Power distribution network fault detection method and device, equipment and storage medium

Abstract

The invention discloses a power distribution network fault detection method and device, equipment and a storage medium. The method comprises the following steps: acquiring parameter marking information of a monitoring device; the parameter marking information comprises function marking information, space coordinate marking information and monitoring number marking information; receiving monitoring data acquired by the monitoring device; when the monitoring data exceeds the corresponding safety working threshold value, marking the monitoring device as a fault node; obtaining the fault type of the power distribution network area monitored by the monitoring device from a fault response library according to the function mark information of the fault node; the fault response library at least comprises fault types; the fault type comprises function mark information. According to the technical scheme provided by the invention, the power distribution network fault detection efficiency can be improved.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical field of power distribution systems, and in particular to a distribution network fault detection method and apparatus, equipment, and storage medium. Background Art

[0002] The distribution network is composed of overhead lines, cables, towers, distribution transformers, disconnectors, reactive power compensators and some ancillary facilities. It is an important network in the power grid that distributes electric energy. In order to ensure the long-term stable operation of the distribution network, it is necessary to understand the working status of the distribution network in a timely manner, so as to facilitate timely and effective maintenance and adjustment of the distribution network. The existing working status monitoring methods mostly use various monitoring devices, such as sensors, to collect data, and then analyze whether the distribution network has a fault by analyzing the collected data.

[0003] Existing fault analysis methods often require manual analysis of data collected by sensors. Specifically, after the data is collected, it is necessary to analyze the specific fault based on the data and the distribution network scenario, which not only wastes manpower but also easily leads to analysis errors. Summary of the invention

[0004] The present invention provides a distribution network fault detection method and device, equipment, and storage medium to improve the efficiency and accuracy of distribution network fault analysis.

[0005] In a first aspect, an embodiment of the present invention provides a distribution network fault detection method, comprising:

[0006] Acquire parameter marking information of the monitoring device; the parameter marking information includes function marking information, space coordinate marking information and monitoring number marking information;

[0007] receiving monitoring data acquired by the monitoring device; and marking the monitoring device as a faulty node when the monitoring data exceeds a corresponding safe working threshold;

[0008] The fault type of the distribution network area monitored by the monitoring device is obtained from a fault response library according to the functional marking information of the fault node; the fault response library at least includes the fault type; the fault type contains the functional marking information.

[0009] In a second aspect, an embodiment of the present invention further provides a distribution network fault detection device, comprising:

[0010] A parameter tag acquisition unit, used to acquire parameter tag information of the monitoring device; the parameter tag information includes function tag information, space coordinate tag information and monitoring number tag information;

[0011] A fault node detection unit, configured to receive monitoring data acquired by the monitoring device; and to mark the monitoring device as a fault node when the monitoring data exceeds a corresponding safe working threshold;

[0012] A fault type determination unit is used to obtain the fault type of the distribution network area monitored by the monitoring device from a fault response library according to the functional marking information of the fault node; the fault response library at least includes the fault type; the fault type contains functional marking information.

[0013] In a third aspect, an embodiment of the present invention further provides a device, the device comprising:

[0014] one or more processors;

[0015] A storage device for storing one or more programs;

[0016] Camera, used to collect image and video data;

[0017] A display, used to display the fault type;

[0018] When the one or more programs are executed by the one or more processors, the one or more processors implement the distribution network fault detection method as described in any one of claims 1-7.

[0019] In a fourth aspect, an embodiment of the present invention further provides a storage medium comprising computer executable instructions, wherein the computer executable instructions, when executed by a computer processor, are used to execute the distribution network fault detection method as described in any one of claims 1-7.

