Reverse gap detection method, system, terminal device, and storage medium

Abstract

This application relates to the field of laser processing technology, and more particularly to a method, system, terminal device, and storage medium for detecting backlash. The backlash detection method includes: controlling a laser cutting machine to return to its mechanical origin, executing a specific scribing program and initiating a reverse grid drawing motion; using a vision system to identify and measure the grid lines; and combining image processing technology to calculate the mechanical backlash. This method eliminates the need for expensive third-party testing tools, is simple to operate, highly automated, and can quickly and accurately detect mechanical backlash. It adapts to the time-varying characteristics of backlash in the belt and synchronous gear transmission structures of laser cutting machines, meets the requirements for equipment error detection, reduces measurement costs, and eliminates human error. The system, terminal device, and storage medium provided in this application, being based on the backlash detection method, also possess the aforementioned technical effects.

Description

Technical Field

[0001] This application relates to the field of laser processing technology, and in particular to a method, system, terminal device and storage medium for detecting backlash. Background Technology

[0002] In the field of laser cutting machines, due to cost constraints and limitations in the structural design of the equipment itself, most laser cutting machines use belt and synchronous gear transmission structures. Due to the material and structural relationship of the synchronous gears and belts, a certain degree of mechanical backlash will be caused. The existence of mechanical backlash causes problems such as the cut circle not being round, not closing, and not sealing.

[0003] To ensure the quality of laser cutting, mechanical backlash compensation is essential. Therefore, when implementing mechanical backlash compensation, the ability to quickly detect the backlash is crucial. Traditional detection methods are twofold: one involves cutting a circular pattern and manually observing the misalignment error at the points where the pattern doesn't close to roughly determine the backlash size. This method is not only inaccurate but also relies on manual judgment, making it prone to human error. The other method uses third-party professional testing tools such as laser interferometers for measurement. While this method offers higher accuracy, the equipment is expensive, the testing process is complex and time-consuming, and requires specialized operators, failing to meet the needs of rapid detection and real-time monitoring in production environments.

[0004] Furthermore, since the backlash of belt and synchronous gear transmission structures changes with factors such as the operating time of the equipment and the temperature of the operating environment, i.e., it is time-varying, there is an urgent need for a method that does not rely on third-party testing tools, is easy to operate, and can quickly and accurately detect mechanical backlash in order to meet the needs of real-time detection and compensation of backlash in the production process. Summary of the Invention

[0005] This application provides a method, system, terminal device, and storage medium for detecting backlash, which can effectively solve the above-mentioned or other potential technical problems.

[0006] The first aspect of this application is to provide a method for detecting backlash, comprising:

[0007] The control equipment returns to the mechanical origin, ensuring that there is no backlash in the positive XY axis directions;

[0008] Execute the scribing program to scribble grid lines with an interval of D on the device. The number of grid lines is N, and the total length is L1.

[0009] Initiate a grid drawing motion in the negative direction of the XY axis. The preset value for the width superposition of the grid in the negative direction is L. The preset mechanical backlash of the device is E. Then the actual width of the first grid line is D1=D+LE, and the width of the nth scale line is Dn=D+L.

[0010] The system identifies grid lines using a vision system, records the number of grid lines along the direction toward the machine origin, and finds the index n of the grid lines that are approximately aligned vertically.

[0011] The error S between approximately aligned grid lines is measured by a camera. When S is less than the preset value L / 2, the final mechanical backlash E = n × L.

[0012] In an optional embodiment according to the first aspect, the return of the control device to the mechanical origin specifically includes:

[0013] The control device starts moving in the negative directions of the X and Y axes, triggers the origin switch, and then moves in the opposite direction a certain distance.

[0014] Perform a second return-to-origin operation;

[0015] After the control device moves a certain distance in the positive direction of the XY axis, the mechanical origin position is determined.

[0016] In an optional embodiment according to the first aspect, the line drawing procedure is performed to draw a grid with an interval of D, where D is 2 mm, the number of grid lines N is 50, and the total length L1 is 100 mm.

[0017] In an optional embodiment according to the first aspect, the initiation of the grid drawing motion is directed toward the negative direction of the XY axis, and the width superposition amount of the negative direction grid is preset to L, where L is 0.02 mm.

