A linear guide rail precision detection method, device, equipment and storage medium

Abstract

The present invention discloses a method, device, equipment and storage medium for detecting the accuracy of a linear guide rail, the method comprising: acquiring image information of the linear guide rail; performing image processing operations according to the image information to obtain single image data; performing surface finish calculation operations of the linear guide rail according to the single image data to obtain surface finish of the linear guide rail; performing horizontality calculation operations of the linear guide rail according to the single image data to obtain horizontality of the linear guide rail; performing linearity calculation operations of the linear guide rail according to the single image data to obtain linearity of the linear guide rail; performing linearity evaluation operations of the linear guide rail according to the surface finish of the linear guide rail, the horizontality of the linear guide rail and the linearity of the linear guide rail to obtain linearity of the linear guide rail. The method can realize comprehensive detection of linear guide rail accuracy.

Description

Technical Field

[0001] The present invention relates to the technical field of guide rail accuracy detection, and in particular to a method, device, electronic equipment and storage medium for detecting the accuracy of a linear guide rail. Background Art

[0002] At present, in the field of mechanical manufacturing, precision detection is the core link to ensure product quality and performance, especially in industries such as aerospace, automobile manufacturing and electronic equipment manufacturing that have extremely high precision requirements. With the continuous pursuit of product quality and precision in modern industry, scientific methods and technologies for mechanical precision design and detection have become particularly critical. These technologies not only meet the basic needs of precision manufacturing, but also lay a solid foundation for improving product performance. In the detection of precision components such as linear guides, a variety of precision detection methods play a vital role, including special instrument detection, special machine tool detection, comparator detection, comprehensive detection methods, special testers and visual detection methods. These technologies enable accurate measurement and analysis of key parameters in the mechanical manufacturing process to ensure that the final product strictly meets the design specifications and performance standards. The application of detection technology has significantly improved the quality and precision of mechanical manufacturing products. At present, the commonly used detection technologies cover digital measurement technology, digital technology and non-contact technology. These technologies provide accurate detection and quantitative analysis methods for the mechanical manufacturing industry with their high resolution and sensitivity.

[0003] In the prior art, although the displacement accuracy of linear guides can be measured by linear displacement sensors and measuring workbenches, there are still obvious technical defects. These devices fail to consider key factors such as the roughness of the linear guide surface and can only measure the displacement accuracy of the linear guide, but cannot fully evaluate the overall accuracy of the linear guide. This limitation restricts its accuracy and reliability in practical applications, making the prior art unable to meet the demand for comprehensive detection of linear guide accuracy.

[0004] In summary, the existing technology has the problem that it is impossible to fully detect the accuracy of the linear guide rail. Summary of the invention

[0005] The present invention provides a linear guide rail accuracy detection method, device, electronic equipment and storage medium to achieve comprehensive detection of the linear guide rail accuracy.

[0006] In a first aspect, in order to solve the above technical problems, the present invention provides a method for detecting the accuracy of a linear guide rail, comprising:

[0007] Obtain image information of the linear guide;

[0008] Performing image processing operations according to the image information to obtain single image data;

[0009] According to the single image data, a linear guide rail surface finish calculation operation is performed to obtain the linear guide rail surface finish;

[0010] According to the single image data, a linear guide rail horizontality calculation operation is performed to obtain the linear guide rail horizontality;

[0011] According to the single image data, a linear guide rail straightness calculation operation is performed to obtain the linear guide rail straightness;

[0012] According to the surface finish of the linear guide rail, the horizontality of the linear guide rail and the straightness of the linear guide rail, a linear guide rail accuracy evaluation operation is performed to obtain the linear guide rail accuracy.

[0013] Preferably, in an optional implementation, acquiring image information of the linear guide rail includes:

[0014] Based on the linear guide rail, the surface direction is adjusted to obtain the guide rail surface direction information;

[0015] Based on the guide rail surface direction information and the area array camera, image information is collected to obtain image information of the linear guide rail.

[0016] Preferably, in an optional implementation manner, performing an image processing operation according to the image information to obtain single image data includes:

[0017] According to the image information, the two-dimensional dot matrix information is spliced ​​to obtain single image data on each surface of the linear guide rail.

[0018] Preferably, in an optional implementation, a linear guide rail surface finish calculation operation is performed according to the single image data to obtain the linear guide rail surface finish, including:

[0019] According to the single image data, a light emission intensity weight calculation formula is used to calculate the weight of the light emission intensity and the grayscale value of each pixel in the single image to obtain the light emission intensity weight;

[0020] According to the single image data and the light emission intensity weight, the average light emission intensity of the linear guide surface is calculated using a linear guide surface average light emission intensity calculation formula to obtain the average light emission intensity of the linear guide surface;

[0021] According to the single image data and the average light intensity on the surface of the linear guide rail, the surface finish of the linear guide rail is obtained by using a linear guide rail surface finish calculation formula;

[0022] The light emission intensity weight calculation formula is as follows:

[0023]

[0024] in, Represents the weight of the light emission intensity and grayscale value of each pixel, Represents the gray value of the pixel The corresponding light emission intensity, represents the light emission intensity weight proportional coefficient, Indicates the pixel number;

[0025] The calculation formula for the average light intensity on the surface of the linear guide is as follows:

[0026]

[0027] in, Represents the average light intensity on the surface of the linear guide, Represents the weight of the light emission intensity and grayscale value of each pixel, Represents the gray value of the pixel. Indicates the pixel number;

[0028] The calculation formula of the surface finish of the linear guide is as follows:

[0029]

[0030] in, Indicates the surface finish of the linear guide. Represents the average light intensity on the surface of the linear guide, Represents grayscale value The corresponding light emission intensity, Indicates the pixel number. Indicates the total number of pixels.

