Bio-based PVC plastic sheet and automatic manufacturing method thereof

Abstract

The invention is applicable to the technical field of PVC (polyvinyl chloride) plastic manufacturing control, and provides a bio-based PVC plastic sheet and an automatic manufacturing method thereof, and the method is applied to an automatic manufacturing control system of the bio-based PVC plastic sheet. The system comprises a data acquisition module, a model training module, a parameter optimization module, a production monitoring module, a quality detection module, a wireless communication module, a memory, an alarm, a processing center and a smart phone. The data acquisition module, the model training module, the parameter optimization module, the production monitoring module, the quality detection module and the wireless communication module are respectively connected with the processing center; the smart phone is in wireless network connection with the wireless communication module in the range of a wireless network or the Internet; the invention further provides a bio-based PVC plastic sheet. According to the invention, extrusion forming parameters can be automatically set, automatic extrusion forming production is realized, and automatic detection is realized.

Description

Technical Field

[0001] The present invention relates to the field of plastic sheet extrusion molding control technology, and in particular to a bio-based PVC plastic sheet and an automatic production method thereof in the field of artificial intelligence. Background Art

[0002] Most of the currently known bio-based PVC plastic sheets are processed by traditional home-based workshops, and some companies adopt semi-automatic extrusion molding, which results in high labor costs and low production efficiency.

[0003] With the application of artificial intelligence in industrial production, labor costs can be reduced and production efficiency can be improved to ensure the production quality level. The same is true in the plastic extrusion molding industry. The trend of intelligent production is an inevitable result of the development of the industry. At the same time, bio-based PVC plastic sheets that meet the needs of different customers are produced. This is the development trend of the plastic extrusion molding industry to meet the needs of environmental protection and recycling. Summary of the invention

[0004] In order to solve the deficiencies in the prior art, the purpose of the present invention is to provide a bio-based PVC plastic sheet and an automatic production method thereof. By setting a data acquisition module, a model training module, a parameter optimization module, a production monitoring module, and a quality inspection module, the extrusion molding parameters can be automatically set, the extrusion molding production can be automatically performed, and the automatic inspection can be performed, thereby realizing the fully automated production of PVC sheets, improving the sheet quality, improving the production efficiency, and reducing the production cost.

[0005] In order to achieve the above purpose, the technical solution adopted by the present invention is:

[0006] A method for automatically making a bio-based PVC plastic sheet is applied to a control system for automatically making a bio-based PVC plastic sheet. The system comprises a data acquisition module, a model training module, a parameter optimization module, a production monitoring module, a quality detection module, a wireless communication module, a memory, an alarm, a processing center, and a smart phone; the data acquisition module, the model training module, the parameter optimization module, the production monitoring module, the quality detection module, the wireless communication module, the memory, and the alarm are respectively connected to the processing center;

[0007] The smart phone is connected to the wireless communication module wireless network within the wireless network or the Internet respectively;

[0008] The wireless communication module is provided with a wireless network unit, which is responsible for sending and receiving wireless signals and automatically networking with the intelligent control terminal within an effective network range;

[0009] The alarm compares the actual model comprehensive evaluation score with the model comprehensive evaluation score standard stored in the memory, and automatically sounds an alarm and notifies to continue training the model if the standard is not met; and compares the various quality information of the sheet with the quality standard of the bio-based PVC plastic sheet stored in the memory, and automatically sounds an alarm and notifies to rework and readjust the parameters if the standard is not met; and compares the various quality data actually detected with the quality standard of the bio-based PVC plastic sheet stored in the memory, and automatically sounds an alarm and notifies to rework if the quality does not meet the standard;

[0010] The memory is responsible for storing information of the data acquisition module, the model training module, the parameter optimization module, the production monitoring module, the quality inspection module, the wireless communication module, and the alarm, as well as the storage of the model comprehensive evaluation sub-standard and the bio-based PVC plastic sheet quality standard;

[0011] The processing center is responsible for the information transmission of the data acquisition module, model training module, parameter optimization module, production monitoring module, quality detection module, wireless communication module, alarm, and memory, and is the hub center of the system. It compares the actual model comprehensive evaluation score with the model comprehensive evaluation score standard stored in the memory: if it meets the standard, it is passed to the abnormal recognition unit for identification; if it does not meet the standard, it is passed to the alarm and notified to continue training the model; and compares the various quality information of the sheet with the quality standard of the bio-based PVC plastic sheet stored in the memory: if it meets the standard, it is set as the formal production process parameter; if it does not meet the standard, it is passed to the alarm and notified to rework and readjust the parameters; and compares the various quality data actually detected with the quality standard of the bio-based PVC plastic sheet stored in the memory: if the quality meets the standard, production or shipment will continue; if the quality does not meet the standard, it is passed to the alarm and notified to rework;

[0012] The data acquisition module includes a data acquisition unit, a data processing unit, a pixel adjustment unit, a grayscale conversion unit, a median filter unit, a feature extraction unit, and a data analysis unit, which collects production and operation data in the production process and extracts feature information for analysis, and passes it to the model training stage;

[0013] The model training module includes a training model unit, a loss function unit, a training verification unit, and an anomaly recognition unit, which is responsible for establishing and training a neural network model based on the collected production data, and passing it to the parameter optimization module;

[0014] The parameter optimization module includes a pressure calculation unit, a speed calculation unit, an extrusion calculation unit, a parameter preset unit, an operation implementation unit, and a sampling verification unit, which is responsible for optimizing the key parameters in the production process according to the trained model and passing them to the production monitoring module;

[0015] The production monitoring module includes a material preparation unit, a mixing and plasticizing unit, an extrusion molding unit, a cooling and shaping unit, and a traction and segmentation unit, which realizes real-time monitoring and management of production data through a cyber-physical system (CPS) and transmits it to the quality inspection module;

[0016] The quality inspection module includes an appearance inspection unit, a component inspection unit, a physical inspection unit, and an environmental inspection unit. The quality data of the PVC plastic sheet is inspected by a plastic sheet inspection device and transmitted to a processing center.

[0017] The present invention provides a method for automatically making a bio-based PVC plastic sheet, comprising the following steps:

[0018] S10, before production, the data acquisition module collects production and operation data in the production process and extracts features for analysis, so as to facilitate subsequent modeling training, model analysis and transfer to the model training stage;

[0019] S20, the model training module establishes and trains a neural network model based on the collected production data to predict the impact of various parameters in the production process on product quality, and transmits it to the parameter optimization module;

[0020] S30, the parameter optimization module optimizes the key parameters in the production process according to the trained model to improve production efficiency and product quality, and transmits the parameters to the production monitoring module;

[0021] S40, the production monitoring module realizes real-time monitoring and management of production data through the cyber-physical system (CPS) to ensure the stability and efficiency of the production process, and transmits it to the quality inspection module;

[0022] S50, the quality inspection module detects various quality data of the PVC plastic sheet through the plastic sheet inspection equipment, realizes automatic inspection, and transmits it to the processing center;

[0023] S60, the processing center compares the quality data actually detected with the quality standards of the bio-based PVC plastic sheet stored in the memory: if the quality meets the standard, continue production or shipment; if the quality does not meet the standard, the alarm is transmitted to the alarm and a notice is given to rework.

[0024] Further, the step S10 comprises the following steps:

[0025] S11. The data acquisition unit obtains various quality defect image information of the bio-based PVC plastic sheet by connecting to the industry database or network platform, and transmits it to the data processing unit;

[0026] S12, the data processing unit performs cropping processing on the acquired image data of various defects of the bio-based PVC plastic sheet, removes invalid or erroneous data, and transmits the data to the pixel adjustment unit;

[0027] S13, the pixel adjustment unit adjusts the brightness contrast according to the calculation formula "y = [x-127.5*(1-I)]*k+127.5*(1+I), y is the pixel value after adjustment (PPI), x is the pixel value before adjustment (PPI), I is the adjusted brightness (cd / m 2 ), k is the adjustment contrast (cd / m 2 )” to obtain the adjusted pixel value and pass it to the grayscale conversion unit;

[0028] S14, the grayscale conversion unit obtains the converted grayscale image according to the pixel grayscale calculation formula "Y = 0.299R + 0.58G + 0.114B, Y is the grayscale value of the image, R, G, B are the brightness values ​​of the red, green, and blue channels in the image respectively", and passes it to the median filtering unit;

[0029] S15, the median filtering unit calculates the median filtering method according to the formula "g(x,y)=med{f(xk,yi),(k,i∈W)}, g(x,y) is the image after median filtering, f(x,y) is the original image, W is the designed two-dimensional template, k, i are the coordinate values ​​of the two-dimensional template" to obtain the image after median filtering, and passes it to the feature extraction unit;

[0030] S16, the feature extraction unit extracts the shape, color, and texture feature information of various defects of the bio-based PVC plastic sheet in the image through the convolution layer of the convolutional neural network after the preprocessing, and transmits it to the data analysis unit;

[0031] S17. The data analysis unit analyzes the extracted features to obtain the characteristic information and process parameters corresponding to the eight quality defects of the bio-based PVC plastic sheet, so as to avoid similar defects in subsequent production.

