A method, system, medium, and computer for controlling a drip machine

Abstract

The present application relates to a kind of drop machine control method, system, medium and computer, the data structure and interactive protocol of the drop formula of the present application are defined uniformly, so that the formula data of different brands drop machine can be collected to process formula library and be centrally managed.Uniformly split and issue greatly reduce the writing time of drop formula, improve the accuracy of formula writing.The subsequent small sample formula library provides basic data support when big data finds color, maximizes the utilization of formula.Effectively reduce the learning cost of operator drop machine, improve the efficiency and accuracy of factory proofing.

Description

Technical Field

[0001] This invention relates to the field of printing and dyeing equipment technology, and more specifically, to a method, system, medium, and computer for controlling a dripping machine. Background Technology

[0002] In the fabric dyeing process, the dyeing factory's laboratory first needs to analyze the color of the sample fabric provided by the customer, and then calculate several pre-mixed formulas required to dye the sample fabric the desired color. Finally, through a series of operations such as sampling and color correction, the optimal formula is determined and handed over to the production department for production. With the increasing variety of dyes and chemicals, the brands of dripping machines used in existing dyeing factories are also constantly increasing. During the sampling process, the need to use different brands of dripping machines and their control software presents the following shortcomings:

[0003] (1) The control software of different brands of dripping machines cannot communicate with each other, the hardware and software are severely coupled, the operation methods are also very different, and the learning cost is high; the data storage formats of different brands of dripping machine systems are very different, which makes it impossible to achieve data sharing and creates data silos, making it difficult to manage and reuse formula data in a unified manner.

[0004] (2) Samplers can only enter the pre-mixed formula one by one in the dispensing machine system, which is inefficient and has a high probability of color matching errors.

[0005] (3) Due to the limited amount of dyes and chemicals in the dripping machine, a formula needs to be split into different dripping machines for dripping. This requires manual memorization and retrieval of the storage location of the dyes and chemicals in different dripping machines, and then manual splitting of the formula and inputting it into the control software of different brands of dripping machines for dripping. This process is time-consuming and prone to errors.

[0006] (4) The factory collects the formulas manually by color card book and archives the formula information and sample cloth on paper. The workload is large, and manual data collection is prone to errors. At the same time, as the data increases, it is troublesome to find the historical drop formulas. Summary of the Invention

[0007] In view of the shortcomings of the existing technology, the purpose of this invention is to provide a control method, system, medium and computer for a dripping machine, so as to solve the problems of incompatibility of control software, serious differences in operation, high learning cost and easy operation error in existing dripping machines.

[0008] The above-mentioned technical objective of the present invention is achieved through the following technical solution: a method for controlling a dripping machine, comprising:

[0009] S1. Obtain the specification information of the dripping machine, and normalize the specification information of different models of dripping machines according to the actual meaning represented by the specification information, and bind the normalized dripping machine to the cloud control server.

[0010] S2. Calculate the color mixing range for each dripping machine based on its specifications.

[0011] S3. Obtain the dyeing standard sample, perform spectral analysis on the dyeing standard sample, obtain the first spectral data of the dyeing standard sample, compare the first spectral data with the color mixing range of the dispensing machine, and determine whether the color of the dyeing standard sample can be mixed by a single dispensing machine.

[0012] S4. If so, the color matching task will be sent to the dripping machine to perform formula prediction and dripping color matching, and the process formula obtained corresponding to the dripping color matching will be sent to the cloud server for storage.

[0013] S5. If not, the color matching task is split into multiple color matching tasks. These multiple color matching tasks are then sent to multiple dispensing machines for formula prediction and dispensing color matching, respectively. All process formulas obtained from the dispensing color matching of the multiple dispensing machines are sent to the cloud server for merging and storage.

[0014] Optionally, the information collected regarding the dripping machine specifications includes: device name, device brand, device model, communication method, IP address, device status, mother liquor bottle number, dye / chemical code, mother liquor concentration, and specific gravity; the normalization process includes:

[0015] S11. Abstract the equipment name, brand, model, communication method, IP address, and status of different drip machines into a drip machine model;

[0016] S12. The mother liquor bottle number, dye code, mother liquor concentration and specific gravity information are renumbered according to a predetermined rule, and the renumbered information is stored in the cloud server.

