A method for detecting surface quality of automobile window mold

Abstract

The present invention relates to the field of mold detection technology, in particular to a method for detecting the surface quality of an automobile window mold, comprising the following steps: step 1: determining an automobile window mold to be detected as a target area, and dividing the target area into a plurality of sub-areas according to each automobile window mold, step 2: classifying various monitoring parameters of the plurality of sub-areas divided in step 1, step 3: analyzing various monitoring parameters of the automobile window mold surface classified in step 2, step 4: evaluating various quality detection indexes of the automobile mold surface analyzed in step 3, step 5: performing comprehensive analysis on the comparison and evaluation results of various quality detection indexes calculated in step 4 to obtain a comprehensive index for mold surface quality detection, and step 6: performing human-computer interaction on the comprehensive index for mold surface quality detection obtained by comprehensive analysis in step 5.

Description

Technical Field

[0001] The invention relates to the technical field of mold detection, in particular to a method for detecting the surface quality of an automobile window mold. Background Art

[0002] Automobile window molds are mainly used to produce glass products required for automobile windshields, windows, sunroofs, etc. In the window processing process, the use of molds is crucial, and the surface quality of automobile window molds directly determines the precision of automobile window products and directly affects the appearance quality of windows. Poor mold surface quality may also lead to reduced production efficiency, ultimately affecting the quality and performance of glass products.

[0003] Traditionally, the surface quality inspection of automobile window molds is mostly done manually, which mainly relies on the experience and skills of the inspectors. This method has the disadvantages of strong subjectivity, low efficiency, and easy to be affected by human factors. In addition, it lacks in-depth mining and analysis of mold surface feature data, and cannot accurately and efficiently inspect the mold surface quality. In addition, with the continuous development of the automobile industry, the requirements for the surface quality of automobile window molds are getting higher and higher. The surface inspection technology of automobile window molds will develop in a more intelligent, automated, and high-precision direction.

[0004] Therefore, a method for detecting the surface quality of automobile window molds is provided to solve the above-mentioned problem. Through computer technology, image processing technology and high-precision measuring equipment, characteristic data of multiple aspects of the surface of the automobile window mold are collected, and then the detection data are analyzed using statistical methods and data analysis software to evaluate the surface quality of the mold. This method can realize fast and accurate detection of the mold surface, greatly improve the detection efficiency and accuracy, thereby ensuring that the final produced automobile window products have precise size and shape. Summary of the invention

[0005] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a method for detecting the surface quality of an automobile window mold to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solution: a method for detecting the surface quality of an automobile window mold, comprising the following steps:

[0007] Step 1: Determine the automobile window mold to be inspected as the target area, and divide the target area into several sub-areas according to each automobile window mold;

[0008] Step 2: Classify the monitoring parameters of the several sub-areas divided in step 1 to obtain the monitoring parameters of the surface quality inspection of the automobile window mold;

[0009] Step 3: Analyze various monitoring parameters of the automobile window mold surface classified in step 2 to obtain various indexes for automobile mold surface quality detection;

[0010] Step 4: Evaluate each index of the automobile mold surface quality inspection analyzed in step 3 to obtain comparative evaluation results;

[0011] Step 5: Perform a comprehensive analysis on the comparative evaluation results of various quality inspection indexes calculated in step 4 to obtain a comprehensive index for mold surface quality inspection;

[0012] Step 6: Perform human-computer interaction on the comprehensive indicators of mold surface quality inspection obtained through comprehensive analysis in step 5.

[0013] Preferably, the monitoring parameters in the mold surface quality detection data acquisition module include target area information, detection personnel identity authentication information, mold surface physical parameters, mold surface coating parameters, mold surface structural parameters, and mold surface usage parameters, wherein the mold surface physical parameters are specifically the roughness value measured by a surface roughness meter, the glossiness value measured by a gloss meter, the mold X, Y and Z three-dimensional coordinate values ​​measured by a profile meter, and the mold surface color Lab value measured by a colorimeter; the mold surface coating parameters are specifically the coating thickness measured by a coating thickness meter, the coating surface resistance value, the cross-sectional area of ​​the interface between the coating and the substrate, and the load value when the coating is pulled apart and damaged; the mold surface structural parameters are specifically the center coordinates of the mold positioning hole, the diameter of the positioning hole, the pressure applied to the mold surface, the displacement of the mold surface due to the application of pressure, the area of ​​the mold cavity highlight zone measured by a highlight detector, and the total area of ​​the cavity surface; the mold surface usage parameters are specifically the thermal expansion coefficient of the mold material, the friction coefficient between the glass product and the mold surface, and the projection area of ​​the demolding gap area projected onto the plane.

