Data processing method and device of power line and computer equipment

Abstract

The invention relates to a data processing method and device of a power line and computer equipment. The method comprises the following steps: acquiring current line data of each data acquisition type obtained by performing data acquisition on a target power line by unmanned aerial vehicle inspection equipment, and optimizing a standard map area corresponding to the target power line according to the current line data of each data acquisition type to obtain an updated map area, and determining an abnormal line area corresponding to the target power line according to difference information between the standard map area and the updated map area. By adopting the method, the operation safety of the power line can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of equipment inspection, and in particular to a data processing method, device and computer equipment for power lines. Background Art

[0002] With the continuous development of the power industry, in order to ensure the reliability of power line operation, it is necessary to collect industrial data on power lines. Among them, industrial data refers to information such as the physical quantities and status of power lines in industrial sites.

[0003] In the existing technology, industrial data can generally only be collected in a single dimension, which reduces the comprehensiveness of power line status analysis and thus reduces the safety of power line operation. Summary of the Invention

[0004] Based on this, it is necessary to provide a data processing method, device and computer equipment for power lines that can improve the safety of power line operation in response to the above technical problems.

[0005] In a first aspect, the present application provides a data processing method for a power line, which is applied to a data processing end and includes:

[0006] Obtain current line data of each data collection type obtained by the drone inspection equipment through data collection on the target power line;

[0007] Based on the current line data of each data collection type, the standard map area corresponding to the target power line is optimized to obtain an updated map area;

[0008] According to the difference information between the standard map area and the updated map area, the abnormal line area corresponding to the target power line is determined.

[0009] In one embodiment, based on the current line data of each data collection type, the standard map area corresponding to the target power line is optimized to obtain an updated map area, including:

[0010] The current line data of each data collection type is fused and processed to obtain the global line data corresponding to the target power line;

[0011] The global line data is used to optimize the standard map area corresponding to the target power line to obtain the updated map area.

[0012] In one embodiment, the method further comprises:

[0013] The area identifier of the abnormal line area is sent to the drone inspection device, so that the drone inspection device performs a secondary inspection of the abnormal line area to obtain abnormal inspection data corresponding to the abnormal line area;

[0014] According to the abnormal inspection data and the standard abnormal characteristics corresponding to the target power line, the inspection results corresponding to the abnormal line area are determined.

[0015] In one embodiment, determining the inspection result corresponding to the abnormal line area based on the standard abnormal features corresponding to the target power line of the abnormal inspection data includes:

[0016] Extract the current abnormal features of the target power line from the abnormal inspection data;

[0017] Determine the feature similarity between the current abnormal feature and each standard abnormal feature corresponding to the target power line, and use the standard abnormal feature with the greatest feature similarity as the target abnormal feature;

[0018] According to the abnormal inspection data and the target abnormal characteristics, the inspection results corresponding to the abnormal line area are determined.

[0019] In a second aspect, the present application provides a data processing method for power lines, which is applied to drone inspection equipment, comprising:

[0020] In response to a data collection instruction for a target power line, the data collection instruction is parsed to obtain at least two data collection types and data collection parameters corresponding to each data collection type;

[0021] According to the data acquisition parameters corresponding to each data acquisition type, data is collected on the target power line to obtain the current line data of each data acquisition type;

[0022] The current line data of each data collection type is sent to the data processing end, so that the data processing end determines the abnormal line area corresponding to the target power line according to the current line data of each data collection type.

[0023] In one embodiment, data is collected on a target power line according to data collection parameters corresponding to each data collection type to obtain current line data of each data collection type, including:

[0024] According to the data acquisition parameters corresponding to each data acquisition type, data pre-acquisition is performed on the target power line to obtain pre-acquired line data of each data acquisition type;

[0025] For each data collection type, reliability verification is performed on the data collection parameters corresponding to the data collection type based on the pre-collected line data of the data collection type and the standard line data range corresponding to the data collection type;

[0026] When the reliability verification of the data acquisition parameters corresponding to each data acquisition type is passed, data acquisition is performed on the target power line according to the data acquisition parameters corresponding to each data acquisition type to obtain the current line data of each data acquisition type;

[0027] In the case that the reliability check of the data acquisition parameters corresponding to the abnormal acquisition types in each data acquisition type fails, the data acquisition parameters corresponding to the abnormal acquisition types in the data acquisition parameters corresponding to each data acquisition type are corrected, and data acquisition is performed on the target power line based on the corrected data acquisition parameters corresponding to each data acquisition type to obtain current line data of each data acquisition type.

[0028] In one embodiment, correcting the data acquisition parameters corresponding to the abnormal data acquisition types among the data acquisition parameters corresponding to the data acquisition types includes:

[0029] Determining parameter correction information based on an error value between pre-collected line data of an abnormal collection type and a threshold value of a standard line data range corresponding to the abnormal collection type;

[0030] According to the parameter correction information, the data collection parameters corresponding to the abnormal collection type are corrected.

