CN110084779A - A kind of extraction of aircraft thickness covering end surface features point and denoising method based on laser scanning - Google Patents
A kind of extraction of aircraft thickness covering end surface features point and denoising method based on laser scanning Download PDFInfo
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- CN110084779A CN110084779A CN201910160318.9A CN201910160318A CN110084779A CN 110084779 A CN110084779 A CN 110084779A CN 201910160318 A CN201910160318 A CN 201910160318A CN 110084779 A CN110084779 A CN 110084779A
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Abstract
The invention discloses a kind of extraction of aircraft thickness covering end surface features point and denoising method based on laser scanning, it is characterized in that scanning the side of thick covering first, characteristic point is extracted by point to plan range, boundary characteristic vertex neighborhood is found out then according to the Euclidean distance of other point to edge feature points in cloud, then denoising is carried out to edge feature point at sharp features and end face short side, finally the characteristic point lacked at sharp features is extracted again.The invention is characterized in that: 1) with the method for by single scan line extracting characteristic point compared with, the characteristic point stability that this method is extracted is more preferable and has degree of precision；2) it is directed to covering end face of different shapes, this method can obtain preferable characteristic point, offer precise data for end face fitting；3) easy to use, efficiency is higher.
Description
Technical field
The present invention relates to a kind of aircraft manufacturing technology, especially a kind of aircraft skin manufacturing technology is specifically a kind of
Aircraft thickness covering end surface features point based on laser scanning extracts and denoising method.
Background technique
It is well known that especially in zigzag covering process, adding in aircraft skin manufacturing process in order to make rational planning for
Work track needs opposite end Surface scan line data sorting and reconstructs end face.Repair amount is extracted using end face, and with end face and another piece
Friendship is asked in covering upper surface, is used for following process trajectory extraction.Extract the boundary of covering end face first when extracting point cloud characteristic point
Characteristic point mainly uses curvature pole currently, there is many scholars to study the boundary characteristic identification of measurement data both at home and abroad
Value method: Milroy M.J and Yang estimates the curvature value of point cloud data using the quadratic polynomial curved surface in local coordinate system,
Point with extreme curvature is found out, boundary point is therefrom extracted；Hu Xin et al. is every in estimation point cloud using the gradient solving method in image procossing
The method resultant curvature of a point, obtains candidate boundary point by threshold value, and main problem existing for these methods is the stabilization of characteristic point
The problem of property is poor, and precision is not high, low efficiency.And scan line point cloud has order, can extract side to plan range according to point
Boundary's characteristic point is a kind of effective method.
Summary of the invention
The purpose of the present invention is for existing covering end surface features point extracting method, that there are stability is poor, precision is not high,
The problem of low efficiency, combining laser scanning technology invent a kind of aircraft thickness covering end surface features point extraction based on laser scanning
With denoising method.
The technical scheme is that
A kind of extraction of aircraft thickness covering end surface features point and denoising method based on laser scanning, it is characterised in that it includes
Following steps
1) edge feature point is extracted to plan range by point in the side for scanning thick covering；
2) boundary characteristic vertex neighborhood is found out according to the Euclidean distance of other point to edge feature points in cloud, then to sharp
Edge feature point carries out denoising at feature and end face short side；
3) characteristic point lacked at sharp features is extracted again.
The Euclidean distance that other points in point cloud arrive edge feature point is calculated, these are then pressed into Euclidean distance ascending order row
Column, use radius r to intercept nearest point as neighborhood, by the angle between edge feature point and neighborhood point subpoint line to sharp
The denoising of the edge feature point of feature and end face.
