Efficient adsorption and release control method and system for electronic vacuum chuck

Abstract

The invention is suitable for the technical field of electronic vacuum chuck control, and provides an efficient adsorption and release control method and system for an electronic vacuum chuck. And determining the adsorption force adjustment amplification of this time, and obtaining a corresponding maintenance reference model and a historical operation log of the target adsorption device. Based on the difference between the actual change trend and the expected change trend of the target adsorption device, the adsorption force adjustment amplification is dynamically optimized, and the method has remarkable innovativeness and beneficial effects. A traditional adsorption force adjusting method often depends on a static model or a preset period, but according to the method, the operation state of the adsorption device is monitored in real time, the actual use condition is combined with a maintenance reference model for comparison, the decline degree of equipment can be accurately quantified, and therefore the adsorption force is dynamically adjusted, and the situation of excessive adjustment or insufficient adjustment is avoided.

Description

Technical Field

[0001] The invention belongs to the technical field of electronic vacuum chuck control, and in particular relates to a high-efficiency adsorption and release control method and system of an electronic vacuum chuck. Background Art

[0002] Electronic vacuum suction cups, as a gripping device commonly used in automated production lines, play an important role in many fields. Its working principle mainly relies on vacuum technology to grip the workpiece through adsorption force. However, traditional adsorption force adjustment methods are usually based on static models or preset cycles. This method fails to fully consider the dynamic changes of workpiece surface deformation and adsorption force decay during long-term use of the adsorption device. Most existing technologies rely on regular maintenance and quantitative adjustment of adsorption force, lacking real-time adjustment capabilities that are highly matched with actual working conditions, resulting in inaccurate adsorption force adjustment, and even over-adsorption or under-adsorption in some cases.

[0003] The main drawback of traditional adsorption force adjustment systems is that they usually rely on the preset working cycle of the equipment or adjust according to the standard deformation model of the workpiece, lacking dynamic monitoring and real-time feedback mechanisms. This method cannot fully consider the changes in the workpiece surface caused by excessive or insufficient adsorption force in actual work. Therefore, in many cases, the adjustment of adsorption force fails to respond in time according to actual use, resulting in a waste of energy efficiency and increased equipment loss. Summary of the invention

[0004] The purpose of the present invention is to provide a method and system for efficiently adsorbing and releasing an electronic vacuum chuck, aiming to solve the problems raised in the background technology.

[0005] The present invention is achieved by a method for controlling efficient adsorption and release of an electronic vacuum chuck, the method comprising:

[0006] When the target adsorption device enters the first maintenance cycle, the adsorption force adjustment increase is determined and the corresponding maintenance reference model and the historical operation log of the target adsorption device are obtained;

[0007] Parse the historical operation logs to analyze whether the target adsorption device has processed a specific category of workpieces predefined in the maintenance reference model. If it is confirmed that the target adsorption device has processed the specific category of workpieces, obtain the specified expected change trend of the workpiece surface deformation characteristics when the target adsorption device processes the specific category of workpieces from the maintenance reference model;

[0008] Based on the historical operation logs, extract the local operation logs of the specified number and interval time rules when the target adsorption device processes the specific category of workpieces, and analyze the actual change trend of the surface deformation of the workpiece when the target adsorption device processes the specific category of workpieces in actual operation based on these local operation logs;

[0009] The deviation between the actual change trend and the specified expected change trend is quantified, and the deviation is used as a correction factor to optimize the increase in the adsorption force adjustment.

[0010] As a further limitation of the technical solution of the embodiment of the present invention, the maintenance reference model refers to the standard expected change trend of the surface deformation degree of the workpiece as the target adsorption device adsorbs different types of workpieces under a standard working environment with the increase of the use time of the target adsorption device, and the standard change trend is represented by a curve graph.

[0011] As a further limitation of the technical solution of the embodiment of the present invention, the step of parsing the historical operation log, analyzing whether the target adsorption device has processed a specific category of workpieces predefined in the maintenance reference model, and if it is confirmed that the target adsorption device has processed the specific category of workpieces, then obtaining the specified expected change trend of the surface deformation characteristics of the workpiece when the target adsorption device processes the specific category of workpieces from the maintenance reference model includes:

[0012] Parse the historical operation log and confirm whether the target adsorption device has processed a specific category of workpieces that matches the predefined category in the maintenance reference model and the number of processed items exceeds a preset threshold;

[0013] If it is confirmed that the workpiece has been processed, the specified expected change trend of the deformation characteristics of the workpiece surface when the target adsorption device processes a specific type of workpiece is obtained from the maintenance reference model.

[0014] As a further limitation of the technical solution of the embodiment of the present invention, based on the historical operation log, extracting the local operation logs of the specified number and interval time rules when the target adsorption device processes the specific category of workpieces, and analyzing the actual change trend of the surface deformation of the workpiece when the target adsorption device processes the specific category of workpieces in actual operation according to these local operation logs includes:

[0015] According to the historical operation logs, extracting several local operation logs that meet the specified quantity and time interval rules when the target adsorption device processes a specific category of workpieces;

[0016] Parse these local operation logs and obtain historical images of the workpiece surface area close to the adsorption device during the process of the target adsorption device adsorbing the workpiece;

[0017] Machine vision technology is used to analyze each historical image to determine the corresponding degree of deformation of the workpiece surface, and all deformation degree values ​​are plotted into a curve graph in chronological order to obtain the actual change trend of the workpiece surface deformation when the target adsorption device processes a specific type of workpiece in actual operation.

[0018] As a further limitation of the technical solution of the embodiment of the present invention, the step of quantifying the deviation between the actual change trend and the specified expected change trend and using the deviation as a correction factor to optimize the adsorption force adjustment increase includes:

[0019] Quantify the difference in average slope between the actual change trend and the expected change trend and determine the value of the difference;

[0020] Call the preset optimization formula, input the deviation value as the correction factor into the preset optimization formula, and optimize the adsorption force adjustment increase this time.

