Sand blasting process management method, electronic equipment and storage medium

Abstract

The embodiment of the invention provides a sand blasting process management method, electronic equipment and a storage medium, and the method comprises the steps: collecting at least one sand blasting parameter of sand blasting equipment, and if the at least one sand blasting parameter is within a preset parameter range, determining that the at least one sand blasting parameter is normal; collecting a detection result of the workpiece subjected to sand blasting treatment by the sand blasting equipment, and if the detection result is within a preset standard range, determining that the sand blasting equipment works normally; and extracting feature data of the detection result, and adjusting the at least one sand blasting parameter based on the feature data. According to the embodiment, normal work of the sand blasting equipment can be guaranteed, the sand blasting parameters are adjusted based on the feature data of the workpiece detection result, the parameter adjusting efficiency is improved, and then the management efficiency of the sand blasting process is improved.

Description

Technical Field

[0001] The present application relates to the field of sandblasting technology, and in particular to a sandblasting process management method, electronic equipment and storage medium. Background Art

[0002] Sandblasting is a workpiece surface treatment process, which is widely used in workpiece surface cleaning, roughening, beautification, etc. The sandblasting process uses compressed air as a power to form a high-speed jet beam, and sprays copper ore sand, quartz sand and other materials at high speed onto the workpiece surface, so that the outer surface or shape of the workpiece surface changes. Related technologies usually use sandblasting robots to perform sandblasting. Operators pre-set the parameters of the sandblasting robot based on the operating requirements, such as spray gun pressure, spray gun movement speed, spray gun angle, etc. During the sandblasting operation, operators may also need to monitor and manually adjust the parameters of the sandblasting robot in real time to adapt to specific operating conditions or workpiece surface conditions. However, the manually set and adjusted parameter setting method lacks flexibility and is difficult to adapt to complex and changing operating environments. Manual parameter adjustment is time-consuming and inefficient. Summary of the invention

[0003] In view of this, it is necessary to provide a sandblasting process management method, electronic equipment and storage medium to solve the problem that manual setting and adjustment of sandblasting equipment parameters lacks flexibility, is time-consuming and inefficient.

[0004] In a first aspect, an embodiment of the present application provides a sandblasting process management method, which is applied to electronic equipment, and the method includes: collecting at least one sandblasting parameter of a sandblasting device, and if the at least one sandblasting parameter is within a preset parameter range, determining that the at least one sandblasting parameter is normal; collecting a detection result of a workpiece sandblasted by the sandblasting device, and if the detection result is within a preset standard range, determining that the sandblasting device is working normally; extracting feature data of the detection result, and adjusting the at least one sandblasting parameter based on the feature data.

[0005] In a possible implementation, the at least one sandblasting parameter includes a moving speed of a spray gun of the sandblasting equipment, and if the at least one sandblasting parameter is within a preset parameter range, determining that the at least one sandblasting parameter is normal includes: determining whether the moving speed is less than or equal to a preset moving speed threshold; if the moving speed is less than or equal to the preset moving speed threshold, determining that the moving speed is normal; if the moving speed is greater than the preset moving speed threshold, determining that the moving speed is abnormal.

[0006] In a possible implementation, the at least one sandblasting parameter also includes the swing amplitude of the spray gun, and if the at least one sandblasting parameter is within a preset parameter range, determining that the at least one sandblasting parameter is normal also includes: if the moving speed is less than or equal to the preset moving speed threshold, judging whether the swing amplitude is less than or equal to the preset swing amplitude threshold; if the swing amplitude is less than or equal to the preset swing amplitude threshold, determining that the swing amplitude is normal; if the swing amplitude is greater than the preset swing amplitude threshold, determining that the swing amplitude is abnormal.

[0007] In a possible implementation, the at least one sandblasting parameter also includes the air pressure of the spray gun, and if the at least one sandblasting parameter is within a preset parameter range, determining that the at least one sandblasting parameter is normal also includes: if the swing amplitude is less than or equal to the preset swing amplitude threshold, judging whether the pressure gauge of the sandblasting equipment is in an on state; if the pressure gauge is in an on state, judging whether the air pressure is less than or equal to the preset air pressure threshold; if the air pressure is greater than the preset air pressure threshold, determining that the air pressure is abnormal; if the air pressure is less than or equal to the preset air pressure threshold, judging whether the air pressure is the same as the previous air pressure; if the air pressure is different from the previous air pressure, determining that the air pressure is normal; if the air pressure is the same as the previous air pressure, accumulating the number of times the air pressure is the same, and if the number of times the air pressure is the same reaches a preset number, determining that the air pressure is abnormal.

