Dense medium coal separation density control and decision-making system based on end-side cloud collaboration

Abstract

The utility model discloses a dense-medium coal separation density control and decision-making system based on end-side cloud collaboration. The dense-medium coal separation density control and decision-making system comprises an ash content meter and a PLC (Programmable Logic Controller), the real-time ash content detection module is connected with the ash content meter through the Ethernet; the Flask rear-end module is connected with the real-time ash content detection module through Axios; the density detection module is connected with the PLC through the Ethernet; the test ash content input module is connected with the Flask rear-end module through Axios; the database storage module is connected with the Flask back-end module through a MySQL protocol; the density decision module is connected with the Flask rear-end module and the density detection module through Axios; the dense medium density decision-making model is connected with the density decision-making module through a TCP / IP protocol; and the dense medium density decision database is connected with the dense medium density decision model and the database storage module through the MySQL protocol. According to the utility model, a dense medium density decision-making scheme is displayed to a production decision maker through a visual method, a dense medium density control loop is guided to make corresponding adjustment, the decision-making efficiency is improved, and the dense medium separation production process is optimized.

Description

Technical Field

[0001] The utility model relates to the technical field of heavy medium coal preparation, and in particular to a heavy medium coal preparation density control and decision-making system based on end-edge-cloud collaboration. Background Art

[0002] Heavy media separation is a crucial step in the coal sorting process. Utilizing the sink-float principle, heavy media is added to the coal washing liquid. Pure coal, with a lower density than the medium, floats, while gangue or medium coal, with a higher density, sinks. These are then collected and separated into different products. Data shows that my country's coal production has increased steadily in recent years, and production is expected to maintain a relatively stable growth trend in the future. As the effective treatment step in coal sorting, heavy media separation has become crucial for improving resource utilization. Driven by intelligent coal mine policies and the next generation of artificial intelligence technologies, intelligent coal heavy media separation is imperative.

[0003] In actual industrial production, due to the long production cycle of the heavy medium separation process, the high degree of correlation between the intermediate processes of the heavy medium, and the many factors affecting the results of the heavy medium separation, the density decision of the heavy medium process has always been made by on-site workers based on the water intake, the ash content of the clean coal, and years of experience. This operation method is often subjective and arbitrary, which is very likely to lead to unsatisfactory clean coal ash content control results, high labor intensity for workers, and unnecessary loss of manpower and material resources. It is also difficult to achieve online continuous detection of clean coal ash content, unable to perceive parameter changes in real time, and difficult to establish accurate mathematical models to ensure the optimization of clean coal ash content in real time.

[0004] At the same time, critical data such as density and clean coal ash content in the heavy medium production process are often of primary concern to production managers. However, statistics for these data are often limited to paper reports and on-site records, without the use of visualization methods such as percentages and progress curves. This data presentation significantly limits production managers' understanding of actual production conditions, hindering the adoption of appropriate density control strategies and the rapid identification of weaknesses and critical control points in actual production. Furthermore, it fails to meet the current requirements for efficient, visual, and refined progress management in project construction. Therefore, building a heavy medium coal preparation density control and decision-making system based on end-edge-cloud collaboration is of great significance. Utility Model Content

[0005] In order to solve the above technical problems, the utility model provides a heavy medium coal preparation density control and decision-making system based on end-edge-cloud collaboration.

[0006] In order to achieve the above technical objectives, the present invention adopts the following technical solutions:

[0007] A dense medium coal preparation density control and decision-making system based on end-edge-cloud collaboration, including:

[0008] The terminal side includes: ash analyzer and PLC; PLC is connected with heavy medium cyclone, density meter, combined medium barrel level gauge, diverter valve, water supply valve, magnetic content meter, and dewatering valve;

[0009] Side, side includes:

[0010] Real-time ash detection module, connected to the ash analyzer via Ethernet;

[0011] The Flask backend module communicates with the real-time ash detection module through Axios;

[0012] Density detection module, connected to PLC communication via Ethernet;

