A sweater yarn material adaptation design and knitting equipment parameter optimization method

Abstract

The application discloses a sweater yarn material adaptation design and knitting equipment parameter optimization method, and relates to the technical field of sweater knitting.The method comprises the following specific steps: S1: using special detection equipment, collecting yarn basic characteristics, critical mechanical threshold, surface characteristics and acid and alkali tolerance performance through standardized tensile test, standardized friction resistance test and special test, and integrating to form a yarn characteristic data set.The application constructs a yarn characteristic-fabric design-finish process-equipment parameter correlation initial parameter database, clearly defines the corresponding technical logic between parameters, provides a basis for setting the initial parameters of the knitting equipment, calls the basic parameters matched with the yarn characteristics from the database, and adjusts the parameters in combination with the finish process parameters, effectively avoids problems such as yarn damage and unstable fabric quality caused by unreasonable parameter setting, and improves the accuracy and rationality of the initial parameter setting of the equipment.

Description

Technical Field

[0001] This invention relates to the field of sweater knitting technology, specifically to a design for sweater yarn material adaptation and a method for optimizing knitting equipment parameters. Background Technology

[0002] In the field of knitwear technology, as consumers' demands for the quality, functionality, and environmental friendliness of sweaters continue to increase, sweater production technology is also constantly developing and innovating. The sweater production process involves multiple stages, each of which has a significant impact on the quality and performance of the final sweater product. In recent years, bio-based yarn, as a new type of environmentally friendly material, has gradually been applied in sweater production due to its advantages such as renewability, biodegradability, and good biocompatibility. Bio-based yarn is usually made from natural biomass raw materials through processing, and its characteristics differ from those of traditional chemical fiber yarns, which brings new challenges to the adaptation of the entire sweater production process.

[0003] In the current sweater production technology system, there are many technical shortcomings regarding bio-based yarns. First, there is a lack of a dedicated critical mechanical threshold testing process for yarns, especially bio-based yarns. Traditional techniques do not obtain core mechanical property parameters such as yarn breakage and abrasion resistance through standardized testing. During the knitting process, it is impossible to accurately grasp the mechanical performance limits of the yarn, making it difficult to effectively control the risk of yarn damage and easily leading to problems such as yarn breakage. Second, traditional design methods do not fully consider the changes in yarn performance and size that may be caused by finishing processes such as dyeing and setting, and do not reserve corresponding adaptation redundancy, making it difficult to guarantee the conformity of the finished product design. This can easily lead to problems such as finished product size not meeting requirements and performance degradation. Third, the traditional method lacks clear technical basis for debugging, which is not only inefficient but also costly to repeat. It is difficult to guarantee the accuracy and stability of equipment parameters. In addition, the dynamic correction of equipment parameters only addresses real-time deviations during the knitting process and does not incorporate the predictive adjustment logic of the finishing process. This makes the parameter stability unable to match the requirements of the entire process, and product quality problems may occur in the finishing stage due to parameter mismatch. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of existing technologies and provide a design method for adapting sweater yarn materials and optimizing knitting equipment parameters. This method utilizes various specialized testing devices during the yarn testing stage to obtain data on the yarn's basic characteristics, critical mechanical thresholds, surface properties, and acid / alkali resistance through standardized testing, forming a complete yarn characteristic dataset. Based on the test results, fabric design parameters are matched. The fabric structure is determined according to the yarn breaking strength threshold, the loop density is set according to the breaking elongation threshold with reserved stretching redundancy, the design weight is adjusted in conjunction with the influence of finishing weight, and the initial parameters of the knitting equipment are set in conjunction with the finishing process, constructing a database of associated initial parameters. The yarn feeding speed, needle pitch, and tension are adjusted according to the yarn abrasion resistance threshold, the lateral shrinkage rate of finishing, and acid / alkali dyeing processes. During knitting, data is collected in real time by sensors, and corrections are triggered according to preset frequencies and changes in finishing processes, achieving dynamic adjustment of equipment parameters. After the finishing process is completed, the finished product performance is tested, and the deviation of the previous parameter positioning is compared. The database parameters are adjusted and iteratively updated, achieving coordinated adaptation of fabric design, equipment parameters, and finishing processes, meeting the technical requirements of sweater production for process precision and stability.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a method for designing and optimizing knitting equipment parameters for adapting sweater yarn materials, the method comprising the following specific steps:

[0006] S1: Using specialized testing equipment, through standardized tensile tests, standardized abrasion resistance tests and special tests, we collect yarn basic properties, critical mechanical thresholds, surface properties and acid and alkali resistance properties, and integrate them to form a yarn property dataset.

