Gradient tension control production method and system for anti-pilling cashmere yarn

Abstract

The application discloses a gradient tension control production method and system of anti-pilling cashmere yarn and relates to the technical field of tension control equipment. The method comprises the following steps: determining a gradient tension pulse according to the constitutive relation of cashmere yarn, deploying a gradient limiter by performing dynamic and static simulation; determining a spiral tension field for each process node; performing dynamic and static over-limit judgment on the spiral tension field by the auxiliary gradient limiter, determining a fiber entanglement state by performing fiber slip characteristic frequency analysis if any item does not meet the requirement, triggering a control decision maker, performing static decision based on uniformity for fiber density and structure, performing dynamic decision of fiber structure damage and friction coefficient for the slip mode, and determining pre-control parameters; and adjusting and managing the yarn guide according to the pre-control parameters. The technical problem that the product quality is unstable due to inaccurate tension control in the prior art is solved, and the technical effect that the product quality stability is improved through gradient tension control is achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of tension control equipment, in particular to a gradient tension control production method and system for anti-pilling cashmere yarn. BACKGROUND

[0002] As a textile raw material, cashmere yarn is widely used in clothing and home textile products due to its delicate softness, warmth and lightness. However, during the spinning and weaving process, due to the strong softness and small friction coefficient of cashmere fibers, they are prone to slip, entangle and break under the action of tension fluctuation, resulting in poor yarn structure uniformity and further causing serious pilling of the fabric, affecting product quality and service life. In the prior art, tension control is mostly constant tension or rough segmented tension adjustment, which cannot fully consider the constitutive property and stress state of fibers at different process stages, resulting in inaccurate tension control and insufficient product quality stability. Especially under long-period continuous processing conditions, the yarn tension fluctuation is more obvious due to the influence of heat, stress and other factors, further aggravating the fiber damage and pilling problem. SUMMARY

[0003] The present application provides a gradient tension control production method and system for anti-pilling cashmere yarn, which solves the technical problem of inaccurate tension control in the prior art leading to unstable product quality.

[0004] In a first aspect, the present application provides a gradient tension control production method for anti-pilling cashmere yarn, which comprises:

[0005] Based on the constitutive relationship of cashmere yarn, gradient tension pulses are determined for the whole processing cycle, and gradient limiters are deployed through dynamic and static simulation, wherein the thermal tension fluctuation and the force-induced tension fluctuation are additional analog quantities; the process stages of cashmere yarn are divided, and distributed sampling is performed through eddy current displacement sensors for each process node to determine the spiral tension field; the gradient limiters are assisted to perform dynamic and static out-of-limit judgment on the spiral tension field, if any item does not meet the requirements, the fiber entanglement state is determined through fiber slip characteristic frequency analysis, the control decision maker is triggered, the static decision based on uniformity is made for fiber density and structure, the dynamic decision of fiber structure damage and friction coefficient is made for slip mode, and the pre-control parameters are determined; and the yarn guide is regulated and managed according to the pre-control parameters.

[0006] In a second aspect, the present application provides a gradient tension control production system for anti-pilling cashmere yarn, which comprises:

[0007] Deployment module: according to the constitutive relation of cashmere yarn, gradient tension pulse is determined for the whole processing cycle, gradient limiters are deployed through dynamic and static simulation, and the thermal tension fluctuation and the force-induced tension fluctuation are additional analog quantities; Tension field determination module: the process stages of cashmere yarn are divided, distributed sampling is performed through eddy current displacement sensors for each process node, and the spiral tension field is determined; Determination module: assist the gradient limiters to determine the dynamic and static over-limit of the spiral tension field, if any item does not meet, the fiber entanglement state is determined through fiber slip characteristic frequency analysis, the control decision maker is triggered, the static decision based on uniformity is made for the fiber density and structure, the dynamic decision of fiber structure damage and friction coefficient is made for the slip mode, and the pre-control parameter is determined; Control and management module: according to the pre-control parameter, the yarn guide is controlled and managed.

