Mechanical arm vacuum adsorption force self-adaptive control system for glass production

Abstract

The invention discloses a mechanical arm vacuum adsorption force self-adaptive control system for glass production, relates to the technical field of mechanical arms, and solves the problems that an accurate deviation positioning and automatic debugging mechanism is lacked, and manual repeated trial and error adjustment often needs to be relied on. A visual standard verification mechanism is constructed, whether the total adsorption force meets the glass adsorption requirement or not is rapidly judged, and a first defense line of adsorption safety is ensured; the comprehensive verification end constructs an external circle and an internal diameter with the center point of the suction cup as the reference, screens the to-be-determined diameter through the regional feature difference and determines the associated steering angle, achieves the precise positioning of the adsorption angle deviation, and controls the mechanical arm suction cup to rotate and adsorb according to the associated steering angle. And a closed-loop optimization process of checking-debugging-re-checking is formed in combination with secondary parameter monitoring, so that the problem of insufficient adsorption force caused by improper adsorption angle is effectively solved.

Description

Technical Field

[0001] This invention relates to the field of robotic arm technology, specifically to an adaptive control system for vacuum adsorption force of a robotic arm used in glass production. Background Technology

[0002] In the glass production process, robotic vacuum adsorption technology is the core means to automate glass handling, assembly and other processes. Its adsorption stability directly determines production efficiency and product yield.

[0003] However, traditional robotic arm vacuum adsorption systems have many technical limitations, which constitute the main pain points in practical applications. The specific background technology is as follows: Traditional adsorption systems mostly use a single vacuum sensor to monitor the overall pressure inside the suction cup, which can only obtain average adsorption force data and cannot identify the local sealing status of the area where the suction cup contacts the glass.

[0004] Because glass production involves a variety of workpiece sizes and specifications, and glass surfaces are prone to dust residue, minor scratches, or irregular edges, a single sensor cannot capture the differences in adsorption force caused by localized leaks. This often results in a situation where "the overall vacuum level meets the standard, but the local adsorption force is insufficient," leading to risks such as glass detachment and breakage. Furthermore, traditional systems often rely on preset fixed values ​​based on manual experience. When changing to different glass sizes or when the working environment changes, the machine must be stopped and the suction cup parameters manually adjusted. This is not only time-consuming and labor-intensive, but also prone to causing low adsorption efficiency or workpiece damage due to improper parameter matching.

[0005] Furthermore, traditional systems lack precise deviation positioning and automatic adjustment mechanisms for key issues affecting sealing performance, such as adsorption angle deviation. They often rely on repeated manual trial and error adjustments, which further increases the uncertainty of the production process and makes it difficult to meet the demands of modern glass production for efficient, precise, and intelligent adsorption operations. Summary of the Invention

[0006] To address the shortcomings of existing technologies, this invention provides a vacuum adsorption force adaptive control system for robotic arms used in glass production. This system solves the problem of lacking precise deviation positioning and automatic adjustment mechanisms, which often require repeated manual trial and error adjustments.

