Safety early warning method and system based on unmanned aerial vehicle three-phase line detection operation

Abstract

The invention belongs to the technical field of power transmission lines, discloses a safety early warning method and system based on three-phase line detection operation of an unmanned aerial vehicle, provides a three-phase overhead line with an adjustable phase-to-phase distance, and fuses discharge monitoring data of the three-phase overhead line with the adjustable phase-to-phase distance through evidence fusion. The accuracy of discharge monitoring is improved, it is ensured that any potential discharge problem can be found and processed in time, and therefore damage to the unmanned aerial vehicle, detection interruption or more serious safety accidents caused by the discharge phenomenon are effectively avoided, the efficiency and reliability of detection work are also remarkably improved, and the detection efficiency is improved. More accurate and effective countermeasures can be formulated; the technical problem of how to accurately monitor the line discharge phenomenon in the process of detecting the three-phase line by using the unmanned aerial vehicle so as to carry out safety early warning is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of power transmission lines, and in particular to a safety early warning method and system based on unmanned aerial vehicle (UAV) three-phase line detection operations. Background Art

[0002] With the rapid advancement of drone technology, drones have shown broad application prospects in many fields, including power transmission line inspection. In high-altitude operations on power transmission lines, especially when drones are used for X-ray inspection, discharge may occur in the transmission lines due to various potential factors, such as meteorological conditions, line aging, equipment failure, etc. This discharge may not only interfere with the normal flight and inspection operations of drones, but may also cause a series of safety issues, posing a serious threat to the surrounding environment and personnel. Therefore, strict monitoring and in-depth experimental analysis of line discharge phenomena that drones may encounter during X-ray inspection operations have become a key link in ensuring the safety and efficiency of drone operations.

[0003] In the existing line discharge monitoring platform, most designs are only built for single-phase lines, which is significantly different from the three-phase lines widely used in actual production environments. Among the different arrangements of three-phase lines, the three-phase vertically arranged lines are more complex and difficult to predict in terms of discharge characteristics due to their spatial distribution characteristics and electric field interactions. In addition, the existing experimental platforms often use a single detection method, such as ultraviolet imaging, in terms of detection methods. Although the single ultraviolet imaging method has a certain effect in discharge detection, it often leads to large detection errors due to its limitations such as being greatly affected by ambient light and low recognition of discharge types. In the three-phase vertically arranged lines, the discharge phenomenon is more complex and changeable due to the mutual coupling and superposition of the electromagnetic fields between the three-phase lines. This complexity not only increases the difficulty of discharge monitoring, but also challenges the accuracy and reliability of a single detection method. Therefore, for the discharge monitoring of three-phase vertically arranged lines, more comprehensive and advanced technical means are needed to ensure the safety and effectiveness of the drone's X-ray detection of three-phase lines. Summary of the invention

[0004] The present invention provides a safety warning method and system based on drone three-phase line detection operations, which solves the technical problem of how to accurately monitor line discharge phenomena during the process of using drones to detect three-phase lines, thereby providing safety warnings.

[0005] A first aspect of the present invention provides a safety warning method based on a three-phase line detection operation using an unmanned aerial vehicle, which is applied to construct a three-phase overhead line with adjustable phase distance through an adjustable support insulator device, comprising:

[0006] A three-phase overhead line with adjustable phase distance is constructed by means of an adjustable post insulator device, wherein the adjustable post insulator device is used to adjust the phase distance of the three-phase overhead line;

[0007] Responding to a safety warning request for an operating drone, reading the safety warning request, determining a three-phase overhead line corresponding to the operating drone, and obtaining different types of initial discharge detection data;

[0008] Preprocessing different types of the initial discharge data to obtain different types of target discharge data;

[0009] fusing different types of target discharge data according to evidence theory to obtain fused data;

[0010] Calculating the discharge probability of the three-phase overhead line using the fused data;

[0011] Determining whether the discharge probability meets a preset discharge requirement;

[0012] If the discharge probability meets the preset discharge requirement, it is determined that the three-phase overhead line is in a discharge state and a warning message is generated for the operating drone.

[0013] Optionally, the different types of initial discharge detection data are specifically discharge detection data generated by different monitoring devices performing discharge detection on the three-phase overhead line.

[0014] Optionally, the preprocessing of different types of initial discharge data to obtain different types of target discharge data includes:

[0015] Performing binary encoding conversion on the different types of initial discharge data to obtain binary discharge data, wherein the binary discharge data includes discharge variable data and non-discharge variable data;

[0016] Performing data cleaning on different types of binary discharge data respectively to obtain cleaned discharge data;

[0017] The formats of the different types of cleaning discharge data are converted respectively to obtain target discharge data, wherein the target discharge data is specifically discharge data in a probability distribution form.

