CN108801171A - A kind of tunnel cross-section deformation analytical method and device - Google Patents
A kind of tunnel cross-section deformation analytical method and device Download PDFInfo
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Abstract
The present invention discloses a kind of tunnel cross-section deformation analytical method, and method includes：Tunnel cross-section information is acquired, to obtain point cloud data collection；The point cloud data collection that tunnel cross-section to be detected is acquired in different times is analyzed and compared, with the deformation tendency of determination tunnel cross-section to be detected.Thus, the section information of tunnel different times can be visualized, the deformation of section, trend whole and that comprehensively detection tunnel cross-section changes over time are determined by the comparison of point cloud data collection, and the measurement accuracy of the application is higher, measurement method is relatively simple to be easy to implement.
Description
Technical field
The present invention relates to Tunnel testing technical fields, in particular to a kind of tunnel cross-section deformation analytical method and dress
It sets.
Background technology
With the continuous improvement of the level of urbanization, urban population also increases sharply, and causes traffic congestion, environmental pollution etc.
A series of problems.City underground has obtained rapid development as a kind of tool for alleviating urban traffic congestion pressure.
Since city underground circuit generally can all pass through main arterial highway and populous center, in applying for subway
It can cause the deformation of subterranean tunnel itself, pipeline and surrounding building during work.Meanwhile subway is in the process of running due to soil
Vertical displacement, horizontal displacement, crack etc. caused by load of the property, underground water and above ground structure of body itself to tunnel
Deformation, in some locations, deformation may be it is obvious that if carry out deformation monitoring not in time, and divides monitoring data
Analysis, it will cause unthinkable serious consequences.
The formulation of deformation monitoring scheme is to carry out the precondition of Deformation Prediction with implementation, is the weight of whole process informationization
Link is wanted, there is great influence to Deformation Prediction, and formulating a rational monitoring scheme is that subway construction progress is normal, has
The essential condition of sequence construction, also provides experience for the construction of similar engineering, avoids the generation of risk and accident.Due to metro operation
Stage because time span is big, influence factor is complicated, disaster social influence is big, therefore to subway work carry out deformation monitoring must be
Long-term, and be continuous.
Wherein, urban subway subway cross section deformation monitoring is a particularly significant and complicated system engineering, monitoring
The design of scheme is the substance in entire monitoring process, and monitoring content is mainly the vertical sedimentation in tunnel, horizontal displacement
The single data target with the convergent deformation of section etc., it is more difficult to reflect global tunnel deformation situation.Method mostly uses entirely at present
Instrument of standing is chosen limited a discrete point on section and is measured, although the measurement accuracy of this total powerstation is higher, measures
Discrete point is difficult to reflect the whole deformation of tunnel cross-section, and at present monitoring method to the analyses of monitoring data and processing with
And it is also perfect not to the utmost to the analysis method of deformation data.
Currently, for that cannot reflect the whole and local situation of change of tunnel cross-section and tunnel cross-section simultaneously in the prior art
At any time the problem of deformation tendency, effective solution scheme is not yet proposed.
Invention content
A kind of tunnel cross-section deformation analytical method of offer of the embodiment of the present invention and device, can solve in the prior art cannot
Reflect simultaneously the whole and local situation of change of tunnel cross-section and tunnel cross-section at any time deformation tendency the problem of.
In order to solve the above technical problems, in a first aspect, the embodiment of the present invention provides a kind of tunnel cross-section deformation analytical method,
The method includes：
Step 1, tunnel cross-section information is acquired, to obtain point cloud data collection；
Step 2, the point cloud data collection that tunnel cross-section to be detected is acquired in different times is analyzed and is compared, with determination
The deformation tendency of the tunnel cross-section to be detected.