[0031] Preferably, in an optional implementation, performing a linear guide rail horizontality calculation operation according to the single image data to obtain the linear guide rail horizontality includes:

[0032] According to the single image data, a horizontal straight line extraction operation to be detected is performed to obtain a horizontal straight line to be detected;

[0033] According to the horizontal straight line, a straight line segmentation operation is performed to obtain a first-level detection horizontal straight line;

[0034] According to the first-level detected horizontal straight line, a horizontal center line calculation operation is performed to obtain a horizontal center line;

[0035] According to the horizontal center line and the single image data, a linear guide rail horizontality calculation operation is performed to obtain the linear guide rail horizontality;

[0036] The linear guide rail horizontality calculation formula is as follows:

[0037]

[0038] in, Indicates The height of pixels, Indicates The horizontal center line of the first-level detection line where the pixel point is located, Indicates the horizontality of the linear guide rail. Indicates the total number of pixels.

[0039] Preferably, in an optional implementation, a linear guide rail straightness calculation operation is performed according to the single image data to obtain the linear guide rail straightness, including:

[0040] According to the single image data, a vertical straight line extraction operation to be detected is performed to obtain a vertical straight line to be detected;

[0041] According to the vertical straight line, a straight line segmentation operation is performed to obtain a first-level detected vertical straight line;

[0042] According to the first-level detected vertical straight line, a vertical center line calculation operation is performed to obtain a vertical center line;

[0043] Performing a linear guide rail straightness calculation operation according to the vertical center line and the single image data to obtain the linear guide rail straightness;

[0044] The linear guide straightness calculation formula is as follows:

[0045]

[0046] in, Indicates The height of pixels, Indicates The vertical center line of the first-level detection line where the pixel point is located, Indicates the straightness of the linear guide. Indicates the total number of pixels.

[0047] Preferably, in an optional embodiment, a linear guide rail accuracy evaluation operation is performed according to the surface finish of the linear guide rail, the horizontality of the linear guide rail and the straightness of the linear guide rail to obtain the linear guide rail accuracy, including:

[0048] According to the surface finish of the linear guide rail, a linear guide rail surface finish scoring formula is used to obtain a linear guide rail surface finish score;

[0049] According to the linear guide rail horizontality, a linear guide rail horizontality scoring formula is used to obtain a linear guide rail horizontality score;

[0050] According to the linear guide straightness, a linear guide straightness scoring formula is used to obtain a linear guide straightness score;

[0051] According to the surface finish score of the linear guide rail, the horizontal score of the linear guide rail and the straightness score of the linear guide rail, the linear guide rail accuracy is obtained by using a linear guide rail evaluation formula;

[0052] The linear guide surface finish scoring formula is as follows:

[0053]

[0054] in, Indicates the surface finish score of the linear guide rail. Indicates the surface finish of the linear guide. Indicates the standard value of the surface finish of the linear guide;

[0055] The linear guide rail horizontality scoring formula is as follows:

[0056]

[0057] in, Indicates the horizontality score of the linear guide rail. Indicates the horizontality of the linear guide rail. Indicates the standard value of the horizontality of the linear guide;

[0058] The linear guide straightness scoring formula is as follows:

[0059]

[0060] in, Indicates the linear guide straightness score, Indicates the straightness of the linear guide. Indicates the standard value of linear guide straightness;

[0061] The linear guide rail accuracy evaluation formula is as follows:

[0062]

[0063] in, Indicates the accuracy of linear guides, Indicates the surface finish weight of the linear guide rail, Indicates the horizontal weight of the linear guide rail, Indicates the linear guide straightness weight, Indicates the surface finish score of the linear guide rail. Indicates the horizontality score of the linear guide rail. Indicates the straightness score of the linear guide.

[0064] In a second aspect, the present invention provides a linear guide rail accuracy detection device, comprising:

[0065] An image information acquisition module, used to acquire image information of the linear guide rail;

[0066] An image processing module, used to perform image processing operations according to the image information to obtain single image data;

[0067] A smoothness calculation module is used to perform a surface smoothness calculation operation of the linear guide rail according to the single image data to obtain the surface smoothness of the linear guide rail;

[0068] A levelness calculation module, used to perform a linear guide rail levelness calculation operation according to the single image data to obtain the linear guide rail levelness;

[0069] A straightness calculation module, used to perform a linear guide rail straightness calculation operation according to the single image data to obtain the linear guide rail straightness;

[0070] The accuracy evaluation module is used to perform an accuracy evaluation operation of the linear guide rail according to the surface finish of the linear guide rail, the horizontality of the linear guide rail and the straightness of the linear guide rail to obtain the accuracy of the linear guide rail.

[0071] In the third aspect, the present invention also provides a linear guide rail accuracy detection device, comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor implements any one of the linear guide rail accuracy detection methods described above when executing the computer program.

[0072] In a fourth aspect, the present invention further provides a computer-readable storage medium, which includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute any one of the above-mentioned linear guide rail accuracy detection methods.

