Automatic raw material batching control system for PVC plastic tile production
Through data collection, fuzzy logic control and machine vision detection, the raw material formula ratio of PVC plastic tiles is dynamically adjusted, which solves the problem of inaccurate ratio in the production process, realizes closed-loop control of the production process, and improves product quality and production efficiency.
Patent Information
- Application Number
- CN202510903484.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-07-01
- Publication Date
- 2025-10-17
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
The raw material ratio in the production of PVC plastic tiles is inaccurate and the production process is unstable. It is difficult to monitor the changes in the raw material status and make dynamic adjustments in real time, resulting in delayed quality control and affecting product quality.
The data acquisition module is used to obtain raw material status and characteristic data, and the fuzzy logic control algorithm and optimization algorithm are used to dynamically adjust the formula ratio. The machine vision detection and deviation analysis module are combined to correct the ratio in real time. Accurate feeding and mixing are achieved through closed-loop control, and the formula is optimized to reduce the defect rate.
It improves the adaptability of the PVC plastic tile production process and the consistency of product quality, reduces the defect rate, improves production efficiency and automation level, and optimizes the quality control system.
Smart Images
Figure CN120802856A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the technical field of raw material automatic batching, and particularly relates to a raw material automatic batching control system for PVC plastic tile production. BACKGROUND
[0002] With the continuous improvement of industrial automation level, the precise control of production process and raw material ratio gradually becomes the key to improving product quality and production efficiency. In the PVC plastic tile production process, batching usually relies on manual experience or simple control algorithm, and there are problems of inaccurate ratio and unstable production process.
[0003] The PVC plastic tile production control mainly depends on fixed raw material ratio, and fails to monitor the state change of raw material and dynamic adjustment in the production process, so that the accuracy of the ratio and the production efficiency cannot be effectively improved, and the quality control is relatively lagging behind, and it is difficult to timely find and correct the quality defects in the production process, thereby affecting the final quality of the product. SUMMARY
[0004] In view of the above existing problems, the present application is proposed.
[0005] Therefore, the present application provides a raw material automatic batching control system for PVC plastic tile production, which solves the problems of lack of dynamic adjustment of raw material ratio and difficulty in timely correction of quality defects.
[0006] To solve the above technical problems, the present application provides the following technical scheme: The present application provides a raw material automatic batching control system for PVC plastic tile production, which comprises a data acquisition module, a state data and a characteristic data of the PVC plastic tile raw material are acquired, and a PVC plastic tile formula ratio is set; a formula analysis module, according to a fuzzy logic control algorithm, the state data of the PVC plastic tile raw material is analyzed to produce the PVC plastic tile formula ratio required for the production of the PVC plastic tile, and the PVC plastic tile formula ratio is adjusted through an optimized dynamic algorithm; a monitoring module, the PVC plastic tile raw material is processed, and the PVC plastic tile raw material feeding amount and flow are monitored in real time; a deviation analysis module, by comparing the PVC plastic tile raw material feeding amount and flow with the set PVC plastic tile batching, a batching deviation is obtained, and is analyzed, and the batching deviation is corrected by adjusting the feeding speed; a quality detection module, a product is processed by a machine vision device, potential quality defects are identified, and a quality defect analysis result is obtained; a feedback optimization module, based on the quality defect analysis result, the set PVC plastic tile batching ratio is optimized, and an accurate PVC plastic tile batching ratio scheme is obtained.
[0007] As a preferred scheme of the raw material automatic batching control system for PVC plastic tile production, the state data and characteristic data of the PVC plastic tile raw material are collected, and the PVC plastic tile formula proportion is set, including the following steps, Based on the state data and characteristic data of the PVC plastic tile raw material, a formula model is constructed by dynamically adjusting the raw material ratio using mathematical modeling and optimization algorithm; The characteristic data of the PVC plastic tile raw material is input into the formula model to obtain the PVC plastic tile formula proportion.
[0008] As a preferred scheme of the raw material automatic batching control system for PVC plastic tile production, the state data of the PVC plastic tile raw material is analyzed to obtain the PVC plastic tile formula proportion required for producing the PVC plastic tile according to the fuzzy logic control algorithm, including the following steps, The state data of the PVC plastic tile raw material is modeled using multiple regression analysis to obtain the formula data of the state data of the PVC plastic tile raw material; The state data of the PVC plastic tile raw material is compared with the formula data of the state data of the PVC plastic tile raw material, and the fuzzy logic control algorithm is used to calculate the PVC plastic tile formula proportion required for producing the PVC plastic tile from the state data of the PVC plastic tile raw material.
[0009] As a preferred scheme of the raw material automatic batching control system for PVC plastic tile production, the PVC plastic tile formula proportion is adjusted by an optimization dynamic algorithm, including the following steps, The particle swarm optimization algorithm is used to dynamically adjust the PVC plastic tile formula proportion, and each particle represents a formula proportion; The multiple regression analysis method is used to analyze the PVC plastic tile formula proportion and the state data of the PVC plastic tile raw material to obtain the quality score of the PVC plastic tile product; According to the quality score of the PVC plastic tile product, the simulated annealing algorithm is used to optimize the raw material formula proportion; The flow controller of the automatic feeding equipment is adjusted to accurately adjust the feeding proportion of the PVC plastic tile, the filler and the reinforcing material, and the adjusted raw material ratio of the PVC plastic tile is obtained.
