CN111826966A

CN111826966A - Method for improving cotton knitted fabric hairiness by using cellulase

Info

Publication number: CN111826966A
Application number: CN202010616210.9A
Authority: CN
Inventors: 王连军; 易兵; 李荣龙; 汤威宜
Original assignee: Hunan Institute of Engineering
Current assignee: Hunan Institute of Engineering
Priority date: 2020-06-30
Filing date: 2020-06-30
Publication date: 2020-10-27

Abstract

The invention discloses a method for improving cotton knitted fabric hairiness by cellulase, which adopts a polishing and dyeing one-bath process, wherein the concentration of the cellulase is determined according to the following model: c_{Concentration of}-0.0237 × yarn count-0.05173 × bath ratio-0.03027 × temperature-0.62214 × time +0.626366 × hairiness grade difference + 3.106193. The invention can accurately adjust the process parameters according to the requirements of the cotton fabric hairiness level, realizes the quantitative control of the improved process, and the concentration calculated according to the cellulase concentration output formula of the invention is applied to the actual mass production, and the finished product can basically meet the customer requirements. And the dosage of the cellulase is lower than the dosage required by the prior production in a unified way, so that the cost is reduced, the bursting strength of the knitted fabric is ensured, and the requirement of reducing the production risk is met.

Description

Method for improving cotton knitted fabric hairiness by using cellulase

Technical Field

The invention relates to a method for improving cotton knitted fabric hairiness, in particular to a method for improving cotton knitted fabric hairiness by cellulase.

Background

Along with the development of economy, the requirements of people on the living standard of substances are gradually improved, clothing consumers pay attention to all indexes in ready-made clothes fabrics and also put forward higher requirements on appearance quality, and besides color uniformity, different customers also put forward various requirements on various aspects such as luster, grains, fabric surface smoothness, hand feeling and the like. Cotton or cotton blended (meaning a cloth woven from one or more different types of blended yarns) or blended fabrics can appear dull and have a surface with fine, soft nap after being used for a period of time. This phenomenon occurs mainly because the microfibrils are attached to the cotton fibers, and during weaving and a series of other actions, the microfibrils are temporarily pressed down, but when the fabric is used, the microfibrils stretch outward, which makes the fibers get a lot of dirt, oil stains and the like, so that the fabric no longer has a previously bright color, becomes dull and dull, and after a period of repeated abrasion, the surface of the clothes woven by the fibers gradually appears cotton heads and hair particles, and the appearance becomes non-smooth and old. These disadvantages occur with innumerable cotton-cotton blended or mixed fabrics. The factors influencing the hairiness are more in the actual production process, and the control on the hairiness is difficult.

The filoplume not only makes the surface of the knitted fabric look unsightly, but also affects other functions of the fabric. Such as fabric rails, are mainly characterized by open weft, closed course and tear, which are called defects in any knitted fabric. The defects are weft-wise residual defects of the cloth cover generated in the weaving process, are closely related to the hairiness index of weft yarns, and show obvious difference according to different indexes. Meanwhile, excessive hairiness can have adverse effects on the properties of the fabric, such as air permeability, pilling, water absorption and the like of the fabric. Meanwhile, the sensory experience of the user on the fabric can be influenced, such as uneven surface, hand feeling, friction performance and the like.

Cotton, which we will generally refer to as cotton for simplicity. It is an important raw material in the textile dyeing and finishing industry, and many companies mainly process cotton fabrics. The cotton fiber has good hygroscopicity, and can absorb moisture in the surrounding atmosphere under normal conditions; the cotton has good air permeability and has the characteristics of softness, warmth retention and the like, but the cotton also has the defects that: such as poor wrinkle resistance, poor water shrinkage, easy deformation, etc. Cotton is an annual plant, is generally used for pure cotton fabrics, and can also be blended with terylene. It is formed by the continuous development and growth of epidermal cells on cotton seeds. The growth cycle of cotton fibers can be roughly divided into three phases: namely the elongation phase, thickening phase and the turning phase as we know. Cotton plays an important role in the textile dyeing and finishing industry, and for many companies, 90% of cotton is produced, so the important role of cotton fiber is self-evident. China is a big cotton-producing country, and the cotton yield of China is listed as the top grass in China at the present stage. Cotton can be planted in most areas of China. The five major producing areas mainly comprise a yellow river basin and a Yangtze river basin, and are also arranged in the northwest inland, the Liaohe river basin and the south China cotton area which are relatively arranged at the back.

