Intelligent detection system for power grid line fault

Abstract

The invention relates to the technical field of power grid fault detection, in particular to an intelligent detection system for power grid line faults, which comprises an acquisition module and an execution module, and is characterized in that the acquisition module is used for acquiring surrounding environment parameters of a to-be-detected cable; the execution module is used for executing the following steps: if the surrounding environment parameters belong to a first target type, performing detection in a first detection mode; if the surrounding environment parameter belongs to a second target type, detecting in a second detection mode; if the surrounding environment parameter belongs to a third target type, detecting in a third detection mode; and if the surrounding environment parameters belong to a fourth target type, performing detection in a fourth detection mode. According to the intelligent detection system for the power grid line fault, the detection mode can be reasonably selected according to the parameters of the surrounding environment where the cable is located, so that the specific position of the cable fault is accurately obtained under the condition that interference is eliminated as much as possible.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid fault detection, and particularly to an intelligent detection system for power grid line faults. Background Art

[0002] The power grid transmission line is an important part of the power system, and its normal operation is crucial for the stability and reliability of the power system; the power grid transmission line refers to the power transmission device connecting the power generation place and the power consumption place, which is used to transmit a large amount of electric energy. It is generally composed of power cables or power transmission towers and other transmission equipment, and is widely used in power systems of various scales, including urban power grids, industrial power grids, and rural power grids, etc.

[0003] During the actual use process, the transmission line is easily affected by various factors, including weather conditions, environmental pollution, biological activities, etc., resulting in easy occurrence of faults. The faults may cause power outages, which have a serious impact on life and industrial production. Therefore, the fault detection of the transmission line is very important; in related technologies, for example, the reference document with the application publication number of CN117629420A discloses a fault detection system and method for overhead distribution network lines. This fault detection system for overhead distribution network lines uses an infrared thermal imager to photograph the overhead line, obtains the infrared thermal image data of the metal conductor, and then analyzes the data through a fault detection model and makes a judgment according to the output result, so as to be able to achieve the effect of detecting the internal fault situation of the line.

[0004] In the research on the fault detection of transmission lines, it is often based on certain quantities for prediction, and the predicted fault types are also common fault types; however, in reality, some ultra-long transmission lines have a very large laying range, and natural conditions such as thick fog, wildfires, snowfall, or other human conditions may occur within the laying range. When these situations occur, they may not only cause faults in the cable, but also affect the cable fault detection result, resulting in the inability to timely know the specific location and specific reason of the fault, thus easily causing huge economic losses. Summary of the Invention

[0005] Based on this, it is necessary to provide an intelligent detection system for power grid line faults to address the problem of low accuracy of detection results in the current power grid line fault detection process.

[0006] The above object is achieved by the following technical solutions: An intelligent detection system for power grid line faults, comprising: An acquisition module for acquiring the surrounding environment parameters of the cable to be detected; An execution module for performing the following steps: If the surrounding environment parameters belong to the first target type, perform detection in the first detection mode; If the surrounding environment parameters belong to the second target type, perform detection in the second detection mode; If the surrounding environment parameters belong to the third target type, perform detection in the third detection mode; If the surrounding environment parameters belong to the fourth target type, perform detection in the fourth detection mode; The first detection device and the second detection device are used to perform detection in the first detection mode or the second detection mode or the third detection mode or the fourth detection mode, and a background board is loaded on the first detection device, and an infrared thermal imager is loaded on the second detection device; The surrounding environment parameters at least include weather information, disaster information, geographical information, environmental information, and building facility information; The first target type is fog, and the first detection mode includes: In the case where the fog mass covers the cable to be detected, when the moving speed of the fog mass is less than the preset speed, perform detection according to the first detection procedure, and when the moving speed of the fog mass is greater than the preset speed, perform detection according to the second detection procedure; The second target type is wildfire, and the second detection mode includes: When the smoke generated by the wildfire flows through the cable to be detected, the first detection device blows away the smoke flowing through the cable to be detected, so that the proportion of the pixel blocks occupied by the smoke in the overall pixel blocks in the image captured by the infrared thermal imager is less than the second set value; The infrared thermal imager takes a picture of the cable to be detected and obtains the seventh image data; When the smoke generated by the wildfire does not flow through the cable to be detected, the first detection device drives the background board to move to the preset position, and the infrared thermal imager takes a picture of the cable to be detected with the background board as the background and obtains the eighth image data; The third target type is a factory, and the flue gas emitted by the factory is used as the background of the cable to be detected. The third detection mode includes: The first detection device drives the background board to move to the preset position, and the infrared thermal imager takes a picture of the cable to be detected with the background board as the background and obtains the ninth image data; The fourth target type is snowing, and the fourth detection mode includes: The first detection device blows away the snow on the cable to be detected, so that the proportion of the pixel blocks occupied by the snow on the cable to be detected in the overall pixel blocks in the image captured by the infrared thermal imager is less than the third set value; The infrared thermal imager takes a picture of the cable to be detected and obtains the tenth image data.