[0013] The ash content entry module communicates with the Flask backend module through Axios;

[0014] The database storage module communicates with the Flask backend module through the MySQL protocol and communicates with the PLC through the TCP / IP protocol;

[0015] The density decision module is connected to the Flask backend module and the density detection module through Axios;

[0016] Visual Web module, connected to the Flask backend module through the switch module;

[0017] The mobile phone web terminal is connected to the visual web module through the wireless communication module;

[0018] The cloud side includes:

[0019] The heavy medium density decision model is connected to the density decision module through the TCP / IP protocol;

[0020] The heavy medium density decision database is connected to the heavy medium density decision model and the database storage module through the MySQL protocol.

[0021] Preferably;

[0022] The real-time ash detection module is used to display the clean coal ash detection data of the ash analyzer through the front-end web interface;

[0023] The density detection module is used to display the detection data of the density meter connected to the PLC through the front-end web interface.

[0024] Preferably;

[0025] The test ash content entry module is used to receive the manually entered test ash content data;

[0026] The database storage module is used to store the ash meter detection data, PLC collection data and manually entered laboratory ash data in the heavy medium coal preparation production process into the heavy medium density decision database;

[0027] The density decision module is used to obtain data from the heavy medium density decision database in real time, derive the recommended value of density decision based on the heavy medium density decision model, and then communicate with the PLC through the density detection module to control the heavy medium density.

[0028] Preferably;

[0029] The Flask backend module is used to interact with the front-end web interface data.

[0030] Preferably;

[0031] The heavy medium density decision model reads the manual ash data entered by the ash entry module and the data collected by PLC through the MySQL protocol to update the model, and then transfers the model structure and parameters to the density decision module through the TCP / IP protocol for use.

[0032] Compared with the prior art, the present invention has the following beneficial effects:

[0033] The utility model proposes a heavy medium coal preparation density control and decision-making system based on end-edge-cloud collaboration. The system realizes near-source execution of data processing and cloud-based execution of complex calculations, thereby compensating for the problems of high cloud computing latency and limited edge computing capabilities in the application process, and realizes real-time monitoring and intelligent analysis and decision-making of the production process, real-time and accuracy of data processing, and diversified display of production data. It supports access from computers within the local area network and mobile browsers, and presents the heavy medium density decision-making plan to production decision makers in a visual way, guiding the heavy medium density control loop to make corresponding adjustments, improving decision-making efficiency, and optimizing the heavy medium separation production process. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0035] Figure 1 It is a schematic structural diagram of the utility model. DETAILED DESCRIPTION

[0036] The specific implementation of the present invention will be further described below with reference to the accompanying drawings.

[0037] like Figure 1As shown in the figure, a dense medium coal preparation density control and decision-making system based on end-edge-cloud collaboration includes:

[0038] The terminal side includes: ash analyzer and PLC; PLC is connected with heavy medium cyclone, density meter, combined medium barrel level gauge, diverter valve, water supply valve, magnetic content meter, and dewatering valve;

[0039] Side, side includes:

[0040] The real-time ash content detection module is connected to the ash content meter via Ethernet. The real-time ash content detection module is used to display the clean coal ash content detection data of the ash content meter through the front-end web interface.

[0041] The Flask backend module communicates with the real-time ash detection module through Axios; the Flask backend module is used to interact with the front-end Web interface data.

[0042] The density detection module is connected to the PLC via Ethernet; the density detection module is used to display the detection data of the density meter connected to the PLC through the front-end web interface.

[0043] The ash content entry module communicates with the Flask backend module through Axios; the ash content entry module is used to receive manually entered ash content data;

[0044] The database storage module communicates with the Flask backend module via the MySQL protocol and with the PLC via the TCP / IP protocol. The database storage module is used to store the ash meter detection data, PLC collection data, and manually entered laboratory ash data in the heavy medium coal preparation production process into the heavy medium density decision database.

