Automatic eyebrow pencil core pressure filling integrated forming control method and system

Abstract

The invention relates to the technical field of automatic eyebrow pencil pressure filling, in particular to an automatic eyebrow pencil core pressure filling integrated forming control method and system. Based on the time sequence heating parameter set, material characteristics of eyebrow pencil core raw materials in a molten state are obtained, an internal stress distribution thermodynamic diagram of the eyebrow pencil core is established, pressure filling parameters of the eyebrow pencil core are controlled by analyzing the stress distribution thermodynamic diagram, and a pressure filling control scheme is obtained; an internal stress distribution thermodynamic diagram group is redrawn after control and optimization are conducted through a pressure filling control scheme, the increment amplitude of the cooling variation state for the internal stress migration trend is calculated through the internal stress distribution thermodynamic diagram group, and whether the increment amplitude meets the preset requirement or not is analyzed to optimize a pressure filling strategy and a cooling strategy or control cooling forming parameters. And a control strategy optimization scheme and a cooling forming control scheme are obtained. The automatic pressure filling production of the eyebrow pencil core can be accurately controlled and reasonably optimized, so that the pressure filling integral forming quality and efficiency of the eyebrow pencil core are improved.

Description

Technical Field

[0001] The invention relates to the technical field of automatic eyebrow pencil pressure filling, and in particular to an automatic eyebrow pencil core pressure filling integrated molding control method and system. Background Art

[0002] Eyebrow pencil core is a cosmetic used to draw eyebrows, usually composed of core and pen shell. Eyebrow pencil core can fill the gaps in eyebrows, shape eyebrows, make eyebrows more stylish and neat, and improve the three-dimensional sense and fullness of eyebrows. Therefore, in order to better emphasize the contour of eyebrows, the texture, hardness, toughness, coloring effect and surface smoothness of eyebrow pencil core are required to be high. These indicators determine the quality of eyebrow pencil core products. Existing eyebrow pencil cores have achieved efficient production of pressure injection integrated molding, but improper control will cause the eyebrow pencil core to produce stress increase or concentration during the pressure injection process, thereby greatly reducing the hardness, toughness and coloring effect of the eyebrow pencil core. At the same time, the control of raw material heating is also very important, which determines whether the color number of the eyebrow pencil core is accurate. In addition, the cooling error during the pressure injection integrated molding process will also cause uneven cooling of the eyebrow pencil core, resulting in embrittlement and material structure changes, thereby producing bubbles, vacancies or depressions and other molding defects, reducing the integrity and molding efficiency of the automatic eyebrow pencil core pressure injection integrated molding. Summary of the invention

[0003] The present invention overcomes the shortcomings of the prior art and provides a method and system for controlling the pressure-filling integrated molding of an automatic eyebrow pencil core.

[0004] To achieve the above object, the technical solution adopted by the present invention is:

[0005] A first aspect of the present invention provides a method for controlling pressure-filling integrated molding of an automatic eyebrow pencil core, comprising the following steps:

[0006] S102: Obtaining production and processing requirements of eyebrow pencil refills, constructing a sparse dictionary for generating a continuous color gradient image expression under a time-series heating parameter range, querying and identifying the production and processing requirements through the sparse dictionary, and obtaining a time-series heating parameter set required for a target color number;

[0007] S104: obtaining material properties of the raw material of the eyebrow pencil core in a molten state based on the time-series heating parameter set, drawing and establishing an internal stress distribution thermodynamic map of the eyebrow pencil core according to the stress test under the material properties, and controlling the pressure filling parameters of the eyebrow pencil core by analyzing the stress distribution thermodynamic map to obtain a pressure filling control scheme;

[0008] S106: redrawing the internal stress distribution heat map group after control tuning through the pressure injection control scheme, calculating the incremental amplitude of the cooling abnormal state for the internal stress migration trend through the internal stress distribution heat map group, analyzing whether the incremental amplitude meets the preset requirements to optimize the pressure injection strategy, the cooling strategy or control the cooling molding parameters, and obtaining the control strategy optimization scheme and the cooling molding control scheme;

[0009] S108: Obtain the molding defect contour and texture of the eyebrow pencil core sample model compared with the expected sample model of the eyebrow pencil core, cluster the molding defect contour and texture into a suspected abnormal control text package, generate an abnormal control clustering label, adjust the abnormal control parameters according to the abnormal control clustering label, and obtain a control calibration plan.

[0010] More specifically, the step S102 includes the following steps:

[0011] Obtain production and processing requirements for eyebrow pencil refills, and extract several kinds of raw materials for eyebrow pencil refills and the established addition ratio parameters of each raw material of eyebrow pencil refills through the production and processing requirements;

[0012] Based on the predetermined addition ratio parameter, the maximum melting point critical value for mixing and heating all raw materials of the eyebrow pencil core until they are fully melted and combined with each other is retrieved in the big data network, and the initial design drawing of the automatic eyebrow pencil core pressure filling device is obtained;

[0013] A multi-dimensional simulation model of an automatic eyebrow pencil core pressure filling device is constructed according to the initial design draft, and a maximum melting point critical value is injected into the multi-dimensional simulation model to simulate heating, so as to obtain multiple groups of continuous color gradient image data in the process of the raw material of the eyebrow pencil core gradually approaching the maximum melting point critical value;

[0014] The time-series heating parameter interval of the eyebrow pencil core raw material gradually approaching the maximum melting point critical value is obtained, a Gaussian random matrix is ​​constructed, and a sparse coding algorithm is introduced to solve the sparse basis function representation of multiple groups of continuous color gradient image data in the Gaussian random matrix, and the sparse coefficient between two adjacent color gradient images is obtained;

[0015] In the sparse coding process, a sparse basis function threshold is preset based on each group of temporal heating parameters in the temporal heating parameter interval, and the sparse basis function in the Gaussian random matrix is ​​iteratively updated according to the sparse coefficient between two adjacent color gradient images until the sparse basis function is less than the sparse basis function threshold, and the iterative update is stopped to obtain a sparse dictionary for expressing a continuous color gradient image under the temporal heating parameter interval;

[0016] The target color number sparse code of the eyebrow pencil core is obtained according to the production and processing requirements, the target color number sparse code is sparsely queried through a sparse dictionary, and the timing heating parameter set required for the target color number is output.

[0017] More specifically, the step S104 includes the following steps:

[0018] According to the time sequence heating parameter set required by the target color number, the heating module of the automatic eyebrow pencil core pressure filling device is controlled to perform heating and melting processing on all the raw materials of the eyebrow pencil core, and at this time, the material properties of the raw materials of the eyebrow pencil core in a molten state are obtained;

[0019] Obtain a historical product evaluation report of an eyebrow pencil refill, and extract a number of internal stress test values ​​and a distribution pattern of stress test values ​​corresponding to the eyebrow pencil refill produced by an automatic eyebrow pencil refill pressure filling device under the material characteristic conditions through the historical product evaluation report;

[0020] Obtain a standard product model diagram of an eyebrow pencil core, construct a heat map framework based on the standard product model diagram, introduce an inverse distance weighted algorithm, and preset a weight power, a search radius, and a number of neighboring points in the inverse distance weighted algorithm according to the distribution pattern of stress test values;

[0021] Define each stress test value as a point to be estimated, calculate the spatial distance value between the current point to be estimated and the adjacent point to be estimated based on the weight power, the search radius and the number of adjacent points, and determine the distance weight between the current point to be estimated and the adjacent point to be estimated according to the spatial distance value;

[0022] The inverse distance weighted interpolation of each point to be estimated is estimated by combining the internal stress test value of the current point to be estimated with the distance weight, a regional grid of all points to be estimated is constructed, and the inverse distance weighted interpolation of each point to be estimated is inserted into the center point of the corresponding regional grid, and finally a heat map of the internal stress distribution of the eyebrow pencil core is generated;

[0023] The ideal density coefficient of the eyebrow pencil core is extracted according to the production and processing requirements, and based on the ideal density coefficient, the optimal internal stress distribution point of the eyebrow pencil core to achieve the ideal density coefficient under the material property conditions and the corresponding optimal internal stress color value range are obtained in the big data network;

[0024] Extracting the actual internal stress color value of the optimal internal stress distribution point in the internal stress distribution thermodynamic map; if the actual internal stress color value is not within the optimal internal stress color value range, extracting the lower limit value of the optimal internal stress color value range, and calculating the hash state function between the lower limit value and the actual internal stress color value;

[0025] The pressure filling time node generating the actual internal stress color value is obtained, and the pressure filling parameters at the pressure filling time node are controlled according to the hash state function to obtain a pressure filling control scheme.