[0007] Further, the first detection procedure includes the following steps: When the fog mass completely covers the cable to be detected, the first detection device blows away the fog mass covering the cable to be detected, so that the proportion of the pixel blocks occupied by the fog mass in the overall pixel blocks in the image captured by the infrared thermal imager is less than the first set value; The infrared thermal imager captures the cable to be detected and obtains the first image data; When the fog mass partially covers the cable to be detected, the infrared thermal imager captures the cable to be detected that is not covered by the fog mass and obtains the second image data; The first detection device blows away the fog mass covering the cable to be detected, so that the proportion of the pixel blocks occupied by the fog mass in the overall pixel blocks in the image captured by the infrared thermal imager is less than the first set value; The infrared thermal imager captures the cable to be detected and obtains the third image data; Taking the second image data as a reference, the third image data is corrected in terms of temperature.

[0008] Furthermore, the second detection procedure includes the following steps: When the fog mass completely covers the cable to be detected, the first detection device blows away the fog mass covering the cable to be detected along the moving direction parallel to the fog mass, so that the proportion of the pixel blocks occupied by the fog mass in the overall pixel blocks in the image captured by the infrared thermal imager is less than the first set value; The infrared thermal imager captures the cable to be detected and obtains the fourth image data; When the fog mass partially covers the cable to be detected, the infrared thermal imager captures the cable to be detected that is not covered by the fog mass and obtains the fifth image data; The first detection device blows away the fog mass covering the cable to be detected along the moving direction parallel to the fog mass, so that the proportion of the pixel blocks occupied by the fog mass in the overall pixel blocks in the image captured by the infrared thermal imager is less than the first set value; The infrared thermal imager captures the cable to be detected and obtains the sixth image data; Taking the fifth image data as a reference, the sixth image data is corrected in terms of temperature.

[0009] Furthermore, the second detection procedure further includes the following steps: Obtain the aggregation speed of the fog mass; The moving speeds of the first detection device and the second detection device are both negatively correlated with the aggregation speed of the fog mass.

[0010] Furthermore, a knocking rod or a flamethrower is loaded on the first detection device; the fourth detection mode further includes the following steps: When the fourth target type is snowing, the first detection device drives the knocking rod to knock the cable to be detected or uses a flamethrower to melt the snow on the cable to be detected, so that the proportion of the pixel blocks occupied by the snow on the cable to be detected in the overall pixel blocks in the image captured by the infrared thermal imager is less than the fourth set value; The infrared thermal imager captures the cable to be detected and obtains the eleventh image data.

[0011] Furthermore, both the first detection device and the second detection device include drones.

[0012] The beneficial effects of the present invention are: When the intelligent detection system for power grid line faults provided by the present invention is in use, if the surrounding environment parameters belong to the first target type, detection is performed in the first detection mode; if the surrounding environment parameters belong to the second target type, detection is performed in the second detection mode; if the surrounding environment parameters belong to the third target type, detection is performed in the third detection mode; if the surrounding environment parameters belong to the fourth target type, detection is performed in the fourth detection mode. Thus, the detection mode can be reasonably selected according to the surrounding environment parameters of the cable, so that the specific location of the cable fault can be accurately obtained while minimizing interference, so as to be able to process the fault in time and avoid causing greater economic losses. Description of the Drawings

[0013] Figure 1 It is a schematic flow chart of an intelligent detection system for power grid line faults provided by an embodiment of the present invention. Detailed Embodiments

[0014] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below through embodiments and in conjunction with the drawings. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0015] The serial numbers assigned to the components herein, such as "first", "second", etc., are only used to distinguish the objects described and do not have any sequential or technical meaning. And the "connection" and "coupling" mentioned in this application, unless otherwise specified, both include direct and indirect connection (coupling). In the description of the present invention, it should be understood that the orientation or positional relationship indicated by the terms "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation of the present invention.

[0016] In the present invention, unless otherwise clearly specified and defined, the first feature being "on" or "under" the second feature may mean that the first and second features are in direct contact, or the first and second features are indirectly in contact through an intermediate medium. Moreover, the first feature being "above", "over" and "on top of" the second feature may mean that the first feature is directly above or obliquely above the second feature, or merely indicates that the horizontal height of the first feature is higher than that of the second feature. The first feature being "under", "beneath" and "underneath" the second feature may mean that the first feature is directly below or obliquely below the second feature, or merely indicates that the horizontal height of the first feature is less than that of the second feature.

