CN104462820A - Method for detecting errors of coordinates of towers of power grids - Google Patents
Method for detecting errors of coordinates of towers of power grids Download PDFInfo
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Abstract
The invention provides a method for detecting errors of coordinates of towers of power grids. The method includes steps of 1), dividing error conditions of the towers of lines into definite error types and indefinite error types which are counted up to seven sub-categories; 2), carrying interpolation vacancy filling on the coordinates of deficiency towers of the error-detected lines; 3), establishing error detection rules for the definite error types; 4), acquiring definite error towers of the error-detected lines by the aid of the error detection rules, recording error types of the towers and carrying out interpolation correction on the towers; 5), verifying error rates of the indefinite error types for the coordinates of corrected lines to obtain error probabilities of the various indefinite error types of the error-detected towers; 6), judging the coordinates of the towers, determining that the coordinates of the towers have the errors if the error probabilities of the indefinite error types of the towers of the error-detected lines are larger than threshold values set by experts, and recording the error types; 7), comprehensively judging the towers and completing error detection work on all the towers of the lines. The method has the advantages that the corresponding error probability can be obtained for each tower, and accordingly indefinite gray zones can be effectively processed; the novel error types can be summarized by the aid of the method, and accordingly the coordinates of most error towers can be ultimately detected.
Description
Technical field
The present invention relates to electrical network shaft tower coordinate measurement and correction field, be specifically related to a kind of method of electrical network shaft tower coordinate measurement.
Background technology
In order to search line fault point timely, reducing the workload of line walking, guaranteeing the reliability service of electrical network, just need to provide shaft tower coordinate more accurately.But due to various mistake and error, cause tower spotting inaccurate.Fundamental purpose checks out the shaft tower coordinate of possible errors herein, solves line fault tower spotting problem.
Electrical network shaft tower, when record longitude and latitude, can produce mistake, by analysis, mainly contain following two kinds of situations and cause error in data:
1, gps data Wrong localization
The gps coordinate of same base shaft tower, has " degree every minute and second ", " degree point " and " radix point " three kinds of form displays at GPS measuring machine.Because the gps data of " degree every minute and second ", " degree point " records inconvenience in computer, some work personnel are when logging data, " degree every minute and second ", " degree point " form are recorded as " radix point " form without formula conversion with regard to wrong, may will cause difference tens kilometers.
2, survey crew measures error
Adopt classic method to measure shaft tower gps coordinate to need to measure each base shaft tower, and require that staff must stand the center of shaft tower, but because the shaft tower radix of transmission line of electricity is many, and most of shaft tower is positioned at the traffic difficulties area such as high mountain, hills, be difficult to ensure that every survey crew can measure shaft tower gps coordinate data as requested.In addition, the gps coordinate of shaft tower to reach after radix point 5, and survey crew, also can " a small discrepancy, a thousand li of mistake " once record one digit number because of carelessness, and the gps data causing part measurement to be returned is inaccurate.
Summary of the invention
The present invention draws clearly make mistakes type and indefinite type of makeing mistakes of shaft tower by probing into, adopt the method for classification error detection, detect clearly to make mistakes from design program (rule) and a little detect with similarity and indefinitely make mistakes a little, realize the fluffing check of electrical network shaft tower coordinate.
Method comprises the following steps: to the electrical network that will detect, and first by the figure of some circuits of picture, sums up clearer and more definite make mistakes type and indefinite type of makeing mistakes; Then type design program (rule) of makeing mistakes that each class is clear and definite is judged, and revise; To indefinite vertex type of makeing mistakes, the method for similarity examination is adopted to obtain a similarity.
Solve the problems of the technologies described above, the present invention adopts following technical scheme:
S101: overhead line structures error situation is divided into clearly make mistakes type and indefinite type of makeing mistakes;
By drawing shaft tower wiring diagram, artificial participation judges to determine clear and definite make mistakes type and indefinite type of makeing mistakes generally have following several type of makeing mistakes substantially.Clear and definite type of makeing mistakes: repeat point, isolated point, shift point, fallibility flex point; Indefinite type of makeing mistakes: isolated point is made mistakes, angle is made mistakes, make mistakes apart from long, type cases of respectively makeing mistakes diagram is shown in Fig. 2,3,4,5.