[0073] Compared with the prior art, the present invention has the following beneficial effects: it realizes a comprehensive detection of the accuracy of the linear guide rail, including the evaluation of the surface finish, levelness and straightness, thereby overcoming the limitation of the prior art that only the displacement accuracy can be measured. By adopting the light emission intensity weight calculation formula, the linear guide rail surface average light emission intensity calculation formula, the surface finish calculation formula, the levelness calculation formula and the straightness calculation formula, the present invention can provide more accurate evaluation results and improve the detection accuracy. By acquiring and processing image information, the present invention makes full use of image data to evaluate the accuracy of the linear guide rail, thereby improving the accuracy and reliability of the detection. In addition, the device and the linear guide rail precision detection equipment provided by the present invention can automatically execute the detection process, reduce manual operation errors, improve detection efficiency, and at the same time reduce the production cost of the enterprise, providing a more cost-effective detection solution.

[0074] In summary, the present invention provides a method for comprehensively detecting the accuracy of linear guide rails by comprehensively using multiple steps such as image information acquisition, image processing, surface finish calculation, levelness calculation, straightness calculation and accuracy evaluation. The method first adjusts the surface direction of the linear guide rail and uses a surface array camera to collect image information, and then splices the collected two-dimensional dot matrix information to obtain single image data on each surface. Then, a specific calculation formula is used to analyze the single image data, and the surface finish, levelness and straightness of the linear guide rail are calculated respectively. Finally, these parameters are combined to perform accuracy evaluation to obtain the accuracy of the linear guide rail. The embodiments of the present invention also include corresponding detection devices, electronic devices and computer-readable storage media, which realize the automation of the detection process, reduce the errors of manual operations, improve the efficiency and accuracy of detection, and reduce costs at the same time, providing enterprises with an efficient, accurate and economical linear guide rail accuracy detection solution. In addition, the advantages of the present invention include improved flexibility and adaptability of detection, the ability to adapt to linear guides of different types and specifications, and good versatility; enhanced objectivity of data, and reduced the impact of human factors on detection results through precise image data processing; and through an integrated evaluation module, the detection results can be quickly obtained, which speeds up the production process and improves overall production efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] Figure 1 It is a schematic flow chart of a method for detecting the accuracy of a linear guide provided by the first embodiment of the present invention;

[0076] Figure 2 It is a schematic structural diagram of a linear guide rail accuracy detection device provided in the second embodiment of the present invention. DETAILED DESCRIPTION

[0077] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0078] Reference Figure 1 The first embodiment of the present invention provides a method for detecting the accuracy of a linear guide rail, comprising the following steps:

[0079] S11, acquiring image information of the linear guide;

[0080] S12, performing image processing operations according to the image information to obtain single image data;

[0081] S13, performing a linear guide rail surface finish calculation operation according to the single image data to obtain the linear guide rail surface finish;

[0082] S14, performing a linear guide rail horizontality calculation operation according to the single image data to obtain the linear guide rail horizontality;

[0083] S15, performing a linear guide rail straightness calculation operation according to the single image data to obtain the linear guide rail straightness;

[0084] S16, performing a linear guide rail accuracy evaluation operation according to the surface finish of the linear guide rail, the horizontality of the linear guide rail and the straightness of the linear guide rail to obtain the linear guide rail accuracy.

[0085] It should be noted that the accuracy detection method of the linear guide is implemented through a series of precise steps, which include obtaining image information of the linear guide, processing the image to obtain single image data, calculating the surface finish, levelness and straightness of the linear guide based on these data, and finally combining these parameters to evaluate the overall accuracy of the linear guide. This process involves precise processing and calculation of image information, ensuring the accuracy and reliability of the detection results. Through this method, the present invention can provide a comprehensive, efficient and economical solution for the accuracy detection of linear guides, meeting the needs of modern industry for high-precision detection.

[0086] In step S11, image information of the linear guide rail is obtained, including:

[0087] Based on the linear guide rail, the surface direction is adjusted to obtain the guide rail surface direction information;

[0088] Based on the guide rail surface direction information and the area array camera, image information is collected to obtain image information of the linear guide rail.

[0089] It should be noted that in step S11, the process of obtaining the linear guide rail image information first involves the precise adjustment of the guide rail surface direction, which is accomplished by a specific mechanical device or an automated system to ensure that the area array camera can capture the image from a predetermined optimal angle. After the adjustment is completed, the area array camera shoots the surface of the linear guide rail according to the set parameters, such as exposure time and focal length, to obtain image data containing surface texture, gloss and other features. This step ensures the accuracy of the image information and provides reliable raw data for subsequent image processing and accuracy calculation.

[0090] It is worth noting that in actual operation, if the length of the linear guide exceeds the single shooting range of the camera, it is necessary to collect multiple images at different positions or angles of the guide, and stitch these images into a complete guide surface image through image processing software. For example, the camera can move along the length direction of the guide and take a series of images at preset intervals, and then the software stitches these images to form a continuous single image covering the entire length of the guide. Such a processing method can ensure the integrity of the image data and provide detailed visual information for the comprehensive analysis of the linear guide. Through this precise image acquisition and processing method, the present invention can provide a comprehensive and efficient solution for the precision detection of linear guides, meet the needs of modern industry for high-precision detection, and provide strong technical support for the manufacture and quality control of linear guides. This process is repeatable, ensures the consistency of the test results, and provides a reliable basis for the precision evaluation of linear guides.

[0091] In step S12, an image processing operation is performed according to the image information to obtain single image data, including:

[0092] According to the image information, the two-dimensional dot matrix information is spliced ​​to obtain single image data on each surface of the linear guide rail.