[0018] Optionally, fusing different types of target discharge data according to evidence theory to obtain fused data includes:

[0019] Classifying the target discharge data of different types according to the discharge results to obtain a plurality of discharge classification data and non-discharge classification data;

[0020] Performing a multiplication operation using a plurality of the discharge classification data to obtain a first multiplication value;

[0021] Performing a multiplication operation using a plurality of the non-discharge classification data to obtain a second multiplication value;

[0022] Performing a sum operation using the first product value and the second product value to obtain a first sum value;

[0023] The fused data is obtained by performing a ratio operation on the first product value and the first sum value.

[0024] Optionally, the calculating the discharge probability of the three-phase overhead line by using the fused data includes:

[0025] The fused data is used to calculate a trust function value, and the trust function value is used as the discharge probability.

[0026] Optionally, the preset discharge requirement is specifically that the discharge probability is greater than or equal to a preset threshold.

[0027] Optionally, it also includes:

[0028] If the discharge probability does not meet the preset discharge requirement, determining that the three-phase overhead line is not in a discharge state;

[0029] Jump to the step of obtaining different types of initial discharge detection data until the operating drone completes the three-phase line detection operation.

[0030] A second aspect of the present invention provides a safety warning system based on a three-phase line detection operation using an unmanned aerial vehicle, which is applied to construct a three-phase overhead line with adjustable phase distance through an adjustable support insulator device, comprising:

[0031] A response module, used to respond to a safety warning request for an operating drone, read the safety warning request, determine the three-phase overhead line corresponding to the operating drone, and obtain different types of initial discharge detection data;

[0032] A preprocessing module, used for preprocessing different types of the initial discharge data to obtain different types of target discharge data;

[0033] A fusion module, used for fusing different types of target discharge data according to evidence theory to obtain fused data;

[0034] A probability calculation module, used to calculate the discharge probability of the three-phase overhead line using the fused data;

[0035] A judging module, used to judge whether the discharge probability meets a preset discharge requirement;

[0036] The early warning module is used to determine that the three-phase overhead line is in a discharge state and generate early warning information for the operating drone if the discharge probability meets the preset discharge requirement.

[0037] A third aspect of the present invention provides an electronic device, comprising a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the processor executes the steps of the safety warning method based on the three-phase line detection operation of an unmanned aerial vehicle as described in any one of the above items.

[0038] A fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed, implements a safety warning method based on a three-phase line detection operation of a drone as described in any one of the above items.

[0039] It can be seen from the above technical solutions that the present invention has the following advantages:

[0040] In the present invention, in response to a safety warning request for an operating drone, the safety warning request is read, the three-phase overhead line corresponding to the operating drone is determined, and different types of initial discharge detection data are obtained; different types of initial discharge data are preprocessed to obtain different types of target discharge data; different types of target discharge data are fused according to evidence theory to obtain fused data; the discharge probability of the three-phase overhead line is calculated using the fused data; it is determined whether the discharge probability meets the preset discharge requirement; if the discharge probability meets the preset discharge requirement, it is determined that the three-phase overhead line is in a discharge state and a warning information is generated for the operating drone; the present invention provides a three-phase overhead line with adjustable phase-to-phase distance, and the discharge monitoring data of the three-phase overhead line is fused through evidence fusion, which improves the accuracy of discharge monitoring and ensures that any potential discharge problems can be discovered and handled in time, thereby effectively avoiding drone damage, detection interruption or more serious safety accidents caused by discharge phenomena, and significantly improving the efficiency and reliability of detection work, which is helpful to formulate more accurate and effective response measures; it solves the technical problem of how to accurately monitor line discharge phenomena during the detection operation of the three-phase line using drones, thereby performing safety warnings. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0042] Figure 1A flowchart of a safety warning method based on a three-phase line detection operation of a drone provided in the first embodiment of the present invention;

[0043] Figure 2 A flowchart of a safety warning method based on a three-phase line detection operation of a drone provided in the second embodiment of the present invention;

[0044] Figure 3 A schematic diagram of the connection between the adjustable post insulator device and the experimental station provided in the second embodiment of the present invention;

[0045] Figure 4 A schematic diagram of the connection between the adjustable post insulator device and the three-phase transmission line provided in the second embodiment of the present invention;

[0046] Figure 5 A front view of a post insulator support provided in the second embodiment of the present invention;

[0047] Figure 6 A side view of a post insulator support provided in the second embodiment of the present invention;

[0048] Figure 7 A top view of a post insulator support provided in the second embodiment of the present invention;

[0049] Figure 8 A schematic diagram of the connection between a post insulator and a triangular support provided in the second embodiment of the present invention;

[0050] Fig. 9 A structural block diagram of a safety warning system based on three-phase line detection operation of a drone provided in Embodiment 3 of the present invention;

[0051] Fig.10 This is a structural block diagram of a computer device provided in Embodiment 4 of the present invention. DETAILED DESCRIPTION

[0052] The embodiments of the present invention provide a safety warning method and system based on drone three-phase line detection operations, which are used to solve the technical problem of how to accurately monitor line discharge phenomena during the process of using drones to detect three-phase lines, thereby providing safety warnings.

