A tobacco primary processing line production awareness and interactive control system

Abstract

The application discloses a tobacco primary processing production line production sensing and interactive control system, which comprises a primary processing production line sensing module, a PLC automatic control system, a second bus communication module, an air conditioner and lighting system, a MongoDB database module and a first bus communication module.The first bus communication module is used for realizing data interaction with the PLC automatic control system to read temperature, flow and weight state parameters of unpacking, moisture recovery, cutting, feeding and drying process equipment in the PLC automatic control system.The second bus communication module is used for realizing data interaction with the air conditioner and lighting system to read running states of the unpacking, moisture recovery, cutting, feeding and drying process equipment and to calculate the switch and power of the air conditioner and lighting system.The MongoDB database module is used for storing upstream and downstream relationships of the unpacking, moisture recovery, cutting, feeding and drying process equipment of the primary processing production line and storing real-time data of equipment temperature, flow and weight state parameters.The application realizes dynamic intelligent control and energy-saving effect.

Description

Technical Field

[0001] This invention belongs to the field of intelligent manufacturing technology in the tobacco industry, specifically relating to a production perception and interactive control system for a tobacco processing production line. Background Technology

[0002] The tobacco processing workshop is highly automated. Taking the tobacco processing process as an example, from unpacking the tobacco leaves to re-moistening, cutting, and then feeding and drying, all of the above processes have been automatically controlled based on PLCs. However, due to the long overall process of the tobacco processing line and the large number of tobacco brands and batches, the PLC system data is relatively isolated, which poses a new challenge to building a smart tobacco workshop with an automation system at its core.

[0003] Therefore, it is necessary to establish a production perception and control interaction system with an automated control system at its core to improve the carbon reduction, energy consumption reduction, cost reduction and efficiency improvement level of tobacco processing. Summary of the Invention

[0004] To address the aforementioned technical problems in existing technologies, this invention provides a production sensing and interactive control system for tobacco processing lines. This system is open and interactive, and can reduce energy consumption in tobacco processing workshops. This invention connects the automatic control system with environmental systems such as lighting and air conditioning, enabling the production environment to dynamically adapt and adjust as production progresses.

[0005] The technical solution adopted in this invention is:

[0006] A tobacco processing production line sensing and interactive control system, characterized in that it includes:

[0007] The sensing module of the silk production line interacts with the PLC automatic control system through the first bus communication module to read the temperature, flow rate, and weight status parameters of the equipment in the unpacking, rehydration, slicing, feeding, and drying processes of the PLC automatic control system.

[0008] The environmental system interactive control module interacts with the air conditioning and lighting systems via the second bus communication module to read the operating status of the equipment in the unpacking, rehumidification, shredding, feeding, and drying processes, and to control the opening and closing of the air conditioning and lighting systems as well as their operating power.

[0009] The MongoDB database module interacts with the silk production line sensing module and the environmental system control module through the database API interface. It is used to read and store the upstream and downstream relationships of the equipment in the unpacking, rehydration, slicing, feeding and drying processes of the silk production line, as well as real-time data on the temperature, flow rate and weight status parameters of the equipment.

[0010] Furthermore, the environmental interaction control module controls the on / off state and operating power of the air conditioning and lighting systems, specifically including:

[0011] The silk production line is divided into N L *N W The grid, the lighting system is divided into The grid, the air conditioning system is divided into The grid;

[0012] The heat status of the wire forming production line grid is determined based on the equipment operating status. If all equipment in the grid is not started, the grid heat result is 0. If some or all equipment in the grid is started, the heat of the grid in the m-th row and n-th column is calculated as shown in the following formula (1):

[0013]

[0014] Where, θ i P represents the heat dissipated in the grid when the i-th device is at full load. i full P represents the load state when the i-th device is at full load. i This indicates the current load status of the i-th device. This represents the base load of the j-th upstream portion of the i-th device. This represents the maximum base load of the current portion of the i-th device, which is the maximum load allocated to that portion;

[0015] The above formula represents the load P of the i-th device. i The heat emitted by the device will only begin to be measured within the current grid when it exceeds the total base load of the upstream portion.