[0093] It should be noted that step S12 is a key link in the image processing operation, and its purpose is to stitch multiple images collected from the area array camera into a complete single image data for subsequent analysis and calculation. This step involves the stitching processing of the two-dimensional dot matrix information to ensure that each surface of the linear guide is accurately captured and integrated into the final image. In the specific implementation of image processing, the collected images need to be preprocessed first, including noise reduction and enhancement, to improve the image quality and highlight the features of the guide surface. Subsequently, multiple images are aligned to a common reference coordinate system through image registration technology. This step is crucial because any alignment error will affect the accuracy of the final stitched image. After the image registration is completed, the aligned images are merged using image fusion technology to eliminate the stitching marks and form a seamless single image. In this process, it is necessary to solve the problems of exposure difference and uneven lighting to ensure that the stitched image is visually coherent. Image registration refers to the process of aligning multiple images to a common reference coordinate system to ensure that the features between images can accurately correspond. Image fusion refers to the technology of merging multiple images into one image, the purpose of which is to eliminate the stitching marks while maintaining the image details. For example, in an embodiment of the present invention, there is a 1.5-meter-long linear guide rail, and the area array camera takes pictures at one end of the guide rail. However, since the length of the guide rail exceeds the single shooting range of the camera, it is necessary to take three pictures at different positions of the guide rail, each covering a length of 0.5 meters. After the shooting is completed, the three images will be input into the image processing program. The program first performs noise reduction and enhancement processing on each image, and then aligns them to a common coordinate system through image registration technology. Finally, the three images are seamlessly spliced ​​into a complete 1.5-meter-long linear guide rail image through image fusion technology. The spliced ​​image clearly shows the entire surface of the guide rail, providing accurate basic data for the subsequent calculation of surface finish, levelness and straightness. This process ensures the integrity and accuracy of the image data and provides reliable visual information for the accuracy evaluation of the linear guide rail.

[0094] It is worth noting that in some cases, there are reflections or shadows on the surface of the linear guide, which will affect the quality of the image and the subsequent accuracy calculation. To this end, specific algorithms can be added to the image processing step to correct these effects, such as using multi-angle shooting and image fusion technology to reduce the impact of reflections and shadows.

[0095] In step S13, a linear guide rail surface finish calculation operation is performed according to the single image data to obtain the linear guide rail surface finish, including:

[0096] According to the single image data, a light emission intensity weight calculation formula is used to calculate the weight of the light emission intensity and the grayscale value of each pixel in the single image to obtain the light emission intensity weight;

[0097] According to the single image data and the light emission intensity weight, the average light emission intensity of the linear guide surface is calculated using a linear guide surface average light emission intensity calculation formula to obtain the average light emission intensity of the linear guide surface;

[0098] According to the single image data and the average light intensity on the surface of the linear guide rail, the surface finish of the linear guide rail is obtained by using a linear guide rail surface finish calculation formula;

[0099] The light emission intensity weight calculation formula is as follows:

[0100]

[0101] in, Represents the weight of the light emission intensity and grayscale value of each pixel, Represents the gray value of the pixel The corresponding light emission intensity, represents the light emission intensity weight proportional coefficient, Indicates the pixel number;

[0102] The calculation formula for the average light intensity on the surface of the linear guide is as follows:

[0103]

[0104] in, Represents the average light intensity on the surface of the linear guide, Represents the weight of the light emission intensity and grayscale value of each pixel, Represents the gray value of the pixel. Indicates the pixel number;

[0105] The calculation formula of the surface finish of the linear guide is as follows:

[0106]

[0107] in, Indicates the surface finish of the linear guide. Represents the average light intensity on the surface of the linear guide, Represents grayscale value The corresponding light emission intensity, Indicates the pixel number. Indicates the total number of pixels.

[0108] It should be noted that step S13 is a key step in the linear guide rail accuracy detection method for calculating the surface finish, and its implementation process involves a detailed analysis of the single image data and a series of mathematical calculations. The purpose of this step is to quantify the smoothness of the linear guide rail surface, which is crucial for evaluating the overall accuracy of the guide rail. First, the light emission intensity weight is calculated for each pixel in the single image data. This calculation is based on the light emission intensity weight calculation formula, which takes into account the gray value of each pixel. The corresponding light emission intensity The relationship between , to adjust the contribution of different pixels to the smoothness evaluation. For example, the light emission intensity weight ratio coefficient Set to 0.15. Of course, the light emission intensity weight ratio coefficient varies according to actual applications and user needs. It can also be set to 0.36, etc., which is not limited in the present invention. Through this formula, the light emission intensity weight of each pixel can be obtained: , these weights reflect the influence of each pixel on the surface finish. Next, the average light intensity calculation formula of the linear guide surface is used to calculate the average light intensity of the entire guide surface. This step is done by converting the gray value of each pixel into With its light emission intensity weight Multiply and sum, then divide by the total number of pixels , and get the average light intensity. This average value is an important parameter for evaluating surface finish, which provides information about the overall light reflection characteristics of the guide surface. Finally, the linear guide surface finish calculation formula is used to obtain the surface finish of the linear guide This formula is obtained by dividing the average light intensity by Divide by the light emission intensity of all pixels The weighted average of the surface finish is The closer this ratio is to 1, the higher the finish of the guide rail surface, that is, the smoother the surface.

[0109] It is worth noting that when implementing this step, specific algorithms and calculation methods are used to ensure that the surface finish information extracted from the image data is accurate and reliable. This method not only improves the accuracy of surface finish evaluation, but also provides an objective standard for the quality control of linear guides through quantitative analysis.

