CN113222416A - Digital evaluation method and system for tunnel whole-process construction quality - Google Patents

Digital evaluation method and system for tunnel whole-process construction quality Download PDF

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CN113222416A
CN113222416A CN202110533227.2A CN202110533227A CN113222416A CN 113222416 A CN113222416 A CN 113222416A CN 202110533227 A CN202110533227 A CN 202110533227A CN 113222416 A CN113222416 A CN 113222416A
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CN113222416B (en
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郑赢豪
荆留杰
贾连辉
贾正文
李鹏宇
陈帅
游宇嵩
刘涛
徐受天
赵严振
孙森震
陈强
时洋
周宇
鞠翔宇
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China Railway Engineering Equipment Group Co Ltd CREG
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Abstract

The invention provides a digital evaluation method and a digital evaluation system for the whole-process construction quality of a tunnel, wherein the system comprises a data acquisition and pretreatment module, an excavation process quality evaluation module, a primary support quality evaluation module, a secondary lining quality evaluation module and a whole-process construction quality evaluation module, the data acquisition and pretreatment module is respectively connected with the excavation process quality evaluation module, the primary support quality evaluation module and the secondary lining quality evaluation module, and the excavation process quality evaluation module, the primary support quality evaluation module and the secondary lining quality evaluation module are all connected with the whole-process construction quality evaluation module. According to the invention, the whole-process construction quality is quantitatively evaluated through 8 evaluation indexes, the problems of relative fracture of construction quality evaluation information of each process of the tunnel, disjointed construction quality evaluation among each process and poor overall evaluation effect are solved, and the accurate evaluation and comprehensive grading of the whole-process construction quality of the drilling and blasting method are realized.

Description

Digital evaluation method and system for tunnel whole-process construction quality
Technical Field
The invention relates to the technical field of tunnel engineering construction, in particular to a method and a system for digitally evaluating the construction quality of a tunnel in a whole process.
Background
The drilling and blasting construction method has the characteristics of strong geological adaptability, suitability for multi-section type excavation and capability of flexibly processing unfavorable geological disasters, and is widely applied to engineering construction of urban underground spaces, subways, water conservancy tunnels, railway tunnels, mountain tunnels, coal mine roadways and the like.
At present, the drilling and blasting construction method forms a whole-process construction scheme which integrates mechanized equipment such as a three-arm drilling jumbo, an arch frame installation jumbo, a concrete wet spraying jumbo, a lining jumbo and the like. Along with the continuous improvement of tunnel construction mechanization degree, whole process construction is more and more favored. The whole-process construction of the tunnel refers to the whole-process operation procedures of drilling, blasting, excavation, primary support, secondary lining and the like which are formed by relying on mechanized equipment and have tight connection and high degree of association. The main purpose of face excavation is to make the tunnel excavation section conform to the design contour line as far as possible on the premise of ensuring the maximum footage, and reduce the overbreak and the underexcavation of the tunnel contour of the excavation section. Therefore, the evaluation of the construction quality of the face excavation mainly comprises the analysis of the overbreak and the calculation of the blasting footage, wherein the overbreak and the underbreak are the most important and strict control. The primary support means mainly comprises anchor rods, vertical steel arch frames, sprayed concrete and the like. Therefore, the evaluation of the construction quality of the primary support section mainly comprises the evaluation of the flatness of the sprayed concrete, the evaluation of the number of anchor rods and the evaluation of the space between the arches. As a permanent supporting means, the secondary lining is the last guarantee of tunnel supporting, and has important significance for ensuring the appearance and the safety of the tunnel. Therefore, the evaluation of the construction quality of the secondary lining mainly comprises cavity detection, wall surface flatness evaluation, concrete strength evaluation and the like.
The outstanding characteristics of whole-process construction are close relation among all the processes, high integration degree and outstanding construction efficiency, so that the control on the construction quality among all the processes is also stricter. However, the evaluation of the construction quality of the whole process of the tunnel is still a great problem which troubles engineering construction personnel, and because the processes in the construction process of the whole process are closely connected and have high association degree, higher requirements are provided for the detection and the evaluation of the construction quality. In order to improve the efficiency of the whole-process construction, it is necessary to provide a method for evaluating the whole-process construction quality of a tunnel.
At present, the tunnel construction quality evaluation usually adopts a traditional sampling measurement method, such as: the tunnel overbreak and underbreak detection is carried out by a level gauge or a section measuring instrument, and the accuracy is poor and continuous measurement cannot be carried out at every 20m measuring position; on the other hand, information which can be used for evaluating the construction quality of each process is relatively cracked, a complete and unified whole-process construction quality detection and evaluation method cannot be formed, the problems of quality evaluation disjointing, poor evaluation effect and the like among the processes are easily caused, the feedback of tunnel construction and support is delayed, and great risks are brought to subsequent tunnel construction and operation and maintenance. The invention provides a method and a system for digitally evaluating the construction quality of a whole tunnel process, aiming at solving the problems of disjointed evaluation, poor evaluation effect and the like of the construction quality among all the tunnel processes.
