Image investigation weather resistance detection device, method and equipment for wind power generation cable

Abstract

The invention discloses an image investigation weather resistance detection device, method and equipment for a wind power generation cable, and belongs to the technical field of electric power facilities. The device comprises an image acquisition module used for acquiring a visible light image and an infrared image at a preset position of a wind power generation cable according to a preset period; the defect identification module is used for identifying the weather resistance defect of the wind power generation cable based on the visible light image and determining an area to be identified; and the defect determination module is used for extracting infrared image features of the to-be-identified area based on the infrared image, identifying whether abnormal features exist in the infrared image features and whether the abnormal features conform to the weather resistance defect, and generating early warning information of the weather resistance defect if the abnormal features conform to the weather resistance defect. According to the technical scheme, the weather resistance defect of the wind power generation cable can be dynamically and accurately detected by acquiring the visible light image and the infrared image of the wind power generation cable, so that reliable guarantee is provided for long-term stable operation of the wind power generation cable in a complex outdoor environment.

Description

Technical Field

[0001] This application belongs to the technical field of power facilities, and particularly relates to an image reconnaissance weather resistance detection device, method and equipment for wind power cables. Background Art

[0002] Wind power cables undertake key power transmission and signal transmission tasks in wind power systems. In order to effectively utilize wind energy, wind turbines need to be built in places with sufficient wind. Therefore, the wind power cables connecting various components of the wind turbine and transmitting power to facilities such as substations are necessarily in an outdoor environment.

[0003] However, wind power cables face challenges from many climate and environmental factors in the outdoor environment. The day-night and seasonal temperature differences, as well as the heat generated during operation, will make the insulating material brittle at low temperatures and soften at high temperatures, accelerating aging; ultraviolet radiation will damage the molecular structure of the outer sheath, causing it to age and crack; moisture will make it damp and reduce the insulation resistance, and in cold regions, it may even freeze and expand, thus damaging the structure; coastal salt spray and chemical substances in industrial pollution areas will cause corrosion to it.

[0004] Once the wind power cable has weather resistance defects, its insulation performance will decline, easily leading to short circuits or grounding faults, thereby causing power transmission interruptions and affecting the normal operation and power generation of the wind power system. Therefore, how to achieve dynamic and accurate detection of the weather resistance defects of wind power cables is an urgent problem for those in this field to solve. Summary of the Invention

[0005] The embodiments of this application provide an image reconnaissance weather resistance detection device, method and equipment for wind power cables, aiming to dynamically and accurately detect the weather resistance defects of wind power cables, so as to provide reliable guarantee for its long-term stable operation in complex outdoor environments.

[0006] In the first aspect, the embodiments of this application provide an image reconnaissance weather resistance detection device for wind power cables, and the device includes:

[0007] A preset acquisition module, configured to acquire a preset position and a preset period for the weather resistance detection of the wind power cable;

[0008] An image acquisition module, configured to acquire visible light images and infrared images at the preset position of the wind power cable according to the preset period; wherein, a high-definition camera and an infrared camera are arranged at the preset position, or a running track of an unmanned reconnaissance device carrying the high-definition camera and the infrared camera is arranged at the preset position;

[0009] A defect recognition module, configured to recognize the weathering defects of the wind power cable based on the visible light image, and determine the location where the weathering defect is located as the area to be identified; wherein, the weathering defect includes at least one of crack, bulge, and corrosion trace;

[0010] A defect determination module, configured to extract the infrared image features of the area to be identified based on the infrared image, and identify whether there are abnormal features in the infrared image features and whether the abnormal features conform to the weathering defects, and generate a warning message for the weathering defects when it is identified as conforming.

[0011] In a second aspect, an embodiment of the present application provides a method for detecting the weather resistance of a wind power cable by image survey, the method includes:

[0012] Obtain a preset position and a preset period for weather resistance detection of the wind power cable through a preset acquisition module;

[0013] Obtain a visible light image and an infrared image of the preset position of the wind power cable through an image acquisition module according to the preset period; wherein, a high-definition camera and an infrared camera are arranged at the preset position, or a running track of an unmanned survey device carrying a high-definition camera and an infrared camera is arranged at the preset position;

[0014] Recognize the weathering defects of the wind power cable based on the visible light image through a defect recognition module, and determine the location where the weathering defect is located as the area to be identified; wherein, the weathering defect includes at least one of crack, bulge, and corrosion trace;

[0015] Extract the infrared image features of the area to be identified based on the infrared image through a defect determination module, and identify whether there are abnormal features in the infrared image features and whether the abnormal features conform to the weathering defects, and generate a warning message for the weathering defects when it is identified as conforming.

[0016] In a third aspect, an embodiment of the present application provides an electronic device, which includes a processor, a memory, and a program or instruction stored on the memory and executable on the processor. When the program or instruction is executed by the processor, the steps of the method described in the first aspect are implemented.

