CN117235438B - Method for removing attached redundant data of tunnel inner diameter tomography measurement data - Google Patents
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Abstract
The invention discloses a method for removing attached redundant data of tunnel inner diameter tomography measurement data, which is characterized in that contour scanning acquisition data of a front laser acquisition system is subjected to multiple cleaning by using an attachment coordinate removing mode with the center as a midpoint progressive proportion after a fitting center value of segment data is obtained through a least square method on contour coordinates, so that effective real segment inner diameter contour data is finally obtained. And acquiring real measurement data of the inner diameter fault surface of the segment without attachments. So that management staff can monitor and data analysis the segment deformation of tunnel shield segments in different time domains.
Description
Technical Field
The invention relates to the technical field of measurement, in particular to a method and computer equipment for removing interference influence of redundant measured data of pipe piece inner diameter attachments in measured data generated when the inner diameter of a tunnel is scanned on real data of pipe piece surface detection based on a laser total station or a laser tomography range finder.
Background
The tunnel shield segment is a main assembly component of the tunnel shield, is the innermost barrier of the tunnel, bears the functions of resisting soil layer pressure, underground water pressure and some special loads, and is shown in fig. 1, and the tunnel after each device is installed is shown in fig. 2 and comprises various devices. Therefore, continuous section structure scanning and continuous deformation measurement and calculation of shield segments are basic works for ensuring continuous operation and safe maintenance of the tunnel. Therefore, in the process of installing and operating the tunnel shield segment, the deformation quantity and the deformation degree of the inner diameter of the tunnel shield segment need to be continuously monitored so as to ensure that the deformation of the inner diameter of the tunnel is in a controllable range.
Typically, tunnel shield segments are a cross-sectional structure that has a rigid, circular-like appearance. The cement prefabricated member is formed by a plurality of cement prefabricated members at the initial stage of installation. Tunnel segments of shield tunnel segments are typically of rigid concrete construction. After the segment is installed, the segment inner diameter keeps an inner diameter approximate to a perfect circle center. The laser total station or the laser tomography scanner scans the inner diameter of the segment to obtain outline data of an approximate circle. And according to a normal detection flow, transversely comparing tunnel segment scanning data acquired for multiple times in different time periods. So as to obtain the change rate and the change quantity of the inner diameter of the segment in a unit time period. The deformation of the segment under the underground continuous stress environment is ensured to be detectable through continuous detection and timely alarm of the data. However, in general, after the implementation of the pipe sheet earthwork is completed on site, the electromechanical equipment on the surface of the pipe sheet is installed according to actual conditions. These devices include power, low current, lighting, cables, support aids, track foundations and rail equipment and corresponding accessories, as shown in fig. 2. The accessories are attached to the inner wall of the duct piece for a long time, the laser scanning system scans the surface of the inner diameter profile attachments during annular scanning, and the real duct piece inner diameter fault measurement data are blocked due to the attachment in the tunnel shield duct piece laser fault scanning data obtained in the measuring process, so that the inner diameter surface of the duct piece cannot be truly scanned. The measurement results in that the scanning accuracy of laser to the inner surface of the segment is blocked due to the existence of the attachments on the inner side of the actual shield segment in the measurement process, and the coordinate parameters of the real inner diameter surface cannot be obtained to perform the later deformation calculation, and the calculation and analysis of the real data of the inner diameter deformation of the segment cannot be ensured.
For the detection of tunnel segments, there are also some researches in the prior art, and corresponding results are obtained, such as
Patent application CN101763102a discloses a tunnel monitoring data granularity processing method, which comprises the following steps: intelligently selecting collected data; storing the intelligently selected data granulation process in a granularity database; establishing a pre-control database, wherein the pre-control database stores training sample data of each granularity level; and determining the real-time state of the current tunnel according to the queried data of a certain granularity level and the training sample data of the same granularity level so as to make a monitoring decision. The method intelligently selects and granulates the collected data, stores the data, and determines the real-time state of the current tunnel according to the queried data of a certain granularity level and training sample data of the same granularity level, thereby making a tunnel monitoring decision. Therefore, the method can analyze the data acquired by the sensor and determine the real-time state of the tunnel.
Patent application CN114692080a discloses a method for detecting and correcting track data anomalies based on active prediction, firstly, active prediction is carried out on existing track data based on position according to K neighbor information, then new data generated by prediction and original data in a dataset are subtracted, a difference matrix is constructed, probability inference of moving track data anomalies is carried out on the basis, then forward scanning of a time window is carried out on the time dimension, data anomaly probability in each window is constructed, matrix data repair is carried out by searching for an abnormal data area, and finally the whole data matrix is corrected. The method can be applied to traffic monitoring of common roads, tunnels and bridges in smart cities.