[0017] As Figure 1 shown, Figure 1 is a schematic flow diagram of an intelligent detection system for power grid line faults provided by an embodiment of the present invention. The intelligent detection system for power grid line faults is set to include: An acquisition module, configured to acquire the surrounding environment parameters of the cable to be detected; An execution module, configured to execute the following steps: If the surrounding environment parameters belong to the first target type, perform detection in the first detection mode; If the surrounding environment parameters belong to the second target type, perform detection in the second detection mode; If the surrounding environment parameters belong to the third target type, perform detection in the third detection mode; If the surrounding environment parameters belong to the fourth target type, perform detection in the fourth detection mode; A first detection device and a second detection device, configured to perform detection in the first detection mode or the second detection mode or the third detection mode or the fourth detection mode, and a background board is loaded on the first detection device, and an infrared thermal imager is loaded on the second detection device; The surrounding environment parameters at least include weather information, disaster information, geographical information, environmental information and building facility information; Specifically in this embodiment, the first target type, the second target type, the third target type and the fourth target type are all pre-set natural conditions or artificially intervened natural conditions; the first detection mode, the second detection mode, the third detection mode and the fourth detection mode are all pre-set execution modes; the first detection device and the second detection device can both be set to include drones, and the drones can fly into the air during use to facilitate the detection of overhead cables; when the surrounding environment parameters of the cable to be detected meet any one of the target types, the corresponding detection mode can be executed through the first detection device and the second detection device, so as to accurately obtain the specific location of the cable fault while trying to exclude interference, so as to be able to process the fault in time and avoid causing greater economic losses.

[0018] More specifically, the cable fault detection methods mainly include electrical methods, audio signal methods, optical methods, acoustic methods, electromagnetic methods, etc. Among them, the optical method mainly uses an infrared thermal imager to detect temperature anomalies along the cable. The temperature anomaly area is the fault area. Detecting cable faults with an infrared thermal imager has the advantage of not directly contacting the cable, which is particularly important for an operating power system because it allows for fault troubleshooting without power interruption, thus avoiding affecting the normal use of the cable while being able to detect cable faults.

[0019] The working principle of an infrared thermal imager is based on the physical properties of infrared rays. Infrared rays are part of the electromagnetic spectrum, with wavelengths between visible light and microwaves, approximately between 0.75 and 1000 micrometers. All objects above absolute zero (-273.15 °C) emit infrared radiation. The infrared thermal imager makes use of this by detecting and measuring the infrared radiation emitted by an object to generate a thermal image. This results in interference from a large amount of infrared radiation emitted by non-target objects during the process of detecting a cable with an infrared thermal imager, thus affecting the misjudgment or missed judgment of cable faults.

[0020] The first target type is fog, and the first detection mode includes: When the fog mass covers the cable to be detected, if the moving speed of the fog mass is less than the preset speed, detection is carried out according to the first detection procedure; if the moving speed of the fog mass is greater than the preset speed, detection is carried out according to the second detection procedure. Specifically, during the process of detecting a cable with an infrared thermal imager, most power grid equipment is exposed to the external environment. Due to solar irradiation and the action of current, the metal parts of the equipment will have a large temperature rise. When infrared temperature measurement of the insulation part is required, the large temperature rise of the metal part will affect the temperature measurement result of the insulation part. Therefore, to ensure accurate temperature measurement, it is generally required to carry out detection before sunrise or after sunset. Before sunrise or after sunset, due to the low temperature and the fact that overhead cables are mostly placed in remote areas such as suburbs and valleys, there is sufficient water vapor near the overhead cables, which is likely to cause fog around the cables. Fog refers to the water vapor condensate composed of small water droplets or ice crystals suspended in the atmosphere near the Earth's surface, which is a common weather phenomenon. When the air temperature reaches the dew point temperature (or is close to the dew point), the water vapor in the air condenses to form fog. When fog appears around the cable to be detected, it indicates that the humidity around the cable to be detected is relatively high. As the humidity increases, the temperature difference of the infrared detection data increases, resulting in abnormal infrared detection results. Under high humidity conditions, power grid equipment is prone to abnormal temperature rise phenomena, which may not necessarily reflect defects or faults in the power grid equipment.