[0053] In order to make the purpose, features and advantages of the present invention more obvious and easy to understand, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described below are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0054] See also Figure 1 , Figure 1 A flowchart of the steps of a safety warning method based on three-phase line detection operation of an unmanned aerial vehicle provided in Example 1 of the present invention.

[0055] The present invention provides a safety warning method based on three-phase line detection operation by unmanned aerial vehicle, which is applied to construct a three-phase overhead line with adjustable phase distance through an adjustable support insulator device, comprising:

[0056] Step 101: respond to a safety warning request for an operating drone, read the safety warning request, determine the three-phase overhead line corresponding to the operating drone, and obtain different types of initial discharge detection data.

[0057] The safety warning request refers to the warning request information for real-time discharge monitoring of three-phase overhead lines with adjustable phase distance when the operating drone performs X-ray inspection on the three-phase overhead lines with adjustable phase distance. The safety warning request carries the preset code and associated location information of the three-phase overhead line being monitored for discharge.

[0058] In an embodiment of the present invention, in response to receiving warning request information for real-time discharge monitoring of a three-phase overhead line with adjustable phase distance when an operating drone performs X-ray detection operations on the three-phase overhead line with adjustable phase distance, the safety warning request is read, the three-phase overhead line with adjustable phase distance that the operating drone is performing discharge monitoring is determined, and initial discharge detection data monitored by different types of monitoring equipment are obtained.

[0059] Step 102: pre-process different types of initial discharge data to obtain different types of target discharge data.

[0060] Preprocessing refers to the binary encoding conversion, data cleaning and format conversion operations on different types of initial discharge data.

[0061] In an embodiment of the present invention, binary encoding conversion, data cleaning and format conversion operations are performed on different types of initial discharge data, thereby converting them into different types of target discharge data, wherein the target discharge data is specifically discharge data in a probability distribution form.

[0062] Step 103: fusing different types of target discharge data according to evidence theory to obtain fused data.

[0063] Evidence theory, referring to DS evidence theory, is a mathematical theory for dealing with uncertainty and incomplete information.

[0064] In an embodiment of the present invention, according to the theory of evidence, the target discharge data in the form of different types of probability distribution obtained in the above steps are fused to obtain fused data.

[0065] Step 104: Calculate the discharge probability of the three-phase overhead line using the fused data.

[0066] The discharge probability refers to the discharge probability of the three-phase overhead line calculated by fusion data based on evidence theory, which is used to further determine whether the three-phase overhead line is in a discharge state.

[0067] In the embodiment of the present invention, the discharge probability of the three-phase overhead line is calculated using fused data.

[0068] Step 105: Determine whether the discharge probability meets the preset discharge requirement.

[0069] In the embodiment of the present invention, it is determined whether the discharge probability meets a preset discharge requirement.

[0070] Step 106: If the discharge probability meets the preset discharge requirement, it is determined that the three-phase overhead line is in a discharge state and a warning message is generated for the operating drone.

[0071] In an embodiment of the present invention, if the discharge probability meets the preset discharge requirement, it is determined that the three-phase overhead line is in a discharge state, and a warning message is sent to the operating drone. The operating drone reads the warning message, obtains that the three-phase overhead line is in a discharge state, and stops the operation.

[0072] In the present invention, a safety warning request for an operating drone is responded to, the safety warning request is read, the three-phase overhead line corresponding to the operating drone is determined, and different types of initial discharge detection data are obtained; different types of initial discharge data are preprocessed to obtain different types of target discharge data; different types of target discharge data are fused according to evidence theory to obtain fused data; the fused data is used to calculate the discharge probability of the three-phase overhead line; it is judged whether the discharge probability meets the preset discharge requirement; if the discharge probability meets the preset discharge requirement, it is determined that the three-phase overhead line is in a discharge state and a warning information is generated for the operating drone; the present invention fuses the discharge monitoring data of the three-phase overhead line through evidence fusion, improves the accuracy of discharge monitoring, ensures that any potential discharge problems can be discovered and handled in time, thereby effectively avoiding drone damage, detection interruption or more serious safety accidents caused by discharge phenomena, and also significantly improves the efficiency and reliability of detection work, which is helpful to formulate more accurate and effective response measures; solves the technical problem of how to accurately monitor line discharge phenomena during the detection operation of three-phase lines using drones, thereby performing safety warnings.

[0073] See also Figure 2 , Figure 2 A flowchart of the steps of a safety warning method based on three-phase line detection operations of an unmanned aerial vehicle is provided in Embodiment 2 of the present invention.

