Search

CN-122024972-A - Bio-based nylon and nanoparticle composite spinning method and system

CN122024972ACN 122024972 ACN122024972 ACN 122024972ACN-122024972-A

Abstract

The invention provides a method and a system for spinning bio-based nylon and nano particles, which relate to the technical field of textile materials and comprise the step of dynamically analyzing a heat transfer state by acquiring melt temperature distribution and a nano phase change material dispersion state. And establishing a temperature-viscosity coupling relation according to the evaluation result and the flow field characteristics to generate a viscosity regulation and control requirement, and further calculating and generating a dynamic heat supply power distribution scheme through a phase change trigger time sequence model to adjust a heating energy input time sequence so as to match the heat absorption and release process of the nano phase change material with the flow of the melt. Based on the spinning fiber quality feedback information, dynamically correcting the phase change trigger model. The invention realizes the accurate synchronous regulation and control of the temperature field in the composite spinning process, and effectively improves the uniformity and stability of the fiber quality.

Inventors

  • ZHANG XIUFENG

Assignees

  • 南通熹居工坊纺织科技有限公司

Dates

Publication Date
20260512
Application Date
20260326

Claims (10)

  1. 1. The composite spinning method of the bio-based nylon and the nano-particles is characterized by comprising the following steps: Acquiring real-time temperature distribution data of a melt to be spun and dispersion state characteristic parameters of a nano phase change material in the melt, and dynamically analyzing the real-time temperature distribution data based on a heat enthalpy-temperature response relation model of the phase change material to obtain a heat transfer state evaluation result; According to the heat transfer state evaluation result and the flow field distribution characteristics of the spinning channel, establishing a temperature-viscosity coupling relation of each position point on a melt flow path, generating a space-distributed viscosity regulation and control requirement, and according to the viscosity regulation and control requirement and the spinning speed constraint condition, calculating a space-time matching relation between each heating section and the melt flow front by establishing a phase change trigger time sequence model of the phase change material in a flow shear field, and generating a dynamic heat supply power distribution scheme synchronous with the flow path; based on the dynamic heat supply power distribution scheme, adjusting the energy input time sequence of each heating section to enable the heat absorption and release process of the nano phase change material to be matched with the time when the melt reaches the corresponding heating section; And collecting quality characteristic data of the fiber after spinning molding, taking the quality characteristic data as feedback information, and dynamically correcting the trigger advance in the phase change trigger time sequence model by reversely tracing time sequence association between fiber defects and temperature fluctuation events in a melt flow process to form feedforward-feedback cooperative control of the spinning process.
  2. 2. The method of claim 1, wherein dynamically resolving the real-time temperature distribution data based on a model of a heat enthalpy-temperature response relationship of the phase change material to obtain a heat transfer state estimation result comprises: Carrying out spatial position matching on the real-time temperature distribution data and the characteristic parameters of the dispersion state of the nano phase-change material in the melt, and identifying the deviation degree between the local concentration distribution of the phase-change material at each position point and the temperature change rate of the position point to obtain a phase-change material distribution uniformity evaluation result; Based on the solid-liquid phase transition latent heat characteristic of the phase change material in the enthalpy-temperature response relation model, calculating the theoretical heat absorbing and releasing capacity of the phase change material at the current temperature of each position point, and mapping the theoretical heat absorbing and releasing capacity into the effective heat absorbing and releasing capacity of each position point in an actual dispersion state by establishing a transfer function of local concentration deviation on the thermal response delay of the phase change material, so as to obtain the actual heat absorbing and releasing capacity distribution considering the influence of dispersion unevenness; And calculating the heat accumulation rate and the heat dissipation rate of each position point in the melt according to the actual heat absorption and release capacity distribution and the temperature gradient change trend in the real-time temperature distribution data, and judging the heat transfer balance state of each position point based on the difference value of the heat accumulation rate and the heat dissipation rate to obtain a heat transfer state evaluation result.