[0045] The density decision module is connected to the Flask backend module and the density detection module through Axios respectively; the density decision module is used to obtain data from the heavy medium density decision database in real time, derive the recommended value of the density decision based on the heavy medium density decision model, and then communicate with the PLC through the density detection module to control the heavy medium density.

[0046] Visual Web module, connected to the Flask backend module through the switch module;

[0047] The mobile phone web terminal is connected to the visual web module through the wireless communication module;

[0048] The cloud side includes:

[0049] The heavy medium density decision model communicates with the density decision module through the TCP / IP protocol; the heavy medium density decision model reads the manual ash data entered by the ash entry module and the data collected by the PLC through the MySQL protocol to update the model, and then passes the model structure and parameters to the density decision module for use through the TCP / IP protocol.

[0050] The heavy medium density decision database is connected to the heavy medium density decision model and the database storage module through the MySQL protocol.

[0051] The utility model proposes a heavy medium coal preparation density control and decision-making system based on end-edge-cloud collaboration, which solves the problems encountered in the current intelligent construction of coal preparation plants, such as the difficulties in data collection and integration, and the reliance on manual experience in the decision-making process. It realizes the real-time collection of production data and presents various process data to production decision makers in a visual way. By establishing a heavy medium coal preparation density control and decision-making system based on end-edge-cloud collaboration, the heavy medium density decision-making plan generated by data analysis is automatically presented to production decision makers, so that production decision makers can better grasp the production data, improve the decision-making accuracy and efficiency, and continuously optimize the production process, providing a new method for realizing the intelligence of heavy medium separation systems.

[0052] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A dense medium coal preparation density control and decision-making system based on end-edge-cloud collaboration, characterized by: include: The terminal side includes: ash analyzer and PLC; PLC is connected with heavy medium cyclone, density meter, combined medium barrel level gauge, diverter valve, water supply valve, magnetic content meter, and dewatering valve; Side, side includes: Real-time ash detection module, connected to the ash analyzer via Ethernet; The Flask backend module communicates with the real-time ash detection module through Axios; Density detection module, connected to PLC communication via Ethernet; The ash content entry module communicates with the Flask backend module through Axios; The database storage module communicates with the Flask backend module through the MySQL protocol and communicates with the PLC through the TCP / IP protocol; The density decision module is connected to the Flask backend module and the density detection module through Axios; Visual Web module, connected to the Flask backend module through the switch module; The mobile phone web terminal is connected to the visual web module through the wireless communication module; The cloud side includes: The heavy medium density decision model is connected to the density decision module through the TCP / IP protocol; The heavy medium density decision database is connected to the heavy medium density decision model and the database storage module through the MySQL protocol.

2. The dense medium coal preparation density control and decision-making system based on end-edge-cloud collaboration according to claim 1 is characterized in that: The real-time ash detection module is used to display the clean coal ash detection data of the ash analyzer through the front-end web interface; The density detection module is used to display the detection data of the density meter connected to the PLC through the front-end web interface.

3. The dense medium coal preparation density control and decision-making system based on end-edge-cloud collaboration according to claim 1 is characterized in that: The test ash content entry module is used to receive the manually entered test ash content data; The database storage module is used to store the ash meter detection data, PLC collection data and manually entered laboratory ash data in the heavy medium coal preparation production process into the heavy medium density decision database; The density decision module is used to obtain data from the heavy medium density decision database in real time, derive the recommended value of density decision based on the heavy medium density decision model, and then communicate with the PLC through the density detection module to control the heavy medium density.

4. The dense medium coal preparation density control and decision-making system based on end-edge-cloud collaboration according to claim 1 is characterized in that: The Flask backend module is used to interact with the front-end web interface data.

5. The dense medium coal preparation density control and decision-making system based on end-edge-cloud collaboration according to claim 1 is characterized in that: The heavy medium density decision model reads the manual ash data entered by the ash entry module and the data collected by PLC through the MySQL protocol to update the model, and then transfers the model structure and parameters to the density decision module through the TCP / IP protocol for use.

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