[0007] S2: Using the critical thresholds of breaking strength and breaking elongation in the yarn characteristic dataset as core constraints, determine the fabric structure type, set the loop density and reserve stretching redundancy, and adjust the design weight in combination with the weight influence law of finishing process to offset finishing deviation.

[0008] S3: Construct an initial parameter database that links yarn characteristics, fabric design, finishing processes, and equipment parameters; adjust the yarn feeding speed based on the yarn abrasion resistance threshold; adjust the needle pitch based on the transverse shrinkage rate of finishing processes; and adjust the tension based on the yarn breaking strength threshold and acid-alkali dyeing process characteristics.

[0009] S4: Enable the coil density sensor and yarn tension sensor to collect real-time data at a preset frequency, trigger correction according to fixed frequency and post-processing changes, and optimize yarn feeding speed and tension parameters by combining process deviation adjustment and post-processing prediction adjustment.

[0010] S5: After finishing, test the finished product's dimensional change rate, strength retention rate, and color fastness performance. Compare the test data with the previous fabric design parameters, equipment initial parameters, and dynamic correction parameters to locate the adaptation deviation and adjust the database parameters. The database is updated once for each production batch.

[0011] Further, in step S1, a yarn fineness meter, twist meter, electronic single yarn strength meter, abrasion tester, coefficient of friction meter, and acid-base resistance test device are used as specialized testing equipment. The yarn fineness parameter is measured using the yarn fineness meter, the twist parameter is measured using the twist meter, and the fiber composition and percentage of each component are determined using a component analyzer to form a basic yarn characteristic dataset. A standardized tensile testing procedure is followed, using an electronic single yarn strength meter to conduct tensile tests and record the critical thresholds for yarn breaking strength and elongation at break. A standardized abrasion resistance testing procedure is followed, using an abrasion tester to conduct tests and record the critical thresholds for yarn abrasion resistance. The coefficient of friction meter is used to measure the yarn's surface friction coefficient and hairiness index. The acid-base resistance test device is used to measure the yarn's strength retention rate after immersing it in a pH 4-9 buffer solution environment, forming yarn surface and chemical resistance performance data. All data are then integrated into a complete yarn characteristic dataset.

[0012] Furthermore, in step S2, the key features of the obtained yarn characteristic dataset are the critical thresholds for breaking strength and breaking elongation as core constraints; the fabric structure type is determined based on the yarn breaking strength threshold. If the yarn breaking strength is lower than the preset critical lower limit, a low-tension fabric structure including plain weave and quilted weave is selected; if the yarn breaking elongation is higher than the preset critical upper limit, a double rib structure is selected.

[0013] Furthermore, in step S2, the maximum allowable stretch of the yarn during the weaving process is calculated based on the critical threshold of yarn breaking elongation, and the loop density parameter is set accordingly, with a stretching redundancy of not less than a preset ratio reserved. Based on the yarn fineness parameter and the influence of finishing process shaping and fulling on weight, the fabric design weight parameter is adjusted in combination with the correlation between yarn fineness, loop density and fabric width coefficient to offset the weight deviation that may occur in the finishing process.

[0014] Furthermore, in step S3, an initial parameter database is constructed that links yarn characteristics, fabric design, finishing processes, and equipment parameters, clarifying the corresponding technical logic between each parameter; a basic yarn feeding speed matching the yarn fineness is retrieved from the database; if the detected yarn abrasion resistance threshold is lower than a preset standard, several levels are divided according to the degree to which the yarn abrasion resistance threshold is lower than the preset standard, and a corresponding yarn feeding speed reduction ratio is set for each level, and the retrieved basic yarn feeding speed is reduced proportionally; a basic stitch length matching the yarn hairiness index is retrieved, and the stitch length is adjusted by amplifying it according to the ratio of the basic stitch length plus the shrinkage compensation coefficient, combined with the transverse shrinkage rate parameter of the finishing process; the basic tensile tension is determined with 80% of the detected yarn breaking strength critical threshold as the upper limit; if the finishing process is acid-base dyeing with pH < 5 or pH > 8, the tensile tension is reduced.

