CN107633504A - Shaft tower inclined degree detection method and device - Google Patents
Shaft tower inclined degree detection method and device Download PDFInfo
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- CN107633504A CN107633504A CN201710666288.XA CN201710666288A CN107633504A CN 107633504 A CN107633504 A CN 107633504A CN 201710666288 A CN201710666288 A CN 201710666288A CN 107633504 A CN107633504 A CN 107633504A
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Abstract
A kind of shaft tower inclined degree detection method provided in an embodiment of the present invention and device, methods described are applied to equipment of taking photo by plane, and methods described includes：The equipment of taking photo by plane obtains the laser radar data and view data of target shaft tower；Point cloud and Image registration mode, the laser radar data and described image data based on direct linear transformation, generate colour point clouds data；Based on the machine learning classification algorithm pre-saved and sample data, target shaft tower cloud data is obtained；According to the target shaft tower cloud data, the slope of the target shaft tower is calculated.Pass through this method, it can realize that the automation of a wide range of inclination of electric power tower degree accurately measures, moreover it is possible to realize the image conversion and digitized description of measurement result, be easy to archive and final-period management, meanwhile avoid the problem of existing measuring method workload is big, risk is high, efficiency is low.
Description
Technical field
The present invention relates to transmission line faultlocating technical field, in particular to a kind of shaft tower inclined degree detection method
And device.
Background technology
Shaft tower is one of basic equipment in transmission line of electricity, and it is line construction construction and fortune that measurement is carried out to its tilt condition
Seek the important content safeguarded.Because shaft tower is chronically exposed to outside, easily by the erosion and artificial destruction of nature, easily send out
The shape that changes or inclination, electrical safety is caused apart from too small, in some instances it may even be possible to rod disconnection occurs.In city or other dense population areas
At domain, important scissors crossing, once tower occurs, consequence will be extremely serious.With building up for China spy/extra high voltage network
Put into operation, high accuracy, the measurement of efficient gradient how are carried out to electric power line pole tower, is power department very concern
However, the existing measuring method to shaft tower gradient, it is necessary to which staff steps on tower operation, exist workload greatly and
The deficiency that risk is high, efficiency is low, measurement accuracy are relatively low.
The content of the invention
In view of this, the purpose of the embodiment of the present invention is to provide a kind of shaft tower inclined degree detection method and device,
To overcome the shortcomings of that the existing measuring method to shaft tower gradient is brought.
In a first aspect, the embodiments of the invention provide a kind of shaft tower inclined degree detection method, methods described is applied to boat
Bat equipment, methods described, including：The equipment of taking photo by plane obtains the laser radar data and view data of target shaft tower；It is based on
The point cloud of direct linear transformation and Image registration mode, the laser radar data and described image data, generate color point
Cloud data；Based on the machine learning classification algorithm pre-saved and sample data, target shaft tower cloud data is obtained；According to institute
Target shaft tower cloud data is stated, the slope of the target shaft tower is calculated.
Second aspect, the embodiments of the invention provide a kind of shaft tower inclined degree detection means, described device is applied to boat
Bat equipment, described device, including：First acquisition module, for obtaining the laser radar data and view data of target shaft tower；
Generation module, for the point cloud based on direct linear transformation and Image registration mode, the laser radar data and the figure
As data, colour point clouds data are generated；Second acquisition module, for based on the machine learning classification algorithm pre-saved and sample
Notebook data, obtain target shaft tower cloud data；Computing module, for according to the target shaft tower cloud data, institute to be calculated
State the slope of target shaft tower.
Shaft tower inclined degree detection method provided in an embodiment of the present invention and device, by equipment of taking photo by plane to collecting
Shaft tower view data and laser radar data handled, generate colour point clouds data, and use sorting algorithm, acquisition
Target shaft tower cloud data, and by target shaft tower cloud data, the slope of the target shaft tower is calculated.Pass through the party
Method, it is possible to achieve the automation of a wide range of inclination of electric power tower degree accurately measures, moreover it is possible to realize measurement result image conversion and
Digitized description, is easy to achieve and final-period management, meanwhile, avoid that existing measuring method workload is big, risk is high, efficiency is low
Problem.