[0032] Further, the step S20 includes the following steps:

[0033] S21, the training model unit trains the labeled category PVC plastic sheet quality defect image data set through a convolutional neural network to obtain the probability of the corresponding category, and passes it to the loss function unit;

[0034] S22, the loss function unit calculates the loss function according to the formula " logy k , J(θ) is the loss function, m is the number of samples, K is the number of categories, X k is the true label of the i-th sample for the k-th category, y kThe minimum mean value of the loss function is obtained for the probability that the i-th sample predicted by the model belongs to the k-th category, and is passed to the training and verification unit;

[0035] S23, the training verification unit calculates the model evaluation score according to the formula "F1=2*[∑T P / ∑(T P +F P )*(∑T P / ∑T P +∑F N )] / [(∑T P / ∑(T P +F P )+(∑T P / ∑T P +∑F N )), F1 is the comprehensive evaluation score of the model, T P is the number of samples correctly predicted as positive, F P is the number of samples incorrectly predicted as positive, F N The comprehensive evaluation score after model training is obtained by "the number of samples incorrectly predicted as negative classes" and passed to the processing center;

[0036] S24, the processing center compares the actual model comprehensive evaluation score with the model comprehensive evaluation score standard stored in the memory: if it meets the standard, it is passed to the abnormal recognition unit for recognition; if it does not meet the standard, it is passed to the alarm and notified to continue training the model;

[0037] S25. The abnormality recognition unit inputs the trained image into the convolutional neural network model, and uses the trained model to match the PVC plastic sheet image obtained in a timely manner during production to confirm whether there are defects and their categories.

[0038] Further, the step S30 comprises the following steps:

[0039] S31, the pressure calculation unit calculates the extrusion pressure according to the extrusion pressure calculation formula "Pi = P*A / Ao, Pi is the extrusion pressure (kg / cm 2 ), P is the pump pressure (kg / cm 2 ), A is the effective area of ​​the injection cylinder (cm 2 ), Ao is the cross-sectional area of ​​the screw (cm 2 )” to obtain the extrusion pressure of the PVC sheet and transmit it to the speed calculation unit;

[0040] S32, speed calculation unit according to the extrusion speed calculation formula "S = Q / A, S is the extrusion speed (cm / h), Q is the pump discharge (cm 3 / h), A is the effective area of ​​the injection cylinder (cm 2)” to obtain the extrusion speed of the PVC sheet and pass it to the extrusion calculation unit;

[0041] S33, the extrusion calculation unit obtains the extrusion amount of the PVC sheet according to the extrusion amount calculation formula "Q = (π*D*H*n) / 4, Q is the extrusion amount, D is the screw diameter, H is the screw groove depth, and n is the screw speed", and transmits it to the parameter preset unit;

[0042] S34, the parameter preset unit matches the parameters optimized by model training with the industry database to obtain the best process parameters as the predetermined process parameters, and transmits them to the operation implementation unit;

[0043] S35, the operation implementation unit automatically inputs the production molding equipment according to the predetermined process parameters to stir, press and mold the required bio-based PVC plastic sheets, and transmits them to the sampling verification unit;

[0044] S36. The sampling verification unit detects the appearance, physical properties, chemical properties, electrical properties, and quality information of the bio-based PVC plastic sheet through testing equipment and transmits it to the processing center;

[0045] S37. The processing center compares the quality information of the sheet with the quality standard of the bio-based PVC plastic sheet stored in the memory: if it meets the standard, it is set as the official production process parameter; if it does not meet the standard, it is transmitted to the alarm and notified to rework and readjust the parameters.

[0046] Further, the step S40 comprises the following steps:

[0047] S41, the material preparation unit mixes the materials according to the predetermined material formula mass ratio: 25-35% PVC resin, 10-15% rubber powder, 8-12% coconut shell powder, 6-10% ethylene-octene copolymer, 5-8% ethylene-vinyl acetate copolymer, 5-10% light calcium carbonate, 5-8% flame retardant modifier, 2-5% lubricant, 0.6-1.5% heat stabilizer, 1-2% light stabilizer, 0.6-1.2 plasticizer, 0.3-0.8% filler through the automatic batching control system, and transmits them to the mixing and plasticizing unit;

[0048] S42, the mixing and plasticizing unit controls the mixer through the frequency converter to stir the various raw materials at a low speed of 60-100°C and 80-100 rpm for 0.5-1 hour to ensure that the resin powder fully absorbs various additives, and then stirs them at a high speed of 110-180°C and 800-1000 rpm for 2-8 hours to form a uniform PVC melt, which is then transferred to the extrusion molding unit;

[0049] S43, the extrusion molding unit extrudes the uniformly mixed PVC material through a twin-screw extruder according to a predetermined sheet thickness at a material temperature of 150-180° C., a mold temperature of 40-60° C., an extrusion pressure of 80-160 MPa (800-1600 bar), and a screw speed of 400 rpm to obtain a PVC plastic sheet, and transfers it to a cooling and shaping unit;

[0050] S44, the cooling and molding unit puts the extruded PVC sheet into a cooling device and rapidly cools it at a temperature of 70-85°C within 5-10 seconds to shape it to a predetermined hardness, and then transfers it to the traction and splitting unit;

[0051] S45, the traction and cutting unit pulls out the cooled PVC sheet at a predetermined traction speed through a traction device and cuts it into sheets of specified lengths through a cutting device, and then packages it for shipment after inspection.

[0052] Further, the step S50 comprises the following steps:

[0053] S51, the appearance inspection unit obtains the image or video of the bio-based PVC plastic sheet through the set high-definition camera and converts it into recognizable appearance quality information, and transmits it to the component inspection unit;

[0054] S52, the component detection unit obtains various components and their proportions in the bio-based PVC plastic sheet sample powder through an infrared spectrometer and transmits them to the physical detection unit;

[0055] S53, the physical testing unit obtains the test data of hardness, density, tensile strength and wear resistance of the bio-based PVC plastic sheet sample and its powder through a hardness tester, a density tester, a plastic tensile measuring instrument and a plastic wear tester, and transmits the data to the environmental protection testing unit;

[0056] S54, the environmental protection testing unit uses a plastic smoke density tester and a RoHS harmful substance detector to determine whether the bio-based PVC plastic sheet sampling powder contains harmful substances such as heavy metals and whether it complies with environmental protection standards.

[0057] The system also includes a computer-readable storage medium containing a memory; the memory stores a computer program, and when the functional modules execute the computer program, the steps of any one of the above-mentioned methods for automatically making a bio-based PVC plastic sheet are implemented; the computer-readable storage medium stores a computer program, and when the functional modules execute the computer program, the steps of any one of the above-mentioned methods for automatically making a bio-based PVC plastic sheet are implemented; and also includes a bio-based PVC plastic sheet production control device, which is implemented by the above-mentioned method for automatically making a bio-based PVC plastic sheet.

[0058] The present invention also provides a bio-based PVC plastic sheet, which contains PVC resin, rubber powder, coconut shell powder, ethylene-octene copolymer, ethylene-vinyl acetate copolymer, light calcium carbonate, flame retardant modifier, lubricant, heat stabilizer, light stabilizer, plasticizer, and filler, and is realized by the above-mentioned automatic production method of bio-based PVC plastic sheet.

[0059] The beneficial effects of the present invention compared with the prior art are as follows:

[0060] By setting up the data acquisition module, model training module, parameter optimization module, production monitoring module and quality inspection module, the extrusion molding parameters can be automatically set, automatic extrusion molding production and automatic inspection can be carried out, thus realizing the fully automated production of PVC sheets, improving the sheet quality, improving production efficiency and reducing production costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or exemplary technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0062] Figure 1 It is a schematic diagram of the system module of the present invention;

[0063] Figure 2 It is a schematic diagram of a data acquisition module of the present invention;

[0064] Figure 3 This is a schematic diagram of a model training module of the present invention;

[0065] Figure 4 It is a schematic diagram of a parameter optimization module of the present invention;

[0066] Figure 5 It is a schematic diagram of a production monitoring module of the present invention;

[0067] Figure 6 It is a schematic diagram of the quality detection module of the present invention;

[0068] Figure 7 It is a schematic diagram of the method flow control program of the present invention;

[0069] Figure 8 This is a schematic diagram of step S10 in the method flow of the present invention;

[0070] Fig. 9 This is a schematic diagram of step S20 in the method flow of the present invention;

[0071] Fig.10This is a schematic diagram of step S30 in the method flow of the present invention;

[0072] Fig.11 This is a schematic diagram of step S40 in the method flow of the present invention;

[0073] Fig.12 It is a program schematic diagram of step S50 in the method flow of the present invention. DETAILED DESCRIPTION

[0074] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0075] The specific implementation of the present invention is described in detail below in conjunction with specific embodiments:

[0076] In order to make the technical problems, technical solutions and beneficial effects to be solved by this application more clearly understood, the application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not used to limit this application.

[0077] It should be noted that when a module is referred to as being "disposed on" another module, it can be directly on the other module or indirectly on the other module. When a module is referred to as being "connected to" another module, it can be directly connected to the other module or indirectly connected to the other module.

[0078] In the description of this application, "multiple" means two or more, unless otherwise clearly and specifically defined; "several" means one or more, unless otherwise clearly and specifically defined; the "bio-based PVC plastic sheet" is referred to as "PVC plastic sheet" or "PVC sheet" or "sheet" in this application.

[0079] In the description of this application, it should be noted that, unless otherwise clearly specified and limited, the terms "connected" and "connection" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances. The terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0080] See also Figure 1As shown, the present invention provides a method for automatically making a bio-based PVC plastic sheet, which is applied to a control system for automatically making a bio-based PVC plastic sheet. The system includes a data acquisition module, a model training module, a parameter optimization module, a production monitoring module, a quality detection module, a wireless communication module, a memory, an alarm, a processing center, and a smart phone; the data acquisition module, the model training module, the parameter optimization module, the production monitoring module, the quality detection module, the wireless communication module, the memory, and the alarm are respectively connected to the processing center.

[0081] The smart phone is connected to the wireless communication module wireless network within the range of a wireless network or the Internet, wherein the wireless network includes the Internet of Things and Wi-Fi, and the Internet of Things includes but is not limited to Z-wave, ZigBee, MQTT, CoAP, HTTP, AMQP, XMPP, websocket, LwM2M and other protocol networks.

