CN110472683B - Method for determining initial point of transmission line channel visual alarm area division - Google Patents
Method for determining initial point of transmission line channel visual alarm area division Download PDFInfo
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Abstract
The method for determining the division of the initial point comprises the steps of dividing a certain number of longitude and latitude grids based on the maximum and minimum longitude and latitude coordinates of an alarm data set, obtaining candidate data in each grid, and obtaining an initial point set after screening. The alarm regions finally obtained based on the initial point set are reasonably distributed, the regions are stable and do not drift, and technical support is provided for identification of alarm high-incidence regions. When the method is used for identifying the visible alarm high-emission area of the power transmission line channel, a reasonable initial point set can be provided for division and clustering, so that the finally obtained alarm area is reasonably distributed, the area is stable and does not drift, technical support is provided for identifying the alarm high-emission area, and the most reasonable and reliable alarm high-emission area is found, so that the power transmission line maintainers can carry out manual deployment in advance, the stable operation of the power transmission line is ensured, the labor cost is saved, and the working efficiency is improved.
Description
Technical Field
The invention relates to a method for determining the division initial point of a visual alarm area of a power transmission line channel, belonging to the technical field of intelligent maintenance of power transmission lines.
Background
Along with the upgrading of the maintenance technology of the power transmission line, the visual remote inspection of the power transmission line channel is widely applied, and the automatic identification of visual information and the marking of alarming objects appearing in images, such as tower cranes, mountain fires, excavators and the like, are already realized at present. The identification of the alarm high-incidence area based on the alarm identification result is beneficial to improving the working efficiency of the power transmission line maintainers, and because the alarm data are provided with longitude and latitude coordinate information and are mutually independent, the cluster analysis is an effective means for realizing the technical goal.
There are many existing cluster analysis algorithms, and typical ones include the following:
dividing and clustering: given a set of N objects, the partitioning method constructs K partitions of data, where each partition represents a cluster (class);
hierarchical clustering: methods divided into coacervation and fragmentation, take coacervation as an example: starting each object to be a cluster independently, combining similar objects from bottom to top successively until an iteration stop condition is met, and the splitting method is opposite in process;
density-based clustering: as long as the density (number of objects or data points) in the "neighborhood" exceeds a certain threshold, the growth of a given cluster continues.
The alarm data is provided with the longitude and latitude coordinate information and the alarm times, and the division clustering in the clustering method is the best method for realizing the identification of the alarm high-incidence area. For a cluster K to be generated, the partitional clustering randomly selects K objects as initial points, and clustering results are sensitive to the initial points. And identifying the application scene of the alarm high-incidence area, wherein the result of the division clustering generated by different initial point sets of the division clustering has certain difference, so that the alarm high-incidence area has dense and drifting conditions.
In summary, how to provide a reasonable and reliable initial point set to provide technical support for identifying an alarm high-incidence region, so that the calculation result is stable, the distribution is reasonable, and the obtained alarm high-incidence region is stable and does not drift is one of the problems to be solved by those skilled in the art.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to provide a method for determining the initial point of the visualized alarm region division of the power transmission line channel. Particularly, when the visible alarm high-incidence areas of the power transmission line channel are identified, alarm data are divided into a specified number of areas according to longitude and latitude coordinates based on a division clustering method, and an initial point set is provided for division clustering.
Summary of the invention:
the method for determining the division of the initial point comprises the steps of dividing a certain number of longitude and latitude grids based on the maximum and minimum longitude and latitude coordinates of an alarm data set, obtaining candidate data in each grid, and obtaining an initial point set after screening. The alarm regions finally obtained based on the initial point set are reasonably distributed, the regions are stable and do not drift, and technical support is provided for identification of alarm high-incidence regions.
The technical scheme of the invention is as follows:
a method for determining the initial point of the visual alarm area division of a transmission line channel is characterized by comprising the following steps:
a. dividing a longitude and latitude grid based on the longitude and latitude coordinates of the visible alarm data of the power transmission line channel and the required area number K; the K is specified, the partition clustering takes a K-means algorithm as a typical representation, and the number K of the areas corresponds to the partition clustering algorithm and is a clustering cluster number K;
b. sequentially traversing each grid, obtaining candidate data in each grid, sequencing the candidate data according to the alarm times, and taking the first K pieces as initial points;
the candidate data refers to the screened alarm data with longitude and latitude coordinates and alarm quantity.