[0021] As a further limitation of the technical solution of the embodiment of the present invention, the preset optimization formula is: , where F opt Refers to the optimized adsorption force adjustment increase, F pre Refers to the increase in the adsorption force adjustment before optimization. Slope actual Refers to the average slope of the actual change trend, Slope tageted Refers to the average slope of the specified expected trend. It refers to the correction factor, that is, the deviation value between the actual change trend and the specified expected change trend, and K refers to the adjustment coefficient of the correction factor.

[0022] An efficient adsorption and release control system for an electronic vacuum chuck, the system comprising: a data acquisition module, a specified expected change trend determination module, an actual change trend generation module and an adjustment increase optimization module, wherein:

[0023] A data acquisition module, used to determine the adsorption force adjustment increase and obtain the corresponding maintenance reference model and the historical operation log of the target adsorption device when the target adsorption device enters the first maintenance cycle;

[0024] The maintenance reference model refers to a standard expected change trend of the surface deformation degree of the workpiece as the use time of the target adsorption device increases when the target adsorption device adsorbs different types of workpieces under a standard working environment, and the standard change trend is represented in the form of a curve graph;

[0025] A specified expected change trend determination module is used to parse the historical operation logs and analyze whether the target adsorption device has processed a specific category of workpieces predefined in the maintenance reference model. If it is confirmed that the target adsorption device has processed the specific category of workpieces, the specified expected change trend of the workpiece surface deformation characteristics when the target adsorption device processes the specific category of workpieces is obtained from the maintenance reference model;

[0026] An actual change trend generation module is used to extract local operation logs of a specified number and interval time rules when the target adsorption device processes the specific category of workpieces based on historical operation logs, and analyze the actual change trend of the workpiece surface deformation when the target adsorption device processes the specific category of workpieces in actual operation based on these local operation logs;

[0027] The adjustment increase optimization module is used to quantify the deviation between the actual change trend and the specified expected change trend, and use the deviation as a correction factor to optimize the adsorption force adjustment increase.

[0028] As a further limitation of the technical solution of the embodiment of the present invention, the specified expected change trend determination module specifically includes:

[0029] A specific category determination unit, used for parsing the historical operation log and confirming whether the target adsorption device has processed a specific category of workpieces matching a predefined category in the maintenance reference model and the number of processed workpieces exceeds a preset threshold;

[0030] The specified expected change trend acquisition unit is used to obtain the specified expected change trend of the workpiece surface deformation characteristics when the target adsorption device processes a specific type of workpiece from the maintenance reference model if the processing is confirmed.

[0031] As a further limitation of the technical solution of the embodiment of the present invention, the actual change trend generation module specifically includes:

[0032] A local operation log acquisition unit is used to extract a number of local operation logs that meet the specified quantity and time interval rules when the target adsorption device processes a specific category of workpieces according to the historical operation logs;

[0033] A local operation log parsing unit is used to parse these local operation logs and obtain historical images of the area of ​​the workpiece surface close to the adsorption device during the process of the target adsorption device adsorbing the workpiece;

[0034] The actual change trend generating unit is used to analyze each historical image using machine vision technology, determine the corresponding degree of deformation of the workpiece surface, and plot all deformation degree values ​​into a curve graph in chronological order, so as to obtain the actual change trend of the workpiece surface deformation when the target adsorption device processes a specific category of workpieces in actual operation.

[0035] As a further limitation of the technical solution of the embodiment of the present invention, the adjustment increase optimization module specifically includes:

[0036] A difference quantification unit is used to quantify the average slope difference between the actual change trend and the expected change trend and determine the difference value;

[0037] The adjustment increase optimization unit is used to call the preset optimization formula, input the deviation value as a correction factor into the preset optimization formula, and optimize the current adsorption force adjustment increase;

[0038] The preset optimization formula is: , where F opt Refers to the optimized adsorption force adjustment increase, F pre Refers to the increase in the adsorption force adjustment before optimization. Slope actual Refers to the average slope of the specified expected change trend, Slope tageted Refers to the average slope of the actual change trend, It refers to the correction factor, that is, the deviation value between the actual change trend and the specified expected change trend, and K refers to the adjustment coefficient of the correction factor.

[0039] Compared with the prior art, the present invention has the following beneficial effects:

[0040] The present invention dynamically optimizes the adsorption force adjustment increment based on the difference between the actual change trend and the expected change trend of the target adsorption device, which has significant innovation and beneficial effects. Traditional adsorption force adjustment methods often rely on static models or preset cycles, while the present invention can accurately quantify the degree of equipment degradation by monitoring the operating status of the adsorption device in real time, combining actual usage with the maintenance reference model for comparison, thereby dynamically adjusting the adsorption force and avoiding over-adjustment or under-adjustment.

[0041] Through this innovative solution, the target adsorption device can be automatically optimized according to the actual deformation during its use, greatly improving the operating efficiency, stability and adaptability of the equipment. In addition, this method can also save energy, extend the service life of the equipment, reduce maintenance costs, and provide a more efficient and intelligent solution for automated production lines. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 A flowchart of a method provided by an embodiment of the present invention;

[0043] Figure 2 A flow chart for determining a specified expected change trend in the method provided in an embodiment of the present invention;

[0044] Figure 3 A flow chart showing the actual change trend in the method provided in the embodiment of the present invention;

[0045] Figure 4 A flow chart for optimizing the adsorption force adjustment increase in the method provided in an embodiment of the present invention;

[0046] Figure 5 An application architecture diagram of a system provided by an embodiment of the present invention;

[0047] Figure 6 A structural block diagram of a module for determining a specified expected change trend in a system provided in an embodiment of the present invention;

[0048] Figure 7 A structural block diagram of an actual change trend generation module in a system provided by an embodiment of the present invention;

[0049] Figure 8 This is a structural block diagram of an adjustment increase optimization module in a system provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0050] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0051] Figure 1 A flow chart of a method provided by an embodiment of the present invention is shown.

