A power transmission line ice floe monitoring method and system, electronic device and medium

Abstract

The application provides a power transmission line floating ice monitoring method and system, and relates to the technical field of power transmission line monitoring, which realizes accurate, efficient and real-time monitoring of the floating ice condition of the power transmission line under complex environmental conditions. The method comprises the following steps: collecting a floating ice image of the power transmission line, and pre-processing the floating ice image of the power transmission line to obtain a binary image; performing edge detection on the binary image to obtain edge information of the power transmission line; calculating the stress state of the power transmission line, and obtaining the thickness of the floating ice based on the stress state and the edge information; and performing early warning judgment and floating ice removal treatment on the power transmission line based on the thickness of the floating ice. The power transmission line floating ice monitoring system is applied to the power transmission line floating ice monitoring method.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power transmission line monitoring, and in particular to a power transmission line ice monitoring method and system, an electronic device and a medium BACKGROUND

[0002] The power transmission line is an important part of the power system, and its operating state directly affects the stability and safety of the power system. Ice is one of the important problems faced by the power transmission line, which can have a negative impact on the operation of the line and even cause line failure in severe cases. Therefore, monitoring and preventing ice on the power transmission line is an important measure to ensure the stable operation of the power system.

[0003] The existing power transmission line ice monitoring methods are mainly divided into two types: based on weighing sensors and based on image processing. The method based on weighing sensors needs to install a weight sensor on the surface of the power transmission line, and the weight change of the power transmission line is monitored to determine the ice condition, but this method needs to be regularly maintained and calibrated, which is costly and susceptible to environmental factors. The method based on image processing acquires images of the power transmission line, processes and analyzes the images, extracts the features of the ice, and thus monitors the ice on the power transmission line. This method has the advantages of high monitoring accuracy and non-contact, but requires complex processing and analysis of the images, which is computationally intensive and has poor real-time performance. SUMMARY

[0004] To solve the above technical problems, the present application provides a power transmission line ice monitoring method, system, electronic device and medium to accurately, efficiently and in real time monitor the ice condition of the power transmission line under complex environmental conditions.

[0005] The present application provides a power transmission line ice monitoring method, which comprises:

[0006] Step S1: acquiring an ice image of the power transmission line and pre-processing the ice image of the power transmission line to obtain a binary image;

[0007] Step S2: performing edge detection on the binary image to obtain edge information of the power transmission line;

[0008] Step S3: calculating the stress state of the power transmission line and obtaining the ice thickness based on the stress state and the edge information;

[0009] Step S4: performing early warning judgment and ice removal processing on the power transmission line based on the ice thickness.

[0010] Preferably, the pre-processing of the ice image of the power transmission line in step S1 to obtain a binary image comprises:

[0011] Gaussian filtering denoising is performed on the power transmission line ice image,

[0012] Binaryzation is performed on the filtered and denoised image to obtain a binary image.

[0013] Preferably, the step S2 comprises: performing edge detection on the binary image based on an adaptive weight Sobel operator edge detection method to obtain edge information of the power transmission line.

[0014] Preferably, the adaptive weight Sobel operator edge detection method comprises:

[0015] Step S2.1: constructing a 4-direction edge detection template based on an adaptive weight Sobel operator;

[0016] Step S2.2: for each of the 4-direction edge detection templates, the center pixel of the template is matched with a current pixel position in the binary image, and an adaptive weight Sobel operator row interval difference value in each template is calculated;

[0017] Step S2.3: comparing the adaptive weight Sobel operator row interval difference values in each template to obtain a maximum value, taking the detection template direction corresponding to the maximum value as the edge gradient direction of the current pixel, and taking the maximum value as the new gray scale of the current pixel.

[0018] Preferably, the step S3 comprises:

[0019] Step S3.1: establishing a three-dimensional model according to the structure parameters of the power transmission line, the structure parameters including tower type, conductor type and phase number;

[0020] Step S3.2: calculating the stress condition of the conductor according to the current environmental data, the environmental data including wind speed, wind direction, air humidity and conductor temperature;

[0021] Step S3.3: calculating the stress state of the conductor based on the three-dimensional model and the stress condition:

[0022] Step S3.4: obtaining the ice thickness according to the stress state and the edge information.