[0031] In a third aspect, the present application further provides a data processing device for a power line, which is applied to a data processing terminal and includes:

[0032] The first acquisition module is used to obtain current line data of various data collection types obtained by the drone inspection equipment from collecting data on the target power line;

[0033] An optimization module is used to optimize the standard map area corresponding to the target power line based on the current line data of each data collection type to obtain an updated map area;

[0034] The abnormality determination module is used to determine the abnormal line area corresponding to the target power line according to the difference information between the standard map area and the updated map area.

[0035] In a fourth aspect, the present application further provides a data processing device for power lines, which is applied to drone inspection equipment, and the device includes:

[0036] an instruction parsing module, configured to respond to a data collection instruction for a target power line and parse the data collection instruction to obtain at least two data collection types and data collection parameters corresponding to each data collection type;

[0037] The second acquisition module is used to collect data from the target power line according to the data collection parameters corresponding to each data collection type, and obtain the current line data of each data collection type;

[0038] The data sending module is used to send the current line data of each data collection type to the data processing end, so that the data processing end determines the abnormal line area corresponding to the target power line according to the current line data of each data collection type.

[0039] In a fifth aspect, the present application further provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0040] Obtain current line data of each data collection type obtained by the drone inspection equipment through data collection on the target power line;

[0041] Based on the current line data of each data collection type, the standard map area corresponding to the target power line is optimized to obtain an updated map area;

[0042] According to the difference information between the standard map area and the updated map area, the abnormal line area corresponding to the target power line is determined.

[0043] In a sixth aspect, the present application further provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0044] In response to a data collection instruction for a target power line, the data collection instruction is parsed to obtain at least two data collection types and data collection parameters corresponding to each data collection type;

[0045] According to the data acquisition parameters corresponding to each data acquisition type, data is collected on the target power line to obtain the current line data of each data acquisition type;

[0046] The current line data of each data collection type is sent to the data processing end, so that the data processing end determines the abnormal line area corresponding to the target power line according to the current line data of each data collection type.

[0047] In a seventh aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:

[0048] Obtain current line data of each data collection type obtained by the drone inspection equipment through data collection on the target power line;

[0049] Based on the current line data of each data collection type, the standard map area corresponding to the target power line is optimized to obtain an updated map area;

[0050] According to the difference information between the standard map area and the updated map area, the abnormal line area corresponding to the target power line is determined.

[0051] In an eighth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:

[0052] In response to a data collection instruction for a target power line, the data collection instruction is parsed to obtain at least two data collection types and data collection parameters corresponding to each data collection type;

[0053] According to the data acquisition parameters corresponding to each data acquisition type, data is collected on the target power line to obtain the current line data of each data acquisition type;

[0054] The current line data of each data collection type is sent to the data processing end, so that the data processing end determines the abnormal line area corresponding to the target power line according to the current line data of each data collection type.

[0055] In a ninth aspect, the present application further provides a computer program product, comprising a computer program, which, when executed by a processor, implements the following steps:

[0056] Obtain current line data of each data collection type obtained by the drone inspection equipment through data collection on the target power line;

[0057] Based on the current line data of each data collection type, the standard map area corresponding to the target power line is optimized to obtain an updated map area;

[0058] According to the difference information between the standard map area and the updated map area, the abnormal line area corresponding to the target power line is determined.

[0059] In a tenth aspect, the present application further provides a computer program product, comprising a computer program, which, when executed by a processor, implements the following steps:

[0060] In response to a data collection instruction for a target power line, the data collection instruction is parsed to obtain at least two data collection types and data collection parameters corresponding to each data collection type;

[0061] According to the data acquisition parameters corresponding to each data acquisition type, data is collected on the target power line to obtain the current line data of each data acquisition type;

[0062] The current line data of each data collection type is sent to the data processing end, so that the data processing end determines the abnormal line area corresponding to the target power line according to the current line data of each data collection type.

[0063] In the above-mentioned power line data processing method, apparatus, and computer equipment, the data processing end obtains current line data of each data collection type obtained by drone inspection equipment through data collection on the target power line, and optimizes the standard map area corresponding to the target power line based on the current line data of each data collection type to obtain an updated map area, thereby determining the abnormal line area corresponding to the target power line based on the difference information between the standard map area and the updated map area. Compared to the related art that only uses inspection data under a single dimension to inspect the operation of the circuit line, the above-mentioned method optimizes the standard map area by combining current line data of multiple data collection types, and determines the abnormal line area based on the difference between the optimized updated map area and the standard map area. This can ensure the reliability of the positioning of the abnormal line area, thereby improving the safety of power line operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments of the present application or related technical descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying any creative work.