S102: fill a vacancy to being carried out interpolation by error detection circuit disappearance shaft tower coordinate;
Show that the situation of disappearance shaft tower coordinate is divided into following 4 kinds through probing into: whole piece power network line disappearance, power network line intercalary delection, power network line start disappearance, power network line terminates disappearance, and suppose that the actual number of shaft tower is N, its corresponding interpolation operation is as follows:
S101-1 whole piece circuit all lacks or whole piece circuit only has the situation of a point, and the benefit value of this situation has little significance, and is inherent shortcoming, does not process.
S101-2 middle line has lacked n (n=1,2 ... N-2) point, if the last point coordinate of disappearance section is (x
1, y
1), disappearance Duan Houyi point coordinate is (x
2, y
2), then in the middle of, the coordinate of i-th missing point is:
Wherein i=1,2...n.
S101-3 circuit starts to have lacked n (n=1,2 ... N-2) point, if disappearance section after first have the point of data to be (x
1, y
1), after disappearance section, second point is (x
2, y
2), if (x
1, y
1) and (x
2, y
2) between distance and direction ratio more reasonably talk about, then the coordinate of i-th point lacked is x
i=x
1+ (x
1-x
2) * i, y
i=y
1+ (y
1-y
2) * i, wherein i=1,2...n.
S101-4 circuit latter end has lacked n (n=1,2 ... N-2) point, if disappearance section before first have the point of data to be (x
1, y
1), before disappearance section, second point is (x
2, y
2), if (x
1, y
1) and (x
2, y
2) between distance and direction ratio comparatively reasonable, then the coordinate of i-th point lacked is x
i=x
1+ (x
1-x
2) * i, y
i=y
1+ (y
1-y
2) * i, wherein i=1,2...n.
S103: set up type error detection rule of clearly makeing mistakes.
S103-1 repeats point (too similitude) debugging step.
It is (x that S103-1-1 is provided with two shaft tower coordinates
1, y
1), (x
2, y
2), first to whole piece line scanning one time, if the absolute value of the difference of current point and next point is less than 0.000001, then a next complex point flag (for array) of attaching most importance to of putting of mark is designated as 1;
S103-1-2 will indicate the point of 1, and carry out interpolation processing (on average), interpolation method processes by the method for S101.
S103-2: isolated point debugging step, Fig. 3 is shown in by isolated point schematic diagram.
S103-2-1 extracts 5 attributes (remove each two points of head and the tail, do not have attribute, think that they do not isolate) of every bar circuit interlude point.
Each point of interlude, has 5 attributes, and L1 is the distance of the distance with left side consecutive point, L2 and the right consecutive point, and L3 is and any the distance of left adjoint point of being separated by, and L4 is and any the distance of right adjoint point of being separated by, and angle 1 is the angle of left and right consecutive point.
S103-2-2 gets L1, and in L2, maximal value is L5, gets L3, and in L4, maximal value is L6.
S103-2-3 is less than 60 degree (being threshold value, self controllable system) when angle 1, and L5 is greater than 2000 meters (being threshold value, self controllable system), when L6 is greater than 2000 meters (being threshold value, self controllable system), thinks the isolated point of changing the time as clear and definite.
S103-2-4 revises isolated point for inserting intermediate value, uses the method in S101.
S103-3: drift point debugging step, Fig. 4 is shown in by shift point schematic diagram.
S103-3-1 first extracts each attribute L1 to be examined, L2.L1 is the distance of this measuring point to be checked and left adjoint point, and L2 is the distance of this measuring point to be checked and right adjoint point.
The attribute L1>3000 that S103-3-2 works as certain point to be detected (is parameters, self controllable system), L2<2000 (is parameters, self controllable system) time think that this point has been likely the starting point of shift point, the coordinate recording it is numbered mark.As Fig. 4, when detecting B point attribute, AB>3000, BC<2000, think that B point may be shift point starting point, then the coordinate of B point numbering is designated as mark.