  3. 3. The method of claim 2, wherein mapping the theoretical heat absorption and release capacity to the effective heat absorption and release capacity of each location point in the actual dispersion state by establishing a transfer function of local concentration deviation to thermal response delay of the phase change material, and obtaining the actual heat absorption and release capacity distribution considering the dispersion non-uniformity effect comprises: Based on the evaluation result of the distribution uniformity of the phase change material, extracting the deviation between the local concentration and the standard concentration at each position point, taking the deviation as an input variable of a transfer function, and calculating the response delay time of the phase change material at each position point when solid-liquid phase transition occurs at the current temperature; Identifying the hysteresis degree of the phase change material actually participating in the heat absorbing and releasing process at each position point according to the response delay time and the temperature change rate in the real-time temperature distribution data, and quantifying the hysteresis degree into heat capacity contribution reduction proportion; And carrying out product operation on the theoretical heat absorption and release capacity and the heat capacity contribution reduction ratio to obtain effective heat absorption and release capacity of each position point in an actual dispersion state, and carrying out spatial distribution reconstruction on the effective heat absorption and release capacity along a melt flow path to obtain actual heat absorption and release capacity distribution considering the influence of dispersion unevenness.
  4. 4. The method of claim 1, wherein establishing a temperature-viscosity coupling relationship for each location point on the melt flow path based on the heat transfer state evaluation result and the flow field distribution characteristics of the spinning channel, generating spatially distributed viscosity regulation requirements comprises: Extracting the heat transfer balance state deviation degree of each position point from the heat transfer state evaluation result, and converting the heat transfer balance state deviation degree into a temperature stability index of the corresponding position point; based on the flow field distribution characteristics of the spinning channel, obtaining the flow velocity vector and the local shear stress distribution of the melt at each position point, carrying out coupling calculation on the temperature stability index and the local shear stress distribution, and identifying the sensitive interval of the limited degree of the movement of the melt molecular chain segment of each position point on the viscosity response under the temperature fluctuation; And establishing a dynamic response relation between the temperature variation and the viscosity variation of each position point according to the sensitive interval to obtain a temperature-viscosity coupling relation, spatially expanding the temperature-viscosity coupling relation along a melt flow path, calibrating each position point to a temperature regulation and control amplitude required for maintaining target viscosity, and generating a spatially distributed viscosity regulation and control requirement.
  5. 5. The method of claim 1, wherein calculating a space-time matching relationship between each heating section and a melt flow front by establishing a phase change trigger timing model of a phase change material in a flow shear field according to the viscosity regulation demand and spinning speed constraint conditions, and generating a dynamic heating power distribution scheme synchronized with a flow path comprises: extracting target temperature regulation amplitude which needs to be achieved by each position point from viscosity regulation requirements, performing correlation operation on the target temperature regulation amplitude and spinning speed constraint conditions, and calculating flow time required by the melt flowing from each heating section to the corresponding position point; based on the shearing stress accumulated by the phase change material in the flowing shearing field in the flowing time, identifying the dynamic offset effect of the shearing stress on the solid-liquid phase transition temperature threshold value of the phase change material, and establishing the influence rule of the shearing stress on the solid-liquid phase transition trigger moment of the phase change material; Performing coupling calculation on the influence rule and the flowing time, and determining the moment point of actually triggering phase change of the phase change material at each heating section in the melt flowing process to obtain a phase change triggering time sequence model; According to the time points of the phase change material triggering phase change at each heating section determined in the phase change triggering time sequence model, predicting the starting time of the phase change material at the time points for starting to release or absorb latent heat, performing time sequence comparison on the starting time and the time of the melt flow front reaching the corresponding position point, and calculating the time difference between the starting time and the time point; And converting the time difference into heating advance or delay of each heating section, performing forward or backward adjustment on heating starting time of each heating section according to the heating advance or delay, determining duration of each heating section according to the target temperature regulation and control amplitude, and generating a dynamic heating power distribution scheme synchronous with a flow path.