[0065] Figure 1 1 is a flow chart of a method for processing data of a power line according to an embodiment;

[0066] Figure 2 A schematic diagram of a process for determining an updated map area in one embodiment;

[0067] Figure 3 A schematic diagram of a process for determining an inspection result in one embodiment;

[0068] Figure 4 A schematic diagram of a flow chart of data processing of a power line in another embodiment;

[0069] Figure 5 A schematic diagram of a process for obtaining current line data in one embodiment;

[0070] Figure 6 is a schematic diagram of a flow chart of data processing of a power line in yet another embodiment;

[0071] Figure 7is a structural block diagram of a data processing device for a power line in one embodiment;

[0072] Figure 8 is a structural block diagram of a data processing device for a power line in another embodiment;

[0073] Figure 9 FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0074] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0075] With the continuous development of the power industry, in order to ensure the reliability of power line operation, it is necessary to collect industrial data on power lines. Among them, industrial data refers to information such as the physical quantities and status of power lines in industrial sites.

[0076] In the existing technology, industrial data can generally only be collected in a single dimension, which reduces the comprehensiveness of power line status analysis and thus reduces the safety of power line operation.

[0077] Based on this, in an exemplary embodiment, a data processing method for a power line is provided, and the method is described by taking the application of the method to a data processing end as an example. Figure 1 As shown, the specific steps include:

[0078] S101, obtaining current line data of various data collection types obtained by the drone inspection equipment through data collection on the target power line.

[0079] Among them, the so-called drone inspection equipment is the drone equipment used to inspect power lines; the so-called target power line is the power line with inspection needs; the so-called data collection type is the data type of the inspection data collected by the drone inspection equipment, for example, it may include but is not limited to point cloud data, image data, location information and inspection information of the area where the target power line is located; the so-called current line data is the inspection data of the target power line collected at the current moment.

[0080] Optionally, in order to improve the comprehensiveness of data collection, the laser radar, visual sensor, communication module and other equipment on the drone inspection equipment can be instructed to collect data on the target power line from multiple preset dimensions, so as to obtain the current line data of each data collection type corresponding to the target power line.

[0081] For example, the laser radar, visual sensor and communication module on the drone inspection equipment can be used to collect images of the target power line from the point cloud data dimension, image data dimension, location information dimension and inspection information dimension, thereby obtaining point cloud data, image data, location information and inspection information of the area where the target power line is located.

[0082] Furthermore, the drone inspection equipment will send the collected data to the airport (drone management end), and the airport will send it to the data processing end.

[0083] S102 , optimizing the standard map area corresponding to the target power line according to the current line data of each data collection type to obtain an updated map area.

[0084] The so-called standard map area is the standard map area where the target power line is located; the so-called updated map area is the map area obtained by updating the standard map area based on the collected data.

[0085] It is understood that to ensure the reliable operation of the target power line, a standard map area corresponding to the target power line can be constructed in advance based on the deployment and location information of each power device on the target power line, as well as the target power line's environmental information. Furthermore, based on the common defect types of each power device on the target power line, a sample defect library corresponding to the target power line is constructed, including, for example, tower damage, various defects, line heating, loose bolts, and so on.

[0086] In an optional embodiment, after obtaining the current route data, the current route data and the standard map area under each data collection type can be simultaneously input into a trained first optimization model, and the first optimization model outputs an updated map area based on the current route data, the standard map area and the model parameters.

[0087] In another optional implementation, the current route data under each data collection type may be fused first, and the result of the fusion process may be used to optimize the standard map area, thereby obtaining an updated map area.

[0088] S103 , determining an abnormal line area corresponding to the target power line according to difference information between the standard map area and the updated map area.

[0089] The so-called abnormal line area is an area where abnormalities exist in the target power line.

[0090] Optionally, a consistency comparison can be performed between the standard map area and the updated map area. If the comparison results are consistent, it can be determined that the target power line is operating normally. If the comparison results are inconsistent, the abnormal line area corresponding to the target power line can be determined based on the difference information and the information type of the abnormal information between the standard map area and the updated map area.

[0091] For example, if the difference information between the standard map area and the updated map area is environmental information, it can be determined that the target power line is operating normally, but the location information corresponding to the abnormal environment needs to be sent to the corresponding operation and maintenance end for management by the operation and maintenance end; if the difference information between the standard map area and the updated map area is line information, it can be determined that there is an abnormality in the operation of the target power line. At this time, the abnormal line area can be determined based on the location information of the abnormal line.

[0092] In the above-mentioned power line data processing method, the data processing end obtains current line data of each data collection type obtained by drone inspection equipment through data collection on the target power line, and optimizes the standard map area corresponding to the target power line based on the current line data of each data collection type to obtain an updated map area, thereby determining the abnormal line area corresponding to the target power line based on the difference information between the standard map area and the updated map area. Compared to the related art that only uses inspection data under a single dimension to inspect the operation of the circuit line, the above-mentioned method optimizes the standard map area by combining current line data of multiple data collection types, and determines the abnormal line area based on the difference between the optimized updated map area and the standard map area. This can ensure the reliability of the positioning of the abnormal line area, thereby improving the safety of power line operation.

[0093] In order to ensure the accuracy of the updated map area, based on the above embodiment, in the embodiment of the present application, an optional method for determining the updated map area is provided, such as Figure 2 As shown, the specific steps include:

[0094] S201 , fusing the current line data of each data collection type to obtain global line data corresponding to the target power line.

