Cable crack identification device, method and equipment and readable storage medium

Abstract

The invention relates to the technical field of cable identification, and provides a cable crack identification device, method and equipment and a readable storage medium, and the cable crack identification device comprises a camera which is used for collecting a cable image; the sonic sensor is used for judging whether the cable has cracks and determining cable crack positions; the magnetic flux leakage sensor is used for judging the cable crack condition according to magnetic field change information when the cable cracks; the crack sensor is used for detecting crack change information on the surface of the cable; the image processor is used for receiving the cable image and processing the cable image; and the main controller is used for outputting a crack identification result according to the processed cable image, the cable crack position, the cable crack condition and the crack change information. According to the invention, manual intervention can be reduced, the position of the cable crack can be automatically and accurately identified, rapid and accurate identification of the cable crack is realized, powerful support is provided for safety maintenance of the cable, and the accuracy of crack detection is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of cable identification, and in particular to a cable crack identification device, method, equipment and readable storage medium. Background Art

[0002] As a key component of power transmission and communication systems, the safety and reliability of cables are crucial to the operation of the system. However, during long-term use, cables may develop cracks due to environmental factors, mechanical stress and other factors. Traditional cable crack detection methods mostly rely on manual inspections, which have the disadvantages of low efficiency, poor accuracy, and difficulty in detecting tiny cracks. It is unable to comprehensively and efficiently identify cracks in the cable insulation, thus affecting the insulation performance and service life of the cable, and easily causing safety accidents such as short circuits and leakage.

[0003] In order to improve the efficiency and accuracy of cable crack identification and reduce manual intervention, it is necessary to use machine vision, image processing, artificial intelligence and other technologies to develop a device that can automatically and accurately identify cable cracks, so as to achieve rapid and accurate identification of cable cracks and provide strong support for the safe maintenance of cables. Summary of the invention

[0004] Based on this, in order to solve the problem that the traditional cable crack detection method cannot comprehensively and efficiently identify the crack situation of the cable insulation skin, the present invention provides a cable crack identification device, method, equipment and readable storage medium, and its specific technical solution is as follows:

[0005] A cable crack identification device, comprising:

[0006] A camera for collecting images of cables;

[0007] Acoustic wave sensor, used to determine whether there are cracks in the cable and determine the location of the cable cracks;

[0008] Magnetic leakage sensor, used to determine the cable crack condition based on the magnetic field change information when the cable cracks;

[0009] Crack sensor, used to detect crack change information on the cable surface;

[0010] An image processor, used for receiving and processing the cable image;

[0011] The main controller is electrically connected to the camera, the acoustic wave sensor, the magnetic flux leakage sensor, the crack sensor and the image processor, and is used to receive the processed cable image, the cable crack position, the cable crack condition and the crack change information, and output the crack recognition result according to the processed cable image, the cable crack position, the cable crack condition and the crack change information.

[0012] The cable crack identification device carries out the cable crack identification task through the coordinated cooperation of a camera, an acoustic wave sensor, a magnetic leakage sensor, a crack sensor and an image processor, and outputs the crack identification result according to the processed cable image, the cable crack position, the cable crack condition and the crack change information, which can reduce manual intervention, automatically and accurately identify the position of the cable crack, realize the rapid and accurate identification of the cable crack, provide strong support for the safe maintenance of the cable, and improve the accuracy of crack detection.

[0013] Preferably, the cable crack identification device further comprises:

[0014] Bracket;

[0015] The multi-position adjustment mechanism comprises a mechanical shaft installed on a bracket, a mechanical arm installed on the mechanical shaft, and a gripper installed at the end of the mechanical arm for grabbing cables, and is used for grabbing and adjusting the position of the cables.

[0016] Preferably, the camera, the acoustic wave sensor, the magnetic flux leakage sensor, the crack sensor, the image processor and the main controller are all mounted on the bracket.

[0017] Preferably, the cable crack identification device further comprises:

[0018] A traction guide rail, mounted on the bracket;

[0019] The mobile motor is installed on the bracket to drive the traction guide rail to move the cable crack identification device along the length of the cable.

[0020] The mobile locator is mounted on a bracket and is used to locate the cable crack identification device.

[0021] Preferably, the image processor comprises:

[0022] An image receiver, used for receiving the collected cable image;

[0023] A signal amplifier, used to amplify the cable image;

[0024] A filter, used for filtering the amplified cable image;

[0025] The analog-to-digital converter is used for performing analog-to-digital conversion on the cable image after filtering.

[0026] A cable crack identification method, applied to the cable crack identification device, comprises the following steps:

[0027] Collect cable images;

[0028] Determine whether there are cracks in the cable and determine the location of the cable cracks;

[0029] Determine the cable crack condition based on the magnetic field change information when the cable cracks;

[0030] Detect crack change information on the cable surface;

[0031] Processing cable images;

[0032] The crack identification result is output based on the processed cable image, cable crack location, cable crack condition and crack change information.

[0033] Preferably, the cable crack identification method further comprises the following steps:

[0034] The position of the cable is adjusted by a multi-position adjustment mechanism to capture potential crack data information related to potential cracks on the cable surface from multiple dimensions;

[0035] The multi-position adjustment mechanism includes a mechanical shaft installed on a bracket, a mechanical arm installed on the mechanical shaft, and a gripper installed at the end of the mechanical arm for grabbing the cable, which is used to grab and adjust the position of the cable.

