Real-time control method for heat setting density of fabric

Abstract

The invention discloses a fabric heat setting density real-time control method, and particularly relates to the technical field of fabric density intelligent control. Comprising the steps of S01, fabric image three-dimensional grid frame division, S02, fabric image information collection, S03, fabric heat setting stability judgment, S04, fabric heat setting density control, S05, fabric heat setting density detection and analysis and S06, fabric heat setting density detection and evaluation. The method comprises the following steps: acquiring fabric image data of each monitoring sub-grid of a three-dimensional grid frame of a target fabric image, calculating a fabric heat stability process effect index and a fabric heat setting density control index, performing fabric density control, and further analyzing to obtain a fabric heat setting density quality detection coefficient. The method can improve the accuracy of data acquisition, can automatically calculate and timely feed back through data analysis, is favorable for improving the intelligent level and quality of the production process, and is suitable for real-time density control of different types of fabric materials.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent fabric density control, and more specifically, to a real-time fabric heat setting density control method. Background Art

[0002] Real-time control technology of fabric heat setting density is a key process in the textile industry. It involves treating the fabric under specific temperature and pressure to achieve a predetermined dimensional stability and shape retention. This process is of great significance for improving the durability, wrinkle resistance and wearing comfort of textiles.

[0003] In the actual application of fabric heat setting, by controlling the key parameters in the heat setting process, production interruptions and scrap rates caused by parameter fluctuations can be reduced. This technology not only optimizes the production process, but also significantly reduces production costs. In addition, the application of real-time control technology also makes the production process more flexible, able to respond quickly to market changes, and shorten the product cycle from design to market, thereby achieving high quality and low cost in the production process.

[0004] However, it still has some shortcomings in actual use. For example, during the fabric heat setting process, a large amount of data needs to be monitored and recorded in real time, and the existing data processing methods may have deficiencies in data processing, making it difficult to quickly and accurately extract and analyze valuable information; Existing methods for detecting density of fabric heat setting are easily restricted by human operation. Most of them adopt destructive sampling methods, which destroy the integrity of the fabric. There is a lack of non-destructive detection technology to realize real-time and continuous monitoring of fabric density, which leads to uneven product density during the fabric heat setting process. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a method for real-time control of fabric heat setting density, which is used to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solution: a method for real-time control of fabric heat setting density, comprising the following steps: Step S01: fabric image three-dimensional grid frame division: used to divide the three-dimensional grid frame of the target fabric image into n monitoring sub-grids by an adaptive division method, and number each monitoring sub-grid of the three-dimensional grid frame of the target fabric image.

[0007] Step S02: Fabric image information acquisition: used to acquire fabric image data of each monitoring sub-grid of the three-dimensional grid framework of the target fabric image, wherein the fabric image information acquisition includes a fabric heat setting process control unit and a fabric heat setting density control unit.

[0008] Step S03: Fabric heat setting stability judgment: used to calculate the fabric heat stability process effect index of each monitoring sub-grid in the three-dimensional grid framework of the target fabric image according to the fabric heat setting process control data of the fabric heat setting process control unit, and perform density control during the fabric heat setting process.

[0009] Step S04: fabric heat setting density control: used to calculate the fabric heat setting density control index of each monitoring sub-grid of the three-dimensional grid framework of the target fabric image according to the fabric heat setting density control data of the fabric heat setting density control unit, and perform fabric density control.

[0010] Step S05: Fabric heat setting density detection analysis: used to calculate the fabric heat setting density quality detection coefficient of the target fabric image according to the fabric thermal stability process effect index and the fabric heat setting density control index of each monitoring sub-grid of the three-dimensional grid framework of the target fabric image.

[0011] Step S06: Fabric heat setting density detection and evaluation: used to obtain the fabric heat setting density quality detection coefficient of the target fabric image, compare it with the preset fabric heat setting density quality detection coefficient, and process it.

[0012] Preferably, the three-dimensional grid framework of the fabric image is divided specifically as follows: A three-dimensional image of the target fabric is acquired by laser scanning technology, a three-dimensional grid frame of the target fabric image is established in three-dimensional space, the three-dimensional grid frame of the target fabric image is divided into n monitoring sub-grids by an adaptive division method, and each monitoring sub-grid of the three-dimensional grid frame of the target fabric image is numbered 1, 2, ...i, ...n in sequence.