Next S103-3-3 judges the lower some C point of B point, judges whether C point is less than 2000 (being parameters, self controllable system) to more lower distance,
If NO, return S103-3-1 to C point to continue to perform.
If yes, judge this section of shift point number, n is used for recording shift point number, and whenever judging that a point is shift point, n adds 1 more.When CD distance is less than 2000; And AD distance subtracts AC distance when being less than 30% of AC distance, thinks that C point is shift point, continue the detection of next point, repeat the detection of two conditions above, when meeting upper two conditions when difference, S103-3-1 is returned to next one point and continues to perform.
The data that S103-3-4 finally records are, a two-dimensional array, and the every a line of array has 2 values, are respectively the starting point subscript m ark of drift, the some number n of drift.The method interpolation correction shift point of above S102 is used according to this record.
S103-4: fallibility flex point debugging step, Fig. 5 is shown in by fallibility flex point schematic diagram.
S103-4-1 fallibility flex point, only appears in interlude, thinks that Origin And Destination can not be fallibility flex point, and 3 attributes of each point of record interlude, are respectively angle 1, left side bearing slope over 10 r
1, right side bearing slope over 10 r
2(obtain angle k by slope
1=arctan (r
1), k
2=arctan (r
2)).
S103-4-2 works as angle 1<60 ° (being threshold value, self controllable system), angle k
1with k
2the absolute value of difference when being less than 30 ° (being threshold value, self controllable system), judging that this point is fallibility flex point, must be that this point is made mistakes.
S103-4-3 is modified to slotting intermediate value.
S104: utilize error detection rule, draw by the shaft tower of clearly makeing mistakes of error detection circuit, record shaft tower make mistakes type go forward side by side row interpolation correct;
S105: the error rate inspection circuit coordinate after correction being carried out to indefinite type of makeing mistakes, draws the error probability of all kinds of indefinite type of makeing mistakes of tested shaft tower;
Basic the having of indefinite type of makeing mistakes: isolated point is made mistakes, angle is made mistakes, make mistakes apart from long, error rate checking procedure is as follows respectively:
S105-1: the error rate inspection that isolated point is made mistakes, Fig. 3 is shown in by isolated point schematic diagram.
S105-1-1 determines attribute
Extract each point of 5 attributes (ignoring head and the tail two points) interlude of every bar circuit interlude point, there are 5 attributes, L1 is the distance with left side consecutive point, the distance of L2 and the right consecutive point, L3 is and any the distance of left adjoint point of being separated by, L4 is and any the distance of right adjoint point of being separated by, and angle 1 is angle.In note L1, L2, maximal value is L5, and get L3, in L4, maximal value is L6.
The isolated point sample that artificial selection 10 makes mistakes, extracts typical case and to make mistakes a little corresponding attribute angle 1, L5, L6.Isolated point sample is in table 1:
Table 1. isolated point sample
| Sample | Angle 1 (degree) | L5 (rice) | L6 (rice) |
| 1 | 0.994248304 | 10150.42708 | 10145.45484 |
| 2 | 0.42215352 | 64988.6565 | 65064.4503 |
| 3 | 1.228023683 | 11161.91042 | 11335.01467 |
| 4 | 1.108053836 | 21008.28548 | 21044.94434 |
| 5 | 5.885267323 | 4703.460851 | 4786.347398 |
| 6 | 7.243553434 | 2504.933457 | 2568.213647 |
| 7 | 34.2855251 | 3449.769865 | 3060.247404 |
| 8 | 5.746662342 | 2130.46451 | 2238.03838 |
| 9 | 0.270904302 | 45621.32281 | 45722.02939 |
| 10 | 1.116956948 | 22254.44682 | 22402.92472 |
S105-1-2 data prediction, in order to avoid extremum must be disturbed, selects attribute discretization, shown in after discretize, attribute sees the following form.
Table 2. attribute discretization
The property value of measuring point to be checked is also by also pressing above-mentioned steps discretize, and the attribute representation obtaining each point is 3 dimensional vector (X
1, X
2, X
3), each sample of makeing mistakes has (an X
1i, X
2i, X
3i) (i=1,2 ... 10, be 10 samples of makeing mistakes).