  6. 6. The method of claim 1, wherein dynamically correcting the trigger advance in the phase change trigger timing model by retrospectively tracking the timing correlation between fiber defects and temperature fluctuation events in the melt flow history using the quality characteristic data as feedback information, forming a feed-forward-feedback cooperative control of the spinning process comprises: extracting the spatial position distribution and defect characteristic types of fiber defects from the quality characteristic data, and calculating the position and temperature state of a heating section of a melt in the flow process, wherein the position and the temperature state are corresponding to the defect forming moment, by means of space-time backward pushing in combination with spinning speed constraint conditions; based on the heating section position and the temperature state, extracting a temperature change track before and after a defect forming moment from real-time temperature distribution data, judging and identifying a temperature fluctuation event deviating from a steady-state temperature path in the temperature change track through track deviation degree, and carrying out causal association mapping on the temperature fluctuation event and the defect characteristic type; According to the result of the causal relation mapping, analyzing and quantifying the delay influence degree of the temperature fluctuation event on the solid-liquid phase transition triggering moment of the phase change material through a delay transfer chain, and converting the delay influence degree into a correction increment of the triggering advance of the corresponding heating section in the phase change triggering time sequence model; And the correction increment is added to the current trigger advance of the phase change trigger time sequence model, the heat supply starting time of each heating section is redefined and updated through time sequence, the updated heat supply starting time is synchronously applied to the real-time generation of a dynamic heat supply power distribution scheme, and the feedforward-feedback cooperative control of the spinning process is formed.
  7. 7. The method of claim 6, wherein identifying temperature fluctuation events in the temperature change trace that deviate from a steady-state temperature path by a trace deviation determination and causally mapping the temperature fluctuation events to the defect signature type comprises: Constructing a temperature evolution datum line of the heating section position under a steady state condition based on a temperature state, and calculating the deviation amplitude between the temperature value of each moment point on a temperature change track and the temperature value of the moment point corresponding to the temperature evolution datum line to obtain track deviation degree distribution; Carrying out time sequence scanning on the track deviation degree distribution, identifying deviation fragments with deviation amplitude exceeding a steady-state allowable range and duration crossing the thermal response critical duration of the phase change material, and marking a temperature change process corresponding to the deviation fragments as a temperature fluctuation event; Extracting fluctuation peak intensity and fluctuation duration from the temperature fluctuation event, and combining the fluctuation peak intensity and the fluctuation duration into a feature vector of the temperature fluctuation event; Establishing a size association weight between the defect size distribution and the fluctuation peak intensity according to the defect size distribution corresponding to the defect feature type, establishing a density association weight between the defect density distribution and the fluctuation duration according to the defect density distribution corresponding to the defect feature type, and mapping the feature vector to the defect feature type through the size association weight and the density association weight to obtain a causal association mapping result.
  8. 8. A bio-based nylon and nanoparticle composite spinning system for implementing the method of any one of the preceding claims 1-7, comprising: The temperature analysis unit is used for acquiring real-time temperature distribution data of a melt to be spun and dispersion state characteristic parameters of the nano phase change material in the melt, and dynamically analyzing the real-time temperature distribution data based on a heat enthalpy-temperature response relation model of the phase change material to obtain a heat transfer state evaluation result; the viscosity regulation and control unit is used for establishing a temperature-viscosity coupling relation of each position point on the melt flow path according to the heat transfer state evaluation result and the flow field distribution characteristic of the spinning channel, generating a space-distributed viscosity regulation and control requirement, and calculating a space-time matching relation between each heating section and the melt flow front by establishing a phase change trigger time sequence model of the phase change material in the flow shear field according to the viscosity regulation and control requirement and the spinning speed constraint condition, so as to generate a dynamic heat supply power distribution scheme synchronous with the flow path; the heat supply matching unit is used for adjusting the energy input time sequence of each heating section based on the dynamic heat supply power distribution scheme so as to match the heat absorption and release process of the nano phase change material with the time when the melt reaches the corresponding heating section; And the cooperative control unit is used for collecting quality characteristic data of the fiber after spinning forming, taking the quality characteristic data as feedback information, and dynamically correcting the trigger advance in the phase change trigger time sequence model by reversely tracing time sequence association between fiber defects and temperature fluctuation events in melt flow process to form feedforward-feedback cooperative control of the spinning process.
  9. 9. An electronic device, comprising: A processor; A memory for storing processor-executable instructions; Wherein the processor is configured to invoke the instructions stored in the memory to perform the method of any of claims 1 to 7.
  10. 10. A computer readable storage medium having stored thereon computer program instructions, which when executed by a processor, implement the method of any of claims 1 to 7.