[0008] In a possible implementation, the method further includes: if the moving speed or the swing amplitude is 0, determining the current state of the sandblasting equipment; if the sandblasting equipment is in an automatic or manual state, continuing to determine whether the swing amplitude is 0; if the swing amplitude is not 0, determining that the swing amplitude is abnormal; if the swing amplitude is 0, continuing to determine the current state of the sandblasting equipment; if the sandblasting equipment is in an automatic or manual state, continuing to determine whether the air pressure is 0; if the air pressure is not 0, determining that the air pressure is abnormal; if the air pressure is 0, continuing to determine the current state of the sandblasting equipment; if the sandblasting equipment is in an automatic or manual state, determining that the sandblasting equipment has a blockage abnormality.

[0009] In a possible implementation, the detection result includes the glossiness of the workpiece, and if the detection result is within a preset standard range, determining that the sandblasting equipment is operating normally includes: judging whether the glossiness is within a preset glossiness range; if the glossiness is within the preset glossiness range, determining that the sandblasting equipment is operating normally; if the glossiness is not within the preset glossiness range, determining that the sandblasting equipment is operating abnormally.

[0010] In one possible implementation, extracting characteristic data of the detection result and adjusting the at least one sandblasting parameter based on the characteristic data include: calculating the difference between the glossiness of multiple points on the first surface of the workpiece and the glossiness of multiple points on the second surface; determining the identification of the difference based on a preset difference range in which the difference lies; calculating the total number of the identifications and the percentage of each identification; analyzing the distribution concentration of the difference based on the total number of the identifications and the percentage of each identification; and adjusting the at least one sandblasting parameter based on the distribution concentration of the difference.

[0011] In a possible implementation, extracting characteristic data of the detection result and adjusting the at least one sandblasting parameter based on the characteristic data include: calculating a first glossiness average of multiple position points on the first surface of the workpiece and a second glossiness average of multiple position points on the second surface; analyzing daily glossiness average change of each position point and glossiness average difference of different position points based on the first glossiness average and the second glossiness average; determining critical data of glossiness average based on daily glossiness average change of each position point and glossiness average difference of different position points, and adjusting the at least one sandblasting parameter based on the critical data of glossiness average.

[0012] In a possible implementation, the method further includes: counting the processing time of each workpiece in each step in the sandblasting process; counting the number of workpieces, the percentage of the number of workpieces and the mean processing time corresponding to each processing time interval of each step; if the percentage of the number of workpieces is within a preset percentage range, determining that the processing time of the workpiece is normal; and adjusting at least one sandblasting parameter based on the mean processing time of the same workstation on different production lines.

[0013] In a possible implementation, the method further includes: respectively calculating the mean and standard deviation of the sandblasting parameters and the test results; determining the normal value range of at least one sandblasting parameter and the test results based on the mean and standard deviation; and eliminating the sandblasting parameters and the test results that are not within the normal value range.

[0014] In a second aspect, an embodiment of the present application provides an electronic device, which includes a processor and a memory, wherein the memory is used to store instructions, and the processor is used to call the instructions in the memory so that the electronic device executes the above-mentioned sandblasting process management method.

[0015] In a third aspect, an embodiment of the present application provides a computer-readable storage medium, including computer instructions, which, when executed on an electronic device, enables the electronic device to execute the above-mentioned sandblasting process management method.

[0016] The sandblasting process management method, electronic device and storage medium provided in the embodiments of the present application can determine whether the sandblasting parameters are normal based on a preset parameter range, and determine whether the sandblasting equipment is working normally based on the comparison between the inspection results of the workpiece and the preset standard range, thereby effectively ensuring the normal operation of the sandblasting equipment, and adjusting the sandblasting parameters based on the characteristic data of the workpiece inspection results. There is no need to manually adjust the parameters, which improves the parameter adjustment efficiency and thereby improves the management efficiency of the sandblasting process. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0018] Figure 1 A schematic diagram of an application scenario of a sandblasting process management method provided in one embodiment of the present application.

[0019] Figure 2 A flow chart of a sandblasting process management method provided in one embodiment of the present application.

[0020] Figure 3 A flow chart of sandblasting parameter determination provided in one embodiment of the present application.

[0021] Figure 4 A workpiece processing time table is provided for an embodiment of the present application.

[0022] Figure 5 This is a flow chart of a sandblasting process management device provided in one embodiment of the present application.

[0023] Figure 6 A schematic diagram of the structure of an electronic device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0024] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application is described in detail below with reference to the accompanying drawings and specific embodiments.

[0025] It should be noted that in this application, "at least one" means one or more, and "more than one" means two or more than two. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural. The terms "first", "second", "third", "fourth", etc. (if any) in the specification, claims and drawings of this application are used to distinguish similar objects, rather than to describe a specific order or sequence.

[0026] In the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a concrete way. The following embodiments and features in the embodiments may be combined with each other without conflict.

