Urban power distribution network fault diagnosis system based on big data

Abstract

The invention discloses a big data-based urban power distribution network fault diagnosis system, which belongs to the technical field of urban power distribution networks and comprises an information acquisition module, a data processing module, a fault diagnosis module, an intelligent management and control module and a data storage module. According to the method, the problem that the urban power distribution network management effect is poor due to the fact that faults of an existing urban power distribution network cannot be diagnosed in time when the existing urban power distribution network distributes power to power utilization equipment of power consumers is solved; and processing the big data-based urban power distribution network information collected in real time, determining urban power distribution network characteristic data, performing fault diagnosis on the urban power distribution network characteristic data, determining an urban power distribution network fault diagnosis result, and formulating an urban power distribution network intelligent management and control method. The urban power distribution network is intelligently managed and controlled based on the urban power distribution network intelligent management and control method, faults of the urban power distribution network can be diagnosed in time, and the urban power distribution network management effect can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of urban distribution network, and in particular to an urban distribution network fault diagnosis system based on big data. Background Art

[0002] A distribution network refers to an electric power grid that receives electric energy from a transmission network or a regional power plant and distributes it locally or step by step according to voltage to various types of users through distribution facilities. It is a network composed of overhead lines, cables, towers, distribution transformers, disconnectors, reactive power compensators and some ancillary facilities, and plays an important role in distributing electric energy in the power grid.

[0003] Among them, when the urban distribution network distributes electricity to the power users' electrical equipment, its urban distribution network faults cannot be diagnosed in time, resulting in poor management of the urban distribution network. Summary of the invention

[0004] The purpose of the present invention is to provide a large-data-based urban distribution network fault diagnosis system, which can timely diagnose urban distribution network faults, improve the management effect of urban distribution networks, and solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] The urban distribution network fault diagnosis system based on big data includes:

[0007] Information collection module, used to collect urban distribution network information based on big data in real time;

[0008] The data processing module is used to process the urban distribution network information based on big data collected in real time and determine the characteristic data of the urban distribution network;

[0009] A fault diagnosis module is used to perform fault diagnosis on characteristic data of the urban distribution network and determine the fault diagnosis result of the urban distribution network;

[0010] An intelligent control module, which is used to formulate an intelligent control method for urban distribution networks, and to intelligently control urban distribution networks based on the intelligent control method for urban distribution networks;

[0011] The data storage module is used to store real-time collected urban distribution network information based on big data and urban distribution network standard data, providing a reference basis for urban distribution network fault diagnosis.

[0012] Preferably, the information collection module includes:

[0013] Online monitoring equipment is used to conduct real-time online monitoring of the power users' power equipment in operation, and automatically obtain the real-time grid data of the power users' power equipment;

[0014] The GPS positioning unit is used to detect the real-time location of the power user's electrical equipment in operation and automatically obtain the grid location data of the power user's electrical equipment;

[0015] A user input unit is used to input user information of power users of power-consuming equipment in operation and obtain power user data in real time;

[0016] Based on the acquired real-time grid data, grid location data and power user data, the urban distribution network information based on big data is determined.

[0017] Preferably, the data processing module includes:

[0018] A data retrieval unit, used to retrieve urban distribution network information based on big data;

[0019] Obtaining urban distribution network information based on big data, and searching the urban distribution network information based on big data one by one based on a sequential retrieval method;

[0020] Filter out duplicate, missing and worthless urban distribution network information included in the urban distribution network information, and determine the urban distribution network information that is valuable for urban distribution network fault diagnosis;

[0021] A data grouping unit, used for grouping the retrieved urban distribution network information;

[0022] Obtain urban distribution network information that is valuable for urban distribution network fault diagnosis, and group the urban distribution network information in a unified manner based on the principle of mutual exclusivity;

[0023] Urban distribution network information groups with different attribute types are determined, and urban distribution network information with the same attribute type is stored in each group.

