Wind power equipment inspection method and system

Abstract

The invention relates to the technical field of field equipment inspection, and particularly discloses a wind power equipment inspection method and system, and the method comprises the steps: obtaining a position distribution table of wind power equipment and a net diagram connected with the wind power equipment, and obtaining road condition information based on the position distribution table and the net diagram; activating a monitoring point preset in the online network based on the road condition information, and acquiring power transmission data of the monitoring point; analyzing the power transmission data, and determining abnormal equipment; and determining inspection parameters according to the abnormal equipment and the road condition information. The method comprises the following steps: establishing a net diagram, acquiring road condition information according to the net diagram, and adjusting the road condition information according to air parameters; activating a monitoring point according to the adjusted road condition information, obtaining power data, positioning abnormal equipment, and then determining an inspection scheme according to the road condition information around the abnormal equipment; a remote monitoring scheme is provided, guidance is provided for the inspection process, the inspection efficiency is improved, and the safety is improved in a disguised manner.

Description

Technical Field

[0001] This invention relates to the field of field equipment inspection technology, specifically a method and system for inspecting wind power equipment. Background Technology

[0002] Wind power equipment is equipment that uses wind energy to generate electricity. Wind power technology and equipment are an important component of the wind power industry, and also the foundation and guarantee for its development.

[0003] Due to the obvious advantages of wind power equipment, its proportion in power generation equipment has been increasing year by year. As a power generation device, the normal operation of wind power equipment affects the living standards of residents. Therefore, it is necessary to carry out regular inspections and maintenance. However, since wind power equipment is generally set up in the field, the inspection and maintenance process is very troublesome when the environment is harsh, and there may even be some safety risks. Therefore, how to improve the safety of the inspection process is the technical problem that the present invention aims to solve. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for inspecting wind power equipment to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] A method for inspecting wind power equipment, the method comprising:

[0007] Obtain a location distribution table of wind power equipment and a network diagram of the lines connecting to the wind power equipment; obtain road condition information based on the location distribution table and the network diagram; the road condition information is a mapping of air parameters.

[0008] Based on the road condition information, activate the monitoring points in the preset online network and obtain the power transmission data of the monitoring points;

[0009] The power transmission data is analyzed to identify abnormal equipment;

[0010] The inspection parameters are determined based on the abnormal equipment and the road condition information.

[0011] As a further aspect of the present invention: the step of obtaining a location distribution table of wind power equipment and a network diagram of the power lines connected to the wind power equipment, and obtaining road condition information based on the location distribution table and the network diagram includes:

[0012] Obtain the network registration information and determine the network map according to the preset scale;

[0013] Obtain the location distribution table of wind power equipment, and based on the location distribution table, query and mark the equipment nodes corresponding to the wind power equipment in the network diagram;

[0014] Based on existing map services, road condition information within a preset range corresponding to the device node is obtained sequentially, and the road condition information is inserted into the network diagram.

[0015] Real-time air parameters are acquired, and the road condition information in the network diagram is corrected based on the air parameters.

[0016] As a further aspect of the present invention: the step of acquiring air parameters in real time and correcting the road condition information in the network diagram based on the air parameters includes:

[0017] Air parameters within the range corresponding to the network map are obtained in real time based on existing weather services; the air parameters are represented by a matrix; the position of each element in the matrix corresponds to the actual position;

[0018] Based on the air parameters, the system queries the preset impact parameter library for impact parameters; the impact parameters are used to characterize the degree of impact on various types of roads.

[0019] Based on spatial scale relationships, the road condition information in the network diagram is corrected according to the queried influence parameters.

[0020] As a further aspect of the present invention: the step of activating monitoring points in a preset online network based on the road condition information and obtaining power transmission data from the monitoring points includes:

[0021] The road condition information is input into a preset information recognition model, which outputs the risk level.

[0022] The monitoring density is determined based on the risk level, and monitoring points in the preset online network are activated based on the monitoring density.

[0023] The queue is determined based on the relative position of the monitoring points in the online network, and power transmission data is acquired in real time based on the queue.

