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CN-121996002-A - Control method for temperature and humidity of lutein steam eyeshade

CN121996002ACN 121996002 ACN121996002 ACN 121996002ACN-121996002-A

Abstract

The invention provides a temperature and humidity control method of a lutein steam eye mask. Belongs to the technical field of functional health care products and intelligent material controlled release. The method comprises the steps of carrying out dynamic environment partitioning on a lutein steam eyeshade production workshop to generate multi-region temperature and humidity baseline data, carrying out simulation prediction on the oxidation rate of iron powder in each partition based on a reaction dynamics model, and generating a feedforward compensation control instruction set by combining raw material batch parameters.

Inventors

  • LIU PENGJU

Assignees

  • 杭州蓓而健康科技有限公司

Dates

Publication Date
20260508
Application Date
20260211

Claims (10)

  1. 1. A method for controlling the temperature and humidity of a lutein vapor eye mask, comprising: S1, carrying out dynamic environment partitioning on a lutein steam eyeshade production workshop to generate multi-region temperature and humidity baseline data, carrying out simulation prediction on the oxidation rate of iron powder in each partition based on a reaction dynamics model, and generating a feedforward compensation control instruction set by combining with raw material batch parameters; s2, deploying a near infrared online monitoring array according to a feedforward compensation control instruction set, and collecting iron powder oxidation heat release curve and lutein characteristic absorption peak data in the production process in real time; S3, constructing a digital twin body according to the dynamic correction data flow, and synchronously simulating the distribution of a workshop temperature and humidity field and a reaction thermal field in a virtual space; S4, encrypting and storing production whole-process data based on a blockchain distributed account book technology, and binding NIR monitoring data, temperature and humidity regulation records and lutein retention rate detection results of each eye cover unit to generate unique digital fingerprints; And S5, dynamically updating a reaction dynamics model parameter library according to the digital twin body optimization result and the blockchain traceability data, transferring the historical batch control experience to new batch production through a transfer learning algorithm to generate a self-adaptive control knowledge graph, and constructing a cognitive level production operation system based on the knowledge graph.
  2. 2. The method for controlling the temperature and humidity of a lutein vapor eye mask according to claim 1, wherein S1 comprises: s11, collecting space layout, equipment distribution and environmental influence factors of a lutein steam eye mask production workshop, synchronously recording initial temperature and humidity data of each production area, and generating a workshop basic environment data set; S12, dividing dynamic environment subareas based on a workshop basic environment data set and combining raw material reaction characteristics, and continuously sampling and analyzing initial temperature and humidity data of each subarea to generate multi-area temperature and humidity baseline data; S13, inputting multi-region temperature and humidity baseline data and raw material batch parameters into a reaction dynamics model, and performing simulation calculation on the iron powder oxidation process of each region to generate time sequence data of the oxidation rate of the iron powder of each region; S14, integrating the multi-region temperature and humidity baseline data and the oxidation rate time sequence data of the iron powder in each region, quantifying the association relation between temperature and humidity deviation and oxidation rate fluctuation, and generating a feedforward compensation control instruction set.
  3. 3. The method for controlling the temperature and humidity of the lutein vapor eye mask according to claim 2, wherein S13 comprises: Integrating multi-region temperature and humidity baseline data and raw material batch parameters, combing the associated dimensions of the two types of data, standardizing the data format and the numerical precision, and generating a reaction dynamics model input data set; Carrying out normalization processing on the model input data set to generate standardized model input data; importing the input data of the standardized model into a reaction dynamics model, setting the simulation boundary conditions and the iteration step length of each partition oxidation reaction, and carrying out simulation calculation of multiple rounds of oxidation processes to generate the original data of the oxidation rate of the iron powder in each partition; And carrying out time sequence alignment and smoothing treatment on the original data of the oxidation rate of the iron powder in each partition, and combing the change rules of the oxidation rate of different time nodes to generate time sequence data of the oxidation rate of the iron powder in each partition.
  4. 4. The method for controlling the temperature and humidity of a lutein vapor eye mask according to claim 1, wherein S2 comprises: S21, according to a feedforward compensation control instruction set, determining monitoring points and monitoring frequencies of all dynamic environment partitions, finishing the layout and the debugging of a near infrared online monitoring array, and generating a real-time monitoring network covering the whole production flow; s22, starting a real-time monitoring network, collecting iron powder oxidation heat release curve and lutein characteristic absorption peak data in the production process, and synchronously recording real-time temperature and humidity data of each monitoring point to generate a multi-dimensional original monitoring data set; s23, inputting the multi-dimensional original monitoring data set into a multivariate statistical process control model, identifying and eliminating abnormal values in the data, completing signal noise reduction and reconstruction, and generating a standardized monitoring data stream; S24, correlating temperature and humidity data, oxidation heat release data and lutein component data in the standardized monitoring data stream, constructing a data coupling model, and generating a dynamically corrected temperature and humidity and component coupling data stream.
