CN110907749A - Method and device for positioning fault underground cable - Google Patents
Method and device for positioning fault underground cable Download PDFInfo
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- CN110907749A CN110907749A CN201911137084.2A CN201911137084A CN110907749A CN 110907749 A CN110907749 A CN 110907749A CN 201911137084 A CN201911137084 A CN 201911137084A CN 110907749 A CN110907749 A CN 110907749A
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- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/08—Locating faults in cables, transmission lines, or networks
- G01R31/081—Locating faults in cables, transmission lines, or networks according to type of conductors
- G01R31/083—Locating faults in cables, transmission lines, or networks according to type of conductors in cables, e.g. underground
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- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/08—Locating faults in cables, transmission lines, or networks
- G01R31/088—Aspects of digital computing
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Abstract
The application relates to a method and a device for positioning a fault underground cable. The method comprises the following steps: receiving an infrared image collected by the robot; identifying the infrared image to determine an image area where the cable is located; inputting the identified image area into a pre-trained fault identification model so as to obtain a fault cable through the fault identification model; obtaining the position of the cable according to the image area corresponding to the fault cable; and outputting the cable position. The method can improve the positioning accuracy.
Description
Technical Field
The application relates to the technical field of underground cables, in particular to a method and a device for positioning a fault underground cable.
Background
Cables buried underground are often exploded due to the temperature rise of the cables during power transmission; or, the cable is damaged due to water inflow of the underground laying pipeline, so that normal transmission of the cable is influenced.
Generally, in order to monitor underground cables, the cables need to be manually checked one by one, thereby reducing the efficiency of monitoring.
Disclosure of Invention
In view of the above, there is a need to provide a method and apparatus for locating a faulty underground cable, which can improve efficiency.
A method of locating a faulty underground cable, the method comprising:
receiving an infrared image collected by the robot;
identifying the infrared image to determine an image area where the cable is located;
inputting the identified image area into a pre-trained fault identification model so as to obtain a fault cable through the fault identification model;
obtaining the position of the cable according to the image area corresponding to the fault cable;
and outputting the cable position.
In one embodiment, the identifying the infrared image to determine the image area where the cable is located includes:
segmenting the infrared image to obtain an image area where the cable is located, and labeling the obtained image area;
and performing position and operation on the infrared image after the mark and the infrared image before the mark to extract an image area where the cable is located.
In one embodiment, the inputting the identified image area into a pre-trained fault recognition model to obtain a faulty cable through the fault recognition model includes:
extracting a historical image of a preset frame before the infrared image, and acquiring a first cable area corresponding to the historical image;
calculating a first similarity of the first cable region and the image region;
and if the first similarity is smaller than a preset value, the cable corresponding to the image area is a fault cable.
In one embodiment, the calculating the first similarity between the first cable region and the image region includes:
and calculating a first similarity of the first cable area and the image area through a cosine function.
In one embodiment, the inputting the identified image area into a pre-trained fault recognition model to obtain a faulty cable through the fault recognition model includes:
acquiring a standard image pre-stored in a database, and acquiring a second cable area corresponding to the standard image;
calculating a second similarity of the second cable region and the image region;
and if the second similarity is smaller than a preset value, the cable corresponding to the image area is a fault cable.
In one embodiment, the calculating the second similarity of the second cable region and the image region includes:
and calculating a second similarity of the second cable area and the image area through a cosine function.
A faulty underground cable locating device, the device comprising:
the receiving module is used for receiving the infrared image collected by the robot;
the identification module is used for identifying the infrared image so as to determine an image area where the cable is located;
the fault judgment module is used for inputting the identified image area into a pre-trained fault identification model so as to obtain a fault cable through the fault identification model;
the position acquisition module is used for acquiring the position of the cable according to the image area corresponding to the fault cable;
and the output module is used for outputting the cable position.
In one embodiment, the identification module comprises:
the marking unit is used for segmenting the infrared image to obtain an image area where the cable is located and marking the obtained image area;
and the operation unit is used for performing position and operation on the infrared image after the mark and the infrared image before the mark so as to extract the image area where the cable is located.
A computer device comprising a memory storing a computer program and a processor implementing the steps of any of the methods described above when the processor executes the computer program.