[0021] Therefore, to ensure the accuracy of cable fault detection, it is set to first obtain the coverage parameter and movement parameter of the fog mass through the first detection device, and then take corresponding detection measures according to the coverage parameter and movement parameter of the fog mass. Specifically, it is set that when the fog mass completely or partially covers the cable to be detected and the movement speed is less than the preset speed, the detection is carried out according to the first detection procedure; when the fog mass completely or partially covers the cable to be detected and the movement speed is greater than or equal to the preset speed, the detection is carried out according to the second detection procedure.

[0022] It can be understood that the coverage parameter and movement parameter of the fog mass can be obtained by loading a high-definition camera on the first detection device to obtain the fog mass image in real time. For example, a neural network is used to identify the fog mass area in the image, and the optical flow method is used to obtain the movement parameter according to the change of the fog mass area between consecutive frames. The specific steps are well-known technical means to those skilled in the art and will not be elaborated and limited here.

[0023] It can be understood that the preset speed is a pre-set speed. When the movement speed of the fog mass is less than the preset speed, it means that the movement speed of the fog mass is slow; when the movement speed of the fog mass is greater than or equal to the preset speed, it means that the movement speed of the fog mass is fast. To avoid affecting the imaging of the infrared thermal imager, different detection procedures are used for shooting.

[0024] The second target type is wildfire, and the second detection mode includes: When the smoke generated by the wildfire flows through the cable to be detected, the first detection device blows away the smoke flowing through the cable to be detected, so that the proportion of the pixel block occupied by the smoke in the overall pixel block in the image taken by the infrared thermal imager is less than the second set value; The infrared thermal imager takes a picture of the cable to be detected and obtains the seventh image data; When the smoke generated by the wildfire does not flow through the cable to be detected, the first detection device drives the background board to move to the preset position, and the infrared thermal imager takes a picture of the cable to be detected with the background board as the background and obtains the eighth image data.

[0025] Specifically, when a wildfire occurs, the smoke generated by the wildfire contains a high amount of heat. When the smoke passes through the cable to be detected, it will heat the cable to be detected, causing the temperature rise of the cable to be detected to be abnormal, resulting in misjudgment during the detection of the cable by the infrared thermal imager; when the smoke does not pass through the cable to be detected, during the detection of the cable by the infrared thermal imager, it may serve as the background, and the image represented by the temperature of the smoke may cover the image represented by the temperature of the cable to be detected, resulting in easy misjudgment.

[0026] Therefore, in order to ensure the accuracy of cable fault detection, it is set to first obtain the flow direction parameters of the smoke generated by the wildfire through the first detection device; when the smoke generated by the wildfire flows through the cable to be detected, the cable to be detected is pre-divided into N test areas along the extension direction, and then the first detection device is controlled to move to the top of the first test area, and the distance between the first detection device and the cable to be detected is set to a preset distance. Under the blowing of the rotor of the first detection device, an area with almost no smoke is formed below it. In this area, the proportion of the pixel block occupied by the fog group in the image taken by the infrared thermal imager in the overall pixel block is less than the second set value, and then the second detection device is controlled to move to the right side of the first test area, and then the infrared thermal imager is used to take a picture to obtain the first seventh image data; repeat the above process until the N test areas on the cable to be detected are all detected, and then all the seventh image data are uniformly processed and analyzed, so as to obtain a more accurate thermal image of the cable while eliminating the interference of smoke as much as possible, thereby improving the accuracy of judging the cable fault location.

[0027] More specifically, when the smoke generated by the wildfire does not flow through the cable to be detected, the first detection device is controlled to move to the top of the first area to be detected, and the background board is allowed to cover the area where the smoke is located. The second detection device is then controlled to move to the side of the first area to be detected, and then a photo is taken with an infrared thermal imager to obtain the first eighth image data. The above process is repeated until all N areas to be tested on the cable to be detected are completed, and then all the eighth image data are uniformly processed and analyzed, so as to obtain a more accurate thermal image of the cable while eliminating smoke interference as much as possible, thereby improving the accuracy of judging the location of the cable fault.

[0028] It can be understood that the second setting value is a preset value; for example, the second setting value can be set to 5%.

[0029] The third target type is a factory, and the smoke emitted by the factory is used as the background of the cable to be tested. The third detection mode includes: The first detection device drives the background plate to move to a preset position, and the infrared thermal imager takes a picture of the cable to be detected with the background plate as the background, and obtains ninth image data.

[0030] Specifically, when there is a factory around the cable to be detected and the smoke emitted by the factory serves as the background of the cable to be detected, due to the high heat content in the smoke, the image represented by the temperature of the smoke may cover the image represented by the temperature of the cable to be detected, which may easily lead to misjudgment.

