Preparation method for biodegradable material for injection molding

Abstract

The present invention relates to the technical field of polymeric compound preparation, and in particular, to a preparation method for a biodegradable material for injection molding. The method comprises: obtaining a material-melting thermal image in a melting zone of a twin-screw extruder during a polylactic acid melting process and melt flow sequences in the material-melting thermal image; obtaining melting coefficients on the basis of thermal value variations in the melt flow sequences; obtaining sequence categories on the basis of the melting coefficients, and obtaining a melting effect on the basis of the degrees of stable distribution in the sequence categories and the distribution of the melting coefficients; and adjusting a screw speed of the twin-screw extruder on the basis of the melting effect. According to the embodiments of the present invention, by analyzing the melting state of polylactic acid during a melting process, the melting effect is accurately quantified, thereby allowing for accurate control of the screw speed of the double-screw extruder, ensuring the quality of masterbatch products in the preparation process.

Description

Preparation method of biodegradable material for injection molding TECHNICAL FIELD

[0001] The present application relates to the technical field of preparing high molecular compounds, in particular to a preparation method of biodegradable material for injection molding. BACKGROUND

[0002] Polylactic acid is a relatively important and practical material in biodegradable materials for injection molding. In the preparation process of polylactic acid, the molten PDLA can be added to the auxiliary agent package and stirred, and then sent into the double screw extruder for granulation to obtain material master batch. The material master batch determines the quality of the finished material in the subsequent process steps, and the quality of the material master batch is mainly affected by the setting of the double screw extruder parameters. If the rotation speed of the double screw extruder is too fast, the mixing principle will be excessively sheared, affecting the stability and quality of the product. If the rotation speed is too slow, the raw materials will not be fully mixed and melted, also affecting the stability and quality of the product. In the prior art, the rotation speed parameter of the double screw extruder is mainly fixed by using empirical values, which cannot determine whether the rotation speed setting is reasonable in real time, thereby increasing the abnormal risk and affecting the quality of the finished product. SUMMARY

[0003] In order to solve the technical problem that the rotation speed parameter of the double screw extruder in the melting process of the biodegradable material is fixed in the prior art, thereby causing abnormal risk in the process and affecting the quality of the finished product, the purpose of the present application is to provide a preparation method of biodegradable material for injection molding. The technical scheme adopted is as follows: the present application provides a preparation method of biodegradable material for injection molding, which comprises the following steps: obtaining a material melting thermodynamic image of a melting region of a double screw extruder in a melting process of polylactic acid in real time; the pixel point sequence along the material extrusion direction in the material melting image is a melt flow sequence; obtaining an extrusion melting factor according to the change trend and change degree of the thermodynamic value in the melt flow sequence; obtaining a melting coefficient of each melt flow sequence according to the difference between the extrusion melting factors between the melt flow sequences and the extrusion melting factor; classifying the melt flow sequences according to the melting coefficient, and obtaining a plurality of sequence categories; obtaining the stable distribution degree of the melt flow sequence in each sequence category; obtaining the melting effect of the material melting thermodynamic image according to the stable distribution degree of all sequence categories and the distribution of the melting coefficient; and adjusting the screw rotation speed of the double screw extruder according to the melting effect.

[0004] Further, the method for obtaining the extrusion melting factor comprises: screening a heat increasing element according to a difference in thermal force value between elements in the melt flow sequence, the last element of which is a melt extrusion element; obtaining the change degree according to a difference in thermal force value between the melt extrusion element and other elements and a change characteristic of the thermal force value at the position of the heat increasing element; obtaining the change trend according to a distribution discreteness of elements in the melt flow sequence; and obtaining the extrusion melting factor according to the change degree and the change trend; the extrusion melting factor is positively correlated with the change degree and negatively correlated with the change trend.

[0005] Further, the method for obtaining the change degree comprises: performing trend item analysis on the melt flow sequence to obtain a trend item intensity at the position of the heat increasing element; taking a difference in thermal force value between the heat increasing element and a previous element as a heat increase factor of the heat increasing element; obtaining the change characteristic of the thermal force value of the heat increasing element according to the heat increase factor and the trend item intensity; taking an accumulated value of a difference in thermal force value between the melt extrusion element and each other element as heat increase sufficiency; and obtaining the change degree according to the change characteristic of the thermal force value of the heat increasing element and the heat increase sufficiency.

[0006] Further, the method for obtaining the change trend comprises: obtaining a quartile range of elements in the melt flow sequence; obtaining a sequence combination between the melt flow sequence and each other melt flow sequence, accumulating a divergence of each sequence combination to obtain an overall divergence of the corresponding melt flow sequence; and obtaining the change trend according to the quartile range and the overall divergence.

