A deicing effect evaluation control method and device based on infrared image analysis

Abstract

The present application relates to a deicing effect evaluation and control method and device based on infrared image analysis, the method comprising obtaining a first infrared image of the transmission line located in front of the deicing equipment and a second infrared image of the transmission line located behind the deicing equipment on each transmission line; training a convolutional neural network model for judging the deicing effect of the transmission line based on the historical first infrared image and the second infrared image; obtaining a deicing evaluation result and residual ice coverage thickness using the trained convolutional neural network model; and controlling the deicing equipment to perform deicing operations based on the deicing evaluation result. The method can evaluate the deicing effect of the deicing equipment on the transmission line by using infrared images, and then control the deicing equipment to operate in a cycle or in a traveling manner, so as to realize the automatic deicing operation of the deicing equipment on the transmission line and ensure the deicing effect.

Description

Technical Field

[0001] The present application relates to the technical field of electric deicing operations, and in particular to a deicing effect evaluation and control method and device based on infrared image analysis. Background Art

[0002] In severe winter weather with rain and snow, transmission lines and towers are easily covered with ice and snow, which can cause cable breakage and tower collapse, resulting in casualties of people and animals around, damage to transmission lines, and huge losses. In addition, since existing overhead transmission lines are characterized by large spans and long lines, it is very difficult to de-ice large-scale transmission lines.

[0003] At present, there are four main methods for removing ice and snow from high-voltage transmission lines: mechanical deicing, thermal ice melting, natural deicing (also known as passive deicing), and mixed methods. Among them, mechanical deicing is a contact deicing operation, which directly contacts the cable through mechanical equipment or manual means, and uses special tools to physically de-ice the cable. In particular, most mechanical deicing equipment, such as deicing robots, is used. By placing the deicing equipment on the transmission cable, the deicing equipment is manually or automatically controlled to move along the transmission cable, and the cable is de-iced using the attached deicing components during the movement. However, this process usually requires maintenance personnel to operate or supervise and evaluate, and it is impossible to automatically evaluate the deicing operation process of the transmission cable. It is not only inefficient, but also imposes a serious workload on maintenance personnel, especially in severe rain and snow weather in winter, which poses a huge test on the physical strength of the staff. For large-scale transmission lines, each deicing equipment needs to be equipped with maintenance personnel, which requires greater labor costs and lower operating efficiency. Summary of the invention

[0004] In order to overcome the above-mentioned deficiencies of the prior art, the present application provides a deicing effect evaluation control method and device based on infrared image analysis, which specifically adopts the following technical solutions:

[0005] A deicing effect evaluation and control method based on infrared image analysis is used to control the movement of deicing equipment in a power line deicing operation device. The power line deicing operation device includes at least one image acquisition device, a data processing center and a plurality of deicing equipment. The method includes the following steps:

[0006] Using an image acquisition device to acquire in real time an infrared image of the transmission line at the location of the deicing equipment on each transmission line, wherein the infrared image of the transmission line includes at least a first infrared image of the transmission line located in front of the deicing equipment and a second infrared image of the transmission line located behind the deicing equipment;

[0007] A convolutional neural network model for judging the deicing effect of a transmission line is obtained by training the first infrared image and the second infrared image of the historical transmission line using a data processing center;

[0008] The infrared image of the transmission line obtained by the image acquisition device is input into the trained convolutional neural network model to obtain the deicing assessment result and residual ice coverage thickness of the corresponding transmission line position;

[0009] Control the deicing operation of the deicing equipment at the current transmission line location based on the deicing assessment results:

[0010] Obtain the residual ice coverage thickness at the current transmission line location and the deicing thickness of the deicing equipment in the last operation as the deicing thickness of the deicing equipment in a single operation;

[0011] The number of times the de-icing equipment operates at the current transmission line location is calculated based on the de-icing thickness and residual ice coverage thickness of the de-icing equipment in a single operation:

[0012] ;

[0013] in N Number of operations for de-icing equipment; is the rounding up operation function; T is the thickness of residual ice cover; The de-icing thickness of the de-icing equipment in a single operation;

[0014] Based on the number of operations of the deicing equipment at the current transmission line position, the deicing equipment is controlled to perform deicing operations back and forth at the current transmission line position.

[0015] Optionally: a single transmission line is divided into several transmission line units according to its length, the image acquisition device acquires the transmission line infrared images of the transmission line units in batches, and controls the de-icing operation of the de-icing equipment within the current transmission line unit based on the transmission line infrared images of the single transmission line unit.