[0052] Specifically, a method for efficiently adsorbing and releasing an electronic vacuum chuck comprises the following steps:

[0053] Step S100, when the target adsorption device enters the first maintenance cycle, the adsorption force adjustment increase is determined and the corresponding maintenance reference model and the historical operation log of the target adsorption device are obtained.

[0054] The maintenance reference model refers to the standard expected change trend of the workpiece surface deformation degree as the target adsorption device adsorbs different types of workpieces under a standard working environment as the target adsorption device is used for an increasing period of time. The standard change trend is represented by a curve graph.

[0055] In the embodiment of the present invention, the target adsorption device refers to a device that uses the vacuum principle to perform adsorption operations, usually including a suction cup, a suction cup control system, a sensor and an actuator. It is mainly used in automated production lines to grab or carry different types of workpieces. The adsorption force of the target adsorption device is achieved by adjusting the vacuum degree and the physical parameters of the adsorption device, and is widely used in the fields of electronic component assembly, automated warehousing, logistics, etc.

[0056] The first maintenance cycle refers to the time point when the target adsorption device is first fully inspected and maintained after a period of normal operation according to the equipment design or the manufacturer's recommended cycle after it is put into use. Usually, the first maintenance cycle is set based on the equipment's workload, usage time or operating conditions. This cycle is usually clearly specified in the equipment's factory instructions or maintenance manual.

[0057] The maintenance reference model comes from the manufacturer of the target adsorption device. It is a standard expected change model established based on the performance data of the device when adsorbing different types of workpieces under standard working conditions, combined with the law of the change of the deformation degree of the workpiece surface over time. The model is constructed through experimental data or historical usage data, usually expressed as a chart or curve, which can accurately reflect the performance change trend of the adsorption device under different workpieces and environmental conditions within a specific time.

[0058] The adsorption force adjustment increment refers to the amount of adsorption force adjustment required by the target adsorption device during the first maintenance cycle. According to the maintenance reference model and historical operation data, the adjustment of the adsorption force increment can ensure that the target adsorption device can continue to stably complete the adsorption task of the workpiece after long-term use. The adsorption force increment is corrected based on the difference between the preset change trend of the model and the actual performance, ensuring that the adsorption force can be effectively adjusted when the equipment ages or the characteristics of the workpiece change.

[0059] In the prior art, the setting of target adsorption device and first maintenance cycle has been widely used. The concept of adsorption force adjustment and maintenance reference model has also been applied in many automatic control systems.

[0060] The historical operation log is derived from the operation data automatically recorded by the target adsorption device during long-term use. The log should include the working status of the suction cup, the type of workpiece being adsorbed, changes in adsorption force, working time, workpiece surface deformation data, system feedback information, and each captured workpiece surface image. Specifically, the historical operation log should record in detail the specific parameters of the suction cup in each operation, such as adsorption force, adsorption time, workpiece type, surface state, degree of deformation, workpiece surface image captured during each operation, and corresponding sensor data. This information provides comprehensive data support for subsequent maintenance, adjustment of adsorption force, and optimization of adsorption device performance, especially the workpiece surface image data, which can be used for subsequent deformation analysis and model correction.

[0061] Furthermore, the method for controlling efficient adsorption and release of the electronic vacuum chuck further comprises the following steps:

[0062] Parse the historical operation logs to analyze whether the target adsorption device has processed a specific category of workpieces predefined in the maintenance reference model. If it is confirmed that it has been processed, obtain the specified expected change trend of the workpiece surface deformation characteristics when the target adsorption device processes the specific category of workpieces from the maintenance reference model.

[0063] Specifically, Figure 2 A flow chart for determining a specified expected change trend is shown.

[0064] The process of parsing the historical operation logs and analyzing whether the target adsorption device has processed a specific category of workpieces predefined in the maintenance reference model, and if it is confirmed that the target adsorption device has processed the specific category of workpieces, obtaining the specified expected change trend of the surface deformation characteristics of the workpiece when the target adsorption device processes the specific category of workpieces from the maintenance reference model specifically includes the following steps:

[0065] Step S201, parsing the historical operation log, and confirming whether the target adsorption device has processed a specific category of workpieces that matches the predefined category in the maintenance reference model and the number of processed workpieces exceeds a preset threshold;

[0066] Step S202: if it is confirmed that the processing has been completed, the specified expected change trend of the deformation characteristics of the workpiece surface when the target adsorption device processes a specific type of workpiece is obtained from the maintenance reference model.

[0067] In the embodiment of the present invention, the specified quantity and time interval rule refers to the local operation logs extracted from the historical operation logs, and their quantity and time interval should be consistent with the curve of the specified expected change trend in the maintenance reference model. In this way, it is ensured that the samples extracted from the historical data can accurately reflect the change trend of the target adsorption device processing the workpiece under the same conditions, so as to be effectively compared with the expected trend.

[0068] Each historical image is analyzed using machine vision technology. The specific implementation process is as follows: First, historical images of the workpiece surface near the adsorption device area are collected through a camera or other imaging device. Then, existing computer vision algorithms, such as image processing technology based on convolutional neural networks (CNN), are applied to perform image preprocessing, feature extraction, and classification. Through these technologies, the system can identify light patterns or surface marks on the workpiece surface and calculate the deformation of the workpiece surface caused by the adsorption force. Machine vision technology compares the images before and after the deformation of the workpiece surface and uses algorithms such as edge detection and morphological analysis to measure the magnitude of the deformation. Finally, these measurements are converted into deformation degrees, and deformation curves are generated according to the time sequence to provide quantitative analysis of the deformation of the workpiece surface.