Other features and advantages of the present invention will illustrate in subsequent specification, also, partly become from specification
It is clear that or by implementing understanding of the embodiment of the present invention.The purpose of the present invention and other advantages can be by saying what is write
Specifically noted structure is realized and obtained in bright book, claims and accompanying drawing.
Brief description of the drawings
In order to illustrate the technical solution of the embodiments of the present invention more clearly, below by embodiment it is required use it is attached
Figure is briefly described, it will be appreciated that the following drawings illustrate only certain embodiments of the present invention, therefore be not construed as pair
The restriction of scope, for those of ordinary skill in the art, on the premise of not paying creative work, can also be according to this
A little accompanying drawings obtain other related accompanying drawings.
Fig. 1 is a kind of block diagram for equipment of taking photo by plane provided in an embodiment of the present invention；
Fig. 2 is a kind of flow chart for shaft tower inclined degree detection method that first embodiment of the invention provides；
Fig. 3 is the flow chart for another shaft tower inclined degree detection method that first embodiment of the invention provides；
Fig. 4 is the calculating schematic diagram for another shaft tower inclined degree detection method that first embodiment of the invention provides；
Fig. 5 is the calculating schematic diagram for another shaft tower inclined degree detection method that first embodiment of the invention provides；
Fig. 6 is a kind of structured flowchart for shaft tower inclined degree detection means that second embodiment of the invention provides；
Fig. 7 is the structured flowchart for another shaft tower inclined degree detection means that second embodiment of the invention provides；
Fig. 8 is the structured flowchart for another shaft tower inclined degree detection means that second embodiment of the invention provides.
Embodiment
Below in conjunction with accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Ground describes, it is clear that described embodiment is only part of the embodiment of the present invention, rather than whole embodiments.Generally exist
The component of the embodiment of the present invention described and illustrated in accompanying drawing can be configured to arrange and design with a variety of herein.
First, noun involved in the embodiment of the present invention is briefly described.
Digital orthophoto map：It is that Differential rectification is carried out to Aero-Space photo and is inlayed, by certain figure amplitude range
Cut the digital orthoimage collection of generation.
Convex closure：Point set on given two dimensional surface, convex closure is exactly that outermost point is connected into the convex polygonal of composition,
It can include point and concentrate all points.The most frequently used algorithm of convex hull is Graham scanning methods and Jarvis step-by-step method algorithms.
Point cloud：The point data set on the product appearance surface obtained by measuring instrument also referred to as point cloud, it is usually used
The spacing of the fewer point of point quantity and point obtained by three dimensional coordinate measuring machine is also bigger, is sparse cloud；And use three-dimensional
The point cloud point quantity that laser scanner or photographic-type scanner obtain is bigger and than comparatively dense, is point off density cloud.
As shown in figure 1, it is a kind of block diagram of equipment 100 of taking photo by plane provided in an embodiment of the present invention.Described take photo by plane sets
Standby 100 can be unmanned plane.
The equipment 100 of taking photo by plane includes：Shaft tower inclined degree detection means, memory 110, storage control 120, processing
Device 130, Peripheral Interface 140, input/output module 150, radar scanner 160 and camera 170.
Wherein, the memory 110, storage control 120, processor 130, Peripheral Interface 140, input/output module
150th, radar scanner 160 and 170 each element of camera are directly or indirectly electrically connected between each other, to realize the biography of data
Defeated or interaction.It is electrically connected with for example, these elements can be realized by one or more communication bus or signal wire between each other.Institute
Described deposit can be stored in including at least one in the form of software or firmware (firmware) by stating shaft tower inclined degree detection means
In reservoir or the SFU software functional unit that is solidificated in the operating system (operating system, OS) of the equipment 100 of taking photo by plane.
The processor 130 is used to perform the executable unit stored in memory 110, such as the shaft tower inclined degree detection means
Including SFU software functional unit or computer program.