[0008] One or more technical solutions provided in the present application have at least the following technical effects or advantages:

[0009] First, according to the constitutive relation of cashmere yarn, gradient tension pulse is determined for the whole processing cycle, gradient limiters are deployed through dynamic and static simulation, and the thermal tension fluctuation and the force-induced tension fluctuation are additional analog quantities. Next, the process stages of cashmere yarn are divided, distributed sampling is performed through eddy current displacement sensors for each process node, and the spiral tension field is determined. Then, assist the gradient limiters to determine the dynamic and static over-limit of the spiral tension field, if any item does not meet, the fiber entanglement state is determined through fiber slip characteristic frequency analysis, the control decision maker is triggered, the static decision based on uniformity is made for the fiber density and structure, the dynamic decision of fiber structure damage and friction coefficient is made for the slip mode, and the pre-control parameter is determined. Finally, according to the pre-control parameter, the yarn guide is controlled and managed. The technical problem of unstable product quality caused by inaccurate tension control in the prior art is solved, and the technical effect of improving product quality stability through gradient tension control is achieved. BRIEF DESCRIPTION OF DRAWINGS

[0010] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0011] Figure 1 The gradient tension control production method flowchart of anti-pilling cashmere yarn provided by the embodiment of the present application;

[0012] Figure 2 The gradient tension control production system structure schematic diagram of anti-pilling cashmere yarn provided by the embodiment of the present application.

[0013] Explanation of reference signs: deployment module 11, tension field determination module 12, determination module 13, regulation management module 14. DETAILED DESCRIPTION

[0014] The present application provides a gradient tension control production method and system for anti-pilling cashmere yarn, which solves the technical problem of unstable product quality caused by inaccurate tension control in the prior art.

[0015] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of protection of the present application.

[0016] It should be noted that the terms "comprising" and "having" are intended to cover non-exclusive inclusion, for example, a process, method, system, product or server comprising a series of steps or units does not have to be limited to only those steps or units clearly listed, but can include other steps or modules that are not clearly listed or inherent to these processes, methods, products or devices.

[0017] Embodiment one, as shown in the present application provides a gradient tension control production method for anti-pilling cashmere yarn, wherein the method comprises: Figure 1 The gradient tension pulse is determined for the whole processing cycle according to the constitutive relation of cashmere yarn, and the gradient limiter is deployed by performing dynamic and static simulation, wherein the thermal tension fluctuation and the force-induced tension fluctuation are additional analog quantities.

[0018] The constitutive relation of cashmere yarn refers to the stress-strain correspondence and the response characteristics of fiber internal slip and entanglement under the conditions of stress and heat.

[0019]

[0020] ​The constitutive relation based on cashmere yarn is used to quantize the tension requirement of yarn in different process stages such as spinning, twisting, drafting and winding, and a gradient tension pulse curve is formed for the whole cycle of processing. The gradient tension pulse is introduced into the visual simulation platform to perform static and dynamic lightweight finite element simulation respectively. The static simulation is used to determine the steady-state tension limiting threshold in each process stage, and the dynamic simulation is used to determine the dynamic tension limiting condition which changes with the fluctuation of processing speed, fiber friction and external disturbance. In the above simulation process, the thermal tension fluctuation and the force-induced tension fluctuation are introduced as additional simulation quantities, that is, the tension response of the yarn under the action of heat and mechanical disturbance is calculated by coupling the temperature field simulation and vibration impact simulation to reflect the stress environment of the yarn in actual production. Finally, according to the superposition result of the static limiting condition and the dynamic limiting condition, a gradient limiter is constructed and deployed, which can monitor and dynamically limit the yarn tension in the production process to ensure that the yarn is in a reasonable tension range in each process stage.

[0021] Further, deploying the gradient limiter comprises:

[0022] In the whole cycle of production, the tension requirement based on the process stage is determined as the gradient tension pulse; for the gradient tension pulse, the visual simulation platform is connected to perform lightweight static tension simulation for each process stage to determine the static limiting condition; lightweight dynamic tension simulation is performed to determine the dynamic limiting condition; and the gradient limiter is constructed according to the static limiting condition and the dynamic limiting condition.

[0023] Firstly, based on the whole cycle of cashmere yarn production, the target tension range required by each process stage is determined respectively by combining the process characteristics of different process stages such as spinning, twisting, drafting and winding, and the target tension range is subjected to stage-by-stage superposition and smoothing to form a continuously changing gradient tension pulse curve. Then, the gradient tension pulse is introduced into the connected visual simulation platform to perform lightweight static tension simulation for different process stages to establish a tension response model of the yarn under steady-state stress condition and determine the corresponding static limiting condition. At the same time, based on the gradient tension pulse, lightweight dynamic tension simulation is further performed to establish a tension response model of the yarn under dynamic processing state by introducing speed disturbance, tension fluctuation and external environmental factors, and determine the corresponding dynamic limiting condition. Finally, the static limiting condition and the dynamic limiting condition are fused and comprehensively analyzed to construct a gradient limiter suitable for the whole cycle of production for real-time limiting monitoring and dynamic adjustment of the yarn tension in actual production process to ensure the continuity and accuracy of tension control.