Patent application CN105735375A discloses a method, a system and a construction method for monitoring stability of a loess tunnel bottom, wherein the system comprises a substrate and inverted arch contact pressure monitoring subsystem, a pile body stress monitoring subsystem, a soil body pore water pressure and water content monitoring subsystem between piles, a soil body water content monitoring subsystem between piles, a substrate deformation monitoring subsystem, a data acquisition module and a data analysis software module; the invention can well master the conditions of the stress, settlement, pore water pressure and water content of the tunnel bottom, provides a reliable basis for judging the stability of the substrate, and also provides powerful data for formulating an emergency treatment scheme of the substrate, thereby filling the defects of the existing specifications, avoiding the condition that the stability of the loess tunnel bottom is not controlled, and providing powerful analysis basis for ensuring the substrate to be in a safe and stable controlled state during construction and operation of the loess tunnel bottom.
Patent application CN113885379A discloses a tunnel boring machine remote monitoring platform based on big data, which comprises an integrated processing module, wherein the integrated processing module is an internal pipeline information processing center of the tunnel boring machine and is mainly responsible for data transmission, storage and comparison. This tunnel boring machine remote monitoring platform based on big data is through setting up pressure boost filter mechanism, when equipment during operation, install pressure boost filter mechanism at the end of intaking of pipeline, the dustcoat blocks the outside at the pipeline with massive impurity, reduce inside jam top probability from the source, the filter core can filter another part impurity, when the inside emergence of pipeline is stopped up, the inside probability of stopping up of dustcoat is biggest, conveniently look for the jam position, avoid taking apart equipment segmentation node and look for, waste time and energy, the dustcoat can prevent the pipeline jam, the inside conveying line of traditional tunnel boring machine has been solved and is stopped up easily at the during operation, and the inconvenient problem of jam point seek.
The patent application CN112284327A discloses a track detector based on data information control and transmission and a use method thereof, wherein an opening groove with an upward opening is formed in a vehicle body, a supporting shaft is rotatably arranged on the front side wall and the rear side wall in the opening groove, a first belt pulley is fixedly arranged on the supporting shaft, a swinging plate is symmetrically and fixedly arranged at the front position and the rear position on the supporting shaft, a rotating plate is rotatably arranged on the outer side of the swinging plate, a driver for driving the rotating plate to rotate is fixedly arranged in the swinging plate on the front side, a mechanical arm is rotatably arranged between the swinging plates, a hinging rod is hinged on the left side of the mechanical arm, and the hinging rod is hinged with the rotating plate; the length degree is adjusted by watching the picture on the display screen, so that the detection is accurate, the front part is cleaned in advance for detection in the machine walking process, the detection is accurate, the error is greatly reduced, and the maintenance trouble is reduced.
Patent application CN113093217a discloses a three-dimensional reconstruction method of a multi-line laser scanning tunnel, which scans and measures the tunnel, acquires data and records the travelling speed and distance; extracting point cloud three-dimensional data of the same position, analyzing, processing and removing statistical outliers; analyzing the data after outlier removal, calculating the gravity center of the data, using the gravity center to represent the actual three-dimensional point of the current position, carrying out adaptive stretching and extension according to the moving actual position to obtain a tunnel three-dimensional preliminary model, filtering by utilizing bilateral filtering, and denoising the data while keeping the edge data free from the influence of far data. The method fully utilizes the characteristic of large data volume of the multi-line radar, and can obtain measurement data with higher precision by fusion filtering of the data; the time for scanning the whole tunnel is also faster while the precision is ensured by scanning three-dimensional data by the mobile multi-line radar, and the method has stronger practical value.
Therefore, in the aspect of obtaining tunnel segment measurement data in the prior art, the following technical defects exist:
when the shield segments are subjected to measurement scanning to obtain scanning data, the data are usually multi-time scanning data on a single effective shield segment, namely coordinate points of laser scanning are usually scanned for a plurality of times at the same place, and equipment is used for obtaining a plurality of coordinates of the same place. But due to the environment, the equipment and the detection of operational disturbances of the carrier platform itself. The detection device will have a proper deviation in the cartesian coordinate system of the same point, i.e. the coordinate data of the same point will have a small error during scanning. Meanwhile, the detection equipment cannot be installed at the circle center of the tunnel shield segment in the detection environment, so that the received data coordinates are all measurement data based on the circle center of the installation point of the actual detection equipment, and are not true circle center points of the true segment.
Therefore, how to acquire the real measurement data of the inner diameter fault surface of the segment without attachments so as to facilitate the management staff to monitor and analyze the segment deformation of the tunnel shield segment in different time domains is a technical problem which needs to be solved urgently. According to the invention, the real segment measurement data of the segment inner diameter fault without attachments is obtained by calculating the data obtained by the laser total station or the laser fault scanner, so that the deformation of the tunnel shield segment inner diameter can be monitored and data analyzed.
