A method for analyzing and processing the quality of pickle ball rotational molding

Abstract

The present invention belongs to the field of quality analysis of rotational molding of pickle balls, and specifically discloses a method for analyzing the quality of rotational molding of pickle balls, which includes: by constructing a comprehensive evaluation system simulation model of the use scenario of pickle balls, the various performances of pickle balls are refined and tested, providing dynamic data support for the performance detection of pickle balls. By importing the actual test data of pickle balls into computer software, a mechanical structure model of pickle balls is established, and on this basis, the mechanical response of pickle balls under different impact loads is simulated and analyzed, so that the monitoring results of the processing quality qualification coefficient of the durability performance of pickle balls are more realistic. Comprehensive testing is carried out from multiple dimensions such as apparent size, internal structure, density performance, elastic performance, impact resistance and friction. At the same time, by testing multiple samples in the same step, the changes in multi-dimensional performance trends are statistically analyzed.

Description

Technical Field

[0001] The invention belongs to the field of quality analysis of pickle ball rotational molding processing, and relates to a method for analyzing and processing quality of pickle ball rotational molding processing. Background Art

[0002] As a popular sporting equipment, the quality of roto-molding of pickle balls directly affects the performance and service life of the product. However, in the current processing quality analysis and processing methods, there is often a lack of sufficient consideration of actual usage scenarios and dynamic performance changes, resulting in the evaluation results being unable to fully reflect the true performance of pickle balls. Therefore, in order to more accurately evaluate the processing quality of pickle ball roto-molding and improve product performance and competitiveness, a new processing quality analysis and processing method is urgently needed to more comprehensively understand the performance characteristics of pickle balls.

[0003] Currently, most existing processing quality analysis methods are image detection and identification of apparent structural defects, without considering the use scenario simulation. Image detection and recognition technology mainly relies on the analysis and processing of static images or video frames. Although it can identify the target objects, features or behaviors in the image, it lacks consideration of dynamic and real-time changing factors in actual use scenarios. For example, in the structural performance analysis of pickleball, image detection and recognition alone may not be able to fully capture the dynamic characteristics of the ball during the actual hitting process, such as friction deformation and rebound state.

[0004] At the same time, the current existing structural performance analysis focuses more on the properties of the materials used to make pickle balls, without considering the actual test data of the finished pickle balls. This makes the evaluation results more process-oriented and theoretical, and cannot fully reflect the performance of pickle balls in actual usage scenarios. Summary of the invention

[0005] In view of this, in order to solve the problems raised in the above background technology, a method for analyzing and processing the quality of pickle ball rotational molding is now proposed.

[0006] The purpose of the present invention can be achieved through the following technical solutions: The present invention provides a method for analyzing and processing the quality of rotational molding of pickle balls, the method comprising: A1, apparent size quality detection: obtaining an image of a finished pickle ball, identifying its apparent color uniformity and size specification compliance rate, and then analyzing the apparent size compliance coefficient of the pickle ball.

[0007] A2. Internal structure detection: Use laser scanning technology to obtain the internal structure image of the pickle ball, analyze the internal structure compliance coefficient of the pickle ball, and then evaluate the size structure processing quality qualification coefficient of the pickle ball. .

[0008] A3. Density performance test: Place the pickle ball in a fixed position in the experimental water tank, observe its submerged position and depth in the static state, determine the main defect types of the internal structure of the pickle ball, and analyze the density quality qualification coefficient of the pickle ball.

[0009] A4. Elasticity performance test: Place the pickle ball in the elasticity test box, measure the rebound height and speed of the pickle ball after being subjected to each specified impact force, analyze the elasticity performance index of the pickle ball, and then evaluate the physical performance processing quality qualification coefficient of the pickle ball .

[0010] A5. Friction test: Place the pickle ball on the friction table, set different friction parameters, observe the wear depth and wear area on the surface of the pickle ball, and evaluate the wear resistance performance index of the pickle ball.

[0011] A6. Impact resistance test: collect the test data of pickle balls, import them into computer simulation software, establish the mechanical structure model of pickle balls, and then set different gradients of impact loads in the simulation environment to evaluate the impact resistance performance index of pickle balls, and then analyze the durability and processing quality qualification coefficient of pickle balls. .

