CN114047729A - Natural plant processing control method, system, computer device and storage medium - Google Patents
Natural plant processing control method, system, computer device and storage medium Download PDFInfo
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- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM]
- G05B19/41865—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM] characterised by job scheduling, process planning, material flow
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
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- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
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Abstract
The present application relates to a natural plant processing control method, system, computer device and storage medium. The method comprises the following steps: acquiring industrial big data in a historical time period; acquiring control instructions of all natural plant processing subsystems; constructing an intelligent model associated with each natural plant processing subsystem according to natural plant knowledge, control instructions and industrial big data; controlling each natural plant processing subsystem according to the intelligent model associated with the corresponding natural plant processing subsystem. By adopting the method, a large amount of natural plant processing data are processed and analyzed, and the central control subsystem can respond to all natural plant processing subsystems in time, so that the automation degree and the control accuracy of the natural plant processing system are improved, and the processing efficiency of the natural plant processing system is further improved.
Description
Technical Field
The present application relates to the field of processing control technologies, and in particular, to a method, a system, a computer device, and a storage medium for controlling natural plant processing.
Background
With the approach of digitalization, informatization and intellectualization of processing, management and decision making of enterprise products, the processing system of the enterprise has the capability of thinking and working like people and gradually becomes the development direction of domestic raw material processing enterprises. However, the organic integration of natural plant processing control with modern scientific technology is not yet tight enough.
In the related art, the natural plant processing system only collects and stores data generated in industrial processing, and although a part of enterprises accumulate a large amount of processing data, the data are not processed, so that the intangible assets accumulated by the enterprises are not well utilized, the automation degree of the current natural plant processing system is low, the control theory is single, and each natural plant processing subsystem in the natural plant processing system cannot respond and accurately control in time, and the problem of low processing efficiency is caused. Therefore, a natural plant processing system is urgently needed.
Disclosure of Invention
In view of the above, there is a need to provide a natural plant processing control method, system, computer device and storage medium for solving the above technical problems.
A method for controlling natural plant processing, the method comprising:
acquiring industrial big data in a historical time period, wherein the industrial big data is used for representing data generated in the processing process of each natural plant processing subsystem;
acquiring control instructions of all natural plant processing subsystems;
constructing an intelligent model associated with each natural plant processing subsystem according to natural plant knowledge, control instructions and industrial big data;
controlling each natural plant processing subsystem according to the intelligent model associated with the corresponding natural plant processing subsystem.
In one embodiment, the natural plant processing subsystems are a raw material storage and transportation subsystem, a field shop production subsystem, and a finished product storage and transportation subsystem, respectively, and accordingly, the data generated by the natural plant processing subsystems during the processing process includes: the raw material storage and transportation subsystem generates raw material data in the processing process, the field workshop production subsystem generates production data in the processing process, and the finished product storage and transportation subsystem generates finished product data in the processing process.
In one embodiment, building an intelligent model associated with each natural plant processing subsystem based on natural plant knowledge, control instructions, and industrial big data comprises:
respectively carrying out data selection, data cleaning and data transformation on the industrial big data to obtain the processed industrial big data;
classifying the processed industrial big data according to the control instruction of each natural plant processing subsystem to obtain the input data of each intelligent model;
and constructing each intelligent model according to the natural plant knowledge and the input data of each intelligent model.
In one embodiment, the data selection, data cleaning and data transformation are respectively performed on the industrial big data to obtain the processed industrial big data, and the method includes:
selecting control data related to the natural plant processing subsystem from the industrial big data according to the control instruction, and acquiring the selected industrial big data;
removing error data in the selected industrial big data to obtain cleaned industrial big data;
and carrying out data standard transformation processing on the cleaned industrial big data to obtain the processed industrial big data.
In one embodiment, classifying the processed industrial big data according to the control command of each natural plant processing subsystem to obtain the input data of each intelligent model comprises:
according to the type of the data in the processed industrial big data, performing feature extraction on the processed industrial big data to obtain different feature variables;
and classifying the characteristic variables according to the control instruction of each natural plant processing subsystem to obtain the input data of each intelligent model.
