CN114091699A - Power communication equipment fault diagnosis method and system - Google Patents
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Abstract
The invention provides a fault diagnosis method and a fault diagnosis system for power communication equipment, wherein the method comprises the following steps: acquiring image data of a background interface of a network management system; performing character extraction on the image data through a CTPN algorithm to obtain character information corresponding to the image data; and judging whether equipment failure occurs or not according to the character information and prestored system failure information, and if so, performing warning processing. The invention utilizes CTPN algorithm based on deep learning to monitor the text information of network management system, network control system and website background, which is beneficial to accurately and rapidly finding out the fault of the power communication equipment and finding out the fault reason; the monitoring can be carried out for a long time in the equipment maintenance, corresponding early warning can be timely given to the equipment under attack, the safety is higher, and the maintenance efficiency of the power communication system is improved.
Description
Technical Field
The invention relates to the technical field of power communication equipment fault diagnosis, in particular to a power communication equipment fault diagnosis method and system.
Background
With the development of social science and technology, the electric power communication system is gradually intelligentized, and the maintenance of the electric power communication system becomes more complicated.
When the conventional electric power communication system such as an SDH optical fiber communication system is regularly maintained and has a fault, manual inspection and repair are needed. When faults occur in a network management system, a network control system, a website and the like, manual work is usually needed to remove the faults one by one, finally the fault occurrence reasons are located, and the efficiency is low; the maintenance of the power communication website is usually performed regularly, workers who perform actions such as malicious access of users cannot find the actions timely, and in addition, according to the traditional scheme for manually checking system faults and manually and regularly maintaining communication equipment, a testing team needs to be arranged to complete the test, and if the test does not meet the conditions, the faults need to be searched again for testing again. After the test is qualified, the dispatching department and the related maintenance department cooperate to complete the switching and restore the service. The process needs to use an engineering truck and professional maintenance personnel, and takes hours to complete, and if the process is in a place with a large area or a rugged road, the service recovery time needs to be calculated according to the day. The traditional method needs to consume high costs including the daily food expenses of operation and maintenance personnel, the oil consumption of vehicles, road cost, maintenance expenses and the like, and the total cost is high.
Disclosure of Invention
In order to solve the above problems in the prior art, the present invention provides a method and a system for diagnosing a fault of an electric power communication device, which can immediately prompt a corresponding prompt when a system fails, and improve the maintenance efficiency of the electric power communication system.
The invention provides a fault diagnosis method for power communication equipment, which comprises the following steps:
acquiring image data of a background interface of a network management system;
performing character extraction on the image data through a CTPN algorithm to obtain character information corresponding to the image data;
and judging whether equipment failure occurs or not according to the text information and prestored system failure information, and if so, performing warning processing.
Further, the extracting characters from the image data by the CTPN algorithm to obtain character information corresponding to the image data includes:
extracting the features of the image data to obtain a feature signal;
determining a target area in the image data according to the characteristic signal;
and processing the characteristic signals in the target area through a BilSTM algorithm, and performing regression classification on the processing result to obtain character information corresponding to the image data.
Further, the performing feature extraction on the image data to obtain a feature signal includes:
drawing a feature map for the image data through a VGG network;
and determining a target region to be selected on the feature map through a sliding window, and extracting features in the target region to be selected to obtain a feature signal.
Further, the processing the feature signal by the BiLSTM algorithm, and performing regression classification on the processing result to obtain the text information corresponding to the image data includes:
processing the characteristic signal through a BilSTM algorithm to obtain a primary processing signal;
performing full connection processing on the primary processing signal through a full connection layer to obtain a secondary processing signal;
and carrying out regression classification on the secondary processing signals to obtain character signals, and after the validity of the character signals is determined, combining the character signals through a text line construction algorithm to obtain character information.