[0023] Preferably, the step S3.2 comprises:

[0024] calculating the wind load, the wind load calculation formula being: F wind = 0.5*ρ*V 2 *A*C d

[0025] wherein, F windis the wind load, p is the air density, V is the wind speed, A is the projected area of the conductor in the direction perpendicular to the airflow, C d is the air resistance coefficient;

[0026] The temperature load is calculated, and the temperature load calculation formula is: F temp = a * E * A * Delta T, wherein F temp is the temperature load, a is the thermal expansion coefficient of the conductor, E is the elastic modulus of the conductor, A is the cross-sectional area of the conductor, and Delta T is the temperature change of the conductor;

[0027] The wind load and the temperature load are added to obtain the stress of the conductor: F total = F wind +F temp .

[0028] Preferably, according to the formula:

[0029] The stress of the lowest point of the conductor of any ice thickness is obtained, and the ice thickness value of the conductor is output in real time according to the stress of the power transmission line at different ice thicknesses and the edge information, wherein the lowest point stress is delta 1 when the conductor specific load is g1, the lowest point stress is delta 2 when the conductor specific load is g2, l is the horizontal span, and E is the elastic modulus of the conductor.

[0030] Compared with the prior art, the power transmission line ice monitoring method provided by the application has the following beneficial effects: first, the power transmission line ice image is collected, and the power transmission line ice image is preprocessed to obtain a clear binary image, which provides a reliable data basis for subsequent edge detection and stress state calculation. Then, the edge information of the power transmission line is obtained by performing edge detection on the binary image, and the clear contour line is calculated, which has high detection accuracy for the image edge and improves the image edge recognition effect; finally, the stress state of the power transmission line is calculated, and the accurate ice thickness under complex environment is obtained based on the stress state and the edge information; based on the ice thickness, the power transmission line is judged and the ice is removed, which can improve the ice monitoring accuracy and reduce the calculation amount.

[0031] The embodiment of the application also provides a power transmission line ice monitoring system, which comprises:

[0032] The preprocessing module is used for collecting the power transmission line ice image and preprocessing the power transmission line ice image to obtain a binary image;

[0033] The edge information extraction module is used for performing edge detection on the binary image to obtain the edge information of the power transmission line;

[0034] A floating ice thickness calculation module calculates a stress state of the power transmission line, and obtains the floating ice thickness based on the stress state and the edge information.

[0035] A pre-warning processing module performs pre-warning judgment and floating ice removal processing on the power transmission line based on the floating ice thickness.

[0036] Compared with the prior art, the power transmission line floating ice monitoring system provided by the present application has the same beneficial effects as the power transmission line floating ice monitoring method described in the above technical solution, and will not be described here.

[0037] The present application also provides an electronic device comprising a bus, a transceiver, a memory, a processor and a computer program stored in the memory and executable on the processor, the transceiver, the memory and the processor being connected through the bus, and the computer program being executed by the processor to implement the steps of the power transmission line floating ice monitoring method described in any one of the above.

[0038] Compared with the prior art, the electronic device provided by the present application has the same beneficial effects as the power transmission line floating ice monitoring method described in the above technical solution, and will not be described here.

[0039] The present application also provides a computer readable storage medium having a computer program stored thereon, the computer program being executed by a processor to implement the steps of the power transmission line floating ice monitoring method described in any one of the above.

[0040] Compared with the prior art, the computer readable storage medium provided by the present application has the same beneficial effects as the power transmission line floating ice monitoring method described in the above technical solution, and will not be described here.

[0041] In order to make the above-mentioned objects, features and advantages of the present application more apparent and easy to understand, the following preferred embodiments are specifically described below, and the accompanying drawings are described in detail as follows. BRIEF DESCRIPTION OF DRAWINGS

[0042] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor based on these drawings.

