CN117424791B - Large-scale power communication network fault diagnosis system - Google Patents
Large-scale power communication network fault diagnosis system Download PDFInfo
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Abstract
The invention provides a fault diagnosis system of a large-scale power communication network, which comprises a local monitoring module and a cloud platform; the local monitoring module is used for acquiring communication monitoring data of the power communication nodes in the power communication network in real time, analyzing node communication states according to the acquired communication monitoring data, obtaining a power communication node fault analysis result, and transmitting the power communication node fault analysis result to the cloud platform; the cloud platform is used for carrying out regional state analysis based on the failure analysis results of the plurality of power communication nodes in the designated region to obtain regional failure analysis results. The invention is helpful to improve the reliability and adaptability of fault diagnosis for large-scale power communication networks.
Description
Technical Field
The invention relates to the technical field of power communication network fault diagnosis, in particular to a large power communication network fault diagnosis system.
Background
With the rapid development of global economy, the power communication network has become one of the indispensable infrastructures of modern society. The stable operation of the power communication network has important significance for guaranteeing energy safety and economic development.
At present, as the scale of the power communication network is continuously enlarged, data in the power communication network is directly collected, analyzed, maintained and the like in a single cloud platform mode, huge data transmission pressure and data processing pressure are required to face in the process of data transmission and fault analysis, and the reliability of data transmission and data processing is insufficient. In the practical application process, the quality of the data cannot be ensured due to the influence of interference factors in various aspects in the data transmission process, so that the reliability and accuracy of fault analysis are further influenced.
Disclosure of Invention
In view of the foregoing, the present invention aims to provide a large-scale power communication network fault diagnosis system.
The aim of the invention is realized by adopting the following technical scheme:
the invention discloses a fault diagnosis system of a large-scale power communication network, which comprises a local monitoring module and a cloud platform; wherein,
the local monitoring module is used for acquiring communication monitoring data of the power communication nodes in the power communication network in real time, analyzing node communication states according to the acquired communication monitoring data, obtaining a power communication node fault analysis result, and transmitting the power communication node fault analysis result to the cloud platform;
the cloud platform is used for carrying out regional state analysis based on the failure analysis results of the plurality of power communication nodes in the designated region to obtain regional failure analysis results.
Preferably, the local monitoring module comprises a first base station unit and a second base station unit; wherein a data communication connection is established between the first base station unit and the second base station unit;
the first base station unit and the second base station unit are respectively connected with all power communication nodes in the same local area, and respectively acquire and collect communication monitoring data of all power communication nodes in the same local area;
the first base station unit and the second base station unit respectively perform node communication state analysis according to the acquired communication monitoring data to obtain fault analysis results of all power communication nodes; sharing the obtained power communication node fault analysis result;
the first base station unit or the second base station unit integrates according to the fault analysis result of the shared power communication node, and when the first base station unit and the second base station unit analyze and judge that the same power communication node has a communication fault at the same time, the power communication node is marked to have a fault; otherwise, when the first base station unit or the second base station unit analyzes and judges that the failure analysis result of the power communication node is normal, marking that the failure analysis result of the power communication node is normal; and transmitting the fault analysis result of the integrated power communication node to the cloud platform.
Preferably, the first base station unit and the second base station unit respectively include a data acquisition unit and a node state analysis unit;
the data acquisition units are respectively connected with the power communication nodes in the designated area to acquire communication monitoring data of the power communication nodes;
the node state analysis unit is used for carrying out node communication state analysis according to the communication monitoring data obtained by the power communication nodes, obtaining a power communication node fault analysis result, and transmitting the power communication node fault analysis result to the cloud platform.
Preferably, the arrangement modes of the first base station unit and the second base station unit specifically include:
dividing a plurality of local power communication nodes in the same area into a local area according to the designated number of power communication nodes;
for the case of setting base station units individually in a local area, the first base station units and the second base station units are set uniformly distributed in the local area, and the first base station units and the second base station units are respectively established with power communication in the local area to respectively acquire communication monitoring data of the power communication nodes.