[0018] In an optional embodiment according to the first aspect, identifying grid lines via a vision system includes identifying grid lines via camera vision, and further includes processing the acquired image as follows:

[0019] Real-time image acquisition and machine coordinate binding: High-precision world coordinates are acquired synchronously when the industrial camera is used to capture images. The positioning data is bound with image metadata to form the original image dataset in world coordinates.

[0020] After performing grayscale conversion on the original image, a binary image is generated using a dynamic thresholding method, which specifically includes initial threshold calculation based on histogram distribution features, noise elimination combined with morphological opening and closing operations, and iterative threshold optimization with edge preservation.

[0021] In an alternative embodiment according to the first aspect, effective feature lines are extracted from the binary image by employing edge detection algorithms based on existing feature preset parameters, gradient distribution, connected component analysis combined with area threshold filtering, and linear features identified through Hough transform.

[0022] In an optional embodiment according to the first aspect, geometric analysis is performed on the identified and filtered feature lines, the center coordinates of each line region are calculated using the contour centroid positioning method, and the pixel coordinates are converted into the world coordinate system through camera calibration parameters.

[0023] In an alternative embodiment according to the first aspect, topological sorting is performed based on the coordinate axis order, and the difference is calculated using the Euclidean distance between adjacent center points.

[0024] In an optional embodiment of the first aspect, the identification of grid lines by a vision system includes measurement using a third-party two-dimensional detection device, during which relevant data is obtained when the grid lines are approximately aligned by comparing the upper and lower grid lines to calculate the mechanical backlash.

[0025] The backlash detection method provided in the first aspect of this application has at least the following technical advantages: Low-cost detection: This method fully utilizes the camera vision system equipped on the laser cutting machine (if the equipment is optional) or common third-party two-dimensional inspection equipment (when no vision solution is selected), eliminating the need to purchase expensive professional inspection equipment such as laser interferometers, significantly reducing inspection costs, and is especially suitable for cost-sensitive SMEs. High autonomy: By eliminating dependence on third-party professional inspection services, enterprises can independently conduct mechanical backlash detection at the production site at any time, without waiting for external inspection agencies, improving the autonomy and flexibility of production, enabling timely detection and resolution of backlash problems, and ensuring production continuity. Simple and efficient operation: The inspection process is designed to be simple and clear. Operators only need to start the equipment and perform the corresponding operations according to the preset program, without the need for complex professional skills training. At the same time, the inspection process is highly automated. From image acquisition to error calculation, everything can be completed automatically by the system, greatly shortening the inspection time, improving inspection efficiency, and meeting the needs of rapid inspection on the production site. Reliable accuracy: Through precise grid line engraving, scientific image processing algorithms, and strict visual matching error control (less than 0.02mm), this method can achieve accurate detection of mechanical backlash. Compared to the traditional, coarse method of judging backlash by cutting a circle, the detection accuracy has been significantly improved. Although it is slightly less accurate than a laser interferometer, it fully meets the error tolerance requirements of belt and synchronous gear transmission mechanisms in laser CO2 processing, providing reliable data support for backlash compensation and effectively improving the precision and product quality of laser cutting. It eliminates human error: the entire detection process requires no manual observation or judgment, avoiding errors caused by operator subjectivity and visual fatigue, ensuring the accuracy and consistency of detection results, and improving the reliability of detection data. Real-time monitoring: it supports one-click rapid measurement and can quickly respond to the time-varying characteristics of backlash in belt and synchronous gear transmission structures. During equipment operation, detection can be performed at any time as needed, realizing real-time monitoring of mechanical backlash, timely detection of changes in backlash and compensation adjustments, ensuring that the laser cutting machine is always in a high-precision working state.

[0026] A second aspect of this application also provides a rapid backlash detection system, based on the aforementioned backlash detection method, comprising:

[0027] The mesh generation module is used to control the equipment to draw mesh lines in both positive and negative directions;

[0028] The visual analysis module is used to identify alignment errors between the upper and lower grids;

[0029] The gap calculation module outputs compensation values ​​based on the alignment error.

[0030] A third aspect of this application also provides a terminal device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the computer program is executed by the processor, it implements the above-described reverse gap detection method.

[0031] In an alternative embodiment according to the third aspect, the memory is a non-volatile memory that stores a reverse gap list.