[0020] The present invention performs parameter marking on monitoring devices to obtain function marking information, spatial coordinate marking information and monitoring number marking information of the monitoring devices when fault detection is performed on the distribution network. Then, the monitoring devices with abnormal monitoring data are detected by detecting the monitoring devices and used as fault nodes. And the function marking information of the fault node is compared with the function marking information of the fault type in the pre-stored fault response library to obtain the fault type of the distribution network area monitored by the monitoring device, so that the fault type of the distribution network can be determined without manual analysis, saving manpower waste and improving the efficiency of distribution network fault analysis. And because the parameter marking information includes function marking information, spatial coordinate marking information and monitoring number marking information at the same time, it is not easy to have the problem of fault analysis error caused by misremembering the fault node or function marking information, thereby improving the accuracy of fault analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 A flow chart of a distribution network fault detection method provided in Embodiment 1 of the present invention;

[0022] Figure 2 A flow chart of another distribution network fault detection method provided in Embodiment 1 of the present invention;

[0023] Figure 3 A flow chart of another distribution network fault detection method provided in Embodiment 1 of the present invention;

[0024] Figure 4 A schematic diagram of the structure of a distribution network fault detection device provided in Embodiment 2 of the present invention;

[0025] Figure 5 A schematic diagram of the structure of a device provided in Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0026] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.

[0027] Embodiment 1

[0028] Figure 1 This is a flow chart of a distribution network fault detection method provided in Embodiment 1 of the present invention. This embodiment is applicable to the case where fault detection of a distribution network is performed based on a monitoring device. The method can be performed by a distribution network fault detection device and specifically includes the following steps:

[0029] Step S101, obtaining parameter marking information of a monitoring device; the parameter marking information includes function marking information, space coordinate marking information and monitoring number marking information.

[0030] The steps and the terms in the steps are explained but not limited. Optionally, the monitoring device may include at least one of the following: a current sensor, a temperature sensor, and a voltage sensor; the monitoring data of the current sensor is the current value; the monitoring data of the temperature sensor is the temperature value; and the monitoring data of the voltage sensor is the voltage value.

[0031] The functional marking information is used to record the corresponding function of the monitoring device, that is, when the monitoring device is a current sensor, the functional marking information can be the current value measured in a certain distribution network area, and the preset current range of the distribution network area is known; the spatial coordinate marking information is used to record the spatial coordinates of the monitoring device in the distribution network; the monitoring number marking information is the unique number assigned to the monitoring device in the distribution network, so when the monitoring data obtained by the monitoring device is abnormal, the distribution network fault detection device can quickly lock the specific monitoring device.

[0032] Step S102: receiving monitoring data acquired by the monitoring device; and marking the monitoring device as a faulty node when the monitoring data exceeds a corresponding safe working threshold.

[0033] The safe working threshold of the monitoring data can be the rated working range of the distribution network area, or the safe working range set by the system. The specific value is set according to the power supply and equipment configuration of the distribution network area, and this embodiment does not limit this. When the monitoring data exceeds the corresponding safe working threshold, it is determined that the monitoring data is abnormal, and the monitoring device corresponding to the monitoring data is marked as a faulty node.

[0034] Step S103, obtaining the fault type of the distribution network area monitored by the monitoring device from the fault response library according to the functional tag information of the fault node; the fault response library at least includes the fault type; the fault type includes the functional tag information.

[0035] This embodiment can also pre-establish a fault response library, which is used to store common fault types of the distribution network, and each fault type is stored in accordance with its fault manifestation, that is, this embodiment uses functional tag information to present its functional manifestation on the monitoring device, so as to lock the specific fault type through the functional tag information of the monitoring device, and can also determine one or more abnormal monitoring devices through the fault type. It should be noted that a fault type may be caused by the abnormality of multiple monitoring devices, so the abnormal monitoring devices in this embodiment can be one or more.