Disclosure of Invention
In view of the above technical problems, an object of the present invention is to provide a method for removing redundant data attached to tunnel inside diameter tomography measurement data, in which effective real segment inside diameter profile data is finally obtained by performing multiple cleaning on profile scanning acquisition data of a front laser acquisition system by using an attachment coordinate removing method using a center as a midpoint progressive proportion after a fitting center value of segment data is obtained by using a least square method on profile coordinates, so as to solve the problems set forth in the background art.
In general, in a laser measurement acquisition system, the current fitting circle center is taken as a base point according to fitting circle center coordinates of different segments and deleting edge coefficients set by lines, and coordinate points outside the outer edge and the inner edge of the coefficients are deleted. And repeatedly calculating the residual coordinate points according to the least square method to obtain the fitting circle center of the fitting calculation of the current residual coordinate points. And calculating and deleting coordinate points which fall outside the outer edge and the inner edge of the coefficient distance in the current residual coordinate points by deleting edge coefficients in gradually reduced scale. And (3) repeating and deleting redundant point positions in the system outside the boundary of the edge coefficient range repeatedly, wherein the rest coordinate data is the optimal set of the effective measurement data of the current duct piece. These points are effective inner diameter measurement points of the segment. Namely, the effective measurement coordinate value of the inner diameter surface of the segment. The cleaned effective measurement coordinate points can provide real calculation and analysis data for the inner diameter deformation of the segment. Meanwhile, the invalid measurement coordinate data and the attached matter outline data are removed due to the fact that the invalid data are cleaned for many times, and finally the actual measurement data left are greatly reduced. The number of calculation load parameters is reduced for the calculation of the deformation of the tunnel segment in the later period and the calculation of the deformation trend in the finite time domain due to the great reduction of the actual measurement data. And simultaneously, the storage space resource requirement of the local measurement data is reduced.
The technical scheme is that the method and the device for cleaning the data acquired by the shield segment laser total station or the laser fault scanner provide a method for cleaning invalid data of attachments in the inner diameter profile of the tunnel segment based on the calculation device associated with the laser total station and the laser fault scanner. Specifically, the invention provides the following technical scheme:
A method for removing attached redundant data of tunnel inner diameter tomography measurement data is characterized by comprising the following steps:
Step S1, a laser scanning system performs laser scanning on the inner diameter of the tunnel segment, and acquired data form a segment detection data set;
Step S2, performing pre-analysis on the acquired segment detection data set, decomposing the segment detection coordinate data, setting segment convergence cleaning boundary coefficients from large to small, and setting convergence boundary coefficient expansion convergence recursion series;
Step S3, calculating the fitting circle center of the current detection coordinate data by utilizing least square fitting based on the acquired detection coordinate data, gradually converging the detection coordinate data range of the boundary region of the interval, and deleting the invalid attachment detection coordinate data outside the boundary region of the convergence interval;
Step S3, repeating the least square method to fit and clean the fitting circle center of the residual measurement coordinate data, repeating deleting the detection coordinate data outside the boundary area of the gradual convergence interval, and converting the residual detection coordinate data after cleaning into a sequence coordinate value calculated by radian;
S4, acquiring corresponding effective measuring segment data boundaries according to the sequence coordinate values, and calculating the range interval of the radian density difference of the residual segment;
And S5, fitting the detection coordinate data by using a least square method to perform equal density point location interpolation on the segment radian density difference out-of-range interval, and combining the equal density point location interpolation of the segment radian density difference out-of-range interval and the residual measurement coordinate data after cleaning to form final cleaning correction segment coordinate data.
Preferably, in the step S1, a laser scanning is provided for the inner diameter profile of the tunnel segment based on a laser total station or a laser tomography scanner, and accurate reflection coordinate data of the tunnel segment surface is obtained, and the reflection coordinate data forms a segment detection data set.