[0014] Preferably, the model for obtaining the mold surface physical performance index in each detection sub-area in each index of the automobile mold surface quality detection is: Where Ppi i represents the physical performance index of the mold surface in the i-th detection sub-area, Pv represents the mold surface profile, (x j ,y j ,z j ) represents the actual measured three-dimensional coordinates of the jth measurement point on the mold surface profile, (x j0 ,y j0 ,z j0 ) represents the design standard value of the jth measuring point, j∈m, m represents the number of measuring points on the mold surface, Max() represents the maximum value, l1 represents the measuring instrument influence factor, Gu represents the glossiness of the mold surface, guj represents the gloss value of the jth mold surface measurement point, l2 represents the gloss measuring instrument influence factor, ΔE represents the color consistency of the mold surface, (L j ,a j ,b j ) represents the L*, a*, b* values ​​of the jth measurement point on the mold surface in the Lab color space, (L j0 ,a j0 ,b j0 ) represents the standard color value of the jth measurement point on the mold surface in the Lab color space, Ra represents the roughness of the mold surface, l3 represents the colorimeter measurement influencing factor, l4 represents the roughness meter measurement influence factor, and They respectively represent the weights of the mold surface profile, the mold surface glossiness and the mold surface color consistency.

[0015] Preferably, the model for obtaining the mold surface coating performance index in each detection sub-area in each index of the automobile mold surface quality detection is: Cpi i =(α1×e 1+Ct +α2×lnF)×ln(Rt), where Cpi i represents the performance index of the mold surface coating in the i-th detection sub-area, Ct represents the coating surface thickness, ct j represents the thickness of the coating at the jth mold surface measurement point, β1 represents the measurement influencing factor, F represents the adhesion of the mold surface coating, G represents the load value when the coating is pulled apart and damaged, S represents the cross-sectional area of ​​the interface between the coating and the substrate, and Rt represents the resistivity of the coating surface. R represents the surface resistance value of the coating, β2 represents the resistance measurement influencing factor, and α1 and α2 represent the weights of the coating surface thickness and the coating adhesion on the mold surface, respectively.

[0016] Preferably, the model for obtaining the mold surface physical performance index in each detection sub-area in each index of the automobile mold surface quality detection is: Spi i represents the mold surface structure performance index of the i-th detection sub-area, Pa represents the mold positioning hole accuracy, (x c ,y c ,z c ) represents the three-dimensional coordinates of the measurement center of the cth positioning hole, (x c0 ,y c0 ,z c0 ) represents the three-dimensional coordinates of the standard center of the cth positioning hole, D crepresents the diameter of the cth positioning hole, Ha represents the area ratio of the highlight area of ​​the mold cavity, s J represents the area of ​​the transverse cavity highlight region at the Jth position, M represents the number of multiple positions, S T represents the total surface area of ​​the mold cavity, Sa represents the deformation of the mold skeleton, d J It represents the displacement of the mold surface at the Jth position due to the applied pressure, f represents the applied pressure value, η1 and η2 represent the weights of the mold positioning hole accuracy and the proportion of the mold cavity highlight area, respectively.

[0017] Preferably, the model for obtaining the mold surface performance index in each detection sub-area in each index of the automobile mold surface quality detection is: Upi i represents the mold surface performance index of the i-th detection sub-area, Fda represents the mold surface demoulding angle suitability, Fda=ln[arctan(μ)+θ], μ represents the friction coefficient between the glass product and the mold surface, θ represents the demoulding angle safety margin, Sap represents the demoulding shrinkage area ratio, sh represents the projection area of ​​the demoulding gap area onto the plane, S T It represents the total surface area of ​​the mold cavity, Tda represents the contour deformation during the heating process of the mold, Pv hou Indicates the profile after heating, Pv qian It represents the contour before heating, Co represents the thermal expansion coefficient of the mold material, and They respectively represent the proportion of the demoulding angle and the contour deformation during the heating process.