[0027] Sandblasting is a workpiece surface treatment process, which is widely used in workpiece surface cleaning, roughening, beautification, etc. The sandblasting process uses compressed air as a power to form a high-speed jet beam, and sprays copper ore sand, quartz sand and other materials at high speed onto the workpiece surface, so that the outer surface or shape of the workpiece surface changes. Related technologies usually use sandblasting robots to perform sandblasting. Operators pre-set the parameters of the sandblasting robot based on the operating requirements, such as spray gun pressure, spray gun movement speed, spray gun angle, etc. During the sandblasting operation, operators may also need to monitor and manually adjust the parameters of the sandblasting robot in real time to adapt to specific operating conditions or workpiece surface conditions. However, the manually set and adjusted parameter setting method lacks flexibility and is difficult to adapt to complex and changing operating environments. Manual parameter adjustment is time-consuming and inefficient.

[0028] The embodiment of the present application provides a sandblasting process management method, which can determine whether the sandblasting parameters are normal based on a preset parameter range, and determine whether the sandblasting equipment is working normally based on the comparison between the inspection results of the workpiece and the preset standard range, effectively ensuring the normal operation of the sandblasting equipment, and adjusting the sandblasting parameters based on the characteristic data of the workpiece inspection results. There is no need to manually adjust the parameters, which improves the parameter adjustment efficiency and thereby improves the management efficiency of the sandblasting process.

[0029] See also Figure 1 , which is a schematic diagram of the application environment of the sandblasting process management method provided in one embodiment of the present application. Figure 1The sandblasting process management system 100 shown includes but is not limited to: an electronic device 1 and a plurality of sandblasting devices 2. The electronic device 1 and the sandblasting devices 2 are connected to each other through a wireless network or a wired network. In an embodiment of the present application, the electronic device 1 and the plurality of sandblasting devices 2 constitute the hardware architecture of the sandblasting process management system. The electronic device 1 may be a server or a personal computer, and the electronic device 1 may deploy a computer program product (such as software code, computer-readable instructions, etc.) programmed and implemented according to the sandblasting process management method provided in an embodiment of the present application, thereby providing sandblasting process management services. The sandblasting device 2 may be a sandblasting robot, including sandblasting components such as a spray gun.

[0030] See also Figure 2 The figure is a flow chart of a sandblasting process management method provided by an embodiment of the present application. The method is applied to Figure 1 In the electronic device shown, the sandblasting process management method includes: S101, collecting at least one sandblasting parameter of a sandblasting device.

[0031] In one embodiment of the present application, at least one sandblasting parameter includes but is not limited to: the moving speed, swing amplitude, and air pressure of the spray gun of the sandblasting device. At least one sandblasting parameter of multiple sandblasting devices can be collected based on a preset period, so as to obtain multiple data corresponding to each sandblasting parameter of each sandblasting device. For example, the preset period can be 10 seconds, 20 seconds, 30 seconds, or other values.

[0032] In one embodiment of the present application, the 3-sigma criterion can be used to filter the data corresponding to each sandblasting parameter. The sandblasting parameter data set usually conforms to the normal distribution, and the mean μ of the multiple data corresponding to each sandblasting parameter is calculated. 1 and standard deviation σ 1 , based on the mean μ 1 and standard deviation σ 1 Determine the normal value range of the sandblasting parameter data, for example, the normal value range is (μ 1 -3σ 1 , μ 1 +3σ 1 ), determine the sandblasting parameter data within the normal value range as normal data, determine the sandblasting parameter data outside the normal value range as abnormal data, and eliminate the abnormal data.

[0033] S102, determining that at least one sandblasting parameter is within a preset parameter range. If at least one sandblasting parameter is within the preset parameter range, the process proceeds to S103; if at least one sandblasting parameter is not within the preset parameter range, determining that at least one sandblasting parameter is abnormal.

[0034] In one embodiment of the present application, the sandblasting parameter data collected in each preset period is judged. If all the sandblasting parameter data are within the preset parameter range, the sandblasting parameter is determined to be normal. If any of the sandblasting parameter data is not within the preset parameter range, the corresponding sandblasting parameter is determined to be abnormal.

[0035] See also Figure 3 As shown, it is a flow chart of sandblasting parameter judgment provided by an embodiment of the present application.

[0036] S1021, determine whether the moving speed is less than or equal to the preset moving speed threshold. If the moving speed is less than or equal to the preset moving speed threshold, it is determined that the moving speed is normal, and the process enters S1023; if the moving speed is greater than the preset moving speed threshold, the process enters S1022. For example, the preset moving speed threshold can be 1m / min (meter per minute), 2m / min, 3m / min.

[0037] S1022, determining that the moving speed is abnormal.

[0038] S1023, determine whether the swing amplitude is less than or equal to the preset swing amplitude threshold. If the swing amplitude is less than or equal to the preset swing amplitude threshold, it is determined that the swing amplitude is normal, and the process enters S1025; if the swing amplitude is greater than the preset swing amplitude threshold, the process enters S1024. For example, the preset swing amplitude threshold can be 6cm, 8cm, or 10cm.