  5. 5. The method for controlling the temperature and humidity of the lutein vapor eye mask of claim 4, wherein S23 comprises: The multi-dimensional original monitoring data set is imported into a multivariate statistical process control model to complete the adaptation of the data format and the model input requirement, and a model adaptation monitoring data set is generated; Carrying out abnormal feature recognition based on the model adaptation monitoring data set, positioning abnormal fluctuation nodes in the data, and generating an abnormal data identification set; removing corresponding abnormal data according to the abnormal data identification set, and reserving effective data fragments to generate an effective monitoring data set; and performing signal noise reduction processing on the effective monitoring data set, eliminating noise influence caused by external interference, and then completing signal reconstruction to generate a standardized monitoring data stream.
  6. 6. The method for controlling the temperature and humidity of the lutein vapor eye mask according to claim 1, wherein S3 comprises: s31, importing a dynamically corrected temperature and humidity and component coupling data stream, and building a digital twin body matched with an actual production scene by combining the workshop space layout and equipment parameters to generate a workshop virtual simulation model; S32, synchronously simulating the distribution of the temperature and humidity field and the reaction thermal field of each dynamic environment partition based on a workshop virtual simulation model, capturing the dynamic change trend of the field distribution, and generating a field distribution dynamic simulation data set; s33, inputting the field distribution dynamic simulation data set into a particle swarm optimization algorithm, performing multi-round iterative optimization on the regulation and control parameters in the digital twin body, and outputting an optimal control parameter combination; s34, combining the optimal control parameter combination, integrating feedforward compensation control logic and real-time feedback control logic, generating feedforward and feedback composite control strategies, and finishing the accurate regulation and control of the heat release curve.
  7. 7. The method for controlling the temperature and humidity of the lutein vapor eye mask of claim 6, wherein S32 comprises: loading a workshop virtual simulation model, and activating a simulation calculation module of each dynamic environment partition to generate a partition simulation calculation environment; In a partitioned simulation computing environment, synchronously carrying out simulation operation of a temperature and humidity field and a reaction thermal field to generate real-time simulation data of the distribution of each partitioned field; carrying out time sequence tracking on the field distribution real-time simulation data of each partition, recording the field distribution change characteristics of different time nodes, and generating a field distribution dynamic change characteristic set; and integrating the field distribution dynamic change feature set to complete time sequence splicing and space integration of the data and generate a field distribution dynamic simulation data set.
  8. 8. The method for controlling the temperature and humidity of the lutein vapor eye mask according to claim 1, wherein S4 comprises: s41, starting a blockchain distributed account book system, importing temperature and humidity regulation, oxidation monitoring, component detection and parameter optimization data of the whole production process, completing data encryption and distributed evidence storage, and generating a production data account book which cannot be tampered; S42, dividing a single eyeshade production unit, associating and binding near infrared monitoring data, temperature and humidity regulation records and lutein retention rate detection results corresponding to each unit, and extracting data characteristics to generate unique digital fingerprints; S43, triggering an intelligent contract based on a block chain technology, and using a digital fingerprint as a core to correlate production full-flow microenvironment parameters with quality detection data, so as to automatically construct a quality tracing chain; s44, establishing a correlation model of the performance of the single-chip product and the micro-environment parameters at the production time through a quality tracing chain, and finishing the two-way mapping of the single-chip product and the micro-environment parameters.
  9. 9. The method for controlling the temperature and humidity of the lutein vapor eye mask of claim 8, wherein S41 comprises: starting a blockchain distributed account book system, completing system operation parameter calibration and node deployment, and generating a safe and stable account book operation environment; importing various data of the whole production process, namely covering temperature and humidity regulation, oxidation monitoring, component detection and parameter optimization data, finishing data classification and format adaptation, and generating standardized account book data; performing encryption processing on the standardized account book data, converting the data form by adopting an encryption algorithm to generate encrypted data fragments, and guaranteeing the safety of data storage and transmission; And synchronizing the encrypted data segments to each blockchain node, completing multi-node verification and data synchronization, and generating a production data account book which cannot be tampered.
  10. 10. The method for controlling the temperature and humidity of the lutein vapor eye mask according to claim 1, wherein S5 comprises: s51, summarizing a digital twin body parameter optimization result and blockchain traceability data, extracting key parameters affecting oxidation reaction and lutein stability, and dynamically updating a reaction dynamics model parameter library; s52, importing historical production batch control data and optimization experience, migrating the historical control experience to a new batch production scene through a migration learning algorithm, mining production commonality rules and differentiation features, and generating a self-adaptive control knowledge graph; S53, based on the self-adaptive control knowledge graph, integrating data monitoring, parameter optimization and quality tracing function modules, and constructing a cognitive level production operation system; S54, executing a self-adaptive regulation strategy through a cognitive level production operation system, optimizing temperature and humidity and reaction parameters in real time, and continuously monitoring lutein retention rate.