Further, the nth round of scanning data of the segment is used as basic coordinate data of the current round, and the specific cleaning method comprises the following steps:
Step S01, shield tunnel segment measurement data obtain a detection data set file from laser detection equipment, wherein the detection data set comprises detection information of the organization detection equipment and a detection coordinate data set D (x m,ym), and m is the number of the obtained measurement point;
Step S02, decomposing attribute data and coordinate data of the detection data set file, and extracting measurement attribute data of the detection segment and segment coordinate data set based on a rectangular coordinate system;
step S03, reading segment engineering design parameters matched with engineering projects from a system, wherein the segment engineering design parameters comprise segment engineering design radius distance parameters R 0;
Step S04, reading a segment engineering attachment convergence boundary coefficient parameter set Fit (n), n >0 and detection radian density Rt, rt >0 matched with engineering projects from a system; gradually retracting the convergent boundary coefficient parameter set from the large-scale cleaning step by step from outside to inside and reducing the range edge of the cleaning strip area;
Step S05, expanding a convergence recursion series S n according to a convergence boundary coefficient, and gradually starting to clean the abnormal discrete coordinate data of the inner diameter attachments of the duct piece; calculating the current fitting circle center (x n,yn) by using least square fitting to the current segment data coordinate set;
Step S06, a circle C n based on a radius R 0 is defined by taking the current fitting (x n,yn) and n >0 as relative coordinate origins and the engineering design radius R 0 of the duct piece as a distance; the arc of the circle C n is used as a boundary, and the outer boundary of the convergence interval strip is respectively calculated according to the current convergence boundary coefficient Fit (n) And an inner measurement boundary di=r 0 ×fit (n) of the convergence interval bar; calculating the distance D n of the measurement coordinate D (x m,ym) to the fitting circle center (x n,yn)/>Deleting from the data set D when D n > DO or D n < DI measurement point coordinates D (x m,ym) are outside the convergence interval bar;
Step S07, returning to the step S05 to repeatedly execute the convergence fitting circle center when the convergence boundary coefficient has not completed the complete convergence recursion series S n and n >0, deleting the coordinate of the measurement coordinate point which does not meet the condition to obtain D (x m,ym), and finally obtaining the rest D r(xm,ym) inner diameter scanning reserved coordinate data set;
Step S08, converting the coordinate data set of the inner diameter scanning reserved coordinate data set D r(xm,ym) into a scanning coordinate set D ra(disn,ran),-π≤ran≤π,Dra data set calculated according to radians, and sequencing the data according to the range of-pi radians; taking a minimum value MinD ra and a maximum value MaxD ra, namely the left and right measurement boundaries of the effective measurement domain;
step S09, in the interval between the minimum value MinD ra and the maximum value MaxD ra, there is a data lack area caused by data cleaning, and these partial data are data vacancies caused by cleaning attachments;
S010, scanning the residual inner diameter from the minimum value MinD ra to the maximum value MaxD ra to obtain a reserved coordinate data set D ra(disn,ran),-π≤ran which is less than or equal to pi, and when (ra n-ran-1) is existed, namely the radian interval density between two points is greater than the detection radian density Rt preset by a system, obtaining a fitting curve in the two points by adopting a least square method, and calculating interpolation points according to the density of the detection radian density Rt to obtain a set D ia(disn,ran),-π≤ran which is less than or equal to pi;
Step S011, combining the D ra(disn,ran) and the D ia(disn,ran) within the limited range radian data field MinD ra～MaxDra to obtain D r＝Dia∪Dra, where the point location of D r within the limited range radian data field MinD ra～MaxDra is the point location of the edge measurement point without attachments after the segment measurement and the cleaning of the attachment coordinate data.
And repeating the steps of cleaning redundant data on two sides of the fitting circle for multiple times, calculating the residual measured data by a least square method in the calculation process to gradually correct the real fitting circle center, and deleting invalid measured data coordinates of attachments or data jump on the inner diameter measured data by gradually converging coefficients and gradually shrinking converging circular arc bands.
After the overrun data deleting operation of the fitting circle is carried out through multiple rounds of cleaning, obtaining the residual detection points, namely the cleaned real segment measurement data; obtaining effective duct piece measuring boundaries on the left side and the right side of the effective duct piece according to the residual duct piece measuring data; and calculating a segment ellipse equation based on the residual cleaning data coordinates by using a least square method from the left and right boundaries of the effective segment data as an effective interval and the residual segment measurement data as basic data.
And fitting the deformation coordinate data corresponding to the inner diameter of the empty real segment in a data-approximation calculation mode by using a least square method in the data-blank area when the attachment coordinate data are cleaned through an elliptic equation, and finally using the cleaned data and the data set obtained through least square method data approximation, namely the deformation coordinate data of the inner diameter of the real segment, to analyze the deformation of the tunnel segment in the later stage and simulate the deformation trend.
In another aspect, the present application also provides a computer readable storage medium storing a computer program for clearing away the attached redundant data of the inside diameter tunnel tomography measurement data, where the computer program is used to execute the method for clearing away the attached redundant data of the inside diameter tunnel tomography measurement data.
In another aspect, the present application further provides a computer device, including a display device, a data input device, and a storage device, where the storage device stores a computer program for clearing redundant data attached to tomographic measurement data of an inside diameter of a tunnel; and the laser scanning system performs laser scanning on the inner diameter of the tunnel segment, the acquired data form segment detection data sets, the segment detection data sets are input into a storage device of the computer device through the data input device, the computer program executes the method for removing the attached redundant data of the tunnel inner diameter tomography measurement data, and the result of the removing method is sent to the display device for display.
The display device includes a plurality of display modes, in which raw coordinate data, washed out coordinate data, interpolated coordinate data, and a finish are displayed in a coordinate system.
The residual coordinate data after washing, and various types of coordinate data selectively display one or more types, and various types of coordinate data are displayed in different colors.
