CN111951520A - System and method for detecting icing thickness of transmission line conductor - Google Patents
System and method for detecting icing thickness of transmission line conductor Download PDFInfo
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Abstract
The invention relates to a system and a method for detecting the icing thickness of a wire of a power transmission line, wherein the method collects and uploads the image and video data of the wire of the power transmission line on site through an image collecting terminal, and an icing detection early warning system carries out the detection of the icing thickness of the wire according to the following steps: 1) preprocessing the image; 2) extracting edges in the image by adopting a Canny edge detection algorithm; 3) obtaining a sub-line segment of the edge of the wire by adopting a Hough linear detection algorithm; 4) determining the edge of each sub-line section by adopting an improved K-means algorithm; 5) fitting to obtain a complete and continuous wire edge; 6) mapping the width of the wire pixel to be an actual width based on a distance mapping model of monocular vision; 7) and comparing the current actual thickness value of the lead with the thickness value of the lead without ice coating, calculating the ice coating thickness value of the lead, and if the ice coating thickness value exceeds an ice coating thickness threshold value, early warning. The system and the method are favorable for accurately and conveniently detecting the icing condition of the wire of the power transmission line.
Description
Technical Field
The invention belongs to the technical field of transmission line detection, and particularly relates to a system and a method for detecting the icing thickness of a transmission line wire.
Background
The ice coating phenomenon of the power transmission line in the mountainous region or the high-altitude region often occurs in winter, and the phenomenon mainly depends on the conditions of the environment such as humidity, temperature, wind speed, wind direction and the like. Under the cold environment in winter, the environment humiture reaches a certain degree, and the icing phenomenon will appear in the transmission line. If the deicing measures are not taken in time, the thickness of the ice layer of the lead is gradually accumulated, when the thickness exceeds the designed anti-ice capacity, line tripping and disconnection accidents can occur, and even tower falling can be caused in severe cases, so that large-range power failure accidents are caused, and huge economic loss is caused; when the wires are iced, the insulation distance between the wires or between the wires and the ground is reduced, so that a short circuit phenomenon occurs, and the safe and stable operation of the power system is damaged. Ice disasters often occur under severe weather conditions, and high altitude and mountain regions are abundant, so that the ice disasters are difficult and risky to observe manually on site. The ice observation station can reduce observation difficulty and risk to a certain extent, but the method has certain error and needs observation personnel to go deep into an ice and snow covered area, so that the method has great potential safety hazard.
The traditional wire icing thickness detection method based on the mechanical model needs to establish a complex model, and the acquired data strictly meet the time sequence requirement and are easily influenced by environmental changes; the icing detection method based on the single machine vision algorithm has insufficient precision, and the extracted lead edge is not smooth and cannot effectively reflect the state of the lead; when the lead edge line segment attribution is classified, the precision of a simple classification or clustering algorithm is insufficient, the complex algorithm has the defect of poor timeliness, and no algorithm specially designed for lead edge classification exists; in the aspect of calculating the real thickness of the lead, the current common method is a linear mapping method, the width of the pixel of the lead is converted into the actual distance according to the proportion, and the width of the near-end lead is consistent with that of the far-end lead in the image, but the width of the near-end lead is different from that of the far-end lead due to the effect of 'near-end-to-far-end-to-small' in vision, which is inconsistent with the actual situation and has a large error.
Therefore, the problem of detecting the icing of the power transmission line still needs to be solved urgently, and the practical value is high.
Disclosure of Invention
The invention aims to provide a system and a method for detecting the icing thickness of a transmission line conductor, which are beneficial to accurately and conveniently detecting the icing condition of the transmission line conductor.