[0024] Preferably, the data processing module further includes:

[0025] A data sorting unit, used to sort the grouped urban distribution network information;

[0026] Acquire urban distribution network information groups with different attribute types, sort the urban distribution network information with the same attribute type stored in each group based on an internal sorting method, and determine the urban distribution network information with a certain sorting order;

[0027] A feature extraction unit, used for extracting features from the sorted urban distribution network information;

[0028] The urban distribution network information with a certain arrangement order is obtained, and the features of the urban distribution network information are extracted to determine the characteristic data of the urban distribution network.

[0029] Preferably, the fault diagnosis module includes:

[0030] A data indexing unit, used to index the stored standard data of urban distribution networks;

[0031] Acquire characteristic data of the urban distribution network, and based on the characteristic data of the urban distribution network, index pre-stored standard data of the urban distribution network that matches the characteristic data of the urban distribution network and is used for fault diagnosis of the urban distribution network from the data storage module;

[0032] A data extraction unit, used to extract the stored standard data of the urban distribution network;

[0033] The indexed standard data of the urban distribution network is obtained, and the indexed standard data of the urban distribution network is extracted.

[0034] Preferably, the fault diagnosis module further includes:

[0035] A data comparison unit, used to compare characteristic data of urban distribution networks;

[0036] Acquire characteristic data of urban distribution networks and standard data of urban distribution networks, compare the characteristic data of urban distribution networks based on the standard data of urban distribution networks, and determine the comparison results of urban distribution networks;

[0037] Analysis and evaluation unit, used to analyze and evaluate the comparison results of urban distribution networks;

[0038] Obtain the comparison results of urban distribution networks, conduct in-depth mining and analysis on the comparison results of urban distribution networks based on data mining technology, and determine the fault diagnosis results of urban distribution networks.

[0039] Preferably, based on the standard data of the urban distribution network, the characteristic data of the urban distribution network is compared, and the following operations are performed:

[0040] Obtain the characteristic data of urban distribution network, denoted as E t ;

[0041] Obtain standard data of urban distribution network, denoted as E b ;

[0042] Based on the standard data of urban distribution networks, the characteristic data of urban distribution networks are compared to determine the comparison results of urban distribution networks;

[0043] For E t <E b If the comparison result of the urban distribution network is determined, the characteristic data of the urban distribution network is within the standard data range of the urban distribution network;

[0044] For E t ≥E bIf the situation is that the comparison result of the urban distribution network is determined to be that the characteristic data of the urban distribution network is not within the standard data range of the urban distribution network.

[0045] Preferably, the comparison result of the urban distribution network is obtained, and the fault diagnosis result of the urban distribution network is determined, and the following operations are performed:

[0046] Obtain comparison results of urban distribution networks;

[0047] Based on data mining technology, the comparison results of urban distribution networks are deeply mined and analyzed to determine the fault diagnosis results of urban distribution networks;

[0048] In the case where the characteristic data of the urban distribution network is within the standard data range of the urban distribution network, the urban distribution network fault diagnosis result determined is that there is no fault in the urban distribution network;

[0049] In case that the characteristic data of the urban distribution network is not within the standard data range of the urban distribution network, the urban distribution network fault diagnosis result determined is that there is a fault in the urban distribution network.

[0050] Preferably, the intelligent management and control module includes:

[0051] A control formulation unit, used to formulate intelligent control methods for urban distribution networks;

[0052] Obtain the fault diagnosis results of urban distribution networks, conduct in-depth mining and analysis on the fault diagnosis results of urban distribution networks based on data mining technology, and determine the intelligent management and control methods of urban distribution networks;

[0053] Intelligent management and control unit, used for intelligent management and control of urban distribution networks;

[0054] Acquire the intelligent control method of urban distribution network, and intelligently control the urban distribution network based on the intelligent control method of urban distribution network;

[0055] Among them, when intelligently controlling the urban distribution network, the following operations are performed:

[0056] In the case that there is no fault in the urban distribution network, the intelligent management and control method of the urban distribution network is to continuously monitor the urban distribution network, monitor and diagnose the urban distribution network fault in real time;

[0057] In the event of a fault in the urban distribution network, the intelligent management and control method of the urban distribution network is to find the location of the power equipment of the power user where the fault occurs in real time, and transmit the location to the management terminal in real time. Based on the management terminal, the fault information is transmitted to the urban distribution network management personnel, and the urban distribution network management personnel are guided to the fault site for maintenance.