[0016] Optionally: when the deicing equipment is controlled to perform deicing operations back and forth at the current transmission line location based on the number of operations of the deicing equipment at the current transmission line location, the image acquisition device simultaneously acquires a second infrared image of the current transmission line location, and determines the temperature of the transmission line in the second infrared image:

[0017] When the temperature of the transmission line in the second infrared image is higher than or equal to the first preset threshold value, it is judged that the residual ice on the transmission line has been cleared, and the number of operations at the current transmission line position is reset to zero; when the temperature of the transmission line in the second infrared image is lower than the first preset threshold value, it is judged that there is still residual ice on the transmission line, and the de-icing equipment continues the de-icing operation according to the number of operations at the current transmission line position.

[0018] Optionally, the deicing equipment is provided with at least an operating speed and a traveling speed, and when the image acquisition device acquires the infrared image of the transmission line at the location of the deicing equipment on each transmission line, the first infrared image is analyzed:

[0019] When the temperature of the transmission line in the first infrared image is higher than or equal to the first preset threshold value, it is judged that the residual ice on the transmission line in front of the deicing equipment has been cleared or is not covered with ice, and the deicing equipment moves at the traveling speed; when the temperature of the transmission line in the first infrared image is lower than the first preset threshold value, it is judged that there is an ice layer on the transmission line in front of the deicing equipment, and the deicing equipment moves at the operating speed.

[0020] Optional: When the residual ice coverage thickness at the corresponding transmission line location is obtained, the image acquisition device analyzes the second infrared image using the conversion relationship between the calibrated grayscale value and temperature to obtain the boundary between the line part and the ice layer part in the infrared image; and calculates the first residual ice coverage thickness based on the number of pixels in the ice layer part and the number of pixels in the line part.

[0021] Optional: When the residual ice cover thickness at the corresponding transmission line location is obtained, the line temperature and the ice layer surface temperature at the corresponding transmission line location are used, and a relationship model between ice layer thickness and temperature difference established based on heat conduction theory is combined to estimate the second residual ice cover thickness at the corresponding transmission line location.

[0022] Optional: Analyze the first residual ice coverage thickness and the second residual ice coverage thickness at the same location in the transmission line:

[0023] When the difference between the first residual ice cover thickness and the second residual ice cover thickness is less than or equal to the second preset threshold, taking the average value of the first residual ice cover thickness and the second residual ice cover thickness as the residual ice cover thickness at the current transmission line location;

[0024] When the difference between the first residual ice cover thickness and the second residual ice cover thickness is greater than a second preset threshold, the maximum value of the first residual ice cover thickness and the second residual ice cover thickness is taken as the residual ice cover thickness at the current transmission line location.

[0025] Optional: The image acquisition device uses a drone with an infrared camera, and the image acquisition device acquires an infrared image of each transmission line, and sends the infrared image of the transmission line to a data processing center; the data processing center analyzes and processes the infrared image of the transmission line to obtain the number of deicing operation cycles of the deicing equipment at the current transmission line position and sends it to the corresponding deicing equipment; the deicing equipment performs deicing operations on the current transmission line position based on the number of deicing operation cycles.

[0026] Optionally: when the deicing equipment is performing deicing operations at the current transmission line location, the data processing center analyzes the first infrared image and the second infrared image of the front and rear positions of the deicing equipment in real time:

[0027] When there is ice on the transmission line in the first infrared image, and the thickness of the ice does not change in the first infrared image and the second infrared image, or the change in the thickness of the ice is lower than a third preset threshold, it is determined that the de-icing equipment is abnormal;

[0028] When there is an ice layer on the transmission line in the first infrared image, and the change in ice layer thickness between the first infrared image and the second infrared image is greater than or equal to a third preset threshold, it is determined that the de-icing equipment is operating normally.