Description

Bio-based nylon and nanoparticle composite spinning method and system Technical Field The invention relates to textile material technology, in particular to a method and a system for spinning bio-based nylon and nano particles. Background In the field of spinning processing of biobased nylon and nanoparticle composites, the prior art generally employs a static or piecewise constant temperature control strategy. In order to improve melt fluidity and fiber forming quality, it is common practice to provide a plurality of independently temperature-controlled heating sections along the spinning channel and to set a fixed heating power for each section according to a preset process profile. For functional composite melts with added nanophase materials, the process design is largely dependent on static thermophysical parameters provided by the material supplier, or by limited prior experimentation to approximately determine the temperature set points for each segment. This control mode defaults to a uniform and stable temperature distribution and nanoparticle dispersion of the melt as it flows through each heating zone, thereby attempting to maintain a global or piecewise constant processing temperature environment. However, the conventional control method described above has significant drawbacks. Because the dispersion state of the nano phase-change material in the dynamic shear flow field can change in real time, a complex space-time coupling relation exists between the phase-change heat absorption and release behavior and the actual temperature field of the melt. The fixed heating power distribution scheme cannot respond to dynamic fluctuations in melt flow front position, local viscosity and real-time thermal state of the phase change material, resulting in mismatch of heat supply in time and space with the actual demand of the melt. The problems of uneven viscosity, nanoparticle agglomeration or disorder of phase change process and the like are caused by unexpected local temperature sudden rise or sudden drop of the melt on a flow path, and the defects of uneven structure, reduced mechanical property, unstable functional property and the like are finally introduced into the formed fiber. The existing method lacks the capability of fine tracing and closed loop correction of temperature events in the melt flow process, is delayed in process adjustment, and is difficult to realize stable preparation of high-quality fibers. Disclosure of Invention The embodiment of the invention provides a method and a system for composite spinning of bio-based nylon and nano particles, which can solve the problems in the prior art. In a first aspect of an embodiment of the present invention, there is provided a bio-based nylon and nanoparticle composite spinning method, including: Acquiring real-time temperature distribution data of a melt to be spun and dispersion state characteristic parameters of a nano phase change material in the melt, and dynamically analyzing the real-time temperature distribution data based on a heat enthalpy-temperature response relation model of the phase change material to obtain a heat transfer state evaluation result; According to the heat transfer state evaluation result and the flow field distribution characteristics of the spinning channel, establishing a temperature-viscosity coupling relation of each position point on a melt flow path, generating a space-distributed viscosity regulation and control requirement, and according to the viscosity regulation and control requirement and the spinning speed constraint condition, calculating a space-time matching relation between each heating section and the melt flow front by establishing a phase change trigger time sequence model of the phase change material in a flow shear field, and generating a dynamic heat supply power distribution scheme synchronous with the flow path; based on the dynamic heat supply power distribution scheme, adjusting the energy input time sequence of each heating section to enable the heat absorption and release process of the nano phase change material to be matched with the time when the melt reaches the corresponding heating section; And collecting quality characteristic data of the fiber after spinning molding, taking the quality characteristic data as feedback information, and dynamically correcting the trigger advance in the phase change trigger time sequence model by reversely tracing time sequence association between fiber defects and temperature fluctuation events in a melt flow process to form feedforward-feedback cooperative control of the spinning process. Dynamically analyzing the real-time temperature distribution data based on the enthalpy-temperature response relation model of the phase change material, and obtaining a heat transfer state evaluation result comprises the following steps: Carrying out spatial position matching on the real-time temperature distribution data and the characteristic parameters of th