[0016] Furthermore, for the lighting system grid and the air conditioning system grid, the heat occupation statistics from the silk production line grid are redistributed to the lighting system grid and the air conditioning system grid. The redistribution method is as follows:

[0017] Search for the index and area of ​​the silk production line grid covered in the m-th row and n-th column grid of the lighting system or air conditioning system. Multiply the area of ​​the covered silk production line grid by the heat value according to the ratio of the area of ​​the covered silk production line grid to the original silk production line grid, and sum them to obtain the heat value of the m-th row and n-th column grid of the lighting system or air conditioning system.

[0018] For a lighting system, if the heat of the grid in the m-th row and n-th column is greater than 0, then the switch for the corresponding area is turned on.

[0019] For air conditioning systems, adjust them as follows:

[0020] For each air conditioning system grid, the deviation between the grid heat at the current moment and the grid heat at the previous moment is calculated as ΔΘ. mn The deviation between the current ambient temperature of the grid and the set temperature of the air conditioning system is calculated as ΔT. mnBy adjusting ΔΘ mn and ΔT mn These two variables are used to establish a fuzzy table and fuzzy rules.

[0021] Furthermore, the specific method for calculating the change in the air conditioner temperature setpoint is as follows:

[0022] For ΔΘ mn and ΔT mn Establish a five-level fuzzy table, which corresponds to the degree of deviation and weight of the five heat change trends or temperature deviation ranges;

[0023] Fuzzy rules reflect the necessity of adjusting the air conditioner temperature setting under different heat change trends and temperature deviations, and are represented by row vector A.

[0024] Calculate the fuzzy result of the air conditioner temperature adjustment, and determine the adjustment range of the set value according to the table lookup method.

[0025] Compared with the prior art, the beneficial effects of the present invention are reflected in:

[0026] It can determine whether the corresponding lighting and air conditioning systems need to be turned on and adjusted based on the operating status of the silk production line equipment, thereby achieving dynamic intelligent control and energy-saving effects. Attached Figure Description

[0027] Figure 1 This is a schematic diagram of the data interaction process of the control system of the present invention.

[0028] Figure 2 This is a schematic diagram of the tobacco flow direction according to the present invention.

[0029] Figure 3 This is a flowchart of the control system method of the present invention.

[0030] in, Figure 2 The three gray conveyor belts transport tobacco from left to right. Detailed Implementation

[0031] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit the scope of the present invention.

[0032] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other.

[0033] The present invention will now be described in detail with reference to the accompanying drawings and exemplary embodiments.

[0034] refer to Figure 1 , Figure 2 and Figure 3 The present invention discloses a tobacco processing production line sensing and interactive control system, comprising a tobacco processing production line sensing module, an environmental system interactive control module, a first bus communication module, a second bus communication module, and a MongoDB database module. The tobacco processing production line sensing module, the environmental system interactive control module, and the MongoDB database module achieve data reading and storage through a database API interface. The tobacco processing production line sensing module and the PLC automatic control system achieve data interaction through the first bus communication module. The environmental system interactive control module and the lighting and air conditioning systems achieve data interaction through the second bus communication module.

[0035] Specifically, the tobacco processing line sensing module reads status parameters such as temperature, flow rate, and weight of equipment in processes like unpacking, rehydration, shredding, feeding, and drying from the PLC automatic control system via the first bus communication module, and obtains the tobacco grade and batch identifier. The sensing module connects to a MongoDB database via a database API interface to store the upstream and downstream relationships of equipment in these processes, as well as real-time data on equipment temperature, flow rate, and weight.

[0036] The above process describes the operating status of the equipment, such as the change in the flow rate of tobacco on the conveyor belt from start to finish: initially 0, then reaching full flow, and then decreasing back to 0. The specific method is not described here.

[0037] Specifically, the environmental system interactive control module connects to the MongoDB database module through the database API interface, reads the operating status of equipment in processes such as unpacking, rehumidification, shredding, feeding, and drying, calculates the switching and power of the lighting and air conditioning systems, and controls the switching and power of the lighting and air conditioning systems through the second bus communication module.

[0038] In this embodiment, the method by which the environmental interactive control system calculates the switching and power of the lighting system and air conditioning system is as follows:

[0039] The silk production line is divided into N L *N W The grid (3x5 solid line grid) is used to divide the lighting system into... The grid (2x4 dashed grid) is used to divide the air conditioning system into... The grid (2x4 dashed grid);

[0040] The heat status of the wire-making production line grid is determined based on the equipment operating status. Specifically, if all equipment in the grid is not started, the grid heat result is 0. If some or all equipment in the grid is started, the heat of the grid in the m-th row and n-th column is calculated as shown in the following formula (1):

[0041]

[0042] Where, θ i P represents the heat dissipated in the grid when the i-th device is at full load (a parameter that needs to be set). i full P represents the load state when the i-th device is at full load. i This indicates the current load status of the i-th device. This represents the base load of the j-th upstream portion of the i-th device. The above formula indicates that when the load P of the i-th device... i The heat emitted by the device will only begin to be measured within the current grid when it exceeds the total base load of the upstream portion.

