Operation and maintenance method and equipment of power distribution network and storage medium

Abstract

The invention discloses an operation and maintenance method and equipment of a power distribution network, and a storage medium. The method comprises the following steps: respectively acquiring real-time operation parameters and real-time image data of electrical equipment in the power distribution network; detecting a first operation state of the electrical equipment according to the real-time operation parameters; detecting a second operation state of the electrical equipment according to the real-time image data; if the first operation state is abnormal and the second operation state is abnormal, determining that an abnormal event occurs in the electrical equipment; and writing the abnormal event into an inspection log of the power distribution network. According to the embodiment of the invention, the operation state of the electrical equipment is doubly detected according to the internal operation parameters and the external appearance of the electrical equipment, when the electrical equipment of the power distribution network is updated, the threshold of synchronously updating the detection logic is relatively low, the updating workload is relatively low, the operation amount of the detection logic is low, and the detection efficiency is relatively high when the massive electrical equipment of the power distribution network is oriented. Resources consumed by daily operation and maintenance detection are small, so that the cost of operation and maintenance detection of the power distribution network is effectively reduced.

Description

Technical Field

[0001] The present invention relates to the field of electric power technology, and in particular to an operation and maintenance method, equipment and storage medium of a distribution network. Background Art

[0002] The power grid is a system that transmits the electric energy collected by power plants to user terminals through transmission lines. It consists of transmission lines, substations and distribution networks, and its main task is to transmit and distribute electric energy.

[0003] In order to ensure the long-term normal operation of the distribution network, operation and maintenance inspections will be carried out regularly. At present, the operation and maintenance inspection method is mainly to collect the operating parameters of each electrical equipment in the distribution network and use deep learning models to identify the status of electrical equipment.

[0004] However, as the distribution network continues to update electrical equipment, deep learning technology needs to be continuously iterated and updated. The threshold for reconstructing deep learning models is high, and the training amount of deep learning models is large. In addition, the amount of computation required by deep learning models is large. When facing the massive electrical equipment in the distribution network, daily operation and maintenance inspections consume a lot of resources, resulting in high costs for distribution network operation and maintenance inspections. Summary of the invention

[0005] In view of this, the present invention provides a distribution network operation and maintenance method, device and storage medium, so as to reduce the cost of distribution network operation and maintenance detection.

[0006] A first aspect of the present invention provides an operation and maintenance method for a distribution network, comprising:

[0007] Collect real-time operating parameters and real-time image data of electrical equipment in the distribution network;

[0008] detecting a first operating state of the electrical device according to the real-time operating parameter;

[0009] detecting a second operating state of the electrical device based on the real-time image data;

[0010] If the first operating state is abnormal and the second operating state is abnormal, determining that an abnormal event occurs in the electrical device;

[0011] The abnormal event is written into the inspection log of the distribution network.

[0012] A second aspect of the present invention provides an operation and maintenance device for a distribution network, comprising:

[0013] A real-time data acquisition module is used to collect real-time operating parameters and real-time image data of electrical equipment in the distribution network;

[0014] A first operating state detection module, used for detecting a first operating state of the electrical device according to the real-time operating parameter;

[0015] A second operating state detection module, used for detecting a second operating state of the electrical device according to the real-time image data;

[0016] an abnormal event determination module, configured to determine that an abnormal event has occurred in the electrical device if the first operating state is abnormal and the second operating state is abnormal;

[0017] The inspection log generation module is used to write the abnormal event into the inspection log of the distribution network.

[0018] A third aspect of the present invention provides an electronic device, the electronic device comprising:

[0019] at least one processor; and

[0020] a memory communicatively connected to the at least one processor; wherein,

[0021] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the operation and maintenance method of the distribution network as described in the first aspect above.

[0022] A fourth aspect of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the operation and maintenance method of the distribution network as described in the first aspect above is implemented.

[0023] A fifth aspect of the present invention provides a computer program product, which includes a computer program. When the computer program is executed by a processor, it implements the operation and maintenance method of the distribution network as described in the first aspect above.