[0036] Optionally, obtaining the fault type of the distribution network area monitored by the monitoring device from the fault response library according to the functional marking information of the fault node may include: obtaining multiple fault types containing functional marking information from the fault response library according to the functional marking information of at least one fault node; obtaining the fault type corresponding to the fault node as the fault type of the distribution network area monitored by the monitoring device through the Euclidean distance calculation formula;

[0037] Among them, the Euclidean distance calculation formula is:

[0038] d(x,y) is the Euclidean distance; n is a positive integer greater than 1; x is the functional labeling information of the fault node; y is the functional labeling information of the fault type; the coordinate of x in the n-dimensional space is x=(x1, x2, …, xn); the coordinate of y in the n-dimensional space is y=(y1, y2, …, xn).

[0039] The function tag information of several adjacent fault nodes is obtained, and several common fault types containing several function tag information are screened from the fault response library. Then, the fault type with the highest similarity to several fault nodes is calculated by the Euclidean distance method as the fault type corresponding to the distribution network area monitored by the fault node. Specifically, it is realized by converting the fault type and the function tag information of the fault node into points in n-dimensional space. In n-dimensional space, the coordinates of the fault node as a point in n-dimensional space are x=(x1, x2, ..., xn), and the coordinates of the fault type as a point in n-dimensional space are y=(y1, y2, ..., xn). The Euclidean distance calculation formula calculates the square root of the sum of the squares of the differences between two points in each dimension in n-dimensional space, that is, the straight-line distance between the two points. The smaller the distance, the higher the similarity between the fault node and the fault type. Based on this, the fault type with the highest similarity to the fault node is found as the fault type of the distribution network area monitored by the monitoring device. This embodiment realizes the timely positioning of distribution network faults through real-time comparison of monitoring data, providing convenient conditions for the operation and maintenance of the distribution network.

[0040] The present invention performs parameter marking on monitoring devices to obtain function marking information, spatial coordinate marking information and monitoring number marking information of the monitoring devices when fault detection is performed on the distribution network. Then, the monitoring devices with abnormal monitoring data are detected by detecting the monitoring devices and used as fault nodes. And the function marking information of the fault node is compared with the function marking information of the fault type in the pre-stored fault response library to obtain the fault type of the distribution network area monitored by the monitoring device, so that the fault type of the distribution network can be determined without manual analysis, saving manpower waste and improving the efficiency of distribution network fault analysis. And because the parameter marking information includes function marking information, spatial coordinate marking information and monitoring number marking information at the same time, it is not easy to have the problem of fault analysis error caused by misremembering the fault node or function marking information, thereby improving the accuracy of fault analysis.

[0041] Optionally, the fault response library may also include maintenance equipment and maintenance operations corresponding to the fault type; after obtaining the fault type of the distribution network area monitored by the monitoring device from the fault response library according to the functional mark of the fault node, it may also include: obtaining the corresponding maintenance equipment according to the fault type; obtaining the inventory information of the maintenance equipment within the set distance range of the fault node according to the spatial coordinate marking information and outputting it to the display device; obtaining the corresponding maintenance operation according to the fault type and outputting it to the display device. In addition to the functional marking information, the fault response library established in this embodiment may also include maintenance equipment and maintenance operations corresponding to the fault type. In this embodiment, on the basis of determining the corresponding fault type, the corresponding maintenance equipment can also be directly obtained, and the inventory information of the maintenance equipment within the set distance range of the fault node can be obtained according to the spatial coordinate marking information, so as to facilitate the operator to retrieve the maintenance equipment nearby and realize the timely response of the fault maintenance. In addition, the maintenance operation can also be directly output to provide step prompts to the maintenance personnel, improve the accuracy of maintenance, and avoid the possibility of maintenance errors.

[0042] This embodiment determines the equipment required for fault repair according to the fault type, obtains the inventory of repair equipment near the fault point, and calls the inventory of repair equipment to the fault node. Specifically, before calling the inventory of repair equipment to the fault point, the spatial coordinates of the power grid repair point are marked, and the cloud synchronization of the available repair equipment inventory of the power grid repair point is performed. After obtaining the center of gravity coordinates of several fault nodes, the repair equipment required for fault repair of the corresponding fault node is transported to the center of gravity coordinates. This embodiment can deliver the required equipment to the repair point in a timely and effective manner, shorten the maintenance time, and provide effective support for the timely recovery of the distribution network after a fault.