A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method of any of the above.
According to the method and the device for positioning the fault underground cable, after the infrared image collected by the robot is received, the image area where the cable is located is determined from the infrared image, and then only the image area is input into the fault recognition model trained in advance, so that the fault cable is obtained through the fault recognition model, the interference position can be filtered, the recognition accuracy is improved, in addition, the server obtains the cable position according to the image area corresponding to the fault cable, and then outputs the cable position, and the processing efficiency is improved.
Drawings
FIG. 1 is a diagram of an embodiment of a method for locating a faulty underground cable;
FIG. 2 is a schematic flow chart of a method for locating a faulty underground cable according to one embodiment;
FIG. 3 is a block diagram of the structure of a faulty underground cable locating device in one embodiment;
FIG. 4 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The method for positioning the fault underground cable can be applied to the application environment shown in figure 1. Wherein the robot 102 and the server 104 communicate over a network. The server 104 receives the infrared image acquired by the robot 102, identifies the infrared image to determine an image area where the cable is located, inputs the identified image area into a pre-trained fault identification model to obtain a faulty cable through the fault identification model, so that the server can obtain a cable position according to the image area corresponding to the faulty cable and output the cable position, and thus, the image area where the cable is located is determined from the infrared image, and then only the partial image area is input into the pre-trained fault identification model to obtain the faulty cable through the fault identification model, so that an interference position can be filtered, the identification accuracy is improved, in addition, the server obtains the cable position according to the image area corresponding to the faulty cable, and further outputs the cable position, and the processing efficiency is improved. The robot 102 may be, but not limited to, a personal computer, a notebook computer, a smart phone, a tablet computer, and a portable wearable image, which can be moved, and the devices that can be moved can be installed on a mobile vehicle to implement the underground cable, and the server 104 can be implemented by an independent server or a server cluster formed by a plurality of servers.
In one embodiment, as shown in fig. 2, a method for locating a faulty underground cable is provided, which is illustrated by applying the method to the server in fig. 1, and includes the following steps:
s202: and receiving the infrared image collected by the robot.
Specifically, the robot runs in a cable trench, and the robot walks while acquiring images, wherein infrared images can be acquired through infrared equipment due to darkness in the cable trench. And transmitting the collected infrared image back to the server in real time.
S204: and identifying the infrared image to determine the image area where the cable is located.
For the accuracy of identification, the server segments the infrared image to obtain an image area where the cable is located, for example, the server segments the infrared image, and then identifies each segment to determine the image area, and optionally, the cable image may be compared with the infrared image to obtain the image area where the cable is located.
S206: inputting the identified image area into a pre-trained fault identification model so as to obtain a fault cable through the fault identification model.
Specifically, after the server acquires the image area, the image area is input into a pre-trained fault recognition model, so as to determine whether a cable corresponding to the image area has a fault through the fault recognition model, for example, the cable image in the image area may be compared with a standard cable image, if the cable image has a defect or deformation, a result that the cable has the fault is output, otherwise, the cable has no fault. In addition, the cable image may be compared with the cable image of the previous frame, that is, the image area in the current frame is compared with the image area in the previous frame, if the color value and the like of the cable image in the corresponding image area are changed, a cable fault is indicated, otherwise, no fault exists. Specifically, the server may select a cable image to determine the width of the cable, compare the cable within the width range with the cable having the same width in the previous frame, and if there is a defect or the missing range is greater than a preset value, it indicates that there is a fault.
S208: and obtaining the cable position according to the image area corresponding to the fault cable.
S210: and outputting the cable position.
Specifically, the server may obtain the cable position according to an image area corresponding to the faulty cable, specifically, each frame of image uploaded by the robot is identified with a geographic position, so that the server may obtain the position of the robot according to the identified geographic position, and further determine the position of the cable according to the position of the robot, for example, when the robot walks along the cable by a preset distance, the robot may obtain a rough position of the cable according to the position of the robot, and then determine the position represented by each pixel in the image according to the scaling of the image, so that the server may obtain the corresponding pixel according to the image area, and further determine the cable position of the faulty cable according to the corresponding pixel, wherein optionally, an average value of coordinates of positions of all pixels in the faulty area may be used as the cable position, the server then outputs the cable location of the failed cable.