Wherein, memory 110 may be, but not limited to, random access memory (Random Access Memory,
RAM), read-only storage (Read Only Memory, ROM), programmable read only memory (Programmable Read-Only
Memory, PROM), erasable read-only memory (Erasable Programmable Read-Only Memory, EPROM),
Electricallyerasable ROM (EEROM) (Electric Erasable Programmable Read-Only Memory, EEPROM) etc..
Wherein, memory 110 is used for storage program, and the processor 130 performs described program after execute instruction is received, foregoing
The method taken photo by plane performed by equipment 100 for the flow definition that any embodiment of the embodiment of the present invention discloses can apply to processor
In 130, or realized by processor 130.
Processor 130 is probably a kind of IC chip, has the disposal ability of signal.Above-mentioned processor 130 can
To be general processor, including central processing unit (Central Processing Unit, abbreviation CPU), network processing unit
(Network Processor, abbreviation NP) etc.；Can also be digital signal processor (DSP), application specific integrated circuit (ASIC),
Ready-made programmable gate array (FPGA) either other PLDs, discrete gate or transistor logic, discrete hard
Part component.It can realize or perform disclosed each method, step and the logic diagram in the embodiment of the present invention.General processor
Can be microprocessor or the processor can also be any conventional processor etc..
Various input/output devices are coupled to processor 130 and memory 110 by the Peripheral Interface 140.At some
In embodiment, Peripheral Interface 140, processor 130 and storage control 120 can be realized in one single chip.Other one
In a little examples, they can be realized by independent chip respectively.
Input/output module 150 is used to be supplied to user input data to realize interacting for user and equipment 100 of taking photo by plane.It is described
Input/output module 150 may be, but not limited to, the data-interface such as I/O mouths, WAN mouths, LAN mouths.
Radar scanner 160 is used to launch laser to transmission line of electricity, and gathers the laser radar data of return, and by laser
Radar data is sent to processor 130 and handled.
Camera 170 can be general camera or industrial camera, for shooting the image data of transmission line of electricity, and
Processor 130 is uploaded to be handled.
First embodiment
Fig. 2 is refer to, Fig. 2 is a kind of flow chart of shaft tower inclined degree detection method provided in an embodiment of the present invention, should
Method is applied to take photo by plane equipment, such as unmanned plane.Methods described includes：
Step S110：The equipment of taking photo by plane obtains the laser radar data and view data of target shaft tower.
Wherein, take photo by plane in equipment described while be provided with camera and radar scanner, the processing of the equipment of taking photo by plane
Device can control camera and radar scanner while work, and gather the view data and laser radar number of target shaft tower respectively
According to, and get target shaft tower laser radar data and view data preserve in memory, to carry out subsequent treatment.
Gathered data can reduce the intractability of data simultaneously.
Step S120：Point cloud and Image registration mode, the laser radar data and institute based on direct linear transformation
View data is stated, generates colour point clouds data.
Equipment of taking photo by plane can be by the way of the point cloud based on direct linear transformation and Image registration to the laser radar
Data and described image data are handled, according to the coordinate of the position relationship of camera and radar scanner determination between the two
Transfer equation, generate colour point clouds data.This method can drop without elements of interior orientation value and the initial approximation of elements of exterior orientation
The low requirement to camera, you can be operated using general camera, saved cost.
Step S130：Based on the machine learning classification algorithm pre-saved and sample data, target shaft tower point cloud is obtained
Data.
Wherein, the equipment of taking photo by plane can be shifted to an earlier date based on the machine learning classification algorithm pre-saved and sample data
Training obtains the discriminant function of the characteristic vector of target shaft tower point cloud, and shaft tower is classified, and rejects the point cloud for being not belonging to shaft tower
Data.Further, by calculating the characteristic vector of the cloud data, and the characteristic vector is inputted into discriminant function, sentenced
Whether the characteristic vector that breaks meets the discriminant function, will determine that result meets the cloud data table of the discriminant function
Sign belongs to shaft tower, and this is categorized as into target shaft tower cloud data.The colouring information of a cloud, classification results essence are added in the present invention
Degree improves 5% than congenic method.
Step S140：According to the target shaft tower cloud data, the slope of the target shaft tower is calculated.