[0043] Figure 1 A flow chart of a power transmission line floating ice monitoring method provided by an embodiment of the present application is shown;

[0044] Figure 2(a) shows a schematic diagram of a horizontal edge detection template provided by the embodiment of the present application;

[0045] Figure 2 (b) shows a schematic diagram of a vertical edge detection template provided by the embodiment of the present application;

[0046] Figure 2 (c) shows a schematic diagram of a 45-degree edge detection template provided by the embodiment of the present application;

[0047] Figure 2 (d) shows a schematic diagram of a 135-degree edge detection template provided by the embodiment of the present application;

[0048] Figure 3 Fig. 4 shows a schematic diagram of a Sobel operator horizontal edge template after calculation provided by the embodiment of the present application;

[0049] Figure 4 Fig. 5 shows a schematic diagram of a power transmission line ice image provided by the embodiment of the present application;

[0050] Figure 5 Fig. 6 shows a schematic diagram of an adaptive weight Sobel edge detection provided by the embodiment of the present application. DETAILED DESCRIPTION

[0051] In the description of the present application, it should be understood that the terms "first", "second" are only for the purpose of description, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined with "first", "second" can explicitly or implicitly include one or more of the features. In the description of the present application, the meaning of "a plurality of" is two or more, unless otherwise specifically limited.

[0052] The "plurality" mentioned in the embodiment refers to two or more. The association relationship of the associated objects is described, which means that there can be three relationships, for example, A and / or B, which can represent the following cases: A exists alone, A and B exist together, and B exists alone. The words such as "exemplary" or "for example" are used to represent examples, illustrations or descriptions, and are intended to present related concepts in a specific way, and should not be interpreted as more preferred or more advantageous than other embodiments or design schemes.

[0053] Figure 1 Fig. 1 shows a flow chart of a power transmission line ice monitoring method provided by the embodiment of the present application, as shown in the figure, the method comprises: Figure 1

[0054] Step S1: collecting a power transmission line ice image, and pre-processing the power transmission line ice image to obtain a binary image. ​

[0055] It should be noted that the high-definition camera is used to collect the ice image of the power transmission line, in addition to the high-definition camera, other suitable image collection devices can be selected according to actual needs, such as infrared sensors, laser scanners, etc. In the collection, the focal length, exposure and other parameters need to be adjusted to obtain sufficient clear image information. Since the collected image generally has noise, the image needs to be denoised. The embodiment of the application adopts Gaussian filter denoising, and the denoised image is binarized. The embodiment of the application adopts a threshold segmentation method for binarization, but other suitable binarization methods can also be selected according to actual needs. The image is converted into a black and white binary image through binarization, and the power transmission line can be clearly distinguished from the background.

[0056] Step S2: edge detection is performed on the binary image to obtain edge information of the power transmission line.

[0057] It should be noted that the step S2 includes: performing edge detection on the binary image based on an adaptive weight Sobel operator edge detection method to obtain edge information of the power transmission line.

[0058] The adaptive weight Sobel operator edge detection method is used to perform edge detection on the binary image to obtain edge information of the power transmission line, including:

[0059] Step S2.1: as shown in (a)-(d), a 4-direction edge detection template is constructed based on an adaptive weight Sobel operator, so as to Figure 2 (a) The template is shown as an example, as shown in (a), if Figure 2 (a) The template is shown as an example, as shown in (a), if Figure 3 The Sobel operator calculation result is: Wherein, is the edge data of the image, f 11 , f 12 , f 13 , f 31 , f 32 , f 33 is the pixel edge operator value in the edge detection template, and A=f 11 +f 12 +f 13 , B=f 31 +f 32 +f 33 , then can be written as: Wherein, A and B are the row pixel edge operator values in the edge detection template, and the adaptive weight Sobel operator row interval difference value is:

[0060] Step S2.2: For each of the four direction detection templates, the template center pixel is corresponded to the current pixel position in the binary image, and the adaptive weight Sobel operator row interval difference value in each template is calculated,

[0061] Step S2.3: The maximum value in the four template calculation results is compared, the maximum value of the adaptive weight Sobel operator row interval difference value in each template is obtained, the detection template direction corresponding to the maximum value is taken as the edge gradient direction of the current pixel, and the maximum value is taken as the new gray scale of the current pixel.