[0018] Preferably, the comparative evaluation results include the following steps:

[0019] Step 4.1: Obtain the mold surface physical performance index analysis calculation results Ppi for each detection sub-area in the mold surface physical index analysis unit i Substituting into the formula: where ρ Ppii Indicates the similarity of mold surface physical performance index evaluation, Ppi represents the set value, Ppi i represents the physical performance index of the mold surface in the i-th detection sub-area;

[0020] Step 4.2: Obtain the mold surface coating performance index analysis calculation result Cpi from each detection sub-area in the mold surface coating index analysis unit i Substituting into the formula: in Indicates the similarity of the physical coating performance index evaluation of the mold surface. Cpi indicates the set value.i represents the performance index of the mold surface coating in the i-th detection sub-area;

[0021] Step 4.3: Obtain the mold surface physical performance index analysis calculation results Spi from each detection sub-area in the mold surface structure index analysis unit i Substituting into the formula: in Indicates the similarity of the mold surface structure performance index evaluation, Spi represents the set value, Spi i represents the mold surface structure performance index of the i-th detection sub-area;

[0022] Step 4.4: Obtain the mold surface usage performance index analysis calculation result Upi from each detection sub-area in the mold surface usage index analysis unit i Substituting into the formula: in Indicates the similarity of the mold surface performance index evaluation, Upi indicates the set value, Upi i Represents the mold surface usage performance index of the i-th detection sub-area.

[0023] Preferably, the comprehensive analysis model of the comprehensive indicators for mold surface quality detection is: Tci represents the comprehensive index of mold surface quality inspection, ξ1, ξ2, ξ3 and ξ4 represent the weights of the similarity of each quality inspection index evaluation, Indicates the similarity of mold surface physical performance index evaluation, Indicates the similarity of the physical coating performance index evaluation on the mold surface, ρ Spii Indicates the similarity of mold surface structure performance index evaluation, Indicates the similarity of the mold surface using performance index evaluation.

[0024] Technical effects and advantages of the present invention:

[0025] 1. The present invention obtains an index to evaluate the physical properties of the mold surface by analyzing the physical parameters of the mold surface. The geometric characteristics of the mold surface have a direct impact on the quality of the mold surface, can reflect the degree of undulation of the mold surface, help to judge the newness of the mold or whether maintenance is needed, and help to find out whether there are abnormal conditions such as pollution and oxidation on the mold surface;

[0026] 2. The present invention obtains an index to evaluate the performance of the mold surface coating by analyzing the mold surface coating parameters, which helps to increase the hardness and wear resistance of the mold, so that the coating can fit tightly on the mold surface to form an effective protective barrier, thereby extending the service life of the mold. At the same time, the resistivity indirectly affects the wear resistance and hardness of the coating, thereby affecting the scratch and wear resistance of the mold surface;

[0027] 3. The present invention analyzes the surface structural parameters of the mold to obtain an index to evaluate the surface structural performance of the mold, provides scientific data support, helps to optimize the stability and accuracy of the mold during the mold closing process, and takes effective measures to reduce the deformation of the mold skeleton to ensure the surface quality and production efficiency of the mold, and ultimately improves the gloss and brightness of the automobile window surface. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 It is a schematic diagram of the overall process of the present invention. DETAILED DESCRIPTION

[0029] 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.

[0030] See also Figure 1 As shown, the present invention provides a method for detecting the surface quality of automobile window molds, comprising: a mold surface quality detection area division module, a mold surface quality detection data acquisition module, a mold surface quality detection data feature analysis module, a mold surface quality detection data analysis and evaluation module, a mold surface quality detection comprehensive analysis module, and a mold surface quality detection human-computer interaction module.