[0082] The wireless communication module is provided with a wireless network unit, which is responsible for sending and receiving wireless signals, and is automatically networked with the intelligent control terminal within an effective network range, and an effective wireless network connection is performed through the Internet of Things system.

[0083] The alarm compares the actual model comprehensive evaluation score with the model comprehensive evaluation score standard stored in the memory, and automatically sounds an alarm and notifies to continue training the model if the standard is not met; and compares the various quality information of the sheet with the quality standard of the bio-based PVC plastic sheet stored in the memory, and automatically sounds an alarm and notifies to rework and readjust parameters if the standard is not met; and compares the various quality data actually detected with the quality standard of the bio-based PVC plastic sheet stored in the memory, and automatically sounds an alarm and notifies to rework if the quality does not meet the standard.

[0084] The memory is responsible for storing information of a data acquisition module, a model training module, a parameter optimization module, a production monitoring module, a quality inspection module, a wireless communication module, and an alarm, as well as storing model comprehensive evaluation sub-standards and bio-based PVC plastic sheet quality standards.

[0085] The processing center is responsible for the information transmission of the data acquisition module, model training module, parameter optimization module, production monitoring module, quality detection module, wireless communication module, alarm, and memory, and is the hub center of the system. It compares the actual model comprehensive evaluation score with the model comprehensive evaluation score standard stored in the memory: if it meets the standard, it is passed to the abnormal recognition unit for identification; if it does not meet the standard, it is passed to the alarm and notified to continue training the model; and compares the various quality information of the sheet with the quality standard of the bio-based PVC plastic sheet stored in the memory: if it meets the standard, it is set as the formal production process parameter; if it does not meet the standard, it is passed to the alarm and notified to rework and readjust the parameters; and compares the various quality data actually detected with the quality standard of the bio-based PVC plastic sheet stored in the memory: if the quality meets the standard, production or shipment continues; if the quality does not meet the standard, it is passed to the alarm and notified to rework.

[0086] See also Figure 2 As shown, the data acquisition module includes a data acquisition unit, a data processing unit, a pixel adjustment unit, a grayscale conversion unit, a median filtering unit, a feature extraction unit, and a data analysis unit. It collects production and operation data in the production process and extracts feature information for analysis to facilitate subsequent model training and parameter optimization, and passes it to the model training stage.

[0087] Furthermore, the data acquisition unit obtains various quality defect image information of the bio-based PVC plastic sheet by connecting to an industry database or a network platform, and transmits it to a data processing unit; the data processing unit performs cropping processing on the acquired various defect image data of the bio-based PVC plastic sheet, removes invalid or erroneous data, and transmits it to a pixel adjustment unit; the pixel adjustment unit obtains the adjusted pixel value according to the brightness contrast adjustment calculation formula "y = [x-127.5*(1-I)]*k+127.5*(1+I)", and transmits it to a grayscale conversion unit; the grayscale conversion unit obtains the adjusted pixel value according to the pixel grayscale calculation formula "Y = 0.299R+0.58G+0.114 B" obtains the converted grayscale image and passes it to the median filtering unit; the median filtering unit obtains the image after median filtering according to the median filtering method calculation formula "g(x,y)=med{f(xk,yi),(k,i∈W)}", and passes it to the feature extraction unit; the feature extraction unit extracts the shape, color, and texture feature information of various defects of the bio-based PVC plastic sheet in the image through the convolution layer of the convolutional neural network, and passes it to the data analysis unit; the data analysis unit analyzes the extracted features to obtain the feature information and process parameters corresponding to the eight quality defects of the PVC sheet as the basis for model training, so as to avoid similar defects in subsequent production.

[0088] See also Figure 3As shown, the model training module includes a training model unit, a loss function unit, a training verification unit, and an anomaly recognition unit, which is responsible for establishing and training a neural network model based on the collected production data to predict the impact of various parameters in the production process on product quality and pass it to the parameter optimization module.

[0089] Furthermore, the training model unit trains the labeled PVC plastic sheet quality defect image data set through a convolutional neural network to obtain the probability of the corresponding category and passes it to the loss function unit; the loss function unit calculates the loss function according to the loss function formula The minimum average value of the loss function is obtained and passed to the training verification unit; the training verification unit calculates the model evaluation score according to the formula "F1 = 2*[∑T P / ∑(T P +F P )*(∑T P / ∑T P +∑F N )] / [(∑T P / ∑(T P +F P )+(∑T P / ∑T P +∑F N ))” obtains the comprehensive evaluation score after model training and transmits it to the processing center; the abnormality recognition unit inputs the trained image into the convolutional neural network model, and uses the trained model to match the PVC plastic sheet image obtained in time during production to confirm whether there are defects and their categories.

[0090] See also Figure 4 As shown, the parameter optimization module includes a pressure calculation unit, a speed calculation unit, an extrusion calculation unit, a parameter preset unit, an operation implementation unit, and a sampling verification unit, which is responsible for optimizing the key parameters in the production process based on the trained model to improve production efficiency and product quality, improve product stability and consistency, and pass them to the production monitoring module.

[0091] Furthermore, the pressure calculation unit obtains the extrusion pressure of the PVC sheet according to the extrusion pressure calculation formula "Pi=P*A / Ao", and transmits it to the speed calculation unit; the speed calculation unit obtains the extrusion speed of the PVC sheet according to the extrusion speed calculation formula "S=Q / A", and transmits it to the extrusion calculation unit; the extrusion calculation unit obtains the extrusion amount of the PVC sheet according to the extrusion amount calculation formula "Q=(π*D*H*n) / 4", and transmits it to the parameter preset unit; the parameter preset unit matches the parameters optimized by model training with the industry database as the best process parameters as the predetermined process parameters for molding optimization, and transmits them to the operation implementation unit; the operation implementation unit automatically inputs the predetermined process parameters into the production molding equipment for stirring, tableting, and molding into the required bio-based PVC plastic sheet, and transmits it to the sampling verification unit; the sampling verification unit detects various quality information of the bio-based PVC plastic sheet through the detection equipment, and transmits it to the processing center.

[0092] See also Figure 5 As shown, the production monitoring module includes a material preparation unit, a mixing and plasticizing unit, an extrusion molding unit, a cooling and shaping unit, and a traction and segmentation unit. The real-time monitoring and management of production data is achieved through a cyber-physical system (CPS) to ensure the stability and efficiency of the production process, and the data is transmitted to the quality inspection module.

[0093] Furthermore, the material preparation unit mixes the materials according to the predetermined material formula mass ratio through an automatic batching control system, and transmits them to the mixing and plasticizing unit; the mixing and plasticizing unit controls the mixer through a frequency converter to stir the various added raw materials at low speed and high speed under predetermined process parameters to form a uniform PVC melt, and transmits it to the extrusion molding unit; the extrusion molding unit extrude the uniformly mixed PVC material under predetermined extrusion process parameters through a twin-screw extruder according to a predetermined sheet thickness to obtain a PVC plastic sheet, and transmits it to the cooling and shaping unit; the cooling and shaping unit puts the extruded PVC sheet into a cooling device to quickly cool it at a predetermined temperature and time, and transmits it to the traction and cutting unit; the traction and cutting unit pulls the cooled PVC sheet out through a traction device at a predetermined traction speed and cuts it into sheets of specified length through a cutting device, and packages and ships it after inspection.

[0094] See also Figure 6 As shown, the quality inspection module includes an appearance inspection unit, a component inspection unit, a physical inspection unit, and an environmental inspection unit. The quality data of the PVC plastic sheet is inspected by the plastic sheet inspection equipment to realize automatic inspection, reduce human inspection errors, improve inspection efficiency, and transmit the data to the processing center.

[0095] Furthermore, the appearance detection unit obtains images or videos of bio-based PVC plastic sheets through a high-definition camera and converts them into recognizable appearance quality information, and transmits them to the component detection unit; the component detection unit obtains various components and their proportions in the bio-based PVC plastic sheet sampling powder through an infrared spectrometer to ensure the quality and performance of the sheet, and transmits them to the physical detection unit; the physical detection unit obtains test data of hardness, density, tensile strength, and wear resistance of bio-based PVC plastic sheet sampling and its powder through physical performance detection equipment, and transmits them to the environmental protection detection unit; the environmental protection detection unit obtains whether the bio-based PVC plastic sheet sampling powder contains heavy metals and whether it meets environmental protection standards through a plastic smoke density tester and a RoHS harmful substance detector.

[0096] System operation working principle:

[0097] Before production, the data acquisition module collects production and operation data in the production process, extracts features for analysis, and passes them to the model training stage; then the model training module establishes a neural network model based on the collected production data and trains it, and passes it to the parameter optimization module; the parameter optimization module optimizes the key parameters in the production process based on the trained model and passes it to the production monitoring module; then the production monitoring module realizes real-time monitoring and management of production data through the information physical system (CPS), and passes it to the quality inspection module; the control quality inspection module detects various quality data of PVC plastic sheets through plastic sheet inspection equipment, and passes it to the processing center; the processing center compares the actual quality data with the quality standards of the bio-based PVC plastic sheets stored in the memory: if the quality meets the standard, production or shipment will continue; if the quality does not meet the standard, it will be passed to the alarm and rework will be notified.

[0098] When the operator or manager is outdoors or away from home, he can use a smartphone to automatically connect to the wireless network or the Internet through the wireless communication module, thereby realizing the combination of smartphones with the Internet and the Internet of Things. Through the mobile phone APP, the production quality of PVC sheets can be remotely monitored in real time, realizing automated production, improving production efficiency and reducing production costs.

