Electronic warp and weft width machine vision measurement method and system

Abstract

The present application relates to a kind of electronic cloth warp and weft line width machine vision measurement method and system, it is related to electronic industry material technical field, it includes response to detection signal, obtains identification information;Acquisition image is collected;Real-time definition and real-time position are obtained by analyzing acquisition image, and maximum definition and the definition position corresponding to maximum definition are obtained;Warp and weft line direction are obtained by analyzing acquisition image;Warp and weft line direction are compared with the standard direction of prearrangement, and rotation direction and rotation angle are obtained;Control mobile control module is translated according to translation mode and obtains translation real-time image;Warp and weft line total number and warp and weft line width are obtained by analyzing translation real-time image;Warp and weft line density is calculated according to warp and weft line total number and total line width distance;Identification information, warp and weft line width and warp and weft line density are integrated to obtain warp and weft line information, and warp and weft line information is output.The present application has the effect of improving the measurement precision of electronic cloth warp and weft line width.

Description

Technical Field

[0001] This invention relates to the field of materials technology in the electronics industry, and in particular to a machine vision measurement method and system for the warp and weft width of electronic fabrics. Background Technology

[0002] Electronic cloth, also known as electronic-grade glass fiber cloth, is woven from ultra-fine electronic-grade glass fiber yarn with a single filament diameter of less than 9 micrometers. Due to its excellent properties such as high strength, insulation and high temperature resistance, it is widely used in consumer electronics, high-end computing power, communications, aerospace and military industries, and is a key industrial basic material.

[0003] In related technologies, the method for measuring warp and weft density is to use a suitable magnification device and manually count the number of warp and weft yarns per unit length. The method for measuring warp and weft width is to take a magnified picture of the electronic fabric and manually measure a certain number of warp and weft yarns.

[0004] Regarding the aforementioned technologies, existing methods for measuring warp and weft widths are limited by factors such as fabric correction angle errors, image clarity, and the reflective properties of the electronic fabric itself, making it difficult to achieve high measurement accuracy. Summary of the Invention

[0005] To improve the measurement accuracy of the warp and weft width of electronic fabric, this invention provides a machine vision measurement method and system for the warp and weft width of electronic fabric.

[0006] In a first aspect, the present invention provides a machine vision method for measuring the warp and weft width of electronic fabric, employing the following technical solution: A machine vision method for measuring the warp and weft width of electronic fabric includes: Step 1: In response to the detection signal, acquire identification information; Step 2: Control the movement control module to move according to the preset focus mode and acquire images; Step 3: Analyze the acquired images to obtain real-time sharpness and real-time location, and perform edge detection and frequency domain analysis on each real-time sharpness to obtain the maximum sharpness and the sharpness location corresponding to the maximum sharpness; Step 4: Control the movement control module to move to a clear position and analyze the acquired image to obtain the latitude and longitude directions; Step 5: Compare the latitude and longitude lines with the preset standard direction to obtain the rotation direction and rotation angle, and then control the movement control module to rotate according to the rotation direction and rotation angle; Step 6: Control the motion control module to perform translation according to the preset translation mode and acquire real-time translation images; Step 7: Analyze the real-time translation image to obtain the total number and width of latitude and longitude lines; Step 8: Obtain the bus width distance based on the real-time translation image, and calculate the latitude and longitude density based on the total number of latitude and longitude lines and the bus width distance; Step 9: Integrate the identification information, latitude and longitude line width, and latitude and longitude line density to obtain latitude and longitude line information, and output the latitude and longitude line information.

[0007] By adopting the above technical solution, the highest-resolution image is obtained through automatic focusing. Then, the shooting angle of the electronic cloth is adjusted according to the image to align the warp and weft directions with the standard direction. Finally, a complete real-time translational image is obtained through translation acquisition. The width and density of the warp and weft are analyzed, calculated, and output. Compared with traditional manual measurement and conventional machine vision measurement methods, this reduces focusing errors and angle deviations caused by manual operation, and can effectively improve the measurement accuracy of the width and density of the warp and weft of the electronic cloth.

[0008] Optionally, it also includes a control method for when latitude and longitude lines overlap, the method comprising: Step 80: Analyze the real-time translation image to obtain the current width; Step 81: If the current width falls within the preset normal line width range, then define the current width as the latitude and longitude line width; Step 82: If the current width does not fall within the normal line width range, obtain the adjacent latitude and longitude line numbers and the intersecting area from the real-time translation image based on the latitude and longitude lines corresponding to the current width; Step 83: Control the motion control module to move according to the preset vertical movement mode and acquire real-time vertical movement images; Step 84: Obtain the intersecting latitude and longitude line numbers corresponding to the current width based on the real-time vertical image and the adjacent latitude and longitude line numbers; Step 85: Obtain the width and number of intersecting latitude and longitude lines based on the intersecting latitude and longitude line numbers and the vertically shifted real-time image; Step 86: Update the total number of latitude and longitude lines and their widths based on the width and number of intersecting latitude and longitude lines; Step 87: Integrate the identification information and the interlaced area to obtain the interlaced information, and output the interlaced information.

[0009] By adopting the above technical solution, in response to the overlapping and interlacing of latitude and longitude lines during the interlacing process, images at different depth levels are acquired by vertical movement, the number of overlapping latitude and longitude lines is distinguished and the measurement results are corrected. This can reduce the statistical errors in line width and total number caused by the overlap of latitude and longitude lines, and further improve the accuracy of the measurement results.

[0010] Optionally, it also includes a control method for when latitude and longitude lines become sticky, the method comprising: Step 830: When the number of intersecting latitude and longitude lines in the vertical real-time image is always 1, the control module moves to the preset edge position according to the vertical movement mode and acquires the edge image; Step 831: Obtain the width of the bifurcated latitude and longitude lines, the number of bifurcated latitude and longitude lines, and the position of the sticky edge based on the intersecting latitude and longitude line numbers and the edge image; Step 832: Update the total number of meridians and the width of meridians based on the width and number of bifurcated meridians; Step 833: Obtain the sticky region based on the location of the sticky edge and the preset electronic cloth area; Step 834: Integrate the identification information and the sticky region to obtain sticky information, and output the sticky information.

[0011] By adopting the above technical solution, in cases where latitude and longitude lines are stuck together and cannot be separated and identified, the individual latitude and longitude lines can be identified by locating the edge of the stuck area. This corrects the measurement results of the total number and line width of latitude and longitude lines, avoids misidentifying multiple stuck latitude and longitude lines as one, and reduces the measurement error caused by latitude and longitude line sticking.

[0012] Optionally, a control method is also included when the edges of latitude and longitude lines are relatively blurred, the method including: Step 70: Perform edge detection on the real-time translation image to obtain the edge gradient magnitude of each latitude and longitude line; Step 71: If the edge gradient magnitude is less than the preset magnitude threshold, then define the corresponding latitude and longitude lines as fuzzy latitude and longitude lines; Step 72: Control the movement control module to move according to the preset fine-tuning focus mode and acquire the fine-tuning focus image; Step 73: Calculate the sharpness of the blurred area by fine-tuning the focus image, and compare the sharpness of each blurred area to obtain the maximum blur sharpness and the corresponding optimal focus position; Step 74: Control the movement control module to move to the optimal focus position and reacquire the corrected width of the blurred latitude and longitude lines; Step 75: Update the width of the latitude and longitude lines based on the corrected width.