In order to achieve the purpose, the invention adopts the technical scheme that: a transmission line wire icing thickness detection system comprises an image acquisition terminal and an icing detection early warning system, wherein the image acquisition terminal comprises a camera unit, an image processing unit, a communication unit and a power supply unit, the camera unit is installed on a field tower and faces a wire erected on a transmission line in the shooting direction so as to take a picture and monitor a video of the transmission line wire in real time, the camera unit is connected with the image processing unit so as to transmit acquired images and video data to the image processing unit for processing, and the image processing unit is connected with the communication unit so as to transmit the processed images and video data to the icing detection early warning system in a wireless communication mode; the power supply unit supplies power to each unit;
the ice coating detection early warning system comprises a communication and analysis unit, a database unit, a historical data query unit, a parameter setting unit, a thickness calculation unit, a display unit and an early warning unit, wherein the communication and analysis unit is communicated with an image acquisition terminal and receives image and video data uploaded by the terminal, the database unit comprises a real-time database and a historical database and is used for storing acquired data, the historical data query unit provides historical ice coating thickness information of a circuit as required, the parameter setting unit sets lead parameters and environmental parameters to calculate the ice coating thickness of the lead, the thickness calculation unit calculates the current thickness value of the lead based on the acquired image and video data, the ice coating thickness value of the lead is calculated by comparing the thickness value with the thickness value of the lead which is not coated with ice, and the display unit is used for displaying the acquired data and the calculation result of the ice coating thickness of the lead, and the early warning unit is used for comparing the calculated icing thickness of the transmission line conductor with a designed bearing capacity threshold of the line, and if the calculated icing thickness exceeds the threshold, sending warning information to operation maintenance personnel.
Further, the power supply unit adopts the solar energy electric power storage mode to supply power, mainly includes solar cell panel, charge and discharge controller, storage battery and POE power supply module, utilizes solar energy to supply power daytime to store unnecessary electric energy in storage battery, use storage battery to supply power night.
The invention also provides a method for detecting the icing thickness of the wire of the power transmission line, which comprises the following steps of collecting and uploading image and video data of the wire of the power transmission line on site through an image collecting terminal, and detecting the icing thickness of the wire by an icing detection early-warning system according to the received image data:
1) preprocessing the image;
2) extracting edges in the image by adopting a Canny edge detection algorithm, wherein the extracted edges comprise the edges of the conducting wires and a large number of interference line segments;
3) detecting straight line segments in the image by using a Hough straight line detection algorithm to obtain sub line segments of the edge of the conducting wire;
4) clustering sub line segments of the edge of the lead by adopting an improved K-means algorithm, and determining the edge of each sub line segment;
5) fitting the obtained wire edge by adopting a least square method to obtain a complete and continuous wire edge;
6) mapping the pixel width of the conducting wire into an actual width based on a monocular vision-based distance mapping model, wherein the actual width is an actual thickness value of the current conducting wire;
7) and comparing the current actual thickness value of the wire obtained by calculation with the thickness value of the wire which is not coated with ice, calculating the thickness value of the coated ice of the wire, and if the thickness value of the coated ice of the wire exceeds the threshold value of the coated ice, carrying out early warning.
Further, in step 1, firstly, the image is gaussian filtered according to equation (1):
then, carrying out graying processing on the image according to the formula (2), and reducing the three-channel color image into a single-channel grayscale image:
Gray＝0.114B+0.587G+0.299R (2)。
further, the step 2 specifically includes the following steps:
201) calculating gradient amplitude and direction to obtain gradient edge:
calculating a gradient amplitude and a gradient angle using gradient calculation formulas as formula (3) and formula (4):
θ＝tanh-1(Gx，Gy) (4)
calculating the gradient by using a Sobel operator to obtain an edge with an excellent effect;
202) the obtained gradient edge is multiple pixel width, and a non-maximum inhibition method is adopted to retain local maximum gradient and inhibit all other gradient values, so that the edge of the multiple pixel width is thinned into single pixel width;
203) and screening the thinned edges by adopting a high-low threshold screening method to obtain all real edges in the image.
