An intelligent management system for textile handicrafts

Abstract

The present invention discloses an intelligent management system for textile handicrafts, and relates to the technical field of intelligent management of textile handicrafts. The intelligent management system for textile handicrafts comprises: a data acquisition module, a defect detection module and a detection feedback module. The present invention obtains textile handicraft detection information by real-time collection and processing of initial textile handicraft detection information, then performs defect detection on a textile handicraft defect image according to the textile handicraft detection information to obtain a defect detection result, and establishes a database according to the textile handicraft defect test result, and finally performs a comprehensive evaluation according to the textile handicraft defect detection result and the textile handicraft detection information in the database to obtain a defect evaluation result, and generates a defect evaluation report, thereby improving the accuracy of textile handicraft defect detection and solving the problem of low accuracy of textile handicraft defect detection in the prior art.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent management of textile handicrafts, and in particular to an intelligent management system for textile handicrafts. Background Art

[0002] With the improvement of living standards, consumers' requirements for the quality of textile handicrafts are constantly increasing. The quality of textiles directly affects their market competitiveness and user satisfaction. Defect detection is an important part of quality control, which can help manufacturers to timely discover and correct defects in the production process and ensure product quality. An effective defect detection system can reduce production costs and improve production efficiency, thereby meeting the high quality requirements of modern textile production. The research and development and application of intelligent management systems for textile handicrafts have improved the production efficiency, product quality and market competitiveness of textile handicrafts, and promoted the high-quality development of the textile industry.

[0003] In the prior art, the defects of textile handicrafts are classified and annotated by collecting images of defects, and then clustering analysis is performed on the images to merge and extract the effective defect areas in the images. Finally, a defect recognition model is established and the new images are detected and identified to achieve the classification and detection of defects in textile handicrafts.

[0004] For example, the invention patent announcement with announcement number: CN109885011B discloses an Internet of Things management system for a textile printing and dyeing factory, including: a production detection module and a cause judgment module; the production detection module includes a silk thread statistics unit, a finished product statistics unit, a production comparison unit and a cause analysis unit; the silk thread statistics unit is used to count the silk threads purchased from different suppliers; the finished product statistics unit is used to count the finished fabrics produced by the silk threads purchased this time, and the output data of the actual fabric production counted by the finished product statistics unit is sent to the production comparison unit, and the cause analysis unit analyzes the difference between the actual output of the fabric production and the theoretical output of the fabric production, and analyzes whether the actual output of the fabric production is less than the theoretical output of the fabric production due to quality problems of the purchased silk threads.

[0005] For example, the textile workshop environment monitoring alarm system disclosed in the invention patent with the announcement number CN104375491B includes: a computer control device, a wireless communication device, a plurality of electrostatic detection devices, a plurality of ultrasonic humidifiers and a plurality of image monitors, each electrostatic detection device is paired with an ultrasonic humidifier and is set at a textile equipment position, each image monitor is set above a different corner position of the textile workshop, the wireless communication device is used for two-way wireless communication with a remote management control platform, the computer control device is connected to the plurality of electrostatic detection devices, the plurality of ultrasonic humidifiers, the plurality of image monitors and the wireless communication device respectively, the humidification operation of the corresponding ultrasonic humidifier is determined based on the detection result of each electrostatic detection device, and whether to alarm is determined based on the monitoring results of the plurality of image monitors. Through the present invention, it is possible to intelligently detect the real-time environmental parameters in the textile workshop and determine whether there is an intrusion by an outsider, and to locate and alarm in time.

[0006] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the present application found that the above technology has at least the following technical problems:

[0007] In the prior art, intelligent management of textile handicrafts involves detection of textile handicraft defects. When the temperature is too high, the yarn strength during detection may be reduced. When the humidity is too high, the yarn strength during detection may be reduced. There is a problem of low accuracy in detecting textile handicraft defects. Summary of the invention

[0008] The embodiments of the present application solve the problem of low accuracy in defect detection of textile handicrafts in the prior art by providing an intelligent management system for textile handicrafts, thereby improving the accuracy of defect detection of textile handicrafts.

[0009] The embodiment of the present application provides an intelligent management system for textile handicrafts, including: a data acquisition module, a defect detection module and a detection feedback module; the data acquisition module is used to preprocess the initial textile handicraft detection information collected in real time to obtain textile handicraft detection information; the defect detection module is used to perform defect detection on the textile handicraft defect image according to the textile handicraft detection information to obtain the textile handicraft defect detection result, and input the textile handicraft detection information into an established database; the detection feedback module is used to perform a comprehensive evaluation based on the textile handicraft defect detection results and the textile handicraft detection information in the database to obtain the defect evaluation result, and generate a defect evaluation report, wherein the defect evaluation result is used to quantitatively describe the severity of the textile handicraft defect.

[0010] Furthermore, the data acquisition module includes a data acquisition unit and a data processing unit; the data acquisition unit is used to collect initial textile handicraft detection information of textile handicrafts in real time, and the initial textile handicraft detection information includes defect image information and environmental information; the data processing unit is used to perform a first preprocessing on the initial textile handicraft detection information to obtain textile handicraft detection information, and obtain the textile handicraft detection information accordingly.

[0011] Furthermore, the defect detection includes fabric surface detection, printing and dyeing quality detection and yarn quality detection; the specific process of the fabric surface detection is: performing a second preprocessing on the defect image information collected by the image acquisition device at a preset time point within a preset time period to obtain the surface defect area of ​​the textile handicraft; recording the obtained surface defect area and the corresponding timestamp in the database to form a fabric surface defect information sequence.

[0012] Furthermore, the specific process of the printing and dyeing quality inspection is: performing a third preprocessing on the defect image information collected by the image acquisition device and the colorimeter at a preset time point within a preset time period to obtain the printing and dyeing defect information of the textile handicraft; recording the printing and dyeing defect information and the corresponding timestamp in the database to form a printing and dyeing quality defect information sequence.

[0013] Furthermore, the specific process of the yarn quality detection is: performing a fourth preprocessing on the initial yarn defect information collected by the micrometer and the tensile testing machine at a preset time point within a preset time period to obtain the yarn defect information of the textile handicraft; recording the yarn defect information and the corresponding timestamp in a database to form a yarn quality defect information sequence.

[0014] Furthermore, the defect evaluation result is obtained according to the surface defect coefficient, the printing and dyeing defect coefficient and the yarn defect coefficient; the specific steps for obtaining the surface defect coefficient are as follows: obtaining the first environmental interference factor for fabric surface detection, the first environmental interference factor including light intensity, temperature and humidity; measuring the defect image information of the textile handicraft defect in the surface simulation environment by an image acquisition device at the first preset time point within the preset time period, and performing the fifth preprocessing to obtain the surface defect information of the textile handicraft, recording the obtained surface defect information and the corresponding timestamp in the database to form a simulated environment surface defect information sequence, obtaining the surface environmental interference factor according to the preset defect area of ​​the textile handicraft and the simulated environment surface defect information sequence, and obtaining the surface defect coefficient accordingly, the surface environmental interference factor is used to digitize the influence of environmental factors on the defect situation of the textile handicraft in the fabric surface detection, the surface defect coefficient is used to comprehensively quantify the severity of the surface defects of the textile handicraft in the fabric surface detection, and the surface defect coefficient is calculated by the following formula:

[0015] ;

[0016] Where i is the number of the first preset time point in the preset time period, , n represents the total number of first preset time points in the preset time period, represents the defect area of ​​the textile handicraft at the first preset time point i within the preset time period, represents the defect area of ​​the preset textile crafts, J represents the surface environmental interference factor, and BM represents the surface defect coefficient;

[0017] The surface environmental interference factor is calculated by the following formula:

[0018] ;

[0019] In the formula, represents the defect area of ​​the textile handicraft at the i-th first preset time point in the first simulation environment, represents the surface defect area of ​​the textile handicraft at the i-th first preset time point in the second simulation environment, It represents the surface defect area of ​​the textile handicraft at the i-th first preset time point under the third simulation environment.