[0015] Furthermore, in step S4, the loop density sensor built into the knitting equipment is activated to collect loop uniformity and loop length deviation, and the yarn tension sensor collects real-time tension values. The data collection frequency is set to once every 10 rows of knitting to form a real-time monitoring dataset. If the detected loop density deviation exceeds ± the allowable deviation range, the yarn feeding speed is adjusted according to the logic of the deviation value plus the speed adjustment coefficient. If the detected yarn tension fluctuation exceeds ± the allowable fluctuation range set based on the basic tension, the tension is adjusted according to the logic of the fluctuation value plus the tension adjustment coefficient. The key parameters of the subsequent finishing process, namely the setting temperature and dyeing pH, are obtained. If the setting temperature is higher than the preset threshold, the tension is reduced in advance according to the preset ratio. If the dyeing pH deviates from the neutral range, the yarn feeding speed is adjusted additionally. A fixed correction frequency is set to perform a comprehensive correction once per preset number of sweaters produced, based on the production batch size. If the finishing process parameters, such as temperature and pH, change, a temporary correction is immediately triggered.

[0016] Furthermore, in step S4, if the detected coil density deviation exceeds the ± allowable deviation range, the yarn feeding speed is adjusted according to the logic of the deviation value plus the speed adjustment coefficient. The adjustment formula is as follows: ,in, This is the adjusted yarn feeding speed. It is the basic yarn feeding speed for database calls. It is the real-time monitoring of coil density deviation. It is the yarn feeding speed adjustment coefficient. It is the deviation of the pH value from the neutral value during the dyeing process. The pH value affects the adjustment coefficient.

[0017] Furthermore, in step S4, if the setting temperature is higher than a preset threshold, the tensile tension is reduced in advance by a preset ratio, and the adjustment formula is as follows: ,in, It is the adjusted tensile tension. The basic tensile tension is determined by the database. It is the amount of yarn tension fluctuation monitored in real time. It is the tension adjustment coefficient. It is the difference between the shaping process temperature and the preset threshold. It is the temperature effect adjustment coefficient.

[0018] Furthermore, in step S5, after the finishing process is completed, a dimensional measuring instrument is used to detect the transverse and longitudinal dimensional change rates of the finished product, a tensile strength testing machine is used to detect the breaking strength retention rate of the finished yarn, and a color fastness tester is used to detect the color fastness of the finished product to reflect the influence of acid and alkali dyeing on yarn performance. The finished product performance test data is compared one-to-one with the fabric design parameters (size, weight), initial equipment parameters, and dynamic correction parameters to locate and adapt deviations. For the deviations, the corresponding parameters in the associated database are adjusted: if the dimensional shrinkage rate exceeds the standard, the needle pitch compensation coefficient is increased; if the strength retention rate is lower than the preset value, the upper limit ratio of the tension is reduced. After each production batch is completed, the yarn characteristic data, process parameters, finished product test data, and parameter library adjustment content are recorded to complete one database iteration update.

[0019] Compared with existing technologies, this method for designing and optimizing knitting equipment parameters to adapt to sweater yarn materials has the following advantages:

[0020] I. This invention constructs an initial parameter database linking yarn characteristics, fabric design, finishing processes, and equipment parameters, clarifying the corresponding technical logic between each parameter. This provides a basis for setting initial parameters for knitting equipment. By calling basic parameters that match yarn characteristics from the database and making targeted adjustments in conjunction with finishing process parameters, it effectively avoids problems such as yarn damage and unstable fabric quality caused by unreasonable parameter settings. This improves the accuracy and rationality of initial parameter settings, reduces debugging costs, and enhances production efficiency and product quality.