[0031] Therefore, to ensure the accuracy of cable fault detection, it is set to control the first detection device to move directly above the first area to be measured, and make the background board cover the area where the flue gas is located. Then, control the second detection device to move directly to the side of the first area to be measured, and then take a picture with an infrared thermal imager to obtain the first ninth image data. Repeat the above process until all N areas to be measured on the cable to be detected are detected, and then uniformly process and analyze all the ninth image data, so as to obtain a relatively accurate thermal imaging map of the cable while minimizing the interference of flue gas, and improve the accuracy of judging the cable fault location.

[0032] The fourth target type is snow, and the fourth detection mode includes: The first detection device blows the snow on the cable to be detected away, so that the proportion of the pixel blocks occupied by the snow on the cable to be detected in the overall pixel blocks in the image captured by the infrared thermal imager is less than the third set value. The infrared thermal imager takes a picture of the cable to be detected and obtains the tenth image data.

[0033] Specifically, when there is snow on the cable to be detected, the presence of the snow will cause some of the heat radiated by the cable to be absorbed by the snow, resulting in a reduction in the radiation that can be captured by the infrared thermal imager, and prone to missed judgments and misjudgments.

[0034] Therefore, to ensure the accuracy of cable fault detection, it is set to divide the cable to be detected into N areas to be measured along the extension direction in advance, and then control the first detection device to move directly above the first area to be measured, and make the distance between the first detection device and the cable to be detected a preset distance. Under the blowing of the rotor of the first detection device, the snow on the first area to be measured is blown off. In this area, the proportion of the pixel blocks occupied by the snow on the cable to be detected in the overall pixel blocks in the image captured by the infrared thermal imager is less than the third set value. Then, control the second detection device to move directly to the side of the first area to be measured, and then take a picture with the infrared thermal imager to obtain the first tenth image data. Then, control the first detection device to move directly above the second area to be measured, and make the distance between the first detection device and the cable to be detected a preset distance. Under the blowing of the rotor of the first detection device, the snow on the second area to be measured is blown off. Then, control the second detection device to move directly to the side of the second area to be measured, and then take a picture with the infrared thermal imager to obtain the second tenth image data. Repeat the above process until all N areas to be measured on the cable to be detected are detected, and then uniformly process and analyze all the tenth image data, so as to obtain a relatively accurate thermal imaging map of the cable while minimizing the interference of snow, and improve the accuracy of judging the cable fault location.

[0035] It can be understood that the third setting value is a preset value; for example, the third setting value can be set to 5%.

[0036] In a further embodiment, the first detection procedure comprises the following steps: When the fog group completely covers the cable to be detected, the first detection device blows away the fog group covering the cable to be detected, so that the proportion of the pixel block occupied by the fog group in the overall pixel block in the image taken by the infrared thermal imager is less than a first set value; The infrared thermal imager photographs the cable to be inspected and obtains first image data; When the fog partially covers the cable to be detected, the infrared thermal imager takes a picture of the cable to be detected that is not covered by the fog, and obtains second image data; The first detection device blows away the fog covering the cable to be detected, so that the proportion of the pixel blocks occupied by the fog in the image taken by the infrared thermal imager in the overall pixel blocks is less than a first set value; The infrared thermal imager photographs the cable to be inspected and obtains third image data; The third image data is temperature-corrected with reference to the second image data.

[0037] Specifically in this embodiment, when the fog completely covers the cable to be detected, the cable to be detected is pre-divided into N test areas along the extension direction, and then the first detection device is controlled to move to the top of the first test area, and the distance between the first detection device and the cable to be detected is set to a preset distance. Under the blowing of the rotor of the first detection device, an area with almost no fog is formed below it. In this area, the proportion of the pixel block occupied by the fog in the image taken by the infrared thermal imager in the overall pixel block is less than a first set value, and then the second detection device is controlled to move to the side of the first test area, and then take a picture with the infrared thermal imager to obtain the first image data; then the first detection device is controlled to move to the top of the second test area, And the first detection device and the cable to be detected are at a preset distance. Under the blowing of the rotor of the first detection device, an area with almost no fog is formed below it. In this area, the proportion of pixel blocks occupied by fog in the image taken by the infrared thermal imager in the overall pixel blocks is less than a first set value. Then the second detection device is controlled to move to the right side of the second area to be detected, and then a photo is taken by the infrared thermal imager to obtain the second first image data; the above process is repeated until all N areas to be detected on the cable to be detected are completed, and then all the first image data are uniformly processed and analyzed, so as to obtain a more accurate thermal image of the cable while eliminating the interference of water mist as much as possible, thereby improving the accuracy of judging the cable fault location.