Preferably, the cloud platform comprises a region fault analysis unit;
the regional fault analysis unit is used for combining the regional node state feature vectors according to the fault analysis results of all the power communication nodes in the preset local region, inputting the regional node state feature vectors into a preset regional fault analysis model according to the obtained node state feature vectors, and analyzing the input regional node state feature vectors by the regional fault analysis model to obtain regional fault analysis results, wherein the regional fault analysis results comprise whether faults occur or not and the fault types.
Preferably, the cloud platform further comprises a global fault analysis unit;
the global fault analysis unit is used for forming a global state characteristic vector according to fault analysis results of all power communication nodes in the whole area, inputting the global state characteristic vector into a preset global fault analysis model according to the obtained global state characteristic vector, and carrying out fault analysis on the global state characteristic vector by the global fault analysis model to obtain a global fault analysis result, wherein the global fault analysis result comprises whether a fault occurs, a fault area and a fault type.
Preferably, the cloud platform further comprises a database module;
the database module is used for classifying, storing and managing the acquired power communication node fault analysis results of all the power communication nodes in the whole area, and constructing a power communication node fault analysis database.
Preferably, the cloud platform further comprises a visualization module;
the visualization module is used for integrating the fault analysis results of all the power communication nodes, the local area fault analysis results and the whole area fault analysis results obtained in the whole area into a large screen display template for visual display.
The beneficial effects of the invention are as follows: the local monitoring module is arranged to collect communication monitoring data of the power communication nodes in each local area in the local large-scale power communication network and conduct communication fault analysis, so that targeted fault analysis can be conducted on the performances of the individual power communication nodes; and further transmitting the fault analysis result of each power communication node to the cloud platform, and carrying out fault analysis on the regional level based on the cloud platform according to the obtained communication fault analysis result of the node to obtain a fault analysis result. Through the hierarchical processing mode, the data transmission and operation pressure of the cloud platform can be reduced, and the reliability and adaptability of fault diagnosis of a large-scale power communication network are improved.
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The invention will be further described with reference to the accompanying drawings, in which embodiments do not constitute any limitation of the invention, and other drawings can be obtained by one of ordinary skill in the art without inventive effort from the following drawings.
Fig. 1 is a schematic structural diagram of a fault diagnosis system for a large-scale power communication network according to an embodiment of the present invention.
Detailed Description
The invention is further described in connection with the following application scenario.
Referring to the embodiment of fig. 1, a fault diagnosis system of a large-scale power communication network is shown, which comprises a local monitoring module and a cloud platform; wherein,
the local monitoring module is used for acquiring communication monitoring data of the power communication nodes in the power communication network in real time, analyzing node communication states according to the acquired communication monitoring data, obtaining a power communication node fault analysis result, and transmitting the power communication node fault analysis result to the cloud platform;
the cloud platform is used for carrying out regional state analysis based on the failure analysis results of the plurality of power communication nodes in the designated region to obtain regional failure analysis results.
Based on the large-scale power communication network fault diagnosis system provided by the embodiment, the local monitoring module is arranged to collect communication monitoring data of the power communication nodes in each local area in the local large-scale power communication network and perform communication fault analysis, so that the performance of the individual power communication nodes can be subjected to targeted fault analysis; and further transmitting the fault analysis result of each power communication node to the cloud platform, and carrying out fault analysis on the regional level based on the cloud platform according to the obtained communication fault analysis result of the node to obtain a fault analysis result. Through the hierarchical processing mode, the data transmission and operation pressure of the cloud platform can be reduced, and the reliability and adaptability of fault diagnosis of a large-scale power communication network are improved.
Preferably, the communication monitoring data comprises data transmission information, node fault information, logic test feedback information and the like.
The local monitoring module can be built based on equipment for collecting and analyzing communication monitoring data of the power communication nodes in the local area, such as an edge server, a base station and the like.