[0020] Furthermore, the specific steps for obtaining the printing and dyeing defect coefficient are as follows: obtaining a second environmental interference factor for printing and dyeing quality detection, wherein the second environmental interference factor includes light intensity, temperature and humidity; measuring the defect image information of the textile handicraft defect in the printing and dyeing simulation environment by a colorimeter and an image acquisition device at a second preset time point within a preset time period, and performing a sixth preprocessing to obtain the printing and dyeing defect information of the textile handicraft, and recording the obtained printing and dyeing defect information and the corresponding timestamp in a database to form a simulated environment printing and dyeing defect information sequence; obtaining the printing and dyeing environment interference factor according to the preset color difference of the textile handicraft, the preset pixel points of the textile handicraft and the simulated environment printing and dyeing defect information sequence, and obtaining the printing and dyeing defect coefficient accordingly, the printing and dyeing environment interference factor is used to digitize the influence of environmental factors on the defect situation of the textile handicraft in the printing and dyeing quality detection, and the printing and dyeing defect coefficient is used to comprehensively quantify the severity of the printing and dyeing defects of the textile handicraft in the printing and dyeing quality detection, and the printing and dyeing defect coefficient is calculated by the following formula:

[0021] ;

[0022] Where p is the number of the second preset time point in the preset time period, , m represents the total number of second preset time points within the preset time period, represents the color difference of the textile handicraft at the pth second preset time point within the preset time period, represents the pixel point of the textile craft at the pth second preset time point within the preset time period, Indicates the color difference of the preset textile crafts, represents the pixel point of the preset textile crafts, YR represents the printing and dyeing defect coefficient, and H represents the printing and dyeing environment interference factor;

[0023] The printing and dyeing environmental interference factor is calculated by the following formula:

[0024] ;

[0025] Where z represents the number of the simulation environment, , represents the fourth simulation environment, represents the fifth simulation environment, represents the sixth simulation environment, represents the color difference of the textile handicraft at the pth second preset time point under the zth simulation environment, Represents the pixel point of the textile handicraft at the pth second preset time point in the zth simulation environment.

[0026] Furthermore, the specific steps for obtaining the yarn defect coefficient are as follows: obtaining the third environmental interference factor in the yarn quality detection process, the third environmental interference factor including light intensity, temperature and humidity; measuring the initial yarn defect information of the textile handicraft defect in the yarn simulation environment by a micrometer and a tensile testing machine at a third preset time point within a preset time period, and performing a seventh preprocessing to obtain the yarn defect information of the textile handicraft, and recording the obtained yarn defect information and the corresponding timestamp in a database to form a simulated environment yarn defect information sequence; obtaining the yarn environmental interference factor according to the preset yarn strength of the textile handicraft, the preset yarn radius of the textile handicraft and the simulated environment yarn defect information sequence, and obtaining the yarn defect coefficient accordingly, the yarn environmental interference factor is used to quantify the influence of environmental factors on the defect situation of the textile handicraft in the yarn quality detection, and the yarn defect coefficient is used to comprehensively quantify the severity of the yarn defects of the textile handicraft in the yarn quality detection, and the yarn defect coefficient is calculated by the following formula:

[0027] ;

[0028] Wherein, t is the number of the third preset time point in the preset time period, , T represents the total number of third preset time points within the preset time period, Indicates the defective yarn strength of the textile handicraft at the tth third preset time point within the preset time period, Indicates the defective yarn radius of the textile handicraft at the tth third preset time point within the preset time period, Indicates the yarn strength of the preset textile craft, represents the yarn radius of the preset textile crafts, SX represents the yarn defect coefficient, and R represents the yarn environmental interference factor;

[0029] The yarn environmental interference factor is calculated by the following formula:

[0030] ;

[0031] Where z represents the number of the simulation environment, , represents the seventh simulation environment, represents the eighth simulation environment, represents the ninth simulation environment, represents the defective yarn strength of the textile craft product at the tth third preset time point under the zth simulation environment, It represents the defective yarn radius of the textile craft product at the tth third preset time point under the zth simulation environment.

[0032] Furthermore, the specific method of obtaining the defect evaluation result is as follows: obtaining the evaluation weight from the preset database, the evaluation weight including the fabric surface detection weight, the printing and dyeing quality detection weight and the yarn quality detection weight; obtaining the defect evaluation result according to the surface defect coefficient, the printing and dyeing defect coefficient, the yarn defect coefficient and the evaluation weight; the defect evaluation result is calculated by the following formula:

[0033] ;

[0034] In the formula, BM represents the surface defect coefficient, YR represents the printing and dyeing defect coefficient, and SX represents the yarn defect coefficient. represents the fabric surface detection weight, Indicates the weight of printing and dyeing quality inspection, represents the yarn quality detection weight, P represents the defect evaluation result, and e represents the natural constant.

[0035] Furthermore, the specific method of obtaining the defect assessment report is as follows: obtaining defect data of textile handicrafts from a database, wherein the defect data includes textile handicraft inspection information, defect detection results of textile handicrafts, and defect assessment results; generating a defect assessment report based on the defect data and defect assessment results, wherein the defect assessment report includes environmental information, defect detection results corresponding to each defect detection, and defect assessment results.

[0036] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0037] 1. By collecting and processing textile handicraft inspection information in real time, defect detection is performed on textile handicraft defect images according to the textile handicraft inspection information to obtain textile handicraft defect detection results, and then defect evaluation results are obtained by combining the textile handicraft inspection information, and finally a defect evaluation report is generated, thereby improving the accuracy of textile handicraft defect detection, thereby achieving an improvement in the accuracy of textile handicraft defect evaluation, and effectively solving the problem of low accuracy of textile handicraft defect detection in the prior art.

[0038] 2. The defect image information of textile handicraft defects in the surface simulated environment is measured by image acquisition equipment and preprocessed to obtain surface defect information. At the same time, the timestamp is recorded to obtain the simulated environment surface defect information sequence. Then, the surface environment interference factor is obtained according to the preset defect area of ​​the textile handicraft and the simulated environment surface defect information sequence. The surface defect coefficient is obtained based on this, thereby quantifying the severity of defects in the fabric surface test, thereby achieving improved accuracy of the surface defect coefficient.

[0039] 3. The defect image information of textile handicraft defects in the printing and dyeing simulation environment is measured by a colorimeter and an image acquisition device, and the printing and dyeing defect information is obtained by preprocessing. At the same time, the timestamp is recorded to obtain the simulated environment printing and dyeing defect information sequence, and then the printing and dyeing environment interference factor is obtained according to the preset textile handicraft color difference, the preset textile handicraft pixel points and the simulated environment printing and dyeing defect information sequence. The printing and dyeing defect coefficient is obtained based on this, thereby quantifying the severity of defects in printing and dyeing quality inspection, thereby achieving improved accuracy of the printing and dyeing defect coefficient. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 A schematic diagram of the structure of an intelligent management system for textile handicrafts provided in an embodiment of the present application;

[0041] Figure 2 A schematic diagram of the change of the yarn defect coefficient provided in the embodiment of the present application;

[0042] Figure 3 A structural schematic diagram of a data acquisition module in an intelligent management system for textile handicrafts provided in an embodiment of the present application. DETAILED DESCRIPTION

[0043] The embodiment of the present application solves the problem of low accuracy of defect detection of textile handicrafts in the prior art by providing an intelligent management system for textile handicrafts. The invention obtains textile handicraft detection information by collecting and processing initial textile handicraft detection information in real time, then performs defect detection on textile handicraft defect images according to the textile handicraft detection information to obtain defect detection results, establishes a database according to the defect detection results, and finally performs a comprehensive evaluation based on the textile handicraft defect detection results and the textile handicraft detection information in the database to obtain defect evaluation results, and generates a defect evaluation report, thereby improving the accuracy of textile handicraft defect detection.