Furthermore, in step 3, Hough transformation depends on a voting mechanism, one point in the parameter space corresponds to a straight line with the original space, the number of curves passing through a certain point in the parameter space is counted, and when the number of curves passing through the point is higher than a threshold value, the curve is the desired detection target; for a straight line, in the two-dimensional plane X-Y, the equation for the straight line is described as a point-skewed equation:
y＝kx+b (6)
knowing (k, b) of the straight lines, a unique straight line on the plane is determined that satisfies the condition; (K, B) is transposed to the parameter space (K, B) as in equation (7):
B＝-Kx+y (7)
passing through a point (X) on the X-Y plane0,y0) In order to avoid the occurrence of a line having an infinite slope in the parameter space, where there are numerous points satisfying (k, b), equation (7) is rewritten into the trigonometric function form of equation (8):
ρ＝xcosθ+ysinθ (8)
setting a threshold as the number of points required by a point set to form a straight line, counting the frequency of intersection of each edge point in the image to one point under a theta-rho coordinate system, and considering that the series of points are on the same straight line when the frequency is higher than the threshold; in this way, the edges of the image edges that are straight lines are determined, which contain all the line edge sub-line segments.
Further, in the step 4, the improved K-means algorithm uses the slope of each sub-line segment and the distance from the slope to the reference line as characteristic quantities, instead of the x and y coordinates of each point for clustering, determines the direction through the slope, determines the position through the distance, then represents each sub-line segment with two parameters, and finally substitutes the two characteristic quantities into the K-means algorithm for clustering, so that the edge to which each sub-line segment belongs can be determined, and the division work of the sub-line segments is completed.
Further, in step 6, based on the distance mapping model of monocular vision, the distance from the lens to the point a to be measured is calculated by using equations (11), (12) and (13), and then the pixel width in the graph is mapped to the actual width by using equation (14), where A, B is the actual point to be measured, and a 'and B' are the projection points A, B in the image:
compared with the prior art, the invention has the following beneficial effects: the system and the method collect and upload the image and video data of the on-site transmission line wire through the image collecting terminal, then combine Canny edge detection, Hough line detection, improved K-means clustering algorithm and least square fitting algorithm in the ice coating detection early warning system, accurately identify the transmission line wire edge, realize the mapping of pixel width and actual width based on the monocular vision distance mapping model, accurately obtain the actual thickness of the detected wire, finally realize the automatic detection and early warning of ice coating through comparison, the detection is accurate, convenient and fast, the manpower and material resources are saved, and the system and the method have strong practicability and wide application prospect.
Drawings
Fig. 1 is a block diagram of a system configuration according to an embodiment of the present invention.
FIG. 2 is a block diagram of an icing detection and warning system according to an embodiment of the present invention.
Fig. 3 is a flow chart of a method implementation of an embodiment of the invention.
FIG. 4 is a schematic diagram of a parameter space in an embodiment of the present invention.
FIG. 5 is a schematic diagram of a distance mapping model based on monocular vision in an embodiment of the present invention.
FIG. 6 is a schematic diagram of a Y-direction planar model in an embodiment of the present invention.
Fig. 7 is a schematic diagram of an X-direction planar model in an embodiment of the present invention.
FIG. 8 is a diagram illustrating a distance mapping model according to an embodiment of the present invention.
FIG. 9 is an original image of a wire in an embodiment of the present invention.
FIG. 10 is an image pre-processed in an embodiment of the invention.
Fig. 11 is an image after Canny edge detection in the embodiment of the present invention.
Fig. 12 is an image after Hough line detection in the embodiment of the present invention.
FIG. 13 is an image after least squares fitting of the wire in an embodiment of the present invention.
Detailed Description
The invention is described in further detail below with reference to the figures and the embodiments.