Preferably, the power communication nodes comprise power communication devices constituting a power communication network, wherein the power communication devices comprise power line protection means, an automation control system, a remote monitoring and data acquisition system, communication devices, etc., wherein each power communication device corresponds to one power communication node in the power communication network;
aiming at the requirements of power communication node fault analysis, corresponding data are collected for the power communication nodes through a local monitoring module.
Preferably, the local monitoring module comprises a first base station unit and a second base station unit; wherein a data communication connection is established between the first base station unit and the second base station unit;
the first base station unit and the second base station unit are respectively connected with all power communication nodes in the same local area, and respectively acquire and collect communication monitoring data of all power communication nodes in the same local area;
the first base station unit and the second base station unit respectively perform node communication state analysis according to the acquired communication monitoring data to obtain fault analysis results of all power communication nodes; sharing the obtained power communication node fault analysis result;
the first base station unit or the second base station unit integrates according to the fault analysis result of the shared power communication node, and when the first base station unit and the second base station unit analyze and judge that the same power communication node has a communication fault at the same time, the power communication node is marked to have a fault; otherwise, when the first base station unit or the second base station unit analyzes and judges that the failure analysis result of the power communication node is normal, marking that the failure analysis result of the power communication node is normal; and transmitting the fault analysis result of the integrated power communication node to the cloud platform.
The reliability of the system is affected by considering that when the power communication node is subjected to fault analysis, the reliability of communication monitoring data acquired from the power communication node is insufficient due to the influence of the complex environment of the power communication network, or the situation that the node communication monitoring data is missing or lost due to other non-equipment fault causes is easy to cause misjudgment of the fault analysis of the power communication node. Therefore, in the above embodiment, a scheme of performing communication monitoring data collection and fault analysis on the power communication nodes in the local area through the double base station units is specifically proposed, which can help to improve reliability and accuracy of fault analysis of the power communication nodes.
When the first base station unit and the second base station unit judge that the power communication node has communication faults, the power communication node is confirmed to have communication faults, otherwise, when only one base station unit or no base station unit judges that the power communication node has communication faults, the power communication node is finally confirmed to have no communication faults; the power communication nodes are directly analyzed in a mode of matching and judging by the double base stations, so that the situation that the normal power communication nodes are misjudged to be faulty can be reduced, the operation pressure of the cloud platform for further carrying out regional state analysis according to the fault analysis result of the power communication nodes is effectively reduced, and the reliability of the regional state analysis is improved.
Wherein the first communication base station unit and the second communication base station unit may be communication base station units that are specifically set for the divided partial areas; the communication base station unit may be configured to simultaneously use the power communication node in the local area as a communication base station unit based on the communication capability of the power communication node.
Preferably, the first base station unit and the second base station unit respectively include a data acquisition unit and a node state analysis unit;
the data acquisition units are respectively connected with the power communication nodes in the designated area to acquire communication monitoring data of the power communication nodes;
the node state analysis unit is used for carrying out node communication state analysis according to the communication monitoring data obtained by the power communication nodes, obtaining a power communication node fault analysis result, and transmitting the power communication node fault analysis result to the cloud platform.
And carrying out fault analysis on the communication capacity or the running state of the power communication node according to the communication monitoring data obtained from the single power communication node, and accurately detecting the fault condition of the power communication node.
Preferably, the arrangement modes of the first base station unit and the second base station unit specifically include:
dividing a plurality of local power communication nodes in the same area into a local area according to the designated number of power communication nodes;
for the case of setting base station units individually in a local area, the first base station units and the second base station units are set uniformly distributed in the local area, and the first base station units and the second base station units are respectively established with power communication in the local area to respectively acquire communication monitoring data of the power communication nodes.
Preferably, in the arrangement of the first base station unit and the second base station unit, when the power communication node in the local area is used as both the base station units, two nodes are selected from the power communication nodes as the first base station unit and the second base station unit, respectively, based on the power communication node already arranged in the local area.