[0058] Preferably, the data storage module includes:

[0059] A real-time storage unit is used to store real-time collected urban distribution network information based on big data, providing favorable support for subsequent viewing of urban distribution network information;

[0060] The reference storage unit is used to store standard data of urban distribution networks and provide a reference basis for comparative analysis of characteristic data of urban distribution networks.

[0061] Compared with the prior art, the present invention has the following beneficial effects:

[0062] The present invention collects urban distribution network information based on big data in real time, processes the urban distribution network information based on big data collected in real time, determines characteristic data of the urban distribution network, diagnoses faults on the characteristic data of the urban distribution network, determines the diagnosis results of the urban distribution network faults, and formulates an intelligent management and control method for the urban distribution network. The urban distribution network is intelligently managed based on the intelligent management and control method for the urban distribution network, and the urban distribution network can be promptly diagnosed for faults in the urban distribution network, thereby improving the management effect of the urban distribution network. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 This is a module schematic diagram of the urban distribution network fault diagnosis system based on big data of the present invention;

[0064] Figure 2 This is an algorithm flow chart of the urban distribution network fault diagnosis system based on big data of the present invention. DETAILED DESCRIPTION

[0065] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0066] In order to solve the problem that the failure of the existing urban distribution network cannot be diagnosed in time when distributing electricity to the power users' electrical equipment, resulting in poor management of the urban distribution network, please refer to Figure 1-Figure 2 , this embodiment provides the following technical solutions:

[0067] The urban distribution network fault diagnosis system based on big data includes:

[0068] Information collection module, used to collect urban distribution network information based on big data in real time;

[0069] In this embodiment, as the preferred technical solution of this embodiment, the information collection module includes:

[0070] Online monitoring equipment is used to conduct real-time online monitoring of the power users' power equipment in operation, and automatically obtain the real-time grid data of the power users' power equipment;

[0071] The GPS positioning unit is used to detect the real-time location of the power user's electrical equipment in operation and automatically obtain the grid location data of the power user's electrical equipment;

[0072] A user input unit is used to input user information of power users of power-consuming equipment in operation and obtain power user data in real time;

[0073] Among them, based on the acquired real-time power grid data, power grid location data and power user data, the urban distribution network information based on big data is determined.

[0074] The data processing module is used to process the urban distribution network information based on big data collected in real time and determine the characteristic data of the urban distribution network;

[0075] In this embodiment, as the preferred technical solution of this embodiment, the data processing module includes:

[0076] A data retrieval unit, used to retrieve urban distribution network information based on big data;

[0077] Obtaining urban distribution network information based on big data, and searching the urban distribution network information based on big data one by one based on a sequential retrieval method;

[0078] Filter out duplicate, missing and worthless urban distribution network information included in the urban distribution network information, and determine the urban distribution network information that is valuable for urban distribution network fault diagnosis;

[0079] A data grouping unit, used for grouping the retrieved urban distribution network information;

[0080] Obtain urban distribution network information that is valuable for urban distribution network fault diagnosis, and group the urban distribution network information in a unified manner based on the principle of mutual exclusivity;

[0081] Urban distribution network information groups with different attribute types are determined, and urban distribution network information with the same attribute type is stored in each group.

[0082] In this embodiment, as a preferred technical solution of this embodiment, the data processing module also includes:

[0083] A data sorting unit, used to sort the grouped urban distribution network information;

[0084] Acquire urban distribution network information groups with different attribute types, sort the urban distribution network information with the same attribute type stored in each group based on an internal sorting method, and determine the urban distribution network information with a certain sorting order;

[0085] A feature extraction unit, used for extracting features from the sorted urban distribution network information;

[0086] The urban distribution network information with a certain arrangement order is obtained, and the features of the urban distribution network information are extracted to determine the characteristic data of the urban distribution network.