Further, step 1 includes：
Step 11, the side same tunnel cross-section to be detected of different times being scanned by three-dimensional laser scanner
Formula acquires tunnel cross-section information；According to the point cloud data collection P in two periods of the tunnel cross-section acquisition of information1And P2。
Further, step 2 includes：
Step 21, round fitting is carried out respectively in respective coordinate system to the point cloud data collection in two periods, with true respectively
The center of circle of fixed two point cloud data collection；
Step 22, two point cloud data collection are placed under the same coordinate system, then overlap the center of circle, with to two cloud numbers
The first registration is carried out according to collection；
Step 23, two point cloud data collection after being registrated according to ICP algorithm pair first carry out the second registration；
Step 24, selected at random wherein a phase point cloud data collection is as datum mark cloud data set, using ANN algorithm another
Phase point cloud data is concentrated, and determines the corresponding points of each datum mark respectively；
Step 25, the relationship for analyzing each pair of datum mark and corresponding points, with the deformation tendency of determination tunnel cross-section to be detected；
Wherein, the datum mark is the point in the datum mark cloud data set.
Further, the step 21, specifically includes：According to the point cloud data collection in two periods of least square method pair each
From coordinate system in carry out round fitting respectively.
Further, step 23 includes：
Step 231, point cloud data collection P is calculated2In each point in point cloud data collection P1In correspondence neighbor point, to obtain
Take first group of N number of corresponding points pair；
Step 232, it determines so that the distance of first group of N number of corresponding points pair and minimum translation parametersAnd rotation parameter
Wherein, the translation parametersAnd rotation parameterFor the parameter in rigid body translation；
Step 233, when the distance of first group of N number of corresponding points pair and when more than or equal to pre-determined distance, according to described cloud
Data set P2, the translation parametersAnd rotation parameterDetermine point cloud data collection P '2；Calculate point cloud data collection P '2In it is each
A point is in point cloud data collection P1In correspondence neighbor point, to obtain second group of N number of corresponding points pair；
Step 234, it when the distance of second group of N number of corresponding points pair and when more than or equal to the pre-determined distance, redefines
New point cloud data collection is simultaneously iterated calculating, until the distance of i-th group of corresponding points pair is less than pre-determined distance.
Further, the step 231, specifically includes：According to preset condition, and using KD-tree structures in P1In really
Determine P2Each point correspondence point of proximity, composition corresponding points to set { (P1, i, P2, i| i=1,2 ..., N) }；
Wherein, preset condition is：ε(P1, P2)=min (d2(P1, iP2, i))；P1, iWith P2, iFor i-th group of corresponding points pair, P1, i
Belong to P1, P2, iBelong to P2。
Further, the step 232, specifically includes：Step 2321, by N number of corresponding points to substituting into object function；It is logical
It crosses iterative algorithm and determines rigid body translation matrixTo determine so that the distance of corresponding points pair and minimum translation parametersWith
Rotation parameter
Wherein, target function value be N number of corresponding points pair distance and, formula is：
Wherein, N P1The number at midpoint, P1, iWith P2, iFor i-th group of corresponding points pair, P1, iBelong to P1, P2, iBelong to P2。It is 3
× 1 translation matrix,For 3 × 3 spin matrix.
Further, target function value be N number of corresponding points pair distance and, formula is：
Wherein, N P1The number at midpoint, P1, iWith P2, iFor i-th group of corresponding points pair, P1, iBelong to P1, P2, iBelong to P2。It is 3
× 1 translation matrix,For 3 × 3 spin matrix, wiTo constrain weight factor.
Further,
Wherein, DDFk(p) deviation factors for being point p,For the regularization standard deviation of point p.
Further, the step 231 further includes：Delete the corresponding points pair that distance is more than distance threshold.
Further, the distance of corresponding points pair is throwing of the Euclidean distance of point-to-point transmission on the radius extended line for overlapping the center of circle
Shadow distance.
