Method and system for intelligently converting hand sample formula into production formula

Abstract

The invention discloses a method and a system for intelligently converting a sample formula into a production formula. According to the technical scheme, the method comprises the following steps: acquiring basic information required by formula conversion; screening matched historical data, and calculating a color difference correction coefficient; calculating a colored light correction formula in combination with historical data and to-be-converted sample information; and comprehensively calculating to obtain a production formula after intelligent conversion. According to the method provided by the invention, various factors of conversion from a sample formula to a production formula are comprehensively considered, and the production history database is combined, so that the one-sidedness and limitation of artificial experience are avoided; meanwhile, an advanced intelligent algorithm is adopted, a correction coefficient and a correction mechanism are introduced, and the problems of high subjectivity, high volatility and low efficiency caused by formula conversion only depending on artificial experience are solved. Compared with an existing method, the method is easy and convenient to operate and learn, in practical application, the requirement for practitioners is low, stability is good, objectivity is high, conversion efficiency and accuracy are improved, and practicability is high.

Description

Technical Field

[0001] The present invention relates to a technology for obtaining a production formula, and in particular to a method and system for intelligently converting a sample formula into a production formula. Background Art

[0002] Printing and dyeing is one of the key steps from raw materials to finished products of textiles, and occupies a vital position in the textile industry chain. It can not only give textiles rich colors and patterns, thereby significantly improving the added value of products, but also meet consumers' demand for personalization and fashion, making textiles more attractive in the market and improving market competitiveness.

[0003] Batch production of products with the color quality specified by customers is an important part of printing and dyeing enterprises. Usually, they first make color samples based on customer samples, and then convert the sample formula into production formula after approval, and arrange for batch production. In theory, if refined management can be achieved, under the premise that the textile substrate and the dyeing materials (dyes, chemical auxiliaries) used in the dyeing process are completely consistent, and the process curve of the entire dyeing process is strictly followed, the "sample formula" can be directly used as the "production formula" to obtain a production sample with a smaller color difference from the color sample, so as to achieve "production success at one time". However, the actual production is not like this, because the vast majority of small samples used by current printing and dyeing companies are "immersion dyeing", while large-scale production has both "immersion dyeing" and "roll dyeing", and even if the dyeing method is the same, there are many types of production equipment used, and there are cylinder differences between the same type of equipment; in addition, dyes and chemicals need to be added during the dyeing process. Due to differences in processing weights and equipment operations, large-scale production cannot be completely consistent with the process operations of small samples; in addition, some companies have relatively rough management and cannot achieve refined management, which will further increase the color difference between small samples and production samples, resulting in a low "one-time success rate" in actual production, requiring additional "rework", extending the production cycle, and significantly increasing production costs. This is one of the problems that has long plagued the printing and dyeing industry at home and abroad.

[0004] In order to improve the "first-time success rate" of actual production, production technicians usually do not directly use the "sample formula" as the "production formula", but use it after conversion. The higher the accuracy of the conversion from the sample to the production formula, the higher the first-time success rate of production. In the early days, printing and dyeing companies with conditions would adopt the "medium sample" method after obtaining qualified samples and formulas, simulate the actual production process through the medium sample machine, adjust the "sample formula" until a formula with qualified color light is obtained, and use it as the converted "production formula" for batch production. However, the added "medium sample" process is more complicated and inefficient than "making samples", which prolongs the production cycle. It is gradually being eliminated because it cannot adapt to the development trend of small batches, multiple varieties, and fast delivery. Currently, there are very few companies using this method. Nowadays, most companies mainly use two methods to "convert small sample formula to large sample formula". The first is that the technicians directly convert the small sample formula according to their own experience to obtain the large sample formula; the second is that after the small sample is confirmed, the "duplicate sample" process is added (in the laboratory, the same textile substrate and dyes used in production are used, and the dyeing process is as consistent as possible to carry out dyeing) to obtain a "duplicate sample formula" with qualified color light, and then convert it into a "production formula" according to their own experience. Compared with the "medium sample", the current two methods, although the "duplicate sample" has one more process, the accuracy of the conversion to the production formula is higher. The two methods are essentially the same and both need to be converted to the production formula. At present, the above two methods still require technicians to combine the properties of the dyes, dyeing processes, and processing methods, and manually convert the formula according to their own professional skills. They are very dependent on the professional level and personal experience of the technicians. The conversion accuracy is not ideal, the subjectivity is strong, and the stability is poor.