[0036] Preferably, the specific method for processing the cable image comprises the following steps:

[0037] Enlarge the cable image;

[0038] Performing filtering on the amplified cable image;

[0039] Perform analog-to-digital conversion on the filtered cable image.

[0040] A cable crack identification device, comprising:

[0041] Controller;

[0042] A memory storing executable instructions;

[0043] The executable instructions may be run on the controller and implement the cable crack identification method.

[0044] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the cable crack identification method is implemented. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The present invention can be further understood from the following description in conjunction with the accompanying drawings. The components in the figures are not necessarily drawn to scale, but the emphasis is placed on illustrating the principles of the embodiments. In different views, the same reference numerals designate corresponding parts.

[0046] Figure 1It is a schematic diagram of the overall structure of a cable crack identification device in one embodiment of the present invention;

[0047] Figure 2 It is a schematic diagram of the overall process of a cable crack identification method in one embodiment of the present invention;

[0048] Figure 3 It is a schematic diagram of a process for processing a cable image in one embodiment of the present invention.

[0049] Description of reference numerals:

[0050] 1. Image processor; 2. Light source; 3. Guide rail; 4. Mobile motor; 5. Charging and discharging battery; 6. Bluetooth chip; 7. Main controller; 8. Magnetic leakage sensor; 9. Crack sensor; 10. Safety protection device; 11. Mechanical axis; 12. Mechanical arm; 13. Multi-position adjustment mechanism; 14. Display screen; 15. Alarm; 16. Camera; 17. Cable working area; 18. Acoustic wave sensor; 19. Mobile locator; 20. Bracket. DETAILED DESCRIPTION

[0051] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with its embodiments. It should be understood that the specific implementation methods described herein are only used to explain the present invention and do not limit the protection scope of the present invention.

[0052] It should be noted that when an element is referred to as being "fixed to" another element, it may be directly on the other element or there may be a central element. When an element is considered to be "connected to" another element, it may be directly connected to the other element or there may be a central element at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only and do not represent the only implementation method.

[0053] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items.

[0054] The “first” and “second” mentioned in the present invention do not represent specific quantities and orders, but are merely used to distinguish names.

[0055] Embodiment 1:

[0056] Since cable cracks are often subtle and diverse in shape, traditional detection methods rely on manual inspections, which make it difficult to accurately capture these subtle changes, resulting in a high rate of missed detection or false detection, insufficient crack detection accuracy, and reduced detection accuracy.

[0057] To solve the above problems, Figure 1 As shown, a cable crack identification device includes a camera 16, an acoustic wave sensor 18, a magnetic flux leakage sensor 8, a crack sensor 9, an image processor 1 and a main controller 7.

[0058] The camera 16 is used to collect cable images; the camera 16 is a high-definition intelligent camera 16, which can realize rapid continuous shooting of cable images to adapt to the image collection of mobile cables.

[0059] The acoustic wave sensor 18 is used to determine whether there is a crack in the cable and to locate the crack in the cable. When ultrasonic waves propagate in the cable, they will produce reflection, refraction, and scattering when encountering cracks. The acoustic wave sensor 18 further determines whether there is a crack in the cable and locates the crack address based on the ultrasonic waves reflected back.

[0060] The magnetic flux leakage sensor 8 is used to determine the cable crack condition according to the magnetic field change information when the cable cracks. The magnetic flux leakage sensor 8 uses the phenomenon of magnetic field leakage when the cable cracks to detect the change of the magnetic field and further determine the cable crack condition.

[0061] The crack sensor 9 is used to detect crack change information on the cable surface. The crack sensor 9 can detect crack changes on the cable surface, has sufficient resolution and sensitivity, and can clearly capture fine cracks on the cable surface.

[0062] The image processor 1 is used for receiving the cable image and processing the cable image.

[0063] Preferably, the image processor 1 includes an image receiver, a signal amplifier, a filter and an analog-to-digital converter.

[0064] The image receiver is used to receive the collected cable image; the signal amplifier is used to amplify the cable image; the filter is used to filter the amplified cable image; and the analog-to-digital converter is used to perform analog-to-digital conversion on the filtered cable image.

[0065] Since the collected cable image signals are usually weak and contain certain noise and interference, it is necessary to use a signal amplifier to appropriately amplify the weak cable image signals, and then use a filter to remove the noise and interference in the cable image signals to make the cable image signals clearer. Finally, this series of analog signals are converted into digital signals through an analog converter for further processing and analysis.

[0066] The main controller 7 is electrically connected to the camera 16, the acoustic wave sensor 18, the magnetic leakage sensor 8, the crack sensor 9 and the image processor 1, and is used to receive the processed cable image, the cable crack position, the cable crack condition and the crack change information, and output the crack identification result according to the processed cable image, the cable crack position, the cable crack condition and the crack change information.