[0110] In step S14, a linear guide rail horizontality calculation operation is performed according to the single image data to obtain the linear guide rail horizontality, including:

[0111] According to the single image data, a horizontal straight line extraction operation to be detected is performed to obtain a horizontal straight line to be detected;

[0112] According to the horizontal straight line, a straight line segmentation operation is performed to obtain a first-level detection horizontal straight line;

[0113] According to the first-level detected horizontal straight line, a horizontal center line calculation operation is performed to obtain a horizontal center line;

[0114] According to the horizontal center line and the single image data, a linear guide rail horizontality calculation operation is performed to obtain the linear guide rail horizontality;

[0115] The linear guide rail horizontality calculation formula is as follows:

[0116]

[0117] in, Indicates The height of pixels, Indicates The horizontal center line of the first-level detection line where the pixel point is located, Indicates the horizontality of the linear guide rail. Indicates the total number of pixels.

[0118] It should be noted that the implementation process of this step involves the extraction, analysis and calculation of horizontal straight line features in single image data to quantify the horizontal deviation of the linear guide. First, the horizontal straight line to be detected is extracted from the single image data. This process uses image recognition technology, such as edge detection algorithm, to identify the horizontal straight line features in the image. These horizontal straight line features represent the upper surface or lower surface of the linear guide and are the basis for calculating the horizontality. Next, the extracted horizontal straight line is subjected to a straight line segmentation operation. Straight line segmentation refers to the segmentation of continuous straight line features into discrete, individually processable line segments for subsequent calculations. In this step, a first-level detection horizontal straight line can be obtained, that is, a straight line segment used for horizontality calculation after segmentation. Then, a horizontal centerline calculation operation is performed on each first-level detection horizontal straight line. The horizontal centerline refers to the geometric centerline of each straight line segment, which represents the axis of symmetry of the straight line segment. By calculating the horizontal centerline of each straight line segment, a theoretical straight line can be obtained, which passes through the geometric center of all straight line segments and reflects the actual horizontal state of the linear guide. Finally, the horizontality of the linear guide is calculated based on the horizontal centerline of each first-level detection horizontal line and the single image data. This calculation process involves quantifying the deviation between the height of each pixel and the horizontal centerline of the first-level detection line where it is located. By taking the average of the absolute values ​​of all pixel deviations, the horizontality of the linear guide can be obtained. The smaller this value is, the higher the levelness of the linear guide is, that is, the upper or lower surface of the linear guide is closer to the ideal horizontal state.

[0119] It is worth noting that horizontal line extraction refers to the process of identifying and extracting horizontal line features from image data. Line segmentation refers to the operation of segmenting continuous line features into discrete line segments. The horizontal centerline refers to the geometric centerline of each line segment, representing the axis of symmetry of the line segment. When implementing this step, precise image processing and calculation methods are used to ensure that the horizontal information extracted from the image data is accurate and reliable.

[0120] In step S15, a linear guide rail straightness calculation operation is performed according to the single image data to obtain the linear guide rail straightness, including:

[0121] According to the single image data, a vertical straight line extraction operation to be detected is performed to obtain a vertical straight line to be detected;

[0122] According to the vertical straight line, a straight line segmentation operation is performed to obtain a first-level detected vertical straight line;

[0123] According to the first-level detected vertical straight line, a vertical center line calculation operation is performed to obtain a vertical center line;

[0124] Performing a linear guide rail straightness calculation operation according to the vertical center line and the single image data to obtain the linear guide rail straightness;

[0125] The linear guide straightness calculation formula is as follows:

[0126]

[0127] in, Indicates The height of pixels, Indicates The vertical center line of the first-level detection line where the pixel point is located, Indicates the straightness of the linear guide. Indicates the total number of pixels.

[0128] It should be noted that the implementation process of this step involves the extraction, analysis and calculation of vertical straight line features in single image data to quantify the straightness deviation of the linear guide. First, the vertical straight line to be detected is extracted from the single image data. This process uses image recognition technology, such as edge detection algorithm, to identify the vertical straight line features in the image. These vertical straight line features represent the side surface of the linear guide and are the basis for calculating the straightness. Next, the extracted vertical straight line is subjected to a straight line segmentation operation. Straight line segmentation refers to the segmentation of continuous straight line features into discrete, individually processable line segments for subsequent calculations. In this step, a first-level detection vertical straight line can be obtained, that is, a straight line segment used for straightness calculation after segmentation. Then, a vertical centerline calculation operation is performed on each first-level detection vertical straight line. The vertical centerline refers to the geometric centerline of each straight line segment, which represents the axis of symmetry of the straight line segment. By calculating the vertical centerline of each straight line segment, a theoretical straight line can be obtained, which passes through the geometric center of all straight line segments and reflects the actual straight line state of the linear guide. Finally, the straightness of the linear guide is calculated based on the vertical centerline of each primary detection vertical line and the single image data. This calculation process involves quantifying the deviation between the height of each pixel and the vertical centerline of the primary detection line where it is located. By averaging the absolute values ​​of all pixel deviations, the straightness of the linear guide can be obtained. The smaller this value is, the higher the straightness of the linear guide is, that is, the closer the side surface of the linear guide is to the ideal straight line state.

