Screw locking state detection method, device and equipment and storage medium

Abstract

The invention discloses a screw locking state detection method, device and equipment and a storage medium, and belongs to the technical field of workpiece quality detection. According to the method, firstly, plane images of a workpiece before and after screw assembly are collected, then an image of a screw hole area is extracted, data processing is carried out, and a gray value change mean value and a hole site image radius before and after assembly are obtained and serve as reference data of a locking state. According to the method, the gray value of an assembled screw hole area image is compared with the radius in the image, hole sites with gray changes and abnormal hole site image radiuses are recognized, possible locking abnormal hole sites are determined, and finally the abnormal hole sites are marked and uploaded to a control console for manual verification, so that the accuracy of the locking abnormal hole sites is improved. According to the scheme, through automatic image processing and data analysis, the accuracy and efficiency of locking detection are effectively improved, and the product quality and compliance are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of workpiece quality detection, and in particular to a method, device, equipment and storage medium for detecting a screw locking state. Background Art

[0002] With the popularization of automation technology, it has greatly improved production efficiency and product quality in various processes and links of the manufacturing industry, while reducing labor costs. Against this backdrop, quality control has become a key factor in the competitiveness of the manufacturing industry. High-quality products can not only meet the needs of consumers, but also enhance the market position and brand reputation of enterprises. Therefore, how to ensure that products meet high standards in every link of the production process has become a major challenge facing the manufacturing industry.

[0003] Among the many production links, screw locking is a seemingly simple but crucial step. It is widely used in various fields such as machinery, electronic equipment, and automobile manufacturing. The firmness of screw locking directly affects the stability and safety of the product. However, the traditional screw locking detection method relies on manual visual inspection, which is inefficient and easily affected by human factors, resulting in unstable detection results. In addition, with the expansion of production scale and the increase in product complexity, manual inspection can no longer meet the modern manufacturing industry's demand for high efficiency and high precision. The existing detection methods cannot meet the production needs of automation and intelligence, especially in high-volume and diversified product lines. Ensuring that the locking status of each screw hole meets the quality standards and avoiding product quality problems caused by poor locking is a technical bottleneck that the current manufacturing industry still needs to break through.

[0004] Therefore, how to intelligently detect the screw locking status on the workpiece and improve product detection efficiency is a technical problem that needs to be solved urgently in this field. Summary of the invention

[0005] The main purpose of the present invention is to provide a method, device, equipment and storage medium for detecting the locking state of screws, aiming to solve the technical problem of how to intelligently detect the locking state of screws on a workpiece and improve the efficiency of product detection.

[0006] To achieve the above object, the present invention provides a method for detecting a screw locking state, the method comprising: Determine the screw hole area image according to the plane image of the processed object; Obtaining image feature data of each screw hole according to the screw hole area image; The locking state of each screw hole area is obtained according to the locking state reference data and the image feature data.

[0007] Optionally, before determining the screw hole area image according to the plane image of the processed object, the method further includes: Respectively acquiring a plane image of the object before screw assembly and a plane image after screw assembly; According to the plane images before and after assembly, the image grayscale value and hole position image radius of each screw hole area before and after assembly are obtained; According to the image grayscale values ​​of each screw hole area before and after assembly, an average grayscale change value of the screw hole area before and after assembly is obtained; According to the hole position image radius of each screw hole area before and after assembly, an average value of the hole position image radius change before and after assembly of the screw hole area is obtained; The average value of the grayscale change and the average value of the hole position image radius change are used as reference data for the locking state.

[0008] Optionally, determining the screw hole area image according to the plane image of the processed object includes: Performing feature recognition on the plane image of the processed object to determine a reference area image; The screw hole area image is determined based on relative position parameters between the reference area image and each screw hole area.

[0009] Optionally, obtaining image feature data of each screw hole according to the screw hole area image includes: Obtaining the grayscale value of each screw hole area image according to the screw hole area image; According to the grayscale values ​​of the images of the screw hole regions, an image grayscale mean is obtained; According to the grayscale mean value of the image and the grayscale value of each screw hole area image, the grayscale difference value of each screw hole is obtained, and the grayscale difference value is used as the image feature data.