[0032] A fourth aspect of this application also provides a computer storage medium, comprising: storing a computer program, wherein when the computer program is executed by a processor, it implements the above-described backlash detection method.

[0033] The advantages of additional aspects of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0034] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0035] Figure 1 A schematic diagram of the backlash detection method provided in this application after the control equipment returns to the mechanical origin;

[0036] Figure 2 A schematic diagram of the back clearance detection method provided in the embodiments of this application during the execution of a scribing procedure;

[0037] Figure 3 This is a schematic diagram of the backlash detection method provided in this application embodiment when a grid drawing motion is initiated in the negative direction of the XY axis, and the preset value L of the width superposition amount of the grid in the negative direction is 0.02.

[0038] Figure 4 The reverse gap detection method provided in this application embodiment is a schematic diagram of the method when the grid lines are identified from right to left by the camera, the number of grid lines is recorded, and the grid lines that are approximately aligned vertically are found. The visual matching error S≤L / 2 is then used for visual matching.

[0039] Figure 5 for Figure 4 A magnified diagram of the camera image. Detailed Implementation

[0040] The technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0041] The components of the embodiments of this application described and illustrated in the accompanying drawings can be arranged and designed in a variety of different configurations. Therefore, the following detailed description of the embodiments of this application provided in the drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0042] In the following text, the terms "comprising," "having," and their cognates, which may be used in various embodiments of this application, are intended only to indicate a particular feature, number, step, operation, element, component, or combination thereof, and should not be construed as primarily excluding the presence of one or more other features, numbers, steps, operations, elements, components, or combinations thereof, or adding the possibility of one or more combinations thereof. Furthermore, the terms "first," "second," "third," etc., are used only for distinguishing descriptions and should not be construed as indicating or implying relative importance.

[0043] Unless otherwise specified, all terms used herein (including technical and scientific terms) shall have the same meaning as commonly understood by one of ordinary skill in the art to which the various embodiments of this application pertain. Terms (such as those defined in commonly used dictionaries) shall be interpreted as having the same meaning as in their contextual meaning in the relevant technical field and shall not be construed as having an idealized or overly formal meaning, unless clearly defined in the various embodiments of this application.

[0044] To facilitate understanding of the embodiments of this application, the background technology involved in the embodiments of the present invention will be introduced first.

[0045] In the field of laser cutting machines, due to cost constraints and limitations in the structural design of the equipment, most laser cutting machines use belt and synchronous gear transmission structures. Due to the material and structural relationship of the synchronous gears and belts, a certain degree of mechanical backlash occurs. This mechanical backlash causes problems such as incomplete or non-circular cuts, gaps, and incomplete sealing. To ensure the quality of laser cutting, mechanical backlash compensation is essential. Therefore, when implementing mechanical backlash compensation, the ability to quickly detect the mechanical backlash is crucial. Traditional detection methods are twofold: one is to cut a circular pattern and then manually observe the misalignment error at the point of non-closure to roughly determine the size of the backlash. This method is not only inaccurate but also relies on manual judgment, easily introducing human error. The other method uses third-party professional testing tools such as laser interferometers for measurement. Although this method has higher accuracy, the equipment is expensive, the testing process is complex and time-consuming, and requires professional operators, failing to meet the needs of rapid detection and real-time monitoring on the production site. Furthermore, since the backlash of belt and synchronous gear transmission structures changes with factors such as the operating time of the equipment and the temperature of the operating environment, i.e., it is time-varying, there is an urgent need for a method that does not rely on third-party testing tools, is easy to operate, and can quickly and accurately detect mechanical backlash in order to meet the needs of real-time detection and compensation of backlash in the production process.

[0046] In view of this, the backlash detection method provided in this application overcomes the shortcomings of existing detection methods. It does not require expensive third-party detection tools. Through vision technology and a specific detection process, it can quickly and accurately detect the mechanical backlash of laser cutting machines, meet the needs of real-time detection on the production site, provide accurate data support for mechanical backlash compensation, thereby improving the precision of laser cutting and product quality, reducing production costs, and increasing production efficiency.

[0047] Specifically, please refer to Figures 1 to 5 The backlash detection method provided in this application includes: controlling the device to return to the mechanical origin so that there is no backlash in the positive direction of the XY axis;

[0048] Execute the scribing program to scribble grid lines with an interval of D on the device. The number of grid lines is N, and the total length is L1.