[0017] In the embodiment of the present application, a preset acquisition module is configured to acquire a preset position and a preset period for weather resistance detection of a wind power cable; an image acquisition module is configured to acquire a visible light image and an infrared image at the preset position of the wind power cable according to the preset period; wherein, a high-definition camera and an infrared camera are arranged at the preset position, or a running track of an unmanned exploration device carrying the high-definition camera and the infrared camera is arranged at the preset position; a defect identification module is configured to identify weather resistance defects of the wind power cable based on the visible light image, and determine the position where the weather resistance defects are located as an area to be identified; wherein, the weather resistance defects include at least one of cracks, bulges, and corrosion marks; a defect determination module is configured to extract infrared image features of the area to be identified based on the infrared image, and identify whether there are abnormal features in the infrared image features and whether the abnormal features conform to the weather resistance defects, and generate a warning message for the weather resistance defects when it is identified as conforming. The above image exploration weather resistance detection device for wind power cables can dynamically and accurately detect weather resistance defects of wind power cables by acquiring visible light images and infrared images of wind power cables, thereby providing a reliable guarantee for its long-term stable operation in a complex outdoor environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 FIG. is a schematic structural diagram of an image exploration weather resistance detection device for a wind power cable provided in Embodiment 1 of the present application;

[0019] Figure 2 FIG. is a schematic structural diagram of an image exploration weather resistance detection device for a wind power cable provided in Embodiment 2 of the present application;

[0020] Figure 3 FIG. is a schematic structural diagram of an image exploration weather resistance detection device for a wind power cable provided in Embodiment 3 of the present application;

[0021] Figure 4 FIG. is a schematic flowchart of an image exploration weather resistance detection method for a wind power cable provided in Embodiment 4 of the present application;

[0022] Figure 5 FIG. is a schematic structural diagram of an electronic device provided in Embodiment 5 of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0023] To make the objectives, technical solutions, and advantages of this application clearer, the following provides a more detailed description of specific embodiments of this application with reference to the accompanying drawings. It can be understood that the specific embodiments described herein are merely for explaining this application and not for limiting this application. Additionally, it should be noted that for ease of description, only parts related to this application rather than all content are shown in the drawings. Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts describe the operations (or steps) as sequential processes, many of the operations can be implemented in parallel, concurrently, or simultaneously. In addition, the order of the operations can be rearranged. The process can be terminated when its operations are completed, but it can also have additional steps not included in the drawings. The process can correspond to a method, function, procedure, subroutine, subprogram, and so on.

[0024] The following will clearly describe the technical solutions in the embodiments of this application with reference to the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are part of the embodiments of this application, rather than all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art belong to the scope of protection of this application.

[0025] The terms "first", "second", etc. in the specification and claims of this application are used to distinguish similar objects, rather than to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of this application can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first", "second", etc. are generally of the same category, and the number of objects is not limited. For example, the first object can be one or multiple. In addition, "and / or" in the specification and claims means at least one of the connected objects, and the character " / " generally indicates an "or" relationship between the associated objects before and after.

[0026] The following combines the accompanying drawings to provide a detailed description of the image exploration weather resistance detection device, method, and equipment for wind power generation cables provided in the embodiments of this application through specific embodiments and their application scenarios.

[0027] Embodiment 1

[0028] Figure 1 It is a schematic structural diagram of the image exploration weather resistance detection device for wind power generation cables provided in Embodiment 1 of this application. As Figure 1 shown, the device includes:

[0029] A preset acquisition module 110, configured to acquire a preset position and a preset period for weather resistance detection of a wind power generation cable;

[0030] An image acquisition module 120 is configured to acquire visible light images and infrared images at preset positions of the wind power cable according to the preset period; wherein, a high-definition camera and an infrared camera are arranged at the preset position, or a running track of an unmanned exploration device carrying the high-definition camera and the infrared camera is arranged at the preset position;

[0031] A defect identification module 130 is configured to identify weather resistance defects of the wind power cable based on the visible light images, and determine the location where the weather resistance defects are located as an area to be identified; wherein, the weather resistance defects include at least one of cracks, bulges, and corrosion marks;

[0032] A defect determination module 140 is configured to extract infrared image features of the area to be identified based on the infrared images, and identify whether there are abnormal features in the infrared image features and whether the abnormal features conform to the weather resistance defects, and generate a warning message for the weather resistance defects when it is identified as conforming.

[0033] This application is applicable to scenarios where cables are provided in a wind power system. Specifically, the determination of the preset position and the preset period, the determination of the area to be identified, and the identification and warning of weather resistance defects, etc. can be executed by an intelligent terminal device. The staff can take corresponding maintenance measures for the positions of the wind power cables with weather resistance defects according to the warning messages of the weather resistance defects to ensure the normal and safe operation of the wind power system.

[0034] Based on the above usage scenarios, it can be understood that the execution subject of this application can be an intelligent terminal device, such as a desktop computer, a notebook computer, a mobile phone, a tablet computer, and an interactive multimedia, etc., and no excessive limitations are made here.

[0035] A preset acquisition module 110 is configured to acquire the preset position and the preset period for the weather resistance detection of the wind power cable.

[0036] A cable is a device for transmitting electricity or signals. A wind power cable is a special cable for transmitting electric energy in a wind power system. Among them, a wind power system can refer to a device system that can convert wind energy into electric energy, and generally consists of a wind turbine, a generator, a converter, a control system, a tower, and other auxiliary devices, etc.

[0037] Weather resistance can refer to the ability of a wind power cable to maintain its performance stability under the action of various climate factors in natural environmental conditions. Weather resistance detection is the detection of the weather resistance of a wind power cable.