[0013] Preferably, the fabric image information collection is specifically as follows: Fabric heat setting process control unit: The heat setting temperature, heat setting time, fabric temperature, and sub-grid area of ​​each monitoring sub-grid of the three-dimensional grid framework used to collect the target fabric image are marked as , , , , where i=1,2,...n, i represents the number of the i-th monitoring subgrid; Fabric heat setting density control unit: The fabric thickness, number of coil wales, number of coil rows, and motor speed of each monitoring sub-grid of the three-dimensional grid framework used to collect the target fabric image are marked as , , , .

[0014] Preferably, the thermal setting stability of the fabric is judged specifically as follows: Step S41: Calculate the uniformity of temperature distribution of each monitoring subgrid through the heat setting temperature and the temperature of the fabric itself:

[0015] in, It is expressed as the uniformity of temperature distribution of the ith monitoring subgrid, It is represented as the heat setting temperature of the ith monitoring subgrid, It is represented as the fabric temperature of the ith monitoring subgrid, Expressed as the mean value of heat setting temperature, It is represented as the mean value of the fabric temperature itself, and n is represented as the number of monitoring subgrids; Step S42: Calculate the fabric heat setting temperature diffusion index of each monitoring sub-grid:

[0016] in, It is represented as the fabric heat setting temperature diffusion index of the i-th monitoring sub-grid, It is represented as the subgrid area of ​​the ith monitoring subgrid, Expressed as the mean of the sub-grid areas, Expressed as the maximum value of the sub-grid area, Expressed as the minimum value of the sub-grid area, Expressed as the standard deviation of the subgrid area; Step S43: The calculation formula of the fabric thermal stability process effect index is:

[0017] in, It is expressed as the fabric thermal stability process effect index of the i-th monitoring sub-grid, It represents the preset fabric heat setting temperature diffusion index, e is represented as a natural constant, It is represented as the thermal setting time of the ith monitoring subgrid, It is represented as the fabric heat setting temperature diffusion index of the i-th monitoring sub-grid.

[0018] Preferably, the fabric image information collection further includes: The fabric thermal stability process effect index of each monitoring sub-grid in the three-dimensional grid framework of the target fabric image is obtained, and compared with the preset fabric thermal stability process effect index. If the fabric thermal stability process effect index of a monitoring sub-grid in the three-dimensional grid framework of the target fabric image is less than the preset fabric thermal stability process effect index, it indicates that the thermal stability of the fabric does not meet expectations, and the density of the fabric should be controlled. Otherwise, it indicates that the thermal stability of the fabric meets expectations, and the density of the fabric should be monitored in real time.

[0019] Preferably, the fabric heat setting density control is specifically as follows: Step S61: Calculate the density of the fabric wales of each monitoring sub-grid according to the fabric thickness, the number of coil wales, and the motor speed:

[0020] in, It is expressed as the density of the fabric longitudinal lines of the ith monitoring sub-grid, It is represented by the number of coil columns of the i-th monitoring sub-grid, Represented as the fabric thickness of the ith monitoring subgrid, It is represented as the motor speed of the i-th monitoring subgrid, and e is represented as a natural constant; Step S62: Calculate the density of the fabric rows of each monitoring subgrid according to the fabric thickness, the number of coil rows, and the motor speed:

[0021] in, It is expressed as the density of the fabric rows of the i-th monitoring sub-grid, It is represented as the number of coil rows of the ith monitoring sub-grid, and e is represented as a natural constant; Step S63: The calculation formula of the fabric heat setting density control index is:

[0022] in, It is expressed as the fabric heat setting density control index of the i-th monitoring sub-grid, It is expressed as the density of the fabric longitudinal lines of the ith monitoring sub-grid, It is expressed as the minimum value of the density of the fabric longitudinal line. It is expressed as the maximum value of the density of the fabric longitudinal line. It is expressed as the density of the fabric rows of the i-th monitoring sub-grid, It is expressed as the mean value of the density of the fabric rows. It is expressed as the allowable difference in the density of the fabric rows. , are respectively expressed as compensation factors for the density of the fabric in rows and the density of the fabric in longitudinal directions, and + =1.