The invention patent application with the application number of 202011296048.3 discloses a tunnel engineering full life cycle safety evaluation method, which comprises the steps of establishing six evaluation indexes of tunnel engineering full life cycle safety evaluation, and carrying out dynamic weight configuration on the six evaluation indexes; carrying out score evaluation on the six evaluation indexes; and calculating the safety evaluation value of the whole life cycle of the tunnel, and determining the technical grade of the safety evaluation. The method covers the whole process of planning design, construction and operation of the tunnel engineering, and can evaluate the safety condition of the tunnel engineering and ensure the safe and continuous development of the whole life cycle of the tunnel engineering. The patent is oriented to the whole life cycle of tunnel engineering planning design, construction and operation, and 6 safety evaluation indexes are a multi-source evaluation index A, an advanced detection index B, a proper treatment index C, a fine detection index D, a monitoring early warning index E and a first aid index F.
The invention is oriented to the mechanized construction process of the whole procedure of the tunnel by the drilling and blasting method, and has obvious difference with the application field of the patent, and the construction quality evaluation indexes in the procedures of excavation, primary support and secondary lining are obviously different from the patent.
Disclosure of Invention
The invention provides a tunnel whole-process construction quality digital evaluation method and system, aiming at the technical problems that the quality evaluation between each process is disjointed, the evaluation effect is poor and the engineering practice requirements are difficult to meet due to the fact that the existing tunnel whole-process construction quality evaluation method is few in research and the construction quality evaluation information of each process is relatively split.
In order to achieve the purpose, the technical scheme of the invention is realized as follows: a digital evaluation system for tunnel whole-process construction quality comprises a data acquisition and preprocessing module, an excavation process quality evaluation module, a primary support quality evaluation module, a secondary lining quality evaluation module and a whole-process construction quality evaluation module, wherein the data acquisition and preprocessing module is respectively connected with the excavation process quality evaluation module, the primary support quality evaluation module and the secondary lining quality evaluation module, and the excavation process quality evaluation module, the primary support quality evaluation module and the secondary lining quality evaluation module are all connected with the whole-process construction quality evaluation module
Further, the data acquisition and preprocessing module preprocesses the acquired three-dimensional point cloud data and transmits the three-dimensional point cloud data to the excavation procedure quality evaluation module, the primary support quality evaluation module and the secondary lining quality evaluation module; the excavation procedure quality evaluation module analyzes the point cloud data of the tunnel face excavation section after pretreatment and calculates the construction quality evaluation index of the excavation procedure section; the primary support quality evaluation module analyzes the point cloud data and the concrete strength data of the pretreated primary support section and calculates the construction quality evaluation index of the primary support section; the secondary lining quality evaluation module analyzes the point cloud data and the concrete strength data of the preprocessed secondary lining section and calculates the construction quality evaluation index of the secondary lining section; and the whole-process construction quality evaluation module comprehensively grades the quality evaluation indexes of all the processes according to the construction quality evaluation indexes of the excavation process section, the primary support section and the secondary lining section, and finally obtains the whole-process construction quality grade of the tunnel.
Further, the data acquisition and preprocessing module comprises a laser scanning acquisition sub-module, a concrete strength acquisition sub-module and a data preprocessing sub-module, the laser scanning acquisition sub-module is connected with the data preprocessing sub-module, the data preprocessing sub-module is connected with the excavation procedure quality evaluation module, the primary support quality evaluation module and the secondary lining quality evaluation module respectively, and the concrete strength acquisition sub-module is connected with the primary support quality evaluation module and the secondary lining quality evaluation module respectively.
Further, the laser scanning acquisition sub-module utilizes a total station scanner to carry out overall process scanning on the tunnel face and the tunnel contour between the tunnel face and the secondary lining, and three-dimensional point cloud data under a geodetic absolute coordinate system are acquired; the concrete strength obtaining submodule utilizes an intelligent electronic resiliometer to measure concrete sprayed on the tunnel rock walls in the primary supporting section and the secondary lining section respectively, and obtains concrete spraying strength values of the primary supporting section and the secondary lining section; the data preprocessing submodule carries out scanning parameter setting, noise point data elimination and point cloud data segmentation on the three-dimensional point cloud data acquired by the laser scanning acquisition submodule, and respectively acquires point cloud data of a tunnel face excavation section, a primary support section and a secondary lining section; the types of the point cloud data are X coordinates, Y coordinates, Z coordinates and echo intensity values.
Furthermore, the excavation procedure quality evaluation module comprises a point cloud data analysis submodule, an undermining evaluation submodule and a blasting footage evaluation submodule, wherein the point cloud data analysis submodule is respectively connected with the undermining evaluation submodule and the blasting footage evaluation submodule;
the point cloud data analysis submodule sequentially selects M points from the boundary point cloud area in a clockwise or anticlockwise direction in the boundary point cloud area of the tunnel face and the peripheral outline through a man-machine interaction mode to form a closed polygonal area, and if the point cloud data of the excavation section is located in the closed polygonal area, the point cloud data of the tunnel face of the excavation section is regarded as the point cloud data of the tunnel face of the excavation section; otherwise, the point cloud data of the tunnel profile of the excavation section is regarded as point cloud data;
the super-under excavation evaluation submodule is used for carrying out super-under excavation analysis on point cloud data of the preprocessed tunnel outline of the excavation section, calculating the super-under excavation amount, comparing the super-under excavation amount with the super-under excavation control requirement, judging whether the tunnel outline of the excavation section meets the super-under excavation requirement or not, and evaluating the construction quality of the tunnel outline of the excavation section;
and the blasting footage evaluation submodule analyzes the point cloud data of the tunnel face of the preprocessed excavation section, calculates the actual blasting footage of the tunnel, and evaluates the construction quality of the tunnel face of the excavation section by taking the actual blasting footage/designed blasting footage as a footage rate.