In one embodiment, controlling each natural plant processing subsystem according to the intelligent model associated with the corresponding natural plant processing subsystem comprises:
acquiring output data of each intelligent model according to each intelligent model;
and controlling the corresponding natural plant processing subsystem according to the output data.
In one embodiment, controlling the corresponding natural plant processing subsystem according to the intelligent model associated with each natural plant processing subsystem comprises:
acquiring data generated by each natural plant processing subsystem at the current moment;
and matching the data generated at the current moment with the intelligent models associated with the natural plant processing subsystems to obtain the optimized intelligent models.
A natural plant processing control system, the system comprising: the system comprises an industrial internet subsystem, a raw material storage and transportation subsystem, a field workshop production subsystem, a finished product storage and transportation subsystem, a central control subsystem and a big data cloud platform subsystem;
the industrial Internet subsystem is used for connecting processing, storage and transportation equipment, a production line, a factory, a supplier, a product and a client through the Internet and is responsible for collecting data to form industrial big data and communicating and storing information and commands;
the raw material storage and transportation subsystem is used for storing and distributing various natural plant processing raw materials, transporting the raw materials to the on-site workshop production subsystem and uploading raw material information to the industrial Internet subsystem;
the field workshop production subsystem is used for managing and controlling corresponding production equipment and processes of a workshop production line, transporting the processed and packaged finished products to the finished product storage and transportation system, and uploading production information on the production line to the industrial Internet subsystem;
the finished product storage and transportation subsystem is used for transporting, distributing, counting, storing and warehousing the finished products obtained by processing and uploading the information of the finished products to the industrial internet subsystem;
the central control subsystem is used for uniformly issuing work orders of the raw material storage and transportation subsystem, the field workshop production subsystem and the finished product storage and transportation subsystem so as to coordinate normal and stable operation of each subsystem and ensure that each natural plant processing subsystem can be mastered;
and the big data cloud platform subsystem is used for establishing a mathematical intelligent model associated with each natural plant processing subsystem by taking industrial big data provided by the industrial internet subsystem as a basis and combining natural plant knowledge judgment with the aid of AI technical means such as data mining and machine learning, and providing a more optimized control strategy, key process points and process parameters for the central control subsystem.
A computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:
acquiring industrial big data in a historical time period, wherein the industrial big data is used for representing data generated in the processing process of each natural plant processing subsystem;
acquiring control instructions of all natural plant processing subsystems;
constructing an intelligent model associated with each natural plant processing subsystem according to natural plant knowledge, control instructions and industrial big data;
controlling each natural plant processing subsystem according to the intelligent model associated with the corresponding natural plant processing subsystem.
A computer-readable storage medium, on which a computer program is stored which, when executed by a processor, carries out the steps of:
acquiring industrial big data in a historical time period, wherein the industrial big data is used for representing data generated in the processing process of each natural plant processing subsystem;
acquiring control instructions of all natural plant processing subsystems;
constructing an intelligent model associated with each natural plant processing subsystem according to natural plant knowledge, control instructions and industrial big data;
controlling each natural plant processing subsystem according to the intelligent model associated with the corresponding natural plant processing subsystem.
The natural plant processing control method, the natural plant processing control system, the computer device and the storage medium acquire industrial big data in a historical time period, wherein the industrial big data is used for representing data generated by each natural plant processing subsystem in the processing process; acquiring control instructions of all natural plant processing subsystems; constructing an intelligent model associated with each natural plant processing subsystem according to natural plant knowledge, control instructions and industrial big data; controlling each natural plant processing subsystem according to the intelligent model associated with the corresponding natural plant processing subsystem.
Compared with the prior art that a large amount of processing and manufacturing data accumulated by natural plant processing enterprises cannot be fully utilized, the automatic degree of the current natural plant processing system is low, the control theory is single, the accumulated large amount of processing data can be processed, intelligent models associated with all natural plant processing subsystems are built according to the data, the central control subsystem can timely control and respond all the natural plant processing subsystems, the automatic degree and the control accuracy of the natural plant processing system can be improved, and the processing efficiency of the natural plant processing system is improved.