[0010] Optionally, obtaining the locking state of each screw hole area according to the locking state reference data and the image feature data includes: According to the locking state reference data, an average value of grayscale change is obtained; According to the grayscale change average value and the grayscale difference value of each screw hole, the abnormal hole position to be confirmed is obtained; Determine the abnormally locked hole position according to the hole position image radius and locking state reference data of the abnormally locked hole position to be confirmed; The locking status of each screw hole area is obtained according to the abnormal locking hole position.

[0011] Optionally, the determining the abnormally locked hole position according to the hole position image radius and the locking state reference data of the abnormally locked hole position to be confirmed includes: According to the locking state reference data, an average value of the hole position image radius change is obtained; Obtaining the hole image radius of the abnormal hole to be confirmed for locking before screw assembly; According to the hole position image radius of the hole position to be confirmed with abnormal locking and the hole position image radius before screw assembly, a hole position image radius change value of each hole position to be confirmed with abnormal locking is obtained; The hole positions with abnormal locking are determined according to the hole position image radius change average value and the hole position image radius change value.

[0012] Optionally, after obtaining the locking state of each screw hole area according to the locking state reference data and the image feature data, the method further includes: Performing a first mark on the abnormal locking hole position to be confirmed on the plane image of the processed object; Performing a second mark on the abnormal locking hole position on the plane image of the processed object; Upload the marked flat image of the processed object to the console for manual verification.

[0013] In addition, in order to achieve the above-mentioned purpose, the present invention provides a screw locking state detection device, the screw locking state detection device comprising: A data acquisition module is used to determine the screw hole area image based on the plane image of the processed object; An image processing module, used to obtain image feature data of each screw hole according to the screw hole area image; The data analysis module is used to obtain the locking state of each screw hole area according to the locking state reference data and the image feature data.

[0014] In addition, to achieve the above-mentioned purpose, the present invention provides a screw locking state detection device, which includes: a memory, a processor, and a screw locking state detection program stored in the memory and executable on the processor, wherein the screw locking state detection program is configured to implement the steps of the screw locking state detection method.

[0015] In addition, to achieve the above-mentioned purpose, the present invention provides a storage medium, on which a screw locking state detection program is stored, and when the screw locking state detection program is executed by a processor, the steps of the screw locking state detection method are implemented.

[0016] The present invention collects the plane image of the workpiece before and after the screw is assembled, then extracts the image of the screw hole area, performs data processing, and obtains the mean value of the gray value change before and after assembly and the hole image radius as reference data for the locking state. By comparing the gray value of the screw hole area image after assembly and the radius size in the image, the hole positions with abnormal gray value change and hole image radius are identified, thereby determining the possible abnormal locking holes. Finally, these abnormal holes are marked and uploaded to the console for manual verification. This solution effectively improves the accuracy and efficiency of locking detection through automated image processing and data analysis, ensuring product quality and compliance. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0018] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0019] Figure 1 This is a flow chart of the first embodiment of the screw locking state detection method of the present application; Figure 2 This is a flow chart of a second embodiment of the screw locking state detection method of the present application; Figure 3 This is a flow chart of a third embodiment of the screw locking state detection method of the present application; Figure 4 This is a schematic diagram of the functional modules of the screw locking status detection device of this application; Figure 5 It is a structural diagram of a terminal device in the hardware operating environment involved in the embodiment of the present application.

[0020] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0021] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0022] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0023] It should be noted that the execution subject of this embodiment may be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, a screw locking state detection device, etc. The following takes the screw locking state detection device as an example to illustrate this embodiment and the following embodiments.

[0024] The present application embodiment provides a method for detecting the screw locking state. Figure 1 , Figure 1 This is a flow chart of the first embodiment of the present application.

[0025] In this embodiment, the screw locking state detection method includes: Step S10: Determine the screw hole area image according to the plane image of the processed object.

[0026] It should be noted that on the plane of the processed object, the position of the screw hole area is fixed. Each screw hole area can be determined by the marking points left on the plane of the object, and then the screw hole areas on the plane image are separately divided to obtain images of each screw hole area.

[0027] In one embodiment, determining the screw hole area image based on the plane image of the processed object includes: performing feature recognition on the plane image of the processed object to determine the reference area image; and determining the screw hole area image based on relative position parameters between the reference area image and each screw hole area.