[0010] As a preferred scheme of the raw material automatic batching control system for PVC plastic tile production, the PVC plastic tile raw material is processed, and the PVC plastic tile raw material feeding amount and flow are monitored in real time, including the following steps, The filling material, the reinforcing material and the PVC plastic tile raw material are mixed by using a mixer according to the adjusted proportion of the PVC plastic tile raw material. The filling material, the reinforcing material and the PVC plastic tile raw material are mixed by using a mixer according to the adjusted proportion of the PVC plastic tile raw material.
[0011] As a preferred scheme of the raw material automatic batching control system for PVC plastic tile production, the comparison of the raw material feeding amount and the set PVC plastic tile batching includes the following steps, The feeding rate and the feeding total amount of the PVC plastic tile, the filling material and the reinforcing material are accurately measured by using a volume flow meter to obtain the actual feeding amount of the PVC plastic tile raw material. The target feeding amount is obtained by analyzing the PVC plastic tile, the filling material and the reinforcing material by using an adjustment algorithm. The feeding deviation of the PVC plastic tile raw material is calculated by comparing the raw material feeding amount and the set PVC plastic tile batching by using a deviation analysis algorithm.
[0012] As a preferred scheme of the raw material automatic batching control system for PVC plastic tile production, the analysis of the feeding deviation includes the following steps, The feeding deviation is analyzed by setting a feeding deviation threshold value. When the feeding deviation is less than the set feeding deviation threshold value, the raw material feeding amount is within the allowable error range, and the current production state is maintained. When the feeding deviation is equal to the set deviation threshold value, the raw material feeding amount is at the critical point of the error range, an alarm is issued, and processing is performed.
[0013] When the feeding deviation is greater than the set deviation threshold value, the raw material feeding amount exceeds the error range, and the feeding amount is adjusted.
[0014] As a preferred scheme of the raw material automatic batching control system for PVC plastic tile production, the correction of the batching deviation by adjusting the feeding speed includes the following steps, The feeding speed is adjusted based on the adjusted feeding amount. The feeding speed of the PVC plastic tile raw material is adjusted by adjusting the speed of the feeding device to obtain the correction result of the batching deviation. When the PVC plastic tile raw material feeding amount is excessive, the flow rate is reduced. When the PVC plastic tile raw material feeding amount is insufficient, the flow rate is increased. When the PVC plastic tile raw material feeding amount is insufficient, the flow rate is increased.
[0015] As a preferred scheme of the raw material automatic batching control system for PVC plastic tile production of the application, wherein: the product is processed by the machine vision device to identify potential quality defects, and the quality defect analysis result is obtained by the following steps, The machine vision device is used to collect the image of the surface of the PVC plastic tile product, the image processing algorithm is used to preliminarily screen out the potential defect area data, and the back propagation algorithm is used to train the convolutional neural network model; The potential defect area data is input into the trained convolutional neural network model, and the defect type and specific position of the PVC plastic tile product are labeled; The region growing method is used to process the defect type and specific position of the PVC plastic tile product, and the specific area and length of the PVC plastic tile defect are obtained; The specific area and length of the PVC plastic tile defect are evaluated by using the feedback evaluation method, and the quality defect analysis result of the PVC plastic tile product is obtained.
[0016] As a preferred scheme of the raw material automatic batching control system for PVC plastic tile production of the application, wherein: based on the quality defect analysis result, the PVC plastic tile batching proportion is optimized, and the accurate PVC plastic tile batching ratio scheme is obtained by the following steps, The Apriori algorithm is used to analyze the quality defect analysis result of the PVC plastic tile product, and the frequently occurring defect type of the PVC plastic tile product is obtained; The chi-square test method is used to analyze the defect type of the PVC plastic tile product, the reason of the defect type of the PVC plastic tile product is obtained, the genetic algorithm is used to optimize the reason of the defect type of the PVC plastic tile product, and the PVC plastic tile batching ratio scheme is obtained.
[0017] The application has the advantages that: the state data of the PVC plastic tile raw material is dynamically analyzed by the fuzzy logic control algorithm, and the accurate formula proportion is generated in real time, which improves the adaptability of the raw material fluctuation and the consistency of the product quality in the PVC plastic tile production process, the formula is optimized by machine vision detection and defect analysis feedback, the closed-loop regulation and control of the production process is realized, the product defect rate is effectively reduced, the production yield and the automation level are improved, the intelligent degree of the batching control is improved, the product quality control system is optimized, and the production efficiency and the finished product stability are significantly enhanced. BRIEF DESCRIPTION OF DRAWINGS
[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments will be briefly introduced as follows. Obviously, the drawings in the following description only constitute some embodiments of the present application, and other drawings can be obtained by those skilled in the art without any creative effort on the basis of these drawings.
[0019] Figure 1 The overall structural diagram of the raw material automatic batching control system for PVC plastic tile production.
[0020] Figure 2 The detailed flow chart of the middle formula analysis module.