Drawings
FIG. 1 is a diagram illustrating an application environment of a natural plant processing control method according to an embodiment;
FIG. 2 is a schematic flow chart of a method for controlling natural plant processing according to an embodiment;
FIG. 3 is a block diagram showing the construction of a natural plant processing control system according to another embodiment;
FIG. 4 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
It will be understood that, as used herein, the terms "first," "second," and the like may be used herein to describe various terms, but these terms are not limited by these terms unless otherwise specified. These terms are only used to distinguish one term from another. For example, the third preset threshold and the fourth preset threshold may be the same or different without departing from the scope of the present application.
The natural plant processing system treatment method provided by the application can be applied to the application environment shown in figure 1. Wherein the terminal 101 communicates with the server 102 via a network. The terminal 101 collects industrial big data in a historical time period. The industrial big data in the historical time period is sent to the server 102. The server 102 constructs an intelligent model associated with each natural plant processing subsystem according to the natural plant knowledge and the industrial big data; controlling each natural plant processing subsystem according to the intelligent model associated with the corresponding natural plant processing subsystem. The terminal 101 may be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, and portable wearable devices, and the server 102 may be implemented by an independent server or a server cluster formed by a plurality of servers.
In one embodiment, as shown in fig. 2, there is provided a natural plant processing system processing method, which is illustrated by using the method as an example of a terminal in fig. 1, and comprises the following steps:
201. acquiring industrial big data in a historical time period, wherein the industrial big data is used for representing data generated in the processing process of each natural plant processing subsystem;
202. acquiring control instructions of all natural plant processing subsystems;
203. constructing an intelligent model associated with each natural plant processing subsystem according to natural plant knowledge, control instructions and industrial big data;
204. controlling each natural plant processing subsystem according to the intelligent model associated with the corresponding natural plant processing subsystem.
For the natural plant processing system in this application, it includes an industrial internet subsystem, individual natural plant processing subsystems, a central control subsystem, and a big data cloud platform subsystem. The industrial internet subsystem is responsible for connecting processing, storage and transportation equipment, production lines, factories, suppliers, products and customers through the internet. Moreover, the industrial internet subsystem is also responsible for acquiring, storing and transmitting data.
In addition, each natural plant processing subsystem is responsible for a specific process in natural plant processing and uploads data generated during the process to the industrial internet subsystem. The central control subsystem is responsible for issuing unified work orders to each natural plant processing subsystem so as to coordinate normal and stable operation of each natural plant processing subsystem and control processing of each natural plant processing subsystem in real time.
The big data cloud platform subsystem establishes intelligent models associated with all the natural plant processing subsystems by means of data mining, machine learning and other technical means on the basis of industrial big data provided by the industrial internet subsystem, and the central control subsystem can control the corresponding natural plant processing subsystems through the intelligent models.
In step 201 described above, the history period refers to a period of time before the current time. Specifically, the industrial internet subsystem acquires industrial big data of several months before the current moment, and transmits the acquired industrial big data to the big data cloud platform subsystem through the communication module. The embodiment of the present invention does not specifically limit the communication module used for transmitting data, and includes but is not limited to: WIFI, GPRS, 3G or 4G, Bluetooth, ZigBee, field bus and Ethernet communication module.
For example, the industrial internet subsystem acquires industrial big data of 3 months before the current time, and then transmits the industrial big data of three months to the big data cloud platform subsystem through the ethernet communication module.
In step 202, the control command refers to the control target of the central control subsystem on the natural plant processing subsystem, and the control targets of different natural plant processing subsystems are different.
In step 203, the natural plant knowledge refers to the related knowledge of the natural plant stored in the big data cloud platform subsystem; the intelligent model associated with each natural plant processing subsystem means that the central control subsystem can effect control of the corresponding natural plant processing subsystem in accordance with the intelligent model. Specifically, after the big data cloud platform subsystem processes the acquired industrial big data, the big data cloud platform subsystem judges the industrial big data by combining the control instruction and the natural plant knowledge stored by the system, and an intelligent model associated with each natural plant processing subsystem is constructed.
In step 204, the central control subsystem may adjust the control strategy of the corresponding natural plant processing subsystem according to the intelligent model associated with each natural plant processing subsystem, thereby controlling the key process points and process parameters of the natural plant processing subsystem.
