An AI-based automatic addition of curve tolerance judgment window method

Abstract

The application belongs to the technical field of servo press detection, and discloses an automatic curve tolerance judgment window adding method based on AI, and the method steps of the curve tolerance judgment window adding method are as follows: step one, data loading and threshold calculation; step two, baseline determination; step three, maximum offset calculation; step four, curve simplification (based on threshold judgment); step five, iterative simplification; step six, simplified curve reconstruction; and step seven, tolerance window generation. The application proposes an innovative automatic data processing scheme for the complex problems in servo press monitoring, greatly reduces the demand for manual intervention by automatically loading historical press curves and accurately calculating tolerance thresholds, effectively improves work efficiency, dynamically compares the maximum distance between points and straight lines, ensures the accuracy of the tolerance judgment window, and makes the change trend of the press process more accurately reflected.

Description

Technical Field

[0001] This invention belongs to the field of servo press fitting inspection technology, specifically an AI-based method for automatically adding curve tolerance judgment windows. Background Technology

[0002] A servo press is a servo-driven press system used to produce various connectors through processes such as pressing, filling, riveting, stamping, and embossing. Servo presses are widely used in automated production plants as well as in manually controlled work environments. Servo press systems are commonly used in automated industry applications, such as engine and transmission system installation, steering systems, chassis, brakes, fuel injection pumps, airbags, and electric motors for components like windshield wipers in the new energy vehicle (NEV) sector. In addition, the medical product, electronics and home appliance, and power tool manufacturing industries are also important application areas for servo press systems.

[0003] In servo press applications, it is often necessary to add tolerance judgment windows to the pressing curve to monitor and evaluate the pressing process, thereby accurately ensuring the pressing process and effectively controlling the consistency of product pressing. For example... Figure 1 , Figure 2 This refers to the upper and lower envelope tolerance judgment windows commonly added to the press-fit curve. As can be seen from the figure, configuring the upper and lower envelope tolerance judgment windows is very complex, requiring accurate input of the coordinate values ​​of each point. For on-site process engineers, constantly adjusting the coordinate values ​​of the judgment windows to achieve accurate monitoring and evaluation of the press-fit process is a waste of time and resources. Therefore, this application addresses the inconveniences of the existing technology by making the following improvements. Summary of the Invention

[0004] The purpose of this invention is to provide an AI-based method for automatically adding curve tolerance judgment windows to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution: an AI-based method for automatically adding a curve tolerance judgment window, wherein the specific steps of the method for adding a curve tolerance judgment window are as follows:

[0006] Step 1, Data Loading and Threshold Calculation: Load historical pressing curve data, and calculate Dx and Dy for each pressing curve; take the maximum value of Dx and Dy as the threshold Dt for curve calculation. This threshold Dt is also used to generate the tolerance value of the curve tolerance judgment window.

[0007] Step 2, determine the baseline: Hash the points on the curve, select the point with the minimum X-axis coordinate as the starting point and the point with the maximum X-axis coordinate as the ending point, and connect these two points to form a straight line as the baseline;

[0008] Step 3, calculate the maximum offset: calculate the maximum distance Dmax from all points on the curve to the baseline (including the starting and ending points);

[0009] Step 4, Simplify the curve (based on threshold judgment):

[0010] If Dmax is less than Dt, then keep the first and last points, delete all intermediate points, and the simplified processing is complete;

[0011] If Dmax is greater than or equal to Dt, then take the point corresponding to Dmax as the new starting point, reconnect it with the ending point to form a new baseline, record the original starting point, and continue to the next step of processing;

[0012] Step 5, Iterative simplification: Repeat steps 3 and 4 above until the maximum distance Dmax from all points to the new baseline is less than Dt, at which point the simplification process ends;

[0013] Step 6, Reconstruct the simplified curve: Use all the points that serve as the starting point and the endpoint of the original curve to form the final simplified curve;

[0014] Step 7, Generate Tolerance Window: Shift the simplified curve from Step 6 along the positive and negative Y-axis by half the distance of Dt. The lines formed are the upper tolerance window and the lower tolerance window. Use these two lines to define the tolerance judgment window of the curve.

[0015] Preferably, the formulas for calculating Dx and Dy in step one are as follows:

[0016]

[0017] Preferably, the upper tolerance window and the lower tolerance window in step seven are respectively:

[0018]

[0019]

[0020] Preferably, the method further includes step eight, namely, dynamically adjusting the threshold Dt: after generating the tolerance window, according to the needs of the actual application scenario, the user is allowed to manually adjust the threshold Dt and re-execute steps two to seven to generate a tolerance judgment window that adapts to different precision requirements.

