CN114418496B - Visual characterization method, visual characterization system, visual characterization electronic equipment and visual characterization medium for steel mill material flow - Google Patents
Visual characterization method, visual characterization system, visual characterization electronic equipment and visual characterization medium for steel mill material flow Download PDFInfo
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Abstract
The invention is suitable for the technical field of logistics, and provides a visual characterization method, a visual characterization system, electronic equipment and a visual characterization medium for material flow of a steel mill, wherein the visual characterization method comprises the following steps: acquiring factory data and a target transportation node in a steel factory, and determining a target transportation mode of a target material flow according to the factory data and the target transportation node; carrying out path classification on the target material flow according to the target transportation mode, and generating a path classification result of the target material flow; determining navigation demand data of the target substance flow according to the path classification result, acquiring the target substance flow data according to the navigation demand data and the factory data, and carrying out visual characterization on the target substance flow data; by adopting the method, the problem that the effective visual representation of the steel mill material flow data cannot be realized in the prior art is solved.
Description
Technical Field
The invention relates to the technical field of logistics, in particular to a visual characterization method, a visual characterization system, electronic equipment and a visual characterization medium for material flow of a steel mill.
Background
The steel mill material flow penetrates through the planning, design, construction, production and other stages of the steel mill factory, and is connected with each key production node of the steel mill, so that the normal operation of the steel mill material flow is ensured to have important significance for the normal operation of the steel mill. The steel mill material flow mainly comprises the transportation and conversion of related substances on connectors of roads, railways, belt presses, pipelines, roller ways and the like of the steel mill in the steel production process. The research of the material flow data has important significance for the operation of the steel mill, for example, the circulation condition of the material flow is displayed in a high-efficiency visual mode, and the characteristics or the connection of the material flow data in different dimensions can be analyzed through the combination of the graph and the number, so that the problems of the material flow system in the steel mill can be found, diagnosed and optimized, and the optimization of the transportation scheme of the steel mill is facilitated. However, current research into steel mill flow is mainly focused on the establishment of a flow model, and efficient visual characterization of steel mill flow data is lacking.
Disclosure of Invention
The invention provides a visual representation method, a visual representation system, electronic equipment and a visual representation medium for steel mill material flow, which are used for solving the problem that effective visual representation of steel mill material flow data cannot be achieved in the prior art.
The visual characterization method for the steel mill material flow provided by the invention comprises the following steps:
Acquiring factory data and a target transportation node in a steel factory, and determining a target transportation mode of a target material flow according to the factory data and the target transportation node;
Carrying out path classification on the target material flow according to the target transportation mode, and generating a path classification result of the target material flow;
And determining navigation demand data of the target substance flow according to the path classification result, acquiring the target substance flow data according to the navigation demand data and the factory data, and carrying out visual characterization on the target substance flow data.
Optionally, the path classification result includes a variable path category and a fixed path category, and determining the navigation requirement data of the target substance flow according to the path classification result includes:
If the path classification result is a variable path type, the target navigation demand data comprises target time data, target space data and target flow associated data;
and if the path classification result is a fixed path class, the target navigation demand data comprises a path planning scheme.
Optionally, after the target substance flow data is obtained according to the navigation requirement data and the factory floor data, the method further includes:
performing start-stop point data representation on the target material flow data, wherein mathematical expression of the start-stop point data of the target material flow data is as follows:
R＝{(xo,yo,to),(xd,yd,td)，m，a}；
Wherein R is start-stop point data of the material flow data, (x o,yo) is start-point position data of the target material flow, t o is transport start time of the target material flow, t d is transport end time of the target material flow, m is target material flow attribute data, and a is associated data of the target material flow.
Optionally, the determining the navigation requirement data of the target substance flow according to the path classification result includes:
And if the path classification result is a variable path class, acquiring target transportation demand data of the target substance flow, and generating a path planning scheme according to the target transportation demand data.
Optionally, the path planning scheme includes a shortest path scheme, and determining the navigation requirement data of the target material flow according to the path classification result includes:
And acquiring start-stop point position data of the target material flow, and generating a shortest path scheme of the target material flow according to the start-stop point position data and the factory data.