On the other hand, the application also provides a system for clearing the attached redundant data of the tunnel inside diameter tomography measurement data, which comprises a laser total station or laser tomography device, a computer device and a data configuration module, wherein the related computing device is used for cleaning invalid data of attachments in the inside diameter profile of a tunnel segment, and the system comprises the computer device, and the laser total station or the laser tomography device, the data configuration module and the computer device are in signal connection; and the data configuration module reads out segment engineering design parameters matched with the engineering project from the system.
Compared with the prior art, the invention has the beneficial effects that:
1. And calculating and cleaning the detection data of the fitted real tunnel segment for multiple times by using a multiple-time least square method to automatically obtain the fitted circle center coordinates of the real segment. And (3) measuring the center origin by self-matching the reference of the segment deformation of different time domains.
2. The independent tunnel segment detection data items can be adapted through the adjustable attachment coordinate convergence coefficient so as to adapt to different tunnel detection segment definitions.
3. The approximation, identification and removal of the multilayer segment attachment data coordinate data are ensured by adopting a gradual cleaning and fitting calculation mode through fitting the segment circle center. And the effective rate of the real duct piece coordinate data is improved.
4. And fitting out density point location data of a vacant data part of the data of the converged cleaned attachments by least square fitting to approximate a real segment inner diameter coordinate data set blocked by deleting the redundant attachments.
5. And fitting the deformation of the inner diameter surface of the segment after removing the attachments by fitting interpolation in a best fitting mode to provide basic data for a segment deformation comparison model in the later stage.
6. And quickly establishing a segment contrast deformation model by taking the circle center coordinates of the real segment and the prefabricated design installation segment as a reference system through cleaning and fitting the circle center coordinate data.
Drawings
FIG. 1 shows a tunnel shield segment inner and outer wall composition structure;
FIG. 2 is a view of the attachment type and mounting structure of the tunnel shield segments;
FIG. 3 illustrates a tunnel shield segment measurement coordinate fault structure;
FIG. 4 shows a tunnel shield segment measurement coordinate fault attachment structure;
FIG. 5 illustrates tunnel shield segment measurement coordinates and fault attachment coordinates;
FIG. 6 is a least square method fitting center logic circle of tunnel shield segment measurement coordinate data;
FIG. 7 illustrates a boundary description of the cleaning data of the least square fitting center logic circle of the tunnel shield segment measurement coordinate data;
FIG. 8 is residual coordinate data after cleaning the attached data of the tunnel shield segments;
FIG. 9 is a graph showing filling of interpolation vacancy data after cleaning tunnel shield segment attachment data;
Fig. 10 is a flow chart of a converging and cleaning algorithm for laser measurement interference data of the inner diameter of a tunnel segment.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Embodiment one:
In the tunnel segment layout, trestle bridges, equipment cabinets, bridge frames and overhead contact lines above the trestle bridges are arranged on the side of the tunnel segment 2, as shown in fig. 2; when the laser total station or the laser fault scanner arranged in the tunnel segment performs laser measurement on the tunnel section, the equipment can form an interference factor of tunnel segment measurement, and scanned data coordinates are as shown in fig. 3, which shows coordinate data obtained after scanning by the laser scanning equipment, wherein tunnels of trestle, bridge, contact net, equipment frame and the like are arranged in daily operation. For this reason, in order to obtain the true coordinate data of the tunnel inner diameter, these interference factors need to be cleaned, and then the cleaning method of the present application for the attachment redundant data of the tunnel inner diameter tomographic measurement data is proposed, the cleaning method includes the following steps;
Step S1, a laser scanning system performs laser scanning on the inner diameter of the tunnel segment, and acquired data form a segment detection data set;
Step S2, performing pre-analysis on the acquired segment detection data set, decomposing the segment detection coordinate data, setting segment convergence cleaning boundary coefficients from large to small, and setting convergence boundary coefficient expansion convergence recursion series;
Step S3, calculating the fitting circle center of the current detection coordinate data by utilizing least square fitting based on the acquired detection coordinate data, gradually converging the detection coordinate data range of the boundary region of the interval, and deleting the invalid attachment detection coordinate data outside the boundary region of the convergence interval;
Step S3, repeating the least square method to fit and clean the fitting circle center of the residual measurement coordinate data, repeating deleting the detection coordinate data outside the boundary area of the gradual convergence interval, and converting the residual detection coordinate data after cleaning into a sequence coordinate value calculated by radian;
S4, acquiring corresponding effective measuring segment data boundaries according to the sequence coordinate values, and calculating the range interval of the radian density difference of the residual segment;
And S5, fitting the detection coordinate data by using a least square method to perform equal density point location interpolation on the segment radian density difference out-of-range interval, and combining the equal density point location interpolation of the segment radian density difference out-of-range interval and the residual measurement coordinate data after cleaning to form final cleaning correction segment coordinate data.