Second aspect, the embodiment of the present invention provide a kind of tunnel cross-section deformation analysis device, and described device is applied to first
In method described in aspect, described device includes：
Collecting unit, for acquiring tunnel cross-section information, to obtain point cloud data collection；
Comparative analysis unit, the point cloud data collection for acquiring tunnel cross-section to be detected in different times carry out analysis and
Comparison, with the deformation tendency of the determination tunnel cross-section to be detected.
Further, the collecting unit is additionally operable to through three-dimensional laser scanner to the same to be detected of different times
The mode that tunnel cross-section is scanned acquires tunnel cross-section information；According to the point in two periods of the tunnel cross-section acquisition of information
Cloud data set P1And P2。
Further, the comparative analysis unit is additionally operable to the point cloud data collection in two periods in respective coordinate system
It is middle to carry out round fitting respectively, to determine the center of circle of two point cloud data collection respectively；Two point cloud data collection are placed in same coordinate
Under system, then the center of circle is overlapped, to carry out the first registration to two point cloud data collection；After being registrated according to ICP algorithm pair first
Two point cloud data collection carry out the second registration；A selected wherein phase point cloud data collection is utilized as datum mark cloud data set at random
ANN algorithm is concentrated in another phase point cloud data, determines the corresponding points of each datum mark respectively；Analyze each pair of datum mark and corresponding points
Relationship, with the deformation tendency of determination tunnel cross-section to be detected；Wherein, the datum mark is in the datum mark cloud data set
Point.
It applies the technical scheme of the present invention, the section information of tunnel different times can be visualized, be passed through
Point cloud data collection comparison determine section deformation, with realize to tunnel cross-section change over time trend entirety and comprehensively
Detection, and the measurement accuracy of the application is higher, and measurement method is relatively simple is easy to implement.
Description of the drawings
Fig. 1 is a kind of flow chart of tunnel cross-section deformation analytical method according to the ... of the embodiment of the present invention；
Fig. 2 is a kind of flow chart of tunnel cross-section deformation analytical method according to the ... of the embodiment of the present invention；
Fig. 3 is a kind of flow chart of tunnel cross-section deformation analytical method according to the ... of the embodiment of the present invention；
Fig. 4 is a kind of flow chart of tunnel cross-section deformation analytical method according to the ... of the embodiment of the present invention；
Fig. 5 is the calculating schematic diagram of distance between a kind of corresponding points pair according to the ... of the embodiment of the present invention；
Fig. 6 is schematic diagram of the two phases point cloud data collection according to the ... of the embodiment of the present invention after the first registration；
Fig. 7 is schematic diagram of the two phases point cloud data collection according to the ... of the embodiment of the present invention after the second phase is registrated；
Fig. 8 is a kind of global deformation tendency schematic diagram of tunnel cross-section to be detected according to the ... of the embodiment of the present invention；
Fig. 9 is that the global deformation result that a kind of true tunnel cross-section to be detected according to the ... of the embodiment of the present invention calculates gained is shown
It is intended to；
Figure 10 is a kind of structure diagram of tunnel cross-section deformation analysis device according to the ... of the embodiment of the present invention.
Specific implementation mode
Present invention is further described in detail in the following with reference to the drawings and specific embodiments, it should be understood that described herein
Specific embodiment be only used to explain the present invention, be not intended to limit the present invention.
In subsequent description, using for indicating that the suffix of such as " module ", " component " or " unit " of element is only
The explanation for being conducive to the present invention, itself does not have a specific meaning.Therefore, " module ", " component " or " unit " can mix
Ground uses.
In order to solve simultaneously reflect in the prior art the whole and local situation of change of tunnel cross-section and tunnel cross-section
At any time the problem of deformation tendency, the embodiment of the present invention provides a kind of tunnel cross-section deformation analytical method, and method includes：
Step 1, tunnel cross-section information is acquired, to obtain point cloud data collection；
Step 2, the point cloud data collection that tunnel cross-section to be detected is acquired in different times is analyzed and is compared, with determination
The deformation tendency of tunnel cross-section to be detected.