[0007] Further, the method for obtaining the melting coefficient comprises: obtaining a maximum extrusion melting factor in all melt flow sequences; obtaining, for a melt flow sequence, an extrusion melting factor difference between the extrusion melting factor of the melt flow sequence and the maximum extrusion melting factor, and obtaining the melting coefficient of the melt flow sequence according to the extrusion melting factor difference and the extrusion melting factor of the melt flow sequence; the melting coefficient is negatively correlated with the extrusion melting factor difference and positively correlated with the extrusion melting factor.

[0008] Further, the method for obtaining the sequence category comprises: clustering the melt flow sequence based on the melting coefficient by using a spectral clustering algorithm to obtain a plurality of sequence categories.

[0009] Further, the method for obtaining the stability distribution degree comprises: obtaining position information of the melt flow sequence in the material melting thermal diagram; in one sequence category, obtaining position distribution uniformity according to distribution of the position information; obtaining melting coefficient stability in the sequence category according to distribution difference of the melting coefficient between the sequence category and other sequence categories and melting coefficient range in the sequence category; and obtaining the stability distribution degree according to the melting coefficient stability and the position distribution uniformity.

[0010] Further, the method for obtaining the melting coefficient stability comprises: in one sequence category, arranging melting coefficients of the melt flow sequence in sequence according to the position information to obtain a melting coefficient sequence; accumulating difference distance of the melting coefficient sequence between the sequence category and each other sequence category to obtain the distribution difference of the sequence category; obtaining the melting coefficient stability according to the distribution difference and the melting coefficient range; and the distribution difference and the melting coefficient range are negatively correlated with the melting coefficient stability.

[0011] Further, the method for obtaining the melting effect comprises: obtaining melting coefficient average values in each sequence category to form a melting coefficient average value set, and negatively correlating entropy in the melting coefficient average value set to obtain a first overall melting stability; taking average stability distribution degree of all the sequence categories as a second overall melting stability; and obtaining the melting effect according to the first overall melting stability and the second overall melting stability.

[0012] Further, the method for adjusting the screw rotation speed of the double-screw extruder according to the melting effect comprises: judging whether adjustment is needed according to the size of the melting effect; if adjustment is needed, inputting the melting effect and a preset screw rotation speed range into a pre-trained neural network to output a rotation speed adjustment value; and adjusting the rotation speed of the double-screw extruder according to the rotation speed adjustment value.

[0013] The present application has the following beneficial effects: in order to evaluate the melting characteristics of the material in the operation process of the twin-screw extruder, the temperature distribution information in the current extrusion process is characterized by the form of the thermodynamic diagram. In order to more accurately analyze the melting temperature characteristics, the melt flow sequence is obtained and the distribution of the thermodynamic value in the sequence is analyzed to obtain the melting coefficient. The melting coefficient can characterize the melting characteristics of the corresponding local position of the corresponding melt flow sequence. For the melting process of biodegradable materials, the melting process at different positions is stable and there is a large temperature change at each position, which indicates that the current melting characteristics are excellent, and the rotational speed of the twin-screw extruder is reasonable. Therefore, the melt flow sequence is classified based on the melting coefficient, and the stable distribution characteristics of the melting coefficient in each sequence category are analyzed to determine the melting effect at the current time. According to the accurate quantified melting effect, the rotational speed parameter of the twin-screw extruder can be set, so that the whole process of the twin-screw extruder is ensured to be at a suitable rotational speed parameter, the process abnormal risk is reduced, and the preparation efficiency of the biodegradable material is improved. BRIEF DESCRIPTION OF DRAWINGS

[0014] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, and the advantages thereof, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained from these drawings without creative labor.

[0015] Fig. 1 is a flow chart of a preparation method of a biodegradable material for injection molding provided by an embodiment of the present application.

[0016] Fig. 2 is a schematic diagram of a material melting thermodynamic image acquisition method provided by an embodiment of the present application.

[0017] Fig. 3 is a schematic diagram of a melt flow sequence in an embodiment of the present application.

[0018] Fig. 4 is a schematic diagram of a spectral clustering result in an embodiment of the present application. DETAILED DESCRIPTION

[0019] In order to further illustrate the technical means and effects adopted by the present application to achieve the predetermined invention purpose, the following will combine the drawings and the preferred embodiments to specifically describe the preparation method of a biodegradable material for injection molding according to the present application, its specific implementation, structure, characteristics and effects. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures or characteristics in one or more embodiments can be combined in any suitable form.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0021] The application provides a preparation method of a biodegradable material for injection molding.

[0022] Referring to FIG. 1, a flowchart of a preparation method of a biodegradable material for injection molding is shown, and the method comprises the following steps.

[0023] In step S1, a material melting thermal image of a biodegradable material for injection molding in a melting region of a double-screw extruder is obtained in real time.