According to the method provided by the embodiment of the invention, the accumulated large amount of processing data is processed, and the intelligent model associated with each natural plant processing subsystem is constructed according to the data, so that the central control subsystem can respond to each natural plant processing subsystem in time, the automation degree and the control accuracy of the natural plant processing system can be improved, and the processing efficiency of the natural plant processing system can be further improved.
In one embodiment, each natural plant processing subsystem is a raw material storage and transportation subsystem, a field workshop production subsystem, a finished product storage and transportation subsystem, respectively; accordingly, data generated during processing by each natural plant processing subsystem includes: the raw material storage and transportation subsystem generates raw material data in the processing process, the field workshop production subsystem generates production data in the processing process, and the finished product storage and transportation subsystem generates finished product data in the processing process.
Specifically, the raw material storage and transportation subsystem is responsible for storing and distributing various natural plant processing raw materials, transporting the natural plant processing raw materials to the on-site workshop production subsystem, and uploading raw material data generated in the process to the industrial internet subsystem.
The field workshop production subsystem is responsible for managing and controlling corresponding production equipment and processes of a workshop production line, transporting the produced and packaged finished products to the finished product storage and transportation subsystem, and uploading production data on the production line to the industrial Internet subsystem.
And the finished product storage and transportation subsystem is responsible for transporting, distributing, counting, storing and warehousing the finished products obtained by processing, and uploading the finished product data generated in the process to the industrial Internet subsystem.
According to the method provided by the embodiment of the invention, the raw material storage and transportation subsystem, the field workshop production subsystem and the finished product storage and transportation subsystem are used for uploading data to the industrial Internet subsystem, so that the industrial Internet subsystem can acquire a large amount of industrial big data, and a data basis is provided for establishing an intelligent model.
In one embodiment, building an intelligent model associated with each natural plant processing subsystem based on natural plant knowledge, control instructions, and industrial big data, comprises:
301. respectively carrying out data selection, data cleaning and data transformation on the industrial big data to obtain the processed industrial big data;
302. classifying the processed industrial big data according to the control instruction of each natural plant processing subsystem to obtain the input data of each intelligent model;
303. and constructing each intelligent model according to the natural plant processing knowledge and the input data of each intelligent model.
In the step 301, the data selection, the data cleaning and the data transformation are respectively performed on the industrial big data, so that valuable information is obtained from the industrial big data, and useful guidance and decision-making services are provided for the processing of the natural plant processing system.
In step 302, the control command of each natural plant processing subsystem refers to a control command issued by the central control subsystem for the natural plant processing subsystem.
In the step 303, data mining, machine learning, and the like are performed on the input data of each intelligent model through an AI technical means, and then judgment is performed by combining with natural plant knowledge in the big data cloud platform subsystem, so that each intelligent model can be constructed.
According to the method provided by the embodiment of the invention, the central control subsystem can timely respond to and accurately control each natural plant processing subsystem by classifying the huge amount of data generated by the natural plant processing subsystems in the processing process and constructing the corresponding intelligent model.
In one embodiment, the data selection, data cleaning and data transformation are respectively performed on the industrial big data to obtain the processed industrial big data, and the method includes:
401. selecting corresponding control data from the industrial big data according to the control instruction, and acquiring the selected industrial big data;
402. removing wrong data in the selected industrial big data to obtain cleaned industrial big data;
403. and carrying out data standard transformation processing on the cleaned industrial big data to obtain the processed industrial big data.
In step 401, according to the control commands of all the natural plant processing subsystems, selecting control data related to all the natural plant processing subsystems from the industrial big data, and obtaining the selected industrial big data, for example, the industrial big data includes data such as temperature, pressure, frequency, and rotation speed, and the data required by the control commands of all the natural plant processing subsystems are temperature, pressure, and frequency, and only the selected temperature, pressure, and frequency are used as the selected industrial big data.
In the step 402, there may be error data of format, content, logic, etc. in the selected industrial big data, for example, the temperature data has 50 ℃, 56 ℃, 400 ℃, 62 ℃, etc., so that it is necessary to remove the error data of 400 ℃ to obtain the cleaned industrial big data.