[0013] By adopting the above technical solution, in the case of unclear edges of latitude and longitude lines leading to difficulty in accurately identifying boundaries, the focus is finely adjusted to re-acquire a clearer local image. The line width measurement results are corrected based on the image at the optimal focus position, which can avoid line width identification errors caused by blurred image edges and further improve measurement accuracy.

[0014] Optional, also includes: Step 740: When the control module moves to the optimal focus position, if the edge gradient amplitude of the blurred latitude and longitude lines is still less than the amplitude threshold, the edge contour is obtained based on the real-time translation image and the blurred latitude and longitude lines. Step 741: Calculate the contour undulation of the fuzzy latitude and longitude lines based on the edge contours; Step 742: When the contour undulation is greater than the preset undulation threshold, the area where the contour undulation is greater than the undulation threshold is defined as the burr area. Step 743: Perform a preset water spraying operation based on the burr area, and obtain a water spraying image after the water spraying operation is performed on the burr area; Step 744: Obtain the water spray correction width corresponding to the burr area based on the water spray image; Step 745: When the water spray correction width falls within the normal line width range, update the latitude and longitude line widths according to the water spray correction width; Step 746: When the water spray correction width does not fall within the normal line width range, integrate the burr area and marking information into burr information and output it.

[0015] By adopting the above technical solution, the problem of undulating contours on the surface of electronic cloth interfering with line width recognition can be addressed by spraying water to wet and adhere the burrs, making the true edges of the warp and weft threads clearer. This effectively reduces the line width recognition deviation caused by lint and burrs, further ensuring the accuracy of the overall measurement results.

[0016] Optional, also includes: Step 7440: Obtain the image of the burr area before the water spraying operation, and extract the width of the burr area before water spraying. Step 7441: Compare the corrected width of the water spray with the original width to obtain the width expansion amount; Step 7442: When the width expansion amount is greater than the preset expansion tolerance threshold, calculate the expansion compensation value based on the width expansion amount and the preset expansion coefficient; Step 7443: Perform reverse compensation on the water spray correction width based on the expansion compensation value to obtain the compensated width; Step 7444: Update the width of the latitude and longitude lines based on the compensated width.

[0017] By adopting the above technical solution, in response to the situation where the warp and weft threads absorb water and expand after water spraying, resulting in an increase in line width, the measurement results can be compensated by calculating the dimensional increase caused by water absorption and expansion and then offsetting the line width measurement deviation caused by the water spraying operation. This not only ensures that the burrs adhere to the clear edges but also avoids introducing new expansion measurement errors, further guaranteeing the accuracy of the line width measurement results.

[0018] Optionally, it also includes a control method for when the direction of the rotated latitude and longitude lines deviates, the method comprising: Step 50: After the control module rotates according to the rotation direction and rotation angle, acquire the rotation acquisition image; Step 51: Analyze the rotated acquired image to obtain the verification latitude and longitude lines; Step 52: Compare the direction of the checked latitude and longitude lines with the standard direction to obtain the deviation angle; Step 53: When the deviation angle is greater than the preset deviation threshold, generate an angle correction amount based on the deviation angle; Step 54: Correct the standard direction according to the angle correction amount; Step 55: When the deviation angle is less than the deviation threshold, continue to execute steps 6 to 9.

[0019] By adopting the above technical solution, residual angular deviations may still exist after rotation adjustment. By verifying and correcting the direction after rotation, it can be ensured that the latitude and longitude lines are aligned with the standard direction, reducing the errors in subsequent line width and density measurements caused by angular deviations, and further improving measurement accuracy.

[0020] Optionally, an optimization method is also included when the deviation angle is less than a deviation threshold, the method comprising: Step 550: When the deviation angle is less than the deviation threshold, obtain the deviation direction based on the deviation angle; Step 551: Compare the deviation direction with the rotation direction to obtain the residual deviation; Step 552: Obtain the historical residual bias and calculate the average residual bias based on the historical residual bias; Step 553: Generate the return compensation angle based on the average residual deviation; Step 554: Correct the standard direction based on the return compensation angle.

[0021] By adopting the above technical solution, this method can compensate for and correct the rotation direction by using historical residual deviations to address errors during the rotation process, thereby offsetting the angle adjustment error caused by transmission clearance, further improving the accuracy of direction adjustment, and better ensuring the accuracy of subsequent measurement results.

[0022] Optionally, it also includes an optimization method for calculating latitude and longitude density, which includes: Step 800: Calculate the current latitude and longitude density based on the total number of latitude and longitude lines and the bus width distance; Step 801: If the current latitude and longitude density falls within the preset qualified density range, define the current latitude and longitude density as the latitude and longitude density; Step 802: If the current latitude and longitude density does not fall within the acceptable density range, the identification information and the current latitude and longitude density are integrated into density non-compliance information and output.

[0023] By adopting the above technical solution, the warp and weft density results are pre-verified. When the measured density exceeds the qualified range corresponding to the electronic fabric category, an abnormality reminder is output immediately. This allows the testing personnel to promptly check the equipment operation status and whether there are any abnormalities in the tested sample, preventing unqualified measurement data from flowing into subsequent stages and improving the reliability of the measurement results and the standardization of the testing process.

[0024] Secondly, the present invention provides a machine vision measurement system for the warp and weft width of electronic fabric, employing the following technical solution: A machine vision measurement system for the warp and weft width of electronic fabric includes: The acquisition module is used to acquire identification information, capture images, pan real-time images, edge images, fine-tune focus images, and water spray images; A memory for storing the program of the machine vision measurement method for the warp and weft width of electronic fabric; The processor loads and executes programs from memory.

[0025] By adopting the above technical solution, the measurement of the warp and weft width and density of electronic cloth can be completed automatically according to the above method and process. Measurement errors can be corrected in different complex scenarios, and the measurement results with higher accuracy can be output stably. It can adapt to the batch testing needs of electronic cloth of different specifications, effectively reduce the workload of manual testing, and improve the efficiency and accuracy of testing operations.

[0026] In summary, the present invention has at least one of the following beneficial technical effects: 1. Through multi-step processing such as automatic focusing and angle correction, the problem of low measurement accuracy caused by factors such as human operation error, warp and weft overlap and stickiness, and edge blurring in traditional manual measurement and conventional machine vision measurement is effectively solved, which can improve the measurement accuracy of the width and density of the warp and weft of electronic cloth. 2. Corresponding correction processes have been set up for different scenarios that affect measurement accuracy, such as overlapping warp and weft lines, adhesion, blurred edges, and surface burrs. The corresponding processing solutions can be adapted according to the actual situation that occurs during the measurement process. The detection needs of electronic cloth with different surface conditions can be met, which improves the applicability of the detection. 3. A multi-level verification and compensation mechanism is set up for the deviations in each step of the measurement process, including retrace compensation for rotation angle deviation, size compensation after water spray expansion, and qualification verification of density results. This mechanism can offset the measurement errors introduced by each step layer by layer, further ensuring the accuracy of the final measurement results. Attached Figure Description

[0027] Figure 1 This is a flowchart of a machine vision measurement method for the warp and weft width of electronic fabric in an embodiment of this application; Figure 2 This is a schematic diagram of the overlap of latitude and longitude lines in the embodiments of this application; Figure 3 This is a schematic diagram of the adhesion of latitude and longitude lines in the embodiments of this application; Figure 4 This is a measurement system architecture diagram in an embodiment of this application. Detailed Implementation

[0028] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments.