[0021] Second, this invention utilizes the built-in sensors of the equipment to collect real-time data on coil density and yarn tension during the knitting process. Corrections are triggered according to preset frequencies and changes in finishing processes. By monitoring coil uniformity, length deviation, and yarn tension fluctuations in real time, problems in the production process can be detected promptly. Based on the deviation and fluctuation values, the feeding speed and tension are dynamically adjusted according to corresponding logic to ensure the stability of the production process. Simultaneously, considering the key parameters of subsequent finishing processes, the equipment parameters are pre-adjusted, effectively avoiding parameter mismatch problems caused by the influence of finishing processes on the fabric, thus improving parameter stability.

[0022] Other advantages, objectives and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination or study, or may be learned from the practice of the invention. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0024] Figure 1 A flowchart illustrating the design and knitting equipment parameter optimization method for adapting to a type of sweater yarn material;

[0025] Figure 2 A flowchart of the initial parameter setting steps for a knitting equipment design and knitting equipment parameter optimization method for adapting to a type of sweater yarn material;

[0026] Figure 3 This is a flowchart illustrating the dynamic calibration steps of a design method for adapting knitting yarn materials to knitting equipment parameters, and a method for optimizing knitting equipment parameters. Detailed Implementation

[0027] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided below.

[0028] This invention provides a design method for adapting knitting yarn materials to sweaters and a method for optimizing knitting equipment parameters. During the yarn testing stage, various specialized testing devices are used to obtain data on the yarn's basic characteristics, critical mechanical thresholds, surface properties, and acid / alkali resistance through standardized experiments, forming a complete yarn characteristic dataset. Based on the test results, fabric design parameters are matched. The fabric structure is determined according to the yarn breaking strength threshold, the loop density is set according to the breaking elongation threshold with reserved stretching redundancy, the design weight is adjusted in conjunction with the influence of finishing weight, and the initial parameters of the knitting equipment are set in conjunction with the finishing process, constructing a database of associated initial parameters. The yarn feeding speed, needle pitch, and tension are adjusted according to the yarn abrasion resistance threshold, the lateral shrinkage rate of finishing, and acid / alkali dyeing processes. During knitting, data is collected in real time by sensors, and corrections are triggered according to preset frequencies and changes in finishing processes to achieve dynamic adjustment of equipment parameters. After the finishing process is completed, the performance of the finished product is tested, the deviation of the previous parameter positioning is compared, the database parameters are adjusted, and iterative updates are completed. This achieves coordinated adaptation of fabric design, equipment parameters, and finishing processes, meeting the technical requirements of sweater production for process precision and stability.

[0029] This invention provides a design method for adapting sweater yarn materials and a method for optimizing knitting equipment parameters, such as... Figure 1 As shown, the method includes the following specific steps:

[0030] S1: Using specialized testing equipment, through standardized tensile tests, standardized abrasion resistance tests and special tests, we collect yarn basic properties, critical mechanical thresholds, surface properties and acid and alkali resistance properties, and integrate them to form a yarn property dataset.

[0031] In one embodiment, several standard samples of bio-based PLA / cotton blended yarn are selected. The samples are pre-treated to remove surface impurities and dust, and then placed in a constant temperature and humidity laboratory for a preset equilibration time to ensure yarn performance stability before testing. During testing, a high-precision yarn fineness meter is used to measure the yarn fineness parameters of each sample, and a digital twist meter is used to measure the twist parameters of multiple test sections evenly selected along the yarn length. A fiber composition analyzer is used to confirm that the PLA and cotton composition ratios meet the preset requirements using a chemical dissolution method. Subsequently, following a standardized tensile testing procedure, multiple tensile tests are performed on each sample using an electronic single yarn strength tester. The average value is obtained through the device's built-in data analysis module, and the yarn breaking strength is accurately recorded. The critical threshold for elongation at break was determined. Following a standardized abrasion resistance test procedure, the yarn was fixed to the clamping device of the abrasion resistance testing machine and subjected to reciprocating friction testing in a preset manner until the yarn broke. The critical threshold for abrasion resistance was recorded. The contact test head of the friction coefficient meter was placed against the yarn surface, and the surface friction coefficient and hairiness index were simultaneously measured. Using an acid-base resistance testing device, the yarn samples were immersed in buffer solutions within a preset pH range, soaked in a constant temperature water bath for a preset time, and then removed. After drying and equilibration, the strength retention rate was measured. Finally, all the above test data were classified and organized, outliers were removed, and integrated into a complete characteristic dataset for the bio-based yarn, serving as the core technical basis for subsequent fabric design and equipment parameter setting.