The invention provides a system for detecting the icing thickness of a transmission line conductor, which comprises an image acquisition terminal and an icing detection early warning system, wherein the image acquisition terminal comprises a camera unit, an image processing unit, a communication unit and a power supply unit, the camera unit is arranged on a field tower, the shooting direction of the camera unit is right opposite to the conductor erected on the transmission line so as to take a picture and monitor the video of the transmission line conductor in real time, the camera unit is connected with the image processing unit so as to transmit acquired images and video data to the image processing unit for processing, and the image processing unit is connected with the communication unit so as to transmit the processed images and video data to the icing detection early warning system in a wireless communication mode; the power supply unit adopts the solar energy electric power storage mode to supply power for each unit, mainly includes solar cell panel, charge and discharge controller, storage battery and POE power supply module, utilizes solar energy to supply power daytime to store unnecessary electric energy in storage battery, use storage battery to supply power night, last power supply time is no less than 10 days.
As shown in fig. 2, the ice coating detection and early warning system comprises a communication and analysis unit, a database unit, a historical data query unit, a parameter setting unit, a thickness calculation unit, a display unit and an early warning unit, wherein the communication and analysis unit is communicated with an image acquisition terminal to receive image and video data uploaded by the terminal, the database unit comprises a real-time database and a historical database and is used for storing acquired data, the historical data query unit provides historical ice coating thickness information of a circuit as required, the parameter setting unit sets lead model parameters and environment parameters according to different transmission line lead types to select proper parameters for conducting lead ice coating thickness calculation, the thickness calculation unit calculates the thickness value of the current lead based on the acquired image and video data and compares the thickness value with the thickness value of the lead without ice coating, the method comprises the steps of calculating a wire icing thickness value, displaying acquired data and a calculation result of the wire icing thickness in the form of a numerical value, an image, a table and the like, comparing the calculated wire icing thickness of the power transmission line with a line design bearing capacity threshold value, and sending alarm information to operation maintenance personnel if the calculated wire icing thickness exceeds the threshold value.
As shown in fig. 3, the invention further provides a method for detecting the thickness of the ice coating on the transmission line conductor, wherein the image and video data of the transmission line conductor on site are collected and uploaded through the image collecting terminal, and the ice coating detection early warning system detects the thickness of the ice coating on the conductor according to the received image data by the following steps:
1) in order to remove a large amount of noise and background interference in the images returned by the field camera unit, the images are preprocessed.
First, the image is gaussian filtered according to equation (1):
the resolution of the returned image of the 200 ten thousand pixel cameras is 1920 × 1080, in order to improve the efficiency of the algorithm, the image is grayed according to the formula (2), and the three-channel color image is reduced to a single-channel grayscale image:
Gray＝0.114B+0.587G+0.299R (2)。
2) and extracting the edge of the wire of the power transmission line, wherein the edge of the image is extracted in the first step. The method adopts a Canny edge detection algorithm to extract the edges in the image, and the extracted edges comprise the edges of the conducting wires and a large number of interference line segments.
The algorithm is a multi-stage detection algorithm, and the error rate of edge detection is low. The detected edge points can be accurately located at the edge centers. Any edge in the image is marked only once, and the fine edge is finally obtained while no false edge is generated in the image. The algorithm specifically comprises the following steps:
201) calculating gradient amplitude and direction to obtain gradient edge:
the edges of the image can point in any direction, so four gradient operators in the horizontal, vertical and diagonal directions are used for calculation. Calculating a gradient amplitude and a gradient angle using gradient calculation formulas as formula (3) and formula (4):
θ＝tanh-1(Gx，Gy) (4)
calculating the gradient by using a Sobel operator to obtain an edge with an excellent effect;
202) the gradient edge is usually obtained to be many pixels wide, and the gradient map in this case does not reflect edge information well. While the edge can only have a precise spot width. Thus, the edges of multiple pixel widths are refined to a single pixel width using a non-maximum suppression method to preserve the local maximum gradient while suppressing all other gradient values.
203) And screening the thinned edges by adopting a high-low threshold screening method to obtain all real edges in the image.
Specifically, the gradient amplitude greater than the high threshold is considered to be a strong edge point, the gradient amplitude lower than the low threshold is considered to be a non-edge point, and the gradient amplitude between the two thresholds is considered to be a weak edge. And determining the property of the weak edge point by finding whether the strong edge point exists in the eight neighborhoods of the weak edge point, if so, determining the weak edge point, and otherwise, determining the weak edge point not.