[0021] Figure 3 The detailed flow chart of the middle monitoring module.
[0022] Figure 4 The detailed flow chart of the batching deviation. DETAILED DESCRIPTION
[0023] In order to make the above objectives, features and advantages of the present application more apparent and comprehensible, the specific embodiments of the present application will be described in detail below with reference to the accompanying drawings.
[0024] In the following description, many specific details are set forth in order to provide a thorough understanding of the present application. However, the present application can be practiced in other ways different from those described herein without departing from the scope of the present application, and those skilled in the art can make similar extensions without departing from the concept of the present application, so the present application is not limited to the specific embodiments disclosed below.
[0025] Secondly, the "one embodiment" or "embodiment" referred to herein means that the specific features, structures or characteristics can be included in at least one implementation of the present application. The "in one embodiment" appearing in different places in the specification does not mean the same embodiment, nor is it an independent or alternative embodiment that excludes other embodiments.
[0026] Reference Figures 1-4 For the first embodiment of the present application, the embodiment provides a raw material automatic batching control system for PVC plastic tile production, including the following steps: A data acquisition module acquires state data and characteristic data of the PVC plastic tile raw materials, and sets the PVC plastic tile formula proportion.
[0027] Based on the state data and characteristic data of the PVC plastic tile raw materials, a formula model is constructed by dynamically adjusting the raw material ratio using mathematical modeling and optimization algorithms; Further, the state data of the PVC plastic tile raw material includes temperature, humidity, viscosity and flow rate, and the characteristic data of the PVC plastic tile raw material includes the type of the PVC plastic tile, the particle size of the filler, and the weather resistance of the pigment. By using the collected state data and characteristic data of the PVC plastic tile raw material, a formula model is established by using mathematical modeling and optimization algorithm. When the state data of the PVC plastic tile raw material changes, the formula model can automatically update the formula adjustment ratio to adapt to the influence of the state data of the PVC plastic tile raw material on the performance of the raw material, effectively avoiding the quality fluctuations that may be caused by using a fixed proportioning method, and more intelligently coping with the formula requirements under different state data of the PVC plastic tile raw material.
[0028] The characteristic data of the PVC plastic tile raw material is input into the formula model to obtain the formula ratio of the PVC plastic tile, which is expressed as, ; Among them, is the formula ratio of the PVC plastic tile, is the parameter of the filler material, is the ratio of the PVC plastic tile, is the parameter of the PVC plastic tile, is the parameter of the reinforcing material, is the ratio of the reinforcing material, is the ratio of the filler material.
[0029] Further, in the production process of the PVC plastic tile, according to the actual production requirements, the formula model calculates the final formula ratio of the PVC plastic tile by inputting the characteristic data of the PVC plastic tile raw material (such as the ratio of the PVC plastic tile, the filler material and the reinforcing material). The ratio R of the PVC plastic tile is usually between 30% and 50%, the ratio F of the filler material may be between 10% and 30%, and the ratio C of the reinforcing material is usually set between 10% and 20%. The parameter of the PVC plastic tile is in the range of (0.4 to 0.6), because the PVC plastic tile plays a key role in the quality of the final product in the production process. The parameter of the filler material is in the range of (0.2 to 0.4), because the role of the filler material is more to reduce the cost and provide certain physical properties. The parameter of the reinforcing material is in the range of 0.2 to 0.3, which mainly functions to improve the strength and durability of the PVC plastic tile.
[0030] The formula analysis module analyzes the PVC plastic tile formula ratio required for producing the PVC plastic tile according to the fuzzy logic control algorithm based on the state data of the PVC plastic tile raw material.
[0031] The state data of the PVC plastic tile raw materials is modeled using a multiple regression analysis to obtain the formula data of the state data of the PVC plastic tile raw materials in the workshop.
[0032] Further, the state data of the PVC plastic tile raw materials is modeled using a multiple regression analysis method to obtain the formula data under different state data of the PVC plastic tile raw materials.
[0033] The state data of the PVC plastic tile raw materials is compared with the formula data collected, and a fuzzy logic control algorithm is used to calculate the formula proportion of the PVC plastic tile required for the production of the PVC plastic tile from the state data of the PVC plastic tile raw materials, and the expression is, wherein, is the formula proportion of the raw materials required for the production of the PVC plastic tile, is the temperature in the workshop, is the humidity in the workshop, is the air pressure in the workshop, is the sensitivity coefficient of the PVC plastic tile, is the sensitivity coefficient of the filler material, is the sensitivity coefficient of the reinforcing material, is the initial proportion.
[0034] Further, according to the type of the PVC plastic tile, the particle size of the filler, and the weather resistance of the pigment, the optimal formula proportion of the raw materials required for the PVC plastic tile under different state data of the PVC plastic tile raw materials can be accurately calculated, so that the formula can respond to the changes in the state data of the PVC plastic tile raw materials in real time, thereby ensuring the consistency and quality of the PVC plastic tile products.
[0035] The formula proportion of the PVC plastic tile is adjusted through an optimized dynamic algorithm.