[0024] It should be noted that in the embodiment of the application, the biodegradable material for injection molding, i.e., polylactic acid, has a brief preparation process as follows:

[0025] (1) After 3 kg of PDLA is melted in a vacuum reaction kettle, an additive package is added for uniform stirring, and the mixture is sent to a double-screw extruder for granulation to obtain a master batch.

[0026] (2) After the master batch, PLLA and a chain extender are uniformly mixed in a high-speed mixer, the mixture is sent to a double-screw extruder for granulation to obtain a heat-resistant semi-transparent biodegradable material.

[0027] (3) After the heat-resistant semi-transparent biodegradable material is dried, it is injection molded, the mold temperature is set to 20℃, the injection speed is set to 40%, and the injection pressure is set to 80 MPa to obtain a biodegradable material for injection molding.

[0028] (4) The biodegradable material for injection molding is tested, and the material heat-resistant temperature in the embodiment of the application is 70℃.

[0029] It should be noted that the embodiment of the application mainly aims at process 1 in the above preparation process, i.e., the process of preparing a master batch by using a double-screw extruder.

[0030] The suitability of the rotation speed of the twin-screw extruder can be reflected by the temperature distribution of the biodegradable material in the melting region. If the rotation speed is suitable, the temperature distribution of the material surface generated by the melting region is relatively uniform and presents obvious high temperature distribution characteristics. Therefore, in order to evaluate the working state of the current twin-screw extruder, it is necessary to obtain the material melting thermodynamic image of the melting region of the twin-screw extruder in the melting process of the biodegradable material in real time. That is, the thermodynamic value of each pixel point in the material melting thermodynamic image can represent the temperature information of the corresponding position, and accurate temperature distribution analysis can be performed according to the thermodynamic map. Please refer to FIG. 2, which shows a material melting thermodynamic image acquisition method provided by an embodiment of the present application. An infrared thermal imaging device is arranged directly above the twin-screw extruder, and the material melting thermodynamic image is acquired through a top-down view. In an embodiment of the present application, the shooting time interval of the material melting thermodynamic image is set to 5 minutes, that is, the material melting thermodynamic image is shot and evaluated every five minutes, and the parameters are adjusted.

[0031] In an embodiment of the present application, in order to avoid the influence of image quality on subsequent data processing, denoising processing is required through a bilateral filtering algorithm. In other embodiments of the present application, other filtering methods can also be selected, which are not limited and elaborated here.

[0032] In an embodiment of the present application, considering that there is background information interference in the photographed material melting thermodynamic image, and the size of the melting region of the twin-screw extruder is fixed, a fixed region of interest division method can be used to divide the melting region in the acquired original material melting thermodynamic image as the region of interest, so as to obtain a material melting thermodynamic image without background information interference for subsequent step analysis. In other embodiments of the present application, background information can also be eliminated by using thermodynamic value threshold segmentation, image segmentation and other processing means, which are not limited and elaborated here.

[0033] The material melting thermodynamic image is mainly used to represent the temperature distribution characteristics in the melting region. In the melting region, the material has a certain flow direction, that is, the extrusion direction of the twin-screw extruder. In order to analyze the thermodynamic value distribution in the melting region, the thermodynamic value of the local region in the melting region needs to be analyzed, so in the material melting image, the pixel point sequence along the material extrusion direction can be regarded as the melt flow sequence. In the subsequent process, the melt flow sequence is analyzed, that is, each melt flow sequence can be regarded as the thermodynamic value information of a part of the local region in the melting region. Please refer to FIG. 3, which shows a melt flow sequence diagram in an embodiment of the present application, that is, there are two melt flow sequences in FIG. 3.

[0034] It should be noted that in one embodiment of the present application, because the position of the infrared thermal imaging device is fixed and the angle of view is fixed, the horizontal direction can be directly set as the material extrusion direction in advance. In one embodiment of the present application, the material extrusion direction can be set according to the position of the infrared thermal imaging device, and details are not described or limited herein.

[0035] Step S2: obtaining an extrusion melting factor according to the change trend and change degree of the thermal value in the melt flow sequence; and obtaining a melting coefficient of each melt flow sequence according to the difference between the extrusion melting factors of the melt flow sequences and the extrusion melting factor.

[0036] When the screw rotation speed of the twin-screw extruder is appropriate, the mixing and melting effect of the PLDA and the additive package is relatively sufficient, the temperature difference between the local areas in the melting area is smaller, and there is no obvious temperature distribution unevenness; at the same time, the appropriate screw rotation speed helps to form a clear and continuous melt flow phenomenon, heat can be rapidly conducted in the mixed material, the mixing and melting effect is more sufficient near the extrusion port of the twin-screw extruder, and has obvious high-temperature characteristics relative to other positions. Therefore, based on this principle, the extrusion melting factor can be obtained according to the change trend and change degree of the thermal value in the melt flow sequence. The extrusion melting factor represents the melting characteristics of the position where the melt flow sequence is located. The more uniform the change trend and the greater the change degree, the better the melting effect of the local area.