[0099] See also Figure 7 As shown, the present invention provides a method for automatically making a bio-based PVC plastic sheet, comprising the following steps:

[0100] S10. Before production, the data acquisition module collects production and operation data during the production process and extracts feature information for analysis, so as to facilitate subsequent model training and parameter optimization, and passes it to the model training stage;

[0101] See also Figure 8As shown, the step S10 includes the following steps:

[0102] S11. The data acquisition unit obtains various quality defect image information of the bio-based PVC plastic sheet by connecting to the industry database or network platform for subsequent data processing and transmits it to the data processing unit;

[0103] It is further explained that the industry database includes a PVC sheet production quality database independently established by the enterprise based on the raw material formula, production process parameters, machine status, production quality and other data of bio-based PVC plastic sheets with different formula ratios each time, as well as a series of data stored in real time from the PVC sheet production quality database shared by other peer enterprises in the industry and PVC sheet production quality data information shared by other network platforms; the PVC sheet production process parameters include parameters of key steps such as ingredient ratio, mixing process, extrusion molding process, cooling and cutting process, and the optimal quality of bio-based PVC plastic sheets can be ensured by controlling these process parameters.

[0104] S12, the data processing unit performs cropping processing on the acquired image data of various defects of the bio-based PVC plastic sheet, removes invalid or erroneous data to ensure the accuracy and integrity of the data, and transmits the data to the pixel adjustment unit;

[0105] It is further explained that after scaling, rotating, flipping and other operations are performed on the acquired images through the PIL library to adapt to different application scenarios and model requirements, the acquired images are cropped or filled according to the task requirements to obtain more concerned areas or meet the requirements of the model input, so as to remove redundant parts and only retain the characteristic information of various defects of the bio-based PVC plastic sheet.

[0106] S13, the pixel adjustment unit obtains the adjusted pixel value according to the brightness contrast adjustment calculation formula "y = [x-127.5*(1-I)]*k+127.5*(1+I), y is the adjusted pixel value (PPI), x is the pixel value (PPI) before adjustment, I is the adjusted brightness (cd / m2), k is the adjusted contrast (cd / m2)", and transmits it to the grayscale conversion unit;

[0107] It is further explained that the pixel value x before adjustment is obtained through the pixel and size conversion formula "x = L*Dp*W*Dp, x is the pixel value before adjustment (PPI), L is the image length (in), Dp is the image resolution (dpi), and W is the image width (in)"; the original image is adjusted to a resolution of 800*600 pixels to ensure that the proportion of various defective images and the number of pixels per inch DPI of the bio-based PVC plastic sheet remain unchanged; the calculation formula for pixel adjustment mainly involves operations such as scaling, brightness and contrast adjustment in image processing. When adjusting the image size, the width or height of the image after adjustment is equal to the original width or height of the image before adjustment multiplied by the image scaling ratio, and the scaling ratio changes according to the need to adjust the size of the image.

[0108] S14, the grayscale conversion unit obtains the converted grayscale image according to the pixel grayscale calculation formula "Y = 0.299R + 0.58G + 0.114B, Y is the grayscale value of the image, R, G, B are the brightness values ​​of the red, green, and blue channels in the image respectively", and passes it to the median filtering unit;

[0109] To further explain, since the brightness value of red accounts for 29.9% of the total brightness value, the brightness value of green accounts for 58.7% of the total brightness value, and the brightness value of blue accounts for 11.4% of the total brightness value, the brightness coefficients of the red, green, and blue channels are taken as 0.299, 0.58, and 0.114 respectively; the color image is converted into a grayscale image, that is, the R, G, and B pixel points at the corresponding position are averaged to obtain the pixel point at that position; the grayscale value range obtained by calculating the formula "Y=0.299R+0.58G+0.114B" is 0 to 255, and the pixels in the color image are composed of the brightness values ​​of 3 channels, so each pixel in the grayscale image only needs one grayscale value to represent.

[0110] S15, the median filtering unit calculates the median filtering method according to the formula "g(x,y)=med{f(xk,yi),(k,i∈W)}, g(x,y) is the image after median filtering, f(x,y) is the original image, W is the designed two-dimensional template, k, i are the coordinate values ​​of the two-dimensional template" to obtain the image after median filtering, and passes it to the feature extraction unit;

[0111] It is further explained that the median filtering method is used to calculate the formula for nonlinear processing of the image, and the pixel values ​​in the template are arranged from small to large according to the grayscale value, and the original pixel values ​​are replaced by the sorted median values ​​as the new grayscale values, and each pixel (x,y)(x,y) in the original image f(x,y)f(x,y) is compared with each point (k,i) in the template W, thereby realizing denoising of the image; the designed two-dimensional template W is usually an odd-sized window, such as 3x3, 5x5, etc.; the median filtering method is to replace the value of a point in an image or digital sequence with the median value of each point in a neighborhood of the point, which can effectively suppress noise and keep the edge information of the image from being blurred, thereby eliminating isolated noise points; and check the sampling value in the input signal to determine whether it represents the signal itself, by using an observation window composed of an odd number of samples, sorting the values ​​in the window, taking the middle value as the output, removing the first value, obtaining a new sample, and repeating the above calculation process to remove noise in the image or other signals.

[0112] S16, the feature extraction unit extracts the shape, color, and texture feature information of various defects of the bio-based PVC plastic sheet in the image through the convolution layer of the convolutional neural network after the preprocessing, and transmits it to the data analysis unit;

[0113] To further illustrate, by classifying and labeling the collected standard images of bio-based PVC plastic sheets with various quality defects, eight types of bio-based PVC plastic sheets with quality defects are classified as follows: "bubble sheet" is category 1, "scratch sheet" is category 2, "stained sheet" is category 3, "indentation sheet" is category 4, "spotted sheet" is category 5, "uneven color sheet" is category 6, "rough surface sheet" is category 7, and "deformed sheet" is category 8; when category 1 is a positive sample, the remaining categories are negative samples, that is, the labeled data is (1,0,0,0,0,0,0,0), when category 2 is a positive sample, the remaining categories are negative samples, that is, the labeled data is (0,1,0,0,0,0,0,0,0), and when category 1 is a positive sample, the remaining categories are negative samples, that is, the labeled data is (0,1,0,0,0,0,0,0,0), When category 3 is a positive sample, the other categories are negative samples, that is, the labeled data is (0,0,1,0,0,0,0,0), when category 4 is a positive sample, the other categories are negative samples, that is, the labeled data is (0,0,0,1,0,0,0,0), when category 5 is a positive sample, the other categories are negative samples, that is, the labeled data is (0,0,0,0,1,0,0,0), when category 6 is a positive sample, the other categories are negative samples, that is, the labeled data is (0,0,0,0,0,1,0,0), when category 7 is a positive sample, the other categories are negative samples, that is, the labeled data is (0,0,0,0,0,0,1,0), when category 8 is a positive sample, the other categories are negative samples, that is, the labeled data is (0,0,0,0,0,0,0,1).

[0114] S17. The data analysis unit analyzes the extracted features to obtain the characteristic information and process parameters corresponding to the eight quality defects of bio-based PVC plastic sheets, which serve as the basis for model training to avoid similar defects in subsequent production.

[0115] It is further explained that the various quality defects of the bio-based PVC plastic sheet and their corresponding countermeasures are as follows: 1) Bubbles: ensure uniform dispersion of additives, control the moisture content of raw materials, optimize process parameters, and ensure complete plasticization; 2) Scratches: ensure material purity, ensure the cleanliness of the mold cavity surface, and ensure the cleanliness of the workshop environment; 3) Stains: ensure material purity, adjust the rationality of temperature and pressure, ensure the cleanliness of the mold cavity surface, and ensure the cleanliness of equipment and workshop environment; 4) Indentation: maintain pressure uniformity and improve the rationality of mold design; 5) Spots: maintain raw material uniformity and adjust temperature rationality; 6) Uneven color: strictly control the quality of raw materials, optimize the selection and use of dyes, and adjust parameters such as temperature, pressure and speed; 7) Rough surface: adjust mold temperature, optimize the feeding system, improve mold design, adjust cooling time, and adjust the amount of lubricant; 8) Deformation: appropriately shorten the heating time, reduce the heating temperature, reduce the melt flow rate, increase the stretching ratio of the sheet, adjust the extrusion direction and mold spacing, use negative mold molding, add a pressure-assisting device, and adjust the mold design.

[0116] S20, the model training module establishes a neural network model based on the collected production data and performs training to predict the impact of various parameters in the production process on product quality, and transmits it to the parameter optimization module;

[0117] See also Fig. 9 As shown, the step S20 includes the following steps:

[0118] S21, the training model unit trains the labeled category PVC plastic sheet quality defect image data set through a convolutional neural network to obtain the probability of the corresponding category, and passes it to the loss function unit;

[0119] It is further explained that the PVC plastic sheet image dataset that has been labeled with categories is trained through the constructed 10-layer deep convolutional neural network structure to obtain the probability of the corresponding category; a labeled dataset of PVC plastic sheet samples is established, including the bounding box coordinates and category labels of the PVC plastic sheet area to train the YOLOv5 model, and the hyperparameters are adjusted to optimize the detection performance; multiple bounding boxes in the model predict the image, each with a confidence score and category probability. For the detection of PVC plastic sheets, the system will screen out boxes with high confidence and belonging to the PVC plastic sheet category, including non-maximum suppression (NMS) and other technologies to remove overlapping prediction boxes to ensure that each PVC plastic sheet is marked only once.