[0043] For example, for Figure 2 The first conveyor belt at the top center states that it spans three grids. Based on the area occupied by the conveyor belt within each grid, their base loads from left to right are 78, 100, and 78, respectively. Its contribution to the grid heat in the first row and first column of the grid is...

[0044]

[0045] This indicates that the conveyor belt in the first row and first column of the grid has no upstream base load. Therefore, when the load on the conveyor belt is 200, the heat generated in the grid of the first row and first column is...

[0046] Similarly, its contribution to the grid heat in the 1st row and 2nd column is...

[0047]

[0048] This indicates that there is an upstream base load on the conveyor belt in the grid of row 1, column 2. Therefore, when the load on the conveyor belt is 200, the heat generated in the grid of the 1st row and 2nd column is...

[0049] Similarly, its contribution to the grid heat in the 1st row and 3rd column is...

[0050]

[0051] This indicates that there is an upstream base load on the conveyor belt in the grid of row 1 and column 3. Therefore, when the load on the conveyor belt is 200, the heat generated in the grid of the 1st row and 3rd column is...

[0052] For the lighting system grid and the air conditioning system grid, the heat occupation statistics from the silk production line grid are redistributed to the lighting system grid and the air conditioning system grid. The redistribution method is as follows: search for the index and area of ​​the silk production line grid covered by the lighting system or air conditioning system grid in the m-th row and n-th column. Multiply the area of ​​the covered silk production line grid by the heat value according to the ratio of the area of ​​the covered silk production line grid to the original silk production line grid, and sum them to obtain the heat value of the lighting system or air conditioning system grid in the m-th row and n-th column.

[0053] Specifically, taking the first row and first column of the lighting system as an example, it occupies the first row and first column of the entire silk production line grid, and part of the first row and second column grid, the second row and first column grid, and the second row and second column grid. Based on the area ratio and the heat of the silk production line grid, the heat of the first row and first column of the lighting system is calculated.

[0054] For a lighting system, if the heat in the grid in row m and column n is greater than 0, then the switch in the corresponding area is turned on.

[0055] For air conditioning systems, adjust them as follows:

[0056] For each air conditioning system grid, the deviation between the grid heat at the current moment and the grid heat at the previous moment is calculated as ΔΘ. mn The deviation between the current ambient temperature of the grid and the set temperature of the air conditioning system is calculated as ΔT. mn By establishing fuzzy tables and fuzzy rules for these two variables, the change in the air conditioning temperature setpoint is calculated. The specific method is as follows:

[0057] For ΔΘ mn and ΔT mn Five fuzzy tables were created, as shown in Table 1 and Table 2, to describe the air conditioning temperature setpoint adjustment strategies and weights under the five heat change trends and temperature deviation ranges, respectively.

[0058] Table 1. Air Conditioning Temperature Setpoint Adjustment Strategies and Weights Corresponding to Five Heat Change Trends Table 1. Air Conditioning Temperature Setpoint Adjustment Strategies and Weights for Five Heat Change Trends

[0059]

[0060]

[0061] Table 2. Air Conditioning Temperature Setpoint Adjustment Strategies and Weights for Five Temperature Deviation Ranges

[0062]

[0063] Fuzzy rules reflect the necessity of adjusting the air conditioner temperature setpoint under different heat change trends and temperature deviations, and are represented by row vector A;

[0064] The row vector A is calculated by setting up matrix M, which is represented as follows:

[0065]

[0066] The matrix above shows that, compared to the heat change trend, temperature deviation is more important for adjusting the temperature setpoint. Therefore, the top right element of the matrix is ​​3, indicating that temperature deviation is more important than heat change trend for adjusting the temperature setpoint, and thus requires more adjustment. The bottom left element... This indicates the reciprocal relationship between the two.

[0067] Multiplying the elements of each row of matrix M and taking the square root, we get:

[0068]

[0069] After normalization, we get:

[0070] A = [0.75 0.25]

[0071] Calculate the fuzzy result of the air conditioner temperature adjustment, and determine the adjustment range of the set value according to the table lookup method.