[0043] On the basis of the above embodiments, because the monitoring device may be exposed to the external environment or not in the external environment, especially for some monitoring devices exposed to the external environment, there is a situation where the data analysis is not accurate enough. This embodiment can also correct the monitoring data in combination with the actual situation and analyze the fault type again. Optionally, before obtaining the fault type of the distribution network area monitored by the monitoring device from the fault response library according to the functional marking information of the fault node, it also includes: judging whether the fault node is exposed to the external environment; if not, marking the fault node as a protection node; if so, marking the fault node as an exposed node, and obtaining the video data of the exposed node; if there are interference factors in the video data, correcting the monitoring data of the monitoring device according to the interference factors; and judging again whether the monitoring device is a fault node based on the corrected monitoring data; interference factors include natural interference types, animal interference types and human interference types. Figure 2 As shown, Figure 2 This is a flow chart of another distribution network fault detection method provided in Embodiment 1 of the present invention. The distribution network fault detection method in this embodiment specifically includes the following steps:

[0044] Step S201, obtaining parameter marking information of the monitoring device; the parameter marking information includes function marking information, space coordinate marking information and monitoring number marking information.

[0045] Step S202: receiving monitoring data acquired by the monitoring device; and marking the monitoring device as a faulty node when the monitoring data exceeds a corresponding safe working threshold.

[0046] Step S203, determine whether the faulty node is exposed to the external environment; if not, execute step S204; if yes, execute step S205;

[0047] Step S204: Mark the faulty node as a protection node, and execute step S206.

[0048] In this embodiment, the faulty nodes exposed to the external environment are called exposed nodes, and the faulty nodes not exposed to the external environment are called protected nodes. Among them, the exposed nodes are easily affected by the external environment and affect the accuracy of the monitoring data output, so there are errors in their determination of the faulty nodes, and the monitoring data needs to be corrected and re-determined whether it is a faulty node. The protected nodes are not affected by the external environment and do not affect the accuracy of the monitoring data. The fault type can be directly determined based on the faulty nodes.

[0049] Step S205, marking the faulty node as an exposed node, and obtaining video data of the exposed node; if there are interference factors in the video data, correcting the monitoring data of the monitoring device according to the interference factors; and judging again whether the monitoring device is a faulty node according to the corrected monitoring data.

[0050] Interference factors include natural interference types, animal interference types, and human interference types. Each monitoring device in the distribution network is located within the irradiation range of the monitoring camera. The computer or controller extracts the frame image from the video screen of the camera, and then uses the edge detection algorithm to detect the boundary information in the frame image to identify the outline and shape of the object as the identification feature. That is, the present embodiment can extract interference factors from the video screen. Optionally, in order to further quickly extract interference factors, a known external factor feature library can be established, and the image recognition features can be matched with the external factor feature library to identify whether these interference factors appear in the video screen. For natural interference types (such as wind, rain, haze, etc.), features such as texture and color in the image can be extracted for identification. For animal interference types (such as birds, insects, etc.), features such as shape, size, and motion trajectory in the image can be extracted for identification. For human interference types (such as occlusion, destruction, etc.), features such as edge changes and color anomalies in the image can be extracted for identification. When the interference type affects the fault node, the monitoring data is corrected according to the degree of influence, and the corrected data is used as real-time monitoring data.

[0051] Step S206: acquiring the fault type of the distribution network area monitored by the monitoring device from the fault response library according to the functional tag information of the fault node; the fault response library at least includes the fault type; and the fault type includes the functional tag information.

[0052] In this embodiment, by marking whether the monitoring device is exposed, and then automatically comparing the monitoring data with the safety working threshold, the monitoring data is corrected after considering the impact of the external environment on the exposed node, and combined with the fault response library to achieve accurate judgment of the fault type, real-time and accurate monitoring of the distribution network is achieved.