[0012] A7. Prediction of performance change trend: Sample the pickle balls of this batch of rotationally molded products, conduct the same test steps on each sample of pickle balls, obtain the performance test pass coefficient of each sample of pickle balls under each processing performance, locate the processing quality defect performance of this batch of samples, and then feed it back to the back-end management personnel.

[0013] Exemplarily, the method for analyzing the apparent size compliance coefficient of a pickle ball is: obtaining a standard molding image of a pickle ball, extracting its standard molding contour and standard raw material filling color , extract the standard thickness of the hole side structure and the standard center distance between adjacent holes from the standard forming contour.

[0014] Extract the contours of each hole and the thickness of the hole side structure from the finished product image of the pickle ball, identify the center distance between each hole and the adjacent holes, and analyze the stability factor of the honeycomb structure of the pickle ball ;

[0015] The designated hexagonal solid area of ​​each hole is taken as the edge solid area of ​​the hole, and the apparent chromaticity of the edge solid area of ​​each hole is identified based on image recognition technology. , analyze the apparent size of the pickle ball compliance coefficient ,in Indicates the set allowable deviation between the apparent chromaticity of the physical area at the edge of the hole and the standard chromaticity. Indicates the set allowable deviation between the apparent chromaticity of the adjacent hole edge solid areas. Indicates The apparent chromaticity of the solid area at the edge of the hole, is the hole number, , Indicates the number of holes.

[0016] For example, the corresponding formula for evaluating the size structure processing quality qualification coefficient of the pickle ball is: from the internal structure image of the pickle ball, identify each defect area in the solid area of ​​the edge of each hole and its defect type and defect area, the defect type includes bubble type and slag inclusion type, analyze the internal structure of the pickle ball to meet the qualification coefficient .

[0017] The defect types corresponding to the defect areas in the solid area of ​​each hole edge of the pickle ball are counted, and the weight comprehensive bias weights of the defect types of bubble type and slag inclusion type in the solid area of ​​each hole edge of the pickle ball are counted, which are recorded as , calculate the instability rate of the pickleball structure ,in Respectively represent The comprehensive bias weight of the defect types of bubble type and slag inclusion type in the solid area of ​​the hole edge.

[0018] Evaluate the size, structure and processing quality of pickleball balls .

[0019] Exemplarily, the density quality qualification coefficient of the pickle ball is analyzed by the steps of: recording the submerged depth of the submerged position of the pickle ball in a static state as , and compare the fixed position of the pickleball with its submerged position in a static state to obtain the deviation distance .

[0020] Get the submerged depth of the pickleball at standard mass , and compare it to the submerged depth of the pickleball when it is at rest.

[0021] Analyze the density quality coefficient of pickleball ,in Indicates the set deviation allowable value of the submerged depth of the submerged position. Indicates the preset reference deviation distance.

[0022] Exemplarily, the process of analyzing the elastic performance index of the pickle ball is as follows: a number of positioning points are evenly arranged on the pickle ball, each positioning point is used as an elastic force test position point, the pickle ball is placed in the elasticity test box according to the position of each positioning point with a specified force, the rebound position of the position of each positioning point is observed, and the rebound height of each position of each positioning point is obtained. Based on this, calculate the decreasing rate of elastic potential energy at each location of the pickleball ,in is the number of the positioning point, , is the number of rebounds, .

[0023] Connect the position of each positioning point with its rebound position to obtain the rebound direction line of each positioning point, obtain the angle between it and any horizontal line on the horizontal plane, and record it as the rebound deflection angle of each positioning point. .

[0024] Get the preset maximum rebound height of the pickleball and the preset appropriate deceleration rate of elastic potential energy , analyze the bounce performance measurement parameters of pickleball ,in They respectively represent the set rebound height and rebound speed corresponding to the allowable deviation values. Indicates The maximum rebound height of the location where the anchor point belongs, Indicates the allowable deviation value of the set rebound deflection angle.

[0025] Exemplarily, the corresponding formula for evaluating the physical properties of the pickle ball processing quality qualification coefficient is: ,in They represent the weights of the density quality qualification coefficient and the elastic performance index corresponding to the qualification coefficient of the pickle ball. , e is a natural constant.