[0069] In step S202, first, the system confirms whether the target adsorption device has processed a sufficient number of workpieces of a specific category, and the number of these workpieces exceeds a preset threshold. If it is confirmed that it has been processed, the system searches the maintenance reference model to find the specified expected change trend related to the specific category of workpieces. The specified expected change trend is usually represented in the form of a curve graph, reflecting the law of the change of the deformation degree of the workpiece surface over time.

[0070] Furthermore, the method for controlling efficient adsorption and release of the electronic vacuum chuck further comprises the following steps:

[0071] Step S300, based on the historical operation logs, extract the local operation logs of the specified number and interval time rules of the target adsorption device when processing the specific category of workpieces, and analyze the actual change trend of the surface deformation of the workpiece when the target adsorption device processes the specific category of workpieces in actual operation based on these local operation logs.

[0072] Specifically, Figure 3 A flow chart showing the actual changing trend is shown.

[0073] Among them, based on the historical operation logs, extracting the local operation logs of the specified number and interval time rules when the target adsorption device processes the specific category of workpieces, and analyzing the actual change trend of the surface deformation of the workpiece when the target adsorption device processes the specific category of workpieces in actual operation based on these local operation logs. Specifically, the following steps are included:

[0074] Step S301, extracting a number of local operation logs that meet the specified quantity and time interval rules when the target adsorption device processes a specific type of workpiece according to the historical operation logs;

[0075] Step S302, parsing these local operation logs, and obtaining therefrom historical images of the workpiece surface area close to the adsorption device during the process of the target adsorption device adsorbing the workpiece;

[0076] In step S303, each historical image is analyzed using machine vision technology to determine the corresponding degree of deformation of the workpiece surface, and all deformation degree values ​​are plotted into a curve graph in chronological order to obtain the actual change trend of the workpiece surface deformation when the target adsorption device processes a specific type of workpiece in actual operation.

[0077] In the embodiment of the present invention, the specified quantity and time interval rule refers to the local operation logs extracted from the historical operation logs, and their quantity and time interval should be consistent with the curve of the specified expected change trend in the maintenance reference model. In this way, it is ensured that the samples extracted from the historical data can accurately reflect the change trend of the target adsorption device processing the workpiece under the same conditions, so as to be effectively compared with the expected trend.

[0078] Each historical image is analyzed using machine vision technology. The specific implementation process is as follows: First, historical images of the workpiece surface near the adsorption device area are collected through a camera or other imaging device. Then, existing computer vision algorithms, such as image processing technology based on convolutional neural networks (CNN), are applied to perform image preprocessing, feature extraction, and classification. Through these technologies, the system can identify light patterns or surface marks on the workpiece surface and calculate the deformation of the workpiece surface caused by the adsorption force. Machine vision technology compares the images before and after the deformation of the workpiece surface and uses algorithms such as edge detection and morphological analysis to measure the magnitude of the deformation. Finally, these measurements are converted into deformation degrees, and deformation curves are generated according to the time sequence to provide quantitative analysis of the deformation of the workpiece surface.

[0079] The actual change trend of the workpiece surface deformation specifically reflects the deformation of the workpiece surface under the action of the adsorption device in the actual operation of the target adsorption device, as the adsorption force changes during the adsorption process, the material properties of the workpiece and the influence of environmental factors. This change trend can show the degree of deformation of the workpiece at different time points or under different adsorption forces, and then reveal the influence of the adsorption force on the deformation of the workpiece surface, as well as the changes in the adsorption device's processing effect on the workpiece in actual work. This information is helpful to analyze the working performance of the target adsorption device, optimize the adsorption force adjustment strategy, and ensure the quality and efficiency of workpiece processing.

[0080] Furthermore, the method for controlling efficient adsorption and release of the electronic vacuum chuck further comprises the following steps:

[0081] Step S400, quantifying the deviation between the actual change trend and the specified expected change trend, and using the deviation as a correction factor to optimize the current adsorption force adjustment increase.

[0082] Specifically, Figure 4 A flow chart for optimizing the adsorption force adjustment increase is shown.

[0083] Among them, quantifying the deviation between the actual change trend and the specified expected change trend, and using the deviation as a correction factor to optimize the adsorption force adjustment increase includes the following steps:

[0084] Step S401, quantifying the average slope difference between the actual change trend and the expected change trend, and determining the difference value;

[0085] Step S402, calling a preset optimization formula, inputting the deviation value as a correction factor into the preset optimization formula, and optimizing the current adsorption force adjustment increase.

[0086] The preset optimization formula is: , where F opt Refers to the optimized adsorption force adjustment increase, Fpre Refers to the increase in the adsorption force adjustment before optimization. Slope actual Refers to the average slope of the actual change trend, Slope tageted Refers to the average slope of the specified expected trend. It refers to the correction factor, that is, the deviation value between the actual change trend and the specified expected change trend, and K refers to the adjustment coefficient of the correction factor.

[0087] In an embodiment of the present invention, the difference in the average slope between the actual change trend and the expected change trend is quantified as a correction factor to optimize the adsorption force adjustment increase this time, because it can effectively reflect the decay of the target adsorption device during use. If the average slope of the actual change trend is greater than the average slope of the expected change trend, it means that the adsorption force of the target adsorption device decays faster than expected with the increase in usage time, which indicates that the performance degradation of the adsorption device is more significant than expected during design. In this case, the system needs to slightly increase the adsorption force adjustment increase to compensate for this additional decay and ensure that the adsorption device can continue to work stably. On the contrary, if the slope of the actual change trend is less than expected, indicating that the decay rate of the adsorption device is slower, the adsorption force adjustment increase can be appropriately reduced to avoid unnecessary energy waste.