Wherein the selection of the first base station unit and the second base station unit may be assigned at the time of the node network set up or the selection of the first base station unit and the second base station unit may be updated (reassigned) periodically.
Preferably, based on the power communication nodes already set in the local area, two nodes are respectively selected from the power communication nodes as the first base station unit and the second base station unit, and specifically includes:
the upper computer acquires positioning information of each power communication node in the local area and establishes a rectangular coordinate system area;Wherein, the method comprises the steps of, wherein,respectively representing the x coordinate and the y coordinate of a coordinate system, wherein the coordinate range is thatM represents the maximum value of coordinates in the coordinate system; and corresponding each power communication node to the rectangular coordinate system area according to the positioning information of each power communication node, namely each power communication node has corresponding coordinates；
Setting two simulated centroid points according to the obtained rectangular coordinate system areaWherein the initial position of the first simulated centroid point is randomly set asThe position of the second simulated centroid point is correspondingly set asThe method comprises the steps of carrying out a first treatment on the surface of the Wherein the superscript 0 indicates a position corresponding to the initial time;
according to the random sequence, sequentially carrying out iterative updating on the positions of the simulated centroid points according to the position information of each power communication node: for the nth iteration, according to the coordinates of the nth power communication nodeTo a distance ofThe position of the more recent simulated centroid point is updated:
wherein,representing the distance after the nth iterationMore recent firstSimulating the location of centroid points, whereinWhen the first simulated centroid point is apartIn the more recent time that it is, the more,the method comprises the steps of carrying out a first treatment on the surface of the Otherwise；Represents the nth-1 th iterationThe location of the centroid point is simulated,representing a sign function, and obtaining corresponding values of 1, -1 or 0 according to positive and negative signs or zero of parameters in the function;representing a preset maximum iterative adjustment distance, wherein;
Updating the position of the other simulated centroid point correspondingly:whereinWhereinRepresenting a set non-operation;
recording the positions of the first simulation centroid point and the second simulation centroid point after finishing the maximum iteration number updating、；
Respectively obtaining the distance between each power communication node and two simulated centroid points、Wherein、Respectively representing the distances from each ith power communication node to the first simulation centroid point and the second simulation centroid point; the obtained distance information is returned to the corresponding power communication node;
each power communication node calculates own performance feedback according to the distance information returned by the upper computer:
wherein,a performance feedback value representing an ith power communication node;representing a transmission capability value of an ith power communication node, wherein, Representing a data transmission rate of the ith power communication node;representing a set standard data transmission rate;the packet loss rate of the ith power communication node is represented;indicating the set standard packet loss rate；Representing a location capability value of an ith power communication node, whereinWherein、Respectively represent distances from the ith power communication node to the first and second simulated centroid points respectively,representing compensation factors, where；Representing an empirical capability value of the ith power communication node,wherein the empirical capability value is determined based on performance of the power communication node as a base station unit before, the higher the accuracy of data transmission and state analysis is when the power communication node is as a historical base station node, the higher the empirical capability value is when the power communication node is as a historical base station unitIs a standard empirical capability value (e.g., 0.7,0.8,0.9, etc.);、、respectively normalized weight factors, which adjust the range of each capability value to be uniformAn index level;
according to the obtained performance feedback values, each power communication node broadcasts the performance feedback values to other power communication nodes in the local area, the performance feedback values of the power communication nodes are counted, and the two power communication nodes with the maximum performance indexes are respectively assigned as a first base station unit and a second base station unit.