[0038] The preset position may refer to the position of the wind power cable where weather resistance testing needs to be carried out. The method for determining the preset position of the wind power cable for weather resistance testing can be to obtain the stress data, annual average temperature amplitude data, and service life data of each position of the wind power cable, and determine the preset position of the wind power cable for weather resistance testing based on the stress data, annual average temperature amplitude data, and service life data.

[0039] The preset period may refer to the time interval at which the event of weather resistance testing occurs repeatedly. The preset period can be preset according to the weather resistance requirements of the wind power cable.

[0040] The image acquisition module 120 is used to acquire visible light images and infrared images at the preset position of the wind power cable according to the preset period.

[0041] A visible light image is an image formed by the reflection or transmission of light in the visible light band by an object. A high-definition camera is a camera device that can capture high-resolution images and videos and has excellent performance in terms of image clarity and detail restoration. A high-definition camera can be used to acquire visible light images at the preset position of the wind power cable.

[0042] An infrared image is an image that shows the temperature distribution and thermal characteristics of the surface of an object. An infrared camera is a device that uses infrared imaging technology to capture and record images. An infrared camera can be used to acquire infrared images at the preset position of the wind power cable.

[0043] The unmanned exploration device can be a device that can obtain visible light images and infrared images of each preset position of the wind power cable through autonomous movement without direct human intervention. It can be understood that the unmanned exploration device can carry a high-definition camera and an infrared camera, and the unmanned exploration device can achieve autonomous movement through a running track.

[0044] The defect identification module 130 is used to identify the weather resistance defects of the wind power cable based on the visible light image, and determine the location where the weather resistance defect is located as the area to be identified.

[0045] Weather resistance defects may refer to problems such as performance degradation or appearance damage of the wind power cable caused by various climate factors during long-term exposure to natural environmental conditions, such as cracks, bulges, and corrosion marks. Specifically, cracks may refer to linear gaps or cracks that appear in the insulation layer and sheath of the wind power cable; bulges may refer to local protrusions or swelling phenomena on the surface of the wind power cable; corrosion marks may refer to rust spots, discoloration, or peeling caused by chemical or electrochemical reactions on the surface of the wind power cable.

[0046] A method for identifying weathering defects of wind power cables based on visible light images can be to pre-train a weathering defect identification model using a large number of visible light images of wind power cables with weathering defects. By inputting the current visible light image into the weathering defect identification model, the weathering defect identification model outputs the location of the weathering defect in the visible light image, and determines the location of the weathering defect as the area to be identified. Among them, the area to be identified can refer to the location of the wind power cable that needs to be further determined whether it is a weathering defect.

[0047] The defect determination module 140 is used to extract the infrared image features of the area to be identified based on the infrared image, and identify whether there are abnormal features in the infrared image features and whether the abnormal features conform to the weathering defects. In the case of identification as conforming, it generates a warning message for the weathering defects.

[0048] The infrared image features of the area to be identified can refer to the temperature distribution features of the area to be identified. The method for extracting the infrared image features of the area to be identified based on the infrared image can be to determine the pixel area of the area to be identified in the infrared image, read the pixel values of each pixel in this pixel area, and determine the temperature data corresponding to each pixel value according to the pre-constructed correlation relationship between the pixel value and the temperature data, so as to obtain the infrared image features of the area to be identified.

[0049] The abnormal features can refer to the infrared image features representing weathering defects. The method for identifying whether there are abnormal features in the infrared image features and whether the abnormal features conform to the weathering defects can be to compare the infrared image features with the preset abnormal features to identify whether there are abnormal features in the infrared image features and whether the abnormal features conform to the weathering defects.

[0050] The warning message for the weathering defects can be information used to warn the staff that there are weathering defects in the wind power cable and maintenance is required. The specific content of the warning message for the weathering defects can include the location of the wind power cable with weathering defects. The method for generating the warning message for the weathering defects can be to pop up a warning window on the display device of the intelligent terminal device, and the specific content of the warning message for the weathering defects is displayed in the warning window.

[0051] In the example of this application, a preset acquisition module is used to acquire the preset position and preset period for the weather resistance detection of a wind power generation cable; an image acquisition module is used to acquire a visible light image and an infrared image at the preset position of the wind power generation cable according to the preset period; wherein, a high-definition camera and an infrared camera are arranged at the preset position, or a running track of an unmanned exploration device carrying the high-definition camera and the infrared camera is arranged at the preset position; a defect identification module is used to identify the weather resistance defects of the wind power generation cable based on the visible light image, and determine the location where the weather resistance defects are located as the area to be identified; wherein, the weather resistance defects include at least one of cracks, bulges and corrosion marks; a defect determination module is used to extract the infrared image features of the area to be identified based on the infrared image, and identify whether there are abnormal features in the infrared image features and whether the abnormal features conform to the weather resistance defects, and generate a warning message for the weather resistance defects when it is identified as conforming. In this technical solution, by acquiring the visible light image and the infrared image of the wind power generation cable, the weather resistance defects of the wind power generation cable can be dynamically and accurately detected, thereby providing a reliable guarantee for its long-term stable operation in a complex outdoor environment.