[0029] In addition, the present application also discloses a deicing effect evaluation control device based on infrared image analysis, which is used to control the movement of deicing equipment in a power transmission line deicing operation device, and the device includes:

[0030] An image acquisition module, used for acquiring, in real time, an infrared image of a power transmission line at a location where a deicing device is located on the power transmission line using an image acquisition device, wherein the infrared image of the power transmission line includes at least a first infrared image of the power transmission line located in front of the deicing device and a second infrared image of the power transmission line located behind the deicing device;

[0031] A model training module, used for obtaining a convolutional neural network model for judging the deicing effect of a transmission line by using a first infrared image and a second infrared image of a historical transmission line trained by a data processing center;

[0032] An image analysis module is used to input the infrared image of the power transmission line obtained by the image acquisition device into the trained convolutional neural network model to obtain a deicing assessment result including the residual ice coverage thickness of the corresponding transmission line;

[0033] The operation control module is used to control the deicing operation of the deicing equipment on the current transmission line based on the deicing assessment results:

[0034] The residual ice coverage thickness is obtained according to the deicing assessment result, and the deicing thickness of the current deicing equipment in the last operation is obtained as the deicing thickness of the deicing equipment in a single operation;

[0035] The number of times the de-icing equipment operates at the current transmission line location is calculated based on the de-icing thickness and residual ice coverage thickness of the de-icing equipment in a single operation:

[0036] ;

[0037] in N Number of operations for de-icing equipment; is the rounding up operation function; T is the thickness of residual ice cover; The de-icing thickness of the de-icing equipment in a single operation;

[0038] Based on the number of operations of the deicing equipment at the current transmission line position, the deicing equipment is controlled to perform deicing operations back and forth at the current transmission line position.

[0039] Beneficial Effects

[0040] The technical solution of this application has the following beneficial effects:

[0041] (1) The de-icing effect evaluation and control method of the present application can evaluate the de-icing effect of the de-icing equipment on the transmission line by using infrared images, and then control the de-icing equipment to operate in a circular manner (i.e., de-icing operation in a certain section of the transmission line) or in a moving manner (i.e., de-icing operation in one direction on the transmission line), thereby realizing the automatic de-icing operation of the de-icing equipment on the transmission line and ensuring the de-icing effect.

[0042] (2) The de-icing effect evaluation and control method of the present application can determine whether there is an ice layer on the transmission line by using infrared images, and control the de-icing equipment to automatically switch the operating speed or travel speed, thereby improving the de-icing operation efficiency.

[0043] (3) The de-icing effect evaluation and control method of the present application can simultaneously control multiple de-icing devices to perform de-icing operations on multiple transmission lines, and control different de-icing devices separately, thereby improving the operation efficiency and being more suitable for de-icing operations on large-scale transmission lines.

[0044] (4) The de-icing effect evaluation and control method of the present application can quickly identify abnormal operation of the de-icing equipment by analyzing and judging the infrared images before and after the de-icing equipment, and promptly alarm to avoid ineffective operation or safety hazards. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 This is a flow chart of the deicing effect evaluation control method in an embodiment of the present application.

[0046] Figure 2 It is a schematic diagram of the structural composition of the power transmission line deicing operation device in the embodiment of the present application.

[0047] Figure 3 1 is a structural diagram of a power transmission line deicing control device in an embodiment of the present application.

[0048] Figure 4 This is a structural diagram of an electronic device in an embodiment of the present application. DETAILED DESCRIPTION

[0049] The present application is further described below in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present application, and cannot be used to limit the scope of protection of the present application. It should be noted that the following detailed descriptions are all exemplary and are intended to provide further explanation of the present application.

[0050] For large-scale transmission lines, ice will increase the weight of the conductors. For example, when the thickness of the conductor ice reaches a certain level, such as 10-30mm or even thicker ice in heavy ice areas, its weight may exceed the load-bearing capacity of the line design, resulting in increased conductor sag, reducing the safe distance between the conductor and the ground or crossing objects, and even causing short circuit accidents between the conductor and objects such as trees and buildings, seriously affecting the safe and stable operation of the power system. In addition, the ice layer will cause the transmission line to bear additional mechanical stress, accelerating the aging and damage of the equipment. In addition, the ice layer will further increase the reactance of the transmission line, and the power loss will increase accordingly, increasing the cost of power transmission.

[0051] At present, most de-icing equipment (such as de-icing robots) is used to de-ice transmission lines, and most de-icing equipment moves on the transmission lines through walking mechanisms, and uses de-icing mechanisms to remove ice. For example, cutting impact, knocking, rolling, etc., or the technology combining asymmetric breaking force and frequency-appropriate vibration force are used to intelligently match de-icing force and vibration frequency, so that ice wrapped on overhead ground wires can fall off quickly. However, the evaluation of transmission lines after de-icing is generally completed manually. If there is residual ice in some areas of the transmission line, secondary operations are required, which seriously delays the de-icing efficiency.

