A three-dimensional laser point cloud data rectification sampling verification method

Abstract

This invention discloses a method for sampling verification of three-dimensional laser point cloud data correction, comprising: randomly selecting the number of sampling points of the tower point cloud using the principle of random sampling to obtain correction error data; estimating the distribution of the point cloud correction error data from multiple aspects to obtain the correction error rate. p Based on the aforementioned correction error rate p Define the correction sampling rules and sampling verification scheme; determine the correction error rate. p The exchange table between the acceptance rate and the correction error rate is based on the error rate. p The number of sampling points and the sampling ratio are selected based on the sample acceptance rate, and the point cloud data skew correction sampling is verified. This invention proposes adding constraints during the point cloud data sampling verification process to eliminate verification errors caused by differences in terrain, tower type, and flight conditions during sampling in the random sampling process.

Description

Technical Field

[0001] This invention relates to the technical field of correction sampling verification, and in particular to a method for correction sampling verification of three-dimensional laser point cloud data. Background Technology

[0002] In recent years, the flight distance for a single sortie during point cloud data acquisition operations has been approximately 200 km. Most of the 220kV and above transmission line towers in Yunnan Province are located in mountainous areas. The absolute coordinate error of the flight trajectory obtained by RTK initially increases linearly with the distance from the takeoff point, but after a certain distance, it evolves into a large non-linear error. Consequently, the obtained absolute coordinates of the point cloud will also become significantly distorted from the actual coordinates as the distance from the takeoff point increases. Furthermore, the large-scale point cloud data acquisition will generate a massive amount of point cloud data, inevitably containing a large number of erroneous coordinates, necessitating correction of the acquired point cloud coordinate data. The current method of randomly sampling the entire transmission line for correction verification is unsuitable for verifying existing point cloud data; therefore, a sampling verification method specifically for point cloud correction is urgently needed. Summary of the Invention

[0003] The purpose of this section is to outline some aspects of embodiments of the present invention and to briefly describe some preferred embodiments. Simplifications or omissions may be made in this section, as well as in the abstract and title of this application, to avoid obscuring the purpose of these documents; however, such simplifications or omissions should not be construed as limiting the scope of the invention.

[0004] In view of the aforementioned existing problems, the present invention is proposed.

[0005] Therefore, the technical problem solved by this invention is that the method of verifying transmission line correction by randomly sampling the entire line is not applicable to the verification of existing point cloud data.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: Randomly sampling the number of tower point cloud sampling points using the principle of random sampling to obtain correction error data; estimating the distribution of the point cloud correction error data from multiple aspects to obtain the correction error rate. p Based on the aforementioned correction error rate p Define the correction sampling rules and sampling verification scheme; determine the correction error rate. p The exchange table between the acceptance rate and the correction error rate is based on the error rate. p The number of sampling points and the sampling ratio are selected based on the sample acceptance rate, and the verification of point cloud data skew correction sampling is completed.

[0007] As a preferred embodiment of the three-dimensional laser point cloud data correction sampling verification method of the present invention, the extraction of the number of sampling points of the tower point cloud includes,

[0008] Random selection x For each base tower, two points are randomly selected for correction verification.

[0009] The point cloud data of the towers are divided according to their voltage levels.

[0010] As a preferred embodiment of the three-dimensional laser point cloud data correction sampling verification method of the present invention, the step of estimating the distribution of the point cloud correction error data from multiple aspects includes:

[0011] From the perspective of overall error correction data, we provide an estimate of the error data distribution;

[0012] The data is divided according to voltage level, including the distribution estimation of the correction error of 500kV and 200kV data.

[0013] An analysis of the distribution of the correction error data is presented.

[0014] As a preferred embodiment of the three-dimensional laser point cloud data correction sampling verification method described in this invention, wherein: the correction error rate p The acquisition includes,

[0015] Based on the error requirements of actual operations and the error normal distribution curve obtained from error estimation, the correction error rate of the point cloud data is obtained. p .