[0026] More specifically, the step S106 includes the following steps:

[0027] The pressure injection of the eyebrow pencil core is controlled and optimized through the pressure injection control scheme, and the internal stress distribution heat map group on the continuous time series after the control optimization of the eyebrow pencil core is redrawn;

[0028] If the actual internal stress color value of the optimal internal stress distribution point after control optimization is still not within the optimal internal stress color value range, then obtain several groups of cooling control change parameters of the cooling molding module for material properties when executing the pressure filling control scheme during the pressure filling process of the eyebrow pencil core;

[0029] Based on the big data network, the material variation index of the material characteristics under different cooling control variation parameters is obtained, and the cooling variation state of the raw material of the eyebrow pencil core by the cooling molding module is determined according to the material variation index and several groups of cooling control variation parameters;

[0030] Extract the migration distribution nodes of each internal stress test value continuous variable in the optimal internal stress distribution point of the eyebrow pencil core through the internal stress distribution heat map group in the continuous time series after the eyebrow pencil core control optimization, and determine the internal stress migration trend of the eyebrow pencil core according to the migration distribution nodes;

[0031] A trade-off algorithm is introduced to calculate the Gini coefficient between the cooling abnormal state and the internal stress migration trend, a smoothing parameter between the cooling abnormal state and the internal stress migration trend is determined according to the Gini coefficient, and a smoothing spline regression model is constructed according to the smoothing parameter;

[0032] The second-order derivatives between several groups of cooling control variation parameters and each internal stress test value are calculated by fitting the spline basis function of the smoothing spline regression model and the kernel function of the cooling variation state at different migration distribution nodes, and the incremental amplitude of the cooling variation state for the internal stress migration trend is determined according to the second-order derivative;

[0033] If the increment is less than the allowable increment, the probability of the eyebrow pencil core material generating the corresponding actual hardness test coefficient due to the pressure injection rate is calculated and analyzed to optimize the control strategy, thereby obtaining the control strategy optimization scheme;

[0034] If the incremental amplitude is greater than the allowable incremental amplitude, the deviation between the incremental amplitude and the allowable incremental amplitude is quantified to obtain a quantized value of the incremental amplitude deviation, and the cooling forming parameters are controlled according to the quantized value of the incremental amplitude deviation to obtain a cooling forming control scheme.

[0035] More specifically, if the increment amplitude in S106 is less than the allowable increment amplitude, the probability of the pressure injection rate causing the eyebrow pencil core material to generate the corresponding actual hardness test coefficient is calculated and analyzed to optimize the control strategy, and a control strategy optimization scheme is obtained, which specifically includes the following steps:

[0036] If the increment amplitude is less than the allowable increment amplitude, the cooling station specification parameters of the cooling molding module are obtained, and the area definition threshold is preset based on the cooling station specification parameters;

[0037] Constraining the defined range in the optimal internal stress distribution point in the eyebrow pencil core until the region definition threshold is reached, obtaining the cooling station range, and obtaining the preset cooling strategy executed by the cooling molding module for the optimal internal stress distribution point in the eyebrow pencil core at multiple preset cooling nodes;

[0038] Constructing a regional model of the cooling station range, obtaining a cooling point pattern map according to a preset cooling strategy, dividing the regional model of the cooling station range into a plurality of sub-regional model blocks based on the cooling point pattern map, and obtaining an actual hardness test coefficient of each sub-regional model block;

[0039] According to the production and processing requirements, the expected hardness coefficient range of the eyebrow pencil core is obtained, and only the sub-region model block whose actual hardness test coefficient is not within the expected hardness coefficient range is marked, and defined as the hardness abnormal region model block;

[0040] Acquire a plurality of instantaneous surface cooling temperature data of each hardness abnormal area model block at a continuous preset cooling node when it is cooled by a cooling molding module, calculate the cumulative deviation of each instantaneous surface cooling temperature data for each preset cooling node, and obtain a plurality of cumulative deviation values;

[0041] Calculating the Hurst index of a plurality of instantaneous surface cooling temperature data according to the plurality of accumulated deviation values, and determining the fluctuation state of the instantaneous surface cooling temperature in each hardness abnormal region model according to the Hurst index;

[0042] Obtaining the pressure injection rate of each hardness abnormal area model block to generate the fluctuation state, introducing the maximum likelihood method, and calculating the probability of the pressure injection rate causing the hardness abnormal area model to generate the corresponding actual hardness test coefficient based on the fluctuation state in the maximum likelihood method to obtain multiple probability values;

[0043] If the probability value is greater than the preset probability value, the pressure injection rate control strategy of the production hardness abnormal area model is controlled and optimized; if the probability value is less than the preset probability value, the cooling control strategy of the production hardness abnormal area model is controlled and optimized to obtain a control strategy optimization solution.

[0044] More specifically, the step S108 includes the following steps:

[0045] The automatic eyebrow pencil core pressure filling equipment is controlled and produced through the pressure filling control scheme, the control strategy optimization scheme and the cooling molding control scheme, and the finished eyebrow pencil core sample is output;

[0046] Constructing a multi-dimensional registration domain and an eyebrow pencil core sample model, dividing the eyebrow pencil core sample model into N sub-model domains in the multi-dimensional registration domain, creating an expected sample model of the eyebrow pencil core according to production and processing requirements, registering and calculating the overlap rate between the eyebrow pencil core sample model and the expected sample model of the eyebrow pencil core, and obtaining the model overlap rate of each sub-model domain;

[0047] Only the sub-model area corresponding to the model overlap rate less than the preset model overlap rate is extracted, marked as the defect model area, the image information of the defect model area is obtained, and the molding defect contour and texture of each defect model area are obtained by extracting the feature vector in the image information;

[0048] Obtain the historical working condition timestamps and corresponding historical control postures of the molding defects in each production and processing module of the automatic eyebrow pencil core pressure filling equipment, and bundle the historical working condition timestamps and corresponding historical control postures into a suspected abnormal control text package;

[0049] The mean shift clustering algorithm is introduced to initialize the centroid of each suspected abnormal control text package, traverse the neighboring points corresponding to each molding defect contour and texture near the centroid and calculate the mean of each neighboring point, and update the current position of the iterative centroid based on the mean to form multiple centroid clusters;

[0050] Construct a control network knowledge graph for the automatic eyebrow pencil refill pressure filling equipment, calculate the Euclidean distance between each molding defect contour and texture and each centroid, assign each molding defect contour and texture to the centroid cluster corresponding to the minimum Euclidean distance, and finally output the abnormal control cluster label of each molding defect contour and texture;

[0051] The abnormal control clustering labels are injected into the control network knowledge graph for identification and matching, and the abnormal control parameters of the molding defect contour and texture generated by each suspected abnormal control text package are obtained. The hash function between the abnormal control parameters and the standard control parameters is calculated, and the abnormal control parameters are adjusted according to the hash function to obtain a control calibration scheme.

