CN113156859A - Visualization system and method for workshop data - Google Patents
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Abstract
The invention discloses a system and a method for visualizing workshop data, and belongs to the technical field of visual signboards. An instruction acquisition module acquires a user instruction and sends the user instruction to a data search module; the data acquisition module acquires corresponding target data according to the user instruction and sends the target data to the data processing module; the data processing module is used for carrying out visualization processing on the target data to obtain visualization data and sending the visualization data to the data display module; and the data display module displays the visual data. By searching for corresponding target data according to the user instruction requirements and analyzing the target data, the target data is visualized, so that users and managers can visually and transparently know workshop data.
Description
Technical Field
The invention relates to the technical field of visual signboards, in particular to a system and a method for visualizing workshop data.
Background
The workshop is a basic unit for organizing production in the manufacturing industry, and the technical progress of the digital twin workshop has important significance for promoting the virtual-real fusion of the whole manufacturing industry. With increasingly severe market competition and increasingly complex product requirements, workshop operation is subject to the pressure of shorter product delivery period, higher reliability requirement, more frequent product variety change and the like, and a workshop management layer needs to master the field operation condition of the workshop in time and discover abnormal disturbance in production in time, so that the production plan and resource allocation are reasonably adjusted, and the production efficiency and reliability are improved. The development of the technology of the internet of things provides a large amount of real-time data of a workshop bottom layer for various application systems of a workshop, and how to intuitively and concisely display the real-time data of the internet of things of the workshop is an engineering problem which needs to be solved urgently by an enterprise.
The above is only for the purpose of assisting understanding of the technical aspects of the present invention, and does not represent an admission that the above is prior art.
Disclosure of Invention
The invention mainly aims to provide a workshop data visualization system, and aims to solve the technical problem that how to visually and transparently display workshop working data for a user in the prior art.
In order to achieve the aim, the invention provides a workshop data visualization system, which comprises an instruction acquisition module, a data processing module and a data display module which are sequentially connected;
the instruction acquisition module: the data searching module is used for acquiring a user instruction and sending the user instruction to the data searching module;
the data acquisition module: the system comprises a data processing module, a data processing module and a data processing module, wherein the data processing module is used for acquiring corresponding target data according to the user instruction and sending the target data to the data processing module;
the data processing module: the data processing module is used for carrying out visualization processing on the target data to obtain visualization data and sending the visualization data to the data display module;
the data display module: for displaying the visualization data.
Optionally, the data obtaining module includes: the system comprises an instruction analysis module and a data searching module;
the instruction analysis module: the system comprises a user instruction, a corresponding feature tag and corresponding target terminal information, wherein the user instruction is used for determining the corresponding feature tag according to the user instruction and determining the corresponding target terminal information according to the feature tag;
the data search module: and the data processing module is used for searching corresponding current working data and historical working data according to the target terminal information, taking the current working data and the historical working data as target data, and sending the target data to the data processing module.
Optionally, the data processing module includes: the data preprocessing module and the data analysis module;
the data preprocessing module: the system comprises a data conversion module, a data storage module, a data processing module and a data processing module, wherein the data conversion module is used for converting the target data through a preset data conversion model to obtain standardized data;
the data analysis module: and the system is used for analyzing the standardized data through a preset data processing model to obtain visual data.
Optionally, the data analysis module comprises: a discrete data processing module;
the discrete data processing module: the data definition method is used for establishing a relation network for discrete data in the standardized data through a Petri network to obtain a discrete data relation network, then performing data definition on each element in the discrete data relation network, using the discrete data relation network subjected to the data definition as visual integral data, and obtaining the visual data through the visual integral data.
Optionally, the data analysis module further comprises: the system comprises a data prediction module and an abnormality detection module;
the data prediction module: the system comprises a data processing module, a data processing module and a data processing module, wherein the data processing module is used for predicting the standardized data through a preset trend prediction model to obtain predicted working trend data in a preset time period of a target terminal, and the predicted working trend data is used as visual prediction data;
the anomaly detection module: the visual prediction data is detected through a data comparison model to obtain abnormal data in the visual prediction data, the abnormal data is used as visual abnormal data, and the visual data is obtained according to the visual whole data, the visual prediction data and the visual abnormal data.