The cotton fiber is mainly composed of cellulose, the cellulose is a natural high molecular compound, the chemical structural formula of the cellulose is repeatedly composed of alpha glucose as a basic structural unit, and the elements of the cellulose are 44.44% of carbon, 6.17% of hydrogen and 49.39% of oxygen. The polymerization degree of the cotton fiber is 6000 to 11000. In addition, about 5% of other substances such as gray matter, wax and the like are attached to the cotton fiber, which are called as companion substances, and the companion substances have influence on the spinning process, scouring, bleaching, scouring, printing, dyeing and post-treatment processing.

The fat-containing wax is generated on the surface of cotton in the growing process, because the existence of the substance plays a certain role in lubricating and protecting the cotton fiber in the spinning process, the substance is one of the reasons that the cotton fiber has good spinning performance, but the cotton wax is easy to melt in a high-temperature environment. Therefore, the cotton cloth is easy to wind the roller and the rubber roller. The original cotton is degreased, the moisture absorption is increased, and the weight of the absorbent cotton can reach 23-24 times of the weight of the absorbent cotton after water absorption.

The yarn length of cotton fiber is related to various factors in the spinning process, and is generally greatly influenced by cotton varieties, growth environment, post-processing equipment and process and the like. The length of the cotton fiber is closely related to the spinning process and the quality of the yarn. Generally, the longer the yarn, the more regular the yarn, the less flock, the finer the spun yarn, the more uniform the yarn, the higher the strength, and the yarn surface is smooth and has less hairiness.

A plurality of fuzz can be seen on the surface of grey cloth before the printing and dyeing processing of the knitted fabric, because the fuzz of the warp and weft in the spinning process is exposed on the cloth surface, and meanwhile, the friction between the woven fabric and a weaving machine can pull the head end of part of fibers to the cloth surface to increase the fuzz. In actual mass production, the aim of improving hairiness can be achieved mainly through cellulose polishing enzyme treatment. The cellulose polishing enzyme and the natural cellulose fiber are reacted, enzyme molecules and the cellulose fiber are adsorbed and then subjected to coordination and complexation reaction to form an intermediate complex, hydrolysis of glycosidic bonds of cellulose molecular bonds is promoted, cellulose molecules are cut off, and proper mechanical friction or impact of water flow on a cloth cover is utilized, so that fuzz (or microfibril) on the surface of the fiber with low crystallinity and fiber ends are effectively removed, and the effects of smoothness of cloth hairiness, clear lines and improvement of softness and drapability of the cloth body are achieved.

Disclosure of Invention

The invention aims to provide a method for improving cotton knitted fabric hairiness by using cellulase, which can realize quantitative improvement of cotton fabric hairiness.

The technical scheme of the invention is as follows:

a method for improving the hairiness of cotton knitted fabric by cellulase adopts a polishing and dyeing one-bath process, and is characterized in that the concentration of the cellulase is determined according to the hairiness grade difference, the yarn count, the bath ratio, the processing temperature and the processing time, and the concentration of the cellulase is determined according to the following model: c_{Concentration of}-0.0237 × yarn count-0.05173 × bath ratio-0.03027 × temperature-0.62214 × time +0.626366 × hairiness grade difference + 3.106193.

Further, the hair-feather level difference is a difference between the target hair-feather level for improvement and the pre-improvement hair-feather level.

Further, the cellulase concentration model was obtained by a regression analysis method.

Further, the influencing factors, yarn count, bath ratio, processing temperature and processing time, were determined by analysis of experimental results (for the sake of simplicity of description, non-critical factors will not be described in detail).

Furthermore, the number of the yarns is preferably 20-50; the bath ratio is preferably 7-20; the processing temperature is preferably 50-60 ℃; the processing time is preferably 1.25-2.25 h.

