Dust control method and system for intelligent spinning workshop

Abstract

The invention belongs to the technical field of factory control. The invention provides a dust control method and system for an intelligent spinning workshop. The method comprises the steps that the area attribute of each spinning area in a spinning workshop is acquired, the area type of each spinning area is determined according to the area attribute, and the area type comprises a manned area and an unmanned area; obtaining spinning operation information of each spinning area, and predicting a corresponding dust generation rate according to the spinning operation information; determining a dust cleaning period of each spinning area according to the dust generation rate and the area type; and controlling the mobile dust cleaning robot to clean dust in each spinning area. Through cooperation of the ventilation dust removal system and the movable dust cleaning robot, comprehensive cleaning of dust in the spinning workshop is achieved, and interference to normal spinning operation of spinning workers is reduced as much as possible.

Description

Technical Field

[0001] The present invention relates to the field of factory control technology, and in particular to a dust control method and system for an intelligent spinning workshop. Background Art

[0002] Dust control in spinning workshops is of great significance for protecting workers' health, improving product quality and achieving environmental sustainability. Existing dust control in spinning workshops is based on ventilation and dust removal systems, that is, ventilation and dust removal systems installed on the wall or ceiling accelerate the air circulation in the spinning workshop to discharge the dust in the workshop. This existing method has a poor cleaning effect for the dust concentration in the spinning machine area located on the lower floor.

[0003] Therefore, how to further improve the dust control effect in the spinning machine area at the lower level of the spinning workshop is a technical problem that needs to be solved at present. Summary of the invention

[0004] In this regard, the present invention provides a dust control method, system, electronic device, computer storage medium and computer program product for an intelligent spinning workshop to solve the above-mentioned technical problems.

[0005] The present invention discloses a dust control method for an intelligent spinning workshop, the method comprising the following steps: Acquire the regional attributes of each spinning area in the spinning workshop, and determine the regional type of each spinning area according to the regional attributes, wherein the regional type includes a manned area and an unmanned area; Acquire spinning operation information of each spinning area, and predict corresponding dust generation rate according to the spinning operation information; Determine the dust cleaning cycle of each spinning area according to the dust generation rate and the area type; Controlling a mobile dust cleaning robot to perform dust cleaning operations on each of the spinning areas; Among them, a fixed ventilation and dust removal system is also arranged in the spinning workshop, and the ventilation and dust removal system is mainly used to clean the dust floating in the upper layer of the spinning workshop.

[0006] In some embodiments, the acquiring of the regional attributes of each spinning area in the spinning workshop and determining the regional type of each spinning area according to the regional attributes include: Acquire the regional attributes of each spinning area in the spinning workshop from the designated port, and parse the regional attributes to obtain the type of spinning machine in the spinning area; According to the spinning machine type, the spinning machine related information is crawled, and according to the spinning machine related information, the area type of each spinning area, the manned area and the unmanned area, is determined.

[0007] In some embodiments, the predicting of the corresponding dust generation rate according to the spinning operation information includes: Analyzing the spinning operation information to obtain spinning raw material information, spinning machine status information, and spinning process parameter information; Inputting the spinning raw material information, the spinning machine state information and the spinning process parameter information into a dust generation rate prediction model based on a large model, the dust generation rate prediction model outputs a predicted ideal dust generation rate; The layout information and ventilation parameter information of the ventilation and dust removal system in the spinning workshop are obtained, a first interference coefficient is determined according to the layout information and the ventilation parameter information, and the dust generation rate is calculated according to the first interference coefficient and the ideal dust generation rate.

[0008] In some embodiments, the obtaining of the layout information and ventilation parameter information of the ventilation and dust removal system in the spinning workshop, and determining the first interference coefficient according to the layout information and the ventilation parameter information, includes: Determine the number of ventilation openings corresponding to each of the spinning areas according to the layout information of the ventilation and dust removal system, and determine the ventilation rate information of a single ventilation opening according to the ventilation parameter information; The first interference coefficient is obtained by matching the number of ventilation openings and the ventilation rate information in a setting comparison table.