[0052] Embodiment 2

[0053] Figure 2 FIG. is a schematic structural diagram of an image exploration weather resistance detection device for a wind power generation cable provided in Embodiment 2 of this application. This solution makes a better improvement on the basis of the above embodiment. The specific improvement is as follows: the preset acquisition module includes: a data acquisition unit, which is used to acquire the stress data, annual average temperature variation data and service life data of each position of the wind power generation cable; a preset position determination unit, which is used to determine the preset position for the weather resistance detection of the wind power generation cable according to the stress data, the annual average temperature variation data and the service life data; a preset period acquisition unit, which is used to acquire the preset period for the weather resistance detection of the wind power generation cable.

[0054] As Figure 2 shown, the device includes:

[0055] A preset acquisition module 210, which is used to acquire the preset position and preset period for the weather resistance detection of a wind power generation cable;

[0056] An image acquisition module 220, which is used to acquire a visible light image and an infrared image at the preset position of the wind power generation cable according to the preset period; wherein, a high-definition camera and an infrared camera are arranged at the preset position, or a running track of an unmanned exploration device carrying the high-definition camera and the infrared camera is arranged at the preset position;

[0057] A defect recognition module 230, configured to recognize weathering defects of the wind power cable based on the visible light image, and determine the location where the weathering defect is located as the area to be identified; wherein, the weathering defect includes at least one of cracks, bulges, and corrosion marks;

[0058] A defect determination module 240, configured to extract infrared image features of the area to be identified based on the infrared image, and identify whether there are abnormal features in the infrared image features and whether the abnormal features conform to the weathering defects, and generate a warning message for the weathering defects when it is recognized as conforming.

[0059] Wherein, the preset acquisition module 210 includes:

[0060] A data acquisition unit 2101, configured to acquire stress data, annual average temperature variation data, and service life data of each position of the wind power cable;

[0061] A preset position determination unit 2102, configured to determine a preset position for weathering detection of the wind power cable according to the stress data, the annual average temperature variation data, and the service life data;

[0062] A preset period acquisition unit 2103, configured to acquire a preset period for weathering detection of the wind power cable.

[0063] The stress data may refer to the magnitude of the force borne by the inside and surface of the wind power cable; the annual average temperature variation data may refer to the average value of the temperature change range of the environment where the wind power cable is located within one year; the service life data may refer to the duration experienced by the wind power cable from the start of use to the current moment.

[0064] The stress data can be collected by a stress sensor; the annual average temperature variation data can be obtained by collecting temperature data through a temperature sensor and statistically calculating according to the temperature data; the service life data can be calculated by referring to the installation date of the wind power cable.

[0065] The method for determining the preset position for weathering detection of the wind power cable according to the stress data, the annual average temperature variation data, and the service life data can be to calculate the aging coefficient of the wind power cable according to the service life data, and determine the position of the wind power cable where its stress data exceeds the preset stress threshold, its annual average temperature variation data exceeds the preset temperature variation threshold, and its aging coefficient exceeds the preset aging threshold as the preset position. Wherein, the preset stress threshold can be 5 megapascals, the preset temperature variation threshold can be 30 degrees Celsius, and the preset aging threshold can be 0.8.

[0066] In this technical solution, optionally, the preset period acquisition unit is specifically configured to:

[0067] Obtain the wind speed data and temperature change speed data at each preset position, and determine a period adjustment coefficient according to the wind speed data and the temperature change speed data;

[0068] Obtain an initial preset period, and determine the preset period for performing weather resistance detection at each preset position according to the initial preset period and the period adjustment coefficient.

[0069] The wind speed data may refer to the magnitude of the air flow velocity per unit time, and the wind speed data can be collected by an anemometer. The temperature change speed data may refer to the rate at which the temperature data changes over time. The temperature change speed data can be obtained by collecting temperature data through a temperature sensor and then statistically analyzing the temperature data.

[0070] The period adjustment coefficient can be a numerical parameter used to adjust the period for performing weather resistance detection on the wind power cable. The method of determining the period adjustment coefficient according to the wind speed data and the temperature change speed data can be to calculate the ratio of the wind speed data to the reference wind speed as the first ratio, calculate the ratio of the temperature change speed data to the reference temperature change speed as the second ratio, and perform a weighted sum calculation on the first ratio and the second ratio according to a preset weight to obtain the period adjustment coefficient.

[0071] The initial preset period can refer to the reference value of the time interval at which the event of performing weather resistance detection repeats initially set. The method of determining the preset period for performing weather resistance detection at each preset position according to the initial preset period and the period adjustment coefficient can be to divide the initial preset period by the period adjustment coefficient to obtain the preset period.