According to the experiment and the analysis of the experimental result, the yarn count, the bath ratio, the processing temperature and the processing time are determined as key influence factors.

The cellulase activity test principle is as follows: the sodium carboxymethylcellulose, namely the CMC aqueous solution has certain viscosity, the cellulase can decompose the cellulose solution, and the viscosity is reduced when the concentration of the cellulose in the solution is reduced; and the lower the viscosity of the solution is reduced in the same time, the stronger the cellulase activity.

The effect of temperature on cellulase activity was as follows:

TABLE 1 Effect of temperature on cellulase Activity

From table 1 and fig. 1 it follows: the viscosity of the CMC solution is lower and lower along with the increase of the temperature, but the viscosity is gradually increased when the temperature exceeds 55 ℃, which shows that the activity of the cellulase is stronger and stronger along with the increase of the temperature, and the activity is reduced when the temperature exceeds 55 ℃, so the optimum temperature of the cellulase is about 55 ℃.

Under the conditions of 50 ℃ and 60 ℃, the improvement conditions of hairiness by different cellulase concentrations and different polishing times are as follows:

TABLE improvement rating of hairiness by different cellulase concentrations at 250 deg.C

From the data in table 2 and fig. 2 follows: under the condition of 50 ℃, the hairiness is improved obviously along with the extension of the processing time, and the hairiness is improved obviously along with the increase of the dosage of the cellulase under the same processing condition, and the improvement degree is not obvious when the dosage is large to a certain degree.

The hairiness improvement after different treatment times with different cellulase dosages at the same bath ratio and temperature of 60 ℃ is shown in table 3:

TABLE improvement rating of different cellulase concentrations at 360 ℃ on hairiness

From the data in table 3 and fig. 3, it follows: at 60 ℃, the improvement trend of the hairiness is basically the same as that at 50 ℃, but the same dosage and the same processing time are better than 50 ℃.

The effect of different bath ratios on hairiness is shown in table 4.

TABLE 4 influence of different bath ratios on hairiness

From table 4, it follows: as shown by the

serial numbers

1,2 and 4, when the concentration of the cellulase is not changed, the effect of the cellulase on the fiber is better along with the increase of the bath ratio; it is found from Nos. 1 and 3 that the polishing effect is deteriorated as the bath ratio is increased when the cellulase is used in an amount calculated on the basis of the weight of the fabric.

Reason analysis: the cellulase directly acts on the fiber, and under the condition of the same concentration, the larger the bath ratio, the more the enzyme in the dye bath relative to the fiber, the greater the chance of combining with the fiber, and the better the polishing effect; under the same o.w.f condition, the chance of enzyme binding to the fiber is reduced due to the increase of bath ratio, and the natural polishing effect is slightly poor.

The effect of different counts on hairiness is as follows:

TABLE 5 Effect of different counts on hairiness

From table 5 and fig. 4, it follows: under the action of the cellulase with the same concentration, the hairiness grade difference is larger and larger along with the increase of the yarn count, which shows that the polishing effect of the cellulase is more obvious along with the thinning of the yarn.

The tester for the fabric surface hairiness of the knitted fabric adopted in the experiment can measure the actual hairiness of the fabric surfaces of the knitted fabrics with different structures. Because the hairiness of the yarn is not uniform or the friction in the weaving process is inconsistent, the hairiness at different positions of the same cloth roll has little difference, in order to reduce the measurement error, 5 hairiness at different positions on the same sample are required to be tested, and finally the average value is taken, so that more accurate hairiness data is ensured. The principle is as follows: the method comprises the steps of storing images of the hairs of the edge of a cloth cover moving at a certain speed by using an image imaging principle and a camera, digitizing image information through system background data conversion, transmitting the data into a software system, simply processing comparison data by using a computer, comparing the comparison data with a preset standard value, and finally judging the grades of the hairs, wherein nine grades are totally divided into 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5 and 5.0.