Optionally, the data display module includes: the system comprises a data pushing module and an instruction sending module;
the data pushing module: the system is used for pushing the visual data;
the instruction sending module: and the system is used for acquiring the working instruction fed back by the user according to the visual data and generating the fed back working instruction to the corresponding target terminal.
Further, in order to achieve the above object, the present invention also provides a method for visualizing plant data, which is applied to the system for visualizing plant data as described above, and the system for visualizing plant data includes: the system comprises an instruction acquisition module, a data processing module and a data display module which are connected in sequence, wherein the visualization method of the workshop data comprises the following steps:
the instruction acquisition module acquires a user instruction and sends the user instruction to the data search module;
the data acquisition module acquires corresponding target data according to the user instruction and sends the target data to the data processing module;
the data processing module is used for carrying out visualization processing on the target data to obtain visualization data and sending the visualization data to a data display module;
and the data display module displays the visual data.
Optionally, the data obtaining module includes: the system comprises an instruction analysis module and a data searching module;
the data acquisition module acquires corresponding target data according to the user instruction and sends the target data to the data processing module, and the data acquisition module comprises:
the instruction analysis module determines a corresponding characteristic label according to the user instruction, and determines corresponding target terminal information according to the characteristic label;
and the data searching module searches corresponding current working data and historical working data according to the target terminal information, takes the current working data and the historical working data as target data, and sends the target data to the data processing module.
Optionally, the data processing module includes: the data preprocessing module and the data analysis module;
the data processing module performs visualization processing on the target data to obtain visualized data, and the visualization processing comprises:
the data preprocessing module converts the target data through a preset data conversion model to obtain standardized data;
and the data analysis module analyzes the standardized data through a preset data processing model to obtain visual data.
Optionally, the data analysis module comprises: a discrete data processing module;
the data analysis module analyzes the standardized data through a preset data processing model to obtain visual data, and the method comprises the following steps:
the discrete data processing module establishes a relation network for discrete data in the standardized data through a Petri network to obtain a discrete data relation network, then performs data definition for each element in the discrete data relation network, and uses the discrete data relation network subjected to data definition as visual integral data to obtain the visual data through the visual integral data.
An instruction acquisition module acquires a user instruction and sends the user instruction to a data search module; the data acquisition module acquires corresponding target data according to the user instruction and sends the target data to the data processing module; the data processing module is used for carrying out visualization processing on the target data to obtain visualization data and sending the visualization data to the data display module; and the data display module displays the visual data. By searching for corresponding target data according to the user instruction requirements and analyzing the target data, the target data is visualized, so that users and managers can visually and transparently know workshop data.
Drawings
FIG. 1 is a block diagram of a first embodiment of a system for visualizing plant data in accordance with the present invention;
FIG. 2 is a block diagram of a second embodiment of a visualization system for plant data according to the present invention;
FIG. 3 is an overall apparatus diagram of an embodiment of a visualization system for plant data of the present invention;
FIG. 4 is a schematic flow chart of a first embodiment of a method for visualizing plant data according to the present invention
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Referring to fig. 1, fig. 1 is a block diagram illustrating a first embodiment of a plant data visualization system according to the present invention.
In this embodiment, the visualization system of plant data includes: the instruction acquisition module 10, the data acquisition module 20, the data processing module 30 and the data display module 40 that connect gradually, when workshop staff or managers promptly the user wants to acquire the work data of certain equipment in workshop or want to know some production data in workshop, through the electronic billboard system who uses the workshop, through assigning the instruction, the visual system of workshop data begins to start.
It should be noted that, when a workshop staff or an administrator issues an instruction to acquire data of a certain device through the electronic billboard, the instruction acquisition module 10 receives an instruction of a user, and then sends the instruction of the user to the data search module 20. For example, when a worker in a workshop clicks to obtain the operating status and the fault status of the equipment, the instruction obtaining module 10 obtains the instruction of the user, and then sends the instruction to obtain the operating status and the fault status of the equipment to the data obtaining module 20.