[0031] The mold surface quality detection area division module is connected to the mold surface quality detection data acquisition module, the mold surface quality detection data feature analysis module is respectively connected to the mold surface quality detection data analysis and evaluation module and the mold surface quality detection data acquisition module, the mold surface quality detection comprehensive analysis module is respectively connected to the mold surface quality detection human-computer interaction module and the mold surface quality detection data analysis and evaluation module, and the mold surface quality detection human-computer interaction module terminal is connected to the mold surface quality detection data feature analysis module.

[0032] The mold surface quality detection area division module is used to divide the automobile window mold to be detected into areas;

[0033] The mold surface quality detection data acquisition module is used to collect mold surface quality feature data, obtain various monitoring parameters for automobile window mold surface quality detection, and transmit the various monitoring parameters to the mold surface quality detection data feature quantization module;

[0034] The mold surface quality detection data feature analysis module is used to analyze various monitoring parameters to obtain various indexes of automobile mold surface quality detection, and transmit each index to the mold surface quality detection data analysis and evaluation module;

[0035] The mold surface quality detection data analysis and evaluation module is used to compare the above-mentioned automobile mold surface quality indicators with the set values, and transmit the comparison and evaluation results to the mold surface quality detection comprehensive analysis module;

[0036] The mold surface quality detection comprehensive analysis module is used to evaluate and compare the above data, conduct a comprehensive analysis, obtain a comprehensive index of mold surface quality detection, and output the comprehensive index to the mold surface quality detection human-computer interaction module;

[0037] The mold surface quality detection human-computer interaction module is used to output the comprehensive indicators input by the above module to the detection management personnel information terminal.

[0038] A method for detecting the surface quality of an automobile window mold comprises the following steps: step 1: determining an automobile window mold to be detected as a target area, and dividing the target area into a plurality of sub-areas according to each automobile window mold; step 2: classifying various monitoring parameters of the plurality of sub-areas divided in step 1 to obtain various monitoring parameters for detecting the surface quality of the automobile window mold; step 3: analyzing various monitoring parameters of the automobile window mold surface classified in step 2 to obtain various indexes for detecting the surface quality of the automobile mold; step 4: evaluating various indexes for detecting the surface quality of the automobile mold analyzed in step 3 to obtain comparative evaluation results; step 5: comprehensively analyzing the comparative evaluation results of various quality detection indexes calculated in step 4 to obtain comprehensive indicators for detecting the surface quality of the mold; and step 6: performing human-computer interaction on the comprehensive indicators for detecting the surface quality of the mold obtained by the comprehensive analysis in step 5.

[0039] Step 1: determine the automobile window mold to be inspected as the target area, and divide the target area into a number of sub-areas according to each automobile window mold, which are sequentially recorded as 1, 2, 3, ..., n;

[0040] What needs to be specifically explained in this embodiment is that the detection environments, detection equipment and mold materials of the several sub-areas are the same.

[0041] Step 2: Classify the monitoring parameters of several sub-areas divided in step 1 to obtain the monitoring parameters of the surface quality inspection of the automobile window mold, including target area information, inspection personnel identity authentication information, mold surface physical parameters, mold surface coating parameters, mold surface structural parameters, and mold surface usage parameters, wherein the mold surface physical parameters are specifically the roughness value measured by a surface roughness meter, the glossiness value measured by a gloss meter, the mold X, Y and Z three-dimensional coordinate values ​​measured by a profile meter, and the mold surface color Lab value measured by a colorimeter; the mold surface coating parameters are specifically the coating thickness measured by a coating thickness meter, the coating surface resistance value, the cross-sectional area of ​​the interface between the coating and the substrate, and the load value when the coating is pulled apart and damaged; the mold surface structural parameters are specifically the center coordinates of the mold positioning hole, the diameter of the positioning hole, the pressure applied to the mold surface, the displacement of the mold surface caused by the pressure applied, the mold cavity highlight area measured by a highlight detector, and the total cavity surface area; the mold surface usage parameters are specifically the thermal expansion coefficient of the mold material, the friction coefficient between the glass product and the mold surface, and the projection area of ​​the demolding gap area projected onto the plane;