[0088] The specific significance and benefit of this optimization method based on the average slope difference is that it can more accurately model and correct the degradation of the equipment. In this way, the adsorption force can be dynamically adjusted according to the actual use of the equipment to ensure the efficiency and stability of the equipment in long-term use. Compared with the traditional adjustment method that only relies on time or fixed rules, this method is more flexible and intelligent, and can effectively extend the service life of the equipment and improve production efficiency.

[0089] In the existing technology, there are relatively few applications that adjust based on slope differences, and most existing methods rely on the use time of the equipment or regular manual maintenance. However, the method of adjusting the adsorption force increase by quantifying the difference between the actual and expected slopes can adapt to changes in the equipment status in real time and has higher intelligence and adaptability.

[0090] The preset optimization formula mentioned above is only a more intuitive calculation method to reflect the impact of the difference between the actual change trend and the expected change trend on the adsorption force adjustment increase. In fact, in addition to using the preset optimization formula, other calculation methods can also be used, such as machine learning algorithms, which automatically optimize the adsorption force adjustment strategy by learning from historical operation data. Through intelligent algorithms, the calculation method of the correction factor can be dynamically adjusted, allowing the system to be optimized under more complex working conditions.

[0091] The following example illustrates how to optimize the adsorption force adjustment increase based on the correction factor:

[0092] Assume that the initial increase in the adsorption force adjustment is 20%. In actual applications, the average slope of the actual change trend of the target adsorption device is 0.8, and the average slope of the expected change trend is 1.0, with a difference of 0.2. According to the preset optimization formula, the correction factor is calculated as the ratio between the difference and the adsorption force adjustment increase, for example, the correction factor is 0.1. Therefore, the optimized adsorption force adjustment increase is the initial adsorption force adjustment increase of 20% multiplied by 1 minus the correction factor of 0.1, that is, the optimized increase is 18%. In this way, the system can ensure that the adsorption force adjustment is more in line with the actual working conditions of the target adsorption device, thereby improving work efficiency and energy saving.

[0093] Furthermore, Figure 5 The application architecture diagram of the system provided by the embodiment of the present invention is shown.

[0094] Among them, in another preferred embodiment provided by the present invention, a high-efficiency adsorption and release control system of an electronic vacuum chuck comprises:

[0095] The data acquisition module 100 is used to determine the adsorption force adjustment increase and obtain the corresponding maintenance reference model and the historical operation log of the target adsorption device when the target adsorption device enters the first maintenance cycle.

[0096] The maintenance reference model refers to the standard expected change trend of the workpiece surface deformation degree as the target adsorption device adsorbs different types of workpieces under a standard working environment as the target adsorption device is used for an increasing period of time. The standard change trend is represented by a curve graph.

[0097] In the embodiment of the present invention, the target adsorption device refers to a device that uses the vacuum principle to perform adsorption operations, usually including a suction cup, a suction cup control system, a sensor and an actuator. It is mainly used in automated production lines to grab or carry different types of workpieces. The adsorption force of the target adsorption device is achieved by adjusting the vacuum degree and the physical parameters of the adsorption device, and is widely used in the fields of electronic component assembly, automated warehousing, logistics, etc.

[0098] The first maintenance cycle refers to the time point when the target adsorption device is first fully inspected and maintained after a period of normal operation according to the equipment design or the manufacturer's recommended cycle after it is put into use. Usually, the first maintenance cycle is set based on the equipment's workload, usage time or operating conditions. This cycle is usually clearly specified in the equipment's factory instructions or maintenance manual.

[0099] The maintenance reference model comes from the manufacturer of the target adsorption device. It is a standard expected change model established based on the performance data of the device when adsorbing different types of workpieces under standard working conditions, combined with the law of the change of the deformation degree of the workpiece surface over time. The model is constructed through experimental data or historical usage data, usually expressed as a chart or curve, which can accurately reflect the performance change trend of the adsorption device under different workpieces and environmental conditions within a specific time.

[0100] The adsorption force adjustment increment refers to the amount of adsorption force adjustment required by the target adsorption device during the first maintenance cycle. According to the maintenance reference model and historical operation data, the adjustment of the adsorption force increment can ensure that the target adsorption device can continue to stably complete the adsorption task of the workpiece after long-term use. The adsorption force increment is corrected based on the difference between the preset change trend of the model and the actual performance, ensuring that the adsorption force can be effectively adjusted when the equipment ages or the characteristics of the workpiece change.

[0101] In the prior art, the setting of target adsorption device and first maintenance cycle has been widely used. The concept of adsorption force adjustment and maintenance reference model has also been applied in many automatic control systems.

[0102] The historical operation log is derived from the operation data automatically recorded by the target adsorption device during long-term use. The log should include the working status of the suction cup, the type of workpiece being adsorbed, changes in adsorption force, working time, workpiece surface deformation data, system feedback information, and each captured workpiece surface image. Specifically, the historical operation log should record in detail the specific parameters of the suction cup in each operation, such as adsorption force, adsorption time, workpiece type, surface state, degree of deformation, workpiece surface image captured during each operation, and corresponding sensor data. This information provides comprehensive data support for subsequent maintenance, adjustment of adsorption force, and optimization of adsorption device performance, especially the workpiece surface image data, which can be used for subsequent deformation analysis and model correction.

[0103] Furthermore, the efficient adsorption and release control system of the electronic vacuum chuck also includes:

[0104] The specified expected change trend determination module 200 is used to parse the historical operation log and analyze whether the target adsorption device has processed a specific category of workpieces predefined in the maintenance reference model. If it is confirmed that it has been processed, the specified expected change trend of the surface deformation characteristics of the workpiece when the target adsorption device processes the specific category of workpieces is obtained from the maintenance reference model.

[0105] Specifically, Figure 6 It shows a structural block diagram of the specified expected change trend determination module 200 in the system provided by an embodiment of the present invention.