[0072] The following is an example code for determining the preset period for performing weather resistance detection at each preset position according to the wind speed data and the temperature change speed data at each preset position:

[0073] # Define a function to obtain wind speed data. Here, it simply simulates collecting data from an anemometer

[0074] def get_wind_speed():

[0075] # In actual application, it should be replaced with the code for reading data from an anemometer

[0076] wind_speed = float(input("Please enter the current wind speed (m / s):"))

[0077] return wind_speed

[0078] # Define a function to obtain temperature change rate data. Here, it simply simulates collecting data from a temperature sensor and making statistics

[0079] def get_temperature_change_rate():

[0080] # In actual applications, it should be replaced with code to read data from a temperature sensor and make statistics

[0081] temperature_change_rate = float(input("Please enter the current temperature change rate (℃ / h):"))

[0082] return temperature_change_rate

[0083] # Define a function to calculate the cycle adjustment coefficient

[0084] def calculate_adjustment_coefficient(wind_speed, temperature_change_rate, base_wind_speed, base_temperature_change_rate, weight_wind, weight_temp):

[0085] # Calculate the first ratio

[0086] first_ratio = wind_speed / base_wind_speed

[0087] # Calculate the second ratio

[0088]

[0089] weight_wind, weight_temp)

[0090] # Determine the preset period

[0091] preset_period = determine_preset_period(initial_preset_period, adjustment_coefficient) print(f"The cycle adjustment coefficient is: {adjustment_coefficient}")

[0092] print(f"The preset period for weather resistance testing at each preset position is: {preset_period} hours")

[0093] The advantage of this solution is that by determining the preset cycle for weather resistance detection at each preset position based on the wind speed data and temperature change speed data at each preset position, the detection work can be more in line with the actual operation of the wind power cable, accurately match the potential risk levels of the wind power cable under different environmental conditions, and reasonably allocate detection resources.

[0094] The advantage of this solution is that by determining the preset positions for weather resistance detection of the wind power cable based on stress data, annual average temperature change amplitude data, and service life data, the weak parts of the wind power cable that are most vulnerable to environmental factors and its own aging can be accurately located, so as to concentrate detection resources and improve detection efficiency.

[0095] Embodiment III

[0096] Figure 3 It is a schematic structural diagram of an image exploration weather resistance detection device for a wind power cable provided in Embodiment III of the present application. This solution makes a better improvement on the basis of the above-mentioned embodiments. The specific improvement is as follows: The defect determination module includes: an anomaly recognition unit, which is used to extract the infrared image features of the area to be identified based on the infrared image, and match the infrared image features and preset anomaly features to identify whether there are anomaly features in the infrared image features; a defect determination unit, which is used to identify whether the anomaly features conform to the weather resistance defects when it is recognized that there are anomaly features in the infrared image features; a score determination unit, which is used to determine the anomaly score of the weather resistance defect according to the visible light image and the infrared image when it is recognized that the anomaly features conform to the weather resistance defects; an early warning generation unit, which is used to generate an early warning message for the weather resistance defect according to the anomaly score.

[0097] As Figure 3 shown, the device includes:

[0098] A preset acquisition module 310, which is used to acquire the preset positions and preset cycles for weather resistance detection of the wind power cable;

[0099] An image acquisition module 320, which is used to acquire the visible light image and the infrared image at the preset positions of the wind power cable according to the preset cycle; wherein, a high-definition camera and an infrared camera are arranged at the preset positions, or a running track of an unmanned exploration device carrying a high-definition camera and an infrared camera is arranged at the preset positions;

[0100] A defect recognition module 330, which is used to recognize the weather resistance defects of the wind power cable based on the visible light image, and determine the location where the weather resistance defects are located as the area to be identified; wherein, the weather resistance defects include at least one of cracks, bulges, and corrosion marks;

[0101] A defect determination module 340, configured to extract infrared image features of the area to be identified based on the infrared image, and identify whether there are abnormal features in the infrared image features and whether the abnormal features conform to the weather resistance defects, and generate a warning message for the weather resistance defects when it is identified as conforming.

[0102] Among them, the defect determination module 340 includes:

[0103] An abnormal feature recognition unit 3401, configured to extract infrared image features of the area to be identified based on the infrared image, and match the infrared image features with preset abnormal features, so as to identify whether there are abnormal features in the infrared image features and whether the abnormal features conform to the weather resistance defects;

[0104] A score determination unit 3402, configured to determine an abnormal score of the weather resistance defect according to the visible light image and the infrared image when it is identified that the abnormal features conform to the weather resistance defects;

[0105] A warning generation unit 3403, configured to generate a warning message for the weather resistance defect according to the abnormal score.

[0106] The preset abnormal features can be the infrared image features presented by the pre-constructed weather resistance defects. The method of matching the infrared image features with the preset abnormal features to identify whether there are abnormal features in the infrared image features and whether the abnormal features conform to the weather resistance defects can be to train a convolutional neural network model in advance using a large number of infrared image samples of weather resistance defects with annotations, so that the convolutional neural network model automatically learns the difference patterns between normal infrared image features and abnormal infrared image features, input the current infrared image into the trained convolutional neural network model, and the convolutional neural network model makes a judgment according to the learned feature patterns, and outputs whether there are abnormal features in the infrared image and the matching degree and category of the abnormal features with the weather resistance defects.

[0107] The abnormal score of the weather resistance defect can be a numerical index used to quantify the severity of the weather resistance defect. The method of determining the abnormal score of the weather resistance defect according to the visible light image and the infrared image can be to determine the defect density data of the weather resistance defect according to the visible light image, determine the maximum temperature difference data of the weather resistance defect according to the infrared image, and determine the abnormal score of the weather resistance defect according to the defect density data and the maximum temperature difference data.