Further, the amount of overbreak and undermining
Figure BDA0003068763190000031
Wherein (x)axis,yaxis,zaxis) The method comprises the following steps of (1) obtaining an axial center point coordinate of an excavation section tunnel outline, (x, y, z) obtaining an outline point cloud coordinate of a tunnel section where the excavation section axial center point is located, and R is a tunnel design radius;
the blasting footage
Figure BDA0003068763190000032
Wherein j is 1,2, N,
Figure BDA0003068763190000033
cloud coordinates of face points of the tunnel excavation section, N is the cloud number of face points of the tunnel excavation section, dblastingAnd (5) blasting footage of the tunnel face of the tunnel excavation section.
Further, the primary support quality evaluation module comprises an arch construction quality evaluation submodule, an anchor rod construction quality evaluation submodule and a spraying quality evaluation submodule, the data preprocessing submodule is respectively connected with the arch construction quality evaluation submodule and the anchor rod construction quality evaluation submodule, and the concrete strength acquisition submodule is connected with the spraying quality evaluation submodule;
the arch construction quality evaluation submodule analyzes the point cloud data of the preprocessed primary support section, accurately identifies the number and position coordinates of arches of the primary support section of the tunnel, and calculates the distance between the arches of the primary support section of the tunnel; calculating the arch spacing deviation value delta d ═ d-d by comparing the calculated distance between two adjacent arches with the distance between the designed adjacent archesdesign|，ddesignFor designing between adjacent archesSo as to judge whether the construction quality of the arch frame meets the site requirement;
the anchor rod construction quality evaluation submodule analyzes point cloud data of a pre-processed primary support section and accurately identifies the number and position coordinates of anchor rods of the primary support section of the tunnel; taking the ratio of the actual number of the anchor rods to the designed number of the anchor rods as an evaluation index, and judging whether the number of the anchor rods meets the design requirement during primary support;
and the spraying quality evaluation submodule compares the actual measured strength of the concrete of the primary support section measured by the concrete strength acquisition submodule with the design strength and judges whether the strength of the concrete sprayed on the wall surface of the tunnel meets the construction requirements or not.
Further, the identification of the tunnel primary support section arch centering is carried out by counting the echo intensity range [ intensity ] of the point cloud data corresponding to the surface of the arch centering1,intensity2]Filtering the preprocessed point cloud data of the primary support section, and if the echo intensity of the point cloud data is within the threshold range [ intensity ]1,intensity2]If the data is internal, the data is regarded as arch center point cloud data, so that the preliminary identification of the arch center is realized; clustering the preliminarily identified arch point cloud data by using a DBSCAN clustering method, and calculating the density of the preliminarily identified arch point cloud data to regard arches with different point cloud densities as different clustering categories to finally obtain point cloud data [ arch ] under different arch category1,arch2,···,archm]M is the number of identification arches; the actual distance between two adjacent arch frames passes through
Figure BDA0003068763190000041
j is more than i and less than or equal to m, and i-j is obtained by calculation as 1,
Figure BDA0003068763190000042
Figure BDA0003068763190000043
respectively point cloud data of surfaces of adjacent i-th and j-th arches, wherein d is an actual distance between the adjacent i-th and j-th arches;
identification of anchor rod of tunnel primary support sectionBy counting the echo intensity range of the corresponding point cloud data on the surface of the anchor rod3,intensity4]Filtering the preprocessed point cloud data of the primary support section, and if the echo intensity of the point cloud data is within the threshold range [ intensity ]3,intensity4]If the point cloud data is not the anchor rod point cloud data, the anchor rod is identified preliminarily; clustering the preliminarily identified anchor rod point cloud data by using a DBSCAN clustering method, and calculating the density of the preliminarily identified anchor rod point cloud data to regard anchor rods with different point cloud densities as different clustering categories to finally obtain point cloud data [ Bolt ] under different anchor rod categories1,Bolt2,···,Boltn]And n is the number of identification arches.
Further, the secondary lining quality evaluation module comprises a cavity detection submodule, a concrete thickness evaluation submodule and a wall construction quality evaluation submodule, the data preprocessing submodule is respectively connected with the cavity detection submodule and the concrete thickness evaluation submodule, and the concrete strength acquisition submodule is connected with the wall construction quality evaluation submodule;
the cavity detection submodule analyzes the point cloud data of the preprocessed tunnel secondary lining section, accurately identifies the height value of the cavity, and judges whether the concrete construction meets the construction requirement or not by comparing the control requirement with the control requirement of the height value of the cavity of the secondary lining section;
the concrete thickness evaluation submodule analyzes the point cloud data of the preprocessed secondary lining section, calculates the spraying thickness of the concrete of the secondary lining section, and judges whether the concrete thickness meets the construction requirement or not by comparing the spraying thickness with the spraying thickness designed by the concrete of the secondary lining section;
the wall construction quality evaluation submodule compares the actual concrete measurement strength of the secondary lining section measured by the concrete strength acquisition submodule with the design strength, and judges whether the concrete strength sprayed by the wall of the secondary lining section of the tunnel meets the construction requirements.
