Adaptive fuzzy control method and system for paper cup hemming forming quality optimization

Abstract

This invention relates to the field of industrial control technology, and discloses an adaptive fuzzy control method and system for optimizing the edge-rolling quality of paper cups. The method includes: Step 1: screening equipment parameters for the edge-rolling equipment; Step 2: extracting the edge-rolling quality characteristics of the paper cup to be tested and determining whether to perform optimization control operations; Step 3: formulating quality optimization instructions and determining the adjustment level; Step 4: determining the adjustment range of the edge-rolling component and performing adaptive fuzzy adjustment on the edge-rolling component. This invention, through the target period, can limit the sampling frequency and interval of the paper cups to be tested, avoiding the negative effects of chaotic sampling order and uncertain quantity. It can also perform dynamic and multi-dimensional evaluation of the edge-rolling quality of the paper cups to be tested, avoiding the situation of poor raw material quality and equipment wear and tear leading to low edge-rolling quality, and achieving accurate evaluation of the edge-rolling quality of paper cups.

Description

Technical Field

[0001] This invention relates to the field of industrial control technology, and more specifically, to an adaptive fuzzy control method and system for optimizing the edge-rolling quality of paper cups. Background Technology

[0002] In the automated production of paper cups, edge rolling is one of the key processes that determines the final quality of the product. Edge rolling involves multiple rounding and pressing operations on the edge of the paper cup rim to form a smooth and tight edge structure. In order to improve the forming quality of paper cup edge rolling, it is necessary to adaptively control the operating parameters of the edge rolling component in the edge rolling forming equipment.

[0003] Reference patent application CN120630707A discloses a data-driven adaptive optimization method and system for lens hardening processes, including real-time acquisition of multiple process parameters during the lens hardening process; invoking a hardening process prediction model to predict lens hardness based on multiple process parameters, comparing the predicted lens hardness parameters with predetermined hardness values ​​to generate a predicted hardness deviation; adaptively optimizing the multiple process parameters based on the predicted hardness deviation to generate optimized process parameters; and feeding the optimized process parameters back to the production control terminal of the lens hardening process to execute the adjustment of the lens hardening process parameters.

[0004] Existing quality optimization control methods typically employ traditional PID control or fixed-parameter logic control to manage relevant parameters during the paper cup edge-rolling process. However, this approach has significant limitations when dealing with dynamic changes in the actual paper cup edge-rolling process. When the material properties of the paper cup raw materials change, the edge-rolling mold of the edge-rolling equipment wears down, or the edge-rolling equipment operates under different conditions, uncontrollable dynamic drift can occur during the paper cup edge-rolling process. This can lead to abnormal phenomena such as dents and wrinkles in the paper cup edge-rolling structure, thus reducing the processing quality of the paper cup edge-rolling.

[0005] In view of this, the present invention proposes an adaptive fuzzy control method and system for optimizing the edge-rolling quality of paper cups to solve the above problems. Summary of the Invention

[0006] To overcome the aforementioned deficiencies of the prior art and to achieve the above objectives, the present invention provides the following technical solution: an adaptive fuzzy control method for optimizing the edge-rolling quality of paper cups, applied to an industrial control system, comprising:

[0007] Step 1: Based on the material parameters of the paper cup, select the equipment parameters that drive the edge-rolling component in the edge-rolling forming equipment from the process database;

[0008] The edge-rolling assembly consists of a lifting mechanism, an extrusion mechanism, and a heating mechanism;

[0009] Step 2: Construct the material-equipment-cycle sequence of the edge-curling forming equipment under different operating conditions, select the target cycle for collecting the paper cups to be tested from the material-equipment-cycle sequence, and extract the edge-curling quality characteristics of the paper cups to be tested in the target cycle. After analyzing and evaluating the edge-curling quality characteristics, determine whether to perform optimization control operations.

[0010] Operating conditions include low load, normal load and full load, and edge curling quality characteristics include aspect ratio, surface roundness and area wrinkling rate.

[0011] Step 3: Identify optimization parameters with potential for adjustment from the equipment parameters, formulate quality optimization instructions corresponding to the optimization parameters, and determine the adjustment level of the quality optimization instructions;

[0012] Step 4: Based on the quality optimization instructions and adjustment levels, determine the adjustment range of the edge curling component, and perform adaptive fuzzy adjustment on the edge curling component until optimization control operations are no longer performed.

[0013] Furthermore, the material parameters include the cup mouth diameter, cup wall pressure resistance, and paper cup thickness; the equipment parameters include the edge rolling displacement, softening temperature, and edge rolling speed.

[0014] Furthermore, the method for constructing the material-equipment-cycle sequence is as follows:

[0015] Import the material parameters and equipment parameters into the edge forming equipment, query the operating conditions of the edge forming equipment, and continuously collect A sample paper cups based on the standard cycle of the operating conditions, and query the forming quality of A sample paper cups respectively.

[0016] The sampled paper cups with low forming quality are recorded as abnormal paper cups, and the abnormal percentage of abnormal paper cups in the sampled paper cups is calculated.

[0017] When the abnormality rate is greater than or equal to 0.5%, the standard period is reduced by one-tenth of the standard period until the abnormality rate in the reduced standard period is less than 0.5%. The reduced standard period is then recorded as the detection period.

[0018] Material parameters, equipment parameters, and testing cycles are sequentially imported into the three sequence positions of the base sequence, and the operating conditions are noted on the base sequence to construct the material-equipment-cycle sequence.

[0019] Furthermore, the method for collecting the aspect ratio is as follows:

[0020] B images of the paper cups to be tested are captured one by one by an industrial camera from the frontal view angle to obtain B frontal view images. The curled edge part in the frontal view image is identified by computer vision technology. A closed boundary line is drawn along the outside of the curled edge part, and the area inside the boundary line is recorded as the curled edge area.

[0021] Measure the distance between the boundary lines in the rolled edge area along the horizontal and vertical directions respectively, and record them as the horizontal height and vertical height. Compare the maximum value of the horizontal height and the maximum value of the vertical height, and calculate the aspect ratio.