[0044] The technical solution in the embodiment of the present application is to solve the problem of low accuracy of the above-mentioned textile handicraft defect detection, and the overall idea is as follows:

[0045] Through the obtained textile handicraft inspection information, defect detection is performed on the textile handicraft defect image to obtain the defect detection result. Finally, the defect evaluation result is obtained by combining the textile handicraft inspection information and a defect evaluation report is generated, thereby achieving the effect of improving the accuracy of textile handicraft defect detection.

[0046] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0047] like Figure 1 As shown, it is a structural schematic diagram of an intelligent management system for textile handicrafts provided in an embodiment of the present application. An intelligent management system for textile handicrafts provided in an embodiment of the present application includes: a data acquisition module, a defect detection module and a detection feedback module; the data acquisition module is used to preprocess the initial textile handicraft detection information collected in real time to obtain textile handicraft detection information, and the textile handicraft detection information includes defect image information and environmental information; the defect detection module is used to perform defect detection on the textile handicraft defect image according to the textile handicraft detection information to obtain the textile handicraft defect detection result, and input the textile handicraft detection information into an established database, and the database is established according to the textile handicraft defect test results; the detection feedback module is used to perform a comprehensive evaluation based on the textile handicraft defect detection results and the textile handicraft detection information in the database to obtain the defect evaluation result, and generate a defect evaluation report, the defect evaluation result is used to quantitatively describe the severity of the textile handicraft defect, and the defect evaluation report includes the environmental information corresponding to each textile handicraft defect image, the textile handicraft defect detection result and the defect evaluation result.

[0048] In this embodiment, the initial textile handicraft detection information represents the textile handicraft defect image and its environmental information; the textile handicraft defect image represents the image data of the flaws or defects existing on the textile handicraft; the environmental information refers to the environmental factors that affect the detection results during the detection process, such as lighting conditions, temperature, and humidity; the preprocessing includes denoising, image enhancement, and image correction; the defect detection includes fabric surface detection, printing and dyeing quality detection, and yarn quality detection; the fabric surface detection is used to identify and detect quality problems on the fabric surface; the printing and dyeing quality detection is used to detect problems in the printing and dyeing process; the yarn quality detection is used to evaluate the quality of the yarn, including the strength and thickness of the yarn; the accuracy of the textile handicraft defect detection is improved.

[0049] Furthermore, the data acquisition module includes a data acquisition unit and a data processing unit; the data acquisition unit is used to collect initial textile handicraft detection information of textile handicrafts in real time, the initial textile handicraft detection information includes defect image information and environmental information, the defect image information represents the information obtained by real-time acquisition of the fabric surface of the textile handicraft by an image acquisition device, the environmental information represents the parameters obtained by real-time monitoring and recording of the detection environment by a sensor, the image acquisition device includes a camera and a scanner, and the parameters include temperature, humidity and light intensity; the data processing unit is used to perform a first preprocessing on the initial textile handicraft detection information to obtain the textile handicraft detection information, the first preprocessing represents denoising, image enhancement and image correction on the initial textile handicraft detection information, and the textile handicraft detection information is obtained accordingly, the denoising represents smoothing the data and removing burst noise by using digital signal processing technology; the digital signal processing technology includes median filtering and Gaussian filtering; image enhancement represents enhancing the defect image information obtained by the image acquisition device, including contrast adjustment, brightness adjustment, etc.; image correction represents transforming the defect image information by using geometric correction, and the geometric correction includes perspective correction and image registration.

[0050] In this embodiment, the camera is used to capture real-time images of the textile surface; the scanner is used to scan the textile surface to obtain a high-resolution image, the sensors include a temperature sensor, a humidity sensor and a light intensity sensor, the first preprocessing represents the processing steps of the initial textile handicraft detection information, including denoising, image enhancement and image correction; denoising means that during the image acquisition and processing, due to the influence of the equipment and the external environment, some unnecessary noise will be generated in the image, and the noise is removed by filtering; image enhancement means that the image is enhanced by adjusting the contrast and brightness; image correction means that due to the influence of the viewing angle, lens distortion and shooting conditions of the image acquisition device, geometric or optical distortion appears in the image, and the accuracy of acquiring image information and environmental information is improved by correcting and modifying the distortion.

[0051] Furthermore, defect detection includes fabric surface detection, printing and dyeing quality detection and yarn quality detection; the specific process of fabric surface detection is: at a preset time point within a preset time period, the defect image information collected by the image acquisition device is subjected to a second preprocessing to obtain the surface defect area of ​​the textile handicraft, and the second preprocessing includes color correction, noise removal and contrast enhancement of the defect image information; the obtained surface defect area and the corresponding timestamp are recorded in a database to form a fabric surface defect information sequence, and the fabric surface defect information sequence represents the result of arranging the surface defect information detected each time in chronological order; fabric surface detection is used to identify and detect the quality of the fabric surface.

[0052] In this embodiment, the preset time period represents a specific time range set in the test environment; the preset time point represents the time interval set in the test environment; the second preprocessing represents the preprocessing of the defect image information in the fabric surface detection; the color correction represents converting the color image into a grayscale image, adjusting the grayscale distribution of the image, and color correcting the image according to a predetermined standard or reference image; the noise removal represents applying a Gaussian filter to smooth the image, remove high-frequency noise components, sort each pixel neighborhood, and replace the pixel value with the median; the contrast enhancement represents adjusting the grayscale of the image, combining with the local histogram equalization, maintaining the image details while enhancing the contrast; the surface defect area represents the area of ​​the fabric surface defect in the defect image information collected in real time; the timestamp represents recording the defect information detected each time and the corresponding collection time in the database to form a time series; the accurate detection and real-time monitoring of the surface quality of textile handicraft fabrics are realized.

[0053] Furthermore, the specific process of printing and dyeing quality inspection is: at a preset time point within a preset time period, the defect image information collected by the image acquisition device and the colorimeter is subjected to a third preprocessing to obtain the printing and dyeing defect information of the textile handicraft, the third preprocessing means color correction, noise removal and contrast enhancement of the defect image information, the printing and dyeing defect information includes color difference and pixel points; the printing and dyeing defect information and the corresponding timestamp are recorded in a database to form a printing and dyeing quality defect information sequence, the printing and dyeing quality defect information sequence means the result of arranging the printing and dyeing defect information detected each time in chronological order; the printing and dyeing quality inspection is used to detect printing and dyeing problems of textile handicrafts.

[0054] In this embodiment, the colorimeter is an instrument for measuring the color difference of textile handicrafts; before measurement, the colorimeter and the image acquisition device need to be calibrated, and the defect image of the textile handicraft is placed in the corresponding test area, and the measurement program is started according to the operating instructions of the colorimeter and the image acquisition device, and the instrument will automatically detect the defect image information of the textile handicraft; the third preprocessing represents the preprocessing of the defect image information in the printing and dyeing quality inspection; color correction represents converting the color image into a grayscale image, adjusting the grayscale distribution of the image, and color correcting the image according to a predetermined standard or reference image; noise removal represents applying a Gaussian filter to smooth the image, remove high-frequency noise components, sort each pixel neighborhood, and replace the pixel value with the median; contrast enhancement represents adjusting the grayscale of the image, combining with local histogram equalization, maintaining the image details while enhancing the contrast; printing and dyeing defect information includes color difference and pixel points; color difference represents the difference between the actual collected printing and dyeing color of the textile handicraft and the standard color; pixel points represent the image pixel points actually collected by the textile handicraft; accurate detection and real-time monitoring of the printing and dyeing quality of the textile handicraft are achieved.

[0055] Furthermore, the specific process of yarn quality detection is as follows: performing a fourth preprocessing on the initial yarn defect information collected by the micrometer and the tensile testing machine at a preset time point within a preset time period to obtain the yarn defect information of the textile handicraft, the fourth preprocessing including data correction, data cleaning and outlier processing of the initial yarn defect information, the yarn defect information including the defective yarn strength and the defective yarn radius; recording the yarn defect information and the corresponding timestamp in a database to form a yarn quality defect information sequence, the yarn quality defect information sequence indicates that the yarn defect information detected each time is arranged in chronological order; yarn quality detection is used to detect yarn quality problems.