[0024] The process stages of cashmere yarn are divided, and the spiral tension field is determined by distributed sampling through eddy current displacement sensors for each process node.

[0025] In the production process of cashmere yarn, according to the actual process flow of yarn processing, the whole production cycle is divided into several process stages, including spinning, twisting, drafting, winding and other key nodes, so as to ensure that the stress characteristics of each stage can be independently identified and monitored.

[0026] For each process node divided, eddy current displacement sensors are arranged at multiple distributed positions on the yarn transmission path to distribute sampling of the small displacement, deviation and tension change of the yarn in the running process, and to obtain real-time displacement response data at different point positions. Based on the distributed sampling results, in combination with the forces acting on the yarn in the movement process, such as guide rollers, tension wheels and friction interfaces, a spiral tension field of the yarn in the spatial distribution is constructed to describe the tension distribution state of the yarn under the joint action of longitudinal drafting and transverse deviation.

[0027] The gradient limiter assists in performing dynamic and static over-limit judgment on the spiral tension field. If any of the conditions is not met, the fiber entanglement state is determined by analyzing the fiber slip characteristic frequency, the control decision maker is triggered, the static decision based on uniformity is made for the fiber density and structure, the dynamic decision of fiber structure damage and friction coefficient is made for the slip mode, and the pre-control parameters are determined.

[0028] After the spiral tension field is determined, the gradient limiter is used to perform dynamic and static over-limit judgment on the spiral tension field. The static over-limit judgment is used to check whether the tension of the yarn under the steady state condition exceeds the preset static limit value, and the dynamic over-limit judgment is used to check whether the tension of the yarn under the action of speed disturbance, friction impact and external environment fluctuation exceeds the dynamic limit value. If the judgment results meet the limit conditions, the yarn maintains in a stable state and does not need to perform further analysis; if any of the conditions is not met, the fiber slip characteristic frequency analysis stage is entered. Specifically, the time sequence signal of the spiral tension field is decomposed in the frequency domain, the fiber slip characteristic frequency is extracted, the slip and entanglement state of the internal fiber of the yarn are identified, and the fiber entanglement state judgment result is obtained. Then the control decision maker is triggered to perform a double-channel decision process. The static decision channel takes the fiber density and structure uniformity as the core decision quantity to perform distributed detection and regulation on the uniformity of the overall structure of the yarn. The dynamic decision channel determines and corrects the mechanical stability of the yarn under dynamic disturbance based on the fiber structure damage and friction coefficient change under the slip mode, and in combination with the temperature and vibration constraint conditions. Finally, the control decision maker fuses the results of the static decision and the dynamic decision to output the pre-control parameters, which are used as the basis for subsequent tension regulation of the guide roller to realize accurate management of the yarn tension and effectively inhibit fiber damage and pilling.

[0029] Further, the gradient limiter assists in performing dynamic and static over-limit judgment on the spiral tension field, including:

[0030] With the first process stage of the production process, the dynamic and static limiting conditions of the first process stage in the gradient limiter are activated, initialized as the first limiter; according to the eddy current displacement sensor, distributed point collection is performed to construct a spiral tension field; based on the spiral tension field, first-order static judgment and second-order dynamic judgment based on the first limiter are executed to determine the limiting judgment result.

[0031] When the auxiliary gradient limiter performs dynamic and static over-limit judgment on the spiral tension field, first, with the production process entering the first process stage, the dynamic and static limiting conditions corresponding to the first process stage in the gradient limiter are automatically activated, and the limiting conditions are initialized as the first limiter for tension monitoring and constraint in this stage. Subsequently, through the eddy current displacement sensor arranged on the yarn transmission path, the displacement changes of multiple distributed points are collected in real time to obtain the small displacement response data of the yarn in the running process. Based on the distributed point collection result, combined with the stress characteristics of the yarn under the action of longitudinal drafting and transverse disturbance, a spiral tension field is constructed to represent the tension distribution of the yarn in space. Finally, according to the spiral tension field signal, the static limiting condition and the dynamic limiting condition in the first limiter are called respectively to execute first-order static judgment and second-order dynamic judgment. The first-order static judgment is used to judge whether the yarn is over-limit under stable stress, and the second-order dynamic judgment is used to check whether the yarn is over-limit under disturbance and fluctuation environment. According to the results of the two judgments, the limiting judgment conclusion is formed comprehensively to provide a basis for subsequent fiber slip frequency analysis and control decision trigger.