[0009] In some embodiments, the step of calculating the dust generation rate according to the first interference coefficient and the ideal dust generation rate includes: Acquire the adjacent spinning areas corresponding to the spinning area, and acquire the dynamic related information of each of the adjacent spinning areas, wherein the dynamic related information includes the traffic intensity of transport vehicles and the number of spinning workers; A second interference coefficient is obtained by evaluating the traffic intensity of the transport vehicle and the number of the spinning workers; The dust generation rate is calculated according to the first interference coefficient, the second interference coefficient and the ideal dust generation rate.

[0010] In some embodiments, determining the dust cleaning cycle of each spinning area according to the dust generation rate and the area type includes: If the area type is a manned area, a first group of dust cleaning cycles is determined, and the first group of dust cleaning cycles includes a number of first dust cleaning cycles; if the area type is an unmanned area, a second group of dust cleaning cycles is determined, and the second group of dust cleaning cycles includes an equal number of second dust cleaning cycles; the first dust cleaning cycle and the second dust cleaning cycle are both configured with corresponding dust generation rate intervals, and the first dust cleaning cycle is greater than the corresponding second dust cleaning cycle; According to the matching relationship between the dust generation rate and the dust generation rate interval, the corresponding first dust cleaning cycle or the second dust cleaning cycle is obtained by screening from the first group of dust cleaning cycles or the second group of dust cleaning cycles.

[0011] The present invention also discloses a dust control system for an intelligent spinning workshop, the system comprising a first acquisition module, a second acquisition module, a cycle determination module, and a control module connected in sequence; The first acquisition module is used to acquire the regional attributes of each spinning area in the spinning workshop, and determine the regional type of each spinning area according to the regional attributes, and the regional type includes a manned area and an unmanned area; The second acquisition module is used to acquire the spinning operation information of each spinning area, and predict the corresponding dust generation rate according to the spinning operation information; The cycle determination module is used to determine the dust cleaning cycle of each spinning area according to the dust generation rate and the area type; The control module is used to control the mobile dust cleaning robot to perform dust cleaning operations on each of the spinning areas; Among them, a fixed ventilation and dust removal system is also arranged in the spinning workshop, and the ventilation and dust removal system is mainly used to clean the dust floating in the upper layer of the spinning workshop.

[0012] The present invention also discloses an electronic device, comprising: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, wherein the processor executes the computer program to implement the method described in any of the preceding items.

[0013] The present invention also discloses a computer storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement any of the above methods.

[0014] The present invention also discloses a computer program product. When the computer program product is run on a terminal, the terminal implements any of the above methods when executing the computer program product.

[0015] In the scheme of the present invention, the conventional ventilation and dust removal system is mainly used to clean the dust floating in the upper and middle layers of the spinning workshop, while the mobile dust cleaning robot is mainly used to clean and control the floating and grounded dust in the spinning machine area in the lower layer of the spinning workshop. Through the coordinated cooperation of the two, the dust in the spinning workshop is fully cleaned. In addition, the present invention also determines the dust cleaning cycle of the mobile dust cleaning robot for each spinning area according to the area type and dust generation rate of each spinning area in the spinning workshop, which can reduce the impact on the spinning workers. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0017] Figure 1 It is a flow chart of a dust control method for an intelligent spinning workshop disclosed in an embodiment of the present invention; Figure 2 is a schematic diagram of a dust generation rate determination process disclosed in an embodiment of the present invention; Figure 3 It is a structural schematic diagram of a dust control system for an intelligent spinning workshop disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0018] The following is a description of the implementation of the present application by specific specific embodiments. People familiar with the technology can easily understand other advantages and effects of the present application from the contents disclosed in this specification. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0019] In addition, the technical features involved in the different embodiments of the present application described below can be combined with each other as long as they do not conflict with each other.

[0020] like Figure 1 As shown, an embodiment of the present invention discloses a dust control method for an intelligent spinning workshop, the method comprising the following steps: Acquire the regional attributes of each spinning area in the spinning workshop, and determine the regional type of each spinning area according to the regional attributes, wherein the regional type includes a manned area and an unmanned area; Acquire spinning operation information of each spinning area, and predict corresponding dust generation rate according to the spinning operation information; Determine the dust cleaning cycle of each spinning area according to the dust generation rate and the area type; Controlling a mobile dust cleaning robot to perform dust cleaning operations on each of the spinning areas; Among them, a fixed ventilation and dust removal system is also arranged in the spinning workshop, and the ventilation and dust removal system is mainly used to clean the dust floating in the upper layer of the spinning workshop.