Wherein, Fig. 3 is refer to, step S140 can include：
Step S141：The equipment of taking photo by plane obtains the first datum mark from the target shaft tower cloud data and generates the first water
Plane.
Due to the data message that target shaft tower cloud data is made up of multiple points in same three-dimensional system of coordinate, take photo by plane
After equipment gets target shaft tower cloud data, the minimum point (X in the lower left corner can be found in all target shaft tower cloud datas
Minimum, Y is minimum, and Z is minimum).In order to prevent the influence due to branch, landform from causing error, as a kind of embodiment, general choosing
Select in vertical direction (Z axis) pre-determined distance higher than minimum point o'clock as the first datum mark P (X1, Y1, Z1), and be based on the first base
P generates first level face M1 on schedule, and first level face M1 includes P points, and parallel in three-dimensional system of coordinate by X-axis and Y-axis institute structure
Into plane.
In the present embodiment, the pre-determined distance can rule of thumb select 15M, and certainly, the value is not limited to 15M,
It can be adjusted according to the situation of actual shaft tower.Pre-determined distance will be taken in the minimum point in the lower left corner as the first datum mark P, can be with
Ensure that the first level face M1 based on the generation of P points intersects with four tower angles of shaft tower.
Step S142：All points intersected with the first level face in the target shaft tower cloud data are extracted, are generated
First object face, obtain the coordinate of the central point in the first object face.
It is possible to further according to algorithm of convex hull, extract all in the target shaft tower cloud data and first water
Point intersecting plane M1, first object face M1 is generated by joining.Because the coordinate of each point is certain, therefore, can obtain
To the central point O1 in first object face coordinate (X2, Y2, Z2).
Step S143：From the target shaft tower cloud data, it is pre- to obtain with the vertical distance of first datum mark
If value o'clock as the second datum mark, generate the second horizontal plane parallel to the first level face.
Wherein, the preset value is h.Then the second datum mark Q coordinate is (X3, Y3, Z3), Z3=Z2+h.Second is horizontal
Face M2 includes Q points, and parallel to the plane being made up of in three-dimensional system of coordinate X-axis and Y-axis.
Step S144：All points intersected with second horizontal plane in the target shaft tower cloud data are extracted, are generated
Second target face, obtain the coordinate of the central point of second target face.
It is possible to further according to algorithm of convex hull, extract all in the target shaft tower cloud data and first water
Point intersecting plane M2, first object face S2 is generated by joining.Because the coordinate of each point is certain, therefore, can obtain
To the central point O2 in first object face coordinate (X4, Y4, Z3), Z3=Z2+h.
Step S145：Obtain the coordinate of projection of the central point of second target face on the first object face.
Wherein, projection line is parallel to Z axis.Project O21Coordinate is designated as (X5, Y5, Z2).
Step S146：The coordinate of central point based on the first object face, second target face central point seat
It is marked with and the coordinate of projection of the central point of second target face on the first object face, the target stem is calculated
The slope of tower.
Further, Fig. 4 is refer to, the central point O1 in first object face coordinate is (X2, Y2, Z2), described
The central point O2 of second target face coordinate is (X4, Y4, Z3), and the central point of second target face is in the first object face
On projection O21Coordinate be (X5, Y5, Z2), the target can be calculated based on formula S=h/d in the equipment of taking photo by plane
The slope S1 of shaft tower, whereinH=Z3-Z2.
Further, in order that obtaining result of calculation has more reliability, different reference points can be taken to calculate inclination again
Rate S2, then final shaft tower slope S=(S1+S2)/2.After tested, typically average can be substantially eliminated due to laser thunder twice
Up to error caused by cloud data skewness.
As a kind of embodiment, Fig. 5 is refer to, before step S120, methods described also includes：
Step S111：The laser radar data and view data are imported data processing software by the equipment of taking photo by plane,
Generate the cloud data and digital orthophoto map of transmission line of electricity.