[0039] S1024, determining that the swing amplitude is abnormal.

[0040] S1025, determining whether the pressure gauge of the sandblasting equipment is in the on state. If the pressure gauge is in the on state, the process proceeds to S1027; if the pressure gauge is in the off state, the process proceeds to S1026.

[0041] S1026, returning a preset flag, the preset flag is used to indicate that the barometer is in the off state. For example, the preset flag is 0.

[0042] S1027, determine whether the air pressure is less than or equal to the preset air pressure threshold. If the air pressure is less than or equal to the preset air pressure threshold, it is determined that the air pressure is normal, and the process enters S1029; if the air pressure is greater than the preset air pressure threshold, the process enters S1028. For example, the preset air pressure threshold can be 0.4Mpa, 0.5Mpa, 0.6Mpa.

[0043] S1028, determining that the air pressure is abnormal.

[0044] S1029, determine whether the air pressure is the same as the previous air pressure. The previous air pressure is the air pressure data collected last time. If the air pressure is different from the previous air pressure, it is determined that the air pressure is normal, and the process enters S1030. If the air pressure is the same as the previous air pressure, the process enters S1031.

[0045] S1030, determining that the sandblasting parameters of the sandblasting equipment are normal.

[0046] S1031, accumulating the number of times when the air pressure is the same.

[0047] S1032: If the number of times the air pressure is the same reaches a preset number, it is determined that the air pressure is abnormal. For example, the preset number may be 3, 5, or 7.

[0048] In another embodiment of the present application, while or before determining whether the moving speed is less than or equal to the preset moving speed threshold, it is also determined whether the moving speed is 0, and while or before determining whether the swing amplitude is less than or equal to the preset swing amplitude threshold, it is determined whether the swing amplitude is 0. If the moving speed or the swing amplitude is 0, the current state of the sandblasting equipment is determined. The state of the sandblasting equipment includes but is not limited to: shutdown state, fault state, offline state, automatic state and manual state. The shutdown state is the state of the sandblasting equipment when it is not working. At this time, the equipment stops running completely, and the power supply and gas supply are cut off. The fault state is that the sandblasting equipment is in a state where the sandblasting operation cannot be performed normally. The offline state means that although the sandblasting equipment has stopped production activities, it still remains on standby so as to quickly resume production. The automatic state means that the sandblasting equipment automatically runs according to the preset procedures and parameters without manual intervention. In the automatic state, the sandblasting equipment can continuously sandblast, and the operator only needs to start and monitor the equipment. The manual state means that the sandblasting equipment requires the operator to manually control each operation step, including opening and closing the spray gun, adjusting the sandblasting parameters, etc.

[0049] If the sandblasting equipment is in a shutdown state, a fault state or an offline state, return to the state of the sandblasting equipment. If the sandblasting equipment is in an automatic or manual state, continue to determine whether the swing amplitude is 0. If the swing amplitude is not 0, determine that the swing amplitude is abnormal. If the swing amplitude is 0, continue to determine the current state of the sandblasting equipment. If the sandblasting equipment is in a shutdown state, a fault state or an offline state, return to the state of the sandblasting equipment. If the sandblasting equipment is in an automatic or manual state, determine whether the air pressure is 0. If the air pressure is not 0, determine that the air pressure is abnormal. If the air pressure is 0, continue to determine the current state of the sandblasting equipment. If the sandblasting equipment is in a shutdown state, a fault state or an offline state, return to the state of the sandblasting equipment. If the sandblasting equipment is in an automatic or manual state, determine that the sandblasting equipment has a blockage abnormality. In one embodiment of the present application, returning to the state of the sandblasting equipment refers to displaying the state of the sandblasting equipment on the display screen of the electronic device.

[0050] S103, determining whether at least one sandblasting parameter is normal.

[0051] S104, determining that at least one sandblasting parameter is abnormal.

[0052] S105, collecting the detection result of the workpiece subjected to sandblasting by the sandblasting equipment.

[0053] In one embodiment of the present application, the inspection results of the workpiece include but are not limited to: glossiness, roughness, uniformity, and cleanliness of the workpiece surface. The inspection results of multiple workpieces blasted by multiple sandblasting devices can be collected based on a preset period, so as to obtain the inspection results of multiple workpieces blasted by each sandblasting device.

[0054] In one embodiment of the present application, the 3-sigma criterion can be used to filter the detection result data of each workpiece. The detection result data set of the workpiece usually conforms to the normal distribution, and the mean μ of the detection result data of multiple workpieces is calculated. 2 and standard deviation σ 2 , based on the mean μ 2 and standard deviation σ 2 Determine the normal value range of the test result data, for example, the normal value range is (μ 2 -3σ 2 , μ 2 +3σ 2 ), determine the test results within the normal value range as normal data, determine the test result data outside the normal value range as abnormal data, and eliminate the abnormal data.