[0024] As a further aspect of the present invention: the step of analyzing the power transmission data to determine the abnormal equipment includes:

[0025] A baseline map is established based on the relative positions of monitoring points in the online network; the baseline map contains mapping areas corresponding to the monitoring points; the shape and size of the mapping areas are determined by road condition information within a preset radius corresponding to the monitoring points; the size of the mapping areas is proportional to the traffic difficulty of the road condition information; the traffic difficulty is determined by parameters of the entities allowed to pass.

[0026] Establish a polar coordinate system centered on the mapping region;

[0027] Read the power transmission data from the queue and fill it into the polar coordinate system; wherein, the angle of the polar coordinates is determined by the derivative of the power transmission data, and the distance of the polar coordinates is determined by the amount of data;

[0028] Based on a pre-defined feature library, anomaly mapping regions are determined in the filled baseline map, and anomalous devices and their predicted anomaly types are determined based on the anomaly mapping regions.

[0029] As a further aspect of the present invention: the step of determining the inspection parameters based on the abnormal equipment and the road condition information includes:

[0030] The maintenance tools are determined based on the predicted anomaly type of each abnormal device;

[0031] The main body of the object is determined based on the shape and size of the mapping area corresponding to each abnormal device;

[0032] The maintenance path is determined based on the location relationship of each abnormal device and the predicted abnormality type.

[0033] The present invention also provides a wind power equipment inspection system, the system comprising:

[0034] The road condition information acquisition module is used to acquire a location distribution table of wind power equipment and a network diagram of the power lines connected to the wind power equipment, and acquire road condition information based on the location distribution table and the network diagram; the road condition information is a mapping of air parameters; the power data acquisition module is used to activate a preset monitoring point in the network based on the road condition information and acquire the power transmission data of the monitoring point;

[0035] The data analysis module is used to analyze the power transmission data and identify abnormal equipment;

[0036] The inspection parameter determination module is used to determine inspection parameters based on the abnormal equipment and the road condition information.

[0037] As a further aspect of the present invention: the road condition information acquisition module includes:

[0038] The wire mesh diagram determination unit is used to obtain wire mesh registration information and determine the wire mesh diagram according to a preset scale.

[0039] The equipment node marking unit is used to obtain the location distribution table of wind power equipment, and query and mark the equipment nodes corresponding to the wind power equipment in the network diagram based on the location distribution table.

[0040] The road condition information filling unit is used to sequentially obtain road condition information within a preset range corresponding to the device node based on existing map services, and insert the road condition information into the network diagram;

[0041] The road condition information correction unit is used to acquire air parameters in real time and correct the road condition information in the network diagram based on the air parameters.

[0042] As a further aspect of the present invention: the power data acquisition module includes:

[0043] The information recognition unit is used to input the road condition information into a preset information recognition model and output the risk level;

[0044] A monitoring point activation unit is used to determine the monitoring density based on the risk level and activate monitoring points in a preset online network based on the monitoring density.

[0045] The acquisition execution unit is used to determine the queue based on the relative position of the monitoring point in the online network, and to acquire power transmission data in real time based on the queue.

[0046] As a further aspect of the present invention: the data analysis module includes:

[0047] A baseline map establishment unit is used to establish a baseline map based on the relative positions of monitoring points in the online network; the baseline map contains a mapping area corresponding to the monitoring point; the shape and size of the mapping area are determined by road condition information within a preset radius corresponding to the monitoring point; the size of the mapping area is proportional to the traffic difficulty of the road condition information; the traffic difficulty is determined by parameters of the allowed traffic entities;

[0048] The polar coordinate system establishment unit is used to establish a polar coordinate system centered on the mapping region.

[0049] A filling execution unit is used to read power transmission data from the queue and fill it into the polar coordinate system; wherein, the angle of the polar coordinates is determined by the derivative of the power transmission data, and the distance of the polar coordinates is determined by the amount of data;

[0050] An anomaly identification unit is used to determine the anomaly mapping area in the filled baseline map based on a preset feature library, and to determine the abnormal device and its predicted anomaly type based on the anomaly mapping area.