[0029] This invention discloses a machine vision method for measuring the warp and weft width of electronic fabric. (Refer to...) Figure 1 A machine vision measurement method for the warp and weft width of electronic fabric includes: Step 1: In response to the detection signal, acquire identification information.

[0030] The detection signal is the trigger command used to initiate the machine vision measurement operation of the electronic fabric warp and weft width. The detection signal is a start command manually triggered by the operator.

[0031] The identification information refers to the unique identification data of the electronic cloth sample to be tested, including sample number, batch number, production date, etc. The identification information is obtained by reading the pre-set QR code label, barcode label, or manually entered sample information on the electronic cloth sample.

[0032] Step 2: Control the movement control module to move according to the preset focus mode and acquire images.

[0033] Reference Figure 4 The motion control module includes a focusing module that drives the vertical movement (movement accuracy 1µm), a rotation module that drives the sample stage to rotate around the central axis (rotation accuracy 0.018°), and a translation module that drives the sample stage to move horizontally (movement accuracy 1µm).

[0034] A focus mode refers to the set of motion parameters followed by an image acquisition device during autofocus, including the starting position, ending position, step size, and speed. The focus mode is preset by the operator based on the depth-of-field range of the image acquisition device and the thickness range of the sample being measured, and then stored in the system.

[0035] The acquired image refers to the image of the electronic cloth surface captured by the image acquisition device when the motion control module moves to a certain position. The acquired image is obtained by triggering the image acquisition device to take pictures frame by frame as the motion control module moves in the focus mode, and then transmitting the image data to the system.

[0036] Before focusing and acquiring images, the electronic cloth is illuminated at an angle by an illumination module to clearly show the warp or weft threads. Here, the illumination module uses two symmetrically distributed 3W LED lights to illuminate the electronic cloth at an angle.

[0037] Step 3: Analyze the acquired images to obtain real-time sharpness and real-time location, and perform edge detection and frequency domain analysis on each real-time sharpness to obtain the maximum sharpness and the sharpness location corresponding to the maximum sharpness.

[0038] Real-time sharpness refers to the quantified value of the image sharpness at the current location. It is obtained by performing edge detection and frequency domain analysis on the acquired image, calculating sharpness evaluation indicators such as edge energy, high-frequency component ratio, or contrast.

[0039] Real-time position refers to the spatial coordinates of the motion control module when acquiring the current image. The real-time position is obtained through position sensors installed on the motion control module.

[0040] Maximum sharpness refers to the maximum value among all real-time sharpness values ​​obtained during focus mode movement, representing the image sharpness corresponding to the optimal focus position. Maximum sharpness is obtained by sorting and comparing the sharpness values ​​calculated at each real-time position, and selecting the largest value as the maximum sharpness.

[0041] The sharp position refers to the spatial coordinates of the motion control module corresponding to the maximum resolution. The sharp position is obtained by using the real-time position corresponding to the maximum resolution as the sharp position.

[0042] Step 4: Control the movement control module to move to a clear position and analyze the acquired image to obtain the latitude and longitude directions.

[0043] The warp and weft directions refer to the directional angles of the warp or weft yarns in the electronic fabric within the image coordinate system. These directions are determined by analyzing the texture direction of images acquired from clear locations, detecting the yarn edges or main texture directions in the image, and calculating the angles between the warp and weft directions and the horizontal direction.

[0044] Step 5: Compare the latitude and longitude lines with the preset standard direction to obtain the rotation direction and rotation angle, and then control the movement control module to rotate according to the rotation direction and rotation angle.

[0045] The standard orientation refers to the angular relationship between the warp and weft directions of the electronic cloth and the image coordinate axes under ideal measurement conditions. The standard orientation is preset by the operator and stored in the control system based on measurement accuracy requirements and image processing algorithm needs.

[0046] The rotation direction refers to the direction in which the motion control module rotates to align the latitude and longitude lines with the standard direction. The rotation direction is calculated by comparing the current latitude and longitude angle with the standard direction angle. If the current angle is greater than the standard angle, it is determined to be a counter-clockwise rotation; if it is less, it is determined to be a clockwise rotation.

[0047] The rotation angle refers to the specific angle value that the motion control module needs to rotate to align the latitude and longitude lines with the standard direction. The rotation angle is obtained by taking the absolute value of the difference between the current latitude and longitude line angle and the standard direction angle.

[0048] Step 6: Control the motion control module to perform translation according to the preset translation mode and acquire real-time translation images.

[0049] Translation mode refers to the set of motion parameters followed by the image acquisition device when it moves at a constant speed in the horizontal direction to measure the width and density of latitude and longitude lines. These parameters include translation speed, translation distance, and sampling interval. The translation mode is preset by the operator according to the measurement accuracy requirements and the size of the electronic fabric, and stored in the control system.

[0050] Real-time translation images refer to a sequence of images of the electronic cloth surface captured by the image acquisition device at various sampling points along the movement trajectory during the uniform movement of the motion control module in translation mode. Real-time translation images are obtained by triggering the image acquisition device to take continuous or intermittent shots during the execution of translation mode, and then transmitting each frame of image data to the image processing system in real time.

[0051] Step 7: Analyze the real-time translation image to obtain the total number and width of latitude and longitude lines.

[0052] The total number of warp and weft threads refers to the total number of warp or weft yarns passing through the translation direction in a real-time translation image. This total number is obtained by performing edge detection or grayscale projection analysis on the yarn texture in the real-time translation image, counting the number of yarn edges or centers in the image sequence. The total number of warp (weft) threads only counts complete warp (weft) threads.

[0053] Warp and weft yarn width refers to the average width of a single warp or weft yarn in the direction perpendicular to the yarn. It is calculated by identifying the positions of the two edges of each yarn in a real-time translational image, determining the pixel distance of each yarn in the width direction, and then converting the pixel distance into actual dimensions using image calibration parameters.

[0054] Step 8: Obtain the bus width distance based on the real-time translation image, and calculate the latitude and longitude density based on the total number of latitude and longitude lines and the bus width distance.

[0055] Bus width distance refers to the total distance from the left edge of the leftmost complete meridian (latitude) line to the left edge of the rightmost meridian (latitude) line in the latitudinal (longitude) scan image. Bus width distance is obtained by stitching together real-time translated images to obtain a latitudinal (latitude) scan image, and analyzing the precise boundaries of the latitudinal (latitude) scan image to obtain the total distance of the meridian (latitude) line.

[0056] Warp and weft density refers to the number of warp or weft threads contained in a unit length of electronic fabric. It is obtained by dividing the total number of warp and weft threads by the bus width.

[0057] Step 9: Integrate the identification information, latitude and longitude line width, and latitude and longitude line density to obtain latitude and longitude line information, and output the latitude and longitude line information.

