation to construct an energy flow model; and inputting the corresponding data in the mine global data into a material flow model, an information flow model and an energy flow model for model parameter optimization, thereby obtaining a digital twin model meeting the requirements. Under the condition, a material flow model, an information flow model and an energy flow model are established according to space-time information, object information and contact information, and then parameters in the established material flow model, information flow model and energy flow model are optimized by utilizing mine global data and combining data processing such as big data analysis, system identification, machine learning and the like, so that a digital twin model is finally formed. In addition, the digital twin model can be combined with three-dimensional GIS information (three-dimensional geographic information) to construct a three-dimensional digital twin model.

Taking a well industrial mine, a strip mine and a coal preparation plant as examples, analyzing material flows, information flows and energy flows in the well industrial mine, the strip mine and the coal preparation plant, representing the material flows, the information flows and the energy flows in a form of a graph, and forming a material flow model, an information flow model and an energy flow model through logical relations and relations among all information.

The information flow model mainly refers to a production process control model and a personnel organization model which take a network as a carrier in the coal mine production process. The production process control model takes equipment objects as nodes, takes production process flows as directions and is combined with a production mode to establish a production process control flow graph. The personnel organization model takes personnel objects as nodes and an organization structure as a main part to establish a personnel organization chart. Wherein, the production process control flow diagram Ga = { Va Ea } takes key equipment as a node Va, takes transportation equipment involved in a production mode as an edge Ea, and takes the material trend as the direction in the actual production process. The personnel organization graph Gp = { Vp, ep } takes personnel as a node Vp, takes the personnel organization architecture relationship as a side Ep, and takes personnel transmission information as a direction.

The material flow model mainly refers to a coal flow model, a water flow model and an air flow model formed in the mutual transformation and transfer process among materials in the coal production process.

The coal flow model is based on a belt conveyor and a gate valve and is combined with a production process flow to establish a coal flow diagram. The coal flow graph Gc = { Vc, ec } is a coal mining machine A, a scraper machine B, a crusher C, a reversed loader D, a belt conveyor E and other equipment, and a lap joint point (such as a lap joint point Bs, be, ds, de, es and Ee) between the equipment is used as a vertex Vc, vc = { A, bs, be, C, ds, de, es and Ee }, the coal flow transportation direction is a flow direction, and the transportation equipment is an edge Ec, ec = { < A, bs >, < Bs, be >, < Be, C >, < C, ds >, < Ds, de >, < De, es >, < Ee > }.

The water flow model is established by taking a pump station and a switch as nodes and combining a production process flow. The water flow diagram Gw = { Vw, ew } takes a pump station Aw and a switch Bw as nodes Vw, vw = { Aw, bw }, takes the trend of a pipeline and a roadway in a production process as an edge Ew, and takes a wind direction as a direction.

The wind flow model is a wind flow graph established by taking a fan and a switch as nodes and combining a production process flow. The draft diagram Gr = { Vr, er } takes the pressure fan Vr as a node, a channel and a blast pipe in the production process as edges Er, and the direction of the blast direction in the flow process is taken as the direction.

The energy flow model mainly uses the conversion and the transfer of energy in the coal production process, and mainly uses current in a well mining industry, an open pit mine and a coal preparation plant. The current model is a current diagram established by taking the cabinet as a node and combining the line trend. The current diagram Gf = { Vf, ef } is a current network formed by taking the cabinet as a node Vf and taking the current branch and current flow direction as an edge Ef and a direction.

In some embodiments, a coal flow model corresponding to a clean coal processing flow of a main washing system block is described by taking a production process control flow of a coal preparation plant as an example. The coal flow model is as follows:

FIG. 4 illustrates a schematic diagram of a partial coal flow model provided by an embodiment of the present disclosure. As shown in fig. 4, in the coal flow model, the direction is from 201 belt machine to 202 scraper machine, then to 203 screen machine, 204 screen machine and 241 screen machine. Oversize products of a 203-screen machine enter 205 shallow grooves, undersize products of the 203-screen machine enter a coal mud barrel, and when coal mud in the coal mud barrel leaks, the coal mud needs to be thrown into the 203-screen machine. Oversize products of the 204 screen machine enter 206 shallow grooves, undersize products of the 204 screen machine enter a coal mud barrel, and when coal mud in the coal mud barrel leaks, the coal mud needs to be pumped into the 204 screen machine. Oversize products of the 241 screen machine enter 242 shallow grooves, undersize products of the 241 screen machine enter a coal mud barrel, and when coal slime in the coal mud barrel leaks, the coal slime needs to be driven into the 241 screen machine. 205 shallow groove undersize (i.e. sediment) enters 246 the medium removing sieve, and 205 shallow groove oversize (i.e. floating) enters 207 the medium removing sieve. The 206 shallow groove undersize enters 237 a medium removing sieve, and the 206 shallow groove oversize enters 208 a medium removing sieve. 242 shallow groove undersize enters 236 de-medium screen and 242 shallow groove oversize enters 243 de-medium screen. 207 medium removal screen floe, 208 medium removal screen floe, 243 medium removal screen floe enter 226 scraper, pass 217 shallow trough, pass 218 medium coal medium removal screen, 261 belt conveyor and crusher, finally enter upper bin. 246 medium removal screening sediments, 237 medium removal screening sediments and 236 medium removal screening sediments enter a 2128 scraper conveyor, pass through a 220 medium coal medium removal screen and enter a waste rock bin through a 701 waste rock adhesive tape machine. It should be noted that the coal flow model in fig. 4 is only a schematic diagram.

In some embodiments, a current model corresponding to a coal preparation plant is taken as an example for description. The current model is as follows:

fig. 5 shows a schematic diagram of a partial current model provided by an embodiment of the present disclosure. As shown in fig. 5, in the current model, the direction is from the current at 10KV, and then the current is shunted to the screening distribution room, the lump coal distribution room, the slack coal distribution room, the product bin distribution room, the raw coal bin distribution room, the loading station distribution room, and the like. 660V, 380V and 220V are graded out from each distribution room to respective distribution cabinet, each distribution cabinet is connected with corresponding number of devices or networks, and current is graded into each device or network through the distribution cabinets. The number of devices is, for example, N. It should be noted that the current model shown in fig. 5 is only a schematic diagram.

In some embodiments, the modeling means 12 is further configured to: the method comprises the steps of fusing and displaying a material flow model, an information flow model and an energy flow model on the basis of a three-dimensional space, displaying in a graph mode, combining common nodes, calculating parameters on the nodes by using different color codes of the material flow, the information flow and the energy flow and combining object attributes and an object method through a balance relation (namely a balance equation) between the nodes, and determining the values of the attributes. For example, if a water flow model and a balance relation are combined, the size and the accuracy of the water discharge can be judged. The total water quantity = (pump station) coal cutter spray + groundwater-displacement.

FIG. 6 illustrates a schematic diagram of a partial three-dimensional digital twin model provided by an embodiment of the present disclosure. As shown in fig. 6, the object 1, the object 2, the object 3, the object 4, the object 5, the object 7, and the object 8 construct an energy flow model by energy flow; the object 2, the object 9, the object 6 and the object 7 construct an information flow model through information flow; object 3, object 6 and object 8 construct an effluent mass flow model by mass flow; the common nodes (i.e., common objects) in the three models are combined, parameters on each node are calculated by combining object attributes and object methods through the balance relationship between the nodes, and the values of the attributes are determined, so that the three-dimensional digital twin model shown in fig. 6 is obtained. It should be noted that the three-dimensional digital twin model shown in fig. 6 is only a schematic diagram.

In the embodiment, the three-dimensional digital twinning model is a model obtained by relying on three-dimensional digital twinning based on a CPS model system.

In some embodiments, the modeling means 12 is further configured to: the digital twin model also comprises a three-dimensional geographic environment model, and the three-dimensional geographic environment model is constructed and obtained based on well working conditions, the geographic environment of the strip mine and the coal preparation plant and production environment data.

In some embodiments, the modeling apparatus 12 builds a three-dimensional GIS geographic environment model in connection with well conditions, open pit mines, coal preparation plant geographic environment, and production environment content. The three-dimensional GIS geographic environment model mainly uses three-dimensional GIS data, establishes a well working condition, strip mine and coal preparation plant data geographic model, and provides a basic environment framework for CPS digital mine model construction.