[0049] Initiate a grid drawing motion in the negative direction of the XY axis. The preset value for the width superposition of the grid in the negative direction is L. The preset mechanical backlash of the device is E. Then the actual width of the first grid line is D1=D+LE, and the width of the nth scale line is Dn=D+L.

[0050] The system identifies grid lines using a vision system, records the number of grid lines along the direction toward the machine origin, and finds the index n of the grid lines that are approximately aligned vertically.

[0051] The error S between approximately aligned grid lines is measured by a camera. When S is less than the preset value L / 2, the final mechanical backlash E = n × L.

[0052] In an optional exemplary embodiment, the return of the control device to the mechanical origin specifically includes:

[0053] The control device starts moving in the negative directions of the X and Y axes, triggers the origin switch, and then moves in the opposite direction a certain distance.

[0054] Perform a second return-to-origin operation;

[0055] After the control device moves a certain distance in the positive direction of the XY axis, the mechanical origin position is determined.

[0056] In an optional exemplary embodiment, the line drawing procedure is performed to draw a grid with an interval of D, where D is 2 mm, the number of grid lines N is 50, and the total length L1 is 100 mm.

[0057] In an optional exemplary embodiment, the initiation of the grid drawing motion is directed in the negative direction of the XY axis, and the preset value of the width superposition of the grid in the negative direction is L, where L is 0.02mm.

[0058] It should be noted that the default value for the width overlap of the negative direction grid is L, where L is the overlap or increase on the width D. The setting value of L is the accuracy requirement of the device. For example, if the accuracy requirement of the device is 0.02mm, then L=0.02mm can be set; if the accuracy requirement is higher, such as 0.01mm, then L=0.01mm can be set.

[0059] In an optional exemplary embodiment, identifying grid lines via a vision system includes identifying grid lines via camera vision, and further includes processing the acquired image as follows:

[0060] Real-time image acquisition and machine coordinate binding: High-precision world coordinates are acquired synchronously when the industrial camera is used to capture images. The positioning data is bound with image metadata to form the original image dataset in world coordinates.

[0061] After performing grayscale conversion on the original image, a binary image is generated using a dynamic thresholding method, which specifically includes initial threshold calculation based on histogram distribution features, noise elimination combined with morphological opening and closing operations, and iterative threshold optimization with edge preservation.

[0062] In an optional exemplary embodiment, effective feature lines are extracted from the binary image by employing edge detection algorithms based on existing feature preset parameters, gradient distribution, connected component analysis combined with area threshold filtering, and Hough transform to identify linear features.

[0063] In an optional exemplary embodiment, geometric analysis is performed on the identified and filtered feature lines. The center coordinates of each line region are calculated using the contour centroid localization method, and the pixel coordinates are converted into the world coordinate system using camera calibration parameters. Specifically, in this embodiment, topological sorting is performed based on the coordinate axis order, and the difference is calculated using the Euclidean distance between adjacent center points.

[0064] In an optional exemplary embodiment, the identification of grid lines by the vision system includes using a third-party two-dimensional detection device for measurement. During the measurement, relevant data on the approximate alignment of the grid lines is obtained by comparing the upper and lower grid lines to calculate the mechanical backlash.

[0065] Example 1: To make the backlash detection method provided in this application clearer, the specific steps are described below with reference to preset values:

[0066] To control the laser cutting machine to return to its mechanical origin: The control device starts moving in the negative X and Y directions. After the origin switch is triggered, it moves in the opposite direction (e.g., 5mm) to perform a second return-to-origin operation, ensuring the accuracy of the origin position. Finally, the control device moves in the positive X and Y directions by a certain offset (e.g., 10mm) to determine this position as the mechanical origin. At this point, there is no backlash in the positive X and Y directions.

[0067] Perform the scribing procedure: After the equipment is at its mechanical origin position, execute the scribing procedure to scribe a grid with an interval of D on the working plane of the equipment. Here, D = 2mm, the number of grid lines N = 50, and the total grid length L1 = 100mm. This regular grid pattern provides a reference for subsequent backlash detection. It is understood that the grid interval D, the number of grid lines N, and the total grid length L1 are not limited here; in other specific embodiments, they can be adaptively adjusted according to the user's specific needs.