[0036] The formula proportion of the PVC plastic tile is dynamically adjusted using a particle swarm optimization algorithm, and each particle represents a formula proportion.
[0037] Furthermore, the particle swarm optimization (PSO) algorithm is used to dynamically adjust the raw material ratio of PVC plastic tiles. In the particle swarm optimization algorithm, each particle represents a possible formula ratio, and the entire particle swarm represents multiple formula schemes. The fitness value of each particle reflects the pros and cons of the formula scheme. The fitness evaluation criteria include the quality of PVC plastic tiles, production efficiency, and adaptability factors. Through iterative optimization, the particle swarm continuously adjusts its position based on the current optimal solution and gradually converges to an ideal formula ratio. During the optimization process, the particle swarm can find the global optimal solution in the multi-dimensional formula space, effectively avoiding local optimal solutions and improving the stability of PVC plastic tile production and product quality.
[0038] The multi-element regression analysis method is used to analyze the formula ratio of PVC plastic tiles and the state data of PVC plastic tile raw materials, obtaining the quality score of PVC plastic tile products.
[0039] Furthermore, while optimizing the formula, the relationship between the ratio of PVC plastic tile raw materials and the state data of PVC plastic tile raw materials (such as temperature, humidity, and air pressure) is modeled using the multiple regression analysis method. Regression analysis can quantitatively describe the interaction between variables and predict the quality of PVC plastic tile products based on changes in the state data of PVC plastic tile raw materials. By inputting different raw material ratios and PVC plastic tile raw material state data into the regression model, the performance of PVC plastic tiles (such as strength, toughness, and appearance) can be predicted. The prediction results can be converted into a quality score of PVC plastic tile products, which can be used to evaluate the effectiveness of the current formula. The quality score serves as an important feedback indicator, helping to adjust production and ensuring that the produced PVC plastic tiles meet predetermined quality requirements.
[0040] Based on the quality score of PVC plastic tile products, the simulated annealing algorithm is used to optimize the raw material formula ratio.
[0041] Furthermore, based on the quality score of PVC plastic tile products, the simulated annealing (SA) algorithm is used to further optimize the raw material formula ratio. Simulated annealing is a random search-based optimization algorithm that simulates the physical annealing process to gradually reduce the temperature and find the global optimal solution from a random initial state. In the optimization process of PVC plastic tile formula, the algorithm first generates an initial formula scheme, then explores new formula combinations through the simulated annealing process, adjusts the formula ratio based on the feedback of the quality score, and controls the "temperature" to determine the probability of accepting new formulas. As the iteration process progresses, the temperature gradually decreases, and the algorithm tends to converge to an optimal solution, thereby obtaining the best raw material formula ratio and improving the quality of PVC plastic tile products.
[0042] The ratio of the PVC plastic tile, the filler material and the reinforcing material is adjusted by adjusting the flow controller of the automatic feeding device to obtain the adjusted raw material ratio of the PVC plastic tile.
[0043] Further, after the optimal raw material formula ratio is obtained, the flow controller of the automatic feeding device is adjusted based on the formula, and the flow of the feeding device is accurately controlled to ensure that the PVC plastic tile, the filler material and the reinforcing material are fed into the production line according to the optimized formula ratio. The flow controller monitors and adjusts the flow rate in real time to ensure that the feeding amount of each raw material matches the formula ratio completely, avoiding the problem of unstable product quality caused by excessive or insufficient feeding. The automatic and fine control is realized, the production process can be efficiently and stably carried out, and the optimized formula requirement is met. The ratio of the PVC plastic tile raw material is accurately controlled through adjustment, so that the quality of each batch of PVC plastic tile products reaches the best level.
[0044] The monitoring module monitors the PVC plastic tile raw material in real time.
[0045] The closed-loop control method is used to accurately match the feeding amount of the filler material, the reinforcing material and the PVC plastic tile raw material with the adjusted PVC plastic tile raw material ratio to obtain the target feeding flow of the PVC plastic tile raw material.
[0046] Further, the closed-loop control method is used to ensure that the feeding amount of the PVC plastic tile raw material matches the adjusted raw material ratio. The closed-loop control continuously monitors and adjusts the feeding amount of the raw material through a feedback mechanism to ensure that the actual feeding amount matches the target formula. When a deviation between the feeding amount and the target amount is detected, the control signal is immediately adjusted.
[0047] The mixer mixes the filler material, the reinforcing material and the PVC plastic tile raw material according to the adjusted PVC plastic tile raw material ratio.
[0048] Further, the mixer mixes the PVC plastic tile, the filler material and the reinforcing material according to the adjusted PVC plastic tile raw material ratio. The mixer accurately controls the feeding amount, stirring speed and time of the raw material to ensure that each raw material is uniformly mixed according to the specified ratio. Any uneven mixing will directly affect the quality of the PVC plastic tile. Efficient mixing equipment can ensure that each batch of produced PVC plastic tile has the same performance, avoiding the problem of inconsistent product performance caused by uneven distribution of raw materials.
[0049] The mass flow meter is used to monitor the target feeding flow and flow rate of the PVC plastic tile raw material in real time.