3) After the edges in the image are obtained, the background interference line segments should also be removed. The field environment of the transmission line is complex and is mixed with a large amount of background interference, so that the wire needs to be extracted from the background interference. The method utilizes the linear posture of the electric transmission line conductor in the image, and adopts a Hough linear detection algorithm to detect the linear section in the image, so as to obtain the sub-line section of the conductor edge.
The Hough transformation depends on a voting mechanism, one point in the parameter space corresponds to a straight line with the original space, the quantity of curves passing a certain point in the parameter space is counted, and when the quantity of the curves passing the point is higher than a threshold value, the target to be detected is obtained. For a straight line, in the two-dimensional plane X-Y, the equation for the straight line is described as a point-skewed equation:
y＝kx+b (6)
knowing the (k, b) of the straight lines, the only straight line on the plane that satisfies this condition is determined. (K, B) is transposed to the parameter space (K, B) as in equation (7):
B＝-Kx+y (7)
passing through a point (X) on the X-Y plane0,y0) In order to avoid the occurrence of a line having an infinite slope in the parameter space, where there are numerous points satisfying (k, b), equation (7) is rewritten into the trigonometric function form of equation (8):
ρ＝xcosθ+ysinθ (8)
setting a threshold value as the number of points required by the point set to form a straight line, counting the frequency of intersection of each edge point in the image at one point under a theta-rho coordinate system, and when the frequency is higher than the threshold value, considering that the series of points are all on the same straight line. In this way, the edges of the image edges that are straight lines are determined, which contain all the line edge sub-line segments.
4) And clustering the sub-line segments of the edge of the wire by adopting an improved K-means algorithm, and determining the edge of each sub-line segment.
The obtained sub-line segments are distributed on each edge of the lead, and the attribution of each sub-line segment needs to be determined. Each wire comprises a left edge and a right edge, namely if the number of the transmission lines in the image is 2, the number of the edges is 4, and the sub-line segments of the wire need to be divided into 4 types. Since the classification category is known, the invention uses a modified K-means algorithm to classify the affiliation of conductor sub-segments.
The K-means algorithm (K-means clustering algorithm) is a partitioning algorithm based on the number of known cluster classes. The distance is used as a criterion of similarity, and the closer the two objects are, the stronger the similarity is. Algorithms are able to handle large data sets and are efficient. Its inputs are data sets and category numbers, and the clustering result is k data sets divided into k categories. The algorithm flow is as follows:
(1) giving a data set with the size of n, making O equal to l, and selecting k initial clustering centers Zj(O), j ═ 1, 2, 3.., k, O represents the cluster centers for different iteration rounds.
(2) Calculating the distance D (x) of each sample data object from the centre of aggregationi，Zj(O)), i ═ 1, 2, 3, …, and classified.
(3) Let O ═ O +1, calculate the new cluster center and the sum of squared error criterion f (objective function) value:
(4) and (3) judging: if the | f (O +1) -f (O) | < theta (f convergence) or the object has no class change, the algorithm is ended, otherwise, the O ═ O +1, and the step (2) is returned.
However, the traditional K-means algorithm is suitable for point sets distributed according to groups or clusters, the effect on the point sets distributed linearly is poor, and in order to improve the defect, the invention provides an improved K-means clustering algorithm. The traditional K-means algorithm classifies each point by distance, respectively calculates the distance from each point to the center point of each cluster or group, finds out the center point with the minimum distance, takes the group or cluster to which the center point belongs as the attribution, and continuously corrects the position of the center point in the process so as to gradually judge the point to which each point belongs. And (3) in the same way, the dimension is increased from a point to a line, a central line is taken from the image, the distance from each sub-line segment to the central line is respectively obtained, and the distance between each sub-line segment and the central line is judged by taking the distance as a criterion. However, to calculate the distance between two lines, it is necessary to ensure that the two lines are parallel, each sub-line segment is often not parallel to the central line, and the distance between the two lines is difficult to solve, so the two lines are parallel in space. And taking a central point on the central line of the image, making an auxiliary line parallel to each sub-line segment through the central point, calculating the distance from the auxiliary line to the sub-line segment parallel to the auxiliary line, and obtaining the distance between the central line and each sub-line segment by the processing mode. Compared with a straight line point-slope equation, the method has the advantages that the physical meanings of two parameters are more definite, and the use is more convenient (the edge straight line segment is the partial edge of the lead and is also called as the edge sub-line segment).