In the step 402, the embodiment of the present invention does not specifically limit the standard transformation process, and includes but is not limited to: feature binarization, feature normalization, continuous feature variation, qualitative feature dummy encoding, and the like.
According to the method provided by the embodiment of the invention, the accuracy of the input data can be improved by carrying out data selection, data cleaning and data transformation processing on the industrial big data, so that the accurate control precision of the intelligent model is improved.
In one embodiment, classifying the processed industrial big data according to the control command of each natural plant processing subsystem, and obtaining the input data of each intelligent model comprises:
501. according to the type of the data in the processed industrial big data, performing feature extraction on the processed industrial big data to obtain different feature variables;
502. and classifying the characteristic variables according to the control command of each model to obtain the input data of each intelligent model.
Specifically, the control commands of each natural plant processing subsystem have corresponding control targets according to respective processing tasks, and the processing tasks of each natural plant processing subsystem may include one or more than two, for example, the tasks of the raw material storage and transportation subsystem are to match the processing raw materials according to the best raw material ratio, complete the preparation of the processing raw materials in the shortest time, and the like.
According to the method provided by the embodiment of the invention, the processed industrial big data is classified through the big data cloud platform subsystem to obtain the input data of each intelligent model, and the accurate control of each natural plant processing subsystem can be realized, so that the processing efficiency of the natural plant processing system is improved, and the labor cost is further reduced.
In one embodiment, controlling each natural plant processing subsystem according to the intelligent model associated with the corresponding natural plant processing subsystem comprises:
601. acquiring output data of each intelligent model according to each intelligent model;
602. and controlling the corresponding natural plant processing subsystem according to the output data.
Specifically, the central control subsystem acquires output data of each intelligent model according to each intelligent model, and matches the output data with the corresponding natural plant processing subsystem, so that the natural plant processing subsystem is controlled by the output data.
According to the method provided by the embodiment of the invention, the central control subsystem can control different natural plant processing subsystems through different intelligent models, so that the control and decision-making capability of the central control subsystem is improved.
In one embodiment, controlling the corresponding natural plant processing subsystem according to the intelligent model associated with each natural plant processing subsystem comprises:
701. acquiring data generated by each natural plant processing subsystem at the current moment;
702. and matching the data generated at the current moment with the intelligent models associated with the natural plant processing subsystems to obtain the optimized intelligent models.
Specifically, the industrial internet subsystem acquires data generated by each natural plant processing subsystem at the current moment, analyzes and processes the data as industrial big data in a historical time period, and then matches the analyzed and processed data with the intelligent model so as to optimize the intelligent model.
According to the method provided by the embodiment, the intelligent model is optimized by acquiring the data generated at the current moment and analyzing and processing the data generated at the current moment, so that the control efficiency of the intelligent model can be improved, and the processing efficiency of the natural plant processing system is improved.
In one embodiment, as shown in fig. 3, there is provided a natural plant processing control system comprising: an industrial internet subsystem 311, a raw material storage and transportation subsystem 312, a field shop production subsystem 313, a finished product storage and transportation subsystem 314, a central control subsystem 315, and a big data cloud platform subsystem 316;
an industrial internet subsystem 311, which is used for connecting processing, storage and transportation equipment, production lines, factories, suppliers, products and customers through the internet to form industrial big data, and is responsible for collecting data to form industrial big data and communicating and storing information and commands;
a raw material storage and transportation subsystem 312, which is used for storing and distributing various natural plant processing raw materials, transporting the raw materials to a field workshop production subsystem 313, and uploading raw material information to an industrial internet subsystem 311;
the field workshop production subsystem 313 is used for managing and controlling corresponding production equipment and processes of a workshop production line, transporting the processed and packaged finished products to the finished product storage and transportation system 314 and uploading production information on the production line to the industrial internet subsystem 311;
a finished product storage and transportation subsystem 314, which is used for transporting, distributing, counting, storing and warehousing the finished products obtained by processing, and uploading the information of the finished products to the industrial internet subsystem 311;
the central control subsystem 315 is used for uniformly issuing work orders to the raw material storage and transportation subsystem 312, the field workshop production subsystem 313 and the finished product storage and transportation subsystem 314 so as to coordinate normal and stable operation of each subsystem and ensure that each natural plant processing subsystem can be mastered;
and the big data cloud platform subsystem 316 is used for establishing a mathematical intelligent model associated with each natural plant processing subsystem by taking industrial big data provided by the industrial internet subsystem 311 as a basis and combining natural plant knowledge judgment with the aid of AI technical means such as data mining and machine learning, and providing a more optimized control strategy, key process points and process parameters for the central control subsystem 315.
