Cable installation risk detection method and device, storage medium and electronic equipment

Abstract

The invention discloses a cable installation risk detection method and device, a storage medium and electronic equipment. Relates to the field of artificial intelligence, the technical field of electronics and other related technical fields, and comprises the following steps: detecting a target image when a target cable is installed on a target object through a target detection model to obtain target operation information; classifying the target image through a target classification model to obtain installation step information corresponding to the target image; and carrying out risk detection on the installation process of the target cable according to the target operation information and the installation step information to obtain a target detection result. According to the method and the device, the problem that the efficiency of detecting the cable installation risk is relatively low because the installation process of the cable is detected manually to determine whether the cable installation has the risk in the related technology is solved.

Description

Technical Field

[0001] The present application relates to the fields of artificial intelligence, electronic technology and other related technical fields, and specifically to a method and device for detecting cable installation risks, a storage medium and an electronic device. Background Art

[0002] At present, the operation mode of power companies is mainly based on manual operation and manual recording. Cable head on-site supervision is a typical representative of this, which has the disadvantages of numerous tools, cumbersome work, difficulty in comprehensive supervision, low efficiency, and high error rate. During the production and installation of cable heads, supervisors are required to conduct on-site supervision according to the production requirements of cable heads. The supervision method is mainly for supervisors to take photos, check on-site, and make records. However, the working method of on-site supervision is difficult to comprehensively and efficiently supervise the entire work process. And because the supervisor is manually supervising, the supervision information is not fully entered and the error rate is high during the supervision process. At the same time, the supervision results of on-site supervision are pictures, which need to be entered twice before entering into the database, resulting in low work efficiency.

[0003] With regard to the problem that the related art uses a manual method to detect the cable installation process to determine whether there are risks in the cable installation, resulting in low efficiency in the cable installation risk detection, no effective solution has been proposed so far. Summary of the invention

[0004] The main purpose of the present application is to provide a cable installation risk detection method and device, storage medium and electronic device, so as to solve the problem that the related art uses manual methods to detect the cable installation process to determine whether there are risks in the cable installation, resulting in low efficiency in cable installation risk detection.

[0005] In order to achieve the above-mentioned purpose, according to one aspect of the present application, a method for detecting cable installation risks is provided. The method comprises: detecting a target image when a target object installs a target cable through a target detection model to obtain target operation information, wherein the target operation information at least comprises: operation behavior information and operation position information of the target object on the target cable; classifying the target image through a target classification model to obtain installation step information corresponding to the target image; performing risk detection on the installation process of the target cable according to the target operation information and the installation step information to obtain a target detection result.

[0006] Furthermore, the target image when the target object installs the target cable is detected by the target detection model to obtain the target operation information, including: performing image segmentation on the target image to obtain multiple target sub-images after segmentation; performing image filtering on the multiple target sub-images to obtain target operation sub-images; performing feature extraction on the target operation sub-images to obtain hand feature information of the target object; and obtaining the target operation information based on the hand feature information.

[0007] Furthermore, classifying the target image through a target classification model to obtain installation step information corresponding to the target image includes: performing image enhancement processing on the target image to obtain an enhanced target image; performing feature extraction on the enhanced target image to obtain initial feature information corresponding to the target cable; screening the initial feature information to obtain target feature information; and classifying the target image according to the target feature information to obtain the installation step information.

[0008] Furthermore, a risk detection is performed on the installation process of the target cable based on the target operation information and the installation step information to obtain a target detection result, including: judging whether the target operation information and the installation step information meet the target detection conditions to obtain a judgment result; if the judgment result indicates that the target operation information and the installation step information meet the target detection conditions, then determining that the target detection result is that there is no risk in the cable installation; if the judgment result indicates that the target operation information and the installation step information do not meet the target detection conditions, then determining that the target detection result is that there is a risk in the cable installation.

[0009] Furthermore, after determining whether the target operation information and the installation step information meet the target detection conditions and obtaining a determination result, the method further includes: when the target detection result is that there is no risk in cable installation, compiling and packaging the target operation information, the installation step information and the target detection result to obtain an installation record file corresponding to the target cable; uploading the installation record file to a target server, wherein the target server is used to store installation records and detection records of multiple cables; when the target detection result is that there is a risk in cable installation, determining, in the target server, a target record file corresponding to the target operation information and the installation step information; and optimizing the installation process of the target cable based on the target record file.

[0010] Furthermore, before detecting the target image when the target object is installing the target cable through the target detection model to obtain the target operation information, the method also includes: acquiring an initial image when the target object is installing the target cable; cleaning the initial image to obtain a cleaned initial image; cropping the cleaned initial image to obtain a cropped initial image; and adjusting the contrast of the cropped initial image to obtain the target image.

[0011] Furthermore, the initial image is cleaned to obtain a cleaned initial image, which includes: performing damage detection on the initial image to clean damaged data in the initial image to obtain a first initial image; performing Laplace transform on the first initial image to clean fuzzy data in the first initial image to obtain a second initial image; and performing similarity calculation on the second initial image to clean similar data in the second initial image to obtain the cleaned initial image.

[0012] In order to achieve the above-mentioned purpose, according to another aspect of the present application, a device for detecting cable installation risks is provided. The device comprises: a first detection unit, which is used to detect the target image when the target object installs the target cable through the target detection model, and obtain the target operation information, wherein the target operation information at least includes: the operation behavior information and operation position information of the target object on the target cable; a classification unit, which is used to classify the target image through the target classification model, and obtain the installation step information corresponding to the target image; a second detection unit, which is used to perform risk detection on the installation process of the target cable according to the target operation information and the installation step information, and obtain the target detection result.