[0087] A fault diagnosis module is used to perform fault diagnosis on characteristic data of the urban distribution network and determine the fault diagnosis result of the urban distribution network;

[0088] In this embodiment, as the preferred technical solution of this embodiment, the fault diagnosis module includes:

[0089] A data indexing unit, used to index the stored standard data of urban distribution networks;

[0090] Acquire characteristic data of the urban distribution network, and based on the characteristic data of the urban distribution network, index pre-stored standard data of the urban distribution network that matches the characteristic data of the urban distribution network and is used for fault diagnosis of the urban distribution network from the data storage module;

[0091] A data extraction unit, used to extract the stored standard data of the urban distribution network;

[0092] The indexed standard data of the urban distribution network is obtained, and the indexed standard data of the urban distribution network is extracted.

[0093] In this embodiment, as a preferred technical solution of this embodiment, the fault diagnosis module also includes:

[0094] A data comparison unit, used to compare characteristic data of urban distribution networks;

[0095] Acquire characteristic data of urban distribution networks and standard data of urban distribution networks, compare the characteristic data of urban distribution networks based on the standard data of urban distribution networks, and determine the comparison results of urban distribution networks;

[0096] Analysis and evaluation unit, used to analyze and evaluate the comparison results of urban distribution networks;

[0097] Obtain the comparison results of urban distribution networks, conduct in-depth mining and analysis on the comparison results of urban distribution networks based on data mining technology, and determine the fault diagnosis results of urban distribution networks.

[0098] In this embodiment, as the preferred technical solution of this embodiment, based on the standard data of the urban distribution network, the characteristic data of the urban distribution network is compared, and the following operations are performed:

[0099] Obtain the characteristic data of urban distribution network, denoted as E t ;

[0100] Obtain standard data of urban distribution network, denoted as E b ;

[0101] Based on the standard data of urban distribution networks, the characteristic data of urban distribution networks are compared to determine the comparison results of urban distribution networks;

[0102] For E t <E b If the comparison result of the urban distribution network is determined, the characteristic data of the urban distribution network is within the standard data range of the urban distribution network;

[0103] For E t ≥E b If the situation is that the comparison result of the urban distribution network is determined to be that the characteristic data of the urban distribution network is not within the standard data range of the urban distribution network.

[0104] In this embodiment, as the preferred technical solution of this embodiment, the comparison result of the urban distribution network is obtained, and the fault diagnosis result of the urban distribution network is determined, and the following operations are performed:

[0105] Obtain comparison results of urban distribution networks;

[0106] Based on data mining technology, the comparison results of urban distribution networks are deeply mined and analyzed to determine the fault diagnosis results of urban distribution networks;

[0107] In the case where the characteristic data of the urban distribution network is within the standard data range of the urban distribution network, the urban distribution network fault diagnosis result determined is that there is no fault in the urban distribution network;

[0108] In case that the characteristic data of the urban distribution network is not within the standard data range of the urban distribution network, the urban distribution network fault diagnosis result determined is that there is a fault in the urban distribution network.

[0109] An intelligent control module, which is used to formulate an intelligent control method for urban distribution networks, and to intelligently control urban distribution networks based on the intelligent control method for urban distribution networks;

[0110] In this embodiment, as the preferred technical solution of this embodiment, the intelligent management and control module includes:

[0111] A control formulation unit, used to formulate intelligent control methods for urban distribution networks;

[0112] Obtain the fault diagnosis results of urban distribution networks, conduct in-depth mining and analysis on the fault diagnosis results of urban distribution networks based on data mining technology, and determine the intelligent management and control methods of urban distribution networks;

[0113] Intelligent management and control unit, used for intelligent management and control of urban distribution networks;

[0114] Acquire the intelligent control method of urban distribution network, and intelligently control the urban distribution network based on the intelligent control method of urban distribution network;

[0115] Among them, when intelligently controlling the urban distribution network, the following operations are performed:

[0116] In the case that there is no fault in the urban distribution network, the intelligent management and control method of the urban distribution network is to continuously monitor the urban distribution network, monitor and diagnose the urban distribution network fault in real time;

[0117] In the event of a fault in the urban distribution network, the intelligent management and control method of the urban distribution network is to find the location of the power equipment of the power user where the fault occurs in real time, and transmit the location to the management terminal in real time. Based on the management terminal, the fault information is transmitted to the urban distribution network management personnel, and the urban distribution network management personnel are guided to the fault site for maintenance.