[0037] Preferably, in one embodiment of the present application, the method for obtaining the extrusion melting factor comprises: in the melt flow sequence, the last element is a melt extrusion element, i.e. the element corresponding to the pixel point closest to the extrusion port. The temperature value of the melt extrusion element is the end point in the temperature conduction process, so the melting characteristics of the current local area can be accurately analyzed based on this element. As shown in FIG. 3, in one melt flow sequence, the last element is marked as a melt extrusion element.

[0038] The thermal increase element is screened according to the thermal value difference between the elements. In one embodiment of the present application, in the melt flow sequence, the thermal value difference between the next element and the previous element is obtained. If the thermal value difference is positive, the corresponding next element is taken as the thermal increase element. In other embodiments of the present application, the screening condition of the thermal increase element can be further limited by setting a thermal value difference threshold, and details are not described or limited herein.

[0039] According to the thermal value difference between the melt extrusion element and other elements and the thermal value change characteristic of the heat increasing element position, the change degree is obtained. The stronger the thermal value difference between the melt extrusion element and other elements, the more smooth the heat conduction process in the melting process is, the melt extrusion element position is obviously larger, and the change degree is greater. The stronger the thermal value change characteristic of the heat increasing element position, the more significant the temperature change in the temperature conduction process is, the more smooth the melting process is, and the change degree is greater.

[0040] According to the distribution discreteness of the elements in the melt flow sequence, the change trend is obtained. The stronger the distribution discreteness, the more uneven the temperature change in the melt flow sequence is, that is, the worse the melting process is.

[0041] According to the change degree and the change trend, the extrusion melting factor is obtained. The greater the change degree, the more smooth the melting process is, the stronger the change trend is, the worse the melting process is, so the extrusion melting factor is positively correlated with the change degree and negatively correlated with the change trend.

[0042] In an embodiment of the present application, after the change degree and the change trend are quantified, the extrusion melting factor can be directly obtained by using the ratio operation, that is, the change trend is used as the denominator and the change degree is used as the numerator to obtain the extrusion melting factor. That is, the extrusion melting factor is expressed by the formula ; wherein represents the extrusion melting factor of the i-th melt flow sequence, represents the change degree of the i-th melt flow sequence, represents the change trend of the i-th melt flow sequence. In other embodiments of the present application, the relevant relationship can also be constructed by using subtraction and other basic mathematical operations, which will not be described here.

[0043] Preferably, in an embodiment of the present application, the method for obtaining the change degree comprises: performing trend item analysis on the melt flow sequence to obtain the trend item strength of the position corresponding to the heat increasing element. In an embodiment of the present application, the trend item analysis adopts the STL sequence decomposition algorithm, which is a technical means well known to those skilled in the art, and will not be described here.

[0044] The thermal value difference between the heat increasing element and the previous element is used as the heat increasing factor of the heat increasing element; and the heat increasing factor and the trend item strength are used to obtain the thermal value change characteristic of the heat increasing element. That is, the greater the heat increasing factor and the greater the trend item strength, the more obvious the thermal value change characteristic of the position corresponding to the heat increasing element is, and the greater the thermal value change characteristic is. In an embodiment of the present application, the multiplication means is used to construct the positive correlation relationship, and the heat increasing factor and the trend item strength are multiplied to obtain the thermal value change characteristic. In other embodiments of the present application, addition and other methods can also be used, which will not be described here.

[0045] The cumulative value of the thermal value difference between the melt extrusion element and each other element is taken as the heat promotion sufficiency. The variation degree is obtained according to the thermal value variation characteristic of the heat increasing element and the heat promotion sufficiency. That is, the greater the thermal value variation characteristic and the greater the heat promotion sufficiency, the greater the variation degree. In an embodiment of the present application, the variation degree is expressed by the formula:

[0046] wherein represents the variation degree of the i th melt flow sequence, represents the number of heat increasing elements in the i th melt flow sequence, is the heat promotion factor of the j th heat increasing element in the i th melt flow sequence, is the trend item strength of the j th heat increasing element in the i th melt flow sequence, is the number of other elements in the i th melt flow sequence except the melt extrusion element, is the thermal value of the melt extrusion element of the i th melt flow sequence, is the thermal value of the k th other element in the i th melt flow sequence, and e is a natural constant.

[0047] In the variation degree formula, a positive correlation is constructed by means of multiplication, and the heat promotion sufficiency is mapped by using an exponential function with a natural constant as the base number when participating in calculation, so as to amplify the data characteristics of the heat promotion sufficiency.