[0067] The main controller 7 is the core part of the entire cable crack identification device. It is mainly responsible for coordinating the workflow of the entire cable crack identification device, including the transmission, storage and analysis and processing of image data, as well as the output and feedback of crack identification results. It can also monitor and remotely control the entire detection process. It pre-processes the collected cable images by using edge detection, filtering and denoising algorithms to enhance crack characteristics, and uses deep learning algorithms to train and learn the pre-processed data, so that the trained cable crack identification model can accurately identify the crack characteristics on the cable surface, automatically identify the cracks on the cable surface according to the crack characteristics, and evaluate the severity of the cracks, thereby improving the accuracy of detection, reducing dependence on manual judgment, and reducing the influence of subjective factors.

[0068] The cable crack identification device carries out the cable crack identification task through the coordinated cooperation of the camera 16, the acoustic wave sensor 18, the leakage magnetic sensor 8, the crack sensor 9 and the image processor 1, and outputs the crack identification result according to the processed cable image, the cable crack position, the cable crack condition and the crack change information, which can reduce manual intervention, automatically and accurately identify the position of the cable crack, realize the rapid and accurate identification of the cable crack, provide strong support for the safe maintenance of the cable, and improve the accuracy of crack detection.

[0069] As a preferred technical solution, the cable crack identification device further includes a bracket 20 and a multi-position adjustment mechanism 13 .

[0070] The bracket 20 is mainly used to support and fix the various components of the cable crack identification device to ensure that they remain stable and accurate during the detection process and adapt to different cable trenches and working environments. Specifically, the camera 16, the acoustic wave sensor 18, the magnetic flux leakage sensor 8, the crack sensor 9, the image processor 1 and the main controller 7 are all installed on the bracket 20. The bracket 20 is provided with a cable working area 17.

[0071] The multi-position adjustment mechanism 13 includes a mechanical axis 11 installed on a bracket 20, a mechanical arm 12 installed on the mechanical axis 11, and a gripper for grabbing the cable installed at the end of the mechanical arm 12, which is used to grab and adjust the position of the cable to facilitate the camera 16, the acoustic wave sensor 18, the leakage magnetic sensor 8 and the crack sensor 9 to fully scan the cable surface when moving along the cable axis to avoid missing tiny cracks.

[0072] Typically, cables are laid underground. To facilitate the camera 16, acoustic wave sensor 18, magnetic flux leakage sensor 8 and crack sensor 9 to move along the axial direction or length direction of the cable to comprehensively scan the cable surface and avoid missing tiny cracks, a movable multi-position adjustment mechanism 13 is provided, and the automated mechanical axis 11 and the automated mechanical arm 12 cooperate to adjust the position angle of the cable to capture the temperature change, acoustic wave reflection, electromagnetic property change and cable surface image on the cable surface from multiple dimensions. The main controller 7 processes and analyzes the temperature change, acoustic wave reflection, electromagnetic property change and cable surface image to identify potential cracks.

[0073] As a preferred technical solution, the cable crack identification device also includes a traction guide rail 3, a moving motor 4 and a moving positioner 19.

[0074] The traction guide rail 3 is installed on the bracket 20; the moving motor 4 is installed on the bracket 20, which is used to drive the traction guide rail 3 to move, and the traction cable crack identification device moves along the length direction of the cable. The moving positioner 19 is installed on the bracket 20, which is used to position the cable crack identification device.

[0075] In order to detect cable cracks in all directions and make the detection of the cable crack identification device more flexible, the cable crack identification device is designed with a traction guide rail 3, a mobile motor 4, a mobile positioner 19, and is equipped with a transmission device and a navigation function. The mobile motor 4 is connected to the traction guide rail 3 through the transmission device, so that the traction guide rail 3 is driven by the mobile motor 4, thereby driving the entire cable crack identification device to move along the cable axis.

[0076] The traction guide rail 3 is mainly made of lightweight materials, has good flexibility and corrosion resistance, can easily adapt to cables of various shapes and sizes, and is convenient for data collection. The mobile motor 4 and the mobile positioner 19 can drive the cable crack identification device to carry out detection work in an orderly manner, and realize the accurate movement of the cable crack identification device to the location where the signal is abnormal or a serious crack is found, ensuring that the cable crack identification device can accurately reach the cable at the designated position to carry out comprehensive detection work.

[0077] This embodiment also provides a cable crack identification method, which is applied to the cable crack identification device, and includes the following steps:

[0078] S1, collect cable images;

[0079] S2, judging whether there is a crack in the cable and determining the location of the crack in the cable;

[0080] S3, judging the cable crack condition according to the magnetic field change information when the cable cracks;

[0081] S4, detecting crack change information on the cable surface;

[0082] S5, processing the cable image;

[0083] Specifically, the specific method for processing the cable image includes the following steps:

[0084] S51, enlarging the cable image;

[0085] S52, performing filtering processing on the amplified cable image;

[0086] S53, performing analog-to-digital conversion on the filtered cable image.

[0087] S6, outputting crack identification results according to the processed cable image, cable crack location, cable crack condition and crack change information.

[0088] As a preferred technical solution, the cable crack identification method further includes the following steps:

[0089] S7, adjusting the position of the cable by the multi-position adjustment mechanism 13, and capturing potential crack data information related to the potential cracks on the cable surface from multiple dimensions;

[0090] The multi-position adjustment mechanism 13 includes a mechanical shaft 11 mounted on a bracket 20, a mechanical arm 12 mounted on the mechanical shaft 11, and a gripper for grabbing cables mounted at the end of the mechanical arm 12, for grabbing and adjusting the position of the cables.