A second aspect of the present invention provides a power communication apparatus fault diagnosis system, including:
the data acquisition module is used for acquiring image data of a background interface of the network management system;
the data processing module is used for carrying out character extraction on the image data through a CTPN algorithm to obtain character information corresponding to the image data;
and the fault diagnosis module is used for judging whether equipment faults occur or not according to the text information and prestored system fault information, and if so, warning processing is carried out.
Further, the data processing module is further configured to:
extracting the features of the image data to obtain a feature signal;
determining a target area in the image data according to the characteristic signal;
and in the target area, processing the characteristic signals through a BilSTM algorithm, and performing regression classification on the processing result to obtain character information corresponding to the image data.
Further, the data processing module is further configured to:
drawing a feature map for the image data through a VGG network;
and determining a target region to be selected on the feature map through a sliding window, and extracting features in the target region to be selected to obtain a feature signal.
Further, the data processing module is further configured to:
processing the characteristic signal through a BilSTM algorithm to obtain a primary processing signal;
carrying out full connection processing on the primary processing signal through a full connection layer to obtain a secondary processing signal;
and carrying out regression classification on the secondary processing signals to obtain character signals, and after the validity of the character signals is determined, combining the character signals through a text line construction algorithm to obtain character information.
A third aspect of the present invention provides an electronic apparatus, comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor implements the power communication device fault diagnosis method according to any one of the first aspect.
A fourth aspect of the present invention provides a computer-readable storage medium including a stored computer program, wherein when the computer program runs, an apparatus in which the computer-readable storage medium is located is controlled to execute the power communication apparatus fault diagnosis method according to any one of the first aspects.
Compared with the prior art, the embodiment of the invention has the beneficial effects that:
the invention provides a fault diagnosis method and a fault diagnosis system for power communication equipment, wherein the method comprises the following steps: acquiring image data of a background interface of a network management system; performing character extraction on the image data through a CTPN algorithm to obtain character information corresponding to the image data; and judging whether equipment failure occurs or not according to the character information and prestored system failure information, and if so, performing warning processing. The invention utilizes CTPN algorithm based on deep learning to monitor the text information of network management system, network control system and website background, which is beneficial to accurately and rapidly finding out the fault of the power communication equipment and finding out the fault reason; the monitoring can be carried out for a long time in the equipment maintenance, corresponding early warning can be timely given to the equipment under attack, the safety is higher, and the maintenance efficiency of the power communication system is improved.
Drawings
In order to more clearly illustrate the technical solution of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a flowchart of a method for diagnosing a fault of a power communication device according to an embodiment of the present invention;
fig. 2 is a flowchart of a CPTN identification process provided by an embodiment of the present invention;
fig. 3 is a flowchart of CPTN identification steps provided by an embodiment of the present invention;
FIG. 4 is a flow chart of a conventional OCR recognition step;
fig. 5 is a flowchart of a power communication device fault diagnosis method according to another embodiment of the present invention;
FIG. 6 is a flow chart of conventional fault detection maintenance procedures;
fig. 7 is an apparatus diagram of a power communication device fault diagnosis system according to an embodiment of the present invention;
fig. 8 is a block diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without inventive step based on the embodiments of the present invention, are within the scope of protection of the present invention.
It should be understood that the step numbers used herein are only for convenience of description and are not used as limitations on the order in which the steps are performed.
It is to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the specification of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
The terms "comprises" and "comprising" indicate the presence of the described features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
The term "and/or" refers to any and all possible combinations of one or more of the associated listed items and includes such combinations.
A first aspect.
Referring to fig. 1, an embodiment of the present invention provides a method for diagnosing a fault of an electric power communication device, including:
and S10, acquiring the image data of the background interface of the network management system.
And S20, performing character extraction on the image data through a CTPN algorithm to obtain character information corresponding to the image data.
Preferably, the step S20 includes:
extracting the features of the image data to obtain a feature signal;
determining a target area in the image data according to the characteristic signal;
and processing the characteristic signals in the target area through a BilSTM algorithm, and performing regression classification on the processing result to obtain character information corresponding to the image data.