[0052] Therefore, this application uses infrared imaging technology as an evaluation method after deicing operations. By analyzing infrared imaging during the deicing operation stage through a data processing center (such as a computer group), the deicing effect can be accurately evaluated, thereby improving deicing efficiency and quality. Infrared imaging technology is a non-contact detection method that does not require direct contact with the power transmission line, thus avoiding safety risks caused by some unstable factors (such as ice hanging falling, etc.) in the line after the deicing operation.

[0053] Combination Figure 1 As shown, the embodiment of the present application discloses a deicing effect evaluation control method based on infrared image analysis, which is used to control the movement of deicing equipment in a power transmission line deicing operation device, such as Figure 2As shown, the power transmission line deicing operation device includes at least one image acquisition device, a data processing center and several deicing equipment. For example, the image acquisition device in the embodiment of the present application can use a drone with an infrared camera, the deicing equipment uses a deicing robot walking along the power transmission line, and the data processing center uses a vehicle-type control center. For multiple power transmission cables between two power transmission support frames, a deicing device can be equipped on each power transmission cable, and each deicing device can be equipped with a drone with an infrared camera. At the same time, the drone follows the deicing equipment to move and fly, monitor the operation process of each deicing device in real time, and collect the corresponding infrared image of the power transmission line. Of course, multiple deicing equipment can also share a drone with an infrared camera. For example, multiple deicing equipment and a drone with an infrared camera are equipped for the power transmission line between two power transmission support frames. The drone can fly between the two power transmission support frames and collect infrared images of different power transmission lines. When deicing large-scale power transmission lines in remote areas, the vehicle-type control center can be used as a data processing and transfer device. By deploying the vehicle-type control center in the operation area, the difficulty of data transmission and network requirements can be reduced.

[0054] The image acquisition device acquires the transmission line infrared image of each transmission line, and sends the transmission line infrared image to the data processing center; the data processing center analyzes and processes the transmission line infrared image to obtain the number of deicing operation cycles of the deicing equipment at the current transmission line position and sends it to the corresponding deicing equipment; the deicing equipment performs deicing operations on the current transmission line position based on the number of deicing operation cycles.

[0055] Furthermore, the deicing effect evaluation and control method based on infrared image analysis in the present application includes the following steps:

[0056] Step S1: using an image acquisition device to acquire in real time an infrared image of the transmission line at the location of the deicing equipment on each transmission line, wherein the infrared image of the transmission line includes at least a first infrared image of the transmission line located in front of the deicing equipment and a second infrared image of the transmission line located behind the deicing equipment.

[0057] Step S2: Using the data processing center to train the first infrared image and the second infrared image of the historical power transmission line to obtain a convolutional neural network model for judging the deicing effect of the power transmission line. It should be noted that in this application, the convolutional neural network model is trained using the annotated first infrared image and the second infrared image in the historical image, wherein when annotating each pair of infrared images collected, the key information annotated is the deicing effect, for example, the deicing effect is divided into categories such as "good deicing", "partial deicing", and "poor deicing", or a more detailed numerical indicator is used to represent the degree of deicing (such as deicing rate of more than 90% is marked as "excellent", 60%-90% is marked as "medium", and less than 60% is marked as "poor", etc.). For the convolutional neural network model, a classic convolutional neural network architecture can be selected as the basis, such as AlexNet, VGGNet, ResNet, etc., or some lightweight architectures suitable for mobile terminals or scenarios with high real-time requirements can be selected, such as MobileNet, ShuffleNet, etc., depending on the application scenario of the subsequent model and the trade-off between accuracy and computing resources.

[0058] Step S3: Input the infrared image of the transmission line obtained by the image acquisition device into the trained convolutional neural network model to obtain the deicing assessment result and residual ice coverage thickness of the corresponding transmission line location.

[0059] Step S4: Controlling the deicing operation of the deicing equipment at the current transmission line location based on the deicing evaluation result:

[0060] (1) Obtain the residual ice coverage thickness at the current transmission line location and the de-icing thickness of the de-icing equipment in the last operation as the de-icing thickness of the de-icing equipment in a single operation; the residual ice coverage thickness can be obtained according to the output result of the trained convolutional neural network model, and the de-icing thickness of the de-icing equipment in the last operation can be obtained according to the difference between the residual ice coverage thickness of the first infrared image and the second infrared image.