[0013] Furthermore, the first detection unit includes: a segmentation module, used to perform image segmentation on the target image to obtain multiple target sub-images after segmentation; a filtering module, used to perform image filtering on the multiple target sub-images to obtain a target operation sub-image; a first extraction module, used to perform feature extraction on the target operation sub-image to obtain hand feature information of the target object; and a first determination module, used to obtain the target operation information based on the hand feature information.

[0014] Furthermore, the classification unit includes: an enhancement module, used to perform image enhancement processing on the target image to obtain an enhanced target image; a second extraction module, used to perform feature extraction on the enhanced target image to obtain initial feature information corresponding to the target cable; a screening module, used to screen the initial feature information to obtain target feature information; and a classification module, used to classify the target image according to the target feature information to obtain the installation step information.

[0015] Further, the second detection unit includes: a judgment module, used to judge whether the target operation information and the installation step information meet the target detection conditions to obtain a judgment result; a second determination module, used to determine that the target detection result is that there is no risk in the cable installation if the judgment result indicates that the target operation information and the installation step information meet the target detection conditions; and a third determination module, used to determine that the target detection result is that there is a risk in the cable installation if the judgment result indicates that the target operation information and the installation step information do not meet the target detection conditions.

[0016] Furthermore, the device also includes: a compilation unit, which is used to judge whether the target operation information and the installation step information meet the target detection condition, and after obtaining the judgment result, if the target detection result is that there is no risk in the cable installation, compile and package the target operation information, the installation step information and the target detection result to obtain the installation record file corresponding to the target cable; a transmission unit, which is used to upload the installation record file to a target server, wherein the target server is used to store installation records and detection records of multiple cables; a determination unit, which is used to determine the target record file corresponding to the target operation information and the installation step information in the target server when the target detection result is that there is a risk in the cable installation; an optimization unit, which is used to optimize the installation process of the target cable based on the target record file.

[0017] Furthermore, the device also includes: an acquisition unit, used to detect the target image when the target object installs the target cable through the target detection model, and before obtaining the target operation information, acquire the initial image when the target object installs the target cable; a cleaning unit, used to clean the initial image to obtain the cleaned initial image; a cropping unit, used to crop the cleaned initial image to obtain the cropped initial image; and an adjustment unit, used to adjust the contrast of the cropped initial image to obtain the target image.

[0018] Furthermore, the cleaning unit includes: a detection module, used to perform damage detection on the initial image to clean the damaged data in the initial image to obtain a first initial image; a transformation module, used to perform Laplace transform on the first initial image to clean the blurred data in the first initial image to obtain a second initial image; and a calculation module, used to perform similarity calculation on the second initial image to clean the similar data in the second initial image to obtain the cleaned initial image.

[0019] In order to achieve the above-mentioned purpose, according to one aspect of the present application, a computer-readable storage medium is provided, wherein the storage medium stores a program, wherein when the program is running, the device where the storage medium is located is controlled to execute any one of the above-mentioned cable installation risk detection methods.

[0020] In order to achieve the above-mentioned purpose, according to another aspect of the present application, an electronic device is further provided, the electronic device comprising one or more processors and a memory, the memory being used to store the one or more processors implementing any one of the above-mentioned methods for detecting cable installation risks.

[0021] Through this application, the following steps are adopted: the target image when the target object installs the target cable is detected by the target detection model to obtain the target operation information, wherein the target operation information at least includes: the target object's operation behavior information and operation position information on the target cable; the target image is classified by the target classification model to obtain the installation step information corresponding to the target image; the installation process of the target cable is risk detected according to the target operation information and the installation step information to obtain the target detection result. Through this application, the problem that the installation process of the cable is detected manually in the related art to determine whether there is a risk in the cable installation, resulting in a relatively low efficiency in the risk detection of cable installation, is solved. In this scheme, the target image of the target object in the process of installing the target cable is detected by the target detection model to obtain the target operation information such as the operation behavior information and the operation position information of the target object in the process of installing the target cable. Then the target classification model is used to classify the target image to obtain the installation step information of the target cable corresponding to the target image. Finally, the installation process of the target cable is risk detected based on the target operation information and the installation step information to obtain the target detection result. The target detection model and target classification model realize automatic detection and automatic classification of target images, which reduces labor costs and time consumption, improves the precision and accuracy of target operation information and installation step information, and reduces the risk of false detection and missed detection. Through real-time detection of target operation information and installation step information, problems can be discovered and feedback can be provided in a timely manner, eliminating the reliance on manual labor and improving the management capabilities of target cables during installation. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0023] Figure 1 is a flow chart of a method for detecting cable installation risks provided in an embodiment of the present application;

[0024] Figure 2is a schematic diagram of cleaning an initial image according to an embodiment of the present application;

[0025] Figure 3 is a schematic diagram of a method for detecting cable installation risks provided in an embodiment of the present application;

[0026] Figure 4 is a schematic diagram of a cable installation risk detection device provided according to an embodiment of the present application;

[0027] Figure 5 is a schematic diagram of an electronic device provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0028] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0029] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0030] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0031] It should be noted that the relevant information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for display, data for analysis, etc.) involved in this disclosure are all information and data authorized by the user or fully authorized by all parties. For example, an interface is set between this system and the relevant user or organization. Before obtaining relevant information, it is necessary to send an acquisition request to the aforementioned user or organization through the interface, and obtain relevant information after receiving the consent information fed back by the aforementioned user or organization.