In this embodiment, the control device 13 is configured to acquire the management demand information, generate an application model using the digital twin model according to the management demand information, acquire real-time mine data corresponding to the management demand information, input the real-time mine data into the application model, and output a response result to the management demand information, thereby implementing management of the mine.

In some embodiments, the management requirement information includes at least one requirement of virtual and real synchronization, event prediction early warning, comprehensive scanning, data validation, reason tracing, data deduction and collaborative analysis. Under the condition, a required application model is obtained by using a data standard system and a full-data-driven hierarchical structured digital twin model, so that various management requirements such as virtual-real synchronization, event prediction early warning, comprehensive scanning, data validation (such as accuracy, reliability and deficiency judgment), reason tracing, data deduction, cooperative analysis and the like in a well industrial mine, a strip mine and a coal preparation plant are met.

In some embodiments, the reliability, accuracy and deficiency of the data in the data processing device 11 by the control device 13 may be determined by comprehensively considering the logical and balance relationships of the data to determine the reliability and accuracy of the collected data according to the object contact and historical data.

In some embodiments, the application model is generated in the control device 13 by using a digital twin model, mainly combining a hierarchical data standard system and a material flow model (coal flow model, water flow model, wind flow model), an information flow model (process control model, personnel organization model) and an energy flow model (current model) in a well mine, a strip mine, a coal preparation plant.

In some embodiments, the control device 13 is specifically configured to: the management requirement information comprises virtual and real synchronization requirements, and the application model comprises a synchronization application model; and generating a synchronous application model by using the material flow model, the information flow model, the energy flow model and the three-dimensional geographic environment model according to virtual-real synchronous requirements, acquiring all real-time mine data, inputting the real-time mine data into the synchronous application model, and outputting action and position change results of all equipment and personnel to realize three-dimensional synchronous monitoring of mine operation. In this case, the full data-driven three-dimensional digital twin synchronization application model is used to achieve virtual-real synchronization of the main scenes, and synchronization of field device actions, actuator actions, environmental changes, device geographic position changes, personnel position changes, device personnel state real-time progress, and three-dimensional display.

In some embodiments, the management requirement information in the control device 13 includes data deduction requirements, and the application model includes a deduction application model. For example, if the existing production process is to be adjusted and switched, a deduction application model generated by the three-dimensional digital twin model can be used for deduction, so that the effect of switching the production process is determined, and a decision maker is helped to make a decision. Taking the coal flow transportation state preview as an example, the current 2 continuous mining access main transportation systems, and if the coal quantity of one continuous mining belt is added, whether the belt can bear the coal quantity or not. And reasonably arranging according to the previewing result. And integrating temperature, vibration, audio and video for comprehensive analysis, determining the fault type and position of the equipment, and realizing the associated collaborative analysis of the equipment.

In some embodiments, the management requirement information in the control device 13 includes event forecast warning requirements and the application models include warning application models. Specifically, based on a CPS model system, an early warning application model is obtained according to an equipment level model, a personnel level model and an environment model so as to carry out accident investigation and hidden danger investigation and realize comprehensive scanning of a mineshaft, an open pit mine and a coal preparation plant. The self-checking and scanning can be carried out according to various forms of events, time, objects, ranges and the like by combining the prior case and the current case. For example, when a current device is abnormal, whether a similar situation exists or not can be inquired by combining the machine account information of the device, so as to prevent in advance. Therefore, the communication of information flow, material flow and energy flow can be opened, and the communication of people, machines, rings and pipes can be realized; and (4) counting and analyzing the service data, and realizing the autonomous identification of unsafe behaviors and abnormal conditions, equipment health diagnosis and video inspection by combining an intelligent algorithm, and realizing the content of prediction and early warning of equipment, personnel and environment.