In a specific implementation manner of the embodiment of the present invention, the performing feature extraction on the image data to obtain a feature signal includes:
drawing a feature map for the image data through a VGG network;
and determining a target region to be selected on the feature map through a sliding window, and extracting features in the target region to be selected to obtain a feature signal.
In another specific implementation manner of the embodiment of the present invention, the processing the feature signal by using a BiLSTM algorithm, and performing regression classification on a processing result to obtain text information corresponding to the image data, includes:
processing the characteristic signal by a BilSTM algorithm to obtain a primary processing signal;
carrying out full connection processing on the primary processing signal through a full connection layer to obtain a secondary processing signal;
and carrying out regression classification on the secondary processing signals to obtain character signals, and after the validity of the character signals is determined, combining the character signals through a text line construction algorithm to obtain character information.
It can be understood that, as shown in fig. 2, the text detection algorithm adopted by the present invention is a CTPN algorithm, which is a text detection algorithm that selects each character frame of a line of characters and then combines all the characters to obtain a complete line of characters.
As shown in fig. 3, the CTPN algorithm includes the following steps: firstly, capturing pictures of an interface of a network management system or a website background, and inputting the pictures into a VGG network; obtaining a feature map through a VGG network; extracting features on the feature map by using a sliding window, and defining a target region to be selected by using the features; sending the obtained features into a BilSTM for sequence feature extraction, and sending the result into a full connection layer: and finally, connecting the recognized character classifications together by using a text line construction algorithm to obtain a text position, and combining all character boxes into a text box to obtain a complete text line.
The conventional Optical Character Recognition (OCR) based on image processing generally adopts five steps of character region positioning, character image correction, row and column segmentation, classifier recognition and post-processing, as shown in fig. 4, the method is divided into three stages according to the processing mode: a preprocessing stage, an identification stage and a post-processing stage. The method has the disadvantages of poor robustness and suitability for simpler text distribution; and the characteristic that intervals exist among texts is not considered by adopting the fast RCNN for target detection, and the CTPN algorithm is used as the text recognition algorithm, so that the accuracy and the stability are better.
And S30, judging whether equipment failure occurs or not according to the character information and pre-stored system failure information, and if so, performing warning processing.
Referring to fig. 5, the present invention performs text recognition on interfaces of an electric power network management system, a network control system, a website background, etc., records extracted text information generated when the interfaces normally operate or abnormally operate into a database by combining a deep learning method, compares the extracted text information with text information obtained by detection during daily maintenance, and gives a corresponding warning to prompt the system of abnormality and prompt maintenance personnel of a corresponding repairing method for common faults when the system is compared to be in fault or the system is about to be in fault; the system also can monitor the indexes of the electric power communication optical cable, such as temperature, strain, lightning stroke and the like monitored by the network management system, can indirectly reflect the temperature, strain and lightning stroke suffered conditions of the power transmission line, feeds the temperature, strain and lightning stroke suffered conditions back to the primary line in real time, and can assist in judging the fault point of the power line; in addition, the access information data of the website background can be input into the corresponding database for comparison, and corresponding early warning is given in time when malicious access occurs, so that the safety of the power communication system and the efficiency of troubleshooting are improved.
As shown in fig. 6, when a power system fails, a conventional scheme for manually checking system failures and manually maintaining communication equipment periodically needs to arrange a test team to complete a test, and if the test fails, the system needs to find a failure again for retesting. After the test is qualified, the dispatching department and the related maintenance department cooperate to complete the switching and restore the service. The process needs to use an engineering truck and professional maintenance personnel, and takes hours to complete, and if the process is in a place with a large area or a rugged road, the service recovery time needs to be calculated according to the day. The method has the advantages that once switching work is completed, the cost consumed by the traditional method comprises the cost of food consumption of operation and maintenance personnel, the oil consumption, road cost, maintenance cost and the like of vehicles, the total cost is high, the method has higher efficiency, manpower and material resources are saved, corresponding prompts can be immediately made under the conditions that a system is in fault, a website is maliciously visited and the like, and the maintenance efficiency of the power communication system is improved.