[0120] S22, the loss function unit calculates the loss function according to the formula " J(θ) is the loss function, m is the number of samples, K is the number of categories, X k is the true label of the i-th sample for the k-th category, y k The minimum mean value of the loss function is obtained for the probability that the i-th sample predicted by the model belongs to the k-th category, and is passed to the training and verification unit;

[0121] Further explanation: by training the labeled category PVC plastic sheet image data set through convolutional neural network, the probability of the corresponding category is obtained, and the data is continuously trained using the back propagation principle until the total loss function of all samples is minimized, so that the probability of the predicted sample is close to 0 in the remaining categories and close to 1 in this category; taking category 1 as an example, when the i-th input is bubble sheet, that is, category 1 is a positive sample, and the other categories are negative samples, the labeled category data X k The output layer data is (1, 0, 0, 0, 0, 0), and the weight threshold is calculated by back-propagation gradient descent. The second training is performed repeatedly until the final curve becomes flat.

[0122] S23, the training verification unit calculates the model evaluation score according to the formula "F1=2*[∑T P / ∑(T P +F P )*(∑T P / ∑T P +∑F N )] / [(∑T P / ∑(T P +F P )+(∑T P / ∑T P +∑F N )), F1 is the comprehensive evaluation score of the model, T P is the number of samples correctly predicted as positive, F P is the number of samples incorrectly predicted as positive, F N The comprehensive evaluation score after model training is obtained by "the number of samples incorrectly predicted as negative classes" and passed to the processing center;

[0123] It is further explained that in the training process, the weights and biases in the network are updated by the back propagation algorithm, and the neural network is trained so that it gradually learns the defect features in the image; the test set is brought into the trained model to determine its accuracy, that is, the test set is used to evaluate the trained model before it can be put into use; the validation set is used to evaluate the performance of the trained model on new data, and the performance of the model can be evaluated by indicators such as accuracy, precision, and recall, and adjusted and improved as needed; the model evaluation score calculation formula is calculated by "Pr = ∑TP / ∑(T P +F P )"Re=∑T P / ∑T P +∑F N ” are substituted into “F1=2*(Pr*Re) / (Pr+Re)” to obtain, where Pr is the precision, Re is the recall, T P Also called true positive, true example, F P Also called false positive, false positive, F N Also called false negative or false negative.

[0124] S24, the processing center compares the actual model comprehensive evaluation score with the model comprehensive evaluation score standard stored in the memory: if it meets the standard, it is passed to the abnormal recognition unit for recognition; if it does not meet the standard, it is passed to the alarm and notified to continue training the model;

[0125] It is further explained that the model comprehensive evaluation score standard is to obtain the optimal evaluation score based on the comprehensive evaluation score of the company's own historical model training of similar PVC plastic sheets and the comprehensive evaluation score of the model training of similar PVC plastic sheets in the industry database; because the model recall rate data size is affected by factors such as data quality, model design, training data volume, and contextual information; when the data in the database is incomplete, inaccurate or redundant, it is difficult for the system to accurately find the data that matches it, resulting in false positives and false negatives; in deep learning, deeper network structures and more training data can enhance the expressiveness of the model, enabling it to better distinguish between targets and backgrounds.

[0126] S25. The abnormality recognition unit inputs the trained image into the convolutional neural network model, and uses the trained model to match the PVC plastic sheet image obtained in a timely manner during production to confirm whether there are defects and their categories.

[0127] It is further explained that the image is input into the model, and the trained model is used to predict the new monitoring image. The presence of defects and their types are determined based on the output results. If the model's judgment on the quality defects of the PVC plastic sheet reaches a certain threshold, the early warning system is triggered and corresponding automatic processing measures are taken in time; the various quality defect types of the PVC plastic sheet include: 1) Bubbles: There are water bubble-shaped protrusions on the surface of the sheet; 2) Scratches: There are scratches on the surface of the sheet; 3) Stains: The surface of the sheet is stained with oil, water stains, etc.; 4) Indentation: There are signs of extrusion on the surface of the sheet; 5) Spots: There are many spots on the surface of the sheet; 6) Uneven color: The color of the sheet surface is different; 7) Rough surface: The surface of the sheet is uneven; 8) Deformation: The surface of the sheet is warped.

[0128] S30, the parameter optimization module optimizes the key parameters in the production process according to the trained model to improve production efficiency and product quality, improve product stability and consistency, and pass it to the production monitoring module;

[0129] See also Fig.10 As shown, the step S30 includes the following steps:

[0130] S31, the pressure calculation unit calculates the extrusion pressure according to the extrusion pressure calculation formula "Pi = P*A / Ao, Pi is the extrusion pressure (kg / cm 2 ), P is the pump pressure (kg / cm 2 ), A is the effective area of ​​the injection cylinder (cm 2 ), Ao is the cross-sectional area of ​​the screw (cm 2 )” to obtain the extrusion pressure of the PVC sheet and transmit it to the speed calculation unit;

[0131] It is further explained that the pump pressure P, the effective area A of the injection cylinder, and the screw cross-sectional area Ao are all known parameters configured by the extruder at the factory; the extrusion pressure Pi is generally between 80 and 160 MPa, which is formed by the thrust and its reaction force. The greater the pressure, the greater the reaction force, and the reaction force is the source of reflux (backflow and leakage), thereby reducing the positive flow and reducing the extrusion volume; the shallower the screw groove, the more stable the extrusion volume, the screw groove depth affects the stability of the extrusion volume, and a shallow screw groove contributes to a more stable extrusion process. In addition, the moisture content and back pressure in the material also affect the extrusion pressure of the PVC sheet.

[0132] S32, speed calculation unit according to the extrusion speed calculation formula "S = Q / A, S is the extrusion speed (cm / h), Q is the pump discharge (cm 3 / h), A is the effective area of ​​the injection cylinder (cm 2 )” to obtain the extrusion speed of the PVC sheet and pass it to the extrusion calculation unit;

[0133] It is further explained that the pump discharge volume Q and the effective area A of the injection cylinder are known parameters of the extruder factory configuration; the extrusion speed of the PVC sheet with a width of 700-800mm and a thickness of 0.3-0.7mm is generally between 5-15 meters per minute. Affected by temperature, pressure, extruder specifications, screw rotation speed, etc., the head temperature must be controlled below the thermal decomposition temperature of the plastic to ensure that the plastic melt has good fluidity. Pressure is generated during the extrusion process. Increasing the head pressure can improve the mixing uniformity and stability of the extruded melt, but excessive pressure will affect the output and should be adjusted according to the specific extruder and material characteristics.

[0134] S33, the extrusion calculation unit obtains the extrusion amount of the PVC sheet according to the extrusion amount calculation formula "Q = (π*D*H*n) / 4, Q is the extrusion amount, D is the screw diameter, H is the screw groove depth, and n is the screw speed", and transmits it to the parameter preset unit;

[0135] Further explanation, the extrusion volume calculation formula "Q = (π*D*H*n) / 4" adopts a twin-screw extruder. If a self-cleaning twin-screw extruder is used, the extrusion volume calculation formula is "Q = V*b*(h1-h2)*(g*F*L) / 6η*(h1+h2)", where b is the screw groove width (cm), h1 and h2 are the filling point thread depth and the end thread depth respectively, η is the plastic viscosity, g is the acceleration of gravity, F is the extrusion pressure, and the other parameters are the same as the twin-screw extruder calculation formula; if a single-screw extruder is used, the extrusion volume calculation formula is "Q = π*D*H*n*tan(φ)", where φ is the helix angle, and the other parameters are the same as the twin-screw extruder calculation formula; the V, b, η, and L are all known parameters of the extruder factory configuration, among which the filling point thread depth h1 and the end thread depth h2 are reference data based on mold flow analysis and historical similar data.

[0136] S34, the parameter preset unit matches the parameters optimized by model training with the industry database to obtain the best process parameters as predetermined process parameters for molding optimization, and transmits them to the operation implementation unit;

[0137] It is further explained that since there are multiple groups of parameters for model training optimization, after matching with the corresponding multiple groups of data in the industry database, different types of data are produced and staggered to form different combinations of predetermined process parameters. During subsequent molding, each group of parameters will be adjusted accordingly according to potential defects that arise to obtain the best process parameters; the industry database includes a data set consisting of the company's historical accumulated molding process parameters, similar process parameters accumulated by various companies in the industry, and similar process parameters published on the Internet.

[0138] S35, the operation implementation unit automatically inputs the production molding equipment according to the predetermined process parameters to stir, press and mold the required bio-based PVC plastic sheets, and transmits them to the sampling verification unit;

[0139] It is further explained that before trial production, the purity, particle size, moisture content, performance stability and other indicators of each raw material are tested by incoming material testing equipment, and the ingredients are automatically weighed and automatically batched according to the predetermined ratio through the automatic batching control system to ensure the performance and quality of the product; the prepared raw materials are placed in the mixer and fully stirred according to the predetermined temperature and time mixing process parameters to ensure that the raw materials are fully mixed and evenly mixed without lumps and particles; the evenly mixed PVC mixed material is sent to the extruder and pressed into sheets under predetermined process parameters to ensure the quality and stability of the sheets; the formed PVC board is cooled according to the predetermined cooling temperature and cooling time, and then cut to the required size; finally, the cut PVC sheets are sent to the inspection area.

[0140] S36. The sampling verification unit detects the appearance, physical properties, chemical properties, electrical properties, and quality information of the bio-based PVC plastic sheet through testing equipment and transmits it to the processing center;

[0141] It is further explained that in the production process, the real-time temperature, pressure, stirring speed and other process parameters of each process are obtained through the intelligent sensors installed in each process to ensure the stability of the production process and the consistency of the product; the appearance quality, physical properties, chemical properties and electrical properties of the bio-based PVC plastic sheet are tested by high-definition cameras, physical properties testing equipment, chemical properties testing equipment and electrical properties testing equipment to obtain appearance quality information such as whether there are bubbles and cracks, whether the color is uniform, physical properties test data such as elongation, bending, impact resistance, chemical properties test data such as weather resistance and corrosion resistance, bio-based carbon content, synthetic polymer content, mass content, etc.