[0051] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention is based on the statistical analysis of wind power equipment to obtain a network diagram containing equipment nodes. Road condition information is obtained from the network diagram, and this information is adjusted in real time according to air parameters to obtain adjusted road condition information. Monitoring points are activated based on the adjusted road condition information to obtain power data, locate abnormal equipment, and then an inspection plan is determined based on the road condition information surrounding the abnormal equipment. This invention provides a remote monitoring solution, guiding the inspection process, improving inspection efficiency, and indirectly enhancing safety. Attached Figure Description

[0052] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention.

[0053] Figure 1 This is a flowchart of the wind power equipment inspection method.

[0054] Figure 2 This is the first sub-flowchart of the wind power equipment inspection method.

[0055] Figure 3 This is the second sub-flowchart of the wind power equipment inspection method.

[0056] Figure 4 This is the third sub-flowchart of the wind power equipment inspection method.

[0057] Figure 5 This is the fourth sub-flowchart of the wind power equipment inspection method.

[0058] Figure 6 This is a block diagram showing the composition and structure of a wind power equipment inspection system. Detailed Implementation

[0059] To make the technical problems to be solved, the technical solutions, and the beneficial effects of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present invention and are not intended to limit the present invention.

[0060] Figure 1 The flowchart below illustrates a wind power equipment inspection method. In this embodiment of the invention, a wind power equipment inspection method includes:

[0061] Step S100: Obtain the location distribution table of wind power equipment and the network diagram of the lines connected to the wind power equipment; obtain road condition information based on the location distribution table and the network diagram; the road condition information is a mapping of air parameters.

[0062] Wind power equipment, as a power generation device, is a component of the power grid. By acquiring the layout information of the power grid and a location distribution table of the wind power equipment, a power grid map can be created. This map reflects the location of the power grid and the wind power equipment. Based on this map, road condition information can be obtained. This road condition information refers to the passable areas surrounding the power grid containing the wind power equipment, including paved roads, dirt roads, and asphalt roads. The road condition information is related to air parameters; different air parameters result in different road condition information.

[0063] Step S200: Activate monitoring points in the preset online network based on the road condition information, and obtain power transmission data of the monitoring points;

[0064] By analyzing the road condition information, corresponding monitoring points can be activated in the online network. Power acquisition equipment is installed at the monitoring points to obtain power transmission data at different locations. The power transmission data is represented by the most basic power parameters, including current and voltage. The monitoring points are pre-set in the online network and updated regularly.

[0065] Step S300: Analyze the power transmission data to identify abnormal devices;

[0066] Power transmission data represents power parameters at different locations. By analyzing these power parameters, it is possible to determine which wind power equipment is malfunctioning; these are called malfunctioning equipment.

[0067] Step S400: Determine the inspection parameters based on the abnormal equipment and the road condition information;

[0068] Once the abnormal equipment is identified, inspection parameters can be determined based on the abnormal equipment and road condition information. These inspection parameters include the inspection path to each abnormal equipment and the main body of the inspection process.

[0069] Figure 2 The first sub-flowchart of the wind turbine inspection method includes obtaining a location distribution table of the wind turbines and a network diagram of the power lines connected to the wind turbines. The step of obtaining road condition information based on the location distribution table and the network diagram includes:

[0070] Step S101: Obtain the wire mesh registration information and determine the wire mesh diagram according to the preset scale;

[0071] By obtaining the registration information of the wire mesh and analyzing the registration information, graphical data can be obtained, which is called a wire mesh diagram.

[0072] Step S102: Obtain the location distribution table of wind power equipment, and query and mark the equipment nodes corresponding to the wind power equipment in the network diagram based on the location distribution table;

[0073] Obtain a location distribution table for wind power equipment. The location distribution table is used to represent the location of each wind power equipment, including the equipment number and location. Based on the location distribution table, the corresponding mapping points, called equipment nodes, can be queried and marked in the generated network diagram. Thus, the network diagram contains equipment nodes.

[0074] Step S103: Based on the existing map service, sequentially obtain the road condition information within the preset range corresponding to the device node, and insert the road condition information into the network map;

[0075] Traffic information can be obtained using existing map services. Based on the map services, traffic information near different device nodes is obtained sequentially, and the traffic information is also inserted into the network map; where "nearby" refers to a preset range.

[0076] Step S104: Obtain air parameters in real time, and correct the road condition information in the network diagram based on the air parameters;

[0077] Road condition information changes with air parameters, and these air parameters can be used to correct the road condition information.