[0017] Optionally, an edge computing layer is established, which is communicatively connected to a cloud server and also communicatively connected to a dripping machine. The edge computing layer is used to receive the process recipe generated by the dripping machine, convert the data information contained in the process recipe according to the predetermined rules, and send the converted process recipe to the cloud server.

[0018] Optionally, during the dispensing color mixing process, the edge computing layer reads the formula data generated by the dispensing machine that is connected to the edge computing layer at predetermined intervals; the edge computing layer also uploads the formula data of the dispensing machine to the cloud server, and the cloud server merges and stores the formula data from the same dispensing machine.

[0019] Optionally, it also includes: dyeing the sample fabric using the process formula, and performing spectral detection and analysis on the dyed sample fabric to obtain the second spectral data corresponding to the process formula; and sending the spectral data to a cloud server for storage.

[0020] Optionally, it also includes: comparing the first spectral data and the second spectral data to determine whether the difference between the two is greater than the spectral difference threshold; if so, re-predicting the formula and re-adjusting the droplet color using the new formula.

[0021] A dripping machine control system, comprising:

[0022] Specification information acquisition module: used to acquire the specification information of the dripping machine;

[0023] Information normalization module: used to normalize the specification information of different models of dripping machines according to the actual meaning represented by the specification information;

[0024] Color toning range calculation module: Calculates the color toning range for each dispensing machine based on the dispensing machine information;

[0025] Spectral data analysis module: used to perform spectral analysis on stained standards, and obtain the first spectral data of the stained standards;

[0026] Color matching judgment module: used to compare the first spectral data with the color matching range of the dispensing machine to determine whether the color of the dyed standard sample can be matched by a single dispensing machine.

[0027] Optional, also includes:

[0028] Spectral data comparison module: used to compare the first spectral data and the second spectral data, and determine whether the difference between the two is greater than the spectral difference threshold;

[0029] Data transmission module: used to read the formula data generated by the dispensing machine at predetermined intervals during the dispensing color mixing process; and upload the formula data to the cloud server;

[0030] Data merging module: Used to merge and store formula data from the same dispensing machine.

[0031] A computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of the method described above.

[0032] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described above.

[0033] In summary, the present invention has the following beneficial effects:

[0034] This application, by defining a unified data structure and interaction protocol for dispensing formulas, enables the collection of formula data from different brands of dispensing machines into a centralized and unified process formula library for management. Automatic formula splitting and distribution significantly reduces dispensing formula writing time and improves formula writing accuracy. Furthermore, the subsequent sample formula library provides basic data support for color matching based on big data, maximizing formula utilization. This effectively reduces the learning cost for operators of dispensing machines and improves the factory's sampling efficiency and accuracy. Attached Figure Description

[0035] Figure 1 This is a flowchart of a drip machine control method according to the present invention;

[0036] Figure 2 This is a structural diagram of a dripping machine control system according to the present invention;

[0037] Figure 3 This is an internal structural diagram of a computer device in an embodiment of the present invention.

[0038] The diagram shows: 1. Specification information acquisition module; 2. Information normalization module; 3. Color range calculation module; 4. Spectral data analysis module; 5. Color judgment module; 6. Spectral data comparison module; 7. Data transmission module; 8. Data merging module. Detailed Implementation

[0039] To make the objectives, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Several embodiments of the present invention are shown in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein.

[0040] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances. The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined with "first" or "second" may explicitly or implicitly include one or more of that feature.

[0041] In this invention, unless otherwise expressly specified and limited, "above" or "below" a second feature can include direct contact between the first and second features, or contact between the first and second features through another feature between them. Furthermore, "above," "over," and "on top" of a second feature includes the first feature being directly above or diagonally above the second feature, or simply indicates that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" of a second feature includes the first feature being directly below or diagonally below the second feature, or simply indicates that the first feature is at a lower horizontal level than the second feature. The terms "vertical," "horizontal," "left," "right," "above," "below," and similar expressions are for illustrative purposes only and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed or operated in a specific orientation, and therefore should not be construed as limiting the invention.