Preferably, according to the invention, each grid is traversed in turn starting from the grid with the smallest longitude and latitude of the grid of longitudes and latitudes. The trellis is traversed in this order and its sequential code implementation is very friendly.
The traversal can be started from other four vertices or from the central point by clockwise or counterclockwise rotation, but has no great influence on the result. No matter how far the traversal is performed, as long as no omission exists, the candidate data are sorted according to the alarm times, the first K pieces are taken, the obtained results are the same, and the time complexity is o (n).
Preferably, according to the present invention, the step a comprises the following detailed steps:
a 1: respectively counting the maximum longitude lng in the alarm data coordinate set based on the alarm data in the step amaxMinimum longitude lngminMaximum latitude latmaxMinimum latitude latmin；
a 2: calculating the difference lng in the longitude direction based on the step a1diff＝lngmax-lngminCalculating the difference lat in the latitude directiondiff＝latmax-latmin；
a 3: and b, calculating the number N of rows and columns of the latitude and longitude grids based on the number K of the alarm areas in the step a:
if the square root of K is an integer, that is, sqrt (K) is an integer, then N ═ sqrt (K);
if the square root of K is not an integer, rounding it, i.e., INT (sqrt (K)), setting N ═ INT (sqrt (K)) + 1;
a 4: calculating the grid division step length of latitude and longitude:
longitude step length lngstep＝lngdiffN, latitude step size latstep＝latdiff/N；
a 5: calculating the longitude and latitude required by the longitude and latitude grid:
calculating N-1 longitude lines in the longitude direction, combining the longitude lines corresponding to the initial maximum and minimum longitude to obtain N +1 longitude lines, wherein the longitude line values are { ng }min,lngmin+lngstep,lngmin+2*lngstep,lngmin+3*lngstep,…,lngmin+(N-1)*lngstep,lngmaxGet N +1 weft threads in the same latitude direction, the weft thread values are in turn { lat }min,latmin+latstep,latmin+2*latstep,latmin+3*latstep,…,latmin+(N-1)*latstep,latmax}；
a 6: and dividing a longitude and latitude grid comprising N regions based on the longitude and latitude lines obtained in the step a 5.
Preferably, according to the present invention, the step b comprises the following detailed steps:
b 1: b, sequentially traversing and searching based on the longitude and latitude grids obtained in the step a until the traversal is completed;
b 2: based on the traversal order of b1, candidate data are found, and the initial candidate data number K is recordedinit＝0：
If 1 or more pieces of alarm data exist in a certain grid, namely the longitude and latitude coordinates of 1 or more pieces of alarm data fall in the grid, recording the longitude and latitude coordinates of the alarm data with the most alarm times in the alarm data in the grid and the alarm times, and counting the number K of the candidate datainitAdding 1;
if the grid has no alarm data, skipping the current grid and continuing to search in the next grid according to the sequence of the step b 1;
b 3: determining the initial set of points includes:
based on the candidate data finding method of step b2, after the trellis traversal is completed,
if K is satisfiedinitStopping searching when the K is more than or equal to K, and recording the KinitReturning the strip data;
if K is found after traversing all gridsinik<K, increasing N in the step a4 by 1, and repeating a4, a5, a6, b1, b2 and b3 until K is satisfied when a grid traversal is performed after a certain divisioninit≥K；
b 4: based on K obtained in step b3initAnd sorting the candidate data according to the alarm times, and taking the first K candidate data with the most alarm times as an initial point set.
Preferably, in step b1, the traversal is from the grid with the smallest longitude and latitude, i.e. including (lng)min,latmin) And sequentially and incrementally searching the grids of the coordinates in the longitude direction, increasing the latitude value after the searching is finished, searching in the longitude direction again until the traversing is finished, and traversing the initial grids and the sequence as shown in the attached figure 2.
Preferably, in the step a4, the step length refers to performing an approximation operation by taking longitude and latitude as a plane coordinate. Because the calculation amount based on the spherical surface is large, and the calculation error based on the plane coordinate is in an acceptable range.