[0091] The cable crack identification device carries out the cable crack identification task through the coordinated cooperation of the camera 16, the acoustic wave sensor 18, the leakage magnetic sensor 8, the crack sensor 9 and the image processor 1, and outputs the crack identification result according to the processed cable image, the cable crack position, the cable crack condition and the crack change information, which can reduce manual intervention, automatically and accurately identify the position of the cable crack, realize the rapid and accurate identification of the cable crack, provide strong support for the safe maintenance of the cable, and improve the accuracy of crack detection.

[0092] This embodiment also provides a cable crack identification device, which includes: a controller; a memory storing executable instructions; wherein the executable instructions can be run on the controller and implement the cable crack identification method.

[0093] This embodiment further provides a computer-readable storage medium storing a computer program, wherein the computer program implements the cable crack identification method when executed by a processor.

[0094] Embodiment 2:

[0095] The existing cable crack detection device or method has the following problems:

[0096] 1. Since cable cracks are often subtle and diverse in shape, traditional detection methods rely on manual inspections, which make it difficult to accurately capture these subtle changes, resulting in a high rate of missed detection or false detection, insufficient crack detection accuracy, and reduced detection accuracy.

[0097] 2. The existing cable crack detection device has limitations in the detection range and cannot conduct comprehensive and all-round detection of the cable, which easily leads to some important but hard-to-reach cracks being ignored, thus affecting the overall detection effect.

[0098] 3. Some cable crack detection devices still rely on manual operation and have a low degree of automation, resulting in slow detection speed, significantly increasing detection time and cost. In addition, due to the strong subjectivity of manual judgment, the detection results are easily affected by human factors.

[0099] 4. In order to achieve specific detection functions, some detection devices often use complex mechanical structures and control systems, which increases the manufacturing difficulty and cost of the equipment, requires higher operating skills and experience during the use of the equipment, reduces the detection speed, and restricts the scope of application of the equipment.

[0100] In order to solve one of the problems existing in the above-mentioned existing cable crack detection device or method, Figure 1 As shown, a cable crack identification device includes a camera 16, an acoustic wave sensor 18, a magnetic flux leakage sensor 8, a crack sensor 9, an image processor 1 and a main controller 7.

[0101] The camera 16 is used to collect cable images; the camera 16 is a high-definition intelligent camera 16, which can realize rapid continuous shooting of cable images to adapt to the image collection of mobile cables.

[0102] The acoustic wave sensor 18 is used to determine whether there is a crack in the cable and to locate the crack in the cable. When ultrasonic waves propagate in the cable, they will produce reflection, refraction, and scattering when encountering cracks. The acoustic wave sensor 18 further determines whether there is a crack in the cable and locates the crack address based on the ultrasonic waves reflected back.

[0103] The magnetic flux leakage sensor 8 is used to determine the cable crack condition according to the magnetic field change information when the cable cracks. The magnetic flux leakage sensor 8 uses the phenomenon of magnetic field leakage when the cable cracks to detect the change of the magnetic field and further determine the cable crack condition.

[0104] The crack sensor 9 is used to detect crack change information on the cable surface. The crack sensor 9 can detect crack changes on the cable surface, has sufficient resolution and sensitivity, and can clearly capture fine cracks on the cable surface.

[0105] The image processor 1 is used for receiving the cable image and processing the cable image.

[0106] Preferably, the image processor 1 includes an image receiver, a signal amplifier, a filter and an analog-to-digital converter.

[0107] The image receiver is used to receive the collected cable image; the signal amplifier is used to amplify the cable image; the filter is used to filter the amplified cable image; and the analog-to-digital converter is used to perform analog-to-digital conversion on the filtered cable image.

[0108] Since the collected cable image signals are usually weak and contain certain noise and interference, it is necessary to use a signal amplifier to appropriately amplify the weak cable image signals, and then use a filter to remove the noise and interference in the cable image signals to make the cable image signals clearer. Finally, this series of analog signals are converted into digital signals through an analog converter for further processing and analysis.

[0109] The main controller 7 is electrically connected to the camera 16, the acoustic wave sensor 18, the magnetic leakage sensor 8, the crack sensor 9 and the image processor 1, and is used to receive the processed cable image, the cable crack position, the cable crack condition and the crack change information, and output the crack identification result according to the processed cable image, the cable crack position, the cable crack condition and the crack change information.

[0110] Since judging the cable crack condition based on the magnetic field change information when a crack appears in the cable, further judging whether the cable has a crack and determining the crack location address based on the received reflected ultrasonic wave, and detecting the crack changes on the cable surface through the crack sensor 9 are all conventional technical means in the field, they will not be repeated here.

[0111] The main controller 7 is the core part of the entire cable crack identification device. It is mainly responsible for coordinating the workflow of the entire cable crack identification device, including the transmission, storage and analysis and processing of image data, as well as the output and feedback of crack identification results. It can also monitor and remotely control the entire detection process. It pre-processes the collected cable images by using edge detection, filtering and denoising algorithms to enhance crack characteristics, and uses deep learning algorithms to train and learn the pre-processed data, so that the trained cable crack identification model can accurately identify the crack characteristics on the cable surface, automatically identify the cracks on the cable surface according to the crack characteristics, and evaluate the severity of the cracks, thereby improving the accuracy of detection, reducing dependence on manual judgment, and reducing the influence of subjective factors.