It applies the technical scheme of the present invention, the section information of tunnel different times can be visualized, be passed through
Point cloud data collection comparison determine section deformation, with realize to tunnel cross-section change over time trend entirety and comprehensively
Detection.And the measurement accuracy of the application is higher, and measurement method is relatively simple is easy to implement.
In one possible implementation, as shown in Fig. 2, step 1 includes：
Step 11, the side same tunnel cross-section to be detected of different times being scanned by three-dimensional laser scanner
Formula acquires tunnel cross-section information；According to the point cloud data collection P in two periods of tunnel cross-section acquisition of information1And P2。
It is understood that the data of three-dimensional laser scanner acquisition are more fully and acquisition precision is higher, tunnel to be detected
Road section can be subway tunnel section, can be swept in different times to same place tunnel cross-section by three-dimensional laser scanner
It retouches.The application is introduced so that the scanning result to two periods compares and analyzes as an example.
In one possible implementation, as shown in figure 3, step 2 includes：
Step 21, round fitting is carried out respectively in respective coordinate system to the point cloud data collection in two periods, with true respectively
The center of circle of fixed two point cloud data collection；
Wherein, step 21, it specifically includes：According to the point cloud data collection in two periods of least square method pair in respective coordinate
Round fitting is carried out in system respectively.
It should be noted that approximating method is not limited to least square method, point cloud data collection is fitted to song as long as can reach
The effect of line.
Step 22, two point cloud data collection are placed under the same coordinate system, the center of circle is overlapped, with to two point cloud data collection
Carry out the first registration；
Wherein, the first registration can be regarded as preliminary registration, and schematic diagram of the two phase point cloud data collection after the first registration can
With reference to figure 6.
Step 23, it is registrated according to ICP (Iterative Closest Point, iteration closest approach algorithm) algorithm pair first
Two point cloud data collection afterwards carry out the second registration；And two phase point cloud data collection second registration after schematic diagram can refer to Fig. 7.
Wherein, the second registration is more accurate compared with the first registration, and two can be obtained in the same coordinate system using ICP algorithm
The optimal registration position of a point cloud data collection, it is understood that be optimal registration image.
Step 24, a selected wherein phase point cloud data collection utilizes ANN as datum mark cloud data set at random)
(Approximate Nearest Neighbor, approximate KNN) algorithm is concentrated in another phase point cloud data, is determined respectively every
The corresponding points of a datum mark；
Step 25, the relationship for analyzing each pair of datum mark and corresponding points, with the deformation tendency of determination tunnel cross-section to be detected；Its
In, the point of point cloud data concentration on the basis of datum mark.
Using high-precision three-dimensional laser scanner, then by ICP method for registering to two issues of tunnel cross-section measurement according into
Then two phase point clouds are carried out neighbor point correspondence, so as to be placed on the section configuration of tunnel different times by row splicing registration
It is visualized under the same coordinate system, determines the deformation of section, it can be achieved that tunnel by the comparison between corresponding points
The entirety of cross section deformation situation and comprehensive detection.
In one possible implementation, as shown in figure 4, step 23 includes：
Step 231, point cloud data collection P is calculated2In each point in point cloud data collection P1In correspondence neighbor point, to obtain
Take first group of N number of corresponding points pair；
Step 231, it specifically includes：According to preset condition, and using KD-tree structures in P1Middle determining P2Each point
Correspondence point of proximity, composition corresponding points to set { (P1, i, P2, i| i=1,2 ..., N) }；
Wherein, preset condition is：ε(P1, P2)=min (d2(P1, iP2, i))；P1, iWith P2, iFor i-th group of corresponding points pair, P1, i
Belong to P1, P2, iBelong to P2。
That is so that ε (P1, P2) minimum P1, iP2, iThe corresponding points pair exactly found.
Step 231 further includes：Delete the corresponding points pair that distance is more than distance threshold.