[0048] Preferably, in an embodiment of the present application, the variation trend obtaining method comprises: obtaining the quartile range of the elements in the melt flow sequence. The greater the quartile range, the more uneven the distribution of the elements in the sequence, and the more obvious the data limit of the element value.

[0049] The sequence combination between the melt flow sequence and each other melt flow sequence is obtained, the divergence of each sequence combination is accumulated, and the overall divergence of the corresponding melt flow sequence is obtained. The greater the overall divergence, the more obvious the dissimilarity between the melt flow sequence and other melt flow sequences, and the more likely the sequence to have an abnormal melting temperature conduction characteristic.

[0050] Therefore, the variation trend can be obtained according to the quartile range and the overall divergence. That is, the greater the quartile range and the greater the overall divergence, the greater the variation trend and the worse the melting characteristic performance. In an embodiment of the present application, the variation trend is expressed by the formula: wherein represents the variation trend of the i th melt flow sequence, is the quartile range of the i th melt flow sequence, is the number of other melt flow sequences except the i th melt flow sequence, is the i-th melt flow sequence, is the b-th other melt flow sequence, is a divergence acquisition function.

[0051] It should be noted that the divergence, quartile distance and other technical features are well-known technical means to those skilled in the art, and will not be described here.

[0052] The extrusion melting factor can represent the melting characteristics of the local position where the corresponding melt flow sequence is located. For the melting region, not only does it need to have obvious melting characteristics at the local position, but it also needs to ensure that the melting characteristics between the local positions are similar to ensure the overall melting effect. Therefore, further according to the difference between the extrusion melting factors of the melt flow sequences and the extrusion melting factor, the melting coefficient of each melt flow sequence is obtained, that is, the greater the difference between the extrusion melting factors, the more abnormal the melt flow sequence is relative to other sequences. Therefore, the melting coefficient obtained by further processing the extrusion melting factor according to the difference between the extrusion melting factors can accurately represent the melting effect and melting normality of the corresponding melt flow sequence.

[0053] Preferably, in an embodiment of the present application, the melting coefficient acquisition method comprises:

[0054] obtaining the maximum extrusion melting factor in all melt flow sequences.

[0055] For a melt flow sequence, the extrusion melting factor difference between the extrusion melting factor of the melt flow sequence and the maximum extrusion melting factor is obtained, and the melting coefficient of the melt flow sequence is obtained according to the extrusion melting factor difference and the extrusion melting factor of the melt flow sequence. The smaller the extrusion melting factor difference, the closer the extrusion melting factor of the melt flow sequence is to the maximum extrusion melting factor, and the greater the melting coefficient, that is, the melting coefficient and the extrusion melting factor difference are negatively correlated; the greater the extrusion melting factor, the better the melting characteristics of the melt flow sequence, that is, the melting coefficient and the extrusion melting factor are positively correlated. In an embodiment of the present application, the melting coefficient is expressed by the formula:

[0056] ; wherein, is the melting coefficient of the i-th melt flow sequence, is a normalization function, is the maximum extrusion melting factor, is a preset fitting parameter. In an embodiment of the present application, the normalization function adopts a linear normalization function, is set to 1, for the purpose of preventing the denominator from being 0.

[0057] That is, in the melting coefficient formula, the inverse form is used to construct the negative correlation, and the product is used to construct the positive correlation. In other embodiments of the present application, other basic mathematical methods can be used to construct the correlation, which will not be described and limited here.

[0058] Step S3: classifying the melt flow sequences according to the melting coefficients to obtain a plurality of sequence categories; obtaining a stable distribution degree of the melt flow sequences in each sequence category; and obtaining the melting effect of the material melting thermodynamic image according to the stable distribution degrees of all sequence categories and the distribution of the melting coefficients.

[0059] The processing of step S2 can accurately quantify the melting characteristics in each melt flow sequence, that is, step S2 is a local analysis process, and further analysis of the overall characteristics of the melting region is required to determine the melting state in the entire melting region. First, the melt flow sequences are classified according to the melting coefficients to obtain a plurality of sequence categories, that is, the melt flow sequences in each sequence category have similar or identical melting coefficients, and the melting coefficients between the melt flow sequences in different sequence categories have certain differences.

[0060] In an embodiment of the present application, each melt flow sequence is regarded as a data point in an undirected graph, the edge weight value between the data points is the absolute value of the difference between the melting coefficients of two sequences, and the spectral clustering algorithm is used to cluster the melt flow sequences, that is, each clustering category represents a sequence category. Please refer to FIG. 4, which shows a spectral clustering result schematic diagram in an embodiment of the present application, wherein each box region represents a category, that is, in the embodiment of the present application, the melt flow sequences are divided into three sequence categories.