[0106] Among them, in the preferred implementation mode provided by the present invention, the specified expected change trend determination module 200 specifically includes:

[0107] The specific category determination unit 201 is used to parse the historical operation log and confirm whether the target adsorption device has processed a specific category of workpieces that matches the predefined category in the maintenance reference model and the number of processed works exceeds a preset threshold;

[0108] The specified expected change trend acquisition unit 202 is used to acquire the specified expected change trend of the workpiece surface deformation characteristics when the target adsorption device processes a specific type of workpiece from the maintenance reference model if the processing is confirmed.

[0109] In the embodiment of the present invention, the specified quantity and time interval rule refers to the local operation logs extracted from the historical operation logs, and their quantity and time interval should be consistent with the curve of the specified expected change trend in the maintenance reference model. In this way, it is ensured that the samples extracted from the historical data can accurately reflect the change trend of the target adsorption device processing the workpiece under the same conditions, so as to be effectively compared with the expected trend.

[0110] Each historical image is analyzed using machine vision technology. The specific implementation process is as follows: First, historical images of the workpiece surface near the adsorption device area are collected through a camera or other imaging device. Then, existing computer vision algorithms, such as image processing technology based on convolutional neural networks (CNN), are applied to perform image preprocessing, feature extraction, and classification. Through these technologies, the system can identify light patterns or surface marks on the workpiece surface and calculate the deformation of the workpiece surface caused by the adsorption force. Machine vision technology compares the images before and after the deformation of the workpiece surface and uses algorithms such as edge detection and morphological analysis to measure the magnitude of the deformation. Finally, these measurements are converted into deformation degrees, and deformation curves are generated according to the time sequence to provide quantitative analysis of the deformation of the workpiece surface.

[0111] In the specified expected change trend acquisition unit 202, first, the system confirms whether the target adsorption device has processed a sufficient number of workpieces of a specific category, and the number of these workpieces exceeds a preset threshold. If it is confirmed that the workpieces have been processed, the system searches the maintenance reference model to find the specified expected change trend related to the specific category of workpieces. The specified expected change trend is usually represented in the form of a curve graph, reflecting the law of the change of the deformation degree of the workpiece surface over time.

[0112] Furthermore, the efficient adsorption and release control system of the electronic vacuum chuck also includes:

[0113] The actual change trend generation module 300 is used to extract local operation logs of a specified number and interval time rules when the target adsorption device processes the specific category of workpieces based on historical operation logs, and analyze the actual change trend of the workpiece surface deformation when the target adsorption device processes the specific category of workpieces in actual operation based on these local operation logs.

[0114] Specifically, Figure 7 It shows a structural block diagram of the actual change trend generating module 300 in the system provided by the embodiment of the present invention.

[0115] Among them, in the preferred implementation mode provided by the present invention, the actual change trend generating module 300 specifically includes:

[0116] The local operation log acquisition unit 301 is used to extract a number of local operation logs that meet the specified quantity and time interval rules when the target adsorption device processes a specific type of workpiece according to the historical operation logs;

[0117] A local operation log parsing unit 302 is used to parse these local operation logs and obtain historical images of the workpiece surface area close to the adsorption device during the process of the target adsorption device adsorbing the workpiece;

[0118] The actual change trend generating unit 303 is used to analyze each historical image using machine vision technology, determine the corresponding degree of deformation of the workpiece surface, and plot all deformation degree values ​​into a curve graph in chronological order to obtain the actual change trend of the workpiece surface deformation when the target adsorption device processes a specific type of workpiece in actual operation.

[0119] In the embodiment of the present invention, the specified quantity and time interval rule refers to the local operation logs extracted from the historical operation logs, and their quantity and time interval should be consistent with the curve of the specified expected change trend in the maintenance reference model. In this way, it is ensured that the samples extracted from the historical data can accurately reflect the change trend of the target adsorption device processing the workpiece under the same conditions, so as to be effectively compared with the expected trend.

[0120] Each historical image is analyzed using machine vision technology. The specific implementation process is as follows: First, historical images of the workpiece surface near the adsorption device area are collected through a camera or other imaging device. Then, existing computer vision algorithms, such as image processing technology based on convolutional neural networks (CNN), are applied to perform image preprocessing, feature extraction, and classification. Through these technologies, the system can identify light patterns or surface marks on the workpiece surface and calculate the deformation of the workpiece surface caused by the adsorption force. Machine vision technology compares the images before and after the deformation of the workpiece surface and uses algorithms such as edge detection and morphological analysis to measure the magnitude of the deformation. Finally, these measurements are converted into deformation degrees, and deformation curves are generated according to the time sequence to provide quantitative analysis of the deformation of the workpiece surface.

[0121] The actual change trend of the workpiece surface deformation specifically reflects the deformation of the workpiece surface under the action of the adsorption device in the actual operation of the target adsorption device, as the adsorption force changes during the adsorption process, the material properties of the workpiece and the influence of environmental factors. This change trend can show the degree of deformation of the workpiece at different time points or under different adsorption forces, and then reveal the influence of the adsorption force on the deformation of the workpiece surface, as well as the changes in the adsorption device's processing effect on the workpiece in actual work. This information is helpful to analyze the working performance of the target adsorption device, optimize the adsorption force adjustment strategy, and ensure the quality and efficiency of workpiece processing.

[0122] Furthermore, the efficient adsorption and release control system of the electronic vacuum chuck also includes:

[0123] The adjustment increase optimization module 400 is used to quantify the deviation between the actual change trend and the specified expected change trend, and use the deviation as a correction factor to optimize the current adsorption force adjustment increase.

[0124] Specifically, Figure 8 It shows a structural block diagram of the adjustment increase optimization module 400 in the system provided by an embodiment of the present invention.