[0053] It can be seen that all external factors that do not enter the video image of the monitoring device are interference factors. For example, if a bird flies by but the bird does not approach the monitoring device, the bird is not an interference factor. Only when the bird approaches the monitoring device will it be considered as an interference factor, and the monitoring data is corrected accordingly. Optionally, if there are interference factors in the video data, the monitoring data of the monitoring device is corrected according to the interference factors, which may include: if there are external factors in the video data, determine whether the external factors interfere with the working environment of the monitoring device; external factors include natural external factors, animal external factors and human external factors; if not, do not correct the monitoring data of the monitoring device; if so, mark the external factors as interference factors, and correct the monitoring data of the monitoring device according to the interference factors. Figure 3 As shown, Figure 3 This is a flow chart of another distribution network fault detection method provided in Embodiment 1 of the present invention. The distribution network fault detection method in this embodiment specifically includes the following steps:

[0054] Step S301, obtaining parameter marking information of the monitoring device; the parameter marking information includes function marking information, space coordinate marking information and monitoring number marking information.

[0055] Step S302: receiving monitoring data acquired by the monitoring device; and marking the monitoring device as a faulty node when the monitoring data exceeds a corresponding safe working threshold.

[0056] Step S303, determine whether the faulty node is exposed to the external environment; if not, execute step S304; if yes, execute step S305;

[0057] Step S304: Mark the faulty node as a protection node, and execute step S309.

[0058] Step S305: Mark the faulty node as a bare node, and obtain video data of the bare node.

[0059] Step S306, determine whether there are external factors in the video data; if so, execute step S307; if not, execute step S309.

[0060] Step S307, determine whether external factors interfere with the working environment of the monitoring device; external factors include natural external factors, animal external factors and human external factors; if so, execute step S308; if not, execute step S309.

[0061] Step S308: Mark the external factor as an interference factor, and correct the monitoring data of the monitoring device according to the interference factor; and determine again whether the monitoring device is a faulty node according to the corrected monitoring data.

[0062] Optionally, judging whether external factors interfere with the working environment of the monitoring device may include: if the external factor is a natural external factor, then determining that the external factor interferes with the working environment of the monitoring device when the ambient temperature of the monitoring device exceeds the rated operating temperature range; if the external factor is an animal external factor, then determining that the external factor interferes with the working environment of the monitoring device when there is an overlapping portion between the animal contour and the monitoring device; if the external factor is a human external factor, then determining that the external factor interferes with the working environment of the monitoring device when there is an overlapping portion between the human body contour and the monitoring device.

[0063] The monitoring devices used for distribution network node detection will have suitable working environment information after they are produced, and unsuitable working environment information is the environment information with interference. When there is natural interference, for example, if the monitoring device has normal working temperature information, when it exceeds the normal working temperature, it will interfere with the monitoring data of the monitoring device; for example, for animal external factors, when birds and insects overlap with the contours of the monitoring device, it is determined that animal interference occurs; for example, for human external factors, when it is identified that the human body movement trajectory overlaps with the monitoring device, it is determined that human interference occurs.

[0064] Optionally, the monitoring data of the monitoring device is corrected according to the interference factor, including: if the interference factor is a natural interference type, adjusting the temperature, humidity and wind speed of the working environment of the monitoring device according to the current meteorological information, and obtaining experimental monitoring data in the working environment; and using the experimental detection data as the corrected monitoring data; if the interference factor is an animal interference type, deleting the real-time monitoring data of the first time period where the animal outline and the monitoring device overlap, and forming fill data to the first time period through the difference method; the fill data is used as the corrected monitoring data; if the interference factor is a human interference type, deleting the real-time monitoring data of the second time period where the human body outline and the monitoring device overlap, and forming fill data to the second time period through the difference method; the fill data is used as the corrected monitoring data.