[0112] The cable crack identification device carries out the cable crack identification task through the coordinated cooperation of the camera 16, the acoustic wave sensor 18, the leakage magnetic sensor 8, the crack sensor 9 and the image processor 1, and outputs the crack identification result according to the processed cable image, the cable crack position, the cable crack condition and the crack change information, which can reduce manual intervention, automatically and accurately identify the position of the cable crack, realize the rapid and accurate identification of the cable crack, provide strong support for the safe maintenance of the cable, and improve the accuracy of crack detection.

[0113] As a preferred technical solution, the cable crack identification device further includes a bracket 20 and a multi-position adjustment mechanism 13 .

[0114] The bracket 20 is mainly used to support and fix the various components of the cable crack identification device to ensure that they remain stable and accurate during the detection process and adapt to different cable trenches and working environments, wherein a cable working area 17 is provided. Specifically, the camera 16, the acoustic wave sensor 18, the magnetic flux leakage sensor 8, the crack sensor 9, the image processor 1 and the main controller 7 are all installed on the bracket 20.

[0115] The multi-position adjustment mechanism 13 includes a mechanical axis 11 installed on a bracket 20, a mechanical arm 12 installed on the mechanical axis 11, and a gripper for grabbing the cable installed at the end of the mechanical arm 12, which is used to grab and adjust the position of the cable to facilitate the camera 16, the acoustic wave sensor 18, the leakage magnetic sensor 8 and the crack sensor 9 to fully scan the cable surface when moving along the cable axis to avoid missing tiny cracks.

[0116] Typically, cables are laid underground. To facilitate the camera 16, acoustic wave sensor 18, magnetic flux leakage sensor 8 and crack sensor 9 to move along the axial direction or length direction of the cable to comprehensively scan the cable surface and avoid missing tiny cracks, a movable multi-position adjustment mechanism 13 is provided, and the automated mechanical axis 11 and the automated mechanical arm 12 cooperate to adjust the position angle of the cable to capture the temperature change, acoustic wave reflection, electromagnetic property change and cable surface image on the cable surface from multiple dimensions. The main controller 7 processes and analyzes the temperature change, acoustic wave reflection, electromagnetic property change and cable surface image to identify potential cracks.

[0117] As a preferred technical solution, the cable crack identification device also includes a traction guide rail 3, a moving motor 4 and a moving positioner 19.

[0118] The traction guide rail 3 is installed on the bracket 20; the moving motor 4 is installed on the bracket 20, which is used to drive the traction guide rail 3 to move, and the traction cable crack identification device moves along the length direction of the cable. The moving positioner 19 is installed on the bracket 20, which is used to position the cable crack identification device.

[0119] In order to detect cable cracks in all directions and make the detection of the cable crack identification device more flexible, the cable crack identification device is designed with a traction guide rail 3, a mobile motor 4, a mobile positioner 19, and is equipped with a transmission device and a navigation function. The mobile motor 4 is connected to the traction guide rail 3 through the transmission device, so that the traction guide rail 3 is driven by the mobile motor 4, thereby driving the entire cable crack identification device to move along the cable axis.

[0120] The traction guide rail 3 is mainly made of lightweight materials, has good flexibility and corrosion resistance, can easily adapt to cables of various shapes and sizes, and is convenient for data collection. The mobile motor 4 and the mobile positioner 19 can drive the cable crack identification device to carry out detection work in an orderly manner, and realize the accurate movement of the cable crack identification device to the location where the signal is abnormal or a serious crack is found, ensuring that the cable crack identification device can accurately reach the cable at the designated position to carry out comprehensive detection work.

[0121] The device also includes an LED light source 2, a display screen 14, an alarm 15, a Bluetooth chip 6, and a charge-discharge battery 5. The LED light source 2, the display screen 14, the alarm 15, the Bluetooth chip 6, and the charge-discharge battery 5 are all electrically connected to a main controller 7.

[0122] The LED light source 2 can illuminate the cable surface, reduce the interference of shadows on the crack image acquisition, provide stable and uniform lighting conditions for image acquisition, and ensure the quality of the collected cable image. The charge-discharge battery 5 can provide a stable power supply for the entire device.

[0123] The display screen 14 can display the detection image, identification results and analysis report of the cable crack in real time; the alarm 15 has a real-time alarm function. Once the device detects a serious crack or abnormal situation, the alarm 15 responds to the alarm command of the main controller 7, automatically triggers the sound and light alarm, and can send alarm information to the remote monitoring center through the Bluetooth chip 6 to remind the staff to take protective measures; the Bluetooth chip 6 can be used for wireless communication with smart phones or other Bluetooth devices to achieve data synchronization, APP function expansion and remote control functions. The main controller feeds back the crack identification results to the smart terminal through the Bluetooth chip 6 for the technicians to monitor the cable crack identification in real time. At the same time, the device is also equipped with necessary safety protection devices 10. If the device itself is found to be abnormal or the working conditions are abnormal, such as water immersion, leakage, etc., when the cable crack is identified in the cable trench, the safety protection device 10 immediately sends an alarm signal through the alarm 15 to notify the operator to take measures to ensure the safety of the operator and the stable operation of the equipment.