[0142] S37. The processing center compares the quality information of appearance, physical properties, chemical properties, electrical properties, and bio-based content with the quality standards of the bio-based PVC plastic sheet stored in the memory: if the standards are met, they are set as formal production process parameters; if the standards are not met, the alarm is transmitted to the alarm and the rework is notified to readjust the parameters.

[0143] It is further explained that the quality standards of the bio-based PVC plastic sheet include no bubbles, scratches, stains, indentations, spots on the surface, consistent surface color, no roughness or deformation, tensile strength, bending strength, and impact strength meeting physical performance test standards, weather resistance and corrosion resistance meeting chemical performance test standards, and carbon, synthetic polymer, and mass content meeting bio-based content test standards; if the quality information actually tested meets the quality standards, it is set as the formal process parameters and can be formally produced; if the quality information actually tested does not meet the quality standards, the corresponding process parameters are reworked and adjusted until the quality standards are met before formal production is started.

[0144] S40, the production monitoring module realizes real-time monitoring and management of production data through the cyber-physical system (CPS) to ensure the stability and efficiency of the production process, and transmits it to the quality inspection module;

[0145] See also Fig.11 As shown, the step S40 includes the following steps:

[0146] S41, the material preparation unit mixes the materials according to the predetermined material formula mass ratio: 25-35% PVC resin, 10-15% rubber powder, 8-12% coconut shell powder, 6-10% ethylene-octene copolymer, 5-8% ethylene-vinyl acetate copolymer, 5-10% light calcium carbonate, 5-8% flame retardant modifier, 2-5% lubricant, 0.6-1.5% heat stabilizer, 1-2% light stabilizer, 0.6-1.2 plasticizer, 0.3-0.8% filler through the automatic batching control system, and transmits them to the mixing and plasticizing unit;

[0147] It is further explained that the rubber powder has excellent properties such as good elasticity, wear resistance, high temperature resistance and chemical stability; the coconut shell powder is glass coconut shell mildew-proof powder, which has excellent environmental protection, mildew resistance and isolation properties; before batching, these bio-based PVC plastic sheet raw materials are properly dried, filtered and other pre-treated, and processed into powder or granular form, and then the purity, particle size, moisture content, performance stability and other indicators are tested, and automatically weighed and automatically batched according to a predetermined ratio through an automatic batching control system; the various additives are environmentally friendly, non-toxic and low-cost; the addition of the rubber powder, coconut shell powder and other bio-based materials makes the PVC sheet have excellent properties such as environmental protection, high temperature resistance, corrosion resistance, wear resistance and surface smoothness.

[0148] S42, the mixing and plasticizing unit controls the mixer through the frequency converter to stir the various raw materials at a low speed of 60-100°C and 80-100 rpm for 0.5-1 hour to ensure that the resin powder fully absorbs various additives, and then stirs at a high speed of 110-180°C and 800-1000 rpm for 2-8 hours to form a uniform PVC melt, which is then transferred to the extrusion molding unit;

[0149] Further explanation: Since the various raw materials of bio-based PVC plastic sheets need to be fully mixed during high-speed stirring to ensure the quality and performance of the product, the setting of stirring time needs to consider the characteristics of the raw materials, the efficiency of the equipment and the production needs. Appropriate stirring time helps to improve the uniformity and consistency of the product, thereby improving the overall performance of the product. According to industry data analysis, it is generally stirred at a low speed for about 1 hour to allow the resin powder time to fully absorb various additives, and then stirred at a high speed for 2-8 hours. The particles of various materials can be quickly mixed to become finer, and the temperature is quickly raised to reach a certain plasticization to ensure that the various raw materials are fully mixed and evenly distributed, thereby ensuring the quality and performance of the final product.

[0150] S43, the extrusion molding unit extrudes the uniformly mixed PVC material through a twin-screw extruder according to a predetermined sheet thickness at a material temperature of 150-180° C., a mold temperature of 40-60° C., an extrusion pressure of 80-160 MPa (800-1600 bar), and a screw speed of 400 rpm to obtain a PVC plastic sheet, and transfers it to a cooling and shaping unit;

[0151] It is further explained that the holding pressure is 40-60% of the injection pressure, and the back pressure does not exceed 30MPa (300bar). Since the extrusion molding temperature of the bio-based PVC sheet needs to be controlled between 185-205°C, which is determined according to the melting temperature and decomposition temperature characteristics of PVC, and since the melting temperature of PVC is close to its decomposition temperature, the temperature is controlled between 150-180°C during the molding process to ensure that the material can be fully melted and not decomposed during the processing; since the material pipe temperature is controlled between 160-190°C to ensure that the material can be fully melted, and the mold temperature is controlled between 40-60°C to avoid decomposition of the material in the mold, the temperature is strictly controlled during the extrusion process to avoid excessively high temperature causing material decomposition, or too low temperature causing the material to be unable to fully melt; the screw speed and temperature are adjusted to control the thickness and width of the sheet.

[0152] S44, the cooling and molding unit puts the extruded PVC sheet into a cooling device and rapidly cools it at a temperature of 70-85°C within 5-10 seconds to shape it to a predetermined hardness, and then transfers it to the traction and splitting unit;

[0153] It is further explained that since too low cooling temperature will affect the plasticization quality of PVC sheet, causing its deformation or excessive internal stress, and too high cooling temperature will cause pores or indentations on its surface, the cooling temperature of the bio-based PVC plastic sheet after extrusion molding should be controlled between 75℃-85℃ to ensure the stability of the sheet's geometric shape and internal structure and prevent the product from deforming under the action of gravity; if the cooling time is too short, the plastic will not be fully cooled and solidified, affecting the product's dimensional accuracy and mechanical properties, and if the cooling time is too long, the production cycle will be extended and production efficiency will be reduced. Therefore, the cooling time of bio-based PVC plastic sheet after extrusion is usually between 5-10 seconds, so that the sheet can be fully cooled and solidified, ensuring the product's dimensional accuracy and mechanical properties, eliminating friction overheating, stabilizing the plastic extrusion pressure, and promoting uniform mixing of the plastic.

[0154] S45, the traction and cutting unit pulls out the cooled PVC sheet at a predetermined traction speed through a traction device and cuts it into sheets of specified lengths through a cutting device, and then packages it for shipment after inspection.

[0155] It is further explained that the pulling speed needs to match the extrusion speed to ensure that the sheet will not be deformed or have quality problems due to uneven speed during the cooling process. The adjustment of the pulling speed needs to be achieved through experiments and continuous fine-tuning in actual production to achieve the best effect. The setting of the cutting length needs to be determined according to the final use and specification requirements of the sheet. Too short a cutting length will result in material waste, while too long a cutting length may affect subsequent processing and handling. Therefore, the pulling speed is automatically adjusted according to the length of the sheet to be divided.

[0156] S50, the quality inspection module detects various quality data of PVC plastic sheets through plastic sheet inspection equipment, realizes automatic inspection, reduces human inspection errors, improves inspection efficiency, and transmits the data to the processing center;

[0157] See also Fig.12 As shown, the step S50 includes the following steps:

[0158] S51, the appearance inspection unit obtains the image or video of the bio-based PVC plastic sheet through the set high-definition camera and converts it into recognizable appearance quality information, and transmits it to the component inspection unit;

[0159] It is further explained that the appearance quality information of the bio-based PVC plastic sheet includes whether there are bubbles, scratches, stains, indentations, spots on the surface, and whether the surface color is consistent, whether the surface is rough, whether it is deformed, etc., all of which are caused by the quality of raw materials, production process, mold design and operation process; the bubbles are caused by unstable temperature, pressure or raw material quality during the production process of the PVC sheet; the scratches are caused by abnormal cleanliness of the mold and the cleanliness of the production environment; the stains are caused by abnormal cleanliness of the mold and the cleanliness of the production environment during the production process; the indentations are caused by uneven pressure or mold problems during the production process; the spots are caused by uneven raw materials, improper temperature control, etc.; the uneven color is caused by the decomposition of PVC resin or improper use of thermal stabilizers; the rough surface and deformation are caused by unreasonable mold design or improper pressure control during the production process.

[0160] S52, the component detection unit obtains various components and their proportions in the bio-based PVC plastic sheet sample powder through an infrared spectrometer to ensure the quality and performance of the sheet, and transmits them to the physical detection unit;

[0161] It is further explained that the infrared spectrometer uses the absorption characteristics of substances to infrared radiation of different wavelengths to analyze molecular structure and chemical composition. When the PVC sheet powder sample absorbs infrared radiation of a certain frequency, the vibration energy level of the molecule transitions, and the light of the corresponding frequency in the transmitted light beam is weakened, resulting in an intensity difference between the corresponding radiation of the reference light path and the sample light path, thereby obtaining the infrared spectrum of the measured PVC sheet powder sample and obtaining various components and their proportions; the various components of the bio-based PVC plastic sheet are obtained by sampling from production, crushing them into powder, and then detecting and analyzing them with an infrared spectrometer.