Further, the identification of the cavity carries out cylindrical surface fitting on the point cloud data of the tunnel secondary lining section after the pretreatment by a least square fitting method,acquiring a cylindrical surface where point cloud data of a secondary lining section of a tunnel are located; if the point cloud data is not in the fitting cylinder, the point cloud data is regarded as a hole area; height value of the cavity
Figure BDA0003068763190000051
(xhole,yhole,zhole) Is the cloud coordinates of points in the hollow area,
Figure BDA0003068763190000052
the coordinates of the tunnel axis point corresponding to the cavity area are obtained, and R is the design radius of the tunnel;
the thickness of the coating
Figure BDA0003068763190000053
(xaxis,yaxis,zaxis) Is the axial center point coordinate of the tunnel contour of the secondary lining section, (x)lining,ylining,zlining) And (3) carrying out point cloud coordinate of the profile of the tunnel section where the axis center point of the secondary lining section is located, wherein eta is the design thickness of concrete sprayed on the primary support section of the tunnel, and R is the design radius of the tunnel.
Further, the whole-process construction quality evaluation module is respectively connected with the undermining evaluation submodule, the blasting footage evaluation submodule, the arch frame construction quality evaluation submodule, the anchor rod construction quality evaluation submodule, the spraying quality evaluation submodule, the cavity detection submodule, the concrete thickness evaluation submodule and the wall surface construction quality evaluation submodule.
Further, the whole-process construction quality evaluation module can comprehensively grade the influence of the quality evaluation indexes of all the processes on the whole-process construction quality, and finally obtains the whole-process construction quality grade of the tunnel, and the implementation steps are as follows:
s5.1, selecting the lowest scores of the undermining evaluation submodule and the blasting footage evaluation submodule in the excavation procedure construction quality evaluation module as the scores of the excavation procedure construction quality evaluation module;
s5.2, selecting the lowest scores of an arch construction quality evaluation submodule, an anchor rod construction quality evaluation submodule and a spraying quality evaluation submodule in the primary support quality evaluation module as the scores of the primary support quality evaluation module;
s5.3, selecting the lowest scores of a cavity detection submodule, a concrete thickness evaluation submodule and a wall construction quality evaluation submodule in the secondary lining quality evaluation module as the scores of the secondary lining quality evaluation module;
and S5.4, accumulating and summing scores of the excavation procedure construction quality evaluation module, the primary support quality evaluation module and the secondary lining quality evaluation module to serve as a total score of the whole procedure construction quality evaluation module, and if the total score is within the range of 0-180, 180-225, 225-270 and 270-300, sequentially evaluating the whole procedure construction quality grades of the tunnel as excellent, good, passing and failing.
A digital evaluation method for tunnel whole-process construction quality comprises the following steps:
after blasting excavation is finished, scanning the tunnel face and the tunnel profile between the tunnel face and the secondary lining in the whole process by using a laser scanner to obtain three-dimensional point cloud data;
extracting point cloud data of tunnel face excavation sections, and calculating construction quality evaluation indexes in an excavation procedure;
extracting point cloud data of the primary support section, and calculating construction quality evaluation indexes of the primary support section;
extracting point cloud data of the secondary lining section, and calculating a construction quality evaluation index of the secondary lining section;
and comprehensively grading the influence of the quality evaluation indexes of the working procedures on the construction quality of the whole working procedure according to the quality evaluation indexes of the excavation working procedure section, the primary support section and the secondary lining section, and finally obtaining the construction quality grade of the whole working procedure of the tunnel.
Further, the construction quality evaluation indexes in the excavation working procedure comprise the excess excavation amount and the ratio of the actual blasting footage to the designed blasting footage of the tunnel; the construction quality evaluation indexes of the primary support section comprise the distance between adjacent arch frames, the ratio of the actual number of anchor rods to the designed number of anchor rods and the actual measured concrete strength of the primary support section; the construction quality evaluation indexes of the secondary lining section comprise the height value of the cavity, the spraying thickness of the concrete of the secondary lining section and the actual measurement strength of the concrete of the secondary lining section.
Further, the comprehensive rating comprises evaluating the construction quality of the whole process of the wall surface of the tunnel, and the implementation method comprises the following steps: the method comprises the steps of measuring tunnel wall surface concrete of a primary supporting section and a secondary lining section by using an intelligent electronic resiliometer, respectively obtaining concrete strength of the primary supporting section and the secondary lining section, comparing the obtained concrete strength with concrete design strength, and determining the whole-process construction quality score of the tunnel wall surface, so as to judge whether the concrete strength sprayed by the wall surface meets construction requirements.