[0024] In this embodiment, real-time operating parameters and real-time image data are collected for the electrical equipment in the distribution network; the first operating state of the electrical equipment is detected based on the real-time operating parameters; the second operating state of the electrical equipment is detected based on the real-time image data; if the first operating state is abnormal and the second operating state is abnormal, it is determined that an abnormal event has occurred in the electrical equipment; and the abnormal event is written into the inspection log of the distribution network. This embodiment double-detects the operating state of the electrical equipment using the operating parameters inside the electrical equipment and the external appearance. When the electrical equipment in the distribution network is updated, the threshold for synchronously updating the detection logic is low, the update workload is low, and the computational complexity of the detection logic is low. When facing a large number of electrical equipment in the distribution network, the resources consumed by daily operation and maintenance detection are small, thereby effectively reducing the cost of operation and maintenance detection of the distribution network.

[0025] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0027] Figure 1 It is a flow chart of a distribution network operation and maintenance method provided in Embodiment 1 of the present invention.

[0028] Figure 2 It is a structural diagram of an operation and maintenance device for a distribution network provided in Embodiment 2 of the present invention.

[0029] Figure 3 It is a structural schematic diagram of an electronic device provided in Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0030] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings 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 should fall within the scope of protection of the present invention.

[0031] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present invention described herein can cover sequential implementations other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0032] Embodiment 1

[0033] See also Figure 1, shows a flow chart of a distribution network operation and maintenance method provided by the first embodiment of the present invention, the method can be executed by a distribution network operation and maintenance device, the distribution network operation and maintenance device can be implemented in the form of hardware and / or software, and the distribution network operation and maintenance device can be configured in an electronic device. Figure 1 As shown, the method includes:

[0034] Step 101: collect real-time operating parameters and real-time image data of electrical equipment in the distribution network.

[0035] In practical applications, the distribution network includes the following electrical equipment:

[0036] 1. Overhead lines: erected above the ground, with transmission wires fixed to pole towers through insulators to transmit electrical energy.

[0037] 2. Cable: It is made of multiple wires twisted together, the wires are insulated from each other, and there is a highly insulating covering layer on the outside. Cables are usually used for urban power distribution and have high reliability and safety.

[0038] 3. Pole tower: used to support overhead lines, usually made of steel or reinforced concrete, divided into wooden poles, concrete poles and metal poles.

[0039] 4. Distribution transformer: Converts high voltage electricity into low voltage electricity suitable for end users. The voltage level is usually 10-35kV and the capacity is 6300kVA and below.

[0040] 5. Switchgear: including circuit breakers, load switches, fuses, etc., used to control and protect circuits.

[0041] 6. Reactive power compensation capacitor: used to improve the power factor of the power system and reduce power loss.

[0042] 7. Lightning protection and grounding devices: protect the distribution network from lightning strikes and ensure equipment safety.

[0043] 8. Complete sets of power distribution equipment: such as switch stations, ring network units, box transformers, etc., used for centralized control and distribution of electrical energy.

[0044] 9. New equipment: such as multifunctional lightning arresters, wireless remote-controlled drop-out fuses, etc., to improve the intelligence and reliability of the distribution network.

[0045] Various electrical devices work together to distribute electrical energy efficiently and safely to end users.

[0046] In this embodiment, sensors may be configured for electrical equipment in the power distribution network to periodically collect real-time operating parameters of the electrical equipment, such as current, voltage, etc.

[0047] In addition, cameras can be configured at the distribution network site to regularly collect real-time image data of electrical equipment in an area, thereby observing the environment of the electrical equipment in the distribution network.

[0048] Real-time operating parameters are structured data and real-time image data are unstructured data. Both can be recorded in the inspection log for efficient processing and analysis.

[0049] In actual applications, sensors and cameras have basically covered the electrical equipment in the distribution network. It is sufficient to directly reuse the existing sensors and cameras, which is low-cost and easy to promote.

[0050] Step 102: Detect a first operating state of the electrical equipment according to the real-time operating parameters.

[0051] In this embodiment, algorithms such as a threshold method and a trend method may be used to detect the first operating state of the electrical device based on real-time operating parameters, and determine whether the electrical device is normal or abnormal from the perspective of the operating parameters.