[0078] Furthermore, the step of acquiring air parameters in real time and correcting the road condition information in the network diagram based on the air parameters includes:

[0079] Air parameters within the range corresponding to the network map are obtained in real time based on existing weather services; the air parameters are represented by a matrix; the position of each element in the matrix corresponds to the actual position;

[0080] Based on the air parameters, the system queries the preset impact parameter library for impact parameters; the impact parameters are used to characterize the degree of impact on various types of roads.

[0081] Based on spatial scale relationships, the road condition information in the network diagram is corrected according to the queried influence parameters.

[0082] The above describes the process of correcting road condition information. First, air parameters may vary slightly in different areas. Therefore, a matrix is ​​needed to represent the air parameters within the range corresponding to the network map. Generally, the differences between the elements in the matrix are not significant. Then, the air parameters are analyzed to determine their impact on different types of roads. For example, when the humidity in the air is high, the soil will become thinner, and cement or asphalt roads may become slippery. If the temperature is low, icing may also occur. The correspondence between air parameters and influencing parameters is determined in advance by the staff, and the determined relationship is represented by the influencing parameter database. Finally, the road condition information is corrected according to the location relationship (spatial scale relationship) using the corresponding air parameters.

[0083] Figure 3 This is the second sub-flowchart of the wind power equipment inspection method. The step of activating monitoring points in the preset online network based on the road condition information and obtaining power transmission data from the monitoring points includes:

[0084] Step S201: Input the road condition information into a preset information recognition model and output the risk level;

[0085] After being corrected for weather parameters, road condition information can reflect environmental characteristics to a certain extent. The probability of risk varies under different environmental characteristics. Therefore, identifying road condition information can output the risk level.

[0086] Step S202: Determine the monitoring density based on the risk level, and activate the monitoring points in the preset online network based on the monitoring density;

[0087] The monitoring density is determined by the risk level, which in turn determines the number of monitoring points selected and their intervals. The higher the risk level, the greater the monitoring density and the more monitoring points there are.

[0088] Step S203: Determine the queue based on the relative position of the monitoring points in the online network, and acquire power transmission data in real time based on the queue;

[0089] Multiple queues are defined, and power transmission data is acquired by the queues. The queues act as buffers during the data acquisition process. It should be noted that each queue corresponds to one monitoring point, and the arrangement of different queues is related to the relative position of the monitoring points in the network.

[0090] Figure 4 The third sub-flowchart of the wind power equipment inspection method includes the step of analyzing the power transmission data to identify abnormal equipment:

[0091] Step S301: Establish a reference map based on the relative positions of monitoring points in the online network; the reference map contains mapping areas corresponding to the monitoring points; the shape and size of the mapping areas are determined by road condition information within a preset radius corresponding to the monitoring points; the size of the mapping areas is proportional to the traffic difficulty of the road condition information; the traffic difficulty is determined by parameters of the permitted traffic entities;

[0092] The relative positional relationship between activated monitoring points is obtained, and a baseline map is established based on the relative positional relationship. The baseline map contains a mapping area corresponding to the monitoring point. The mapping area can be a rectangle, a circle, a triangular shape, etc., determined by road condition information. The road condition information can be used to determine the parameter of traffic difficulty. The higher the traffic difficulty, the larger the size of the mapping area.

[0093] Step S302: Establish a polar coordinate system centered on the mapping region;

[0094] A polar coordinate system is established with the mapping region as the center. In a base map, there are multiple mapping regions, and multiple polar coordinate systems are established.

[0095] Step S303: Read the power transmission data in the queue and fill it into the polar coordinate system; wherein, the angle of the polar coordinates is determined by the derivative of the power transmission data, and the distance of the polar coordinates is determined by the amount of data;

[0096] Read power transmission data from the queue, query the monitoring point corresponding to the queue, analyze the power transmission data, and fill it into the polar coordinate system. The filling method is to calculate the derivative of the power transmission data, which reflects the change characteristics, determine a certain angle region based on the derivative, and then count how many data appear within that angle and fill it within that angle range.

[0097] It should be noted that the power transmission data is discrete data, with each moment corresponding to a single power transmission data point. The time interval is preset by the staff, and the setting method is to determine the acquisition frequency of the acquisition equipment at the monitoring point.