Optionally, the performing path classification on the target material flow according to the target transportation mode, and generating a path classification result of the target material flow includes:
If the target transportation mode is a first transportation mode, the path classification result is a fixed path type, and the first transportation mode comprises railway transportation, pipeline transportation, belt conveyor transportation and roller way transportation;
And if the target transportation mode is a second transportation mode, the path classification result is a variable path class, and the second transportation mode comprises road transportation.
Optionally, the visually characterizing the target substance flow includes:
And acquiring target visual demand data of the target substance flow, and performing visual characterization on the target substance flow by adopting a target characterization mode based on the target visual demand data, wherein the target characterization mode comprises a substance flow Sang Ji diagram, a substance flow start-stop diagram and a substance flow path navigation diagram.
The invention also provides a visual characterization system of steel mill material flow, which comprises:
The transportation mode module is used for acquiring plant data and target transportation nodes in the steel plant and determining a target transportation mode of a target material flow according to the plant data and the target transportation nodes;
the classification module is used for carrying out path classification on the target material flow according to the target transportation mode and generating a path classification result of the target material flow;
The visual module is used for determining navigation demand data of the target substance flow according to the path classification result, acquiring the target substance flow data according to the navigation demand data and the factory data, and carrying out visual characterization on the target substance flow data, and the transportation mode module, the classification module and the visual module are connected.
The present invention also provides an electronic device including: a processor and a memory;
The memory is used for storing a computer program, and the processor is used for executing the computer program stored by the memory so as to enable the electronic equipment to execute the visual characterization method of the steel mill material flow.
The invention also provides a computer readable storage medium having stored thereon a computer program which when executed by a processor implements a method of visual characterization of a steelworks flow as described above.
As described above, the invention provides a visual characterization method of steel mill material flow, which has the following beneficial effects: firstly, acquiring factory data and a target transportation node in a steel factory, and determining a target transportation mode of a target material flow according to the factory data and the target transportation node; then, carrying out path classification on the target material flow according to the target transportation mode, and generating a path classification result of the target material flow; and finally, determining the navigation demand data of the target material flow according to the path classification result, acquiring the target material flow data according to the navigation demand data and the plant area data, and visually characterizing the target material flow data, thereby realizing the effective visual characterization of the target material flow data in the steel plant, being convenient for timely finding, diagnosing and optimizing the problem of the logistics system in the steel plant and being beneficial to optimizing the transportation scheme in the steel plant.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of a visual characterization method of a steel mill material flow in an embodiment of the invention;
FIG. 2 is a material flow path navigation diagram in an embodiment of the present invention;
FIG. 3 is a flow Sang Jitu of material in an embodiment of the present invention;
FIG. 4 is a flow chart of a material flow initiation point in an embodiment of the invention;
FIG. 5 is a block diagram of a visual representation system of steel mill material flow in an embodiment of the invention;
fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
Other advantages and effects of the present invention will become apparent to those skilled in the art from the following disclosure, which describes the embodiments of the present invention with reference to specific examples. The invention may be practiced or carried out in other embodiments that depart from the specific details, and the details of the present description may be modified or varied from the spirit and scope of the present invention. It should be noted that the following embodiments and features in the embodiments may be combined with each other without conflict.
It should be noted that the illustrations provided in the following embodiments merely illustrate the basic concept of the present invention by way of illustration, and only the components related to the present invention are shown in the drawings and are not drawn according to the number, shape and size of the components in actual implementation, and the form, number and proportion of the components in actual implementation may be arbitrarily changed, and the layout of the components may be more complicated.
In order to illustrate the technical scheme of the invention, the following description is made by specific examples.
FIG. 1 is a flow chart of a method for visual characterization of steel mill flow provided in one embodiment of the invention.
As shown in fig. 1, the visual characterization method of the steel mill material flow includes steps S110 to S130:
S110, acquiring factory data and target transportation nodes in a steel factory, and determining a target transportation mode of a target material flow according to the factory data and the target transportation nodes;
s120, carrying out path classification on the target material flow according to the target transportation mode, and generating a path classification result of the target material flow;
S130, determining navigation demand data of the target substance flow according to the path classification result, acquiring the target substance flow data according to the navigation demand data and the factory data, and carrying out visual characterization on the target substance flow data.