It can be understood that, after the data obtaining module 20 receives the demand instruction of the user, the data obtaining module 20 searches for the corresponding target data according to the demand instruction of the user, and the data obtaining module 20 has a preset database, which is used for collecting all working data of the workshop in real time, real-time working data of various devices, information of workers, and production data. After acquiring the target data, the data acquisition module 20 sends the target data to the data processing module 30.
Further, the data acquisition module 20 includes: the system comprises an instruction analysis module and a data searching module; the instruction analysis module: the system comprises a user instruction, a corresponding feature tag and corresponding target terminal information, wherein the user instruction is used for determining the corresponding feature tag according to the user instruction and determining the corresponding target terminal information according to the feature tag; the data search module: and the data processing module is used for searching corresponding current working data and historical working data according to the target terminal information, taking the current working data and the historical working data as target data, and sending the target data to the data processing module.
It should be noted that after receiving an instruction sent by a user, each instruction corresponds to a different feature tag, and feature extraction is performed on the user instruction, so that the feature tag corresponding to the user instruction is obtained, and target terminal device information corresponding to target data to be searched is determined. For example, in a food production plant, when a user gives an instruction to acquire packaging data, the instruction is subjected to feature extraction, and then the determined target terminal device information includes a packaging machine, which is the type of the target terminal device.
It can be understood that after the information of the target terminal is obtained, the current working data and the historical working data corresponding to the target terminal are searched in the preset database of the data obtaining module 20, and the current working data and the historical working data are used as the target data, where the working data includes not only the operation condition of the terminal device, but also the production condition and the management condition related to the terminal device, and the staff condition related to the terminal device. For example, if the current target terminal device is a packaging machine, the number of devices operated historically by the packaging machine, which devices are operated historically, the operation time, the failure condition and time, the production condition, the number of workers, the sex and name of the workers, the number of devices operated currently, which devices are operated currently, the operation time, the failure condition and time, the production condition, the number of workers, the sex and name of the workers, and other data related to the target terminal device may be acquired, which is not limited in this embodiment.
In a specific implementation, after the corresponding target data is acquired, the data search module in the data acquisition module 20 sends the target data to the data processing module 30, so that the data processing module 30 analyzes the target data. In this embodiment, the instruction is subjected to feature extraction to obtain the corresponding target terminal, and then the relevant data corresponding to the terminal is searched, so that the workload is reduced, and the searching efficiency is improved.
It should be noted that, since the target data acquired by the data acquisition module 20 is original data, the original data are discrete and not related to each other, and cannot be seen at a glance, the target data cannot be directly pushed to an electronic watch panel to be displayed to a user, and the data processing module 30 needs to perform visualization processing on the target data to correlate the data and be able to be seen at a glance, and finally convert the data into visualized data, and then send the visualized data to the data display module 40.
It is understood that the data display module 40 displays the visual data through the electronic billboard after receiving the visual data, so that the user can see the data at a glance.
Further, the data display module 40 includes: the system comprises a data pushing module and an instruction sending module; the data pushing module: the system is used for pushing the visual data; the instruction sending module: and the system is used for acquiring the working instruction fed back by the user according to the visual data and generating the fed back working instruction to the corresponding target terminal.
It should be noted that, when the user views the visualized data, some instructions may be issued according to the visualized data. For example, after the user receives the visual data of the packaging machines, the user knows that the operation time of one packaging machine is too long according to the displayed data, the user sends a closing instruction to close the packaging machine, and the closing instruction sent by the user is sent to the corresponding target packaging machine through the instruction sending module in the data display module 40 to close the packaging machine.
In specific implementation, the data display module 40 in this embodiment can not only display data, but also send a related instruction fed back by a user, so that the corresponding terminal device can perform corresponding adjustment, and normal operation of the workshop device is ensured.