A second aspect.
Referring to fig. 7, an embodiment of the invention provides a power communication equipment fault diagnosis system, including:
and the data acquisition module 10 is used for acquiring image data of a background interface of the network management system.
And the data processing module 20 is configured to perform character extraction on the image data through a CTPN algorithm to obtain character information corresponding to the image data.
Preferably, the data processing module 20 is further configured to:
extracting the features of the image data to obtain a feature signal;
determining a target area in the image data according to the characteristic signal;
and processing the characteristic signals in the target area through a BilSTM algorithm, and performing regression classification on the processing result to obtain character information corresponding to the image data.
Preferably, the data processing module 20 is further configured to:
drawing a feature map for the image data through a VGG network;
and determining a target region to be selected on the feature map through a sliding window, and extracting features in the target region to be selected to obtain a feature signal.
Preferably, the data processing module 20 is further configured to:
processing the characteristic signal through a BilSTM algorithm to obtain a primary processing signal;
carrying out full connection processing on the primary processing signal through a full connection layer to obtain a secondary processing signal;
and carrying out regression classification on the secondary processing signals to obtain character signals, and after the validity of the character signals is determined, combining the character signals through a text line construction algorithm to obtain character information.
And the fault diagnosis module 30 is configured to determine whether an equipment fault occurs according to the text information and pre-stored system fault information, and if so, perform warning processing.
The system provided by the invention monitors the text information of a network management system, a network control system and a website background by using a CTPN algorithm based on deep learning, and is favorable for accurately and rapidly finding out the fault of the power communication equipment and finding out the fault reason; the monitoring can be carried out for a long time in the equipment maintenance, corresponding early warning can be timely given to the equipment under attack, the safety is higher, and the maintenance efficiency of the power communication system is improved.
In a third aspect.
The present invention provides an electronic device, including:
a processor, a memory, and a bus;
the bus is used for connecting the processor and the memory;
the memory is used for storing operation instructions;
the processor is configured to, by invoking the operation instruction, execute the instruction to cause the processor to perform an operation corresponding to the power communication device fault diagnosis method shown in the first aspect of the present application.
In an alternative embodiment, an electronic device is provided, as shown in fig. 8, the electronic device 5000 shown in fig. 8 includes: a processor 5001 and a memory 5003. The processor 5001 and the memory 5003 are coupled, such as via a bus 5002. Optionally, the electronic device 5000 may also include a transceiver 5004. It should be noted that the transceiver 5004 is not limited to one in practical application, and the structure of the electronic device 5000 is not limited to the embodiment of the present application.
The processor 5001 may be a CPU, general purpose processor, DSP, ASIC, FPGA or other programmable logic device, transistor logic device, hardware component, or any combination thereof. Which may implement or perform the various illustrative logical blocks, modules, and circuits described in connection with the disclosure. The processor 5001 may also be a combination of computing functions, e.g., comprising one or more microprocessors, a combination of a DSP and a microprocessor, or the like.
The memory 5003 may be, but is not limited to, a ROM or other type of static storage device that can store static information and instructions, a RAM or other type of dynamic storage device that can store information and instructions, an EEPROM, a CD-ROM or other optical disk storage, optical disk storage (including compact disk, laser disk, optical disk, digital versatile disk, blu-ray disk, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.
The memory 5003 is used for storing application program codes for executing the present solution, and the execution is controlled by the processor 5001. The processor 5001 is configured to execute application program code stored in the memory 5003 to implement the teachings of any of the foregoing method embodiments.
Among them, electronic devices include but are not limited to: mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and the like, and fixed terminals such as digital TVs, desktop computers, and the like.
A fourth aspect.
The present invention provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements a power communication apparatus fault diagnosis method shown in the first aspect of the present application.