[0072] When the heat change trend ΔΘ mn =0, temperature deviation ΔT mn When = 0, according to the fuzzy table, the resulting fuzzy vectors are [0,0.1,0.8,0.1,0] and [0,0.1,0.8,0.1,0], which together form a matrix:

[0073]

[0074] A multiplied by R yields:

[0075] [0,0.1,0.8,0.1,0], take the maximum value, that is, the third element 0.8, which corresponds to the adjustment method of keeping the set value unchanged, so the set value remains unchanged.

[0076] When the heat change trend ΔΘ mn = -10, temperature deviation ΔT mn When = 0, according to the fuzzy table, the resulting fuzzy vectors are [0.9,0.1,0,0,0] and [0,0.1,0.8,0.1,0], which together form a matrix:

[0077]

[0078] A multiplied by R yields:

[0079] [0.675,0.1,0.2,0.025,0], take the maximum value, that is, the first element 0.675, which corresponds to the adjustment method of greatly increasing the set value, so the set value is increased by 2 on the original basis.

[0080] The adjustment methods are shown in Table 3.

[0081] Table 3. Adjustment methods corresponding to set values

[0082]

[0083] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A production sensing and interactive control system for a tobacco processing line, characterized in that, include: The sensing module of the silk production line interacts with the PLC automatic control system through the first bus communication module to read the temperature, flow rate, and weight status parameters of the equipment in the unpacking, rehydration, slicing, feeding, and drying processes of the PLC automatic control system. The environmental system interactive control module interacts with the air conditioning and lighting systems via the second bus communication module to read the operating status of the equipment in the unpacking, rehumidification, shredding, feeding, and drying processes, and to control the opening and closing of the air conditioning and lighting systems as well as their operating power. The MongoDB database module connects to the silk production line sensing module and the environmental system interaction control module through the database API interface. It is used to read and store the upstream and downstream relationships of the equipment in the unpacking, rehydration, slicing, feeding and drying processes of the silk production line, as well as store real-time data of equipment temperature, flow rate and weight status parameters. The environmental interaction control module controls the on / off state and operating power of the air conditioning and lighting systems, specifically including: Divide the silk production line into The grid, the lighting system is divided into The grid, the air conditioning system is divided into The grid; The heat status of the wire-making production line grid is determined based on the equipment's operating status. If all equipment within the grid is not running, the grid heat result is 0. If some or all equipment within the grid is running, then the result is... Line 1 The heat of the grid is calculated as shown in equation (1): （1） in, Indicates the first The heat dissipated in the grid when a device is at full load Indicates the first The load status of each device at full load. Indicates the first The current load status of each device Indicates the first The first device The base load of the upstream section, This represents the maximum base load of the current portion of the i-th device, which is the maximum load allocated to that portion; The above formula indicates that when the first The load of each device The heat emitted by the device will only begin to be measured within the current grid when it exceeds the total base load of the upstream portion; For the lighting system grid and the air conditioning system grid, the heat occupation data statistically obtained from the silk production line grid is redistributed to the lighting system grid and the air conditioning system grid. The redistribution method is as follows: Search lighting system or air conditioning system Line 1 The index and area of ​​the covered silk production line grid in the column grid are multiplied by the heat value according to the ratio of the covered silk production line grid area to the original silk production line grid, and then summed to obtain the lighting system or air conditioning system. Line 1 The heat of the grid; For lighting systems, if the first Line 1 If the heat of a grid column is greater than 0, then the switch for the corresponding area will be turned on. For air conditioning systems, adjust them as follows: For each air conditioning system grid, the deviation between the current grid heat and the previous grid heat is calculated as follows: The deviation between the current ambient temperature of the grid and the set temperature of the air conditioning system is calculated as follows: Through the and These two variables are used to establish a fuzzy table and fuzzy rules; the specific method for calculating the change in the air conditioning temperature setpoint is as follows: right and Establish a five-level fuzzy table, which corresponds to the degree of deviation and weight of the five heat change trends or temperature deviation ranges; Fuzzy rules reflect the necessity of adjusting the air conditioner temperature setting under different heat change trends and temperature deviations, and are represented by row vector A. Calculate the fuzzy result of the air conditioner temperature adjustment, and determine the adjustment range of the set value according to the table lookup method.

Images