[0022] Furthermore, the method for collecting the smoothness of the curved surface is as follows:

[0023] Convert each of the B front view images into a grayscale image, and mark the pixels located within the curled edge area in the grayscale image one by one, denoted as the target pixel.

[0024] When the maximum horizontal height and the maximum vertical height of the curled edge area are equal, draw auxiliary lines containing the maximum horizontal height and the maximum vertical height in the curled edge area, and record the intersection of the two auxiliary lines as the center point.

[0025] Draw a curled circle with the center point as the center and half the maximum horizontal height as the radius. Count the number of all pixels and the target pixel within the curled circle. Compare the number of target pixels with the number of all pixels to calculate the smoothness of the curved surface.

[0026] When the maximum horizontal height and the maximum vertical height of the curled edge area are not equal, the larger of the two values ​​is recorded as the target value. The target line containing the target value is drawn in the curled edge area, and the midpoint of the target line is recorded as the target point.

[0027] Mark C boundary points at equal intervals along the boundary line of the curled edge area, and measure the distance from the target point to each of the C boundary points to obtain the distance between the C points.

[0028] After removing the maximum and minimum values ​​of the point spacing, the remaining C-2 point spacing values ​​are summed and averaged to obtain the average spacing value. The average spacing value is then compared with half of the target value to calculate the surface roundness.

[0029] Furthermore, the method for collecting regional wrinkle rate is as follows:

[0030] The pixels located on the boundary lines in the B rolled edge regions are recorded as sampling points. With the sampling points as the centers and the unit length as the radius, D sampling circles in external tangency relationship are drawn.

[0031] The number of sampling points located in the sampling circle is counted one by one to obtain D sampling values. The sampling circle with a sampling value greater than the upper limit value of the unit is recorded as a wrinkled circle.

[0032] The number of wrinkled circles was counted, and the number of wrinkled circles was compared with the number of sampled circles to calculate the wrinkling rate of the region.

[0033] Furthermore, the method for determining whether to perform optimization control operations is as follows:

[0034] When the aspect ratio is greater than the safe aspect ratio value, the aspect ratio is recorded as a poor feature; when the surface roundness is less than the safe surface value, the surface roundness is recorded as a poor feature; when the regional wrinkle rate is greater than the regional safe value, the regional wrinkle rate is recorded as a poor feature.

[0035] The paper cup with one defective feature is recorded as the observation paper cup, and the paper cup with two or three defective features is recorded as the substandard paper cup. The B paper cups are numbered in ascending order according to the sampling time. The serial number of the substandard paper cup is recorded as the substandard serial number, and three consecutive substandard serial numbers are recorded as the substandard unit.

[0036] The number of paper cups observed within the target period was counted, and the observation ratio was calculated by comparing the number of observed paper cups with the number of paper cups to be tested.

[0037] When the observed proportion is greater than the observed threshold, or when there are at least three substandard units, an optimization control operation is performed; otherwise, no optimization control operation is performed.

[0038] Furthermore, the quality optimization instructions include instructions to reduce the crimping displacement value, increase the softening temperature value, and reduce the crimping speed value; the adjustment levels include level one, level two, and level three.

[0039] The method for determining the adjustment level is as follows:

[0040] The number of aspect ratios, surface roundness, and regional wrinkle rates that are recorded as poor features within the target period are compared with the number of paper cups to be tested, and the first proportion value, the second proportion value, and the third proportion value are calculated.

[0041] When the first proportion, the second proportion, and the third proportion are at When the range is within a certain range, the adjustment level will be set to Level 1.

[0042] When the first proportion, the second proportion, and the third proportion are at When the range is within the specified range, the adjustment level will be determined as Level 2.

[0043] When the first proportion, the second proportion, and the third proportion are at When the range is within the specified range, the adjustment level will be set to level three.

[0044] Furthermore, the adaptive fuzzy adjustment control method is as follows:

[0045] When a command to reduce the hem displacement value is issued, 5% of the hem displacement value is recorded as an adjustment range, and the adjustment level of the command to reduce the hem displacement value is identified.

[0046] If the adjustment level is Level 1, Level 2, or Level 3, the industrial control system reduces the downward movement distance of the extrusion mechanism by one, two, or three adjustment increments, respectively.

[0047] When an instruction to increase the softening temperature value is given, 10% of the softening temperature value is recorded as an adjustment range, and the adjustment level of the instruction to increase the softening temperature value is identified.

[0048] If the adjustment level is Level 1, Level 2, or Level 3, the industrial control system will increase the heating temperature of the heating mechanism by one, two, or three adjustment increments, respectively.

[0049] When a command to reduce the crimping speed value is given, 8% of the crimping speed value is recorded as an adjustment range, and the adjustment level of the command to reduce the crimping speed value is identified.

[0050] If the adjustment level is Level 1, Level 2, or Level 3, the lifting speed of the lifting mechanism controlled by the industrial control system will be reduced by one, two, or three adjustment increments, respectively.

[0051] An adaptive fuzzy control system for optimizing the edge forming quality of paper cups is applied to industrial control systems. It is used to implement an adaptive fuzzy control method for optimizing the edge forming quality of paper cups. The system includes a parameter filtering module, a control decision module, an instruction determination module, and a fuzzy control module. The modules are connected to each other via wired or wireless networks.

[0052] The parameter filtering module is used to filter out the equipment parameters that drive the edge-rolling component in the edge-rolling forming equipment from the process database based on the material parameters of the paper cup.

[0053] The edge-rolling assembly consists of a lifting mechanism, an extrusion mechanism, and a heating mechanism;

[0054] The control and judgment module is used to construct the material-equipment-cycle sequence of the edge-forming equipment under different operating conditions, select the target cycle for collecting the paper cup to be tested from the material-equipment-cycle sequence, extract the edge-curling quality characteristics of the paper cup to be tested in the target cycle, and determine whether to execute the optimization control operation after analyzing and evaluating the edge-curling quality characteristics.

[0055] Operating conditions include low load, normal load and full load, and edge curling quality characteristics include aspect ratio, surface roundness and area wrinkling rate.