Compared with the prior art, the invention has the beneficial effects that: the construction quality between all the procedures of the tunnel is digitally recorded by means of a laser scanning technology, 8 evaluation indexes of ultra-short excavation analysis evaluation, blasting footage evaluation, arch frame construction quality evaluation, anchor rod construction quality evaluation, spraying quality evaluation, cavity monitoring evaluation, concrete thickness evaluation and wall surface construction quality evaluation are provided for quantitatively evaluating the construction quality of the whole procedure, the problems of disjointed construction quality evaluation and poor overall evaluation effect among all the procedures of the tunnel are solved, and accurate evaluation and comprehensive grading of the construction quality of the whole procedure of a drilling and blasting method are realized.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a functional block diagram of an evaluation system of the present invention.
FIG. 2 is a functional block diagram of the data acquisition and preprocessing module of FIG. 1 according to the present invention.
FIG. 3 is a functional block diagram of the quality evaluation module of FIG. 1 according to the present invention.
Fig. 4 is a functional frame diagram of the module for evaluating the quality of preliminary bracing in fig. 1 according to the present invention.
FIG. 5 is a functional frame diagram of the secondary lining quality evaluation module shown in FIG. 1 according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without inventive effort based on the embodiments of the present invention, are within the scope of the present invention.
Embodiment 1, as shown in fig. 1, a digital evaluation system for tunnel whole process construction quality includes a data acquisition and preprocessing module, an excavation process quality evaluation module, a primary support quality evaluation module, a secondary lining quality evaluation module, and a whole process construction quality evaluation module, wherein the data acquisition and preprocessing module is respectively connected to the excavation process quality evaluation module, the primary support quality evaluation module, and the secondary lining quality evaluation module, the excavation process quality evaluation module, the primary support quality evaluation module, and the secondary lining quality evaluation module are all connected to the whole process construction quality evaluation module, and the data acquisition and preprocessing module preprocesses acquired three-dimensional point cloud data and transmits the three-dimensional point cloud data to the excavation process quality evaluation module, the primary support quality evaluation module, and the secondary lining quality evaluation module; the excavation procedure quality evaluation module analyzes the point cloud data of the tunnel face excavation section after pretreatment and calculates the construction quality evaluation index of the excavation procedure section; the primary support quality evaluation module analyzes the point cloud data and the concrete strength data of the pretreated primary support section and calculates the construction quality evaluation index of the primary support section; the secondary lining quality evaluation module analyzes the point cloud data and the concrete strength data of the preprocessed secondary lining section and calculates the construction quality evaluation index of the secondary lining section; and according to the construction quality evaluation indexes of the excavation process section, the primary support section and the secondary lining section, the whole-process construction quality evaluation module comprehensively grades the quality evaluation indexes of all the processes, and finally obtains the whole-process construction quality grade of the tunnel.
As shown in fig. 2, the data acquisition and preprocessing module includes a laser scanning acquisition sub-module, a concrete strength acquisition sub-module and a data preprocessing sub-module, the laser scanning acquisition sub-module is connected with the data preprocessing sub-module, the data preprocessing sub-module is connected with the excavation process quality evaluation module, the preliminary bracing quality evaluation module and the secondary lining quality evaluation module, respectively, and the concrete strength acquisition sub-module is connected with the preliminary bracing quality evaluation module and the secondary lining quality evaluation module, respectively.
The laser scanning acquisition sub-module scans the tunnel face and the tunnel contour between the tunnel face and the secondary lining in the whole process by using a total station scanner to acquire three-dimensional point cloud data under a geodetic absolute coordinate system, wherein the data are X coordinates, Y coordinates, Z coordinates and echo intensity values, spherical targets are respectively arranged between the face excavation process and the primary support process and between the primary support process and the secondary lining process as coordinate known points, and the ground coordinates of the targets are conveniently utilized for point cloud segmentation in the later period. The concrete strength obtaining submodule utilizes the intelligent electronic resiliometer to measure concrete sprayed on the tunnel rock walls in the primary supporting section and the secondary lining section respectively, and obtains concrete spraying strength values of the primary supporting section and the secondary lining section. The data preprocessing submodule carries out scanning parameter setting, noise point data elimination and point cloud data segmentation on the three-dimensional point cloud data acquired by the laser scanning acquisition submodule, and the specific implementation steps are as follows:
s1.3.1, by modifying the setting parameters of the total station laser scanner: scanning distance, point spacing and scanning mode, so that the precision of the obtained three-dimensional point cloud data meets the requirement of a field, and the configurability of scanning parameters is realized;
s1.3.2, counting the range of the echo intensity of the point cloud corresponding to non-target objects such as trolleys and constructors in the tunnel, and rejecting noise data such as trolleys and constructors if the echo intensity in the original point cloud data is within the range of the echo intensity of the point cloud of the non-target objects by comparing the echo intensity in the original point cloud data with the range of the echo intensity of the point cloud of the non-target objects. And the original point cloud data is three-dimensional point cloud data under an earth absolute coordinate system, which is obtained by scanning the tunnel face and the tunnel contour between the tunnel face and the secondary lining in the whole process by using a total station type scanner.
S1.3.3, segmenting the tunnel point cloud data preprocessed in the step S1.3.2 according to the geodetic absolute coordinates of the spherical target between the tunnel face excavation process and the primary support process and the geodetic absolute coordinates of the spherical target between the primary support process and the secondary lining process, and respectively obtaining the point cloud data of the tunnel face excavation section, the primary support section and the secondary lining section.