[0032] The present invention is described below in conjunction with preferred implementation steps. Figure 1 is a flow chart of a method for detecting cable installation risks provided in an embodiment of the present application, such as Figure 1 As shown, the method comprises the following steps:

[0033] Step S101, detecting a target image of a target object installing a target cable through a target detection model to obtain target operation information, wherein the target operation information at least includes: operation behavior information and operation position information of the target object on the target cable.

[0034] Optionally, the target image of the worker (ie, the target object) when installing the target cable is detected and recognized through a ResNet50 model or other models (ie, a target detection model) to obtain the worker's operation behavior information and operation position information during the cable installation process.

[0035] Step S102: classify the target image using the target classification model to obtain installation step information corresponding to the target image.

[0036] Optionally, the target image is classified by a YOLOv8 model or other models (ie, a target classification model) to obtain installation step information of the cable in the target image.

[0037] It should be noted that the installation steps include but are not limited to: pretreatment, inserting the cold shrink joint body, crimping the intermediate connecting tube, shrinking the cold shrink joint body, installing the copper shielding mesh and the inner wire, internal shaping, connecting the external ground wire, installing the armor belt and restoring the outer sheath, etc.

[0038] Step S103, performing risk detection on the installation process of the target cable according to the target operation information and the installation step information to obtain a target detection result.

[0039] Optionally, the target operation information and installation step information corresponding to the target cable are detected according to preset target detection conditions to see if there are risks, such as improper operation, wrong position, missing steps, etc. According to the target detection results, corresponding processing measures are taken, such as alarms, reminders, corrective operations, etc., to ensure the safety and accuracy of the target cable during installation.

[0040] In summary, the target image of the target object during the installation of the target cable is detected by the target detection model, and the target operation information such as the operation behavior information and operation position information of the target object during the installation of the target cable is obtained. Then the target classification model is used to classify the target image, and the installation step information of the target cable corresponding to the target image is obtained. Finally, the installation process of the target cable is risk detected based on the target operation information and installation step information, and the target detection result is obtained. The target detection model and the target classification model realize the automatic detection and automatic classification of the target image, which reduces the labor cost and time consumption, and also improves the precision and accuracy of the target operation information and installation step information, and reduces the risk of false detection and missed detection. By real-time detection of the target operation information and installation step information, problems can be discovered and feedback can be given in time, which gets rid of the dependence on manual labor and improves the management ability of the target cable during the installation process.

[0041] Optionally, in the cable installation risk detection method provided in the embodiment of the present application, a target image of a target object when installing a target cable is detected by a target detection model, and target operation information is obtained, including: performing image segmentation on the target image to obtain multiple target sub-images after segmentation; performing image filtering on the multiple target sub-images to obtain target operation sub-images; performing feature extraction on the target operation sub-images to obtain hand feature information of the target object; and obtaining target operation information based on the hand feature information.

[0042] In an optional embodiment, the target image is segmented, and different objects or regions in the image are identified and segmented to obtain multiple target sub-images. Then, various image processing techniques are used to filter each segmented target sub-image, including but not limited to filtering, edge detection, color analysis, etc., to filter out the target operation sub-image about the hand shape of the target object when operating the target cable. Then, the target sub-image is feature extracted by the ResNet50 model or other models, and the coordinate information of 21 key points of the target object's hand (i.e., hand feature information) is output. The key points include the joints and fingertip positions of the fingers, which can describe the hand posture and movement in detail. Finally, the target operation information of the target object is identified based on the coordinates of the 21 key points.

[0043] It should be noted that the 21 key points of the hand include: wrist key points (the center point of the wrist is taken as a key point), thumb key points (the base, first joint, second joint and fingertips of the thumb are taken as four key points), index finger key points (the base, first joint, second joint and fingertips of the index finger are taken as four key points), middle finger key points (the base, first joint, second joint and fingertips of the middle finger are taken as four key points), ring finger key points (the base, first joint, second joint and fingertips of the ring finger are taken as four key points), and little finger key points (the base, first joint, second joint and fingertips of the little finger are taken as four key points).

[0044] It should be noted that after obtaining the target operation information of the target object, it is necessary to manually correct it, check the position of each key point, and make fine adjustments based on the actual situation to control the error within 3 to 5 pixels, so as to obtain more accurate data and prediction models.

[0045] By detecting the target image when the target object is installing the target cable through the target detection model, the target operation information can be obtained quickly and accurately.

[0046] Optionally, in the cable installation risk detection method provided in the embodiment of the present application, the target image is classified by a target classification model to obtain installation step information corresponding to the target image, including: performing image enhancement processing on the target image to obtain an enhanced target image; performing feature extraction on the enhanced target image to obtain initial feature information corresponding to the target cable; screening the initial feature information to obtain target feature information; and classifying the target image according to the target feature information to obtain installation step information.

[0047] In an optional embodiment, the target image is subjected to online data enhancement, including but not limited to: adjusting the image size, upper and lower mirroring, left and right mirroring, etc., to obtain an enhanced target image. The enhanced target image is subjected to feature extraction through a YOLOv8 model or other models to obtain a plurality of initial feature information, and the importance of each initial feature information is evaluated, and feature information with a higher importance score is selected as the target feature information. Image classification is performed based on the target feature information to obtain installation step information, and the installation steps include but are not limited to: pretreatment, inserting the cold shrink joint body, crimping the intermediate connecting tube, shrinking the cold shrink joint body, installing the copper shielding net and the inner wire, internal shaping, connecting the outer ground wire, installing the armor belt and restoring the outer sheath, etc.