[0023] Preferably, the fabric heat setting density control further comprises: The fabric heat setting density control index of each monitoring sub-grid of the three-dimensional grid framework of the target fabric image is obtained, and compared with the preset fabric heat setting density control index interval. If the fabric heat setting density control index of a monitoring sub-grid of the three-dimensional grid framework of the target fabric image is greater than the maximum value of the preset fabric heat setting density control index interval, it indicates that the fabric longitudinal density of the monitoring sub-grid does not meet expectations, and the coil length of the fabric longitudinal row should be increased. If the fabric heat setting density control index of a monitoring sub-grid of the three-dimensional grid framework of the target fabric image is less than the minimum value of the preset fabric heat setting density control index interval, it indicates that the fabric horizontal row density of the monitoring sub-grid does not meet expectations, and the coil length of the fabric horizontal row should be increased. If the fabric heat setting density control index of a monitoring sub-grid of the three-dimensional grid framework of the target fabric image is within the preset fabric heat setting density control index interval, it indicates that the fabric density of the monitoring sub-grid meets expectations.

[0024] Preferably, the calculation formula of the fabric heat setting density quality detection coefficient is:

[0025] in, Expressed as fabric heat setting density quality detection coefficient, Expressed as the preset fabric thermal stability process effect index, It is expressed as the fabric thermal stability process effect index of the i-th monitoring sub-grid, It is represented as the fabric heat setting density control index of the ith monitoring sub-grid, and n is represented as the number of monitoring sub-grids.

[0026] Preferably, the fabric heat setting density detection and evaluation is specifically as follows: The fabric heat setting density quality detection coefficient of the target fabric image is obtained, and compared with the preset fabric heat setting density quality detection coefficient. If the fabric heat setting density quality detection coefficient of the target fabric image is less than the preset fabric heat setting density quality detection coefficient, it indicates that the quality detection of the production process related to the heat setting density of the fabric image does not meet expectations, and the operator should be notified to check; otherwise, it indicates that the quality detection of the production process related to the heat setting density of the fabric image is qualified.

[0027] Technical effects and advantages of the present invention: The present invention provides a real-time control method for fabric heat setting density, which collects fabric image data of each monitoring subgrid of a three-dimensional grid frame of a target fabric image, calculates the fabric thermal stability process effect index of each monitoring subgrid of the three-dimensional grid frame of the target fabric image according to fabric heat setting process control data of a fabric heat setting process control unit, calculates the fabric heat setting density control index of each monitoring subgrid of the three-dimensional grid frame of the target fabric image according to fabric heat setting density control data of a fabric heat setting density control unit, and compares it with a preset fabric heat setting density control index interval. If the three-dimensional grid frame of the target fabric image is If the fabric heat setting density control index of a monitoring sub-grid of the three-dimensional grid frame is greater than the maximum value of the preset fabric heat setting density control index interval, it indicates that the fabric longitudinal density of the monitoring sub-grid does not meet expectations, and the coil length of the fabric longitudinal row should be increased. If the fabric heat setting density control index of a monitoring sub-grid of the three-dimensional grid frame of the target fabric image is less than the minimum value of the preset fabric heat setting density control index interval, it indicates that the fabric horizontal row density of the monitoring sub-grid does not meet expectations, and the coil length of the fabric horizontal row should be increased. If the fabric heat setting density control index of a monitoring sub-grid of the three-dimensional grid frame of the target fabric image is within the preset fabric heat setting density control index interval, it indicates that the fabric horizontal row density of the monitoring sub-grid does not meet expectations, and the coil length of the fabric horizontal row should be increased. If the density control index is within the range, it indicates that the fabric density of the monitoring subgrid meets expectations. The three-dimensional grid framework is used to collect image data of the target fabric, which can improve the accuracy of data collection. The fabric heat setting effect is automatically calculated through data analysis, and timely feedback is given to adjust the fabric coil length, thereby avoiding waste and loss in the production process, which is beneficial to improving the intelligence level of the production process and the quality of product production. The present invention provides a real-time control method for fabric heat setting density. According to the fabric thermal stability process effect index and the fabric heat setting density control index of each monitoring subgrid of the three-dimensional grid framework of the target fabric image, the fabric heat setting density quality detection coefficient of the target fabric image is calculated and compared with the preset fabric heat setting density quality detection coefficient. If the fabric heat setting density quality detection coefficient of the target fabric image is less than the preset fabric heat setting density quality detection coefficient, it indicates that the quality detection of the heat setting density-related production process of the fabric image does not meet expectations, and the operator should be notified to check it. Otherwise, it indicates that the quality detection of the heat setting density-related production process of the fabric image is qualified. By comprehensively evaluating the quality detection of the fabric heat setting density, automated quality control is realized, human errors are reduced, and it is suitable for real-time density control of different types of fabric materials. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is a schematic diagram of the connection of the method steps of the present invention.

