Control methods and devices for reducing downtime of filament production line equipment

Abstract

This invention relates to the field of tobacco processing line equipment control technology, and provides a control method and apparatus for reducing downtime of tobacco processing line equipment. The method includes: collecting actual operating data of the target tobacco processing line equipment to be controlled, and collecting the actual frequency of the bottom belt of the material buffer cabinet; extracting first actual operating data and the first bottom belt actual frequency during stable operation of the elevator from the actual operating data and the actual bottom belt frequency; statistically analyzing multiple actual operating characteristic data under the first bottom belt actual frequency; calculating the Pearson correlation coefficient between the multiple actual operating characteristic data to determine the target actual operating characteristic data affecting the downtime of the target tobacco processing line equipment; and setting the target tobacco processing line equipment based on the target actual operating characteristic data to control the target tobacco processing line equipment and reduce downtime. This achieves a reduction in the downtime and frequency of the tobacco processing line equipment.

Description

Technical Field

[0001] This invention relates to the field of tobacco processing line equipment control technology, and in particular to a control method and device for reducing downtime of tobacco processing line equipment. Background Technology

[0002] With the increasing emphasis on high-quality development, data analysis of tobacco processing lines is crucial for quality analysis and innovation in production methods. As assembly line equipment, tobacco processing lines experience numerous breakpoints, and segmented shutdowns are common during production. This leads to quality fluctuations, unnecessary equipment start-ups and shutdowns, equipment damage, and energy waste.

[0003] Therefore, how to reduce the downtime and frequency of tobacco processing line equipment has become an urgent problem to be solved. Summary of the Invention

[0004] This invention provides a control method and apparatus for reducing downtime of tobacco processing line equipment, which solves the defects of existing technology in tobacco processing line equipment that has many start-stop cycles and long start-stop times, causing equipment damage and energy waste, and reduces the downtime and number of shutdowns of tobacco processing line equipment.

[0005] This invention provides a control method for reducing downtime of wire-making equipment, comprising: The actual operating data of the target silk-making line equipment to be controlled is collected, and the actual frequency of the bottom band of the material buffer cabinet is collected. The material buffer cabinet is connected to the elevator and the target silk-making line equipment respectively. The elevator is used to transport materials to the material buffer cabinet. Extract the first actual operating data and the first actual frequency of the bottom strip from the actual operating data and the actual frequency of the bottom strip when the hoist is running stably; Based on the first actual operating data and the first baseband actual frequency, statistical analysis is performed on multiple actual operating characteristic data at the first baseband actual frequency. Calculate the Pearson correlation coefficient among the multiple actual operating characteristic data to determine the target actual operating characteristic data that affect the downtime of the target yarn-making line equipment; Based on the actual operating characteristic data of the target, the target silk-making line equipment is configured to control the target silk-making line equipment to reduce downtime.

[0006] In one possible implementation, the method further includes: According to a sliding window with a preset time period, the first actual operating data and the first actual frequency of the bottom band are extracted from the actual operating data and the actual frequency of the bottom band during multiple normal data sampling periods when the elevator is running stably. The multiple normal data sampling periods are the time periods when the data fluctuation amplitude is less than a preset threshold and no alarm of full feed bin or empty material buffer cabinet occurs. The feed bin is connected to the elevator and is used to provide material to the elevator.

[0007] In one possible implementation, the method further includes: Using the Pearson correlation coefficient, with the downtime index as the dependent variable and the multiple actual operating characteristic data as independent variables, correlation analysis was performed to obtain the correlation coefficient between each actual operating characteristic data and the downtime index. The actual operating characteristic data corresponding to the independent variables whose correlation coefficients are greater than a preset threshold are used as the target actual operating characteristic data affecting the downtime of the target yarn-making line equipment.

[0008] In one possible implementation, the method further includes: Using the actual operational characteristic data of the target as the horizontal axis and the downtime index as the vertical axis, a correlation curve is plotted. The horizontal axis data corresponding to the lowest point in the correlation curve is taken as the optimal value of the target's actual operating characteristic data. The target yarn-making line equipment is set with the optimal value to control the target yarn-making line equipment to reduce downtime.