[0058] Latitude and longitude information refers to a complete measurement result data package obtained by combining identification information, latitude and longitude width, and latitude and longitude density according to a preset data format. Latitude and longitude information is obtained by splicing or packaging the identification information field, latitude and longitude width field, and latitude and longitude density field according to the system's preset data structure.

[0059] Latitude and longitude information is displayed by sending it to a local display device, or uploaded to a remote monitoring platform via a communication module for recording and subsequent analysis.

[0060] It is worth noting that the latitude and longitude lines described in the above steps are only abbreviations for longitude or latitude. For example, the total number of latitude and longitude lines refers to the total number of longitude lines or the total number of latitude lines, and the width of latitude and longitude lines refers to the width of longitude lines or the width of latitude lines. In the process of measuring the density of latitude and longitude lines, the measurement methods for longitude lines and latitude lines are the same. For example, the movement control module is adjusted and translated according to the direction of the longitude lines to measure the total distance and total number of longitude lines and then calculate the density of longitude lines. Similarly, the measurement of latitude lines is also done by adjusting and translating the movement control module according to the direction of the latitude lines to measure the total distance and total number of latitude lines and then calculate the density of latitude lines.

[0061] Reference Figure 2 It also includes a control method for when latitude and longitude lines overlap, the method comprising: Step 80: Analyze the real-time translation image to obtain the current width.

[0062] The current width refers to the width of the warp and weft line currently being measured in the real-time panning image. The current width is obtained by performing edge detection on the yarn texture in the real-time panning image, identifying the positions of the two edges of the current warp and weft line, calculating the pixel distance between the two edges, and then converting this value into the actual size using image calibration parameters.

[0063] Step 81: If the current width falls within the preset normal line width range, then define the current width as the latitude and longitude line width.

[0064] The normal thread width range refers to the minimum and maximum allowable range of warp and weft thread widths in the qualified product standard for electronic fabric. It is used to determine whether the width of a single warp or weft thread is within the acceptable range. The normal thread width range is preset by the staff according to product quality standards and process requirements and stored in the control system.

[0065] If the current width is between the lower and upper limits of the normal line width range, it means that the width of the latitude and longitude line is normal and no special processing is required. The current width can be directly used as the latitude and longitude line width in subsequent calculations.

[0066] Step 82: If the current width does not fall within the normal line width range, obtain the adjacent latitude and longitude line numbers and the intersecting area from the real-time translation image based on the latitude and longitude lines corresponding to the current width.

[0067] The adjacent latitude and longitude line numbers refer to the numbers of the latitude and longitude lines adjacent to the current latitude and longitude line in the image. The adjacent latitude and longitude line numbers are obtained by identifying the position of the current latitude and longitude line in the real-time translation image, searching along the direction perpendicular to the latitude and longitude line, and extracting the numbers of the two nearest latitude and longitude lines on its left and right sides.

[0068] An interlacing region refers to a location where the distance between the current latitude and longitude line and its adjacent latitude and longitude lines is abnormal, and there may be overlap or intersection. Interlacing regions are obtained by locating the edge positions of the current latitude and longitude line and its adjacent latitude and longitude lines in a real-time panning image, and marking areas where the distance between the edges is less than a preset minimum spacing threshold as interlacing regions.

[0069] Step 83: Control the motion control module to move according to the preset vertical movement mode and acquire real-time vertical movement images.

[0070] The vertical movement mode refers to the set of motion parameters that the motion control module moves perpendicular to the translation direction to observe the overlapping area when it detects an anomaly in the latitude and longitude lines. These parameters include the vertical movement distance, vertical movement speed, and sampling interval. The vertical movement mode is preset by the staff according to the measurement accuracy requirements and the thickness of the electronic cloth, and stored in the control system.

[0071] Vertical real-time images refer to a sequence of images of the electronic cloth surface captured by the image acquisition device along the vertical trajectory during the movement of the motion control module in vertical movement mode. These images are obtained by triggering the image acquisition device to capture images during the execution of vertical movement mode and then transmitting the image data to the image processing system.

[0072] Step 84: Obtain the intersecting latitude and longitude line numbers corresponding to the current width based on the vertical real-time image and the adjacent latitude and longitude line numbers.

[0073] Interlaced latitude and longitude line numbers refer to the numbers of other latitude and longitude lines within the intersection area of ​​the current latitude and longitude line and its adjacent lines in a vertically shifting real-time image. Interlaced latitude and longitude line numbers are obtained by performing image analysis on the vertically shifting real-time image, detecting the edges of all visible latitude and longitude lines within the intersection area, and comparing the detected latitude and longitude line numbers with the numbers of adjacent latitude and longitude lines.

[0074] Step 85: Obtain the width and number of intersecting latitude and longitude lines based on the intersecting latitude and longitude line numbers and the vertically shifted real-time image.

[0075] The width of the interlaced warp and weft yarns refers to the width value of each warp and weft yarn corresponding to the interlaced warp and weft yarn number in the vertically shifted real-time image. The width of the interlaced warp and weft yarns is obtained by performing edge detection on the yarns corresponding to each interlaced warp and weft yarn number in the vertically shifted real-time image and calculating the width of each warp and weft yarn separately.

[0076] The number of intersecting latitude and longitude lines refers to the total number of intersecting latitude and longitude lines detected within the intersecting area. This number is obtained by counting the numbered intersecting latitude and longitude lines.

[0077] Step 86: Update the total number of latitude and longitude lines and their widths based on the width and number of intersecting latitude and longitude lines.

[0078] By re-detecting the width and number of interlacing latitude and longitude lines in the interlacing area, the measurement bias caused by previous overlap is corrected. The total number of latitude and longitude lines is updated to the original total number of latitude and longitude lines minus the original erroneous count plus the number of interlacing latitude and longitude lines, and the width of the latitude and longitude lines is updated to the average width value recalculated based on the width of the interlacing latitude and longitude lines.

[0079] Step 87: Integrate the identification information and the interlaced area to obtain the interlaced information, and output the interlaced information.

[0080] Interleaving information refers to the abnormal area report data package obtained by integrating identification information and characteristic data such as the location and size of interleaved areas. Interleaving information is obtained by combining the identification information field with the characteristic fields such as the coordinates, size, and shape of the interleaved area according to a preset format.

[0081] Interleaved information is displayed by sending it to a local display device, or uploaded to a remote monitoring platform via a communication module for recording and processing.

[0082] Reference Figure 3 It also includes a control method for when latitude and longitude lines become sticky, the method comprising: Step 830: When the number of intersecting latitude and longitude lines in the vertical real-time image is always 1, the control module moves to the preset edge position according to the vertical movement mode and acquires the edge image.

[0083] Edge position refers to the coordinates of the boundary area of ​​the electronic cloth sample in the vertical direction. The edge position is set in advance by the staff based on the size and placement of the electronic cloth sample and stored in the control system.

[0084] When the number of intersecting warp and weft threads in the real-time vertical movement image is always 1, it indicates that no multiple intersecting warp and weft threads were detected during the vertical movement process. The warp and weft threads may have become stuck together (two or more yarns stick together). At this time, the control module moves to the edge of the electronic cloth according to the vertical movement mode and takes an edge image at that position.