[0005] At the end of the 19th century, the development of chromatography provided a scientific basis for textile color matching. With the development of computer technology, computer-aided color matching methods came into being and entered a stage of rapid development in the 1980s. At present, computer color measurement and matching systems have been widely used in laboratory color imitation and sample making in printing and dyeing enterprises. However, compared with laboratory color imitation, actual production is more complex and has high trial and error costs. Therefore, at present, computer technology is rarely used in the actual production stage at home and abroad, and it is almost not used in the "conversion of sample formula to production formula" to obtain the "production head cylinder formula".

[0006] With the rapid development of digitalization and intelligence, using digitalization and automation technology to try to solve the problems encountered in the printing and dyeing industry is a future development trend. Therefore, applying advanced intelligent technology to the "conversion of sample formula to production formula" to solve the problem of "low one-time success rate of production" meets the needs of the industry and is a future development trend of the industry. Summary of the invention

[0007] A brief summary of one or more aspects is given below to provide a basic understanding of these aspects. This summary is not an exhaustive overview of all conceived aspects, and is neither intended to identify the key or critical elements of all aspects nor to define the scope of any or all aspects. Its only purpose is to give some concepts of one or more aspects in a simplified form as a prelude to a more detailed description that will be given later.

[0008] The purpose of the present invention is to solve the above-mentioned problems and to provide a method and system for intelligent conversion of sample formulation into production formula. The method and system are simple and easy to learn and operate. In practical applications, the method and system have low requirements for practitioners, good stability, strong objectivity, and improve the efficiency and accuracy of the conversion, and are highly practical.

[0009] The technical solution of the present invention is: the present invention discloses a method for intelligently converting a sample formulation into a production formulation, the method comprising:

[0010] Step S1: Obtain the basic information required for formula conversion: light source type, textile fiber type, textile specifications, and reflectance value R of the sample color to be converted 小 , dyeing formula A of the sample color to be converted 小 , production process, equipment number to be produced, including dyeing formula A of the sample color to be converted 小 Including dye combinations and corresponding concentrations;

[0011] Step S2: Filtering historical data in the database that are the same as those in step S1 in terms of fiber type, specification, dye combination, and production process of the textiles, wherein the database stores historical records of related information of "sample formula → production formula";

[0012] Step S3: Among the historical data filtered out in step S2, further filter out H historical data of "the production equipment number is the same, and the color difference between the sample color and the color to be converted is less than or equal to k value" and "the production equipment number is different, and the color difference between the sample color and the color to be converted is less than or equal to km value", and sort them;

[0013] Step S4: Obtain relevant information of T historical data before sorting: reflectance value of sample color Dyeing formula for sample colors Produces the reflectance value of the color Dyeing formulas for production colors

[0014] Step S5: Based on the basic information of step S1 and the historical data of step S4, the converted production formula A is obtained by calculation according to the following formula: 生 :

[0015]

[0016] Among them, A 生 Represents the converted production formula,

[0017] Indicates the dyeing formula of the production color of the first historical data in sorting order,

[0018] A 小 The dyeing formula representing the color of the sample to be converted,

[0019] The dyeing formula for the sample color of the first sorted historical data is shown.

[0020] η represents the color difference correction coefficient,

[0021] A 校 Indicates a production shade correction formula.

[0022] According to an embodiment of the method for intelligently converting a sample formula into a production formula of the present invention, in step S2, in the historical records of the "sample formula→production formula" related information of the database, basic information includes: light source type, fiber type of textile, specification of textile, production process, production equipment number, reflectance value of sample color, dyeing formula of sample color, reflectance value of production color, dyeing formula of production color.

[0023] According to an embodiment of the method for intelligently converting a sample formulation into a production formulation of the present invention, in step S3, the k value ranges from a constant of 5 to 100, the m value ranges from a constant of 0 to k, and H is a natural number of 1 to 100; in step S4, the T value ranges from a natural number of 1 to H.

[0024] According to an embodiment of the method for intelligently converting a sample recipe into a production recipe of the present invention, in step S3, the factors affecting the sorting of historical data are: the production equipment number, the color difference between the sample color of the historical data and the color of the sample to be converted, and the sorting method of the historical data further includes:

[0025] 1) First, divide the historical data into two parts: the same part as the production equipment number and the part with different numbers of the equipment to be produced;

[0026] 2) Sort the two parts of data by color difference. The smaller the color difference value, the higher the ranking.

[0027] 3) For the different parts of the production equipment number and the equipment number to be produced, sort them and compare them with the "color difference of the same part of the production equipment number and the equipment number to be produced" in sequence, and sort them according to the following rules:

[0028] ① Color difference of the same part of the production equipment number - color difference of different parts of the production equipment number ≥n

[0029] Then the data of different parts of the production equipment number are sorted first;

[0030] ② Color difference of the same part of the production equipment number - color difference of different parts of the production equipment number <n

[0031] Then the data of different parts of the production equipment number are sorted at the end;

[0032] Where n is a constant ranging from 0.1 to k;

[0033] 4) Obtain the final comprehensive ranking results of the two parts of historical data.