The specific regression method is as follows:

TABLE 6 cellulase polishing finishing influencing factors

Overview of regression analysis

Regression analysis is the most common statistical method for dealing with the interrelations between variables, based on past observations of the interrelations of one variable with other variables, and predicting, with some degree of accuracy, the value of an unknown variable. It is used to find the statistics behind randomness. The regression analysis is mainly used for determining the correlation and the degree of correlation among variables for research, obtaining the degree of correlation by establishing a regression model, and simultaneously carrying out estimation, prediction and the like.

In the regression analysis discussion, it is generally assumed that the dependent variables follow a normal distribution. If there is only one influencing factor (independent variable), it is called a univariate regression or a single regression. The unary regression can be generally divided into two types, unary linear regression and unary non-linear regression, the unary linear regression is described by a straight line, and the unary non-linear regression is described by a curve. If there are two or more independent variables, called multiple regression or complex regression, it can also be classified into multiple linear regression and multiple nonlinear regression.

In practice a large number of laws exhibit a non-linear relationship. Such as common logarithmic models, exponential models, power exponential models, hyperbolic models, parabolic models, normal distribution models, etc., which can be converted into linear relationships, the regression fitting operation is performed by using the least square method.

Establishment of multiple linear regression model

If the change of things is influenced by various factors, and the influence factors and a large amount of data are more, the factors can not be judged to be main factors, the factors are secondary factors, and whether the factors interact with each other or not, in order to judge the influence factors more comprehensively and accurately, a multivariate linear regression model can be generally established or converted into a linear regression problem, so that the influence level of the variables on the corresponding variables can be judged and shown through a multivariate linear regression system, the primary and secondary positions of various influence factors are distinguished, and an effective method for solving the problem is searched.

Based on one dependent variable y influenced by n independent variables x₁，x₂，...，x₃Under the assumption that the n observation sets are affected by y_i，x_1i，x_2i，..x_ki1, 2.., n. The multiple linear regression equation is then expressed as:

in the formula beta₀，β₁，β₂，…β_kIn order to determine the parameters to be determined,_iis a random variable. If a, b₁，b₂，...b_kAre each beta₀，β₁，β₂，…β_kThe regression model is then:

wherein a is a constant term, b₁,b₂,...b_kIs the partial regression coefficient (partial regression coefficient) to be determined. The significance of the partial regression coefficient b (i ═ 1, 2.. k) is when the other independent variables x_j(j ≠ i) is a value in which the independent variable x changes by one unit and the dependent variable y changes by the average, when all of (j ≠ i) are fixed.

According to the principle of least square method, the sum of squares of the residual errors of multiple linear regression equations is minimized to obtain a and b_i(i＝1，2，...m)。

The sum of the squares of the residuals of the multiple linear regression equation can be expressed as

From the requirements for extrema

From this, the following normal equation set can be obtained

By solving the normal equation set, a and bi (i ═ 1, 2.. m) can be obtained.

If order

The normal system of equations may become

L₁₁b₁+L₁₂b₂+...+L_1mb_m＝L_1y

L₂₁b₁+L₂₂b₂+...+L_2mb_m＝L_2y

......

L_m1b₁+L_m2b₂+...+L_mmb_m＝L_my

Expressed in matrix form

Then L, B, F, B, L^-1F

If the matrix L is to be formed^-1The element is marked as c_ik(i, k ═ 1, 2.. m) then the regression coefficients:

multiple linear regression significance test:

variance test method:

the sum of squares of deviations:

sum of squares of total deviations:

regression sum of squares:

sum of squares of residuals:

mean sum of squares of deviation and degree of freedom

Sum of squares of total deviation S_TThe degree of freedom of (a) is f ═ n-1

Regression sum of squares S_RThe degree of freedom of (A) is: f is m

Sum of squares of residual errors S_eThe degree of freedom of (A) is: f is n-m-1

The relationship between the three degrees of freedom is: f. of_T＝f_R+f_e

The sum of the squares of the respective mean deviations is:

the significance test was performed by the F test method:

the degree of freedom following the F distribution is (m, n-m-1). At a given significance level α, F is looked up from the F distribution table_α(m, n-m-1) when F>F_0.01(m, n-m-1), the regression equation established is highly significant, so the table is looked up when F_0.01(m，n-m-1)≧F≧F_0.05(m, n-m-1), the established multiple nonlinear regression equation is significant when F_0.05(m，n-m-1)≧F≧F_0.1(m, n-m-1), the regression equation established is significant at a confidence level of 0.1, when F<F_0.1(m, n-m-1), the regression equation established is not significant.