In order to further improve the reliability of data acquisition of the base station unit to the power communication node on the basis of the dual base station mode, the above embodiment of the present invention particularly proposes a technical scheme for setting assignment of the dual base station unit. According to the specific positions of the power communication nodes in actual conditions, the position information of each power communication node is counted in a mode of establishing a simulation coordinate system, and the optimal positions of the double base station units can be accurately analyzed by carrying out iterative operation of optimal simulation centroid points based on the position information of each node, wherein in the process of updating and iterating the simulation centroid points, the limitation of random initial positions and maximum adjustment distances is particularly added, the positions of the two simulation centroid points are adjusted in a matched mode, and the global adaptability of the positions of the simulation centroid points is improved. Meanwhile, based on the calculated simulated centroid point position information, each power communication node calculates a performance feedback value of the power communication node, wherein a performance feedback value calculation function is provided, and the power communication node can be comprehensively evaluated by integrating the transmission performance, the position performance and the experience performance of the power communication node, so that the power communication node with the optimal performance is selected as a base station unit; by the arrangement of the double base station units, the two base station units can be facilitated to realize mutual interaction and cooperation, the integral distance from the power communication nodes to the base station units is reduced, and the reliability and the integral performance of global data transmission of each power communication node in a local area are improved. The reliability of fault analysis of communication monitoring data acquired by the power communication node through the base station unit is indirectly improved.
After the assignment of the base station unit is completed, a corresponding data processing module (node state analysis unit) is further arranged in the corresponding power communication node so as to complete the task of fault analysis of the communication monitoring data obtained by the base station node unit and each power communication node in the local area.
In another embodiment, in order to cope with a case where the power communication nodes are periodically updated and assigned, a node state analysis unit is provided in each power communication node in advance to cope with a data processing task after being assigned as a base station unit.
Preferably, the cloud platform comprises a region fault analysis unit;
the regional fault analysis unit is used for combining the regional node state feature vectors according to the fault analysis results of all the power communication nodes in the preset local region, inputting the regional node state feature vectors into a preset regional fault analysis model according to the obtained node state feature vectors, and analyzing the input regional node state feature vectors by the regional fault analysis model to obtain regional fault analysis results, wherein the regional fault analysis results comprise whether faults occur or not and the fault types.
Regional fault analysis is comprehensively carried out according to the fault analysis results of all the power communication nodes by arranging a regional fault analysis unit in the cloud platform, so that the power communication network faults in the local region can be further mined based on the fault conditions of all the power communication nodes and the relevance among the fault nodes, and the intelligent level of the power communication network fault diagnosis can be improved.
Preferably, the area fault analysis model is built based on a convolutional neural network, wherein the convolutional neural network comprises an input layer, a convolutional layer, a first Dropout layer, a first pooling layer, an attention mechanism module, an acceptance layer, a second Dropout layer, a second pooling layer, a full-connection layer and an output layer which are sequentially connected; the method comprises the steps that an area node state feature vector is input by an input layer, an activation function adopted by a convolution layer is a Sigmiod function, and a first Dropout layer carries out random elimination on parameters obtained by the first convolution layer; the first pooling layer adopts maximum pooling operation; the attention mechanism further extracts high-dimensional feature information, and gives a larger weight to important features to obtain a new feature matrix; the acceptance layer consists of 3 convolution layers, the first convolution layer adopts a size of，，The convolution kernel of (1) performs multi-scale network fault feature extraction, wherein the number of channels is 16, 8 and 8 respectively; the second convolution layer adoptsAndmulti-scale features are extracted by the convolution kernel of (1), wherein the number of channels is 16 and 16 respectively; the third convolution layer adopts 2The convolution kernel of (2) extracts multi-scale features, and the channel numbers are respectively 32 and 16; the second Dropout layer carries out random elimination on parameters obtained by the acceptance layer, and the second pooling layer adopts maximum pooling operation; the full-connection layer converts the obtained feature data into one-dimensional feature vectors, and the output layer classifies and identifies the obtained one-dimensional feature vectors based on a softmax classifier to obtain corresponding region fault analysis results.
The multi-scale feature extraction structure of the acceptance layer can effectively increase the network width and promote the richness of feature extraction.
Preferably, the cloud platform further comprises a global fault analysis unit;
the global fault analysis unit is used for forming a global state feature vector according to fault analysis results of all the power communication nodes in the whole area, inputting the global state feature vector into a preset global fault analysis model according to the obtained global state feature vector, and carrying out fault analysis on the global state feature vector by the global fault analysis model to obtain a global fault analysis result, wherein the global fault analysis result comprises whether a fault occurs, a fault area and a fault type.