[0026] Exemplarily, the steps for evaluating the wear resistance of a pickle ball are as follows: replacing various friction materials on a friction table to obtain the friction strength thereof , adjust the rotation speed of the friction table, obtain the rotation speeds corresponding to various friction materials, and then collect the surface images of the pickle ball at various friction materials corresponding to various rotation speeds. is the type number of friction material, .

[0027] The wear depth and wear area of ​​the pickle ball surface are extracted from the surface images of the pickle ball at various friction materials corresponding to various rotation speeds, and are recorded as , is the number of the rotation speed, .

[0028] Evaluation of the wear resistance of pickleball ,in Respectively represent the pickleball in The reference wear depth and reference wear area are set under different friction materials. Respectively represent the pickleball in The maximum wear depth and maximum wear area in the surface images corresponding to the friction materials at each rotation speed.

[0029] Exemplarily, the specific method for analyzing the durability performance processing quality qualification coefficient of the pickle ball is: using simulation software to calculate the damage amplitude and damage type of each damaged area of ​​the pickle ball under various gradient impact load conditions.

[0030] The damage types of each damaged area of ​​the pickle ball under various gradient impact load states are compared with the preset damage influence factors corresponding to various types, so as to obtain the damage state influence factors of each damaged area of ​​the pickle ball under various gradient impact load states.

[0031] Analyze the breakage of pickleball under various gradient impact loads and select the maximum value , and obtain the impact load to which the maximum value belongs .

[0032] Evaluating the impact resistance of pickleball ,in Indicates the specified gradient impact load.

[0033] Analysis of the durability and processing quality of pickleball ,in They represent the weights of the impact resistance and wear resistance of the pickle ball corresponding to the qualified coefficients. .

[0034] Exemplarily, the various processing properties include size and structure processing properties, physical property processing properties, and durability processing properties.

[0035] The performance inspection qualified coefficients under the processing performances include the dimensional structure processing quality qualified coefficient under the dimensional structure processing performance, the physical property processing quality qualified coefficient under the physical property processing performance, and the durability performance processing quality qualified coefficient under the durability performance processing performance.

[0036] Exemplarily, the method for identifying the quality defects of the samples in this batch is to obtain the performance test qualification coefficient of each sample of the pickle ball corresponding to each processing performance. , is the number of the sample pickleball, .

[0037] Analysis of the abnormal rate of trend change corresponding to the qualified coefficient of dimensional structure processing quality under dimensional structure processing performance ,in Indicates that the size structure processing quality qualification coefficient of the sample pickle ball corresponds to the specified threshold value, Represents the total number of sample pickleballs.

[0038] Similarly, obtain the abnormal rate of trend change corresponding to the physical property processing quality qualification coefficient under the physical property processing performance , Durability performance processing performance Durability performance processing quality qualified coefficient corresponding to the abnormal rate of trend change .

[0039] Obtain the threshold value of the abnormal rate of trend change corresponding to the performance inspection qualified coefficient under each preset processing performance, screen out the processing performance whose abnormal rate of trend change corresponding to the performance inspection qualified coefficient exceeds the preset abnormal rate threshold of trend change, and record it as the processing quality defect performance of this batch of samples.

[0040] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) The present invention constructs a comprehensive evaluation system simulation model of the use scenarios of pickle balls, conducts refined testing of various performances of pickle balls, provides dynamic data support for the performance testing of pickle balls, and thus improves the accuracy of the evaluation.

[0041] (2) The present invention imports actual test data of pickle balls into computer software to establish a mechanical structure model of pickle balls. The data simulated based on actual monitoring data is closer to reality. On this basis, the mechanical response of pickle balls under different impact loads is simulated and analyzed to evaluate their impact resistance. This can more accurately reflect the stress conditions and structural changes of pickle balls in actual use, making the monitoring results of the durability performance and processing quality qualification coefficient of pickle balls more realistic, and thus more reliable and effective.

[0042] (3) The present invention conducts comprehensive testing from multiple dimensions such as apparent size, internal structure, density performance, elasticity, impact resistance and friction. This multi-dimensional testing can provide a more comprehensive and accurate performance evaluation and help to discover potential quality problems. At the same time, by testing multiple samples in the same steps and statistically analyzing the changes in multi-dimensional performance trends, it is helpful to discover performance fluctuations and quality defects in batch samples, which can better guide product development and production process improvements, making quality control more scientific and accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0044] Figure 1 The present invention is a schematic flow chart of the steps for implementing the method.