[0052] In some typical anomalies, the parameters generated during the operation of electrical equipment fluctuate violently. Therefore, the use of real-time operating parameters can quickly identify these typical anomalies.

[0053] Taking the threshold method as an example, the standard parameter range configured for the electrical equipment can be queried based on the type of electrical equipment and the type of real-time operating parameters, where the standard parameter range represents a reasonable fluctuation range of the operating parameters when the electrical equipment is in a normal operating state.

[0054] Real-time operating parameters are compared to standard reference ranges.

[0055] If the real-time operating parameter is within the standard parameter range, it is determined that the first operating state of the electrical equipment is normal.

[0056] If the real-time operating parameter is outside the standard parameter range, it is determined that the first operating state of the electrical equipment is abnormal.

[0057] In this embodiment, the threshold method has a clear framework and simple calculations. When electrical equipment is updated, the data source and its corresponding standard reference range are mainly updated. The development threshold and development workload are low, and it can be quickly updated following the update of electrical equipment.

[0058] Step 103: Detect a second operating state of the electrical device according to the real-time image data.

[0059] In this embodiment, image analysis may be performed on the real-time image data to detect the second operating state of the electrical device, and determine whether the electrical device is normal or abnormal from the perspective of appearance.

[0060] In some typical anomalies, there are obvious changes in the appearance of electrical equipment. These typical anomalies can be quickly identified using real-time image data.

[0061] In one embodiment of the present invention, step 103 may include the following steps:

[0062] Step 1031: Query standard image data configured for electrical equipment.

[0063] In this embodiment, when it is historically determined that the electrical equipment is operating normally, multiple frames of image data can be collected from it, and one frame of image data can be selected as standard image data based on factors such as clarity and brightness. At this time, the standard image data configured for the electrical equipment can be queried based on the ID of the electrical equipment.

[0064] Step 1032: Align the real-time image data with the standard image data with the goal of minimizing the offset.

[0065] In actual applications, due to factors such as camera offset, maintenance of electrical equipment, external force impact, etc., the appearance of the electrical equipment changes, and / or the real-time image data and the standard image data are offset. Therefore, the real-time image data and the standard image data can be aligned with the goal of minimizing the offset so that the offset between the real-time image data and the standard image data is minimized.

[0066] In one embodiment of the present invention, step 1032 further includes the following steps:

[0067] Step 10321: extract real-time edge data from real-time image data.

[0068] In this embodiment, edge detection algorithms such as Canny may be used to extract real-time edge data from real-time image data, and the frame of the real-time image data may be represented by edge data, which may reduce the amount of data and thus reduce the amount of subsequent calculations.

[0069] Step 10322: Extract standard edge data from the standard image data.

[0070] In this embodiment, edge detection algorithms such as Canny may be used to extract standard edge data from standard image data, and the frame of the standard image data may be represented by the edge data, which may reduce the amount of data and thus reduce the amount of subsequent calculations.

[0071] If the standard edge data has been extracted from the standard image data in advance, the standard edge data extracted from the standard image data can be read from a cache, a database, etc., to avoid repeated operations.

[0072] Step 10323: Set a translation vector between the real-time image data and the standard image data.

[0073] In this embodiment, a translation vector may be set between the real-time image data and the standard image data, indicating that when the real-time image data moves according to the translation vector, it may be aligned with the standard image data.

[0074] Generally, the translation vector includes a horizontal axis component and a vertical axis component, wherein the horizontal axis component represents the distance moved on the horizontal axis, and the vertical axis component represents the distance moved on the vertical axis.

[0075] The translation vector (including the horizontal axis component and the vertical axis component) is an unknown quantity and needs to be solved.

[0076] Step 10324: Add the translation vector based on the difference between the real-time edge data and the standard edge data to obtain an error value.

[0077] Assuming that the real-time edge data moves according to the translation vector, at this time, the translation vector is subtracted from the difference between the real-time edge data and the standard edge data to obtain an error value to characterize the deviation between the real-time edge data and the standard edge data.

