CN107817504B - Airborne laser radar point cloud data processing method - Google Patents
Airborne laser radar point cloud data processing method Download PDFInfo
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- CN107817504B CN107817504B CN201711025507.2A CN201711025507A CN107817504B CN 107817504 B CN107817504 B CN 107817504B CN 201711025507 A CN201711025507 A CN 201711025507A CN 107817504 B CN107817504 B CN 107817504B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/88—Lidar systems specially adapted for specific applications
- G01S17/93—Lidar systems specially adapted for specific applications for anti-collision purposes
- G01S17/933—Lidar systems specially adapted for specific applications for anti-collision purposes of aircraft or spacecraft
Abstract
The invention relates to the technical field of power transmission line inspection, in particular to a point cloud data processing method of an airborne laser radar. According to the characteristic of the data points when the helicopter suspends, the data points are split when the monotonicity of the x value or the y value of the data points changes by taking time as a sequence, and the region with data overlapping is split, so that the problems of data point overlapping and redundancy caused by errors of a position attitude sensor due to hovering of the helicopter are solved.
Description
Technical Field
The invention relates to the technical field of power transmission line inspection, in particular to a point cloud data processing method of an airborne laser radar.
Background
In the inspection of the power transmission line, the helicopter-mounted laser radar is often used for collecting the condition of the power transmission line, and the data collection and reduction effects of the helicopter-mounted laser radar depend on the collection precision of the position attitude sensor in the equipment to a great extent. When the helicopter is used for inspection operation, the laser radar moves along with the helicopter and performs data acquisition along the direction vertical to the flight direction, and the flight route does not retreat or repeat; if the airplane hovers, the airplane can not be absolutely static in the air, and the airplane can swing forwards, backwards, leftwards and rightwards to a certain extent when hovering. The situation that the laser radar repeatedly collects data occurs at the moment. During suspension, due to the limitation of the principle of the position and attitude sensor, errors are easy to occur in position and attitude data, when the errors are large, the data are in a messy state during suspension, the data are overlapped before and after suspension, and the analysis result of the data is seriously influenced.
Disclosure of Invention
The invention aims to overcome at least one defect in the prior art, and provides an airborne laser radar point cloud data processing method.
In order to solve the technical problems, the invention adopts the following technical scheme:
the airborne laser radar point cloud data processing method is based on point cloud data acquired by an airborne laser radar, wherein the point cloud data has time and three-dimensional coordinate xyz attributes, xy is a horizontal plane coordinate, and z is a vertical coordinate, and the method specifically comprises the following steps:
s1: sequencing each data point in the laser point cloud according to the time sequence, and then executing the step S2;
s2: sequentially detecting the x value or the y value of each data point, splitting the data by taking the first data point which is monotonically changed as a demarcation point when the x value or the y value of each data point is changed from increasing to decreasing or from decreasing to increasing, and then executing the step S3;
s3: judging whether the data point is detected completely, if so, completing data splitting, and executing step S4; if not, continuing to execute step S2 for the remaining detection points;
s4: and (4) detecting each split section of data independently to judge whether obstacles exist in the safety distance around the lead.
The laser point cloud data is characterized in that each point has attributes such as measurement time and three-dimensional xyz coordinates, wherein xy is a horizontal coordinate, z is a vertical coordinate, and as the aircraft flies along the line during flying, if no hovering exists, two coordinate values of x and y on the plane are monotone increasing or monotone decreasing functions of time. The invention divides data according to the characteristics of flight data collection by the time characteristic, and divides the data when the data point is changed from increasing to decreasing or from decreasing to increasing, and processes the data by sections.
Compared with the prior art, the beneficial effects are: according to the characteristic of the data points when the helicopter is suspended, the data points are split when the monotonicity of the x value or the y value of the data points changes by taking time as an order, and the region with data overlapping is split, so that the problem of processing redundant data is solved.
Drawings
FIG. 1 is a flow chart of an embodiment of the present invention.
Detailed Description
The invention is further described with reference to the accompanying drawings, which are meant to be illustrative only and not to be construed as limiting the patent.