Preferably, in the step a5, the longitude and the latitude refer to those obtained by regarding the longitude and the latitude as plane coordinates to perform an approximation operation.
Technical term interpretation:
the SQRT (K) in step a3 is the square root operation performed on K.
INT (SQRT (K)) in step a3 means that integer calculation is performed on SQRT (K) and fractional parts are discarded.
Compared with the prior art, the invention has the following advantages and beneficial effects:
(1) the invention carries out division clustering identification on the alarm high-incidence area to determine the initial point set, and the calculated alarm high-incidence area is stable and does not drift.
(2) The initial points determined by the invention are uniformly distributed and have reasonable values, and reasonable initial points are provided for dividing and clustering, so that the finally obtained alarm areas are reasonably distributed.
(3) The invention calculates by taking the longitude and latitude coordinates as the plane coordinates, thereby improving the calculation efficiency and ensuring that the error is within an acceptable range.
Drawings
FIG. 1 is a schematic flow chart of a model of the determination method of the present invention;
FIG. 2 is a schematic diagram of the traversal start grid and sequence of the latitude and longitude grid of the present invention;
FIG. 3 is a comparison graph of clustering results based on a selected initial point set and a random initial point set according to an embodiment of the present invention.
Detailed Description
The present invention is further illustrated by, but not limited to, the following examples.
As shown in fig. 1.
Example (b):
collecting visual image alarm data of a certain power transmission line, and preprocessing the visual image alarm data to obtain 8794 pieces of alarm data.
Each piece of alarm data includes: the longitude of a certain point alarm, the latitude of the certain point alarm and the number of times of the certain point alarm are required to be divided and clustered, the number K of divided areas is required to be 275, namely, data is divided into 275 clusters, and 275 reasonable initial points are required to be determined in order to ensure that clustering results are distributed reasonably, stably and do not drift. The K value is determined by human selection or calculation according to other models, and is not the technical scheme of the invention.
The following is a presentation of a portion of the alarm data of the above 8794 pieces of alarm data:
the embodiment describes a method for determining an initial point for dividing a visualized alarm area of a power transmission line channel, which includes the following steps:
a. dividing a longitude and latitude grid based on the longitude and latitude coordinates of the visible alarm data of the power transmission line channel and the required area number K; the K is specified, the partition clustering takes a K-means algorithm as a typical representation, and the number K of the areas corresponds to the partition clustering algorithm and is a clustering cluster number K;
the step a comprises the following detailed steps:
a 1: respectively counting the maximum longitude lng in the alarm data coordinate set based on the alarm data in the step amaxMinimum longitude lngminMaximum latitude latmaxMinimum latitude latmin(ii) a Maximum longitude lng thereinmax121.74595 minimum longitude lngmin115.33386 maximum latitude latmax38.00827 minimum latitude latmin＝34.67971；
a 2: calculating the difference lng in the longitude direction based on the step a1diff＝lngmax-lngminCalculating the difference lat in the latitude directiondiff＝latmax-latmin(ii) a Wherein a difference lng in the longitudinal direction is calculateddiff＝lngmax-lngminThe difference lat in the latitudinal direction is calculated as 6.41209diff＝latmax-latmin＝3.32856；
a 3: and b, calculating the number N of rows and columns of the latitude and longitude grids based on the number K of the alarm areas in the step a:
if the square root of K is an integer, that is, sqrt (K) is an integer, then N ═ sqrt (K);
if the square root of K is not an integer, rounding it, i.e., INT (sqrt (K)), setting N ═ INT (sqrt (K)) + 1;