[0085] An edge image refers to a surface image captured by an image acquisition device at the edge of the electronic cloth when the motion control module moves to the edge position. Edge images are obtained by triggering the image acquisition device to capture images after the motion control module reaches the edge position and then transmitting the image data to the image processing system.

[0086] Step 831: Obtain the width of the bifurcated latitude and longitude lines, the number of bifurcated latitude and longitude lines, and the position of the sticky edge based on the intersecting latitude and longitude line numbers and the edge image.

[0087] The bifurcation width refers to the width of the warp and weft threads that bifurcate due to adhesion in the edge image. It is obtained by locating the yarn positions corresponding to the intersecting warp and weft thread numbers in the edge image, performing edge detection at the bifurcation point at that position, and measuring the width of each branch yarn after bifurcation.

[0088] The number of bifurcated latitude and longitude lines refers to the total number of latitude and longitude lines that bifurcate due to adhesion in the edge image. The number of bifurcated latitude and longitude lines is obtained by counting the bifurcated latitude and longitude lines detected in the edge image.

[0089] The sticky edge location refers to the specific coordinates of the location where the warp and weft threads stick together in the edge region of the electronic cloth. The sticky edge location is obtained by detecting the edge coordinates of the sticky yarn region in the edge image.

[0090] Step 832: Update the total number of meridians and the width of meridians based on the width and number of bifurcated meridians.

[0091] By utilizing the number and width of latitude and longitude lines re-identified due to stickiness and bifurcation in the edge image, the previous erroneous measurements of the total number and width of latitude and longitude lines caused by stickiness are corrected. The total number of latitude and longitude lines is updated to the original total number of latitude and longitude lines minus the number missed due to stickiness, plus the number of bifurcation latitude and longitude lines; the width of latitude and longitude lines is updated to the average width value recalculated based on the width of the bifurcation latitude and longitude lines.

[0092] Step 833: Obtain the sticky region based on the sticky edge position and the preset electronic cloth area.

[0093] The electron cloth area refers to the complete area of ​​the electron cloth sample in the image coordinate system. The electron cloth area is set and stored in advance by the staff through calibration plates or manual annotation.

[0094] A viscous region refers to the area within the electron cloth region where the viscous edge is located, which may be affected by viscosity. The viscous region is obtained by using the viscous edge as the starting point of the region boundary, combining it with the range of the electron cloth region, and generating a region containing the viscous position according to a preset expansion rule.

[0095] Step 834: Integrate the identification information and the sticky region to obtain sticky information, and output the sticky information.

[0096] Viscous information refers to the viscous anomaly report data package obtained by integrating identification information and characteristic data such as the location and size of the viscous region. Viscous information is obtained by combining the identification information field with characteristic fields such as the coordinates and dimensions of the viscous region according to a preset format.

[0097] Sticky information is displayed by sending it to a local display device, or uploaded to a remote monitoring platform via a communication module for recording and processing.

[0098] This also includes a control method for when the edges of latitude and longitude lines are relatively blurred, and the method includes: Step 70: Perform edge detection on the real-time translation image to obtain the edge gradient magnitude of each latitude and longitude line.

[0099] Edge gradient magnitude refers to the rate of change of pixel grayscale at the edge positions of each latitude and longitude line in a real-time translated image, used to characterize the sharpness of the latitude and longitude line edges. Edge gradient magnitude is obtained by performing gradient calculations on the edge positions of each latitude and longitude line in the real-time translated image, calculating the rate of change of pixel grayscale at the edge along the direction perpendicular to the yarn, and then extracting the edge gradient magnitude corresponding to each latitude and longitude line.

[0100] Step 71: If the edge gradient magnitude is less than the preset magnitude threshold, then the corresponding latitude and longitude lines are defined as fuzzy latitude and longitude lines.

[0101] Amplitude threshold refers to the minimum edge gradient amplitude limit value used to distinguish between sharp and blurry edges of latitude and longitude lines. The amplitude threshold is set in advance by the staff based on the imaging quality of the image acquisition equipment, lighting conditions, and algorithm sensitivity requirements, and stored in the control system.

[0102] Blurred latitude and longitude lines refer to latitude and longitude lines in a real-time translational image whose edge gradient magnitude is lower than a threshold value. Blurred latitude and longitude lines are obtained by comparing the edge gradient magnitude of each latitude and longitude line with the threshold value one by one, and marking those latitude and longitude lines with edge gradient magnitude values ​​less than the threshold value as blurred latitude and longitude lines.

[0103] Step 72: Control the movement control module to move according to the preset fine-tuning focus mode and acquire the fine-tuning focus image.

[0104] Fine-tuning focus mode refers to the set of motion parameters followed by the motion control module when it detects blurred lines of latitude and longitude, allowing for small-range, precise movements. These parameters include the starting position, ending position, movement step size (smaller than in focus mode), and movement speed. Fine-tuning focus mode is preset by the operator based on the lens's depth of field and degree of blur, and stored in the control system.

[0105] Fine-tuning focus images refer to the sequence of images of the electronic cloth surface captured by the image acquisition device at various fine-tuning positions as the motion control module moves according to the fine-tuning focus mode. Fine-tuning focus images are obtained by triggering the image acquisition device to capture images during the execution of the fine-tuning focus mode and then transmitting each frame of image data to the image processing system.

[0106] Step 73: Calculate the sharpness of the fine-tuned focus image to obtain the sharpness of the blurred areas, and compare the sharpness of each blurred area to obtain the maximum blur sharpness and the corresponding optimal focus position.

[0107] Blurry region sharpness refers to the quantified value of the image sharpness in the area containing the blurred latitude and longitude lines in a fine-tuned focus image. Blurry region sharpness is obtained by extracting a local area containing the blurred latitude and longitude lines from the fine-tuned focus image, performing edge detection or frequency domain analysis on this local area, and calculating sharpness evaluation indicators such as edge energy, high-frequency component ratio, or contrast.

[0108] Maximum blur sharpness refers to the maximum sharpness achieved in the blurred area during the fine-tuning focus mode movement. Maximum blur sharpness is obtained by sorting and comparing the blur sharpness values ​​calculated at each fine-tuning position, and selecting the value with the largest value.

[0109] The optimal focus position refers to the spatial coordinates of the motion control module corresponding to the maximum blur sharpness. The optimal focus position is obtained by using the real-time position corresponding to the maximum blur sharpness as the optimal focus position.

[0110] Step 74: Move the control module to the optimal focus position and reacquire the corrected width of the blurred latitude and longitude lines.

[0111] The corrected width refers to the width value obtained by re-measuring the blurred latitude and longitude lines under optimal focusing conditions after moving the motion control module to the optimal focusing position. The corrected width is obtained by re-capturing the area containing the blurred latitude and longitude lines using the image acquisition device after moving the motion control module to the optimal focusing position, and then performing edge detection and width calculation on the blurred latitude and longitude lines in the re-captured image.

[0112] Step 75: Update the width of the latitude and longitude lines based on the corrected width.

[0113] The corrected width, obtained by re-measuring at the optimal focus position, replaces the original width value corresponding to the blurred latitude and longitude line in the latitude and longitude line width data, making the overall latitude and longitude line width data more accurate. The width value corresponding to the blurred latitude and longitude line in the latitude and longitude line width data is updated with the corrected width.