Taking the device operation state of the belt conveyor as an example, a three-level device structure of the belt conveyor, the belt conveyor components and the belt conveyor parts is established for the belt conveyor. The state analysis of the belt conveyor equipment combines equipment coal flow information, position motor current information, motor vibration information, coal flow direction in process control flow and the belt conveyor building relation, integrates the logical relation of current, motor vibration, coal flow and coal flow, and builds a belt conveyor running state model (namely a belt conveyor early warning application model). And establishing an equipment fault database according to the trend matching of the coal flow and the current magnitude and the motor vibration data, and determining whether the equipment state is abnormal or not according to the characteristic difference between the current equipment vibration data and the fault database and the current magnitude.

In the CPS intelligent mine modeling system, the CPS intelligent mine modeling system comprises a data processing device, a modeling device and a control device, wherein the data processing device is used for acquiring mine global data, extracting the mine global data and establishing a class, an object and a connection relation based on the class and the object; the modeling device is used for constructing a digital twin model of the intelligent mine by combining material flow, information flow, energy flow and a balance equation based on mine global data and a connection relation, wherein the digital twin model comprises a material flow model, an information flow model and an energy flow model; the control device acquires the management demand information, generates an application model by using the digital twin model according to the management demand information, acquires real-time mine data corresponding to the management demand information, inputs the real-time mine data into the application model, and outputs a response result aiming at the management demand information so as to realize management of the mine. Under the condition, the mine global data, the connection relation based on the class and the object, the material flow, the information flow, the energy flow and the balance equation are comprehensively utilized to obtain a digital twin model of the intelligent mine, then the real-time mine data and the application model are obtained according to the management demand information, and the real-time mine data are input into the application model to obtain a response result aiming at the management demand information, so that the mine can be comprehensively managed. In addition, the system disclosed by the invention realizes high-performance redundant distributed uniform data acquisition according to a uniform data standard system of data standards, acquisition standards and management standards by using a data information network at the bottom of people, machines, rings and pipes of a drifting industrial mine, a strip mine and a coal preparation plant. Establishing a data standard system with a hierarchical framework in the form of objects and relations by combining material flows, information flows and energy flows, providing a complete data base, combining three-dimensional GIS information, establishing a coal flow model, a water flow model, an air flow model, a process control model, a personnel organization model and an electric current model by taking the material flows, the information flows and the energy flows as main lines, optimizing parameters in the models by combining a model big data analysis, a system identification and a machine learning multi-algorithm to form a three-dimensional digital twin model, and opening all data model relations for a CPS intelligent mine model; the method is characterized by also combining field needs, carrying out event early warning, comprehensive scanning, accuracy judgment, abnormality identification, reason result tracing and event deduction according to business needs and business current situation analysis on the basis of a data layer and a model layer, solving the problems of filling automation and informatization short boards, supplementing intelligent equipment and intelligent sensing means, providing a basis for the implementation of an integrated control platform, removing a fussy function sub-item menu mode by utilizing a brand-new object picture display framework, and enabling all pictures and function display not to exceed three-level drilling; and (4) quick and convenient curve chart calling. GIS information is fused, and flexible and friendly interface effects and user experience are provided by combining professional users aiming at the aspects of control, service and information.

The following are embodiments of the disclosed method, and for details not disclosed in the embodiments of the disclosed method, reference is made to the embodiments of the disclosed system. The embodiment of the method disclosed by the invention provides a CPS intelligent mine management method. The CPS intelligent mine management method adopts the CPS intelligent mine modeling system of the system embodiment to realize the comprehensive management of the mine.

Fig. 7 shows a flow diagram of a CPS intelligent mine management method provided by the embodiment of the disclosure. As shown in fig. 7, the CPS intelligent mine management method includes:

s11, collecting mine global data, extracting the mine global data, and establishing a class, an object and a connection relation based on the class and the object;

s12, constructing a digital twin model of the intelligent mine by combining material flow, information flow, energy flow and a balance equation based on mine global data and a connection relation, wherein the digital twin model comprises a material flow model, an information flow model and an energy flow model;

and S13, acquiring management demand information, generating an application model by using a digital twin model according to the management demand information, acquiring real-time mine data corresponding to the management demand information, inputting the real-time mine data into the application model, and outputting a response result aiming at the management demand information so as to realize the management of the mine.