[0007] To achieve the above objectives, the present invention provides the following technical solution: an adaptive control system for vacuum adsorption force of a robotic arm used in glass production, comprising: At the machine vision end, the overall external contour of the glass is scanned to identify the dimensional data associated with the glass; The parameter monitoring end monitors the transmission of various array sensors during the adsorption process of the robotic arm suction cup in real time, confirms the adsorption force parameters associated with each array sensor, and transmits the adsorption force parameters of each array sensor to the feature analysis end. On the feature analysis end, based on the adsorption force parameters associated with each array sensor and the dimensional parameters of the glass, the required adsorption force for the corresponding glass is determined, and it is identified whether the total adsorption force associated with the robotic arm's suction cups meets the standard. The specific method is as follows: The adsorption force parameters associated with each array sensor are determined and summed to obtain the total adsorption force associated with the entire robotic arm suction cup, and the total adsorption force is calibrated as XF. Then extract the size data associated with the glass, and confirm the required adsorption force XQ associated with the same size data from the big data in the cloud. The required adsorption force is a preset value. If XF ≥ XQ, then proceed with the normal adsorption process. If XF < XQ, then perform the comprehensive verification. The integrated calibration end calibrates the internal midpoint of the robotic arm's suction cup. Based on this midpoint, multiple sets of internal axes are determined. Then, based on the characteristics of the adsorption force changes associated with these internal axes, the associated steering angles are determined and transmitted to the fixed-point debugging end. The specific method is as follows: The suction areas associated with the entire robotic arm's suction cup are marked, and based on the suction force parameters associated with each array sensor, the suction force parameters associated with each different suction area are identified, and the suction force parameters associated with different suction areas are marked as X. k , where k represents different adsorption regions; The center point of the suction area corresponding to the robotic arm's suction cup is marked as the feature midpoint. Using the feature midpoint as the center and the maximum inner diameter of the suction area as the diameter, an outer circle is constructed with the feature midpoint as the center. Several sets of internal diameters associated with the outer circle are identified. Different suction areas associated with the same set of internal diameters are recorded as similar suction areas. Multiple sets of suction force parameters X associated with similar suction areas are then assigned. k Mean processing is performed to confirm the mean parameters, and the confirmed mean parameters are used as the regional characteristics of the same type of adsorption region. From the confirmed sets of regional features, select the two sets of regional features with the largest numerical differences, and record the two sets of regional features as undetermined features. Record the built-in diameter associated with the two sets of undetermined features as undetermined diameters, determine the maximum included angle between the two sets of undetermined diameters, record the confirmed maximum included angle as the associated steering angle, and transmit the confirmed associated steering angle to the fixed-point debugging terminal.

[0008] Preferably, the fixed-point debugging end determines the turning point in the adsorption area according to the determined associated turning angle, and controls the robotic arm suction cup to rotate and adsorb again according to the calibrated turning point, and then re-executes the parameter monitoring end to identify whether its various parameters meet the standards. The specific method for re-controlling the robotic arm's suction cup is as follows: Identify two sets of undetermined diameters associated with the associated turning angle, and record the intersection of the undetermined diameter and the edge contour of the adsorption region as the undetermined intersection point. Randomly select a set of associated turning angles as the undetermined angle, and record the two sets of undetermined intersection points associated with the undetermined angle as the angle association point. Determine the central angle JZ between the two angle-related points with respect to the turning angle, identify the built-in diameter associated with the central angle, and record the intersection of the built-in diameter and the adsorption region as the turning point. Control the robotic arm's suction cup to rotate clockwise or counterclockwise (JZ) to change the original suction point targeting the angle-related point to the turning point, completing the secondary suction process of the glass and re-verifying the values.

[0009] This invention provides an adaptive control system for vacuum adsorption force of a robotic arm used in glass production. Compared with existing technologies, it has the following advantages: This invention relies on array sensors to collect adsorption force parameters of each area in real time, and realizes the accurate quantification of single-point adsorption force by calculating the difference between "atmospheric pressure and monitoring pressure". It breaks through the limitation of traditional single sensor average vacuum degree detection and can promptly detect local sealing abnormalities. The feature analysis end compares the sum of adsorption force parameters with the adsorption force required by the cloud to build an intuitive compliance verification mechanism, quickly determining whether the total adsorption force meets the glass adsorption requirements, ensuring the first line of defense for adsorption safety. The comprehensive verification end constructs an outer circle and an inner diameter based on the center point of the suction cup, filters the undetermined diameter through regional feature differences, and determines the associated turning angle to achieve precise positioning of adsorption angle deviation; The fixed-point debugging end controls the rotation of the robotic arm's suction cup to adsorb based on the associated turning angle. Combined with secondary parameter monitoring, it forms a closed-loop optimization process of "verification-debugging-re-verification", which effectively solves the problem of insufficient adsorption force caused by improper adsorption angle. Overall, the system achieves full-process adaptive control from glass size recognition and adsorption force monitoring to deviation adjustment. This not only improves the stability and safety of glass adsorption and reduces the risk of glass damage or detachment due to adsorption failure, but also reduces manual intervention, shortens debugging time, and significantly improves the efficiency and intelligence level of adsorption operations in the glass production process. Attached Figure Description

[0010] Figure 1 This is a schematic diagram of the principle framework of the present invention. Detailed Implementation