[0125] Among them, in the preferred embodiment provided by the present invention, the adjustment increase optimization module 400 specifically includes:

[0126] The difference quantification unit 401 is used to quantify the average slope difference between the actual change trend and the expected change trend, and determine the difference value;

[0127] The adjustment increase optimization unit 402 is used to call a preset optimization formula, input the deviation value as a correction factor into the preset optimization formula, and optimize the current adsorption force adjustment increase.

[0128] The preset optimization formula is: , where F opt Refers to the optimized adsorption force adjustment increase, Fpre Refers to the increase in the adsorption force adjustment before optimization. Slope actual Refers to the average slope of the specified expected change trend, Slope tageted Refers to the average slope of the actual change trend, It refers to the correction factor, that is, the deviation value between the actual change trend and the specified expected change trend, and K refers to the adjustment coefficient of the correction factor.

[0129] In an embodiment of the present invention, the difference in the average slope between the actual change trend and the expected change trend is quantified as a correction factor to optimize the adsorption force adjustment increase this time, because it can effectively reflect the decay of the target adsorption device during use. If the average slope of the actual change trend is greater than the average slope of the expected change trend, it means that the adsorption force of the target adsorption device decays faster than expected with the increase in usage time, which indicates that the performance degradation of the adsorption device is more significant than expected during design. In this case, the system needs to slightly increase the adsorption force adjustment increase to compensate for this additional decay and ensure that the adsorption device can continue to work stably. On the contrary, if the slope of the actual change trend is less than expected, indicating that the decay rate of the adsorption device is slower, the adsorption force adjustment increase can be appropriately reduced to avoid unnecessary energy waste.

[0130] The specific significance and benefit of this optimization method based on the average slope difference is that it can more accurately model and correct the degradation of the equipment. In this way, the adsorption force can be dynamically adjusted according to the actual use of the equipment to ensure the efficiency and stability of the equipment in long-term use. Compared with the traditional adjustment method that only relies on time or fixed rules, this method is more flexible and intelligent, and can effectively extend the service life of the equipment and improve production efficiency.

[0131] In the existing technology, there are relatively few applications that adjust based on slope differences, and most existing methods rely on the use time of the equipment or regular manual maintenance. However, the method of adjusting the adsorption force increase by quantifying the difference between the actual and expected slopes can adapt to changes in the equipment status in real time and has higher intelligence and adaptability.

[0132] The preset optimization formula mentioned above is only a more intuitive calculation method to reflect the impact of the difference between the actual change trend and the expected change trend on the adsorption force adjustment increase. In fact, in addition to using the preset optimization formula, other calculation methods can also be used, such as machine learning algorithms, which automatically optimize the adsorption force adjustment strategy by learning from historical operation data. Through intelligent algorithms, the calculation method of the correction factor can be dynamically adjusted, allowing the system to be optimized under more complex working conditions.

[0133] The following example illustrates how to optimize the adsorption force adjustment increase based on the correction factor:

[0134] Assume that the initial increase in the adsorption force adjustment is 20%. In actual applications, the average slope of the actual change trend of the target adsorption device is 0.8, and the average slope of the expected change trend is 1.0, with a difference of 0.2. According to the preset optimization formula, the correction factor is calculated as the ratio between the difference and the adsorption force adjustment increase, for example, the correction factor is 0.1. Therefore, the optimized adsorption force adjustment increase is the initial adsorption force adjustment increase of 20% multiplied by 1 minus the correction factor of 0.1, that is, the optimized increase is 18%. In this way, the system can ensure that the adsorption force adjustment is more in line with the actual working conditions of the target adsorption device, thereby improving work efficiency and energy saving.

[0135] It should be understood that, although each step in the flow chart of each embodiment of the present invention is shown in sequence according to the indication of the arrow, these steps are not necessarily performed in sequence according to the order indicated by the arrow. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be performed in other orders. Moreover, at least a portion of the steps in each embodiment may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these sub-steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with at least a portion of other steps or sub-steps or stages of other steps.

[0136] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0137] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0138] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

[0139] 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 and improvements made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. An efficient adsorption and release control method for an electronic vacuum chuck, characterized in that: The method comprises: When the target adsorption device enters the first maintenance cycle, the adsorption force adjustment increase is determined and the corresponding maintenance reference model and the historical operation log of the target adsorption device are obtained; Parse the historical operation logs to analyze whether the target adsorption device has processed a specific category of workpieces predefined in the maintenance reference model. If it is confirmed that the target adsorption device has processed the specific category of workpieces, obtain the specified expected change trend of the workpiece surface deformation characteristics when the target adsorption device processes the specific category of workpieces from the maintenance reference model; Based on the historical operation logs, extract the local operation logs of the specified number and interval time rules when the target adsorption device processes the specific category of workpieces, and analyze the actual change trend of the surface deformation of the workpiece when the target adsorption device processes the specific category of workpieces in actual operation based on these local operation logs; The deviation between the actual change trend and the specified expected change trend is quantified, and the deviation is used as a correction factor to optimize the increase in the adsorption force adjustment.

2. The high-efficiency adsorption and release control method of the electronic vacuum chuck according to claim 1, characterized in that: The maintenance reference model refers to the standard expected change trend of the workpiece surface deformation degree as the target adsorption device adsorbs different types of workpieces under a standard working environment as the target adsorption device is used for an increasing period of time. The standard change trend is represented by a curve graph.

3. The high-efficiency adsorption and release control method of the electronic vacuum chuck according to claim 2, characterized in that: The steps of parsing the historical operation logs and analyzing whether the target adsorption device has processed a specific category of workpieces predefined in the maintenance reference model, and if it is confirmed that the target adsorption device has processed the specific category of workpieces, obtaining the specified expected change trend of the workpiece surface deformation characteristics when the target adsorption device processes the specific category of workpieces from the maintenance reference model include: Parse the historical operation log and confirm whether the target adsorption device has processed a specific category of workpieces that matches the predefined category in the maintenance reference model and the number of processed items exceeds a preset threshold; If it is confirmed that the workpiece has been processed, the specified expected change trend of the deformation characteristics of the workpiece surface when the target adsorption device processes a specific type of workpiece is obtained from the maintenance reference model.