The boundary characteristic point extracting method is:
Piecemeal processing is carried out to the scanning result of covering, M scan line is extracted every time and is handled, M value be 20-50 it
Between, point P in scan line is first extracted when seeking side edge feature pointi,j(0≤i≤29,4≤j≤24) fit a plane side
Journey is the plane of Ax+By+Cz=D；N point of single scan line (n in every scan line is not necessarily equal), if dj0、dj1、dj2
Respectively adjacent 3 points Pj、Pj+1、Pj+2To the distance of plane, a fixed threshold value is δ；It recycles formula (1) to calculate point and arrives plane
Distance, Pj、Pj+1、Pj+2Distance to plane is respectively dj0、dj1、dj2；J is gradually increased by 0 at this time, works as dj0、dj1、dj2For the first time
P when less than threshold valuejFor edge feature point, if edge feature point is jth in single scan line ' a point at this time；Seek another side
When boundary's characteristic point, j is gradually reduced by n-2, works as dj0、dj1、dj2P when being respectively less than threshold value for the first timej+2For edge feature point, if at this time
Edge feature point is jth '+k points in single scan line；Finding out two sides edge feature point is Pj'And Pj'+k, extract every scanning
Point P on linej'、Pj'+[k/3]、Pj'+[2*k/3]、Pj'+kAs characteristic point；
The edge feature point denoising method is: first calculate point cloud in other point to edge feature point it is European away from
From, then by these press Euclidean distance ascending order arrangement, use radius r to intercept nearest point as NrNeighborhood passes through boundary characteristic
Angle between point and neighborhood point subpoint line judges whether the edge feature point removes；It is uncertain due to what is counted in neighborhood
Property, using list structure storing data, by the N of edge feature point PrNeighborhood point is orderly stored in chained list _ nrlist (P, rs) in,
Radius of neighbourhood rsIt is set as 3~5 times of a spacing；Then judge whether edge feature point should remove, the specific steps are as follows:
Point fit Plane in step 1 neighborhood, neighborhood point project in plane；
Step 2 is ranked up subpoint；
Step 3 fillet characteristic point and subpoint seek the angle theta between adjacent straight line；
Step 4 analyzes angle theta, finds out maximum angle θmax, work as θmaxEdge feature point is located at point cloud at 120 ° of <
Inside edge feature point and should remove at this time with the characteristic point on the same straight line of edge feature point；Otherwise boundary characteristic point
In point cloud boundary, it should retain.
The characteristic point is extracted again refer to edge feature point denoising after point missing at sharp features, need again from removal
Edge feature point in extract；One threshold δ is set, removal edge feature point and characteristic point P are askedjDistance DjIf Dj< δ is then mentioned
Take the edge feature point；Then removal edge feature point and characteristic point P are askedj+k/3、Pj+2*k/3、Pj+kDistance simultaneously extracts corresponding boundary
Characteristic point is characterized a little.
Beneficial effects of the present invention:
1) compared with the method for extracting characteristic point by single scan line, the characteristic point stability that this method is extracted is more preferable and has
Degree of precision；
2) it is directed to covering end face of different shapes, this method can obtain preferable characteristic point, provide for end face fitting
Accurate data；
3) easy to use, efficiency is higher.
Detailed description of the invention
Fig. 1 is that edge feature point extracts schematic diagram.
Fig. 2 is edge feature point recognition methods.
Fig. 3 shows edge feature point at short side and sharp features.
Fig. 4 is edge feature point denoising.
Fig. 5 shows missing characteristic point missing at sharp features.
Specific embodiment
The present invention is further illustrated with reference to the accompanying drawings and examples.
As shown in Figs. 1-5.
A kind of extraction of aircraft thickness covering end surface features point and denoising method based on laser scanning, it is characterised in that: including
Following steps
1) characteristic point is extracted to plan range by point in the side for scanning thick covering；
2) boundary characteristic vertex neighborhood is found out according to the Euclidean distance of other point to edge feature points in cloud, then to sharp
Edge feature point carries out denoising at feature and end face short side；
3) characteristic point lacked at sharp features is extracted.