based on 275 initial points required by conditions, calculating the number N of rows and columns of the longitude and latitude grid, wherein the number N is INT (SQRT (275)) +1 is 17;
a 4: calculating the grid division step length of latitude and longitude:
longitude step length lngstep＝lngdiffN, latitude step size latstep＝latdiff/N；
Wherein, longitude step length lngstep＝lngdiffN ≈ 0.37718, latitude step latstep＝latdiff/N≈0.19580；
The step length refers to carrying out approximation operation by taking longitude and latitude as a plane coordinate;
a 5: calculating the longitude and latitude required by the longitude and latitude grid:
calculating N-1 longitude lines in the longitude direction, combining the longitude lines corresponding to the initial maximum and minimum longitude to obtain N +1 longitude lines, wherein the longitude line values are { ng }min,lngmin+lngstep,lngmin+2*lngstep,lngmin+3*lngstep,…,lngmin+(N-1)*
lngstep,lngmaxGet N +1 weft threads in the same latitude direction, the weft thread values are in turn { lat }min,latmin+latstep,latmin+2*latstep,latmin+3*latstep,…,latmin+(N-1)*latstep,latmax}; the longitude and the latitude are regarded as plane coordinates to carry out approximation operation;
calculating the longitude and latitude required by the longitude and latitude grid, calculating 16 longitude lines in the longitude direction, combining the initial maximum and minimum longitude to obtain 18 longitude lines, wherein the longitude values are sequentially {115.33386,115.71104,116.08822,116.46540,116.84258,117.21976,117.59694,117.97412,118.35130,118.72848,119.10566,119.48284,119.86002,120.23720,120.61438,120.99156,121.36874,121.74595}, the latitude directions are the same to obtain 18 latitude lines, and the latitude values are sequentially {34.67971,34.87551,35.07131,35.26711,35.46291,35.65871,35.85451,36.05031,36.24611,36.44191,36.63771,36.83351,37.02931,37.22511,37.42091,37.61671,37.81251 and 38.00827 };
a 6: dividing a longitude and latitude grid containing N x N areas based on the longitude and latitude lines obtained in the step a5, namely, dividing 289 grids.
b. Sequentially traversing each grid, obtaining candidate data in each grid, sequencing the candidate data according to the alarm times, and taking the first K pieces as initial points;
the candidate data refers to the screened alarm data with longitude and latitude coordinates and alarm quantity.
Sequentially traversing each grid from the grid with the minimum longitude and latitude in the longitude and latitude grids:
wherein, the number K of candidate data is recordedinitWhen the candidate data is searched for from the grid with the minimum latitude and longitude { (115.33386,34.67971), (115.33386,34.87551), (115.71104,34.87551), (115.71104,34.67971) }, no data is judged to fall in the range, the search is continued on the next grid, namely { (115.71104,34.67971), (115.71104,34.87551), (116.08822,34.87551), (116.08822,34.67971) }, two pieces of data are arranged in the grid, the alarm times are respectively 7 and 2, the coordinate of the data with the alarm time of 7 and the alarm time are recorded, the recording format is (115.95842,34.82965,7), and K is recordedinitAs for 1, continuing other grid traversals, it should be specifically pointed out that after traversing { (121.36874,34.67971), (121.36874,34.87551), (121.74595,34.87551), (121.74595,34.67971) }, starting from { (115.71104,34.87551), (115.71104,35.07131), (116.08822,35.07131), (116.0882234.87551) } to continue traversals, that is, traversing the longitude direction first, increasing the latitude value after completing, and continuing to traverse until all traversals are completed;
it is further noted that the above traversal order is only one way of optimizing the present invention, but does not exclude the use of other types of traversal, for example, it is possible to start from the other four vertices, or to start from the center point with clockwise or counterclockwise turns, but without much impact on the result. No matter how far the traversal is performed, as long as no omission exists, the candidate data are sorted according to the alarm times, the first K pieces are taken, the obtained results are the same, and the time complexity is o (n).