[0052] A second aspect of the present invention provides an automatic eyebrow pencil refill pressure filling one-piece molding control system, the automatic eyebrow pencil refill pressure filling one-piece molding control system includes a memory and a processor, the memory stores an automatic eyebrow pencil refill pressure filling one-piece molding control method program, when the automatic eyebrow pencil refill pressure filling one-piece molding control method program is executed by the processor, any one of the steps of the automatic eyebrow pencil refill pressure filling one-piece molding control method is implemented.

[0053] The present invention solves the technical defects existing in the background technology, and the beneficial technical effects of the present invention are:

[0054] The production and processing requirements of the eyebrow pencil core are obtained, and a sparse dictionary for generating a continuous color gradient image expression under a time-series heating parameter interval is constructed. The production and processing requirements are queried and identified through the sparse dictionary to obtain the time-series heating parameter set required for the target color number; the material properties of the raw material of the eyebrow pencil core in a molten state are obtained based on the time-series heating parameter set, and an internal stress distribution thermodynamic map of the eyebrow pencil core is drawn and established according to the stress test under the material properties, and the pressure filling parameters of the eyebrow pencil core are controlled by analyzing the stress distribution thermodynamic map to obtain a pressure filling control scheme; the incremental amplitude of the cooling abnormal state for the internal stress migration trend is calculated through the internal stress distribution thermodynamic map group, and whether the incremental amplitude meets the preset requirements is analyzed to optimize the pressure filling strategy, the cooling strategy or control the cooling molding parameters, and obtain a control strategy optimization scheme and a cooling molding control scheme; the molding defect contour and texture of the eyebrow pencil core sample model compared with the expected sample model of the eyebrow pencil core are obtained, the molding defect contour and texture are clustered into abnormal control deviation behavior, and abnormal control clustering labels are generated, and the abnormal control parameters are adjusted according to the abnormal control clustering labels to obtain a control deviation calibration scheme. The present invention can accurately control and reasonably optimize the automatic pressure filling production of the eyebrow pencil core, so as to improve the completeness of the pressure filling integrated molding of the eyebrow pencil core and ensure the overall quality and efficiency of the eyebrow pencil core. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, drawings of other embodiments can be obtained based on these drawings without paying creative work.

[0056] Figure 1 A first method flow chart of a method for controlling pressure filling and integrated molding of an automatic eyebrow pencil core is shown;

[0057] Figure 2 A second method flow chart of an automatic eyebrow pencil core pressure filling integrated molding control method is shown;

[0058] Figure 3 The system framework diagram of an automatic eyebrow pencil core pressure filling integrated molding control system is shown. DETAILED DESCRIPTION

[0059] In order to more clearly understand the above-mentioned purpose, features and advantages of the present invention, the present invention is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0060] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Therefore, the protection scope of the present invention is not limited to the specific embodiments disclosed below.

[0061] The first aspect of the present invention provides a method for controlling pressure injection and integrated molding of an automatic eyebrow pencil core. Figure 1 As shown, the following steps are included:

[0062] S102: Obtaining production and processing requirements of eyebrow pencil refills, constructing a sparse dictionary for generating a continuous color gradient image expression under a time-series heating parameter range, querying and identifying the production and processing requirements through the sparse dictionary, and obtaining a time-series heating parameter set required for a target color number;

[0063] S104: obtaining material properties of the raw material of the eyebrow pencil core in a molten state based on the time-series heating parameter set, drawing and establishing an internal stress distribution thermodynamic map of the eyebrow pencil core according to the stress test under the material properties, and controlling the pressure filling parameters of the eyebrow pencil core by analyzing the stress distribution thermodynamic map to obtain a pressure filling control scheme;

[0064] S106: redrawing the internal stress distribution heat map group after control tuning through the pressure injection control scheme, calculating the incremental amplitude of the cooling abnormal state for the internal stress migration trend through the internal stress distribution heat map group, analyzing whether the incremental amplitude meets the preset requirements to optimize the pressure injection strategy, the cooling strategy or control the cooling molding parameters, and obtaining the control strategy optimization scheme and the cooling molding control scheme;

[0065] S108: Obtain the molding defect contour and texture of the eyebrow pencil core sample model compared with the expected sample model of the eyebrow pencil core, cluster the molding defect contour and texture into a suspected abnormal control text package, generate an abnormal control clustering label, adjust the abnormal control parameters according to the abnormal control clustering label, and obtain a control calibration plan.

[0066] More specifically, the step S102 is as follows: Figure 2 As shown, the specific steps include:

[0067] S202: Obtaining production and processing requirements of eyebrow pencil refills, and extracting several kinds of raw materials of eyebrow pencil refills and predetermined addition ratio parameters of each raw material of eyebrow pencil refills according to the production and processing requirements;

[0068] S204: Based on the predetermined addition ratio parameter, a maximum melting point critical value for mixing and heating all raw materials of the eyebrow pencil core until they are fully melted and combined with each other is retrieved in the big data network, and an initial design drawing of an automatic eyebrow pencil core pressure filling device is obtained;

[0069] S206: constructing a multi-dimensional simulation model of an automatic eyebrow pencil core pressure filling device according to the initial design drawing, injecting the maximum melting point critical value into the multi-dimensional simulation model to simulate heating, so as to obtain multiple groups of continuous color gradient image data in the process of the raw material of the eyebrow pencil core gradually approaching the maximum melting point critical value;

[0070] S208: obtaining a time-series heating parameter interval of the process in which the raw material of the eyebrow pencil core gradually approaches the maximum melting point critical value, constructing a Gaussian random matrix, introducing a sparse coding algorithm to solve the sparse basis function representation of multiple groups of continuous color gradient image data in the Gaussian random matrix, and obtaining a sparse coefficient between two adjacent color gradient images;

[0071] S210: During the sparse coding process, a sparse basis function threshold is preset based on each group of temporal heating parameters in the temporal heating parameter interval, and a sparse basis function in a Gaussian random matrix is ​​iteratively updated according to a sparse coefficient between two adjacent color gradient images until the sparse basis function is less than the sparse basis function threshold, and the iterative update is stopped to obtain a sparse dictionary for expressing a continuous color gradient image under the temporal heating parameter interval;

[0072] S212: Obtain a sparse code of a target color number of the eyebrow pencil core according to production and processing requirements, perform a sparse query on the sparse code of the target color number through a sparse dictionary, and output a set of sequential heating parameters required for the target color number.

[0073] It should be noted that eyebrow pencil refills are cosmetic tools used to draw and modify eyebrows. Their main raw materials are usually a mixture of wax, oil, pigment, etc., and since the properties of different eyebrow pencil refill raw materials change after heating and mixing, proper control of the heating temperature can ensure the color stability of the refill. For example, if the heating temperature is too high or too low, the pigment may decompose or change color, resulting in uneven color or obvious color difference when the eyebrow pencil is colored, thus affecting its coloring effect on the eyebrows. Therefore, in order to ensure the production of the required color number, it is very important to control the appropriate heating parameters of the eyebrow pencil refill raw materials. However, if the heating parameters are not controlled according to the adaptability of the required color number of the eyebrow pencil refill during pressure filling of the eyebrow pencil refill, the color number of the eyebrow pencil refill produced may deviate from the target color number, reducing the pressure filling quality of the eyebrow pencil refill product and failing to meet the production and sales requirements of the eyebrow pencil refill. This method constructs a sparse dictionary describing the correlation between multiple groups of continuous color gradient image data and their corresponding sequential heating parameter intervals in the process of the heating temperature of the raw materials of the eyebrow pencil core gradually approaching the maximum melting point critical value. The sparse dictionary expresses the sparse features of the different colors of the eyebrow pencil core raw materials in the process of reaching the maximum melting point critical value and the corresponding required sequential heating parameter values. Then, the target color number of the eyebrow pencil core is sparsely encoded and queried in the sparse dictionary, and the sparse features required for the target color number can be matched. The sparse features describe the required sequential heating parameter set. This method can quickly match and query the accurate heating parameters required to produce the eyebrow pencil core of the target color number, thereby improving the heating control accuracy of the target color number when the automatic eyebrow pencil core is pressure-filled, ensuring that the materials are mixed evenly, effectively improving the heating stability of the raw materials of the eyebrow pencil core, and ensuring that it meets the production requirements of the eyebrow pencil core.