S105-1-3 defines similarity formula:
Wherein through experiment discussion, find a=2 time, namely think angle isolated point judge in significance level account for 1/2, L5 and L6 respectively account for 1/4 time, error detection effect is best.Owing to there being 10 isolated point samples, then obtain 10 r
i(i=1,2...10), gets r=max (r
i) be just the similarity size of measuring point to be checked and isolated point.
The error detection of S105-1-4 similarity relates to optimization details:
A, make mistakes a little for dissimilar, different attributes can be extracted, make these belong to the difference of this kind of points of performance difference and normal point.
B, when carrying out similarity system design, can think that other attributes of some Attribute Relative are more important, as angle accounts for 2/5, other 3 attributes respectively account for 1/5, and the analog result made like this is better.
C, after finding the erroneous point of certain quasi-representative, the attribute of some erroneous point may be too abnormal, as distance is greater than 50000 meters, like this when similarity system design, impact can be caused larger.So carry out discretize to property value, can think to be just that 50000,0-500m can think to be a class as being greater than 50000, etc.
D, certain type sample are typically made mistakes and have a little been looked for 10, can compare the similar value of tested point and these 10 points, select maximum similar value as with such similar value, thus ensure the pardon that the typical fault type of choosing is made mistakes a little to this class.
The definition of e, likelihood can be considered voluntarily to optimize and how to define, and is two vectorial similaritys.
F, model can be continued to optimize, and make mistakes a little if any what do not detect, then can sum up a kind of type of makeing mistakes newly, then be detected by similarity, thus sophisticated model, reach the effect of anticipation.
S105-2: the error rate that angle is made mistakes a little is checked.Be less than 60 ° because flex point is defined as angle, other attributes are ever-changing, so when flex point similarity checks mistake, if angle is less, the probability that this point is made mistakes is larger.First draw the angle belonging to each point.
First the angle of each point is processed, when being greater than the angle of 100 °, think that it can be that flex point is made mistakes scarcely.In order to obtain an error probability, angle angle being greater than 100 ° is defined as 100 °, and its error probability is decided to be 0% like this.
The error rate that angle is made mistakes a little is:
R=(100-corner dimension)/100, wherein r ∈ [0,1]
S105-3: apart from the long error rate inspection made mistakes a little.
The distance of this point and adjacent 2 is L1, L2, gets L=max (L1, L2), to the point of L>=2000, thinks that it has an error probability, if L be greater than 7000 think that this point is necessarily made mistakes.
Apart from long error rate of makeing mistakes a little:
wherein
S106: be greater than expert by the indefinite wrong shaft tower type error probability of error detection circuit and set threshold value, just judge this shaft tower coordinate mistake, misregistration type;
S107: according to type and the indefinite type detection result of makeing mistakes of clearly makeing mistakes, comprehensive descision, completes circuit all shaft tower error detections work.
The method of comprehensive descision is: in clear and definite type error detection and indefinite type error-detecting method, as long as there is a kind of method to be judged as mistake, then comprehensive descision result be just mistake; All do not misdeem, then this shaft tower coordinate does not have mistake.During in following table, comprehensive descision one arranges, 1 representative makes mistakes, and 0 representative does not make mistakes.
Calibration method sat by the classification similarity detection of grid shaft tower that patent of the present invention proposes, compared to traditional direct method carrying out error detection according to program (rule), an error probability can be drawn to each shaft tower, instead of directly draw the certain mistake of certain shaft tower, have ignored indefinite gray area.The method can continue to optimize model in addition, when carrying out test model effect quality to sample, if find that the shaft tower coordinate of some mistake does not detect, then can sum up the feature of this kind of shaft tower coordinate, be summarized as new type of makeing mistakes, thus carry out similarity examination again, finally reach the wrong shaft tower coordinate detecting the overwhelming majority.