[0042] The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0043] This invention provides a method for controlling a dripping machine, such as... Figure 1 As shown, it includes:

[0044] S1. Obtain the specification information of the dripping machine, and normalize the specification information of different models of dripping machines according to the actual meaning represented by the specification information, and bind the normalized dripping machine to the cloud control server.

[0045] S2. Calculate the color mixing range for each dripping machine based on its specifications.

[0046] S3. Obtain the dyeing standard sample, perform spectral analysis on the dyeing standard sample, obtain the first spectral data of the dyeing standard sample, compare the first spectral data with the color mixing range of the dispensing machine, and determine whether the color of the dyeing standard sample can be mixed by a single dispensing machine.

[0047] S4. If so, the color matching task will be sent to the dripping machine to perform formula prediction and dripping color matching, and the process formula obtained corresponding to the dripping color matching will be sent to the cloud server for storage.

[0048] S5. If not, the color matching task is split into multiple color matching tasks. These multiple color matching tasks are then sent to multiple dispensing machines for formula prediction and dispensing color matching, respectively. All process formulas obtained from the dispensing color matching of the multiple dispensing machines are sent to the cloud server for merging and storage.

[0049] In practical applications, existing dyeing and printing manufacturers often need to install multiple brands or models of dispensing machines within their factories to reduce reliance on a particular brand or to expand their business scope. Since these dispensing machines differ in control logic, signal transmission, and naming conventions, their specifications need to be rewritten in a standardized format. The control methods for these machines then need to be integrated into a unified cloud platform, enabling control and operation via a cloud server. When a dispensing color matching task is received, the standard sample is first analyzed. Then, using existing databases or the operator's experience, the color corresponding to the standard sample is divided into several different "pre-formulas." These pre-formulas are then distributed to different dispensing machines via the cloud server for dispensing experiments, yielding multiple sample results. Finally, the sample results are compared with the dyeing standard sample to determine the sample whose color is closest to the standard sample, which is then selected as the final choice. This patent first abstracts and unifies the different brands of drip machines, enabling unified management of drip machines of different brands and models. This effectively solves the problem of information silos between existing drip machines of different brands, reduces the learning cost for operators, and improves the operating efficiency of staff.

[0050] Furthermore, the specifications of the drip collection machine include: device name, device brand, device model, communication method, IP address, device status, mother liquor bottle number, dye / chemical code, mother liquor concentration, and specific gravity; the normalization process includes:

[0051] S11. Abstract the equipment name, brand, model, communication method, IP address, and status of different drip machines into a drip machine model;

[0052] S12. The mother liquor bottle number, dye code, mother liquor concentration and specific gravity information are renumbered according to a predetermined rule, and the renumbered information is stored in the cloud server.

[0053] In practical applications, the dispensing machine is abstractly modeled, mainly including information such as device name, brand, model, communication method, IP address, status, and mother liquor information, eliminating differences between different physical devices. This transforms the dispensing machine into an abstract online device. Since the signals generated or received by the dispensing machine are unique to it—for example, the coding for the color of some mother liquors differs between brand A and brand B—and the unit quantity of liquid dispensed varies between different machines during the color mixing process, these differences need to be eliminated by abstracting and unifying the different dispensing machines. This allows users to control different machines to perform the same operation using a specific set of rules. Specifically, the device name, brand, model, communication method, IP address, and status of different dispensing machines are all abstracted into a dispensing machine model. In other words, a single dispensing machine model replaces a specific dispensing machine device. Users only need to distinguish between dispensing machines in the management system, without needing to determine the specific name, model, brand, IP address, etc. As for the specific information about the dripping process in the dripping machine, the operator needs to understand it. This means that this relevant information needs to be standardized and a unified interaction protocol needs to be generated. Then, based on the unified interaction protocol, the operator can manage dripping machines of different brands in a unified manner through the cloud server system.

[0054] Furthermore, this application also provides a specific predetermined rule: A process formula library is constructed to uniformly collect process formulas completed by different models of dripping machines. Based on attribute fields with common meanings for different models of dripping machines, a unified process formula data structure is defined, mainly including information such as color number, dripping code, dripping version, fabric weight, liquor ratio, standard liquid dripping weight, dye code, dye name, and dye concentration, thereby adapting and summarizing formula data from different models of dripping machines. A unified rule is defined for the dripping code in the dripping machine, consisting of a color code + serial number + initials of the sampler's name. Simultaneously, different formulas using the same formula modification and dye / chemical concentration conversion are distinguished by the dripping version, thereby automatically identifying the color code information during process formula collection for association with actual sample fabrics in the factory.