[0098] Step S304: Determine the abnormal mapping area in the filled baseline map based on the preset feature library, and determine the abnormal device and its predicted abnormal type according to the abnormal mapping area;

[0099] A feature library is pre-established. By traversing and identifying the reference map according to the feature library, it can be determined whether there are any abnormalities in each mapping area and its filling content in the reference map. If there are abnormalities, the corresponding mapping area is marked as an abnormal mapping area. The mapping area corresponds to the monitoring point, and the abnormal mapping area corresponds to the abnormal monitoring point. The abnormal equipment can be identified by the abnormal monitoring point. The identification rules are pre-set by the staff based on the laws of electricity.

[0100] During the process of marking the abnormal mapping area, the corresponding abnormal type in the feature library can be queried to determine the abnormal type of the monitoring point. The abnormal type of the monitoring point can then be used to determine the predicted abnormal type of the abnormal device.

[0101] The feature library contains feature items and anomaly type items, and the features in the feature items are image features.

[0102] Figure 5 The fourth sub-flowchart of the wind power equipment inspection method includes the step of determining inspection parameters based on the abnormal equipment and the road condition information:

[0103] Step S401: Determine the maintenance tools based on the predicted anomaly type of each abnormal device;

[0104] Step S402: Determine the main body of the object based on the shape and size of the mapping area corresponding to each abnormal device;

[0105] Step S403: Determine the maintenance path based on the location relationship of each abnormal device and the predicted abnormality type.

[0106] The above content defines the process for determining inspection parameters. Inspection parameters include the main body involved in the inspection process, which is generally the inspection vehicle; maintenance tools are used to detect abnormal equipment, and the selection process is determined by the predicted type of abnormality; in addition, maintenance path is also included, that is, the movement path of the inspection vehicle.

[0107] Figure 6 This is a block diagram of the composition of a wind power equipment inspection system. In a preferred embodiment of the method of the present invention, a wind power equipment inspection system is provided, the system 10 comprising:

[0108] The road condition information acquisition module 11 is used to acquire a location distribution table of wind power equipment and a network diagram of the lines connected to the wind power equipment, and to acquire road condition information based on the location distribution table and the network diagram; the road condition information is a mapping of air parameters.

[0109] The power data acquisition module 12 is used to activate monitoring points in a preset online network based on the road condition information and acquire power transmission data of the monitoring points;

[0110] Data analysis module 13 is used to analyze the power transmission data and identify abnormal equipment;

[0111] The inspection parameter determination module 14 is used to determine inspection parameters based on the abnormal equipment and the road condition information.

[0112] The road condition information acquisition module 11 includes:

[0113] The wire mesh diagram determination unit is used to obtain wire mesh registration information and determine the wire mesh diagram according to a preset scale.

[0114] The equipment node marking unit is used to obtain the location distribution table of wind power equipment, and query and mark the equipment nodes corresponding to the wind power equipment in the network diagram based on the location distribution table.

[0115] The road condition information filling unit is used to sequentially obtain road condition information within a preset range corresponding to the device node based on existing map services, and insert the road condition information into the network diagram;

[0116] The road condition information correction unit is used to acquire air parameters in real time and correct the road condition information in the network diagram based on the air parameters.

[0117] The power data acquisition module 12 includes:

[0118] The information recognition unit is used to input the road condition information into a preset information recognition model and output the risk level;

[0119] A monitoring point activation unit is used to determine the monitoring density based on the risk level and activate monitoring points in a preset online network based on the monitoring density.

[0120] The acquisition execution unit is used to determine the queue based on the relative position of the monitoring point in the online network, and to acquire power transmission data in real time based on the queue.

[0121] The data analysis module 13 includes:

[0122] A baseline map establishment unit is used to establish a baseline map based on the relative positions of monitoring points in the online network; the baseline map contains a mapping area corresponding to the monitoring point; the shape and size of the mapping area are determined by road condition information within a preset radius corresponding to the monitoring point; the size of the mapping area is proportional to the traffic difficulty of the road condition information; the traffic difficulty is determined by parameters of the allowed traffic entities;

[0123] The polar coordinate system establishment unit is used to establish a polar coordinate system centered on the mapping region.