Further, the nth round of scanning data of the segment is used as basic coordinate data of the current round, and the specific cleaning method comprises the following steps:
Step S01, shield tunnel segment measurement data obtain a detection data set file from laser detection equipment, wherein the detection data set comprises detection information of the organization detection equipment and a detection coordinate data set D (x m,ym), and m is the number of the obtained measurement point;
Step S02, decomposing attribute data and coordinate data of the detection data set file, and extracting measurement attribute data of the detection segment and segment coordinate data set based on a rectangular coordinate system;
step S03, reading segment engineering design parameters matched with engineering projects from a system, wherein the segment engineering design parameters comprise segment engineering design radius distance parameters R 0;
Step S04, reading a segment engineering attachment convergence boundary coefficient parameter set Fit (n), n >0 and detection radian density Rt, rt >0 matched with engineering projects from a system; gradually retracting the convergent boundary coefficient parameter set from the large-scale cleaning step by step from outside to inside and reducing the range edge of the cleaning strip area;
Step S05, expanding a convergence recursion series S n according to a convergence boundary coefficient, and gradually starting to clean the abnormal discrete coordinate data of the inner diameter attachments of the duct piece; calculating the current circle center (x n,yn) by using least square fitting to the current segment data coordinate set;
Step S06, defining a circle C n based on a radius R 0 by taking a current circle center (x n,yn), n >0 as a relative coordinate origin and the engineering design radius R 0 of the segment as a distance; the arc of the circle C n is used as a boundary, and the outer boundary of the convergence interval strip is respectively calculated according to the current convergence boundary coefficient Fit (n) And an inner measurement boundary di=r 0 ×fit (n) of the convergence interval bar; calculating the distance D n of the measurement coordinate D (x m,ym) to the fitting circle center (x n,yn)/>Deleting from the data set D when D n > DO or D n < DI measurement point coordinates D (x m,ym) are outside the convergence interval bar;
Step S07, returning to the step S05 to repeatedly execute the convergence fitting circle center when the convergence boundary coefficient has not completed the complete convergence recursion series S n and n >0, deleting the coordinate of the measurement coordinate point which does not meet the condition to obtain D (x m,ym), and finally obtaining the rest D r(xm,ym) inner diameter scanning reserved coordinate data set;
Step S08, converting the coordinate data set of the inner diameter scanning reserved coordinate data set D r(xm,ym) into a scanning coordinate set D ra(disn,ran),-π≤ran≤π,Dra data set calculated according to radians, and sequencing the data according to the range of-pi radians; taking a minimum value MinD ra and a maximum value MaxD ra, namely the left and right measurement boundaries of the effective measurement domain;
step S09, in the interval between the minimum value MinD ra and the maximum value MaxD ra, there is a data lack area caused by data cleaning, and these partial data are data vacancies caused by cleaning attachments;
S010, scanning the residual inner diameter from the minimum value MinD ra to the maximum value MaxD ra to obtain a reserved coordinate data set D ra(disn,ran),-π≤ran which is less than or equal to pi, and when (ra n-ran-1) is existed, namely the radian interval density between two points is greater than the detection radian density Rt preset by a system, obtaining a fitting curve in the two points by adopting a least square method, and calculating interpolation points according to the density of the detection radian density Rt to obtain a set D ia(disn,ran),-π≤ran which is less than or equal to pi;
Step S011, combining the D ra(disn,ran) and the D ia(disn,ran) within the limited range radian data field MinD ra～MaxDra to obtain D r＝Dia∪Dra, where the point location of D r within the limited range radian data field MinD ra～MaxDra is the point location of the edge measurement point without attachments after the segment measurement and the cleaning of the attachment coordinate data.
And (3) by repeatedly cleaning redundant data on two sides of the fitting circle for multiple times, calculating the residual measured data by a least square method in the calculation process to gradually correct the true fitting circle center, and deleting invalid measured data coordinates of attachments or data jump on the inner diameter measured data by gradually converging coefficients and gradually shrinking converging circular arc bands.
After the overrun data deleting operation of the fitting circle is carried out through multiple rounds of cleaning, obtaining the residual detection points, namely the cleaned real segment measurement data; obtaining effective duct piece measuring boundaries on the left side and the right side of the effective duct piece according to the residual duct piece measuring data; and calculating a segment ellipse equation based on the residual cleaning data coordinates by using a least square method from the left and right boundaries of the effective segment data as an effective interval and the residual segment measurement data as basic data.
And fitting the deformation coordinate data corresponding to the inner diameter of the empty real duct piece in the data empty region by using a least square method through a data approximation calculation mode when cleaning the attachment coordinate data through an elliptic equation, and finally, using the cleaned data and the data set obtained through the least square method data approximation, namely the deformation coordinate data of the inner diameter of the real duct piece, for analysis of the deformation of the tunnel duct piece in the later stage and simulation of the deformation trend.