Accompanying drawing explanation
Fig. 1 is the schematic flow sheet of a kind of overhead power transmission line pole tower coordinate classification error-detecting method in the embodiment of the present invention;
Fig. 2 is that in the embodiment of the present invention, shaft tower is clearly made mistakes the schematic diagram of type and indefinite type of makeing mistakes;
Fig. 3 is the schematic diagram of shaft tower isolated point type in the embodiment of the present invention;
Fig. 4 is the schematic diagram of shift point type in the embodiment of the present invention;
Fig. 5 is the schematic diagram of fallibility Kneetype in the embodiment of the present invention;
Embodiment (algorithm case)
Below in conjunction with accompanying drawing and specific embodiment, technical scheme of the present invention is further described.
Shown in Figure 1, a kind of overhead power transmission line pole tower coordinate classification error-detecting method, comprises the following steps:
According to tens thousand of the overhead line structures coordinates (shaft tower of makeing mistakes to be detected) that certain electrical network gathers, therefrom select 10 circuits to check this classification error-detecting method as sample, the correct coordinates of these 10 overhead line structures determines.Shaft tower data to be detected, shown in following sheet form.
The shaft tower data that table 3. is to be detected
| Shaft tower title | Shaft tower longitude | Shaft tower latitude |
| 1 shaft tower | 113.665694 | 24.687697 |
| 2 shaft towers | 113.665395 | 24.688 |
| 3 shaft towers | 113.665084 | 24.688264 |
| 4 shaft towers | 113.664756 | 24.688539 |
| 5 shaft towers | 113.664111 | 24.68899 |
| 6 shaft towers | 113.664061 | 24.689214 |
| 7 shaft towers | 113.663834 | 24.689485 |
| …… | …… | …… |
| 48 shaft towers | 113.64051 | 24.789503 |
| 1 shaft tower | 113.65388 | 24.690671 |
| 2 shaft towers | 113.666855 | 24.686709 |
| 3 shaft towers | 113.653652 | 24.690597 |
| …… | …… | …… |
| 54 shaft towers | 113.5825 | 24.750833 |
S101: overhead line structures error situation is divided into clearly make mistakes type and indefinite type of makeing mistakes, amounts to 7 groups;
Probe into the clear and definite type of makeing mistakes drawn to have: repeat point, isolated point, shift point, fallibility flex point; Indefinite type of makeing mistakes has: isolated point is made mistakes, angle is made mistakes, make mistakes apart from long, and details are shown in Fig. 2.
S102: fill a vacancy to being carried out interpolation by error detection circuit disappearance shaft tower coordinate;
S103: set up type error detection rule of clearly makeing mistakes, detailed rules sees above step S103 in instructions;
S104: utilize error detection rule, draw by the shaft tower of clearly makeing mistakes of error detection circuit, record shaft tower make mistakes type go forward side by side row interpolation correct;
Whether Programmable detection result is as shown in the table, carry out being the judgement of type of clearly makeing mistakes, if be type of clearly makeing mistakes, then to a little slotting intermediate value correction that makes mistakes to each measuring point to be checked.Following table for shaft tower after longitude and latitude, judged result and amendment before amendment is in, latitude table, complex point of wherein whether attaching most importance to, whether be isolated point, whether be shift point, whether be during fallibility flex point 4 arranges, 1 representative is the type, and 0 to be represented as be not the type.
Table 4. Programmable detection result
S105: the error rate inspection circuit coordinate after correction being carried out to indefinite type of makeing mistakes, draws the error probability of all kinds of indefinite type of makeing mistakes of tested shaft tower.
Calculate the error probability of indefinite type of makeing mistakes, each shaft tower to be detected is for indefinite type of error: isolated point is made mistakes, angle is made mistakes, obtain an error probability respectively apart from long makeing mistakes, and result is as shown in the table.
The error probability of the indefinite type of makeing mistakes of table 5.
S106: be greater than expert by the indefinite wrong shaft tower type error probability of error detection circuit and set threshold value, just judge this shaft tower coordinate mistake, misregistration type.
Probe into the threshold value of each indefinite type of makeing mistakes of this power network line is set to 0.7, error detection is effective.
S107: according to type and the indefinite type detection result of makeing mistakes of clearly makeing mistakes, comprehensive descision, completes circuit all shaft tower error detections work;
The method of comprehensive descision is: in clear and definite type error detection and indefinite type error-detecting method, in 7 group error-detecting methods, as long as there are class methods to be judged as mistake, then comprehensive descision result be just mistake; All do not misdeem, then this shaft tower coordinate does not have mistake.Comprehensive descision the results are shown in following table, and during in table, comprehensive descision one arranges, 1 representative makes mistakes, and 0 representative does not make mistakes.