[0065] When the interference factor is a natural interference type: according to the meteorological information, the monitoring data is corrected for temperature, humidity and wind speed environmental factors, that is, the natural interference is removed to obtain the monitoring data, so as to obtain accurate monitoring data; when the interference factor is an animal interference type, the inaccurate monitoring data due to the interference is directly removed, and the removed monitoring data is refilled by interpolation. For example, the monitoring data points before the interference occurs can be connected with the monitoring data points after the interference occurs through a straight line or a smooth curve to form filling data, and the filling data is used as the basis for judging the subsequent fault nodes of the monitoring data; similarly, when the interference factor is a man-made interference type, the filling data can also be formed by the above interpolation method, or it can be: record the monitoring data in the second time period, and contact the interference maintenance personnel to negotiate the data correction. In this embodiment, the influence of external factors on the data monitored by the monitoring device is considered, and the fault diagnosis is performed after the monitoring data is corrected, so as to ensure the comprehensive, accurate and effective monitoring of the distribution network.

[0066] Step S309: acquiring the fault type of the distribution network area monitored by the monitoring device from the fault response library according to the functional tag information of the fault node; the fault response library at least includes the fault type; and the fault type includes the functional tag information.

[0067] This embodiment first determines whether there are external factors based on the video screen, and determines whether the external factors constitute interference factors, and determines the influence relationship between the interference type and the corresponding fault node, corrects the monitoring data according to the interference type, and uses the corrected data as real-time monitoring data to determine the fault node. This embodiment makes accurate judgments on interference factors, and makes targeted corrections based on the type of interference factors, further improving the accuracy of monitoring data and the accuracy of distribution network fault detection.

[0068] Embodiment 2

[0069] like Figure 4 As shown, Figure 4 A schematic diagram of the structure of a distribution network fault detection device provided in Embodiment 2 of the present invention, the distribution network fault detection device comprising:

[0070] The parameter tag acquisition unit 11 is used to acquire the parameter tag information of the monitoring device; the parameter tag information includes function tag information, space coordinate tag information and monitoring number tag information;

[0071] A fault node detection unit 12 is used to receive monitoring data acquired by the monitoring device; and when the monitoring data exceeds the corresponding safe working threshold, mark the monitoring device as a fault node;

[0072] The fault type determination unit 13 is used to obtain the fault type of the distribution network area monitored by the monitoring device from the fault response library according to the functional marking information of the fault node; the fault response library at least includes the fault type; the fault type includes the functional marking information.

[0073] The present invention performs parameter marking on monitoring devices to obtain function marking information, spatial coordinate marking information and monitoring number marking information of the monitoring devices when fault detection is performed on the distribution network. Then, the monitoring devices with abnormal monitoring data are detected by detecting the monitoring devices and used as fault nodes. And the function marking information of the fault node is compared with the function marking information of the fault type in the pre-stored fault response library to obtain the fault type of the distribution network area monitored by the monitoring device, so that the fault type of the distribution network can be determined without manual analysis, saving manpower waste and improving the efficiency of distribution network fault analysis. And because the parameter marking information includes function marking information, spatial coordinate marking information and monitoring number marking information at the same time, it is not easy to have the problem of fault analysis error caused by misremembering the fault node or function marking information, thereby improving the accuracy of fault analysis.

[0074] The distribution network fault detection device provided in the embodiment of the present invention can execute the distribution network fault detection method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0075] Embodiment 3

[0076] Figure 5 A schematic diagram of a device structure provided in Embodiment 3 of the present invention is shown in FIG. Figure 5 As shown, the device includes a processor 610, a memory 620, an input device 630, and an output device 640; the number of processors 610 in the device can be one or more. Figure 5 A processor 610 is taken as an example; the processor 610, memory 620, input device 630 and output device 640 in the device can be connected via a bus or other means. Figure 5 The example of connecting through bus is taken in the following.