TABLE 7 multiple linear regression analysis of variance table

From the data in Table 7, regression analysis was performed by using computer EXCEL, and the data are shown in Table 8:

TABLE 8 Linear regression data

The examination table shows: f_0.01(5, 56) ═ 3.119, since F > F_0.01(5, 56), the regression equation established is highly significant. The regression equation is then: c_{Concentration of}-0.0237 × count-0.05173 × bath ratio-0.03027 × temperature-0.62214 × time +0.626366 × difference in hairiness grade + 3.106193.

The invention has the beneficial effects that:

(1) the method can accurately adjust the process parameters according to the requirements of the cotton fabric hairiness level, realizes quantitative control of the improved process, and has strong operability, high accuracy and small error through experimental verification.

(2) The concentration calculated according to the cellulase concentration output formula of the invention is applied to actual large-scale production, and the finished product can basically meet the requirements of customers. Although some cloth types have errors due to the cloth type structure and the like, the cloth types can be controlled within an acceptable range. And the dosage of the cellulase is lower than the dosage required by the prior production in a unified way, so that the cost is reduced, the bursting strength of the knitted fabric is ensured, and the requirement of reducing the production risk is met.

Drawings

FIG. 1 is a graph showing the effect of temperature on cellulase activity.

FIG. 2 is a graph showing the effect of different polishing times on the level of improvement of hairiness at 50 ℃.

FIG. 3 is a graph showing the effect of different polishing times on the level of improvement of the hairiness at 60 ℃.

FIG. 4 is a graph showing the effect of different counts on hairiness.

FIG. 5 shows a hairiness tester for knitted fabric used in the present invention: 1. the system comprises a test platform, a lens 2, a lens 3, a lens cone 4, an emergency brake switch 5 and a test computer.

FIG. 6 is a standard drawing of the hairiness grade of the cloth surface of a knitted fabric.

FIG. 7 is a diagram of an interface for detecting the entry of a cloth cover hairiness instrument.

Fig. 8 is a schematic view of the placement of the cloth sample.

FIG. 9 is a diagram of a screen image display interface.

FIG. 10 is a computer operation interface diagram of the cloth cover hairiness instrument.

FIG. 11 is an initial interface diagram of a production data process for a textile contract.

FIG. 12 is a diagram of the initial interface of the production data process of the sample contract.

FIG. 13 is an input interface diagram of the textile boiled cloth feather.

FIG. 14 is a drawing of an input interface of the middle-sample boiled cloth feather.

FIG. 15 is a diagram of a large-scale production cellulase output interface.

Detailed Description

The present invention will be described in further detail with reference to specific examples, but the present invention is not limited thereto.

The hairiness tester shown in fig. 5 is adopted in the experiment to test the hairiness on the surface of the cloth, and the principle is as follows: the method comprises the steps of storing images of the hairs of the edge of a cloth cover moving at a certain speed by using an image imaging principle and a camera, digitizing image information through system background data conversion, transmitting the data into a software system, simply processing comparison data by using a computer, comparing the comparison data with a preset standard value, and finally judging the grades of the hairs, wherein nine grades are totally divided into 1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5 and 5.0.

Firstly, defining the hairiness larger than 2mm as long hair and smaller than 2mm as short hair, respectively analyzing and calculating the proportion of the external hairiness shadow area to the corresponding total area in the length range of 2mm by a hairiness tester for the sample plate evaluated as a hairiness standard sample plate, and recording the corresponding hairiness grade in the system.

Secondly, when a cloth sample to be tested is placed on a test platform, the machine drives the cloth sample to move, a group of proportion of the shadow area of the hair feather to the corresponding total area within the length range of 2mm can be obtained, the data of the proportion is transmitted to a computer system, the computer judges which interval of the standard sample plate the shadow area falls in through operation, and finally the hair feather grade of the cloth cover is directly given through a rounding calculation mode.