[0074] More specifically, the step S104 includes the following steps:

[0075] According to the time sequence heating parameter set required by the target color number, the heating module of the automatic eyebrow pencil core pressure filling device is controlled to perform heating and melting processing on all the raw materials of the eyebrow pencil core, and at this time, the material properties of the raw materials of the eyebrow pencil core in a molten state are obtained;

[0076] Obtain a historical product evaluation report of an eyebrow pencil refill, and extract a number of internal stress test values ​​and a distribution pattern of stress test values ​​corresponding to the eyebrow pencil refill produced by an automatic eyebrow pencil refill pressure filling device under the material characteristic conditions through the historical product evaluation report;

[0077] Obtain a standard product model diagram of an eyebrow pencil core, construct a heat map framework based on the standard product model diagram, introduce an inverse distance weighted algorithm, and preset a weight power, a search radius, and a number of neighboring points in the inverse distance weighted algorithm according to the distribution pattern of stress test values;

[0078] Define each stress test value as a point to be estimated, calculate the spatial distance value between the current point to be estimated and the adjacent point to be estimated based on the weight power, the search radius and the number of adjacent points, and determine the distance weight between the current point to be estimated and the adjacent point to be estimated according to the spatial distance value;

[0079] The inverse distance weighted interpolation of each point to be estimated is estimated by combining the internal stress test value of the current point to be estimated with the distance weight, a regional grid of all points to be estimated is constructed, and the inverse distance weighted interpolation of each point to be estimated is inserted into the center point of the corresponding regional grid, and finally a heat map of the internal stress distribution of the eyebrow pencil core is generated;

[0080] The ideal density coefficient of the eyebrow pencil core is extracted according to the production and processing requirements, and based on the ideal density coefficient, the optimal internal stress distribution point of the eyebrow pencil core to achieve the ideal density coefficient under the material property conditions and the corresponding optimal internal stress color value range are obtained in the big data network;

[0081] Extracting the actual internal stress color value of the optimal internal stress distribution point in the internal stress distribution thermodynamic map; if the actual internal stress color value is not within the optimal internal stress color value range, extracting the lower limit value of the optimal internal stress color value range, and calculating the hash state function between the lower limit value and the actual internal stress color value;

[0082] The pressure filling time node generating the actual internal stress color value is obtained, and the pressure filling parameters at the pressure filling time node are controlled according to the hash state function to obtain a pressure filling control scheme.

[0083] It should be noted that during the pressure-filled integrated molding process of the eyebrow pencil core, the control of pressure also has an important impact on the quality and performance of the eyebrow pencil core. If the pressure is too high, it may cause an increase in the internal stress of the raw material, thereby shortening the long-term stability and service life of the eyebrow pencil core, making the eyebrow pencil core more prone to brittleness and breakage during use, and reducing the overall pressure-filled quality of the eyebrow pencil core product. Therefore, it is necessary to test and analyze the internal stress and distribution of the eyebrow pencil core after pressure filling. First, the internal stress data and the distribution pattern of the data are tested, and then a heat map expressing the changes in the internal stress of the eyebrow pencil core is constructed based on the internal stress data and the distribution pattern to further visualize the analysis of the impact of stress on the quality of the eyebrow pencil core. The construction of the heat map can greatly improve the analysis accuracy and efficiency of the internal stress changes, reduce the calculation steps, and effectively ensure the reliability of the internal stress analysis results. Since the production of eyebrow pencil cores will set certain density coefficient requirements, and the density coefficient can reflect the quality of the eyebrow pencil core, in order to achieve the ideal density coefficient, it is necessary to ensure that the stress of the eyebrow pencil core is in the best position, that is, the best internal stress distribution point, to avoid the phenomenon of excessive internal stress concentration. Therefore, it is finally determined whether the actual internal stress color value of the best internal stress distribution point of the eyebrow pencil core is within the best internal stress color value range. If not, it means that the eyebrow pencil core may have an increase or concentration of internal stress. This is due to improper control of the pressure filling parameters at the pressure filling time node where the internal stress concentration or increase phenomenon occurs during the pressure filling process. Therefore, it is necessary to reasonably control the pressure filling parameters. This method can accurately and reasonably control the pressure filling parameters during the pressure filling of the eyebrow pencil core, thereby avoiding the phenomenon of internal stress concentration or increase in the eyebrow pencil core, and improving the overall service life and coloring quality of the eyebrow pencil core.

[0084] More specifically, the step S106 includes the following steps:

[0085] The pressure injection of the eyebrow pencil core is controlled and optimized through the pressure injection control scheme, and the internal stress distribution heat map group on the continuous time series after the control optimization of the eyebrow pencil core is redrawn;

[0086] If the actual internal stress color value of the optimal internal stress distribution point after control optimization is still not within the optimal internal stress color value range, then obtain several groups of cooling control change parameters of the cooling molding module for material properties when executing the pressure filling control scheme during the pressure filling process of the eyebrow pencil core;

[0087] Based on the big data network, the material variation index of the material characteristics under different cooling control variation parameters is obtained, and the cooling variation state of the raw material of the eyebrow pencil core by the cooling molding module is determined according to the material variation index and several groups of cooling control variation parameters;

[0088] Extract the migration distribution nodes of each internal stress test value continuous variable in the optimal internal stress distribution point of the eyebrow pencil core through the internal stress distribution heat map group in the continuous time series after the eyebrow pencil core control optimization, and determine the internal stress migration trend of the eyebrow pencil core according to the migration distribution nodes;

[0089] A trade-off algorithm is introduced to calculate the Gini coefficient between the cooling abnormal state and the internal stress migration trend, a smoothing parameter between the cooling abnormal state and the internal stress migration trend is determined according to the Gini coefficient, and a smoothing spline regression model is constructed according to the smoothing parameter;

[0090] Obtaining a spline basis function of a smoothing spline regression model and a kernel function of a cooling abnormal state at different migration distribution nodes, calculating second-order derivatives between several groups of cooling control change parameters and each internal stress test value by fitting the spline basis function and the kernel function, and determining the incremental amplitude of the cooling abnormal state for the internal stress migration trend according to the second-order derivative;

[0091] If the increment is less than the allowable increment, the probability of the eyebrow pencil core material generating the corresponding actual hardness test coefficient due to the pressure injection rate is calculated and analyzed to optimize the control strategy, thereby obtaining the control strategy optimization scheme;

[0092] If the incremental amplitude is greater than the allowable incremental amplitude, the deviation between the incremental amplitude and the allowable incremental amplitude is quantified to obtain a quantized value of the incremental amplitude deviation, and the cooling forming parameters are controlled according to the quantized value of the incremental amplitude deviation to obtain a cooling forming control scheme.