[0114] This also includes: Step 740: When the control module moves to the optimal focus position, if the edge gradient amplitude of the blurred latitude and longitude lines is still less than the amplitude threshold, the edge contour is obtained based on the real-time translation image and the blurred latitude and longitude lines.

[0115] Edge contours refer to the edge shape trajectory lines of blurred latitude and longitude lines in a real-time translational image. Edge contours are obtained by performing edge detection on blurred latitude and longitude lines in a real-time translational image, extracting the pixel sets of the edges on both sides of the latitude and longitude lines, and then connecting the edge pixels in sequence to form a continuous edge curve.

[0116] Step 741: Calculate the contour undulation of the fuzzy latitude and longitude lines based on the edge contour.

[0117] Profile undulation refers to the degree of fluctuation of the edge profile of a fuzzy warp and weft yarn along the yarn direction, and is used to measure the smoothness of the yarn edge. Profile undulation is obtained by fitting a straight line to each point on the edge profile, calculating the absolute value of the deviation of each edge point from the fitted straight line, and statistically analyzing all deviation values ​​(such as calculating the root mean square error or the maximum deviation value).

[0118] Step 742: When the contour undulation is greater than the preset undulation threshold, the region where the contour undulation is greater than the undulation threshold is defined as the burr region.

[0119] The undulation threshold refers to the maximum allowable undulation of the warp and weft yarn edge contours, used to determine whether burrs exist on the yarn edges. The undulation threshold is pre-set by staff according to the electronic fabric product quality standards and stored in the control system.

[0120] A burr region refers to a localized area where the undulation of the warp and weft yarn edges exceeds a certain threshold. This region exhibits surface defects such as loose fibers, fuzz, or fly waste. Burr regions are determined by calculating the contour undulation segment by segment along the yarn direction and marking continuous segments with undulation exceeding the threshold as burr regions.

[0121] Step 743: Perform a preset water spraying operation based on the burr area, and obtain a water spraying image after the water spraying operation is performed on the burr area.

[0122] The water spraying operation is a physical process that sprays fine water mist onto the burr areas of the electronic cloth surface to eliminate or suppress the burrs. The water spraying operation involves sending the position coordinates of the burr area to the water spraying mechanism, which then sprays water at a predetermined rate and angle onto the burr area.

[0123] A water-spray image refers to a surface image captured by an image acquisition device in the burr area after water spraying. The water-spray image is obtained by moving the control module to the burr area after the water spraying operation is completed, triggering the image acquisition device to capture the image, and then transmitting the image data to the image processing system.

[0124] Step 744: Obtain the water spray correction width corresponding to the burr area based on the water spray image.

[0125] The water-jet correction width refers to the warp and weft width values ​​obtained by re-measuring the burr area in the water-jet image after water-jet processing. The water-jet correction width is obtained by performing edge detection on the burr area in the water-jet image, identifying the edge positions of the yarns after water-jet processing, and calculating the width between the two edges.

[0126] Step 745: When the water spray correction width falls within the normal line width range, update the latitude and longitude line widths based on the water spray correction width.

[0127] When the water-jet correction width is between the lower and upper limits of the normal yarn width range, it indicates that the water-jet treatment has effectively eliminated the burrs, restoring the yarn width to the acceptable range. Updating the warp and weft widths based on the water-jet correction width means updating the width value corresponding to the burr area in the warp and weft width data to the water-jet correction width, or recalculating the average warp and weft width including the water-jet correction width.

[0128] Step 746: When the water spray correction width does not fall within the normal line width range, integrate the burr area and marking information into burr information and output it.

[0129] Burr information refers to the burr defect report data package obtained by integrating identification information and characteristic data such as the location and size of the burr area. Burr information is obtained by combining the identification information field with the coordinates, size, shape, and other characteristic fields of the burr area according to a preset format.

[0130] The burr information is displayed by sending it to a local display device, or uploaded to a remote monitoring platform via a communication module for recording and processing.

[0131] This also includes: Step 7440: Obtain the image of the burr area before the water spraying operation, and extract the width of the burr area before water spraying.

[0132] The image before water spraying refers to the original surface image of the burr area captured by the image acquisition device before the water spraying operation is performed. The image before water spraying is obtained by controlling the movement control module to move to the burr area position before performing the water spraying operation in step 743, triggering the image acquisition device to capture and store the image data.

[0133] The pre-spray width refers to the width of the warp and weft threads in the burr area measured in the image before water spraying. The pre-spray width is obtained by performing edge detection on the burr area in the image before water spraying, identifying the positions of the two edges of the yarn before spraying, and then calculating the width between the two edges.

[0134] Step 7441: Compare the corrected width of the water spray with the original width to obtain the width expansion amount.

[0135] Width expansion refers to the increase in yarn width after water spraying in the burr area, relative to the width before water spraying. Width expansion is obtained by subtracting the original width from the water-sprayed width.

[0136] Step 7442: When the width expansion amount is greater than the preset expansion tolerance threshold, calculate the expansion compensation value based on the width expansion amount and the preset expansion coefficient.

[0137] The expansion tolerance threshold refers to the maximum allowable expansion of yarn width after water spraying, used to determine whether water spraying causes excessive yarn expansion. The expansion tolerance threshold is pre-set by staff based on experimental data on the effects of water spraying on yarn fibers and stored in the control system.

[0138] The expansion coefficient refers to the conversion ratio between the amount of yarn width expansion and the required compensation value. The expansion coefficient is an empirical coefficient obtained by staff through pre-calibration experiments, measuring the required compensation values ​​under different expansion amounts.

[0139] The expansion compensation value refers to the numerical value used to compensate for excessive yarn expansion caused by water spraying. The expansion compensation value is calculated by subtracting the expansion tolerance threshold from the width expansion amount and then multiplying it by the expansion coefficient.

[0140] Step 7443: Perform reverse compensation on the water spray correction width based on the expansion compensation value to obtain the compensated width.

[0141] The compensated width refers to the measured value that is closer to the true width of the yarn after subtracting the expansion compensation value from the water jet correction width. The compensated width is obtained by subtracting the expansion compensation value from the water jet correction width.

[0142] Step 7444: Update the width of the latitude and longitude lines based on the compensated width.

[0143] The width value corresponding to the burr area in the latitude and longitude line width data is replaced with the compensated width to make the overall latitude and longitude line width data more accurate. The width value corresponding to the burr area in the latitude and longitude line width data is updated to the compensated width.

[0144] This also includes a control method for when the direction of the rotated latitude and longitude lines deviates, the method comprising: Step 50: After the control module rotates according to the rotation direction and rotation angle, acquire the rotation acquisition image.

[0145] Rotation-acquired images refer to images of the electronic fabric surface captured by the image acquisition device in the current rotation state after the motion control module completes the rotation operation according to the rotation direction and angle. Rotation-acquired images are obtained by triggering the image acquisition device to capture images after the motion control module completes the rotation, and then transmitting the image data to the image processing system.

[0146] Step 51: Analyze the rotated acquired image to obtain the direction of the latitude and longitude lines for verification.