[0032] S2: Using the critical thresholds of breaking strength and breaking elongation in the yarn characteristic dataset as core constraints, determine the fabric structure type, set the loop density and reserve stretching redundancy, and adjust the design weight in combination with the weight influence law of finishing process to offset finishing deviation.

[0033] In one embodiment, using the acquired yarn characteristic dataset as the core constraint, and considering the characteristics of bio-based PLA / cotton blended yarns that combine rigidity and a certain degree of toughness, a plain weave structure is selected by comparing the critical thresholds of yarn breaking strength and breaking elongation with preset critical value ranges. This structure, due to its numerous interlacing points and uniform stress distribution, can effectively adapt to the mechanical properties of PLA / cotton blended yarns, avoiding yarn overload caused by high-tension structures. Based on the critical threshold of breaking elongation, and combined with the mechanical tension fluctuation law generated by the needle bed movement during the weaving process, the maximum allowable stretch of the yarn during the weaving process is calculated. The yarn is measured and the loop density parameters are set accordingly, with a preset stretching redundancy to ensure that the yarn stretching is always within a safe range during the reciprocating motion of the needle bed. At the same time, based on the yarn fineness parameters and the characteristics of the finishing process, the influence of the setting process (PLA fibers need to be set in a specific temperature range to stabilize their shape) on the basis weight is considered. The relationship between yarn fineness, loop density and fabric design width is referenced, and the fabric design basis weight parameters are adjusted. A compensation amount is preset specifically for possible basis weight changes after setting to ensure that the finished basis weight meets the preset design requirements, while also taking into account the warmth and breathability of the sweater.

[0034] S3: Construct an initial parameter database that links yarn characteristics, fabric design, finishing processes, and equipment parameters; adjust the yarn feeding speed based on the yarn abrasion resistance threshold; adjust the needle pitch based on the transverse shrinkage rate of finishing processes; and adjust the tension based on the yarn breaking strength threshold and acid-alkali dyeing process characteristics.

[0035] In one embodiment, such as Figure 2As shown, the process first calls a pre-built database linking yarn characteristics, fabric design parameters, finishing process parameters, and equipment parameters. This database is built based on historical production data of the same type of yarn and compatibility test results of different equipment models, and contains complete parameter correspondence logic. Based on the measured yarn fineness, the database retrieves the basic yarn feeding speed that matches the fineness and plain weave structure. Then, the detected yarn abrasion resistance threshold is compared with the preset PLA / cotton blended yarn abrasion resistance standard in the database. If the abrasion resistance threshold is lower than the preset standard, the basic yarn feeding speed is adjusted downwards according to the abrasion resistance threshold grading-speed adjustment ratio correspondence stored in the database. This adjustment ratio is based not only on the compatibility test between the abrasion resistance characteristics of PLA yarn and the operating characteristics of the knitting equipment, but also on targeted fine-tuning of the needle bed material and needle pitch distribution characteristics of the computerized flat knitting machine used in this case, ensuring that the abrasion resistance between the yarn and the equipment components is minimized after adjustment. The wiping time is reduced to lower the risk of wear. Next, based on the measured yarn hairiness index, the corresponding basic stitch length is retrieved from the database. Combined with the preset transverse shrinkage rate parameter of the reactive dyeing process, the stitch length is adjusted according to the logic of the basic stitch length plus the shrinkage rate compensation coefficient. Considering the actual accuracy requirements of the stitch length adjustment, the adjustment results are processed to ensure compliance. Finally, the basic tension is determined with the preset ratio of the yarn breaking strength critical threshold as the upper limit. Since the pH value of this dyeing process is in the preset acidic range, and PLA fiber is prone to slight strength decay in an acidic environment, the basic tension is adjusted downward according to the tension adjustment rules of the acid-alkali dyeing process in the database, to avoid strength loss of the yarn due to tension superposition in subsequent dyeing. Based on the above adjustments, the initial parameters of the computer flat knitting machine used in this project are finally determined, including yarn feeding speed, stitch length, and tension, and entered into the equipment control system.