[0093] It should be noted that in the process of pressure-filling integrated molding of eyebrow pencil core, the control of the cooling stage also has an important influence on the quality and performance of the eyebrow pencil. Proper control of cooling parameters can ensure the stability of the molecular structure inside the core material, avoid internal stress concentration or stratification, ensure that the core maintains consistent performance during use, and improve the hardness and toughness of the eyebrow pencil core; but if improper control of cooling parameters leads to uneven or too fast cooling, it may cause uneven shrinkage of the core material, and eventually cause deformation, bending or internal stress of the eyebrow pencil core, affecting the feel, touch and coloring effect during use. The speed of the pressure filling rate of the eyebrow pencil core will directly affect the cooling effect. For example, if the pressure filling rate is too fast, the internal material of the eyebrow pencil core cannot be fully cooled, thereby increasing the internal stress of the eyebrow pencil core. Therefore, it is necessary to formulate a reasonable control plan and strategy optimization for the cooling parameters during the pressure filling process of the eyebrow pencil core to reduce the abnormal stress phenomenon of the eyebrow pencil core caused by cooling errors. The method analyzes the material variation index and cooling control variation parameters of the material properties under different cooling control variation parameters during the pressure filling process of the eyebrow pencil core, thereby obtaining the cooling variation state of the eyebrow pencil core material and the internal stress migration trend of the eyebrow pencil core due to the cooling control variation parameters, and further constructs a smoothing spline regression model to calculate the incremental amplitude of the cooling variation state for the internal stress migration trend. The incremental amplitude is the unit increase amplitude of the internal stress of the eyebrow pencil core when the cooling control changes, which can reflect the influence of the cooling molding parameters on the quality of the eyebrow pencil core material, so as to control the pressure filling behavior and cooling behavior of the eyebrow pencil core in a targeted manner, improve the balance and stability of the cooling and pressure filling of the eyebrow pencil core, reduce the probability of improper cooling control affecting the quality of the eyebrow pencil core, and ensure the integrity of the eyebrow pencil core formed by pressure filling.

[0094] It should be noted that the material variation index is an index of changes or variations in the material structure of the eyebrow pencil core under the cooling control change parameters. It can express the impact of changes in cooling parameters on the internal materials of the eyebrow pencil core, provide accurate analysis basis for subsequent incremental amplitude calculation, and improve the accuracy of parameter control. If the incremental amplitude is less than the allowable incremental amplitude, it means that the stress increase in the internal material structure of the eyebrow pencil core is not caused by improper cooling and molding parameters. It is mainly due to the excessive pressure injection rate that the internal material of the eyebrow pencil core cannot be fully cooled, so it is necessary to adjust the pressure injection strategy and cooling control strategy; if the incremental amplitude is greater than the allowable incremental amplitude, it means that the unreasonable cooling molding parameters have caused the internal stress of the eyebrow pencil core to increase in unit amount and migrate in a concentrated manner, so it is necessary to rationalize the cooling molding parameter control of the cooling molding module to improve the cooling quality of the eyebrow pencil core, avoid the phenomenon of abnormal stress of the internal material of the eyebrow pencil core caused by cooling errors, and have high control reliability.

[0095] More specifically, if the increment amplitude in step S106 is less than the allowable increment amplitude, the probability of the eyebrow pencil core material generating the corresponding actual hardness test coefficient due to the pressure injection rate is calculated and analyzed to optimize the control strategy, and a control strategy optimization scheme is obtained, which specifically includes the following steps:

[0096] If the increment amplitude is less than the allowable increment amplitude, the cooling station specification parameters of the cooling molding module are obtained, and the area definition threshold is preset based on the cooling station specification parameters;

[0097] Constraining the defined range in the optimal internal stress distribution point in the eyebrow pencil core until the region definition threshold is reached, obtaining the cooling station range, and obtaining the preset cooling strategy executed by the cooling molding module for the optimal internal stress distribution point in the eyebrow pencil core at multiple preset cooling nodes;

[0098] Constructing a regional model of the cooling station range, obtaining a cooling point pattern map according to a preset cooling strategy, dividing the regional model of the cooling station range into a plurality of sub-regional model blocks based on the cooling point pattern map, and obtaining an actual hardness test coefficient of each sub-regional model block;

[0099] According to the production and processing requirements, the expected hardness coefficient range of the eyebrow pencil core is obtained, and only the sub-region model block whose actual hardness test coefficient is not within the expected hardness coefficient range is marked, and defined as the hardness abnormal region model block;

[0100] Acquire a plurality of instantaneous surface cooling temperature data of each hardness abnormal area model block at a continuous preset cooling node when it is cooled by a cooling molding module, calculate the cumulative deviation of each instantaneous surface cooling temperature data for each preset cooling node, and obtain a plurality of cumulative deviation values;

[0101] Calculating the Hurst index of a plurality of instantaneous surface cooling temperature data according to the plurality of accumulated deviation values, and determining the fluctuation state of the instantaneous surface cooling temperature in each hardness abnormal region model according to the Hurst index;

[0102] Obtaining the pressure injection rate of each hardness abnormal area model block to generate the fluctuation state, introducing the maximum likelihood method, and calculating the probability of the pressure injection rate causing the hardness abnormal area model to generate the corresponding actual hardness test coefficient based on the fluctuation state in the maximum likelihood method to obtain multiple probability values;

[0103] If the probability value is greater than the preset probability value, the pressure injection rate control strategy of the production hardness abnormal area model is controlled and optimized; if the probability value is less than the preset probability value, the cooling control strategy of the production hardness abnormal area model is controlled and optimized to obtain a control strategy optimization solution.

[0104] It should be noted that if the incremental amplitude is less than the allowable incremental amplitude, the cooling molding parameters have little effect on the internal material structure of the eyebrow pencil core. When the cooling molding parameters do not affect the internal material structure of the eyebrow pencil core, the actual internal stress color value of the optimal internal stress distribution point is still not within the optimal internal stress color value range. This may be due to the fact that the pressure injection rate of the eyebrow pencil core material is too fast under the reasonable cooling molding parameter conditions, causing the internal material to be unable to be fully cooled, or the cooling position of the eyebrow pencil core material by the cooling station is unreasonable, resulting in the stress concentration or increase of the internal material of the eyebrow pencil core injected by pressure. Therefore, this method can be based on the fluctuation state of the instantaneous surface temperature when the eyebrow pencil core material is processed according to the cooling station of the cooling molding module when the incremental amplitude is less than the allowable incremental amplitude, and further analyze the probability relationship of the pressure injection rate causing the eyebrow pencil core material to generate a substandard hardness test coefficient, so as to determine the corresponding control optimization strategy required when the actual internal stress color value is still not within the optimal internal stress color value range through probability analysis. Through this method, correct control optimization measures can be taken to adjust the pressure injection rate and cooling position to eliminate the abnormal stress phenomenon of the internal material of the pressure-injected eyebrow pencil core, improve the qualified rate of the pressure-injected toughness and hardness of the eyebrow pencil core material, improve the quality and efficiency of the pressure-injected one-piece molding of the eyebrow pencil core, and help improve the overall coloring quality and effect of the eyebrow pencil core. Among them, the cumulative deviation is an important parameter for calculating the instantaneous surface temperature fluctuation state, which aims to improve the timing dependence of the instantaneous surface cooling temperature data and each preset cooling node, ensure the accuracy of the expression of the fluctuation state, and reduce the result analysis error.