[0029] Figure 2 It is a schematic diagram of the fabric image information acquisition structure of the present invention. DETAILED DESCRIPTION

[0030] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0031] See also Figure 1 As shown, the present invention provides a real-time control method for fabric heat setting density, including step S01: three-dimensional grid framework division of fabric image, step S02: fabric image information collection, step S03: fabric heat setting stability judgment, step S04: fabric heat setting density control, step S05: fabric heat setting density detection and analysis, step S06: fabric heat setting density detection and evaluation.

[0032] The step S01: fabric image three-dimensional grid framework division is connected with the step S02: fabric image information acquisition, the step S02: fabric image information acquisition is connected with the step S03: fabric heat setting stability judgment, S03: fabric heat setting stability judgment is connected with the step S04: fabric heat setting density control, the step S04: fabric heat setting density control is connected with the step S05: fabric heat setting density detection and analysis, the step S05: fabric heat setting density detection and analysis is connected with the step S06: fabric heat setting density detection and evaluation.

[0033] The step S01: fabric image three-dimensional grid frame division is used to divide the three-dimensional grid frame of the target fabric image into n monitoring sub-grids by adaptive division, and number each monitoring sub-grid of the three-dimensional grid frame of the target fabric image.

[0034] In a possible design, the three-dimensional grid framework of the fabric image is specifically divided as follows: A three-dimensional image of the target fabric is acquired by laser scanning technology, a three-dimensional grid frame of the target fabric image is established in three-dimensional space, the three-dimensional grid frame of the target fabric image is divided into n monitoring sub-grids by an adaptive division method, and each monitoring sub-grid of the three-dimensional grid frame of the target fabric image is numbered 1, 2, ...i, ...n in sequence.

[0035] See also Figure 2 As shown, the step S02: fabric image information acquisition is used to acquire fabric image data of each monitoring sub-grid of the three-dimensional grid framework of the target fabric image, the fabric image information acquisition includes a fabric heat setting process control unit and a fabric heat setting density control unit, and the fabric image data includes fabric heat setting process control data and fabric heat setting density control data.

[0036] In a possible design, the fabric image information collection is specifically as follows: Fabric heat setting process control unit: The heat setting temperature, heat setting time, fabric temperature, and sub-grid area of ​​each monitoring sub-grid of the three-dimensional grid framework used to collect the target fabric image are marked as , , , , where i=1,2,...n, i represents the number of the i-th monitoring subgrid; Fabric heat setting density control unit: The fabric thickness, number of coil wales, number of coil rows, and motor speed of each monitoring sub-grid of the three-dimensional grid framework used to collect the target fabric image are marked as , , , .

[0037] The step S03: fabric heat setting stability judgment is used to calculate the fabric heat stability process effect index of each monitoring sub-grid of the three-dimensional grid framework of the target fabric image according to the fabric heat setting process control data of the fabric heat setting process control unit, and perform density control during the fabric heat setting process.