Optionally, the mine global data includes personnel data, equipment data, process data, production data, consumption data, safety data, operation data and environmental data related to the mine industrial mine, the strip mine and the coal preparation plant; the classes comprise personnel classes, equipment classes and environment classes; the class is a collection of objects, and the connection relationship comprises a connection relationship between the class and a connection relationship between the objects.

Optionally, the extracting the mine universe data in step S11, and establishing a class, an object, and a connection relationship based on the class and the object, includes: extracting the mine global data, dividing the mine global data into different classes, and further obtaining objects in each class; aiming at each class, combining one direction of material flow, information flow and energy flow to obtain the attribute of the class and the time-space function of each object; and determining the connection relation between the classes and the connection relation between the objects based on the attributes of the classes.

Optionally, in step S12, an object of the device class is used as a node or an object of the personnel class is used as a node, and an information flow model is constructed by combining the connection relationship, the information flow, the time-space function of each node, and the balance equation; taking an object of the equipment class as a node, and constructing a mass flow model by combining a connection relation, a material flow, a time-space function and a balance equation of each node; taking an object of the equipment class as a node, and combining a connection relation, the energy flow, a time-space function of each node and a balance equation to construct an energy flow model; and inputting the corresponding data in the mine global data into a material flow model, an information flow model and an energy flow model for model parameter optimization, thereby obtaining a digital twin model meeting the requirements.

Optionally, the digital twin model in step S12 further includes a three-dimensional geographic environment model; and constructing and obtaining a three-dimensional geographic environment model based on the well working condition, the open pit mine and the geographic environment and production environment data of the coal preparation plant.

Optionally, the management requirement information in step S13 includes at least one requirement of virtual-real synchronization, event prediction and early warning, comprehensive scanning, data validation, reason tracing, data deduction, and collaborative analysis.

Optionally, the control device in step S13 is specifically configured to: the management requirement information comprises virtual and real synchronization requirements, and the application model comprises a synchronization application model; and according to the virtual-real synchronization requirements, generating a synchronization application model by using a material flow model, an information flow model, an energy flow model and a three-dimensional geographic environment model, acquiring all real-time mine data, inputting the real-time mine data into the synchronization application model, and outputting the action and position change results of all equipment and personnel so as to realize three-dimensional synchronization monitoring of mine operation.

It should be noted that the aforementioned explanation of the CPS intelligent mine modeling system embodiment is also applicable to the CPS intelligent mine management method of the embodiment, and is not repeated herein.

The above-mentioned serial numbers of the embodiments of the present disclosure are merely for description and do not represent the merits of the embodiments.

In the CPS intelligent mine management method, mine global data are collected, extracted and the connection relation between classes, objects and the objects is established based on the classes and the objects; constructing a digital twin model of the intelligent mine by combining material flow, information flow, energy flow and a balance equation based on mine global data and a connection relation, wherein the digital twin model comprises a material flow model, an information flow model and an energy flow model; acquiring management demand information, generating an application model by using a digital twin model according to the management demand information, acquiring real-time mine data corresponding to the management demand information, inputting the real-time mine data into the application model, and outputting a response result aiming at the management demand information so as to realize management of the mine. Under the condition, the mine global data, the connection relation based on the class and the object, the material flow, the information flow, the energy flow and the balance equation are comprehensively utilized to obtain a digital twin model of the intelligent mine, then the real-time mine data and the application model are obtained according to the management demand information, and the real-time mine data are input into the application model to obtain a response result aiming at the management demand information, so that the mine can be comprehensively managed. The method disclosed by the invention takes the production characteristics of the industrial mine, the open pit mine and the coal preparation plant, takes people, machines, rings and pipes as research objects, takes the relation among information flow, material flow and energy flow as the relation, and forms twin data taking class/object, space-time and relation as the core. On the basis of twin data based on basic data and a logic model, parameters of the logic model and an application model are optimized by combining big data analysis, system identification and machine learning algorithm, an intelligent algorithm scene is constructed, the reason traceability is thoroughly realized, the scene can be deduced, events can be inquired, personnel positioning can be found, the equipment state can be seen, the environment state can be found, faults can be early warned, events can be predicted, and data can be judged. The method disclosed by the invention provides an idea and technical support for intelligent mine construction, improves the utilization rate of coal enterprise data, and promotes the intelligent construction process of coal enterprises.