[0021] The present invention adopts a mobile dust cleaning robot to clean dust in each spinning area in a spinning workshop, and the cleaning cycle of the mobile dust cleaning robot for each spinning area is different. The dust cleaning cycle is determined in the following way: first, the regional attributes of each spinning area in the spinning workshop are obtained, and the regional type of each spinning area is determined according to the regional attributes, that is, a manned area or an unmanned area. At the same time, the spinning operation information of each spinning area is also obtained, and the dust generation rate of the spinning area is predicted according to the spinning operation information, that is, the amount of dust generated per unit time, and the unit of the amount of dust here can be a weight unit. Finally, the dust cleaning cycle of each spinning area is determined based on the dust generation rate and regional type obtained in the above steps, and the mobile dust cleaning robot is controlled to perform mobile cleaning operations on each spinning area according to the dust cleaning cycle, and cooperates with a conventional ventilation and dust removal system to achieve better cleaning control of the dust in the spinning workshop.

[0022] Therefore, in the scheme of the present invention, the conventional ventilation and dust removal system is mainly used to clean the dust floating in the upper and middle layers of the spinning workshop, while the mobile dust cleaning robot is mainly used to clean and control the floating and grounded dust in the spinning machine area in the lower layer of the spinning workshop. Through the coordinated cooperation of the two, the dust in the spinning workshop is fully cleaned. In addition, the present invention also determines the dust cleaning cycle of the mobile dust cleaning robot for each spinning area according to the area type and dust generation rate of each spinning area in the spinning workshop, which can reduce the impact on the spinning workers.

[0023] Among them, the mobile dust cleaning robot mainly includes a controller, a communicator, a detection and navigation component, a driving component, a dust collection component, etc. The controller is used to control the detection and navigation component, the driving component, the dust collection component, etc. based on the received dust cleaning task, so as to realize the cleaning of the dust located in the spinning machine area in each spinning area. The communicator is used to receive the dust cleaning task from the control system, and the dust cleaning task at least includes the location number of each spinning area and the dust cleaning cycle. The dust collection component can be a barrel-shaped structure, that is, the adsorbed dust (cotton dust, linen dust, etc.) can be placed in the barrel-shaped structure, and the dust in the barrel-shaped structure is automatically dumped when the dust is full; the dust collection component can also be a sufficiently long hose, which transmits the dust adsorbed by the mobile dust cleaning robot to the dust storage area.

[0024] In some embodiments, the acquiring of the regional attributes of each spinning area in the spinning workshop and determining the regional type of each spinning area according to the regional attributes include: Acquire the regional attributes of each spinning area in the spinning workshop from the designated port, and parse the regional attributes to obtain the type of spinning machine in the spinning area; According to the spinning machine type, the spinning machine related information is crawled, and according to the spinning machine related information, the area type of each spinning area, the manned area and the unmanned area, is determined.

[0025] In an embodiment of the present invention, the regional attributes of each spinning area in a spinning workshop are pre-stored in a designated memory, such as a cloud, a local server, etc., and the regional attributes of each spinning area in the spinning workshop can be accessed from these memories through corresponding ports. The regional attributes include the type of spinning machines in each spinning area, and the above-mentioned spinning machine type information can be obtained by parsing the regional attributes. Then, the spinning machine related information corresponding to the spinning machine type is crawled on the network, and the crawled spinning machine related information is comprehensively analyzed to determine whether the type of spinning machine is a manned operation type or an unmanned operation type, and then determine whether the regional type of each spinning area is a manned area or an unmanned area.

[0026] It should be noted that the regional type of each spinning area can also be determined by analyzing whether there are spinning workers in each spinning area, but there are often people moving around in the spinning workshop, such as maintenance workers, finished product transport personnel, and cross-region movement of spinning workers in other spinning areas (areas with people), which can easily lead to misjudgment of the regional type of each spinning area. Therefore, the present invention preferably uses the above-mentioned solution of analyzing the regional type of the corresponding spinning area based on the type of the spinning machine.