[0009] In one possible implementation, the method further includes: Obtain the first actual operating data of the target yarn-making equipment after it has been reset; Based on the first actual operating data, the downtime of the target yarn-making line equipment was statistically analyzed to obtain the statistical results; The target yarn-making equipment is monitored based on the statistical results.

[0010] In one possible implementation, the method further includes: Obtain target actual operating characteristic data for various grades of materials; By using the actual operational characteristic data corresponding to each grade of material, a seamless switching between different grades of materials can be achieved.

[0011] The present invention also provides a control device for reducing downtime of wire-making equipment, comprising the following modules: The data acquisition module is used to collect the actual operating data of the target yarn-making line equipment to be controlled, and to collect the actual frequency of the bottom band of the material buffer cabinet. The material buffer cabinet is connected to the elevator and the target yarn-making line equipment respectively. The elevator is used to transport materials to the material buffer cabinet. The data interception module is used to extract the first actual operating data and the first actual frequency of the bottom strip when the hoist is running stably from the actual operating data and the actual frequency of the bottom strip; The data statistics module is used to collect statistics on multiple actual operating characteristic data at the first baseband actual frequency based on the first actual operating data and the first baseband actual frequency. The determination module is used to calculate the Pearson correlation coefficient between the multiple actual operating characteristic data and determine the target actual operating characteristic data that affect the downtime of the target yarn-making line equipment. The control module is used to set the target silk-making line equipment based on the actual operating characteristic data of the target, and to control the target silk-making line equipment to reduce downtime.

[0012] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the control method for reducing downtime of the filament-making equipment as described above.

[0013] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the control method for reducing downtime of the filament-making equipment as described above.

[0014] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the control method for reducing downtime of the filament-making equipment as described above.

[0015] The present invention provides a control method and apparatus for reducing downtime of a yarn-making line. This method involves collecting actual operating data of the target yarn-making line and the actual frequency of the bottom band of a material buffer cabinet. The material buffer cabinet is connected to both a hoist and the target yarn-making line, and the hoist transports materials to the material buffer cabinet. The method extracts first actual operating data and a first actual bottom band frequency from the actual operating data and the actual bottom band frequency, indicating stable operation of the hoist. Based on the first actual operating data and the first actual bottom band frequency, multiple actual operating characteristic data are statistically analyzed at the first actual bottom band frequency. The Pearson correlation coefficient between these multiple actual operating characteristic data is calculated to determine the target actual operating characteristic data affecting the downtime of the target yarn-making line. Finally, the target yarn-making line is configured based on the target actual operating characteristic data to control and reduce downtime. Compared to existing technologies where tobacco processing line equipment experiences frequent and prolonged start-stop cycles, leading to equipment damage and energy waste, this solution addresses these issues by determining the relationship between multiple operational characteristic data points and the shutdown index during steady-state production. This identifies target data influencing shutdowns, enabling precise control of the target tobacco processing line equipment. This effectively reduces the number and duration of shutdowns, significantly minimizing equipment damage and energy waste, and achieving efficient and stable production. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0017] Figure 1 This is one of the flowcharts illustrating the control method for reducing downtime of wire-making equipment provided by the present invention.

[0018] Figure 2 This is the second flowchart illustrating the control method for reducing downtime of wire-making equipment provided by the present invention.

[0019] Figure 3 This is a schematic diagram of the Pearson correlation coefficients between multiple actual operational characteristic data provided by the present invention.

[0020] Figure 4 This is a schematic diagram of the control device for reducing downtime of yarn-making equipment provided by the present invention.

[0021] Figure 5 This is a schematic diagram showing the relationship between the set frequency of the bottom belt and the discharge speed of the same grade of material provided by the present invention.

[0022] Figure 6 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0024] To facilitate understanding of the embodiments of the present invention, further explanations and descriptions will be provided below with reference to the accompanying drawings and specific embodiments. These embodiments do not constitute a limitation on the embodiments of the present invention.

[0025] Figure 1 This is one of the flowcharts illustrating the control method for reducing downtime of yarn-making equipment provided by the present invention, such as... Figure 1 As shown, the method includes the following: S11. Collect the actual operating data of the target silk-making line equipment to be controlled, and collect the actual frequency of the bottom band of the material buffer cabinet.