[0062] As Figures 4-5 shown, the contour line calculated by the adaptive weight Sobel operator is clear, the feature line has good contrast with the background, it has strong anti-interference ability, the positioning boundary is accurate and continuous, and rich image detail information is obtained.

[0063] Step S3: Calculate the stress state of the power transmission line, and obtain the ice thickness based on the stress state and the edge information.

[0064] It should be noted that the step S3 includes:

[0065] Step S3.1: A three-dimensional model is established according to the structure parameters of the power transmission line, and the structure parameters include tower type, conductor type and phase number. For example, each type of tower can be modeled as one or more three-dimensional objects, and the model of the conductor can be described by its path in the three-dimensional space. Each segment of the conductor in the model can be described by its start and end coordinates in the three-dimensional space, the radius of the conductor and other information. Through this model, the actual environment of the power transmission line can be more accurately simulated, providing a reliable basis for subsequent stress calculation.

[0066] Step S3.2: The stress of the conductor is calculated according to the current environmental data, and the environmental data includes wind speed, wind direction, air humidity and conductor temperature;

[0067] Specifically, the wind load is calculated, and the wind load calculation formula is: F wind =0.5*ρ*V 2 *A*C d Wherein, F wind is the wind load, ρ is the air density, V is the wind speed, A is the projection area of the conductor in the direction perpendicular to the airflow, and C d is the air resistance coefficient;

[0068] The temperature load is calculated, and the temperature load calculation formula is: F temp =α*E*A*ΔT, wherein F tempis the temperature load, a is the thermal expansion coefficient of the conductor, E is the elastic modulus of the conductor, A is the cross-sectional area of the conductor, and ΔT is the temperature change of the conductor;

[0069] The wind load and the temperature load are added to obtain the force condition of the conductor: F total = F wind +F temp .

[0070] Step S3.3: Calculate the stress state of the conductor based on the three-dimensional model and the force condition.

[0071] It should be noted that for the ice-floating power transmission line, the conductor stress can be calculated by the following formula:

[0072]

[0073] wherein δ is the stress, V is the wind speed, T is the temperature, P is the ice weight, q is the unit length ice weight, and A is the cross-sectional area of the conductor.

[0074] Step S3.4: Obtain the ice thickness according to the stress state and the edge information.

[0075] It should be noted that the conductor is assumed to be an ideal flexible line, and therefore, if the ice load is considered to be added gradually in n stages, the stress and deformation of the conductor should satisfy Hooke's law. When the stress of the conductor increases due to the ice, the increased stress satisfies the following formula:

[0076]

[0077] wherein Δδ represents the increased stress, L0 represents the original length of the conductor, ΔL represents the increased elongation of the conductor, and E is the elastic modulus of the conductor;

[0078] It is assumed that the ambient temperature is t, the lowest point stress of the conductor is δ1 when the specific load of the conductor is g1, and the length is L1. When the specific load of the conductor due to the ice is g2, the lowest point stress is δ2, and the length is L2. According to formula (1), we have:

[0079]

[0080] The calculation formula of the conductor length L is:

[0081] wherein l is the horizontal span, and the calculation of L2 and L1 is substituted into formula (2). It is considered that the difference between the horizontal span l and the length L of the conductor in the original state is relatively small, and therefore, l = L. After rearrangement, we have:

[0082]

[0083] The stress of the lowest point of the conductor of any ice thickness under the temperature condition can be obtained from the above formula under the temperature condition, and the ice thickness value of the conductor is output in real time according to the stress of the power transmission line under different ice thicknesses and the edge information.

[0084] Step S4: warning judgment and ice removal processing of the power transmission line based on the ice thickness.

[0085] It should be noted that whether the ice thickness reaches the preset thickness is determined, if yes, the ice position is determined according to the image, the laser heat parameters are determined according to the ice thickness, the laser generator is used to remove the ice of the power transmission line according to the ice position and the laser heat parameters until the ice thickness is lower than the preset thickness

[0086] Compared with the prior art, the power transmission line ice monitoring method provided by the embodiment of the application has the following beneficial effects:

[0087] (1) The image of the ice on the power transmission line is collected, and the image of the ice on the power transmission line is denoised by Gaussian filtering, and the denoised image is binarized to obtain a clear binary image, which provides a reliable data basis for subsequent edge detection and stress state calculation.