[0048] It should be noted that pretreatment: the operator begins to strip the outer insulation of the cable and retain a certain amount of steel armor, which is tied and fixed with copper wire, and the rest is stripped; a certain amount of inner sheath is retained from the steel armor break, and the remaining inner sheath and filler are stripped; from the top of the core wire downward, according to the different specifications of the cable, use PVC tape to mark and strip the corresponding length of copper shielding; from the top of the core wire downward, measure the outer semi-conductive layer, mark and strip the measured semi-conductive layer with PVC tape according to the cable specifications, and wrap several layers of tape on the insulation layer to protect the insulation layer; after sanding the groove smooth with sandpaper, remove the PVC tape; from the end of each phase core wire downward, remove half the length of the insulation layer of the middle connecting tube to expose the wire; chamfer the insulation layer at the break and sand it smooth with sandpaper; wipe the insulation layer and copper wire of each phase with cable cleaning paper, and the other end of the cable is stripped according to the same size. Insert the cold shrink joint body: insert the cold shrink joint body into each phase at the long end of the cable stripping, and insert the copper shielding net into each phase at the short end. Crimping the intermediate connecting pipe: Use crimping pliers to crimp the intermediate connecting pipes of each phase as required, and polish the connecting pipes to make them smooth and clean. Take a certain distance inward from the outer semi-conductor break at both ends, and wrap it with PVC tape to mark it as the shrink positioning point. Shrinking the main body of the cold shrink joint: Clean the surface of the insulation layer and evenly apply silicone grease, align the cold shrink joint with the shrink positioning point, and pull out the support bar to allow the joint to shrink naturally. Install the copper shielding mesh and inner wire: Pull the copper shielding mesh sleeve open and put it on the outside of the main body of each phase joint. Polish the copper shielding layer with sandpaper, insert the ground wire into the bifurcation of the three-core cable, wrap the three-phase copper shielding layer for one week and then lead it out. Use a constant force spring to tie the ground wire and the copper shielding mesh sleeve to the copper shielding layer of the three-core cable. Pull the other end of the ground wire to the short end and tie it in the same way. Finally, wrap two layers of PVC tape on the constant force spring. Internal shaping: Backfill the filler, fill the concave part, and make the joint neat. Wrap it with transparent PVC tape to tighten it. Wrap two layers of waterproof tape between the inner sheaths of the two cables, half overlapping, and stretch until they turn pale white. Connect the external ground wire: Use a saw blade and sandpaper to polish the steel armor and remove the anti-rust paint. Use a constant force spring to fix the ground wire to one end of the steel armor, and wrap it around the waterproof tape to fix it on the other end of the steel armor. Wrap two layers of PVC tape on the constant force spring. Then overlap the outer sheaths of the cables at both ends and wrap them with two layers of waterproof glue. Install the armor belt and restore the outer sheath: Wear latex gloves and open the outer packaging of the armor belt. Start from one end and wrap the armor belt half overlapping to the other end, and then wrap it back until it is used up.

[0049] It should be noted that after obtaining the installation step information corresponding to the target cable, it is necessary to manually correct it, check whether each step is correct, and make fine adjustments based on the actual situation, so as to obtain more accurate data and classification models.

[0050] By classifying the target image through the target classification model, the installation step information corresponding to the target image can be obtained quickly and accurately.

[0051] Optionally, in the cable installation risk detection method provided in the embodiment of the present application, a risk detection is performed on the installation process of the target cable based on the target operation information and the installation step information, and the target detection result is obtained, including: judging whether the target operation information and the installation step information meet the target detection conditions, and obtaining a judgment result; if the judgment result indicates that the target operation information and the installation step information meet the target detection conditions, then determining that the target detection result is that there is no risk in the cable installation; if the judgment result indicates that the target operation information and the installation step information do not meet the target detection conditions, then determining that the target detection result is that there is a risk in the cable installation.

[0052] The target operation information and installation step information are detected and analyzed based on the predefined target detection conditions through the pre-established model or algorithm. It is determined whether the target operation information and installation step information meet the target detection conditions: if they meet the target detection conditions, it is determined that there is no risk in the installation process of the target cable; if they do not meet the target detection conditions, it is determined that there is a risk in the installation process of the target cable.

[0053] Through the above steps, it is possible to effectively determine whether the target operation information and installation step information meet the target detection conditions, and then take corresponding measures to handle them.

[0054] Optionally, in the cable installation risk detection method provided in the embodiment of the present application, after determining whether the target operation information and installation step information meet the target detection conditions and obtaining the judgment result, the method also includes: when the target detection result is that there is no risk in the cable installation, compiling and packaging the target operation information, installation step information and target detection result to obtain an installation record file corresponding to the target cable; uploading the installation record file to the target server, wherein the target server is used to store installation records and detection records of multiple cables; when the target detection result is that there is a risk in the cable installation, determining the target record file corresponding to the target operation information and installation step information in the target server; and optimizing the installation process of the target cable based on the target record file.