[0011] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0012] First Embodiment Please see Figure 1 This application provides an adaptive control system for vacuum adsorption force of a robotic arm for glass production, including a machine vision end, a parameter monitoring end, a feature analysis end, a comprehensive verification end, and a fixed-point debugging end. The machine vision end and the parameter monitoring end are electrically connected to the input node of the feature analysis end, and the feature analysis end, the comprehensive verification end, and the fixed-point debugging end are electrically connected sequentially from the output node to the input node. In the machine vision section, a panoramic scan of the glass involved in adsorption is performed to confirm the overall external outline of the glass, identify the associated size data of the glass, and transmit the identified size data to the feature analysis section. Specifically, a panoramic image of the glass is confirmed using a vision device, and the overall edge outline of the glass is confirmed based on the Sobel algorithm. The overall appearance size of the glass is then confirmed based on the edge outline. Subsequently, an acoustic device is used to detect the internal thickness of the glass and confirm the thickness data, thereby comprehensively determining the overall size of the glass and confirming the comprehensive parameters of the glass. The acoustic device is located inside the machine vision section and can effectively detect the relevant thickness of the corresponding glass. The size data includes the outline length and thickness. Generally, only the thickness of a single point inside the glass needs to be detected. The parameter monitoring end monitors the transmission of various array sensors during the adsorption process of the robotic arm's suction cup in real time, confirming the adsorption force parameter associated with each array sensor (directly output by the array sensor; the adsorption force data of the corresponding array sensor monitoring area is confirmed based on the monitored pressure data and the actual atmospheric pressure data, i.e., the difference between atmospheric pressure and monitored pressure). The adsorption force parameter of each array sensor is transmitted to the feature analysis end. The adsorption force parameter is determined as follows: the pressure parameter monitored by the corresponding array sensor is calibrated as YL1, and the pressure parameter associated with the actual atmosphere is calibrated as YL2. The adsorption force parameter is determined by the formula: adsorption force parameter = YL2 - YL1. In the feature analysis section, based on the adsorption force parameters associated with each array sensor and the size parameters of the glass, the required adsorption force for the corresponding glass is determined, and it is identified whether the total adsorption force associated with the robotic arm suction cup meets the standard. If it meets the standard, normal adsorption processing is performed; if it does not meet the standard, a comprehensive verification is executed. Specifically, in the corresponding big data, each different piece of glass is associated with different size parameters. Based on the size parameters, the associated total adsorption force can be effectively determined. Then, a comprehensive verification is performed to determine whether the adsorption force generated by the robotic arm suction cup meets the standard, and a comprehensive explanation is provided.

[0013] The integrated calibration end calibrates the internal midpoint of the robotic arm's suction cup, then determines multiple sets of internal axes based on the internal midpoint, and determines the associated turning angle based on the adsorption force change characteristics associated with the internal axes, and transmits the determined associated turning angle to the fixed-point debugging end; specifically, the so-called associated turning angle means that the glass needs to be re-adsorbed, and during the second adsorption process, the fixed point needs to be re-confirmed and the adsorption angle associated with the suction cup needs to be adjusted so that the corresponding glass surface and the suction cup can achieve a sufficient adsorption effect.

[0014] Second Embodiment As a further embodiment of Embodiment 1, this embodiment mainly focuses on the process of verifying the total adsorption force of the robotic arm's suction cup, and its main execution end is the feature analysis end. Specifically, the feature analysis end identifies whether the total adsorption force associated with the robotic arm's suction cup meets the standard in the following way: The adsorption force parameters associated with each array sensor are determined and summed to obtain the total adsorption force associated with the entire robotic arm suction cup, and the total adsorption force is calibrated as XF. Next, extract the size data associated with the glass, and confirm the required adsorption force XQ associated with the same size data from the cloud big data. The required adsorption force is a preset value, which is preset by the operator in the cloud big data and belongs to the standard value. Each different size data is associated with a different required adsorption force. If XF≥XQ, it means that the total adsorption force of the robotic arm's suction cup meets the standard, and the normal adsorption process can be carried out. If XF < XQ, it means that the total adsorption force of the robotic arm's suction cup does not meet the standard. In this case, the comprehensive verification end is executed to verify the comprehensive adsorption characteristics of the entire robotic arm's suction cup and evaluate the correlation between adsorption characteristics.