[0061] (2) Calculate the number of times the de-icing equipment operates at the current transmission line location based on the de-icing thickness of the de-icing equipment in a single operation and the thickness of the residual ice cover:

[0062] ;

[0063] in N Number of operations for de-icing equipment; is the rounding up operation function; T is the thickness of residual ice cover; The de-icing thickness of the de-icing equipment in a single operation;

[0064] (3) Based on the number of times the de-icing equipment has been operated at the current transmission line location, the de-icing equipment is controlled to perform de-icing operations back and forth at the current transmission line location.

[0065] Furthermore, in step S4 of the present application, when the deicing equipment is controlled to perform deicing operations back and forth at the current transmission line position based on the number of operations of the deicing equipment at the current transmission line position, the image acquisition device simultaneously acquires a second infrared image of the current transmission line position, and determines the temperature of the transmission line in the second infrared image:

[0066] When the temperature of the transmission line in the second infrared image is higher than or equal to the first preset threshold, it is judged that the residual ice on the transmission line has been cleared, and the number of operations at the current transmission line position is reset to zero; when the temperature of the transmission line in the second infrared image is lower than the first preset threshold, it is judged that there is still residual ice on the transmission line, and the deicing equipment continues the deicing operation according to the number of operations at the current transmission line position. By monitoring the temperature of the transmission line in the second infrared image, the effect of the deicing operation on the transmission line can be judged in time to avoid the ice layer on the line not being completely cleared, and it can also avoid the deicing equipment from continuing to operate after the ice layer has been completely cleared, causing damage to the transmission line.

[0067] In addition, the deicing equipment in the present application is at least provided with an operating speed and a travel speed. When the image acquisition device acquires the infrared image of the transmission line at the location of the deicing equipment on each transmission line in step S1, the first infrared image is analyzed:

[0068] When the temperature of the power transmission line in the first infrared image is higher than or equal to the first preset threshold, it is judged that the residual ice on the power transmission line in front of the deicing device has been cleared or is not covered with ice, and the deicing device moves at the travel speed; when the temperature of the power transmission line in the first infrared image is lower than the first preset threshold, it is judged that there is an ice layer on the power transmission line in front of the deicing device, and the deicing device moves at the operating speed. By monitoring the temperature of the power transmission line in the second infrared image, it can be judged whether there is an ice layer on the power transmission line, especially for the situation where the ice layer on the power transmission line is unevenly distributed (for example, some areas of the power transmission line are covered with ice, and other areas are not covered with ice). Based on the existence of the ice layer, the travel speed of the deicing device can be intelligently controlled, and the operating speed can be maintained in the ice-covered area to ensure the deicing effect of the deicing device, while the travel speed can be maintained at a higher speed in the un-ice-covered area to improve the deicing efficiency.

[0069] It should be noted that when obtaining the residual ice cover thickness at the corresponding transmission line location in step S3 of the present application, the image acquisition device can use the conversion relationship between the calibrated grayscale value and temperature to analyze the second infrared image to obtain the boundary between the line part and the ice layer part in the infrared image; and calculate the first residual ice cover thickness based on the number of pixels in the ice layer part and the number of pixels in the line part.

[0070] Alternatively, another method is to use the line temperature and ice surface temperature at the corresponding transmission line location, combined with a relationship model between ice thickness and temperature difference established based on heat conduction theory, to estimate the second residual ice cover thickness at the corresponding transmission line location.

[0071] Furthermore, the present application can also obtain the corresponding first residual ice coverage thickness and second residual ice coverage thickness respectively through the above two methods, and finally analyze the first residual ice coverage thickness and the second residual ice coverage thickness at the same position in the transmission line:

[0072] When the difference between the first residual ice cover thickness and the second residual ice cover thickness is less than or equal to the second preset threshold, taking the average value of the first residual ice cover thickness and the second residual ice cover thickness as the residual ice cover thickness at the current transmission line location;

[0073] When the difference between the first residual ice cover thickness and the second residual ice cover thickness is greater than a second preset threshold, the maximum value of the first residual ice cover thickness and the second residual ice cover thickness is taken as the residual ice cover thickness at the current transmission line location.

[0074] By comparing the first residual ice coverage thickness with the second residual ice coverage thickness, the number of cycle operations of the de-icing equipment can be accurately obtained, thereby improving the control accuracy of the equipment. At the same time, the situation in which incomplete de-icing is caused by a change in the single de-icing rate of the de-icing equipment can be avoided, thereby improving the de-icing quality.