[0061] For a sequence category, the closer the melting coefficients between the melt flow sequences in the sequence category, and the closer the local region positions corresponding to the melt flow sequences, the higher the stability within the sequence category. If the stability between each sequence category is high, and the overall melting coefficient distribution is uniform, it means that the current melting region has uniform melting characteristics, and the melting effect is better. Therefore, the embodiment of the present application obtains the stable distribution degree of the melt flow sequences in each sequence category. According to the stable distribution degrees of all sequence categories and the distribution of the melting coefficients, the melting effect of the material melting thermodynamic image is obtained.

[0062] Preferably, in an embodiment of the present application, the method for obtaining the stable distribution degree comprises:

[0063] For the stability of melt flow sequence in a sequence category, on one hand is the distribution stability of melting coefficient, on the other hand is the distribution stability of melt flow sequence position. Therefore, first of all, the position information of melt flow sequence in the material melting thermodynamic map is obtained. In an embodiment of the present application, the coordinates of the first element of melt flow sequence in the material melting thermodynamic map image are taken as the position information of the corresponding melt flow sequence. In other embodiments of the present application, the coordinate information of other representative elements in the sequence can also be selected as the position information, which is not described and limited here.

[0064] In a sequence category, the position distribution uniformity is obtained according to the distribution of position information. In an embodiment of the present application, the distance between position information can be calculated according to the coordinates corresponding to the position information by using the Euclidean distance calculation formula, and the maximum distance between melt flow sequences can be negatively correlated and normalized to obtain the position distribution uniformity, that is, the greater the maximum distance between melt flow sequences in a sequence category, the more obvious the position information distribution discreteness in the current sequence category, and the smaller the corresponding position distribution uniformity. In other embodiments of the present application, the position distribution uniformity can also be obtained by using statistical characteristics such as variance, standard deviation, and entropy of the distance, which is not limited and described here.

[0065] According to the distribution difference of melting coefficient between the sequence category and other sequence categories, and the melting coefficient range in the sequence category, the melting coefficient stability in the corresponding sequence category is obtained. The greater the distribution difference, the more specific the sequence category is relative to other sequence categories, the more abnormal the sequence category is, and the smaller the melting coefficient stability is; the greater the melting coefficient range, the more obvious the difference of melting coefficient distribution in the sequence category is, the more discrete the distribution is, and the smaller the melting coefficient stability is.

[0066] The stable distribution degree is obtained according to the melting coefficient stability and the position distribution uniformity. In an embodiment of the present application, the stable distribution degree is expressed by the formula:

[0067] ; wherein represents the stable distribution degree of the pth sequence category, represents the exponential function with the natural constant as the base number, is the maximum distance of position information between melt flow sequences in the pth sequence category, is the melting coefficient stability of the melting coefficient in the pth sequence category.

[0068] That is, in the stable distribution degree formula, the position distribution uniformity is obtained by negatively correlating and normalizing the maximum distance by using the exponential function with the natural constant as the base number, and then multiplied by the melting coefficient stability to construct a positive correlation relationship by using multiplication.

[0069] Preferably, in one embodiment of the present application, the method for obtaining the melt coefficient stability comprises:

[0070] In one sequence category, the melt coefficients of the melt flow sequence are sequentially arranged according to the position information to obtain a melt coefficient sequence. In one embodiment of the present application, the rule for the sequential arrangement is to arrange in ascending order according to the distance from the position information to the image origin. In other embodiments of the present application, the reference point is not the origin, but the top point, center, or other reference points of the image, or the order is not ascending, but descending, and other order sorting methods can be selected, as long as the method for sequentially arranging according to the position information in each sequence category is consistent.

[0071] The distribution difference of the sequence category is obtained by accumulating the difference distance of the melt coefficient sequence between the sequence category and each other sequence category. In one embodiment of the present application, the difference distance is the DTW distance, and in other embodiments of the present application, the Euclidean distance or other distances can be selected, which are not limited here.

[0072] The melt coefficient stability is obtained according to the distribution difference and the melt coefficient range. The greater the distribution difference is, the more specific the sequence category is, and the smaller the melt coefficient stability is. The greater the melt coefficient range is, the more obvious the difference of the melt coefficient distribution in the sequence category is, and the more discrete the distribution is, and the smaller the melt coefficient stability is. That is, the distribution difference and the melt coefficient range are negatively correlated with the melt coefficient stability. In one embodiment of the present application, the melt coefficient stability is expressed by the formula:

[0073] ; wherein is the melt coefficient stability of the melt coefficient in the pthsequence category, is the maximum melt coefficient in the pthsequence category, is the minimum melt coefficient in the pthsequence category, is the number of other sequence categories except the pthsequence category, is the melt coefficient sequence of the pthsequence category, is the melt coefficient sequence of the qthother sequence category, is the DTW distance calculation function, is a preset hyperparameter. In one embodiment of the present application the value is 1.