[0015] Third Embodiment In the specific implementation process, compared with the above embodiments, this embodiment mainly focuses on the correlation verification process of the comprehensive verification end, and comprehensively confirms the correlation turning angle corresponding to the robotic arm suction cup; The specific method for determining the associated steering angle in the comprehensive verification end is as follows: The suction areas associated with the entire robotic arm's suction cup are marked, and based on the suction force parameters associated with each array sensor, the suction force parameters associated with each different suction area are identified, and the suction force parameters associated with different suction areas are marked as X. k , where k represents different adsorption regions; The center point of the suction area corresponding to the robotic arm's suction cup is marked as the feature midpoint. Using the feature midpoint as the center and the maximum inner diameter of the suction area as the diameter, an outer circle is constructed with the feature midpoint as the center. Several sets of internal diameters associated with the outer circle are identified. Different suction areas associated with the same set of internal diameters are recorded as similar suction areas. Multiple sets of suction force parameters X associated with similar suction areas are then assigned. k Mean processing is performed to confirm the mean parameters, and the confirmed mean parameters are used as the regional characteristics of the same type of adsorption region. From the confirmed sets of regional features, select the two sets of regional features with the largest numerical difference, and record the two sets of regional features as undetermined features. Record the built-in diameter associated with the two sets of undetermined features as undetermined diameters, determine the maximum included angle between the two sets of undetermined diameters, record the confirmed maximum included angle as the associated turning angle, and transmit the confirmed associated turning angle to the fixed-point debugging terminal. Specifically, in order to achieve better fixed-point debugging results, during the angle confirmation process, it is necessary to identify the inner diameter difference axis with the greatest difference based on the differences between different inner diameter areas. From the identified inner diameter difference axis, the built-in included angle is selected and used as the specific included angle that needs to be changed, thereby confirming and adjusting the angle so that the corresponding glass can achieve the optimal adsorption treatment effect during the adsorption process.

[0016] Among them, the fixed-point debugging end determines the turning point in the adsorption area according to the determined associated turning angle, and controls the robotic arm suction cup to rotate and adsorb again according to the calibrated turning point, and then re-executes the parameter monitoring end to identify whether its various parameters meet the standards. The specific method for re-controlling the robotic arm's suction cup is as follows: Identify the two sets of undetermined diameters associated with the associated turning angle, and record the intersection of the undetermined diameter and the edge contour of the adsorption region as the undetermined intersection point. Randomly select a set of associated turning angles as the undetermined angles, and record the two sets of undetermined intersection points associated with the undetermined angles as angle association points. There are generally two sets of undetermined angles. The two sets of undetermined diameters will produce four sets of included angles, among which the opposite angles are equal. Then there are two associated turning angles with the same value. Determine the central angle JZ between the two angle-related points with respect to the turning angle, identify the built-in diameter associated with the central angle, and record the intersection of the built-in diameter and the adsorption region as the turning point. Control the robotic arm's suction cup to rotate clockwise or counterclockwise (JZ) to change the original suction point targeting the angle-related point to the turning point, completing the secondary suction process of the glass and re-verifying the values. Specifically, in the subsequent numerical verification process, the total adsorption force and the required adsorption force are evaluated again to identify whether the numerical relationship between the adsorption forces meets the standards. Based on the identification results, the adsorption area of ​​the suction cup of the adsorption arm is re-marked and confirmed. From the marked and confirmed process, the relevant characteristics of the robotic arm suction cup are comprehensively confirmed until the adsorption force characteristics associated with the robotic arm suction cup meet the standards.

[0017] Some of the data in the above formulas are numerical calculations with dimensions removed, and the contents not described in detail in this specification are all prior art known to those skilled in the art.

[0018] The above embodiments are only used to illustrate the technical methods of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of the present invention without departing from the spirit and scope of the technical methods of the present invention.