[0042] Step 3: Analyze various monitoring parameters of the automobile window mold surface classified in step 2, including a mold surface physical index analysis unit, a mold surface coating index analysis unit, a mold surface structure index analysis unit, and a mold surface usage index analysis unit, wherein the mold surface physical index analysis unit is used to calculate the mold surface physical parameters, the mold surface coating index analysis unit is used to calculate the mold surface coating parameters, the mold surface structure index analysis unit is used to calculate the mold surface structure parameters, and the mold surface usage index analysis unit is used to calculate the mold surface usage parameters, and the analysis includes the following steps;

[0043] Step 3.1: Analyze the physical parameters of the mold surface. The geometric characteristics of the mold surface have a direct impact on the quality of the mold surface. They can reflect the degree of undulation of the mold surface, help to judge the newness of the mold or whether maintenance is needed, and help to find out whether the mold surface is contaminated, oxidized or other abnormal conditions. The model for obtaining the mold surface physical performance index in each detection sub-area in the mold surface physical index analysis unit is: Where Ppi i represents the physical performance index of the mold surface in the i-th detection sub-area, Pv represents the mold surface profile, (x j ,y j ,z j ) represents the actual measured three-dimensional coordinates of the jth measurement point on the mold surface profile, (x j0 ,y j0 ,z j0) represents the design standard value of the jth measuring point, j∈m, m represents the number of measuring points on the mold surface, Max() represents the maximum value, l1 represents the measuring instrument influence factor, Gu represents the glossiness of the mold surface, gu j represents the gloss value of the jth mold surface measurement point, l2 represents the gloss measuring instrument influence factor, ΔE represents the color consistency of the mold surface, (L j ,a j ,b j ) represents the L*, a*, b* values ​​of the jth measurement point on the mold surface in the Lab color space, (L j0 ,a j0 ,b j0 ) represents the standard color value of the jth measurement point on the mold surface in the Lab color space, Ra represents the roughness of the mold surface, l3 represents the colorimeter measurement influencing factor, l4 represents the roughness meter measurement influence factor, and Respectively represent the weights of the mold surface profile, the mold surface glossiness and the mold surface color consistency value;

[0044] Step 3.2: Analyze the mold surface coating parameters. The mold surface coating increases the hardness and wear resistance of the mold. The thickness of the coating is an important factor affecting the mold surface quality. The coating with strong adhesion can fit tightly on the mold surface to form an effective protective barrier, thereby extending the service life of the mold. At the same time, the resistivity indirectly affects the wear resistance and hardness of the coating, thereby affecting the scratch and wear resistance of the mold surface. The model for obtaining the mold surface coating performance index in each detection sub-area in the mold surface coating index analysis unit is: Cpi i =(α1×e 1+Ct +α2×lnF)×ln(Rt), where Cpi i represents the performance index of the mold surface coating in the i-th detection sub-area, Ct represents the coating surface thickness, ct j represents the thickness of the coating at the jth mold surface measurement point, β1 represents the measurement influencing factor, F represents the adhesion of the mold surface coating, G represents the load value when the coating is pulled apart and damaged, S represents the cross-sectional area of ​​the interface between the coating and the substrate, and Rt represents the resistivity of the coating surface. R represents the surface resistance value of the coating, β2 represents the resistance measurement influencing factor, α1 and α2 represent the weights of the coating surface thickness and the coating adhesion on the mold surface, respectively;

[0045] Step 3.3: Analyze the mold surface structure parameters. The accuracy of the mold positioning hole directly affects the stability and accuracy of the mold during the mold closing process. The deformation of the mold skeleton will directly affect the shape and size of the mold cavity, which will seriously affect the mold surface quality. The mold surface with a high proportion of highlight area usually has better wear resistance and corrosion resistance. The model for obtaining the mold surface physical performance index in each detection sub-area in the mold surface structure index analysis unit is: Spi i represents the mold surface structure performance index of the i-th detection sub-area, Pa represents the mold positioning hole accuracy, (x c ,y c ,z c ) represents the three-dimensional coordinates of the measurement center of the cth positioning hole, (x c0 ,y c0 ,z c0 ) represents the three-dimensional coordinates of the standard center of the cth positioning hole, D c represents the diameter of the cth positioning hole, Ha represents the area ratio of the highlight area of ​​the mold cavity, s J represents the area of ​​the transverse cavity highlight region at the Jth position, M represents the number of multiple positions, S T represents the total surface area of ​​the mold cavity, Sa represents the deformation of the mold skeleton, d J represents the displacement of the mold surface at the Jth position due to the applied pressure, f represents the applied pressure value, η1 and η2 represent the weights of the mold positioning hole accuracy and the proportion of the mold cavity highlight area respectively;