[0045] Figure 2 This is an image of the finished pickle ball product of the present invention.

[0046] Figure numerals: 1. The designated hexagonal solid area to which the hole belongs. DETAILED DESCRIPTION

[0047] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0048] See also Figure 1 As shown, the present invention provides a method for analyzing and processing the quality of rotational molding of pickle balls, the method comprising: A1, apparent size quality detection: obtaining a finished product image of the pickle ball, identifying its apparent color uniformity and size specification compliance rate, and then analyzing the apparent size compliance coefficient of the pickle ball.

[0049] See also Figure 2 As shown, in a specific embodiment of the present invention, the method for analyzing the apparent size compliance coefficient of the pickle ball is: obtaining the standard molding image of the pickle ball from the cloud database, extracting its standard molding contour and standard raw material filling color , extract the standard thickness of the hole side structure from the standard forming profile , Standard center distance between adjacent holes .

[0050] Extract the contours of each hole and the thickness of the hole side structure from the finished pickle ball image , identify the center distance between each hole and the adjacent holes , is the hole number, .

[0051] Analysis of the stability factor of the honeycomb structure of the pickleball ,in Indicates the allowable deviation value of the thickness of the hole side structure. Indicates the allowable deviation of the center distance between the two holes. Indicates the number of holes.

[0052] The designated hexagonal solid area of ​​each hole is taken as the edge solid area of ​​the hole, and the apparent chromaticity of the edge solid area of ​​each hole is identified based on image recognition technology. , analyze the apparent size of the pickle ball compliance coefficient ,in Indicates the set allowable deviation between the apparent chromaticity of the physical area at the edge of the hole and the standard chromaticity. Indicates the set allowable deviation between the apparent chromaticity of the adjacent hole edge solid areas. Indicates The apparent chromaticity of the solid area at the edge of a hole.

[0053] A2. Internal structure detection: Use laser scanning technology to obtain the internal structure image of the pickle ball, analyze the internal structure compliance coefficient of the pickle ball, and then evaluate the size structure processing quality qualification coefficient of the pickle ball. .

[0054] In a specific embodiment of the present invention, the corresponding formula for evaluating the size structure processing quality qualification coefficient of the pickle ball is: the image texture features corresponding to each defect type in the internal defect area of ​​the pickle ball are obtained from the cloud database, and the defect types include bubble type and slag inclusion type. Based on the image recognition technology, each defect area in the entity area of ​​the edge of each hole and its defect type and defect area are identified from the internal structure image of the pickle ball, and its defect area is recorded as , analyze the internal structure of the pickleball ,in The setting of the defect area refers to the defect area. is the number of the defect area, .

[0055] The defect types corresponding to the defect areas in the solid area of ​​each hole edge of the pickle ball are counted. If the defect type corresponding to a defect area in the solid area of ​​a hole edge is a bubble type, the weight bias weight of the defect area in the solid area of ​​the hole edge is recorded as , if the defect type of the defect area in the solid area of ​​the hole edge is the slag inclusion type, then the weight bias weight of the defect area in the solid area of ​​the hole edge is recorded as , the weight bias weight of each defect area in the solid area of ​​each hole edge of the pickle ball is obtained by statistics , and then sum them up to get the weight comprehensive bias weights of the defect types of bubble type and slag inclusion type in the solid area of ​​the edge of each hole in the pickle ball, which are recorded as , calculated by the formula The instability rate of the pickleball structure is obtained, where Respectively represent The comprehensive bias weight of the defect types of bubble type and slag inclusion type in the solid area of ​​the hole edge.

[0056] Evaluate the size, structure and processing quality of pickleball balls .

[0057] A3. Density performance test: Place the pickle ball in a fixed position in the experimental water tank, observe its submerged position and depth in the static state, determine the main defect types of the internal structure of the pickle ball, and analyze the density quality qualification coefficient of the pickle ball.

[0058] In a specific embodiment of the present invention, the density quality qualification coefficient of the pickle ball is analyzed by the steps of: recording the submerged depth of the submerged position of the pickle ball in a static state as , and compare the fixed position of the pickleball with its submerged position in a static state to obtain the deviation distance .