[0078] For example, if the standard edge data is represented as Real-time edge data is represented as Then the error value is:

[0079]

[0080] Where E is the error value, is the horizontal coordinate of the i-th pixel in the real-time edge data, is the ordinate of the i-th pixel in the real-time edge data, is the horizontal coordinate of the i-th pixel in the standard edge data, is the ordinate of the i-th pixel in the standard edge data, n is the set of pixels, t x is the horizontal component of the translation vector, t y is the longitudinal component of the translation vector.

[0081] Step 10325, solving the translation vector with the optimization goal of minimizing the error value to align the real-time image data with the standard image data.

[0082] In this embodiment, the error value is set as the objective function, and the translation vector is solved with the minimization of the output value of the objective function as the optimization goal. When the translation vector is obtained, the real-time image data is moved according to the translation vector to achieve alignment of the real-time image data with the standard image data.

[0083] In a specific implementation, on the one hand, the average value of the horizontal coordinates of each pixel point in the real-time edge data is subtracted from the average value of the horizontal coordinates of each pixel point in the standard edge data to obtain the horizontal axis reference value.

[0084] Then, the horizontal axis reference value can be expressed as:

[0085]

[0086] Among them, Δt x is the horizontal axis reference value, is the horizontal coordinate of the i-th pixel in the real-time edge data, is the horizontal coordinate of the i-th pixel in the standard edge data, n is the set of pixels, is the average value of the horizontal coordinates of the pixels in the real-time edge data, It is the average value of the horizontal coordinates of the pixels in the standard edge data.

[0087] On the other hand, the average value of the ordinates of each pixel point in the real-time edge data is subtracted from the average value of the ordinates of each pixel point in the standard edge data to obtain a ordinate reference value.

[0088] Then, the vertical axis reference value can be expressed as:

[0089]

[0090] Among them, Δt y is the vertical axis reference value, is the ordinate of the i-th pixel in the real-time edge data, is the ordinate of the i-th pixel in the standard edge data, n is the set of pixels, is the average value of the vertical coordinates of the pixels in the real-time edge data, It is the average value of the vertical coordinates of the pixels in the standard edge data.

[0091] The horizontal axis search range is generated based on the horizontal axis reference value. For example, a step size is added or subtracted from the horizontal axis reference value to obtain the horizontal axis search range.

[0092] The vertical axis search range is generated based on the vertical axis reference value. For example, a step size is added or subtracted from the vertical axis reference value to obtain the vertical axis search range.

[0093] With minimizing the error value as the optimization goal, greedy algorithms, exhaustive methods and other methods are used to search for the horizontal axis component of the translation vector within the horizontal axis search range and the vertical axis component of the translation vector within the vertical axis search range to align the real-time image data with the standard image data.

[0094] This embodiment reasonably converges the search range of the translation vector, which can effectively reduce the amount of calculation.

[0095] Step 1033: If the alignment is completed, locate the part where the real-time image data and the standard image data are different.

[0096] If the real-time image data and the standard image data are aligned, the difference between the real-time image data and the standard image data can be located.

[0097] In the specific implementation, the corrosion operation and the dilation operation are performed on the real-time image data and the standard image data respectively, so as to realize the opening operation, eliminate the small areas with higher brightness, and will not obviously change the area of ​​other object areas, so as to make the shape of the electrical equipment smoother.

[0098] If the erosion operation and the dilation operation are completed, a differential operation is performed on the real-time edge data and the standard edge data to obtain a portion where the real-time image data and the standard image data differ.

[0099] Step 1034: Identify the second operating state of the electrical equipment based on the location.

[0100] In this embodiment, a geometric analysis may be performed on the portion where the real-time image data differs from the standard image data, thereby identifying the second operating state of the electrical device.

[0101] In a specific implementation, a variety of geometric parameters may be counted for the parts; wherein the geometric parameters include at least one of the total area of ​​the parts, the maximum single area of ​​the parts, the number of parts, and the size of the minimum circumscribed rectangle of the parts.

[0102] Use weighted summation and other methods to integrate multiple geometric parameters into geometric index values.

[0103] The standard geometric range configured for the electrical equipment is queried based on the type of the electrical equipment, wherein the standard geometric range is the interval within which the geometric index value fluctuates reasonably when the appearance of the electrical equipment is normal.

[0104] Compares the geometry metric value to the standard geometry range.