[0075] Optionally: when the deicing equipment is performing deicing operations at the current transmission line location, the data processing center analyzes the first infrared image and the second infrared image of the front and rear positions of the deicing equipment in real time:

[0076] When there is ice on the transmission line in the first infrared image, and the thickness of the ice does not change in the first infrared image and the second infrared image, or the change in the thickness of the ice is lower than a third preset threshold, it is determined that the de-icing equipment is abnormal;

[0077] When there is an ice layer on the transmission line in the first infrared image, and the change in ice layer thickness between the first infrared image and the second infrared image is greater than or equal to a third preset threshold, it is determined that the de-icing equipment is operating normally.

[0078] Furthermore, in the present application, a single transmission line can be divided into several transmission line units according to its length, and the image acquisition device acquires the transmission line infrared images of the transmission line units in batches, and controls the deicing operation of the deicing equipment within the current transmission line unit based on the transmission line infrared images of the single transmission line unit. For example, the transmission line between two transmission support frames can be divided into multiple transmission line units according to its length, and the deicing equipment performs deicing operation on each transmission line unit in turn. When the operation of the corresponding transmission line unit is completed, the deicing equipment enters the next transmission line unit, and the image acquisition device performs image acquisition for the deicing operation process of each transmission line unit. This method can further reduce the number of image acquisition devices arranged, especially for the situation where there are multiple transmission lines, the multiple transmission lines can be divided into sections at the same length interval, and each section only needs one image acquisition device for image acquisition, and in the present application, a drone can be used to collect data for each transmission line unit in turn, and then control the operation process of the deicing equipment in the current transmission line unit, which not only reduces the equipment cost, but also ensures the deicing efficiency.

[0079] Combination Figure 3 As shown, in addition, the present application also discloses a deicing effect evaluation control device based on infrared image analysis, which is used to control the movement of deicing equipment in a power transmission line deicing operation device, and the device includes:

[0080] An image acquisition module, used for acquiring, in real time, an infrared image of a power transmission line at a location where a deicing device is located on the power transmission line using an image acquisition device, wherein the infrared image of the power transmission line includes at least a first infrared image of the power transmission line located in front of the deicing device and a second infrared image of the power transmission line located behind the deicing device;

[0081] A model training module, used for obtaining a convolutional neural network model for judging the deicing effect of a transmission line by using a first infrared image and a second infrared image of a historical transmission line trained by a data processing center;

[0082] An image analysis module is used to input the infrared image of the power transmission line obtained by the image acquisition device into the trained convolutional neural network model to obtain a deicing assessment result including the residual ice coverage thickness of the corresponding transmission line;

[0083] The operation control module is used to control the deicing operation of the deicing equipment on the current transmission line based on the deicing assessment results:

[0084] The residual ice coverage thickness is obtained according to the deicing assessment result, and the deicing thickness of the current deicing equipment in the last operation is obtained as the deicing thickness of the deicing equipment in a single operation;

[0085] The number of times the de-icing equipment operates at the current transmission line location is calculated based on the de-icing thickness and residual ice coverage thickness of the de-icing equipment in a single operation:

[0086] ;

[0087] in N Number of operations for de-icing equipment; is the rounding up operation function; T is the thickness of residual ice cover; The de-icing thickness of the de-icing equipment in a single operation;

[0088] Based on the number of operations of the deicing equipment at the current transmission line position, the deicing equipment is controlled to perform deicing operations back and forth at the current transmission line position.

[0089] The device provided in the embodiment of the present application can achieve Figure 1 To avoid repetition, the various processes implemented by the method embodiment will not be described again here.

[0090] like Figure 4 As shown, the embodiment of the present application also provides an electronic device, including a processor and a memory, a program or instruction stored in the memory and executable on the processor, and when the program or instruction is executed by the processor, the following is achieved: Figure 1 The various processes of the method embodiment shown in the figure can achieve the same technical effect. To avoid repetition, they will not be described again here.

[0091] The embodiment of the present application also provides a readable storage medium on which a program or instruction is stored. When the program or instruction is executed by a processor, the above Figure 1 The various processes of the method embodiments described above can achieve the same technical effect, and will not be described again here to avoid repetition.