[0034] According to an embodiment of the method for intelligently converting a sample recipe into a production recipe of the present invention, in step S5, the calculation method of the color difference correction coefficient η is as follows:

[0035] Color Difference Correction Factor

[0036]

[0037] The values ​​of s are as follows:

[0038] When T≤H, s=T; when T>H, s=H;

[0039] The dyeing formula representing the production color of the sorted i-th historical data;

[0040] Represents the coloring formula of the sample color of the sorted i-th historical data.

[0041] According to an embodiment of the method for intelligently converting a sample formula to a production formula of the present invention, in step S5, the production color light correction formula A 校 The calculation method is as follows:

[0042] 1) Calculate according to the following formula to obtain the reflectance value r of the theoretical conversion color 转 ;

[0043]

[0044] The values ​​of s are as follows:

[0045] When T≤H, s=T; when T>H, s=H;

[0046] R 转 Represents the reflectance value of the theoretical converted color,

[0047] R 小 Indicates the reflectance value of the sample color to be converted.

[0048] Indicates the reflectance value of the production color of the first sorted historical data.

[0049] Indicates the reflectance value of the sample color of the first sorted historical data;

[0050] represents the reflectance value of the production color of the sorted i-th historical data;

[0051] Represents the reflectance value of the sample color of the sorted i-th historical data;

[0052] 2) Based on the reflectivity value R 转 , R 小 , and obtain the theoretical formula A corresponding to the reflectivity through the color matching system 转 ,

[0053] 3) Calculate according to the following formula to obtain the production color light correction formula A 校 :

[0054]

[0055] in,

[0056] A 转 Indicates the theoretical dyeing formula corresponding to the theoretical conversion color,

[0057] Indicates the theoretical dyeing formula corresponding to the color of the sample to be converted.

[0058] Indicates the theoretical dyeing formula corresponding to the production color of the first historical data in sorting order,

[0059] Indicates the dyeing formula of the production color of the first sorted historical data.

[0060] The present invention also discloses a system for intelligently converting a sample formulation into a production formulation, the system comprising:

[0061] The basic information acquisition module is used to obtain the basic information required for formula conversion: light source type, fiber type of textile, specifications of textile, reflectance value R of the sample color to be converted 小 , dyeing formula A of the sample color to be converted 小 , production process, equipment number to be produced, including dyeing formula A of the sample color to be converted 小 Including dye combinations and corresponding concentrations;

[0062] A data screening module is used to screen the historical data of the textiles in the database that have the same fiber type, specification, dye combination, and production process as those in the basic information acquisition module, wherein the database stores the historical records of the relevant information of "sample formula → production formula";

[0063] The data sorting module is used to further select H pieces of historical data of "the production equipment number is the same, and the color difference between the sample color and the sample color to be converted is less than or equal to k value" and "the production equipment number is different, and the color difference between the sample color and the sample color to be converted is less than or equal to km value" from the historical data filtered by the data filtering module, and sort them;

[0064] The historical data acquisition module is used to obtain relevant information of the historical data before sorting: the reflectance value of the sample color Dyeing formula for sample colors Produces the reflectance value of the color Dyeing formulas for production colors

[0065] The formula conversion calculation module is used to calculate the converted production formula A based on the basic information obtained by the basic information acquisition module and the historical data obtained by the historical data acquisition module according to the following formula: 生 :

[0066]

[0067] Among them, A 生 Represents the converted production formula,

[0068] Indicates the dyeing formula of the production color of the first historical data in sorting order,

[0069] A 小 The dyeing formula representing the color of the sample to be converted,

[0070] The dyeing formula for the sample color of the first sorted historical data is shown.

[0071] η represents the color difference correction coefficient,

[0072] A 校 Indicates a production shade correction formula.

[0073] The present invention also discloses a computer system for intelligent conversion of small sample formulations into production formulas, comprising a memory, a processor, and program instructions stored in the memory for execution by the processor, wherein the processor executes the program instructions to implement the steps of the method for intelligent conversion of small sample formulations into production formulas as described above.

[0074] The present invention also discloses a computer-readable storage medium for intelligent conversion of a sample formulation into a production formulation, which stores program instructions executable by a processor to implement the steps of the method for intelligent conversion of a sample formulation into a production formulation as described above.

[0075] The present invention also discloses a computer program product, including a computer program, which, when executed by a processor, implements the steps of the method for intelligently converting a small sample recipe into a production recipe as described above.