As shown in fig. 3, the excavation process quality evaluation module analyzes the point cloud data of the tunnel face excavation section after the pretreatment, calculates quantitative face excavation quality evaluation indexes for digital evaluation, and can be divided into a point cloud data analysis submodule, an undermining evaluation submodule and a blasting footage evaluation submodule, wherein the point cloud data analysis submodule is respectively connected with the undermining evaluation submodule and the blasting footage evaluation submodule.
And the point cloud data analysis submodule sequentially selects M points from the boundary point cloud area in a clockwise or anticlockwise direction in the boundary point cloud area of the tunnel face and the peripheral outline in a man-machine interaction mode to form a closed polygonal area, so that the point cloud data of the tunnel face can be conveniently extracted. If the point cloud data of the excavation section is located in the closed polygonal area, the point cloud data of the tunnel face of the excavation section is regarded as the point cloud data of the tunnel face of the excavation section; otherwise, the point cloud data of the tunnel profile of the excavation section is regarded as point cloud data. The number M of the selected points can be set to be 20-30, and the points need to be uniformly distributed along the axial direction of the tunnel, so that the integrity of the cloud data extraction of the tunnel face points is ensured.
And the super-under excavation evaluation submodule is used for carrying out super-under excavation analysis on the point cloud data of the tunnel profile of the preprocessed excavation section, calculating the super-under excavation amount and evaluating the construction quality of the tunnel profile of the excavation section. The super short cut amount passes
Figure BDA0003068763190000081
Calculated to obtain (x)axis,yaxis,zaxis) The method comprises the following steps of (1) obtaining an axial center point coordinate of an excavation section tunnel outline, (x, y, z) obtaining an outline point cloud coordinate of a tunnel section where the excavation section axial center point is located, (R) obtaining a tunnel design radius, and (delta) obtaining an overbreak and underbreak amount corresponding to the tunnel outline point cloud. And the blasting footage evaluation submodule judges whether the profile of the tunnel at the excavation section meets the undermining requirement or not by comparing the actually calculated undermining amount with the undermining control requirement. And if the over-under excavation amount of the tunnel profile of the excavation section is respectively in a range of more than 30cm, 20-30 cm, 10-20 cm and within 10cm, the construction quality score of the tunnel profile of the excavation section is correspondingly 0-40 min, 40-60 min, 60-80 min and 80-100 min.
And the blasting footage evaluation submodule analyzes the point cloud data of the tunnel face of the preprocessed excavation section tunnel and calculates the actual blasting footage of the tunnel. Blasting footage through
Figure BDA0003068763190000091
Calculated, where j ═ 1,2, · · N, (x)axis,yaxis,zaxis) For the axial center point coordinates of the tunnel profile of the excavation section,
Figure BDA0003068763190000092
cloud coordinates of face points of the tunnel excavation section, N is the cloud number of face points of the tunnel excavation section, dblastingAnd (5) blasting footage of the tunnel face of the tunnel excavation section. And the blasting footage evaluation submodule takes the actual blasting footage/the designed blasting footage as the footage rate and is used for evaluating the construction quality of the tunnel face of the excavation section. And if the blasting footage of the tunnel face of the excavation section is respectively below 75%, 75-85%, 85-95% and 95-100%, the construction quality scores of the tunnel face of the excavation section are respectively 0-40 min, 40-60 min, 60-80 min and 80-100 min.
As shown in fig. 4, the preliminary bracing quality evaluation module analyzes the point cloud data of the preliminary bracing section of the tunnel after pretreatment, calculates quantitative preliminary bracing quality evaluation indexes for digital evaluation, and can be divided into an arch construction quality evaluation submodule, an anchor construction quality evaluation submodule and a spraying quality evaluation submodule, the data pretreatment submodule is respectively connected with the arch construction quality evaluation submodule and the anchor construction quality evaluation submodule, and the concrete strength acquisition submodule is connected with the spraying quality evaluation submodule.
And the arch construction quality evaluation submodule analyzes the point cloud data of the preprocessed primary support section, accurately identifies the number and position coordinates of arches of the primary support section of the tunnel, and calculates the distance between the arches of the primary support section of the tunnel. The arch center identification is realized by counting the echo intensity range of the corresponding point cloud data on the surface of the arch center1,intensity2]Filtering the preprocessed point cloud data of the primary support section, and if the echo intensity of the point cloud data is within the threshold range [ intensity ]1,intensity2]And if so, the data is regarded as arch point cloud data, so that the preliminary identification of the arch is realized. Clustering the preliminarily identified arch point cloud data by using a DBSCAN clustering method, and calculating the density of the preliminarily identified arch point cloud data to regard arches with different point cloud densities as different clustering categories to finally obtain point cloud data [ arch ] under different arch category1,arch2,···,archm]And m is the number of identification arches. The actual distance between two adjacent arch frames passes through
Figure BDA0003068763190000093
j is more than i and less than or equal to m, and i-j is obtained by calculation as 1,
Figure BDA0003068763190000094
Figure BDA0003068763190000095
the data are respectively the point cloud data of the surfaces of the i-th arch and the j-th arch, and d is the actual distance between the adjacent i-th arch and the j-th arch. The distance between two adjacent arches is actually measured and compared with the distance between two adjacent arches, and the arch distance deviation value delta d is calculated as | d-ddesign|，ddesignThe distance between adjacent arches is designed so as to judge whether the construction quality of the arches meets the field requirement. Taking IV surrounding rock as an example, the arch center spacing is 0.8m, if the absolute value of the arch spacing deviation is respectively within more than 10cm, 5 cm-10 cm and 5cmThe construction quality of the arch frame is 0-60 minutes, 60-80 minutes and 80-100 minutes.