[0056] In this embodiment, the micrometer is a precision instrument for measuring the radius of defective yarn; the tensile testing machine is an instrument for testing the strength of defective yarn; the fourth preprocessing represents the preprocessing step of the initial yarn defect information in the yarn quality detection, including data correction, data cleaning and outlier processing; data correction represents the correction of systematic errors caused by sensor errors or measurement deviations, using standard length yarn for measurement, recording the sensor readings, and then mapping the sensor output values ​​to the true value range; data cleaning represents the removal of irrelevant or invalid data in the data set, including missing values, duplicate values ​​and invalid values; wherein the missing value represents the expected value in the initial yarn defect information. There is no data at the location where there is data; invalid values ​​indicate data that obviously deviates from the overall trend of the initial yarn defect information. Generally, if a value exceeds the set reasonable threshold range, it is considered to be an invalid value; repeated values ​​indicate data records that appear repeatedly in the initial yarn defect information; outlier processing indicates identifying and processing outliers in the data; outliers indicate data that obviously deviates from the overall trend of the initial yarn defect information. Generally, if a value exceeds the mean value plus or minus 2 times the standard deviation, it is considered to be an outlier; yarn defect information includes defective yarn strength and defective yarn radius; accurate detection and real-time monitoring of yarn quality of textile handicrafts are realized.

[0057] Furthermore, the defect evaluation result is obtained according to the surface defect coefficient, the printing and dyeing defect coefficient and the yarn defect coefficient; the specific steps for obtaining the surface defect coefficient are as follows: obtaining the first environmental interference factor for fabric surface detection, the first environmental interference factor including light intensity, temperature and humidity; measuring the defect image information of the textile handicraft defect in the surface simulation environment by an image acquisition device at a first preset time point within a preset time period, and performing a fifth preprocessing to obtain the surface defect information of the textile handicraft, recording the obtained surface defect information and the corresponding timestamp in a database to form a simulated environment surface defect information sequence, the surface simulation environment is set according to the first environmental interference factor, the surface simulation environment includes a first simulation environment, a second simulation environment and a third simulation environment, and the simulated environment surface defect information sequence represents the fabric surface of the textile handicraft corresponding to the first simulation environment, the second simulation environment and the third simulation environment. The surface defect information sequence, the first simulation environment is used to simulate the defect conditions of textile handicrafts within different light intensity ranges under preset temperature and preset humidity, the second simulation environment is used to simulate the defect conditions of textile handicrafts within different humidity ranges under preset temperature and preset light intensity, and the third simulation environment is used to simulate the defect conditions of textile handicrafts within different temperature ranges under preset humidity and preset light intensity; the surface environment interference factor is obtained according to the defect area of ​​the preset textile handicraft and the surface defect information sequence of the simulation environment, and the surface defect coefficient is obtained by combining the defect area of ​​the preset textile handicraft and the surface quality defect information sequence. The surface environment interference factor is used to quantify the influence of environmental factors on the defect conditions of textile handicrafts in fabric surface detection, and the surface defect coefficient is used to comprehensively quantify the severity of surface defects of textile handicrafts in fabric surface detection. The surface defect coefficient is calculated by the following formula:

[0058] ;

[0059] Where i is the number of the first preset time point in the preset time period, , n represents the total number of first preset time points in the preset time period, represents the defect area of ​​the textile handicraft at the first preset time point i within the preset time period, represents the defect area of ​​the preset textile crafts, J represents the surface environmental interference factor, and BM represents the surface defect coefficient;

[0060] The surface environmental interference factor is calculated by the following formula:

[0061] ;

[0062] In the formula, represents the defect area of ​​the textile handicraft at the i-th first preset time point in the first simulation environment, represents the surface defect area of ​​the textile handicraft at the i-th first preset time point in the second simulation environment, It represents the surface defect area of ​​the textile handicraft at the i-th first preset time point under the third simulation environment.

[0063] In this embodiment, the preset temperature and preset humidity represent specific temperature and humidity set in the test environment, which are used to simulate the temperature and humidity conditions of textile handicrafts in actual use; the preset temperature and preset humidity are obtained from a preset database, and generally the preset temperature is 25°C and the preset humidity is 50%; the preset light intensity represents a specific light intensity set in the test environment, which is used to simulate the light intensity under sunlight conditions; the preset time represents a specific time period set in the test environment; the preset light intensity and preset time are obtained from a preset database, and are usually set according to the ISO 105-B02 standard.

[0064] The surface defect coefficient is an indicator used to quantify the severity of surface defects in textile handicrafts during fabric surface inspection, including the impact of environmental interference factors on defect detection; when the surface environmental interference factor increases, the surface defect coefficient decreases, and when the defect area at the first preset time point within the preset time period increases, the surface defect coefficient increases.

[0065] The algorithm of this embodiment combines the "surface environmental interference factor" and the "defect area of ​​textile handicrafts" to obtain the "surface defect coefficient" through comprehensive analysis, and the various parameters are related to each other and do not exist independently. They are a whole, and the "surface defect coefficient" cannot be obtained by simple combination and addition. For example, in this formula, the "defect area of ​​textile handicrafts at the first preset time point within the preset time period" is conducive to increasing the "surface defect coefficient", which does not necessarily mean that the "surface defect coefficient" is large. At this time, the "surface environmental interference factor" also needs to be considered. The "surface environmental interference factor" can also determine the severity of the surface defects at the next moment. The correlation and mutual influence between various factors are considered in a quantitative way. The algorithm itself is obtained through comprehensive analysis, which can accurately and quantitatively analyze the severity of surface defects, indicating the effect of accurately evaluating the surface defect coefficient. Therefore, accurate analysis is performed by establishing a mathematical form.

[0066] The surface environmental interference factor is used to quantify the impact of environmental interference factors on the defects of textile crafts in fabric surface detection; the defect area of ​​the textile crafts is preset. Taking 10 (square millimeters) and n as 3 as an example, the statistical table of changes in surface environmental interference factors is shown in Table 1:

[0067] Table 1 Statistics of changes in surface environmental interference factors

[0068] The first preset time point number i Defect area of ​​the first simulation environment (mm2) Defect area of ​​the second simulation environment (mm2) Defect area of ​​the third simulation environment (square millimeters) Surface environmental interference factor J 1 [19.345，10.672，13.48] [17.545，15.469，14.989] [19.783，15.244，13.034] 0.728 2 [13.785，17.408，19.836] [16.366，18.893，13.308] [16.41，13.868，10.881] 0.766 3 [13.631，16.656，17.241] [13.584，17.086，18.593] [10.761，14.979，13.645] 0.691 4 [15.928，13.926，18.522] [19.149，12.411，18.522] [15.885，14.666，11.572] 0.749 5 [17.53，11.093，17.876] [15.536，13.579，18.067] [10.329，16.595，14.294] 0.647 ... ... ... ... ...

[0069] From Table 1, it can be seen that the larger the defect area of ​​the first simulation environment, the defect area of ​​the second simulation environment, and the defect area of ​​the third simulation environment, the greater the surface environmental interference factor; the specific situation is compared based on the calculation results of the corresponding data, and the corresponding operating coefficient relationship cannot be estimated based solely on the size of a single independent variable.

[0070] The algorithm of this embodiment combines "the surface defect area of ​​the textile handicraft at the first preset time point under the first simulation environment", "the surface defect area of ​​the textile handicraft at the first preset time point under the second simulation environment" and "the surface defect area of ​​the textile handicraft at the first preset time point under the third simulation environment" to obtain the "surface environment interference factor" through comprehensive analysis. In addition, each parameter is related to each other and does not exist independently. It is a whole and cannot be obtained by simply combining and adding. For example, in this formula, "the surface defect area of ​​the textile handicraft at the first preset time point under the first simulation environment" is conducive to increasing the "surface environment interference factor" and does not necessarily mean that The "surface environmental interference factor" is large. At this time, it is also necessary to consider the "surface defect area of ​​the textile handicraft at the first preset time point under the second simulation environment" and the "surface defect area of ​​the textile handicraft at the first preset time point under the third simulation environment". It can also determine the degree of environmental interference in the fabric surface test at the next moment. The correlation and mutual influence between various factors are considered in a quantitative way. The algorithm itself is obtained through comprehensive analysis, which can accurately and quantitatively analyze the degree of environmental interference in the fabric surface test, and shows the effect of numerical environmental interference factors on the defect situation of textile handicrafts in fabric surface detection. Therefore, accurate analysis is carried out by establishing mathematical forms.