[0076] Compared with the prior art, the present invention has the following beneficial effects:

[0077] 1) The conversion model from sample formula to production formula established in the present invention comprehensively considers various factors of the conversion from sample formula to production formula, and combines the historical database of enterprise production, thereby avoiding the one-sidedness and limitations of manual experience, reducing the technical requirements for practitioners, and having wide applicability, high accuracy and strong practicality;

[0078] 2) The conversion model from sample formula to production formula established by the present invention adopts advanced intelligent algorithms, introduces correction coefficients and calibration mechanisms, has fast calculation speed, strong objectivity and good accuracy, and solves the problems of strong subjectivity, large volatility and low efficiency caused by relying on manual experience for formula conversion at present;

[0079] 3) Compared with the existing manual conversion methods, the intelligent conversion method of sample formulation to production formula provided by the present invention is simple and easy to learn, has low requirements on practitioners in practical applications, good stability, strong objectivity, high accuracy and efficiency, and strong practicality. BRIEF DESCRIPTION OF THE DRAWINGS

[0080] The above features and advantages of the present invention can be better understood after reading the detailed description of the embodiments of the present disclosure in conjunction with the following drawings. In the drawings, the components are not necessarily drawn to scale, and components with similar related properties or features may have the same or similar reference numerals.

[0081] Figure 1 A flow chart of an embodiment of the method for intelligently converting a sample formulation into a production formulation of the present invention is shown.

[0082] Figure 2 A schematic diagram showing an embodiment of a system for intelligently converting a sample recipe into a production recipe of the present invention. DETAILED DESCRIPTION

[0083] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. Note that the aspects described below in conjunction with the accompanying drawings and specific embodiments are only exemplary and should not be construed as limiting the scope of protection of the present invention in any way.

[0084] Step S1: Obtain the basic information required for formula conversion: light source type, textile fiber type, textile specifications, and reflectance value R of the sample color to be converted 小 , dyeing formula A of the sample color to be converted 小 , production process, equipment number to be produced, including dyeing formula A of the sample color to be converted 小 Includes dye combinations and corresponding concentrations.

[0085] In this step, the light source type includes: one of D65, CWF, A, TL84, U3000, UL35, and TL83;

[0086] In this step, the fiber type of the textile includes: one of natural fiber, regenerated fiber and synthetic fiber.

[0087] Step S2: Filter historical data in the database that are the same as those in step S1 in terms of fiber type, specification, dye combination, and production process of the textiles, wherein the database stores historical records of the relevant information of "sample formula → production formula".

[0088] In this step, in the historical records of the "sample formula → production formula" related information of the database, basic information includes: light source type, fiber type of textile, specification of textile, production process, production equipment number, reflectance value of sample color, dyeing formula of sample color, reflectance value of production color, dyeing formula of production color.

[0089] Step S3: Among the historical data filtered out in step S2, further filter out H historical data of "the production equipment number is the same, and the color difference between the sample color and the color to be converted is less than or equal to k value" and "the production equipment number is different, and the color difference between the sample color and the color to be converted is less than or equal to km value", and sort them;

[0090] In this step, the standard types of color difference are: CIE DE, DE CMC(l：c) , one of DE2000;

[0091] In this step: the k value ranges from a constant of 5 to 100, more preferably a constant of 5 to 25;

[0092] In this step: the value of m ranges from 0 to k, more preferably from 1 to 10;

[0093] In this step: H is a natural number from 1 to 100;

[0094] In this step, the factors that affect the sorting of historical data are: the production equipment number, the color difference between the sample color of the historical data and the color of the sample to be converted, and the sorting method of the historical data is as follows:

[0095] 1) First, divide the historical data into two parts: the same part and the different part of the production equipment number and the equipment number to be produced; 2) Then sort the two parts of data according to the color difference, the smaller the color difference value, the higher the ranking;

[0096] 3) For the different parts of the production equipment number and the equipment number to be produced, sort them and compare them with the "color difference of the same part of the production equipment number and the equipment number to be produced" in sequence, and sort them according to the following rules:

[0097] ① Color difference of the same part of the production equipment number - color difference of different parts of the production equipment number ≥n

[0098] The data of different parts of the production equipment number are sorted first;

[0099] ② Color difference of the same part of the production equipment number - color difference of different parts of the production equipment number <n

[0100] The data of different parts of the production equipment number are sorted at the end;

[0101] wherein n is a constant of 0.1 to k, more preferably a constant of 1 to 8;

[0102] 4) Obtain the final comprehensive ranking results of the two parts of historical data.

[0103] Step S4: Obtain relevant information of T historical data before sorting: reflectance value of sample color Dyeing formula for sample colors Produces the reflectance value of the color Dyeing formulas for production colors

[0104] In this step: the T value is a natural number of 1 to H, more preferably a natural number of 1 to 10.