[0021] Preferably, the method further includes step nine, namely, anomaly detection: after generating the tolerance judgment window, the original pressing curve is traversed to determine whether each point on the curve falls within the tolerance judgment window. If there is a point that exceeds the tolerance window range, it is marked as an anomaly point and an anomaly report is output.

[0022] Preferably, the method further includes step ten, namely data visualization: displaying the original pressing curve, the simplified curve, and the tolerance judgment window to the user in the form of a graphical interface, so that the user can intuitively understand the curve tolerance and conduct subsequent analysis.

[0023] Preferably, the method also supports simultaneous processing of multiple curves, enabling the simultaneous loading and processing of multiple pressing curves, generating their respective tolerance judgment windows, thereby improving processing efficiency and automation level.

[0024] The beneficial effects of this invention are as follows:

[0025] This invention effectively solves the complex problem of tolerance judgment window setting in servo press pressing curve monitoring. Through a highly automated data processing method—loading historical curves and automatically calculating the threshold Dt—it significantly reduces manual intervention and improves work efficiency. Its mechanism of dynamically calculating Dmax and comparing it with the threshold Dt ensures the accuracy of the tolerance window, accurately reflecting changes in the pressing process and improving monitoring accuracy. This method is highly flexible, applicable to various curve types, and can adapt to different monitoring needs by adjusting the Dt calculation method. Simultaneously, it saves engineers time and effort, allowing them to focus more on process optimization and problem solving. The generated simplified curves and tolerance windows are clear and intuitive, facilitating rapid anomaly identification and response. Furthermore, this method is simple to implement and maintain, easily integrated into existing systems, and reduces maintenance costs. In summary, this solution brings a convenient, efficient, and accurate new experience to servo press pressing monitoring. Attached Figure Description

[0026] Figure 1 This is a schematic diagram of the tolerance judgment window for the existing press-fitting curve;

[0027] Figure 2 A schematic diagram showing the parameter settings for the existing press-fitting curve tolerance judgment window;

[0028] Figure 3 This is a schematic diagram of the loading and pressing history curve of the present invention;

[0029] Figure 4 This invention provides a flowchart illustrating the process of automatically adding a tolerance judgment window. Figure 1 ;

[0030] Figure 5 This invention provides a flowchart illustrating the process of automatically adding a tolerance judgment window. Figure 2 ;

[0031] Figure 6 This invention provides a flowchart illustrating the process of automatically adding a tolerance judgment window. Figure 3 ;

[0032] Figure 7 This invention provides a flowchart illustrating the process of automatically adding a tolerance judgment window. Figure 4 ;

[0033] Figure 8 This invention provides a flowchart illustrating the process of automatically adding a tolerance judgment window. Figure 5 ;

[0034] Figure 9 This is a simplified diagram showing the addition of a tolerance judgment window to the curve in this invention.

[0035] Figure 10 This is a schematic diagram showing the automatic addition of a tolerance judgment window to the press-fit curve of the present invention. Detailed Implementation

[0036] 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.

[0037] like Figures 1 to 10 As shown, this embodiment of the invention provides an AI-based method for automatically adding curve tolerance judgment windows. The specific steps of this method are as follows:

[0038] Step 1, Data Loading and Threshold Calculation: Load historical pressing curve data, and calculate Dx and Dy for each pressing curve; take the maximum value of Dx and Dy as the threshold Dt for curve calculation. This threshold Dt is also used to generate the tolerance value of the curve tolerance judgment window.

[0039] like Figure 3 As shown, curve 1 (green): Dx = 72.05, Dy = 37.2

[0040] Curve 2 (red): Dx = 71.95, Dy = 36.6

[0041] Curve 3 (blue): Dx = 80.6, Dy = 36.8

[0042] Curve 4 (purple): Dx = 69.55, Dy = 37.45

[0043] Curve 5 (orange): Dx = 68.45, Dy = 37.1

[0044] Based on the above data, Dt = 72.05;

[0045] Figure 3The seemingly continuous curve in the image is actually a series of discrete points in the underlying data of the controller. These points are labeled according to the acquisition order, but for ease of description and calculation, only about 30 points are retained, such as... Figure 4 , Figure 5 , Figure 6 , Figure 7 , Figure 8 As shown;

[0046] Step 2, determine the baseline: Hash the points on the curve, select the point with the minimum X-axis coordinate as the starting point and the point with the maximum X-axis coordinate as the ending point, and connect these two points to form a straight line as the baseline;

[0047] Step 3, calculate the maximum offset: calculate the maximum distance Dmax from all points on the curve to the baseline (including the starting and ending points);

[0048] The calculation results in the table below show that the maximum distance is 323.359 (the 10th point).

[0049]

[0050]

[0051] Take the 10th point as the new starting point and draw a straight line with the last point. Calculate the maximum distance Dmax from the 10th point to this line. From the calculation results in the table below, the maximum distance is 488.272 (the 13th point).