[0129] In step S16, the linear guide rail accuracy evaluation operation is performed according to the surface finish of the linear guide rail, the horizontality of the linear guide rail and the straightness of the linear guide rail to obtain the linear guide rail accuracy, including:

[0130] According to the surface finish of the linear guide rail, a linear guide rail surface finish scoring formula is used to obtain a linear guide rail surface finish score;

[0131] According to the linear guide rail horizontality, a linear guide rail horizontality scoring formula is used to obtain a linear guide rail horizontality score;

[0132] According to the linear guide straightness, a linear guide straightness scoring formula is used to obtain a linear guide straightness score;

[0133] According to the surface finish score of the linear guide rail, the horizontal score of the linear guide rail and the straightness score of the linear guide rail, the linear guide rail accuracy is obtained by using a linear guide rail evaluation formula;

[0134] The linear guide surface finish scoring formula is as follows:

[0135]

[0136] in, Indicates the surface finish score of the linear guide rail. Indicates the surface finish of the linear guide. Indicates the standard value of the surface finish of the linear guide;

[0137] The linear guide rail horizontality scoring formula is as follows:

[0138]

[0139] in, Indicates the horizontality score of the linear guide rail. Indicates the horizontality of the linear guide rail. Indicates the standard value of the horizontality of the linear guide;

[0140] The linear guide straightness scoring formula is as follows:

[0141]

[0142] in, Indicates the linear guide straightness score, Indicates the straightness of the linear guide. Indicates the standard value of linear guide straightness;

[0143] The linear guide rail accuracy evaluation formula is as follows:

[0144]

[0145] in, Indicates the accuracy of linear guides, Indicates the surface finish weight of the linear guide rail, Indicates the horizontal weight of the linear guide rail, Indicates the linear guide straightness weight, Indicates the surface finish score of the linear guide rail. Indicates the horizontality score of the linear guide rail. Indicates the straightness score of the linear guide.

[0146] It should be noted that it involves evaluating the overall accuracy of the linear guide. This step is performed after the calculation of surface finish, levelness and straightness is completed. The purpose is to combine these parameters to obtain the overall accuracy score of the linear guide. In step S16, the linear guide surface finish score formula is first used to determine the surface finish score. This formula converts the actual measured surface finish into With the preset standard value The comparison is performed and the corresponding score is given according to the comparison result. If the measured value reaches or exceeds the standard value, the score is 1; if it is lower than the standard value, the score is the ratio of the actual value to the standard value. Next, the linear guide levelness scoring formula is used to determine the levelness score. This formula also converts the actual measured level With the preset standard value The linear guide straightness score is determined using the linear guide straightness scoring formula. This formula converts the actual measured straightness into With the preset standard value Compare and give corresponding scores. Finally, combine these three scores with their respective weights , and , the overall accuracy of the linear guide is calculated by the linear guide evaluation formula This formula combines the effects of surface finish, levelness and straightness on linear guide accuracy through weighted average to produce a comprehensive score, which serves as the final evaluation result of linear guide accuracy.

[0147] It is worth noting that this evaluation process not only provides a quantitative accuracy index, but also allows different accuracy parameters to be given different emphasis according to different application scenarios and requirements through the introduction of weights. Such a design makes the evaluation method of the present invention more flexible and can adapt to different industrial application requirements.

[0148] In order to facilitate the understanding of the present invention, some preferred embodiments of the present invention are further described below.

[0149] A 2-meter-long linear guide rail needs to be tested for accuracy. This linear guide rail will be used in a high-precision automated robotic arm, so its accuracy requirements are very high.

[0150] Step 1: Obtain image information of the linear guide. First, use an area array camera to capture images of the linear guide. Since the length of the guide exceeds the single-shot range of the camera, multiple shots are required at different positions of the guide. Specifically, shots are taken at the start, middle, and end positions of the guide, covering a length of 0.67 meters each time. The camera automatically shoots according to preset parameters and stores the image data.

[0151] Step 2: Image processing operations. The three images captured are then input into an image processing program. The program first performs noise reduction and enhancement on each image to improve image quality and highlight the features of the rail surface. Then, through image registration technology, the three images are aligned to a common reference coordinate system. Finally, image fusion technology is used to seamlessly stitch the three images into a complete 2-meter-long linear rail image.

[0152] Step 3: Calculate surface finish. The stitched image data is used to calculate the surface finish of the linear guide. The light emission intensity weight calculation formula is used to calculate the light emission intensity weight of each pixel, and then these weights are used to calculate the average light emission intensity of the linear guide surface. Finally, the surface finish of the linear guide is calculated based on the average light emission intensity and the light emission intensity of each pixel.

[0153] Step 4: Calculate the horizontality. Extract the horizontal straight line features from the single image data and perform line segmentation operations to obtain the first-level detected horizontal straight lines. Then, calculate the horizontal center line of each straight line, and calculate the horizontality of the linear guide based on these center lines and image data.

[0154] Step 5: Straightness calculation. The same method is used to calculate the straightness of the linear guide. The vertical line features are extracted from the image data, and the line segmentation operation is performed to obtain the first-level detected vertical lines. Then, the vertical center line of each line is calculated, and the straightness of the linear guide is calculated based on these center lines and the image data.

[0155] Step 6: Accuracy evaluation. Based on the calculated surface finish, levelness and straightness, as well as their respective weights, the linear guide evaluation formula is used to calculate the overall accuracy of the linear guide. For example, if the surface finish score is 0.9, the levelness score is 1.0, the straightness score is 0.95, and the weights are 0.3, 0.3 and 0.4 respectively, the overall accuracy P of the linear guide is 0.3*0.9+0.3*1.0+0.4*0.95=0.935.