[0050] Further, the mass flow meter is used to monitor the feeding flow and flow rate of the PVC plastic tile raw materials in real time at this step, to ensure the accuracy of raw material feeding during production. The mass flow meter can measure the flow of substances through the pipeline and feed back the specific flow data in real time. The control can be compared with the target feeding flow, so as to make necessary adjustments. If the flow of the raw materials deviates from the target value, a warning will be given and automatic correction will be made to ensure that each batch of PVC plastic tile raw materials in the production process is within the accurate proportioning range.
[0051] The deviation analysis module compares the feeding amount and flow of the PVC plastic tile raw materials with the set PVC plastic tile ingredients, obtains the ingredient deviation, and analyzes and corrects the ingredient deviation by adjusting the feeding speed.
[0052] The volume flow meter is used to accurately measure the feeding rate and total feeding amount of the PVC plastic tile, filler material and reinforcing material, and obtain the actual feeding amount of the PVC plastic tile raw materials.
[0053] Further, the volume flow meter is used to measure the feeding rate and total feeding amount of the PVC plastic tile, filler material and reinforcing material in real time. Through the accurate measurement of the flow of each raw material by the accurate measurement sensor, it is ensured that the quantity requirement of each raw material feeding is met. The high accuracy of the volume flow meter can timely find the deviation of the feeding amount, so as to provide accurate basis for subsequent adjustment, reduce the raw material misfeeding or waste caused by human error or equipment failure, and ensure the efficient operation of the production line and the consistency of product quality.
[0054] The adjustment algorithm is used to analyze the PVC plastic tile, filler material and reinforcing material to obtain the target feeding amount.
[0055] Further, the adjustment algorithm calculates the target feeding amount of each raw material according to the data of the volume flow meter and the production target, and makes appropriate adjustments according to the properties of different raw materials and production needs (such as the viscosity of the PVC plastic tile and the particle size of the filler material), which improves the feeding accuracy in the production process. Moreover, the formula can be dynamically adjusted according to real-time data to ensure that any changes in the production process can be responded in time, avoid the deviation of the proportioning, and ensure the quality and production efficiency of the product.
[0056] The deviation analysis algorithm is used to compare the feeding amount of the PVC plastic tile raw materials with the set PVC plastic tile ingredients, calculate the feeding deviation of the PVC plastic tile raw materials, and the expression is, ; Among them, is the feeding deviation, the target feeding amount, the actual feeding amount.
[0057] Further, the possible errors in raw material feeding are accurately identified, thereby providing a basis for subsequent adjustment. By accurately calculating the feeding deviation, the batching process can be further optimized, and the quality fluctuations caused by the deviation can be reduced.
[0058] The feeding deviation is analyzed.
[0059] The feeding deviation is analyzed by setting a feeding deviation threshold value; Further, by analyzing the influence of different feeding deviations on the quality of PVC plastic tiles, a reasonable range that can ensure product quality and tolerate certain errors to reduce adjustment frequency is found. The value of the feeding deviation threshold is between ±1% and ±5%. The feeding deviation analysis is to determine whether the raw material feeding quantity meets the production standard. By setting a deviation threshold value, the degree of deviation can be determined to ensure that the raw material feeding is within the allowed error range. If the deviation exceeds the allowed range, an alarm will be issued and automatic adjustment will be performed, which helps to effectively prevent inaccurate raw material feeding during production and ensures the quality and production efficiency of PVC plastic tiles.
[0060] When the feeding deviation is less than the set deviation threshold value, the raw material feeding quantity is within the allowed error range, and the current production state is maintained.
[0061] Further, when the deviation is less than the preset threshold value, it indicates that the raw material feeding quantity meets the production requirements, and the actual raw material feeding quantity is not much different from the set target. No additional adjustment is made to avoid excessive intervention and maintain a stable feeding state during production, which can effectively improve production efficiency and reduce production interruptions caused by frequent adjustments.
[0062] When the feeding deviation is equal to the set deviation threshold value, the raw material feeding quantity is at the critical point of the error range, and an alarm is issued and processed.
[0063] Further, the feeding deviation is exactly equal to the set threshold value, indicating that the raw material feeding quantity is at the critical point of the error range, and an alarm is issued to remind the operator to pay attention. This means that the feeding quantity is close to the upper limit of the allowed error range, which may cause slight fluctuations in production quality. Although the current production state can continue, the triggering of the alarm prompts the operator to check and report for processing to ensure that larger deviations do not occur in the following production.
[0064] When the feeding deviation is greater than the set deviation threshold value, the raw material feeding quantity exceeds the error range, and the feeding quantity is adjusted.
[0065] Further, when the deviation is greater than the preset threshold, it means that the raw material is over-delivered, and measures will be taken to automatically adjust the delivery amount. The adjustment algorithm will be started immediately to reduce the deviation by correcting the delivery rate and flow parameters of the raw material, so as to ensure that the raw material ratio returns to the target range. This automatic adjustment mechanism can quickly respond to changes in deviation and avoid fluctuations in production quality and waste of raw materials.
[0066] The delivery speed is adjusted to correct the batching deviation.
[0067] The delivery speed is adjusted based on the adjusted delivery amount.