[0088] (2) The binary image is edge detected based on the adaptive weight Sobel operator edge detection method to obtain the edge information of the power transmission line, and the clear contour line is calculated, which has high detection accuracy for the image edge and improves the image edge recognition effect.

[0089] (3) The stress state of the power transmission line is calculated, the accurate ice thickness under complex environment is obtained based on the stress state and the edge information, the warning judgment and the ice removal processing of the power transmission line based on the ice thickness can improve the ice monitoring accuracy and reduce the calculation amount, and the ice thickness of the conductor is output in real time.

[0090] The embodiment of the application also provides a power transmission line ice monitoring system, which comprises:

[0091] The preprocessing module is used for collecting the image of the ice on the power transmission line and preprocessing the image of the ice on the power transmission line to obtain a binary image.

[0092] The edge information extraction module is used for edge detecting the binary image to obtain the edge information of the power transmission line.

[0093] The ice thickness calculation module calculates the stress state of the power transmission line, and obtains the ice thickness based on the stress state and the edge information.

[0094] The warning processing module is used for warning judgment and ice removal processing of the power transmission line based on the ice thickness.

[0095] Compared with the prior art, the power transmission line floating ice monitoring system provided by the embodiment of the present application has the same beneficial effects as the power transmission line floating ice monitoring method described above, and will not be repeated here.

[0096] In addition, the embodiment of the present application also provides an electronic device, which includes a bus, a transceiver, a memory, a processor and a computer program stored in the memory and executable on the processor, the transceiver, the memory and the processor are connected through the bus respectively, the computer program is executed by the processor to realize each process of the power transmission line floating ice monitoring method embodiment described above, and the same technical effects can be achieved, in order to avoid repetition, which will not be repeated here.

[0097] In addition, the embodiment of the present application also provides a computer readable storage medium, which stores a computer program, the computer program is executed by the processor to realize each process of the power transmission line floating ice monitoring method embodiment described above, and the same technical effects can be achieved, in order to avoid repetition, which will not be repeated here.

[0098] The above is only a specific embodiment of the present application, but the protection scope of the present application is not limited to this, any skilled person in the art can easily think of changes or alternative technical solutions within the technical range disclosed by the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for monitoring floating ice on transmission lines, characterized in that, include: Step S1: Acquire images of floating ice on the transmission line and preprocess the images to obtain a binary image; Step S2: Perform edge detection on the binary image to obtain the edge information of the transmission line; Step S2 includes: performing edge detection on the binary image based on the adaptive weighted Sobel operator edge detection method to obtain the edge information of the transmission line; The adaptive weighted Sobel operator-based edge detection method performs edge detection on the binary image to obtain edge information of the transmission line, including: Step S2.1: Construct a 4-direction edge detection template based on the adaptive weight Sobel operator; wherein, the 4-direction edge detection template is: Step S2.2: For each template in the 4-direction edge detection template, match the center pixel of the template with the current pixel position in the binary image, and calculate the adaptive weight Sobel operator row interval difference value in each template; Step S2.3: Compare the row interval difference values ​​of the adaptive weight Sobel operator in each template to obtain the maximum value, take the detection template direction corresponding to the maximum value as the edge gradient direction of the current pixel, and take the maximum value as the new gray level of the current pixel; Step S3: Calculate the stress state of the transmission line, and obtain the ice thickness based on the stress state and the edge information; Step S3 includes: Step S3.1: Establish a three-dimensional model based on the structural parameters of the transmission line, including tower type, conductor type, and number of phases; Step S3.2: Calculate the stress on the conductor based on the current environmental data, including wind speed, wind direction, air humidity, and conductor temperature; Step S3.2 includes: The formula for calculating wind load is: F wind =0.5*ρ*V 2 *A*C d Among them, F wind Where ρ is wind load, V is air density, A is wind speed, and C is the projected area of ​​the conductor perpendicular to the airflow direction. d This refers to the air drag coefficient; Calculate the temperature load using the formula: F temp = α*E*A*ΔT, where, F temp α is the temperature load, E is the thermal expansion coefficient of the conductor, A is the elastic modulus of the conductor, and ΔT is the temperature change of the conductor. Adding the wind load and temperature load together, we obtain the stress condition of the conductor: F total =F wind +F temp ; Step S3.3: Calculate the stress state of the conductor based on the three-dimensional model and the stress conditions: Step S3.4: Obtain the thickness of the floating ice based on the stress state and the edge information; Step S4: Based on the thickness of the floating ice, perform early warning judgment and floating ice removal processing on the transmission line.