[0038] In a possible design, the thermal setting stability of the fabric is judged specifically as follows: Step S41: Calculate the uniformity of temperature distribution of each monitoring subgrid through the heat setting temperature and the temperature of the fabric itself:

[0039] in, It is expressed as the uniformity of temperature distribution of the ith monitoring subgrid, It is represented as the heat setting temperature of the ith monitoring subgrid, It is represented as the fabric temperature of the ith monitoring subgrid, Expressed as the mean value of heat setting temperature, It is represented as the mean value of the fabric temperature itself, and n is represented as the number of monitoring subgrids; in, , ; Step S42: Calculate the fabric heat setting temperature diffusion index of each monitoring sub-grid:

[0040] in, It is represented as the fabric heat setting temperature diffusion index of the i-th monitoring sub-grid, It is represented as the subgrid area of ​​the ith monitoring subgrid, Expressed as the mean of the sub-grid areas, Expressed as the maximum value of the sub-grid area, Expressed as the minimum value of the sub-grid area, Expressed as the standard deviation of the subgrid area; in, , ; Step S43: The calculation formula of the fabric thermal stability process effect index is:

[0041] in, It is expressed as the fabric thermal stability process effect index of the i-th monitoring sub-grid, It represents the preset fabric heat setting temperature diffusion index, e is represented as a natural constant, It is represented as the thermal setting time of the ith monitoring subgrid, It is represented as the fabric heat setting temperature diffusion index of the i-th monitoring subgrid; Step S44: Obtain the fabric thermal stability process effect index of each monitoring sub-grid of the three-dimensional grid framework of the target fabric image, and compare it with the preset fabric thermal stability process effect index. If the fabric thermal stability process effect index of a monitoring sub-grid of the three-dimensional grid framework of the target fabric image is less than the preset fabric thermal stability process effect index, it indicates that the thermal stability of the fabric does not meet expectations, and the density of the fabric should be controlled. Otherwise, it indicates that the thermal stability of the fabric meets expectations, and the density of the fabric is monitored in real time.

[0042] The step S04: fabric heat setting density control is used to calculate the fabric heat setting density control index of each monitoring sub-grid of the three-dimensional grid framework of the target fabric image according to the fabric heat setting density control data of the fabric heat setting density control unit, and perform fabric density control.

[0043] In a possible design, the fabric heat setting density control is specifically as follows: Step S61: Calculate the density of the fabric wales of each monitoring sub-grid according to the fabric thickness, the number of coil wales, and the motor speed:

[0044] in, It is expressed as the density of the fabric longitudinal lines of the ith monitoring sub-grid, It is represented by the number of coil columns of the i-th monitoring sub-grid, Represented as the fabric thickness of the ith monitoring subgrid, It is represented as the motor speed of the i-th monitoring subgrid, and e is represented as a natural constant; Step S62: Calculate the density of the fabric rows of each monitoring subgrid according to the fabric thickness, the number of coil rows, and the motor speed:

[0045] in, It is expressed as the density of the fabric rows of the i-th monitoring sub-grid, It is represented as the number of coil rows of the ith monitoring sub-grid, and e is represented as a natural constant; Step S63: The calculation formula of the fabric heat setting density control index is:

[0046] in, It is expressed as the fabric heat setting density control index of the i-th monitoring sub-grid, It is expressed as the density of the fabric longitudinal lines of the ith monitoring sub-grid, It is expressed as the minimum value of the density of the fabric longitudinal line. It is expressed as the maximum value of the density of the fabric longitudinal line. It is expressed as the density of the fabric rows of the i-th monitoring sub-grid, It is expressed as the mean value of the density of the fabric rows. It is expressed as the allowable difference in the density of the fabric rows. , are respectively expressed as compensation factors for the density of the fabric in rows and the density of the fabric in longitudinal directions, and + =1; Step S64: obtaining the fabric heat setting density control index of each monitoring sub-grid of the three-dimensional grid frame of the target fabric image, and comparing them with the preset fabric heat setting density control index interval; if the fabric heat setting density control index of a monitoring sub-grid of the three-dimensional grid frame of the target fabric image is greater than the maximum value of the preset fabric heat setting density control index interval, it indicates that the fabric longitudinal density of the monitoring sub-grid does not meet expectations, and the coil length of the fabric longitudinal row should be increased; if the fabric heat setting density control index of a monitoring sub-grid of the three-dimensional grid frame of the target fabric image is less than the minimum value of the preset fabric heat setting density control index interval, it indicates that the fabric horizontal row density of the monitoring sub-grid does not meet expectations, and the coil length of the fabric horizontal row should be increased; if the fabric heat setting density control index of a monitoring sub-grid of the three-dimensional grid frame of the target fabric image is within the preset fabric heat setting density control index interval, it indicates that the fabric density of the monitoring sub-grid meets expectations.