[0108] In this technical solution, optionally, the score determination unit is specifically configured to:

[0109] Determine the defect density data of the weather resistance defect according to the visible light image;

[0110] Determine the maximum temperature difference data of the weathering defect based on the infrared image;

[0111] Determine the anomaly score of the weathering defect based on the defect density data and the maximum temperature difference data.

[0112] The defect density data may refer to the pixel proportion of weathering defects per unit area in the visible light image. The method for determining the defect density data of weathering defects based on the visible light image may be to count the number of pixels occupied by the area to be identified and the total number of pixels in the visible light image, and divide the number of pixels by the total number of pixels in the visible light image to obtain the defect density data of weathering defects.

[0113] The maximum temperature difference data may refer to the difference between the maximum temperature value and the minimum temperature value in the temperature distribution at the location of the weathering defect. The method for determining the maximum temperature difference data of weathering defects based on the infrared image may be to read the pixel values of each pixel of the weathering defect in the infrared image, and determine the temperature data corresponding to each pixel value according to the pre-established correlation between pixel values and temperature data, count the maximum and minimum values of the temperature data, and subtract the minimum value from the maximum value to obtain the maximum temperature difference data of the weathering defect.

[0114] The method for determining the anomaly score of weathering defects based on the defect density data and the maximum temperature difference data may be to perform normalization processing on the defect density data and the maximum temperature difference data, and perform weighted summation calculation on the normalized defect density data and maximum temperature difference data according to the preset weight coefficients to obtain the anomaly score of the weathering defect.

[0115] The following is an example code for determining the anomaly score of weathering defects based on visible light images and infrared images:

[0116]

[0117]

[0118]

[0119]

[0120] In this technical solution, optionally, the score determination unit is further configured to:

[0121] Obtain the temperature change rate data, humidity data, and salt fog concentration data at the preset position where the weathering defect is located;

[0122] Determine the environmental severity index according to the temperature change rate data, the humidity data, and the salt fog concentration data;

[0123] Obtain the historical maintenance record score of the preset position where the weather resistance defect is located;

[0124] Determine the abnormal score of the weather resistance defect according to the defect density data, the maximum temperature difference data, the environmental severity index, and the historical maintenance record score.

[0125] The humidity data can reflect the water vapor content in the air, and the humidity data can be collected by a humidity sensor. The salt fog concentration data can refer to the content of salt fog particles in the air, and the salt fog concentration data can be collected by a smoke concentration sensor.

[0126] The environmental severity index can be a quantitative index that comprehensively measures the degree of influence of the environment on the weather resistance of wind power cables. The method of determining the environmental severity index according to the temperature change rate data, the humidity data, and the salt fog concentration data can adopt the combination of the analytic hierarchy process and the grey relational analysis method.

[0127] The historical maintenance record score can be a value obtained after quantitatively evaluating the preset position where the weather resistance defect of the wind power cable is located in the past maintenance work. The historical maintenance record score can comprehensively consider various key information in the historical maintenance process, and is used to reflect the quality, effect of the past maintenance work, and the overall maintenance status of the wind power cable. The historical maintenance record score can be obtained by evaluating the historical maintenance record of the wind power cable.

[0128] The method of determining the abnormal score of the weather resistance defect according to the defect density data, the maximum temperature difference data, the environmental severity index, and the historical maintenance record score can adopt normalizing the defect density data, the maximum temperature difference data, the environmental severity index, and the historical maintenance record score, and performing weighted summation calculation on the normalized defect density data, the maximum temperature difference data, the environmental severity index, and the historical maintenance record score according to the preset weight coefficient to obtain the abnormal score of the weather resistance defect.

[0129] The advantage of this solution is that by introducing the environmental severity index and the historical maintenance record score on the basis of the defect density data of the visible light image and the maximum temperature difference data of the infrared image, multi-dimensional information can be integrated to more comprehensively and accurately evaluate the weather resistance defects of wind power cables.

[0130] The advantage of this solution is that by determining the abnormal score of the weather resistance defect according to the defect density data of the visible light image and the maximum temperature difference data of the infrared image, quantitative evaluation of the weather resistance defect can be realized, and the complex cable surface defect condition and internal thermal anomaly situation can be converted into intuitive numerical values, which is convenient for quickly judging the severity of the weather resistance defect.

[0131] The method for generating a warning message for weather resistance defects can pop up a warning window on the display device of the intelligent terminal device, and the location and abnormal score of the weather resistance defects are displayed in the warning window.

[0132] The advantage of this solution is that by comparing the infrared image features and the preset abnormal features to identify whether there are abnormal features in the infrared image features and whether the abnormal features conform to the weather resistance defects, the potential problems of the wind power cable can be accurately located, and the efficient screening of the weather resistance defects can be realized.

[0133] In this technical solution, optionally, the defect determination module further includes:

[0134] A preset period adjustment unit for adjusting the preset period according to the abnormal score.

[0135] The method for adjusting the preset period according to the abnormal score can be to divide the abnormal score by the preset abnormal score benchmark to obtain a period adjustment coefficient, and divide the current preset period by the period adjustment coefficient to obtain the adjusted preset period.

[0136] The advantage of this solution is that by adjusting the preset period according to the abnormal score, the detection work can be made more scientific and flexible, the detection resources can be reasonably allocated, and the operation and maintenance efficiency can be improved.