[0036] S4: Enable the coil density sensor and yarn tension sensor to collect real-time data at a preset frequency, trigger correction according to fixed frequency and post-processing changes, and optimize yarn feeding speed and tension parameters by combining process deviation adjustment and post-processing prediction adjustment.

[0037] In one embodiment, the built-in coil density sensor and yarn tension sensor of the computerized flat knitting machine are activated. The coil density sensor is installed under the needle bed close to the fabric formation area, and the yarn tension sensor is installed at a key node in the yarn feeding channel to ensure accurate acquisition of core parameters during the knitting process. The data acquisition frequency is set to once per preset number of rows knitted, with multiple data points collected each time and averaged by the equipment control system to avoid random errors from single acquisitions. During production, a fixed-frequency comprehensive calibration is performed after producing a preset number of sweaters according to a preset batch calibration ratio. This calibration frequency is set based on the scale of the current production batch, allowing for timely detection of deviations without excessively impacting production efficiency. Figure 3As shown, when the preset number of sweaters has been produced, there is a deviation between the real-time coil density collected by the coil density sensor and the designed coil density. The equipment control system automatically calls the coil density deviation adjustment logic, analyzes the cause of the deviation, and then precisely adjusts the yarn feeding speed. The adjustment formula is as follows: ,in, This is the adjusted yarn feeding speed. It is the basic yarn feeding speed for database calls. It is the real-time monitoring of coil density deviation. It is the yarn feeding speed adjustment coefficient. It is the deviation of the pH value from the neutral value during the dyeing process. The pH value affects the adjustment coefficient; simultaneously, the real-time tension collected by the yarn tension sensor fluctuates from the initial tension. The system synchronously uses tension adjustment logic to adjust the tension back to ensure that the parameters return to a reasonable range. The adjustment formula is as follows: ,in, It is the adjusted tensile tension. The basic tensile tension is determined by the database. It is the amount of yarn tension fluctuation monitored in real time. It is the tension adjustment coefficient. It is the difference between the shaping process temperature and the preset threshold. This is a temperature-affected adjustment coefficient. During subsequent production, if the temperature of the finishing and setting process exceeds the preset threshold due to process optimization, the equipment control system will immediately trigger a temporary correction upon receiving the process change signal. Based on the post-finishing process prediction adjustment logic, the tension will be lowered in advance to cope with yarn shrinkage that may be caused by high-temperature setting. Throughout the knitting process, fixed and temporary corrections are performed according to the actual production situation. All correction data (including adjustment time, parameters before and after adjustment, and triggering reasons) are recorded in real time in the production log of the equipment control system for easy traceability.

[0038] S5: After finishing, test the finished product's dimensional change rate, strength retention rate, and color fastness performance. Compare the test data with the previous fabric design parameters, equipment initial parameters, and dynamic correction parameters to locate the adaptation deviation and adjust the database parameters. The database is updated once for each production batch.

[0039] In one embodiment, after all finishing processes are completed, finished sweaters from different production periods are randomly selected as test samples according to sampling specifications to ensure representativeness. During testing, a high-precision dimensional measuring instrument is used to measure the dimensional shrinkage rate along the transverse and longitudinal baselines of the finished sweaters. A strength testing machine is used to test the strength of the yarn after disassembly to obtain the breaking strength retention rate. A color fastness tester is used to measure the color fastness to washing and the color fastness to rubbing, respectively, to comprehensively obtain the performance data of the finished product. Subsequently, these test data are compared one by one with the fabric design parameters, equipment initial parameters, and dynamic correction parameters. Not only are deviations from the design values ​​compared, but trend analysis is also performed based on historical data of similar batches to accurately locate adaptation deviations. For example, if the lateral shrinkage rate is close to the preset upper limit, it is mainly related to the setting of the stitch length compensation coefficient; while the strength retention rate meets the preset requirements and has redundancy, indicating that the tension parameter setting is reasonable. Regarding the deviation trend of the lateral shrinkage rate, technicians find the corresponding parameter entries for this type of bio-based PLA / cotton blended yarn in the associated initial parameter database, adjust the stitch length compensation coefficient upwards, and note that the adjustment is to adapt to the lateral shrinkage characteristics of reactive dyeing. Finally, the yarn characteristic dataset, fabric design parameters, equipment initial and calibration parameters, finished product performance test data, and the adjusted stitch length compensation coefficient in the database are completely recorded to form the production technical file for this batch, completing the iterative update of the parameter library. The updated database can be directly used for the subsequent production of sweaters using the same type of bio-based PLA / cotton blended yarn, achieving rapid and accurate parameter setting and reducing the debugging cycle.