Yet another embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored, which, when run on a computer, enables the computer to perform the corresponding content in the aforementioned method embodiments.
Claims (10)
1. A power communication equipment fault diagnosis method is characterized by comprising the following steps:
acquiring image data of a background interface of a network management system;
performing character extraction on the image data through a CTPN algorithm to obtain character information corresponding to the image data;
and judging whether equipment failure occurs or not according to the character information and prestored system failure information, and if so, performing warning processing.
2. The method for diagnosing the fault of the power communication equipment according to claim 1, wherein the extracting the characters from the image data through the CTPN algorithm to obtain the character information corresponding to the image data comprises:
extracting the features of the image data to obtain a feature signal;
determining a target area in the image data according to the characteristic signal;
and processing the characteristic signals in the target area through a BilSTM algorithm, and performing regression classification on the processing result to obtain character information corresponding to the image data.
3. The power communication equipment fault diagnosis method according to claim 2, wherein the performing feature extraction on the image data to obtain a feature signal comprises:
drawing a feature map for the image data through a VGG network;
and determining a target region to be selected on the feature map through a sliding window, and extracting features in the target region to be selected to obtain a feature signal.
4. The method for diagnosing the fault of the power communication equipment as claimed in claim 2, wherein the processing the characteristic signals by the BiLSTM algorithm and the regression classification of the processing results to obtain the text information corresponding to the image data comprises:
processing the characteristic signal through a BilSTM algorithm to obtain a primary processing signal;
performing full connection processing on the primary processing signal through a full connection layer to obtain a secondary processing signal;
and carrying out regression classification on the secondary processing signals to obtain character signals, and after the validity of the character signals is determined, combining the character signals through a text line construction algorithm to obtain character information.
5. A power communication device fault diagnosis system, characterized by comprising:
the data acquisition module is used for acquiring image data of a background interface of the network management system;
the data processing module is used for carrying out character extraction on the image data through a CTPN algorithm to obtain character information corresponding to the image data;
and the fault diagnosis module is used for judging whether equipment faults occur or not according to the text information and prestored system fault information, and if so, warning processing is carried out.
6. The power communication device fault diagnosis system of claim 5, wherein the data processing module is further configured to:
extracting the features of the image data to obtain a feature signal;
determining a target area in the image data according to the characteristic signal;
and processing the characteristic signals in the target area through a BilSTM algorithm, and performing regression classification on the processing result to obtain character information corresponding to the image data.
7. The power communication equipment fault diagnosis system according to claim 6, wherein the data processing module is further configured to:
drawing a feature map for the image data through a VGG network;
and determining a target region to be selected on the feature map through a sliding window, and extracting features in the target region to be selected to obtain a feature signal.
8. The power communication device fault diagnosis system of claim 6, wherein the data processing module is further configured to:
processing the characteristic signal through a BilSTM algorithm to obtain a primary processing signal;
carrying out full connection processing on the primary processing signal through a full connection layer to obtain a secondary processing signal;
and carrying out regression classification on the secondary processing signals to obtain character signals, and after the validity of the character signals is determined, combining the character signals through a text line construction algorithm to obtain character information.
9. An electronic apparatus, characterized by comprising a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, the processor implementing the power communication device fault diagnosis method according to any one of claims 1 to 4 when executing the computer program.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium comprises a stored computer program, wherein when the computer program runs, the apparatus where the computer-readable storage medium is located is controlled to execute the power communication apparatus fault diagnosis method according to any one of claims 1 to 4.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116630991A (en) * | 2023-07-24 | 2023-08-22 | 广东电网有限责任公司佛山供电局 | Power transmission line state evaluation method and system |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116630991A (en) * | 2023-07-24 | 2023-08-22 | 广东电网有限责任公司佛山供电局 | Power transmission line state evaluation method and system |
| CN116630991B (en) * | 2023-07-24 | 2024-01-09 | 广东电网有限责任公司佛山供电局 | Power transmission line state evaluation method and system |
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