[0056] The instruction determination module is used to identify optimization parameters with potential for optimization from the equipment parameters, formulate quality optimization instructions corresponding to the optimization parameters, and determine the adjustment level of the quality optimization instructions;

[0057] The fuzzy control module is used to determine the adjustment range of the edge curling component based on the quality optimization instructions and adjustment levels, and to perform adaptive fuzzy adjustment on the edge curling component until the optimization control operation is no longer executed.

[0058] The technical effects of the adaptive fuzzy control method and system for optimizing the edge-rolling quality of paper cups in this invention are as follows:

[0059] (1): By constructing a material-equipment-cycle sequence, this invention can provide a dynamic and reasonable basis for the target cycle of evaluating the edge forming quality of paper cups. It can limit the sampling frequency and sampling interval of the paper cups to be tested, avoiding the negative situations of chaotic sampling order and uncertain quantity of the paper cups to be tested. At the same time, by analyzing the edge forming quality characteristics of the paper cups to be tested, dynamic and multi-dimensional evaluation operations can be performed on the edge forming quality of the paper cups to be tested in a specific time period. This avoids the limitations of the evaluation results of the single-dimensional evaluation method and realizes the dynamic and multi-dimensional accurate evaluation effect of the edge forming quality of paper cups.

[0060] (2): By determining the adjustment level of the quality optimization instruction and determining the adjustment range based on the adjustment level, the present invention can optimize and control the edge forming equipment with different adjustment ranges according to different instruction optimization instructions. This allows the equipment parameters of different edge forming components to perform adaptive fuzzy control operations under the limitation of the adjustment range, ensuring that the edge forming quality of the produced paper cups can be dynamically correlated with the paper cup raw materials, real-time operating conditions and edge forming component performance from multiple sources. This avoids the situation where the paper cup edge forming dynamic offset is caused by poor raw material quality and equipment wear and tear, resulting in low quality. This ensures the adaptive fuzzy control effect of the paper cup edge forming quality and effectively improves the forming quality of paper cup edge forming. Attached Figure Description

[0061] Figure 1 This is a flowchart illustrating the adaptive fuzzy control method for optimizing the edge-rolling quality of paper cups provided in Embodiment 1 of the present invention.

[0062] Figure 2 This is a schematic diagram of the architecture of an adaptive fuzzy control system for optimizing the edge-rolling quality of paper cups, provided in Embodiment 2 of the present invention. Detailed Implementation

[0063] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0064] Example 1: Please refer to Figure 1 As shown in this embodiment, the adaptive fuzzy control method for optimizing the edge-rolling quality of paper cups is applied to an industrial control system and includes:

[0065] Step 1: Based on the material parameters of paper cup edge rolling forming, select the equipment parameters of the edge rolling forming equipment from the process database;

[0066] When evaluating and controlling the quality of paper cup edge rolling, a comprehensive analysis from multiple dimensions is required. These dimensions include, but are not limited to, paper cup material, forming equipment, and process requirements, to ensure that the final paper cup edge rolling maintains a high quality.

[0067] Material parameters refer to the diverse parameters of the raw materials of paper cups used in the edge-rolling forming equipment, which can represent the material factors that affect the quality of the paper cup edge rolling.

[0068] In this embodiment, the material parameters include the cup opening diameter, the cup wall pressure resistance, and the paper cup thickness.

[0069] The cup rim diameter refers to the inner diameter of the cup rim before the paper cup undergoes the edge-rolling process; it can be used to represent the size of the cup rim diameter when the paper cup is involved in the edge-rolling process.

[0070] The compressive strength of a cup wall refers to the minimum pressure required for the cup wall to deform under pressure before the cup has undergone edge rolling. It can be used to express the compressive strength of the paper cup material itself.

[0071] The thickness value of a paper cup refers to the thickness of the cup wall itself before the edge-rolling process, which can be used to represent the supporting thickness of the paper cup material itself.

[0072] In this embodiment, the cup opening diameter, cup wall pressure resistance, and paper cup thickness are all inherent parameters of the paper cup itself, and these parameters are obtained by looking up the technical parameter table of the paper cup.

[0073] After obtaining the cup opening diameter, cup wall pressure resistance, and paper cup thickness, it is necessary to use these values ​​as a basis to filter and match the corresponding equipment parameters from the process database. This ensures that the equipment parameters can serve as the basis for the edge-rolling forming equipment to perform paper cup edge-rolling forming processing.

[0074] In this embodiment, the edge-rolling forming equipment is used to perform positioning, lifting, heating, softening, and pressing edge-rolling operations on the mouth of a paper cup. In this edge-rolling forming equipment, positioning and lifting are achieved by a lifting mechanism that can be raised and lowered, pressing edge-rolling is achieved by a pressing mechanism that can be embedded in the inner cavity of the paper cup, and heating and softening are achieved by a heating mechanism embedded in the pressing mechanism. This drives the edge-rolling forming equipment to perform a complete set of forming operations on the mouth of the paper cup, including lifting, heating, and pressing edge-rolling.

[0075] Equipment parameters are the operating data required by the edge-rolling forming equipment when it performs edge-rolling forming on the rim of paper cups. They serve as the initial benchmark for achieving edge-rolling operations on paper cups and as the direct object for adaptive fuzzy control when the edge-rolling quality of paper cups is poor.

[0076] Specifically, the equipment parameters include the edge-rolling displacement value, softening temperature value, and edge-rolling speed value;

[0077] The edge-rolling displacement value refers to the downward movement of the extrusion mechanism of the edge-rolling forming equipment during the paper cup edge-rolling forming process. It can be used to represent the amount of material used to soften and roll up the cup rim during the paper cup edge-rolling forming process.

[0078] The softening temperature value refers to the softening temperature of the electric heating mechanism during the paper cup edge forming process by the lifting mechanism of the edge forming equipment. It can be used to represent the heating temperature at which the cup rim material softens during the paper cup edge forming process.