[0040] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A method for designing and optimizing knitting equipment parameters to adapt to sweater yarn materials, characterized in that, The method includes the following specific steps: S1: Using specialized testing equipment, through standardized tensile tests, standardized abrasion resistance tests and special tests, we collect yarn basic properties, critical mechanical thresholds, surface properties and acid and alkali resistance properties, and integrate them to form a yarn property dataset. S2: Using the critical thresholds of breaking strength and breaking elongation in the yarn characteristic dataset as core constraints, determine the fabric structure type, set the loop density and reserve stretching redundancy, and adjust the design weight in combination with the weight influence law of finishing process to offset finishing deviation. S3: Construct an initial parameter database that links yarn characteristics, fabric design, finishing processes, and equipment parameters; adjust the yarn feeding speed based on the yarn abrasion resistance threshold; adjust the needle pitch based on the transverse shrinkage rate of finishing processes; and adjust the tension based on the yarn breaking strength threshold and acid-alkali dyeing process characteristics. S4: Enable the coil density sensor and yarn tension sensor to collect real-time data at a preset frequency, trigger correction according to fixed frequency and post-processing changes, and optimize yarn feeding speed and tension parameters by combining process deviation adjustment and post-processing prediction adjustment. S5: After finishing, test the finished product's dimensional change rate, strength retention rate, and color fastness performance. Compare the test data with the previous fabric design parameters, equipment initial parameters, and dynamic correction parameters to locate the adaptation deviation and adjust the database parameters. The database is updated once for each production batch.

2. The method for designing and optimizing knitting equipment parameters for adapting sweater yarn materials according to claim 1, characterized in that, In step S1, a yarn fineness meter, twist meter, electronic single yarn strength meter, abrasion resistance tester, friction coefficient meter, and acid and alkali resistance test device are used as specialized testing equipment. The yarn fineness parameter is measured using the yarn fineness meter, the twist parameter is measured using the twist meter, and the fiber composition and percentage of each component are determined using a component analyzer, forming a basic yarn characteristic dataset. A standardized tensile testing procedure is followed, using the electronic single yarn strength meter to conduct tensile tests and record the critical thresholds for yarn breaking strength and elongation at break. A standardized abrasion resistance testing procedure is followed, using the abrasion resistance tester to conduct tests and record the critical thresholds for yarn abrasion resistance. The surface friction coefficient and hairiness index of the yarn are measured using the friction coefficient meter, and the strength retention rate is measured after immersing the yarn in a pH 4-9 buffer solution using the acid and alkali resistance test device, forming yarn surface and chemical resistance performance data. All data are then integrated into a complete yarn characteristic dataset.

3. The method for designing and optimizing knitting equipment parameters for adapting sweater yarn materials according to claim 1, characterized in that, In step S2, the key features of the obtained yarn characteristic dataset are the critical thresholds for breaking strength and breaking elongation as core constraints. The fabric structure type is determined based on the yarn breaking strength threshold. If the yarn breaking strength is lower than the preset lower threshold, a low-tension fabric structure including plain weave and quilted weave is selected. If the yarn breaking elongation is higher than the preset upper threshold, a double rib structure is selected.

4. The method for designing and optimizing knitting equipment parameters for adapting sweater yarn materials according to claim 1, characterized in that, In step S2, the maximum allowable stretch of the yarn during the weaving process is calculated based on the critical threshold of yarn breaking elongation. The loop density parameter is set accordingly, and a stretching redundancy of not less than a preset ratio is reserved. Based on the yarn fineness parameter and the influence of finishing process shaping and fulling on weight, the fabric design weight parameter is adjusted in combination with the correlation between yarn fineness, loop density and fabric width coefficient to offset the weight deviation that may occur in the finishing process.