The laser radar data of target shaft tower and view data can be imported into data processing software by equipment of taking photo by plane, complete
The pretreatment of paired laser radar data and view data, generates the cloud data of target shaft tower and digital positive photograph respectively
As figure.Wherein, Coordinate Conversion can be carried out to laser radar data, removes the operation such as noise spot.Pretreatment can eliminate data
Data error caused by being influenceed by factors such as systematic error, multipath effect, larger dust granules in gatherer process, disappears
Except redundancy point data, the preferable laser radar data of visual effect and image data are can obtain, shaft tower gradient is improved and measures knot
The accuracy of fruit.
Wherein, data processing software can be TerraSolid, the IE handled laser radar data, to picture number
According to PhotoScan, Pix4D handled etc..Above software is only for example, it will be understood that can be applied to the present invention and be implemented
The data processing software of example is not limited thereto.
Correspondingly, step S120：It is point cloud of the equipment of taking photo by plane based on direct linear transformation and Image registration mode, described
The cloud data and digital orthophoto map of transmission line of electricity, generate colour point clouds data.
A kind of shaft tower inclined degree detection method that the present embodiment provides, by equipment of taking photo by plane to the shaft tower that collects
View data and laser radar data are handled, and generate colour point clouds data, and use sorting algorithm, obtain target shaft tower
Cloud data, and by target shaft tower cloud data, the slope of the target shaft tower is calculated.With it, can be with
Realize that the automation of a wide range of inclination of electric power tower degree accurately measures, moreover it is possible to which the image conversion and digitlization for realizing measurement result are retouched
State, be easy to archive and final-period management, meanwhile, avoid the problem of existing measuring method workload is big, risk is high, efficiency is low.
Second embodiment
Fig. 6 is refer to, Fig. 6 is a kind of knot for shaft tower inclined degree detection means 400 that second embodiment of the invention provides
Structure block diagram.Described device is applied to equipment of taking photo by plane.The structured flowchart shown in Fig. 6 will be illustrated below, shown device includes：
First acquisition module 410, generation module 420, the second acquisition module 430 and computing module 440.
First acquisition module 410, for obtaining the laser radar data and view data of target shaft tower；
Generation module 420, for the point cloud based on direct linear transformation and Image registration mode, the laser radar data
And described image data, generate colour point clouds data；
Second acquisition module 430, for based on the machine learning classification algorithm pre-saved and sample data, obtaining mesh
Mark post tower cloud data；
Computing module 440, for according to the target shaft tower cloud data, the inclination of the target shaft tower to be calculated
Rate.
Wherein, Fig. 7 is refer to, second acquisition module 430 can include：
Submodule 431 is trained, for being obtained based on the machine learning classification algorithm pre-saved and sample data, training
The discriminant function of the characteristic vector of target shaft tower point cloud；
Computing submodule 432, for calculating the characteristic vector of the cloud data；
Classification submodule 433, for the characteristic vector to be met to, the cloud data of the discriminant function is categorized as
Target shaft tower cloud data.
The computing module 440 can include：
Acquisition submodule 441, for obtaining the first datum mark generation first level from the target shaft tower cloud data
Face；
Extracting sub-module 442, all in the target shaft tower cloud data intersect for extracting with the first level face
Point, generation first object face, obtain the coordinate of the central point in the first object face；
The acquisition submodule 441, it is additionally operable to from the target shaft tower cloud data, obtains and first datum mark
Vertical distance be preset value o'clock as the second datum mark, generate the second horizontal plane parallel to the first level face；
The extracting sub-module 442, it is additionally operable to extract all in the target shaft tower cloud data and the described second level
The intersecting point in face, generates the second target face, obtains the coordinate of the central point of second target face；
The acquisition submodule 441, it is additionally operable to obtain the central point of second target face on the first object face
Projection coordinate；
Calculating sub module 443, in the coordinate, second target face for the central point based on the first object face
The coordinate of the projection of the coordinate of heart point and the central point of second target face on the first object face, is calculated institute
State the slope of target shaft tower.
Wherein, the central point O1 in first object face coordinate is (X2, Y2, Z2), the center of second target face
Point O2 coordinate is (X4, Y4, Z3), the projection O2 of the central point of second target face on the first object face1Seat
It is designated as (X5, Y5, Z2), the slope S1 of the target shaft tower can be calculated in the calculating sub module based on S=h/d, its
InH=Z3-Z2.