[0071] Furthermore, the specific steps for obtaining the printing and dyeing defect coefficient are as follows: obtain the second environmental interference factor for printing and dyeing quality detection, the second environmental interference factor includes light intensity, temperature and humidity; at a second preset time point within a preset time period, measure the defect image information of the textile handicraft defects in the printing and dyeing simulation environment by using a colorimeter and an image acquisition device, and perform a sixth preprocessing to obtain the printing and dyeing defect information of the textile handicraft, and record the obtained printing and dyeing defect information and the corresponding timestamp in the database to form a simulated environment printing and dyeing defect information sequence, the printing and dyeing simulation environment is set according to the second environmental interference factor, the printing and dyeing simulation environment includes a fourth simulation environment, a fifth simulation environment and a sixth simulation environment, the simulated environment printing and dyeing defect information sequence represents the printing and dyeing quality defect information sequence of the textile handicraft corresponding to the fourth simulation environment, the fifth simulation environment and the sixth simulation environment, the fourth simulation environment is used to simulate the preset temperature, The defects of textile handicrafts within different light intensity ranges under preset humidity, the fifth simulation environment is used to simulate the defects of textile handicrafts within different humidity ranges under preset temperature and preset light intensity, and the sixth simulation environment is used to simulate the defects of textile handicrafts within different temperature ranges under preset humidity and preset light intensity; the printing and dyeing environment interference factor is obtained according to the color difference of the preset textile handicraft, the pixel points of the preset textile handicraft and the printing and dyeing defect information sequence of the simulated environment, and the printing and dyeing defect coefficient is obtained by combining the color difference of the preset textile handicraft, the pixel points of the preset textile handicraft and the printing and dyeing quality defect information sequence. The printing and dyeing environment interference factor is used to quantify the influence of environmental factors on the defects of textile handicrafts in printing and dyeing quality inspection, and the printing and dyeing defect coefficient is used to comprehensively quantify the severity of printing and dyeing defects of textile handicrafts in printing and dyeing quality inspection. The printing and dyeing defect coefficient is calculated by the following formula:

[0072] ;

[0073] Where p is the number of the second preset time point in the preset time period, , m represents the total number of second preset time points within the preset time period, represents the color difference of the textile handicraft at the pth second preset time point within the preset time period, represents the pixel point of the textile craft at the pth second preset time point within the preset time period, Indicates the color difference of the preset textile crafts, represents the pixel point of the preset textile crafts, YR represents the printing and dyeing defect coefficient, and H represents the printing and dyeing environment interference factor;

[0074] The printing and dyeing environmental interference factor is calculated by the following formula:

[0075] ;

[0076] Where z represents the number of the simulation environment, , represents the fourth simulation environment, represents the fifth simulation environment, represents the sixth simulation environment, represents the color difference of the textile handicraft at the pth second preset time point under the zth simulation environment, Represents the pixel point of the textile handicraft at the pth second preset time point in the zth simulation environment.

[0077] In this embodiment, the preset temperature and preset humidity represent specific temperature and humidity set in the test environment, which are used to simulate the temperature and humidity conditions of textile handicrafts in actual use; the preset temperature and preset humidity are obtained from a preset database, and generally the preset temperature is 25°C and the preset humidity is 50%; the preset light intensity represents a specific light intensity set in the test environment, which is used to simulate the light intensity under sunlight conditions; the preset time represents a specific time period set in the test environment; the preset light intensity and preset time are obtained from a preset database, and are usually set according to the ISO 105-B02 standard.

[0078] The printing and dyeing defect coefficient represents an indicator used to quantify the severity of defects in textile handicrafts in printing and dyeing quality inspection, including the impact of environmental interference factors on defect detection; when the printing and dyeing environmental interference factor increases, the printing and dyeing defect coefficient decreases; when the color difference of the textile handicraft at the second preset time point within the preset time period increases, the printing and dyeing defect coefficient increases; when the pixel point of the textile handicraft at the second preset time point within the preset time period increases, the printing and dyeing defect coefficient decreases.

[0079] The algorithm of this embodiment combines the "printing and dyeing environment interference factor", "the pixel points of the textile handicraft at the second preset time point within the preset time period" and "the color difference of the textile handicraft at the second preset time point within the preset time period", and comprehensively analyzes to obtain the "printing and dyeing defect coefficient". In addition, the various parameters are related and do not exist independently. They are a whole, and the "printing and dyeing defect coefficient" cannot be obtained by simple combination and addition. For example, in this formula, "the color difference of the textile handicraft at the second preset time point within the preset time period" is conducive to increasing the "printing and dyeing defect coefficient", which does not necessarily mean that the "printing and dyeing defect coefficient" is large. At this time, the "printing and dyeing environment interference factor" needs to be considered. In addition, the "pixel points of the textile handicraft at the second preset time point within the preset time period" can also determine the severity of the printing and dyeing defects at the next moment. The correlation and mutual influence between various factors are considered in a quantitative way. The algorithm itself is obtained by comprehensive analysis, which can accurately and quantitatively analyze the severity of printing and dyeing defects, indicating the effect of accurately evaluating the printing and dyeing defect coefficient. Therefore, accurate analysis is performed by establishing a mathematical form.

[0080] The printing and dyeing environment interference factor is used to quantify the impact of environmental interference factors on the defects of textile handicrafts in printing and dyeing quality inspection; when the color difference of the textile handicraft at the second preset time point under the simulated environment increases, the printing and dyeing environment interference factor increases; when the pixel point of the textile handicraft at the second preset time point under the simulated environment increases, the printing and dyeing environment interference factor decreases.

[0081] The algorithm of this embodiment combines "the color difference of the textile handicraft at the second preset time point under the fourth simulation environment", "the color difference of the textile handicraft at the second preset time point under the fifth simulation environment", "the color difference of the textile handicraft at the second preset time point under the sixth simulation environment", "the pixel points of the textile handicraft at the second preset time point under the fourth simulation environment", "the pixel points of the textile handicraft at the second preset time point under the fifth simulation environment" and "the pixel points of the textile handicraft at the second preset time point under the sixth simulation environment" to obtain the "printing and dyeing environment interference factor" through comprehensive analysis. In addition, the various parameters are related to each other and do not exist independently. They are a whole and cannot be obtained by simple combination and addition. For example, in this formula, "the color difference of the textile handicraft at the second preset time point under the fourth simulation environment" is conducive to increasing the "printing and dyeing environment interference factor" and does not necessarily represent the "printing and dyeing environment interference factor". The "environmental interference factor" is large. At this time, it is also necessary to consider "the color difference of the textile handicraft at the second preset time point under the fifth simulation environment", "the color difference of the textile handicraft at the second preset time point under the sixth simulation environment", "the pixel points of the textile handicraft at the second preset time point under the fourth simulation environment", "the pixel points of the textile handicraft at the second preset time point under the fifth simulation environment" and "the pixel points of the textile handicraft at the second preset time point under the sixth simulation environment". It can also determine the degree of environmental interference in the printing and dyeing quality test at the next moment. The correlation and mutual influence between various factors are considered in a quantitative way. The algorithm itself is obtained by comprehensive analysis, which can accurately quantify the degree of environmental interference in the printing and dyeing quality test, and shows the effect of the numerical environmental interference factors on the defects of textile handicrafts in printing and dyeing quality detection. Therefore, accurate analysis is carried out by establishing mathematical forms.