[0137] Embodiment 4

[0138] Figure 4 It is a schematic flowchart of the image exploration weather resistance detection method for the wind power cable provided by Embodiment 4 of this application. As Figure 4 shown, it specifically includes the following steps:

[0139] S401. Obtain the preset position and preset period for the weather resistance detection of the wind power cable through the preset acquisition module;

[0140] S402. Obtain the visible light image and infrared image at the preset position of the wind power cable according to the preset period through the image acquisition module; wherein, a high-definition camera and an infrared camera are arranged at the preset position, or a running track of an unmanned exploration device carrying the high-definition camera and the infrared camera is arranged at the preset position;

[0141] S403. Identify the weather resistance defects of the wind power cable based on the visible light image through the defect identification module, and determine the location of the weather resistance defects as the area to be identified; wherein, the weather resistance defects include at least one of cracks, bulges, and corrosion marks;

[0142] S404. The defect determination module extracts the infrared image features of the area to be identified based on the infrared image, and identifies whether there are abnormal features in the infrared image features and whether the abnormal features conform to the weathering defects. When it is identified as conforming, a warning message for the weathering defects is generated.

[0143] In the embodiment of the present application, a preset acquisition module acquires a preset position and a preset period for the weathering detection of the wind power cable; an image acquisition module acquires a visible light image and an infrared image at the preset position of the wind power cable according to the preset period; wherein, a high-definition camera and an infrared camera are arranged at the preset position, or, a running track of an unmanned exploration device carrying the high-definition camera and the infrared camera is arranged at the preset position; a defect identification module identifies the weathering defects of the wind power cable based on the visible light image, and determines the location where the weathering defects are located as the area to be identified; wherein, the weathering defects include at least one of cracks, bulges, and corrosion marks; the defect determination module extracts the infrared image features of the area to be identified based on the infrared image, and identifies whether there are abnormal features in the infrared image features and whether the abnormal features conform to the weathering defects. When it is identified as conforming, a warning message for the weathering defects is generated. The above method for detecting the weathering of the wind power cable by image exploration can dynamically and accurately detect the weathering defects of the wind power cable by acquiring the visible light image and the infrared image of the wind power cable, thereby providing a reliable guarantee for its long-term stable operation in a complex outdoor environment.

[0144] The method for detecting the weathering of the wind power cable by image exploration provided by the embodiment of the present application corresponds to the device for detecting the weathering of the wind power cable by image exploration provided by the above embodiment, and has the same functional modules and beneficial effects. To avoid repetition, it will not be elaborated here.

[0145] Embodiment Five

[0146] As Figure 5 shown, the embodiment of the present application further provides an electronic device 500, including a processor 501, a memory 502, a program or instruction stored on the memory 502 and executable on the processor 501. When the program or instruction is executed by the processor 501, it implements each process of the above embodiment of the device for detecting the weathering of the wind power cable by image exploration, and can achieve the same technical effect. To avoid repetition, it will not be elaborated here.

[0147] It should be noted that the electronic device in the embodiment of the present application includes the above-mentioned mobile electronic device and non-mobile electronic device.

[0148] Embodiment Six

[0149] The embodiments of the present application further provide a readable storage medium, on which a program or instructions are stored. When the program or instructions are executed by a processor, each process of the above-mentioned image exploration weather resistance detection device for wind power cables in the embodiments is implemented, and the same technical effects can be achieved. To avoid repetition, it will not be elaborated here.

[0150] Among them, the processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs, etc.

[0151] Embodiment Seven

[0152] The embodiments of the present application further provide a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is used to run a program or instructions to implement each process of the above-mentioned image exploration weather resistance detection device for wind power cables in the embodiments, and the same technical effects can be achieved. To avoid repetition, it will not be elaborated here.

[0153] It should be understood that the chip mentioned in the embodiments of the present application can also be referred to as a system-on-chip, system chip, chip system, or system-on-chip, etc.

[0154] It should be noted that in this article, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed, or further includes elements inherent to such process, method, article or device. Without more limitations, an element defined by the statement "including a..." does not exclude the existence of another identical element in the process, method, article or device including that element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in a reverse order according to the functions involved. For example, the described methods may be performed in an order different from that described, and various steps may be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0155] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-described embodiment methods can be implemented by means of software plus a necessary general hardware platform. Of course, they can also be implemented by hardware, but in many cases, the former is a better implementation method. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art can be embodied in the form of a computer software product. The computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions for causing a terminal (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present application.

[0156] The embodiments of the present application have been described above in conjunction with the accompanying drawings. However, the present application is not limited to the above specific implementation manners. The above specific implementation manners are merely illustrative and not restrictive. Under the inspiration of the present application, those of ordinary skill in the art can also make many forms without departing from the purpose of the present application and the scope protected by the claims, and all of them belong to the protection scope of the present application.

[0157] The above is only the preferred embodiment of the present application and the technical principles applied. The present application is not limited to the specific embodiments described herein. Various obvious changes, re-adjustments, and substitutions that can be made by those skilled in the art will not depart from the protection scope of the present application. Therefore, although the present application has been described in more detail through the above embodiments, the present application is not limited to the above embodiments. Without departing from the concept of the present application, it can also include more other equivalent embodiments, and the scope of the present application is determined by the scope of the claims.