[0162] S53, the physical testing unit obtains the test data of hardness, density, tensile strength and wear resistance of the bio-based PVC plastic sheet sample and its powder through a hardness tester, a density tester, a plastic tensile measuring instrument and a plastic wear tester, and transmits the data to the environmental protection testing unit;

[0163] It is further explained that the density detector, plastic tensile measuring instrument, and plastic wear tester are respectively controlled by intelligent control software, and the bio-based PVC plastic sheet sampling powder input into the detection area is detected one by one through the conveying device, and the density, tensile strength, and wear resistance test data of the bio-based PVC plastic sheet sampling powder in the detection area are obtained respectively, and the test data are transferred to the memory for storage; the hardness data of the PVC sheet is obtained by testing the hardness of the sampled blocks of PVC sheet input into the detection area through a hardness tester, and the hardness is transferred to the memory for storage.

[0164] S54, the environmental protection testing unit uses a plastic smoke density tester and a RoHS harmful substance detector to determine whether the bio-based PVC plastic sheet sampling powder contains harmful substances such as heavy metals and whether it complies with environmental protection standards.

[0165] It is further explained that the plastic smoke density tester and the RoHS harmful substance detector are respectively controlled by intelligent control software, and the bio-based PVC plastic sheet sampling powder input into the detection area is detected one by one through the conveying device, and the detection data of heavy metal harmful substances and their content in the bio-based PVC plastic sheet sampling powder in the detection area and whether the content meets the environmental protection standards are obtained respectively, and are transmitted to the memory for storage; the heavy metal harmful substances include lead, cadmium, barium salts, etc., which are usually used as stabilizers, but may have adverse effects on the human reproductive system and endocrine system after long-term contact or ingestion; the environmental protection standard refers to the bio-based components and their content in the bio-based PVC plastic sheet sampling powder, and the performance of biodegradable plastics must meet specific national standards and test methods.

[0166] S60, the processing center compares the quality data actually detected with the quality standards of the bio-based PVC plastic sheet stored in the memory: if the quality meets the standard, continue production or shipment; if the quality does not meet the standard, the alarm is transmitted to the alarm and a notice is given to rework.

[0167] It is further explained that the quality standards of the bio-based PVC plastic sheet include appearance quality such as no bubbles, scratches, stains, indentations, spots on the surface, consistent surface color, smooth surface, no deformation, width and thickness meeting the standards, physical indicators such as hardness, density, tensile strength, wear resistance meeting the standards, harmful substances such as heavy metal content meeting the standards, and meeting environmental protection standards, that is, the bio-based components and their contents, and the performance of biodegradable plastics meet specific national standards. These quality standards must not only meet national standards but also meet the standards of the country or region where the customer is located, and must also meet the standards specified by the customer; the bio-based PVC plastic sheet is non-toxic and has no side effects, so its waste or scrapped garbage can be crushed and recycled after preliminary treatment, and can be re-extruded into similar PVC sheets.

[0168] Further explanation: the above steps are displayed in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows, unless clearly stated in this article. There is no strict order restriction for the execution of these steps, and these steps can also be executed in other orders, and some steps can include multiple sub-steps or multiple stages, which are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps; if the actual units of the parameters of the above formulas are inconsistent with those in the formulas, the unit recognition is performed through the machine control system and automatically converted to the units in the formulas, so as to ensure the consistency of the units.

[0169] Further explanation, the present invention is described according to the content implemented by the software program of the automatic production control system of a bio-based PVC plastic sheet. For each automatic production method of a bio-based PVC plastic sheet, it is divided into several modules or units to implement the software program instructions generated by each step. The software program instructions include the automatic production method of a bio-based PVC plastic sheet described above.

[0170] The system provided by the present invention also includes a computer-readable storage medium containing a memory; the memory stores a computer program, and when the functional modules execute the computer program, the steps of the above-mentioned method for automatically making a bio-based PVC plastic sheet are implemented; the computer-readable storage medium stores a computer program, and when the computer program is executed by the functional modules, the steps of the above-mentioned method for automatically making a bio-based PVC plastic sheet are implemented; and also includes a bio-based PVC plastic sheet production control device, which is implemented by the above-mentioned method for automatically making a bio-based PVC plastic sheet.

[0171] It is further explained that the computer program is divided into multiple modules / units, and the multiple modules / units are stored in the memory and executed by each module / unit to complete the present invention; the multiple modules / units can be a series of computer program instructions that can complete specific functions, and the instructions are used to describe the execution process of the computer program in each module / unit.

[0172] It is further explained that the control device is composed of the above-mentioned related equipment or devices. According to the production needs of the enterprise, it can be made into a complete set of PVC plastic sheet production line, or it can be made into a unit device of each functional module belonging to each step. The packaging bags and supporting materials required for production are connected and transmitted in segments through the conveyor belt. These equipment structures are not described in detail here, and no structural restrictions are imposed. The above only describes the automatic control function of the software.

[0173] The present invention also provides a bio-based PVC plastic sheet material, which is realized by using the above-mentioned automatic production method of the bio-based PVC plastic sheet material.

[0174] It is obvious to those skilled in the art that the present application is not limited to the details of the above exemplary embodiments, and that the present application can be implemented in other specific forms without departing from the spirit or basic features of the present application. Therefore, no matter from which point of view, the embodiments should be regarded as exemplary and non-restrictive, and the scope of the present application is defined by the attached claims rather than the above description, and therefore it is intended that all changes that fall within the meaning and scope of the equivalent elements of the claims are included in the present application.

[0175] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present application and are not intended to limit it. Although the present application has been described in detail with reference to the preferred embodiments, a person of ordinary skill in the art should understand that the technical solution of the present application can be modified or replaced by equivalents, and all of these should be included in the scope of protection of the present application.

Claims

1. A bio-based PVC plastic sheet and an automatic production method thereof, characterized in that: The method is applied to a bio-based PVC plastic sheet production quality control system, the system comprises a data acquisition module, a model training module, a parameter optimization module, a production monitoring module, a quality detection module, a wireless communication module, a memory, an alarm, a processing center, and a smart phone; the data acquisition module, the model training module, the parameter optimization module, the production monitoring module, the quality detection module, the wireless communication module, the memory, and the alarm are respectively connected to the processing center; the smart phone is respectively connected to the wireless communication module wireless network within the wireless network or the Internet; the method comprises the following steps: S10, before production, the data acquisition module collects production and operation data during the production process and extracts features for analysis, and passes them to the model training stage; S20, the model training module establishes a neural network model based on the collected production data and performs training to predict the impact of various parameters in the production process on product quality, and transmits it to the parameter optimization module; S30, the parameter optimization module optimizes the key parameters in the production process according to the trained model to improve production efficiency and product quality, and transmits the parameters to the production monitoring module; S40, the production monitoring module realizes real-time monitoring and management of production data through the cyber-physical system (CPS) to ensure the stability and efficiency of the production process, and transmits it to the quality inspection module; S50, the quality inspection module detects various quality data of the PVC plastic sheet through the plastic sheet inspection equipment, realizes automatic inspection, and transmits it to the processing center; S60, the processing center compares the quality data actually detected with the quality standards of the bio-based PVC plastic sheet stored in the memory: if the quality meets the standard, continue production or shipment; if the quality does not meet the standard, the alarm is transmitted to the alarm and a notice is given to rework.

2. A method for producing a bio-based PVC plastic sheet as claimed in claim 1, characterized in that: The system also includes: the smart phone is connected to the wireless network of the wireless communication module within the range of a wireless network or the Internet; the wireless communication module is provided with a wireless network unit, which is responsible for sending and receiving wireless signals, and is automatically networked with the intelligent control terminal within the effective network range; the alarm compares the actual model comprehensive evaluation score with the model comprehensive evaluation score standard stored in the memory, and automatically issues a sound alarm and notifies to continue training the model if it does not meet the standard; and compares the various quality information of the sheet with the quality standard of the bio-based PVC plastic sheet stored in the memory, and automatically issues a sound alarm and notifies to rework and readjust the parameters if it does not meet the standard; and compares the various quality data actually detected with the quality standard of the bio-based PVC plastic sheet stored in the memory, and automatically issues a sound alarm and notifies to rework if the quality does not meet the standard; the memory is responsible for the storage of information of the data acquisition module, the model training module, the parameter optimization module, the production monitoring module, the quality detection module, the wireless communication module, the alarm, and the storage of the model comprehensive evaluation score standard and the bio-based PVC plastic sheet quality standard; The processing center is responsible for the information transmission of the data acquisition module, model training module, parameter optimization module, production monitoring module, quality detection module, wireless communication module, alarm, and memory, and is the hub center of the system. It compares the actual model comprehensive evaluation score with the model comprehensive evaluation score standard stored in the memory: if it meets the standard, it is passed to the abnormal recognition unit for identification; if it does not meet the standard, it is passed to the alarm and notified to continue training the model; and compares the various quality information of the sheet with the quality standard of the bio-based PVC plastic sheet stored in the memory: if it meets the standard, it is set as the formal production process parameter; if it does not meet the standard, it is passed to the alarm and notified to rework and readjust the parameters; and compares the various quality data actually detected with the quality standard of the bio-based PVC plastic sheet stored in the memory: if the quality meets the standard, production or shipment will continue; if the quality does not meet the standard, it is passed to the alarm and notified to rework; The data acquisition module includes a data acquisition unit, a data processing unit, a pixel adjustment unit, a grayscale conversion unit, a median filter unit, a feature extraction unit, and a data analysis unit, which collects production and operation data in the production process and extracts feature information for analysis, and passes it to the model training stage; The model training module includes a training model unit, a loss function unit, a training verification unit, and an anomaly recognition unit, which is responsible for establishing and training a neural network model based on the collected production data, and passing it to the parameter optimization module; The parameter optimization module includes a pressure calculation unit, a speed calculation unit, an extrusion calculation unit, a parameter preset unit, an operation implementation unit, and a sampling verification unit, which is responsible for optimizing the key parameters in the production process according to the trained model and passing them to the production monitoring module; The production monitoring module includes a material preparation unit, a mixing and plasticizing unit, an extrusion molding unit, a cooling and shaping unit, and a traction and segmentation unit, which realizes real-time monitoring and management of production data through a cyber-physical system (CPS) and transmits it to the quality inspection module; The quality inspection module includes an appearance inspection unit, a component inspection unit, a physical inspection unit, and an environmental inspection unit. The quality data of the PVC plastic sheet is inspected by a plastic sheet inspection device and transmitted to a processing center.