Table 6. comprehensive descision result
Analysis result finds that this classification similarity detects the method for shaft tower coordinate, relatively more flexible when error detection, and can better detect wrong shaft tower.
Comprehensive above analysis, the method for a kind of electrical network shaft tower coordinate of the present invention error detection, based on classification debugging and similarity process, finds out the electrical network shaft tower of makeing mistakes.The method can draw an error probability to each shaft tower to be detected, instead of directly draws the certain mistake of certain shaft tower, have ignored indefinite gray area.Can be controlled to make mistakes the quantity of shaft tower, process has certain dirigibility, and effect is better than program (rule) directly judges.
Claims (5)
1. an overhead power transmission line pole tower coordinate classification error-detecting method, comprises the following steps:
Overhead line structures error situation is divided into clearly make mistakes type and indefinite type of makeing mistakes by S101, amounts to 7 groups;
S102 fills a vacancy to being carried out interpolation by error detection circuit disappearance shaft tower coordinate;
S103 sets up type error detection rule of clearly makeing mistakes;
S104 utilize error detection rule, draw by the shaft tower of clearly makeing mistakes of error detection circuit, record shaft tower make mistakes type go forward side by side row interpolation correct;
S105 carries out the error rate inspection of indefinite type of makeing mistakes to the circuit coordinate after correction, draws by the error probability of all kinds of indefinite type of makeing mistakes of error detection shaft tower;
S106 is greater than expert by the indefinite wrong shaft tower type error probability of error detection circuit and sets threshold value, just judges this shaft tower coordinate mistake, misregistration type;
S107 is according to type and the indefinite type detection result of makeing mistakes of clearly makeing mistakes, and comprehensive descision, completes circuit all shaft tower error detections work.
2. a kind of overhead power transmission line pole tower coordinate classification error-detecting method according to claim 1, is characterized in that: probe in described step S101 and drawn four kinds of clear and definite types of makeing mistakes: repeat point, isolated point, shift point, fallibility flex point; Three kinds of indefinite types of makeing mistakes: isolated point is made mistakes, angle is made mistakes, make mistakes apart from long.
3. a kind of overhead power transmission line pole tower coordinate classification error-detecting method according to claim 1, it is characterized in that: described step S102, probe into and drawn 4 kinds of deletion conditions: whole piece power network line disappearance, power network line intercalary delection, power network line start disappearance, power network line terminates disappearance, and carried out corresponding average of inserting respectively and fill a vacancy.
4. a kind of overhead power transmission line pole tower coordinate classification error-detecting method according to claim 1, is characterized in that: described type error detection rule of clearly makeing mistakes is as follows:
S103-1 repeats point (too similitude) debugging step.
It is (x that S103-1-1 is provided with two shaft tower coordinates
1, y
1), (x
2, y
2), first to whole piece line scanning one time, if the absolute value of the difference of current point and next point is less than 0.000001, then a next complex point flag (for array) of attaching most importance to of putting of mark is designated as 1;
S103-1-2 will indicate the point of 1, and carry out interpolation processing (on average), interpolation method processes by the method for S101.
S103-2: isolated point debugging step, Fig. 3 is shown in by isolated point schematic diagram.
S103-2-1 extracts 5 attributes (remove each two points of head and the tail, do not have attribute, think that they do not isolate) of every bar circuit interlude point.
Each point of interlude, has 5 attributes, and L1 is the distance of the distance with left side consecutive point, L2 and the right consecutive point, and L3 is and any the distance of left adjoint point of being separated by, and L4 is and any the distance of right adjoint point of being separated by, and angle 1 is the angle of left and right consecutive point.
S103-2-2 gets L1, and in L2, maximal value is L5, gets L3, and in L4, maximal value is L6.