During determining corresponding points pair, by distance calculate by point pair between the big distance of distance in threshold value point to carry out
It rejects, removes ineligible point pair, influence when it calculates succeeding target function can be eliminated, to promote registration essence
Degree.
In one possible implementation, the distance of corresponding points pair is that the Euclidean distance of point-to-point transmission is overlapping the half of the center of circle
Projector distance on diameter extended line.The method that calculating corresponding points are adjusted the distance can regard a kind of improvement to ICP algorithm as, in original
On the basis of having algorithm, in calculating target function, the error of original point-to-point is measured into mode and is changed to a little along radius side
Upward distance, the i.e. error of point-to-point transmission are projector distance of its Euclidean distance on radius extended line.As shown in figure 5, the party
Method is according to tunnel cross-section point cloud is generally circular and its subsequent deformation feature is calculated into row distance, so as to obtain optimal point
Cloud registration result.
Step 232, it determines so that the distance of first group of N number of corresponding points pair and minimum translation parametersAnd rotation parameterWherein, translation parametersAnd rotation parameterFor the parameter in rigid body translation；
Wherein, step 232, it specifically includes：Step 2321, by N number of corresponding points to substituting into object function；It is calculated by iteration
Method determines rigid body translation matrixTo determine so that the distance of corresponding points pair and minimum translation parametersAnd rotation parameter
Wherein, target function value be N number of corresponding points pair distance and, formula is：
Wherein, N P1The number at midpoint, P1, iWith P2, iFor i-th group of corresponding points pair, P1, iBelong to P1, P2, iBelong to P2。It is 3
× 1 translation matrix,For 3 × 3 spin matrix.Object function can also be denoted as error function.
Step 233, when the distance of first group of N number of corresponding points pair and when more than or equal to pre-determined distance, according to point cloud data
Collect P2, translation parametersAnd rotation parameterDetermine point cloud data collection P '2；Calculate point cloud data collection P '2In each point point
Cloud data set P1In correspondence neighbor point, to obtain second group of N number of corresponding points pair；
Step 234, it when the distance of second group of N number of corresponding points pair and when more than or equal to pre-determined distance, redefines new
Point cloud data collection is simultaneously iterated calculating, until the distance of i-th group of corresponding points pair is less than pre-determined distance.
Unlike the formula of above-mentioned object function, in one possible implementation, target function value is N number of right
The distance that should put pair and, formula can be：
Wherein, N P1The number at midpoint, P1, iWith P2, iFor i-th group of corresponding points pair, P1, iBelong to P1, P2, iBelong to P2。It is 3
× 1 translation matrix,For 3 × 3 spin matrix, wiTo constrain weight factor.
Wherein, DDFk(p) deviation factors for being point p,For the regularization standard deviation of point p.In order to eliminate off
The influence that group's point and noise spot calculate object function, needs to each corresponding points to distributing different weights.Such as：It is judged as
The corresponding points pair of noise or outlier smaller weight are arranged for it, to reduce abnormal corresponding points to being caused to registration accuracy
Influence, improve registration accuracy.
It briefly introduces below to the weight factor introduced in the application.