[0032] Further, if the limiting judgment result meets the dynamic and static limiting conditions, the subsequent analysis process is terminated; if the limiting judgment result exists for any item not to meet, the control decision maker is triggered.

[0033] When the limiting judgment result shows that the yarn meets the dynamic and static limiting conditions in the current process stage, the system determines that the yarn tension is within the stable controlled range, and at this time, no additional analysis and intervention is needed, and the subsequent analysis process is terminated to reduce the system calculation burden and ensure the production efficiency.

[0034] If the limiting judgment result exists for any item not to meet, that is, the yarn has over-limit situation under static stable condition or dynamic disturbance condition, the system automatically triggers the control decision maker. After the control decision maker is started, it will further analyze the fiber state combined with the spiral tension field data collected in the previous sequence, and enter the entangled state recognition and dynamic and static collaborative decision process based on the fiber slip characteristic frequency, so as to generate pre-control parameters for tension control, realize dynamic correction and feedback control of abnormal tension state.

[0035] Further, the fiber entangled state is determined by performing fiber slip characteristic frequency analysis to trigger the control decision maker, including:

[0036] According to the spiral tension field, the fiber slip characteristic frequency is extracted, the fiber entanglement state is determined, and the spiral tension field is one-to-one corresponding to the distributed point of the eddy current displacement sensor; for the fiber entanglement state, the dynamic and static cooperative decision of the auxiliary control decision maker is executed to determine the pre-control parameter.

[0037] When the dynamic and static state of the spiral tension field exceeds the limit determination result exists not satisfied item, the system enters the fiber slip characteristic frequency analysis stage to determine the fiber entanglement state and trigger the control decision maker. Specifically, based on the distributed point sampling data of the eddy current displacement sensor, the time sequence change signal of the spiral tension field is frequency spectrum decomposed and characteristic extracted, and the slip characteristic frequency of the yarn at different positions is identified. The fiber slip characteristic frequency can reflect the relative slip degree of the internal fiber of the yarn under uneven stress or friction disturbance, and by comparing and analyzing the frequency characteristics of each point, it is further determined whether the fiber at the corresponding point is in the entangled state, so as to realize the one-to-one corresponding mapping of the fiber entangled state and the distributed point of the eddy current displacement sensor. Subsequently, the identified fiber entangled state is taken as the input quantity, and the control decision maker is triggered to start the decision-making process. The control decision maker respectively analyzes the yarn tension state from the static and dynamic decision channels: the static channel takes the fiber density and structure uniformity as the judgment basis, and the dynamic channel combines the fiber structure damage under the slip mode and the friction coefficient for real-time correction. Finally, the static and dynamic decision results are cooperatively fused in the control decision maker, and the pre-control parameter is outputted for controlling the guide to implement accurate tension feedback regulation, thereby effectively improving the fiber stress state.

[0038] Further, before triggering the control decision maker, the construction of the control decision maker includes:

[0039] The static decision channel is deployed with the uniformity of the fiber density and structure as the first self-attention decision quantity. The dynamic decision channel is deployed with the fiber structure damage under the slip mode as the second self-attention decision quantity, and the friction coefficient based on the fiber entanglement degree as the third self-attention decision quantity. The static decision channel and the dynamic decision channel are parallel as the control decision maker, and the control parameter of the guide is outputted.

[0040] Specifically, the fiber density and the yarn structure uniformity are taken as the first self-attention decision quantity, which is used to represent whether there is uneven fiber distribution or local density fluctuation in the overall processing of the yarn, thereby establishing a static decision channel, which is mainly responsible for the inspection and correction of the uniformity of the yarn under stable tension; the fiber structure damage under the slip mode (such as pilling rate, breakage, etc.) is taken as the second self-attention decision quantity, and the friction coefficient calculated based on the fiber entanglement degree is taken as the third self-attention decision quantity, both of which constitute a dynamic decision channel, which is mainly used for real-time analysis and control of the structure damage and friction changes caused by fiber slip, friction disturbance and external environmental influence during the operation of the yarn; the static decision channel and the dynamic decision channel are deployed in a parallel manner to form a complete control decision maker, which can make multi-parameter fusion judgment on the state of the yarn in different dimensions, and output the control parameters of the guide device according to the judgment result as the basis for subsequent tension feedback adjustment and structure correction, so as to ensure the force balance and structure stability of cashmere yarn in the whole cycle processing.