[0077] The memory 620, as a computer-readable storage medium, can be used to store software programs, computer executable programs and modules, such as program instructions / modules corresponding to the distribution network fault detection method in the embodiment of the present invention (for example, the parameter tag acquisition unit 11, the fault node detection unit 12 and the fault type determination unit 13 in the distribution network fault detection device). The processor 610 executes various functional applications and data processing of the device by running the software programs, instructions and modules stored in the memory 620, that is, realizing the above-mentioned distribution network fault detection method.

[0078] The memory 620 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the terminal, etc. In addition, the memory 620 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some instances, the memory 620 may further include a memory remotely arranged relative to the processor 610, and these remote memories may be connected to the device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0079] The input device 630 may be used to receive input digital or character information and generate key signal input related to user settings and function control of the device. The output device 640 may include a display device such as a display screen.

[0080] Embodiment 4

[0081] Embodiment 4 of the present invention further provides a storage medium comprising computer executable instructions, wherein the computer executable instructions are used to execute a distribution network fault detection method when executed by a computer processor, the method comprising:

[0082] Acquire parameter marking information of the monitoring device; the parameter marking information includes function marking information, space coordinate marking information and monitoring number marking information;

[0083] receiving monitoring data acquired by the monitoring device; and marking the monitoring device as a faulty node when the monitoring data exceeds a corresponding safe working threshold;

[0084] The fault type of the distribution network area monitored by the monitoring device is obtained from a fault response library according to the functional marking information of the fault node; the fault response library at least includes the fault type; the fault type contains the functional marking information.

[0085] Of course, the storage medium containing computer executable instructions provided in an embodiment of the present invention, whose computer executable instructions are not limited to the method operations described above, can also execute related operations in the distribution network fault detection method provided in any embodiment of the present invention.

[0086] Through the above description of the implementation methods, the technicians in the relevant field can clearly understand that the present invention can be implemented by means of software and necessary general hardware, and of course it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory (FLASH), hard disk or optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, server, or network device, etc.) to execute the methods described in each embodiment of the present invention.

[0087] It is worth noting that in the embodiment of the above-mentioned search device, the various units and modules included are only divided according to functional logic, but are not limited to the above-mentioned division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of the present invention.

[0088] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A distribution network fault detection method, characterized in that: include: Acquire parameter marking information of the monitoring device; the parameter marking information includes function marking information, space coordinate marking information and monitoring number marking information; Receiving monitoring data acquired by the monitoring device; and marking the monitoring device as a faulty node when the monitoring data exceeds a corresponding safe working threshold; Acquire the fault type of the distribution network area monitored by the monitoring device from the fault response library according to the functional tag information of the fault node; The fault response library at least includes fault types; the fault types include function tag information.

2. The method for detecting distribution network faults according to claim 1, characterized in that: The fault response library also includes maintenance equipment and maintenance operations corresponding to the fault type; After obtaining the fault type of the distribution network area monitored by the monitoring device from the fault response library according to the functional tag of the fault node, the method further includes: Acquire the corresponding maintenance equipment according to the fault type; acquire the inventory information of the maintenance equipment within the set distance range of the fault node according to the spatial coordinate marking information and output it to the display device; The corresponding maintenance operation is obtained according to the fault type and output to a display device.

3. The method for detecting distribution network faults according to claim 1, characterized in that: Before acquiring the fault type of the distribution network area monitored by the monitoring device from the fault response library according to the functional tag information of the fault node, the method further includes: Determine whether the faulty node is exposed to the external environment; if not, mark the faulty node as a protection node; If so, the faulty node is marked as an exposed node, and the video data of the exposed node is obtained; if there are interference factors in the video data, the monitoring data of the monitoring device is corrected according to the interference factors; and based on the corrected monitoring data, it is determined again whether the monitoring device is a faulty node; the interference factors include natural interference types, animal interference types and human interference types.