[0026] In this embodiment of the invention, the material buffer cabinet is connected to both the elevator and the target silk-making line equipment. The elevator is used to transport materials to the material buffer cabinet, and the material buffer cabinet is used to supply materials to the target silk-making line equipment.

[0027] The actual operating data of the target silk-making line equipment to be controlled is collected by a programmable logic controller (PLC), and the actual frequency of the bottom band of the material buffer cabinet is also collected.

[0028] S12. Extract the first actual operating data and the first actual frequency of the bottom belt from the actual operating data and the actual frequency of the bottom belt when the hoist is running stably.

[0029] When the elevator is running stably, the target yarn-making line equipment and material buffer cabinet are also in normal working condition. Therefore, the first actual operating data and the first actual frequency of the bottom belt can be extracted from the actual operating data and the actual frequency of the bottom belt for multiple stable operating periods of the elevator.

[0030] S13. Based on the first actual operating data and the first baseband actual frequency, statistically analyze multiple actual operating characteristic data under the first baseband actual frequency.

[0031] Statistically analyze multiple actual operating characteristic data under the actual frequency of the first base band for each stable operating period. These multiple actual operating characteristic data include: the cumulative total production at the last moment of the grouped data period, the production weight during the period, the downtime during the period, the ratio of downtime to total time, the non-downtime, the flow rate of the material buffer cabinet when it is not stopped (the average discharge speed of the buffer cabinet when it is not stopped), the average flow rate during the period, the number of downtimes during the period, the downtime index (number of downtimes / length of the data period), and the set flow rate of the buffer cabinet.

[0032] S14. Calculate the Pearson correlation coefficient between the multiple actual operating characteristic data to determine the target actual operating characteristic data that affect the downtime of the target yarn-making line equipment.

[0033] Using the Pearson correlation coefficient, with the downtime index as the dependent variable and multiple actual operating characteristic data as independent variables, correlation analysis was performed to obtain the correlation coefficient between each actual operating characteristic data and the downtime index. The actual operating characteristic data corresponding to the independent variable with a correlation coefficient greater than a preset threshold were taken as the target actual operating characteristic data affecting the downtime of the target yarn-making line equipment.

[0034] S15. Based on the actual operating characteristic data of the target, the target silk-making line equipment is configured to control the target silk-making line equipment to reduce downtime.

[0035] A correlation curve is plotted using the actual operating characteristic data of the target as the x-axis and the downtime index as the y-axis. The x-axis data corresponding to the lowest point in the correlation curve is taken as the optimal value of the actual operating characteristic data of the target. The target silk-making line equipment is set with the optimal value to control the target silk-making line equipment to reduce downtime.

[0036] Optionally, the first actual operating data of the target yarn-making line equipment after resetting can be obtained; the downtime of the target yarn-making line equipment can be statistically analyzed based on the first actual operating data to obtain statistical results; the target yarn-making line equipment can be monitored based on the statistical results, allowing the operator to manually confirm or correct the optimal bottom band frequency, and then the operating parameters of the target yarn-making line equipment can be reset.

[0037] The present invention provides a control method for reducing downtime of a yarn-making line. This method involves collecting actual operating data of the target yarn-making line and the actual frequency of the bottom band of a material buffer cabinet. The material buffer cabinet is connected to both a hoist and the target yarn-making line, and the hoist transports materials to the material buffer cabinet. The method extracts first actual operating data and a first actual bottom band frequency from the actual operating data and the actual bottom band frequency, indicating stable operation of the hoist. Based on the first actual operating data and the first actual bottom band frequency, multiple actual operating characteristic data are statistically analyzed at the first actual bottom band frequency. The Pearson correlation coefficient between these multiple actual operating characteristic data is calculated to determine the target actual operating characteristic data affecting the downtime of the target yarn-making line. Finally, the method configures the target yarn-making line based on the target actual operating characteristic data to control and reduce downtime. Compared to existing technologies where tobacco processing line equipment experiences frequent and prolonged start-stop cycles, leading to equipment damage and energy waste, this method identifies the relationship between multiple operational characteristic data and the shutdown index during steady-state production. This allows for the determination of target data influencing shutdowns, enabling precise control of the target tobacco processing line equipment. This effectively reduces the number and duration of shutdowns, significantly minimizing equipment damage and energy waste, and achieving efficient and stable production.