[0055] S106, judging whether the test result is within the preset standard range. If the test result is within the preset standard range, the process proceeds to S107; if the test result is not within the preset standard range, the process proceeds to S108.

[0056] In one embodiment of the present application, taking the detection result as glossiness as an example, it is determined whether the glossiness is within the preset glossiness range. If the glossiness is within the preset glossiness range, it is determined that the sandblasting equipment is working normally; if the glossiness is not within the preset glossiness range, it is determined that the sandblasting equipment is working abnormally. For example, the preset glossiness range is (20, 50) GU, where GU is a gloss unit. The workpiece surface may include multiple position points, and the glossiness of the workpiece surface may be the average glossiness of multiple position points, or the glossiness of any position point.

[0057] In one embodiment of the present application, the glossiness of the workpiece surface can be measured by a glossiness detection device (such as a glossiness tester), and the glossiness detection device calculates the glossiness by emitting a light beam to the workpiece surface and measuring the intensity of the reflected light. For example, the glossiness is the difference between the reflected light energy (luminous flux) and the reflected light energy (luminous flux) of a standard black glass sample in the same reflection direction.

[0058] S107, confirm that the sandblasting equipment is working properly.

[0059] S108, determining that the sandblasting equipment is operating abnormally.

[0060] S109, extracting characteristic data of the detection result, and adjusting at least one sandblasting parameter based on the characteristic data.

[0061] In one embodiment of the present application, the difference between the detection results of multiple positions on the first surface of the workpiece and the detection results of multiple positions on the second surface is calculated, the identification of the difference is determined based on the preset difference range in which the difference is located, the total number of identifications and the percentage of each identification are calculated, the distribution concentration of the difference is analyzed based on the total number of identifications and the percentage of each identification, and at least one sandblasting parameter is adjusted based on the distribution concentration of the difference. For example, based on the percentage of each identification, the preset difference range with the largest percentage is determined, that is, the range with the highest distribution concentration of the difference, and it is determined whether the preset difference range with the largest percentage is a normal difference range. If the preset difference range with the largest percentage is not a normal difference range, at least one sandblasting parameter is adjusted.

[0062] For example, the detection result is the glossiness of the workpiece surface, the difference between the glossiness of multiple points on the first surface of the workpiece and the glossiness of multiple points on the second surface is calculated, the identification of the difference is determined based on the preset difference range in which the difference is located, the total number of identifications and the percentage of each identification are calculated, the distribution concentration of the difference is analyzed based on the total number of identifications and the percentage of each identification, and at least one sandblasting parameter is adjusted based on the distribution concentration of the difference. Among them, the correspondence between multiple first points on the first surface and multiple second points on the second surface can be established in advance, and multiple glossiness differences can be obtained by calculating the difference between the glossiness of each first point and the glossiness of the corresponding second point.

[0063] For example, the workpiece is a mobile phone, and the first surface is a large surface, that is, the surface with the largest area on the workpiece, such as the display surface of a mobile phone. The second surface is a side surface, such as the plane where the power button of the mobile phone is located. The preset difference range includes but is not limited to: the first preset difference range (2, +∞), the second preset difference range (1, 2], the third preset difference range (0, 1], the fourth preset difference range (-1, 0], the fifth preset difference range (-2, -1]. The first preset difference range and the fifth preset difference range are abnormal difference ranges, and the second to fourth are normal difference ranges. The first preset difference range corresponds to an identifier 1, the second preset difference range corresponds to an identifier 2, the third preset difference range corresponds to an identifier 3, the fourth preset difference range corresponds to an identifier 4, and the fifth preset difference range corresponds to an identifier 5. Based on the total number of identifiers and the percentage of each identifier, the preset difference range with the most difference distribution is determined, and at least one sandblasting parameter is adjusted based on the preset difference range with the most difference distribution.

[0064] In one embodiment of the present application, the sandblasting parameters of the sandblasting equipment for processing workpieces whose preset difference range of gloss difference distribution is the largest and is not the normal difference range can be adjusted to be the same as the sandblasting parameters of the sandblasting equipment for processing workpieces whose preset difference range of gloss difference distribution is the largest and is the normal difference range. In another embodiment of the present application, multiple sample data of sandblasting parameters and multiple sample data of gloss difference distribution concentration can also be used as training data to train and establish a machine learning model, such as a neural network model, a support vector machine model, a random forest model, etc. The sandblasting parameters are the input data of the machine learning model, and the distribution concentration of the gloss difference is the predicted data (i.e., output data) of the machine learning model, so that by adjusting the sandblasting parameters, the preset difference range with the largest gloss difference distribution concentration predicted by the machine learning model is the normal difference range.