[0074] The present invention provides a safety warning method based on three-phase line detection operation by unmanned aerial vehicle, which is applied to construct a three-phase overhead line with adjustable phase distance through an adjustable support insulator device, comprising:

[0075] Before step 201, a three-phase overhead line with adjustable phase distance is constructed by means of an adjustable post insulator device, and the adjustable post insulator device is used to achieve phase distance adjustment of the three-phase overhead line.

[0076] Step 201: respond to a safety warning request for an operating drone, read the safety warning request, determine the three-phase overhead line corresponding to the operating drone, and obtain different types of initial discharge detection data.

[0077] Please note that Figure 3-Figure 8 As shown, 1. triangular bracket; 2. horizontal base; 3. support insulator; 4. screw; 5. mounting plate; 6. roller.

[0078] A safety warning method based on three-phase line detection operation by drone in the present invention is applied to a three-phase overhead line with adjustable phase distance formed by an adjustable post insulator device, and the operating drone performs X-ray detection operation on the three-phase overhead line formed by the adjustable post insulator device, and the adjustable post insulator device is used to realize the phase distance adjustment of the three-phase overhead line;

[0079] The adjustable post insulator device comprises two oppositely arranged post insulator brackets;

[0080] Two oppositely arranged support insulator brackets are connected via a three-phase transmission line, and one end of the three-phase transmission line is connected to the experimental station;

[0081] The post insulator support includes a triangular support, a horizontal base and three post insulators;

[0082] A horizontal base is arranged at the bottom of the tripod support, and the horizontal base is used to fix the tripod support on a horizontal ground;

[0083] The three post insulators are movably connected in the vertical direction of the triangular bracket through rollers;

[0084] The three post insulators correspond one to one with the three-phase transmission lines;

[0085] One end of the post insulator is mounted on one side of the mounting plate by means of screws, and the other side of the mounting plate is movably connected to a roller. The roller is used to lift and lower the post insulator in the vertical direction of the triangular bracket.

[0086] A discharge monitoring point is set on the horizontal ground away from the adjustable device of the support insulator, and a line discharge monitoring device is installed at the discharge monitoring point. The line discharge monitoring device includes multiple different types of monitoring devices, including but not limited to high-sensitivity electric field detectors, ultraviolet imagers and ultrasonic detectors.

[0087] The electric field detector captures the electric field changes caused by line discharge; the ultraviolet imager captures ultraviolet radiation, and light spots will appear in the ultraviolet image when discharge occurs; the ultrasonic detector captures the ultrasonic signal data generated by the discharge phenomenon and monitors the discharge phenomenon. When detecting the discharge of overhead transmission lines, the electric field detector must have high precision (the electric field measurement error does not exceed ±5% of the full scale), a wide measurement range (capable of covering strong electric field changes from 1kV / m to 1000kV / m), and fast response capabilities (millisecond response time) to ensure accurate capture of the subtle electric field changes generated by the line discharge. The parameter requirements of the ultraviolet imager include high ultraviolet sensitivity (capable of detecting weak ultraviolet radiation as low as nanowatts / cm² solid angle), high-resolution imaging (pixel resolution of not less than 1024x768 to clearly display the discharge light spots), and a wide ultraviolet wavelength detection range (covering most ultraviolet bands generated by discharge), so as to effectively capture and present the ultraviolet image light spots generated during discharge, providing an intuitive basis for fault location. Ultrasonic sensors must have high sensitivity (±1dB accuracy), a wide frequency range (20kHz to 200MHz), strong anti-interference ability and stability, and be used in conjunction with a special coupling agent.

[0088] Receive and process signal data from the line discharge monitoring device, where the electric field detector data is the electric field strength value; the ultraviolet imager data is the captured discharge picture, and whether discharge occurs is determined by detecting whether there are light spots on the image; the ultrasonic detector data is the ultrasonic data spectrum, and whether discharge occurs is determined by detecting whether there is ultrasound generated by the discharge.

[0089] Furthermore, the different types of initial discharge detection data are specifically discharge detection data generated by different monitoring devices performing discharge detection on the three-phase overhead line.

[0090] In the embodiment of the present invention, the specific implementation process of step 201 is similar to step 101 and will not be repeated here.

[0091] Step 202: pre-process different types of initial discharge data to obtain different types of target discharge data.

[0092] Further, step 202 may include the following sub-steps:

[0093] S11. Perform binary encoding conversion on different types of initial discharge data to obtain binary discharge data, wherein the binary discharge data includes discharge variable data and non-discharge variable data, 1 represents discharge variable data, and 0 represents non-discharge variable data.

[0094] In an embodiment of the present invention, binary encoding conversion is performed respectively according to different types of initial discharge data to obtain binary discharge data, wherein the binary discharge data includes discharge variable data and non-discharge variable data, that is, the discharge data monitored by the monitoring device is represented by 01, thereby obtaining binary discharge data, 1 indicates that the monitoring device detects discharge, and 0 indicates that the monitoring device detects no discharge.