[0055] Optionally, an edge computing layer is established, which is communicatively connected to a cloud server and also communicatively connected to a dripping machine. The edge computing layer is used to receive the process recipe generated by the dripping machine, convert the data information contained in the process recipe according to the predetermined rules, and send the converted process recipe to the cloud server.

[0056] In practical applications, bidirectional communication is achieved between the cloud server and the industrial control computer service, as well as between the industrial control computer service and the dripping control software. This enables the cloud server to control the dripping machine's data files and collect formula data, thereby achieving unified management of formula data on the cloud server and realizing unified cloud-based data management. Using an edge computing layer to manage the dripping machine improves its computing power while avoiding problems such as delayed control or data loss caused by network latency.

[0057] Optionally, during the dispensing color mixing process, the edge computing layer reads the formula data generated by the dispensing machine that is connected to the edge computing layer at predetermined intervals; the edge computing layer also uploads the formula data of the dispensing machine to the cloud server, and the cloud server merges and stores the formula data from the same dispensing machine.

[0058] Furthermore, this application establishes a middleware platform, GEMI, between the cloud server and the edge computing layer to encrypt and decrypt data transmitted between the edge computing layer and the cloud server. In this embodiment, the unified process and interaction protocol for distributing color formulas to the dispensing machine first encrypts the protocol content on the cloud server, generates a msgId, and transmits it to the edge control unit via the GEMI platform. The edge control unit uses the msgId to request the cloud server to query the encrypted protocol content, decrypts the data, identifies the specific dispensing machine, writes the color formula into the dispensing machine database, and simultaneously returns an ACK to the cloud server to update the color formula distribution status. The cloud server is actually a microservice with a B / S architecture, supporting multiple users to simultaneously operate online and write formulas into the dispensing machine database, thus solving the problem of low utilization of dispensing machine equipment.

[0059] Furthermore, it also includes: dyeing the sample fabric using the process formula, and performing spectral detection and analysis on the dyed sample fabric to obtain the second spectral data corresponding to the process formula; and sending the spectral data to a cloud server for storage.

[0060] In practical applications, when using samples for prototyping, multiple sample formulations need to be pre-allocated and distributed to different dispensing machines for prototyping. Regardless of whether the sample meets people's needs or whether the difference between it and the first spectral data is small, the sample data must be stored in the formulation library of the cloud server so that the cloud server's formulation library can be gradually enriched. The sampler uses a colorimeter to measure the spectral data of the actual colored cloth for each process formulation through the cloud server. Then, the big data algorithm of the cloud server can use the data in these process formulation libraries to recommend more accurate pre-formulation formulations for the factory for new standard colored cloth samples. The process formulations of the new dispensing completed process continue to be collected and added to the process formulation library, thus achieving a virtuous cycle. This solves the problems of difficult collection of process formulations and long time consumption from sample pre-formulation to production formulation, helping the factory reduce costs and increase efficiency.

[0061] Furthermore, it also includes: comparing the first spectral data and the second spectral data to determine whether the difference between them is greater than the spectral difference threshold. If so, the formula prediction is redone, and the new formula is used to redo the droplet color adjustment. Specifically, during the droplet color adjustment process, color-adjusted samples can be made one by one to avoid excessive sampling costs due to too many experimental samples. Therefore, after each sample is made, it is compared with the sample. When the difference between the sampled product and the dyed standard sample is large enough, it is necessary to redo the color adjustment and make a new sample.

[0062] like Figure 3 As shown, the present invention also provides a dripping machine control system, comprising:

[0063] Specification information acquisition module: used to acquire the specification information of the dripping machine;

[0064] Information normalization module: used to normalize the specification information of different models of dripping machines according to the actual meaning represented by the specification information;

[0065] Color toning range calculation module: Calculates the color toning range for each dispensing machine based on the dispensing machine information;

[0066] Spectral data analysis module: used to perform spectral analysis on stained standards, and obtain the first spectral data of the stained standards;

[0067] Color matching judgment module: used to compare the first spectral data with the color matching range of the dispensing machine to determine whether the color of the dyed standard sample can be matched by a single dispensing machine.