In step S110 of the present embodiment, the factory floor data includes location data including, but not limited to, location data of equipment in the factory floor, location data of the truck scale, transportation-related location data including, but not limited to, location data of transportation nodes, location data of transportation means including, but not limited to, railways, roads, pipes, taping machines, and roller tables, and the location data includes planned location data and actual location data; production data includes, but is not limited to, process data, production demand data, quality data, product data, raw material data, transportation related production data including, but not limited to, transportation flow data, transportation path data for a material flow, production data including planned production data and actual production data. The transport node is a transport point in the process of transporting a substance flow that is initiated, passed or reached, and the target substance flow is a substance flow associated with the target transport node, i.e. the transport path of the target substance flow comprises the target transport node. The specific implementation method for determining the target transportation mode of the target material flow according to the factory data and the target transportation node comprises the steps of determining the position data and the target material flow of the target transportation node according to the factory data and the target transportation node, and determining the target transportation mode of the target material flow according to the position data and the target material flow of the target transportation node, wherein the target transportation mode comprises, but is not limited to, road transportation, railway transportation, rolling mill transportation, tape machine transportation and pipeline transportation.
In step S120 of the present embodiment, a specific implementation method for generating a path classification result of a target substance flow by performing path classification on the target substance flow according to a target transportation mode includes generating a path classification result of the target substance flow by performing path classification on the target substance flow according to variability data of a transportation path of the target substance flow. Performing path classification on the target material flow according to the target transportation mode, wherein generating a path classification result of the target material flow comprises the following steps: if the target transportation mode is a first transportation mode, the path classification result is a fixed path type, and the first transportation mode comprises railway transportation, pipeline transportation, belt conveyor transportation and roller way transportation; and if the target transportation mode is a second transportation mode, the path classification result is a variable path class, and the second transportation mode comprises road transportation.
In step S130 of the present embodiment, the navigation demand data includes, but is not limited to, space demand data of the material flow, time demand data of the material flow, flow rate related demand data of the material flow, transportation path demand data of the material flow, and demand data of the truck scale. Specifically, the space demand data includes start and end point data of material flow transportation, the time demand data includes start and end time of material flow transportation, a time period corresponding to larger material flow, the flow related demand data includes flow direction data, flow data (flow data of transportation nodes, flow data of material flow) and flow characteristic data of material flow, the demand data of truck scale includes weighing demand data of truck scale and number demand data of truck scale, the transportation path demand data of material flow includes a path planning scheme, the path planning scheme includes an optimal path planning scheme, and the optimal path planning scheme includes a shortest path planning scheme. If the classification result of the target material flow is a fixed path type, the navigation demand data of the target material flow comprises space demand data, time demand data, flow demand data and weighing demand data of the truck scale; if the classification result of the target material flow is the variable path type, the navigation demand data of the target material flow comprises space demand data, time demand data, flow demand data, weighing demand data of the truck scale and transportation path data of the material flow.
In one embodiment, the material flow data includes start-stop data of the material flow, a transport start time of the material flow, a transport end time of the material flow, attribute data of the material flow, and association data of the material flow. The starting and ending point data of the target substance flow data are expressed, and the mathematical expression of the starting and ending point data of the target substance flow data is as follows:
R＝{(xo,yo,to),(xd,yd,td)，m，a}；
Wherein R is start-stop point data of the material flow data, (x o,yo) is start position data of the target material flow, t o is transport start time of the target material flow, t d is transport end time of the target material flow, m is target material flow attribute data, and a is related data of the target material flow.