[0065] In another embodiment of the present application, a first gloss average of multiple positions on the first surface of a workpiece and a second gloss average of multiple positions on the second surface are calculated, a third gloss average of the same positions on the first surfaces of different workpieces is calculated, and a fourth gloss average of the same positions on the second surfaces of different workpieces is calculated. Based on the first gloss average, the second gloss average, the third gloss average and the fourth gloss average, the daily gloss average change of each position point and the difference in gloss averages at different positions and on different workpiece surfaces are analyzed. Based on the daily gloss average change of each position point, the difference in gloss averages at different positions and on different workpiece surfaces, and the critical data of the gloss average, at least one sandblasting parameter is adjusted.

[0066] The critical data of the gloss mean is the boundary value at which the gloss mean or the gloss mean difference changes from normal to abnormal. After determining the critical data of the gloss mean, the sandblasting parameter corresponding to the critical data of the gloss mean is obtained, and at least one sandblasting parameter is adjusted based on the sandblasting parameter corresponding to the critical data. For example, the sandblasting parameter is adjusted to be not close to the sandblasting parameter corresponding to the gloss critical data.

[0067] In another embodiment of the present application, multiple sample data of sandblasting parameters, multiple sample data of gloss mean, and multiple sample data of gloss mean difference can be used as training data to train and establish a machine learning model, such as a neural network model, a support vector machine model, a random forest model, etc., so that by adjusting the sandblasting parameters, the gloss mean predicted by the machine learning model is less than or equal to the critical data of the gloss mean, and the gloss mean difference predicted by the machine learning model is less than or equal to the critical data of the gloss mean difference.

[0068] In one embodiment of the present application, the method also includes: counting the processing time of each workpiece in each step in the sandblasting process, counting the number of workpieces, the percentage of the number of workpieces and the average processing time corresponding to each processing time interval of each step, if the percentage of the number of workpieces is within a preset percentage range, determining that the processing time of the workpiece is normal, and adjusting at least one sandblasting parameter based on the average processing time of the same workstation on different production lines.

[0069] See also Figure 4 As shown, it is a workpiece processing time table provided by an embodiment of the present application. Taking the scanning process as an example, the processing time interval is divided into 0-10 seconds, 10-20 seconds, 20-30 seconds, 30-60 seconds, 60-600 seconds, and more than 600 seconds. It is judged whether the percentage of the number of workpieces corresponding to each processing time interval is within the corresponding preset percentage range. If the percentage of the number of workpieces corresponding to each processing time interval is within the corresponding preset percentage range, it is determined that the processing time of the workpiece is normal. For example, for the scanning point 00:e0:4c:04:d1:19, the number of workpieces corresponding to the processing time interval 0-10 seconds is 921, the total number of workpieces is 1853, the percentage of the number of workpieces corresponding to the processing time interval 0-10 seconds is 49.7%, the preset percentage range corresponding to the processing time interval 0-10 seconds is 40%-60%, and the percentage of the number of workpieces corresponding to the processing time interval 0-10 seconds is within the corresponding preset percentage range. It is determined that the processing time of the workpiece corresponding to the processing time interval 0-10 seconds is normal.

[0070] In one embodiment of the present application, the mean processing time corresponding to the same processing time interval of the same workstation on different production lines is obtained, the workstation with the smallest mean processing time is determined, and the sandblasting parameters of the sandblasting equipment in other workstations are adjusted to the sandblasting parameters of the sandblasting equipment in the workstation with the smallest mean processing time. For example, the mean processing time corresponding to the processing time interval of 0-10 seconds of workstation 1 on production line 1 is 2.97 seconds, and the mean processing time corresponding to the processing time interval of 0-10 seconds of workstation 1 on production line 2 is 5.12 seconds, then the sandblasting parameters of the sandblasting equipment in workstation 1 of production line 2 are adjusted to the sandblasting parameters of the sandblasting equipment in workstation 1 of production line 1.

[0071] In one embodiment of the present application, the method further includes: displaying abnormal prompt information on a display screen of an electronic device, and displaying the sandblasting parameters and workpiece detection results collected in real time. For example, when the movement speed of the spray gun is abnormal, the swing amplitude is abnormal, or the air pressure is abnormal, or when there is material blockage in the sandblasting equipment, the corresponding abnormal prompt information is displayed to output the corresponding abnormal warning. For example, the sandblasting parameters and workpiece detection results collected in real time are displayed in the form of a curve graph.

[0072] See also Figure 5, which is a schematic diagram of the structure of a sandblasting process management device provided in one embodiment of the present application. In one embodiment of the present application, the sandblasting process management device 200 may include a plurality of functional modules composed of computer program segments. The computer program segments in the sandblasting process management device 200 may be stored in a memory of an electronic device and executed by at least one processor to perform the sandblasting process management function.