[0124] A filling execution unit is used to read power transmission data from the queue and fill it into the polar coordinate system; wherein, the angle of the polar coordinates is determined by the derivative of the power transmission data, and the distance of the polar coordinates is determined by the amount of data;

[0125] An anomaly identification unit is used to determine the anomaly mapping area in the filled baseline map based on a preset feature library, and to determine the abnormal device and its predicted anomaly type based on the anomaly mapping area.

[0126] All the functions that the above-mentioned wind power equipment inspection method can achieve are performed by computer equipment. The computer equipment includes one or more processors and one or more memories. The one or more memories store at least one piece of program code. The program code is loaded and executed by the one or more processors to realize the functions of the wind power equipment inspection method.

[0127] The processor fetches instructions from memory one by one, analyzes the instructions, and then performs the corresponding operations according to the instructions, generating a series of control commands to enable the various parts of the computer to act automatically, continuously, and in a coordinated manner, forming an organic whole. This enables the input of programs and data, as well as the calculation and output of results. The arithmetic or logical operations generated in this process are all performed by the arithmetic unit. The memory includes a read-only memory (ROM), which is used to store computer programs. The memory is protected by an external protection device.

[0128] For example, a computer program can be divided into one or more modules, one or more of which are stored in memory and executed by a processor to perform the present invention. The one or more modules can be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in a terminal device.

[0129] Those skilled in the art will understand that the above description of the service equipment is merely an example and does not constitute a limitation on the terminal equipment. It may include more or fewer components than described above, or a combination of certain components, or different components, such as input / output devices, network access devices, buses, etc.

[0130] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. This processor is the control center of the terminal device, connecting various parts of the user terminal via various interfaces and lines.

[0131] The aforementioned memory can be used to store computer programs and / or modules. The aforementioned processor implements various functions of the aforementioned terminal device by running or executing the computer programs and / or modules stored in the memory, and by calling data stored in the memory. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as information collection template display function, product information publishing function, etc.); the data storage area may store data created based on the use of the berth status display system (such as product information collection templates corresponding to different product types, product information that different product providers need to publish, etc.). In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0132] If the modules / units integrated into the terminal device are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the modules / units in the systems of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the functions of the various system embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0133] It should be noted that, in this document, the term "comprising" or any other variation thereof is intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0134] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A wind power plant inspection method, characterized in that, The method comprises: obtaining a position distribution table of wind power equipment and a line network diagram connected with the wind power equipment, and obtaining road condition information based on the position distribution table and the line network diagram; the road condition information is a mapping of air parameters; activating a preset monitoring point in the line network based on the road condition information, and obtaining power transmission data of the monitoring point; analyzing the power transmission data to determine an abnormal device; determining an inspection parameter according to the abnormal device and the road condition information.

2. The wind power plant inspection method according to claim 1, characterized in that, The step of obtaining a position distribution table of wind power equipment and a line network diagram connected with the wind power equipment, and obtaining road condition information based on the position distribution table and the line network diagram comprises: obtaining line network record information, and determining a line network diagram according to a preset scale; obtaining a position distribution table of wind power equipment, and querying and marking a device node corresponding to the wind power equipment in the line network diagram based on the position distribution table; sequentially obtaining road condition information within a preset range corresponding to the device node based on an existing map service, and inserting the road condition information into the line network diagram; real-time obtaining of air parameters, and correction of the road condition information in the line network diagram according to the air parameters.

3. The wind power plant inspection method according to claim 2, characterized in that, The step of real-time obtaining of air parameters, and correction of the road condition information in the line network diagram according to the air parameters comprises: real-time obtaining of air parameters within a range corresponding to the line network diagram based on an existing weather service; the air parameters are represented by a matrix; the position of each element in the matrix corresponds to an actual position; querying of influence parameters in a preset influence parameter library according to the air parameters; the influence parameters are used to represent the influence degree on each type of road; correction of the road condition information in the line network diagram according to the queried influence parameters based on a spatial scale relationship.