[0095] The so-called global line data refers to the overall inspection data of the area where the target power line is located.

[0096] In an optional embodiment, the current line data of each data acquisition type can be simultaneously input into a trained fusion model, and the fusion model outputs the global line data corresponding to the target power line based on the current line data of each data acquisition type and model parameters.

[0097] In another optional embodiment, for each location information, the current line data of each data collection type on the location information can be superimposed and fused to obtain the line data on the location information; then, the line data on each location information is combined to obtain the global line data corresponding to the target power line.

[0098] S202 , using global line data, optimizing the standard map area corresponding to the target power line to obtain an updated map area.

[0099] Optionally, the global line data and the standard map area corresponding to the target power line can be simultaneously input into the second optimization model, and the second optimization model outputs the updated map area corresponding to the target power line based on the global line data, the standard map area and the model parameters.

[0100] In the embodiment of the present application, the standard map area is optimized by using the aggregated global route data to obtain the updated map area, which can ensure the accuracy of the updated map area.

[0101] In order to ensure the accuracy of the inspection results of the target power line, based on the above embodiment, in the embodiment of the present application, an optional method for determining the inspection results is provided, such as Figure 3 As shown, the specific steps include:

[0102] S301, sending the area identifier of the abnormal line area to the drone inspection device, so that the drone inspection device performs a secondary inspection on the abnormal line area to obtain abnormal inspection data corresponding to the abnormal line area.

[0103] Among them, the so-called area identifier is the unique identification information corresponding to the abnormal line area. Furthermore, the location information of the abnormal line area can be determined based on the area identifier; the so-called secondary inspection is to re-inspect the abnormal line area in the target power line; the so-called abnormal inspection data is the line data collected from the secondary inspection of the abnormal line area.

[0104] Optionally, after determining the abnormal line area, the area identification of the abnormal line area can be sent to the drone inspection equipment; the drone inspection equipment can parse the area identification of the abnormal line area to obtain the location information of the abnormal line area, and perform a secondary inspection on the abnormal line area based on the location information of the abnormal line area, and collect abnormal inspection data corresponding to the abnormal line area.

[0105] Furthermore, the drone inspection equipment can send the collected abnormal inspection data to the data processing end.

[0106] S302 : Determine an inspection result corresponding to the abnormal line area based on the abnormal inspection data and various standard abnormal features corresponding to the target power line.

[0107] Among them, the so-called standard abnormal features are the line defects in the sample defect library corresponding to the target power line, such as tower damage, various defects, line heating, loose bolts, etc.

[0108] In an optional embodiment, the abnormal inspection data can be input into the inspection result determination model trained based on the standard abnormal features corresponding to the target power line. The inspection result determination model outputs the inspection result corresponding to the abnormal line area based on the abnormal inspection data and model parameters.

[0109] In another optional embodiment, the current abnormal characteristics of the target power line can be extracted from the abnormal inspection data; the feature similarity between the current abnormal characteristics and the standard abnormal characteristics corresponding to the target power line is determined, and the standard abnormal feature with the greatest feature similarity is used as the target abnormal feature; based on the abnormal inspection data and the target abnormal characteristics, the inspection result corresponding to the abnormal line area is determined.

[0110] Among them, the so-called current abnormal feature is the abnormal line feature in the target power line at the current moment; the so-called feature similarity is used to characterize the similarity between the abnormal line feature and the standard abnormal feature; the so-called target abnormal feature is the standard abnormal feature with the greatest similarity to the current abnormal feature.

[0111] Optionally, current abnormal features related to the target power line can be extracted from the abnormal inspection data, and for each standard abnormal feature, the feature similarity of the standard abnormal feature can be determined based on the degree of similarity between the standard abnormal feature and the current abnormal feature.

[0112] Furthermore, the standard abnormal feature with the greatest feature similarity among all standard abnormal features can be used as the target abnormal feature; thereafter, the inspection results corresponding to the abnormal line area can be generated based on the image information and the target abnormal feature in the abnormal inspection data, and the inspection results can be sent to the operation and maintenance end, so that the operation and maintenance end can formulate an abnormal recovery plan based on the image information and the target abnormal feature in the inspection results.

[0113] In the embodiment of the present application, by determining the inspection result corresponding to the abnormal line area based on the abnormal inspection data and the standard abnormal characteristics corresponding to the target power line, the accuracy of the inspection result can be guaranteed.

[0114] On the basis of the above embodiments, in the embodiments of the present application, the method is applied to drone inspection equipment as an example to illustrate a data processing method for power lines, such as Figure 4As shown, the specific steps include:

[0115] S401 : In response to a data collection instruction for a target power line, the data collection instruction is parsed to obtain at least two data collection types and data collection parameters corresponding to each data collection type.

[0116] The so-called data collection instruction is an instruction for collecting data from the target power line; the so-called data collection parameters are relevant parameters during data collection, including but not limited to collection accuracy and collection range. It is understood that collaborative information between different collection channels can be established based on the communication protocol, and data collection instructions can be established based on the distribution information of the power lines.