[0059] Get the submerged depth of the pickleball ball under standard quality conditions from the cloud database , and compare it to the submerged depth of the pickleball when it is at rest.

[0060] Analyze the density quality coefficient of pickleball ,in Indicates the set deviation allowable value of the submerged depth of the submerged position. Indicates the preset reference deviation distance.

[0061] A4. Elasticity performance test: Place the pickle ball in the elasticity test box, measure the rebound height and speed of the pickle ball after being subjected to each specified impact force, analyze the elasticity performance index of the pickle ball, and then evaluate the physical performance processing quality qualification coefficient of the pickle ball .

[0062] In a specific embodiment of the present invention, the process of analyzing the elastic performance index of the pickle ball is as follows: a number of positioning points are evenly arranged on the pickle ball, each positioning point is used as an elastic force test position point, the pickle ball is placed in the elasticity test box according to the position of each positioning point with a specified force, the rebound position of the position of each positioning point is observed, and the rebound height of each position of each positioning point is obtained. , is the number of the positioning point, , is the number of rebounds, .

[0063] Calculate the rate of decrease of elastic potential energy at each location of the pickleball ,in Indicates The location of the anchor point The rebound height, is the total number of rebounds.

[0064] Connect the position of each positioning point with its rebound position to obtain the rebound direction line of each positioning point, obtain the angle between it and any horizontal line on the horizontal plane, and record it as the rebound deflection angle of each positioning point. .

[0065] Get the preset maximum rebound height of the pickleball and the preset appropriate deceleration rate of elastic potential energy , analyze the bounce performance measurement parameters of pickleball ,in They respectively represent the set rebound height and rebound speed corresponding to the allowable deviation values. Indicates The maximum rebound height of the location where the anchor point belongs, Indicates the allowable deviation value of the set rebound deflection angle.

[0066] In another specific embodiment of the present invention, the corresponding formula for evaluating the physical properties of the pickle ball processing quality qualification coefficient is: ,in They represent the weights of the density quality qualification coefficient and the elastic performance index corresponding to the qualification coefficient of the pickle ball. , e is a natural constant.

[0067] A5. Friction test: Place the pickle ball on the friction table and set different friction parameters, including friction speed and friction strength. Observe the wear depth and wear area on the surface of the pickle ball to evaluate the wear resistance of the pickle ball.

[0068] In a specific embodiment of the present invention, the steps of evaluating the wear resistance index of the pickle ball are as follows: replacing various friction materials on the friction table to obtain their friction strength , adjust the rotation speed of the friction table, obtain the rotation speeds corresponding to various friction materials, and then collect the surface images of the pickle ball at various friction materials corresponding to various rotation speeds. is the type number of friction material, .

[0069] The apparent texture features corresponding to the friction state are obtained from the cloud database, and then the wear depth and wear area of ​​the pickle ball surface are extracted from the apparent images of the pickle ball at various rotation speeds corresponding to various friction materials based on image recognition technology, which are recorded as , is the number of the rotation speed, .

[0070] Evaluation of the wear resistance of pickleball ,in Respectively represent the pickleball in The reference wear depth and reference wear area are set under different friction materials. Respectively represent the pickleball in The maximum wear depth and maximum wear area in the surface images corresponding to the friction materials at each rotation speed.

[0071] The present invention constructs a comprehensive evaluation system simulation model of the pickle ball usage scenario, conducts a refined test on various performances of the pickle ball, provides dynamic data support for the performance test of the pickle ball, and thus improves the accuracy of the evaluation.

[0072] A6. Impact resistance test: Collect all test data of pickle balls, including the size structure processing quality qualification coefficient, physical property processing quality qualification coefficient and wear resistance index of pickle balls, and import them into computer simulation software to establish the mechanical structure model of pickle balls, and then set different gradients of impact loads in the simulation environment to evaluate the impact resistance index of pickle balls, and then analyze the durability processing quality qualification coefficient of pickle balls. .

[0073] In a specific embodiment of the present invention, the specific method for analyzing the durability performance processing quality qualification coefficient of the pickle ball is: the damage amplitude of each damaged area of ​​the pickle ball under various gradient impact load conditions is calculated by simulation software. and damage type.