[0046] Step 3.4: Analyze the mold surface usage parameters. The size of the demoulding angle directly affects the smoothness of the mold surface. The proportion of scratches on the automobile window mold surface can quantitatively evaluate the scratches on the automobile window mold surface and provide a decision-making basis for subsequent mold maintenance, repair or replacement. The model for obtaining the mold surface usage performance index in each detection sub-area in the mold surface usage index analysis unit is: Upi i represents the mold surface performance index of the i-th detection sub-area, Fda represents the mold surface demoulding angle suitability, Fda=ln[arctan(μ)+θ], μ represents the friction coefficient between the glass product and the mold surface, θ represents the demoulding angle safety margin, Sap represents the demoulding shrinkage area ratio,

[0047] sh represents the projection area of ​​the demoulding gap area onto the plane, S T It represents the total surface area of ​​the mold cavity, Tda represents the contour deformation during the heating process of the mold, Pv houIndicates the profile after heating, Pv qian It represents the contour before heating, Co represents the thermal expansion coefficient of the mold material, and They represent the proportion of the demoulding angle and the contour deformation during heating respectively;

[0048] Step 4: Evaluate each index of the automobile mold surface quality detection analyzed in step 3 to obtain a comparative evaluation result, including the following steps;

[0049] Step 4.1: Obtain the mold surface physical performance index analysis calculation results Ppi for each detection sub-area in the mold surface physical index analysis unit i Substituting into the formula: in Indicates the similarity of mold surface physical performance index evaluation, Ppi represents the set value, Ppi i represents the physical performance index of the mold surface in the i-th detection sub-area;

[0050] Step 4.2: Obtain the mold surface coating performance index analysis calculation result Cpi from each detection sub-area in the mold surface coating index analysis unit i Substituting into the formula: in Indicates the similarity of the physical coating performance index evaluation of the mold surface. Cpi indicates the set value. i represents the performance index of the mold surface coating in the i-th detection sub-area;

[0051] Step 4.3: Obtain the mold surface physical performance index analysis calculation results Spi from each detection sub-area in the mold surface structure index analysis unit i Substituting into the formula: in Indicates the similarity of the mold surface structure performance index evaluation, Spi represents the set value, Spi i represents the mold surface structure performance index of the i-th detection sub-area;

[0052] Step 4.4: Obtain the mold surface usage performance index analysis calculation result Upi from each detection sub-area in the mold surface usage index analysis unit i Substituting into the formula: in Indicates the similarity of the mold surface performance index evaluation, Upi indicates the set value, Upi i represents the mold surface performance index of the i-th detection sub-area;

[0053] Step 5: Comprehensively analyze the comparative evaluation results of various quality inspection indexes calculated in step 4 to obtain the comprehensive indicators of mold surface quality inspection. The comprehensive analysis model is: Tci represents the comprehensive index of mold surface quality inspection, ξ1, ξ2, ξ3 and ξ4 represent the weights of the similarity of each quality inspection index evaluation, Indicates the similarity of mold surface physical performance index evaluation, Indicates the similarity of the physical coating performance index evaluation on the mold surface. Indicates the similarity of mold surface structure performance index evaluation, Indicates the similarity of the mold surface evaluation using performance index;

[0054] Step 6: Perform human-computer interaction on the comprehensive indicators of mold surface quality inspection obtained by comprehensive analysis in step 5. When the comprehensive indicators are within the set allowable range, it means that the mold surface quality is qualified. If the comprehensive indicators exceed the allowable range, the inspection personnel are prompted to take timely measures to strictly control and inspect the physical performance indicators to ensure that the surface quality of the mold meets the design requirements; focus on the thickness, adhesion, resistivity and other aspects of the coating to ensure the performance and service life of the mold; strictly control the accuracy of the mold positioning holes, focus on the rigidity and stability of the mold skeleton, and take effective measures to reduce the deformation of the mold skeleton to ensure the surface quality and production efficiency of the mold.