Description

Control method for temperature and humidity of lutein steam eyeshade Technical Field The invention provides a temperature and humidity control method of a lutein steam eye mask, and belongs to the technical field of functional health care products and intelligent material controlled release. Background In the field of lutein steam eyeshade production, the traditional process has a plurality of difficulties to be solved urgently. Currently, most production modes are highly dependent on the environment, and fluctuation of temperature and humidity of workshops can seriously influence the quality of products. When the relative humidity in summer exceeds 70%, the oxidation reaction of the iron powder starts in advance, and when the temperature in winter is lower than 15 ℃, the reaction activation is delayed, which makes the production process difficult to control stably. Meanwhile, the active ingredient monitoring link is seriously lost. The lutein is not provided with an effective on-line detection means after being added, is extremely easy to degrade in a high-temperature and high-humidity environment, and causes that the lutein content in the final product fluctuates by more than 30 percent, and the quality of the product is uneven. In the aspect of process control, temperature and humidity regulation depends on a fixed set value, and cannot be flexibly adjusted according to batch differences of raw materials. For example, the change of the particle size distribution of the iron powder affects the oxidation reaction rate, but the conventional process cannot respond correspondingly. The quality tracing is also rough, only the batch number is recorded, and the microenvironment parameters at specific production time cannot be related to the performance of the single-chip product. Moreover, the prior published patent stays on the general measure layers of 'temperature control workshop', 'humidity adjustment', and the like, the reaction dynamics, the stability of active ingredients and the intelligent manufacturing depth cannot be fused, a cognitive level production operation system with 'reverse modeling-feedforward compensation-digital twin' is constructed, and the transition of the manufacturing range of the intelligent pharmaceutical level is difficult to realize. Therefore, it is urgent to develop a novel temperature and humidity control method. Disclosure of Invention The invention provides a control method of temperature and humidity of a lutein steam eye mask, which is used for solving the problems mentioned in the background art: The invention provides a temperature and humidity control method of a lutein steam eye mask, which comprises the following steps: S1, carrying out dynamic environment partitioning on a lutein steam eyeshade production workshop to generate multi-region temperature and humidity baseline data, carrying out simulation prediction on the oxidation rate of iron powder in each partition based on a reaction dynamics model, and generating a feedforward compensation control instruction set by combining with raw material batch parameters; s2, deploying a near infrared online monitoring array according to a feedforward compensation control instruction set, and collecting iron powder oxidation heat release curve and lutein characteristic absorption peak data in the production process in real time; S3, constructing a digital twin body according to the dynamic correction data flow, and synchronously simulating the distribution of a workshop temperature and humidity field and a reaction thermal field in a virtual space; S4, encrypting and storing production whole-process data based on a blockchain distributed account book technology, and binding NIR monitoring data, temperature and humidity regulation records and lutein retention rate detection results of each eye cover unit to generate unique digital fingerprints; And S5, dynamically updating a reaction dynamics model parameter library according to the digital twin body optimization result and the blockchain traceability data, transferring the historical batch control experience to new batch production through a transfer learning algorithm to generate a self-adaptive control knowledge graph, and constructing a cognitive level production operation system based on the knowledge graph. The lutein steam eyeshade has the beneficial effects that the stability of the production process is improved by the temperature and humidity control method of the lutein steam eyeshade, and the variation coefficient of an exothermic curve can be controlled within 3% when the relative humidity of a workshop fluctuates by 40-80%, so that the stable oxidation reaction of iron powder is ensured. The degradation risk of lutein is reduced, the lutein retention rate is up to more than 95% by utilizing on-line monitoring and accurate regulation, and the product efficacy is ensured. The quality traceability is enhanced, production microenvironment parameters are associated w