[0068] Further, the precise batching control by adjusting the delivery rate of the equipment is achieved by calculating the difference between the actual delivery amount and the target amount, dynamically adjusting the discharge speed of the equipment, so that the delivery amount returns to the expected range. Real-time monitoring and flexible adjustment of equipment parameters ensure that the raw material delivery process is highly accurate and ensures the consistency of product quality.
[0069] The discharge speed of the PVC plastic tile raw material is adjusted by adjusting the speed of the delivery equipment to obtain the correction result of the batching deviation, and the expression is ; Wherein, is the correction result of the batching deviation, is the total amount of the PVC plastic tile raw material, is the adjustment coefficient.
[0070] Further, when the deviation of the PVC plastic tile raw material is detected, adjusting the speed of the delivery equipment can directly affect the discharge speed, thereby correcting the formula deviation. According to the real-time data acquisition and deviation analysis result, the correction result of the batching deviation is calculated, and the correction result is used to indicate whether the raw material delivery amount needs to be adjusted.
[0071] When , the PVC plastic tile raw material is over-delivered, and the flow rate is reduced.
[0072] Further, when the correction result is positive, it means that the current delivery amount of the raw material exceeds the target set value, that is, the delivery amount is excessive, and the delivery rate of the raw material will be reduced to ensure that the raw material is no longer over-delivered, avoiding waste and quality fluctuations. By adjusting the speed of the delivery equipment to reduce the flow rate, the excessive delivery situation is reduced. Through accurate flow regulation.
[0073] When , the PVC plastic tile raw material is under-delivered, and the flow rate is increased.
[0074] Further, when the correction result is negative, it indicates that the current raw material feeding amount is insufficient and the target set formula proportion has not been reached. The feeding rate will be automatically increased to increase the feeding amount of the raw material to make up for the insufficient part. The adjusted feeding rate will cause more raw materials to enter the production line, ensuring that the final formula proportion meets the production requirements.
[0075] The quality detection module processes the product through machine vision equipment, identifies potential quality defects, and obtains quality defect analysis results.
[0076] The machine vision equipment captures images of the surface of the PVC plastic tile product, and uses image processing algorithms to preliminarily screen out potential defect area data.
[0077] Further, the machine vision equipment captures images of the surface of the PVC plastic tile through high-precision cameras, such as denoising and grayscale, to ensure the stability of image quality, and applies image processing algorithms (such as edge detection) for preliminary screening, thereby identifying potential defect areas in the image, which can quickly locate possible defect areas such as cracks, bubbles or uneven coating, providing basic data required for subsequent defect analysis. The image processing algorithm automatically screens according to the predetermined standards of the PVC plastic tile surface characteristics (such as color, brightness and texture), generating coordinate and size information of the potential defect area.
[0078] And use the back propagation algorithm to train the convolutional neural network model, output the potential defect area data to the trained convolutional neural network model, and label the defect type and specific location of the PVC plastic tile product.
[0079] Further, after preliminarily screening the potential defect area, it is input as a feature into the convolutional neural network (CNN) for deep learning training. Convolutional neural networks are good at image feature extraction, so they can automatically learn and identify various defect types on the surface of PVC plastic tiles, such as cracks, color differences and bubbles. Through the back propagation algorithm (Backpropagation), the CNN model is constantly optimized, gradually improving the accuracy of defect classification and positioning. After training, the CNN model can automatically identify the defect type and accurately mark the location and range of the defect on the surface of the PVC plastic tile, generating defect labeling data. The final output result will include the specific type of each defect (such as cracks and bubbles) and the specific location coordinates in the image.
[0080] The region growing method is used to process the defect type and specific location of the PVC plastic tile product, and the specific area and length of the PVC plastic tile defect are obtained.
[0081] Further, the region growing method is an image processing technique based on pixel similarity, which is used to further refine the defect area. It can start from the initial pixel point of the defect area and gradually expand to the adjacent pixel points until the pixel value difference in the region exceeds the preset threshold. The defect area can be accurately separated from the background to obtain the specific boundary and shape of the defect. For PVC plastic tile products, the region growing method can help extract the accurate area and length of each defect, and further quantify the severity of the defect.
[0082] The specific area and length of the PVC plastic tile defect are evaluated using the feedback evaluation method, and the quality defect analysis result of the PVC plastic tile product is obtained.
[0083] Further, after extracting the area and length of the PVC plastic tile defect, the defect is analyzed by the feedback evaluation method. The feedback evaluation method will evaluate the severity of each defect in combination with the quality standard of the PVC plastic tile product. The quality standard will involve the area ratio of the defect, the uniformity of the defect distribution, and the morphological factors of the defect. The evaluation algorithm will determine the impact on the overall product quality according to the area and length of the defect and the tolerance of the production process to the defect. When the defect area is greater than a certain predetermined threshold, it may indicate that the product is unqualified. In combination with the actual production demand, the quality score of the product is calculated, and the quality defect analysis result of the PVC plastic tile product is finally obtained.
[0084] The feedback optimization module optimizes the set PVC plastic tile ingredient ratio based on the quality defect analysis result to obtain an accurate PVC plastic tile ingredient ratio scheme.