[0038] More specifically, when the fog mass partially covers the cable to be detected, the cable to be detected is also divided into N regions to be detected along the extension direction in advance. Then, the second detection device is controlled to move to the exact side of the first region to be detected that is not covered by the fog mass, and then a photo is taken by the infrared thermal imager to obtain the first second image data. The above process is repeated until all the regions to be detected on the cable to be detected that are not covered by the fog mass are detected.

[0039] Then, the first detection device is controlled to move directly above the first region to be detected covered by the fog mass, and a preset distance is set between the first detection device and the cable to be detected. Under the blowing of the rotor of the first detection device, a region with almost no fog mass is formed below it. In this region, the proportion of the pixel blocks occupied by the fog mass in the overall pixel blocks in the image taken by the infrared thermal imager is less than the first set value. Then, the second detection device is controlled to move to the exact side of this region, and then a photo is taken by the infrared thermal imager to obtain the first third image data. The above process is repeated until all the regions to be detected on the cable to be detected covered by the fog mass are detected.

[0040] Since the second image data is obtained by taking pictures of the regions to be detected on the cable to be detected without fog mass coverage, the temperature accuracy of the cable characterized by the second image data is higher. Therefore, the third image data can be corrected in terms of temperature with reference to the second image data to improve the temperature of the cable characterized by the third image data. Then, all the second image data and the corrected third image data are uniformly processed and analyzed, so as to obtain a relatively accurate thermal imaging map of the cable while minimizing the interference of water mist, and improve the accuracy in judging the cable fault location.

[0041] It can be understood that when correcting the third image data in terms of temperature with reference to the second image data, assuming that the temperatures at the same coordinates on the second image data and the third image data are A1 and A2 respectively, and both A1 and A2 are normal temperatures, then A2 can be corrected by the formula (A2 + A2 * (A1 - A2) / A1). For example, when A1 = 20 °C and A2 = 15 °C, the corrected A2 = (15 + 15 * (20 - 15) / 20) = 18.375 °C. When correcting the abnormal temperature point A3, A3 can be directly corrected by the formula (A3 + A3 * (A1 - A3) / A1).

[0042] It can be understood that the first set value is a preset value. For example, the first set value can be set to 5%.

[0043] It is understandable that in order to improve the efficiency of detection, the first detection device and the second detection device can also be set to move synchronously along the extension direction of the cable to be detected, so that the infrared thermal imager can continuously take pictures of the cable to be detected, thereby shortening the detection time.

[0044] In other embodiments, the second detection procedure includes the following steps: When the fog group completely covers the cable to be detected, the first detection device blows away the fog group covering the cable to be detected in a direction parallel to the moving direction of the fog group, so that the proportion of the pixel block occupied by the fog group in the overall pixel block in the image taken by the infrared thermal imager is less than a first set value; The infrared thermal imager photographs the cable to be inspected and obtains fourth image data; When the fog partially covers the cable to be detected, the infrared thermal imager photographs the cable to be detected that is not covered by the fog, and obtains fifth image data; The first detection device blows away the fog covering the cable to be detected in a direction parallel to the moving direction of the fog, so that the proportion of the pixel block occupied by the fog in the image taken by the infrared thermal imager in the overall pixel block is less than a first set value; The infrared thermal imager photographs the cable to be inspected and obtains sixth image data; The sixth image data is corrected in temperature with reference to the fifth image data.

[0045] Specifically in this embodiment, when the fog completely covers the cable to be detected, the first detection device can be set to move in a direction parallel to the moving direction of the fog (when the first detection device is a drone, the drone moves in the opposite direction of the moving direction of the fog), so that under the blowing of the drone's fan blades, an area with almost no fog can be formed on the cable to be detected. In this area, the proportion of pixel blocks occupied by fog in the image taken by the infrared thermal imager in the overall pixel blocks is less than the first set value, and the movement of the fog can be accelerated, thereby reducing the water vapor around the subsequent cable to be detected; during use, the first detection device and the second detection device are first controlled to move synchronously along the extension direction of the cable to be detected, and at the same time, the infrared thermal imager is used to continuously take pictures of the cable to be detected until all N areas to be detected on the cable to be detected are detected, and then all the fourth image data are uniformly processed and analyzed, so as to obtain a more accurate thermal image of the cable while eliminating the interference of water mist as much as possible, thereby improving the accuracy of judging the location of the cable fault.

[0046] More specifically, when the fog partially covers the cable to be detected, the second detection device is first controlled to move along the extension direction of the cable to be detected in the area to be detected that is not covered by the fog, and at the same time, the cable to be detected is continuously photographed by an infrared thermal imager to obtain the fifth image data corresponding to all the areas to be detected that are not covered by the fog.