The improved K-means algorithm adopts the slope of each sub-line segment and the distance between the slope and a reference line as characteristic quantities to replace x and y coordinates of each point for clustering, determines the direction through the slope, determines the position through the distance, then represents each sub-line segment by two parameters respectively, and finally substitutes the two characteristic quantities into the K-means algorithm for clustering to determine the edge of each sub-line segment, thereby completing the division work of the sub-line segments.
5) And fitting the obtained wire edge by adopting a least square method to obtain a complete and continuous wire edge.
After obtaining each wire and the edge sub-line sections corresponding to the left and right edges of each wire, fitting the wire to obtain complete and continuous wire edges. As the result obtained by improving the K-means clustering algorithm has higher precision, each edge of the lead can be obtained by only using a simple fitting algorithm to fit the sub-line segment.
6) And mapping the pixel width of the conducting wire into an actual width based on a monocular vision-based distance mapping model, namely, the actual thickness value of the current conducting wire.
The wire thickness is calculated after the wire edge is obtained through fitting, and the wire thickness is calculated because the widths of the near end and the far end of the wire in the image are different, but the actual width values of the two values are basically consistent, and the problem cannot be solved through linear mapping, so that the method is realized by adopting a distance mapping model based on monocular vision, and the mapping model is shown in fig. 5. For the analysis calculation, the analysis is performed by decomposing the data into Y, X directions, which are shown in fig. 6 and 7.
Calculating the distance from the lens to the point A to be measured based on a monocular vision distance mapping model and equations (11), (12) and (13), and then mapping the pixel width in the graph to be actual width by adopting equation (14) in combination with the distance mapping model and the geometric knowledge of FIG. 8, wherein A, B is the actual point to be measured, A 'and B' are the projection points A, B in the image:
7) and comparing the current actual thickness value of the wire obtained by calculation with the thickness value of the wire which is not coated with ice, calculating the thickness value of the coated ice of the wire, and if the thickness value of the coated ice of the wire exceeds the threshold value of the coated ice, carrying out early warning.
And (3) calculating the icing thickness D of the lead according to the formula (15) by setting the thickness of the non-iced lead to be D1 and the current thickness of the lead to be D2:
D＝D1-D2 (15)
and setting an icing thickness threshold T as a basis for judging early warning according to the experiment and historical data. And when D exceeds the early warning value T, early warning is carried out, the state of the lead is continuously observed, deicing treatment is carried out if necessary, and if D is less than T, the system enters the next operation period.
The ability of the present invention to detect the thickness of ice coating on a wire is demonstrated in a specific embodiment below.
Example 1
1. Original wire image
There is a lot of noise in the original wire image background as shown in fig. 9.
2. Image pre-processing
Image noise is removed through image preprocessing, and meanwhile, the contrast of the foreground and background areas of the image is improved, as shown in fig. 10, so that subsequent identification is facilitated.
3. Canny edge detection
The Canny edge detection algorithm is used for extracting the edges in the image, as shown in fig. 11, a large number of interference line segments exist in the image, and the edges of the conducting wires can be completely detected.
4. Hough line detection
And detecting straight line segments in the image through a Hough straight line detection algorithm on the basis of Canny detection, and detecting a lower graph of an effect graph, wherein only the edge of a lead is in the image at the moment.