[0085] The Apriori algorithm is used to analyze the quality defect analysis result of the PVC plastic tile product to obtain the frequently occurring defect types of the PVC plastic tile product.
[0086] Further, the Apriori algorithm is a classic association rule learning algorithm widely used to discover frequent itemsets and infer association rules. The Apriori algorithm will be applied to the quality defect analysis result of the PVC plastic tile product to mine the association patterns between different defect types. It will analyze the defect data of the PVC plastic tile and extract the feature information of each defect, such as defect type, area, and severity. Through the Apriori algorithm, it can identify the frequently occurring defect type combinations and find out which defects often occur together.
[0087] The chi-square test method is used to analyze the defect types of the PVC plastic tile product to obtain the causes of the defect types of the PVC plastic tile product.
[0088] Further, the Chi-squared Test is a statistical method used to test the independence between two or more categorical variables, and the Chi-squared Test will be used to analyze the association between the defect types of PVC plastic tile products and related factors (such as raw material ratio and production process). The data of defect types and various factors that may affect defects (such as temperature, humidity and raw material characteristics) will be collected, and the Chi-squared Test method will be used to determine whether there is a statistically significant association between the defect types.
[0089] The genetic algorithm is used to optimize the causes of defect types of PVC plastic tile products, and the PVC plastic tile batching ratio scheme is obtained, which is expressed as, ; Among them, is the PVC plastic tile batching ratio scheme, is the total number of defect types of PVC plastic tile products, is the defect area of the PVC plastic tile product of the th defect type, is the defect severity of the th defect type, is the index of the defect type.
[0090] Further, the genetic algorithm is an optimization algorithm that simulates the natural selection process and is suitable for solving complex optimization problems. The genetic algorithm will be used to optimize the raw material ratio of PVC plastic tile according to the causes of defects (such as batching ratio factors). The genetic algorithm searches for the optimal batching ratio by simulating the process of "natural selection" to reduce or eliminate the quality defects of PVC plastic tile; is the defect area of the PVC plastic tile product of the th defect type, usually in square centimeters (cm²), and the value range may vary from 0 to 1000 cm² depending on the specific production process, is the defect severity of the th defect type, and the defect severity is usually represented by a grade (e.g. 1-5 grade), with 1 representing a slight defect and 5 representing a severe defect.
[0091] In summary, the present application dynamically analyzes the state data of the raw materials of PVC plastic tile through the fuzzy logic control algorithm, and generates accurate formula proportions in real time, improving the adaptability to raw material fluctuations and the consistency of product quality in the production process of PVC plastic tile. The formula is optimized through machine vision detection and defect analysis feedback, realizing closed-loop regulation and control of the production process, effectively reducing the product defect rate, improving the production yield and automation level, and improving the intelligent degree of batching control, optimizing the product quality control system, and significantly enhancing the production efficiency and product stability.
[0092] It should be noted that the above examples are only used to illustrate the technical solutions of the present application but not to limit the present application. Although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or equivalently replaced without departing from the spirit and scope of the present application, and all these modifications and equivalents should be included in the scope of the claims of the present application.
Claims
1. An automatic batching control system for raw materials used in the production of PVC plastic tiles, characterized by: include, The data acquisition module collects the status data and characteristic data of the PVC plastic tile raw materials and sets the formula ratio of the PVC plastic tile; The formula analysis module analyzes the status data of PVC plastic tile raw materials based on the fuzzy logic control algorithm to determine the PVC plastic tile formula ratio required for producing PVC plastic tiles, and adjusts the PVC plastic tile formula ratio through a dynamic optimization algorithm; The monitoring module processes the PVC plastic tile raw materials and monitors the input amount and flow of the PVC plastic tile raw materials in real time; Deviation analysis module, by comparing the amount and flow of PVC plastic tile raw materials with the set PVC plastic tile ingredients, obtains the ingredient deviation, analyzes it, and corrects the ingredient deviation by adjusting the feeding speed; The quality inspection module processes products through machine vision equipment, identifies potential quality defects, and obtains quality defect analysis results; The feedback optimization module optimizes the set PVC plastic tile ingredient ratio based on the quality defect analysis results to obtain an accurate PVC plastic tile ingredient ratio plan.
2. The automatic batching control system for raw materials used in the production of PVC plastic tiles according to claim 1, characterized in that: Collecting the status data and characteristic data of PVC plastic tile raw materials and setting the formula ratio of PVC plastic tile includes the following steps: Based on the status data and characteristic data of PVC plastic tile raw materials, mathematical modeling and optimization algorithms are used to dynamically adjust the raw material ratio and build a formula model; The characteristic data of PVC plastic tile raw materials are input into the formula model to obtain the formula ratio of PVC plastic tiles.
3. The automatic batching control system for raw materials used in the production of PVC plastic tiles according to claim 2, characterized in that: According to the fuzzy logic control algorithm, the state data of the PVC plastic tile raw materials are analyzed and the PVC plastic tile formula ratio required for producing PVC plastic tiles includes the following steps: Use multiple regression analysis to model the state data of PVC plastic tile raw materials and obtain the formula data of the state data of PVC plastic tile raw materials; By comparing the collected status data of PVC plastic tile raw materials with the formula data of the status data of PVC plastic tile raw materials, the fuzzy logic control algorithm is used to calculate the PVC plastic tile formula ratio required for producing PVC plastic tiles based on the status data of PVC plastic tile raw materials.