[0105] Step S5: Based on the basic information of step S1 and the historical data of step S4, the converted production formula A is obtained by calculation according to the following formula: 生 , and output.

[0106]

[0107] Among them: A 生 Indicates: the production formula after conversion;

[0108] Indicates: the dyeing formula of the production color of the first historical data in sorting order;

[0109] A小 Indicates: the dyeing formula of the sample color to be converted;

[0110] Indicates: the dyeing formula of the sample color of the first sorted historical data;

[0111] η represents: color difference correction coefficient;

[0112] A 校 Meaning: Produces a color-corrected formula.

[0113] In this step: the calculation method of the color difference correction coefficient η is as follows:

[0114] Color Difference Correction Factor

[0115] Among them: the value of s is as follows:

[0116] When T≤H, s=T; when T>H, s=H;

[0117] Represents: the dyeing formula of the production color of the sorted i-th historical data;

[0118] Represents: the dyeing formula of the sample color of the sorted i-th historical data.

[0119] In this step: the production of color light correction formula A 校 The calculation method is as follows:

[0120] 1) Calculate according to the following formula to obtain the reflectance value R of the theoretical conversion color 转 ;

[0121]

[0122] Among them: the value of s is as follows:

[0123] When T≤H, s=T; when T>H, s=H;

[0124] R 转 Indicates: reflectance value of theoretical conversion color;

[0125] R 小 Indicates: the reflectance value of the sample color to be converted;

[0126] Indicates: the reflectance value of the production color of the first historical data in sorting order;

[0127] Indicates: the reflectance value of the sample color of the first historical data sorted;

[0128] represents the reflectance value of the production color of the sorted i-th historical data;

[0129] Represents the reflectance value of the sample color of the sorted i-th historical data.

[0130] 2) Based on the reflectivity value R 转 , R 小 , through the color matching system, obtain the theoretical formula A corresponding to the reflectivity 转 ,

[0131] 3) Calculate according to the following formula to obtain the production color light correction formula A 校 .

[0132]

[0133] in:

[0134] A 转 Indicates: theoretical dyeing formula corresponding to theoretical conversion color;

[0135] Indicates: the theoretical dyeing formula corresponding to the color of the sample to be converted;

[0136] Indicates: the theoretical dyeing formula corresponding to the production color of the first historical data in sorting order;

[0137] Indicates: the dyeing formula of the production color of the first sorted historical data.

[0138] Figure 2 The principle of an embodiment of the system for intelligently converting sample recipes to production recipes of the present invention is shown. Figure 2 The system of this embodiment includes: a basic information acquisition module, a data screening module, a data sorting module, a historical data acquisition module, and a formula conversion calculation module.

[0139] The basic information acquisition module is used to obtain the basic information required for formula conversion: light source type, fiber type of textile, specifications of textile, reflectance value R of the color of the sample to be converted 小 , dyeing formula A of the sample color to be converted 小 , production process, equipment number to be produced, including dyeing formula A of the sample color to be converted 小 Includes dye combinations and corresponding concentrations.

[0140] In this module, the light source type includes: one of D65, CWF, A, TL84, U3000, UL35, and TL83;

[0141] In this module, the fiber type of the textile includes: natural fiber, regenerated fiber, and synthetic fiber.

[0142] The data screening module is used to screen the historical data of the textiles with the same fiber type, specification, dye combination and production process as those in the basic information acquisition module in the database, wherein the historical records of the relevant information of "sample formula → production formula" are stored in the database.

[0143] In this module, in the relevant information history record of "sample formula→production formula" in the database, basic information includes: light source type, fiber type of textile, specification of textile, production process, production equipment number, reflectance value of sample color, dyeing formula of sample color, reflectance value of production color, dyeing formula of production color.

[0144] The data sorting module is used to further filter out H historical data of "the production equipment number is the same, and the color difference between the sample color and the sample color to be converted is less than or equal to k value" and "the production equipment number is different, and the color difference between the sample color and the sample color to be converted is less than or equal to km value" from the historical data filtered out by the data filtering module, and sort them.