4. The wind power plant inspection method according to claim 1, characterized in that, The step of activating a preset monitoring point in the line network based on the road condition information, and obtaining power transmission data of the monitoring point comprises: inputting the road condition information into a preset information recognition model, and outputting a risk level; determining a monitoring density according to the risk level, and activating a monitoring point in the preset line network based on the monitoring density; determining a queue according to the relative position of the monitoring point in the line network, and real-time obtaining of power transmission data based on the queue.

5. The wind power plant inspection method according to claim 4, characterized in that, The step of analyzing the power transmission data to determine an abnormal device comprises: establishing a reference map according to the relative position of the monitoring point in the line network; the reference map contains a mapping area corresponding to the monitoring point; the shape and size of the mapping area are determined by the road condition information within a preset radius corresponding to the monitoring point; the size of the mapping area is proportional to the difficulty of passing; the difficulty of passing is determined by the parameters of the allowed passing subject; establishing a polar coordinate system with the mapping area as the center; reading the power transmission data in the queue, and filling into the polar coordinate system; wherein, the angle of the polar coordinate is determined by the derivative of the power transmission data, and the distance of the polar coordinate is determined by the data amount; determining an abnormal mapping area in the filled reference map based on a preset feature library, and determining an abnormal device and a predicted abnormal type of the abnormal device according to the abnormal mapping area.

6. The wind power plant inspection method according to claim 5, characterized in that, The step of determining an inspection parameter according to the abnormal device and the road condition information comprises: determining a maintenance tool according to the predicted abnormal type of each abnormal device; determining a carrying subject according to the shape and size of the mapping area corresponding to each abnormal device; The maintenance path is determined according to the positional relationship of each abnormal device and the predicted abnormal type.

7. A wind power plant inspection system, characterized in that The system comprises: A road condition information acquisition module is configured to acquire a location distribution table of wind power equipment and a line network diagram connected to the wind power equipment, and acquire road condition information based on the location distribution table and the line network diagram; the road condition information is a mapping of air parameters; A power data acquisition module is configured to activate monitoring points in a preset line network based on the road condition information, and acquire power transmission data of the monitoring points; A data analysis module is configured to analyze the power transmission data and determine abnormal equipment; An inspection parameter determination module is configured to determine inspection parameters according to the abnormal equipment and the road condition information.

8. The wind power plant inspection system of claim 7, wherein, The road condition information acquisition module comprises: A line network diagram determination unit is configured to acquire line network filing information and determine a line network diagram according to a preset scale; An equipment node marking unit is configured to acquire a location distribution table of wind power equipment, query and mark equipment nodes corresponding to the wind power equipment in the line network diagram based on the location distribution table; A road condition information filling unit is configured to sequentially acquire road condition information within a preset range corresponding to the equipment nodes based on existing map services, and insert the road condition information into the line network diagram; A road condition information correction unit is configured to acquire air parameters in real time, and correct the road condition information in the line network diagram according to the air parameters.

9. The wind power plant inspection system of claim 7, wherein, The power data acquisition module comprises: An information recognition unit is configured to input the road condition information into a preset information recognition model, and output a risk level; A monitoring point activation unit is configured to determine a monitoring density according to the risk level, and activate monitoring points in a preset line network based on the monitoring density; An acquisition execution unit is configured to determine a queue according to the relative positions of the monitoring points in the line network, and acquire power transmission data in real time based on the queue.

10. The wind power plant inspection system of claim 9, wherein, The data analysis module comprises: A reference map establishment unit is configured to establish a reference map according to the relative positions of the monitoring points in the line network; the reference map contains a mapping area corresponding to the monitoring points; the shape and size of the mapping area are determined by road condition information within a preset radius corresponding to the monitoring points; the size of the mapping area is directly proportional to the difficulty of passing through the road condition information; the difficulty of passing through is determined by parameters of a passing subject; A polar coordinate system establishment unit is configured to establish a polar coordinate system with the mapping area as the center; A filling execution unit is configured to read power transmission data in the queue and fill it into the polar coordinate system; wherein the angle of the polar coordinate is determined by the derivative of the power transmission data, and the distance of the polar coordinate is determined by the data amount; An abnormality recognition unit is configured to determine an abnormal mapping area in the filled reference map based on a preset feature library, and determine abnormal equipment and a predicted abnormal type of the abnormal equipment according to the abnormal mapping area.

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