[0074] The damage type of each damaged area of ​​the pickle ball under various gradient impact loads is compared with the preset damage influence factors of various types, and the damage state influence factors of each damaged area of ​​the pickle ball under various gradient impact loads are obtained. , is the gradient number of the impact load, , is the number of the damaged area, .

[0075] Analyze the breakage of pickleball under various gradient impact loads ,in Indicates the set reference damage amplitude of the pickle ball under the specified gradient impact load state, and selects the maximum value from the damage of the pickle ball under various gradient impact load states , and obtain the impact load to which the maximum value belongs .

[0076] Evaluating the impact resistance of pickleball ,in Indicates the specified gradient impact load.

[0077] Analysis of the durability and processing quality of pickleball ,in They represent the weights of the impact resistance and wear resistance of the pickle ball corresponding to the qualified coefficients. .

[0078] The present invention establishes a mechanical structure model of the pickle ball by importing actual test data of the pickle ball into computer software. The data simulated based on the actual monitoring data is closer to reality. On this basis, the mechanical response of the pickle ball under different impact loads is simulated and analyzed, and its impact resistance is evaluated. This can more accurately reflect the stress conditions and structural changes of the pickle ball in actual use, making the monitoring results of the durability performance and processing quality qualification coefficient of the pickle ball more realistic, and thus more reliable and effective.

[0079] A7. Prediction of performance change trend: Sample the pickle balls of this batch of rotationally molded products, conduct the same test steps on each sample of pickle balls, obtain the performance test pass coefficient of each sample of pickle balls under each processing performance, locate the processing quality defect performance of this batch of samples, and then feed it back to the back-end management personnel.

[0080] In a specific embodiment of the present invention, the various processing properties include size and structure processing properties, physical property processing properties, and durability processing properties.

[0081] The performance inspection qualified coefficients under the processing performances include the dimensional structure processing quality qualified coefficient under the dimensional structure processing performance, the physical property processing quality qualified coefficient under the physical property processing performance, and the durability performance processing quality qualified coefficient under the durability performance processing performance.

[0082] In another specific embodiment of the present invention, the method for identifying the quality defects of the samples in this batch is as follows: according to the method for obtaining the performance test qualification coefficient of each processing performance of the pickle ball, the performance test qualification coefficient of each sample pickle ball corresponding to each processing performance is obtained in the same way. , is the number of the sample pickleball, .

[0083] Analysis of the abnormal rate of trend change corresponding to the qualified coefficient of dimensional structure processing quality under dimensional structure processing performance ,in Indicates that the size structure processing quality qualification coefficient of the sample pickle ball corresponds to the specified threshold value, Represents the total number of sample pickleballs.

[0084] Similarly, obtain the abnormal rate of trend change corresponding to the physical property processing quality qualification coefficient under the physical property processing performance , Durability performance processing performance Durability performance processing quality qualified coefficient corresponding to the abnormal rate of trend change .

[0085] Obtain the threshold value of the abnormal rate of trend change corresponding to the performance inspection qualified coefficient under each preset processing performance, screen out the processing performance whose abnormal rate of trend change corresponding to the performance inspection qualified coefficient exceeds the preset abnormal rate threshold of trend change, and record it as the processing quality defect performance of this batch of samples.

[0086] The present invention conducts comprehensive testing from multiple dimensions such as apparent size, internal structure, density performance, elasticity, impact resistance and friction. This multi-dimensional testing can provide a more comprehensive and accurate performance evaluation, which helps to discover potential quality problems. At the same time, by testing multiple samples in the same steps and statistically analyzing the changes in multi-dimensional performance trends, it is helpful to discover performance fluctuations and quality defects in batch samples, which can better guide product development and production process improvements, making quality control more scientific and accurate.

[0087] The above contents are merely examples and explanations of the concept of the present invention. Those skilled in the art may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they shall all fall within the protection scope of the present invention.