[0047] The step S05: fabric heat setting density detection analysis is used to calculate the fabric heat setting density quality detection coefficient of the target fabric image according to the fabric heat stability process effect index and the fabric heat setting density control index of each monitoring sub-grid of the three-dimensional grid framework of the target fabric image.

[0048] In a possible design, the calculation formula of the fabric heat setting density quality detection coefficient is:

[0049] in, Expressed as fabric heat setting density quality detection coefficient, Expressed as the preset fabric thermal stability process effect index, It is expressed as the fabric thermal stability process effect index of the i-th monitoring sub-grid, It is represented as the fabric heat setting density control index of the ith monitoring sub-grid, and n is represented as the number of monitoring sub-grids.

[0050] The step S06: fabric heat setting density detection and evaluation is used to obtain a fabric heat setting density quality detection coefficient of the target fabric image, compare it with a preset fabric heat setting density quality detection coefficient, and process it.

[0051] In a possible design, the fabric heat setting density detection and evaluation is specifically as follows: The fabric heat setting density quality detection coefficient of the target fabric image is obtained, and compared with the preset fabric heat setting density quality detection coefficient. If the fabric heat setting density quality detection coefficient of the target fabric image is less than the preset fabric heat setting density quality detection coefficient, it indicates that the quality detection of the production process related to the heat setting density of the fabric image does not meet expectations, and the operator should be notified to check; otherwise, it indicates that the quality detection of the production process related to the heat setting density of the fabric image is qualified.

[0052] In the present embodiment, it should be specifically explained that the present invention collects fabric image data of each monitoring sub-grid of the three-dimensional grid framework of the target fabric image, calculates the fabric thermal stability process effect index of each monitoring sub-grid of the three-dimensional grid framework of the target fabric image according to the fabric heat setting process control data of the fabric heat setting process control unit, calculates the fabric heat setting density control index of each monitoring sub-grid of the three-dimensional grid framework of the target fabric image according to the fabric heat setting density control data of the fabric heat setting density control unit, and compares it with the preset fabric heat setting density control index range. If the fabric heat setting density control index of a monitoring sub-grid of the three-dimensional grid framework of the target fabric image is greater than the maximum value of the preset fabric heat setting density control index range, it indicates that the fabric longitudinal density of the monitoring sub-grid does not meet expectations and should be increased. The coil length of the fabric longitudinal row. If the fabric heat setting density control index of a monitoring subgrid of the three-dimensional grid framework of the target fabric image is less than the minimum value of the preset fabric heat setting density control index interval, it indicates that the fabric horizontal row density of the monitoring subgrid does not meet expectations, and the coil length of the fabric horizontal row should be increased. If the fabric heat setting density control index of a monitoring subgrid of the three-dimensional grid framework of the target fabric image is within the preset fabric heat setting density control index interval, it indicates that the fabric density of the monitoring subgrid meets expectations. The three-dimensional grid framework is used to collect image data of the target fabric, which can improve the accuracy of data collection, automatically calculate the fabric heat setting effect through data analysis, and provide timely feedback to adjust the fabric coil length, thereby avoiding waste and loss in the production process, which is conducive to improving the intelligence level of the production process and the quality of product production; The present invention calculates a fabric heat setting density quality detection coefficient of a target fabric image according to a fabric heat stability process effect index and a fabric heat setting density control index of each monitoring sub-grid of a three-dimensional grid framework of a target fabric image, and compares the coefficient with a preset fabric heat setting density quality detection coefficient. If the fabric heat setting density quality detection coefficient of the target fabric image is less than the preset fabric heat setting density quality detection coefficient, it indicates that the quality detection of a production process related to the heat setting density of the fabric image does not meet expectations, and an operator should be notified to check. Otherwise, it indicates that the quality detection of a production process related to the heat setting density of the fabric image is qualified. By comprehensively evaluating the quality detection of the fabric heat setting density, automated quality control is achieved, human errors are reduced, and the method is suitable for real-time density control of different types of fabric materials.