[0052] Point number Distance from a point to a line 10 0 11 211.247 12 445.408 13 488.272 14 488.095 15 461.994 16 432.043 17 381.506 18 357.552 19 351.288 20 348.401 21 255.227 22 231.56 23 135.92 24 129.006 25 107.716 26 80.4352 27 59.1795 28 43.1689 29 30.4594 30 0

[0053] Take the 13th point as the new starting point, and draw a straight line with the last point. Calculate the maximum distance Dmax from the 13th point to this line. If the calculation results in the table below do not exceed Dt (a pre-set threshold), then the process ends.

[0054] Point number Distance from a point to a line 13 0 14 15.8325 15 11.1964 16 1.86702 17 13.9199 18 16.4457 19 18.3711 20 17.1024 21 2.41585 22 4.55965 23 23.0157 24 21.5584 25 15.9894 26 9.42698 27 1.00758 28 4.95055 29 14.112 30 0

[0055] From the above algorithm, we can find points numbered 1, 10, 13, and 30. Connecting these points and combining them with the tolerance value Dt of the curve tolerance judgment window, the upper tolerance window is formed by adding Dt / 2 to the Y-axis coordinate; the lower tolerance window is formed by subtracting Dt / 2 from the Y-axis coordinate. Figure 9 As shown;

[0056] Following the same method, the final curve tolerance judgment window can be fitted from the five historical curves in the first step, such as... Figure 10 As shown.

[0057] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0058] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for automatically adding curve tolerance judgment windows based on AI, characterized in that: The specific steps for adding a curve tolerance judgment window are as follows: Step 1, Data Loading and Threshold Calculation: Load historical pressing curve data, and calculate Dx and Dy for each pressing curve; take the maximum value of Dx and Dy as the threshold Dt for curve calculation. This threshold Dt is also used to generate the tolerance value of the curve tolerance judgment window. Step 2, determine the baseline: Hash the points on the curve, select the point with the minimum X-axis coordinate as the starting point and the point with the maximum X-axis coordinate as the ending point, and connect these two points to form a straight line as the baseline; Step 3, calculate the maximum offset: calculate the maximum distance Dmax from all points on the curve to the baseline; Step 4, simplify the curve: If Dmax is less than Dt, then keep the first and last points, delete all intermediate points, and the simplified processing is complete; If Dmax is greater than or equal to Dt, then take the point corresponding to Dmax as the new starting point, reconnect it with the ending point to form a new baseline, record the original starting point, and continue to the next step of processing; Step 5, Iterative simplification: Repeat steps 3 and 4 above until the maximum distance Dmax from all points to the new baseline is less than Dt, at which point the simplification process ends; Step 6, Reconstruct the simplified curve: Use all the points that serve as the starting point and the endpoint of the original curve to form the final simplified curve; Step 7, Generate Tolerance Window: Shift the simplified curve from Step 6 along the positive and negative Y-axis by half the distance of Dt. The lines formed are the upper tolerance window and the lower tolerance window. Use these two lines to define the tolerance judgment window of the curve. The formulas for calculating Dx and Dy in step one are as follows: Dx= ; That= 。 2. The method for automatically adding curve tolerance judgment windows based on AI according to claim 1, characterized in that: The upper tolerance window and lower tolerance window in step seven are respectively: Upper tolerance window = Y-axis coordinate + ; Lower tolerance window = Y-axis coordinate - .

3. The method for automatically adding curve tolerance judgment windows based on AI according to claim 1, characterized in that: The method also includes step eight, namely, dynamically adjusting the threshold Dt: after generating the tolerance window, the user is allowed to manually adjust the threshold Dt according to the needs of the actual application scenario, and steps two to seven are re-executed to generate a tolerance judgment window that adapts to different precision requirements.

4. The method for automatically adding curve tolerance judgment windows based on AI according to claim 1, characterized in that: The method also includes step nine, namely, anomaly detection: after generating the tolerance judgment window, the original pressing curve is traversed to determine whether each point on the curve falls within the tolerance judgment window. If there is a point that exceeds the tolerance window range, it is marked as an anomaly point and an anomaly report is output.

5. The method for automatically adding curve tolerance judgment windows based on AI according to claim 1, characterized in that: The method also includes step ten, namely data visualization: the original pressing curve, the simplified curve, and the tolerance judgment window are displayed to the user in the form of a graphical interface so that the user can intuitively understand the curve tolerance and conduct subsequent analysis.

6. The method for automatically adding curve tolerance judgment windows based on AI according to claim 1, characterized in that: This method also supports simultaneous processing of multiple curves, enabling the simultaneous loading and processing of multiple pressing curves, generating their respective tolerance judgment windows, thereby improving processing efficiency and automation.

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