[0068] Initiate the grid drawing motion in the negative XY direction: The device is initiated to draw a grid in the negative XY direction. The width overlap of the negative direction grid is defined as L, where L = 0.02 mm. Assuming a mechanical backlash E exists, the actual width of the first grid line is D1 = D + LE, and the width of the nth scale line is Dn = D + L. During the grid drawing process in the negative direction, the actual width of the grid lines will change due to the backlash. The backlash is calculated by analyzing these changes.

[0069] Grid line recognition using camera vision: The camera vision system is used to identify grid lines. During the recognition process, the number of grid lines is recorded along the direction closest to the machine origin, i.e., from right to left in the view direction. Grid lines that are approximately aligned vertically are found, with the visual matching error less than a preset value (0.02mm). During the recognition process, the acquired images also need to be processed as follows:

[0070] Real-time image acquisition and machine coordinate binding: High-precision world coordinates are acquired synchronously when the industrial camera is used to capture images. The positioning data is bound with the image metadata to form the original image dataset in world coordinates, ensuring that the grid line positions in the image correspond to the actual machine coordinates.

[0071] Adaptive binarization processing: After performing grayscale conversion on the original image, a dynamic thresholding method is used to generate a binary image. Specifically, this includes initial threshold calculation based on histogram distribution characteristics, noise reduction combined with morphological opening and closing operations, and iterative threshold optimization with edge preservation to improve image sharpness and the recognizability of grid lines.

[0072] Feature data filtering mechanism: Effective feature lines are extracted from the binary image, and edge detection algorithms based on existing feature preset parameters (such as known line width and height), gradient distribution-based edge detection algorithms, connected component analysis combined with area threshold filtering, and Hough transform to identify linear features are used to accurately filter the features of grid lines.

[0073] Regional center localization and coordinate mapping: Geometric analysis is performed on the selected feature lines, and the center coordinates of each line region are calculated using the contour centroid localization method. The pixel coordinates are then converted into the world coordinate system through camera calibration parameters, realizing the conversion from image coordinates to actual machine coordinates.

[0074] Center sorting and difference compensation: Topological sorting is performed based on the coordinate axis order, and the difference is calculated using the Euclidean distance between adjacent center points, thereby accurately identifying and locating grid lines.

[0075] Calculating the mechanical backlash: The error S between approximately aligned grid lines is measured using a camera. When S is less than a preset value L / 2, the final mechanical backlash is calculated using the formula E=n×L. Here, n is the grid line number when counting from right to left, L is the preset value for the width superposition of the grid lines in the negative direction, and S is the measured error value between the approximately aligned grid lines. If the laser cutting machine does not use a camera vision solution, a third-party two-dimensional detection device is used for measurement. During measurement, the relevant data when the grid lines are approximately aligned is obtained by comparing the upper and lower grid lines, and the mechanical backlash is calculated using the same method.

[0076] Example 2: Specific example, taking a preset model laser cutting machine as an example, using a belt and synchronous gear transmission structure, to explain in detail the implementation process of the backlash detection method of the present invention.

[0077] Returning the control equipment to its mechanical origin: The operator selects the return-to-origin command on the laser cutting machine's control system interface. Upon receiving the command, the equipment begins to move in the negative X and Y directions. After triggering the origin switch, the equipment continues to move 5mm in the reverse direction, then performs a second return-to-origin operation to eliminate any potential deviations in the origin position caused by mechanical structure or other factors. Finally, the equipment moves 10mm in the positive X and Y directions, establishing this position as the mechanical origin. At this point, there is no backlash in the positive X and Y directions, preparing the equipment for subsequent inspection.

[0078] Executing the scribing program: After the equipment is at its mechanical origin position, the operator inputs the scribing program command into the control system, setting the grid line spacing D=2mm and the number of grid lines N=50. The equipment, according to the program command, precisely scribes the grid pattern on the working plane, ultimately forming a grid with a total length L1=100mm. During the scribing process, the laser head of the laser cutting machine moves according to the preset path and parameters to ensure the accuracy and quality of the grid lines.