[0105] If the geometric index value is within the standard geometric range, it is determined that the second operating state of the electrical equipment is normal.

[0106] If the geometric index value is outside the standard geometric range, the second operating state of the electrical equipment is determined to be abnormal.

[0107] In this embodiment, the framework of image detection is clear and the operation is simple. When the electrical equipment is updated, the data source and its corresponding standard geometric range are mainly updated. The development threshold is low, the development workload is low, and it can be quickly updated following the update of the electrical equipment.

[0108] Step 104: If the first operating state is abnormal and the second operating state is abnormal, it is determined that an abnormal event occurs in the electrical equipment.

[0109] If the first operating state is abnormal and the second operating state is abnormal, it can be determined that a relatively typical abnormal event has occurred in the electrical equipment.

[0110] In addition, if the first operating state is normal and / or the second operating state is normal, it can be determined that the operating state of the electrical device is normal.

[0111] Step 105: Write the abnormal event into the inspection log of the distribution network.

[0112] In this embodiment, abnormal events of electrical equipment can be written into the inspection log of the distribution network. When the inspection log is transferred to the data middle station and the abnormal event of the electrical equipment is detected, other more accurate mechanisms can be called to further detect the operating status of the electrical equipment, and the operation and maintenance personnel can also be prompted to inspect the electrical equipment. This embodiment does not limit this.

[0113] In this embodiment, real-time operating parameters and real-time image data are collected for the electrical equipment in the distribution network; the first operating state of the electrical equipment is detected based on the real-time operating parameters; the second operating state of the electrical equipment is detected based on the real-time image data; if the first operating state is abnormal and the second operating state is abnormal, it is determined that an abnormal event has occurred in the electrical equipment; and the abnormal event is written into the inspection log of the distribution network. This embodiment double-detects the operating state of the electrical equipment using the operating parameters inside the electrical equipment and the external appearance. When the electrical equipment in the distribution network is updated, the threshold for synchronously updating the detection logic is low, the update workload is low, and the computational complexity of the detection logic is low. When facing a large number of electrical equipment in the distribution network, the resources consumed by daily operation and maintenance detection are small, thereby effectively reducing the cost of operation and maintenance detection of the distribution network.

[0114] This embodiment can be applied to screening projects such as preliminary screening in distribution network operation and maintenance scenarios, screening of typical faults of some electrical equipment, and can achieve the effect of accurate and rapid screening.

[0115] Embodiment 2

[0116] See also Figure 2 , shows a schematic diagram of the structure of a distribution network operation and maintenance device provided by Embodiment 2 of the present invention. Figure 2 As shown, the device comprises:

[0117] The real-time data acquisition module 201 is used to respectively collect real-time operating parameters and real-time image data of electrical equipment in the distribution network;

[0118] A first operating state detection module 202, configured to detect a first operating state of the electrical device according to the real-time operating parameters;

[0119] A second operating state detection module 203, configured to detect a second operating state of the electrical device according to the real-time image data;

[0120] An abnormal event determination module 204, configured to determine that an abnormal event occurs in the electrical device if the first operating state is abnormal and the second operating state is abnormal;

[0121] The inspection log generating module 205 is used to write the abnormal event into the inspection log of the distribution network.

[0122] In one embodiment of the present invention, the first operating status detection module 202 includes:

[0123] A standard parameter range query module, used to query the standard parameter range configured for the electrical equipment;

[0124] A first normal determination module, configured to determine that the first operating state of the electrical device is normal if the real-time operating parameter is within the standard parameter range;

[0125] The first abnormality determination module is used to determine that the first operating state of the electrical equipment is abnormal if the real-time operating parameter is outside the standard parameter range.

[0126] In one embodiment of the present invention, the second operating status detection module 203 includes:

[0127] A standard image data query module, used to query the standard image data configured for the electrical equipment;

[0128] An image data alignment module, used to align the real-time image data with the standard image data with the goal of minimizing the offset;

[0129] A difference location positioning module, used for locating a location where the real-time image data differs from the standard image data if the alignment is completed;

[0130] The part state identification module is used to identify the second operating state of the electrical device according to the part.