[0147] Verifying the warp and weft direction refers to re-extracting the warp and weft direction angles after performing texture direction analysis on the rotated image. This is used to verify whether the rotation operation was accurate and in place. Verifying the warp and weft direction involves performing the same texture direction analysis process as in step 4 on the rotated image, detecting the yarn edges or main texture direction in the image, and calculating the angle between the warp and weft direction and the horizontal direction.

[0148] Step 52: Compare the direction of the checked latitude and longitude lines with the standard direction to obtain the deviation angle.

[0149] The deviation angle refers to the angular difference between the calibration latitude and longitude direction and the standard direction, used to characterize the residual directional error after a rotation operation. The deviation angle is obtained by subtracting the standard direction angle from the calibration latitude and longitude direction angle and taking the absolute value.

[0150] Step 53: When the deviation angle is greater than the preset deviation threshold, generate an angle correction amount based on the deviation angle.

[0151] The deviation threshold refers to the maximum permissible angular deviation between the latitude and longitude lines and the standard direction after rotation. It is used to determine whether further correction is needed during the rotation operation. The deviation threshold is preset by the operator based on the measurement accuracy requirements and the allowable error range of the image processing algorithm, and stored in the control system.

[0152] Angle correction refers to the adjustment angle value used to correct for a standard direction. The angle correction is obtained by using the difference between the deviation angle and the deviation threshold as the angle correction, or by directly generating a correction value equal to the deviation angle.

[0153] Step 54: Correct the standard direction according to the angle correction amount.

[0154] The stored standard direction parameters are updated using the angle correction amount, ensuring that subsequent rotation calibration operations are based on the corrected standard direction. The value obtained by adding or subtracting the angle correction amount to the standard direction angle is used as the new standard direction and stored in the control system.

[0155] Step 55: When the deviation angle is less than the deviation threshold, continue to execute steps 6 to 9.

[0156] When the deviation angle is less than the deviation threshold, it means that the direction of the rotated latitude and longitude lines has met the accuracy requirements and no direction correction is needed.

[0157] This also includes an optimization method when the deviation angle is less than the deviation threshold, which includes: Step 550: When the deviation angle is less than the deviation threshold, the deviation direction is obtained based on the deviation angle.

[0158] The deviation direction refers to the direction of the deviation of the checked latitude and longitude lines relative to the standard direction, and is used to determine the orientation of the residual error. The deviation direction is obtained by comparing the angle of the checked latitude and longitude lines with the angle of the standard direction. If the angle of the checked direction is greater than the angle of the standard direction, it is determined to be a positive deviation; if it is less than the angle of the standard direction, it is determined to be a negative deviation.

[0159] Step 551: Compare the deviation direction with the rotation direction to obtain the residual deviation.

[0160] Residual deviation refers to the uncorrected directional deviation of the latitude and longitude lines relative to the standard direction after the rotation operation is completed. The residual deviation is calculated by comparing the deviation direction with the rotation direction performed in step 5. If the deviation direction is the same as the rotation direction, the residual deviation is positive; if the deviation direction is opposite to the rotation direction, the residual deviation is negative. Finally, the residual deviation value is obtained by combining the deviation angle with the direction sign.

[0161] Step 552: Obtain the historical residual bias and calculate the average residual bias based on the historical residual bias.

[0162] Historical residual deviation refers to the residual deviation values ​​recorded and stored by the system during multiple rotational calibration operations prior to this test. Historical residual deviation is obtained by reading the residual deviation values ​​recorded in previous measurements for this device or product type from the system's stored historical calibration record table.

[0163] The average residual deviation is the deviation value obtained by statistically averaging historical residual deviations. It is the arithmetic mean obtained by summing all historical residual deviation values ​​and dividing by the number of historical records.

[0164] Step 553: Generate the return compensation angle based on the average residual deviation.

[0165] The return stroke compensation angle refers to the compensation angle value applied in advance to eliminate the mechanical return stroke backlash of the rotating mechanism or the inertial error of the system. The return stroke compensation angle is obtained by using the average residual deviation as the reference value of the return stroke compensation angle, or by multiplying the average residual deviation by a preset compensation coefficient, and is used to offset the inherent directional deviation of the system in advance during subsequent rotation calibration.

[0166] Step 554: Correct the standard direction based on the return compensation angle.

[0167] The stored standard direction parameters are corrected and updated using the return stroke compensation angle, so that the inherent mechanical return stroke deviation of the system is pre-calculated during subsequent rotation calibration operations. The value obtained by adding the return stroke compensation angle to the standard direction angle is used as the new standard direction and stored in the control system to eliminate repeatability deviations caused by mechanical backlash in the rotating mechanism.

[0168] This also includes an optimized method for calculating latitude and longitude density, which includes: Step 800: Calculate the current latitude and longitude density based on the total number of latitude and longitude lines and the bus width distance.

[0169] The current latitude and longitude density refers to the density value calculated based on the total number of latitude and longitude lines actually detected and the bus width distance in this measurement. The current latitude and longitude density is obtained by dividing the total number of latitude and longitude lines by the bus width distance.

[0170] Step 801: If the current latitude and longitude density falls within the preset qualified density range, define the current latitude and longitude density as latitude and longitude density.

[0171] The acceptable density range refers to the minimum and maximum allowable range of warp and weft density of electronic fabric within the acceptable product standard. It is used to determine whether the current density meets the quality requirements. The acceptable density range is preset by staff according to product quality standards and process requirements and stored in the control system.

[0172] When the current warp and weft density is between the lower and upper limits of the qualified density range, it indicates that the warp and weft density of the electronic cloth is qualified. The current warp and weft density is formally defined as the warp and weft density of the sample and used for integration and output in subsequent step 9.

[0173] Step 802: If the current latitude and longitude density does not fall within the acceptable density range, the identification information and the current latitude and longitude density are integrated into density non-compliance information and output.

[0174] Density non-compliance information refers to a density defect report data package obtained by integrating identification information and the current latitude and longitude density. Density non-compliance information is obtained by combining the identification information field with the current latitude and longitude density value according to a preset format.

[0175] Information indicating density non-compliance is displayed on a local display device, or uploaded to a remote monitoring platform via a communication module for recording and quality traceability.

[0176] Based on the same inventive concept, embodiments of the present invention provide a machine vision measurement system for the warp and weft width of electronic fabric.

[0177] A machine vision measurement system for the warp and weft width of electronic fabric includes: The acquisition module is used to acquire identification information, capture images, pan real-time images, edge images, fine-tune focus images, and water spray images; A memory for storing a machine vision measurement method for the warp and weft width of an electronic cloth; The processor loads and executes programs from memory.