[0068] Furthermore, a drip dispensing machine control system also includes:

[0069] Spectral data comparison module: used to compare the first spectral data and the second spectral data, and determine whether the difference between the two is greater than the spectral difference threshold;

[0070] Data transmission module: used to read the formula data generated by the dispensing machine at predetermined intervals during the dispensing color mixing process; and upload the formula data to the cloud server;

[0071] Data merging module: Used to merge and store formula data from the same dispensing machine.

[0072] For specific limitations regarding the control system of a dripping machine, please refer to the limitations of the control method for a dripping machine mentioned above, which will not be repeated here. Each module in the aforementioned control system can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the operations corresponding to each module.

[0073] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 3 As shown, the computer device includes a processor, memory, network interface, and database connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system, computer programs, and database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage medium. When the computer program is executed by the processor, it implements a drip machine control method.

[0074] Those skilled in the art will understand that Figure 3 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0075] In one embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to perform the following steps: a drip machine control method, including:

[0076] S1. Obtain the specification information of the dripping machine, and normalize the specification information of different models of dripping machines according to the actual meaning represented by the specification information, and bind the normalized dripping machine to the cloud control server.

[0077] S2. Calculate the color mixing range for each dripping machine based on its specifications.

[0078] S3. Obtain the dyeing standard sample, perform spectral analysis on the dyeing standard sample, obtain the first spectral data of the dyeing standard sample, compare the first spectral data with the color mixing range of the dispensing machine, and determine whether the color of the dyeing standard sample can be mixed by a single dispensing machine.

[0079] S4. If so, the color matching task will be sent to the dripping machine to perform formula prediction and dripping color matching, and the process formula obtained corresponding to the dripping color matching will be sent to the cloud server for storage.

[0080] S5. If not, the color matching task is split into multiple color matching tasks. These multiple color matching tasks are then sent to multiple dispensing machines for formula prediction and dispensing color matching, respectively. All process formulas obtained from the dispensing color matching of the multiple dispensing machines are sent to the cloud server for merging and storage.

[0081] In one embodiment, the information collected from the dripping machine includes: device name, device brand, device model, communication method, IP address, device status, mother liquor bottle number, dye / chemical code, mother liquor concentration, and specific gravity; the normalization process includes:

[0082] S11. Abstract the equipment name, brand, model, communication method, IP address, and status of different drip machines into a drip machine model;

[0083] S12. The mother liquor bottle number, dye code, mother liquor concentration and specific gravity information are renumbered according to a predetermined rule, and the renumbered information is stored in the cloud server.

[0084] In one embodiment, an edge computing layer is established, which is communicatively connected to a cloud server and also communicatively connected to a dispensing machine. The edge computing layer is used to receive the process recipe generated by the dispensing machine, convert the data information contained in the process recipe according to the predetermined rules, and send the converted process recipe to the cloud server.

[0085] In one embodiment, during the dispensing color mixing process, the edge computing layer reads the formula data generated by the dispensing machine that is connected to the edge computing layer at predetermined time intervals; the edge computing layer also uploads the formula data of the dispensing machine to a cloud server, and the cloud server merges and stores the formula data from the same dispensing machine.

[0086] In one embodiment, the method further includes: dyeing a sample fabric using the process formula, performing spectral detection and analysis on the dyed sample fabric to obtain second spectral data corresponding to the process formula; and sending the spectral data to a cloud server for storage.

[0087] In one embodiment, the method further includes: comparing the first spectral data and the second spectral data to determine whether the difference between the two is greater than a spectral difference threshold; if so, re-predicting the formula and re-adjusting the droplet color using the new formula.