It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present disclosure may be executed in parallel, sequentially or in different orders, and the present disclosure is not limited thereto as long as the desired results of the technical aspects of the present disclosure can be achieved.

The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the protection scope of the present disclosure.

Claims

1. A CPS intelligent mine modeling system is characterized by comprising a data processing device, a modeling device and a control device;

the modeling device is used for constructing a digital twin model of the intelligent mine by combining material flow, information flow, energy flow and an equilibrium equation based on the mine global data and the connection relation, and the digital twin model comprises a material flow model, an information flow model and an energy flow model;

2. The CPS intelligent mine modeling system of claim 1, wherein the mine universe data includes personnel data, equipment data, process data, production data, consumption data, security data, operational data, and environmental data involved in a minefield, a strip mine, a coal preparation plant; the classes comprise personnel classes, equipment classes and environment classes; the class is the collection of the objects, and the connection relationship comprises the connection relationship between the classes and the connection relationship between the objects.

3. The CPS intelligent mine modeling system as defined in claim 2, wherein the data processing apparatus is specifically configured to:

extracting the mine global data, dividing the mine global data into different classes, and further obtaining objects in each class;

for each class, combining one direction of material flow, information flow and energy flow to obtain the attribute of the class and the time-space function of each object;

and determining the connection relation between the classes and the connection relation between the objects based on the attributes of the classes.

4. The CPS intelligent mine modeling system of claim 3, wherein the modeling apparatus is specifically configured to:

the method comprises the steps that an object of a device class is used as a node or an object of a person class is used as a node, and an information flow model is built by combining a connection relation, information flow and a time-space function and a balance equation of each node;

taking an object of the equipment class as a node, and constructing a mass flow model by combining a connection relation, a material flow, a time-space function and a balance equation of each node;

taking the object of the equipment class as a node, and combining the connection relation, the energy flow, the time-space function of each node and a balance equation to construct an energy flow model;

and inputting the data of the corresponding class in the mine global data into a material flow model, an information flow model and an energy flow model for model parameter optimization, thereby obtaining a digital twin model meeting the requirements.

5. The CPS intelligent mine modeling system of claim 2 or 4, wherein the modeling apparatus is further configured to:

the digital twin model further comprises a three-dimensional geographic environment model, the environment data comprises geographic environment and production environment data, and the three-dimensional geographic environment model is constructed and obtained based on well working conditions, open mines and the geographic environment and production environment data of the coal preparation plant.

6. The CPS intelligent mine modeling system of claim 5, wherein the management requirement information includes at least one requirement of virtual-real synchronization, event prediction early warning, comprehensive scanning, data validation, reason tracing, data deduction, collaborative analysis.

7. The CPS intelligent mine modeling system of claim 6, wherein the control device is specifically configured to:

the management requirement information comprises virtual and real synchronization requirements, and the application model comprises a synchronization application model;

and generating the synchronous application model by using the material flow model, the information flow model, the energy flow model and the three-dimensional geographic environment model according to the virtual-real synchronous requirements, acquiring all real-time mine data, inputting the real-time mine data into the synchronous application model, and outputting action and position change results of all equipment and personnel so as to realize three-dimensional synchronous monitoring of mine operation.

8. A method of managing a CPS intelligent mine based on the CPS intelligent mine modeling system as claimed in any one of claims 1 to 7, comprising:

the method comprises the steps of collecting mine global data, extracting the mine global data, and establishing a class, an object and a connection relation based on the class and the object;

9. The CPS intelligent mine management method as claimed in claim 8, wherein the extracting the mine universe data, establishing classes, objects and class-and-object-based connection relationships comprises:

10. The CPS intelligent mine management method as claimed in claim 8, wherein the digital twin model further comprises a three-dimensional geographic environment model;

and constructing and obtaining the three-dimensional geographic environment model based on the well working condition, the open pit mine, the geographic environment of the coal preparation plant and the production environment data.