4. The automatic batching control system for raw materials used in the production of PVC plastic tiles according to claim 3, characterized in that: The process of adjusting the proportion of PVC plastic tile formula by optimizing dynamic algorithm includes the following steps: The particle swarm optimization algorithm is used to dynamically adjust the formula ratio of PVC plastic tiles, and each particle represents a formula ratio; The multiple regression analysis method was used to analyze the data of PVC plastic tile formula ratio and PVC plastic tile raw material status to obtain the quality score of PVC plastic tile products. According to the quality score of PVC plastic tile products, the simulated annealing algorithm is used to optimize the raw material formula ratio; The proportion of PVC plastic tiles, filling materials and reinforcing materials is precisely adjusted by adjusting the flow controller of the automatic feeding equipment to obtain the adjusted proportion of PVC plastic tile raw materials.
5. The automatic batching control system for raw materials used in the production of PVC plastic tiles according to claim 4, characterized in that: Processing PVC plastic tile raw materials and real-time monitoring of the input amount and flow of PVC plastic tile raw materials include the following steps: A closed-loop control method is used to match the feeding amounts of the filling material, the reinforcing material and the PVC plastic tile raw material with the adjusted ratio of the PVC plastic tile raw material to obtain a target feeding flow rate of the PVC plastic tile raw material; Use a mixer to mix the filling material, the reinforcing material and the PVC plastic tile raw material according to the adjusted ratio of the PVC plastic tile raw material; A mass flow meter is used to monitor the target delivery flow and flow rate of PVC plastic tile raw materials in real time.
6. The automatic batching control system for raw materials used in the production of PVC plastic tiles according to claim 5, characterized in that: By comparing the amount of PVC plastic tile raw materials with the set PVC plastic tile ingredients, the ingredient deviation is obtained, including the following steps: Use a volume flow meter to accurately measure the feeding rate and total amount of PVC plastic tiles, filling materials and reinforcement materials to obtain the actual feeding amount of PVC plastic tile raw materials; Use adjustment algorithms to analyze PVC plastic tiles, filling materials, and reinforcement materials to obtain target delivery quantities; The deviation analysis algorithm is used to compare the amount of PVC plastic tile raw materials input with the set PVC plastic tile ingredients, and the input deviation of PVC plastic tile raw materials is calculated.
7. The automatic batching control system for raw materials used in the production of PVC plastic tiles according to claim 6, characterized in that: The analysis of delivery deviation includes the following steps: Set delivery deviation thresholds to analyze delivery deviations; When the delivery deviation is less than the set delivery deviation threshold, the raw material delivery amount is within the allowable error range and the current production status is maintained; When the delivery deviation is equal to the set deviation threshold, the raw material delivery amount is at the critical point of the error range, and an alarm is issued and processed. When the input deviation is greater than the set deviation threshold, the raw material input amount exceeds the error range and the input amount is adjusted.
8. The automatic batching control system for raw materials used in the production of PVC plastic tiles according to claim 7, characterized in that: The correction of the batching deviation by adjusting the feeding speed includes the following steps: Adjust the delivery speed based on the adjusted delivery amount; By adjusting the rate of the feeding equipment, the feeding speed of the PVC plastic tile raw materials is regulated to obtain the correction result of the material deviation; when When the PVC plastic tile raw materials are added in excess, the flow rate will be reduced; when When the PVC plastic tile raw material is insufficient, increase the flow rate.
9. The automatic batching control system for raw materials used in the production of PVC plastic tiles according to claim 8, characterized in that: Processing products through machine vision equipment to identify potential quality defects and obtaining quality defect analysis results includes the following steps: Use machine vision equipment to collect images of the surface of PVC plastic tile products, use image processing algorithms to preliminarily screen out data on potential defect areas, and use backpropagation algorithms to train convolutional neural network models; The potential defect area data is input into the trained convolutional neural network model to mark the defect type and specific location of the PVC plastic tile products; The defect type and specific location of PVC plastic tile products are processed using the region growing method to obtain the specific area and length of the PVC plastic tile defects; The feedback evaluation method is used to evaluate the specific area and length of PVC plastic tile defects, and the quality defect analysis results of PVC plastic tile products are obtained.
10. The automatic batching control system for raw materials used in the production of PVC plastic tiles according to claim 9, characterized in that: Based on the quality defect analysis results, the PVC plastic tile ingredient ratio is optimized to obtain an accurate PVC plastic tile ingredient ratio scheme, including the following steps: The Apriori algorithm is used to analyze the quality defect analysis results of PVC plastic tile products and the frequently occurring defect types of PVC plastic tile products are obtained; The chi-square test method is used to analyze the defect types of PVC plastic tile products, and the causes of the defect types of PVC plastic tile products are obtained. The genetic algorithm is used to optimize the causes of the defect types of PVC plastic tile products, and the PVC plastic tile ingredient ratio scheme is obtained.