5. Least square method fitting wire
The wire edges obtained through least square fitting are made to be complete wire edges and are drawn on the original image, as shown in fig. 13, the fitted wire edges (yellow lines) can be seen to wrap the two sides of each wire well, and the algorithm effect is good.
6. Wire thickness calculation
The width of the conducting wire in the image is uniform, the pixel width values of the middle position of the conducting wire at the moment are calculated to be 17.1667 pixels and 18.0414 pixels respectively through the method, the width of the conducting wire on the left side is smaller because two conducting wires in the image are two-split conducting wires, the height of the conducting wire on the left side is 80 centimeters lower than that of the conducting wire on the right side, the pixel width value of the conducting wire on the left side is calculated to be 17.9257 pixels after the height difference is adjusted, and the width values of the conducting wires are very close to each other and.
7. Distance mapping
And mapping the pixel width into an actual width, wherein the model precision meets the requirement.
8. Icing State analysis
The calculated thickness value of the lead is close to the non-icing thickness value of the lead, and the difference value does not exceed the threshold value, so that the lead is judged to be in a non-icing state and is consistent with the actual condition.
The above are preferred embodiments of the present invention, and all changes made according to the technical scheme of the present invention that produce functional effects do not exceed the scope of the technical scheme of the present invention belong to the protection scope of the present invention.
Claims (8)
1. A wire icing thickness detection system of a power transmission line is characterized by comprising an image acquisition terminal and an icing detection early warning system, wherein the image acquisition terminal comprises a camera unit, an image processing unit, a communication unit and a power supply unit, the camera unit is installed on a field tower, the shooting direction of the camera unit is right opposite to a wire erected on the power transmission line, so that the wire of the power transmission line is shot and monitored in real time through video recording, the camera unit is connected with the image processing unit, so that acquired images and video data are transmitted to the image processing unit for processing, and the image processing unit is connected with the communication unit, so that the processed images and video data are sent to the icing detection early warning system in a wireless communication mode; the power supply unit supplies power to each unit;
the ice coating detection early warning system comprises a communication and analysis unit, a database unit, a historical data query unit, a parameter setting unit, a thickness calculation unit, a display unit and an early warning unit, wherein the communication and analysis unit is communicated with an image acquisition terminal and receives image and video data uploaded by the terminal, the database unit comprises a real-time database and a historical database and is used for storing acquired data, the historical data query unit provides historical ice coating thickness information of a circuit as required, the parameter setting unit sets lead parameters and environmental parameters to calculate the ice coating thickness of the lead, the thickness calculation unit calculates the current thickness value of the lead based on the acquired image and video data, the ice coating thickness value of the lead is calculated by comparing the thickness value with the thickness value of the lead which is not coated with ice, and the display unit is used for displaying the acquired data and the calculation result of the ice coating thickness of the lead, and the early warning unit is used for comparing the calculated icing thickness of the transmission line conductor with a designed bearing capacity threshold of the line, and if the calculated icing thickness exceeds the threshold, sending warning information to operation maintenance personnel.
2. The system of claim 1, wherein the power supply unit supplies power by using a solar power storage mode, and mainly comprises a solar cell panel, a charge-discharge controller, a storage battery pack and a POE power supply module, wherein the solar power supply module supplies power by using solar energy in the daytime, stores redundant electric energy in the storage battery pack, and supplies power by using the storage battery pack at night.
3. The method for detecting the icing thickness of the wire of the power transmission line is characterized in that an image acquisition terminal is used for acquiring and uploading image and video data of the wire of the power transmission line on site, and an icing detection early warning system carries out wire icing thickness detection according to the received image data by the following steps:
1) preprocessing the image;
2) extracting edges in the image by adopting a Canny edge detection algorithm, wherein the extracted edges comprise the edges of the conducting wires and a large number of interference line segments;
3) detecting straight line segments in the image by using a Hough straight line detection algorithm to obtain sub line segments of the edge of the conducting wire;
4) clustering sub line segments of the edge of the lead by adopting an improved K-means algorithm, and determining the edge of each sub line segment;
5) fitting the obtained wire edge by adopting a least square method to obtain a complete and continuous wire edge;
6) mapping the pixel width of the conducting wire into an actual width based on a monocular vision-based distance mapping model, wherein the actual width is an actual thickness value of the current conducting wire;
7) and comparing the current actual thickness value of the wire obtained by calculation with the thickness value of the wire which is not coated with ice, calculating the thickness value of the coated ice of the wire, and if the thickness value of the coated ice of the wire exceeds the threshold value of the coated ice, carrying out early warning.