Embodiment two:
a computer-readable storage medium storing a computer program for clearing away data of an inside diameter tunnel tomography measurement data adhesion redundancy, characterized by: the computer program is used for executing a method for removing the attached redundant data of the fault scanning measurement data in the tunnel.
Embodiment III:
the computer equipment comprises a display device, a data input device and a storage device, wherein the storage device stores a computer program for removing the attached redundant data of the tunnel inner diameter tomography measurement data, a laser scanning system scans the inner diameter of the tunnel segment by laser, acquired data form a segment detection data set, the segment detection data set is input into the storage device of the computer equipment through the data input device, the computer program executes a method for removing the attached redundant data of the tunnel inner diameter tomography measurement data, and the result of the removing method is sent to the display device for display.
Preferably, the display device includes a plurality of display modes, the original coordinate data, the washed out coordinate data, the interpolation coordinate data, and the remaining coordinate data after washing are displayed in a coordinate system, and each type of coordinate data selectively displays one or more types, and each type of coordinate data is displayed in a different color.
Embodiment four:
The system comprises a laser total station or laser fault scanner device, a computer device and a data configuration module, wherein the related computing device is used for cleaning invalid data of attachments in the inner diameter profile of a tunnel segment, and the computer device is used for signal connection; and the data configuration module reads out segment engineering design parameters matched with the engineering project from the system.
The method for acquiring the data logic center coordinates through least square fitting comprises the following steps:
Searching for the optimal function matching of the data by minimizing the square sum of errors, and simply obtaining unknown data by using a least square method, wherein the square sum of errors between the obtained data and actual data is minimized;
y i is the segment measurement data set obtained by the laser measurement device measurement, then E is the error of the fit
According to the equation for a circle:
(x0-xi)2+(y0-yi)2＝R2
we can know that x 0、y0 where f takes the minimum value is the center of the set of measured hash coordinate points of these segments,
Wherein,
f(x,y)＝(xi-x0)2+(yi-y0)2-R2
Therefore: f= Σf (x i,yi)2
When F obtains a corresponding extremum, the state that the radius R is 0 distance does not exist in the actual detection state of the tunnel segment.
∑F(xi,yi)＝0
Is provided with
Wherein the method comprises the steps of
The coordinate solving value of the circle center and the fitting radius of the circle can be finally solved by unfolding calculation as follows
The coordinate set of segment data points obtained by measurement is (x i,yi).
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (9)
1. A method for removing attached redundant data of tunnel inner diameter tomography measurement data is characterized in that the nth round of scanning data of a duct piece is used as basic coordinate data of a current wheel to clean, and the specific cleaning method comprises the following steps:
Step S01, shield tunnel segment measurement data obtain a detection data set file from laser detection equipment, wherein the detection data set comprises detection information of the laser detection equipment and a detection coordinate data set D (x m,ym), and m is the number of the obtained measurement point; step S02, decomposing attribute data and coordinate data of the detection data set file, and extracting measurement attribute data of the detection segment and segment coordinate data set based on a rectangular coordinate system;
step S03, reading segment engineering design parameters matched with engineering projects from a system, wherein the segment engineering design parameters comprise segment engineering design radius distance parameters R 0;
step S04, reading a segment engineering attachment convergence boundary coefficient parameter set Fit (n), n >0 and detecting radian density Rt, rt >0 matched with engineering projects from a system; based on the convergence boundary coefficient parameter set, cleaning is started from a large range according to the sequence of the tunnel from outside to inside, and the range edge of the cleaning strip area is gradually retracted and reduced;
Step S05, expanding a convergence recursion series S n according to a convergence boundary coefficient, and gradually starting to clean the abnormal discrete coordinate data of the inner diameter attachments of the duct piece; calculating the current circle center (x n,yn) by using least square method fitting based on the current segment data coordinate set;
Step S06, defining a circle C n based on a radius R 0 by taking a current circle center (x n,yn), n >0 as a relative coordinate origin and the engineering design radius R 0 of the segment as a distance; the arc of the circle C n is used as a boundary, and the outer boundary of the convergence interval strip is respectively calculated according to the current convergence boundary coefficient Fit (n) And an inner measurement boundary di=r 0 ×fit (n) of the convergence interval bar; calculating the distance D n,/>, of the measurement coordinate D (x m,ym) to the center of the circle (x n,yn)When D n > DO or D n < DI, namely the measurement point position coordinate D (x m,ym) is located outside the convergence interval bar, deleting the data coordinate from the data set D n;
Step S07, returning to the step S05 to repeatedly execute the convergence fitting circle center when the convergence boundary coefficient has not completed the complete convergence recursion series S n and n >0, deleting the coordinate of the measurement coordinate point which does not meet the condition to obtain D (x m,ym), and finally obtaining the rest D r(xm,ym) inner diameter scanning reserved coordinate data set;
Step S08, reserving a coordinate data set D r(xm,ym for inner diameter scanning), converting the coordinate data set into a scanning coordinate set D ra(disn,ran),-π≤ran≤π,Dra data set calculated according to radians, and sequencing the data according to the range of-pi radians; taking a minimum value MinD ra and a maximum value MaxD ra, namely the left and right measurement boundaries of the effective measurement domain; step S09, in the interval between the minimum value MinD ra and the maximum value MaxD ra, there are areas with lack of data caused by data cleaning, where the areas with lack of data are data gaps caused by cleaning attachments;
S010, scanning the residual inner diameter from the minimum value MinD ra to the maximum value MaxD ra to obtain a reserved coordinate data set D ra(disn,ran),-π≤ran which is less than or equal to pi, and when (ra n-ran-1) is existed, namely the radian interval density between two points is greater than the detection radian density Rt preset by a system, obtaining a fitting curve in the two points by adopting a least square method, and calculating interpolation points according to the density of the detection radian density Rt to obtain a set D ia(disn,ran),-π≤ran which is less than or equal to pi;
Step S011, combining the D ra(disn,ran) and the D ia(disn,ran) within the limited range radian data field MinD ra～MaxDra to obtain D r＝Dia∪Dra, where the point location of D r within the limited range radian data field MinD ra～MaxDra is the point location of the edge without attachment obtained after the segment is measured and the attachment coordinate data is cleaned.