[0092] The present application also provides a computer program product, including computer instructions, which, when executed by a processor, implement the above Figure 1 The various processes of the method embodiments described above can achieve the same technical effect, and will not be described again here to avoid repetition.

[0093] It should be understood that "one embodiment" or "an embodiment" mentioned throughout the specification means that specific features, structures or characteristics related to the embodiment are included in at least one embodiment of the present application. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. In addition, these specific features, structures or characteristics can be combined in one or more embodiments in any suitable manner. It should be understood that in various embodiments of the present application, the size of the sequence number of the above-mentioned processes does not mean the order of execution, and the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application. The above-mentioned sequence numbers of the embodiments of the present application are only for description and do not represent the advantages and disadvantages of the embodiments.

[0094] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0095] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another device, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0096] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0097] In addition, all functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may be a separate unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0098] A person skilled in the art can understand that all or part of the steps of implementing the above method embodiment can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above method embodiment; and the aforementioned storage medium includes: mobile storage devices, read-only memories (ROM), magnetic disks or optical disks, etc., various media that can store program codes.

[0099] Alternatively, if the above-mentioned integrated unit of the present application is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application can essentially or in other words, the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a device (which can be a terminal or a platform, etc.) to execute all or part of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROMs, magnetic disks, or optical disks.

[0100] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A deicing effect evaluation and control method based on infrared image analysis, which is used to control the movement of deicing equipment in a power line deicing operation device, wherein the power line deicing operation device comprises at least one image acquisition device, a data processing center and a plurality of deicing equipment, and is characterized in that: The method comprises the following steps: Using an image acquisition device to acquire in real time an infrared image of the transmission line at the location of the deicing equipment on each transmission line, wherein the infrared image of the transmission line includes at least a first infrared image of the transmission line located in front of the deicing equipment and a second infrared image of the transmission line located behind the deicing equipment; A convolutional neural network model for judging the deicing effect of a transmission line is obtained by training the first infrared image and the second infrared image of the historical transmission line using a data processing center; The infrared image of the transmission line obtained by the image acquisition device is input into the trained convolutional neural network model to obtain the deicing assessment result and residual ice coverage thickness of the corresponding transmission line position; Control the deicing operation of the deicing equipment at the current transmission line location based on the deicing assessment results: Obtain the residual ice coverage thickness at the current transmission line location and the deicing thickness of the deicing equipment in the last operation as the deicing thickness of the deicing equipment in a single operation; The number of times the de-icing equipment operates at the current transmission line location is calculated based on the de-icing thickness and residual ice coverage thickness of the de-icing equipment in a single operation: ; in N The number of operations for de-icing equipment; is the rounding up operation function; T is the thickness of residual ice cover; The de-icing thickness of the de-icing equipment in a single operation; Based on the number of operations of the deicing equipment at the current transmission line position, the deicing equipment is controlled to perform deicing operations back and forth at the current transmission line position.

2. The deicing effect evaluation and control method according to claim 1, characterized in that: A single transmission line is divided into several transmission line units according to its length. The image acquisition device acquires the transmission line infrared images of the transmission line units in batches, and controls the deicing operation of the deicing equipment within the current transmission line unit based on the transmission line infrared images of the single transmission line unit.

3. The deicing effect evaluation and control method according to claim 1, characterized in that: When the deicing equipment is controlled to perform deicing operations back and forth at the current transmission line location based on the number of operations of the deicing equipment at the current transmission line location, the image acquisition device simultaneously acquires a second infrared image of the current transmission line location and determines the temperature of the transmission line in the second infrared image: When the temperature of the transmission line in the second infrared image is higher than or equal to the first preset threshold value, it is judged that the residual ice on the transmission line has been cleared, and the number of operations at the current transmission line position is reset to zero; when the temperature of the transmission line in the second infrared image is lower than the first preset threshold value, it is judged that there is still residual ice on the transmission line, and the de-icing equipment continues the de-icing operation according to the number of operations at the current transmission line position.

4. The deicing effect evaluation and control method according to claim 3, characterized in that: The deicing equipment is at least provided with an operating speed and a traveling speed. When the image acquisition device acquires the infrared image of the transmission line at the location of the deicing equipment on each transmission line, the first infrared image is analyzed: When the temperature of the transmission line in the first infrared image is higher than or equal to the first preset threshold value, it is judged that the residual ice on the transmission line in front of the deicing equipment has been cleared or is not covered with ice, and the deicing equipment moves at the traveling speed; when the temperature of the transmission line in the first infrared image is lower than the first preset threshold value, it is judged that there is an ice layer on the transmission line in front of the deicing equipment, and the deicing equipment moves at the operating speed.