[0041] Further, the auxiliary control decision maker performs dynamic and static cooperative decision of tension feedback adjustment to determine the pre-control parameter, including:

[0042] The fiber entanglement state is introduced into the control decision maker, and the distributed inspection evaluation and control decision of the first self-attention decision quantity are performed according to the static decision channel to determine the first control parameter; the distributed inspection and control decision of the second self-attention decision quantity and the third self-attention decision quantity are performed in parallel according to the dynamic decision channel to determine the second control parameter and the third control parameter; the extreme values of each mapping parameter are taken according to the first control parameter, the second control parameter and the third control parameter to determine the pre-control parameter.

[0043] Specifically, the fiber entanglement state is introduced into the control decision maker, and the first self-attention decision quantity with fiber density and structure uniformity as the core is called in the static decision channel to inspect and evaluate the structure uniformity of the yarn at distributed points, and the static control decision is made combined with the evaluation result to obtain the first control parameter. In the dynamic decision channel, the second self-attention decision quantity and the third self-attention decision quantity are called in parallel, wherein the second self-attention decision quantity is based on the fiber structure damage feature under the slip mode, and the third self-attention decision quantity is based on the friction coefficient corresponding to the fiber entanglement degree, both of which perform distributed inspection on the stress and damage state of the yarn under dynamic disturbance environment, and accordingly perform corresponding dynamic control decision to obtain the second control parameter and the third control parameter respectively. The first control parameter, the second control parameter and the third control parameter are multi-dimensionally fused, the extreme values of the numerical values of each parameter in different mapping spaces are screened and combined (for example, some maximum parameters, that is, the larger the control is, the better, take the maximum value, some minimum parameters take the minimum value), and the pre-control parameter is determined comprehensively.

[0044] Further, the distributed detection and regulation decision of the second self-attention decision quantity and the third self-attention decision quantity is executed in parallel, including:

[0045] The first temperature data and the second vibration data are determined by combining the temperature sensor and the vibration sensor; the first dynamic condition of the thermal tension fluctuation is determined according to the first temperature data; the second dynamic condition of the force-induced tension fluctuation is determined according to the second vibration data; and the first dynamic condition and the second dynamic condition are introduced into the dynamic decision channel as decision constraint conditions.

[0046] In the process of executing the distributed detection and regulation decision of the second self-attention decision quantity and the third self-attention decision quantity in parallel, first, the multi-source data under the processing environment and the yarn running state are collected in real time by the temperature sensor and the vibration sensor arranged on the production path, wherein the temperature sensor is used to obtain the thermal effect data generated by the yarn in the processes such as friction, drafting and winding, to obtain the first temperature data; the vibration sensor is used to capture the dynamic response signal of the yarn under the action of tension fluctuation, mechanical disturbance and equipment vibration, to obtain the second vibration data. Subsequently, the tension variation law of the yarn under the action of heat is calculated according to the first temperature data, combined with the yarn constitutive relation and thermodynamic parameters, to determine the first dynamic condition of the thermal tension fluctuation; and then the second dynamic condition of the force-induced tension fluctuation is determined according to the second vibration data, combined with the frequency spectrum analysis and vibration amplitude characteristics, to reflect the tension fluctuation characteristics of the yarn under the action of external force disturbance. Finally, the first dynamic condition and the second dynamic condition are introduced into the dynamic decision channel as the constraint conditions of the second self-attention decision quantity (fiber structure damage) and the third self-attention decision quantity (friction coefficient), so that the dynamic channel can consider the coupling effect of thermal disturbance and force disturbance when executing the distributed detection and regulation decision, thereby outputting the dynamic regulation parameters more in line with the actual working conditions.

[0047] The yarn guide is regulated and managed according to the pre-regulation parameters.

[0048] After obtaining the pre-regulation parameters, the pre-regulation parameters are used as the control input of the yarn guide operation to regulate and manage the yarn guide. Specifically, the static control quantity reflecting the fiber uniformity in the pre-regulation parameters is used to adjust the guide angle and tension distribution path of the yarn guide to ensure the force balance of the yarn in the running process; and the dynamic control quantity reflecting the fiber structure damage and the friction coefficient in the pre-regulation parameters is used to real-time correct the yarn feeding speed, yarn guide spacing and yarn guide pressure of the yarn guide, so as to offset the tension fluctuation caused by the slip mode and friction disturbance.