[0016] As a preferred embodiment of the three-dimensional laser point cloud data correction sampling verification method described in this invention, the correction sampling rules include:

[0017] The number of correction verification towers shall not be less than 10% of the total number of towers;

[0018] The first and last poles of the transmission line must be selected;

[0019] This is a must-have when there is a significant height difference between the two base poles;

[0020] At least one tension bar or corner bar should be selected.

[0021] As a preferred embodiment of the three-dimensional laser point cloud data correction sampling verification method described in this invention, the sampling scheme includes the following:

[0022] The sampling points are determined using the percentage sampling method. n include,

[0023] ;

[0024] in, n Indicates the number of sampling points. α Indicates the sampling percentage.N Indicates the total number of poles and towers on the line;

[0025] Randomly select towers to be tested N i Form a set of towers to be verified S n ,

[0026] ;

[0027] in, S n This represents the set of towers to be verified. N i Number i The tower to be inspected n This indicates the number of towers to be verified.

[0028] As a preferred embodiment of the three-dimensional laser point cloud data correction sampling verification method described in this invention, it includes:

[0029] Based on correction error rate p Number of sampling points n And the experimental counting to verify whether the point cloud correction quality is qualified. d To obtain the reception rate of point cloud data for a certain line that meets the quality requirements for correction. L 1,

[0030] ;

[0031] in, L 1 indicates the reception rate of point cloud data from a certain line that meets the required quality for correction. p This represents the error correction rate. n Indicates the number of sampling points. d This represents the experimental count used to verify whether the point cloud correction quality is up to standard.

[0032] As a preferred embodiment of the three-dimensional laser point cloud data correction sampling verification method described in this invention, it includes:

[0033] According to the sampling rules, in the total number of towers on the line N Selected k Towers that meet the sampling rules and are to be inspected are added to the set of towers to be verified. S n Form a new set of towers to be verified S m ,

[0034] .

[0035] As a preferred embodiment of the three-dimensional laser point cloud data correction sampling verification method described in this invention, it includes:

[0036] when k base rod and S n When the included rods are completely overlapping m=n , k base rod and S n When the included rods are not completely overlapping m>n ;

[0037] .

[0038] As a preferred embodiment of the three-dimensional laser point cloud data correction sampling verification method described in this invention, it further includes:

[0039] Based on correction error rate p Number of sampling points m And the experimental counting to verify whether the point cloud correction quality is qualified. d To obtain the reception rate of point cloud data for a certain line that meets the quality requirements for correction. L 2,

[0040] ;

[0041] in, L 2 indicates the reception rate of point cloud data from a certain line that meets the required quality correction standards. p This represents the error correction rate. m Indicates the number of sampling points. d This represents the experimental count used to verify whether the point cloud correction quality is up to standard.

[0042] The beneficial effects of this invention are as follows: This invention proposes to eliminate verification errors caused by differences in terrain, tower type, and flight conditions during sampling by adding restrictive conditions during the point cloud data sampling verification process. Attached Figure Description

[0043] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein:

[0044] Figure 1 A diagram showing the proportion of transmission line tower point cloud correction verification samples divided by voltage level in a three-dimensional laser point cloud data correction sampling verification method provided in an embodiment of the present invention.

[0045] Figure 2This invention provides a method for correcting and sampling verification of three-dimensional laser point cloud data, as an embodiment of the present invention.

[0046] Figure 3 A schematic diagram of the basic process and a curve of measured correction error data of a three-dimensional laser point cloud data correction sampling verification method provided in an embodiment of the present invention;

[0047] Figure 4 A typical probability density curve fitting diagram of a three-dimensional laser point cloud data correction sampling verification method provided in an embodiment of the present invention;

[0048] Figure 5 The graph shows the relationship between the sample reception rate and the error rate and the number of sampling points in a three-dimensional laser point cloud data correction sampling verification method provided in an embodiment of the present invention. Detailed Implementation

[0049] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0050] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0051] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0052] This invention is described in detail with reference to the schematic diagrams. When detailing the embodiments of this invention, for ease of explanation, the cross-sectional views illustrating the device structure may be partially enlarged, not adhering to the usual scale. Furthermore, the schematic diagrams are merely examples and should not be construed as limiting the scope of protection of this invention. In actual fabrication, the three-dimensional spatial dimensions of length, width, and depth should be included.