[0073] In one embodiment of the present application, the sandblasting process management device 200 can be divided into multiple functional modules according to the functions it performs. The functional modules of the sandblasting process management device 200 may include: an acquisition module 201, a determination module 202, and an adjustment module 203. The module in the embodiment of the present application refers to a series of computer program segments that can be executed by at least one processor and can complete fixed functions, which are stored in a memory.

[0074] The acquisition module 201 is used to acquire at least one sandblasting parameter of the sandblasting equipment.

[0075] The determination module 202 is configured to determine that at least one sandblasting parameter is normal if at least one sandblasting parameter is within a preset parameter range.

[0076] The acquisition module 201 is also used to acquire the detection results of the workpiece subjected to the sandblasting treatment by the sandblasting equipment.

[0077] The determination module 202 is also used to determine that the sandblasting equipment is operating normally if the detection result is within a preset standard range.

[0078] The adjustment module 203 is used to extract characteristic data of the detection result, and adjust at least one sandblasting parameter based on the characteristic data.

[0079] See also Figure 6 , which is a schematic diagram of the structure of an electronic device provided by an embodiment of the present application. The electronic device 1 includes, but is not limited to, a processor 10, a memory 20, and a computer program stored in the memory 20 and executable on the processor 10. For example, the computer program is a sandblasting process management program. When the processor 10 executes the computer program, the steps in the sandblasting process management method are implemented.

[0080] Exemplarily, the computer program may be divided into one or more modules / units, which are stored in the memory 20 and executed by the processor 10 to complete the present application. The one or more modules / units may be a series of computer program instruction segments capable of completing specific functions, and the instruction segments are used to describe the execution process of the computer program in the electronic device 1.

[0081] Those skilled in the art will understand that the schematic diagram is merely an example of the electronic device 1 and does not constitute a limitation on the electronic device 1. The electronic device 1 may include more or fewer components than shown in the diagram, or a combination of certain components, or different components. For example, the electronic device 1 may also include input and output devices, network access devices, buses, etc.

[0082] The processor may be a central processing unit (CPU), or other general-purpose processors, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The processor is the control center of the electronic device 1, and uses various interfaces and lines to connect various parts of the entire electronic device 1.

[0083] The memory can be used to store the firmware program and / or module / unit, and the processor implements various functions of the electronic device 1 by running or executing the computer program and / or module / unit stored in the memory, and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required for a function, etc.; the data storage area can store data created according to the use of the electronic device 1, etc. In addition, the memory can include volatile and non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other storage devices.

[0084] If the module / unit integrated in the electronic device 1 is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above-mentioned method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory).

[0085] The expanded contents of the specific embodiments of the computer-readable storage medium described in this application are basically the same as the embodiments of the above-mentioned sandblasting process management method, and will not be elaborated here.

[0086] It is obvious to those skilled in the art that the present application is not limited to the details of the above exemplary embodiments, and that the present application can be implemented in other specific forms without departing from the spirit or basic features of the present application. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-restrictive, and the scope of the present application is limited by the attached claims rather than the above description, so it is intended to include all changes that fall within the meaning and scope of the equivalent elements of the claims in the present application. Any figure mark in the claims should not be regarded as limiting the claims involved. In addition, it is obvious that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices stated in the device claim can also be implemented by the same unit or device through software or hardware. The words first, second, etc. are used to indicate names, and do not indicate any particular order.

[0087] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present application and are not intended to limit it. Although the present application has been described in detail with reference to the preferred embodiments, a person of ordinary skill in the art should understand that the technical solution of the present application may be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present application.

Claims

1. A sandblasting process management method, applied to electronic equipment, characterized in that: The method comprises: Collecting at least one sandblasting parameter of the sandblasting equipment, and if the at least one sandblasting parameter is within a preset parameter range, determining that the at least one sandblasting parameter is normal; Collecting the test results of the workpiece subjected to the sandblasting treatment by the sandblasting equipment, and if the test results are within a preset standard range, determining that the sandblasting equipment is working properly; Extract characteristic data of the detection result, and adjust the at least one sandblasting parameter based on the characteristic data.

2. The sandblasting process management method according to claim 1, characterized in that: The at least one sandblasting parameter includes a moving speed of a spray gun of the sandblasting device, and if the at least one sandblasting parameter is within a preset parameter range, determining that the at least one sandblasting parameter is normal includes: Determining whether the moving speed is less than or equal to a preset moving speed threshold; If the moving speed is less than or equal to the preset moving speed threshold, determining that the moving speed is normal; If the moving speed is greater than the preset moving speed threshold, it is determined that the moving speed is abnormal.