In the embodiment, a user instruction is acquired through an instruction acquisition module and is sent to the data search module; the data acquisition module acquires corresponding target data according to the user instruction and sends the target data to the data processing module; the data processing module is used for carrying out visualization processing on the target data to obtain visualization data and sending the visualization data to the data display module; and the data display module displays the visual data. The corresponding target data are searched according to the user instruction requirements and analyzed, and the target data are visualized, so that the user and the management personnel can visually and transparently know various working conditions and various data of the workshop.
Referring to fig. 2, fig. 2 is a block diagram illustrating a second embodiment of the visualization system of plant data according to the present invention, and the second embodiment of the visualization system of plant data according to the present invention is provided based on the above embodiment.
In this embodiment, the data processing module 30 includes: a data preprocessing module 31 and a data analysis module 32;
it should be noted that, since the data acquired by the data acquisition module 20 is raw data, which includes only numerical data and qualitative data, all raw data need to be standardized by the data preprocessing module 31 using the data conversion model, and finally standardized data is obtained. For example, the obtained target data includes 10 workers managing the packaging machine, wherein the number of the male workers is 4, the number of the female workers is 6, and the data is normalized to be the workers { 14 }, { 26 }, wherein male is represented by 1 and female is represented by 2. Meanwhile, since different data cannot be compared under the same standard due to different variables, it is necessary to obtain standardized values by subjecting the target data to dimensionless processing.
It should be noted that, after the target data is normalized, since the normalized data are not associated with each other and the predicted data cannot be obtained, the data analysis module 32 needs to connect the normalized data through modeling by analysis to obtain a correlation network between the data, and finally obtain the visualized data.
Further, the data analysis module 32 includes: a discrete data processing module; the discrete data processing module: the data definition method is used for establishing a relation network for discrete data in the standardized data through a Petri network to obtain a discrete data relation network, then performing data definition on each element in the discrete data relation network, using the discrete data relation network subjected to the data definition as visual integral data, and obtaining the visual data through the visual integral data.
It can be understood that, since discrete data exists in the normalized data, that is, the obtained normalized data are not correlated with each other, the discrete data in the normalized data need to be correlated with each other through the discrete data processing module. Establishing a main flow for standardized data through a Petri network, connecting all discretized data through a relation network to obtain an initial discrete data relation network, refining the data and the relation in the initial relation network to create a secondary flow in the main flow, finally defining and assigning attributes of all elements in the flow, and analyzing the probability and the performance of the whole network to finally obtain complete visual whole data.
In specific implementation, in this embodiment, by establishing a network model, relationships among all the standardized data are interconnected, and finally, the obtained visualized overall data displayed by the overall relationship network can make a user clear, more clear and more clear.
Further, the data analysis module further comprises: the system comprises a data prediction module and an abnormality detection module; the data prediction module: the system comprises a data processing module, a data processing module and a data processing module, wherein the data processing module is used for predicting the standardized data through a preset trend prediction model to obtain predicted working trend data in a preset time period of a target terminal, and the predicted working trend data is used as visual prediction data; the anomaly detection module: the visual prediction data is detected through a data comparison model to obtain abnormal data in the visual prediction data, the abnormal data is used as visual abnormal data, and the visual data is obtained according to the visual whole data, the visual prediction data and the visual abnormal data.
It should be noted that, as shown in fig. 3, fig. 3 is an overall device diagram of a visualization system of plant data, where a data prediction module included in the visualization system predicts the plant data based on the obtained standardized data to obtain predicted working data of the target terminal within a preset time period, and finally uses the predicted working data within the preset time period as the visualized prediction data, where the preset time period may be 10 minutes in the future, half an hour in the future, or other time values, and the preset time period is not limited in this embodiment, and the preset trend prediction model is obtained by training an initialized neural network model based on a large amount of sample data (i.e., working data of different devices).