[0038] Figure 2 This is a second schematic flowchart of the control method for reducing downtime of yarn-making equipment provided by the present invention, as shown below. Figure 2 As shown, the method includes the following: S21. Collect the actual operating data of the target silk-making line equipment to be controlled, and collect the actual frequency of the bottom band of the material buffer cabinet.

[0039] In this embodiment of the invention, the material buffer cabinet is connected to both the elevator and the target silk-making line equipment. The elevator is used to transport materials to the material buffer cabinet, and the material buffer cabinet is used to supply materials to the target silk-making line equipment.

[0040] The programmable logic controller (PLC) collects the actual operating data of the target silk-making line equipment to be controlled for various grades of materials and the actual frequency of the bottom band of the material buffer cabinet.

[0041] Each data entry contains data items as shown in Table 1: Table 1 Set flow High-speed setting value of feed bin bottom belt frequency Actual traffic Feed hopper bottom belt frequency medium speed setting value Cumulative weight Low-speed setting value of feed bin bottom belt frequency Feed bin tail full of light #1 Buffer Cabinet Empty Detection Photoelectric Switch Low-position photoelectric sensor at the feed bin junction #1 Buffer Cabinet Bottom Band Frequency Setting Value High-level photoelectric sensor at the feed bin junction Actual frequency value at the bottom of cache cabinet #1 Photoelectric sensor in feed bin lifting section #2 Buffer Cabinet Empty Detection Photoelectric Switch Feed hopper bottom belt frequency setting value #2 Buffer Cabinet Bottom Band Frequency Setting Value Actual value of feed bin bottom belt frequency Actual frequency value at the bottom of cache cabinet #2 Increase the actual frequency The main objects of analysis are shown in Table 2: Table 2 The relevant parameters include: set flow rate, actual flow rate, cumulative weight, feed bin tail full photoelectric sensor, #1 buffer cabinet empty photoelectric switch, #1 buffer cabinet bottom band frequency set value, and #1 buffer cabinet bottom band frequency actual value.

[0042] S22. According to a sliding window with a preset time period, extract the first actual operating data and the first actual bottom band frequency from the actual operating data and the actual bottom band frequency during multiple normal data sampling periods when the hoist is running stably.

[0043] S23. Based on the first actual operating data and the first baseband actual frequency, statistically analyze multiple actual operating characteristic data under the first baseband actual frequency.

[0044] Among them, multiple normal data sampling periods are the time periods when the data fluctuation amplitude is less than the preset threshold and no alarm of full feed bin or empty material buffer cabinet occurs. The feed bin is connected to the elevator and is used to provide materials to the elevator.

[0045] Data from stable operation (stable flow rate) of the hoist is extracted and grouped into sets for each grade and the set frequency of each buffer cabinet's bottom band. Multiple actual operating characteristic data (excluding the set flow rate) are calculated for each group of data at the actual frequency of the first bottom band. Several actual operational characteristic data include: the cumulative total production at the last moment of the grouped data period, the production weight during the period, the downtime during the period, the ratio of downtime to total time, the non-downtime, the flow rate of the buffer cabinet when it is not stopped (the average discharge speed of the buffer cabinet when it is not stopped), the average flow rate during the period, the number of downtimes during the period, the downtime index (number of downtimes / length of the data period), and the set flow rate of the buffer cabinet.

[0046] Table 3 is obtained: Table 3 It is worth noting that the average flow rate during the period is basically consistent with the set flow rate. This indicates that the average flow rate of the buffer tank is basically consistent with the flow rate of the belt scale. If it is necessary to reduce downtime, it is initially determined that the flow rate of the buffer tank when it is not stopped needs to be adjusted to be the same as the set flow rate of the belt scale.

[0047] S24. Using the Pearson correlation coefficient, with the downtime index as the dependent variable and the multiple actual operating characteristic data as independent variables, a correlation analysis is performed to obtain the correlation coefficient between each actual operating characteristic data and the downtime index.