[0117] Optionally, to ensure data collection reliability, after obtaining a data collection instruction for the target power line, the instruction can be parsed to obtain current parsing information, at least two data collection types, and data collection parameters corresponding to each data collection type. The current parsing information is used to indicate the data processing method in the current parsing process.

[0118] Furthermore, the current resolution deviation rate can be obtained based on the difference between the current resolution information and the preset standard resolution information, and it can be determined whether the current resolution deviation rate is greater than or equal to the set standard resolution deviation rate. If so, a resolution adjustment strategy is generated based on the difference between the current resolution information and the preset standard resolution information, and the current acquisition instruction is subjected to a secondary analysis based on the resolution adjustment strategy; if not, subsequent data acquisition processing is performed directly based on the data acquisition parameters corresponding to each data acquisition type obtained by the first analysis.

[0119] S402 , performing data collection on the target power line according to the data collection parameters corresponding to each data collection type, and obtaining current line data of each data collection type.

[0120] Optionally, multi-channel data acquisition parameters may be established based on the data acquisition parameters corresponding to each data acquisition type, and the data acquisition parameters of each acquisition channel may be analyzed to establish linkage information of the acquisition channels.

[0121] Furthermore, linkage collection information of the collection channels can be established based on the linkage information, and collection deviation information can be analyzed based on the linkage collection information; then, the linkage collection parameters can be adjusted based on the collection deviation information, and according to the linkage collection parameters, in the process of data collection of the target power line, the collection parameters of different collection channels can be dynamically adjusted to obtain the current line data of each data collection type.

[0122] S403 , sending the current line data of each data collection type to the data processing end, so that the data processing end determines the abnormal line area corresponding to the target power line according to the current line data of each data collection type.

[0123] Optionally, after collecting the current line data, the current line data of each data collection type can be sent to the data processing end through the airport; after receiving the current line data, the data collection end can optimize the standard map area corresponding to the target power line according to the current line data of each data collection type to obtain an updated map area, and determine the abnormal line area corresponding to the target power line based on the difference information between the standard map area and the updated map area.

[0124] In the above-mentioned data processing method for power lines, the drone inspection equipment parses the data acquisition instructions to obtain at least two data acquisition types and data acquisition parameters corresponding to each data acquisition type, and performs data acquisition on the target power line according to the data acquisition parameters corresponding to each data acquisition type to obtain current line data of each data acquisition type; then, the current line data of each data acquisition type is sent to the data processing end, so that the data processing end determines the abnormal line area corresponding to the target power line according to the current line data of each data acquisition type, thereby ensuring the accuracy of data acquisition.

[0125] In order to ensure the reliability of the current line data acquisition, based on the above embodiment, in the embodiment of the present application, an optional method for obtaining the current line data is provided, such as Figure 5 As shown, the specific steps include:

[0126] S501 , performing data pre-collection on a target power line according to data collection parameters corresponding to each data collection type, to obtain pre-collected line data of each data collection type.

[0127] The so-called pre-collection is the data collection and processing performed in a short period of time before the formal data collection, which is used to test the accuracy of the data collection parameters. The so-called pre-collected line data is the line data collected during the pre-collection process.

[0128] Optionally, data pre-collection may be performed on the target power line within a preset time period according to data collection parameters corresponding to each data collection type, thereby obtaining pre-collected line data of each data collection type.

[0129] S502 , for each data collection type, performing reliability verification on data collection parameters corresponding to the data collection type based on pre-collected line data of the data collection type and a standard line data range corresponding to the data collection type.

[0130] The so-called standard line data range is the data range corresponding to the standard line data. Furthermore, the so-called standard line data is used to represent standardized line data.

[0131] Optionally, for each data collection type, the pre-collected line data of the data collection type may be compared with a standard line data range corresponding to the data collection type, thereby performing reliability verification on the data collection parameters corresponding to the data collection type.

[0132] Exemplarily, if the pre-collected line data of the data collection type is within the standard line data range corresponding to the data collection type, the reliability check of the data collection parameters corresponding to the data collection type passes; if the pre-collected line data of the data collection type is outside the standard line data range corresponding to the data collection type, the reliability check of the data collection parameters corresponding to the data collection type fails.

[0133] S503 , when the reliability checks of the data acquisition parameters corresponding to each data acquisition type are all passed, data acquisition is performed on the target power line according to the data acquisition parameters corresponding to each data acquisition type to obtain current line data of each data acquisition type.

[0134] Optionally, when the reliability checks of the data acquisition parameters corresponding to each data acquisition type are passed, it is proved that the data acquisition parameters corresponding to each data acquisition type are reliable. At this time, data acquisition can be directly performed on the target power line according to the data acquisition parameters corresponding to each data acquisition type to obtain the current line data of each data acquisition type.

[0135] S504, when the reliability check of the data acquisition parameters corresponding to the abnormal acquisition type in each data acquisition type fails, the data acquisition parameters corresponding to the abnormal acquisition type in the data acquisition parameters corresponding to each data acquisition type are corrected, and data acquisition is performed on the target power line based on the corrected data acquisition parameters corresponding to each data acquisition type to obtain current line data of each data acquisition type.