In one embodiment, determining navigation demand data for a target substance flow based on the path classification result includes: and if the path classification result is a variable path type, acquiring target transportation demand data of the target material flow, and generating a path planning scheme according to the target transportation demand data. Determining navigation demand data for the target substance flow based on the path classification result further includes: and acquiring start-stop point position data of the target material flow, and generating a shortest path scheme of the target material flow according to the start-stop point position data and the factory data. Specifically, a Dijkstra algorithm may be used to generate a shortest path scheme of the target substance flow, and a specific implementation method of generating the shortest path scheme of the target substance flow by using the Dijkstra algorithm includes:
S210, each material flow transportation node is given P, Q two types of numbers, P is a node set of the shortest path from a known starting point (O point) to other nodes, and Q is a node set of the unknown shortest path;
S220, carrying out initialization processing, wherein the set P only comprises a starting point i=1, the rest points are numbered on Q, D (i) represents the shortest path from the starting point to the point i, which is found currently, the starting point D (1) =0, the distance which is not connected with the starting point i=1 is infinite, and D (i, j) represents the weight values of the i node and the j node, and the weight values comprise the road surface condition, the lane width, the passing time and other influencing factors;
s230, checking the distances from the points in all Q sets to the nodes in the P sets, updating the shortest path, and selecting the node with the shortest distance to move from the Q sets to the P sets;
S240, setting i as an intermediate point, and modifying D (i) +d (i, j) < D (j) into D (i) +d (i, j), wherein D (j) represents the shortest path from the starting point to the point j which is found currently;
S250, repeating the step S230 and the step S240 for n-1 times until all nodes in Q are put into P.
The shortest path scheme for generating the target material flow by using the Dijkstra algorithm can be implemented in ArcGIS, transCAD, cube, for example, in ArcGIS, a network data set is established on a road, a node, etc. of a steel plant, and a series of attributes such as connectivity, turning model, weight, etc. are assigned in the network data set. Finally, the navigation function can be realized through the shortest path analysis of the software, and the visual characterization of the target substance flow can be carried out, see fig. 2.
In one embodiment, visually characterizing the target substance flow includes: and obtaining target visual demand data of the target substance flow, and performing visual characterization on the target substance flow by adopting a target characterization mode based on the target visual demand data, wherein the target characterization mode comprises a substance flow Sang Ji diagram, a substance flow start-stop diagram and a substance flow path navigation diagram. Specifically, stream Sang Jitu: the navigation requirement for the fixed path material flow generally does not need to record a specific moving path, does not need to know the specific geographic position of the starting and ending points, only describes the transportation or conversion relation of the material flow between a pair of starting and ending points, and can also be used for representing the material flow transmission profile between the starting and ending points in a variable path material flow transportation mode; mass flow OD profile: for some special requirements, if the geographical position of the starting point and the destination point is needed to be known, the special requirements can be represented by using an OD diagram commonly adopted in traffic planning, and the special requirements are applicable to characterization of navigation requirements of fixed-path material flows and variable-path material flows; substance flow path navigation map: the method is applied to variable path material flow navigation, namely road transportation of the road material flow, and simultaneously describes the material flow relation between starting and ending points, the specific spatial geographic position of the starting and ending points of the material flow and the specific transportation path of the material flow.
In an embodiment, the visual representation of the target material flow by using the material flow Sang Jitu is shown in fig. 3, wherein a Sang Jitu node represents a start point and an end point in the material flow, and the flow from different sources can be gathered and separated at the node, so that the transfer of the flow scene is reflected; the positions among the nodes are distributed through the material flow transfer time, so that the occurrence sequence of the material flow is reflected; the height of a node represents the amount of material flow that converges to that node. Displaying the flow rate of the material flow by using the edge width, wherein the edge color represents the type or class of the material flow, and one node can have a plurality of edges to represent the flow rate which can enter in a plurality of different directions and the outlet flow rate in a plurality of different directions; the target material flow is visually represented by the material flow Sang Jitu, so that the flow distribution of the material flow and the circulation relationship between the nodes are effectively described. Visual characterization of a target stream using stream Sang Jitu referring to fig. 4, where the OD line connects the start and stop points of the material and the width of the line indicates the mass flow rate.
In an embodiment, the visual representation method of the steel mill material flow further includes obtaining target flow data of a target transportation node, if the target flow data is greater than a preset flow threshold, obtaining the target material flow according to the target transportation node and the plant data, and adjusting a transportation path of the target material flow; and if the target flow data is larger than the preset flow threshold, acquiring the target material flow according to the target transportation node and the factory data, and adjusting the transportation time of the target material flow. The problem of material flow transportation blockage caused by overlarge flow of the transportation node is avoided by adjusting the transportation time and the transportation path of the target material flow.