[0082] Furthermore, the specific steps for obtaining the yarn defect coefficient are as follows: obtaining the third environmental interference factor in the yarn quality detection process, the third environmental interference factor including light intensity, temperature and humidity; measuring the initial yarn defect information of the textile handicraft defects in the yarn simulation environment by a micrometer and a tensile testing machine at a third preset time point within a preset time period, and performing a seventh pretreatment to obtain the yarn defect information of the textile handicraft, and recording the obtained yarn defect information and the corresponding timestamp in a database to form a simulated environment yarn defect information sequence, the yarn simulation environment is set according to the third environmental interference factor, the yarn simulation environment includes a seventh simulation environment, an eighth simulation environment and a ninth simulation environment, the simulated environment yarn defect information sequence represents the printing and dyeing quality defect information sequence of the textile handicraft corresponding to the seventh simulation environment, the eighth simulation environment and the ninth simulation environment, and the seventh simulation environment is used to simulate the preset temperature, The defect conditions of textile handicrafts within different light intensity ranges under preset humidity, the eighth simulation environment is used to simulate the defect conditions of textile handicrafts within different humidity ranges under preset temperature and preset light intensity, and the ninth simulation environment is used to simulate the defect conditions of textile handicrafts within different temperature ranges under preset humidity and preset light intensity; the yarn environmental interference factor is obtained according to the yarn strength of the preset textile handicraft, the yarn radius of the preset textile handicraft and the yarn defect information sequence of the simulated environment, and the yarn defect coefficient is obtained by combining the yarn strength of the preset textile handicraft, the yarn radius of the preset textile handicraft and the yarn quality defect information sequence. The yarn environmental interference factor is used to quantify the influence of environmental factors on the defect conditions of textile handicrafts in yarn quality detection, and the yarn defect coefficient is used to comprehensively quantify the severity of yarn defects of textile handicrafts in woven yarn quality detection. The yarn defect coefficient is calculated by the following formula:

[0083] ;

[0084] Wherein, t is the number of the third preset time point in the preset time period, , T represents the total number of third preset time points within the preset time period, Indicates the defective yarn strength of the textile handicraft at the tth third preset time point within the preset time period, Indicates the defective yarn radius of the textile handicraft at the tth third preset time point within the preset time period, Indicates the yarn strength of the preset textile craft, represents the yarn radius of the preset textile crafts, SX represents the yarn defect coefficient, and R represents the yarn environmental interference factor;

[0085] The yarn environmental interference factor is calculated by the following formula:

[0086] ;

[0087] Where z represents the number of the simulation environment, , represents the seventh simulation environment, represents the eighth simulation environment, represents the ninth simulation environment, represents the defective yarn strength of the textile craft product at the tth third preset time point under the zth simulation environment, It represents the defective yarn radius of the textile craft product at the tth third preset time point under the zth simulation environment.

[0088] In this embodiment, the preset temperature and preset humidity represent specific temperature and humidity set in the test environment, which are used to simulate the temperature and humidity conditions of textile handicrafts in actual use; the preset temperature and preset humidity are obtained from a preset database, and generally the preset temperature is 25°C and the preset humidity is 50%; the preset light intensity represents a specific light intensity set in the test environment, which is used to simulate the light intensity under sunlight conditions; the preset time represents a specific time period set in the test environment; the preset light intensity and preset time are obtained from a preset database, and are usually set according to the ISO 105-B02 standard.

[0089] like Figure 2 As shown, it is a schematic diagram of the change of the yarn defect coefficient provided in an embodiment of the present application, that is, the yarn defect coefficient is inversely proportional to the printing and dyeing environmental factor, and the yarn defect coefficient is proportional to the defective yarn strength and the defective yarn radius; it can be seen from the figure that the yarn defect coefficient represents the severity of defects in the quantitative textile handicraft during the yarn quality detection process, including the influence of environmental interference factors on defect detection; when the yarn environmental interference factor increases, the yarn defect coefficient decreases, when the defective yarn strength of the textile handicraft at the third preset time point within the preset time period increases, the yarn defect coefficient increases, and when the defective yarn radius of the textile handicraft at the third preset time point within the preset time period increases, the yarn defect coefficient increases.

[0090] The algorithm of this embodiment combines "the color difference of the textile handicraft at the second preset time point under the fourth simulation environment", "the color difference of the textile handicraft at the second preset time point under the fifth simulation environment", "the color difference of the textile handicraft at the second preset time point under the sixth simulation environment", "the pixel points of the textile handicraft at the second preset time point under the fourth simulation environment", "the pixel points of the textile handicraft at the second preset time point under the fifth simulation environment" and "the pixel points of the textile handicraft at the second preset time point under the sixth simulation environment" to obtain the "printing and dyeing environment interference factor" through comprehensive analysis. In addition, the various parameters are related and do not exist independently. They are a whole. The "surface environment interference factor" cannot be obtained by simple combination and addition. For example, in this formula, "the color difference of the textile handicraft at the second preset time point under the fourth simulation environment" "Difference" is conducive to increasing the "printing and dyeing environment interference factor", which does not necessarily mean that the "printing and dyeing environment interference factor" is large. At this time, it is also necessary to consider "the color difference of the textile handicraft at the second preset time point under the fifth simulation environment", "the color difference of the textile handicraft at the second preset time point under the sixth simulation environment", "the pixel points of the textile handicraft at the second preset time point under the fourth simulation environment", "the pixel points of the textile handicraft at the second preset time point under the fifth simulation environment" and "the pixel points of the textile handicraft at the second preset time point under the sixth simulation environment". It can also determine the degree of environmental interference in the printing and dyeing quality test at the next moment. It takes into account the correlation and mutual influence of various factors in a quantitative way, and obtains its own algorithm through comprehensive analysis, which can accurately and quantitatively analyze the degree of environmental interference in the printing and dyeing quality test.

[0091] The algorithm of this embodiment combines the "yarn environment interference factor", "the defective yarn strength of the textile handicraft at the third preset time point within the preset time period" and "the defective yarn radius of the textile handicraft at the third preset time point within the preset time period", and comprehensively analyzes to obtain the "yarn defect coefficient", and the various parameters are related and do not exist independently. They are a whole, and the "yarn defect coefficient" cannot be obtained by simple combination and addition. For example, in this formula, the "defective yarn strength of the textile handicraft at the third preset time point within the preset time period" is conducive to increasing the "yarn defect coefficient", which does not necessarily mean that the "yarn defect coefficient" is large. At this time, the "yarn environment interference factor" needs to be considered. In addition, the "defective yarn radius of the textile handicraft at the third preset time point within the preset time period" can also determine the severity of the yarn defects at the next moment. The correlation and mutual influence between various factors are considered in a quantitative way. The algorithm itself is obtained by comprehensive analysis, which can accurately and quantitatively analyze the severity of the yarn defects, indicating the effect of accurately evaluating the yarn defect coefficient. Therefore, accurate analysis is performed by establishing a mathematical form.

[0092] The yarn environmental interference factor is used to quantify the influence of environmental interference factors on the defects of textile handicrafts in yarn quality detection; when the defective yarn strength of the textile handicraft at the third preset time point under the simulated environment increases, the yarn environmental interference factor increases; when the defective yarn radius of the textile handicraft at the third preset time point under the simulated environment increases, the yarn environmental interference factor increases. In general, the yarn environmental interference factor is proportional to the defective yarn strength and the defective yarn radius.