S103-2-3 is less than 60 degree (being threshold value, self controllable system) when angle 1, and L5 is greater than 2000 meters (being threshold value, self controllable system), when L6 is greater than 2000 meters (being threshold value, self controllable system), thinks the isolated point of changing the time as clear and definite.
S103-2-4 revises isolated point for inserting intermediate value, uses the method in S101.
S103-3: drift point debugging step, Fig. 4 is shown in by shift point schematic diagram.
S103-3-1 first extracts each attribute L1 to be examined, L2.L1 is the distance of this measuring point to be checked and left adjoint point, and L2 is the distance of this measuring point to be checked and right adjoint point.
The attribute L1>3000 that S103-3-2 works as certain point to be detected (is parameters, self controllable system), L2<2000 (is parameters, self controllable system) time think that this point has been likely the starting point of shift point, the coordinate recording it is numbered mark.As Fig. 4, when detecting B point attribute, AB>3000, BC<2000, think that B point may be shift point starting point, then the coordinate of B point numbering is designated as mark.
Next S103-3-3 judges the lower some C point of B point, judges whether C point is less than 2000 (being parameters, self controllable system) to more lower distance,
If NO, return S103-3-1 to C point to continue to perform.
If yes, judge this section of shift point number, n is used for recording shift point number, and whenever judging that a point is shift point, n adds 1 more.When CD distance is less than 2000; And AD distance subtracts AC distance when being less than 30% of AC distance, thinks that C point is shift point, continue the detection of next point, repeat the detection of two conditions above, when meeting upper two conditions when difference, S103-3-1 is returned to next one point and continues to perform.
The data that S103-3-4 finally records are, a two-dimensional array, and the every a line of array has 2 values, are respectively the starting point subscript m ark of drift, the some number n of drift.The method interpolation correction shift point of above S102 is used according to this record.
S103-4: fallibility flex point debugging step, Fig. 5 is shown in by fallibility flex point schematic diagram.
S103-4-1 fallibility flex point, only appears in interlude, thinks that Origin And Destination can not be fallibility flex point, and 3 attributes of each point of record interlude, are respectively angle 1, left side bearing slope over 10 r
1, right side bearing slope over 10 r
2(obtain angle k by slope
1=arctan (r
1), k
2=arctan (r
2)).
S103-4-2 works as angle 1<60 ° (being threshold value, self controllable system), angle k
1with k
2the absolute value of difference when being less than 30 ° (being threshold value, self controllable system), judging that this point is fallibility flex point, must be that this point is made mistakes.
S103-4-3 is modified to slotting intermediate value.
5. a kind of overhead power transmission line pole tower coordinate classification error-detecting method according to claim 1, it is characterized in that: the error rate inspection of described indefinite type of makeing mistakes, concrete steps are as follows:
S105-1: the error rate inspection that isolated point is made mistakes, Fig. 3 is shown in by isolated point schematic diagram.
S105-1-1 determines attribute
Extract each point of 5 attributes (ignoring head and the tail two points) interlude of every bar circuit interlude point, there are 5 attributes, L1 is the distance with left side consecutive point, the distance of L2 and the right consecutive point, L3 is and any the distance of left adjoint point of being separated by, L4 is and any the distance of right adjoint point of being separated by, and angle 1 is angle.In note L1, L2, maximal value is L5, and get L3, in L4, maximal value is L6.
The isolated point sample that artificial selection 10 makes mistakes, extracts typical case and to make mistakes a little corresponding attribute angle 1, L5, L6.
S105-1-2 data prediction, in order to avoid extremum must be disturbed, selects attribute discretization.
The property value of measuring point to be checked is also by also pressing above-mentioned steps discretize, and the attribute representation obtaining each point is 3 dimensional vector (X
1, X
2, X
3), each sample of makeing mistakes has (an X
1i, X
2i, X
3i) (i=1,2 ... 10, be 10 samples of makeing mistakes).
S105-1-3 defines similarity formula:
Wherein through experiment discussion, find a=2 time, namely think angle isolated point judge in significance level account for 1/2, L5 and L6 respectively account for 1/4 time, error detection effect is best.Owing to there being 10 isolated point samples, then obtain 10 r
i(i=1,2...10), gets r=max (r
i) be just the similarity size of measuring point to be checked and isolated point.