In an embodiment, the visual representation method of the steel mill material flow further includes obtaining the material flow to be weighed, matching the material flow to be weighed with the target truck scale according to truck scale data of the factory, and generating a transportation scheme of the material flow to be weighed according to the target truck scale. The visual representation method of the steel mill material flow further comprises the steps of obtaining the position data and the transportation data of the truck scale, matching the planned material flow to be weighed according to the truck scale and the transportation data, and adjusting the position of the truck scale if the matched material flow to be weighed of the truck scale is larger than a preset material flow threshold value within a preset time. The problem of overlong waiting time in the material flow weighing process caused by unreasonable arrangement of the position of the truck scale is avoided by adjusting the position of the truck scale.
The embodiment provides a visual characterization method of a steel mill material flow, which comprises the steps of firstly, acquiring factory data and a target transportation node in a steel mill, and determining a target transportation mode of the target material flow according to the factory data and the target transportation node; then, carrying out path classification on the target material flow according to the target transportation mode, and generating a path classification result of the target material flow; finally, determining navigation demand data of the target material flow according to the path classification result, acquiring the target material flow data according to the navigation demand data and the plant area data, and performing visual representation on the target material flow data, thereby realizing effective visual representation on the target material flow data in the steel plant; aiming at the requirements of steel plants on material flow navigation and visualization, the embodiment combines OD data visualization, GIS technology and steel plant material flow, researches the space-time mode, path navigation requirement and visual characterization mode of 2 types of material flow, realizes the integration of graph, module and number, and the achievement can be applied to steel plant production practice: firstly, comparing the relation among a plurality of dimensions in the data through the material flow data, further optimizing a steel mill material flow transportation scheme, and adjusting a transportation path; and secondly, providing services such as optimal path planning, optimal facility point recommendation and the like for steel mill staff.
Based on the same inventive concept as the visual characterization method of the steel mill material flow, correspondingly, the embodiment also provides a visual characterization system of the steel mill material flow.
Fig. 5 is a block diagram of a visual representation system of a steel mill mass flow provided by the present invention.
As shown in fig. 5, the visual characterization system of the steel mill material flow comprises: 51 transportation mode module, 52 classification module and 53 visualization module.
The transportation mode module is used for acquiring factory data and target transportation nodes in the steel factory and determining a target transportation mode of a target material flow according to the factory data and the target transportation nodes;
the classification module is used for carrying out path classification on the target material flow according to the target transportation mode and generating a path classification result of the target material flow;
The visual module is used for determining navigation demand data of the target substance flow according to the path classification result, acquiring the target substance flow data according to the navigation demand data and the factory data, and carrying out visual characterization on the target substance flow data, and the transportation mode module, the classification module and the visual module are connected.
In some exemplary embodiments, the classification module includes:
the classification unit is used for classifying the target navigation demand data into a variable path class according to the path classification result, wherein the target navigation demand data comprises target time data, target position data and target flow data; and if the path classification result is a fixed path class, the target navigation demand data comprises a path planning scheme.
In some exemplary embodiments, the visual characterization system for steel mill material flows described above includes:
The start-stop point representation unit is used for representing start-stop point data of the target substance flow data, and the mathematical expression of the start-stop point data of the target substance flow data is as follows:
R＝{(xo,yo,to),(xd,yd,td)，m，a}；
Wherein R is start-stop point data of the material flow data, (x o,yo) is start-point position data of the target material flow, t o is transport start time of the target material flow, t d is transport end time of the target material flow, m is target material flow attribute data, and a is associated data of the target material flow.
In some exemplary embodiments, the visualization module includes:
The navigation data unit is used for if the path classification result is a variable path type, the target navigation demand data comprise target time data, target space data and target flow associated data, and if the path classification result is a fixed path type, the target navigation demand data comprise a path planning scheme;
The path planning unit is used for acquiring target transportation demand data of the target substance flow if the path classification result is a variable path class, and generating a path planning scheme according to the target transportation demand data;
And the shortest path unit is used for acquiring the start-stop point position data of the target substance flow and generating a shortest path scheme of the target substance flow according to the start-stop point position data and the factory data.