[0118] The data storage module is used to store real-time collected urban distribution network information based on big data and urban distribution network standard data, providing a reference basis for urban distribution network fault diagnosis.

[0119] In this embodiment, as a preferred technical solution of this embodiment, the data storage module includes:

[0120] A real-time storage unit is used to store real-time collected urban distribution network information based on big data, providing favorable support for subsequent viewing of urban distribution network information;

[0121] The reference storage unit is used to store standard data of urban distribution networks and provide a reference basis for comparative analysis of characteristic data of urban distribution networks.

[0122] It should be noted that when the urban distribution network fault diagnosis system is used to diagnose the urban distribution network fault, the urban distribution network fault diagnosis situation is shown in Table 1:

[0123] Table 1: Fault diagnosis of urban distribution network

[0124]

[0125] Therefore, the urban distribution network information based on big data is collected in real time, and the urban distribution network information based on big data collected in real time is processed to determine the characteristic data of the urban distribution network, perform fault diagnosis on the characteristic data of the urban distribution network, determine the fault diagnosis results of the urban distribution network, and formulate an intelligent management and control method for the urban distribution network. The urban distribution network can be intelligently managed based on the intelligent management and control method for the urban distribution network, so that the urban distribution network faults can be diagnosed in time, and the management effect of the urban distribution network can be improved.

[0126] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0127] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. The urban distribution network fault diagnosis system based on big data is characterized by: include: Information collection module, used to collect urban distribution network information based on big data in real time; The data processing module is used to process the urban distribution network information based on big data collected in real time and determine the characteristic data of the urban distribution network; A fault diagnosis module is used to perform fault diagnosis on characteristic data of the urban distribution network and determine the fault diagnosis result of the urban distribution network; An intelligent control module, which is used to formulate an intelligent control method for urban distribution networks, and to intelligently control urban distribution networks based on the intelligent control method for urban distribution networks; The data storage module is used to store real-time collected urban distribution network information based on big data and urban distribution network standard data, providing a reference basis for urban distribution network fault diagnosis.

2. The urban distribution network fault diagnosis system based on big data according to claim 1 is characterized in that: The information collection module includes: Online monitoring equipment is used to conduct real-time online monitoring of the power users' power equipment in operation, and automatically obtain the real-time grid data of the power users' power equipment; The GPS positioning unit is used to detect the real-time location of the power user's electrical equipment in operation and automatically obtain the grid location data of the power user's electrical equipment; A user input unit is used to input user information of power users of power-consuming equipment in operation and obtain power user data in real time; Based on the acquired real-time grid data, grid location data and power user data, the urban distribution network information based on big data is determined.

3. The urban distribution network fault diagnosis system based on big data according to claim 2 is characterized in that: The data processing module comprises: A data retrieval unit, used to retrieve urban distribution network information based on big data; Obtaining urban distribution network information based on big data, and searching the urban distribution network information based on big data one by one based on a sequential retrieval method; Filter out duplicate, missing and worthless urban distribution network information included in the urban distribution network information, and determine the urban distribution network information that is valuable for urban distribution network fault diagnosis; A data grouping unit, used for grouping the retrieved urban distribution network information; Obtain urban distribution network information that is valuable for urban distribution network fault diagnosis, and group the urban distribution network information in a unified manner based on the principle of mutual exclusivity; Urban distribution network information groups with different attribute types are determined, and urban distribution network information with the same attribute type is stored in each group.

4. The urban distribution network fault diagnosis system based on big data according to claim 3 is characterized in that: The data processing module also includes: A data sorting unit, used to sort the grouped urban distribution network information; Acquire urban distribution network information groups with different attribute types, sort the urban distribution network information with the same attribute type stored in each group based on an internal sorting method, and determine the urban distribution network information with a certain sorting order; A feature extraction unit, used for extracting features from the sorted urban distribution network information; The urban distribution network information with a certain arrangement order is obtained, and the features of the urban distribution network information are extracted to determine the characteristic data of the urban distribution network.