[0028] It can be understood that in this step, more basic image processing technology can be used to analyze and identify reserved features in the plane image of the processed object. These features can be pre-designed marks. More accurate methods include, for example, QR codes, bar codes or specific patterns. Simpler methods rely on intuitive geometric shapes, color differences or texture features in the image. For example, image processing technology is used to detect places where the brightness changes dramatically in the image. These places are usually the edges of objects. Using this area with certain characteristics as a reference point for subsequent steps can simplify the difficulty of extracting the image of the screw hole area.

[0029] It should be understood that, in the present embodiment, the reference area refers to a square area whose upper left corner is at a fixed length from the edges of the workpieces on both sides after the workpiece is aligned, and the side length of the area is known. After obtaining the plane image of the workpiece, the position of the area in the image is first determined, and then the workpiece image is leveled according to the offset of the reference area, and then the screw hole area image in the image is divided out accordingly according to the horizontal angle and distance formed by each hole position and the reference area.

[0030] It should be noted that for the workpieces to be processed with the same specifications and processing tasks, the positions of the screw holes on the workpieces are fixed. Therefore, after setting the reference area on the workpiece, the relative positions of all the screw holes and the reference area are determined. Taking the commonly used polar coordinate system as an example, the orientation and distance between the screw holes and the reference area are used as index items. After finding the reference area in the plane image of any workpiece, the image of the screw hole area can be determined one by one according to the direction and distance. The divided area image should be slightly larger than the general screw hole diameter in terms of length and width of the image to ensure that the divided image completely contains the original image of the screw hole.

[0031] Step S20: obtaining image feature data of each screw hole according to the screw hole area image.

[0032] It should be noted that in the process of automatically detecting the screw locking status, it is necessary to extract useful information from the screw hole area image for subsequent analysis and judgment. The detailed process of obtaining image feature data includes: first preprocessing the image, which includes using filters (such as Gaussian blur) to reduce the noise in the image and improve the accuracy of subsequent feature extraction, or by adjusting the brightness, contrast or using edge enhancement algorithms to highlight the key features in the image, that is, first performing image noise reduction and enhancement processing; after the preprocessing is completed, it is necessary to further perform grayscale processing, that is, converting the color image into a grayscale image, which can reduce the complexity of data processing while retaining the structural information of the image. After the processing is completed, the grayscale histogram of the screw hole area needs to be calculated, which helps to analyze the grayscale distribution of the image. In addition to using grayscale values ​​as feature data, edge detection algorithms (such as the Canny algorithm) can also be used to identify the edges of screw holes to determine the position and shape of the screw holes. In addition, shape recognition techniques (such as contour detection) can be used to extract shape features of screw holes. These shape features include area, perimeter, convex hull, etc. When some conventional methods cannot extract features that clearly distinguish the components, the texture features of the screw hole area can be further analyzed, such as gray-level co-occurrence matrix (GLCM) or local binary pattern (LBP). These features help identify surface defects or foreign matter.

[0033] It is understandable that after acquiring the features in the image, it is necessary to further quantify the features and convert the image features into numerical values ​​and statistical data in order to analyze, compare and understand their distribution and changes. The quantified features can be easily compared and calculated. For example, by comparing the area or perimeter of two screw hole area images, it can be determined whether they have the same size, or by comparing the grayscale mean of two screw hole area images, it can be determined whether they have the same surface reflective properties or wear status. If the grayscale mean values ​​of the two screw holes are similar, it may indicate that their surface conditions are similar; if the grayscale mean values ​​are very different, it may indicate that one screw hole area is smoother or more worn than the other, or is affected by different lighting conditions.

[0034] In one embodiment, image feature data of each screw hole is obtained according to the screw hole area image, including: obtaining the grayscale value of each screw hole area image according to the screw hole area image; obtaining the image grayscale mean according to the grayscale value of each screw hole area image; obtaining the grayscale difference value of each screw hole according to the image grayscale mean and the grayscale value of each screw hole area image, and using the grayscale difference value as the image feature data.