[0145] In this module, the standard types of color difference are: CIE DE, DE CMC(l：c) , one of DE2000;

[0146] In this module: the range of the k value is: a constant of 5 to 100, more preferably a constant of 5 to 25;

[0147] In this module: the value of m ranges from 0 to k, more preferably from 1 to 10;

[0148] In this module: H is a natural number from 1 to 100;

[0149] In this module, the factors that affect the sorting of historical data are: production equipment number, color difference between the sample color of historical data and the color of the sample to be converted, and the sorting method of the historical data is as follows:

[0150] (1) First, the historical data is divided into two parts: the same production equipment number and the equipment number to be produced are the same, and the different parts;

[0151] (2) sorting the two parts of data respectively according to the color difference, the smaller the color difference value, the higher the ranking;

[0152] (3) For the different parts of the production equipment number and the equipment number to be produced, compare them in order with the "color difference of the same part of the production equipment number and the equipment number to be produced", and sort them according to the following rules:

[0153] ① Color difference of the same part of the production equipment number - color difference of different parts of the production equipment number ≥n

[0154] The data of different parts of the production equipment number are sorted first;

[0155] ② Color difference of the same part of the production equipment number - color difference of different parts of the production equipment number <n

[0156] The data of different parts of the production equipment number are sorted at the end;

[0157] wherein n is a constant of 0.1 to k, more preferably a constant of 1 to 8;

[0158] (4) Obtain the final comprehensive ranking results of the two parts of historical data.

[0159] The historical data acquisition module obtains the relevant information of the T historical data before sorting: the reflectance value of the sample color Dyeing formula for sample colors Produces the reflectance value of the color Dyeing formulas for production colors

[0160] In this module: the T value is a natural number from 1 to H, and more preferably a natural number from 1 to 10.

[0161] The formula conversion calculation module calculates the converted production formula A based on the basic information obtained by the basic information acquisition module and the historical data obtained by the historical data acquisition module according to the following formula: 生 , and output.

[0162]

[0163] Among them: A 生 Indicates: the production formula after conversion;

[0164] Indicates: the dyeing formula of the production color of the first historical data in sorting order;

[0165] A 小 Indicates: the dyeing formula of the sample color to be converted;

[0166] Indicates: the dyeing formula of the sample color of the first sorted historical data;

[0167] η represents: color difference correction coefficient;

[0168] A 校 Meaning: Produces a color-corrected formula.

[0169] In this module: the calculation method of the color difference correction coefficient η is as follows:

[0170] Color Difference Correction Factor

[0171]

[0172] Among them: the value of s is as follows:

[0173] When T≤H, s=T; when T>H, s=H;

[0174] Represents: the dyeing formula of the production color of the sorted i-th historical data;

[0175] Represents: the dyeing formula of the sample color of the sorted i-th historical data.

[0176] In this module: Production of a color correction formula A 校 The calculation method is as follows:

[0177] 1) Calculate according to the following formula to obtain the reflectance value R of the theoretical conversion color 转 ;

[0178]

[0179] Among them: the value of s is as follows:

[0180] When T≤H, s=T; when T>H, s=H;

[0181] R 转 Indicates: reflectance value of theoretical conversion color;

[0182] R 小 Indicates: the reflectance value of the sample color to be converted;

[0183] Indicates: the reflectance value of the production color of the first historical data in sorting order;

[0184] Indicates: the reflectance value of the sample color of the first historical data sorted;

[0185] represents the reflectance value of the production color of the sorted i-th historical data;

[0186] Represents the reflectance value of the sample color of the sorted i-th historical data.

[0187] 2) Based on the reflectivity value R 转 , R 小 , through the color matching system, obtain the theoretical formula A corresponding to the reflectivity 转 ,

[0188] 3) Calculate according to the following formula to obtain the production color light correction formula A 校 .

[0189]

[0190] in:

[0191] A 转 Indicates: theoretical dyeing formula corresponding to theoretical conversion color;

[0192] Indicates: the theoretical dyeing formula corresponding to the color of the sample to be converted;

[0193] Indicates: the theoretical dyeing formula corresponding to the production color of the first historical data in sorting order;

[0194] Indicates: the dyeing formula of the production color of the first sorted historical data.

[0195] In addition, the present invention also discloses a computer system for intelligent conversion of sample formulations into production formulas, comprising a memory, a processor, and program instructions stored in the memory for execution by the processor, wherein the processor executes the program instructions to implement the steps of the aforementioned method embodiment for intelligent conversion of sample formulations into production formulas.

[0196] In addition, the present invention also discloses a computer-readable storage medium for intelligent conversion of sample formulations into production formulas, which stores program instructions executable by a processor to implement the steps of the aforementioned method embodiment for intelligent conversion of sample formulations into production formulas.

[0197] In addition, the present invention also discloses a computer program product, including a computer program, which, when executed by a processor, implements the steps of the aforementioned method embodiment for intelligent conversion of a sample formula into a production formula.

[0198] Although the above methods are illustrated and described as a series of actions for simplicity of explanation, it should be understood and appreciated that these methods are not limited by the order of the actions, because according to one or more embodiments, some actions may occur in a different order and / or concurrently with other actions from those illustrated and described herein or not illustrated and described herein but understandable to those skilled in the art.