[0055] In an optional embodiment, when there is no risk in the installation process of the target cable: compile and package the target operation information, installation step information and target detection results to generate an installation record file. Ensure that the file contains sufficient information to record the installation process of the cable. And upload the generated installation record file to the target server. When there is a risk in the installation process of the target cable: find the target record file corresponding to the target operation information and installation step information in the target server, and analyze the risk points and problems in the cable installation process based on the information provided by the target record file to optimize the cable installation process.

[0056] It should be noted that the installation record file is uploaded to the target server through the communication module (including: Bluetooth and WIFI).

[0057] Through the above process, the cable installation process can be effectively recorded and managed, potential risks can be discovered and resolved in a timely manner, and the efficiency and reliability of the installation process can be improved. At the same time, through the storage and analysis of record files, valuable experience and reference can be provided for future installation processes.

[0058] Optionally, in the cable installation risk detection method provided in the embodiment of the present application, before detecting the target image when the target object installs the target cable through the target detection model to obtain the target operation information, the method also includes: acquiring the initial image when the target object installs the target cable; cleaning the initial image to obtain the cleaned initial image; cropping the cleaned initial image to obtain the cropped initial image; adjusting the contrast of the cropped initial image to obtain the target image.

[0059] In an optional embodiment, an initial image of the target object during the installation of the target cable is collected by AR glasses, and the image is cleaned to remove noise and irrelevant information in the image data to obtain a cleaned initial image. The cleaned initial image is then cropped according to a specified cropping position and cropping size to highlight key areas to obtain a cropped initial image. Finally, the image is adjusted using a contrast adjustment tool to adjust parameters such as brightness, contrast, and exposure, or by applying algorithms such as histogram equalization to adjust the contrast, so as to enhance the clarity and visual effect of the image.

[0060] By performing preprocessing operations such as cleaning, cropping, and contrast adjustment on the initial image, we can ensure that the image data input to the model is of high quality and representativeness, thereby improving the overall performance of the system.

[0061] Optionally, in the cable installation risk detection method provided in the embodiment of the present application, the initial image is cleaned to obtain the cleaned initial image, which includes: performing damage detection on the initial image to perform data cleaning on damaged data in the initial image to obtain a first initial image; performing Laplace transform on the first initial image to perform data cleaning on fuzzy data in the first initial image to obtain a second initial image; performing similarity calculation on the second initial image to perform data cleaning on similar data in the second initial image to obtain a cleaned initial image.

[0062] In an optional embodiment, Figure 2 Schematic diagram of cleaning the initial image according to an embodiment of the present application. Figure 2As shown, the number of damaged images in the initial image is detected and counted by an algorithm or function library. When an abnormal error occurs during the process of opening the initial image, it means that the image is damaged. All detected damaged images are removed from the image data set to ensure that the image files in the data set are available, and the first initial image is obtained. Then, Laplace transform is performed on each first initial image, and the edges in the image are detected by calculating the second-order derivative of the image. The larger the calculation result, the more edges and details there are in the image, and the clearer the image is; the smaller the calculation result, the blurrier the image is. Images with calculation results less than the threshold are removed from the image data set to ensure that the image data set is clear, and the second initial image is obtained. Finally, the similarity between the feature vectors in the second initial image is calculated by measurement methods such as cosine similarity, Euclidean distance, and Hamming distance, and images with similarity lower than the threshold are removed from the data set to obtain the cleaned initial image.

[0063] By performing damage detection, Laplace transform and similarity calculation on the initial image, the images that do not meet the requirements can be filtered and cleaned quickly and accurately, thereby improving the quality of the image.

[0064] It should be noted that Figure 3 is a schematic diagram of a method for detecting cable installation risks provided in an embodiment of the present application. Figure 3 As shown, the initial image of the target object during the installation of the target cable is collected by AR glasses, and the initial image is cleaned, cropped, and contrast adjusted to obtain the target image.

[0065] Then, the target image is segmented, filtered and feature extracted to obtain the hand feature information of the target object when operating the target cable. The target detection model is used to detect the hand feature information to obtain the target operation information such as the target object's operation behavior information and operation position information on the target cable. At the same time, the target image is enhanced, feature extracted and feature screened to obtain the most important target feature information corresponding to the target cable. The target classification model is used to classify the installation step of the target cable based on the target feature information to obtain the installation step information.

[0066] Finally, determine whether the target operation information and installation step information meet the target detection conditions. If they meet the target detection conditions, it means that there is no risk in the installation process of the target cable; if they do not meet the target detection conditions, it means that there is a risk in the installation process of the target cable, and obtain the target record file corresponding to the target operation information and installation step information in the target server, and optimize the installation process of the target cable according to the target record file.

[0067] The cable installation risk detection method provided by the embodiment of the present application detects the target image when the target object installs the target cable through the target detection model to obtain the target operation information, wherein the target operation information at least includes: the target object's operation behavior information and operation position information on the target cable; the target image is classified by the target classification model to obtain the installation step information corresponding to the target image; the installation process of the target cable is risk detected according to the target operation information and the installation step information to obtain the target detection result, which solves the problem that the installation process of the cable is detected manually in the related art to determine whether there is a risk in the cable installation, resulting in a relatively low efficiency in the risk detection of cable installation. In summary, in this scheme, the target image of the target object in the process of installing the target cable is detected by the target detection model to obtain the target operation information such as the operation behavior information and the operation position information of the target object in the installation process of the target cable. Then the target classification model is used to classify the target image to obtain the installation step information of the target cable corresponding to the target image. Finally, the installation process of the target cable is risk detected based on the target operation information and the installation step information to obtain the target detection result. The target detection model and target classification model realize automatic detection and automatic classification of target images, which reduces labor costs and time consumption, improves the precision and accuracy of target operation information and installation step information, and reduces the risk of false detection and missed detection. Through real-time detection of target operation information and installation step information, problems can be discovered and feedback can be provided in a timely manner, eliminating the reliance on manual labor and improving the management capabilities of target cables during installation.