And the anchor rod construction quality evaluation submodule analyzes the point cloud data of the preliminary bracing section to accurately identify the number and position coordinates of anchor rods in the preliminary bracing section of the tunnel. The identification of the anchor rod at the primary support section of the tunnel is realized by counting the echo intensity range of the corresponding point cloud data on the surface of the anchor rod3,intensity4]Filtering the preprocessed point cloud data of the primary support section, and if the echo intensity of the point cloud data is within the threshold range [ intensity ]3,intensity4]And the data is regarded as anchor rod point cloud data, so that the initial identification of the anchor rod is realized. Clustering the preliminarily identified anchor rod point cloud data by using a DBSCAN clustering method, and calculating the density of the preliminarily identified anchor rod point cloud data to regard anchor rods with different point cloud densities as different clustering categories to finally obtain point cloud data [ Bolt ] under different anchor rod categories1,Bolt2,···,Boltn]And n is the number of identification arches. The anchor rod construction quality evaluation submodule takes the ratio of the actual number of the anchor rods to the designed number of the anchor rods as an evaluation index, and judges whether the number of the anchor rods meets the design requirement during primary support. If the ratio of the actual number of the anchor rods to the designed number of the anchor rods is within 80%, 80% -95% and exceeds 95%, the construction quality of the anchor rods is 0-60 min, 60-80 min and 80-100 min.
And the spraying quality evaluation submodule compares the actual measured strength of the concrete of the primary support section measured by the concrete strength acquisition submodule with the design strength and judges whether the strength of the concrete sprayed on the wall surface of the tunnel meets the construction requirements or not. The design strength is determined in the specification according to the characteristics of concrete materials and the setting time after spraying. Taking IV surrounding rock as an example, C25 concrete is adopted to spray the tunnel rock wall, and if the actual measured strength of the concrete is less than 10MPa and 10-15 MPa after 24 hours, the evaluation scores of the concrete strength are 0-60 minutes and 60-100 minutes respectively.
The concrete strength value is obtained by measuring the tunnel concrete wall surface through the intelligent electronic resiliometer, and the concrete strength value can be measured after the concrete is sprayed for 24 hours before measurement, so that the condensed tunnel wall surface has certain self-stability.
As shown in fig. 5, the secondary lining quality evaluation module analyzes the point cloud data of the preprocessed tunnel secondary lining section, calculates a quantified secondary lining quality evaluation index, and performs digital evaluation, and the evaluation can be divided into a cavity detection submodule, a concrete thickness evaluation submodule and a wall construction quality evaluation submodule. The data preprocessing submodule is respectively connected with the cavity detection submodule and the concrete thickness evaluation submodule, and the concrete strength obtaining submodule is connected with the wall surface construction quality evaluation submodule.
And the cavity detection submodule analyzes the point cloud data of the preprocessed tunnel secondary lining section to accurately identify the height value of the cavity. Considering that the plane where the cavity is located and the wall surface of the secondary lining section tunnel are not in the same cylindrical surface, the cavity identification is used for performing cylindrical surface fitting on the point cloud data of the preprocessed tunnel secondary lining section through a least square fitting method to obtain the cylindrical surface where the point cloud data of the tunnel secondary lining section is located. And if the point cloud data is not in the fitting cylinder, the point cloud data is regarded as a hole area. Height value of cavity passing through
Figure BDA0003068763190000101
Calculated to obtain (x)hole,yhole,zhole) Is the cloud coordinates of points in the hollow area,
Figure BDA0003068763190000102
the method comprises the steps of obtaining tunnel center point coordinates corresponding to a cavity area, wherein R is a tunnel design radius, and sigma is a cavity height value. And the cavity detection submodule judges whether the concrete construction meets the construction requirements or not by comparing the cavity detection submodule with the control requirements of the cavity height value of the secondary lining section. If the height of the cavity is respectively within the range of more than or equal to 45cm, 30 cm-45 cm, 5 cm-30 cm and less than or equal to 5cm, the detection and evaluation of the cavity are divided into 0-40 min, 40-60 min, 60-80 min and 80-100 min.
And the concrete thickness evaluation submodule analyzes the point cloud data of the preprocessed secondary lining section and calculates the spraying thickness of the concrete of the secondary lining section. Thickness of the coating is passed
Figure BDA0003068763190000103
Calculated to obtain (x)axis,yaxis,zaxis) Is the axial center point coordinate of the tunnel contour of the secondary lining section, (x)lining,ylining,zlining) And (3) carrying out point cloud coordinate of the profile of the section of the tunnel where the axial center point of the secondary lining section is located, wherein eta is the design thickness of concrete sprayed on the primary support section of the tunnel, R is the design radius of the tunnel, and epsilon is the spraying thickness of the concrete of the secondary lining section. And comparing the thickness with the spraying thickness designed by the concrete of the secondary lining section to judge whether the thickness of the concrete meets the construction requirement. And if the spraying thickness of the concrete of the secondary lining section is within 45cm and exceeds 45 ranges, the evaluation scores of the thickness of the concrete are 0-60 minutes and 60-100 minutes.