Furthermore, a global state feature vector is constructed by combining fault analysis results of all the power communication nodes, global fault analysis is carried out on the large-scale communication network based on the global state feature vector, and the method is beneficial to obtaining a power communication network fault diagnosis result with pertinence and integrity and improves the intelligent level of the system.
Preferably, the cloud platform further comprises a database module;
the database module is used for classifying, storing and managing the acquired power communication node fault analysis results of all the power communication nodes in the whole area, and constructing a power communication node fault analysis database.
Preferably, the cloud platform further comprises a visualization module;
the visualization module is used for integrating the fault analysis results of all the power communication nodes, the local area fault analysis results and the whole area fault analysis results obtained in the whole area into a large screen display template for visual display.
It should be noted that, in each embodiment of the present invention, each functional unit/module may be integrated in one processing unit/module, or each unit/module may exist alone physically, or two or more units/modules may be integrated in one unit/module. The integrated units/modules described above may be implemented either in hardware or in software functional units/modules.
From the description of the embodiments above, it will be apparent to those skilled in the art that the embodiments described herein may be implemented in hardware, software, firmware, middleware, code, or any suitable combination thereof. For a hardware implementation, the processor may be implemented in one or more of the following units: an Application Specific Integrated Circuit (ASIC), a Digital Signal Processor (DSP), a Digital Signal Processing Device (DSPD), a Programmable Logic Device (PLD), a Field Programmable Gate Array (FPGA), a processor, a controller, a microcontroller, a microprocessor, other electronic units designed to perform the functions described herein, or a combination thereof. For a software implementation, some or all of the flow of an embodiment may be accomplished by a computer program to instruct the associated hardware. When implemented, the above-described programs may be stored in or transmitted as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a computer. The computer readable media can include, but is not limited to, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, 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.
Finally, it should be noted that the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the scope of the present invention, and although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solution of the present invention without departing from the spirit and scope of the technical solution of the present invention.
Claims (7)
1. The fault diagnosis system for the large-scale power communication network is characterized by comprising a local monitoring module and a cloud platform; wherein,
the local monitoring module is used for acquiring communication monitoring data of the power communication nodes in the power communication network in real time, analyzing node communication states according to the acquired communication monitoring data, obtaining a power communication node fault analysis result, and transmitting the power communication node fault analysis result to the cloud platform;
the local monitoring module comprises a first base station unit and a second base station unit; wherein a data communication connection is established between the first base station unit and the second base station unit;
the first base station unit and the second base station unit are respectively connected with all power communication nodes in the same local area, and respectively acquire and collect communication monitoring data of all power communication nodes in the same local area;
the first base station unit and the second base station unit respectively perform node communication state analysis according to the acquired communication monitoring data to obtain fault analysis results of all power communication nodes; sharing the obtained power communication node fault analysis result;
the first base station unit or the second base station unit integrates according to the fault analysis result of the shared power communication node, and when the first base station unit and the second base station unit analyze and judge that the same power communication node has a communication fault at the same time, the power communication node is marked to have a fault; otherwise, when the first base station unit or the second base station unit analyzes and judges that the failure analysis result of the power communication node is normal, marking that the failure analysis result of the power communication node is normal; transmitting the fault analysis result of the integrated power communication node to a cloud platform;
the cloud platform is used for carrying out regional state analysis based on the failure analysis results of the plurality of power communication nodes in the designated region to obtain regional failure analysis results.
2. The fault diagnosis system for a large power communication network according to claim 1, wherein the first base station unit and the second base station unit include a data acquisition unit and a node state analysis unit, respectively;
the data acquisition unit is respectively connected with the power communication nodes in the designated area to acquire communication monitoring data of the power communication nodes;
the node state analysis unit is used for carrying out node communication state analysis according to the communication monitoring data of the power communication nodes to obtain power communication node fault analysis results, and transmitting the power communication node fault analysis results to the cloud platform.