5. The method for designing and optimizing knitting equipment parameters for adapting sweater yarn materials according to claim 1, characterized in that, In step S3, an initial parameter database is constructed that links yarn characteristics, fabric design, finishing processes, and equipment parameters, clarifying the corresponding technical logic between each parameter. A basic yarn feeding speed matching the yarn fineness is retrieved from the database. If the detected yarn abrasion resistance threshold is lower than a preset standard, several levels are defined based on the degree to which the yarn abrasion resistance threshold is lower than the preset standard. A corresponding yarn feeding speed reduction ratio is set for each level, and the retrieved basic yarn feeding speed is proportionally reduced. A basic stitch length matching the yarn hairiness index is retrieved, and combined with the transverse shrinkage rate parameter of the finishing process, the stitch length is amplified and adjusted according to the ratio of the basic stitch length plus the shrinkage rate compensation coefficient. The basic tensile tension is determined with 80% of the detected yarn breaking strength critical threshold as the upper limit. If the finishing process is acid-base dyeing with pH < 5 or pH > 8, the tensile tension is reduced.

6. The method for designing and optimizing knitting equipment parameters for adapting sweater yarn materials according to claim 1, characterized in that, In step S4, the loop density sensor built into the knitting equipment is activated to collect loop uniformity and loop length deviation, and the yarn tension sensor collects real-time tension values. The data collection frequency is set to once every 10 rows of knitting to form a real-time monitoring dataset. If the loop density deviation is detected to exceed ± allowable deviation range, the yarn feeding speed is adjusted according to the logic of the deviation value plus the speed adjustment coefficient. If the yarn tension fluctuation is detected to exceed ± allowable fluctuation range set based on the basic tension, the tension is adjusted according to the logic of the fluctuation value plus the tension adjustment coefficient. The key parameters of the subsequent finishing process are obtained: setting temperature and dyeing pH. If the setting temperature is higher than the preset threshold, the tension is reduced in advance according to the preset ratio. If the dyeing pH deviates from the neutral range, the yarn feeding speed is adjusted. A fixed correction frequency is set to perform a comprehensive correction once per preset number of sweaters produced, based on the production batch size. If the finishing process parameters temperature and pH change, a temporary correction is triggered immediately.

7. The method for designing and optimizing knitting equipment parameters for adapting sweater yarn materials according to claim 6, characterized in that, In step S4, if the detected coil density deviation exceeds the ± allowable deviation range, the yarn feeding speed is adjusted according to the logic of the deviation value plus the speed adjustment coefficient. The adjustment formula is as follows: ,in, This is the adjusted yarn feeding speed. It is the basic yarn feeding speed for database calls. It is the real-time monitoring of coil density deviation. It is the yarn feeding speed adjustment coefficient. It is the deviation of the pH value from the neutral value during the dyeing process. The pH value affects the adjustment coefficient.

8. The method for designing and optimizing knitting equipment parameters for adapting sweater yarn materials according to claim 6, characterized in that, In step S4, if the setting temperature is higher than a preset threshold, the tensile tension is reduced in advance by a preset ratio. The adjustment formula is as follows: ,in, It is the adjusted tensile tension. The basic tensile tension is determined by the database. It is the amount of yarn tension fluctuation monitored in real time. It is the tension adjustment coefficient. It is the difference between the shaping process temperature and the preset threshold. It is the temperature effect adjustment coefficient.

9. The method for designing and optimizing knitting equipment parameters for adapting sweater yarn materials according to claim 1, characterized in that, In step S5, after the finishing process is completed, a dimensional measuring instrument is used to detect the transverse and longitudinal dimensional change rates of the finished product, a tensile strength testing machine is used to detect the breaking strength retention rate of the finished yarn, and a color fastness tester is used to detect the color fastness of the finished product to reflect the influence of acid and alkali dyeing on yarn performance. The finished product performance test data is compared one-to-one with the fabric design parameters (dimensions, weight), initial equipment parameters, and dynamic correction parameters to identify and adapt deviations. For the deviations, the corresponding parameters in the associated database are adjusted: if the dimensional shrinkage rate exceeds the standard, the needle pitch compensation coefficient is increased; if the strength retention rate is lower than the preset value, the upper limit of the tension is reduced. After each production batch is completed, the yarn characteristic data, process parameters, finished product test data, and parameter library adjustment content are recorded to complete one database iteration update.

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