[0053] Furthermore, in the description of this invention, it should be noted that the terms "upper," "lower," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. These terms are used solely for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. In addition, the terms "first," "second," or "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0054] Unless otherwise explicitly specified and limited, the terms "installation," "connection," and "joining" in this invention should be interpreted broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; similarly, they can refer to mechanical connections, electrical connections, or direct connections, or indirect connections through an intermediate medium, or internal connections between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances. Example

[0055] Reference Figure 1 As an embodiment of the present invention, a method for correcting and validating three-dimensional laser point cloud data by sampling is provided, comprising:

[0056] S1: Randomly select the number of sampling points in the tower point cloud using the principle of random sampling to obtain the correction error data. It should be noted that the selection of the number of tower point cloud sampling points includes...

[0057] Random selection x For each base tower, two points are randomly selected for correction verification.

[0058] The point cloud data of the towers is divided according to the voltage level.

[0059] S2: Estimate the distribution of point cloud correction error data from multiple perspectives and obtain the correction error rate. p .

[0060] It should be noted that:

[0061] The distribution of point cloud correction error data is estimated from multiple perspectives, including:

[0062] From the perspective of overall error correction data, we provide an estimate of the error data distribution;

[0063] The data is divided according to voltage level, including the distribution estimation of the correction error of 500kV and 200kV data.

[0064] An analysis of the distribution of the correction error data is presented.

[0065] Correction error rate p The acquisition includes,

[0066] Based on the error requirements of actual operations and the error normal distribution curve obtained from error estimation, the correction error rate of the point cloud data is obtained. p .

[0067] S3: Based on correction error rate p Set up corrective sampling rules and sampling verification schemes.

[0068] It should be noted that:

[0069] Corrective sampling rules include,

[0070] The number of correction verification towers shall not be less than 10% of the total number of towers;

[0071] The first and last poles of the transmission line must be selected;

[0072] This is a must-have when there is a significant height difference between the two base poles;

[0073] At least one tension bar or corner bar should be selected.

[0074] The sampling plan includes,

[0075] The sampling points are determined using the percentage sampling method. n include,

[0076] ;

[0077] in, n Indicates the number of sampling points. α Indicates the sampling percentage. N Indicates the total number of poles and towers on the line;

[0078] Randomly select towers to be tested N i Form a set of towers to be verified S n ,

[0079] ;

[0080] in, S n This represents the set of towers to be verified. N i Number i The tower to be inspected n This indicates the number of towers to be verified.

[0081] include,

[0082] Based on correction error rate p Number of sampling points n And the experimental counting to verify whether the point cloud correction quality is qualified. dTo obtain the reception rate of point cloud data for a certain line that meets the quality requirements for correction. L 1,

[0083] ;

[0084] in, L 1 indicates the reception rate of point cloud data from a certain line that meets the required quality for correction. p This represents the error correction rate. n Indicates the number of sampling points. d This represents the experimental count used to verify whether the point cloud correction quality is up to standard.

[0085] include,

[0086] According to the sampling rules, in the total number of poles and towers of the line N Selected k Towers that meet the sampling rules and are to be inspected are added to the set of towers to be verified. S n Form a new set of towers to be verified S m ,

[0087] .

[0088] include,

[0089] when k base rod and S n When the included rods are completely overlapping m=n , k base rod and S n When the included rods are not completely overlapping m>n ;

[0090] .

[0091] It also includes,

[0092] Based on correction error rate p Number of sampling points m And the experimental counting to verify whether the point cloud correction quality is qualified. d To obtain the reception rate of point cloud data for a certain line that meets the quality requirements for correction. L 2,

[0093] ;

[0094] in, L 2 indicates the reception rate of point cloud data from a certain line that meets the required quality correction standards. p This represents the error correction rate. m Indicates the number of sampling points. dThis represents the experimental count used to verify whether the point cloud correction quality is up to standard.