3. The sandblasting process management method according to claim 2, characterized in that: The at least one sandblasting parameter also includes the swing amplitude of the spray gun, and if the at least one sandblasting parameter is within a preset parameter range, determining that the at least one sandblasting parameter is normal further includes: If the moving speed is less than or equal to the preset moving speed threshold, determining whether the swing amplitude is less than or equal to the preset swing amplitude threshold; If the swing amplitude is less than or equal to the preset swing amplitude threshold, it is determined that the swing amplitude is normal; If the swing amplitude is greater than the preset swing amplitude threshold, it is determined that the swing amplitude is abnormal.

4. The sandblasting process management method according to claim 3, characterized in that: The at least one sandblasting parameter further includes the air pressure of the spray gun, and if the at least one sandblasting parameter is within a preset parameter range, determining that the at least one sandblasting parameter is normal further includes: If the swing amplitude is less than or equal to the preset swing amplitude threshold, determining whether the air pressure gauge of the sandblasting equipment is in an on state; If the barometer is in an on state, determining whether the air pressure is less than or equal to a preset air pressure threshold; If the air pressure is greater than the preset air pressure threshold, determining that the air pressure is abnormal; If the air pressure is less than or equal to the preset air pressure threshold, determining whether the air pressure is the same as the previous air pressure; If the air pressure is different from the previous air pressure, determining that the air pressure is normal; If the air pressure is the same as the previous air pressure, the number of times the air pressure is the same is accumulated, and if the number of times the air pressure is the same reaches a preset number, it is determined that the air pressure is abnormal.

5. The sandblasting process management method according to claim 4, characterized in that: The method further comprises: If the moving speed or the swing amplitude is 0, determining the current state of the sandblasting device; If the sandblasting equipment is in automatic or manual state, continue to determine whether the swing amplitude is 0; If the swing amplitude is not 0, it is determined that the swing amplitude is abnormal; If the swing amplitude is 0, continue to determine the current state of the sandblasting equipment; If the sandblasting equipment is in automatic or manual state, continue to determine whether the air pressure is 0; If the air pressure is not 0, determining that the air pressure is abnormal; If the air pressure is 0, continue to determine the current state of the sandblasting equipment; If the sandblasting equipment is in an automatic or manual state, it is determined that the sandblasting equipment has a material blockage abnormality.

6. The sandblasting process management method according to claim 1, wherein: The detection result includes the glossiness of the workpiece, and if the detection result is within a preset standard range, it is determined that the sandblasting equipment is working properly, including: Determining whether the glossiness is within a preset glossiness range; If the glossiness is within the preset glossiness range, it is determined that the sandblasting equipment is working properly; If the glossiness is not within the preset glossiness range, it is determined that the sandblasting equipment is operating abnormally.

7. The sandblasting process management method according to claim 6, wherein: The extracting characteristic data of the detection result and adjusting the at least one sandblasting parameter based on the characteristic data comprises: Calculating the difference between the glossiness of a plurality of positions on the first surface of the workpiece and the glossiness of a plurality of positions on the second surface; Determining an identification of the difference based on a preset difference range in which the difference lies; Calculate the total number of said marks and the percentage of each mark; Analyzing the distribution concentration of the difference based on the total number of the identifications and the percentage of each identification; The at least one blasting parameter is adjusted based on a concentration of the distribution of the differences.

8. The sandblasting process management method according to claim 6, wherein: The extracting characteristic data of the detection result and adjusting the at least one sandblasting parameter based on the characteristic data comprises: Calculate a first glossiness average value of a plurality of position points on a first surface of the workpiece and a second glossiness average value of a plurality of position points on a second surface; Based on the first gloss average value and the second gloss average value, analyzing the daily gloss average change of each location point and the gloss average difference of different location points; The at least one sandblasting parameter is adjusted based on the daily glossiness average change of each location point, the glossiness average difference of different location points and the critical data of the glossiness average.

9. The sandblasting process management method according to claim 1, wherein: The method further comprises: Count the processing time of each workpiece in each step of the sandblasting process; Count the number of workpieces, percentage of workpieces and mean processing time corresponding to each processing time interval of each process; If the percentage of the number of workpieces is within a preset percentage range, it is determined that the processing time of the workpiece is normal; The at least one blasting parameter is adjusted based on the average processing time of the same workstation on different production lines.

10. The sandblasting process management method according to claim 1, wherein: The method further comprises: Calculating the mean and standard deviation of the sandblasting parameters and the test results respectively; Determining a normal value range of the at least one blasting parameter and the detection result based on the mean and the standard deviation; The sandblasting parameters and the detection results that are not within the normal value range are eliminated.

11. An electronic device, characterized in that: The electronic device comprises a processor and a memory, the memory is used to store instructions, and the processor is used to call the instructions in the memory, so that the electronic device executes the sandblasting process management method according to any one of claims 1 to 10.

12. A computer-readable storage medium, characterized in that: The method comprises computer instructions, and when the computer instructions are executed on an electronic device, the electronic device executes the sandblasting process management method according to any one of claims 1 to 10.

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