[0047] Then control the first detection device and the second detection device to move synchronously along the extending direction of the cable to be detected in the area to be detected covered by the fog mass. At the same time, continuously take pictures of the cable to be detected through the infrared thermal imager until all the areas to be detected on the cable to be detected covered by the fog mass are detected, so as to obtain the sixth image data corresponding to all the areas to be detected covered by the fog mass.

[0048] Since the fifth image data is obtained by photographing the area to be detected on the cable to be detected without fog mass coverage, the temperature accuracy of the cable characterized by the fifth image data is higher. Therefore, the fifth image data can be used as a reference to correct the temperature of the sixth image data, so as to improve the temperature of the cable characterized by the sixth image data. Then, uniformly process and analyze all the fifth image data and the corrected sixth image data, so as to obtain a relatively accurate thermal imaging map of the cable while minimizing the interference of water mist, and improve the accuracy in judging the cable fault location.

[0049] It can be understood that the temperature correction of the sixth image data can refer to the temperature correction method of the third image data.

[0050] In other embodiments, the second detection program further includes the following steps: Obtain the aggregation speed of the fog mass; The moving speeds of the first detection device and the second detection device are both negatively correlated with the aggregation speed of the fog mass.

[0051] Specifically in this embodiment, before detection, the fog mass can be blown by the first detection device, and then the first detection device leaves its original position. During the movement of the first detection device, at the same time, take the aggregation image of the fog mass through the high-definition camera thereon, so as to represent the aggregation speed of the fog mass by recording the aggregation time of the fog mass. And the shorter the aggregation time of the fog mass, the faster the aggregation speed of the fog mass, and vice versa; when the aggregation speed of the fog mass is faster, it will cause the area of the region without fog mass formed under the unmanned aerial vehicle to be smaller, affecting the thermal imaging quality. At this time, the moving speeds of the first detection device and the second detection device can be reduced to ensure the area of the region without fog mass formed under the unmanned aerial vehicle; when the aggregation speed of the fog mass is slower, the moving speeds of the first detection device and the second detection device can be increased to improve the detection efficiency.

[0052] In some other embodiments, a knocking rod or a flamethrower is loaded on the first detection device; the fourth detection mode further includes the following steps: The first detection device drives the knocking rod to knock the cable to be detected or melts the snow on the cable to be detected by the flamethrower, so that the proportion of the pixel blocks occupied by the snow on the cable to be detected in the image taken by the infrared thermal imager in the overall pixel blocks is less than a fourth set value; The infrared thermal imager photographs the cable to be inspected and obtains eleventh image data.

[0053] Specifically in this embodiment, in order to ensure the accuracy of cable fault detection, it is set to pre-divide the cable to be detected into N test areas along the extension direction, and then control the first detection device to move above the first test area, and make the first detection device and the cable to be detected at a preset distance, the first detection device synchronously drives the knocking rod to knock the cable to be detected or melt the snow on the cable to be detected by the flamethrower. In this area, the proportion of the pixel block occupied by the snow on the cable to be detected in the image taken by the infrared thermal imager in the overall pixel block is less than the fourth set value, and then the second detection device is controlled to move to the right side of the first test area, and then take a picture with the infrared thermal imager to obtain the first eleventh image data; repeat the above process until the N test areas on the cable to be detected are all detected, and then all the eleventh image data are uniformly processed and analyzed, so as to obtain a more accurate thermal image of the cable while eliminating the interference of snow as much as possible, thereby improving the accuracy of judging the cable fault location.

[0054] More specifically, when the first detection device synchronously drives the knocking rod to knock the cable to be detected, the first detection device can be controlled to fly left and right to drive the knocking rod to swing back and forth under the action of inertia, thereby completing the knocking work on the cable to be detected.

[0055] It can be understood that the fourth setting value is a preset value; for example, the fourth setting value can be set to 5%.

[0056] The technical features of the above embodiments may be arbitrarily combined. 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 specification.

[0057] The above embodiments only express several implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present invention. It should be pointed out that, for those of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention.