[0027] In some embodiments, the predicting of the corresponding dust generation rate according to the spinning operation information includes: Analyzing the spinning operation information to obtain spinning raw material information, spinning machine status information, and spinning process parameter information; Inputting the spinning raw material information, the spinning machine state information and the spinning process parameter information into a dust generation rate prediction model based on a large model, the dust generation rate prediction model outputs a predicted ideal dust generation rate; The layout information and ventilation parameter information of the ventilation and dust removal system in the spinning workshop are obtained, a first interference coefficient is determined according to the layout information and the ventilation parameter information, and the dust generation rate is calculated according to the first interference coefficient and the ideal dust generation rate.

[0028] In the embodiment of the present invention, the spinning machine will generate a certain amount of dust during the spinning operation, and the dust generation rate is mainly related to factors such as spinning raw materials, spinning machine state, spinning process parameters, etc. The specific analysis is as follows: Spinning raw materials: Different fiber raw materials, such as cotton, linen, chemical fiber, etc., have different surface properties and breaking strength, resulting in different dust amounts during the spinning process. For example, when polyester staple fibers are spun at high speeds, the chemical fiber oil on their surface is easily peeled off to form adhesions, which affects the operation of the spinning machine and the quality of the yarn.

[0029] Spinning machine status: If the spinning machine is not properly maintained, the wear, deformation, aging and other problems of the equipment parts will cause the spinning machine to fail to fully exert its mechanical efficiency, thereby increasing the production rate of dust. Regular maintenance can reduce the occurrence of failures, extend the life of the equipment, and reduce the generation rate of dust.

[0030] Spinning process parameters: The process parameters in the spinning process, such as spinning speed, tension, temperature and humidity, will affect the generation of dust. For example, the higher the spinning speed, the greater the friction and breakage of the fiber, which may lead to more dust generation.

[0031] like Figure 2 As shown, the present invention obtains the above-mentioned dust generation rate prediction model based on the large model in advance, and the dust generation rate prediction model performs in-depth processing on the above-mentioned information that affects the dust generation rate, that is, obtains the ideal dust generation rate without interference from other factors. It should be noted that before the spinning raw material information, spinning machine state information and spinning process parameter information are input into the dust generation rate prediction model, the corresponding measured features can also be extracted according to the corresponding relationship between each factor and the dust generation rate, and then the measured features are combined into a feature matrix, and then the feature matrix is ​​input into the dust generation rate prediction model.

[0032] Among them, the dust generation rate prediction model is obtained by fine-tuning and training a general large model such as ChatGPT. The training data used for training is small sample training data, that is, the amount of training data used for the traditional vertical model based on neural network algorithm is smaller, for example, 100. Each training data may include the dust generation rate collected in the working state of the spinning machine, as well as the corresponding spinning raw material information, spinning machine status information, and spinning process parameter information.

[0033] At the same time, although the ventilation and dust removal system in the spinning workshop is mainly used to clean the dust in the upper layer of the spinning workshop, it will also take away the dust in the spinning machine area in the lower layer to a certain extent, so the dust generation rate (that is, the actual generation rate) in the spinning machine area is not directly equal to the above-mentioned ideal dust generation rate, but slightly less. In this regard, it is set to obtain the layout information and ventilation parameter information of the ventilation and dust removal system in the spinning workshop, and the corresponding first interference coefficient is determined based on this. According to the first interference coefficient and the ideal dust generation rate obtained above, the dust generation rate of the corresponding spinning area can be calculated. For example, dust generation rate = ideal dust generation rate * (1-first interference coefficient). The first interference coefficient is a value less than 1.

[0034] In some embodiments, the obtaining of the layout information and ventilation parameter information of the ventilation and dust removal system in the spinning workshop, and determining the first interference coefficient according to the layout information and the ventilation parameter information, includes: Determine the number of ventilation openings corresponding to each of the spinning areas according to the layout information of the ventilation and dust removal system, and determine the ventilation rate information of a single ventilation opening according to the ventilation parameter information; The first interference coefficient is obtained by matching the number of ventilation openings and the ventilation rate information in a setting comparison table.