In practical engineering application, the different zones of registration model often have different importances.It is right that the application passes through
Corresponding points are to applying different weights, the registration accuracy of model important area is constrained and ensured using weights.Existing
In research, mainly to distinguish whether point set participates in being registrated, weights only have 0 and 1 for the setting of weights.This mode is easy to weed out
Normal corresponding points pair, reduce the precision of registration.Weight factor w is introduced as a result,i, original error function is improved,
Formula is as follows：
Constraint weight factor is defined as participating in the significance level of the point set of registration, can be obtained by minimizing the error function
Obtain translation parametersAnd rotation parameterMethod is as shown in Figure 4.In order to reduce abnormal corresponding points shadow caused by registration accuracy
It rings, the size that the corresponding weight factor of point cloud data collection should be measured with abnormal point is inversely proportional, i.e., the point is the possibility of abnormal point
Bigger, then the corresponding weight factor of point should be smaller.Abnormal point metric function N (p) is introduced as a result, p is current measurement point,
Weight factor is expressed asIn order to enable metric function correctly to reflect, point p is the possibility of abnormal point, will be measured
Function is defined as：
Wherein DDFk(p) deviation factors for being point p,For the regularization standard deviation of point p.The two distinguishes table
It is shown as：
It is expressed as：
Wherein Nkd(q) it indicates and k closest point q point, Nkd(p) it indicates and k closest point p point.Pass through a little
Correlation between p and surrounding neighbor point is inferred to the probability size that point p belongs to abnormal point.And this probability value is turned into point p
Distance calculate weight be brought into final object function.Recycle svd algorithm, you can to minimizing the target letter of Weight
Number is solved, and the rotation transformation R and translation transformation T between two section point clouds subject to registration is calculated.
It introduces weights in object function to be constrained, using the direction of search of control of right optimization algorithm, so as to have
Effect ensures the registration accuracy of normal region, reduces influence of the abnormal point to registration accuracy.Subway tunnel is carried out in different times
When scanning, the position of three-dimensional laser scanner can not be fixed, two phase section point cloud data Ji Chu of same position in subway tunnel
In two different coordinate systems.It, can be by least square fitting annulus, tentatively since subway tunnel section is substantially close to circle
Two phase section point cloud circles are overlapped by the center of circle for determining section point cloud in the same coordinate system, you can realize two phase section point clouds
Preliminary registration.Using improved ICP algorithm, by introducing the concept of weights constraint, by more important in registration point cloud
Region assign higher weight, so as to obtain the high registration accuracy of two phase section point clouds.Finally by two phase point cloud numbers
It is that can be appreciated that comprehensive deformation (can refer to Fig. 8 and Fig. 9) of tunnel cross-section according to the distance between the corresponding points pair of collection.
The embodiment of the present invention also provides a kind of tunnel cross-section deformation analysis device, and device is for executing shown in above-described embodiment
Method, as shown in Figure 10, which includes：
Collecting unit 901, for acquiring tunnel cross-section information, to obtain point cloud data collection；
Comparative analysis unit 902, the point cloud data collection for acquiring tunnel cross-section to be detected in different times are divided
Analysis and comparison, with the deformation tendency of determination tunnel cross-section to be detected.
The section information of tunnel different times can be visualized, be determined by the comparison of point cloud data collection disconnected
The deformation in face changes over time the entirety of trend and comprehensive detection to realize to tunnel cross-section.And the measurement of the application
Precision is higher, and measurement method is relatively simple is easy to implement.
In one possible implementation, collecting unit 901 are additionally operable to through three-dimensional laser scanner to different times
The mode that is scanned of same tunnel cross-section to be detected, acquire tunnel cross-section information；According to tunnel cross-section acquisition of information two
The point cloud data collection P in period1And P2。
In one possible implementation, comparative analysis unit 902 is additionally operable to exist to the point cloud data collection in two periods
Round fitting is carried out in respective coordinate system respectively, to determine the center of circle of two point cloud data collection respectively；By two point cloud data collection
It is placed under the same coordinate system, then overlaps the center of circle, to carry out the first registration to two point cloud data collection；According to ICP algorithm pair
Two point cloud data collection after first registration carry out the second registration；A selected wherein phase point cloud data collection is as datum mark cloud at random
Data set is concentrated using ANN algorithm in another phase point cloud data, determines the corresponding points of each datum mark respectively；Analyze each pair of base
On schedule with the relationship of corresponding points, with the deformation tendency of determination tunnel cross-section to be detected；Wherein, point cloud data collection on the basis of datum mark
In point.