4. The high-efficiency adsorption and release control method of the electronic vacuum chuck according to claim 3 is characterized in that: Based on the historical operation logs, extracting the local operation logs of the specified quantity and interval time rule when the target adsorption device processes the specific category of workpieces, and analyzing the actual change trend of the surface deformation of the workpiece when the target adsorption device processes the specific category of workpieces in actual operation according to these local operation logs, the steps include: According to the historical operation logs, extracting several local operation logs that meet the specified quantity and time interval rules when the target adsorption device processes a specific category of workpieces; Parse these local operation logs and obtain historical images of the workpiece surface area close to the adsorption device during the process of the target adsorption device adsorbing the workpiece; Machine vision technology is used to analyze each historical image to determine the corresponding degree of deformation of the workpiece surface, and all deformation degree values ​​are plotted into a curve graph in chronological order to obtain the actual change trend of the workpiece surface deformation when the target adsorption device processes a specific type of workpiece in actual operation.

5. The high-efficiency adsorption and release control method of the electronic vacuum chuck according to claim 4, characterized in that: The steps of quantifying the deviation between the actual change trend and the specified expected change trend and using the deviation as a correction factor to optimize the adsorption force adjustment increase include: Quantify the difference in average slope between the actual change trend and the expected change trend and determine the value of the difference; Call the preset optimization formula, input the deviation value as the correction factor into the preset optimization formula, and optimize the adsorption force adjustment increase this time.

6. The high-efficiency adsorption and release control method of the electronic vacuum chuck according to claim 5, characterized in that: The preset optimization formula is: , where F opt Refers to the optimized adsorption force adjustment increase, F pre Refers to the increase in the adsorption force adjustment before optimization. Slope actual Refers to the average slope of the actual change trend, Slope tageted Refers to the average slope of the specified expected trend. It refers to the correction factor, that is, the deviation value between the actual change trend and the specified expected change trend, and K refers to the adjustment coefficient of the correction factor.

7. The electronic vacuum chuck has an efficient adsorption and release control system, characterized in that: The system comprises: a data acquisition module, a specified expected change trend determination module, an actual change trend generation module and an adjustment increase optimization module, wherein: A data acquisition module, used to determine the adsorption force adjustment increase and obtain the corresponding maintenance reference model and the historical operation log of the target adsorption device when the target adsorption device enters the first maintenance cycle; The maintenance reference model refers to a standard expected change trend of the surface deformation degree of the workpiece as the use time of the target adsorption device increases when the target adsorption device adsorbs different types of workpieces under a standard working environment, and the standard change trend is represented in the form of a curve graph; A specified expected change trend determination module is used to parse the historical operation logs and analyze whether the target adsorption device has processed a specific category of workpieces predefined in the maintenance reference model. If it is confirmed that the target adsorption device has processed the specific category of workpieces, the specified expected change trend of the workpiece surface deformation characteristics when the target adsorption device processes the specific category of workpieces is obtained from the maintenance reference model; An actual change trend generation module is used to extract local operation logs of a specified number and interval time rules when the target adsorption device processes the specific category of workpieces based on historical operation logs, and analyze the actual change trend of the workpiece surface deformation when the target adsorption device processes the specific category of workpieces in actual operation based on these local operation logs; The adjustment increase optimization module is used to quantify the deviation between the actual change trend and the specified expected change trend, and use the deviation as a correction factor to optimize the adjustment increase of the adsorption force.

8. The high-efficiency adsorption and release control system of the electronic vacuum chuck according to claim 7, characterized in that: The specified expected change trend determination module specifically includes: A specific category determination unit, used for parsing the historical operation log and confirming whether the target adsorption device has processed a specific category of workpieces matching a predefined category in the maintenance reference model and the number of processed workpieces exceeds a preset threshold; The specified expected change trend acquisition unit is used to obtain the specified expected change trend of the workpiece surface deformation characteristics when the target adsorption device processes a specific type of workpiece from the maintenance reference model if the processing is confirmed.

9. The high-efficiency adsorption and release control system of the electronic vacuum chuck according to claim 8, characterized in that: The actual change trend generation module specifically includes: A local operation log acquisition unit is used to extract a number of local operation logs that meet the specified quantity and time interval rules when the target adsorption device processes a specific category of workpieces according to the historical operation logs; A local operation log parsing unit is used to parse these local operation logs and obtain therefrom historical images of the workpiece surface area close to the adsorption device during the process of the target adsorption device adsorbing the workpiece; The actual change trend generating unit is used to analyze each historical image using machine vision technology, determine the corresponding degree of deformation of the workpiece surface, and plot all deformation degree values ​​into a curve graph in chronological order, so as to obtain the actual change trend of the workpiece surface deformation when the target adsorption device processes a specific category of workpieces in actual operation.

10. The high-efficiency adsorption and release control system of the electronic vacuum chuck according to claim 9, characterized in that: The adjustment increase optimization module specifically includes: A difference quantification unit is used to quantify the average slope difference between the actual change trend and the expected change trend and determine the difference value; The adjustment increase optimization unit is used to call the preset optimization formula, input the deviation value as a correction factor into the preset optimization formula, and optimize the current adsorption force adjustment increase; The preset optimization formula is: , where F opt Refers to the optimized adsorption force adjustment increase, F pre Refers to the increase in the adsorption force adjustment before optimization. Slope actual Refers to the average slope of the specified expected change trend, Slope tageted Refers to the average slope of the actual change trend, It refers to the correction factor, that is, the deviation value between the actual change trend and the specified expected change trend, and K refers to the adjustment coefficient of the correction factor.

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