[0105] More specifically, the step S108 includes the following steps:

[0106] The automatic eyebrow pencil core pressure filling equipment is controlled and produced through the pressure filling control scheme, the control strategy optimization scheme and the cooling molding control scheme, and the finished eyebrow pencil core sample is output;

[0107] Constructing a multi-dimensional registration domain and an eyebrow pencil core sample model, dividing the eyebrow pencil core sample model into N sub-model domains in the multi-dimensional registration domain, creating an expected sample model of the eyebrow pencil core according to production and processing requirements, registering and calculating the overlap rate between the eyebrow pencil core sample model and the expected sample model of the eyebrow pencil core, and obtaining the model overlap rate of each sub-model domain;

[0108] Only the sub-model area corresponding to the model overlap rate less than the preset model overlap rate is extracted, marked as the defect model area, the image information of the defect model area is obtained, and the molding defect contour and texture of each defect model area are obtained by extracting the feature vector in the image information;

[0109] Obtain the historical working condition timestamps and corresponding historical control postures of the molding defects in each production and processing module of the automatic eyebrow pencil core pressure filling equipment, and bundle the historical working condition timestamps and corresponding historical control postures into a suspected abnormal control text package;

[0110] The mean shift clustering algorithm is introduced to initialize the centroid of each suspected abnormal control text package, traverse the neighboring points corresponding to each molding defect contour and texture near the centroid and calculate the mean of each neighboring point, and update the current position of the iterative centroid based on the mean to form multiple centroid clusters;

[0111] Construct a control network knowledge graph for the automatic eyebrow pencil refill pressure filling equipment, calculate the Euclidean distance between each molding defect contour and texture and each centroid, assign each molding defect contour and texture to the centroid cluster corresponding to the minimum Euclidean distance, and finally output the abnormal control cluster label of each molding defect contour and texture;

[0112] The abnormal control clustering labels are injected into the control network knowledge graph for identification and matching, and the abnormal control parameters of the molding defect contour and texture generated by each suspected abnormal control text package are obtained. The hash function between the abnormal control parameters and the standard control parameters is calculated, and the abnormal control parameters are adjusted according to the hash function to obtain a control calibration scheme.

[0113] It should be noted that molding defects include bubbles, voids, cracks, bends and dents. The automatic eyebrow pencil core pressure filling equipment is a mechanical device. When the equipment is in long-term operation or regular maintenance is not performed, it is inevitable that the control parameters of a certain production and processing module will deviate from the standard control parameters when the eyebrow pencil core material is pressure filled, causing the production and processing module to have abnormal control deviation behavior. These abnormal control deviation behaviors may cause molding defects with different contours and textures on the eyebrow pencil core material. For example, when the pressure filling module produces inappropriate parameters of abnormal pressure filling control deviation, it will cause molding shape defects such as bubbles, voids or cracks on the surface of the eyebrow pencil core material. Therefore, accurately calibrating and repairing these abnormal control deviation behaviors is crucial for the pressure filling production of eyebrow pencil refills; to address the above problems, this method accurately clusters the molding defect contours and textures on the eyebrow pencil refill sample model on the suspected abnormal control text packages of each production and processing module that cause these molding defect contours and textures, thereby accurately locating and tracing the abnormal control parameters that cause these molding defect contours and textures in the pressure filling production process of the production and processing module, so that the abnormal control parameters can be further regulated and calibrated, so as to intelligently eliminate the phenomenon of frequent molding defects caused by abnormal control of the automatic eyebrow pencil refill pressure filling equipment, achieve the adaptive control abnormal optimization effect of the automatic eyebrow pencil refill pressure filling equipment, improve the integrity of the one-piece molding of the eyebrow pencil refill pressure filling, and greatly improve the economic benefits and reliability.

[0114] In addition, the automatic eyebrow pencil core pressure filling integrated molding control method further includes the following steps:

[0115] The surface flaw detection of the eyebrow pencil core sample after pressure filling is performed by an ultrasonic flaw detector to obtain a plurality of surface flaw detection waveform data of the eyebrow pencil core sample;

[0116] Preset multiple control points, introduce the NURBS curve method to embed the surface flaw detection waveform data of the eyebrow pencil core sample, and obtain the NURBS curve of each surface flaw detection waveform of the eyebrow pencil core sample;

[0117] A finite difference algorithm is introduced, and based on multiple control points, the NURBS curve of each surface flaw detection waveform is converted into a partial differential equation group in the finite difference algorithm, and the partial differential equation group is solved to obtain the actual surface flaw detection waveform equation solution of each surface flaw detection waveform;

[0118] Obtaining reference surface flaw detection waveform data of the eyebrow pencil core installation slot, constructing a NURBS curve of the reference surface flaw detection waveform, transforming and solving the NURBS curve of the reference surface flaw detection waveform, and obtaining a solution to the reference surface flaw detection waveform equation of the eyebrow pencil core installation slot;

[0119] Preset an allowable equation solution difference interval, calculate the equation solution difference between the actual surface flaw detection waveform equation solution and the reference surface flaw detection waveform equation solution, and if the equation solution difference is within the allowable equation solution difference interval, mark the eyebrow pencil core sample as a qualified product and output it;

[0120] If the difference of the solution to the equation is not within the allowable difference interval of the solution to the equation, the eyebrow pencil core sample is marked as an unqualified product and added to the list of defective products, thereby obtaining an eyebrow pencil core detection control decision.

[0121] It should be noted that after the production of the eyebrow pencil core is completed, it is usually necessary to install it in a dedicated eyebrow pencil shell for the convenience of users. Therefore, the size of the eyebrow pencil core installation slot of the eyebrow pencil shell should be highly consistent with the eyebrow pencil core that is pressure-filled. However, if the surface of the eyebrow pencil core has phenotypic defects such as bending, deformation or depression, it may cause the eyebrow pencil core to be unable to form a highly consistent installation relationship with the eyebrow pencil core installation slot, making it difficult to install the eyebrow pencil core in the eyebrow pencil shell, greatly reducing the scrap rate of eyebrow pencil product production, increasing production cost output, and significantly reducing economic benefits. Therefore, this method can convert the waveform data of the surface flaw detection of the eyebrow pencil core by the ultrasonic flaw detector into a NURBS curve, and obtain the equation solution by solving the partial differential equation of the NURBS curve. By comparing the difference between the actual equation solution and the reference equation solution of the eyebrow pencil core installation slot, it can be determined whether the eyebrow pencil core fits the eyebrow pencil shell, thereby further determining whether the eyebrow pencil core is qualified. This method can be used to inspect the quality of eyebrow pencil refills during pressure filling, improve the quality of eyebrow pencil refill product assembly, avoid a high scrap rate, and have high economic benefits. Among them, the Chinese name of the NURBS curve is non-uniform rational B-spline curve, which is a curve and surface used to accurately describe complex and subtle data changes. The NURBS curve can accurately represent complex surface flaw detection waveform surfaces, improve the accuracy of subsequent partial differential equation conversion expression, reduce the error of solving equations, and improve the reliability of product appearance surface comparison detection.

[0122] In addition, the automatic eyebrow pencil core pressure filling integrated molding control method further includes the following steps:

[0123] Obtaining evaluation data of eyebrow pencil refill products, extracting a number of effect evaluation assessment indicators through the evaluation data, and obtaining an expected effect evaluation threshold value of each effect evaluation assessment indicator;

[0124] Draw and construct an effect evaluation radar chart according to each of the expected effect evaluation thresholds, and extract the user's effect reaching evaluation radar area for the eyebrow pencil refill product through the effect evaluation radar chart;

[0125] Obtain the actual effect evaluation radar area of ​​the current eyebrow pencil core product, remove the radar area that overlaps between the effect standard evaluation radar area and the actual effect evaluation radar area in the effect evaluation radar chart, and obtain the area value of the non-overlapping radar area;

[0126] Acquire actual control parameters when each production and processing module in the automatic eyebrow pencil refill pressure filling equipment pressure fills the eyebrow pencil refill product, introduce the Spearson correlation coefficient to calculate the correlation between the actual control parameters and the area value, and obtain multiple correlations;

[0127] Extract the production and processing modules corresponding to the correlation degree greater than the preset correlation degree, mark them as abnormal production and processing modules, obtain the working condition data of each abnormal production and processing module, introduce the Bayesian inference algorithm to calculate the defective rate of defective products produced when the eyebrow pencil core product is pressure-filled under the working condition data conditions, and obtain multiple defective rates;

[0128] If the defective rate is greater than the preset defective rate, the abnormal production and processing module with the defective rate greater than the preset defective rate will be marked as an abnormal fault module, and the working condition data of the abnormal fault module will be operated and maintained.