[0178] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional modules is used as an example. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device, and unit described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0179] The above description is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, any improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A machine vision measurement method for the warp and weft width of electronic fabric, characterized in that, include: Step 1: In response to the detection signal, acquire identification information; Step 2: Control the movement control module to move according to the preset focus mode and acquire images; Step 3: Analyze the acquired images to obtain real-time sharpness and real-time location, and perform edge detection and frequency domain analysis on each real-time sharpness to obtain the maximum sharpness and the sharpness location corresponding to the maximum sharpness; Step 4: Control the movement control module to move to a clear position and analyze the acquired image to obtain the latitude and longitude directions; Step 5: Compare the latitude and longitude lines with the preset standard direction to obtain the rotation direction and rotation angle, and then control the movement control module to rotate according to the rotation direction and rotation angle; Step 6: Control the motion control module to perform translation according to the preset translation mode and acquire real-time translation images; Step 7: Analyze the real-time translation image to obtain the total number and width of latitude and longitude lines; Step 8: Obtain the bus width distance based on the real-time translation image, and calculate the latitude and longitude density based on the total number of latitude and longitude lines and the bus width distance; Step 9: Integrate the identification information, latitude and longitude line width, and latitude and longitude line density to obtain latitude and longitude line information, and output the latitude and longitude line information; This also includes a control method for when latitude and longitude lines overlap, the method comprising: Step 80: Analyze the real-time translation image to obtain the current width; Step 81: If the current width falls within the preset normal line width range, then define the current width as the latitude and longitude line width; Step 82: If the current width does not fall within the normal line width range, obtain the adjacent latitude and longitude line numbers and the intersecting area from the real-time translation image based on the latitude and longitude lines corresponding to the current width; Step 83: Control the motion control module to move according to the preset vertical movement mode and acquire real-time vertical movement images; Step 84: Obtain the intersecting latitude and longitude line numbers corresponding to the current width based on the real-time vertical image and the adjacent latitude and longitude line numbers; Step 85: Obtain the width and number of intersecting latitude and longitude lines based on the intersecting latitude and longitude line numbers and the vertically shifted real-time image; Step 86: Update the total number of latitude and longitude lines and their widths based on the width and number of intersecting latitude and longitude lines; Step 87: Integrate the identification information and the interlaced area to obtain the interlaced information, and output the interlaced information.

2. The machine vision measurement method for the warp and weft width of electronic fabric according to claim 1, characterized in that, It also includes a control method for when latitude and longitude lines become sticky, the method comprising: Step 830: When the number of intersecting latitude and longitude lines in the vertical real-time image is always 1, the control module moves to the preset edge position according to the vertical movement mode and acquires the edge image; Step 831: Obtain the width of the bifurcated latitude and longitude lines, the number of bifurcated latitude and longitude lines, and the position of the sticky edge based on the intersecting latitude and longitude line numbers and the edge image; Step 832: Update the total number of meridians and the width of meridians based on the width and number of bifurcated meridians; Step 833: Obtain the sticky region based on the location of the sticky edge and the preset electronic cloth area; Step 834: Integrate the identification information and the sticky region to obtain sticky information, and output the sticky information.

3. The machine vision measurement method for the warp and weft width of electronic fabric according to claim 1, characterized in that, It also includes a control method for when the edges of latitude and longitude lines are relatively blurred, which includes: Step 70: Perform edge detection on the real-time translation image to obtain the edge gradient magnitude of each latitude and longitude line; Step 71: If the edge gradient magnitude is less than the preset magnitude threshold, then define the corresponding latitude and longitude lines as fuzzy latitude and longitude lines; Step 72: Control the movement control module to move according to the preset fine-tuning focus mode and acquire the fine-tuning focus image; Step 73: Calculate the sharpness of the blurred area by fine-tuning the focus image, and compare the sharpness of each blurred area to obtain the maximum blur sharpness and the corresponding optimal focus position; Step 74: Control the movement control module to move to the optimal focus position and reacquire the corrected width of the blurred latitude and longitude lines; Step 75: Update the width of the latitude and longitude lines based on the corrected width.

4. The machine vision measurement method for the warp and weft width of electronic fabric according to claim 3, characterized in that, Also includes: Step 740: When the control module moves to the optimal focus position, if the edge gradient amplitude of the blurred latitude and longitude lines is still less than the amplitude threshold, the edge contour is obtained based on the real-time translation image and the blurred latitude and longitude lines. Step 741: Calculate the contour undulation of the fuzzy latitude and longitude lines based on the edge contours; Step 742: When the contour undulation is greater than the preset undulation threshold, the area where the contour undulation is greater than the undulation threshold is defined as the burr area. Step 743: Perform a preset water spraying operation based on the burr area, and obtain a water spraying image after the water spraying operation is performed on the burr area; Step 744: Obtain the water spray correction width corresponding to the burr area based on the water spray image; Step 745: When the water spray correction width falls within the normal line width range, update the latitude and longitude line widths according to the water spray correction width; Step 746: When the water spray correction width does not fall within the normal line width range, integrate the burr area and marking information into burr information and output it.

5. The machine vision measurement method for the warp and weft width of electronic fabric according to claim 4, characterized in that, Also includes: Step 7440: Obtain the image of the burr area before the water spraying operation, and extract the width of the burr area before water spraying. Step 7441: Compare the corrected width of the water spray with the original width to obtain the width expansion amount; Step 7442: When the width expansion amount is greater than the preset expansion tolerance threshold, calculate the expansion compensation value based on the width expansion amount and the preset expansion coefficient; Step 7443: Perform reverse compensation on the water spray correction width based on the expansion compensation value to obtain the compensated width; Step 7444: Update the width of the latitude and longitude lines based on the compensated width.

6. The machine vision measurement method for the warp and weft width of electronic fabric according to claim 1, characterized in that, It also includes a control method for when the direction of the rotated latitude and longitude lines deviates, the method including: Step 50: After the control module rotates according to the rotation direction and rotation angle, acquire the rotation acquisition image; Step 51: Analyze the rotated acquired image to obtain the verification latitude and longitude lines; Step 52: Compare the direction of the checked latitude and longitude lines with the standard direction to obtain the deviation angle; Step 53: When the deviation angle is greater than the preset deviation threshold, generate an angle correction amount based on the deviation angle; Step 54: Correct the standard direction according to the angle correction amount; Step 55: When the deviation angle is less than the deviation threshold, continue to execute steps 6 to 9.

7. The machine vision measurement method for the warp and weft width of electronic fabric according to claim 6, characterized in that, It also includes an optimization method when the deviation angle is less than the deviation threshold, which includes: Step 550: When the deviation angle is less than the deviation threshold, obtain the deviation direction based on the deviation angle; Step 551: Compare the deviation direction with the rotation direction to obtain the residual deviation; Step 552: Obtain the historical residual bias and calculate the average residual bias based on the historical residual bias; Step 553: Generate the return compensation angle based on the average residual deviation; Step 554: Correct the standard direction based on the return compensation angle.

8. The machine vision measurement method for the warp and weft width of electronic fabric according to claim 1, characterized in that, It also includes an optimized method for calculating latitude and longitude density, which includes: Step 800: Calculate the current latitude and longitude density based on the total number of latitude and longitude lines and the bus width distance; Step 801: If the current latitude and longitude density falls within the preset qualified density range, define the current latitude and longitude density as the latitude and longitude density; Step 802: If the current latitude and longitude density does not fall within the acceptable density range, the identification information and the current latitude and longitude density are integrated into density non-compliance information and output.

9. A machine vision measurement system for the warp and weft width of electronic fabric, characterized in that, include: The acquisition module is used to acquire identification information, capture images, pan real-time images, edge images, fine-tune focus images, and water spray images; A memory for storing a program for a machine vision measurement method for the warp and weft width of an electronic cloth as described in any one of claims 1 to 8; The processor loads and executes programs from memory.

Images