[0068] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0069] The present application also provides a device for detecting cable installation risks. It should be noted that the device for detecting cable installation risks in the present application can be used to execute the method for detecting cable installation risks provided in the present application. The following is an introduction to the device for detecting cable installation risks provided in the present application.

[0070] Figure 4 Schematic diagram of a cable installation risk detection device according to an embodiment of the present application. Figure 4 As shown, the device includes: a first detection unit 401, a classification unit 402, and a second detection unit 403.

[0071] The first detection unit 401 is used to detect the target image when the target object installs the target cable through the target detection model to obtain target operation information, wherein the target operation information at least includes: operation behavior information and operation position information of the target object on the target cable;

[0072] A classification unit 402 is used to classify the target image through a target classification model to obtain installation step information corresponding to the target image;

[0073] The second detection unit 403 is used to perform risk detection on the installation process of the target cable according to the target operation information and the installation step information to obtain a target detection result.

[0074] The cable installation risk detection device provided by the embodiment of the present application comprises a first detection unit 401 that detects the target image when the target object installs the target cable through the target detection model to obtain the target operation information, wherein the target operation information at least includes: the target object's operation behavior information and operation position information on the target cable; the classification unit 402 classifies the target image through the target classification model to obtain the installation step information corresponding to the target image; the second detection unit 403 performs risk detection on the installation process of the target cable according to the target operation information and the installation step information to obtain the target detection result, which solves the problem that the installation process of the cable is detected manually in the related art to determine whether there is a risk in the cable installation, resulting in a relatively low efficiency in the risk detection of the cable installation. In this scheme, the target image of the target object in the process of installing the target cable is detected through the target detection model to obtain the target operation information such as the operation behavior information and the operation position information of the target object in the process of installing the target cable. Then the target classification model is used to classify the target image to obtain the installation step information of the target cable corresponding to the target image. Finally, the installation process of the target cable is risk detected based on the target operation information and the installation step information to obtain the target detection result. The target detection model and target classification model realize automatic detection and automatic classification of target images, which reduces labor costs and time consumption, improves the precision and accuracy of target operation information and installation step information, and reduces the risk of false detection and missed detection. Through real-time detection of target operation information and installation step information, problems can be discovered and feedback can be provided in a timely manner, eliminating the reliance on manual labor and improving the management capabilities of target cables during installation.

[0075] Optionally, in the cable installation risk detection device provided in the embodiment of the present application, the first detection unit includes: a segmentation module, used to perform image segmentation on the target image to obtain multiple target sub-images after segmentation; a filtering module, used to perform image filtering on the multiple target sub-images to obtain a target operation sub-image; a first extraction module, used to perform feature extraction on the target operation sub-image to obtain hand feature information of the target object; and a first determination module, used to obtain target operation information based on the hand feature information.

[0076] Optionally, in the cable installation risk detection device provided in the embodiment of the present application, the classification unit includes: an enhancement module, used to perform image enhancement processing on the target image to obtain an enhanced target image; a second extraction module, used to perform feature extraction on the enhanced target image to obtain initial feature information corresponding to the target cable; a screening module, used to screen the initial feature information to obtain target feature information; and a classification module, used to classify the target image according to the target feature information to obtain installation step information.

[0077] Optionally, in the cable installation risk detection device provided in the embodiment of the present application, the second detection unit includes: a judgment module, used to judge whether the target operation information and installation step information meet the target detection conditions to obtain a judgment result; a second determination module, used to determine that the target detection result is that there is no risk in the cable installation if the judgment result indicates that the target operation information and installation step information meet the target detection conditions; and a third determination module, used to determine that the target detection result is that there is a risk in the cable installation if the judgment result indicates that the target operation information and installation step information do not meet the target detection conditions.

[0078] Optionally, in the cable installation risk detection device provided in the embodiment of the present application, the device also includes: a compilation unit, which is used to judge whether the target operation information and installation step information meet the target detection conditions, and after obtaining the judgment result, when the target detection result is that there is no risk in the cable installation, compile and package the target operation information, installation step information and target detection result to obtain an installation record file corresponding to the target cable; a transmission unit, which is used to upload the installation record file to a target server, wherein the target server is used to store installation records and detection records of multiple cables; a determination unit, which is used to determine the target record file corresponding to the target operation information and installation step information in the target server when the target detection result is that there is a risk in the cable installation; an optimization unit, which is used to optimize the installation process of the target cable based on the target record file.

[0079] Optionally, in the cable installation risk detection device provided in the embodiment of the present application, the device also includes: an acquisition unit, used to detect the target image when the target object installs the target cable through the target detection model, and before obtaining the target operation information, acquire the initial image when the target object installs the target cable; a cleaning unit, used to clean the initial image to obtain the cleaned initial image; a cropping unit, used to crop the cleaned initial image to obtain the cropped initial image; and an adjustment unit, used to adjust the contrast of the cropped initial image to obtain the target image.