The big data cloud platform subsystem 316 comprises a big data integration layer, a big data analysis layer, data modeling, an application scene layer and an intelligent model.
In the natural plant processing process, equipment control has the characteristics of instantaneity and accuracy, the required data are not many in variety, but the data volume is huge, and data sensing, analysis, decision and control are required to form a real-time closed-loop information flow.
Specifically, the industrial big data are data resources generated by various sensors, instrument equipment, control, workshop production records, enterprises and the like; primarily data generated, collected and processed by industrial equipment and industrial software, as well as intermediate process control and quality inspection data.
The big data integration layer collects data from different sources and stores the data in a centralized manner, and provides accurate basic data for the big data analysis layer and the application scene layer.
The big data analysis layer comprises data preparation and feature extraction. Aiming at a specific business target, a natural plant processing big data set is flexibly organized, various big data analysis mining algorithms and technologies are flexibly selected and combined to use, valuable information and knowledge are obtained from big data, and decision-making service is provided for production guidance and business models.
Wherein, the data preparation is to provide correct data with a preset format for solving the service problem; data preparation includes data selection, data cleansing, and the like, and various combinations of methods are tried in the process. Feature extraction refers to the fact that simple and abstract features can be automatically extracted and combined into more complex features by adopting some AI algorithms, such as deep learning. In the exploratory analysis process, different methods are tried to convert data and the quality of feature extraction is evaluated by data modeling.
Data modeling refers to establishing an algorithm library, and inserting prepared data into each model when applied to match the best model.
The application scenario layer is distributed in the whole life cycle of natural plant processing design, research and development, production, manufacture and supply and sale, and the application scenario layer determines the upper limit of the big data value. And organizing corresponding data according to different application scenes to construct various applications.
The intelligent model comprises an intelligent model A, an intelligent model B and an intelligent model C, the intelligent models are respectively corresponding to the intelligent models constructed by the raw material storage and transportation subsystem 312, the field workshop production subsystem 313 and the finished product storage and transportation subsystem 314, and the independent model construction is carried out according to different natural plant processing subsystem data, so that data squeezing is avoided, and the constructed models can timely and accurately respond to and control the natural plant processing subsystem.
According to the system provided by the embodiment of the invention, the big data cloud platform subsystem 316 is used for carrying out corresponding data processing, analysis, mining and modeling on the data of each natural plant processing subsystem in the natural plant processing system, and the model of each natural plant processing subsystem is respectively constructed while making full use of a large amount of manufacturing data, so that the natural plant processing subsystems are timely and accurately responded and controlled, and the processing efficiency of the natural plant processing system is further improved.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 4. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer device is used for storing the preset threshold value. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a natural plant processing control system.
Those skilled in the art will appreciate that the architecture shown in fig. 4 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided, comprising a memory and a processor, the memory having a computer program stored therein, the processor implementing the following steps when executing the computer program:
acquiring industrial big data in a historical time period, wherein the industrial big data is used for representing data generated in the processing process of each natural plant processing subsystem;
acquiring control instructions of all natural plant processing subsystems;
constructing an intelligent model associated with each natural plant processing subsystem according to natural plant knowledge, control instructions and industrial big data;
controlling each natural plant processing subsystem according to the intelligent model associated with the corresponding natural plant processing subsystem.