In addition, as a kind of embodiment, Fig. 8 is refer to, described device can also include：
Import modul 450, for the laser radar data and view data to be imported into data processing software, generation is defeated
The cloud data and digital orthophoto map of electric line, correspondingly,
The generation module 420, for the point cloud based on direct linear transformation and Image registration mode, the transmission line of electricity
Cloud data and digital orthophoto map, generate colour point clouds data.
The present embodiment realizes the process of respective function to each functional unit of shaft tower inclined degree detection means 400, please join
Above-mentioned Fig. 1 is seen to the content described in embodiment illustrated in fig. 5, and here is omitted.
In summary, shaft tower inclined degree detection method provided in an embodiment of the present invention and device, by being set to taking photo by plane
Handled for the view data to the shaft tower collected and laser radar data, generate colour point clouds data, and use and divide
Class algorithm, target shaft tower cloud data is obtained, and by target shaft tower cloud data, the inclination of the target shaft tower is calculated
Rate.With it, it can realize that the automation of a wide range of inclination of electric power tower degree accurately measures, moreover it is possible to realize measurement result
Image conversion and digitized description, be easy to achieve and final-period management, meanwhile, avoid that existing measuring method workload is big, risk
High, the problem of efficiency is low.
In several embodiments provided herein, it should be understood that disclosed apparatus and method, can also pass through
Other modes are realized.Device embodiment described above is only schematical, for example, flow chart and block diagram in accompanying drawing
Show the device of multiple embodiments according to the present invention, method and computer program product architectural framework in the cards,
Function and operation.At this point, each square frame in flow chart or block diagram can represent the one of a module, program segment or code
Part, a part for the module, program segment or code include one or more and are used to realize holding for defined logic function
Row instruction.It should also be noted that at some as in the implementation replaced, the function that is marked in square frame can also with different from
The order marked in accompanying drawing occurs.For example, two continuous square frames can essentially perform substantially in parallel, they are sometimes
It can perform in the opposite order, this is depending on involved function.It is it is also noted that every in block diagram and/or flow chart
The combination of individual square frame and block diagram and/or the square frame in flow chart, function or the special base of action as defined in performing can be used
Realize, or can be realized with the combination of specialized hardware and computer instruction in the system of hardware.
In addition, each functional module in each embodiment of the present invention can integrate to form an independent portion
Point or modules individualism, can also two or more modules be integrated to form an independent part.
If the function is realized in the form of software function module and is used as independent production marketing or in use, can be with
It is stored in a computer read/write memory medium.Based on such understanding, technical scheme is substantially in other words
The part to be contributed to prior art or the part of the technical scheme can be embodied in the form of software product, the meter
Calculation machine software product is stored in a storage medium, including some instructions are causing a computer equipment (can be
People's computer, server, or network equipment etc.) perform all or part of step of each embodiment methods described of the present invention.
And foregoing storage medium includes：USB flash disk, mobile hard disk, read-only storage (ROM, Read-Only Memory), arbitrary access are deposited
Reservoir (RAM, Random Access Memory), magnetic disc or CD etc. are various can be with the medium of store program codes.Need
Illustrate, herein, such as first and second or the like relational terms be used merely to by an entity or operation with
Another entity or operation make a distinction, and not necessarily require or imply between these entities or operation any this reality be present
The relation or order on border.Moreover, term " comprising ", "comprising" or its any other variant are intended to the bag of nonexcludability
Contain, so that process, method, article or equipment including a series of elements not only include those key elements, but also including
The other element being not expressly set out, or also include for this process, method, article or the intrinsic key element of equipment.
In the absence of more restrictions, the key element limited by sentence "including a ...", it is not excluded that including the key element
Process, method, other identical element also be present in article or equipment.
The preferred embodiments of the present invention are the foregoing is only, are not intended to limit the invention, for the skill of this area
For art personnel, the present invention can have various modifications and variations.Within the spirit and principles of the invention, that is made any repaiies
Change, equivalent substitution, improvement etc., should be included in the scope of the protection.It should be noted that：Similar label and letter exists
Similar terms is represented in following accompanying drawing, therefore, once being defined in a certain Xiang Yi accompanying drawing, is then not required in subsequent accompanying drawing
It is further defined and explained.