[0093] The algorithm of this embodiment combines "the defective yarn strength of the textile handicraft at the third preset time point under the seventh simulation environment", "the textile handicraft at the third preset time point under the eighth simulation environment, please determine first", "the defective yarn strength of the textile handicraft at the third preset time point under the ninth simulation environment", "the defective yarn radius of the textile handicraft at the third preset time point under the seventh simulation environment", "the defective yarn radius of the textile handicraft at the third preset time point under the eighth simulation environment" and "the defective yarn radius of the textile handicraft at the third preset time point under the ninth simulation environment", and comprehensively analyzes to obtain the "yarn environment interference factor", and the various parameters are related to each other, and do not exist independently. It is a whole, and the "yarn environment interference factor" cannot be obtained by simple combination and addition. For example, in this formula, "the defective yarn strength of the textile handicraft at the third preset time point under the seventh simulation environment" is conducive to increasing the "yarn environment interference factor", and does not necessarily represent The "yarn environment interference factor" is large. At this time, it is also necessary to consider "please determine the textile handicrafts at the third preset time point under the eighth simulation environment", "the defective yarn strength of the textile handicrafts at the third preset time point under the ninth simulation environment", "the defective yarn radius of the textile handicrafts at the third preset time point under the seventh simulation environment", "the defective yarn radius of the textile handicrafts at the third preset time point under the eighth simulation environment" and "the defective yarn radius of the textile handicrafts at the third preset time point under the ninth simulation environment" can also determine the degree of environmental interference in the yarn quality test at the next moment. The correlation and mutual influence between various factors are considered in a quantitative way. The algorithm itself is obtained through comprehensive analysis, which can accurately and quantitatively analyze the degree of environmental interference in the yarn quality test, and shows the effect of the numerical environmental interference factors on the defect situation of textile handicrafts in yarn quality detection. Therefore, accurate analysis is carried out by establishing mathematical forms.

[0094] Furthermore, the specific method for obtaining the defect evaluation result is as follows: obtaining the evaluation weight from the preset database, the evaluation weight includes the fabric surface detection weight, the printing and dyeing quality detection weight and the yarn quality detection weight, the fabric surface detection weight represents the proportion of fabric surface detection in the defect detection of textile handicrafts, the printing and dyeing quality detection weight represents the proportion of printing and dyeing quality detection in the defect detection of textile handicrafts, and the yarn quality detection weight represents the proportion of yarn quality detection in the defect detection of textile handicrafts; obtaining the defect evaluation result according to the surface defect coefficient, the printing and dyeing defect coefficient, the yarn defect coefficient and the evaluation weight; the defect evaluation result is calculated by the following formula:

[0095] ;

[0096] In the formula, BM represents the surface defect coefficient, YR represents the printing and dyeing defect coefficient, and SX represents the yarn defect coefficient. represents the fabric surface detection weight, Indicates the weight of printing and dyeing quality inspection, represents the yarn quality detection weight, P represents the defect evaluation result, and e represents the natural constant.

[0097] In this embodiment, the defect assessment result represents the overall defect situation of the textile handicraft; the fabric surface detection weight represents the proportion of fabric surface detection in the defect detection of textile handicrafts, the printing and dyeing quality detection weight represents the proportion of printing and dyeing quality detection in the defect detection of textile handicrafts, and the yarn quality detection weight represents the proportion of yarn quality detection in the defect detection of textile handicrafts; the surface defect coefficient is used to quantify the indicator of the severity of defects in the fabric surface detection link, the printing and dyeing defect coefficient is used to quantify the indicator of the severity of defects in the printing and dyeing quality detection link, and the yarn defect coefficient is used to quantify the indicator of the severity of defects in the yarn quality detection link; the accuracy of defect assessment of textile handicrafts is improved.

[0098] The algorithm of this embodiment combines the "surface defect coefficient", "printing and dyeing defect coefficient" and "yarn defect coefficient" to obtain a "defect evaluation result" through comprehensive analysis, and the various parameters are related and do not exist independently. They are a whole, and the "defect evaluation result" cannot be obtained by simple combination and addition. For example, the "surface defect coefficient" in this formula is conducive to increasing the "defect evaluation result", which does not necessarily mean that the "defect evaluation result" is large. At this time, the "printing and dyeing defect coefficient" also needs to be considered. In addition, the "yarn defect coefficient" can also determine the severity of the yarn defects at the next moment. The correlation and mutual influence between various factors are considered in a quantitative way. The algorithm itself is obtained through comprehensive analysis, which can accurately quantify and comprehensively analyze the severity of the defects, indicating the effect of comprehensive evaluation of textile handicrafts. Therefore, accurate analysis is performed by establishing a mathematical form.

[0099] Specifically, the fabric surface detection weight is obtained from a preset database. In a specific embodiment, a fitting curve is obtained by fitting the relationship between the surface defect coefficient and the defect evaluation result by the surface defect area of ​​the textile handicraft and the preset defect area of ​​the textile handicraft, and the corresponding fabric surface detection weight is determined according to the surface defect coefficient obtained from the fitting curve.

[0100] Specifically, the printing and dyeing quality detection weight is obtained from a preset database. In a specific embodiment, a fitting curve is obtained by fitting the relationship between the printing and dyeing defect coefficient and the defect evaluation result through the color difference of the textile handicraft and the preset textile handicraft color difference, and the printing and dyeing defect coefficient is obtained according to the fitting curve to determine the corresponding printing and dyeing quality detection weight.

[0101] Specifically, the yarn quality detection weight is obtained from a preset database. In a specific embodiment, the relationship between the yarn defect coefficient and the defect evaluation result is fitted by the defect yarn strength of the textile handicraft and the preset defect yarn strength of the textile handicraft to obtain a fitting curve, and the yarn defect coefficient is obtained according to the fitting curve to determine the corresponding yarn quality detection weight.

[0102] Furthermore, the specific method of obtaining the defect assessment report is as follows: obtaining the defect data of the textile handicraft from the database, the defect data including the inspection information of the textile handicraft, the defect inspection results of the textile handicraft and the defect assessment results; generating a defect assessment report based on the defect data and the defect assessment results, the defect assessment report including environmental information, the defect inspection results corresponding to each defect inspection and the defect assessment results.

[0103] In this embodiment, defect data refers to defect detection data on textile handicrafts obtained from the database, including textile handicraft detection information, defect detection results, and defect evaluation results; defect evaluation results are used to represent the overall defect situation of textile handicrafts; defect evaluation reports are used to record the defect situation of textile handicrafts in detail. The defect evaluation report includes environmental information, defect detection results corresponding to various defect detections, and the final defect evaluation results; environmental information includes light intensity, temperature, and humidity during defect detection; defect detection results corresponding to various defect detections include surface defect coefficients, printing and dyeing defect coefficients, and yarn defect coefficients; quality control efficiency is improved.

[0104] To sum up, the embodiments of the present application collect and process textile handicraft inspection information in real time, then perform defect detection on textile handicraft defect images according to the textile handicraft inspection information to obtain textile handicraft defect detection results, then combine the textile handicraft inspection information to obtain defect evaluation results, and finally generate a defect evaluation report, thereby improving the accuracy of textile handicraft defect detection, and further achieving improved accuracy of textile handicraft defect evaluation, effectively solving the problem of low accuracy of textile handicraft defect detection in the prior art.