[0079] The edge-rolling speed value refers to the speed at which the lifting mechanism of the edge-rolling forming equipment drives the paper cup upward during the edge-rolling forming process. It can quickly represent the speed at which the cup rim material is rolled during the edge-rolling forming process.

[0080] When selecting equipment parameters, it is necessary to use the material parameters queried in real time as a basis to select the corresponding equipment parameters from the process database, so that the equipment parameters can serve as the basic data for the edge forming equipment to process paper cups.

[0081] In this embodiment, the process database is based on a large number of historical material parameters of different types and corresponding equipment parameters. After combining a set of material parameters with a corresponding set of equipment parameters, a process database with one-to-one correspondence between material parameters and equipment parameters is generated.

[0082] Step 2: Construct a material-equipment-cycle sequence, select the target cycle from the material-equipment-cycle sequence, and collect the edge curling quality characteristics of the paper cup to be tested in the target cycle. After analyzing and evaluating the edge curling quality characteristics, determine whether to perform optimization control operations.

[0083] Ideally, the equipment parameters would perfectly match the material parameters of the paper cup itself. However, in actual paper cup edge rolling processing, due to the interference of negative factors such as changes in the paper cup material itself, fluctuations in the external environment, and wear and tear on the edge rolling forming equipment, the equipment parameters cannot perfectly match the material parameters, resulting in low quality of paper cup edge rolling produced by the edge rolling forming equipment based on the equipment parameters.

[0084] In order to analyze and evaluate the edge-rolling quality of paper cups produced by the edge-rolling forming equipment, it is necessary to conduct regular sampling inspections of the edge-rolling quality of paper cups. Therefore, it is necessary to set the duration of the paper cup sampling inspection, i.e., the target cycle; so that the target cycle can serve as the duration span between two adjacent paper cup edge-rolling forming quality inspections.

[0085] When obtaining the target cycle, the target cycle is not set randomly, but must be adapted to the material parameters and equipment parameters. Therefore, it is necessary to construct a material-equipment-cycle sequence to determine the target cycle based on the detection cycles corresponding to different material parameters and equipment parameters in historical cases.

[0086] The material-equipment-cycle sequence refers to the combination of material parameters, equipment parameters, and inspection cycles of the edge-rolling forming equipment under different operating conditions, thereby achieving a three-in-one effect of material parameters, equipment parameters, and inspection cycles.

[0087] In this embodiment, the operating condition is used to represent the efficiency of the current working state of the edge-forming equipment. Specifically, the operating conditions include low load condition, normal load condition, and full load condition; the unit output of the edge-forming equipment for processing paper cups corresponding to the low load condition, normal load condition, and full load condition is from low to high.

[0088] The method for constructing the material-equipment-cycle sequence is as follows:

[0089] Import the material and equipment parameters into the edge-rolling forming equipment, query the operating conditions of the edge-rolling forming equipment, and continuously collect A sample paper cups based on the standard cycle of the operating conditions, and query the forming quality of each A sample paper cup; the standard cycle refers to the time interval between two adjacent sampling paper cups set under different operating conditions. The duration of the standard cycle corresponding to low load, normal load and full load conditions are different; for example, the standard cycle for low load is 300s, the standard cycle for normal load is 150s, and the standard cycle for full load is 60s; the forming quality is used to represent the specific result of the edge-rolling forming quality of the sample paper cups, and the forming quality includes high quality and low quality.

[0090] The sampled paper cups with low forming quality are recorded as abnormal paper cups, and the abnormal percentage of abnormal paper cups in the sampled paper cups is calculated.

[0091] When the abnormal percentage is greater than or equal to 0.5%, it means that there are a lot of abnormal paper cups. The standard cycle needs to be shortened. The standard cycle is reduced by one-tenth of the standard cycle. The standard cycle is continuously reduced until the abnormal percentage in the reduced standard cycle is less than 0.5%. The reduced standard cycle is then recorded as the detection cycle.

[0092] Material parameters, equipment parameters, and testing cycles are sequentially imported into the three sequence positions of the basic sequence, and the operating conditions are noted on the basic sequence, thus converting the basic sequence into a material-equipment-cycle sequence. The basic sequence is a sequence without any substantial content; the sequence positions are the smallest units that make up the basic sequence and provide positional constraints for importing material parameters, equipment parameters, and testing cycles.

[0093] The target cycle refers to the detection cycle corresponding to the material parameters and equipment parameters of the edge forming equipment under the current operating conditions. It can be used as the interval between two consecutive paper cup quality sampling inspections by the edge forming equipment.

[0094] Specifically, when selecting a target cycle, after querying the operating conditions, material parameters, and equipment parameters of the edge-rolling forming equipment in real time, the corresponding testing cycle can be selected from the material-equipment-cycle sequence, and this testing cycle can be recorded as the target cycle.

[0095] Edge curling quality features are used to represent the structure and shape of paper cup edge curling in multiple dimensions, and serve as the basis for judging the overall quality of paper cup edge curling. When collecting edge curling quality features, it is necessary to continuously collect B paper cups within the target cycle of the edge curling forming equipment, and record these B paper cups as the paper cups to be tested.

[0096] Specifically, the characteristics of rolled edges include aspect ratio, surface roundness, and regional wrinkle rate.

[0097] The aspect ratio refers to the ratio between the horizontal length and the vertical length of the rolled edge of the paper cup being tested. The larger the aspect ratio, the greater the difference between the horizontal and vertical rolled edges of the paper cup being tested, and the lower the quality of the paper cup being tested.

[0098] The method for collecting the aspect ratio is as follows:

[0099] B front view images are obtained by capturing images of B paper cups to be tested from the frontal angle using an industrial camera;

[0100] The curled edges in the front view image are identified using computer vision technology. A closed boundary line is drawn along the outside of the curled edges, and the area inside the boundary line is recorded as the curled edge area.

[0101] Measure the distance between the boundary lines in the rolled edge area along the horizontal and vertical directions respectively, and record them as horizontal height and vertical height. Compare the maximum value of the horizontal height and the maximum value of the vertical height, and calculate the aspect ratio.