[0136] The so-called abnormal collection type is a data collection type that fails the reliability check of the data collection parameters.

[0137] Optionally, when the reliability check of the data acquisition parameters corresponding to the abnormal acquisition type fails in each data acquisition type, the data acquisition parameters corresponding to the abnormal acquisition type can be corrected; thereafter, data acquisition is performed on the target power line based on the data acquisition parameters corresponding to each data acquisition type after correction to obtain the current line data of each data acquisition type.

[0138] In an optional implementation, the data acquisition parameters corresponding to the abnormal acquisition type may be directly input into a trained correction model, and the correction processing model outputs the corrected data acquisition parameters based on the data acquisition parameters and the model parameters.

[0139] In another optional embodiment, parameter correction information can be determined based on the error between the pre-collected line data of the abnormal collection type and a threshold value within the standard line data range corresponding to the abnormal collection type. Based on the parameter correction information, the data collection parameters corresponding to the abnormal collection type are corrected. The parameter correction information is information related to the correction of the data collection parameters corresponding to the abnormal collection type.

[0140] Specifically, an upper error limit and a lower error limit can be determined based on a threshold within the standard line data range. The pre-collected line data can then be compared with the lower error limit to obtain a first error value. The pre-collected line data can then be compared with the upper error limit to obtain a second error value. Parameter correction information can then be generated based on the first and second error values.

[0141] Furthermore, the data acquisition parameters corresponding to the abnormal acquisition type may be corrected based on the parameter correction information. For example, the parameter adjustment values ​​in the parameter correction information may be used to correct the data acquisition parameters corresponding to the abnormal acquisition type.

[0142] In an embodiment of the present application, data pre-collection processing is introduced. By performing reliability verification on the data collection parameters corresponding to the data collection type based on the standard line data range corresponding to the data collection type and the pre-collected line data, and correcting the data collection parameters that fail, the reliability of data collection can be effectively improved.

[0143] Figure 6 This is a schematic diagram of the interaction between the data processing end and the drone inspection equipment in another embodiment of the power line data processing method. Based on the above embodiment, this embodiment provides another optional example of the power line data processing method. Figure 6 The specific implementation process is as follows:

[0144] S601, the data processing end sends a data collection instruction to the drone inspection equipment through the airport.

[0145] S602: The UAV inspection device parses the data collection instruction to obtain at least two data collection types and data collection parameters corresponding to each data collection type.

[0146] S603 , performing data collection on the target power line according to the data collection parameters corresponding to each data collection type, and obtaining current line data of each data collection type.

[0147] Optionally, data pre-collection is performed on the target power line according to the data collection parameters corresponding to each data collection type to obtain pre-collected line data of each data collection type; for each data collection type, reliability verification is performed on the data collection parameters corresponding to the data collection type according to the pre-collected line data of the data collection type and the standard line data range corresponding to the data collection type; when the reliability verification of the data collection parameters corresponding to each data collection type passes, data collection is performed on the target power line according to the data collection parameters corresponding to each data collection type to obtain current line data of each data collection type; when there is an abnormal collection type in each data collection type and the reliability verification of the data collection parameters corresponding to the abnormal collection type fails, the data collection parameters corresponding to the abnormal collection type in the data collection parameters corresponding to each data collection type are corrected, and data collection is performed on the target power line according to the corrected data collection parameters corresponding to each data collection type to obtain current line data of each data collection type.

[0148] Furthermore, parameter correction information is determined based on the error value between the pre-collected line data of the abnormal collection type and the threshold value of the standard line data range corresponding to the abnormal collection type; and the data collection parameters corresponding to the abnormal collection type are corrected based on the parameter correction information.

[0149] S604, the drone inspection device sends the current line data of each data collection type to the data processing end.

[0150] S605: The data processing end performs fusion processing on the current line data of each data collection type to obtain the global line data corresponding to the target power line.

[0151] S606 , using the global line data, optimizing the standard map area corresponding to the target power line to obtain an updated map area.

[0152] S607 : Determine the abnormal line area corresponding to the target power line according to the difference information between the standard map area and the updated map area.

[0153] S608: Send the area identifier of the abnormal line area to the drone inspection device, so that the drone inspection device performs a secondary inspection on the abnormal line area to obtain abnormal inspection data corresponding to the abnormal line area.

[0154] S609 , determining an inspection result corresponding to the abnormal line area according to the abnormal inspection data and various standard abnormal features corresponding to the target power line.

[0155] Optionally, the current abnormal features of the target power line are extracted from the abnormal inspection data; the feature similarity between the current abnormal features and the standard abnormal features corresponding to the target power line is determined, and the standard abnormal feature with the greatest feature similarity is used as the target abnormal feature; based on the abnormal inspection data and the target abnormal feature, the inspection result corresponding to the abnormal line area is determined.

[0156] The specific process of the above S601-S609 can be found in the description of the above method embodiment. The implementation principle and technical effects are similar and will not be repeated here.