[0074] In the melt coefficient stability formula, the distribution difference and the melt coefficient range are quantified together by using the multiplication operation, and the negative correlation mapping is further realized by the reciprocal form.

[0075] Preferably, in one embodiment of the present application, the method for obtaining the melting effect comprises:

[0076] An average value of the melting coefficient in each sequence category is obtained to form an average value set of the melting coefficient, and an entropy in the average value set of the melting coefficient is negatively correlated to obtain a first overall melting stability. The greater the entropy is, the more chaotic the distribution of the average value of the melting coefficient is, that is, the greater the difference in the melting coefficient between different sequence categories is, and the smaller the first overall melting stability is.

[0077] The average stable distribution degree of all sequence categories is taken as a second overall melting stability. The melting effect is obtained according to the first overall melting stability and the second overall melting stability. That is, the greater the first overall melting stability and the second overall melting stability are, the better the melting effect is.

[0078] In one embodiment of the present application, the melting effect is expressed by a formula as follows:

[0079] ; wherein is the melting effect, is a normalization function, is an entropy of the average value set of the melting coefficient, is an exponential function with a natural constant as a base number, is an average stable distribution degree. That is, the exponential function with the natural constant as the base number is negatively correlated to be normalized, and a positive correlation is constructed by a multiplication method.

[0080] Step S4: adjusting the screw rotation speed of the twin-screw extruder according to the melting effect.

[0081] The greater the melting effect is, the better the melting state of the current melting area is, and the more reasonable the parameter setting of the twin-screw extruder is. If the melting effect is poor, it is necessary to adjust the screw rotation speed of the twin-screw extruder according to the melting effect so that the melting effect reaches an ideal state.

[0082] Preferably, in one embodiment of the present application, it is judged whether adjustment is needed according to the size of the melting effect. If adjustment is needed, the melting effect and a preset screw rotation speed range are input into a pre-trained neural network to output a rotation speed adjustment value, and the twin-screw extruder is adjusted in rotation speed according to the rotation speed adjustment value. In one embodiment of the present application, the screw rotation speed range is set to 300 to 500 revolutions per minute.

[0083] In one embodiment of the present application, a melting effect threshold is set. If the melting effect is less than the melting effect threshold, it is considered that adjustment is needed, otherwise it is considered that adjustment is not needed. Because the melting effect has been normalized, the melting effect threshold is set to 0.7.

[0084] In one embodiment of the present application, the neural network is a recurrent neural network, in which the mean square error is used as the loss function, and the adaptive momentum stochastic optimization method is used for training. Before training, the data set needs to be labeled by considering, the input data is the melting effect and the preset screw speed range, and the output data is the speed adjustment value. The specific training method of the recurrent neural network is a technical means known to those skilled in the art, and will not be described here.

[0085] In one embodiment of the present application, after obtaining the speed adjustment value, it is directly applied to the parameter setting of the next image acquisition time stage. Through continuous detection and adjustment, the master batch preparation ends.

[0086] In summary, the embodiment of the present application obtains the thermal image of the material in the melting region of the twin-screw extruder and the melt flow sequence during the polylactic acid melting process. The melting coefficient is obtained according to the change of the thermal value in the melt flow sequence. The sequence category is obtained according to the melting coefficient. The melting effect is obtained according to the stable distribution degree in the sequence category and the distribution of the melting coefficient. The screw speed of the twin-screw extruder is adjusted according to the melting effect. The embodiment of the present application accurately quantifies the melting effect by analyzing the melting state during the polylactic acid melting process, and then accurately controls the screw speed of the twin-screw extruder, thereby ensuring the quality of the master batch product in the preparation process.

[0087] It should be noted that the above-mentioned embodiments of the present application are only for description, and do not represent the advantages and disadvantages of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are also possible or may be advantageous.

[0088] Each embodiment in the specification is described in a progressive manner, and the same or similar parts between each embodiment can be referred to each other. Each embodiment focuses on the difference from other embodiments.

Claims

1. A method for producing a biodegradable material for injection molding, characterized by, The method comprises: Real-time obtaining a material melting thermodynamic image of a melting zone of a double-screw extruder in a melting process of polylactic acid; a pixel point sequence along a material extrusion direction in the material melting image is a melt flow sequence; Obtaining an extrusion melting factor according to a change trend and a change degree of a thermodynamic value in the melt flow sequence; obtaining a melting coefficient of each melt flow sequence according to a difference between the extrusion melting factors of the melt flow sequences and the extrusion melting factor of the melt flow sequence; Classifying the melt flow sequences according to the melting coefficients to obtain a plurality of sequence categories; obtaining a stable distribution degree of the melt flow sequences in each sequence category; obtaining a melting effect of the material melting thermodynamic image according to the stable distribution degrees of all sequence categories and the distribution of the melting coefficients; Adjusting a screw rotation speed of the double-screw extruder according to the melting effect.