[0079] Initiating the grid drawing motion in the negative XY direction: After completing the positive grid drawing, the device automatically initiates the grid drawing motion program in the negative XY direction. For example, if the device's accuracy requirement is 0.02mm, the width overlap of the negative direction grid can be defined as L=0.02mm. Due to the mechanical backlash in the device, when drawing the grid in the negative direction, the actual width of the first grid line becomes D1=D+LE (E is the mechanical backlash), and the width of the nth scale line is Dn=D+L. During the grid drawing process, the device's motion control system precisely controls the laser head's movement speed and position to ensure the uniformity and accuracy of the grid lines.

[0080] Camera vision is used to identify grid lines: The industrial camera equipped with the equipment starts working while drawing a grid in the negative direction, acquiring images on the working plane in real time and simultaneously obtaining high-precision world coordinates. The positioning data is bound with image metadata to form the original image dataset in world coordinates. The acquired original images are first converted to grayscale to facilitate subsequent processing. Then, a dynamic thresholding method is used to generate binary images. The specific process is as follows: an initial threshold is calculated based on histogram distribution characteristics, and the pixels in the image are divided into foreground and background according to the comparison of grayscale values ​​with the threshold; morphological opening and closing operations are combined to eliminate noise points and small interference areas in the image; iterative threshold optimization with edge preservation is used to further improve the contrast of the image and the clarity of the grid lines. When extracting effective feature lines from the binary image, the features of the grid lines are accurately screened using methods such as preset parameters based on existing features (the grid line width is known to be 0.1 mm, and the height is determined according to the actual situation), edge detection algorithms based on gradient distribution, connected component analysis combined with area threshold filtering (setting an area threshold to filter out interference areas with too small an area), and Hough transform to identify linear features. Geometric analysis was performed on the selected feature lines. The center coordinates of each line region were calculated using the contour centroid localization method, and the pixel coordinates were converted to the world coordinate system using camera calibration parameters. Finally, topological sorting was performed based on the coordinate axis order, and the difference between adjacent center points was calculated using the Euclidean distance. The number of grid lines was recorded from right to left to find grid lines that were approximately aligned vertically, while ensuring that the visual matching error was less than 0.02 mm.

[0081] Calculate the mechanical backlash: Measure the error S between approximately aligned grid lines using a camera. Assuming counting from right to left, find the grid line number n=15 that is approximately aligned. The measured error S=0.008mm, satisfying S≤L / 2. According to the formula E=n×L, the final mechanical backlash E=15×0.02=0.3mm. After obtaining the mechanical backlash, the operator can input this data into the laser cutting machine's backlash compensation system. The equipment will automatically adjust the cutting path based on the compensation data to compensate for the impact of the backlash on cutting accuracy and improve cutting quality.

[0082] Example 3: Using the same model laser cutting machine as in Example 2, but without the camera vision solution, a third-party two-dimensional inspection device is used for mechanical backlash detection. Similarly, the device is first controlled to return to the machine origin, and a scribing program is executed to draw a grid with an interval of D=2mm, a quantity of N=50 lines, and a total length L1=100mm. Then, the grid drawing motion in the negative XY direction is started, and the width superposition amount of the negative direction grid is defined as L=0.02mm.

[0083] After completing the mesh depiction, the 2D detection device is placed on the working plane of the laser cutting machine. The device's position and angle are adjusted to clearly capture the mesh pattern on the working plane. Images of the upper and lower mesh lines are captured using the image acquisition system of the 2D detection device. The device's built-in image processing software is used to compare the upper and lower mesh lines, and the approximately aligned mesh lines are manually observed and recorded as their index n. Simultaneously, the measurement function of the device is used to measure the error S between the approximately aligned mesh lines. Assuming the found approximately aligned mesh line index n=12, and the measured error S=0.007mm, satisfying S≤L / 2, the final mechanical backlash E=12×0.02=0.24mm is calculated using the formula E=n×L. The calculated mechanical backlash data is input into the laser cutting machine's control system for subsequent backlash compensation operations, thereby achieving the detection and compensation of the laser cutting machine's mechanical backlash and ensuring cutting accuracy.

[0084] This application also provides a rapid backlash detection system, based on the above-described backlash detection method, comprising:

[0085] The mesh generation module is used to control the equipment to draw mesh lines in both positive and negative directions;

[0086] The visual analysis module is used to identify alignment errors between the upper and lower grids;

[0087] The gap calculation module outputs compensation values ​​based on the alignment error.