[0199] Those skilled in the art will further appreciate that the various illustrative logic blocks, modules, circuits, and algorithm steps described in conjunction with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or a combination of the two. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps are generally described above in terms of their functionality. Whether such functionality is implemented as hardware or software depends on the specific application and the design constraints imposed on the overall system. The technician may implement the described functionality in different ways for each specific application, but such implementation decisions should not be interpreted as resulting in a departure from the scope of the present invention.

[0200] The various illustrative logic blocks, modules, and circuits described in conjunction with the embodiments disclosed herein may be implemented or performed with a general purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. The processor may also be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in cooperation with a DSP core, or any other such configuration.

[0201] The steps of the method or algorithm described in conjunction with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. The software module may reside in a RAM memory, a flash memory, a ROM memory, an EPROM memory, an EEPROM memory, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to a processor so that the processor can read and write information from / to the storage medium. In an alternative, a storage medium may be integrated into a processor. The processor and the storage medium may reside in an ASIC. The ASIC may reside in a user terminal. In an alternative, the processor and the storage medium may reside in a user terminal as discrete components.

[0202] In one or more exemplary embodiments, the functions described may be implemented in hardware, software, firmware, or any combination thereof. If implemented as a computer program product in software, each function may be stored on or transmitted by a computer-readable medium as one or more instructions or codes. Computer-readable media include both computer storage media and communication media, including any medium that facilitates the transfer of a computer program from one place to another. Storage media may be any available medium that can be accessed by a computer. As an example and not limitation, such a computer-readable medium may include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, disk storage or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of an instruction or data structure and can be accessed by a computer. Any connection is also properly referred to as a computer-readable medium. For example, if the software is transmitted from a website, a server, or other remote source using a coaxial cable, a fiber optic cable, a twisted pair, a digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwaves, the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwaves are included in the definition of the medium. Disk and disc as used herein include compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk and Blu-ray disc, wherein disk often reproduces data magnetically, while disc reproduces data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.

[0203] The previous description of the disclosure is provided to enable any person skilled in the art to make or use the disclosure. Various modifications to the disclosure will be apparent to those skilled in the art, and the general principles defined herein may be applied to other variations without departing from the spirit or scope of the disclosure. Thus, the disclosure is not intended to be limited to the examples and designs described herein, but should be granted the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for intelligently converting a sample formulation into a production formulation, characterized in that: Methods include: Step S1: Obtain the basic information required for formula conversion: light source type, textile fiber type, textile specifications, and reflectance value R of the sample color to be converted 小 , dyeing formula A of the sample color to be converted 小 , production process, equipment number to be produced, including dyeing formula A of the sample color to be converted 小 Including dye combinations and corresponding concentrations; Step S2: Filter historical data in the database that are the same as those in step S1 in terms of fiber type, specification, dye combination, and production process of the textile, wherein the database stores historical records of related information of "sample formula → production formula"; Step S3: Among the historical data filtered out in step S2, further filter out H historical data of "the production equipment number is the same, and the color difference between the sample color and the color to be converted is less than or equal to k value" and "the production equipment number is different, and the color difference between the sample color and the color to be converted is less than or equal to km value", and sort them; Step S4: Obtain relevant information of T historical data before sorting: reflectance value of sample color Dyeing formula for sample colors Produces the reflectance value of the color Dyeing formulas for production colors Step S5: Based on the basic information of step S1 and the historical data of step S4, the converted production formula A is obtained by calculation according to the following formula: 生 : Among them, A 生 Represents the converted production formula, Indicates the dyeing formula of the production color of the first sorted historical data, A 小 The dyeing formula representing the color of the sample to be converted, The dyeing formula for the sample color of the first sorted historical data is shown. η represents the color difference correction coefficient, A 校 Indicates a production shade correction formula.

2. The method for intelligently converting a sample recipe into a production recipe according to claim 1, characterized in that: In step S2, in the historical records of the "sample formula→production formula" related information of the database, basic information includes: light source type, fiber type of textile, specification of textile, production process, production equipment number, reflectance value of sample color, dyeing formula of sample color, reflectance value of production color, dyeing formula of production color.

3. The method for intelligently converting a sample recipe into a production recipe according to claim 1, characterized in that: In step S3, the k value ranges from a constant of 5 to 100, the m value ranges from a constant of 0 to k, and H is a natural number of 1 to 100; in step S4, the T value ranges from any natural number of 1 to H.