4. The method for detecting distribution network faults according to claim 3, characterized in that: If there are interference factors in the video data, the monitoring data of the monitoring device is corrected according to the interference factors, including: If there are external factors in the video data, determine whether the external factors interfere with the working environment of the monitoring device; the external factors include natural external factors, animal external factors and human external factors; if not, do not correct the monitoring data of the monitoring device; If so, the external factor is marked as an interference factor, and the monitoring data of the monitoring device is corrected according to the interference factor.

5. The method for detecting distribution network faults according to claim 4, characterized in that: Determining whether the external factors interfere with the working environment of the monitoring device includes: If the external factor is a natural external factor, then when the ambient temperature of the monitoring device exceeds the rated operating temperature range, it is determined that the external factor interferes with the working environment of the monitoring device; If the external factor is an animal external factor, then when the animal outline overlaps with the monitoring device, it is determined that the external factor interferes with the working environment of the monitoring device; If the external factor is a human external factor, it is determined that the external factor interferes with the working environment of the monitoring device when the human body contour overlaps with the monitoring device; Correcting the monitoring data of the monitoring device according to the interference factor includes: If the interference factor is a natural interference type, the temperature, humidity and wind speed of the working environment of the monitoring device are adjusted according to the current meteorological information, and experimental monitoring data are obtained under the working environment; and the experimental detection data is used as the corrected monitoring data; If the interference factor is an animal interference type, the real-time monitoring data of the first time period where the animal outline and the monitoring device overlap is deleted, and fill-in data is formed to the first time period by using the difference method; the fill-in data is used as the corrected monitoring data; If the interference factor is of the human interference type, the real-time monitoring data of the second time period where the human body contour and the monitoring device overlap is deleted, and the filling data to the second time period is formed by the difference method; the filling data is used as the corrected monitoring data.

6. The method for detecting distribution network faults according to claim 1, characterized in that: Acquiring the fault type of the distribution network area monitored by the monitoring device from the fault response library according to the functional tag information of the fault node, including: Acquire multiple fault types containing the functional tag information from the fault response library according to the functional tag information of at least one of the fault nodes; Obtaining the fault type corresponding to the fault node by using the Euclidean distance calculation formula as the fault type of the distribution network area monitored by the monitoring device; The Euclidean distance calculation formula is: d(x,y) is the Euclidean distance; n is a positive integer greater than 1; x is the functional label information of the fault node; y is the functional label information of the fault type; the coordinate of x in the n-dimensional space is x=(x1, x2, ..., xn); the coordinate of y in the n-dimensional space is y=(y1, y2, ..., xn).

7. The method for detecting distribution network faults according to claim 1, characterized in that: The monitoring device includes at least one of the following: a current sensor, a temperature sensor, and a voltage sensor; The monitoring data of the current sensor is the current value; the monitoring data of the temperature sensor is the temperature value; and the monitoring data of the voltage sensor is the voltage value.

8. A distribution network fault detection device, characterized in that: include: A parameter tag acquisition unit, used to acquire parameter tag information of a monitoring device; The parameter marking information includes function marking information, space coordinate marking information and monitoring number marking information; A fault node detection unit, used to receive monitoring data acquired by the monitoring device; and marking the monitoring device as a faulty node when the monitoring data exceeds a corresponding safe working threshold; A fault type determination unit, configured to obtain the fault type of the distribution network area monitored by the monitoring device from a fault response library according to the functional tag information of the fault node; The fault response library at least includes fault types; the fault types include function tag information.

9. A device, characterized in that: The device comprises: one or more processors; A storage device for storing one or more programs; Camera, used to collect image and video data; A display, used to display the fault type; When the one or more programs are executed by the one or more processors, the one or more processors implement the distribution network fault detection method as described in any one of claims 1-7.

10. A storage medium comprising computer executable instructions, wherein the computer executable instructions are used to execute the distribution network fault detection method according to any one of claims 1 to 7 when executed by a computer processor.

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