[0048] Calculate the Pearson correlation coefficient ([-1, +1], representing the degree of positive or negative correlation) between various actual operational characteristic data and display it visually. For example... Figure 3 As shown (only the bottom left part needs to be viewed). The following conclusions can be drawn: 1. The higher the set frequency of the buffer cabinet bottom band, the higher the downtime as a percentage of the total running time; the two are strongly correlated. 2. The higher the set frequency of the buffer cabinet bottom belt, the faster the material discharge speed when the buffer cabinet is not stopped. This is obvious and the data can be verified to be correct. 3. The higher the frequency of the buffer cabinet bottom band setting, the greater the number of downtimes, indicating a moderate correlation. Based on this, we can conclude that optimizing the buffer cabinet setting frequency can help mitigate the problem of excessive downtime. 4. The longer the downtime during the data period, the greater the number of downtimes, showing a strong correlation. Therefore, we can conclude that each downtime is roughly the same in duration. 5. The higher the downtime / total time, the greater the traffic when the cache cabinet is not down. This causal relationship is also quite clear, which verifies that the data is correct. 6. If the buffer cabinet has a high set flow rate, then the discharge flow rate when the machine is not stopped will be large, and the average flow rate will also be large. This is also quite clear.

[0049] S25. The actual operating characteristic data corresponding to the independent variable whose correlation coefficient is greater than a preset threshold is taken as the target actual operating characteristic data affecting the downtime of the target yarn-making line equipment.

[0050] S26. Using the actual operating characteristic data of the target as the horizontal axis and the downtime index as the vertical axis, plot a correlation curve.

[0051] S27. Take the horizontal coordinate data corresponding to the lowest point in the correlation curve as the optimal value of the target's actual operating characteristic data.

[0052] The following provides a unified explanation of S25-S27: The relationship between frequency, flow rate, and downtime index is shown in Table 4: Table 4 Downtime Index Cache cabinet bottom with set frequency Set flow 2.5 10 6500 3.34 10 6800 3.54 10 6500 3.55 10 6500 3.79 15 5500 3.89 15 6500 3.93 30 6800 As can be seen from Table 4, the higher the frequency setting of the buffer cabinet bottom band, the greater the number of downtimes.

[0053] The following two perspectives explore methods for finding the optimal frequency: 1. Upon actual observation of the data in Table 5, it was found that the total quantity of each batch of material was the same for each grade.

[0054] Table 5 Assume that when the buffer cabinet is unloaded, the entire cross section falls simultaneously.

[0055] H is the height of the material inside the buffer cabinet, M is the total weight of a batch of material, V is the volume of a batch of material, w is the width of the buffer cabinet, S is the bottom area of ​​the buffer cabinet, ρ is the density of tobacco shreds, F is the set frequency of the bottom belt of the buffer cabinet, g is the actual discharge flow rate of the buffer cabinet, and ν is the linear velocity of the bottom belt of the buffer cabinet.

[0056] Then there is, (1); For the same brand and the same buffer cabinet, where ρ and S are constants, using a to replace 1 / ρS, we have: (2); Regarding the relationship between H and g: (3) (4) in dV = wH·dL Substituting into equation (4) above, we get (5); dL / dt Let ν be the linear velocity. Substituting this into equation (5), we get... (6); Since ν∽f, the above equation (6) can be written as (7), among which, b For coefficients; Substituting formula (2) into the above formula (7), we get (8); make bρwa=x ,get (9) According to the result of the above formula (9), the bottom belt setting frequency is directly proportional to the outlet flow rate when the machine is not stopped and inversely proportional to the total amount of the current batch of materials.

[0057] 2: Select data from three different baseband frequencies for the same brand, as shown in Table 6: Table 6 Brand Weight of each batch of material Set flow Cache cabinet bottom with set frequency Flow rate (kg / h) when the machine is not shut down 6 5700 6500 15 9106.4 6 5700 6500 10 8406.4 6 5700 6500 30 12048.0 The horizontal axis is set with the frequency at the bottom of the buffer cabinet, and the vertical axis is the non-shutdown flow rate. According to... Figure 5 As shown, it can be assumed that for the same grade, the relationship between the bottom belt setting frequency and the discharge speed is linear. This is consistent with the conclusion of angle 1.

[0058] Using linear regression, we obtain y = 6456.2 + 185.31X In theory, the discharge flow rate at the bottom of the buffer cabinet should be close to the actual flow rate of the belt scale to ensure that the current downtime frequency can be reduced.

[0059] Using the fitted function relationship, it can be found that the actual frequency needs to be set relatively small in order to closely match the flow rate of the belt scale.