[0035] It should be understood that in this embodiment, the main comparison is the difference in grayscale value changes. Since the grayscale value will be affected by different lighting, directly using the grayscale value of the screw hole image with normal locking that is reserved in advance is likely to cause result deviation. However, under the same lighting conditions, the grayscale value change of the screw hole image before and after the locking is completed should be the same. Therefore, the process of judging the locking state of the screw hole in this embodiment is to first obtain the grayscale value of each screw hole in the image, then calculate the average grayscale value, and subtract the grayscale value of each screw hole from the grayscale average value. In the obtained difference, if it is close to the grayscale change value obtained in the previous step, it means that the hole position may have a poor locking state. By comprehensively analyzing the grayscale value of the screw hole area image, this embodiment can accurately identify and judge the screw locking state, effectively improving the reliability and efficiency of detection.

[0036] Step S30: Obtaining the locking state of each screw hole area according to the locking state reference data and the image feature data.

[0037] It should be noted that, in this embodiment, the image feature data obtained in the above steps are compared and analyzed with the pre-set reference data of the locking state. This process involves comparing the grayscale value, shape parameters such as area and perimeter, and texture features of the actually measured screw hole area with the standard sample with good locking. Through this comparison, it can be evaluated whether the locking state of each screw hole meets the quality standard.

[0038] It is understandable that this comparative analysis allows the system to automatically identify screw holes that may have locking problems. For example, if the grayscale change value of a screw hole is significantly different from the reference data, or its shape parameters indicate significant deformation after assembly, this may indicate that the locking state of the screw hole is poor. Through this step, an accurate assessment of the locking state of each screw hole can be achieved, defects in production can be discovered in a timely manner, and appropriate measures can be taken to correct them. This method not only improves the accuracy and efficiency of detection, but also helps to improve the quality of the final product, ensuring that the locking of each screw hole meets the design requirements. In addition, by continuously collecting and analyzing this data, the production process can be further optimized and production efficiency can be improved.

[0039] In one embodiment, after obtaining the locking status of each screw hole area based on the locking status reference data and the image feature data, it also includes: making a first mark on the abnormal locking hole positions to be confirmed on the plane image of the processed object; making a second mark on the abnormal locking hole positions on the plane image of the processed object; and uploading the marked plane image of the processed object to the console for manual verification.

[0040] It should be understood that in the process of locking state detection, for the purpose of preventing missed detection, for the hole positions that may have locking abnormalities and the hole positions that are very likely to have locking abnormalities, in this embodiment, they correspond to the hole positions with locking abnormalities to be confirmed and the hole positions with locking abnormalities, respectively. Since this is the result of machine judgment, the final manual verification is still required, and the two types of hole positions are marked with different types of marks, which can greatly reduce the workload of manual verification. For example, for a workpiece with dozens of screw holes, the number of hole positions that workers need to verify may not exceed five, and the possibility of problems in each hole position is distinguished. Therefore, this hierarchical marking method not only improves the efficiency of manual verification, but also makes the verification process more targeted. Workers can first focus on those hole positions that have been marked as being very likely to have locking abnormalities, thereby quickly solving the most likely problems. Then, for the abnormal hole positions to be confirmed, workers can conduct further inspections to determine whether corrective measures are needed.

[0041] The present embodiment provides a method for detecting the locking status of a screw. The present embodiment determines a screw hole area image based on a plane image of a processed object; obtains image feature data of each screw hole based on the screw hole area image; and obtains the locking status of each screw hole area based on locking status reference data and the image feature data.

[0042] In summary, this embodiment achieves efficient and accurate identification of the screw locking status by combining automated detection with manual verification, which not only improves the accuracy and efficiency of production quality control, but also reduces the workload of manual inspection and the risk of missed inspections, while providing data support for continuous improvement of production processes and product quality.

[0043] Reference Figure 2 , Figure 2 This is a flow chart of a second embodiment of a method for detecting a screw locking state of the present application. Based on the above-mentioned first embodiment, the second embodiment of the method for detecting a screw locking state of the present application is proposed.

[0044] In this embodiment, before step S10, the method for detecting the screw locking state further includes: Step S001: obtaining the image grayscale value and hole position image radius of each screw hole area before and after assembly based on the plane images before and after assembly.

[0045] It should be noted that, in this embodiment, the plane images of the workpiece before and after assembly are obtained with the aim of obtaining the image radius size and the change in grayscale value of each screw hole before and after assembly. Since the image grayscale value and hole image radius before and after assembly can be obtained for each hole individually, a separate comparison can be directly performed when identifying the locking state, thereby further improving the accuracy of state recognition.