[0095] S12, performing data cleaning on different types of binary discharge data respectively to obtain cleaned discharge data.

[0096] In the embodiment of the present invention, data cleaning is performed on different types of binary discharge data respectively, and obviously erroneous data is deleted to obtain cleaned discharge data.

[0097] S13, performing format conversion on different types of cleaning discharge data respectively to obtain target discharge data, wherein the target discharge data is specifically discharge data in a probability distribution form.

[0098] In the embodiment of the present invention, different types of cleaning discharge data are format-converted to obtain target discharge data in the form of probability distribution so as to be applicable to the evidence theory.

[0099] The different types of cleaning discharge data are formatted into target discharge data in the form of basic probability distribution. The specific formula is as follows:

[0100] Assume that m is the BPA function on the recognition frame U, A is a subset of U, is an empty set, then m(A) represents the support for A. The higher the support, the greater the possibility of A. U includes two subsets, namely, discharge and no discharge, and satisfies the following formula:

[0101]

[0102] U includes two subsets, namely, discharge and no discharge.

[0103] For ease of understanding, the following is an application example:

[0104] In a line operation where discharge occurred, the UV imager took 500 photos and tested them, of which 350 photos showed discharge, while 150 photos showed no discharge. The target discharge data of the UV imager in the form of probability distribution is expressed as m1(discharge)=0.7, m1(no discharge)=0.3; the ultrasonic detector detected 500 sets of data, of which 450 data showed discharge, while 50 data showed no discharge. The target discharge data of the ultrasonic detector in the form of probability distribution is expressed as m2(discharge)=0.9, m2(no discharge)=0.1. At this time, the accuracy of the UV imager is 70%, and the accuracy of the ultrasonic detector is 90%.

[0105] Step 203: fusing different types of target discharge data according to evidence theory to obtain fused data.

[0106] Fusing data refers to classifying the same type of target discharge data according to the discharge results to obtain multiple discharge classification data and non-discharge classification data, and then fusing the two different types of classification data to obtain fused data.

[0107] Further, step 203 may include the following sub-steps:

[0108] S21 . Classify different types of target discharge data according to discharge results to obtain a plurality of discharge classification data and non-discharge classification data.

[0109] The discharge result refers to the two discharge results detected by the monitoring device: discharge and no discharge.

[0110] It is worth mentioning that the target discharge data includes target discharge data detected by the monitoring device in a discharge state and target discharge data detected by the monitoring device in a non-discharge state.

[0111] The discharge classification data refers to extracting the target discharge data whose discharge status is monitored by the monitoring device from all types of target discharge data.

[0112] The non-discharge classification data refers to extracting the target discharge data in which the monitoring device detects a non-discharge state from all types of target discharge data.

[0113] In the embodiment of the present invention, all different types of target discharge data are classified according to the two discharge results of discharge and non-discharge, so as to obtain discharge classification data and non-discharge classification data corresponding to each type.

[0114] S22. Perform a multiplication operation using the plurality of discharge classification data to obtain a first multiplication value.

[0115] S23, performing a multiplication operation using a plurality of non-discharge classification data to obtain a second multiplication value.

[0116] S24. Perform a sum operation using the first product value and the second product value to obtain a first sum value.

[0117] S25. Perform a ratio operation on the first product value and the first sum value to obtain fused data.

[0118] It should be noted that for ease of understanding, the following uses ultraviolet imagers and ultrasonic detectors as examples:

[0119] In a specific implementation, in order to facilitate the implementation of the method, the above-mentioned process S22-S25 can be converted into a formula encapsulation form, wherein the calculation method of the fused data can be as follows:

[0120] M=m1(discharge) m2(discharge)+ m2(no discharge) m1(no discharge)

[0121] m(discharge) = m1(discharge) m2(discharge) / M

[0122] Wherein, M represents the first sum value, m1(discharge) represents the discharge classification data when the monitoring device is an ultraviolet imager, m2(discharge) represents the discharge classification data when the monitoring device is an ultrasonic detector, m2(non-discharge) represents the non-discharge classification data when the monitoring device is an ultrasonic detector, m1(non-discharge) represents the non-discharge classification data when the monitoring device is an ultraviolet imager, and m(discharge) represents the fusion data.

[0123] For ease of understanding, the following is an application example:

[0124] According to the Dempster combination rule of evidence theory, the BPA of the UV imager and the ultrasonic detector are fused, and the normalization factor is calculated to ensure that the sum of the probability distribution after fusion is 1;

[0125] The Dempster combination rules are as follows:

[0126] For two independent m1 and m2, their combined m is given by:

[0127]

[0128] Where K is a normalization factor used to ensure that m(U) = 1. The calculation formula for K is:

[0129]

[0130] Continuing the above application example, m1(discharge)=0.7, m2(discharge)=0.9, m1(non-discharge)=0.3, m2(non-discharge)=0.1, then:

[0131] 1-K= m1(discharge) m2(discharge)+ m2(no discharge) m1(no discharge)=0.66

[0132] m(discharge) = m1(discharge) m2(discharge) / 0.66=0.95

[0133] After DS evidence theory fusion, the fusion judgment of the ultraviolet imager and the ultrasonic detector is m(discharge) =0.95, m(no discharge) =0.05, and the accuracy is improved to 95%.