Claims

1. A method for analyzing and processing the quality of rotational molding of pickle balls, characterized in that: The method comprises the following steps: A1. Apparent size quality inspection: Get the finished product image of the pickle ball, identify its apparent color uniformity and size specification compliance rate, and then analyze the apparent size compliance coefficient of the pickle ball; A2. Internal structure detection: Use laser scanning technology to obtain the internal structure image of the pickle ball, analyze the internal structure compliance coefficient of the pickle ball, and then evaluate the size structure processing quality qualification coefficient of the pickle ball. ; A3. Density performance test: Place the pickle ball in a fixed position in the experimental water tank, observe its submerged position and depth in the static state, determine the main defect types of the internal structure of the pickle ball, and analyze the density quality qualification coefficient of the pickle ball; A4. Elasticity performance test: Place the pickle ball in the elasticity test box, measure the rebound height and speed of the pickle ball after being subjected to each specified impact force, analyze the elasticity performance index of the pickle ball, and then evaluate the physical performance processing quality qualification coefficient of the pickle ball ; A5. Friction test: Place the pickle ball on the friction table, set different friction parameters, observe the wear depth and wear area on the surface of the pickle ball, and evaluate the wear resistance index of the pickle ball; A6. Impact resistance test: collect the test data of pickle balls, import them into computer simulation software, establish the mechanical structure model of pickle balls, and then set different gradients of impact loads in the simulation environment to evaluate the impact resistance performance index of pickle balls, and then analyze the durability and processing quality qualification coefficient of pickle balls. ; A7. Prediction of performance change trend: Sample and extract each sample of the rotationally molded pickle ball in this batch, conduct the same step test on each sample of the pickle ball, obtain the performance test qualification coefficient of each sample of the pickle ball under each processing performance, locate the processing quality defect performance of this batch of samples, and then feed it back to the back-end management personnel; The method for analyzing the apparent size compliance coefficient of the pickle ball is: Get the standard molding image of the pickle ball and extract its standard molding contour and standard raw material filling color , extract the standard thickness of the hole side structure from the standard forming profile , Standard center distance between adjacent holes ; Extract the contours of each hole and the thickness of the hole side structure from the finished pickle ball image , identify the center distance between each hole and the adjacent holes , is the hole number, , Analyze the stability factor of the honeycomb structure of the pickle ball ,in Indicates the allowable deviation value of the thickness of the hole side structure. Indicates the allowable deviation of the center distance between the two holes. Indicates the number of holes; The designated hexagonal solid area of ​​each hole is taken as the edge solid area of ​​the hole, and the apparent chromaticity of the edge solid area of ​​each hole is identified based on image recognition technology. , analyze the apparent size of the pickle ball compliance coefficient ,in Indicates the set allowable deviation between the apparent chromaticity of the physical area at the edge of the hole and the standard chromaticity. Indicates the set allowable deviation between the apparent chromaticity of the adjacent hole edge solid areas. Indicates The apparent chromaticity of the solid area at the edge of the hole, is the hole number, , Indicates the number of holes; The corresponding formula for evaluating the size and structure processing quality of pickle balls is: From the internal structure image of the pickle ball, the defect areas, defect types and defect areas in the solid area of ​​each hole edge are identified, and the defect areas are recorded as , defect types include bubble type and slag inclusion type, analyze the internal structure of the pickle ball to meet the coefficient ,in The setting of the defect area refers to the defect area. is the number of the defect area, ; The defect types corresponding to the defect areas in the solid area of ​​each hole edge of the pickle ball are counted, and the weight comprehensive bias weights of the defect types of bubble type and slag inclusion type in the solid area of ​​each hole edge of the pickle ball are counted, which are recorded as , calculate the instability rate of the pickleball structure ,in Respectively represent The weight of the defect types in the solid area of ​​the edge of each hole is the comprehensive bias weight of the bubble type and the slag inclusion type; Evaluate the size, structure and processing quality of pickleball balls ; The steps of analyzing the density quality qualification coefficient of the pickle ball are as follows: The submerged depth of the pickleball in the static state is recorded as , and compare the fixed position of the pickleball with its submerged position in a static state to obtain the deviation distance ; Get the submerged depth of the pickleball at standard mass , and compare it to the submerged depth of the pickleball when it is at rest; Analyze the density quality coefficient of pickleball ,in Indicates the set deviation allowable value of the submerged depth of the submerged position. Indicates the preset reference deviation distance; The process of analyzing the elastic performance index of the pickle ball is as follows: Evenly distribute several positioning points on the pickle ball, take each