4. The method for intelligently converting a sample recipe into a production recipe according to claim 1, characterized in that: In step S3, the factors affecting the sorting of historical data are: the production equipment number, the color difference between the sample color of the historical data and the color of the sample to be converted, and the historical data sorting method further includes: 1) First, divide the historical data into two parts: the same part as the production equipment number and the part with different equipment numbers to be produced; 2) Sort the two parts of data by color difference. The smaller the color difference value, the higher the ranking. 3) For the different parts of the production equipment number and the equipment number to be produced, sort them and compare them with the "color difference of the same part of the production equipment number and the equipment number to be produced" in sequence, and sort them according to the following rules: ① Color difference of the same part of the production equipment number - color difference of different parts of the production equipment number ≥n Then the data of different parts of the production equipment number are sorted first; ② Color difference of the same part of the production equipment number - color difference of different parts of the production equipment number <n Then the data of different parts of the production equipment number are sorted at the end; Where n is a constant ranging from 0.1 to k; 4) Obtain the final comprehensive ranking results of the two parts of historical data.

5. The method for intelligently converting a sample recipe into a production recipe according to claim 1, characterized in that: In step S5, the color difference correction coefficient η is calculated as follows: Color Difference Correction Factor The values ​​of s are as follows: When T≤H, s=T; when T>H, s=H; The dyeing formula representing the production color of the sorted i-th historical data; Represents the coloring formula of the sample color of the sorted i-th historical data.

6. The method for intelligently converting a sample recipe into a production recipe according to claim 1, characterized in that: In step S5, the color correction formula A is produced 校 The calculation method is as follows: 1) Calculate according to the following formula to obtain the reflectance value R of the theoretical conversion color 转 ; in, The values ​​of s are as follows: When T≤H, s=T; when T>H, s=H; R 转 Represents the reflectance value of the theoretical converted color, R 小 Indicates the reflectance value of the sample color to be converted. Indicates the reflectance value of the production color of the first sorted historical data. Indicates the reflectance value of the sample color of the first sorted historical data; represents the reflectance value of the production color of the sorted i-th historical data; Represents the reflectance value of the sample color of the sorted i-th historical data; 2) Based on the reflectivity value R 转 , R 小 , and obtain the theoretical formula A corresponding to the reflectivity through the color matching system 转 , 3) Calculate according to the following formula to obtain the production color light correction formula A 校 : in, A 转 Indicates the theoretical dyeing formula corresponding to the theoretical conversion color, Indicates the theoretical dyeing formula corresponding to the color of the sample to be converted. Indicates the theoretical dyeing formula corresponding to the production color of the first historical data in sorting order, Indicates the dyeing formula of the production color of the first sorted historical data.

7. A system for intelligently converting sample formulation into production formulation, characterized in that: The system includes: The basic information acquisition module is used to obtain the basic information required for formula conversion: light source type, fiber type of textile, specifications of textile, reflectance value R of the color of the sample to be converted 小 , dyeing formula A of the sample color to be converted 小 , production process, equipment number to be produced, including dyeing formula A of the sample color to be converted 小 Including dye combinations and corresponding concentrations; A data screening module is used to screen historical data in the database that have the same fiber type, specification, dye combination, and production process as the textiles in the basic information acquisition module, wherein the database stores historical records of related information of "sample formula → production formula"; The data sorting module is used to further select H pieces of historical data of "the production equipment number is the same, and the color difference between the sample color and the sample color to be converted is less than or equal to k value" and "the production equipment number is different, and the color difference between the sample color and the sample color to be converted is less than or equal to km value" from the historical data filtered by the data filtering module, and sort them; The historical data acquisition module is used to obtain relevant information of the historical data before sorting: the reflectance value of the sample color Dyeing formula for sample colors Produces the reflectance value of the color Dyeing formulas for production colors The formula conversion calculation module is used to calculate the converted production formula A based on the basic information obtained by the basic information acquisition module and the historical data obtained by the historical data acquisition module according to the following formula: 生 : Among them, A 生 Represents the converted production formula, Indicates the dyeing formula of the production color of the first sorted historical data, A 小 The dyeing formula representing the color of the sample to be converted, The dyeing formula for the sample color of the first sorted historical data is shown. η represents the color difference correction coefficient, A 校 Indicates a production shade correction formula.

8. A computer system for intelligently converting sample formulations into production formulations, characterized in that: The method comprises a memory, a processor and program instructions stored in the memory and executable by the processor, wherein the processor executes the program instructions to implement the steps of the method for intelligently converting a sample formulation into a production formulation as described in any one of claims 1 to 6.

9. A computer-readable storage medium for intelligently converting a sample recipe into a production recipe, characterized in that: It stores program instructions executable by a processor to implement the steps of the method for intelligently converting a sample formulation into a production formulation 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 a processor, the steps of the method for intelligently converting a sample recipe into a production recipe are implemented as described in any one of claims 1 to 6.

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