In one embodiment, the processor, when executing the computer program: each natural plant processing subsystem is raw materials storage and transportation subsystem, on-the-spot workshop production subsystem, finished product storage and transportation subsystem respectively, and correspondingly, the data that each natural plant processing subsystem produced in the course of working includes: the raw material storage and transportation subsystem generates raw material data in the processing process, the field workshop production subsystem generates production data in the processing process, and the finished product storage and transportation subsystem generates finished product data in the processing process.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
respectively carrying out data selection, data cleaning and data transformation on the industrial big data to obtain the processed industrial big data;
classifying the processed industrial big data according to the control instruction of each natural plant processing subsystem to obtain the input data of each intelligent model;
and constructing each intelligent model according to the natural plant knowledge and the input data of each intelligent model.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
selecting control data related to the natural plant processing subsystem from the industrial big data according to the control instruction, and acquiring the selected industrial big data;
removing error data in the selected industrial big data to obtain cleaned industrial big data;
and carrying out data standard transformation processing on the cleaned industrial big data to obtain the processed industrial big data.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
according to the type of the data in the processed industrial big data, performing feature extraction on the processed industrial big data to obtain different feature variables;
and classifying the characteristic variables according to the control instruction of each natural plant processing subsystem to obtain the input data of each intelligent model.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
acquiring output data of each intelligent model according to each intelligent model;
and controlling the corresponding natural plant processing subsystem according to the output data.
In one embodiment, the processor, when executing the computer program, further performs the steps of:
acquiring data generated by each natural plant processing subsystem at the current moment;
and matching the data generated at the current moment with the intelligent models associated with the natural plant processing subsystems to obtain the optimized intelligent models.
In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of:
acquiring industrial big data in a historical time period, wherein the industrial big data is used for representing data generated in the processing process of each natural plant processing subsystem;
acquiring control instructions of all natural plant processing subsystems;
constructing an intelligent model associated with each natural plant processing subsystem according to natural plant knowledge, control instructions and industrial big data;
controlling each natural plant processing subsystem according to the intelligent model associated with the corresponding natural plant processing subsystem.
In one embodiment, the computer program when executed by the processor further performs the steps of: each natural plant processing subsystem is respectively a raw material storage and transportation subsystem, a field workshop production subsystem, a finished product storage and transportation subsystem, and correspondingly, the data generated by each natural plant processing subsystem in the processing process comprises: the raw material storage and transportation subsystem generates raw material data during the production process, production data during the production process, and finished product data generated by the finished product storage and transportation subsystem.
In one embodiment, the computer program when executed by the processor further performs the steps of:
respectively carrying out data selection, data cleaning and data transformation on the industrial big data to obtain the processed industrial big data;
classifying the processed industrial big data according to the control instruction of each natural plant processing subsystem to obtain the input data of each intelligent model;
and constructing each intelligent model according to the natural plant knowledge and the input data of each intelligent model.
In one embodiment, the computer program when executed by the processor further performs the steps of:
selecting control data related to the natural plant processing subsystem from the industrial big data according to the control instruction, and acquiring the selected industrial big data;
removing error data in the selected industrial big data to obtain cleaned industrial big data;
and carrying out data standard transformation processing on the cleaned industrial big data to obtain the processed industrial big data.
In one embodiment, the computer program when executed by the processor further performs the steps of:
according to the type of the data in the processed industrial big data, performing feature extraction on the processed industrial big data to obtain different feature variables;
and classifying the characteristic variables according to the control instruction of each natural plant processing subsystem to obtain the input data of each intelligent model.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring output data of each intelligent model according to each intelligent model;
and controlling the corresponding natural plant processing subsystem according to the output data.
In one embodiment, the computer program when executed by the processor further performs the steps of:
acquiring data generated by each natural plant processing subsystem at the current moment;
and matching the data generated at the current moment with the intelligent models associated with the natural plant processing subsystems to obtain the optimized intelligent models.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database or other medium used in the embodiments provided herein can include at least one of non-volatile and volatile memory. Non-volatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical storage, or the like. Volatile Memory can include Random Access Memory (RAM) or external cache Memory. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A method for controlling natural plant processing, said method comprising:
acquiring industrial big data in a historical time period, wherein the industrial big data is used for representing data generated in the processing process of each natural plant processing subsystem;
acquiring control instructions of the natural plant processing subsystems;
constructing an intelligent model associated with each natural plant processing subsystem according to the natural plant knowledge, the control instructions and the industrial big data;
controlling each natural plant processing subsystem according to the intelligent model associated with the corresponding natural plant processing subsystem.