The error detection of S105-1-4 similarity relates to optimization details:
A, make mistakes a little for dissimilar, different attributes can be extracted, make these belong to the difference of this kind of points of performance difference and normal point.
B, when carrying out similarity system design, can think that other attributes of some Attribute Relative are more important, as angle accounts for 2/5, other 3 attributes respectively account for 1/5, and the analog result made like this is better.
C, after finding the erroneous point of certain quasi-representative, the attribute of some erroneous point may be too abnormal, as distance is greater than 50000 meters, like this when similarity system design, impact can be caused larger.So carry out discretize to property value, can think to be just that 50000,0-500m can think to be a class as being greater than 50000, etc.
D, certain type sample are typically made mistakes and have a little been looked for 10, can compare the similar value of tested point and these 10 points, select maximum similar value as with such similar value, thus ensure the pardon that the typical fault type of choosing is made mistakes a little to this class.
The definition of e, likelihood can be considered voluntarily to optimize and how to define, and is two vectorial similaritys.
F, model can be continued to optimize, and make mistakes a little if any what do not detect, then can sum up a kind of type of makeing mistakes newly, then be detected by similarity, thus sophisticated model, reach the effect of anticipation.
S105-2: the error rate that angle is made mistakes a little is checked.Be less than 60 ° because flex point is defined as angle, other attributes are ever-changing, so when flex point similarity checks mistake, if angle is less, the probability that this point is made mistakes is larger.First draw the angle belonging to each point.
First the angle of each point is processed, when being greater than the angle of 100 °, think that it can be that flex point is made mistakes scarcely.In order to obtain an error probability, angle angle being greater than 100 ° is defined as 100 °, and its error probability is decided to be 0% like this.
The error rate that angle is made mistakes a little is:
R=(100-corner dimension)/100, wherein r ∈ [0,1]
S105-3: apart from the long error rate inspection made mistakes a little.
The distance of this point and adjacent 2 is L1, L2, gets L=max (L1, L2), to the point of L>=2000, thinks that it has an error probability, if L be greater than 7000 think that this point is necessarily made mistakes.
Apart from long error rate of makeing mistakes a little:
wherein
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111256702A (en) * | 2020-04-27 | 2020-06-09 | 天津市普迅电力信息技术有限公司 | Unmanned aerial vehicle autonomous inspection method for inspection of power tower |
| CN112163055A (en) * | 2020-09-09 | 2021-01-01 | 四川长园工程勘察设计有限公司 | Tower labeling method |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102855649A (en) * | 2012-08-23 | 2013-01-02 | 山东电力集团公司电力科学研究院 | Method for splicing high-definition image panorama of high-pressure rod tower on basis of ORB (Object Request Broker) feature point |
| CN103246936A (en) * | 2013-04-24 | 2013-08-14 | 广东电网公司中山供电局 | System and method for pre-warning of typhoon risks of overhead transmission lines of grid |
-
2014
- 2014-12-10 CN CN201410752980.0A patent/CN104462820B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102855649A (en) * | 2012-08-23 | 2013-01-02 | 山东电力集团公司电力科学研究院 | Method for splicing high-definition image panorama of high-pressure rod tower on basis of ORB (Object Request Broker) feature point |
| CN103246936A (en) * | 2013-04-24 | 2013-08-14 | 广东电网公司中山供电局 | System and method for pre-warning of typhoon risks of overhead transmission lines of grid |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111256702A (en) * | 2020-04-27 | 2020-06-09 | 天津市普迅电力信息技术有限公司 | Unmanned aerial vehicle autonomous inspection method for inspection of power tower |
| CN111256702B (en) * | 2020-04-27 | 2020-08-21 | 天津市普迅电力信息技术有限公司 | Unmanned aerial vehicle autonomous inspection method for inspection of power tower |
| CN112163055A (en) * | 2020-09-09 | 2021-01-01 | 四川长园工程勘察设计有限公司 | Tower labeling method |
| CN112163055B (en) * | 2020-09-09 | 2023-11-21 | 成都深瑞同华科技有限公司 | Tower labeling method |
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