[0035] In the embodiment of the present invention, the layout information of the ventilation and dust removal system refers to the number of vents corresponding to each spinning area, and the ventilation parameter information refers to the ventilation rate information of a single vent. The number of vents and the ventilation rate information of a single vent will affect the dust cleaning ability of the ventilation and dust removal system for the corresponding spinning area, that is, when the number of vents is more and the ventilation rate of a single vent is higher, the corresponding dust cleaning ability is stronger, and when the number of vents is less and the ventilation rate of a single vent is lower, the corresponding dust cleaning ability is weaker.

[0036] At the same time, a corresponding first interference coefficient is configured in advance for each different group of [number of vents, ventilation rate information], so as to construct a setting comparison table, which includes a plurality of corresponding relationships between the first interference coefficient and [number of vents, ventilation rate information]. In addition, in the process of establishing the above corresponding relationship, the actual area size of each spinning area, whether it is open or not, and other information can also be considered. Correspondingly, a setting comparison table can be configured for each group of spinning areas, and the details will not be repeated.

[0037] In some embodiments, the step of calculating the dust generation rate according to the first interference coefficient and the ideal dust generation rate includes: Acquire the adjacent spinning areas corresponding to the spinning area, and acquire the dynamic related information of each of the adjacent spinning areas, wherein the dynamic related information includes the traffic intensity of transport vehicles and the number of spinning workers; A second interference coefficient is obtained by evaluating the traffic intensity of the transport vehicle and the number of the spinning workers; The dust generation rate is calculated according to the first interference coefficient, the second interference coefficient and the ideal dust generation rate.

[0038] In an embodiment of the present invention, for a specific spinning area, in addition to the influence of the fixed ventilation and dust removal system arranged at a high place, it will also be affected by the adjacent spinning area, that is, some dust generated in the adjacent spinning area will also be blown to the spinning area. In response to this technical problem, the present invention further obtains dynamic related information of each adjacent spinning area, and the dynamic related information includes the traffic intensity of the transport vehicle and the number of spinning workers. Among them, the traffic intensity of the transport vehicle refers to the traffic intensity of the transport vehicles that transport spinning raw materials or finished cloths in the corresponding adjacent spinning area, which is mainly determined by parameters such as the size of the transport vehicle, the frequency of passage per unit time, and the size of the spinning raw materials or finished cloths. The greater the traffic intensity, the easier it is for the dust in the adjacent spinning area to be blown to the spinning area.

[0039] Similar to the traffic intensity of the transport vehicle, the number of spinners will also affect the amount or probability of dust in the adjacent spinning area being blown to the spinning area. Specifically, when the adjacent spinning area is a manned area, the work activities of the spinners will increase the airflow, causing more dust to be blown to the spinning area, and the amount of dust blown is proportional to the number of spinners.

[0040] Therefore, the traffic intensity of the transport vehicles in each adjacent spinning area is accumulated, and the number of spinning workers in each adjacent spinning area is also accumulated, and then the second interference coefficient can be obtained through evaluation and analysis. Obviously, the second interference coefficient is positively correlated with the traffic intensity of the transport vehicles and the number of spinning workers. However, the present invention does not limit the specific calculation formula of the second interference coefficient. Moreover, the second interference coefficient and the traffic intensity of the transport vehicles and the number of spinning workers can also be corresponded in the form of a comparison table, and the appropriate second interference coefficient can be determined by looking up the table later, and there is no limitation on this.

[0041] In addition, the dust generation rate=the ideal dust generation rate*(1-the first interference coefficient+the second interference coefficient).

[0042] In some embodiments, determining the dust cleaning cycle of each spinning area according to the dust generation rate and the area type includes: If the area type is a manned area, a first group of dust cleaning cycles is determined, and the first group of dust cleaning cycles includes a number of first dust cleaning cycles; if the area type is an unmanned area, a second group of dust cleaning cycles is determined, and the second group of dust cleaning cycles includes an equal number of second dust cleaning cycles; the first dust cleaning cycle and the second dust cleaning cycle are both configured with corresponding dust generation rate intervals, and the first dust cleaning cycle is greater than the corresponding second dust cleaning cycle; According to the matching relationship between the dust generation rate and the dust generation rate interval, the corresponding first dust cleaning cycle or the second dust cleaning cycle is obtained by screening from the first group of dust cleaning cycles or the second group of dust cleaning cycles.