The standard sample of the knitted fabric cloth cover hairiness grade is shown in figure 6. The standard sample for the fabric surface hairiness grade of the knitted fabric is a standard sample for evaluating hairiness, which is provided by a past client and analyzes past production data, is evaluated by professional personnel who professionally evaluate the hairiness grade, and a finished product produced according to the standard sample is large in goods and obtains generally agreed hairiness quality, so the sample is set as the standard sample for evaluating the hairiness.

The sampling steps are as follows:

(1) plain cloth woven from the greige yarn to be produced and a pattern plate after boiling the cloth are prepared, and then the cloth plate is cut into a4 size pattern plate.

(2) The customer template was cut into a4 size template.

Measurement procedure

(1) Turning on the light source of the image lamp.

(2) And (3) turning on the feather detection software ImageView20170118, selecting a detection standard 'standard value 20161106', inputting an operator '01', logging in to a detection interface (as shown in FIG. 7), and adjusting the brightness of the light source of the image lamp to be yellowish.

(3) And folding the cloth sample to be tested in the radial direction, and lightly brushing or lightly grinding the folded surface by hands to make the surface hairiness of the fabric stand up.

(4) The folded cloth sample is placed under a transparent glass plate, a computer measurement interface is observed, and the position of the cloth sample is adjusted, so that the folding surface of the test cloth sample is parallel to the upper and lower boundaries of the measurement interface as much as possible (as shown in fig. 8).

(5) The distance between the light source and the test cloth sample, i.e. the size of Z, is adjusted to make the image of the cloth sample on the screen as clear as possible (as shown in fig. 9).

(6) Clicking the automatic test (as shown in figure 10), displaying the hairiness grade below the screen after the test is finished, recording the hairiness grade and recording the hairiness grade into a system (path: production center (weaving) data-inputting knitting process data-inputting cloth boiling data-modifying).

Matters of attention

(1) If the cloth sample displayed on the screen exceeds the boundary in the test process, the test is stopped, and the position of the cloth sample on the test interface is adjusted and then the test is carried out again.

(2) To ensure the accuracy of the test results, each layout should be tested at least 5 times, and the average value is taken as the test result.

Example 1

A method for improving the hairiness of cotton knitted fabric by cellulase adopts a polishing and dyeing one-bath process, and comprises the following specific processes: the number of branches is 30, the bath ratio is 7, the processing temperature is 50 ℃, the processing time is 1.25h, the hairiness grade difference is 1.2, and the concentration model C of the cellulase_{Concentration of}The cellulase concentration is 0.4g/L, calculated by-0.0237 times of yarn count-0.05173 times of bath ratio-0.03027 times of temperature-0.62214 times of time +0.626366 times of hairiness grade difference + 3.106193.

Example 2

A method for improving the hairiness of cotton knitted fabric by cellulase adopts a polishing and dyeing one-bath process, and comprises the following specific processes: count of 40, bath ratio of 7, processing temperature of 50 deg.C, processing time of 2.0h, hairiness grade difference of 2.7, and cellulase concentration model C_{Concentration of}The cellulase concentration is 0.8g/L, calculated by-0.0237 times of yarn count-0.05173 times of bath ratio-0.03027 times of temperature-0.62214 times of time +0.626366 times of hairiness grade difference + 3.106193.

Example 3

A method for improving the hairiness of cotton knitted fabric by cellulase adopts a polishing and dyeing one-bath process, and comprises the following specific processes: count of 40, bath ratio of 7, processing temperature of 50 deg.C, processing time of 2.0h, hairiness grade difference of 2.7, and cellulase concentration model C_{Concentration of}-0.0237 x yarn count-0.05173The concentration of the cellulase is 0.8g/L, and the calculation is carried out by multiplying the bath ratio by-0.03027, multiplying the temperature by-0.62214, multiplying the time by 0.626366, multiplying the hairiness grade difference by 3.106193.