[0129] It should be noted that after the pressure filling of the eyebrow pencil refill is completed, in order to further understand the product quality, a series of product effect evaluations can reflect the quality of the product's pressure filling. If the actual effect evaluation result of the eyebrow pencil refill is significantly deviated from the expected effect evaluation result, it means that a certain production and processing module of the automatic eyebrow pencil refill pressure filling equipment may have an abnormality or failure in the production of the eyebrow pencil refill, resulting in the final eyebrow pencil refill product effect failing to meet the standard. Therefore, this method can trace the faulty production and processing module of the automatic eyebrow pencil refill pressure filling equipment that causes the eyebrow pencil refill to fail to meet the standard, and perform operation and maintenance control on it, so as to repair the error of the production and processing module in the integrated molding of the eyebrow pencil refill pressure filling, reduce the defective rate of defective eyebrow pencil refills, and improve the coloring effect quality of the eyebrow pencil refill.

[0130] The second aspect of the present invention provides an automatic eyebrow pencil core pressure filling integrated molding control system, such as Figure 3 As shown, the automatic eyebrow pencil core pressure filling one-piece molding control system includes a memory 31 and a processor 32, and the memory 31 stores an automatic eyebrow pencil core pressure filling one-piece molding control method program. When the automatic eyebrow pencil core pressure filling one-piece molding control method program is executed by the processor 32, any one of the steps of the automatic eyebrow pencil core pressure filling one-piece molding control method is implemented.

[0131] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art who is familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for controlling pressure filling and integrated molding of automatic eyebrow pencil core, characterized in that: The following steps are involved: S102: Obtaining production and processing requirements of eyebrow pencil refills, constructing a sparse dictionary for generating a continuous color gradient image expression under a time-series heating parameter range, querying and identifying the production and processing requirements through the sparse dictionary, and obtaining a time-series heating parameter set required for a target color number; S104: obtaining material properties of the raw material of the eyebrow pencil core in a molten state based on the time-series heating parameter set, drawing and establishing an internal stress distribution thermodynamic map of the eyebrow pencil core according to the stress test under the material properties, and controlling the pressure filling parameters of the eyebrow pencil core by analyzing the stress distribution thermodynamic map to obtain a pressure filling control scheme; S106: redrawing the internal stress distribution heat map group after control tuning through the pressure injection control scheme, calculating the incremental amplitude of the cooling abnormal state for the internal stress migration trend through the internal stress distribution heat map group, analyzing whether the incremental amplitude meets the preset requirements to optimize the pressure injection strategy, the cooling strategy or control the cooling molding parameters, and obtaining the control strategy optimization scheme and the cooling molding control scheme; S108: Obtain the molding defect contour and texture of the eyebrow pencil core sample model compared with the expected sample model of the eyebrow pencil core, cluster the molding defect contour and texture into a suspected abnormal control text package, generate an abnormal control clustering label, adjust the abnormal control parameters according to the abnormal control clustering label, and obtain a control calibration plan.

2. The automatic eyebrow pencil core pressure filling integrated molding control method according to claim 1, characterized in that: The step S102 specifically includes the following steps: Obtain production and processing requirements for eyebrow pencil refills, and extract several kinds of raw materials for eyebrow pencil refills and the established addition ratio parameters of each raw material of eyebrow pencil refills through the production and processing requirements; Based on the predetermined addition ratio parameter, the maximum melting point critical value for mixing and heating all raw materials of the eyebrow pencil core until they are fully melted and combined with each other is retrieved in the big data network, and the initial design drawing of the automatic eyebrow pencil core pressure filling device is obtained; A multi-dimensional simulation model of an automatic eyebrow pencil core pressure filling device is constructed according to the initial design draft, and a maximum melting point critical value is injected into the multi-dimensional simulation model to simulate heating, so as to obtain multiple groups of continuous color gradient image data in the process of the raw material of the eyebrow pencil core gradually approaching the maximum melting point critical value; The time-series heating parameter interval of the eyebrow pencil core raw material gradually approaching the maximum melting point critical value is obtained, a Gaussian random matrix is ​​constructed, and a sparse coding algorithm is introduced to solve the sparse basis function representation of multiple groups of continuous color gradient image data in the Gaussian random matrix, and the sparse coefficient between two adjacent color gradient images is obtained; In the sparse coding process, a sparse basis function threshold is preset based on each group of temporal heating parameters in the temporal heating parameter interval, and the sparse basis function in the Gaussian random matrix is ​​iteratively updated according to the sparse coefficient between two adjacent color gradient images until the sparse basis function is less than the sparse basis function threshold, and the iterative update is stopped to obtain a sparse dictionary for expressing a continuous color gradient image under the temporal heating parameter interval; The target color number sparse code of the eyebrow pencil core is obtained according to the production and processing requirements, the target color number sparse code is sparsely queried through a sparse dictionary, and the timing heating parameter set required for the target color number is output.

3. The automatic eyebrow pencil core pressure filling integrated molding control method according to claim 1, characterized in that: The step S104 specifically includes the following steps: According to the time sequence heating parameter set required by the target color number, the heating module of the automatic eyebrow pencil core pressure filling device is controlled to perform heating and melting processing on all the raw materials of the eyebrow pencil core, and at this time, the material properties of the raw materials of the eyebrow pencil core in a molten state are obtained; Obtain a historical product evaluation report of an eyebrow pencil refill, and extract a number of internal stress test values ​​and a distribution pattern of stress test values ​​corresponding to the eyebrow pencil refill produced by an automatic eyebrow pencil refill pressure filling device under the material characteristic conditions through the historical product evaluation report; Obtain a standard product model diagram of an eyebrow pencil core, construct a heat map framework based on the standard product model diagram, introduce an inverse distance weighted algorithm, and preset a weight power, a search radius, and a number of neighboring points in the inverse distance weighted algorithm according to the distribution pattern of stress test values; Define each stress test value as a point to be estimated, calculate the spatial distance value between the current point to be estimated and the adjacent point to be estimated based on the weight power, the search radius and the number of adjacent points, and determine the distance weight between the current point to be estimated and the adjacent point to be estimated according to the spatial distance value; The inverse distance weighted interpolation of each point to be estimated is estimated by combining the internal stress test value of the current point to be estimated with the distance weight, a regional grid of all points to be estimated is constructed, and the inverse distance weighted interpolation of each point to be estimated is inserted into the center point of the corresponding regional grid, and finally a heat map of the internal stress distribution of the eyebrow pencil core is generated; The ideal density coefficient of the eyebrow pencil core is extracted according to the production and processing requirements, and based on the ideal density coefficient, the optimal internal stress distribution point of the eyebrow pencil core to achieve the ideal density coefficient under the material property conditions and the corresponding optimal internal stress color value range are obtained in the big data network; Extracting the actual internal stress color value of the optimal internal stress distribution point in the internal stress distribution thermodynamic map; if the actual internal stress color value is not within the optimal internal stress color value range, extracting the lower limit value of the optimal internal stress color value range, and calculating the hash state function between the lower limit value and the actual internal stress color value; The pressure filling time node generating the actual internal stress color value is obtained, and the pressure filling parameters at the pressure filling time node are controlled according to the hash state function to obtain a pressure filling control scheme.