[0049] Further, initialization of the gradient limiters is performed for each process stage in the whole production cycle, and the initialized gradient limiters are cooperated with the control decision maker to perform dynamic and static judgment and control decision based on the spiral tension field to feedback regulate the dynamic tension of the yarn guide.

[0050] For each process stage in the whole production cycle of cashmere yarn, initialization of the gradient limiters is performed, so that the corresponding static and dynamic limit conditions are established for each process stage, thereby forming a limit monitoring unit corresponding to each process stage. Subsequently, the initialized gradient limiters are cooperated with the control decision maker to synchronously receive data collected by the eddy current displacement sensor, temperature sensor and vibration sensor during the production process, to construct a spiral tension field, and to perform real-time dynamic and static judgment based on the spiral tension field. When the judgment result shows that the tension exceeds the limit condition, the control decision maker is triggered to start the cooperative decision of the static and dynamic channels, and the corresponding pre-control parameters are output. Finally, the yarn guide is dynamically feedback regulated according to the pre-control parameters, including real-time adjustment of the guide angle, yarn feeding speed and yarn guide spacing of the yarn guide, so as to maintain the balance and stability of the yarn tension in the whole cycle, thereby avoiding fiber slippage, entanglement and breakage, and effectively improving the anti-pilling performance and quality stability of cashmere yarn products.

[0051] In summary, the embodiments of the present application have at least the following technical effects:

[0052] First, based on the constitutive relation of cashmere yarn, gradient tension pulses are determined for the whole production cycle, and gradient limiters are deployed through dynamic and static simulation, wherein the thermal tension fluctuation and the force tension fluctuation are additional simulation quantities. Then, the process stages of cashmere yarn are divided, and distributed sampling is performed by the eddy current displacement sensor for each process node to determine the spiral tension field. Then, the gradient limiters assist in the dynamic and static over-limit judgment of the spiral tension field. If any item does not meet the requirement, fiber entanglement state is determined through fiber slippage characteristic frequency analysis, the control decision maker is triggered, static decision based on uniformity is made for fiber density and structure, dynamic decision of fiber structure damage and friction coefficient is made for slippage mode, and pre-control parameters are determined. Finally, the yarn guide is regulated and managed according to the pre-control parameters. The technical problem of inaccurate tension control in the prior art leading to unstable product quality is solved, and the technical effect of improving product quality stability through gradient tension control is achieved.

[0053] Embodiment two, based on the same inventive concept as the gradient tension control production method of anti-pilling cashmere yarn in the foregoing embodiments, as shown in Figure 2 The present application provides a gradient tension control production system for anti-pilling cashmere yarn, wherein the system comprises:

[0054] The deployment module 11: with the constitutive relation of cashmere yarn, determine the gradient tension pulse for the whole processing cycle, through dynamic and static simulation, deploy the gradient limiter, wherein the thermal tension fluctuation and the force-induced tension fluctuation are additional analog quantities; the tension field determination module 12: divide the process stage of cashmere yarn, for each process node, through the distributed sampling of eddy current displacement sensor, determine the spiral tension field; the determination module 13: assist the gradient limiter, make dynamic and static out-of-limit judgment on the spiral tension field, if any item does not meet, through fiber slip characteristic frequency analysis to determine the fiber entanglement state, trigger the control decision maker, make static decision based on uniformity for fiber density and structure, make dynamic decision of fiber structure damage and friction coefficient for slip mode, determine the pre-control parameter; the control management module 14: according to the pre-control parameter, control and manage the yarn guide.

[0055] Further, the deployment module 11 is used to execute the following method:

[0056] In the whole production cycle, determine the tension demand based on the process stage as the gradient tension pulse; for the gradient tension pulse, through the connection of visual simulation platform, execute lightweight static tension simulation for each process stage, determine the static limiting condition; execute lightweight dynamic tension simulation, determine the dynamic limiting condition; according to the static limiting condition and the dynamic limiting condition, build the gradient limiter.

[0057] Further, the determination module 13 is used to execute the following method:

[0058] With the first process stage of production process, the dynamic and static limiting conditions of the first process stage in the gradient limiter are activated, and the first limiter is initialized; according to the eddy current displacement sensor, distributed point collection is carried out, and the spiral tension field is constructed; according to the spiral tension field, first-order static judgment and second-order dynamic judgment based on the first limiter are executed, and the limiting judgment result is determined.