Specific computation is as follows:
1) feature point extraction:
Piecemeal processing is carried out to the scanning result of covering A, 30 (can also between 20-50 item arbitrary number) be extracted every time and sweeps
It retouches line to be handled, point P in scan line is first extracted when seeking side edge feature pointi,j(0≤i≤29,4≤j≤24) fit
Plane A, B, C, D that one plane equation is Ax+By+Cz=D are respectively that fit Plane calculates resulting constant, such as Fig. 1 (a)；
N point of single scan line (n in every scan line is not necessarily equal), such as Fig. 1 (b), if dj0、dj1、dj2It is 3 points respectively adjacent
Pj、Pj+1、Pj+2To the distance of plane, a fixed threshold value is δ；It recycles formula (1) to calculate point and arrives plan range, Pj、Pj+1、Pj+2
Distance to plane is respectively dj0、dj1、dj2；J is gradually increased by 0 at this time, works as dj0、dj1、dj2P when being respectively less than threshold value for the first timejFor
Edge feature point, if edge feature point is jth ' a point in single scan line at this time；When seeking other side edge feature point, by j
It is gradually reduced by n-2, works as dj0、dj1、dj2P when being respectively less than threshold value for the first timej+2For edge feature point, if edge feature point is single at this time
Jth '+k points in scan line；Finding out two sides edge feature point is Pj'And Pj'+k, extract point P in every scan linej'、
Pj'+[k/3]、Pj'+[2*k/3]、Pj'+kAs characteristic point；
2) edge feature point denoises:
When scanning covering interface, it will appear scanning situation as shown in Figure 3 at interface short side and sharp features, this
When the edge feature point that extracts be located on lateral inner or interface short side, denoised.First to point Yun Jinhang before denoising
It deletes, the point between edge feature point and edge feature point is taken in every scan line and extracts the point of side.In order to which aspect denoises,
Individually scanning covering side after extraction edge feature point also is located at interface short side coboundary characteristic point inside cloud, at this time
Two kinds of situations are considered as a kind of situation.
The Euclidean distance that other points in point cloud arrive edge feature point is calculated first, these are then pressed into Euclidean distance ascending order
Arrangement, uses radius r to intercept nearest point as NrNeighborhood is sentenced by the angle between edge feature point and neighborhood point subpoint line
Whether the edge feature point that breaks removes.Due to the uncertainty counted in neighborhood, using list structure storing data, by boundary spy
Levy the N of point PrNeighborhood point is orderly stored in chained list _ nrlist (P, rs) in, radius of neighbourhood rsIt is usually arranged as the 3~5 of a spacing
Times.Then judge whether edge feature point should remove, the specific steps are as follows:
Point fit Plane in step 1 neighborhood, neighborhood point project in plane.
Step 2 is ranked up subpoint.
Step 3 fillet characteristic point and subpoint seek the angle theta between adjacent straight line.
Step 4 analyzes angle theta, finds out maximum angle θmax, work as θmaxEdge feature point is located at point cloud at 120 ° of <
Inside edge feature point and should remove at this time with the characteristic point on the same straight line of edge feature point；Otherwise boundary characteristic point
In point cloud boundary, it should retain, such as Fig. 4.
3) characteristic point is extracted again
Point missing at sharp features, needs the edge feature point again from removal after edge feature point denoising as shown in Figure 5
Middle extraction.One threshold δ is set, removal edge feature point and characteristic point P are askedjDistance DjIf Dj< δ then extracts the boundary characteristic
Point.Then removal edge feature point and characteristic point P are askedj+k/3、Pj+2*k/3、Pj+kDistance is simultaneously extracted corresponding edge feature point and is characterized
Point.
Part that the present invention does not relate to is the same as those in the prior art or can be realized by using the prior art.
Claims (6)
1. a kind of aircraft thickness covering end surface features point based on laser scanning extracts and denoising method, it is characterised in that it includes such as
Lower step
1) edge feature point is extracted to plan range by point in the side for scanning thick covering；
2) boundary characteristic vertex neighborhood is found out according to the Euclidean distance of other point to edge feature points in cloud, then to sharp features
And edge feature point carries out denoising at the short side of end face；
3) characteristic point lacked at sharp features is extracted again.