The method comprises the following steps of (1) acquiring point cloud data when an airplane is suspended, wherein the point cloud data is in disorder on a horizontal plane when the point cloud data is suspended, and the following method is adopted for processing the disorder data:
as shown in fig. 1, a method for processing point cloud data of an airborne laser radar is based on point cloud data acquired by the airborne laser radar, wherein the point cloud data has time and three-dimensional coordinate xyz attributes, xy is a horizontal plane coordinate, and z is a vertical coordinate, and specifically includes the following steps:
s1: as shown in the following table, step S2 is executed after each data point in the laser point cloud is sorted according to the time sequence;
s2: sequentially detecting the x value or the y value of each data point, splitting the data by taking the first data point which is monotonically changed as a demarcation point when the x value or the y value of each data point is changed from increasing to decreasing or from decreasing to increasing, and then executing the step S3;
as shown in the following table, the local point cloud data sorted by time is as follows, it can be seen that the 1 st to 4 th row of data x is monotonously decreased, y is monotonously increased, and in the 5 th row, x is increased, y is decreased, and the data is split into two segments from the 5 th row of data;
| serial number | X | Y | Z | Time |
| 1 | 319195.69 | 2662848.05 | 131.8999939 | 376747.520329 |
| 2 | 319195.55 | 2662848.14 | 131.9700012 | 376747.520331 |
| 3 | 319195.29 | 2662848.28 | 132.1600037 | 376747.520331 |
| 4 | 319193.65 | 2662849.02 | 133.7799988 | 376747.520333 |
| 5 | 319195.23 | 2662848.34 | 132.1699982 | 376747.520333 |
| 6 | 319194.85 | 2662848.54 | 132.4799957 | 376747.520335 |
S3: judging whether the data point is detected completely, if so, completing data splitting, and executing step S4; if not, continuing to execute step S2 for the remaining detection points;
s4: and (4) detecting each split section of data independently to judge whether obstacles exist in the safety distance around the lead.
It should be understood that the above-described embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the claims of the present invention.
Claims (1)
1. The airborne laser radar point cloud data processing method is characterized by comprising the following steps of based on point cloud data acquired by an airborne laser radar, wherein the point cloud data has time and three-dimensional coordinate xyz attributes, xy is a horizontal plane coordinate, and z is a vertical coordinate:
s1: sequencing each data point in the laser point cloud according to the time sequence, and then executing the step S2;
s2: sequentially detecting the x value or the y value of each data point, splitting the data by taking the first data point which is monotonically changed as a demarcation point when the x value or the y value of each data point is changed from increasing to decreasing or from decreasing to increasing, and then executing the step S3;
s3: judging whether the data point is detected completely, if so, completing data splitting, and executing step S4; if not, continuing to execute step S2 for the remaining detection points;
s4: and (4) detecting each split section of data independently to judge whether obstacles exist in the safety distance around the lead.
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| CN110120097B (en) * | 2019-05-14 | 2020-09-04 | 南京林业大学 | Semantic modeling method for airborne point cloud of large scene |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101702200A (en) * | 2009-11-03 | 2010-05-05 | 武汉大学 | Automatic classification method of airborne laser radar point cloud data |
| CN103606852A (en) * | 2013-11-26 | 2014-02-26 | 广东电网公司电力科学研究院 | Power line inspection method of unmanned helicopter |
| CN104050715A (en) * | 2014-06-23 | 2014-09-17 | 华北电力大学 | High-precision three-dimensional reconstruction method for power transmission line and corridor |
| CN104236499A (en) * | 2014-10-15 | 2014-12-24 | 厦门大学 | Automatic measurement method for railway on basis of point cloud data |
| CN104732588A (en) * | 2015-03-30 | 2015-06-24 | 中国测绘科学研究院 | Power line three-dimensional reconstructing method based on airborne laser radar point cloud |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR100949788B1 (en) * | 2009-11-06 | 2010-03-30 | 주식회사 범아엔지니어링 | Method for examining the quality of airborne lidar data |
| JP5356269B2 (en) * | 2010-01-29 | 2013-12-04 | 株式会社パスコ | Laser data filtering method and apparatus |
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101702200A (en) * | 2009-11-03 | 2010-05-05 | 武汉大学 | Automatic classification method of airborne laser radar point cloud data |
| CN103606852A (en) * | 2013-11-26 | 2014-02-26 | 广东电网公司电力科学研究院 | Power line inspection method of unmanned helicopter |
| CN104050715A (en) * | 2014-06-23 | 2014-09-17 | 华北电力大学 | High-precision three-dimensional reconstruction method for power transmission line and corridor |
| CN104236499A (en) * | 2014-10-15 | 2014-12-24 | 厦门大学 | Automatic measurement method for railway on basis of point cloud data |
| CN104732588A (en) * | 2015-03-30 | 2015-06-24 | 中国测绘科学研究院 | Power line three-dimensional reconstructing method based on airborne laser radar point cloud |
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