[0060] Therefore, there are two reasons for this judgment.

[0061] a) Main reason: The load capacity of the current buffer cabinet bottom drive motor exceeds the needs of this section, which means that the motor needs to run at a lower frequency to reduce the shutdown frequency.

[0062] b) Using only 3 points for fitting introduces a certain error.

[0063] S28. Set the target yarn-making equipment with the optimal value to control the target yarn-making equipment to reduce downtime.

[0064] The target silk-making line equipment is set according to the optimal value of the buffer cabinet bottom band frequency obtained above, thereby controlling the target silk-making line equipment to reduce downtime.

[0065] Furthermore, the system acquires the first actual operating data of the target yarn-making line after resetting; based on the first actual operating data, it calculates the downtime of the target yarn-making line and obtains statistical results; and it monitors the target yarn-making line based on the statistical results. The operator is allowed to manually confirm or correct the optimal underband frequency and then reset the operating parameters of the target yarn-making line.

[0066] The present invention provides a control method for reducing downtime of a yarn-making line. This method involves collecting actual operating data of the target yarn-making line and the actual frequency of the bottom band of a material buffer cabinet. The material buffer cabinet is connected to both a hoist and the target yarn-making line, and the hoist transports materials to the material buffer cabinet. The method extracts first actual operating data and a first actual bottom band frequency from the actual operating data and the actual bottom band frequency, indicating stable operation of the hoist. Based on the first actual operating data and the first actual bottom band frequency, multiple actual operating characteristic data are statistically analyzed at the first actual bottom band frequency. The Pearson correlation coefficient between these multiple actual operating characteristic data is calculated to determine the target actual operating characteristic data affecting the downtime of the target yarn-making line. Finally, the method configures the target yarn-making line based on the target actual operating characteristic data to control and reduce downtime. This method determines the relationship between multiple operational characteristic data and the downtime index during the steady-state production process, identifies the target data affecting downtime, and then precisely controls the target yarn-making line equipment, effectively reducing the number and duration of downtime, significantly reducing equipment damage and energy waste, and achieving efficient and stable production goals.

[0067] The control device for reducing downtime of filament-making equipment provided by the present invention will be described below. The control device for reducing downtime of filament-making equipment described below can be referred to in correspondence with the control method for reducing downtime of filament-making equipment described above.

[0068] Figure 4 This is a schematic diagram of the control device for reducing downtime of yarn-making equipment provided by the present invention, specifically including: The data acquisition module 401 is used to acquire the actual operating data of the target silk-making line equipment to be controlled, and to acquire the actual frequency of the bottom band of the material buffer cabinet. The material buffer cabinet is connected to the elevator and the target silk-making line equipment respectively. The elevator is used to transport materials to the material buffer cabinet. The data interception module 402 is used to intercept the first actual operating data and the first actual frequency of the bottom strip when the hoist is running stably from the actual operating data and the actual frequency of the bottom strip; The data statistics module 403 is used to statistically analyze multiple actual operating characteristic data at the first baseband actual frequency based on the first actual operating data and the first baseband actual frequency. The determination module 404 is used to calculate the Pearson correlation coefficient between the multiple actual operating characteristic data and determine the target actual operating characteristic data that affect the downtime of the target yarn-making line equipment. The control module 405 is used to set the target silk-making line equipment based on the actual operating characteristic data of the target, and control the target silk-making line equipment to reduce downtime.

[0069] In one possible implementation, the data interception module 402 is further configured to intercept, from the actual operating data and the actual frequency of the bottom band, the first actual operating data and the first actual frequency of the bottom band during multiple normal data sampling periods when the elevator is running stably, according to a sliding window of a preset time period. The multiple normal data sampling periods are time periods in which the data fluctuation amplitude is less than a preset threshold and no alarm of full feed bin or empty material buffer cabinet occurs. The feed bin is connected to the elevator and is used to provide material to the elevator.

[0070] In one possible implementation, the determining module 404 is further configured to use the Pearson correlation coefficient, with the downtime index as the dependent variable and the multiple actual operating characteristic data as independent variables, to perform correlation analysis to obtain the correlation coefficient between each actual operating characteristic data and the downtime index; and to use the actual operating characteristic data corresponding to the independent variable whose correlation coefficient is greater than a preset threshold as the target actual operating characteristic data affecting the downtime of the target yarn-making equipment.