[0053] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A real-time control method for fabric heat setting density, characterized in that: The following steps are involved: Step S01: dividing the three-dimensional grid frame of the fabric image: dividing the three-dimensional grid frame of the target fabric image into n monitoring sub-grids by an adaptive division method, and numbering each monitoring sub-grid of the three-dimensional grid frame of the target fabric image; Step S02: fabric image information acquisition: used to acquire fabric image data of each monitoring sub-grid of the three-dimensional grid framework of the target fabric image, wherein the fabric image information acquisition includes a fabric heat setting process control unit and a fabric heat setting density control unit; Step S03: judging the fabric heat setting stability: used to calculate the fabric heat stability process effect index of each monitoring sub-grid of the three-dimensional grid framework of the target fabric image according to the fabric heat setting process control data of the fabric heat setting process control unit, and perform density control during the fabric heat setting process; Step S04: fabric heat setting density control: used to calculate the fabric heat setting density control index of each monitoring sub-grid of the three-dimensional grid framework of the target fabric image according to the fabric heat setting density control data of the fabric heat setting density control unit, and perform fabric density control; Step S05: Fabric heat setting density detection analysis: used to calculate the fabric heat setting density quality detection coefficient of the target fabric image according to the fabric thermal stability process effect index and the fabric heat setting density control index of each monitoring sub-grid of the three-dimensional grid framework of the target fabric image; Step S06: Fabric heat setting density detection and evaluation: used to obtain the fabric heat setting density quality detection coefficient of the target fabric image, compare it with the preset fabric heat setting density quality detection coefficient, and process it.

2. A method for real-time control of fabric heat setting density according to claim 1, characterized in that: The three-dimensional grid framework of the fabric image is specifically divided as follows: A three-dimensional image of the target fabric is acquired by laser scanning technology, a three-dimensional grid frame of the target fabric image is established in three-dimensional space, the three-dimensional grid frame of the target fabric image is divided into n monitoring sub-grids by an adaptive division method, and each monitoring sub-grid of the three-dimensional grid frame of the target fabric image is numbered 1, 2, ...i, ...n in sequence.

3. A method for real-time control of fabric heat setting density according to claim 1, characterized in that: The fabric image information collection is specifically as follows: Fabric heat setting process control unit: The heat setting temperature, heat setting time, fabric temperature, and sub-grid area of ​​each monitoring sub-grid of the three-dimensional grid framework used to collect the target fabric image are marked as , , , , where i=1,2,...n, i represents the number of the i-th monitoring subgrid; Fabric heat setting density control unit: The fabric thickness, number of coil wales, number of coil rows, and motor speed of each monitoring sub-grid of the three-dimensional grid framework used to collect the target fabric image are marked as , , , .

4. A method for real-time control of fabric heat setting density according to claim 1, characterized in that: The thermal setting stability of the fabric is determined specifically as follows: Step S41: Calculate the uniformity of temperature distribution of each monitoring subgrid through the heat setting temperature and the temperature of the fabric itself: in, It is expressed as the uniformity of temperature distribution of the ith monitoring subgrid, It is represented as the heat setting temperature of the ith monitoring subgrid, It is represented as the fabric temperature of the ith monitoring subgrid, Expressed as the mean value of heat setting temperature, It is represented as the mean value of the fabric temperature itself, and n is represented as the number of monitoring subgrids; Step S42: Calculate the fabric heat setting temperature diffusion index of each monitoring sub-grid: in, It is represented as the fabric heat setting temperature diffusion index of the i-th monitoring sub-grid, It is represented as the subgrid area of ​​the ith monitoring subgrid, Expressed as the mean of the sub-grid areas, Expressed as the maximum value of the sub-grid area, Expressed as the minimum value of the sub-grid area, Expressed as the standard deviation of the subgrid area; Step S43: The calculation formula of the fabric thermal stability process effect index is: in, It is expressed as the fabric thermal stability process effect index of the i-th monitoring sub-grid, It represents the preset fabric heat setting temperature diffusion index, e is represented as a natural constant, It is represented as the thermal setting time of the ith monitoring subgrid, It is represented as the fabric heat setting temperature diffusion index of the i-th monitoring sub-grid.