In the specific implementation, the obtained normal working data of the target terminal device is trained to obtain a data comparison model, the visual prediction data is compared and analyzed through an abnormality detection module based on the data comparison model, whether the visual prediction data is abnormal in a preset time period or not is judged, if yes, the visual abnormal data is obtained, and finally the visual overall data, the visual prediction data and the visual abnormal data are sent to a data display module as the visual data. In the embodiment, the standardized data is predicted and abnormal, so that the finally obtained visualized data is more comprehensive.
In the embodiment, the target data is converted through a preset data conversion model through a data preprocessing module to obtain standardized data; the data analysis module analyzes the standardized data through a preset data processing model to obtain visual data, and the obtained target original data is subjected to standardized processing and is analyzed, so that the visual data is displayed more uniformly and comprehensively.
Referring to fig. 4, fig. 4 is a schematic flow chart of a first embodiment of the method for visualizing the plant data according to the present invention, which is applied to the system for visualizing the plant data as described above, and the system for visualizing the plant data includes: the system comprises an instruction acquisition module, a data processing module and a data display module which are connected in sequence, wherein the visualization method of the workshop data comprises the following steps:
step S10, the instruction obtaining module obtains a user instruction, and sends the user instruction to the data searching module.
In this embodiment, the visualization system of plant data includes: the instruction acquisition module, the data processing module and the data display module that connect gradually, when workshop staff or administrator promptly the user want to acquire the working data of certain equipment in workshop or want to know some production data in workshop, through the electron billboard system that uses the workshop, through assigning the instruction, the visual system of workshop data begins to start.
It should be noted that, when a workshop staff or an administrator issues a data instruction for acquiring a certain device through the electronic billboard, the instruction acquisition module receives the instruction of the user and then sends the user instruction to the data search module. For example, when a worker in a workshop clicks to acquire the operating state and the fault state of the equipment, the instruction acquisition module acquires the instruction of the user and then sends the instruction for acquiring the operating state and the fault state of the equipment to the data acquisition module.
And step S20, the data acquisition module acquires corresponding target data according to the user instruction and sends the target data to a data processing module.
It can be understood that, after the data acquisition module receives the demand instruction of the user, the data acquisition module searches for the corresponding target data according to the demand instruction of the user, and the data acquisition module is provided with a preset database which is used for acquiring all working data of a workshop in real time and acquiring real-time working data and staff information of various devices and production data. After the target data is acquired, the data acquisition module sends the target data to the data processing module.
Further, the data acquisition module comprises: the system comprises an instruction analysis module and a data searching module; the data acquisition module acquires corresponding target data according to the user instruction and sends the target data to the data processing module, and the data acquisition module comprises: the instruction analysis module determines a corresponding characteristic label according to the user instruction, and determines corresponding target terminal information according to the characteristic label; and the data searching module searches corresponding current working data and historical working data according to the target terminal information, takes the current working data and the historical working data as target data, and sends the target data to the data processing module.
It should be noted that after receiving an instruction sent by a user, each instruction corresponds to a different feature tag, and feature extraction is performed on the user instruction, so that the feature tag corresponding to the user instruction is obtained, and target terminal device information corresponding to target data to be searched is determined. For example, in a food production plant, when a user gives an instruction to acquire packaging data, the instruction is subjected to feature extraction, and then the determined target terminal device information includes a packaging machine, which is the type of the target terminal device.
It can be understood that after the information of the target terminal is obtained, the current working data and the historical working data corresponding to the target terminal are searched in the preset database of the data acquisition module, and the current working data and the historical working data are used as the target data, and the working data not only include the operation condition of the terminal device, but also include the production condition and the management condition related to the terminal device, and the condition of the staff related to the terminal device. For example, if the current target terminal device is a packaging machine, the number of devices operated historically by the packaging machine, which devices are operated historically, the operation time, the failure condition and time, the production condition, the number of workers, the sex and name of the workers, the number of devices operated currently, which devices are operated currently, the operation time, the failure condition and time, the production condition, the number of workers, the sex and name of the workers, and other data related to the target terminal device may be acquired, which is not limited in this embodiment.