3. The method for producing a bio-based PVC plastic sheet according to claim 1, characterized in that: The step S10 comprises the following steps: S11. The data acquisition unit obtains various quality defect image information of the bio-based PVC plastic sheet by connecting to the industry database or network platform, and transmits it to the data processing unit; S12, the data processing unit performs cropping processing on the acquired image data of various defects of the bio-based PVC plastic sheet, removes invalid or erroneous data, and transmits the data to the pixel adjustment unit; S13, the pixel adjustment unit adjusts the brightness contrast according to the calculation formula "y = [x-127.5*(1-I)]*k+127.5*(1+I), y is the pixel value after adjustment (PPI), x is the pixel value before adjustment (PPI), I is the adjusted brightness (cd / m 2 ), k is the adjustment contrast (cd / m 2 )” to obtain the adjusted pixel value and pass it to the grayscale conversion unit; S14, the grayscale conversion unit obtains the converted grayscale image according to the pixel grayscale calculation formula "Y = 0.299R + 0.58G + 0.114B, Y is the grayscale value of the image, R, G, B are the brightness values ​​of the red, green, and blue channels in the image respectively", and passes it to the median filtering unit; S15, the median filter unit calculates the median filter method formula "g(x,y) = med{f(xk,yi), (k,i∈W)}, g(x,y) is the image after median filtering, f(x,y) is the original image, W is the designed two-dimensional template, k, i are the coordinate values ​​of the two-dimensional template" to obtain the image after median filtering, and passes it to the feature extraction unit; S16, the feature extraction unit extracts the shape, color, and texture feature information of various defects of the bio-based PVC plastic sheet in the image through the convolution layer of the convolutional neural network after the preprocessing, and transmits it to the data analysis unit; S17. The data analysis unit analyzes the extracted features to obtain the characteristic information and process parameters corresponding to the eight quality defects of the bio-based PVC plastic sheet, so as to avoid similar defects in subsequent production.

4. The method for producing a bio-based PVC plastic sheet according to claim 1, characterized in that: The step S20 comprises the following steps: S21, the training model unit trains the labeled category PVC plastic sheet quality defect image data set through a convolutional neural network to obtain the probability of the corresponding category, and passes it to the loss function unit; S22, loss function unit is calculated according to the loss function formula" J(θ) is the loss function, m is the number of samples, K is the number of categories, Xk is the true label of the i-th sample for the k-th category, and yk is the probability predicted by the model that the i-th sample belongs to the k-th category. The minimum average value of the loss function is obtained and passed to the training and verification unit; S23, the training verification unit calculates the model evaluation score according to the formula "F1=2*[∑T P / ∑(T P +F P )*(∑T P / ∑T P +∑F N )] / [(∑T P / ∑(T P +F P )+(∑T P / ∑T P +∑F N )), F1 is the comprehensive evaluation score of the model, T P is the number of samples correctly predicted as positive, F P is the number of samples incorrectly predicted as positive, F N The comprehensive evaluation score after model training is obtained by "the number of samples incorrectly predicted as negative classes" and passed to the processing center; S24, the processing center compares the actual model comprehensive evaluation score with the model comprehensive evaluation score standard stored in the memory: if it meets the standard, it is passed to the abnormal recognition unit for recognition; if it does not meet the standard, it is passed to the alarm and notified to continue training the model; S25. The abnormality recognition unit inputs the trained image into the convolutional neural network model, and uses the trained model to match the PVC plastic sheet image obtained in a timely manner during production to confirm whether there are defects and their categories.

5. The method for producing a bio-based PVC plastic sheet according to claim 1, characterized in that: The step S30 comprises the following steps: S31, the pressure calculation unit calculates the extrusion pressure according to the extrusion pressure calculation formula "Pi = P*A / Ao, Pi is the extrusion pressure (kg / cm 2 ), P is the pump pressure (kg / cm 2 ), A is the effective area of ​​the injection cylinder (cm 2 ), Ao is the cross-sectional area of ​​the screw (cm 2 )” to obtain the extrusion pressure of the PVC sheet and transmit it to the speed calculation unit; S32, speed calculation unit according to the extrusion speed calculation formula "S = Q / A, S is the extrusion speed (cm / h), Q is the pump discharge (cm 3 / h), A is the effective area of ​​the injection cylinder (cm 2 )” to obtain the extrusion speed of the PVC sheet and pass it to the extrusion calculation unit; S33, the extrusion calculation unit obtains the extrusion amount of the PVC sheet according to the extrusion amount calculation formula "Q = (π*D*H*n) / 4, Q is the extrusion amount, D is the screw diameter, H is the screw groove depth, and n is the screw speed", and transmits it to the parameter preset unit; S34, the parameter preset unit matches the parameters optimized by model training with the industry database to obtain the best process parameters as the predetermined process parameters, and transmits them to the operation implementation unit; S35, the operation implementation unit automatically inputs the production molding equipment according to the predetermined process parameters to stir, press and mold the required bio-based PVC plastic sheets, and transmits them to the sampling verification unit; S36. The sampling verification unit detects the appearance, physical properties, chemical properties, electrical properties, and quality information of the bio-based PVC plastic sheet through testing equipment and transmits it to the processing center; S37. The processing center compares the quality information of the PVC sheet with the quality standards of the bio-based PVC plastic sheet stored in the memory: if the standards are met, they are set as formal production process parameters; if the standards are not met, the alarm is transmitted to the alarm and the rework is notified to readjust the parameters.

6. A method for producing a bio-based PVC plastic sheet as claimed in claim 1, characterized in that: The step S40 comprises the following steps: S41, the material preparation unit mixes the materials according to the predetermined material formula mass ratio: 25-35% PVC resin, 10-15% rubber powder, 8-12% coconut shell powder, 6-10% ethylene-octene copolymer, 5-8% ethylene-vinyl acetate copolymer, 5-10% light calcium carbonate, 5-8% flame retardant modifier, 2-5% lubricant, 0.6-1.5% heat stabilizer, 1-2% light stabilizer, 0.6-1.2 plasticizer, 0.3-0.8% filler through the automatic batching control system, and transmits them to the mixing and plasticizing unit; S42, the mixing and plasticizing unit controls the mixer through the frequency converter to stir the various raw materials at a low speed of 60-100°C and 80-100 rpm for 0.5-1 hour to ensure that the resin powder fully absorbs various additives, and then stirs them at a high speed of 110-180°C and 800-1000 rpm for 2-8 hours to form a uniform PVC melt, which is then transferred to the extrusion molding unit; S43, the extrusion molding unit extrudes the uniformly mixed PVC material through a twin-screw extruder according to a predetermined sheet thickness at a material temperature of 150-180° C., a mold temperature of 40-60° C., an extrusion pressure of 80-160 MPa (800-1600 bar), and a screw speed of 400 rpm to obtain a PVC plastic sheet, and transfers it to a cooling and shaping unit; S44, the cooling and molding unit puts the extruded PVC sheet into a cooling device and rapidly cools it at a temperature of 70-85°C within 5-10 seconds to shape it to a predetermined hardness, and then transfers it to the traction and splitting unit; S45, the traction and cutting unit pulls out the cooled PVC sheet at a predetermined traction speed through a traction device and cuts it into sheets of specified lengths through a cutting device, and then packages it for shipment after inspection.

7. The method for producing a bio-based PVC plastic sheet according to claim 1, characterized in that: The step S50 comprises the following steps: S51, the appearance inspection unit obtains the image or video of the bio-based PVC plastic sheet through the set high-definition camera and converts it into recognizable appearance quality information, and transmits it to the component inspection unit; S52, the component detection unit obtains various components and their proportions in the bio-based PVC plastic sheet sample powder through an infrared spectrometer and transmits them to the physical detection unit; S53, the physical testing unit obtains the test data of hardness, density, tensile strength and wear resistance of the bio-based PVC plastic sheet sample and its powder through a hardness tester, a density tester, a plastic tensile measuring instrument and a plastic wear tester, and transmits the data to the environmental protection testing unit; S54, the environmental protection testing unit uses a plastic smoke density tester and a RoHS harmful substance detector to determine whether the bio-based PVC plastic sheet sampling powder contains harmful substances such as heavy metals and whether it complies with environmental protection standards.

8. A method for producing a bio-based PVC plastic sheet as described in claims 1-7, characterized in that: The system also includes a computer-readable storage medium containing a memory; the memory stores a computer program, and when the functional modules execute the computer program, the steps of the method for making a bio-based PVC plastic sheet described in any one of claims 1 to 7 are implemented; the computer-readable storage medium stores a computer program, and when the computer program is executed by the functional modules, the method for making a bio-based PVC plastic sheet described in any one of claims 1 to 7 is implemented; and also includes a bio-based PVC plastic sheet production control device, which is implemented by the automatic method for making a bio-based PVC plastic sheet described in claims 1 to 7.

9. A bio-based PVC plastic sheet, comprising resin, rubber powder, coconut shell powder, ethylene-octene copolymer, ethylene-vinyl acetate copolymer, light calcium carbonate, flame retardant modifier, lubricant, heat stabilizer, light stabilizer, plasticizer, and filler, characterized in that: The method is realized by using the bio-based PVC plastic sheet production method described in any one of claims 1 to 7.

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