[0102] The formula for calculating the aspect ratio is:

[0103] ;

[0104] In the formula, The aspect ratio is . This is the maximum horizontal height. This represents the maximum vertical height.

[0105] Surface roundness refers to the extent to which the rolled edge of the paper cup being tested maintains the same consistency with the circular structure. It can be used to represent the roundness of the rolled edge. The greater the surface roundness, the closer the overall structure of the paper cup being tested is to a circle, and the higher the quality of the paper cup being tested.

[0106] The method for collecting the smoothness of curved surfaces is as follows:

[0107] Convert each of the B front view images into a grayscale image, and mark the pixels located within the curled edge area in the grayscale image one by one, denoted as the target pixel.

[0108] When the maximum horizontal height and the maximum vertical height of the curled edge area are equal, draw auxiliary lines containing the maximum horizontal height and the maximum vertical height in the curled edge area, and record the intersection of the two auxiliary lines as the center point.

[0109] Draw a curled circle with the center point as the center and half the maximum horizontal height as the radius. Count the number of all pixels and the target pixel within the curled circle. Compare the number of target pixels with the number of all pixels to calculate the smoothness of the curved surface.

[0110] When the maximum horizontal height and the maximum vertical height of the curled edge area are not equal, the larger of the two values ​​is recorded as the target value. The target line containing the target value is drawn in the curled edge area, and the midpoint of the target line is recorded as the target point.

[0111] Mark C boundary points at equal intervals along the boundary line of the curled edge area, and measure the distance from the target point to each of the C boundary points to obtain the distance between the C points.

[0112] After removing the maximum and minimum values ​​of the point spacing, the remaining C-2 point spacing values ​​are summed and averaged to obtain the average spacing value. The average spacing value is then compared with half of the target value to calculate the surface roundness.

[0113] The formula for calculating the roundness of a curved surface is:

[0114] ;

[0115] In the formula, For the smoothness of the curved surface, For the first The distance between points, This is the target value.

[0116] It should be noted that by distinguishing the relationship between the maximum value of the horizontal height and the maximum value of the vertical height, two parallel methods can be provided for the acquisition and calculation of surface roundness, so as to meet the acquisition needs of surface roundness under different conditions and shapes, and improve the applicability and accuracy of surface roundness.

[0117] The area wrinkle rate refers to the proportion of wrinkled and raised structures on the arc-shaped outer surface of the paper cup being tested. It can be used to represent the smoothness of the rolled edge of the paper cup being tested. The larger the area wrinkle rate, the worse the smoothness of the rolled edge of the paper cup being tested, and the lower the quality of the paper cup being tested.

[0118] The method for collecting regional wrinkle rate data is as follows:

[0119] Let the pixels located on the boundary line in the B curled regions be the sampling points. With the sampling points as the centers and the unit length as the radius, draw D sampling circles on the boundary line that are in an external tangent relationship. The unit length is used to divide the boundary line of the curled region into equal parts and is used as the radius for drawing the sampling circles.

[0120] The number of sampling points located in the sampling circle is counted one by one to obtain D sample values, and the D sample values ​​are compared with the unit upper limit value respectively.

[0121] Sampling circles with sampled values ​​greater than the unit upper limit are designated as wrinkled circles. The number of wrinkled circles is counted, and the region wrinkling rate is calculated by comparing the number of wrinkled circles with the number of sampled circles. The unit upper limit is directly proportional to the unit length; the larger the unit length, the larger the unit upper limit. For example, when the unit length is the distance between three adjacent pixels, the unit upper limit is 6.

[0122] It should be noted that each set of aspect ratio, surface roundness, and area wrinkle rate collected can be used as a basis for judging the quality of the edge rolling of the same paper cup under test. Furthermore, by analyzing the three dimensions of aspect ratio, surface roundness, and area wrinkle rate, a comprehensive analysis and control effect on the edge rolling quality of B paper cups under test can be achieved.

[0123] After collecting the aspect ratio, surface roundness, and regional wrinkle rate of B paper cups to be tested, it is necessary to analyze and evaluate them one by one to determine the quality of the edge forming of the paper cups to be tested, and use this as the basis for determining whether to perform optimization control operations.

[0124] Specifically, the method for determining whether to perform optimization control operations is as follows:

[0125] The aspect ratio, surface roundness, and regional wrinkle rate of each of the B paper cups to be tested are compared with the safety values ​​for aspect ratio, surface roundness, and regional wrinkle rate, respectively. The safety values ​​for aspect ratio, surface roundness, and regional wrinkle rate refer to the minimum, maximum, and minimum values ​​for aspect ratio, surface roundness, and regional wrinkle rate, respectively, when the characteristics are considered poor. The specific values ​​for aspect ratio, surface roundness, and regional wrinkle rate are calculated and set based on a large number of historical aspect ratio, surface roundness, and regional wrinkle rate values.

[0126] When the ratio of the horizontal to the vertical axis is greater than the safe value, it indicates that the difference between the horizontal length and the vertical length of the paper cup under test is too large. At this time, the edge curling quality of the paper cup under test is low, and the ratio of the horizontal to the vertical axis is recorded as a poor feature.

[0127] When the roundness of the curved surface is less than the safety value of the curved surface, it means that the overall structure of the paper cup being tested is not as close to a circle as possible. At this time, the edge curling quality of the paper cup being tested is low, and the roundness of the curved surface is recorded as an inferior feature.

[0128] When the area wrinkle rate is greater than the area safety value, it indicates that the proportion of wrinkles and protrusions on the outer surface of the paper cup being tested is relatively high. At this time, the edge curling quality of the paper cup being tested is low, and the area wrinkle rate is recorded as a poor feature.

[0129] The paper cups to be tested with one defective feature are recorded as observation paper cups, and the paper cups to be tested with two or three defective features are recorded as substandard paper cups. The B paper cups to be tested are numbered in ascending order according to the sampling time.

[0130] The serial number of the substandard paper cup is recorded as the substandard serial number, and three consecutive substandard serial numbers are recorded as a substandard unit.