[0080] Optionally, in the cable installation risk detection device provided in the embodiment of the present application, the cleaning unit includes: a detection module, used to perform damage detection on the initial image to perform data cleaning on the damaged data in the initial image to obtain a first initial image; a transformation module, used to perform Laplace transform on the first initial image to perform data cleaning on the blurred data in the first initial image to obtain a second initial image; and a calculation module, used to perform similarity calculation on the second initial image to perform data cleaning on the similar data in the second initial image to obtain a cleaned initial image.

[0081] The cable installation risk detection device includes a processor and a memory. The above-mentioned first detection unit 401, classification unit 402, second detection unit 403, etc. are all stored in the memory as program units, and the processor executes the above-mentioned program units stored in the memory to realize accurate detection of cable installation risks.

[0082] The processor includes a kernel, which calls the corresponding program unit from the memory. One or more kernels can be set, and the accurate detection of cable installation risks can be achieved by adjusting kernel parameters.

[0083] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0084] An embodiment of the present invention provides a computer-readable storage medium on which a program is stored. When the program is executed by a processor, a method for detecting cable installation risks is implemented.

[0085] An embodiment of the present invention provides a processor, which is used to run a program, wherein the method for detecting cable installation risks is executed when the program is running.

[0086] like Figure 5As shown, an embodiment of the present invention provides an electronic device, the device includes a processor, a memory, and a program stored in the memory and executable on the processor, and the processor implements the following steps when executing the program: detecting a target image when a target object installs a target cable through a target detection model to obtain target operation information, wherein the target operation information at least includes: operation behavior information and operation position information of the target object on the target cable; classifying the target image through a target classification model to obtain installation step information corresponding to the target image; performing risk detection on the installation process of the target cable based on the target operation information and the installation step information to obtain a target detection result.

[0087] Optionally, the target image when the target object is installing the target cable is detected by a target detection model to obtain target operation information including: performing image segmentation on the target image to obtain multiple target sub-images after segmentation; performing image filtering on the multiple target sub-images to obtain target operation sub-images; performing feature extraction on the target operation sub-images to obtain hand feature information of the target object; and obtaining target operation information based on the hand feature information.

[0088] Optionally, classifying the target image through a target classification model to obtain installation step information corresponding to the target image includes: performing image enhancement processing on the target image to obtain an enhanced target image; performing feature extraction on the enhanced target image to obtain initial feature information corresponding to the target cable; screening the initial feature information to obtain target feature information; and classifying the target image according to the target feature information to obtain installation step information.

[0089] Optionally, a risk detection is performed on the installation process of the target cable based on the target operation information and the installation step information, and the target detection result obtained includes: judging whether the target operation information and the installation step information meet the target detection conditions, and obtaining a judgment result; if the judgment result indicates that the target operation information and the installation step information meet the target detection conditions, then determining that the target detection result is that there is no risk in the cable installation; if the judgment result indicates that the target operation information and the installation step information do not meet the target detection conditions, then determining that the target detection result is that there is a risk in the cable installation.

[0090] Optionally, after determining whether the target operation information and installation step information meet the target detection conditions and obtaining the determination result, the method further includes: when the target detection result is that there is no risk in the cable installation, compiling and packaging the target operation information, installation step information and target detection result to obtain an installation record file corresponding to the target cable; uploading the installation record file to a target server, wherein the target server is used to store installation records and detection records of multiple cables; when the target detection result is that there is a risk in the cable installation, determining, in the target server, a target record file corresponding to the target operation information and installation step information; and optimizing the installation process of the target cable based on the target record file.

[0091] Optionally, before detecting the target image when the target object is installing the target cable through the target detection model to obtain the target operation information, the method also includes: acquiring an initial image when the target object is installing the target cable; cleaning the initial image to obtain a cleaned initial image; cropping the cleaned initial image to obtain a cropped initial image; and adjusting the contrast of the cropped initial image to obtain the target image.

[0092] Optionally, the initial image is cleaned to obtain a cleaned initial image, including: performing damage detection on the initial image to clean damaged data in the initial image to obtain a first initial image; performing Laplace transform on the first initial image to clean blurred data in the first initial image to obtain a second initial image; performing similarity calculation on the second initial image to clean similar data in the second initial image to obtain a cleaned initial image.

[0093] The devices in this article can be servers, PCs, PADs, mobile phones, etc.

[0094] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing a program that initializes the following method steps: detecting a target image when a target object installs a target cable through a target detection model to obtain target operation information, wherein the target operation information at least includes: operation behavior information and operation position information of the target object on the target cable; classifying the target image through a target classification model to obtain installation step information corresponding to the target image; performing risk detection on the installation process of the target cable based on the target operation information and the installation step information to obtain a target detection result.

[0095] Optionally, the target image when the target object is installing the target cable is detected by a target detection model to obtain target operation information including: performing image segmentation on the target image to obtain multiple target sub-images after segmentation; performing image filtering on the multiple target sub-images to obtain target operation sub-images; performing feature extraction on the target operation sub-images to obtain hand feature information of the target object; and obtaining target operation information based on the hand feature information.

[0096] Optionally, classifying the target image through a target classification model to obtain installation step information corresponding to the target image includes: performing image enhancement processing on the target image to obtain an enhanced target image; performing feature extraction on the enhanced target image to obtain initial feature information corresponding to the target cable; screening the initial feature information to obtain target feature information; and classifying the target image according to the target feature information to obtain installation step information.