[0095] S4: Determine the error correction rate p The exchange table between acceptance rate and correction error rate is based on the error rate. p The number of sampling points and the sampling ratio are selected based on the sample acceptance rate, and the verification of point cloud data skew correction sampling is completed.

[0096] This invention proposes to eliminate verification errors caused by differences in terrain, tower type, and flight conditions during sampling by adding constraints during the point cloud data sampling verification process. Example

[0097] Reference Figures 2 to 5 This is the second embodiment of the present invention. Unlike the first embodiment, this embodiment provides a verification test of a three-dimensional laser point cloud data correction sampling verification method. In order to verify and explain the technical effect of the method, this embodiment uses a traditional technical solution to compare and test with the method of the present invention, and compares the test results with scientific demonstration methods to verify the real effect of the method.

[0098] Based on the principle of random sampling, 806 transmission line towers were randomly selected from the overall data of Yunnan Province. Two points were taken from each tower, totaling 1604 points (8 points were discarded due to the sparse point cloud) for correction verification. The transmission line tower point cloud data was divided according to the voltage level of the towers. This sampling mainly included 220kV and 500kV lines. The number of tower point cloud sampling points were: 588 towers, 1176 points (73.3%), and 214 towers, 428 points, respectively. The distribution is as follows: Figure 2 As shown.

[0099] The correction error values ​​of the transmission line point cloud data collected during this correction process are arranged in the order of collection and plotted as a line graph, as shown below. Figure 3 The horizontal axis represents the number of actual error values ​​observed in this correction sampling, the vertical axis represents the error value of the sampling points in this correction, and the broken line represents the trend of error value changing with the number of error points. Figure 3 From this, we can initially determine that the data meets a certain condition. Normal distribution, of which The mean, The variance is denoted as σ. Statistical learning processing was performed on the sampled point cloud correction error data. The data were arranged in ascending order. By observing the sorted data, the minimum value was 0.02, the maximum value was 0.50, the median was 0.27, the mean was 0.2717, and the standard deviation was 0.1011. The results are shown in Table 1 below.

[0100] Table 1: Overall statistics of point cloud correction data deviation values.

[0101] property Maximum value Maximum value median mean Standard deviation numerical values 0.02 0.50 0.27 0.2727 0.1011

[0102] The probability density function fitting tool for random variables in MATLAB was used to fit the above frequency distribution curves to the probability density curves of normal, gamma, Rayleigh, and inverse Gaussian distributions. The fitting results are as follows: Figure 4 As shown in Table 2, the log-likelihood values ​​for each probability density distribution are as follows.

[0103] Table 2: Differences in log-likelihood values ​​for typical probability density fitting.

[0104] Distribution Name normal distribution Gamma distribution Rayleigh distribution Inverse Gaussian distribution log-likelihood value 1399.79 1368.41 1257.1 1248.5

[0105] From Table 2 and Figure 4 It can be seen that the normal distribution probability density curve fits the frequency statistical histogram of the error values ​​of the transmission line point cloud data best, with a log-likelihood value of 1399.79, while the inverse Gaussian distribution probability density curve fits the frequency statistical histogram of the error values ​​of the transmission line point cloud data worst, with a log-likelihood value of 1248.5. Based on the actual operational requirement of an error value of no less than 0.5 meters, and combining the above-estimated normal distribution curve of the error, the deviation from the mean of 0.5 meters is... α The quantile is 0.5, so the point cloud data correction error rate is 5%.

[0106] In the process of verifying the correction of 3D laser point cloud data for power transmission lines, due to interference from various factors during the sampling process, we often cannot accurately obtain the actual correction error rate for each line. However, we can use the formula... The relationship between sample acceptance rate and error rate and number of sampling points was calculated and presented in tables and graphs. Table 3 shows the relationship between sample acceptance rate and error rate and number of sampling points, and the graph shows the relationship between sample acceptance rate and error rate and number of sampling points. Figure 5 As shown, in the verification of three-dimensional laser point cloud data correction sampling for transmission lines, we can select the number of sampling points and the sampling ratio based on the correction error rate and sample reception rate of the specific line.