[0156] In summary, the specific embodiments of the present invention provide a systematic method for comprehensively detecting the accuracy of linear guide rails. This method starts with obtaining image information of the linear guide rail, and ensures the accuracy of the image data by accurately adjusting the direction of the guide rail surface and using a surface array camera to collect images. In the image processing stage, advanced image stitching technology is used to merge multiple images into a single image, retaining the complete information of the guide rail surface. Subsequently, the image data is analyzed by a calculation formula to quantify the surface finish, levelness and straightness of the linear guide rail, which are key indicators for evaluating the accuracy of the guide rail. In the calculation of the surface finish, the present invention adopts a light emission intensity weight calculation formula, combines the gray value of the pixel point and the light emission intensity, calculates the weight of each pixel point, and then obtains the surface finish. The calculation of levelness and straightness involves extracting straight line features from the image data, performing straight line segmentation and center line calculation, and finally obtaining the levelness and straightness values ​​by quantifying the deviation. Finally, these parameters are combined to obtain the overall accuracy score of the linear guide rail through a weighted evaluation formula. This scoring system not only provides a quantitative accuracy indicator, but also, by introducing weights, allows the evaluation process to be adjusted according to different application scenarios and requirements, increasing the flexibility and adaptability of the method.

[0157] Reference Figure 2 The second embodiment of the present invention provides a linear guide rail accuracy detection device, comprising:

[0158] An image information acquisition module, used to acquire image information of the linear guide rail;

[0159] An image processing module, used to perform image processing operations according to the image information to obtain single image data;

[0160] A smoothness calculation module is used to perform a surface smoothness calculation operation of the linear guide rail according to the single image data to obtain the surface smoothness of the linear guide rail;

[0161] A levelness calculation module, used to perform a linear guide rail levelness calculation operation according to the single image data to obtain the linear guide rail levelness;

[0162] A straightness calculation module, used to perform a linear guide rail straightness calculation operation according to the single image data to obtain the linear guide rail straightness;

[0163] The accuracy evaluation module is used to perform an accuracy evaluation operation of the linear guide rail according to the surface finish of the linear guide rail, the horizontality of the linear guide rail and the straightness of the linear guide rail to obtain the accuracy of the linear guide rail.

[0164] It should be noted that the linear guide rail accuracy detection device provided in an embodiment of the present invention is used to execute all process steps of a linear guide rail accuracy detection method in the above embodiment. The working principles and beneficial effects of the two correspond one to one, and thus will not be described in detail.

[0165] The embodiment of the present invention further provides an electronic device. The electronic device includes: a processor, a memory, and a computer program stored in the memory and executable on the processor, such as a linear guide rail accuracy detection program. When the processor executes the computer program, the steps in the above-mentioned linear guide rail accuracy detection method embodiments are implemented, such as Figure 1 Alternatively, when the processor executes the computer program, the functions of the modules / units in the above-mentioned device embodiments are realized, such as the accuracy assessment module.

[0166] Exemplarily, the computer program may be divided into one or more modules / units, which are stored in the memory and executed by the processor to implement the present invention. The one or more modules / units may be a series of computer program instruction segments capable of implementing specific functions, which are used to describe the execution process of the computer program in the electronic device.

[0167] The electronic device may be a computing device such as a desktop computer, a notebook, a PDA, and a smart tablet. The electronic device may include, but is not limited to, a processor and a memory. Those skilled in the art will appreciate that the above components are merely examples of electronic devices and do not constitute a limitation on the electronic device. The electronic device may include more or fewer components than the above components, or may combine certain components, or different components. For example, the electronic device may also include input and output devices, network access devices, buses, etc.

[0168] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the electronic device, and uses various interfaces and lines to connect various parts of the entire electronic device.

[0169] The memory can be used to store the computer program and / or module, and the processor realizes various functions of the electronic device by running or executing the computer program and / or module stored in the memory, and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area can store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0170] Wherein, if the module / unit integrated in the electronic device is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Wherein, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0171] It should be noted that the device embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, in the accompanying drawings of the device embodiments provided by the present invention, the connection relationship between the modules indicates that there is a communication connection between them, which may be specifically implemented as one or more communication buses or signal lines. A person of ordinary skill in the art may understand and implement it without paying any creative effort.

[0172] The specific embodiments described above further illustrate the purpose, technical solutions and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. It is particularly pointed out that for those skilled in the art, any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for detecting the accuracy of a linear guide rail, characterized in that: Executed by a computer, including: Obtain image information of the linear guide; Performing image processing operations according to the image information to obtain single image data; According to the single image data, a linear guide rail surface finish calculation operation is performed to obtain the linear guide rail surface finish; According to the single image data, a linear guide rail horizontality calculation operation is performed to obtain the linear guide rail horizontality; According to the single image data, a linear guide rail straightness calculation operation is performed to obtain the linear guide rail straightness; According to the surface finish of the linear guide rail, the horizontality of the linear guide rail and the straightness of the linear guide rail, an accuracy evaluation operation of the linear guide rail is performed to obtain the accuracy of the linear guide rail; Wherein, performing a linear guide rail surface finish calculation operation according to the single image data to obtain the linear guide rail surface finish includes: According to the single image data, a light emission intensity weight calculation formula is used to calculate the weight of the light emission intensity and the grayscale value of each pixel in the single image to obtain the light emission intensity weight; According to the single image data and the light emission intensity weight, the average light emission intensity of the linear guide surface is calculated using a linear guide surface average light emission intensity calculation formula to obtain the average light emission intensity of the linear guide surface; According to the single image data and the average light intensity on the surface of the linear guide rail, the surface finish of the linear guide rail is obtained by using a linear guide rail surface finish calculation formula; The light emission intensity weight calculation formula is as follows: in, Represents the weight of the light emission intensity and grayscale value of each pixel, Represents the gray value of the pixel The corresponding light emission intensity, represents the light emission intensity weight proportional coefficient, Indicates the pixel number; The calculation formula for the average light intensity on the surface of the linear guide is as follows: in, Represents the average light intensity on the surface of the linear guide, Indicates the gray value of the pixel; The calculation formula of the surface finish of the linear guide is as follows: in, Indicates the surface finish of the linear guide. Indicates the total number of pixels.