Claims

1. An adaptive control system for vacuum adsorption force of a robotic arm used in glass production, characterized in that, include: At the machine vision end, the overall external contour of the glass is scanned to identify the dimensional data associated with the glass; The parameter monitoring end monitors the transmission of various array sensors during the adsorption process of the robotic arm suction cup in real time, confirms the adsorption force parameters associated with each array sensor, and transmits the adsorption force parameters of each array sensor to the feature analysis end. On the feature analysis end, based on the adsorption force parameters associated with each array sensor and the size parameters of the glass, the required adsorption force of the corresponding glass is confirmed, and it is identified whether the total adsorption force associated with the robotic arm suction cup meets the standard. The integrated calibration end calibrates the internal midpoint of the robotic arm's suction cup, then determines multiple sets of built-in axes based on the internal midpoint, and determines the associated turning angle based on the adsorption force change characteristics associated with the built-in axes, and transmits the determined associated turning angle to the fixed-point debugging end.

2. The adaptive control system for vacuum adsorption force of a robotic arm used in glass production according to claim 1, characterized in that, The specific method by which the feature analysis terminal identifies whether the total adsorption force associated with the robotic arm's suction cup meets the standard is as follows: The adsorption force parameters associated with each array sensor are determined and summed to obtain the total adsorption force associated with the entire robotic arm's suction cup, and the total adsorption force is calibrated as XF. Then extract the size data associated with the glass, and confirm the required adsorption force XQ associated with the same size data from the big data in the cloud. The required adsorption force is a preset value. If XF ≥ XQ, then the normal adsorption process can be performed.

3. The adaptive control system for vacuum adsorption force of a robotic arm used in glass production according to claim 2, characterized in that, If XF < XQ, then perform the comprehensive verification.

4. The adaptive control system for vacuum adsorption force of a robotic arm used in glass production according to claim 1, characterized in that, The specific method by which the comprehensive verification terminal determines the characteristics of adsorption force changes is as follows: The suction areas associated with the entire robotic arm's suction cup are marked, and based on the suction force parameters associated with each array sensor, the suction force parameters associated with each different suction area are identified, and the suction force parameters associated with different suction areas are marked as X. k , where k represents different adsorption regions; The center point of the suction area corresponding to the robotic arm's suction cup is marked as the feature midpoint. Using the feature midpoint as the center and the maximum inner diameter of the suction area as the diameter, an outer circle is constructed with the feature midpoint as the center. Several sets of internal diameters associated with the outer circle are identified. Different suction areas associated with the same set of internal diameters are recorded as similar suction areas. Multiple sets of suction force parameters X associated with similar suction areas are then assigned. k Mean processing is performed to confirm the mean parameters, and the confirmed mean parameters are used as the regional characteristics of the same type of adsorption region.

5. The adaptive control system for vacuum adsorption force of a robotic arm used in glass production according to claim 1, characterized in that, The specific method by which the integrated verification terminal determines the associated steering angle is as follows: From the confirmed sets of regional features, select the two sets of regional features with the largest numerical differences, and record the two sets of regional features as undetermined features. Record the built-in diameter associated with the two sets of undetermined features as undetermined diameters, determine the maximum included angle between the two sets of undetermined diameters, record the confirmed maximum included angle as the associated steering angle, and transmit the confirmed associated steering angle to the fixed-point debugging terminal.

6. The adaptive control system for vacuum adsorption force of a robotic arm used in glass production according to claim 5, characterized in that, The fixed-point debugging end determines the turning point in the adsorption area based on the determined associated turning angle, and controls the robotic arm suction cup to rotate and adsorb again based on the calibrated turning point. Then, the parameter monitoring end is re-executed to identify whether each parameter meets the standard.

7. The adaptive control system for vacuum adsorption force of a robotic arm used in glass production according to claim 6, characterized in that, The specific method by which the fixed-point debugging end re-controls the robotic arm's suction cup is as follows: Identify two sets of undetermined diameters associated with the associated turning angle, and record the intersection of the undetermined diameter and the edge contour of the adsorption region as the undetermined intersection point. Randomly select a set of associated turning angles as the undetermined angle, and record the two sets of undetermined intersection points associated with the undetermined angle as the angle association point. Determine the central angle JZ between the two angle-related points with respect to the turning angle, identify the built-in diameter associated with the central angle, and record the intersection of the built-in diameter and the adsorption region as the turning point. Control the robotic arm's suction cup to rotate clockwise or counterclockwise (JZ) to change the original suction point targeting the angle-related point to the turning point, completing the secondary suction process of the glass and re-verifying the values.

Images