[0131] The number of paper cups observed within the target period was counted, and the observation ratio was calculated by comparing the number of observed paper cups with the number of paper cups to be tested.

[0132] When the observed proportion exceeds the observation threshold, or when there are at least three substandard units, the overall quality of the paper cups produced by the edge-rolling forming equipment within a target cycle is poor, and an optimization control operation is executed; otherwise, the optimization control operation is not executed.

[0133] It should be noted that the prerequisite for determining to perform optimization control operations is that the observed proportion is greater than the observed threshold or there is one of the three inferior units. In this case, it is necessary to optimize the paper cup edge forming quality of the edge forming equipment.

[0134] Step 3: When performing optimization control operations, identify optimization parameters with optimization adjustment potential from the equipment parameters, formulate quality optimization instructions, and determine the adjustment level of the quality optimization instructions;

[0135] When the optimization control operation is executed, the equipment parameters of the edge-rolling forming equipment can be adjusted to optimize the edge-rolling quality of paper cups, thereby improving the quality of paper cup edge-rolling.

[0136] In this embodiment, the optimized parameter refers to the parameter object among the equipment parameters that has the potential for optimization and adjustment and can be used to improve the paper cup edge rolling forming quality of the edge rolling forming equipment.

[0137] Specifically, when identifying optimization parameters, the specific type of the curling quality feature marked as a poor feature is first identified. When the aspect ratio is marked as a poor feature, the downward movement of the extrusion mechanism of the curling forming equipment is relatively large, so the curling displacement value is recorded as an optimization parameter. When the roundness of the curved surface is marked as a poor feature, the heating temperature of the heating mechanism of the curling forming equipment is relatively low, so the softening temperature value is recorded as an optimization parameter. When the area wrinkle rate is marked as a poor feature, the upward movement of the paper cup driven by the lifting mechanism of the curling forming equipment is relatively large, so the curling speed value is recorded as an optimization parameter.

[0138] After obtaining the optimized parameters, the optimized parameters can be analyzed, and based on the analysis results, quality optimization instructions for controlling the edge-rolling forming equipment can be formulated, so that the quality optimization instructions can serve as a guide for improving the edge-rolling forming quality of paper cups.

[0139] Specifically, the quality optimization instructions include instructions to reduce the edge displacement value, increase the softening temperature value, and reduce the edge speed value.

[0140] When formulating quality optimization instructions, they should be based on the optimization parameters. Specifically, when the optimization parameter is the edge curling displacement value, an instruction to decrease the edge curling displacement value should be formulated; when the optimization parameter is the softening temperature value, an instruction to increase the softening temperature value should be formulated; and when the optimization parameter is the edge curling speed value, an instruction to decrease the edge curling speed value should be formulated.

[0141] When formulating quality optimization instructions, it is also necessary to determine the adjustment level corresponding to the formulated instruction optimization instructions so that each instruction optimization instruction can have an accurate and reasonable adjustment control range in subsequent adaptive fuzzy control.

[0142] Specifically, the adjustment levels include Level 1, Level 2, and Level 3; and the adjustment range of the optimization parameters corresponding to Level 1, Level 2, and Level 3 is from low to high.

[0143] The method for determining the adjustment level is as follows:

[0144] The number of aspect ratios, surface roundness, and regional wrinkle rates that are considered inferior features within the target period are counted one by one and recorded as the first reference value, the second reference value, and the third reference value, respectively.

[0145] The first reference value, the second reference value, and the third reference value are compared with the number of paper cups to be tested one by one, and the first proportion value, the second proportion value, and the third proportion value are calculated.

[0146] When the first proportion, the second proportion, and the third proportion are at When the range is within a certain range, the adjustment of the optimization parameters does not need to be significant, so the adjustment level is set to level one.

[0147] When the first proportion, the second proportion, and the third proportion are at When the range is within a certain range, if the adjustment of the optimization parameters is moderate, then the adjustment level is determined to be level two.

[0148] When the first proportion, the second proportion, and the third proportion are at When the range is within a certain range, a larger adjustment to the optimization parameters is required, so the adjustment level is set to level three.

[0149] It should be noted that the specific values ​​of the first, second, and third percentage values ​​are all greater than 0 and less than or equal to 1, and are set in one-third increments. At the same time, the sum of the first, second, and third percentage values ​​is 1.

[0150] Step 4: Based on the quality optimization instructions and adjustment levels, control the edge forming equipment to adaptively adjust the optimization parameters using fuzzy logic, and analyze the adjusted edge forming quality characteristics until the edge forming equipment no longer performs optimization control operations.

[0151] After determining the quality optimization instructions and adjustment levels, adaptive fuzzy control processing can be performed on the edge-rolling forming equipment to ensure that the edge-rolling forming equipment can adjust its parameters based on the optimization instructions and adjustment levels, thereby improving the quality of paper cup edge-rolling.

[0152] In this embodiment, adaptive fuzzy adjustment is used to make slight adjustments to the relevant parameters of the edge forming equipment within a non-fixed range, so that the lifting mechanism, heating mechanism and extrusion mechanism of the edge forming equipment can be increased or decreased slightly.

[0153] Specifically, the adaptive fuzzy adjustment control method is as follows:

[0154] When the quality optimization instruction is to reduce the curling displacement value, 5% of the current curling displacement value is recorded as an adjustment range, and the adjustment level of the instruction to reduce the curling displacement value is identified.

[0155] If the adjustment level is Level 1, Level 2 or Level 3, the industrial control system sends a command to the edge forming equipment to reduce the edge displacement value, thereby controlling the extrusion mechanism to reduce the downward movement distance by one, two or three adjustment increments respectively.

[0156] When the quality optimization command is to increase the softening temperature value, 10% of the current softening temperature value is recorded as an adjustment range, and the adjustment level of the command to increase the softening temperature value is identified.

[0157] If the adjustment level is Level 1, Level 2, or Level 3, the industrial control system sends a command to the edge forming equipment to increase the softening temperature value, thereby controlling the heating mechanism to increase the heating temperature by one, two, or three adjustment increments, respectively.