2. The method for detecting the accuracy of a linear guide rail according to claim 1, characterized in that: Get linear guide image information, including: Based on the linear guide rail, the surface direction is adjusted to obtain the guide rail surface direction information; Based on the guide rail surface direction information and the area array camera, image information is collected to obtain image information of the linear guide rail.

3. The method for detecting the accuracy of a linear guide rail according to claim 1, characterized in that: Performing image processing operations according to the image information to obtain single image data includes: According to the image information, the two-dimensional dot matrix information is spliced ​​to obtain single image data on each surface of the linear guide rail.

4. The method for detecting the accuracy of a linear guide rail according to claim 1, characterized in that: According to the single image data, a linear guide rail horizontality calculation operation is performed to obtain the linear guide rail horizontality, including: According to the single image data, a horizontal straight line extraction operation to be detected is performed to obtain a horizontal straight line to be detected; According to the horizontal straight line, a straight line segmentation operation is performed to obtain a first-level detection horizontal straight line; According to the first-level detected horizontal straight line, a horizontal center line calculation operation is performed to obtain a horizontal center line; According to the horizontal center line and the single image data, a linear guide rail horizontality calculation operation is performed to obtain the linear guide rail horizontality; The linear guide rail horizontality calculation formula is as follows: in, Indicates The height of pixels, Indicates The horizontal center line of the first-level detection line where the pixel point is located, Indicates the horizontality of the linear guide rail. Indicates the total number of pixels.

5. The method for detecting the accuracy of a linear guide rail according to claim 1, characterized in that: According to the single image data, a linear guide rail straightness calculation operation is performed to obtain the linear guide rail straightness, including: According to the single image data, a vertical straight line extraction operation to be detected is performed to obtain a vertical straight line to be detected; According to the vertical straight line, a straight line segmentation operation is performed to obtain a first-level detected vertical straight line; According to the first-level detected vertical straight line, a vertical center line calculation operation is performed to obtain a vertical center line; Performing a linear guide rail straightness calculation operation according to the vertical center line and the single image data to obtain the linear guide rail straightness; The linear guide straightness calculation formula is as follows: in, Indicates The height of pixels, Indicates The vertical center line of the first-level detection line where the pixel point is located, Indicates the straightness of the linear guide. Indicates the total number of pixels.

6. The method for detecting the accuracy of a linear guide rail according to claim 1, characterized in that: According to the surface finish of the linear guide rail, the horizontality of the linear guide rail and the straightness of the linear guide rail, the linear guide rail accuracy evaluation operation is performed to obtain the linear guide rail accuracy, including: According to the surface finish of the linear guide rail, a linear guide rail surface finish scoring formula is used to obtain a linear guide rail surface finish score; According to the linear guide rail horizontality, a linear guide rail horizontality scoring formula is used to obtain a linear guide rail horizontality score; According to the linear guide straightness, a linear guide straightness scoring formula is used to obtain a linear guide straightness score; According to the surface finish score of the linear guide rail, the horizontal score of the linear guide rail and the straightness score of the linear guide rail, the linear guide rail accuracy is obtained by using a linear guide rail evaluation formula; The linear guide surface finish scoring formula is as follows: in, Indicates the surface finish score of the linear guide rail. Indicates the surface finish of the linear guide. Indicates the standard value of the surface finish of the linear guide; The linear guide rail horizontality scoring formula is as follows: in, Indicates the horizontality score of the linear guide rail. Indicates the horizontality of the linear guide rail. Indicates the standard value of the horizontality of the linear guide; The linear guide straightness scoring formula is as follows: in, Indicates the linear guide straightness score, Indicates the straightness of the linear guide. Indicates the standard value of linear guide straightness; The linear guide rail accuracy evaluation formula is as follows: in, Indicates the accuracy of linear guides, Indicates the surface finish weight of the linear guide, Indicates the horizontal weight of the linear guide rail, Indicates the linear guide straightness weight, Indicates the surface finish score of the linear guide rail. Indicates the horizontality score of the linear guide rail. Indicates the straightness score of the linear guide.

7. A linear guide rail accuracy detection device, characterized in that: include: An image information acquisition module, used to acquire image information of the linear guide rail; An image processing module, used to perform image processing operations according to the image information to obtain single image data; A smoothness calculation module is used to perform a surface smoothness calculation operation of the linear guide rail according to the single image data to obtain the surface smoothness of the linear guide rail; A levelness calculation module, used to perform a linear guide rail levelness calculation operation according to the single image data to obtain the linear guide rail levelness; A straightness calculation module, used to perform a linear guide rail straightness calculation operation according to the single image data to obtain the linear guide rail straightness; The accuracy evaluation module is used to perform an accuracy evaluation operation of the linear guide rail according to the surface finish of the linear guide rail, the horizontality of the linear guide rail and the straightness of the linear guide rail to obtain the accuracy of the linear guide rail.

8. A linear guide rail precision detection device, characterized in that: The method comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein when the processor executes the computer program, the method for detecting the accuracy of a linear guide rail as claimed in any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the linear guide rail accuracy detection method according to any one of claims 1 to 6.

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