[0071] In one possible implementation, the control module 405 is further configured to plot a correlation curve using the target actual operating characteristic data as the abscissa and the downtime index as the ordinate; take the abscissa data corresponding to the lowest point in the correlation curve as the optimal value of the target actual operating characteristic data; set the target silk-making line equipment with the optimal value to control the target silk-making line equipment to reduce downtime.

[0072] In one possible implementation, the data acquisition module 401 is further configured to acquire the first actual operating data of the reset target silk-making line equipment; calculate the downtime of the target silk-making line equipment based on the first actual operating data to obtain statistical results; and monitor the target silk-making line equipment based on the statistical results.

[0073] In one possible implementation, the data acquisition module 401 is further configured to acquire target actual operating characteristic data corresponding to various grades of materials; and to perform non-disruptive switching of different grades of materials using the target actual operating characteristic data corresponding to each grade of material.

[0074] Figure 6 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 6 As shown, the electronic device may include: a processor 610, a communications interface 620, a memory 630, and a communications bus 640, wherein the processor 610, the communications interface 620, and the memory 630 communicate with each other through the communications bus 640. The processor 610 can call logic instructions in the memory 630 to execute a control method for reducing downtime of the silk-making line equipment. This method includes: collecting actual operating data of the target silk-making line equipment to be controlled, and collecting the actual frequency of the bottom band of a material buffer cabinet, wherein the material buffer cabinet is connected to both the elevator and the target silk-making line equipment, and the elevator is used to transport materials to the material buffer cabinet; extracting first actual operating data and a first actual bottom band frequency from the actual operating data and the actual bottom band frequency during stable operation of the elevator; statistically analyzing multiple actual operating characteristic data at the first actual bottom band frequency based on the first actual operating data and the first actual bottom band frequency; calculating the Pearson correlation coefficient between the multiple actual operating characteristic data to determine the target actual operating characteristic data affecting the downtime of the target silk-making line equipment; and setting the target silk-making line equipment based on the target actual operating characteristic data to control the target silk-making line equipment to reduce downtime.

[0075] Furthermore, the logical instructions in the aforementioned memory 630 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0076] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the control method for reducing downtime of the silk-making line equipment provided by the above methods. The method includes: collecting actual operating data of the target silk-making line equipment to be controlled, and collecting the actual frequency of the bottom band of the material buffer cabinet, wherein the material buffer cabinet is connected to the elevator and the target silk-making line equipment respectively, and the elevator is used to transport materials to the material buffer cabinet; extracting first actual operating data and first bottom band actual frequency when the elevator is running stably from the actual operating data and the bottom band actual frequency; statistically analyzing multiple actual operating characteristic data under the first bottom band actual frequency based on the first actual operating data and the first bottom band actual frequency; calculating the Pearson correlation coefficient between the multiple actual operating characteristic data to determine the target actual operating characteristic data affecting the downtime of the target silk-making line equipment; and setting the target silk-making line equipment based on the target actual operating characteristic data to control the target silk-making line equipment to reduce downtime.

[0077] In another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements a control method for reducing downtime of a silk-making line provided by the methods described above. This method includes: collecting actual operating data of the target silk-making line to be controlled, and collecting the actual frequency of the bottom band of a material buffer cabinet, wherein the material buffer cabinet is connected to both a hoist and the target silk-making line, and the hoist is used to transport materials to the material buffer cabinet; extracting first actual operating data and a first actual frequency of the bottom band from the actual operating data and the actual frequency of the bottom band during stable operation of the hoist; statistically analyzing multiple actual operating characteristic data at the first actual frequency of the bottom band based on the first actual operating data and the first actual frequency of the bottom band; calculating the Pearson correlation coefficient between the multiple actual operating characteristic data to determine target actual operating characteristic data affecting the downtime of the target silk-making line; and setting the target silk-making line based on the target actual operating characteristic data to control the target silk-making line to reduce downtime.