5. The urban distribution network fault diagnosis system based on big data according to claim 4 is characterized in that: The fault diagnosis module comprises: A data indexing unit, used to index the stored standard data of urban distribution networks; Acquire characteristic data of the urban distribution network, and based on the characteristic data of the urban distribution network, index pre-stored standard data of the urban distribution network that matches the characteristic data of the urban distribution network and is used for fault diagnosis of the urban distribution network from the data storage module; A data extraction unit, used to extract the stored standard data of the urban distribution network; The indexed standard data of the urban distribution network is obtained, and the indexed standard data of the urban distribution network is extracted.

6. The urban distribution network fault diagnosis system based on big data according to claim 5 is characterized in that: The fault diagnosis module also includes: A data comparison unit, used to compare characteristic data of urban distribution networks; Acquire characteristic data of urban distribution networks and standard data of urban distribution networks, compare the characteristic data of urban distribution networks based on the standard data of urban distribution networks, and determine the comparison results of urban distribution networks; Analysis and evaluation unit, used to analyze and evaluate the comparison results of urban distribution networks; Obtain the comparison results of urban distribution networks, conduct in-depth mining and analysis on the comparison results of urban distribution networks based on data mining technology, and determine the fault diagnosis results of urban distribution networks.

7. The urban distribution network fault diagnosis system based on big data according to claim 6 is characterized in that: Based on the standard data of urban distribution networks, the characteristic data of urban distribution networks are compared and the following operations are performed: Obtain the characteristic data of urban distribution network, denoted as E t ; Obtain standard data of urban distribution network, denoted as E b ; Based on the standard data of urban distribution networks, the characteristic data of urban distribution networks are compared to determine the comparison results of urban distribution networks; For E t <E b If the comparison result of the urban distribution network is determined, the characteristic data of the urban distribution network is within the standard data range of the urban distribution network; For E t ≥E b If the situation is that the comparison result of the urban distribution network is determined to be that the characteristic data of the urban distribution network is not within the standard data range of the urban distribution network.

8. The urban distribution network fault diagnosis system based on big data according to claim 7 is characterized in that: Obtain the comparison results of the urban distribution network, determine the fault diagnosis results of the urban distribution network, and perform the following operations: Obtain comparison results of urban distribution networks; Based on data mining technology, the comparison results of urban distribution networks are deeply mined and analyzed to determine the fault diagnosis results of urban distribution networks; In the case where the characteristic data of the urban distribution network is within the standard data range of the urban distribution network, the urban distribution network fault diagnosis result determined is that there is no fault in the urban distribution network; In case that the characteristic data of the urban distribution network is not within the standard data range of the urban distribution network, the urban distribution network fault diagnosis result determined is that there is a fault in the urban distribution network.

9. The urban distribution network fault diagnosis system based on big data according to claim 8 is characterized in that: The intelligent management and control module includes: A control formulation unit, used to formulate intelligent control methods for urban distribution networks; Obtain the fault diagnosis results of urban distribution networks, conduct in-depth mining and analysis on the fault diagnosis results of urban distribution networks based on data mining technology, and determine the intelligent management and control methods of urban distribution networks; Intelligent management and control unit, used for intelligent management and control of urban distribution networks; Acquire the intelligent control method of urban distribution network, and intelligently control the urban distribution network based on the intelligent control method of urban distribution network; Among them, when intelligently controlling the urban distribution network, the following operations are performed: In the case that there is no fault in the urban distribution network, the intelligent management and control method of the urban distribution network is to continuously monitor the urban distribution network, monitor and diagnose the urban distribution network fault in real time; In the event of a fault in the urban distribution network, the intelligent management and control method of the urban distribution network is to find the location of the power equipment of the power user where the fault occurs in real time, and transmit the location to the management terminal in real time. Based on the management terminal, the fault information is transmitted to the urban distribution network management personnel, and the urban distribution network management personnel are guided to the fault site for maintenance.

10. The urban distribution network fault diagnosis system based on big data according to claim 9 is characterized in that: The data storage module comprises: A real-time storage unit is used to store real-time collected urban distribution network information based on big data, providing favorable support for subsequent viewing of urban distribution network information; The reference storage unit is used to store standard data of urban distribution networks and provide a reference basis for comparative analysis of characteristic data of urban distribution networks.

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