[0158] When the quality optimization instruction is to reduce the edge curling speed value, 8% of the current edge curling speed value is recorded as an adjustment range, and the adjustment level of the instruction to reduce the edge curling speed value is identified.

[0159] If the adjustment level is Level 1, Level 2, or Level 3, the industrial control system sends a command to the edge forming equipment to reduce the edge forming speed, thereby controlling the lifting mechanism to reduce the lifting speed by one, two, or three adjustment increments, respectively.

[0160] After adaptively adjusting the edge-forming equipment, it is necessary to sample the paper cups produced by the adjusted edge-forming equipment to obtain test paper cups for further analysis and evaluation. Steps two, three, and four are repeated on the sampled test paper cups until the adaptive fuzzy control stops when no further optimization control operations are performed. Ultimately, the optimized control effect of edge-forming quality of paper cups produced by the edge-forming equipment is achieved.

[0161] Example 2: Please refer to Figure 2 As shown, the parts not described in detail in this embodiment are described in Embodiment 1. An adaptive fuzzy control system for optimizing the edge forming quality of paper cups is provided and applied to an industrial control system. It is used to implement an adaptive fuzzy control method for optimizing the edge forming quality of paper cups, including a parameter filtering module, a control determination module, an instruction determination module, and a fuzzy control module. The modules are connected to each other via wired or wireless networks.

[0162] The parameter filtering module is used to filter out the equipment parameters that drive the edge-rolling component in the edge-rolling forming equipment from the process database based on the material parameters of the paper cup.

[0163] The edge-rolling assembly consists of a lifting mechanism, an extrusion mechanism, and a heating mechanism;

[0164] The control and judgment module is used to construct the material-equipment-cycle sequence of the edge-forming equipment under different operating conditions, select the target cycle for collecting the paper cup to be tested from the material-equipment-cycle sequence, extract the edge-curling quality characteristics of the paper cup to be tested in the target cycle, and determine whether to execute the optimization control operation after analyzing and evaluating the edge-curling quality characteristics.

[0165] Operating conditions include low load, normal load and full load, and edge curling quality characteristics include aspect ratio, surface roundness and area wrinkling rate.

[0166] The instruction determination module is used to identify optimization parameters with potential for optimization from the equipment parameters, formulate quality optimization instructions corresponding to the optimization parameters, and determine the adjustment level of the quality optimization instructions;

[0167] The fuzzy control module is used to determine the adjustment range of the edge curling component based on the quality optimization instructions and adjustment levels, and to perform adaptive fuzzy adjustment on the edge curling component until the optimization control operation is no longer executed.

[0168] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention.

Claims

1. An adaptive fuzzy control method for optimizing the edge-rolling quality of paper cups, applied to industrial control systems, characterized in that: include: Step 1: Based on the material parameters of the paper cup, select the equipment parameters that drive the edge-rolling component in the edge-rolling forming equipment from the process database; The edge-rolling assembly consists of a lifting mechanism, an extrusion mechanism, and a heating mechanism; Step 2: Construct the material-equipment-cycle sequence of the edge-curling forming equipment under different operating conditions, select the target cycle for collecting the paper cups to be tested from the material-equipment-cycle sequence, and extract the edge-curling quality characteristics of the paper cups to be tested in the target cycle. After analyzing and evaluating the edge-curling quality characteristics, determine whether to perform optimization control operations. Operating conditions include low load, normal load and full load, and edge curling quality characteristics include aspect ratio, surface roundness and area wrinkling rate. The method for collecting the aspect ratio is as follows: B images of the paper cups to be tested are captured one by one by an industrial camera from the frontal view angle to obtain B frontal view images. The curled edge part in the frontal view image is identified by computer vision technology. A closed boundary line is drawn along the outside of the curled edge part, and the area inside the boundary line is recorded as the curled edge area. Measure the distance between the boundary lines in the rolled edge area along the horizontal and vertical directions respectively, and record them as the horizontal height and vertical height. Compare the maximum value of the horizontal height and the maximum value of the vertical height, and calculate the aspect ratio. The method for collecting the smoothness of curved surfaces is as follows: Convert each of the B front view images into a grayscale image, and mark the pixels located within the curled edge area in the grayscale image one by one, denoted as the target pixel. When the maximum horizontal height and the maximum vertical height of the curled edge area are equal, draw auxiliary lines containing the maximum horizontal height and the maximum vertical height in the curled edge area, and record the intersection of the two auxiliary lines as the center point. Draw a curled circle with the center point as the center and half the maximum horizontal height as the radius. Count the number of all pixels and the target pixel within the curled circle. Compare the number of target pixels with the number of all pixels to calculate the smoothness of the curved surface. When the maximum horizontal height and the maximum vertical height of the curled edge area are not equal, the larger of the two values ​​is recorded as the target value. The target line containing the target value is drawn in the curled edge area, and the midpoint of the target line is recorded as the target point. Mark C boundary points at equal intervals along the boundary line of the curled edge area, and measure the distance from the target point to each of the C boundary points to obtain the distance between the C points. After removing the maximum and minimum values ​​of the point spacing, the remaining C-2 point spacing values ​​are summed and averaged to obtain the average spacing value. The average spacing value is then compared with half of the target value to calculate the surface roundness. The method for collecting regional wrinkle rate data is as follows: The pixels located on the boundary lines in the B rolled edge regions are recorded as sampling points. With the sampling points as the centers and the unit length as the radius, D sampling circles in external tangency relationship are drawn. The number of sampling points located in the sampling circle is counted one by one to obtain D sampling values. The sampling circle with a sampling value greater than the upper limit value of the unit is recorded as a wrinkled circle. The number of wrinkled circles was counted, and the number of wrinkled circles was compared with the number of sampling circles to calculate the wrinkling rate of the region. Step 3: Identify optimization parameters with potential for adjustment from the equipment parameters, formulate quality optimization instructions corresponding to the optimization parameters, and determine the adjustment level of the quality optimization instructions; Step 4: Based on the quality optimization instructions and adjustment levels, determine the adjustment range of the edge curling component, and perform adaptive fuzzy adjustment on the edge curling component until optimization control operations are no longer performed.