[0055] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

[0056] The above contents are merely examples and explanations of the concept of the present invention. The technicians in this technical field 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 claims, they should all fall within the protection scope of the present invention.

Claims

1. A method for detecting the surface quality of automobile window molds, characterized in that: The following steps are involved: Step 1: Determine the automobile window mold to be inspected as the target area, and divide the target area into several sub-areas according to each automobile window mold; Step 2: Classify the monitoring parameters of the several sub-areas divided in step 1 to obtain the monitoring parameters of the surface quality inspection of the automobile window mold; The monitoring parameters include target area information, inspection personnel identity authentication information, mold surface physical parameters, mold surface coating parameters, mold surface structural parameters, and mold surface usage parameters, wherein the mold surface physical parameters are specifically the roughness value measured by a surface roughness meter, the glossiness value measured by a gloss meter, the mold X, Y and Z three-dimensional coordinate values ​​measured by a profile meter, and the mold surface color Lab value measured by a colorimeter; the mold surface coating parameters are specifically the coating thickness measured by a coating thickness meter, the coating surface resistance value, the cross-sectional area of ​​the interface between the coating and the substrate, and the load value when the coating is pulled apart and damaged; the mold surface structural parameters are specifically the center coordinates of the mold positioning hole, the diameter of the positioning hole, the pressure applied to the mold surface, the displacement of the mold surface caused by the pressure applied, the mold cavity highlight area measured by a highlight detector, and the total cavity surface area; the mold surface usage parameters are specifically the thermal expansion coefficient of the mold material, the friction coefficient between the glass product and the mold surface, and the projection area of ​​the demolding gap area projected onto the plane; Step 3: Analyze various monitoring parameters of the automobile window mold surface classified in step 2 to obtain various indexes for automobile mold surface quality detection; The model for obtaining the mold surface physical performance index in each detection sub-area in each index of the automobile mold surface quality detection is: Where Ppi i represents the physical performance index of the mold surface in the i-th detection sub-area, Pv represents the mold surface profile, (x j ,y j ,z j ) represents the actual measured three-dimensional coordinates of the jth measurement point on the mold surface profile, (x j0 ,y j0 ,z j0 ) represents the design standard value of the jth measuring point, j∈m, m represents the number of measuring points on the mold surface, Max() represents the maximum value, l1 represents the measuring instrument influence factor, Gu represents the glossiness of the mold surface, gu j represents the gloss value of the jth mold surface measurement point, l2 represents the gloss measuring instrument influence factor, ΔE represents the color consistency of the mold surface, (L j ,a j ,b j ) represents the L*, a*, b* values ​​of the jth measurement point on the mold surface in the Lab color space, (L j0 ,a j0 ,b j0 ) represents the standard color value of the jth measurement point on the mold surface in the Lab color space, Ra represents the roughness of the mold surface, l3 represents the colorimeter measurement influencing factor, l4 represents the roughness meter measurement influence factor, and Respectively represent the weights of the mold surface profile, the mold surface glossiness and the mold surface color consistency value; The model for obtaining the mold surface coating performance index in each detection sub-area in the automobile mold surface quality detection index is: Cpi i =(α1×e 1+Ct +α2×lnF)×ln(Rt), where Cpi i represents the performance index of the mold surface coating in the i-th detection sub-area, Ct represents the coating surface thickness, ct j represents the thickness of the coating at the jth mold surface measurement point, β1 represents the measurement influencing factor, F represents the adhesion of the mold surface coating, G represents the load value when the coating is pulled apart and damaged, S represents the cross-sectional area of ​​the interface between the coating and the substrate, and Rt represents the resistivity of the coating surface. R represents the surface resistance value of the coating, β2 represents the resistance measurement influencing factor, α1 and α2 represent the weights of the coating surface thickness and the coating adhesion on the mold surface, respectively; The model for