[0059] Further, the determination module 13 is used to execute the following method:

[0060] If the limiting judgment result meets the dynamic and static limiting conditions, terminate the subsequent analysis process; if the limiting judgment result exists any item that does not meet, trigger the control decision maker.

[0061] Further, the determination module 13 is used to execute the following method:

[0062] According to the spiral tension field, extract the fiber slip characteristic frequency to determine the fiber entanglement state, wherein the fiber entanglement state and the distributed point of eddy current displacement sensor are one-to-one correspondence; for the fiber entanglement state, assist the control decision maker to execute the dynamic and static cooperative decision of tension feedback adjustment, and determine the pre-control parameter.

[0063] Further, the determination module 13 is configured to perform the following method:

[0064] The static decision channel is deployed based on the first self-attention decision quantity of the uniformity of the fiber density and structure, the dynamic decision channel is deployed based on the second self-attention decision quantity of the fiber structure damage in the slip mode and the third self-attention decision quantity of the friction coefficient based on the fiber entanglement degree, and the static decision channel and the dynamic decision channel are parallel as the control decision maker, wherein the control parameter of the yarn guide is output.

[0065] Further, the determination module 13 is configured to perform the following method:

[0066] The fiber entanglement state is introduced into the control decision maker, the distributed detection evaluation and regulation decision of the first self-attention decision quantity is performed according to the static decision channel, the first regulation parameter is determined, the distributed detection and regulation decision of the second self-attention decision quantity and the third self-attention decision quantity is performed in parallel according to the dynamic decision channel, the second regulation parameter and the third regulation parameter are determined, and the extreme value of each mapping parameter is taken according to the first regulation parameter, the second regulation parameter and the third regulation parameter, and the pre-regulation parameter is determined by combination.

[0067] Further, the determination module 13 is configured to perform the following method:

[0068] The first temperature data and the second vibration data are determined by combining the temperature sensor and the vibration sensor, the first dynamic condition of the thermal tension fluctuation is determined according to the first temperature data, the second dynamic condition of the force-induced tension fluctuation is determined according to the second vibration data, and the first dynamic condition and the second dynamic condition are introduced into the dynamic decision channel as the decision constraint condition.

[0069] Further, the regulation and management module 14 is configured to perform the following method:

[0070] The initialization of the gradient limiter is performed for each process stage in the whole production cycle, the dynamic and static determination and regulation decision based on the solenoid tension field are performed by cooperating the initialized gradient limiter and the control decision maker, and the feedback regulation of the dynamic tension is performed on the yarn guide.

[0071] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description, and does not represent the advantages and disadvantages of the embodiments. The above describes a specific embodiment of the present application. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are also possible or can be advantageous.

[0072] The above description is only the preferred embodiment of the present application, and is not intended to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

[0073] The specification and drawings are only exemplary and illustrative of the present application and are to be considered within the scope of the present application. Obviously, those skilled in the art can make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application belong to the scope of the present application and equivalent technology, the present application is intended to include these modifications and variations.

Claims

1. A method for controlling the gradient tension in the production of anti-pilling cashmere yarn, characterized in that, The method includes: Based on the constitutive relationship of cashmere yarn, gradient tension pulses are determined for the entire processing cycle. Gradient limiters are deployed through dynamic and static simulations, where thermal tension fluctuations and force-induced tension fluctuations are additional simulation quantities. The cashmere yarn process is divided into stages, and for each process node, distributed sampling is performed using eddy current displacement sensors to determine the spiral tension field. The gradient limiter is used to determine the dynamic and static limits of the helical tension field. If any condition is not met, the fiber entanglement state is determined by analyzing the fiber slip characteristic frequency, which triggers the control decision-maker to make static decisions based on uniformity for fiber density and structure, and dynamic decisions based on fiber structure damage and friction coefficient for slip mode, thereby determining the pre-adjustment parameters. The yarn guide is controlled and managed according to the pre-adjustment parameters. The deployment of gradient limiters includes: Based on the entire production cycle, determine the tension requirements at each process stage, and use them as gradient tension pulses; For the gradient tension pulse, by connecting to a visualization simulation platform, lightweight static tension simulation is performed stage by stage of the process to determine the static limit conditions; Perform lightweight dynamic tension simulation to determine dynamic limit conditions; The gradient limiter is constructed based on the static and dynamic limiting conditions.