[0097] Optionally, a risk detection is performed on the installation process of the target cable based on the target operation information and the installation step information, and the target detection result obtained includes: judging whether the target operation information and the installation step information meet the target detection conditions, and obtaining a judgment result; if the judgment result indicates that the target operation information and the installation step information meet the target detection conditions, then determining that the target detection result is that there is no risk in the cable installation; if the judgment result indicates that the target operation information and the installation step information do not meet the target detection conditions, then determining that the target detection result is that there is a risk in the cable installation.

[0098] Optionally, after determining whether the target operation information and installation step information meet the target detection conditions and obtaining the determination result, the method further includes: when the target detection result is that there is no risk in the cable installation, compiling and packaging the target operation information, installation step information and target detection result to obtain an installation record file corresponding to the target cable; uploading the installation record file to a target server, wherein the target server is used to store installation records and detection records of multiple cables; when the target detection result is that there is a risk in the cable installation, determining, in the target server, a target record file corresponding to the target operation information and installation step information; and optimizing the installation process of the target cable based on the target record file.

[0099] Optionally, before detecting the target image when the target object is installing the target cable through the target detection model to obtain the target operation information, the method also includes: acquiring an initial image when the target object is installing the target cable; cleaning the initial image to obtain a cleaned initial image; cropping the cleaned initial image to obtain a cropped initial image; and adjusting the contrast of the cropped initial image to obtain the target image.

[0100] Optionally, the initial image is cleaned to obtain a cleaned initial image, including: performing damage detection on the initial image to clean damaged data in the initial image to obtain a first initial image; performing Laplace transform on the first initial image to clean blurred data in the first initial image to obtain a second initial image; performing similarity calculation on the second initial image to clean similar data in the second initial image to obtain a cleaned initial image.

[0101] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0102] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0103] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0104] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0105] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0106] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0107] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0108] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0109] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0110] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A method for detecting cable installation risks, characterized in that: include: Detecting a target image when a target object is installing a target cable through a target detection model to obtain target operation information, wherein the target operation information at least includes: operation behavior information and operation position information of the target object on the target cable; Classify the target image by using a target classification model to obtain installation step information corresponding to the target image; A risk detection is performed on the installation process of the target cable according to the target operation information and the installation step information to obtain a target detection result.

2. The method according to claim 1, characterized in that The target detection model is used to detect the target image when the target object is installing the target cable, and the target operation information obtained includes: Performing image segmentation on the target image to obtain a plurality of target sub-images after segmentation; Performing image filtering on the multiple target sub-images to obtain a target operation sub-image; Performing feature extraction on the target operation sub-image to obtain hand feature information of the target object; The target operation information is obtained according to the hand feature information.

3. The method according to claim 1, characterized in that Classifying the target image by a target classification model to obtain installation step information corresponding to the target image includes: Performing image enhancement processing on the target image to obtain an enhanced target image; Performing feature extraction on the enhanced target image to obtain initial feature information corresponding to the target cable; Screening the initial feature information to obtain target feature information; The target image is classified according to the target feature information to obtain the installation step information.

4. The method according to claim 1, characterized in that: Performing risk detection on the installation process of the target cable according to the target operation information and the installation step information, and obtaining the target detection result includes: Determine whether the target operation information and the installation step information meet the target detection condition, and obtain a determination result; If the judgment result indicates that the target operation information and the installation step information meet the target detection condition, then determining that the target detection result is that there is no risk in the cable installation; If the judgment result indicates that the target operation information and the installation step information do not meet the target detection condition, then it is determined that the target detection result is that there is a risk in the cable installation.

5. The method according to claim 4, characterized in that After determining whether the target operation information and the installation step information meet the target detection condition and obtaining the determination result, the method further includes: When the target detection result indicates that there is no risk in cable installation, compile and package the target operation information, the installation step information and the target detection result to obtain an installation record file corresponding to the target cable; Uploading the installation record file to a target server, wherein the target server is used to store installation records and detection records of multiple cables; In the case where the target detection result is that there is a risk in the cable installation, determining, in the target server, a target record file corresponding to the target operation information and the installation step information; The installation process of the target cable is optimized according to the target record file.

6. The method according to claim 1, characterized in that Before detecting the target image when the target object is installing the target cable by the target detection model to obtain the target operation information, the method further includes: Acquiring an initial image of the target object when the target cable is installed; Cleaning the initial image to obtain a cleaned initial image; Cropping the cleaned initial image to obtain a cropped initial image; The contrast of the cropped initial image is adjusted to obtain the target image.

7. The method according to claim 6, characterized in that Cleaning the initial image to obtain the cleaned initial image includes: Performing damage detection on the initial image to clean damaged data in the initial image to obtain a first initial image; Performing Laplace transform on the first initial image to clean the blurred data in the first initial image to obtain a second initial image; A similarity calculation is performed on the second initial image to clean similar data in the second initial image to obtain the cleaned initial image.

8. A cable installation risk detection device, characterized in that: include: A first detection unit is used to detect a target image when a target object installs a target cable through a target detection model to obtain target operation information, wherein the target operation information at least includes: operation behavior information and operation position information of the target object on the target cable; A classification unit, used to classify the target image through a target classification model to obtain installation step information corresponding to the target image; The second detection unit is used to perform risk detection on the installation process of the target cable according to the target operation information and the installation step information to obtain a target detection result.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein when the program is executed, the storage medium is controlled to execute the cable installation risk detection method according to any one of claims 1 to 7 on a device.

10. An electronic device, characterized in that: It includes one or more processors and a memory, wherein the memory is used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the cable installation risk detection method described in any one of claims 1 to 7.

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