[0088] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0089] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0090] The above description is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A method for controlling a dripping machine, characterized in that, include: S1. Obtain the specification information of the dripping machine, and normalize the specification information of different models of dripping machines according to the actual meaning represented by the specification information, and bind the normalized dripping machine to the cloud control server. S2. Calculate the color mixing range for each dripping machine based on its specifications. S3. Obtain the dyeing standard sample, perform spectral analysis on the dyeing standard sample, obtain the first spectral data of the dyeing standard sample, compare the first spectral data with the color mixing range of the dispensing machine, and determine whether the color of the dyeing standard sample can be mixed by a single dispensing machine. S4. If so, the color matching task will be sent to the dripping machine to perform formula prediction and dripping color matching, and the process formula obtained corresponding to the dripping color matching will be sent to the cloud server for storage. S5. If not, the color matching task is split into multiple color matching tasks. These multiple color matching tasks are then sent to multiple dispensing machines for formula prediction and dispensing color matching, respectively. All process formulas obtained from the dispensing color matching of the multiple dispensing machines are sent to the cloud server for merging and storage.

2. The method for controlling a dripping machine according to claim 1, characterized in that, The specifications include: equipment name, equipment brand, equipment model, communication method, IP address, equipment status, mother liquor bottle number, dye / chemical code, mother liquor concentration, and specific gravity; the normalization process includes: S11. Abstract the equipment name, brand, model, communication method, IP address, and status of different drip machines into a drip machine model; S12. The mother liquor bottle number, dye code, mother liquor concentration and specific gravity information are renumbered according to a predetermined rule, and the renumbered information is stored in the cloud server.

3. The method for controlling a dripping machine according to claim 2, characterized in that, An edge computing layer is established, which communicates with the cloud server and also communicates with the drip machine; The edge computing layer is used to receive the process recipe generated by the dripping machine, convert the data information contained in the process recipe according to the predetermined rules, and send the converted process recipe to the cloud server.

4. The method for controlling a dripping machine according to claim 3, characterized in that, During the liquid coloring process, the edge computing layer reads the formula data generated by the liquid dispensing machine, which is connected to the edge computing layer, at predetermined intervals. The edge computing layer also uploads the formula data of the dripping machine to the cloud server, which then merges and stores the formula data from the same dripping machine.

5. The method for controlling a dripping machine according to claim 1, characterized in that, Also includes: The sample fabric was dyed using the process formula, and the dyed sample fabric was subjected to spectral detection and analysis to obtain the second spectral data corresponding to the process formula. The spectral data is sent to a cloud server for storage.

6. The method for controlling a dripping machine according to claim 5, characterized in that, Also includes: Compare the first spectral data and the second spectral data to determine whether the difference between them is greater than the spectral difference threshold. If so, re-predict the formula and use the new formula to re-adjust the color of the droplets.

7. A drip dispensing machine control system, characterized in that, include: Specification information acquisition module: used to acquire the specification information of the dripping machine; Information normalization module: It is used to normalize the specification information of different models of dripping machines according to the actual meaning represented by the specification information, and bind the normalized dripping machine to the cloud control server. Color mixing range calculation module: Calculates the color mixing range for each dispensing machine based on the specifications of the dispensing machine; Spectral data analysis module: used to perform spectral analysis on stained standards, and obtain the first spectral data of the stained standards; Color matching judgment module: used to compare the first spectral data with the color matching range of the dripping machine, and determine whether the color of the dyed standard sample can be matched by a dripping machine alone. If so, the color matching task is sent to the dripping machine to perform formula prediction and dripping color matching, and the process formula obtained by dripping color matching is sent to the cloud server for storage. If not, the color matching task is split into multiple color matching tasks, which are then distributed to multiple dispensing machines for formula prediction and dispensing color matching, respectively. All process formulas obtained from the dispensing color matching of multiple dispensing machines are sent to the cloud server for merging and storage.

8. A dripping machine control system according to claim 7, characterized in that, Also includes: Spectral data comparison module: used to compare the first spectral data and the second spectral data, and determine whether the difference between the two is greater than the spectral difference threshold; wherein, the second spectral data is obtained through the following steps: dyeing the sample fabric using the process formula, and performing spectral detection and analysis on the dyed sample fabric to obtain the second spectral data corresponding to the process formula; Data transmission module: used to read the formula data generated by the dispensing machine at predetermined intervals during the dispensing color mixing process; and upload the formula data to the cloud server; Data merging module: Used to merge and store formula data from the same dispensing machine.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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