In some exemplary embodiments, the visualization module further comprises:
And the visualization unit is used for acquiring target visual demand data of the target substance flow and carrying out visual characterization on the target substance flow by adopting a target characterization mode based on the target visual demand data, wherein the target characterization mode comprises a substance flow Sang Ji diagram, a substance flow start-stop diagram and a substance flow path navigation diagram.
The present embodiment also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements any of the methods of the present embodiments.
In one embodiment, referring to fig. 6, the present embodiment further provides an electronic device 600, including a memory 601, a processor 602, and a computer program stored on the memory and executable on the processor, where the processor 602 implements the steps of the method according to any of the embodiments above when executing the computer program.
The computer readable storage medium in this embodiment, as will be appreciated by those of ordinary skill in the art: all or part of the steps for implementing the method embodiments described above may be performed by computer program related hardware. The aforementioned computer program may be stored in a computer readable storage medium. The program, when executed, performs steps including the method embodiments described above; and the aforementioned storage medium includes: various media that can store program code, such as ROM, RAM, magnetic or optical disks.
The electronic device provided in this embodiment includes a processor, a memory, a transceiver, and a communication interface, where the memory and the communication interface are connected to the processor and the transceiver and perform communication therebetween, the memory is used to store a computer program, the communication interface is used to perform communication, and the processor and the transceiver are used to run the computer program, so that the electronic device performs each step of the above method.
In this embodiment, the memory may include a random access memory (Random Access Memory, abbreviated as RAM), and may further include a non-volatile memory (non-volatile memory), such as at least one disk memory.
The processor may be a general-purpose processor, including a central processing unit (Central Processing Unit, abbreviated as CPU), a network processor (Network Processor, abbreviated as NP), etc.; but may also be a digital signal processor (DIGITAL SIGNAL Processing, DSP), application Specific Integrated Circuit (ASIC), field-Programmable gate array (FPGA) or other Programmable logic device, discrete gate or transistor logic device, discrete hardware components.
In the foregoing embodiments, references in the specification to "this embodiment," "one embodiment," "another embodiment," "in some exemplary embodiments," or "other embodiments" indicate that a particular feature, structure, or characteristic described in connection with the embodiments is included in at least some, but not necessarily all, embodiments. Multiple occurrences of "this embodiment," "one embodiment," "another embodiment," and "like" do not necessarily all refer to the same embodiment.
In the above embodiments, while the present invention has been described in conjunction with specific embodiments thereof, many alternatives, modifications and variations of these embodiments will be apparent to those skilled in the art in light of the foregoing description. For example, other memory structures (e.g., dynamic RAM (DRAM)) may use the embodiments discussed. The embodiments of the invention are intended to embrace all such alternatives, modifications and variances which fall within the broad scope of the appended claims.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for system embodiments, since they are substantially similar to method embodiments, the description is relatively simple, as relevant to see a section of the description of method embodiments.
The invention is operational with numerous general purpose or special purpose computing system environments or configurations. For example: personal computers, server computers, hand-held or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like.
The invention may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The invention may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
The above embodiments are merely illustrative of the principles of the present invention and its effectiveness, and are not intended to limit the invention. Modifications and variations may be made to the above-described embodiments by those skilled in the art without departing from the spirit and scope of the invention. It is therefore intended that all equivalent modifications and changes made by those skilled in the art without departing from the spirit and technical spirit of the present invention shall be covered by the appended claims.