Claims

1. An image survey and weather resistance detection device for wind power cables, characterized in that: The device comprises: A preset acquisition module is used to obtain a preset position and a preset period for weather resistance testing of a wind power cable; An image acquisition module, used for acquiring a visible light image and an infrared image at a preset position of the wind power generation cable according to the preset period; wherein the preset position is provided with a high-definition camera and an infrared camera, or the preset position is provided with a running track of an unmanned survey equipment carrying a high-definition camera and an infrared camera; A defect recognition module, used for identifying weather resistance defects of the wind power generation cable based on the visible light image, and determining the location of the weather resistance defects as the area to be identified; wherein the weather resistance defects include at least one of cracks, bulges and corrosion marks; The defect determination module is used to extract the infrared image features of the area to be identified based on the infrared image, and to identify whether there are abnormal features in the infrared image features and whether the abnormal features meet the requirements of the weather resistance defects, and to generate early warning information of the weather resistance defects when the abnormal features are identified as being met.

2. The image survey and weather resistance detection device for wind power cable according to claim 1 is characterized in that: The preset acquisition module includes: A data acquisition unit, used to acquire stress data, annual average temperature variation data and service life data of each position of the wind power cable; A preset position determination unit, used to determine a preset position for weather resistance testing of the wind power cable according to the stress data, the annual average temperature variation data and the service life data; The preset period acquisition unit is used to acquire the preset period for weather resistance testing of the wind power generation cable.

3. The image survey and weather resistance detection device for wind power cables according to claim 2 is characterized in that: The preset period acquisition unit is specifically used for: Obtaining wind speed data and temperature change rate data at each preset position, and determining a period adjustment coefficient according to the wind speed data and the temperature change rate data; An initial preset period is obtained, and a preset period for performing weather resistance testing at each preset position is determined according to the initial preset period and the period adjustment coefficient.

4. The image survey and weather resistance detection device for wind power cable according to claim 1, characterized in that: The defect determination module comprises: an abnormality identification unit, configured to extract infrared image features of the area to be identified based on the infrared image, and compare the infrared image features with preset abnormal features to identify whether there are abnormal features in the infrared image features and whether the abnormal features conform to the weather resistance defects; a score determination unit, configured to determine an abnormality score of the weather resistance defect according to the visible light image and the infrared image when the abnormal feature is identified as being consistent with the weather resistance defect; An early warning generation unit is used to generate early warning information of the weather resistance defect according to the abnormal score.

5. The image survey and weather resistance detection device for wind power cable according to claim 4 is characterized in that: The score determination unit is specifically used to: determining defect density data of the weather resistance defect according to the visible light image; Determine the maximum temperature difference data of the weather resistance defect according to the infrared image; An abnormal score of the weather resistance defect is determined according to the defect density data and the maximum temperature difference data.

6. The image survey and weather resistance detection device for wind power cable according to claim 5, characterized in that: The score determination unit is further used for: Obtaining temperature change rate data, humidity data, and salt spray concentration data at a preset location where the weather resistance defect is located; Determining an environmental severity index according to the temperature change rate data, the humidity data, and the salt spray concentration data; Obtaining a historical maintenance record score for a preset location of the weather resistance defect; An abnormal score of the weather resistance defect is determined according to the defect density data, the maximum temperature difference data, the environmental severity index, and the historical maintenance record score.

7. The image survey and weather resistance detection device for wind power cable according to claim 4, characterized in that: The defect determination module further includes: A preset period adjustment unit is used to adjust the preset period according to the abnormality score.

8. A method for image survey and weather resistance detection of wind power cables, characterized in that: The method comprises: The preset position and preset period for weather resistance testing of the wind power cable are obtained through a preset acquisition module; Obtaining a visible light image and an infrared image at a preset position of the wind power cable according to the preset period by an image acquisition module; wherein a high-definition camera and an infrared camera are provided at the preset position, or a running track of an unmanned survey equipment carrying a high-definition camera and an infrared camera is provided at the preset position; Identifying the weather resistance defect of the wind power cable based on the visible light image through a defect recognition module, and determining the location of the weather resistance defect as the area to be identified; wherein the weather resistance defect includes at least one of a crack, a bulge, and a corrosion mark; The defect determination module extracts the infrared image features of the area to be identified based on the infrared image, and identifies whether there are abnormal features in the infrared image features and whether the abnormal features meet the weather resistance defects. If the abnormal features are identified as being in compliance, early warning information of the weather resistance defects is generated.

9. The image survey weather resistance detection method for wind power cable according to claim 8, characterized in that: The preset acquisition module is used to obtain the preset position and preset period for the weather resistance test of the wind power cable, including: The data acquisition unit is used to obtain stress data, annual average temperature variation data and service life data of each position of the wind power cable; Determining, by a preset position determination unit, a preset position for weather resistance testing of the wind power generation cable according to the stress data, the annual average temperature variation data and the service life data; The preset period for weather resistance testing of the wind power generation cable is obtained by a preset period acquisition unit.

10. An electronic device, characterized in that: It includes a processor, a memory, and a program or instruction stored in the memory and executable on the processor. When the program or instruction is executed by the processor, the steps of the image survey and weather resistance detection method for wind power cables as described in any one of claims 8 to 9 are implemented.

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