It should be noted that herein, the terms "include", "comprise" or its any other variant are intended to non-row
His property includes, so that process, method, article or device including a series of elements include not only those elements, and
And further include other elements that are not explicitly listed, or further include for this process, method, article or device institute it is intrinsic
Element.In the absence of more restrictions, the element limited by sentence " including one ... ", it is not excluded that including
There is also other identical elements in the process of the element, method, article or device.
The embodiments of the present invention are for illustration only, can not represent the quality of embodiment.
Through the above description of the embodiments, those skilled in the art can be understood that above-described embodiment side
Method can add the mode of required general hardware platform to realize by software, naturally it is also possible to by hardware, but in many cases
The former is more preferably embodiment.Based on this understanding, technical scheme of the present invention substantially in other words does the prior art
Going out the part of contribution can be expressed in the form of software products, which is stored in a storage medium
In (such as ROM/RAM, magnetic disc, CD), including some instructions are used so that a mobile terminal (can be mobile phone, computer, clothes
Be engaged in device, air conditioner or the network equipment etc.) execute method described in each embodiment of the present invention.
The embodiment of the present invention is described above in conjunction with figure, but the invention is not limited in above-mentioned specific realities
Mode is applied, the above mentioned embodiment is only schematical, rather than restrictive, and those skilled in the art exist
Under the enlightenment of the present invention, without breaking away from the scope protected by the purposes and claims of the present invention, many shapes can be also made
Formula, all of these belong to the protection of the present invention.
Claims (14)
1. a kind of tunnel cross-section deformation analytical method, which is characterized in that the method includes：
Step 1, tunnel cross-section information is acquired, to obtain point cloud data collection；
Step 2, the point cloud data collection that tunnel cross-section to be detected is acquired in different times is analyzed and is compared, described in determination
The deformation tendency of tunnel cross-section to be detected.
2. according to the method described in claim 1, it is characterized in that, step 1 includes：
Step 11, it in such a way that three-dimensional laser scanner is scanned the same tunnel cross-section to be detected of different times, adopts
Collect tunnel cross-section information；According to the point cloud data collection P in two periods of the tunnel cross-section acquisition of information1And P2。
3. according to the method described in claim 1, it is characterized in that, step 2 includes：
Step 21, round fitting is carried out respectively in respective coordinate system to the point cloud data collection in two periods, to determine two respectively
The center of circle of a point cloud data collection；
Step 22, two point cloud data collection are placed under the same coordinate system, then overlap the center of circle, with to two point cloud data collection
Carry out the first registration；
Step 23, two point cloud data collection after being registrated according to iteration closest approach ICP algorithm pair first carry out the second registration；
Step 24, a selected wherein phase point cloud data collection utilizes approximate KNN algorithm ANN as datum mark cloud data set at random
It is concentrated in another phase point cloud data, determines the corresponding points of each datum mark respectively；
Step 25, the relationship for analyzing each pair of datum mark and corresponding points, with the deformation tendency of the determination tunnel cross-section to be detected；
Wherein, the datum mark is the point in the datum mark cloud data set.
4. according to the method described in claim 3, it is characterized in that,
The step 21, specifically includes：According to the point cloud data collection in two periods of least square method pair in respective coordinate system
Round fitting is carried out respectively.
5. according to the method described in claim 3, it is characterized in that, step 23 includes：
Step 231, point cloud data collection P is calculated2In each point in point cloud data collection P1In correspondence neighbor point, to obtain
One group of N number of corresponding points pair；
Step 232, it determines so that the distance of first group of N number of corresponding points pair and minimum translation parametersAnd rotation parameterIts
In, the translation parametersWith the rotation parameterFor the parameter in rigid body translation；
Step 233, when the distance of first group of N number of corresponding points pair and when more than or equal to pre-determined distance, according to the point cloud data
Collect P2, the translation parametersWith the rotation parameterDetermine point cloud data collection P '2；Calculate point cloud data collection P '2In it is each
A point is in point cloud data collection P1In correspondence neighbor point, to obtain second group of N number of corresponding points pair；
Step 234, it when the distance of second group of N number of corresponding points pair and when more than or equal to the pre-determined distance, redefines new
Point cloud data collection is simultaneously iterated calculating, until the distance of i-th group of corresponding points pair is less than pre-determined distance.