2. The method for monitoring floating ice on transmission lines according to claim 1, characterized in that, Step S1 involves preprocessing the image of floating ice on the transmission line to obtain a binary image, including: Gaussian filtering was applied to the image of floating ice on the transmission line to remove noise. Binarization is performed on the filtered and denoised image to obtain a binary image.

3. The method for monitoring floating ice on transmission lines according to claim 2, characterized in that, According to the formula: The stress at the lowest point of the conductor for any ice thickness is obtained. Based on the stress of the transmission line at different ice thicknesses and edge information, the ice thickness value of the conductor is output in real time. The lowest point stress is δ1 when the conductor load is g1 and δ2 when the conductor load is g2. l is the horizontal span and E is the elastic modulus of the conductor.

4. A system for monitoring floating ice on power transmission lines, characterized in that, include: The preprocessing module is used to acquire images of floating ice on transmission lines and preprocess the images to obtain binary images. An edge information extraction module is used to perform edge detection on the binary image to obtain the edge information of the power transmission line; This method is used to perform edge detection on the binary image based on the adaptive weighted Sobel operator edge detection method. The adaptive weighted Sobel operator-based edge detection method performs edge detection on the binary image to obtain edge information of the transmission line, including: A four-directional edge detection template is constructed based on the adaptive weight Sobel operator; wherein, the four-directional edge detection template is: For each of the four-directional edge detection templates, the center pixel of the template is mapped to the current pixel position in the binary image, and the adaptive weight Sobel operator row interval difference value in each template is calculated. The maximum value is obtained by comparing the row interval difference values ​​of the adaptive weight Sobel operator in each template. The detection template direction corresponding to the maximum value is taken as the edge gradient direction of the current pixel, and the maximum value is taken as the new gray level of the current pixel. The ice thickness calculation module calculates the stress state of the transmission line and obtains the ice thickness based on the stress state and the edge information. The calculation of the stress state of the transmission line, and the determination of the ice thickness based on the stress state and the edge information, includes: A three-dimensional model is established based on the structural parameters of the transmission line, including tower type, conductor type, and number of phases. The stress condition of the conductor is calculated based on current environmental data, including wind speed, wind direction, air humidity, and conductor temperature; the stress state of the conductor is calculated based on a three-dimensional model and the stress condition; and the thickness of the floating ice is obtained based on the stress state and the edge information. The stress on the conductor is calculated based on current environmental data, including wind speed, wind direction, air humidity, and conductor temperature. The formula for calculating wind load is: F wind =0.5*ρ*V 2 *A*C d Among them, F wind Where ρ is wind load, V is air density, A is wind speed, and C is the projected area of ​​the conductor perpendicular to the airflow direction. d This refers to the air drag coefficient; Calculate the temperature load using the formula: F temp = α*E*A*ΔT, where, F temp α is the temperature load, E is the thermal expansion coefficient of the conductor, A is the elastic modulus of the conductor, and ΔT is the temperature change of the conductor. Adding the wind load and temperature load together, we obtain the stress condition of the conductor: F total =F wind +F temp ; The early warning processing module is used to make early warning judgments and remove floating ice from the transmission line based on the thickness of the floating ice.

5. An electronic device comprising a bus, a transceiver, a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the transceiver, the memory, and the processor are connected via the bus, characterized in that, When the computer program is executed by the processor, it implements the steps in the method for monitoring floating ice on transmission lines as described in any one of claims 1-3.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps in the method for monitoring floating ice on transmission lines as described in any one of claims 1-3.

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