[0134] Step 204: Calculate the discharge probability of the three-phase overhead line using the discharge fusion data and the non-discharge fusion data.

[0135] Further, step 204 may include the following sub-steps:

[0136] S31. Calculate the trust function value using the discharge fusion data, and use the trust function value as the discharge probability.

[0137] In a specific implementation, in order to facilitate the implementation of the method, the above process can be converted into a formula encapsulation form, wherein the calculation method of the trust function value can be as follows:

[0138]

[0139] It should be noted that the discharge fusion data m (discharge) and the non-discharge fusion data m (non-discharge) are obtained in the above calculation.

[0140] Wherein, Bel(A) represents the trust function value, specifically refers to the degree of confidence that the three-phase overhead line is in the discharge state (A), m(B) represents the fused data m(discharge), and A indicates that the three-phase overhead line is in the discharge state.

[0141] In the embodiment of the present invention, the trust function value is used as the discharge probability.

[0142] For ease of understanding, the following is an application example:

[0143] According to the fused BPA, the trust function is determined, and the discharge state is judged by the trust function.

[0144] The trust function Bel(A) represents the degree of confidence in proposition A. The calculation formula of the trust function value Bel(A) is:

[0145]

[0146] In the above example, Bel(discharge) = 0.95, Bel(no discharge) = 0.05.

[0147] Then the probability of discharge occurring is 0.95.

[0148] Step 205: Determine whether the discharge probability meets the preset discharge requirement.

[0149] Furthermore, the preset discharge requirement is specifically that the discharge probability is greater than or equal to a preset threshold.

[0150] It is worth mentioning that the preset threshold is preferably 0.9. It is understandable that when Bel (discharge) is greater than 0.9, it is considered that the probability of discharge is very high. In the example, the calculated discharge probability is 0.95, so it is further determined that discharge occurs.

[0151] In the embodiment of the present invention, it is determined whether the discharge probability meets a preset discharge requirement.

[0152] Step 206: If the discharge probability meets the preset discharge requirement, it is determined that the three-phase overhead line is in a discharge state and a warning message is generated for the operating drone.

[0153] In an embodiment of the present invention, when the discharge probability is greater than or equal to a preset threshold, the preset discharge requirement is met, the three-phase overhead line is determined to be in a discharge state, and an early warning message is sent to the operating drone. The operating drone reads the early warning message, obtains that the three-phase overhead line is in a discharge state, and stops operating.

[0154] Step 207: If the discharge probability does not meet the preset discharge requirement, it is determined that the three-phase overhead line is not in a discharge state.

[0155] In the embodiment of the present invention, if the discharge probability does not meet the preset discharge requirement, it is determined that the three-phase overhead line is not in a discharge state.

[0156] Step 208: Jump to the step of obtaining different types of initial discharge detection data until the operating drone completes the three-phase line detection operation.

[0157] In the embodiment of the present invention, the process jumps to the step of obtaining different types of initial discharge detection data until the operating drone completes the three-phase line detection operation.

[0158] In the present invention, a safety warning request for an operating drone is responded to, the safety warning request is read, the three-phase overhead line corresponding to the operating drone is determined, and different types of initial discharge detection data are obtained; different types of initial discharge data are preprocessed to obtain different types of target discharge data; different types of target discharge data are fused according to evidence theory to obtain fused data; the fused data is used to calculate the discharge probability of the three-phase overhead line; it is judged whether the discharge probability meets the preset discharge requirement; if the discharge probability meets the preset discharge requirement, it is determined that the three-phase overhead line is in a discharge state and a warning information is generated for the operating drone; the present invention fuses the discharge monitoring data of the three-phase overhead line through evidence fusion, improves the accuracy of discharge monitoring, ensures that any potential discharge problems can be discovered and handled in time, thereby effectively avoiding drone damage, detection interruption or more serious safety accidents caused by discharge phenomena, and also significantly improves the efficiency and reliability of detection work, which is helpful to formulate more accurate and effective response measures; solves the technical problem of how to accurately monitor line discharge phenomena during the detection operation of three-phase lines using drones, thereby performing safety warnings.

[0159] See also Fig. 9 , Fig. 9 A structural block diagram of a safety warning system based on drone three-phase line detection operations provided in Example 3 of the present invention.