The step b comprises the following detailed steps:
b 1: b, sequentially traversing and searching based on the longitude and latitude grids obtained in the step a until the traversal is completed; wherein the traversal is from the grid with the smallest longitude and latitude, i.e. (lng)min,latmin) The grids of the coordinates are sequentially and incrementally searched in the longitude direction, the latitude value is increased after the searching is finished, the grids are searched in the longitude direction again until the traversing is finished, and the traversing initial grids and the sequence are shown in the attached figure 2;
b 2: based on the traversal order of b1, candidate data are found, and the initial candidate data number K is recordedinit＝0：
If 1 or more pieces of alarm data exist in a certain grid, namely the longitude and latitude coordinates of 1 or more pieces of alarm data fall in the grid, recording the longitude and latitude coordinates of the alarm data with the most alarm times in the alarm data in the grid and the alarm times, and counting the number K of the candidate datainitAdding 1;
if the grid has no alarm data, skipping the current grid and continuing to search in the next grid according to the sequence of the step b 1;
b 3: determining the initial set of points includes:
based on the candidate data finding method of step b2, after the trellis traversal is completed,
if K is satisfiedinitStopping searching when the K is more than or equal to K, and recording the KinitReturning the strip data;
if K is found after traversing all gridsinik<K, increasing N in the step a4 by 1, and repeating a4, a5, a6, b1, b2 and b3 until K is satisfied when a grid traversal is performed after a certain divisioninitK is more than or equal to K, namely:
after the grid traversal is completed, Kinit＝167<275 adding 1 to the value N in step c, i.e. N18 + 119, repeating b 1-b 3, and K26, respectivelyinit＝296>275, namely 296 pieces of candidate data are obtained;
the method specifically comprises the following steps:
N＝17，Kinit＝167；
N＝18，Kinit＝175；
N＝19，Kinit＝186；
N＝20，Kinit＝199；
N＝21，Kinit＝217；
N＝22，Kinit＝230；
N＝23，Kinit＝248；
N＝24，Kinit＝266；
N＝25，Kinit＝274；
N＝26，Kinit＝296；
b 4: based on K obtained in step b3initSorting the candidate data according to the alarm times, and taking the first K candidate data with the most alarm times as an initial point set;
the overall iteration results are shown above: based on the 296 candidate data obtained in the step b3, sorting the 296 candidate data according to the alarm times, and taking the top 275 candidate data with the most alarm times as an initial point set to select the following columns:
{(117.68882,37.84073,2422),(118.6858,36.65259,1765),(117.41418,37.52693,1302),(118.0214,37.17649,1144),(118.4065,35.3196,1140),(118.35224,37.27825,955),(119.396,36.73582,934),……,(118.77481,35.03757,11),(117.33595,35.95528,11),(118.57061,37.92901,11)}。
the comparative experiment shows that:
in the embodiments, the latitude and longitude grids formed based on the alarm data are used to find the data with the most alarm times in each grid as the candidate data, and finally the initial point set is obtained based on the candidate data.
The initial point set calculated based on this embodiment and the existing random initial point set adopted are respectively applied to the classified clustering, and the comparison of the calculation results is performed for 5 times, and part of comparison data is shown in fig. 3, so that it can be seen that the clustering results of the random initial point set are different each time, and the distribution randomness of the coordinate points at the centers of the regions is very high, but the results calculated based on the method of this embodiment are stable, do not drift, and are reasonably distributed.
In summary, the initial point set obtained by the invention has reasonable coordinate distribution and heavy data weight, compared with a random initial point, the calculation time is increased by only 84 milliseconds, and based on the initial point set, the result obtained by dividing and clustering is stable and does not drift, so that a powerful technical support is provided for automatic identification of the alarm high-incidence area, and the matching degree between the obtained alarm high-incidence area and the real maintenance condition is extremely high after the confirmation of maintenance personnel.
Claims (7)
1. A method for determining the initial point of the visual alarm area division of a transmission line channel is characterized by comprising the following steps:
a. dividing a longitude and latitude grid based on the longitude and latitude coordinates of the visible alarm data of the power transmission line channel and the required area number K; the K is specified, the partition clustering takes a K-means algorithm as a typical representation, and the number K of the areas corresponds to the partition clustering algorithm and is a clustering cluster number K;
b. sequentially traversing each grid, obtaining candidate data in each grid, sequencing the candidate data according to the alarm times, and taking the first K pieces as initial points;
the candidate data refers to the screened alarm data with longitude and latitude coordinates and alarm quantity.
2. The method as claimed in claim 1, wherein each grid is traversed sequentially starting from the grid with the smallest longitude and latitude in the longitude and latitude grid.