3. The fault diagnosis system for large power communication network according to claim 1, wherein the arrangement of the first base station unit and the second base station unit specifically comprises:
dividing a plurality of local power communication nodes in the same area into a local area according to the designated number of power communication nodes;
for the case of setting base station units individually in a local area, the first base station units and the second base station units are set uniformly distributed in the local area, and the first base station units and the second base station units are respectively established with power communication in the local area to respectively acquire communication monitoring data of the power communication nodes.
4. The large power communication network fault diagnosis system according to claim 1, wherein the cloud platform comprises a regional fault analysis unit;
the regional fault analysis unit is used for combining the regional node state feature vectors according to the fault analysis results of all the power communication nodes in the preset local region, inputting the regional node state feature vectors into a preset regional fault analysis model according to the obtained node state feature vectors, and analyzing the input regional node state feature vectors by the regional fault analysis model to obtain regional fault analysis results, wherein the regional fault analysis results comprise whether faults occur or not and the fault types.
5. The large power communication network fault diagnosis system according to claim 4, wherein the cloud platform further comprises a global fault analysis unit;
the global fault analysis unit is used for forming a global state characteristic vector according to fault analysis results of all power communication nodes in the whole area, inputting the global state characteristic vector into a preset global fault analysis model according to the obtained global state characteristic vector, and carrying out fault analysis on the global state characteristic vector by the global fault analysis model to obtain a global fault analysis result, wherein the global fault analysis result comprises whether a fault occurs, a fault area and a fault type.
6. The large power communication network fault diagnosis system of claim 4, wherein the cloud platform further comprises a database module;
the database module is used for classifying, storing and managing the obtained fault analysis results of all the power communication nodes in the whole area and constructing a power communication node fault analysis database.
7. The large power communication network fault diagnosis system of claim 4, wherein the cloud platform further comprises a visualization module;
the visualization module is used for integrating the fault analysis results of all the power communication nodes, the local area fault analysis results and the whole area fault analysis results obtained in the whole area into a large screen display template for visual display.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2022100723A1 (en) * | 2020-11-13 | 2022-05-19 | 中兴通讯股份有限公司 | Network fault diagnosis method and apparatus, and computer device and readable medium |
| CN115460647A (en) * | 2022-10-21 | 2022-12-09 | 北京中电飞华通信有限公司 | Internet of things fault positioning method and system based on eSIM card and 5G base station |
| CN116131453A (en) * | 2023-01-08 | 2023-05-16 | 国网辽宁省电力有限公司丹东供电公司 | Accurate positioning and inquiring system for power communication faults |
| CN116684256A (en) * | 2023-08-01 | 2023-09-01 | 苏州浪潮智能科技有限公司 | Node fault monitoring method, device and system, electronic equipment and storage medium |
| CN117169652A (en) * | 2023-09-07 | 2023-12-05 | 湖南科技学院 | Distribution network fault detection positioning system based on artificial intelligence |
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2022100723A1 (en) * | 2020-11-13 | 2022-05-19 | 中兴通讯股份有限公司 | Network fault diagnosis method and apparatus, and computer device and readable medium |
| CN115460647A (en) * | 2022-10-21 | 2022-12-09 | 北京中电飞华通信有限公司 | Internet of things fault positioning method and system based on eSIM card and 5G base station |
| CN116131453A (en) * | 2023-01-08 | 2023-05-16 | 国网辽宁省电力有限公司丹东供电公司 | Accurate positioning and inquiring system for power communication faults |
| CN116684256A (en) * | 2023-08-01 | 2023-09-01 | 苏州浪潮智能科技有限公司 | Node fault monitoring method, device and system, electronic equipment and storage medium |
| CN117169652A (en) * | 2023-09-07 | 2023-12-05 | 湖南科技学院 | Distribution network fault detection positioning system based on artificial intelligence |
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