2. The gradient tension control production method for anti-pilling cashmere yarn as described in claim 1, characterized in that, The gradient limiter assists in determining the dynamic and static limits of the helical tension field, including: During the first stage of the production process, the dynamic and static limiting conditions of the first stage within the gradient limiter are activated and initialized as the first limiter. Based on the eddy current displacement sensor, distributed point acquisition is performed to construct a helical tension field; Based on the spiral tension field, a first-order static judgment and a second-order dynamic judgment based on the first limiter are performed to determine the limit judgment result.

3. The gradient tension control production method for anti-pilling cashmere yarn as described in claim 2, characterized in that, If the limit determination result satisfies the dynamic and static limit conditions, the subsequent analysis process is terminated. If any of the limit determination results are not met, the control decision-maker is triggered.

4. The gradient tension control production method for anti-pilling cashmere yarn as described in claim 3, characterized in that, The fiber entanglement state is determined by performing fiber slip characteristic frequency analysis, triggering the control decision-maker, including: Based on the helical tension field, the fiber slip characteristic frequency is extracted to determine the fiber entanglement state, wherein the fiber entanglement state corresponds one-to-one with the distributed points of the eddy current displacement sensor; For the fiber entanglement state, the auxiliary control decision-maker performs dynamic and static coordinated decision-making for tension feedback regulation to determine the pre-regulation parameters.

5. The gradient tension control production method for anti-pilling cashmere yarn as described in claim 4, characterized in that, Before triggering the control decision-maker, the construction of the control decision-maker includes: Static decision channels are deployed using fiber density and structural uniformity as the first self-attention decision parameters. Using fiber structure damage in the slip mode as the second self-attention decision quantity and the friction coefficient based on fiber entanglement degree as the third self-attention decision quantity, a dynamic decision channel is deployed. The static decision channel and the dynamic decision channel are used in parallel as the control decision-maker, wherein the control parameters of the yarn guide are used as the output.

6. The gradient tension control production method for anti-pilling cashmere yarn as described in claim 5, characterized in that, The auxiliary control decision-maker performs dynamic and static coordinated decision-making for tension feedback regulation, determining pre-regulation parameters, including: The fiber entangled state is introduced into the control decision-maker, and the distributed verification, evaluation and control decision of the first self-attention decision quantity is performed according to the static decision channel to determine the first control parameter; Based on the dynamic decision-making channel, the distributed verification and control decisions of the second and third self-attention decision quantities are executed in parallel to determine the second and third control parameters. Based on the first control parameter, the second control parameter, and the third control parameter, the extreme values ​​of each mapping parameter are taken, and the pre-control parameter is determined by combination.

7. The gradient tension control production method for anti-pilling cashmere yarn as described in claim 6, characterized in that, The distributed verification and control decisions of the second and third self-attention decision quantities are executed in parallel, including: By combining a temperature sensor and a vibration sensor, the first temperature data and the second vibration data are determined. Based on the first temperature data, determine the first dynamic condition for the thermal tension fluctuation; Based on the second vibration data, determine the second dynamic condition for force-induced tension fluctuation; The first dynamic condition and the second dynamic condition are imported into the dynamic decision-making channel as decision constraints.

8. The gradient tension control production method for anti-pilling cashmere yarn as described in claim 1, characterized in that, For each process stage of the entire production cycle, the gradient limiter is initialized, and the initialized gradient limiter and control decision-maker are coordinated to make dynamic and static judgments and control decisions based on the spiral tension field, and to perform dynamic tension feedback control of the yarn guide.

9. A gradient tension control production system for anti-pilling cashmere yarn, characterized in that, A method for controlling gradient tension in the production of anti-pilling cashmere yarn according to any one of claims 1-8, the system comprising: Deployment module: Based on the constitutive relationship of cashmere yarn, gradient tension pulses are determined for the entire processing cycle. Gradient limiters are deployed through dynamic and static simulations. Thermal tension fluctuations and force-induced tension fluctuations are additional simulation quantities. Tension field determination module: Divide the cashmere yarn process into stages, and determine the spiral tension field for each process node by performing distributed sampling through eddy current displacement sensors; Judgment Module: Assists the gradient limiter in performing dynamic and static limit judgments on the helical tension field. If any condition is not met, the fiber entanglement state is determined by analyzing the fiber slip characteristic frequency, triggering the control decision-maker to make static decisions based on uniformity for fiber density and structure, and dynamic decisions on fiber structure damage and friction coefficient for slip mode, thus determining the pre-adjustment parameters. Control and management module: Controls and manages the yarn guide according to the pre-control parameters.

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