6. according to the method described in claim 5, it is characterized in that,
The step 231, specifically includes：According to preset condition, and using KD-tree structures in P1Middle determining P2Each point
Correspondence point of proximity, composition corresponding points to set { (P1, i, P2, i| i=1,2 ..., N) }；
Wherein, preset condition is：ε(P1, P2)min(d2(P1, iP2,i))；P1, iWith P2, iFor i-th group of corresponding points pair, P1, iBelong to P1,
P2, iBelong to P2。
7. according to the method described in claim 5, it is characterized in that,
The step 232, specifically includes：Step 2321, by N number of corresponding points to substituting into object function；It is true by iterative algorithm
Determine rigid body translation matrixTo determine so that the distance of corresponding points pair and minimum translation parametersAnd rotation parameter
Wherein, target function value be N number of corresponding points pair distance and, formula is：
Wherein, N P1The number at midpoint, P1, iWith P2, iFor i-th group of corresponding points pair, P1, iBelong to P1, P2, iBelong to P2。It is 3 × 1
Translation matrix,For 3 × 3 spin matrix.
8. according to the method described in claim 5, it is characterized in that,
Target function value be N number of corresponding points pair distance and, formula is：
Wherein, N P1The number at midpoint, P1, iWith P2, iFor i-th group of corresponding points pair, P1, iBelong to P1, P2, iBelong to P2。It is 3 × 1
Translation matrix,For 3 × 3 spin matrix, wiTo constrain weight factor.
9. according to the method described in claim 8, it is characterized in that,
Wherein, DDFk(p) deviation factors for being point p,For the regularization standard deviation of point p.
10. according to the method described in claim 5, it is characterized in that,
The step 231 further includes：Delete the corresponding points pair that distance is more than distance threshold.
11. according to the method described in claim 5, it is characterized in that,
The distance of corresponding points pair is projector distance of the Euclidean distance of point-to-point transmission on the radius extended line for overlapping the center of circle.
12. a kind of tunnel cross-section deformation analysis device, which is characterized in that described device is appointed in requiring 1 to 11 for perform claim
Method described in meaning one, described device include：
Collecting unit, for acquiring tunnel cross-section information, to obtain point cloud data collection；
Comparative analysis unit, the point cloud data collection for acquiring tunnel cross-section to be detected in different times carry out analysis and it is right
Than with the deformation tendency of the determination tunnel cross-section to be detected.
13. device according to claim 12, which is characterized in that
The collecting unit is additionally operable to sweep the same tunnel cross-section to be detected of different times by three-dimensional laser scanner
The mode retouched acquires tunnel cross-section information；According to the point cloud data collection P in two periods of the tunnel cross-section acquisition of information1And
P2。
14. device according to claim 12, which is characterized in that
The comparative analysis unit is additionally operable to carry out the point cloud data collection in two periods respectively in respective coordinate system round quasi-
It closes, to determine the center of circle of two point cloud data collection respectively；Two point cloud data collection are placed under the same coordinate system, then by the center of circle
It overlaps, to carry out the first registration to two point cloud data collection；Two points after being registrated according to iteration closest approach ICP algorithm pair first
Cloud data set carries out the second registration；A selected wherein phase point cloud data collection is as datum mark cloud data set at random, most using approximation
Nearest neighbor algorithm ANN is concentrated in another phase point cloud data, determines the corresponding points of each datum mark respectively；Analyze each pair of datum mark with it is right
The relationship that should be put, with the deformation tendency of determination tunnel cross-section to be detected；Wherein, the datum mark is the datum mark cloud data set
In point.
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