2. The method for preparing a biodegradable material for injection molding according to claim 1, characterized in that: The method for obtaining the extrusion melting factor comprises: In the melt flow sequence, the last element is a melt extrusion element; a thermal increase element is screened according to a thermodynamic value difference between elements; the change degree is obtained according to a thermodynamic value difference between the melt extrusion element and other elements and a thermodynamic value change characteristic of the thermal increase element position; The change trend is obtained according to a distribution discreteness of elements in the melt flow sequence; The extrusion melting factor is obtained according to the change degree and the change trend; the extrusion melting factor is positively correlated with the change degree and negatively correlated with the change trend.

3. The method for preparing a biodegradable material for injection molding according to claim 2, characterized in that: The method for obtaining the change degree comprises: Trend item analysis is performed on the melt flow sequence to obtain a trend item intensity of the thermal increase element corresponding position; a thermodynamic value difference between the thermal increase element and a previous element is taken as a heat increase factor of the thermal increase element; the thermodynamic value change characteristic of the thermal increase element is obtained according to the heat increase factor and the trend item intensity; An accumulated value of the thermodynamic value difference between the melt extrusion element and each other element is taken as heat increase sufficiency; The change degree is obtained according to the thermodynamic value change characteristic of the thermal increase element and the heat increase sufficiency.

4. The method for preparing a biodegradable material for injection molding according to claim 2, characterized in that: The method for obtaining the change trend comprises: A quartile range of elements in the melt flow sequence is obtained; A sequence combination between the melt flow sequence and each other melt flow sequence is obtained; a divergence of each sequence combination is accumulated to obtain an overall divergence of the corresponding melt flow sequence; The change trend is obtained according to the quartile range and the overall divergence.

5. The method for preparing a biodegradable material for injection molding according to claim 1, characterized in that: The method for obtaining the melting coefficient comprises: A maximum extrusion melting factor in all melt flow sequences is obtained; For a melt flow sequence, an extrusion melting factor difference between the extrusion melting factor of the melt flow sequence and the maximum extrusion melting factor is obtained; the melting coefficient of the melt flow sequence is obtained according to the extrusion melting factor difference and the extrusion melting factor of the melt flow sequence; the melting coefficient is negatively correlated with the extrusion melting factor difference and positively correlated with the extrusion melting factor.

6. The method for preparing a biodegradable material for injection molding according to claim 1, characterized in that: The method for obtaining the sequence category comprises: Clustering the melt flow sequence based on the melting coefficient using a spectral clustering algorithm to obtain a plurality of sequence categories.

7. The method for preparing a biodegradable material for injection molding according to claim 1, characterized in that: The method for obtaining the stable distribution degree comprises: obtaining position information of the melt flow sequence in the material melting thermal diagram; In one of the sequence categories, the position distribution uniformity is obtained according to the distribution of the position information, and the melting coefficient stability in the sequence category is obtained according to the distribution difference of the melting coefficient between the sequence category and other sequence categories and the melting coefficient range in the sequence category. The melting coefficient stability is obtained according to the melting coefficient stability and the position distribution uniformity.

8. The method for preparing a biodegradable material for injection molding according to claim 7, characterized in that: The method for obtaining the melting coefficient stability comprises: In one of the sequence categories, the melting coefficient sequence of the melt flow sequence is arranged in sequence according to the position information, and the melting coefficient sequence is obtained. The distribution difference of the sequence category is obtained by accumulating the difference distance of the melting coefficient sequence between the sequence category and each other sequence category. The melting coefficient stability is obtained according to the distribution difference and the melting coefficient range; the distribution difference and the melting coefficient range are negatively correlated with the melting coefficient stability.

9. The method for preparing a biodegradable material for injection molding according to claim 1, characterized in that: The method for obtaining the melting effect comprises: obtaining the average value of the melting coefficient in each sequence category and forming an average value set of the melting coefficient, and negatively correlating the entropy in the average value set of the melting coefficient to obtain a first overall melting stability; The average stable distribution degree of all the sequence categories is taken as a second overall melting stability; the melting effect is obtained according to the first overall melting stability and the second overall melting stability.

10. The method for preparing a biodegradable material for injection molding according to claim 1, characterized in that: The method for adjusting the screw rotation speed of the double screw extruder according to the melting effect comprises: determining whether adjustment is needed according to the size of the melting effect, if adjustment is needed, inputting the melting effect and a preset screw rotation speed range into a pre-trained neural network to output a rotation speed adjustment value; and adjusting the rotation speed of the double screw extruder according to the rotation speed adjustment value.

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