2. The method for removing the attached redundant data of the inside diameter tomography measurement data of the tunnel according to claim 1, wherein: in the step S01, a laser scanning is provided for the inner diameter profile of the tunnel segment based on a laser total station or a laser tomography scanner, so as to obtain accurate reflection coordinate data of the tunnel segment surface, and the reflection coordinate data form a segment detection data set.
3. The method for removing the attached redundant data of the inside diameter tomography measurement data of the tunnel according to claim 1, wherein: and repeatedly cleaning redundant data on two sides of the fitting circle for multiple rounds, calculating the residual measured data by a least square method in the calculation process, gradually correcting the real fitting circle center, gradually reducing the convergent arc band by adjusting the convergent boundary coefficient Fit (n), and deleting attachments or invalid measured data coordinates of data jump on the inner diameter measured data.
4. A method for removing redundant data attached to tomographic measurement data of an inside diameter of a tunnel according to claim 3, wherein: after the overrun data deleting operation of the fitting circle is carried out through multiple rounds of cleaning, obtaining the residual detection points, namely the cleaned real segment measurement data; acquiring effective duct piece measurement boundaries at the left side and the right side of the tunnel according to the residual duct piece measurement data; and calculating an elliptic equation of the segment based on the residual cleaning data coordinates by using a least square method by taking the left and right boundaries of the effective segment data as an effective interval and the residual segment measurement data as basic data.
5. The method for removing the attached redundant data of the inside diameter tomography measurement data of the tunnel according to claim 4, wherein: fitting the corresponding deformation coordinate data corresponding to the inside diameter of the vacant real segment in a data approximation calculation mode by using a least square method in the region where the data vacancy appears when the attachment coordinate data are cleaned through an elliptic equation, and finally, approximating the cleaned data and the data set which is fitted through the least square method data, namely the deformation coordinate data of the inside diameter of the real segment, to be used for analysis of the deformation of the tunnel segment in the later period and simulation of the deformation trend.
6. A computer-readable storage medium storing a computer program for clearing away data of an inside diameter tunnel tomography measurement data adhesion redundancy, characterized by: the computer program is stored in a readable storage medium for performing the method for cleaning up the inside diameter tunnel tomography measurement data adhesion redundancy data according to any one of claims 1 to 5.
7. A computer device comprising a display device, a data input device and a storage device, said storage device storing a computer program for cleaning redundant data attached to tomographic measurement data of an inside diameter of a tunnel, characterized in that:
the laser scanning system performs laser scanning on the inner diameter of the tunnel segment, acquired data form segment detection data sets, the segment detection data sets are input into storage equipment of the computer equipment through the data input equipment, the computer program executes the method for removing the attached redundant data of the tunnel inner diameter tomography measurement data according to any one of claims 1-5, and the result of the removing method is sent to the display equipment for display.
8. A computer device according to claim 7, wherein: the display device includes a plurality of display modes; the original coordinate data, the washed coordinate data, the interpolation coordinate data and the remaining coordinate data after washing are displayed in the coordinate system, one or more types of all types of coordinate data are selectively displayed, and all types of coordinate data are displayed in different colors.
9. A system for removing redundant data attached to tunnel inside diameter tomography measurement data, the system comprising a laser total station or laser tomography device, a computer device, and a data configuration module, wherein the associated computing device is used for cleaning invalid data of attachments in the inside diameter profile of a tunnel segment, and the system comprises the computer device as claimed in claim 7, and the laser total station or laser tomography device, the data configuration module and the computer device are in signal connection; and the data configuration module reads out segment engineering design parameters matched with the engineering project from the system.
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