[0131] In one embodiment of the present invention, the image data alignment module includes:

[0132] A real-time edge data extraction module, used to extract real-time edge data from the real-time image data;

[0133] A standard edge data extraction module, used to extract standard edge data from the standard image data;

[0134] A translation vector setting module, used for setting a translation vector between the real-time image data and the standard image data;

[0135] an error value calculation module, configured to obtain an error value by subtracting the translation vector based on the difference between the real-time edge data and the standard edge data;

[0136] The translation vector solving module is used to solve the translation vector with the optimization goal of minimizing the error value, so as to align the real-time image data with the standard image data.

[0137] In one embodiment of the present invention, the error value is:

[0138]

[0139] Wherein, E is the error value, is the horizontal coordinate of the i-th pixel point in the real-time edge data, is the ordinate of the i-th pixel in the real-time edge data, is the horizontal coordinate of the i-th pixel point in the standard edge data, is the ordinate of the i-th pixel in the standard edge data, n is the set of pixels, t x is the horizontal axis component of the translation vector, t y is the longitudinal component of the translation vector.

[0140] In one embodiment of the present invention, the translation vector solving module includes:

[0141] A horizontal axis reference value calculation module, used to subtract the average value of the horizontal coordinates of each pixel point in the standard edge data from the average value of the horizontal coordinates of each pixel point in the real-time edge data to obtain a horizontal axis reference value;

[0142] A vertical axis reference value calculation module, used to subtract the average value of the vertical coordinates of each pixel point in the standard edge data from the average value of the vertical coordinates of each pixel point in the real-time edge data to obtain a vertical axis reference value;

[0143] A horizontal axis search range generating module, used for generating a horizontal axis search range based on the horizontal axis reference value;

[0144] A vertical axis search range generating module, used for generating a vertical axis search range based on the vertical axis reference value;

[0145] A translation vector search module is used to search for the horizontal axis component of the translation vector within the horizontal axis search range and the vertical axis component of the translation vector within the vertical axis search range with the optimization goal of minimizing the error value, so as to align the real-time image data with the standard image data.

[0146] In one embodiment of the present invention, the difference location positioning module includes:

[0147] An opening operation execution module, used for sequentially performing an erosion operation and an expansion operation on the real-time image data and the standard image data respectively;

[0148] The differential operation execution module is used to perform a differential operation on the real-time edge data and the standard edge data if the erosion operation and the dilation operation are completed, so as to obtain a portion where the real-time image data and the standard image data are different.

[0149] In one embodiment of the present invention, the part state recognition module includes:

[0150] A geometric parameter statistics module, used for counting various geometric parameters of the parts; the geometric parameters include at least one of the total area of ​​the parts, the maximum single area of ​​the parts, the number of the parts, and the size of the minimum circumscribed rectangle of the parts;

[0151] A geometric index value fusion module, used for fusing the plurality of geometric parameters into a geometric index value;

[0152] A standard geometry range query module, used for querying the standard geometry range configured for the electrical equipment;

[0153] A second normal determination module, configured to determine that the second operating state of the electrical device is normal if the geometric index value is within the standard geometric range;

[0154] The second abnormality determination module is used to determine that the second operating state of the electrical equipment is abnormal if the geometric index value is outside the standard geometric range.

[0155] The operation and maintenance device of the distribution network provided in the embodiment of the present invention can execute the operation and maintenance method of the distribution network provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the operation and maintenance method of the distribution network.

[0156] Embodiment 3

[0157] See also Figure 3, showing a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0158] like Figure 3 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0159] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0160] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the operation and maintenance method of the distribution network.

[0161] In some embodiments, the operation and maintenance method of the distribution network may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the operation and maintenance method of the distribution network described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute the operation and maintenance method of the distribution network by any other appropriate means (e.g., by means of firmware).

[0162] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0163] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0164] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0165] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0166] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0167] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0168] Embodiment 4

[0169] An embodiment of the present invention further provides a computer program product, which includes a computer program. When the computer program is executed by a processor, it implements the operation and maintenance method of the distribution network provided in any embodiment of the present invention.

[0170] In the process of implementation, the computer program product can be written in one or more programming languages ​​or a combination thereof to perform the computer program code of the present invention, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (for example, using an Internet service provider to connect through the Internet).