In a specific implementation, after the corresponding target data is acquired, the data search module in the data acquisition module sends the target data to the data processing module, so that the data processing module analyzes the target data. In this embodiment, the instruction is subjected to feature extraction to obtain the corresponding target terminal, and then the relevant data corresponding to the terminal is searched, so that the workload is reduced, and the searching efficiency is improved.
Step S30, the data processing module performs visualization processing on the target data to obtain visualized data, and sends the visualized data to a data display module.
It should be noted that, since the target data acquired by the data acquisition module is original data, the original data are discrete and not related to each other, and cannot be seen at a glance, the target data cannot be directly pushed to an electronic viewing panel to be displayed to a user, and the target data needs to be visualized by the data processing module, so that the data are related to each other and can be seen at a glance, and finally converted into visualized data, and then the visualized data is sent to the data display module.
Further, the data processing module comprises: the data preprocessing module and the data analysis module; the data processing module performs visualization processing on the target data to obtain visualized data, and the visualization processing comprises: the data preprocessing module converts the target data through a preset data conversion model to obtain standardized data; and the data analysis module analyzes the standardized data through a preset data processing model to obtain visual data.
Further, the data analysis module includes: a discrete data processing module; the data analysis module analyzes the standardized data through a preset data processing model to obtain visual data, and the method comprises the following steps: the discrete data processing module establishes a relation network for discrete data in the standardized data through a Petri network to obtain a discrete data relation network, then performs data definition for each element in the discrete data relation network, and uses the discrete data relation network subjected to data definition as visual integral data to obtain the visual data through the visual integral data.
It can be understood that, since discrete data exists in the normalized data, that is, the obtained normalized data are not correlated with each other, the discrete data in the normalized data need to be correlated with each other through the discrete data processing module. Establishing a main flow for standardized data through a Petri network, connecting all discretized data through a relation network to obtain an initial discrete data relation network, refining the data and the relation in the initial relation network to create a secondary flow in the main flow, finally defining and assigning attributes of all elements in the flow, and analyzing the probability and the performance of the whole network to finally obtain complete visual whole data.
In specific implementation, in this embodiment, by establishing a network model, relationships among all the standardized data are interconnected, and finally, the obtained visualized overall data displayed by the overall relationship network can make a user clear, more clear and more clear.
And step S40, the data display module displays the visual data.
It can be understood that, after receiving the visual data, the data display module displays the visual data through the electronic billboard, so that the user can see the data at a glance.
In the embodiment, a user instruction is acquired through an instruction acquisition module and is sent to the data search module; the data acquisition module acquires corresponding target data according to the user instruction and sends the target data to the data processing module; the data processing module is used for carrying out visualization processing on the target data to obtain visualization data and sending the visualization data to the data display module; and the data display module displays the visual data. The corresponding target data are searched according to the user instruction requirements and analyzed, and the target data are visualized, so that the user and the management personnel can visually and transparently know various working conditions and various data of the workshop.
Further, it is to be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solution of the present invention or portions thereof that contribute to the prior art may be embodied in the form of a software product, where the computer software product is stored in a storage medium (e.g. Read Only Memory (ROM)/RAM, magnetic disk, optical disk), and includes several instructions for enabling a terminal device (e.g. a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. A system for visualizing plant data, the system comprising: the system comprises an instruction acquisition module, a data processing module and a data display module which are connected in sequence;
the instruction acquisition module: the data searching module is used for acquiring a user instruction and sending the user instruction to the data searching module;
the data acquisition module: the system comprises a data processing module, a data processing module and a data processing module, wherein the data processing module is used for acquiring corresponding target data according to the user instruction and sending the target data to the data processing module;
the data processing module: the data processing module is used for carrying out visualization processing on the target data to obtain visualization data and sending the visualization data to the data display module;
the data display module: for displaying the visualization data.
2. The system for visualizing plant data as in claim 1, wherein the data acquisition module comprises: the system comprises an instruction analysis module and a data searching module;
the instruction analysis module: the system comprises a user instruction, a corresponding feature tag and corresponding target terminal information, wherein the user instruction is used for determining the corresponding feature tag according to the user instruction and determining the corresponding target terminal information according to the feature tag;
the data search module: and the data processing module is used for searching corresponding current working data and historical working data according to the target terminal information, taking the current working data and the historical working data as target data, and sending the target data to the data processing module.