[0043] In the embodiment of the present invention, the spinning area is divided into a manned area and an unmanned area according to the type of the spinning machine (i.e., whether the spinning personnel are required to participate). When the spinning area is a manned area, a first group of dust cleaning cycles is configured, which includes multiple first dust cleaning cycles; when the spinning area is an unmanned area, a second group of dust cleaning cycles is configured, which includes multiple second dust cleaning cycles. Moreover, the first dust cleaning cycle corresponding to the manned area is greater than the second dust cleaning cycle of the unmanned area.

[0044] The reason for such setting is that when the mobile dust cleaning robot cleans the dust in the spinning area, it will interfere with the spinning operation of the spinners. Therefore, the mobile dust cleaning robot is set to clean the dust in the manned area with a longer first dust cleaning cycle. In the unmanned area, there is no such interference problem, so the dust cleaning operation is set to be performed with a shorter second dust cleaning cycle, which can ensure the cleanliness of the spinning area and reduce the amount of dust blown to the manned area.

[0045] After determining the corresponding first group of dust cleaning cycles or the second group of dust cleaning cycles, the corresponding first dust cleaning cycle or the second dust cleaning cycle can be matched according to the dust generation rate determined above. The dust generation rate and the dust cleaning cycle are obviously negatively correlated, that is, when the dust generation rate is higher, the dust cleaning cycle is set to be smaller and the dust cleaning is performed at a higher frequency, and vice versa, the dust cleaning cycle is set to be longer and the dust cleaning is performed at a lower frequency.

[0046] like Figure 3 As shown, an embodiment of the present invention further discloses a dust control system for an intelligent spinning workshop, the system comprising a first acquisition module, a second acquisition module, a cycle determination module, and a control module connected in sequence; The first acquisition module is used to acquire the regional attributes of each spinning area in the spinning workshop, and determine the regional type of each spinning area according to the regional attributes, and the regional type includes a manned area and an unmanned area; The second acquisition module is used to acquire the spinning operation information of each spinning area, and predict the corresponding dust generation rate according to the spinning operation information; The cycle determination module is used to determine the dust cleaning cycle of each spinning area according to the dust generation rate and the area type; The control module is used to control the mobile dust cleaning robot to perform dust cleaning operations on each of the spinning areas; Among them, a fixed ventilation and dust removal system is also arranged in the spinning workshop, and the ventilation and dust removal system is mainly used to clean the dust floating in the upper layer of the spinning workshop.

[0047] An embodiment of the present invention further discloses an electronic device, comprising: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, wherein the processor executes the computer program to implement the method described in the above embodiment.

[0048] An embodiment of the present invention further discloses a computer storage medium, wherein the computer storage medium stores a computer program, and the computer program is executed by a processor to implement the method described in the above embodiment.

[0049] The embodiment of the present invention further discloses a computer program product. When the computer program product is run on a terminal, the terminal implements the method described in the above embodiment.

[0050] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0051] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0052] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0053] The above description is only a preferred embodiment of the present invention and is not intended to limit the protection scope of the present invention.

Claims

1. A dust control method for an intelligent spinning workshop, characterized in that: The method comprises the following steps: Acquire the regional attributes of each spinning area in the spinning workshop, and determine the regional type of each spinning area according to the regional attributes, wherein the regional type includes a manned area and an unmanned area; Acquire spinning operation information of each spinning area, and predict corresponding dust generation rate according to the spinning operation information; Determine the dust cleaning cycle of each spinning area according to the dust generation rate and the area type; Controlling a mobile dust cleaning robot to perform dust cleaning operations on each of the spinning areas; Among them, a fixed ventilation and dust removal system is also arranged in the spinning workshop, and the ventilation and dust removal system is mainly used to clean the dust floating in the upper layer of the spinning workshop.

2. The dust control method for an intelligent spinning workshop according to claim 1 is characterized in that: Acquiring the regional attributes of each spinning area in the spinning workshop, and determining the regional type of each spinning area according to the regional attributes, including: Acquire the regional attributes of each spinning area in the spinning workshop from the designated port, and parse the regional attributes to obtain the type of spinning machine in the spinning area; The spinning machine related information is crawled according to the spinning machine type, and the area type of each spinning area is determined according to the spinning machine related information.