5. The deicing effect evaluation and control method according to claim 1, characterized in that: When the residual ice coverage thickness at the corresponding transmission line location is obtained, the image acquisition device analyzes the second infrared image using the conversion relationship between the calibrated grayscale value and the temperature to obtain the boundary between the line part and the ice layer part in the infrared image; and calculates the first residual ice coverage thickness based on the number of pixels in the ice layer part and the number of pixels in the line part.

6. The deicing effect evaluation and control method according to claim 5, characterized in that: When the residual ice cover thickness at the corresponding transmission line location is obtained, the line temperature and the ice surface temperature at the corresponding transmission line location are used, and the relationship model between the ice layer thickness and the temperature difference established based on the heat conduction theory is combined to estimate the second residual ice cover thickness at the corresponding transmission line location.

7. The deicing effect evaluation and control method according to claim 6, characterized in that: The first residual ice coverage thickness and the second residual ice coverage thickness at the same location of the transmission line are analyzed: When the difference between the first residual ice cover thickness and the second residual ice cover thickness is less than or equal to the second preset threshold, taking the average value of the first residual ice cover thickness and the second residual ice cover thickness as the residual ice cover thickness at the current transmission line location; When the difference between the first residual ice cover thickness and the second residual ice cover thickness is greater than a second preset threshold, the maximum value of the first residual ice cover thickness and the second residual ice cover thickness is taken as the residual ice cover thickness at the current transmission line location.

8. The deicing effect evaluation and control method according to claim 1, characterized in that: The image acquisition device uses a drone with an infrared camera, and the image acquisition device acquires the transmission line infrared image of each transmission line, and sends the transmission line infrared image to a data processing center; the data processing center analyzes and processes the transmission line infrared image to obtain the deicing operation cycle number of the deicing equipment at the current transmission line position and sends it to the corresponding deicing equipment; The deicing equipment performs deicing operations on the current transmission line location based on the number of deicing operation cycles.

9. The deicing effect evaluation and control method according to claim 1, characterized in that: When the deicing equipment performs deicing operation at the current transmission line position, the data processing center analyzes the first infrared image and the second infrared image of the front and rear positions of the deicing equipment in real time: When there is ice on the transmission line in the first infrared image, and the thickness of the ice does not change in the first infrared image and the second infrared image, or the change in the thickness of the ice is lower than a third preset threshold, it is determined that the de-icing equipment is abnormal; When there is an ice layer on the transmission line in the first infrared image, and the change in ice layer thickness between the first infrared image and the second infrared image is greater than or equal to a third preset threshold, it is determined that the de-icing equipment is operating normally.

10. A deicing effect evaluation control device based on infrared image analysis, which is used to control the movement of deicing equipment in a power transmission line deicing operation device, characterized in that: The device comprises: An image acquisition module, used for acquiring, in real time, an infrared image of a power transmission line at a location where a deicing device is located on the power transmission line using an image acquisition device, wherein the infrared image of the power transmission line includes at least a first infrared image of the power transmission line located in front of the deicing device and a second infrared image of the power transmission line located behind the deicing device; A model training module, used for obtaining a convolutional neural network model for judging the deicing effect of a transmission line by using a first infrared image and a second infrared image of a historical transmission line trained by a data processing center; An image analysis module is used to input the infrared image of the power transmission line obtained by the image acquisition device into the trained convolutional neural network model to obtain a deicing assessment result including the residual ice coverage thickness of the corresponding transmission line; The operation control module is used to control the deicing operation of the deicing equipment on the current transmission line based on the deicing assessment results: The residual ice coverage thickness is obtained according to the deicing assessment result, and the deicing thickness of the current deicing equipment in the last operation is obtained as the deicing thickness of the deicing equipment in a single operation; The number of times the de-icing equipment operates at the current transmission line location is calculated based on the de-icing thickness and residual ice coverage thickness of the de-icing equipment in a single operation: ; in N The number of operations for de-icing equipment; is the rounding up operation function; T is the thickness of residual ice cover; The de-icing thickness of the de-icing equipment in a single operation; Based on the number of operations of the deicing equipment at the current transmission line position, the deicing equipment is controlled to perform deicing operations back and forth at the current transmission line position.

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