[0046] It can be understood that since this step occurs before the locking status inspection, it is equivalent to obtaining a set of reference data accurate to the locking status of each hole position in advance. This set of reference data includes some features related to the screw holes before and after locking, which improves the directness and reliability of status identification.

[0047] Step S002: obtaining an average grayscale change of the screw hole regions before and after assembly according to the grayscale values ​​of the images of the screw hole regions before and after assembly.

[0048] It is understandable that the change in gray value can reflect a variety of factors, including but not limited to the change in the coverage of the hole surface caused by the screw locking, the change in the shadow inside the hole, and the surface wear that may occur during the assembly process. By calculating the average value of these changes, a relatively objective indicator can be obtained to evaluate the overall change of the entire workpiece surface during the locking process.

[0049] Step S003: obtaining an average value of the change in the hole position image radius of each screw hole area before and after assembly according to the hole position image radius of each screw hole area before and after assembly.

[0050] It should be noted that the change in the hole image radius can intuitively reflect the physical size change of the hole during the assembly process. For example, if the screw is properly locked, we expect to see a decrease in the hole radius because the head of the screw will be embedded in the hole, causing the hole edge to move inward. On the contrary, if the hole radius changes little or increases, this may indicate that the locking is not successful or there are other problems.

[0051] It is understood that by calculating the average value of the hole image radius variation, we can get a baseline for evaluating the effectiveness of the overall assembly process. This average value helps to identify possible systematic problems in the assembly process, such as insufficient machine pressure, improper screw size, or assembly technique problems.

[0052] It should be understood that if the radius variation of a particular screw hole is significantly different from the average, this may indicate that there is a problem with that hole location. By monitoring the variation in hole radius, it is possible to predict maintenance that may be required on the equipment to avoid future production interruptions.

[0053] Step S004: taking the grayscale variation average value and the hole position image radius variation average value as locking state reference data.

[0054] It should be noted that the purpose of the locking status reference data is to provide a set of standardized and quantifiable benchmarks for the automated detection of screw locking quality.

[0055] It can be understood that in this embodiment, the average value of grayscale change and the average value of hole image radius change are selected as reference data for locking status. Combining two different types of data (grayscale and radius) can provide a more comprehensive locking status evaluation. The two types of data verify each other, which can reduce the misjudgment that may occur from a single data source. This method can adapt to different production environments and different types of workpieces, and has good flexibility and adaptability.

[0056] The present embodiment provides a method for detecting the locking state of screws, which obtains a plane image of the processed object before screw assembly and a plane image of the object after screw assembly; obtains the image grayscale value and hole image radius of each screw hole area before and after assembly based on the plane images before and after assembly; obtains the average grayscale change of the screw hole area before and after assembly based on the image grayscale value of each screw hole area before and after assembly; obtains the average hole image radius change of the screw hole area before and after assembly based on the hole image radius of each screw hole area before and after assembly; and uses the average grayscale change and the average hole image radius change as locking state reference data.

[0057] In summary, the beneficial effect of this embodiment is that it provides an accurate and comprehensive method for detecting the screw locking status, effectively improves the detection accuracy and production efficiency, reduces manual intervention and production costs, enhances product quality control, ensures continuous improvement of the process, and improves production flexibility and adaptability, thereby meeting regulatory requirements and enhancing market competitiveness.

[0058] Reference Figure 3 , Figure 3 This is a flow chart of a third embodiment of a method for detecting a screw locking state of the present application. Based on the above-mentioned first embodiment, the third embodiment of the method for detecting a screw locking state of the present application is proposed.

[0059] Step S301: Obtaining abnormal hole positions to be confirmed for locking according to the grayscale change average value and the grayscale difference values ​​of each screw hole.

[0060] It should be noted that by comparing the grayscale difference value of each screw hole area with the average grayscale change, those screw holes that deviate significantly from the normal locking state can be identified, where the grayscale difference value refers to the difference between the grayscale change of a single screw hole and the average change, and the average grayscale change is the average value of the grayscale change of all screw holes.

[0061] It is understandable that the purpose of this step is to mark those holes that may have locking problems. The average value of the grayscale change provides a benchmark, and the grayscale difference value of each screw hole provides the degree of difference between the actual measurement value and this benchmark. If the grayscale difference value of a screw hole exceeds the preset threshold, this indicates that the locking status of the screw hole may not meet the requirements, and it is therefore marked as a hole position with abnormal locking to be confirmed.