4. The method for detecting the thickness of the ice coating on the conducting wire of the power transmission line as claimed in claim 3, wherein in the step 1, firstly, the image is subjected to Gaussian filtering according to the following formula (1):
then, carrying out graying processing on the image according to the formula (2), and reducing the three-channel color image into a single-channel grayscale image:
Gray＝0.114B+0.587G+0.299R (2)。
5. the method for detecting the thickness of the ice coating on the conducting wire of the power transmission line according to claim 3, wherein the step 2 specifically comprises the following steps:
201) calculating gradient amplitude and direction to obtain gradient edge:
calculating a gradient amplitude and a gradient angle using gradient calculation formulas as formula (3) and formula (4):
θ＝tanh-1(Gx,Gy) (4)
calculating the gradient by using a Sobel operator to obtain an edge with an excellent effect;
202) the obtained gradient edge is multiple pixel width, and a non-maximum inhibition method is adopted to retain local maximum gradient and inhibit all other gradient values, so that the edge of the multiple pixel width is thinned into single pixel width;
203) and screening the thinned edges by adopting a high-low threshold screening method to obtain all real edges in the image.
6. The method for detecting the icing thickness of the conducting wire of the power transmission line according to the claim 3, wherein in the step 3, Hough transformation depends on a voting mechanism, one point in a parameter space corresponds to a straight line with an original space, the number of curves passing a certain point in the parameter space is counted, and when the number of curves passing the point is higher than a threshold value, the required detection target is obtained; for a straight line, in the two-dimensional plane X-Y, the equation for the straight line is described as a point-skewed equation:
y＝nx+b (6)
knowing (k, b) of the straight lines, a unique straight line on the plane is determined that satisfies the condition; (K, B) is transposed to the parameter space (K, B) as in equation (7):
B＝-Kx+y (7)
passing through a point (X) on the X-Y plane0,y0) In order to avoid the occurrence of a line having an infinite slope in the parameter space, where there are numerous points satisfying (k, b), equation (7) is rewritten into the trigonometric function form of equation (8):
ρ＝x cosθ+y sinθ (8)
setting a threshold as the number of points required by a point set to form a straight line, counting the frequency of intersection of each edge point in the image to one point under a theta-rho coordinate system, and considering that the series of points are on the same straight line when the frequency is higher than the threshold; in this way, the edges of the image edges that are straight lines are determined, which contain all the line edge sub-line segments.
7. The method for detecting the thickness of the ice coated on the wire of the power transmission line according to claim 3, wherein in the step 4, the improved K-means algorithm uses the slope of each sub-line segment and the distance between the slope and the datum line as characteristic quantities to replace x and y coordinates of each point to perform clustering, determines the direction through the slope, determines the position through the distance, then represents each sub-line segment by two parameters respectively, and finally substitutes the two characteristic quantities into the K-means algorithm to perform clustering, so that the edge to which each sub-line segment belongs can be determined, and the sub-line segment is divided.
8. The method for detecting the thickness of the ice coating on the conducting wire of the power transmission line as claimed in claim 3, wherein in the step 6, the distance from the lens to the point a to be measured is calculated by using the following equations (11), (12) and (13) based on a monocular vision distance mapping model, and then the pixel width in the graph is mapped to be the actual width by using the equation (14), wherein A, B is the actual point to be measured, and A 'and B' are the projection points A, B in the image:
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