[0088] The backlash rapid detection system provided in this application is based on the aforementioned backlash detection method and therefore also has the aforementioned technical effects.

[0089] This application also provides a terminal device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the computer program is executed by the processor, it implements the reverse gap detection method as described above.

[0090] In an optional exemplary embodiment, the memory is a non-volatile memory that stores a reverse gap list.

[0091] The terminal device provided in this application is used to implement the above-mentioned backlash detection method, and therefore also has the above-mentioned technical effects.

[0092] This application also provides a computer storage medium, comprising: storing a computer program, wherein when the computer program is executed by a processor, it implements the backlash detection method as described above.

[0093] The computer storage medium provided in this application is used to implement the above-described backlash detection method, and therefore also has the above-described technical effects.

[0094] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can also be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings show the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that, in alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and combinations of blocks in the block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0095] In addition, the functional modules or units in the various embodiments of this application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0096] If the aforementioned functions are implemented as software functional modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a smartphone, personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application.

[0097] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A method for detecting backlash, characterized in that, include: Control the equipment to return to the mechanical origin, so that there is no backlash in the positive direction of the X-axis or Y-axis; Execute the scribing program to scribing grid vertical lines with an interval width of D on the equipment. The scribing program uses the laser scribing function built into the laser cutting machine to scribing the grid vertical lines. The number of grid vertical lines is N, and the total length is L1. Initiate a vertical grid line drawing motion in the negative direction of the X-axis or Y-axis. The preset value for the width superposition of the grid vertical intervals in the negative direction is L. The preset mechanical backlash of the equipment is E. Then, the width of the first grid vertical interval is D1=D+LE, and the width of the nth grid vertical interval is Dn=D+L. Identify the grid vertical lines through the vision system, record the number of the grid vertical intervals along the direction towards the mechanical origin, and find the index n of the grid vertical intervals that are approximately aligned vertically. The error S between the vertical grid lines that are approximately aligned vertically is measured by the camera equipped on the laser cutting machine or by a third-party two-dimensional detection device. When S≤L / 2, the final mechanical backlash E=n×L.

2. The backlash detection method according to claim 1, characterized in that, The control device returning to the mechanical origin specifically includes: The control device starts moving in the negative directions of the X and Y axes, triggers the origin switch, and then moves in the opposite direction a certain distance. Perform a second return-to-origin operation; After the control device moves a certain distance in the positive direction of the X and Y axes, the mechanical origin position is determined.

3. The backlash detection method according to claim 1, characterized in that, The process of identifying grid vertical lines using a vision system includes identifying grid vertical lines using an industrial camera, and also includes processing the acquired images as follows: Real-time image acquisition is bound to the machine coordinate system. High-precision world coordinates are acquired synchronously when the industrial camera is shooting. The world coordinate positioning data is bound with the image metadata to form the original image dataset in the world coordinate system. After performing grayscale conversion on the original image, a binary image is generated using a dynamic thresholding method, which includes: initial threshold calculation based on histogram distribution features, noise elimination combined with morphological opening and closing operations, and iterative threshold optimization with edge preservation.

4. The backlash detection method according to claim 3, characterized in that, When extracting effective feature lines from a binary image, the following methods are used to accurately select the feature lines of the grid vertical lines: pre-setting parameters based on existing features, edge detection algorithms based on gradient distribution, filtering interference areas by combining connected component analysis with area thresholds, and identifying linear features through Hough transform.

5. A rapid backlash detection system, characterized in that, The reverse clearance detection method based on any one of claims 1 to 4 includes: The mesh generation module is used to control the equipment to draw vertical lines in both positive and negative directions. The visual analysis module is used to identify alignment errors of the vertical lines in the upper and lower grids; The gap calculation module outputs compensation values ​​based on the alignment error.

6. A terminal device, characterized in that, include: The memory, the processor, and the computer program stored in the memory and executable on the processor, wherein when executed by the processor, the computer program implements the backlash detection method as described in any one of claims 1 to 4.

7. The terminal device according to claim 6, characterized in that, The memory is a non-volatile memory, and the non-volatile memory stores a reverse gap list.

8. A computer storage medium, characterized in that, include: The device contains a computer program that, when executed by a processor, implements the backlash detection method as described in any one of claims 1 to 4.

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