[0171] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0172] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A distribution network operation and maintenance method, characterized in that: include: Collect real-time operating parameters and real-time image data of electrical equipment in the distribution network; detecting a first operating state of the electrical device according to the real-time operating parameter; detecting a second operating state of the electrical device based on the real-time image data; If the first operating state is abnormal and the second operating state is abnormal, determining that an abnormal event occurs in the electrical device; The abnormal event is written into the inspection log of the distribution network.

2. The method according to claim 1, characterized in that The detecting the first operating state of the electrical device according to the real-time operating parameter comprises: Querying the standard parameter range configured for the electrical equipment; If the real-time operating parameter is within the standard parameter range, determining that the first operating state of the electrical equipment is normal; If the real-time operating parameter is outside the standard parameter range, it is determined that the first operating state of the electrical equipment is abnormal.

3. The method according to claim 1 or 2, characterized in that: The detecting the second operating state of the electrical device according to the real-time image data comprises: querying standard image data configured for the electrical device; Aligning the real-time image data with the standard image data with the goal of minimizing the offset; If the alignment is completed, locating the part where the real-time image data differs from the standard image data; A second operating state of the electrical device is identified based on the location.

4. The method according to claim 3, characterized in that The step of aligning the real-time image data with the standard image data with the goal of minimizing the offset comprises: extracting real-time edge data from the real-time image data; extracting standard edge data from the standard image data; Setting a translation vector between the real-time image data and the standard image data; Subtracting the translation vector based on the difference between the real-time edge data and the standard edge data to obtain an error value; The translation vector is solved with the optimization goal of minimizing the error value to align the real-time image data with the standard image data.

5. The method according to claim 4, characterized in that The error value is: Wherein, E is the error value, is the horizontal coordinate of the i-th pixel point in the real-time edge data, is the ordinate of the i-th pixel in the real-time edge data, is the horizontal coordinate of the i-th pixel point in the standard edge data, is the ordinate of the i-th pixel in the standard edge data, n is the set of pixels, t x is the horizontal axis component of the translation vector, t y is the longitudinal component of the translation vector.

6. The method according to claim 5, characterized in that The step of solving the translation vector with the optimization goal of minimizing the error value to align the real-time image data with the standard image data includes: The average value of the horizontal coordinates of each pixel point in the standard edge data is subtracted from the average value of the horizontal coordinates of each pixel point in the real-time edge data to obtain a horizontal axis reference value; The average value of the vertical coordinates of each pixel point in the real-time edge data is subtracted from the average value of the vertical coordinates of each pixel point in the standard edge data to obtain a vertical axis reference value; generating a horizontal axis search range based on the horizontal axis reference value; generating a vertical axis search range based on the vertical axis reference value; With the optimization goal of minimizing the error value, the horizontal axis component of the translation vector is searched within the horizontal axis search range, and the vertical axis component of the translation vector is searched within the vertical axis search range, so as to align the real-time image data with the standard image data.

7. The method according to claim 4, characterized in that The locating a part where the real-time image data differs from the standard image data includes: performing an erosion operation and a dilation operation on the real-time image data and the standard image data respectively; If the erosion operation and the dilation operation are completed, a differential operation is performed on the real-time edge data and the standard edge data to obtain a portion where the real-time image data and the standard image data differ.

8. The method according to claim 7, characterized in that The step of identifying the second operating state of the electrical device according to the location includes: Counting a plurality of geometric parameters of the parts; the geometric parameters include at least one of the total area of ​​the parts, the maximum single unit area of ​​the parts, the number of the parts, and the size of the minimum circumscribed rectangle of the parts; Merging the plurality of geometric parameters into a geometric index value; Querying the standard geometric range configured for the electrical device; If the geometric index value is within the standard geometric range, determining that the second operating state of the electrical equipment is normal; If the geometric index value is outside the standard geometric range, it is determined that the second operating state of the electrical equipment is abnormal.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the operation and maintenance method of the distribution network as described in any one of claims 1-8.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the operation and maintenance method of the distribution network according to any one of claims 1 to 8 is implemented.

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