[0124] Specifically, the safety protection device 10 includes but is not limited to a water leakage sensor or a water immersion sensor for detecting water seepage in the cable trench, a leakage detector for detecting whether the cable is leaking electricity, a temperature sensor for detecting the working temperature of the cable crack identification device, a leakage sensor for detecting whether the cable crack identification device has leakage current, and a temperature-sensitive fire detector. The water leakage sensor or the water immersion sensor leakage and electricity detector, the temperature sensor, the leakage sensor, and the temperature-sensitive fire detector are all electrically connected to the main controller 7. The main controller 7 determines whether the cable crack identification device itself has an abnormal situation or an abnormal working condition by receiving and processing and analyzing the signals fed back by the water leakage sensor or the water immersion sensor leakage and electricity detector, the temperature sensor, the leakage sensor, and the temperature-sensitive fire detector. If the cable crack identification device itself has an abnormal situation or an abnormal working condition such as water seepage, leakage, or excessive working temperature, the safety protection device 10 immediately controls the alarm 15 through the main controller 7 to send an alarm signal to notify the operator to take measures to ensure the safety of the operator and the stable operation of the equipment.

[0125] This embodiment also provides a cable crack identification method, which is applied to the cable crack identification device. Figure 2 As shown, it includes the following steps:

[0126] S1, collect cable images;

[0127] S2, judging whether there is a crack in the cable and determining the location of the crack in the cable;

[0128] S3, judging the cable crack condition according to the magnetic field change information when the cable cracks;

[0129] S4, detecting crack change information on the cable surface;

[0130] S5, processing the cable image;

[0131] Specifically, if Figure 3 As shown, the specific method for processing the cable image includes the following steps:

[0132] S51, enlarging the cable image;

[0133] S52, performing filtering processing on the amplified cable image;

[0134] S53, performing analog-to-digital conversion on the filtered cable image.

[0135] S6, outputting crack identification results according to the processed cable image, cable crack location, cable crack condition and crack change information.

[0136] As a preferred technical solution, the cable crack identification method further includes the following steps:

[0137] S7, capturing potential crack data information related to potential cracks on the cable surface from multiple dimensions through the multi-position adjustment mechanism 13;

[0138] Among them, the multi-position adjustment mechanism 13 includes a mechanical axis 11 installed on the bracket 20, a mechanical arm 12 installed on the mechanical axis 11, and a data acquisition component installed at the end of the mechanical arm 12. The data acquisition component is used to capture potential crack data information related to potential cracks on the cable surface from multiple dimensions.

[0139] Since the collected cable image signals are usually weak and contain certain noise and interference, it is necessary to use a signal amplifier to appropriately amplify the weak cable image signals, and then use a filter to remove the noise and interference in the cable image signals to make the cable image signals clearer. Finally, this series of analog signals are converted into digital signals through an analog converter for further processing and analysis.

[0140] The cable crack identification method is responsible for coordinating the workflow of the entire cable crack identification device through the main controller 7, including the transmission, storage and analysis and processing of image data, as well as the output and feedback of crack identification results. It can also monitor and remotely control the entire detection process. The collected cable images are pre-processed by using edge detection, filtering and denoising algorithms to enhance crack characteristics. The pre-processed data is trained and learned using a deep learning algorithm, so that the trained cable crack identification model can accurately identify the crack characteristics on the cable surface, automatically identify the cracks on the cable surface according to the crack characteristics, and evaluate the severity of the cracks, thereby improving the accuracy of detection, reducing dependence on manual judgment, and reducing the influence of subjective factors.

[0141] The cable crack identification device carries out the cable crack identification task through the coordinated cooperation of the camera 16, the acoustic wave sensor 18, the leakage magnetic sensor 8, the crack sensor 9 and the image processor 1, and outputs the crack identification result according to the processed cable image, the cable crack position, the cable crack condition and the crack change information, which can reduce manual intervention, automatically and accurately identify the position of the cable crack, realize the rapid and accurate identification of the cable crack, provide strong support for the safe maintenance of the cable, and improve the accuracy of crack detection.

[0142] This embodiment also provides a cable crack identification device, which includes: a controller; a memory storing executable instructions; wherein the executable instructions can be run on the controller and implement the cable crack identification method.

[0143] This embodiment further provides a computer-readable storage medium storing a computer program, wherein the computer program implements the cable crack identification method when executed by a processor.

[0144] In summary, the present invention has the following beneficial effects:

[0145] 1. The accuracy of crack detection can be improved by using the camera 16, the acoustic wave sensor 18, the magnetic flux leakage sensor 8, the crack sensor 9 and the image processor 1 to coordinate and cooperate to carry out the cable crack identification task.

[0146] 2. By setting the traction guide rail 3, the moving motor 4, and the moving positioner 19, the traction guide rail 3 has good flexibility and corrosion resistance, can easily adapt to cables of various shapes and sizes, and is equipped with an efficient transmission device and positioning system, ensuring the precise movement and positioning of various sensors during the detection process.

[0147] 3. By being equipped with necessary Bluetooth chips 6, safety protection devices 10 and alarms 15, remote control is supported, fully protecting the safety of operators and the safety of equipment operation.