According to the method for positioning the underground cable with the fault, after the infrared image collected by the robot is received, the image area where the cable is located is determined from the infrared image, and then only the partial image area is input into the fault recognition model trained in advance, so that the cable with the fault is obtained through the fault recognition model, the interference position can be filtered, the recognition accuracy is improved, in addition, the server obtains the cable position according to the image area corresponding to the cable with the fault, and then outputs the cable position, and the processing efficiency is improved.
In one embodiment, the identifying the infrared image to determine the image area where the cable is located includes: segmenting the infrared image to obtain an image area where the cable is located, and labeling the obtained image area; and performing position and operation on the infrared image after the mark and the infrared image before the mark to extract an image area where the cable is located.
Specifically, when the server determines the image area where the cable is located, the server may first identify the area of the cable by means of segmentation, then label the image of the area where the cable is located, so that pixels of the images of other areas are deleted, or replaced with white, and the like, then perform bitwise and operation on the infrared image after the label and the infrared image before the label, so as to completely filter out interference at unrelated positions, and further extract the image area only including the cable area, thereby laying a foundation for subsequent identification.
In one embodiment, the inputting the identified image area into a pre-trained fault recognition model to obtain a faulty cable through the fault recognition model includes: extracting a historical image of a preset frame before the infrared image, and acquiring a first cable area corresponding to the historical image; calculating a first similarity of the first cable region and the image region; and if the first similarity is smaller than a preset value, the cable corresponding to the image area is a fault cable.
In one embodiment, the calculating the first similarity between the first cable region and the image region includes: and calculating a first similarity of the first cable area and the image area through a cosine function.
Specifically, in this embodiment, whether the cable is faulty or not is determined by the acquired image, for example, a previous preset frame history image before the infrared image may be extracted, and a first cable region in the preset frame history image may be extracted, where the server may be the first cable region extracted in the processing process according to the previous preset frame image, that is, when the server processes the preset frame image in the previous time, the first cable region and the preset frame image are respectively and correspondingly stored, so that the server may directly acquire the first cable region in the step, and respectively calculate similarities between the first cable region and the image region, where the similarity calculation may be performed by a cosine function, the server may calculate an average value of the obtained similarities to obtain a first similarity, and determine whether the first similarity is smaller than a preset value, if the first similarity is smaller than the preset value, the cable corresponding to the image area is a faulty cable.
The preset value may be adjusted according to the current environment, for example, if the current environment is dark, the preset value becomes smaller correspondingly, otherwise, the preset value becomes larger correspondingly.
In one embodiment, the inputting the identified image area into a pre-trained fault recognition model to obtain a faulty cable through the fault recognition model includes: acquiring a standard image pre-stored in a database, and acquiring a second cable area corresponding to the standard image; calculating a second similarity of the second cable region and the image region; and if the second similarity is smaller than a preset value, the cable corresponding to the image area is a fault cable.
In one embodiment, the calculating the second similarity of the second cable region and the image region includes: and calculating a second similarity of the second cable area and the image area through a cosine function.
Specifically, in this embodiment, the server determines whether the cable is faulty according to a pre-stored standard image, for example, the server acquires a second cable region in the standard image, and then calculates the similarity between the second cable region and the image region, where the similarity may be calculated by a cosine function, the server may calculate an average value of the obtained similarities to obtain a second similarity, and determine whether the second similarity is smaller than a preset value, and if the second similarity is smaller than the preset value, the cable corresponding to the image region is a faulty cable.
The preset value may be adjusted according to the current environment, for example, if the current environment is dark, the preset value becomes smaller correspondingly, otherwise, the preset value becomes larger correspondingly.
It should be understood that, although the steps in the flowchart of fig. 2 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a portion of the steps in fig. 2 may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.
In one embodiment, as shown in fig. 3, there is provided a faulty underground cable positioning device, comprising:
a receiving module 100, configured to receive an infrared image acquired by a robot;
the identification module 200 is used for identifying the infrared image to determine an image area where the cable is located;
a fault judgment module 300, configured to input the identified image area into a pre-trained fault identification model, so as to obtain a faulty cable through the fault identification model;
a position obtaining module 400, configured to obtain a cable position according to an image area corresponding to a faulty cable;
an output module 500 for outputting the cable position.