[0157] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above can include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0158] Based on the same inventive concept, embodiments of the present application also provide a power line data processing device for implementing the aforementioned power line data processing method. The implementation solution provided by this device is similar to the implementation solution described in the aforementioned method. Therefore, the specific limitations of the one or more power line data processing device embodiments provided below can be found in the above-mentioned limitations of the power line data processing method and will not be repeated here.

[0159] In an exemplary embodiment, Figure 7 As shown, a data processing device 1 for a power line is provided, which is applied to a data processing end and includes: a first acquisition module 10, an optimization module 20 and an abnormality determination module 30, wherein:

[0160] The first acquisition module 110 is used to acquire current line data of various data collection types obtained by the drone inspection equipment from collecting data on the target power line;

[0161] An optimization module 120 is configured to optimize the standard map area corresponding to the target power line based on the current line data of each data collection type to obtain an updated map area;

[0162] The abnormality determination module 130 is configured to determine an abnormal line area corresponding to a target power line according to difference information between the standard map area and the updated map area.

[0163] In an exemplary embodiment, the optimization module 120 is specifically configured to:

[0164] The current line data of each data collection type are fused to obtain the global line data corresponding to the target power line; the global line data is used to optimize the standard map area corresponding to the target power line to obtain the updated map area.

[0165] In an exemplary embodiment, the power line data processing device 1 further includes a result determination module, wherein the so-called result determination module includes:

[0166] A data acquisition unit is used to send the area identifier of the abnormal line area to the drone inspection device, so that the drone inspection device performs a secondary inspection on the abnormal line area to obtain abnormal inspection data corresponding to the abnormal line area;

[0167] The result determination unit is used to determine the inspection result corresponding to the abnormal line area according to the abnormal inspection data and various standard abnormal features corresponding to the target power line.

[0168] In an exemplary embodiment, the result determination unit is specifically configured to:

[0169] Extract the current abnormal features of the target power line from the abnormal inspection data; determine the feature similarity between the current abnormal features and the standard abnormal features corresponding to the target power line, and use the standard abnormal feature with the greatest feature similarity as the target abnormal feature; determine the inspection results corresponding to the abnormal line area based on the abnormal inspection data and the target abnormal features.

[0170] In an exemplary embodiment, Figure 8 As shown, a data processing device 2 for a power line is provided, which is applied to a data processing end and includes: an instruction parsing module 210, a second acquisition module 220 and a data sending module 230:

[0171] The instruction parsing module 210 is configured to parse the data collection instruction in response to the data collection instruction for the target power line to obtain at least two data collection types and data collection parameters corresponding to each data collection type;

[0172] The second acquisition module 220 is used to collect data from the target power line according to the data collection parameters corresponding to each data collection type, and obtain the current line data of each data collection type;

[0173] The data sending module 230 is used to send the current line data of each data collection type to the data processing end, so that the data processing end determines the abnormal line area corresponding to the target power line according to the current line data of each data collection type.

[0174] In an exemplary embodiment, the second acquisition module 220 includes:

[0175] A pre-collection unit, configured to pre-collect data on a target power line according to data collection parameters corresponding to each data collection type, and obtain pre-collected line data of each data collection type;

[0176] A verification unit is used to perform reliability verification on data acquisition parameters corresponding to each data acquisition type based on pre-collected line data of the data acquisition type and a standard line data range corresponding to the data acquisition type;

[0177] The first acquisition unit is configured to acquire data from a target power line according to the data acquisition parameters corresponding to each data acquisition type, if the reliability verification of the data acquisition parameters corresponding to each data acquisition type is passed, to obtain current line data of each data acquisition type;

[0178] The second acquisition unit is used to correct the data acquisition parameters corresponding to the abnormal acquisition type among the data acquisition parameters corresponding to each data acquisition type when the reliability check of the data acquisition parameters corresponding to the abnormal acquisition type among the data acquisition parameters corresponding to each data acquisition type fails, and to perform data acquisition on the target power line based on the corrected data acquisition parameters corresponding to each data acquisition type to obtain current line data of each data acquisition type.

[0179] In an exemplary embodiment, the second acquisition unit is specifically configured to:

[0180] Parameter correction information is determined based on the error value between the pre-collected line data of the abnormal collection type and the threshold value of the standard line data range corresponding to the abnormal collection type; and the data collection parameters corresponding to the abnormal collection type are corrected based on the parameter correction information.

[0181] Each module in the aforementioned power line data processing device may be implemented in whole or in part through software, hardware, or a combination thereof. Each module may be embedded in or independent of a processor in a computer device in the form of hardware, or may be stored in a memory in the computer device in the form of software, so that the processor can call and execute the corresponding operations of each module.

[0182] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Figure 9As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, abbreviated as I / O) and a communication interface. The processor, memory and input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database of the computer device is used to store line data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a data processing method for a power line is implemented.

[0183] Those skilled in the art will understand that Figure 9 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0184] In one embodiment, a computer device is further provided, including a memory and a processor. The memory stores a computer program, and the processor implements the steps in the above method embodiments when executing the computer program.