[0160] The present invention provides a safety warning system based on three-phase line detection operation by unmanned aerial vehicle, which is applied to construct a three-phase overhead line with adjustable phase distance through an adjustable support insulator device, and comprises:

[0161] The response module 301 is used to respond to the safety warning request for the operating drone, read the safety warning request, determine the three-phase overhead line corresponding to the operating drone, and obtain different types of initial discharge detection data;

[0162] A preprocessing module 302 is used to preprocess different types of initial discharge data to obtain different types of target discharge data;

[0163] A fusion module 303 is used to fuse different types of target discharge data according to evidence theory to obtain fused data;

[0164] A probability calculation module 304, used to calculate the discharge probability of the three-phase overhead line using the fused data;

[0165] A judgment module 305 is used to judge whether the discharge probability meets the preset discharge requirement;

[0166] The early warning module 306 is used to determine that the three-phase overhead line is in a discharge state and generate early warning information to the operating drone if the discharge probability meets the preset discharge requirement.

[0167] Furthermore, the different types of initial discharge detection data are specifically discharge detection data generated by different monitoring devices performing discharge detection on the three-phase overhead line.

[0168] Furthermore, the preprocessing module 302 includes:

[0169] A binary code conversion submodule is used to perform binary code conversion according to different types of initial discharge data to obtain binary discharge data, wherein the binary discharge data includes discharge variable data and non-discharge variable data, 1 represents the discharge variable data, and 0 represents the non-discharge variable data;

[0170] A data cleaning submodule is used to clean different types of binary discharge data to obtain cleaned discharge data;

[0171] The format conversion submodule is used to perform format conversion on different types of cleaning discharge data to obtain target discharge data, wherein the target discharge data is specifically discharge data in a probability distribution form.

[0172] Furthermore, the fusion module 303 includes:

[0173] A classification submodule, used to classify different types of target discharge data according to the discharge results, and obtain a plurality of discharge classification data and non-discharge classification data;

[0174] A first multiplication submodule, configured to perform a multiplication operation using a plurality of discharge classification data to obtain a first multiplication value;

[0175] A second multiplication submodule is used to perform a multiplication operation using a plurality of non-discharge classification data to obtain a second multiplication value;

[0176] A first sum submodule, used for performing a sum operation using the first product value and the second product value to obtain a first sum;

[0177] The fusion data submodule is used to perform a ratio operation using the first product value and the first sum value to obtain fusion data.

[0178] Further, the probability calculation module 304 includes:

[0179] The discharge probability submodule is used to calculate the trust function value by using the fused data, and use the trust function value as the discharge probability.

[0180] Furthermore, the preset discharge requirement is specifically that the discharge probability is greater than or equal to a preset threshold.

[0181] Furthermore, it also includes:

[0182] A determination module, used for determining that the three-phase overhead line is not in a discharge state if the discharge probability does not meet a preset discharge requirement;

[0183] The jump module is used to jump to the step of obtaining different types of initial discharge detection data until the operating drone completes the three-phase line detection operation.

[0184] In the present invention, a safety warning request for an operating drone is responded to, the safety warning request is read, the three-phase overhead line corresponding to the operating drone is determined, and different types of initial discharge detection data are obtained; different types of initial discharge data are preprocessed to obtain different types of target discharge data; different types of target discharge data are fused according to evidence theory to obtain fused data; the fused data is used to calculate the discharge probability of the three-phase overhead line; it is judged whether the discharge probability meets the preset discharge requirement; if the discharge probability meets the preset discharge requirement, it is determined that the three-phase overhead line is in a discharge state and a warning information is generated for the operating drone; the present invention fuses the discharge monitoring data of the three-phase overhead line through evidence fusion, improves the accuracy of discharge monitoring, ensures that any potential discharge problems can be discovered and handled in time, thereby effectively avoiding drone damage, detection interruption or more serious safety accidents caused by discharge phenomena, and also significantly improves the efficiency and reliability of detection work, which is helpful to formulate more accurate and effective response measures; solves the technical problem of how to accurately monitor line discharge phenomena during the detection operation of three-phase lines using drones, thereby performing safety warnings.

[0185] See also Fig.10 , Fig.10 This is a structural block diagram of a computer device provided in Embodiment 4 of the present invention.

[0186] An electronic device according to an embodiment of the present invention includes: a memory 401 and a processor 402, wherein the memory 402 stores a computer program; when the computer program is executed by the processor 402, the processor 402 executes a safety warning method based on a three-phase line detection operation of a drone as in any of the above embodiments.