2. the aircraft thickness covering end surface features point according to claim 1 based on laser scanning extracts and denoising method,
It is characterized in that, calculates the Euclidean distance that other points in point cloud arrive edge feature point, these are then pressed into Euclidean distance ascending order row
Column, use radius r to intercept nearest point as neighborhood, by the angle between edge feature point and neighborhood point subpoint line to sharp
The denoising of the edge feature point of feature and end face.
3. the aircraft thickness covering end surface features point according to claim 2 based on laser scanning extracts and denoising method,
It is characterized in that, characteristic point is extracted again at sharp features.
4. the aircraft thickness covering end surface features point according to claim 1 based on laser scanning extracts and denoising method,
Being characterized in that the boundary characteristic point extracting method is:
Piecemeal processing is carried out to the scanning result of covering, M scan line is extracted every time and is handled, M value between 20-50,
Point P in scan line is first extracted when seeking side edge feature pointi,j(0≤i≤29,4≤j≤24) fit a plane equation
For the plane of Ax+By+Cz=D；N point of single scan line (n in every scan line is not necessarily equal), if dj0、dj1、dj2Point
It Wei not adjacent 3 points Pj、Pj+1、Pj+2To the distance of plane, a fixed threshold value is δ；It recycles formula (1) to calculate point and arrives plane separation
From Pj、Pj+1、Pj+2Distance to plane is respectively dj0、dj1、dj2；J is gradually increased by 0 at this time, works as dj0、dj1、dj2It is small for the first time
P when threshold valuejFor edge feature point, if edge feature point is jth in single scan line ' a point at this time；Seek another lateral boundaries
When characteristic point, j is gradually reduced by n-2, works as dj0、dj1、dj2P when being respectively less than threshold value for the first timej+2For edge feature point, if side at this time
Boundary's characteristic point is jth '+k points in single scan line；Finding out two sides edge feature point is Pj'And Pj'+k, extract every scan line
Upper Pj'、Pj'+[k/3]、Pj'+[2*k/3]、Pj'+kAs characteristic point；
5. the aircraft thickness covering end surface features point according to claim 1 based on laser scanning extracts and denoising method,
Being characterized in that the edge feature point denoising method is: calculate first other points in point cloud to edge feature point it is European away from
From, then by these press Euclidean distance ascending order arrangement, use radius r to intercept nearest point as NrNeighborhood passes through boundary characteristic
Angle between point and neighborhood point subpoint line judges whether the edge feature point removes；It is uncertain due to what is counted in neighborhood
Property, using list structure storing data, by the N of edge feature point PrNeighborhood point is orderly stored in chained list _ nrlist (P, rs) in,
Radius of neighbourhood rsIt is set as 3~5 times of a spacing；Then judge whether edge feature point should remove, the specific steps are as follows:
Point fit Plane in step 1 neighborhood, neighborhood point project in plane；
Step 2 is ranked up subpoint；
Step 3 fillet characteristic point and subpoint seek the angle theta between adjacent straight line；
Step 4 analyzes angle theta, finds out maximum angle θmax, work as θmaxEdge feature point is located inside point cloud at 120 ° of <,
It edge feature point and should be removed with the characteristic point on the same straight line of edge feature point at this time；Otherwise edge feature point is located at point cloud
Boundary, it should retain.
6. the aircraft thickness covering end surface features point according to claim 1 based on laser scanning extracts and denoising method,
Be characterized in that the characteristic point extract again refer to edge feature point denoising after point missing at sharp features, need again from removal
Edge feature point in extract；One threshold δ is set, removal edge feature point and characteristic point P are askedjDistance DjIf Dj< δ is then mentioned
Take the edge feature point；Then removal edge feature point and characteristic point P are askedj+k/3、Pj+2*k/3、Pj+kDistance simultaneously extracts corresponding boundary
Characteristic point is characterized a little.
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