[0107] Table 3: Relationship between sample acceptance rate and the number of sampling inspection points and error rate.

[0108] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for sampling and verifying three-dimensional laser point cloud data for deviation correction, characterized in that, include: By randomly selecting the number of sampling points in the tower point cloud using the principle of random sampling, the point cloud correction error data is obtained. The distribution of the point cloud correction error data is estimated from multiple perspectives to obtain the correction error rate. p ; Based on the aforementioned correction error rate p Set corrective sampling rules and sampling verification schemes; The aforementioned correction error rate is determined. p The exchange table between the acceptance rate and the correction error rate is based on the error rate. p The number of sampling points and the sampling ratio are selected based on the sample acceptance rate. The extraction of the number of sampling points in the tower point cloud includes, Random selection x For each base tower, two points are randomly selected for correction verification. The point cloud data of the towers are divided according to their voltage levels; The estimation of the distribution of the point cloud correction error data from multiple aspects includes... From the perspective of overall error correction data, we provide an estimate of the error data distribution; The data is divided according to voltage level, including the distribution estimation of the correction error of 500kV and 200kV data. An analysis of the distribution of the correction error data is given; Corrective sampling rules include, The number of correction verification towers shall not be less than 10% of the total number of towers; The first and last poles of the transmission line must be selected; This is a must-have when there is a significant height difference between the two base poles; At least one tension bar or corner bar should be selected; The sampling plan includes, The sampling points are determined using the percentage sampling method. n include, ； in, n Indicates the number of sampling points. α Indicates the sampling percentage. N Indicates the total number of poles and towers on the line; Randomly select towers to be tested N i Form a set of towers to be verified S n , ； in, S n This represents the set of towers to be verified. N i Number i The tower to be inspected n Indicates the number of towers to be verified; By adding constraints during the point cloud data sampling verification process, verification errors caused by differences in terrain, tower type, and flight conditions during sampling can be eliminated during random sampling.

2. The three-dimensional laser point cloud data correction sampling verification method as described in claim 1, characterized in that: The correction error rate p The acquisition includes, Based on the error requirements of actual operations and the error normal distribution curve obtained from error estimation, the correction error rate of the point cloud data is obtained. p .

3. The three-dimensional laser point cloud data correction sampling verification method as described in claim 2, characterized in that: include, Based on correction error rate p Number of sampling points n And the experimental counting to verify whether the point cloud correction quality is qualified. d To obtain the reception rate of point cloud data for a certain line that meets the quality requirements for correction. L 1, ； in, L 1 indicates the reception rate of point cloud data from a certain line that meets the required quality for correction. p This represents the error correction rate. n Indicates the number of sampling points. d This represents the experimental count used to verify whether the point cloud correction quality is up to standard.

4. The three-dimensional laser point cloud data correction sampling verification method as described in claim 3, characterized in that: include, According to the sampling rules, in the total number of towers on the line N Selected k Towers that meet the sampling rules and are to be inspected are added to the set of towers to be verified. S n Form a new set of towers to be verified S m , 。 5. The three-dimensional laser point cloud data correction sampling verification method as described in claim 4, characterized in that: include, when k base rod and S n When the included rods are completely overlapping m=n , k base rod and S n When the included rods are not completely overlapping m>n ; 。 6. The three-dimensional laser point cloud data correction sampling verification method as described in any one of claims 3 to 5, characterized in that: It also includes, Based on correction error rate p Number of sampling points m And the experimental counting to verify whether the point cloud correction quality is qualified. d To obtain the reception rate of point cloud data for a certain line that meets the quality requirements for correction. L 2, ； in, L 2 indicates the reception rate of point cloud data from a certain line that meets the required quality correction standards. p This represents the error correction rate. m Indicates the number of sampling points. d This represents the experimental count used to verify whether the point cloud correction quality is up to standard.

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