[0105] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0106] The present invention is described with reference to flowcharts and / or block diagrams of systems, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0107] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0108] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0109] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0110] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. An intelligent management system for textile handicrafts, characterized in that: It includes data acquisition module, defect detection module and detection feedback module; The data acquisition module is used to pre-process the initial textile handicraft detection information collected in real time to obtain textile handicraft detection information; The defect detection module is used to perform defect detection on the textile handicraft defect image according to the textile handicraft detection information to obtain the textile handicraft defect detection result, and input the textile handicraft detection information into the established database; The detection feedback module is used to perform a comprehensive evaluation based on the textile handicraft defect detection results and textile handicraft detection information in the database to obtain a defect evaluation result, and generate a defect evaluation report, wherein the defect evaluation result is used to quantitatively describe the severity of the textile handicraft defect; The defect evaluation result is obtained according to the surface defect coefficient, the printing and dyeing defect coefficient and the yarn defect coefficient; The specific steps for obtaining the surface defect coefficient are as follows: Acquire a first environmental interference factor for fabric surface detection, wherein the first environmental interference factor includes light intensity, temperature and humidity; At a first preset time point within a preset time period, defect image information of a defect of a textile handicraft in a surface simulation environment is measured by an image acquisition device, and a fifth preprocessing is performed to obtain surface defect information of the textile handicraft, and the obtained surface defect information and a corresponding time stamp are recorded in a database to form a simulated environment surface defect information sequence; The surface environmental interference factor is obtained according to the preset defect area of ​​the textile handicraft and the simulated environment surface defect information sequence, and the surface defect coefficient is obtained accordingly. The surface environmental interference factor is used to quantify the influence of environmental factors on the defect situation of the textile handicraft in the fabric surface detection. The surface defect coefficient is used to comprehensively quantify the severity of the surface defects of the textile handicraft in the fabric surface detection. The surface defect coefficient is calculated by the following formula: ； Where i is the number of the first preset time point in the preset time period, , n represents the total number of first preset time points in the preset time period, represents the defect area of ​​the textile handicraft at the first preset time point i within the preset time period, represents the defect area of ​​the preset textile crafts, J represents the surface environmental interference factor, and BM represents the surface defect coefficient; The surface environmental interference factor is calculated by the following formula: ； In the formula, represents the defect area of ​​the textile handicraft at the i-th first preset time point in the first simulation environment, represents the surface defect area of ​​the textile handicraft at the i-th first preset time point in the second simulation environment, represents the surface defect area of ​​the textile handicraft at the i-th first preset time point under the third simulation environment; The specific steps for obtaining the printing and dyeing defect coefficient are as follows: Acquire a second environmental interference factor for printing and dyeing quality detection, wherein the second environmental interference factor includes light intensity, temperature and humidity; At a second preset time point within the preset time period, defect image information of defects of the textile handicraft in the printing and dyeing simulation environment is measured by a colorimeter and an image acquisition device, and a sixth preprocessing is performed to obtain printing and dyeing defect information of the textile handicraft, and the obtained printing and dyeing defect information and the corresponding timestamp are recorded in a database to form a simulated environment printing and dyeing defect information sequence; The printing and dyeing environment interference factor is obtained according to the color difference of the preset textile handicraft, the pixel points of the preset textile handicraft and the simulated environment printing and dyeing defect information sequence, and the printing and dyeing defect coefficient is obtained accordingly. The printing and dyeing environment interference factor is used to quantify the influence of environmental factors on the defects of textile handicrafts in printing and dyeing quality inspection. The printing and dyeing defect coefficient is used to comprehensively quantify the severity of printing and dyeing defects of textile handicrafts in printing and dyeing quality inspection. The printing and dyeing defect coefficient is calculated by the following formula: ； Where p is the number of the second preset time point in the preset time period, , m represents the total number of second preset time points within the preset time period, represents the color difference of the textile handicraft at the pth second preset time point within the preset time period, represents the pixel point of the textile craft at the pth second preset time point within the preset time period, Indicates the color difference of the preset textile crafts, represents the pixel point of the preset textile crafts, YR represents the printing and dyeing defect coefficient, and H represents the printing and dyeing environment interference factor; The printing and dyeing environmental interference factor is calculated by the following formula: ； In the formula, z represents the number of the simulation environment, , represents the fourth simulation environment, represents the fifth simulation environment, Indicates the sixth simulation environment represents the color difference of the textile handicraft at the pth second preset time point under the zth simulation environment, represents a pixel of the textile craft at the pth second preset time point under the zth simulation environment; The specific steps for obtaining the yarn defect coefficient are as follows: Acquiring a third environmental interference factor in the yarn quality detection process, wherein the third environmental interference factor includes light intensity, temperature and humidity; At a third preset time point within a preset time period, initial yarn defect information of the textile handicraft defect in the yarn simulation environment is measured by a micrometer and a tensile testing machine, and the yarn defect information of the textile handicraft is obtained by performing a seventh preprocessing, and the obtained yarn defect information and the corresponding timestamp are recorded in a database to form a simulated environment yarn defect information sequence; The yarn environmental interference factor is obtained according to the yarn strength of the preset textile handicraft, the yarn radius of the preset textile handicraft and the simulated environment yarn defect information sequence, and the yarn defect coefficient is obtained accordingly. The yarn environmental interference factor is used to quantify the influence of environmental factors on the defect situation of the textile handicraft in the yarn quality detection. The yarn defect coefficient is used to comprehensively quantify the severity of the yarn defects of the textile handicraft in the yarn quality detection. The yarn defect coefficient is calculated by the following formula: ； Wherein, t is the number of the third preset time point in the preset time period, , T represents the total number of third preset time points within the preset time period, Indicates the defective yarn strength of the textile handicraft at the tth third preset time point within the preset time period, Indicates the defective yarn radius of the textile handicraft at the tth third preset time point within the preset time period, Indicates the yarn strength of the preset textile craft, represents the yarn radius of the preset textile crafts, SX represents the yarn defect coefficient, and R represents the yarn environmental interference factor; The yarn environmental interference factor is calculated by the following formula: ； In the formula, z represents the number of the simulation environment, , represents the seventh simulation environment, represents the eighth simulation environment, represents the ninth simulation environment, represents the defective yarn strength of the textile craft product at the tth third preset time point under the zth simulation environment, represents the defective yarn radius of the textile handicraft at the tth third preset time point under the zth simulation environment; The specific method of obtaining the defect evaluation result is as follows: Obtaining evaluation weights from a preset database, wherein the evaluation weights include fabric surface detection weights, printing and dyeing quality detection weights, and yarn quality detection weights; Defect assessment results are obtained according to the surface defect coefficient, printing and dyeing defect coefficient, yarn defect coefficient and assessment weight; The defect evaluation result is calculated by the following formula: ； In the formula, BM represents the surface defect coefficient, YR represents the printing and dyeing defect coefficient, and SX represents the yarn defect coefficient. represents the fabric surface detection weight, Indicates the weight of printing and dyeing quality inspection, represents the yarn quality detection weight, P represents the defect evaluation result, and e represents the natural constant.

2. An intelligent management system for textile handicrafts as claimed in claim 1, characterized in that; The data acquisition module includes a data acquisition unit and a data processing unit; The data acquisition unit is used to collect initial textile craft detection information of the textile craft in real time, wherein the initial textile craft detection information includes defect image information and environmental information; The data processing unit is used to perform a first preprocessing on the initial textile handicraft detection information to obtain the textile handicraft detection information, and obtain the textile handicraft detection information accordingly.

3. An intelligent management system for textile handicrafts as claimed in claim 1, characterized in that: The defect detection includes fabric surface detection, printing and dyeing quality detection and yarn quality detection; The specific process of fabric surface detection is as follows: Performing a second preprocessing on the defect image information collected by the image acquisition device at a preset time point within a preset time period to obtain the surface defect area of ​​the textile handicraft; The obtained surface defect area and the corresponding timestamp are recorded in the database to form a fabric surface defect information sequence.

4. An intelligent management system for textile handicrafts as claimed in claim 3, characterized in that: The specific process of the printing and dyeing quality inspection is as follows: Performing a third preprocessing on the defect image information collected by the image acquisition device and the colorimeter at a preset time point within a preset time period to obtain printing and dyeing defect information of the textile handicraft; The printing and dyeing defect information and the corresponding timestamp are recorded in the database to form a printing and dyeing quality defect information sequence.

5. An intelligent management system for textile handicrafts as claimed in claim 3, characterized in that: The specific process of yarn quality detection is as follows: Performing a fourth preprocessing on the initial yarn defect information collected by the micrometer and the tensile testing machine at a preset time point within a preset time period to obtain the yarn defect information of the textile handicraft; The yarn defect information and the corresponding timestamp are recorded in the database to form a yarn quality defect information sequence.

6. An intelligent management system for textile handicrafts as claimed in claim 1, characterized in that: The specific method of obtaining the defect assessment report is as follows: Acquire defect data of textile handicrafts from a database, wherein the defect data includes inspection information of textile handicrafts, defect inspection results of textile handicrafts, and defect evaluation results; A defect assessment report is generated based on the defect data and the defect assessment results. The defect assessment report includes environmental information, defect detection results corresponding to various defect detections, and defect assessment results.

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