[0062] It should be understood that the reason for performing grayscale value detection before image radius detection is that grayscale value detection is a detection method with lower computing power and is easier to implement than extracting features from the original image and calculating the radius of the screw holes and nuts in the image. Therefore, detecting the grayscale value first during the preliminary screening process can increase the processing speed of the system.

[0063] Step S302: determining the abnormally locked hole position according to the hole position image radius and the locking state reference data of the abnormally locked hole position to be confirmed.

[0064] In one embodiment, the method of determining the abnormally locked hole position based on the hole position image radius of the hole position to be confirmed with abnormal locking and the locking status reference data includes: obtaining an average value of the hole position image radius change based on the locking status reference data; obtaining the hole position image radius of the hole position to be confirmed with abnormal locking before screw assembly; obtaining the hole position image radius change value of each hole position to be confirmed with abnormal locking based on the hole position image radius of the hole position to be confirmed with abnormal locking and the hole position image radius before screw assembly; determining the abnormally locked hole position based on the average value of the hole position image radius change and the hole position image radius change value.

[0065] It is understandable that when a screw is screwed into a screw hole, the head of the screw usually embeds into the hole, resulting in a reduction in the effective radius of the hole. This physical change will be reflected in the image, as a change in the radius of the circle representing the hole or nut radius in the image. In addition, after the screw is locked, the screw head may change the light reflection characteristics of the surface around the hole. This change may affect the grayscale value distribution of the image, thereby affecting the identification of the hole edge and further affecting the measured radius. The screw head may block part of the hole wall, causing the visible edge position of the hole to change when viewed from certain angles. In some special cases, if the force applied is too large, it may cause a slight deformation of the workpiece surface, thereby affecting the position of the hole edge, that is, the different depths of screw insertion may also cause changes in the image radius of the hole. The average value of the hole image radius change in the locked state reference data represents the change in the hole radius that should occur after the screw is locked under normal circumstances.

[0066] It should be understood that in this embodiment, by comparing the radius change value of the hole to be confirmed with the average value of the radius change after normal screw locking, it is determined which holes may have problems with the locking state. This method can effectively identify those holes with poor locking, so as to conduct further inspection or rework to ensure product quality.

[0067] Step S303: obtaining the locking status of each screw hole area according to the abnormal locking hole position.

[0068] It should be noted that since the position of each hole on the workpiece plane is known, the sorting numbers and parameters correspond one to one. By marking the locking status of all holes one by one, especially marking the abnormally locked holes, a locking status detection table of all screw hole areas of the workpiece can be obtained. Such a detection table not only clearly shows the locking status of each screw hole, but also facilitates subsequent quality control and production management.

[0069] Understandably, this inspection table provides an instant feedback mechanism for the production line, allowing operators to quickly identify and address those holes with abnormal locking, in this way, the risk of defective products entering the market can be minimized.

[0070] The present embodiment provides a method for detecting the locking status of a screw. The present embodiment obtains an average grayscale change value based on the locking status reference data; obtains the abnormal locking hole position to be confirmed based on the grayscale change average grayscale change value and the grayscale difference value of each screw hole; determines the abnormal locking hole position based on the hole position image radius of the abnormal locking hole position to be confirmed and the locking status reference data; and obtains the locking status of each screw hole area based on the abnormal locking hole position.

[0071] In summary, the beneficial effect of this embodiment lies in the comprehensive application of the detection method of grayscale change and hole image radius change, which realizes efficient and accurate identification of the screw locking state and provides a structured and automated evaluation process, which not only improves production efficiency and product quality, but also reduces costs and reduces the defective rate. By providing a clear locking state detection table, it enhances the instant feedback and response capabilities of the production line, ensuring the traceability of product quality and continuous optimization of production.

[0072] Reference Figure 4 The present application also provides a screw locking state detection device, the screw locking state detection device comprising: The data acquisition module 10 is used to determine the screw hole area image according to the plane image of the processed object; An image processing module 20, used to obtain image feature data of each screw hole according to the screw hole area image; The data analysis module 30 is used to obtain the locking state of each screw hole area according to the locking state reference data and the image feature data.