[0148] 4. A movable multi-position adjustment mechanism 13 is provided, and the position angle of the cable is adjusted by the automated mechanical axis 11 and the automated mechanical arm 12 in coordination, so as to facilitate a comprehensive scan of the cable surface and avoid missing tiny cracks. It is possible to capture cable characteristic parameters such as temperature changes, sound wave reflections, changes in electromagnetic properties, and cable surface images on the cable surface from multiple dimensions to identify potential cracks.

[0149] 5. The cable crack identification device has high integration, optimizes the structure of the device, makes the overall structure more compact and reasonable, and adopts a simple and intuitive charging and discharging battery 5, thereby extending the service life of the device and making the overall appearance more beautiful.

[0150] Embodiment three:

[0151] It should be understood that this embodiment at least includes all the technical features of the above embodiments, and is further described in detail based on the above embodiments.

[0152] In this embodiment, the cable crack identification method also includes the following steps: obtaining multi-dimensional parameters that affect the aging cracks of the cable to be detected, extracting the multi-dimensional parameters to obtain multi-dimensional eigenvalues; calculating the aging crack index of the cable to be detected based on the multi-dimensional eigenvalues; controlling the multi-position adjustment mechanism, LED light source, mobile motor and camera action according to the aging crack index, and the specific strategy for controlling the multi-position adjustment mechanism, LED light source, mobile motor and camera action is to control the robot arm and gripper action in the multi-position adjustment mechanism according to the size of the aging crack index, thereby adjusting the angle of each rotation of the cable and the number of times the cable rotates, and controlling the power of the LED light source to adjust the brightness, and controlling the mobile motor to drive the traction mechanism to adjust the number of movements within a preset front and rear moving distance range, and adjusting the frequency of the camera taking cable images.

[0153] Specifically, the number of times the cable rotates, the brightness of the LED light source, the number of movements within the moving distance range, and the frequency of the camera taking cable images are all directly proportional to the aging crack index, and the angle of each cable rotation is inversely proportional to the aging crack index.

[0154] The aging crack index characterizes the aging degree of the cable and the probability of cracks. The larger the aging crack index is, the higher the possibility of aging cracks in the cable can be considered. For cables to be detected with low aging crack probability, the workload of collecting and analyzing their surface images, such as the number of images collected, can be reduced to a certain extent, and the efficiency of cable crack identification can be improved on the premise of ensuring the completion of cable crack identification. For cables with high aging degree and high crack probability, that is, cables with high aging crack probability, the frequency of cable surface image acquisition and the brightness of the light source can be increased. By obtaining multiple cable surface images at different angles, the cable surface can be fully scanned and identified as much as possible to avoid missing tiny cracks. Because in many cases, the cables that need to be cracked are often hundreds of meters or even thousands of meters long, the above method can be used to detect and identify cracks on the cable surface, which will undoubtedly improve work efficiency.

[0155] This embodiment calculates the aging crack index of the cable to be detected, controls the multi-position adjustment mechanism, LED light source, mobile motor and camera action according to the aging crack index, analyzes the cable surface image to complete crack identification, and can improve the intelligence level of the cable crack identification device and the work efficiency of cable crack identification.

[0156] Preferably, each dimension characteristic value includes the total time of the parameter value exceeding the preset standard parameter threshold and the parameter ratio value between the parameter mean of the parameter value exceeding the preset standard parameter threshold and the preset standard threshold. Among them, T i Indicates the total time that the parameter value of the i-th dimension exceeds the preset standard parameter threshold, PR i Indicates the parameter ratio between the parameter mean of the parameter value exceeding the preset standard parameter threshold of the i-th dimension and the preset standard threshold, α i It represents the adjustment factor of the i-th dimension feature, which can be set by the technician, n represents the number of dimensions of the multi-dimensional feature value, RT represents the working life of the cable, and LT represents the design life of the cable.

[0157] The angle of each cable rotation = Angle / (β1×AgingCracks), where Angle represents a preset basic rotation angle, β1 represents an angle rotation adjustment coefficient, and β1×AgingCracks is greater than 1.

[0158] The number of rotations of the cable each time=RC×β2×AgingCracks, wherein RC represents a preset basic number of rotations, β2 represents a rotation number adjustment coefficient, and β2×AgingCracks is greater than 1.

[0159] LED light source brightness=BR×β3×AgingCracks, where BR represents a preset basic brightness, β3 represents a brightness adjustment coefficient, and β3×AgingCracks is greater than 1.

[0160] The number of moves within the moving distance range=LC×β4×AgingCracks, where LC represents the preset basic number of moves, β4 represents the movement number adjustment coefficient, and β4×AgingCracks is greater than 1.

[0161] The frequency of the camera capturing the cable image=FR×β5×AgingCracks, wherein FR represents a preset basic capturing frequency, β5 represents a capturing frequency adjustment coefficient, and β5×AgingCracks is greater than 1.