Claims

1. An intelligent detection system for power grid line faults, characterized in that, Including: An acquisition module, configured to acquire the ambient environment parameters of the cable to be detected; An execution module, configured to perform the following steps: If the ambient environment parameters belong to the first target type, perform detection in the first detection mode; If the ambient environment parameters belong to the second target type, perform detection in the second detection mode; If the ambient environment parameters belong to the third target type, perform detection in the third detection mode; If the ambient environment parameters belong to the fourth target type, perform detection in the fourth detection mode; A first detection device and a second detection device, configured to perform detection in the first detection mode or the second detection mode or the third detection mode or the fourth detection mode, and a background board is loaded on the first detection device, and an infrared thermal imager is loaded on the second detection device; The ambient environment parameters at least include weather information, disaster information, geographical information, environmental information, and building facility information; The first target type is fog, and the first detection mode includes: When the fog mass covers the cable to be detected, when the moving speed of the fog mass is less than the preset speed, perform detection according to the first detection procedure, and when the moving speed of the fog mass is greater than the preset speed, perform detection according to the second detection procedure; The second target type is wildfire, and the second detection mode includes: When the smoke generated by the wildfire flows through the cable to be detected, the first detection device blows away the smoke flowing through the cable to be detected, so that the proportion of the pixel blocks occupied by the smoke in the overall pixel blocks in the image captured by the infrared thermal imager is less than the second set value; The infrared thermal imager captures the cable to be detected and obtains seventh image data; When the smoke generated by the wildfire does not flow through the cable to be detected, the first detection device drives the background board to move to a preset position, and the infrared thermal imager captures the cable to be detected with the background board as the background and obtains eighth image data; The third target type is a factory, and the flue gas emitted by the factory serves as the background of the cable to be detected, and the third detection mode includes: The first detection device drives the background board to move to a preset position, and the infrared thermal imager captures the cable to be detected with the background board as the background and obtains ninth image data; The fourth target type is snowing, and the fourth detection mode includes: The first detection device blows away the snow on the cable to be detected, so that the proportion of the pixel blocks occupied by the snow on the cable to be detected in the overall pixel blocks in the image captured by the infrared thermal imager is less than the third set value; The infrared thermal imager captures the cable to be detected and obtains tenth image data.

2. The intelligent detection system for power grid line faults according to claim 1, characterized in that, The first detection procedure includes the following steps: When the fog mass completely covers the cable to be detected, the first detection device blows away the fog mass covering the cable to be detected, so that the proportion of the pixel blocks occupied by the fog mass in the overall pixel blocks in the image captured by the infrared thermal imager is less than the first set value; The infrared thermal imager captures the cable to be detected and obtains first image data; When the fog mass partially covers the cable to be detected, the infrared thermal imager captures the cable to be detected without the fog mass covering it and obtains second image data; The first detection device blows away the fog mass covering the cable to be detected, so that the proportion of the pixel blocks occupied by the fog mass in the overall pixel blocks in the image captured by the infrared thermal imager is less than the first set value; The infrared thermal imager takes a picture of the cable to be detected and obtains the third image data; Taking the second image data as a reference, the third image data is corrected in terms of temperature.

3. The intelligent detection system for power grid line faults according to claim 1, characterized in that, The second detection procedure includes the following steps: When the fog mass completely covers the cable to be detected, the first detection device blows away the fog mass covering the cable to be detected along the moving direction parallel to the fog mass, so that the proportion of the pixel blocks occupied by the fog mass in the overall pixel blocks in the image taken by the infrared thermal imager is less than the first set value; The infrared thermal imager takes a picture of the cable to be detected and obtains the fourth image data; When the fog mass partially covers the cable to be detected, the infrared thermal imager takes a picture of the cable to be detected without fog mass coverage and obtains the fifth image data; The first detection device blows away the fog mass covering the cable to be detected along the moving direction parallel to the fog mass, so that the proportion of the pixel blocks occupied by the fog mass in the overall pixel blocks in the image taken by the infrared thermal imager is less than the first set value; The infrared thermal imager takes a picture of the cable to be detected and obtains the sixth image data; Taking the fifth image data as a reference, the sixth image data is corrected in terms of temperature.

4. The intelligent detection system for power grid line faults according to claim 1, characterized in that, The second detection procedure further includes the following steps: Obtain the aggregation speed of the fog mass; The moving speeds of the first detection device and the second detection device are both negatively correlated with the aggregation speed of the fog mass.

5. The intelligent detection system for power grid line faults according to claim 1, characterized in that, A knocking rod or a flamethrower is loaded on the first detection device; The detection in the fourth detection mode further includes the following steps: The first detection device drives the knocking rod to knock on the cable to be detected or sprays fire through the flamethrower to melt the snow on the cable to be detected, so that the proportion of the pixel blocks occupied by the snow on the cable to be detected in the overall pixel blocks in the image taken by the infrared thermal imager is less than the fourth set value; The infrared thermal imager takes a picture of the cable to be detected and obtains the eleventh image data.

6. The intelligent detection system for power grid line faults according to claim 1, characterized in that, Both the first detection device and the second detection device include drones.

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