Claims (8)
1. A method for visual characterization of a steel mill stream, comprising:
Acquiring factory data and a target transportation node in a steel factory, and determining a target transportation mode of a target material flow according to the factory data and the target transportation node;
Carrying out path classification on the target material flow according to the target transportation mode, and generating a path classification result of the target material flow;
Determining navigation demand data of the target substance flow according to the path classification result, acquiring the target substance flow data according to the navigation demand data and the factory data, and carrying out visual characterization on the target substance flow data; the path classification result includes a variable path category and a fixed path category, and the determining navigation requirement data of the target substance flow according to the path classification result includes: if the path classification result is a variable path type, the navigation demand data comprises target time data, target space data and target flow associated data; if the path classification result is a fixed path class, the navigation demand data comprises a path planning scheme; after the target material flow data is obtained according to the navigation demand data and the factory floor data, the method further comprises the following steps: performing start-stop point data representation on the target material flow data, wherein mathematical expression of the start-stop point data of the target material flow data is as follows:
R＝{(xo,yo,to),(xd,yd,td)，m，a}；
Wherein R is start-stop point data of the material flow data, (x o,yo) is start-point position data of the target material flow, t o is transport start time of the target material flow, t d is transport end time of the target material flow, m is target material flow attribute data, and a is associated data of the target material flow.
2. The visual characterization method of steel mill material flow according to claim 1, wherein the determining navigation demand data of the target material flow according to the path classification result comprises:
And if the path classification result is a variable path class, acquiring target transportation demand data of the target substance flow, and generating a path planning scheme according to the target transportation demand data.
3. The visual characterization method of steel mill material flow according to claim 1, wherein the path planning scheme includes a shortest path scheme, and wherein determining navigation demand data of the target material flow according to the path classification result includes:
And acquiring start-stop point position data of the target material flow, and generating a shortest path scheme of the target material flow according to the start-stop point position data and the factory data.
4. The visual representation method of steel mill material flow according to claim 1, wherein the performing the path classification on the target material flow according to the target transportation mode, and generating the path classification result of the target material flow comprises:
If the target transportation mode is a first transportation mode, the path classification result is a fixed path type, and the first transportation mode comprises railway transportation, pipeline transportation, belt conveyor transportation and roller way transportation;
And if the target transportation mode is a second transportation mode, the path classification result is a variable path class, and the second transportation mode comprises road transportation.
5. The method of visual characterization of a steel mill stream according to claim 1, wherein said visually characterizing the target stream comprises:
And acquiring target visual demand data of the target substance flow, and performing visual characterization on the target substance flow by adopting a target characterization mode based on the target visual demand data, wherein the target characterization mode comprises a substance flow Sang Ji diagram, a substance flow start-stop diagram and a substance flow path navigation diagram.
6. A visual characterization system for steel mill streams, comprising:
The transportation mode module is used for acquiring plant data and target transportation nodes in the steel plant and determining a target transportation mode of a target material flow according to the plant data and the target transportation nodes;
the classification module is used for carrying out path classification on the target material flow according to the target transportation mode and generating a path classification result of the target material flow;
The visual module is used for determining navigation demand data of the target substance flow according to the path classification result, acquiring the target substance flow data according to the navigation demand data and the factory data, and carrying out visual characterization on the target substance flow data, and the transportation mode module, the classification module and the visual module are connected; determining navigation demand data of the target substance flow according to the path classification result, acquiring the target substance flow data according to the navigation demand data and the factory data, and carrying out visual characterization on the target substance flow data; the path classification result includes a variable path category and a fixed path category, and the determining navigation requirement data of the target substance flow according to the path classification result includes: if the path classification result is a variable path type, the navigation demand data comprises target time data, target space data and target flow associated data; if the path classification result is a fixed path class, the navigation demand data comprises a path planning scheme; after the target material flow data is obtained according to the navigation demand data and the factory floor data, the method further comprises the following steps: performing start-stop point data representation on the target material flow data, wherein mathematical expression of the start-stop point data of the target material flow data is as follows:
R＝{(xo,yo,to),(xd,yd,td)，m，a}；
Wherein R is start-stop point data of the material flow data, (x o,yo) is start-point position data of the target material flow, t o is transport start time of the target material flow, t d is transport end time of the target material flow, m is target material flow attribute data, and a is associated data of the target material flow.
7. An electronic device comprising a processor, a memory, and a communication bus;
the communication bus is used for connecting the processor and the memory;
The processor is configured to execute a computer program stored in the memory to implement the method of any one of claims 1-5.
8. A computer readable storage medium, characterized in that it has stored thereon a computer program for causing the computer to perform the method according to any of claims 1-5.
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