To verify the accuracy of the model, the procedure used was as follows:

the established yarn boiling cloth feather database program is linked with the production system, and the use of the program is introduced as follows:

a. program initial interface (as shown in fig. 11 and 12):

the current process shows the data of cloth production data (as shown in FIG. 11) that the customer has made an order or developed independently and the data of cloth production data (as shown in FIG. 12) that the large goods are going to be produced:

boiling cloth according to standard cylinder type and standard formula, measuring hairiness of each cloth sample according to standard measuring gesture after boiling cloth, finding out corresponding contract and cloth or sample number in the system, clicking 'modification' button, inputting hairiness corresponding to the cloth of the boiled cloth into a production system (such as figures 13 and 14), and directly extracting data by a computer system when producing large goods.

b. Cellulase output interface in polishing finishing

The output of the cellulase needs to refer to the data such as the type of the produced knitted fabric, the dyeing process used, the difference of the feather level required before and after production and the like.

For example, taking 26S/1 fine cotton plain cloth as an example, firstly, the system will judge whether the list has a processing requirement for improving hairiness, if so, the system will search whether a middle sample is made according to the contract number of the order, and if so, the hair feather level of the cloth can be counted; if not, automatically jumping to a textile system to search the boiled cloth hairiness of the contract cloth; secondly, taking out the hairiness grade required by the client from the system; and finally, calculating the type and the dosage of the cellulase by a computer background system according to the type, the hairiness grade, the dyeing temperature and the polishing finishing time of the yarn and displaying the type and the dosage on a working single interface (as shown in figure 15):

model validation

In order to verify the accuracy of the cellulase concentration output model, an order to be polished is randomly extracted from a workshop, the hair feather after boiling and the hair feather of a sample coming from a client are evaluated, and the concentration is calculated by using a cellulase concentration output formula, as shown in table 9:

TABLE 9 cellulase concentration output validation

Note:

cloth 1: 20S/1 fine cotton plain cloth

Cloth 2: 26S/1 fine cotton plain cloth

Cloth 3: 30S/1 common cotton 1X1 rib fabric

Cloth 4: 30S/1 fine cotton and 20D spandex plain cloth

Cloth 5: 40S/1 fine cotton and 20D spandex plain cloth

Cloth 6: 40S/1 fine cotton double-sided cloth

Cloth 7: 16S/1 common cotton plain cloth

Cloth 8: 40S/1 fine cotton 1X1 rib fabric

Cloth 9: 32S/1 fine cotton and 70D spandex lampwick cloth

Cloth 10: 32S/1 fine cotton and 30D spandex plain cloth

From table 9 it can be derived: the concentration calculated according to the cellulase concentration output formula is applied to actual large-product production, and the finished product can basically meet the requirements of customers. Although some cloth types have errors due to the cloth type structure and the like, the cloth types are within the acceptance range. The model can be obtained from the above steps and used for outputting the concentration of the cellulase, the actual production requirement of large goods can be met, and the dosage of the cellulase is lower than the dosage required by the existing production in a unified way, so that the cost can be reduced, the bursting strength of knitted fabrics can be ensured, and the requirement for reducing the production risk can be met.

Claims

1. A method for improving the hairiness of cotton knitted fabric by cellulase adopts a polishing and dyeing one-bath process, and is characterized in that the concentration of the cellulase is determined according to the hairiness grade difference, the yarn count, the bath ratio, the processing temperature and the processing time, and the concentration of the cellulase is determined according to the following model: c_{Concentration of}-0.0237 times yarn count-0.05173 times bath ratio-0.03027 times temperature-0.62214 timesInterval +0.626366 × difference in hairiness level + 3.106193.

2. The method for improving the hairiness of a cotton knitted fabric using cellulase according to claim 1, wherein the hairiness level difference is a difference between a target hairiness level to be improved and a hairiness level before improvement.

3. The method for improving the hairiness of a cotton knitted fabric using cellulase according to claim 1, wherein the cellulase concentration model is obtained by a regression analysis method.

4. The method of improving plumes in cotton knitted fabrics with cellulase according to claim 1, wherein the influencing factors of yarn number, bath ratio, processing temperature and processing time are determined by analysis of experimental results.

5. The method for improving the hairiness of a cotton knitted fabric using cellulase according to claim 1, wherein the number of yarns is 20 to 50; the bath ratio is 7-20; the processing temperature is 50-60 ℃; the processing time is 1.25-2.25 h.