obtaining the mold surface physical performance index in each detection sub-area in each index of the automobile mold surface quality detection is: Spi i represents the mold surface structure performance index of the i-th detection sub-area, Pa represents the mold positioning hole accuracy, (x c ,y c ,z c ) represents the three-dimensional coordinates of the measurement center of the cth positioning hole, (x c0 ,y c0 ,z c0 ) represents the three-dimensional coordinates of the standard center of the cth positioning hole, D c represents the diameter of the cth positioning hole, Ha represents the area ratio of the highlight area of ​​the mold cavity, s J represents the area of ​​the transverse cavity highlight region at the Jth position, M represents the number of multiple positions, S T represents the total surface area of ​​the mold cavity, Sa represents the deformation of the mold skeleton, d J represents the displacement of the mold surface at the Jth position due to the applied pressure, f represents the applied pressure value, η1 and η2 represent the weights of the mold positioning hole accuracy and the proportion of the mold cavity highlight area respectively; The model for obtaining the mold surface performance index in each detection sub-area in each index of the automobile mold surface quality detection is: Upi i represents the mold surface performance index of the i-th detection sub-area, Fda represents the mold surface demoulding angle suitability, Fda=ln[arctan(μ)+θ], μ represents the friction coefficient between the glass product and the mold surface, θ represents the demoulding angle safety margin, Sap represents the demoulding shrinkage area ratio, sh represents the projection area of ​​the demoulding gap area onto the plane, S T It represents the total surface area of ​​the mold cavity, Tda represents the contour deformation during the heating process of the mold, Pv hou Indicates the profile after heating, Pv qian It represents the contour before heating, Co represents the thermal expansion coefficient of the mold material, and They represent the proportion of the demoulding angle and the contour deformation during heating respectively; Step 4: Evaluate each index of the automobile mold surface quality inspection analyzed in step 3 to obtain comparative evaluation results; The comparative evaluation results include the following steps: Step 4.1: Obtain the mold surface physical performance index analysis calculation results Ppi for each detection sub-area in the mold surface physical index analysis unit i Substituting into the formula: in Indicates the similarity of mold surface physical performance index evaluation, Ppi represents the set value, Ppi i represents the physical performance index of the mold surface in the i-th detection sub-area; Step 4.2: Obtain the mold surface coating performance index analysis calculation result Cpi from each detection sub-area in the mold surface coating index analysis unit i Substituting into the formula: in Indicates the similarity of the physical coating performance index evaluation of the mold surface. Cpi indicates the set value. i represents the performance index of the mold surface coating in the i-th detection sub-area; Step 4.3: Obtain the mold surface physical performance index analysis calculation results Spi from each detection sub-area in the mold surface structure index analysis unit i Substituting into the formula: in Indicates the similarity of the mold surface structure performance index evaluation, Spi represents the set value, Spi i represents the mold surface structure performance index of the i-th detection sub-area; Step 4.4: Obtain the mold surface usage performance index analysis calculation result Upi from each detection sub-area in the mold surface usage index analysis unit i Substituting into the formula: in Indicates the similarity of the mold surface performance index evaluation, Upi indicates the set value, Upi i represents the mold surface performance index of the i-th detection sub-area; Step 5: Perform a comprehensive analysis on the comparative evaluation results of various quality inspection indexes calculated in step 4 to obtain a comprehensive index for mold surface quality inspection; The comprehensive analysis model of the mold surface quality inspection comprehensive index is: Where Tci represents the comprehensive index of mold surface quality inspection, ξ1, ξ2, ξ3 and ξ4 represent the weights of the similarity of each quality inspection index evaluation. Indicates the similarity of mold surface physical performance index evaluation, Indicates the similarity of the physical coating performance index evaluation on the mold surface. Indicates the similarity of mold surface structure performance index evaluation, Indicates the similarity of the mold surface evaluation using performance index; Step 6: Perform human-computer interaction on the comprehensive indicators of mold surface quality inspection obtained through comprehensive analysis in step 5.

Images