The foregoing is only a specific embodiment of the invention, but protection scope of the present invention is not limited thereto, any
Those familiar with the art the invention discloses technical scope in, change or replacement can be readily occurred in, should all be contained
Cover within protection scope of the present invention.Therefore, protection scope of the present invention described should be defined by scope of the claims.
Claims (10)
1. a kind of shaft tower inclined degree detection method, it is characterised in that methods described is applied to equipment of taking photo by plane, methods described bag
Include：
The equipment of taking photo by plane obtains the laser radar data and view data of target shaft tower；
Point cloud and Image registration mode, the laser radar data and described image data based on direct linear transformation, it is raw
Into colour point clouds data；
Based on the machine learning classification algorithm pre-saved and sample data, target shaft tower cloud data is obtained；
According to the target shaft tower cloud data, the slope of the target shaft tower is calculated.
2. according to the method for claim 1, it is characterised in that it is described according to the target shaft tower cloud data, calculate
To the slope of the target shaft tower, including：
The equipment of taking photo by plane obtains the first datum mark generation first level face from the target shaft tower cloud data；
All points intersected with the first level face in the target shaft tower cloud data are extracted, generation first object face, are obtained
To the coordinate of the central point in the first object face；
From the target shaft tower cloud data, obtain and o'clock be used as the with the vertical distance of first datum mark for preset value
Two datum marks, generate the second horizontal plane parallel to the first level face；
All points intersected with second horizontal plane in the target shaft tower cloud data are extracted, the second target face is generated, obtains
To the coordinate of the central point of second target face；
Obtain the coordinate of projection of the central point of second target face on the first object face；
The coordinate of central point based on the first object face, second target face central point coordinate and described second
The coordinate of projection of the central point of target face on the first object face, the slope of the target shaft tower is calculated.
3. according to the method for claim 2, it is characterised in that the central point O1 in first object face coordinate for (X2,
Y2, Z2), the central point O2 of second target face coordinate is (X4, Y4, Z3), and the central point of second target face is in institute
State the projection O2 on first object face1Coordinate be (X5, Y5, Z2), the equipment of taking photo by plane is calculated described based on S=h/d
The slope S1 of target shaft tower, whereinH=Z3-Z2.
4. according to the method for claim 1, it is characterised in that in the point cloud based on direct linear transformation and Image registration side
Formula, the laser radar data and described image data, before generating colour point clouds data, methods described also includes：
The laser radar data and view data are imported data processing software by the equipment of taking photo by plane, and generate transmission line of electricity
Cloud data and digital orthophoto map；
Correspondingly, point cloud and Image registration mode, the point of the transmission line of electricity of the equipment of taking photo by plane based on direct linear transformation
Cloud data and digital orthophoto map, generate colour point clouds data.
5. according to the method for claim 1, it is characterised in that it is described based on the machine learning classification algorithm pre-saved with
And sample data, target shaft tower cloud data is obtained, including：
The equipment of taking photo by plane obtains target shaft tower point based on the machine learning classification algorithm pre-saved and sample data, training
The discriminant function of the characteristic vector of cloud；
Calculate the characteristic vector of the cloud data；
The characteristic vector is met that the cloud data of the discriminant function is categorized as target shaft tower cloud data.
6. a kind of shaft tower inclined degree detection means, it is characterised in that described device is applied to equipment of taking photo by plane, described device, bag
Include：
First acquisition module, for obtaining the laser radar data and view data of target shaft tower；
Generation module, for the point cloud based on direct linear transformation and Image registration mode, the laser radar data and institute
View data is stated, generates colour point clouds data；
Second acquisition module, for based on the machine learning classification algorithm pre-saved and sample data, obtaining target shaft tower
Cloud data；
Computing module, for the slope of the target shaft tower according to the target shaft tower cloud data, to be calculated.