3. The dust control method for an intelligent spinning workshop according to claim 2 is characterized in that: The corresponding dust generation rate is predicted based on the spinning operation information, including: Analyzing the spinning operation information to obtain spinning raw material information, spinning machine status information, and spinning process parameter information; Inputting the spinning raw material information, the spinning machine state information and the spinning process parameter information into a dust generation rate prediction model based on a large model, the dust generation rate prediction model outputs a predicted ideal dust generation rate; The layout information and ventilation parameter information of the ventilation and dust removal system in the spinning workshop are obtained, a first interference coefficient is determined according to the layout information and the ventilation parameter information, and the dust generation rate is calculated according to the first interference coefficient and the ideal dust generation rate.

4. The dust control method for an intelligent spinning workshop according to claim 3 is characterized in that: Acquiring the layout information and ventilation parameter information of the ventilation and dust removal system in the spinning workshop, and determining a first interference coefficient according to the layout information and the ventilation parameter information, including: Determine the number of ventilation openings corresponding to each of the spinning areas according to the layout information of the ventilation and dust removal system, and determine the ventilation rate information of a single ventilation opening according to the ventilation parameter information; The first interference coefficient is obtained by matching the number of ventilation openings and the ventilation rate information in a setting comparison table.

5. The dust control method for an intelligent spinning workshop according to claim 4 is characterized in that: The dust generation rate is calculated according to the first interference coefficient and the ideal dust generation rate, comprising: Acquire the adjacent spinning areas corresponding to the spinning area, and acquire the dynamic related information of each of the adjacent spinning areas, wherein the dynamic related information includes the traffic intensity of transport vehicles and the number of spinning workers; A second interference coefficient is obtained by evaluating the traffic intensity of the transport vehicle and the number of the spinning workers; The dust generation rate is calculated according to the first interference coefficient, the second interference coefficient and the ideal dust generation rate.

6. The dust control method for an intelligent spinning workshop according to claim 1 is characterized in that: Determining the dust cleaning cycle of each spinning area according to the dust generation rate and the area type includes: If the area type is a manned area, a first group of dust cleaning cycles is determined, and the first group of dust cleaning cycles includes a number of first dust cleaning cycles; if the area type is an unmanned area, a second group of dust cleaning cycles is determined, and the second group of dust cleaning cycles includes an equal number of second dust cleaning cycles; the first dust cleaning cycle and the second dust cleaning cycle are both configured with corresponding dust generation rate intervals, and the first dust cleaning cycle is greater than the corresponding second dust cleaning cycle; According to the matching relationship between the dust generation rate and the dust generation rate interval, the corresponding first dust cleaning cycle or the second dust cleaning cycle is obtained by screening from the first group of dust cleaning cycles or the second group of dust cleaning cycles.

7. A dust control system for an intelligent spinning workshop, the system comprising a first acquisition module, a second acquisition module, a cycle determination module, and a control module connected in sequence; characterized in that: The first acquisition module is used to acquire the regional attributes of each spinning area in the spinning workshop, and determine the regional type of each spinning area according to the regional attributes, and the regional type includes a manned area and an unmanned area; The second acquisition module is used to acquire the spinning operation information of each spinning area, and predict the corresponding dust generation rate according to the spinning operation information; The cycle determination module is used to determine the dust cleaning cycle of each spinning area according to the dust generation rate and the area type; The control module is used to control the mobile dust cleaning robot to perform dust cleaning operations on each of the spinning areas; Among them, a fixed ventilation and dust removal system is also arranged in the spinning workshop, and the ventilation and dust removal system is mainly used to clean the dust floating in the upper layer of the spinning workshop.

8. An electronic device, comprising: At least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, wherein the processor executes the computer program to implement the method according to any one of claims 1 to 6.

9. A computer storage medium storing a computer program, characterized in that: The computer program is executed by a processor to implement the method according to any one of claims 1 to 6.

10. A computer program product comprising a computer program stored on a non-transitory computer readable medium, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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