3. The system for visualizing plant data of claim 1 wherein the data processing module comprises: the data preprocessing module and the data analysis module;
the data preprocessing module: the system comprises a data conversion module, a data storage module, a data processing module and a data processing module, wherein the data conversion module is used for converting the target data through a preset data conversion model to obtain standardized data;
the data analysis module: and the system is used for analyzing the standardized data through a preset data processing model to obtain visual data.
4. The system for visualizing plant data as in claim 3, wherein the data analysis module comprises: a discrete data processing module;
the discrete data processing module: the data definition method is used for establishing a relation network for discrete data in the standardized data through a Petri network to obtain a discrete data relation network, then performing data definition on each element in the discrete data relation network, using the discrete data relation network subjected to the data definition as visual integral data, and obtaining the visual data through the visual integral data.
5. The system for visualizing plant data of claim 4 wherein the data analysis module further comprises: the system comprises a data prediction module and an abnormality detection module;
the data prediction module: the system comprises a data processing module, a data processing module and a data processing module, wherein the data processing module is used for predicting the standardized data through a preset trend prediction model to obtain predicted working trend data in a preset time period of a target terminal, and the predicted working trend data is used as visual prediction data;
the anomaly detection module: the visual prediction data is detected through a data comparison model to obtain abnormal data in the visual prediction data, the abnormal data is used as visual abnormal data, and the visual data is obtained according to the visual whole data, the visual prediction data and the visual abnormal data.
6. The system for visualization of plant data according to any one of claims 1 to 5, wherein the data display module comprises: the system comprises a data pushing module and an instruction sending module;
the data pushing module: the system is used for pushing the visual data;
the instruction sending module: and the system is used for acquiring the working instruction fed back by the user according to the visual data and generating the fed back working instruction to the corresponding target terminal.
7. A visualization method of plant data, characterized in that it is applied to the visualization system of plant data according to any one of claims 1 to 6, said visualization system of plant data comprising: the system comprises an instruction acquisition module, a data processing module and a data display module which are connected in sequence, wherein the visualization method of the workshop data comprises the following steps:
the instruction acquisition module acquires a user instruction and sends the user instruction to the data search module;
the data acquisition module acquires corresponding target data according to the user instruction and sends the target data to the data processing module;
the data processing module is used for carrying out visualization processing on the target data to obtain visualization data and sending the visualization data to a data display module;
and the data display module displays the visual data.
8. The method for visualizing plant data as in claim 7, wherein the data acquisition module comprises: the system comprises an instruction analysis module and a data searching module;
the data acquisition module acquires corresponding target data according to the user instruction and sends the target data to the data processing module, and the data acquisition module comprises:
the instruction analysis module determines a corresponding characteristic label according to the user instruction, and determines corresponding target terminal information according to the characteristic label;
and the data searching module searches corresponding current working data and historical working data according to the target terminal information, takes the current working data and the historical working data as target data, and sends the target data to the data processing module.
9. The method for visualizing plant data as in claim 7, wherein the data processing module comprises: the data preprocessing module and the data analysis module;
the data processing module performs visualization processing on the target data to obtain visualized data, and the visualization processing comprises:
the data preprocessing module converts the target data through a preset data conversion model to obtain standardized data;
and the data analysis module analyzes the standardized data through a preset data processing model to obtain visual data.
10. The method for visualizing plant data of claim 9 wherein the data analysis module comprises: a discrete data processing module;
the data analysis module analyzes the standardized data through a preset data processing model to obtain visual data, and the method comprises the following steps:
the discrete data processing module: the data definition method is used for establishing a relation network for discrete data in the standardized data through a Petri network to obtain a discrete data relation network, then performing data definition on each element in the discrete data relation network, using the discrete data relation network subjected to the data definition as visual integral data, and obtaining the visual data through the visual integral data.
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