2. The method of claim 1, wherein each of the natural plant processing subsystems is a raw material storage and transportation subsystem, a field shop production subsystem, and a finished product storage and transportation subsystem, respectively, and accordingly, the data generated by each of the natural plant processing subsystems during the processing comprises: the raw material storage and transportation subsystem generates raw material data in the processing process, the field workshop production subsystem generates production data in the processing process, and the finished product storage and transportation subsystem generates finished product data in the processing process.
3. The method of claim 1, wherein said building an intelligent model associated with each natural plant processing subsystem from natural plant knowledge, said control instructions, and industrial big data comprises:
respectively carrying out data selection, data cleaning and data transformation on the industrial big data to obtain the processed industrial big data;
classifying the processed industrial big data according to the control instruction of each natural plant processing subsystem to obtain the input data of each intelligent model;
and constructing each intelligent model according to the natural plant knowledge and the input data of each intelligent model.
4. The method according to claim 3, wherein the performing data selection, data cleaning and data transformation on the industrial big data respectively to obtain the processed industrial big data comprises:
selecting control data related to a natural plant processing subsystem from the industrial big data according to the control instruction, and acquiring the selected industrial big data;
removing error data in the selected industrial big data to obtain cleaned industrial big data;
and carrying out data standard transformation processing on the cleaned industrial big data to obtain the processed industrial big data.
5. The method of claim 3, wherein the classifying the processed industrial big data according to the control command of each natural plant processing subsystem to obtain the input data of each intelligent model comprises:
according to the type of the data in the processed industrial big data, performing feature extraction on the processed industrial big data to obtain different feature variables;
and classifying the characteristic variables according to the control instruction of each natural plant processing subsystem to obtain the input data of each intelligent model.
6. The method of claim 1, wherein said controlling a corresponding natural plant processing subsystem according to said intelligent model associated with each natural plant processing subsystem comprises:
acquiring output data of each intelligent model according to each intelligent model;
and controlling the corresponding natural plant processing subsystem according to the output data.
7. The method of claim 1, wherein said controlling the corresponding natural plant processing subsystem according to the intelligent model associated with each natural plant processing subsystem comprises:
acquiring data generated by each natural plant processing subsystem at the current moment;
and matching the data generated at the current moment with the intelligent models associated with the natural plant processing subsystems to obtain the optimized intelligent models.
8. A natural plant processing control system, comprising: the system comprises an industrial internet subsystem, a raw material storage and transportation subsystem, a field workshop production subsystem, a finished product storage and transportation subsystem, a central control subsystem and a big data cloud platform subsystem;
the industrial Internet subsystem is used for connecting processing, storage and transportation equipment, a production line, a factory, a supplier, a product and a client through the Internet and is responsible for collecting data to form industrial big data and communicating and storing information and commands;
the raw material storage and transportation subsystem is used for storing and distributing various natural plant processing raw materials, transporting the raw materials to the on-site workshop production subsystem and uploading raw material information to the industrial Internet subsystem;
the field workshop production subsystem is used for managing and controlling corresponding production equipment and processes of a workshop production line, transporting the processed and packaged finished products to the finished product storage and transportation system, and uploading production information on the production line to the industrial Internet subsystem;
the finished product storage and transportation subsystem is used for transporting, distributing, counting, storing and warehousing the finished products obtained by processing and uploading the information of the finished products to the industrial internet subsystem;
the central control subsystem is used for uniformly issuing work orders of the raw material storage and transportation subsystem, the field workshop production subsystem and the finished product storage and transportation subsystem so as to coordinate normal and stable operation of each subsystem and ensure that each natural plant processing subsystem can be mastered;
and the big data cloud platform subsystem is used for establishing a mathematical intelligent model associated with each natural plant processing subsystem by taking industrial big data provided by the industrial internet subsystem as a basis and combining natural plant knowledge judgment with the aid of AI technical means such as data mining and machine learning, and providing a more optimized control strategy, key process points and process parameters for the central control subsystem.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.
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