[0073] In one embodiment, the data acquisition module 10 is further used to respectively obtain a plane image of the processed object before screw assembly and a plane image after screw assembly; based on the plane images before and after assembly, the image grayscale values ​​and hole image radius of each screw hole area before and after assembly are obtained; based on the image grayscale values ​​of each screw hole area before and after assembly, the average grayscale change of the screw hole area before and after assembly is obtained; based on the hole image radius of each screw hole area before and after assembly, the average hole image radius change before and after assembly is obtained; and the grayscale change average value and the hole image radius change average value are used as locking state reference data.

[0074] In one embodiment, the image processing module 20 is further used to perform feature recognition on the plane image of the processed object to determine a reference area image; and determine the screw hole area image based on relative position parameters between the reference area image and each screw hole area.

[0075] In one embodiment, the data analysis module 30 is further used to obtain the grayscale value of each screw hole area image based on the screw hole area image; obtain the image grayscale mean based on the grayscale value of each screw hole area image; obtain the grayscale difference value of each screw hole based on the image grayscale mean and the grayscale value of each screw hole area image, and use the grayscale difference value as the image feature data.

[0076] In one embodiment, the data analysis module 30 is also used to obtain the locking status of each screw hole area based on the locking status reference data and the image feature data, including: obtaining the grayscale change average value based on the locking status reference data; obtaining the abnormal locking hole position to be confirmed based on the grayscale change average value and the grayscale difference value of each screw hole; determining the abnormal locking hole position based on the hole position image radius of the abnormal locking hole position to be confirmed and the locking status reference data; and obtaining the locking status of each screw hole area based on the abnormal locking hole position.

[0077] In one embodiment, the data analysis module 30 is further used to obtain an average value of hole position image radius change based on the locking status reference data; obtain the hole position image radius of the to-be-confirmed abnormal locking hole before screw assembly; obtain hole position image radius change values ​​of each to-be-confirmed abnormal locking hole based on the hole position image radius of the to-be-confirmed abnormal locking hole and the hole position image radius before screw assembly; determine the abnormal locking hole based on the average value of the hole position image radius change and the hole position image radius change value.

[0078] In one embodiment, the image processing module 20 is also used to make a first mark on the abnormal locking hole positions to be confirmed on the plane image of the processed object; make a second mark on the abnormal locking hole positions on the plane image of the processed object; and upload the marked plane image of the processed object to the console for manual verification.

[0079] An embodiment of the present application also provides a screw locking status detection device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the screw locking status detection method in the above-mentioned embodiment 1.

[0080] Reference below Figure 5, which shows a schematic diagram of the structure of a screw locking state detection device suitable for implementing the embodiment of the present application. The screw locking state detection device in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 4 The screw locking status detection device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0081] like Figure 5 As shown, the screw locking state detection device may include a processing device 1001 (such as a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the screw locking state detection device are also stored. The processing device 1001, ROM1002 and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the screw locking state detection device to communicate with other devices wirelessly or wired to exchange data. Although the figure shows a screw locking state detection device with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or provided instead.

[0082] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0083] The screw locking state detection device provided by the present application adopts the screw locking state detection method in the above embodiment, which can solve the technical problem of how to intelligently detect the screw locking state on the workpiece and improve the product detection efficiency in the field. Compared with the prior art, the beneficial effects of the screw locking state detection device provided by the present application are the same as the beneficial effects of the screw locking state detection method provided by the above embodiment, and the other technical features of the screw locking state detection device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0084] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0085] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0086] The present application also provides a storage medium, on which a screw locking state detection program is stored. When the screw locking state detection program is executed by a processor, the steps of the screw locking state detection method described in any one of the above are implemented.

[0087] The storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM: Random Access Memory), a read-only memory (ROM: Read Only Memory), an erasable programmable read-only memory (EPROM: Erasable Programmable Read Only Memory or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM: CD-Read Only Memory), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, system or device. The program code contained on the storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency: Radio Frequency), etc., or any suitable combination of the above.

[0088] The storage medium may be included in the screw locking state detection device; or may exist independently without being assembled into the screw locking state detection device.

[0089] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by the screw locking state detection device, the screw locking state detection device: determines the screw hole area image based on the plane image of the processed object; obtains the image feature data of each screw hole based on the screw hole area image; obtains the locking state of each screw hole area based on the locking state reference data and the image feature data.