5. A method for real-time control of fabric heat setting density according to claim 4, characterized in that: The fabric image information collection also includes: The fabric thermal stability process effect index of each monitoring sub-grid in the three-dimensional grid framework of the target fabric image is obtained, and compared with the preset fabric thermal stability process effect index. If the fabric thermal stability process effect index of a monitoring sub-grid in the three-dimensional grid framework of the target fabric image is less than the preset fabric thermal stability process effect index, it indicates that the thermal stability of the fabric does not meet expectations, and the density of the fabric should be controlled. Otherwise, it indicates that the thermal stability of the fabric meets expectations, and the density of the fabric should be monitored in real time.

6. A method for real-time control of fabric heat setting density according to claim 1, characterized in that: The fabric heat setting density control is specifically as follows: Step S61: Calculate the density of the fabric wales of each monitoring sub-grid according to the fabric thickness, the number of coil wales, and the motor speed: in, It is expressed as the density of the fabric longitudinal lines of the ith monitoring sub-grid, It is represented by the number of coil columns of the i-th monitoring sub-grid, Represented as the fabric thickness of the ith monitoring subgrid, It is represented as the motor speed of the i-th monitoring subgrid, and e is represented as a natural constant; Step S62: Calculate the density of the fabric rows of each monitoring subgrid according to the fabric thickness, the number of coil rows, and the motor speed: in, It is expressed as the density of the fabric rows of the i-th monitoring sub-grid, It is represented as the number of coil rows of the ith monitoring sub-grid, and e is represented as a natural constant; Step S63: The calculation formula of the fabric heat setting density control index is: in, It is expressed as the fabric heat setting density control index of the i-th monitoring sub-grid, It is expressed as the density of the fabric longitudinal lines of the ith monitoring sub-grid, It is expressed as the minimum value of the density of the fabric longitudinal line. It is expressed as the maximum value of the density of the fabric longitudinal line. It is expressed as the density of the fabric rows of the i-th monitoring sub-grid, It is expressed as the mean value of the density of the fabric rows. It is expressed as the allowable difference in the density of the fabric rows. , are respectively expressed as compensation factors for the density of the fabric in rows and the density of the fabric in longitudinal directions, and + =1.

7. A method for real-time control of fabric heat setting density according to claim 6, characterized in that: The fabric heat setting density control also includes: The fabric heat setting density control index of each monitoring sub-grid of the three-dimensional grid framework of the target fabric image is obtained, and compared with the preset fabric heat setting density control index interval. If the fabric heat setting density control index of a monitoring sub-grid of the three-dimensional grid framework of the target fabric image is greater than the maximum value of the preset fabric heat setting density control index interval, it indicates that the fabric longitudinal density of the monitoring sub-grid does not meet expectations, and the coil length of the fabric longitudinal row should be increased. If the fabric heat setting density control index of a monitoring sub-grid of the three-dimensional grid framework of the target fabric image is less than the minimum value of the preset fabric heat setting density control index interval, it indicates that the fabric horizontal row density of the monitoring sub-grid does not meet expectations, and the coil length of the fabric horizontal row should be increased. If the fabric heat setting density control index of a monitoring sub-grid of the three-dimensional grid framework of the target fabric image is within the preset fabric heat setting density control index interval, it indicates that the fabric density of the monitoring sub-grid meets expectations.

8. A method for real-time control of fabric heat setting density according to claim 1, characterized in that: The calculation formula of the fabric heat setting density quality detection coefficient is: in, Expressed as fabric heat setting density quality detection coefficient, Expressed as the preset fabric thermal stability process effect index, It is expressed as the fabric thermal stability process effect index of the i-th monitoring sub-grid, It is represented as the fabric heat setting density control index of the ith monitoring sub-grid, and n is represented as the number of monitoring sub-grids.

9. A method for real-time control of fabric heat setting density according to claim 1, characterized in that: The fabric heat setting density detection and evaluation is specifically as follows: The fabric heat setting density quality detection coefficient of the target fabric image is obtained, and compared with the preset fabric heat setting density quality detection coefficient. If the fabric heat setting density quality detection coefficient of the target fabric image is less than the preset fabric heat setting density quality detection coefficient, it indicates that the quality detection of the production process related to the heat setting density of the fabric image does not meet expectations, and the operator should be notified to check; otherwise, it indicates that the quality detection of the production process related to the heat setting density of the fabric image is qualified.

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