7. device according to claim 6, it is characterised in that computing module, including：
Acquisition submodule, for obtaining the first datum mark generation first level face from the target shaft tower cloud data；
Extracting sub-module, it is raw for extracting all points intersected with the first level face in the target shaft tower cloud data
Into first object face, the coordinate of the central point in the first object face is obtained；
The acquisition submodule, it is additionally operable to from the target shaft tower cloud data, it is vertical with first datum mark to obtain
Distance is preset value o'clock as the second datum mark, generates the second horizontal plane parallel to the first level face；
The extracting sub-module, it is additionally operable to extract and all in the target shaft tower cloud data intersects with second horizontal plane
Point, the second target face is generated, obtains the coordinate of the central point of second target face；
The acquisition submodule, it is additionally operable to obtain projection of the central point of second target face on the first object face
Coordinate；
Calculating sub module, the central point of coordinate, second target face for the central point based on the first object face
The coordinate of the projection of coordinate and the central point of second target face on the first object face, is calculated the target
The slope of shaft tower.
8. device according to claim 7, it is characterised in that the central point O1 in first object face coordinate for (X2,
Y2, Z2), the central point O2 of second target face coordinate is (X4, Y4, Z3), and the central point of second target face is in institute
State the projection O2 on first object face1Coordinate be (X5, Y5, Z2), institute is calculated based on S=h/d in the calculating sub module
The slope S1 of target shaft tower is stated, whereinH=Z3-Z2.
9. device according to claim 6, it is characterised in that described device also includes：
Import modul, for the laser radar data and view data to be imported into data processing software, generate transmission line of electricity
Cloud data and digital orthophoto map；
Correspondingly, the generation module, for the point cloud based on direct linear transformation and Image registration mode, the transmission line of electricity
Cloud data and digital orthophoto map, generate colour point clouds data.
10. device according to claim 6, it is characterised in that second acquisition module, including：
Submodule is trained, for obtaining target stem based on the machine learning classification algorithm pre-saved and sample data, training
The discriminant function of the characteristic vector of tower point cloud；
Computing submodule, for calculating the characteristic vector of the cloud data；
Classification submodule, for the characteristic vector to be met to, the cloud data of the discriminant function is categorized as target shaft tower
Cloud data.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103017734A (en) * | 2012-12-11 | 2013-04-03 | 湖北省电力公司检修分公司 | Pole and tower gradient of slope measuring method based on laser radar |
| CN103779808A (en) * | 2013-12-30 | 2014-05-07 | 国家电网公司 | Power transmission line intelligent inspection system based on LiDAR |
| CN105333861A (en) * | 2015-12-02 | 2016-02-17 | 中国测绘科学研究院 | Pole and tower skew detection method and device based on laser-point cloud |
| CN106504362A (en) * | 2016-10-18 | 2017-03-15 | 国网湖北省电力公司检修公司 | Power transmission and transformation system method for inspecting based on unmanned plane |
-
2017
- 2017-08-07 CN CN201710666288.XA patent/CN107633504A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103017734A (en) * | 2012-12-11 | 2013-04-03 | 湖北省电力公司检修分公司 | Pole and tower gradient of slope measuring method based on laser radar |
| CN103779808A (en) * | 2013-12-30 | 2014-05-07 | 国家电网公司 | Power transmission line intelligent inspection system based on LiDAR |
| CN105333861A (en) * | 2015-12-02 | 2016-02-17 | 中国测绘科学研究院 | Pole and tower skew detection method and device based on laser-point cloud |
| CN106504362A (en) * | 2016-10-18 | 2017-03-15 | 国网湖北省电力公司检修公司 | Power transmission and transformation system method for inspecting based on unmanned plane |
Non-Patent Citations (3)
| Title |
|---|
| 《电子测量与仪器学报》: "基于地面激光雷达的输电线路铁塔倾斜度测量", 《电子测量与仪器学报》 * |
| 宋恒嘉: "车载激光点云和光学影像的配准方法研究", 《测绘通报》 * |
| 管海燕: "《中国博士学位论文全文数据库信息科技辑》", 《中国博士学位论文全文数据库信息科技辑》 * |
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