3. The method for determining the initial point of the visual alarm region division of the power transmission line channel according to claim 1, wherein the step a comprises the following detailed steps:
a 1: respectively counting the maximum longitude lng in the alarm data coordinate set based on the alarm data in the step amaxMinimum longitude lngminMaximum latitude latmaxMinimum latitude latmin；
a 2: calculating the difference lng in the longitude direction based on the step a1diff＝lngmax-lngminCalculating the difference lat in the latitude directiondiff＝latmax-latmin；
a 3: and b, calculating the number N of rows and columns of the latitude and longitude grids based on the number K of the alarm areas in the step a:
if the square root of K is an integer, that is, sqrt (K) is an integer, then N ═ sqrt (K);
if the square root of K is not an integer, rounding it, i.e., INT (sqrt (K)), setting N ═ INT (sqrt (K)) + 1;
a 4: calculating the grid division step length of latitude and longitude:
longitude step length lngstep＝lngdiffN, latitude step size latstep＝latdiff/N；
a 5: calculating the longitude and latitude required by the longitude and latitude grid:
calculating N-1 longitude lines in the longitude direction, combining the longitude lines corresponding to the initial maximum and minimum longitude to obtain N +1 longitude lines, wherein the longitude line values are { ng }min,lngmin+lngstep,lngmin+2*lngstep,lngmin+3*lngstep,…,lngmin+(N-1)*
lngstep,lngmaxGet N +1 weft threads in the same latitude direction, the weft thread values are in turn { lat }min,latmin+latstep,latmin+2*latstep,latmin+3*latstep,…,latmin+(N-1)*latstep,latmax}；
a 6: and dividing a longitude and latitude grid comprising N regions based on the longitude and latitude lines obtained in the step a 5.
4. The method for determining the initial point of the visual alarm area division of the power transmission line channel according to claim 1, wherein the step b comprises the following detailed steps:
b 1: b, sequentially traversing and searching based on the longitude and latitude grids obtained in the step a until the traversal is completed;
b 2: based on the traversal order of b1, candidate data are found, and the initial candidate data number K is recordedinit＝0：
If 1 or more pieces of alarm data exist in a certain grid, namely the longitude and latitude coordinates of 1 or more pieces of alarm data fall in the grid, recording the longitude and latitude coordinates of the alarm data with the most alarm times in the alarm data in the grid and the alarm times, and counting the number K of the candidate datainitAdding 1;
if the grid has no alarm data, skipping the current grid and continuing to search in the next grid according to the sequence of the step b 1;
b 3: determining the initial set of points includes:
based on the candidate data finding method of step b2, after the trellis traversal is completed,
if K is satisfiedinitStopping searching when the K is more than or equal to K, and recording the KinitReturning the strip data;
if K is found after traversing all gridsinik<K, increasing N in the step a4 by 1, and repeating a4, a5, a6, b1, b2 and b3 until K is satisfied when a grid traversal is performed after a certain divisioninit≥K；
b 4: based on K obtained in step b3initAnd sorting the candidate data according to the alarm times, and taking the first K candidate data with the most alarm times as an initial point set.
5. The method as claimed in claim 4, wherein in step b1, the traversal is from a grid with the smallest longitude and latitude, i.e. including (lng)min,latmin) And sequentially carrying out incremental search according to the longitude direction on the grid of the coordinate, increasing the latitude value after the search is finished, and searching according to the longitude direction again until the traversal is finished.
6. The method for determining the initial point of dividing the visualized alarm area of the power transmission line channel as claimed in claim 3, wherein said step length in step a4 is performed by taking longitude and latitude as a plane coordinate for approximation.
7. The method for determining the initial point of the electric transmission line channel visual alarm area division according to claim 3, wherein the longitude and the latitude of the step a5 are determined as plane coordinates to perform approximation operation.
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| CN105512803B (en) * | 2015-11-26 | 2019-12-10 | 国网北京市电力公司 | Processing method and processing device of power data |
| CN106447104A (en) * | 2016-09-27 | 2017-02-22 | 贵州电网有限责任公司输电运行检修分公司 | Power transmission line operation and maintenance area grid dividing and coding method |
| CN108306756B (en) * | 2017-12-21 | 2021-03-30 | 国网北京市电力公司 | Holographic evaluation system based on power data network and fault positioning method thereof |
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