[0162] Specifically, the multi-dimensional parameters include but are not limited to the current value, vibration value and environmental parameters of the cable. The environmental parameters include the ambient temperature and humidity values ​​and the ambient pH such as the pH of soil and rainwater. The multi-dimensional characteristic values ​​include the total time of current values ​​exceeding the preset standard current threshold, the current ratio value between the current mean of the current values ​​exceeding the preset standard current threshold and the preset standard current threshold, the total time of vibration values ​​exceeding the preset standard vibration threshold, the vibration ratio value between the vibration mean of the vibration values ​​exceeding the preset standard vibration threshold and the preset standard vibration threshold, the total time of ambient temperature exceeding the preset standard ambient temperature value, the ambient temperature ratio value between the ambient temperature mean of the ambient temperature values ​​exceeding the preset standard ambient temperature value and the preset standard ambient temperature value, the total time of ambient humidity values ​​exceeding the preset standard ambient humidity value, the ambient humidity ratio value between the ambient humidity mean of the ambient humidity values ​​exceeding the preset standard ambient humidity value and the preset standard ambient humidity value, the total time of ambient acidity exceeding the preset standard acidity value, the ambient acidity ratio value between the ambient acidity mean of the ambient acidity exceeding the preset standard acidity value and the preset standard acidity value, the total time of ambient alkalinity exceeding the preset standard acidity value and the ambient acidity ratio value between the ambient alkalinity mean of the ambient alkalinity exceeding the preset standard acidity value and the preset standard acidity value.

[0163] By setting the aging crack index The aging crack index can be better calculated based on the multi-dimensional eigenvalues, and then the multi-position adjustment mechanism, LED light source, mobile motor and camera action can be controlled more accurately and targetedly. For cables to be detected with low aging crack probability, the workload of collecting and analyzing their surface images, such as the number of image collections, can be reduced to a certain extent. On the premise of ensuring the completion of cable crack identification, the efficiency of cable crack identification is improved. For cables with high aging degree and high crack probability, that is, cables with high aging crack probability, the frequency of cable surface image collection and the brightness of the light source can be increased. By obtaining multiple cable surface images at different angles, the cable surface can be scanned and identified as comprehensively and carefully as possible to complete crack identification, avoid missing tiny cracks, and improve the intelligence of the cable crack identification device and the work efficiency of cable crack identification.

[0164] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0165] The above-mentioned embodiments only express several implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A cable crack identification device, characterized in that: The cable crack identification device comprises: A camera for collecting images of cables; Acoustic wave sensor, used to determine whether there are cracks in the cable and determine the location of the cable cracks; Magnetic leakage sensor, used to determine the cable crack condition based on the magnetic field change information when the cable cracks; Crack sensor, used to detect crack change information on the cable surface; An image processor, used for receiving and processing the cable image; The main controller is electrically connected to the camera, the acoustic wave sensor, the magnetic flux leakage sensor, the crack sensor and the image processor, and is used to receive the processed cable image, the cable crack position, the cable crack condition and the crack change information, and output the crack recognition result according to the processed cable image, the cable crack position, the cable crack condition and the crack change information.

2. A cable crack identification device as claimed in claim 1, characterized in that: The cable crack identification device also includes: Bracket; The multi-position adjustment mechanism comprises a mechanical shaft installed on a bracket, a mechanical arm installed on the mechanical shaft, and a gripper installed at the end of the mechanical arm for grabbing cables, and is used for grabbing and adjusting the position of the cables.

3. A cable crack identification device as claimed in claim 2, characterized in that: The camera, the acoustic wave sensor, the magnetic flux leakage sensor, the crack sensor, the image processor and the main controller are all installed on the bracket.

4. A cable crack identification device as claimed in claim 3, characterized in that: The cable crack identification device also includes: A traction guide rail, mounted on the bracket; The mobile motor is installed on the bracket to drive the traction guide rail to move the cable crack identification device along the length of the cable. The mobile locator is mounted on a bracket and is used to locate the cable crack identification device.

5. A cable crack identification device as claimed in claim 4, characterized in that: Image processors include: An image receiver, used for receiving the collected cable image; A signal amplifier, used to amplify the cable image; A filter, used for filtering the amplified cable image; The analog-to-digital converter is used for performing analog-to-digital conversion on the cable image after filtering.

6. A cable crack identification method, applied to the cable crack identification device according to any one of claims 1 to 5, characterized in that: The cable crack identification method comprises the following steps: Collect cable images; Determine whether there are cracks in the cable and determine the location of the cable cracks; Determine the cable crack condition based on the magnetic field change information when the cable cracks; Detect crack change information on the cable surface; Processing the cable image; The crack identification result is output based on the processed cable image, cable crack location, cable crack condition and crack change information.

7. A cable crack identification method as claimed in claim 6, characterized in that: The cable crack identification method further comprises the following steps: The position of the cable is adjusted by a multi-position adjustment mechanism to capture potential crack data information related to potential cracks on the cable surface from multiple dimensions; The multi-position adjustment mechanism includes a mechanical shaft installed on a bracket, a mechanical arm installed on the mechanical shaft, and a gripper installed at the end of the mechanical arm for grabbing the cable, which is used to grab and adjust the position of the cable.

8. A cable crack identification method as claimed in claim 7, characterized in that: The specific method for processing the cable image includes the following steps: Enlarge the cable image; Performing filtering on the amplified cable image; Perform analog-to-digital conversion on the filtered cable image.

9. A cable crack identification device, characterized in that: The cable crack identification device comprises: Controller; A memory storing executable instructions; The executable instructions may be run on the controller and implement the cable crack identification method as described in any one of claims 6 to 8.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the cable crack identification method according to any one of claims 6 to 8 is implemented.

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