[0090] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0091] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0092] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0093] The storage medium provided in this application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned screw locking state detection method, and can solve the technical problem of how to intelligently detect the screw locking state on the workpiece and improve the product detection efficiency. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the screw locking state detection method provided in the above-mentioned embodiment, and will not be repeated here.

[0094] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A method for detecting a screw locking state, characterized in that: The screw locking state detection method comprises: Determine the screw hole area image according to the plane image of the processed object; Obtaining image feature data of each screw hole according to the screw hole area image; The locking state of each screw hole area is obtained according to the locking state reference data and the image feature data.

2. The method for detecting screw locking status according to claim 1, characterized in that: Before determining the screw hole area image according to the plane image of the processed object, the method further includes: Respectively acquiring a plane image of the object before screw assembly and a plane image after screw assembly; According to the plane images before and after assembly, the image grayscale value and hole position image radius of each screw hole area before and after assembly are obtained; According to the image grayscale values ​​of each screw hole area before and after assembly, an average grayscale change value of the screw hole area before and after assembly is obtained; According to the hole position image radius of each screw hole area before and after assembly, an average value of the hole position image radius change before and after assembly of the screw hole area is obtained; The average value of the grayscale change and the average value of the hole position image radius change are used as reference data for the locking state.

3. The method for detecting screw locking status according to claim 1, characterized in that: The step of determining the screw hole area image according to the plane image of the processed object includes: Performing feature recognition on the plane image of the processed object to determine a reference area image; The screw hole area image is determined based on relative position parameters between the reference area image and each screw hole area.

4. The method for detecting screw locking status according to claim 1, characterized in that: The step of obtaining image feature data of each screw hole according to the screw hole area image includes: Obtaining the grayscale value of each screw hole area image according to the screw hole area image; According to the grayscale values ​​of the images of the screw hole regions, an image grayscale mean is obtained; According to the grayscale mean value of the image and the grayscale value of each screw hole area image, the grayscale difference value of each screw hole is obtained, and the grayscale difference value is used as the image feature data.

5. The method for detecting screw locking status according to claim 1, characterized in that: The method of obtaining the locking state of each screw hole area according to the locking state reference data and the image feature data includes: According to the locking state reference data, an average value of grayscale change is obtained; According to the grayscale change average value and the grayscale difference value of each screw hole, the abnormal hole position to be confirmed is obtained; Determine the abnormally locked hole position according to the hole position image radius and locking state reference data of the abnormally locked hole position to be confirmed; The locking status of each screw hole area is obtained according to the abnormal locking hole position.

6. The method for detecting the screw locking state according to claim 5, characterized in that: The step of determining the abnormally locked hole position according to the hole position image radius of the abnormally locked hole position to be confirmed and the reference data of the locked state includes: According to the locking state reference data, an average value of the hole position image radius change is obtained; Obtaining the hole image radius of the abnormal hole to be confirmed for locking before screw assembly; According to the hole position image radius of the hole position to be confirmed with abnormal locking and the hole position image radius before screw assembly, a hole position image radius change value of each hole position to be confirmed with abnormal locking is obtained; The hole positions with abnormal locking are determined according to the hole position image radius change average value and the hole position image radius change value.

7. The method for detecting screw locking status according to claim 1, characterized in that: After obtaining the locking state of each screw hole area according to the locking state reference data and the image feature data, the method further includes: Performing a first mark on the abnormal locking hole position to be confirmed on the plane image of the processed object; Performing a second mark on the abnormal locking hole position on the plane image of the processed object; Upload the marked flat image of the processed object to the console for manual verification.

8. A screw locking state detection device, characterized in that: The screw locking state detection device comprises: A data acquisition module is used to determine the screw hole area image based on the plane image of the processed object; An image processing module, used to obtain image feature data of each screw hole according to the screw hole area image; The data analysis module is used to obtain the locking state of each screw hole area according to the locking state reference data and the image feature data.

9. A screw locking state detection device, characterized in that: The screw locking state detection device includes: a memory, a processor, and a screw locking state detection program stored in the memory and executable on the processor, wherein the screw locking state detection program is configured to implement the steps of the screw locking state detection method according to any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium stores a screw locking state detection program, and when the screw locking state detection program is executed by the processor, the steps of the screw locking state detection method according to any one of claims 1 to 7 are implemented.

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