[0185] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0186] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0187] It should be noted that the data involved in this application (including but not limited to line data, etc.) are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0188] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. In particular, any reference to memory, database, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the various embodiments provided herein may be, but are not limited to, general-purpose processors, central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), programmable logic devices (PLDs), quantum computing-based data processing logic devices, artificial intelligence (AI) processors, and the like.

[0189] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0190] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A method for processing data of a power line, characterized in that: Applied to a data processing end, the method includes: Obtain current line data of each data collection type obtained by the drone inspection equipment through data collection on the target power line; Optimizing the standard map area corresponding to the target power line according to the current line data of each data collection type to obtain an updated map area; An abnormal line area corresponding to the target power line is determined according to difference information between the standard map area and the updated map area.

2. The method according to claim 1, characterized in that The optimizing the standard map area corresponding to the target power line according to the current line data of each data collection type to obtain the updated map area includes: Performing fusion processing on the current line data of each data acquisition type to obtain the global line data corresponding to the target power line; The global line data is used to optimize the standard map area corresponding to the target power line to obtain an updated map area.

3. The method according to claim 1, characterized in that The method further comprises: Sending the area identifier of the abnormal line area to the drone inspection device, so that the drone inspection device performs a secondary inspection on the abnormal line area to obtain abnormal inspection data corresponding to the abnormal line area; An inspection result corresponding to the abnormal line area is determined based on the abnormal inspection data and various standard abnormal features corresponding to the target power line.

4. The method according to claim 3, characterized in that The determining, based on the standard abnormal features corresponding to the target power line in the abnormal inspection data, an inspection result corresponding to the abnormal line area includes: Extracting current abnormal features of the target power line from the abnormal inspection data; Determine the feature similarity between the current abnormal feature and each standard abnormal feature corresponding to the target power line, and use the standard abnormal feature with the greatest feature similarity as the target abnormal feature; An inspection result corresponding to the abnormal line area is determined based on the abnormal inspection data and the target abnormal characteristics.

5. A method for processing data of a power line, characterized in that: Applied to drone inspection equipment, the method includes: In response to a data collection instruction for a target power line, the data collection instruction is parsed to obtain at least two data collection types and data collection parameters corresponding to each data collection type; Performing data collection on the target power line according to the data collection parameters corresponding to each data collection type to obtain current line data of each data collection type; The current line data of each data collection type is sent to the data processing end, so that the data processing end determines the abnormal line area corresponding to the target power line according to the current line data of each data collection type.

6. The method according to claim 5, characterized in that The step of collecting data on the target power line according to the data collection parameters corresponding to each data collection type to obtain current line data of each data collection type includes: Pre-collecting data on the target power line according to the data collection parameters corresponding to each data collection type to obtain pre-collected line data of each data collection type; For each data collection type, based on the pre-collected line data of the data collection type and the standard line data range corresponding to the data collection type, the reliability check is performed on the data collection parameters corresponding to the data collection type; When the reliability checks of the data acquisition parameters corresponding to the data acquisition types are all passed, data acquisition is performed on the target power line according to the data acquisition parameters corresponding to the data acquisition types to obtain current line data of the data acquisition types; In the event that the reliability check of the data acquisition parameters corresponding to the abnormal acquisition types in each data acquisition type fails, the data acquisition parameters corresponding to the abnormal acquisition types in the data acquisition parameters corresponding to each data acquisition type are corrected, and data acquisition is performed on the target power line based on the corrected data acquisition parameters corresponding to each data acquisition type to obtain current line data of each data acquisition type.

7. The method according to claim 5, characterized in that Correcting the data collection parameters corresponding to the abnormal data collection type in the data collection parameters corresponding to each data collection type includes: determining parameter correction information based on an error value between the pre-collected line data of the abnormal collection type and a threshold value of a standard line data range corresponding to the abnormal collection type; According to the parameter correction information, the data acquisition parameters corresponding to the abnormal acquisition type are corrected.

8. A data processing device for a power line, characterized in that: Applied to a data processing end, the device comprises: The first acquisition module is used to obtain current line data of various data collection types obtained by the drone inspection equipment from collecting data on the target power line; An optimization module, configured to optimize the standard map area corresponding to the target power line according to the current line data of each data collection type to obtain an updated map area; The abnormality determination module is used to determine the abnormal line area corresponding to the target power line according to the difference information between the standard map area and the updated map area.

9. A data processing device for a power line, characterized in that: Applied to UAV inspection equipment, the device includes: an instruction parsing module, configured to respond to a data collection instruction for a target power line and parse the data collection instruction to obtain at least two data collection types and data collection parameters corresponding to each data collection type; A second acquisition module is used to collect data on the target power line according to the data acquisition parameters corresponding to each data acquisition type, and obtain current line data of each data acquisition type; The data sending module is used to send the current line data of each data collection type to the data processing end, so that the data processing end determines the abnormal line area corresponding to the target power line according to the current line data of each data collection type.

10. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

Images