4. The automatic eyebrow pencil core pressure filling integrated molding control method according to claim 1, characterized in that: The step S106 specifically includes the following steps: The pressure injection of the eyebrow pencil core is controlled and optimized through the pressure injection control scheme, and the internal stress distribution heat map group on the continuous time series after the control optimization of the eyebrow pencil core is redrawn; If the actual internal stress color value of the optimal internal stress distribution point after control optimization is still not within the optimal internal stress color value range, then obtain several groups of cooling control change parameters of the cooling molding module for material properties when executing the pressure filling control scheme during the pressure filling process of the eyebrow pencil core; Based on the big data network, the material variation index of the material characteristics under different cooling control variation parameters is obtained, and the cooling variation state of the raw material of the eyebrow pencil core by the cooling molding module is determined according to the material variation index and several groups of cooling control variation parameters; Extract the migration distribution nodes of each internal stress test value continuous variable in the optimal internal stress distribution point of the eyebrow pencil core through the internal stress distribution heat map group in the continuous time series after the eyebrow pencil core control optimization, and determine the internal stress migration trend of the eyebrow pencil core according to the migration distribution nodes; A trade-off algorithm is introduced to calculate the Gini coefficient between the cooling abnormal state and the internal stress migration trend, a smoothing parameter between the cooling abnormal state and the internal stress migration trend is determined according to the Gini coefficient, and a smoothing spline regression model is constructed according to the smoothing parameter; The second-order derivatives between several groups of cooling control variation parameters and each internal stress test value are calculated by fitting the spline basis function of the smoothing spline regression model and the kernel function of the cooling variation state at different migration distribution nodes, and the incremental amplitude of the cooling variation state for the internal stress migration trend is determined according to the second-order derivative; If the increment is less than the allowable increment, the probability of the eyebrow pencil core material generating the corresponding actual hardness test coefficient due to the pressure injection rate is calculated and analyzed to optimize the control strategy, thereby obtaining the control strategy optimization scheme; If the incremental amplitude is greater than the allowable incremental amplitude, the deviation between the incremental amplitude and the allowable incremental amplitude is quantified to obtain a quantized value of the incremental amplitude deviation, and the cooling forming parameters are controlled according to the quantized value of the incremental amplitude deviation to obtain a cooling forming control scheme.

5. The automatic eyebrow pencil core pressure filling integrated molding control method according to claim 4, characterized in that: If the increment amplitude in S106 is less than the allowable increment amplitude, the probability of the pressure injection rate causing the eyebrow pencil core material to generate the corresponding actual hardness test coefficient is calculated and analyzed to optimize the control strategy, and a control strategy optimization scheme is obtained, which specifically includes the following steps: If the increment amplitude is less than the allowable increment amplitude, the cooling station specification parameters of the cooling molding module are obtained, and the area definition threshold is preset based on the cooling station specification parameters; Constraining the defined range in the optimal internal stress distribution point in the eyebrow pencil core until the region definition threshold is reached, obtaining the cooling station range, and obtaining the preset cooling strategy executed by the cooling molding module for the optimal internal stress distribution point in the eyebrow pencil core at multiple preset cooling nodes; Constructing a regional model of the cooling station range, obtaining a cooling point pattern map according to a preset cooling strategy, dividing the regional model of the cooling station range into a plurality of sub-regional model blocks based on the cooling point pattern map, and obtaining an actual hardness test coefficient of each sub-regional model block; According to the production and processing requirements, the expected hardness coefficient range of the eyebrow pencil core is obtained, and only the sub-region model block whose actual hardness test coefficient is not within the expected hardness coefficient range is marked, and defined as the hardness abnormal region model block; Acquire a plurality of instantaneous surface cooling temperature data of each hardness abnormal area model block at a continuous preset cooling node when it is cooled by a cooling molding module, calculate the cumulative deviation of each instantaneous surface cooling temperature data for each preset cooling node, and obtain a plurality of cumulative deviation values; Calculating a number of Hurst exponents of instantaneous surface cooling temperature data according to a plurality of accumulated deviation values, and determining a fluctuation state of the instantaneous surface cooling temperature in each hardness abnormal region model according to the Hurst exponent; Obtaining the pressure injection rate of each hardness abnormal area model block to generate the fluctuation state, introducing the maximum likelihood method, and calculating the probability of the pressure injection rate causing the hardness abnormal area model to generate the corresponding actual hardness test coefficient based on the fluctuation state in the maximum likelihood method to obtain multiple probability values; If the probability value is greater than the preset probability value, the pressure injection rate control strategy of the production hardness abnormal area model is controlled and optimized; if the probability value is less than the preset probability value, the cooling control strategy of the production hardness abnormal area model is controlled and optimized to obtain a control strategy optimization solution.

6. The automatic eyebrow pencil core pressure filling integrated molding control method according to claim 1, characterized in that: The step S108 specifically includes the following steps: The automatic eyebrow pencil core pressure filling equipment is controlled and produced through the pressure filling control scheme, the control strategy optimization scheme and the cooling molding control scheme, and the finished eyebrow pencil core sample is output; Constructing a multi-dimensional registration domain and an eyebrow pencil core sample model, dividing the eyebrow pencil core sample model into N sub-model domains in the multi-dimensional registration domain, creating an expected sample model of the eyebrow pencil core according to production and processing requirements, registering and calculating the overlap rate between the eyebrow pencil core sample model and the expected sample model of the eyebrow pencil core, and obtaining the model overlap rate of each sub-model domain; Only the sub-model area corresponding to the model overlap rate less than the preset model overlap rate is extracted, marked as the defect model area, the image information of the defect model area is obtained, and the molding defect contour and texture of each defect model area are obtained by extracting the feature vector in the image information; Obtain the historical working condition timestamps and corresponding historical control postures of the molding defects in each production and processing module of the automatic eyebrow pencil core pressure filling equipment, and bundle the historical working condition timestamps and corresponding historical control postures into a suspected abnormal control text package; The mean shift clustering algorithm is introduced to initialize the centroid of each suspected abnormal control text package, traverse the neighboring points corresponding to each molding defect contour and texture near the centroid and calculate the mean of each neighboring point, and update the current position of the iterative centroid based on the mean to form multiple centroid clusters; Construct a control network knowledge graph for the automatic eyebrow pencil refill pressure filling equipment, calculate the Euclidean distance between each molding defect contour and texture and each centroid, assign each molding defect contour and texture to the centroid cluster corresponding to the minimum Euclidean distance, and finally output the abnormal control cluster label of each molding defect contour and texture; The abnormal control clustering labels are injected into the control network knowledge graph for identification and matching, and the abnormal control parameters of the molding defect contour and texture generated by each suspected abnormal control text package are obtained. The hash function between the abnormal control parameters and the standard control parameters is calculated, and the abnormal control parameters are adjusted according to the hash function to obtain a control calibration scheme.

7. An automatic eyebrow pencil core pressure filling integrated molding control system, characterized in that: The automatic eyebrow pencil refill pressure-filling integrated molding control system includes a memory and a processor, wherein the memory stores an automatic eyebrow pencil refill pressure-filling integrated molding control method program, and when the automatic eyebrow pencil refill pressure-filling integrated molding control method program is executed by the processor, the steps of the automatic eyebrow pencil refill pressure-filling integrated molding control method as described in any one of claims 1 to 6 are implemented.

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