[0078] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0079] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0080] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A control method for reducing downtime of wire-making equipment, characterized in that, include: The actual operating data of the target silk-making line equipment to be controlled is collected, and the actual frequency of the bottom band of the material buffer cabinet is collected. The material buffer cabinet is connected to the elevator and the target silk-making line equipment respectively. The elevator is used to transport materials to the material buffer cabinet. Extract the first actual operating data and the first actual frequency of the bottom strip from the actual operating data and the actual frequency of the bottom strip when the hoist is running stably; Based on the first actual operating data and the first baseband actual frequency, statistical analysis is performed on multiple actual operating characteristic data at the first baseband actual frequency. Calculate the Pearson correlation coefficient among the multiple actual operating characteristic data to determine the target actual operating characteristic data that affect the downtime of the target yarn-making line equipment; Based on the actual operating characteristic data of the target, the target silk-making line equipment is configured to control the target silk-making line equipment to reduce downtime.

2. The method according to claim 1, characterized in that, The step of extracting the first actual operating data and the first actual frequency of the bottom band from the actual operating data and the actual frequency of the bottom band during stable operation of the hoist includes: According to a sliding window with a preset time period, the first actual operating data and the first actual frequency of the bottom band are extracted from the actual operating data and the actual frequency of the bottom band during multiple normal data sampling periods when the elevator is running stably. The multiple normal data sampling periods are the time periods when the data fluctuation amplitude is less than a preset threshold and no alarm of full feed bin or empty material buffer cabinet occurs. The feed bin is connected to the elevator and is used to provide material to the elevator.

3. The method according to claim 1, characterized in that, The calculation of the Pearson correlation coefficient among the multiple actual operating characteristic data to determine the target actual operating characteristic data affecting the downtime of the target yarn-making line equipment includes: Using the Pearson correlation coefficient, with the downtime index as the dependent variable and the multiple actual operating characteristic data as independent variables, correlation analysis was performed to obtain the correlation coefficient between each actual operating characteristic data and the downtime index. The actual operating characteristic data corresponding to the independent variables whose correlation coefficients are greater than a preset threshold are used as the target actual operating characteristic data affecting the downtime of the target yarn-making line equipment.

4. The method according to claim 3, characterized in that, The step of setting up the target yarn-making line equipment based on the actual operating characteristic data of the target, and controlling the target yarn-making line equipment to reduce downtime, includes: Using the actual operational characteristic data of the target as the horizontal axis and the downtime index as the vertical axis, a correlation curve is plotted. The horizontal axis data corresponding to the lowest point in the correlation curve is taken as the optimal value of the target's actual operating characteristic data. The target yarn-making line equipment is set with the optimal value to control the target yarn-making line equipment to reduce downtime.

5. The method according to claim 4, characterized in that, The method further includes: Obtain the first actual operating data of the target yarn-making equipment after it has been reset; Based on the first actual operating data, the downtime of the target yarn-making line equipment was statistically analyzed to obtain the statistical results; The target yarn-making equipment is monitored based on the statistical results.

6. The method according to claim 1, characterized in that, The method further includes: Obtain target actual operating characteristic data for various grades of materials; By using the actual operational characteristic data corresponding to each grade of material, a seamless switching between different grades of materials can be achieved.

7. A control device for reducing downtime of yarn-making equipment, characterized in that, include: The data acquisition module is used to collect the actual operating data of the target yarn-making line equipment to be controlled, and to collect the actual frequency of the bottom band of the material buffer cabinet. The material buffer cabinet is connected to the elevator and the target yarn-making line equipment respectively. The elevator is used to transport materials to the material buffer cabinet. The data interception module is used to extract the first actual operating data and the first actual frequency of the bottom strip when the hoist is running stably from the actual operating data and the actual frequency of the bottom strip; The data statistics module is used to collect statistics on multiple actual operating characteristic data at the first baseband actual frequency based on the first actual operating data and the first baseband actual frequency. The determination module is used to calculate the Pearson correlation coefficient between the multiple actual operating characteristic data and determine the target actual operating characteristic data that affect the downtime of the target yarn-making line equipment. The control module is used to set the target silk-making line equipment based on the actual operating characteristic data of the target, and to control the target silk-making line equipment to reduce downtime.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the control method for reducing downtime of the wire-making equipment as described in any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the control method for reducing downtime of the wire-making equipment as described in any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the control method for reducing downtime of the wire-making equipment as described in any one of claims 1 to 6.

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