positioning point as the elastic force test position point, place the pickle ball into the elasticity test box according to the position of each positioning point with a specified force, observe the rebound position of each positioning point, and obtain the rebound height of each positioning point. Based on this, calculate the decreasing rate of elastic potential energy at each location of the pickleball ,in is the number of the positioning point, , is the number of rebounds, ; Connect the position of each positioning point with its rebound position to obtain the rebound direction line of each positioning point, obtain the angle between it and any horizontal line on the horizontal plane, and record it as the rebound deflection angle of each positioning point. ; Get the preset maximum rebound height of the pickleball and the preset appropriate deceleration rate of elastic potential energy , analyze the bounce performance measurement parameters of pickleball ,in They respectively represent the set rebound height and rebound speed corresponding to the allowable deviation values. Indicates The maximum rebound height of the location where the anchor point belongs, Indicates the allowable deviation value of the set rebound deflection angle; The corresponding formula for evaluating the physical performance processing quality coefficient of the pickle ball is: ,in They represent the weights of the density quality qualification coefficient and the elastic performance index corresponding to the qualification coefficient of the pickle ball. , e is a natural constant; The steps for evaluating the wear resistance of the pickle ball are as follows: Replace various friction materials on the friction table to obtain their friction strength , adjust the rotation speed of the friction table, obtain the rotation speeds corresponding to various friction materials, and then collect the surface images of the pickle ball at various friction materials corresponding to various rotation speeds. is the type number of friction material, ; The wear depth and wear area of ​​the pickle ball surface were extracted from the surface images of the pickle ball at various friction materials corresponding to various rotation speeds, and were recorded as , is the number of the rotation speed, ; Evaluation of the wear resistance of pickleball ,in Respectively represent the pickleball in The reference wear depth and reference wear area are set under different friction materials. Respectively represent the pickleball in The maximum wear depth and maximum wear area in the surface images corresponding to the friction materials at each rotation speed; The specific method for analyzing the durability performance and processing quality qualification coefficient of the pickle ball is as follows: The damage amplitude and damage type of each damaged area of ​​the pickle ball under various gradient impact load conditions are calculated by simulation software; Compare the damage types of each damaged area of ​​the pickle ball under various gradient impact loads with the preset damage influence factors corresponding to various types, and obtain the damage state influence factors of each damaged area of ​​the pickle ball under various gradient impact loads; Analyze the breakage of pickleball under various gradient impact loads and select the maximum value , and obtain the impact load to which the maximum value belongs ; Evaluating the impact resistance of pickleball ,in Indicates the specified gradient impact load; Analysis of the durability and processing quality of pickleball ,in They represent the weights of the impact resistance and wear resistance of the pickle ball corresponding to the qualified coefficients. ; The method for identifying the quality defects of the samples in this batch is as follows: Obtain the performance test qualification coefficient of each sample of pickle ball corresponding to each processing performance , is the number of the sample pickleball, ; Analysis of the abnormal rate of trend change corresponding to the qualified coefficient of dimensional structure processing quality under dimensional structure processing performance ,in Indicates that the size structure processing quality qualification coefficient of the sample pickle ball corresponds to the specified threshold value, represents the total number of sample pickleballs; Similarly, obtain the abnormal rate of trend change corresponding to the physical property processing quality qualification coefficient under the physical property processing performance , Durability performance processing performance Durability performance processing quality qualified coefficient corresponding to the abnormal rate of trend change ; Obtain the threshold value of the abnormal rate of trend change corresponding to the performance inspection qualified coefficient under each preset processing performance, screen out the processing performance whose abnormal rate of trend change corresponding to the performance inspection qualified coefficient exceeds the preset abnormal rate threshold of trend change, and record it as the processing quality defect performance of this batch of samples.

2. A method for analyzing and processing the quality of rotational molding of pickle balls according to claim 1, characterized in that: The processing properties include size and structure processing properties, physical properties processing properties, and durability processing properties; The performance inspection qualified coefficients under the processing performances include the dimensional structure processing quality qualified coefficient under the dimensional structure processing performance, the physical property processing quality qualified coefficient under the physical property processing performance, and the durability performance processing quality qualified coefficient under the durability performance processing performance.

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