[0187] The memory 401 may be an electronic memory such as a flash memory, an EEPROM (electrically erasable programmable read-only memory), an EPROM, a hard disk or a ROM. The memory 401 has a storage space 403 for a program code 413 for executing any method step in the above method. For example, the storage space 403 for the program code may include individual program codes 413 for implementing the various steps in the above method, respectively. These program codes may be read from or written to one or more computer program products. These computer program products include program code carriers such as hard disks, compact disks (CDs), memory cards or floppy disks. The program code may be compressed, for example, in an appropriate form. When these codes are run by a computing and processing device, the computing and processing device performs the various steps in the method described above. These program codes may be read from or written to one or more computer program products. These computer program products include program code carriers such as hard disks, compact disks (CDs), memory cards or floppy disks. The program code may be compressed, for example, in an appropriate form. When these codes are executed by a computing and processing device, they cause the computing and processing device to execute the various steps of the safety warning method based on the three-phase line detection operation of the drone described above.

[0188] Embodiment 5 of the present invention further provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, a safety warning method based on a three-phase line detection operation of a drone as in any of the above embodiments is implemented.

[0189] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0190] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0191] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0192] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0193] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0194] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A safety warning method based on three-phase line detection operation of unmanned aerial vehicle, characterized in that: Applicable to construct three-phase overhead lines with adjustable phase distance through adjustable support insulator devices, including: Responding to a safety warning request for an operating drone, reading the safety warning request, determining a three-phase overhead line corresponding to the operating drone, and obtaining different types of initial discharge detection data; Preprocessing different types of the initial discharge data to obtain different types of target discharge data; fusing different types of target discharge data according to evidence theory to obtain fused data; Calculating the discharge probability of the three-phase overhead line using the fused data; Determining whether the discharge probability meets a preset discharge requirement; If the discharge probability meets the preset discharge requirement, it is determined that the three-phase overhead line is in a discharge state and a warning message is generated for the operating drone.

2. The safety warning method based on three-phase line detection operation of unmanned aerial vehicle according to claim 1 is characterized in that: The different types of initial discharge detection data are specifically discharge detection data generated by different monitoring devices performing discharge detection on the three-phase overhead line.

3. The safety warning method based on three-phase line detection operation of unmanned aerial vehicle according to claim 1 is characterized in that: The preprocessing of different types of initial discharge data to obtain different types of target discharge data includes: Performing binary encoding conversion on the different types of initial discharge data to obtain binary discharge data, wherein the binary discharge data includes discharge variable data and non-discharge variable data; Performing data cleaning on different types of binary discharge data respectively to obtain cleaned discharge data; The formats of the different types of cleaning discharge data are converted respectively to obtain target discharge data, wherein the target discharge data is specifically discharge data in a probability distribution form.

4. The safety warning method based on three-phase line detection operation of unmanned aerial vehicle according to claim 1 is characterized in that: The method of fusing different types of target discharge data according to the evidence theory to obtain fused data includes: Classifying the target discharge data of different types according to the discharge results to obtain a plurality of discharge classification data and non-discharge classification data; Performing a multiplication operation using a plurality of the discharge classification data to obtain a first multiplication value; Performing a multiplication operation using a plurality of the non-discharge classification data to obtain a second multiplication value; Performing a sum operation using the first product value and the second product value to obtain a first sum value; The fused data is obtained by performing a ratio operation on the first product value and the first sum value.

5. The safety warning method based on three-phase line detection operation of unmanned aerial vehicle according to claim 1 is characterized in that: The using the fused data to calculate the discharge probability of the three-phase overhead line includes: The fused data is used to calculate a trust function value, and the trust function value is used as the discharge probability.

6. The safety warning method based on three-phase line detection operation of unmanned aerial vehicle according to claim 5 is characterized in that: The preset discharge requirement specifically means that the discharge probability is greater than or equal to a preset threshold.

7. The safety warning method based on three-phase line detection operation of unmanned aerial vehicle according to claim 1 is characterized in that: Also includes: If the discharge probability does not meet the preset discharge requirement, determining that the three-phase overhead line is not in a discharge state; Jump to the step of obtaining different types of initial discharge detection data until the operating drone completes the three-phase line detection operation.

8. A safety warning system based on drone three-phase line detection operation, characterized in that: Applicable to construct three-phase overhead lines with adjustable phase distance through adjustable support insulator devices, including: A response module, used to respond to a safety warning request for an operating drone, read the safety warning request, determine the three-phase overhead line corresponding to the operating drone, and obtain different types of initial discharge detection data; A preprocessing module, used for preprocessing different types of the initial discharge data to obtain different types of target discharge data; A fusion module, used for fusing different types of target discharge data according to evidence theory to obtain fused data; A probability calculation module, used to calculate the discharge probability of the three-phase overhead line using the fused data; A judging module, used to judge whether the discharge probability meets a preset discharge requirement; The early warning module is used to determine that the three-phase overhead line is in a discharge state and generate early warning information for the operating drone if the discharge probability meets the preset discharge requirement.

9. An electronic device, characterized in that: It includes a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the processor executes the steps of the safety warning method based on the three-phase line detection operation of an unmanned aerial vehicle as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed, the safety warning method based on the three-phase line detection operation of the unmanned aerial vehicle as described in any one of claims 1-7 is implemented.

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