In one embodiment, the identification module comprises:
the marking unit is used for segmenting the infrared image to obtain an image area where the cable is located and marking the obtained image area;
and the operation unit is used for performing position and operation on the infrared image after the mark and the infrared image before the mark so as to extract the image area where the cable is located.
In one embodiment, the failure determining module may include:
the frame extraction unit is used for extracting a preset frame historical image before the infrared image and acquiring a first cable area corresponding to the historical image;
a first calculating unit for calculating a first similarity between the first cable region and the image region;
and the first judging unit is used for judging that the cable corresponding to the image area is a fault cable if the first similarity is smaller than a preset value.
In one embodiment, the first calculation unit is further configured to calculate a first similarity between the first cable region and the image region by a cosine function.
In one embodiment, the failure determining module may include:
the standard image acquisition unit is used for acquiring a standard image pre-stored in a database and acquiring a second cable area corresponding to the standard image;
a second calculating unit for calculating a second similarity of the second cable region and the image region;
and the second judging unit is used for judging that the cable corresponding to the image area is a fault cable if the second similarity is smaller than a preset value.
In one embodiment, the second calculation unit is further configured to calculate a second similarity between the second cable region and the image region by a cosine function.
The specific definition of the faulty underground cable positioning device can be referred to the definition of the faulty underground cable positioning method in the foregoing, and the detailed description is omitted here. The modules in the fault underground cable positioning device can be wholly or partially realized by software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 4. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a method of locating a faulty underground cable.
Those skilled in the art will appreciate that the architecture shown in fig. 4 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, there is provided a computer device comprising a memory storing a computer program and a processor implementing the following steps when the processor executes the computer program: receiving an infrared image collected by the robot; identifying the infrared image to determine an image area where the cable is located; inputting the identified image area into a pre-trained fault identification model so as to obtain a fault cable through the fault identification model; obtaining the position of the cable according to the image area corresponding to the fault cable; and outputting the cable position.
In one embodiment, said identifying said infrared image to determine the image area where the cable is located, as implemented by the processor executing the computer program, comprises: segmenting the infrared image to obtain an image area where the cable is located, and labeling the obtained image area; and performing position and operation on the infrared image after the mark and the infrared image before the mark to extract an image area where the cable is located.
In one embodiment, said inputting the identified image regions into a pre-trained fault recognition model implemented when the processor executes the computer program to derive a faulty cable through the fault recognition model, comprises: extracting a historical image of a preset frame before the infrared image, and acquiring a first cable area corresponding to the historical image; calculating a first similarity of the first cable region and the image region; and if the first similarity is smaller than a preset value, the cable corresponding to the image area is a fault cable.
In one embodiment, said calculating a first similarity of said first cable region to said image region, as implemented by a processor executing a computer program, comprises: and calculating a first similarity of the first cable area and the image area through a cosine function.
In one embodiment, said inputting the identified image regions into a pre-trained fault recognition model implemented when the processor executes the computer program to derive a faulty cable through the fault recognition model, comprises: acquiring a standard image pre-stored in a database, and acquiring a second cable area corresponding to the standard image; calculating a second similarity of the second cable region and the image region; and if the second similarity is smaller than a preset value, the cable corresponding to the image area is a fault cable.
In one embodiment, said calculating a second similarity of said second cable region to said image region, as implemented by a processor executing a computer program, comprises: and calculating a second similarity of the second cable area and the image area through a cosine function.
In one embodiment, a computer-readable storage medium is provided, having a computer program stored thereon, which when executed by a processor, performs the steps of: receiving an infrared image collected by the robot; identifying the infrared image to determine an image area where the cable is located; inputting the identified image area into a pre-trained fault identification model so as to obtain a fault cable through the fault identification model; obtaining the position of the cable according to the image area corresponding to the fault cable; and outputting the cable position.