2. The self-adaptive fuzzy control method for paper cup hemming forming quality optimization as claimed in claim 1 wherein, Material parameters include cup mouth diameter, cup wall pressure resistance, and paper cup thickness; equipment parameters include edge rolling displacement, softening temperature, and edge rolling speed.

3. The self-adaptive fuzzy control method for paper cup hemming forming quality optimization as claimed in claim 2, wherein, The method for constructing the material-equipment-cycle sequence is as follows: Import the material parameters and equipment parameters into the edge forming equipment, query the operating conditions of the edge forming equipment, and continuously collect A sample paper cups based on the standard cycle of the operating conditions, and query the forming quality of A sample paper cups respectively. The sampled paper cups with low forming quality are recorded as abnormal paper cups, and the abnormal percentage of abnormal paper cups in the sampled paper cups is calculated. When the abnormality rate is greater than or equal to 0.5%, the standard period is reduced by one-tenth of the standard period until the abnormality rate in the reduced standard period is less than 0.5%. The reduced standard period is then recorded as the detection period. Material parameters, equipment parameters, and testing cycles are sequentially imported into the three sequence positions of the base sequence, and the operating conditions are noted on the base sequence to construct the material-equipment-cycle sequence.

4. The self-adaptive fuzzy control method for paper cup hemming forming quality optimization as claimed in claim 3, wherein, The method for determining whether to perform optimization control operations is as follows: When the aspect ratio is greater than the safety value, the aspect ratio is recorded as a poor feature; when the surface roundness is less than the safety value, the surface roundness is recorded as a poor feature. When the regional wrinkle rate is greater than the regional safety value, the regional wrinkle rate is recorded as a poor feature; The paper cup with one defective feature is recorded as the observation paper cup, and the paper cup with two or three defective features is recorded as the substandard paper cup. The B paper cups are numbered in ascending order according to the sampling time. The serial number of the substandard paper cup is recorded as the substandard serial number, and three consecutive substandard serial numbers are recorded as the substandard unit. The number of paper cups observed within the target period was counted, and the observation ratio was calculated by comparing the number of observed paper cups with the number of paper cups to be tested. When the observed proportion is greater than the observed threshold, or when there are at least three substandard units, it is determined to perform an optimization control operation. Conversely, optimization control operations are not performed.

5. The adaptive fuzzy control method for optimizing the edge-rolling quality of paper cups according to claim 4, characterized in that, Quality optimization commands include commands to reduce edge displacement, increase softening temperature, and reduce edge speed; adjustment levels include level one, level two, and level three. The method for determining the adjustment level is as follows: The number of aspect ratios, surface roundness, and regional wrinkle rates that are recorded as poor features within the target period are compared with the number of paper cups to be tested, and the first proportion value, the second proportion value, and the third proportion value are calculated. When the first proportion, the second proportion, and the third proportion are at When the range is within a certain range, the adjustment level will be set to Level 1. When the first proportion value, the second proportion value and the third proportion value are in the interval [0.5, 1], the adjustment level is determined as a second level. When the first proportion value, the second proportion value and the third proportion value are in the interval [0.5, 1], the adjustment level is determined as a second level When the first proportion value, the second proportion value and the third proportion value are in the interval the adjustment level is determined as a third level.

6. The self-adaptive fuzzy control method for paper cup hemming forming quality optimization as claimed in claim 5, wherein, The adaptive fuzzy adjustment control method is as follows: When a command to reduce the hem displacement value is issued, 5% of the hem displacement value is recorded as an adjustment range, and the adjustment level of the command to reduce the hem displacement value is identified. If the adjustment level is Level 1, Level 2, or Level 3, the industrial control system reduces the downward movement distance of the extrusion mechanism by one, two, or three adjustment increments, respectively. When an instruction to increase the softening temperature value is given, 10% of the softening temperature value is recorded as an adjustment range, and the adjustment level of the instruction to increase the softening temperature value is identified. If the adjustment level is Level 1, Level 2, or Level 3, the industrial control system will increase the heating temperature of the heating mechanism by one, two, or three adjustment increments, respectively. When a command to reduce the crimping speed value is given, 8% of the crimping speed value is recorded as an adjustment range, and the adjustment level of the command to reduce the crimping speed value is identified. If the adjustment level is Level 1, Level 2, or Level 3, the lifting speed of the lifting mechanism controlled by the industrial control system will be reduced by one, two, or three adjustment increments, respectively.

7. An adaptive fuzzy control system for optimizing the quality of paper cup hemming forming, applied to an industrial control system, for implementing the adaptive fuzzy control method for optimizing the quality of paper cup hemming forming according to any one of claims 1-6, characterized in that, It includes a parameter filtering module, a control determination module, an instruction determination module, and a fuzzy control module, wherein the modules are connected to each other via wired or wireless networks; The parameter filtering module is used to filter out the equipment parameters that drive the edge-rolling component in the edge-rolling forming equipment from the process database based on the material parameters of the paper cup. The edge-rolling assembly consists of a lifting mechanism, an extrusion mechanism, and a heating mechanism; The control and judgment module is used to construct the material-equipment-cycle sequence of the edge-forming equipment under different operating conditions, select the target cycle for collecting the paper cup to be tested from the material-equipment-cycle sequence, extract the edge-curling quality characteristics of the paper cup to be tested in the target cycle, and determine whether to execute the optimization control operation after analyzing and evaluating the edge-curling quality characteristics. Operating conditions include low load, normal load and full load, and edge curling quality characteristics include aspect ratio, surface roundness and area wrinkling rate. The instruction determination module is used to identify optimization parameters with potential for optimization from the equipment parameters, formulate quality optimization instructions corresponding to the optimization parameters, and determine the adjustment level of the quality optimization instructions; The fuzzy control module is used to determine the adjustment range of the edge curling component based on the quality optimization instructions and adjustment levels, and to perform adaptive fuzzy adjustment on the edge curling component until the optimization control operation is no longer executed.

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