In one embodiment, said identifying said infrared image to determine the image area where the cable is located, implemented when the computer program is executed by the processor, comprises: segmenting the infrared image to obtain an image area where the cable is located, and labeling the obtained image area; and performing position and operation on the infrared image after the mark and the infrared image before the mark to extract an image area where the cable is located.
In one embodiment, the inputting of the identified image regions into a pre-trained fault recognition model implemented when a computer program is executed by a processor to derive a faulty cable through the fault recognition model comprises: extracting a historical image of a preset frame before the infrared image, and acquiring a first cable area corresponding to the historical image; calculating a first similarity of the first cable region and the image region; and if the first similarity is smaller than a preset value, the cable corresponding to the image area is a fault cable.
In one embodiment, said calculating a first similarity of said first cable region to said image region, implemented when the computer program is executed by the processor, comprises: and calculating a first similarity of the first cable area and the image area through a cosine function.
In one embodiment, the inputting of the identified image regions into a pre-trained fault recognition model implemented when a computer program is executed by a processor to derive a faulty cable through the fault recognition model comprises: acquiring a standard image pre-stored in a database, and acquiring a second cable area corresponding to the standard image; calculating a second similarity of the second cable region and the image region; and if the second similarity is smaller than a preset value, the cable corresponding to the image area is a fault cable.
In one embodiment, said calculating a second similarity of said second cable region to said image region, implemented when the computer program is executed by the processor, comprises: and calculating a second similarity of the second cable area and the image area through a cosine function.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A method of locating a faulty underground cable, the method comprising:
receiving an infrared image collected by the robot;
identifying the infrared image to determine an image area where the cable is located;
inputting the identified image area into a pre-trained fault identification model so as to obtain a fault cable through the fault identification model;
obtaining the position of the cable according to the image area corresponding to the fault cable;
and outputting the cable position.
2. The method of claim 1, wherein the identifying the infrared image to determine the image area where the cable is located comprises:
segmenting the infrared image to obtain an image area where the cable is located, and labeling the obtained image area;
and performing position and operation on the infrared image after the mark and the infrared image before the mark to extract an image area where the cable is located.
3. The method of claim 1, wherein inputting the identified image regions into a pre-trained fault recognition model to derive faulty cables through the fault recognition model comprises:
extracting a historical image of a preset frame before the infrared image, and acquiring a first cable area corresponding to the historical image;
calculating a first similarity of the first cable region and the image region;
and if the first similarity is smaller than a preset value, the cable corresponding to the image area is a fault cable.
4. The method of claim 3, wherein said calculating a first similarity of the first cable region to the image region comprises:
and calculating a first similarity of the first cable area and the image area through a cosine function.
5. The method of claim 1, wherein inputting the identified image regions into a pre-trained fault recognition model to derive faulty cables through the fault recognition model comprises:
acquiring a standard image pre-stored in a database, and acquiring a second cable area corresponding to the standard image;
calculating a second similarity of the second cable region and the image region;
and if the second similarity is smaller than a preset value, the cable corresponding to the image area is a fault cable.
6. The method of claim 5, wherein said calculating a second similarity of the second cable region to the image region comprises:
and calculating a second similarity of the second cable area and the image area through a cosine function.
7. A faulty underground cable locating device, the device comprising:
the receiving module is used for receiving the infrared image collected by the robot;
the identification module is used for identifying the infrared image so as to determine an image area where the cable is located;
the fault judgment module is used for inputting the identified image area into a pre-trained fault identification model so as to obtain a fault cable through the fault identification model;
the position acquisition module is used for acquiring the position of the cable according to the image area corresponding to the fault cable;
and the output module is used for outputting the cable position.
8. The apparatus of claim 7, wherein the identification module comprises:
the marking unit is used for segmenting the infrared image to obtain an image area where the cable is located and marking the obtained image area;
and the operation unit is used for performing position and operation on the infrared image after the mark and the infrared image before the mark so as to extract the image area where the cable is located.
9. A computer device comprising a memory and a processor, the memory storing a computer program, wherein the processor implements the steps of the method of any one of claims 1 to 6 when executing the computer program.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 6.
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| CN113984018A (en) * | 2021-10-27 | 2022-01-28 | 南方电网数字电网研究院有限公司 | Site digital standard investigation method based on mobile phone positioning |
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