The wall construction quality evaluation submodule compares the actual concrete measurement strength of the secondary lining section measured by the concrete strength acquisition submodule with the design strength, and judges whether the concrete strength sprayed by the wall of the secondary lining section of the tunnel meets the construction requirements. The design strength is determined in the specification according to the characteristics of concrete materials and the setting time after spraying. Taking IV surrounding rock as an example, C25 concrete is adopted to spray the tunnel rock wall, if the actual measured strength of the concrete is less than 10MPa and 10-15 MPa after 24 hours, the wall construction quality is divided into 0-60 minutes and 60-100 minutes.
The concrete strength value is obtained by measuring the tunnel concrete wall surface through the intelligent electronic resiliometer, and the concrete strength value can be measured after the concrete is sprayed for 24 hours before measurement, so that the condensed tunnel wall surface has certain self-stability.
The whole-process construction quality evaluation module is respectively connected with the undermining evaluation submodule, the blasting footage evaluation submodule, the arch construction quality evaluation submodule, the anchor rod construction quality evaluation submodule, the spraying quality evaluation submodule, the cavity detection submodule, the concrete thickness evaluation submodule and the wall construction quality evaluation submodule. The whole-process construction quality evaluation module can comprehensively grade the influence of the quality evaluation indexes of all the processes on the whole-process construction quality, and finally obtains the whole-process construction quality grade of the tunnel, and the specific implementation steps are as follows:
s5.1, selecting the lowest scores of the undermining evaluation submodule and the blasting footage evaluation submodule in the excavation procedure construction quality evaluation module as the scores of the excavation procedure construction quality evaluation module, so that project managers can accurately position evaluation indexes with lower scores in the excavation procedure, and the operation flow of the construction procedure is optimized in time;
s5.2, selecting the lowest scores of an arch construction quality evaluation submodule, an anchor rod construction quality evaluation submodule and a spraying quality evaluation submodule in the primary support quality evaluation module as scores of the primary support quality evaluation module, so that project managers can accurately position evaluation indexes with lower scores in the primary support, and the operation flow of the construction process can be optimized in time;
s5.3, selecting the lowest scores of a cavity detection submodule, a concrete thickness evaluation submodule and a wall construction quality evaluation submodule in the secondary lining quality evaluation module as scores of the secondary lining quality evaluation module, so that project managers can accurately position evaluation indexes with lower scores in the secondary lining, and the operation flow of a construction process can be optimized in time;
and S5.4, accumulating and summing scores of the excavation procedure construction quality evaluation module, the primary support quality evaluation module and the secondary lining quality evaluation module to serve as a total score of the whole procedure construction quality evaluation module, and if the total score is within the range of 0-180, 180-225, 225-270 and 270-300, sequentially evaluating the whole procedure construction quality grades of the tunnel as excellent, good, passing and failing.
The invention can comprehensively grade the influence of the quality evaluation indexes of each process on the construction quality of the whole process, and has good universality.
Embodiment 2, a method for digitally evaluating the construction quality of a tunnel in a whole process, comprising the following steps: after blasting excavation is finished, scanning the tunnel face and the tunnel profile between the tunnel face and the secondary lining in the whole process by using a laser scanner to obtain three-dimensional point cloud data; extracting point cloud data of tunnel face excavation sections, and calculating construction quality evaluation indexes in an excavation procedure; extracting point cloud data of the primary support section, and calculating construction quality evaluation indexes of the primary support section; extracting point cloud data of the secondary lining section, and calculating a construction quality evaluation index of the secondary lining section; according to the quality evaluation indexes of the excavation process section, the primary support section and the secondary lining section, the influence of the quality evaluation indexes of the processes on the construction quality of the whole process is comprehensively graded, the construction quality grade of the whole process of the tunnel is finally obtained, and the tunnel construction method has good universality.
Preferably, the construction quality evaluation indexes in the excavation working procedure comprise the excess excavation amount and the ratio of the actual blasting footage to the designed blasting footage of the tunnel; the construction quality evaluation indexes of the primary support section comprise the distance between adjacent arch frames, the ratio of the actual number of anchor rods to the designed number of anchor rods and the actual measured concrete strength of the primary support section; the construction quality evaluation indexes of the secondary lining section comprise the height value of the cavity, the spraying thickness of the concrete of the secondary lining section and the actual measurement strength of the concrete of the secondary lining section.
Preferably, the comprehensive rating includes evaluating the construction quality of the tunnel wall surface in the whole process, and the implementation method includes: the method comprises the steps of measuring tunnel wall surface concrete of a primary supporting section and a secondary lining section by using an intelligent electronic resiliometer, respectively obtaining concrete strength of the primary supporting section and the secondary lining section, comparing the obtained concrete strength with concrete design strength, and determining the whole-process construction quality score of the tunnel wall surface, so as to judge whether the concrete strength sprayed by the wall surface meets construction requirements.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.

Claims (15)

1. The digital evaluation system for the tunnel whole-process construction quality is characterized by comprising a data acquisition and preprocessing module, an excavation process quality evaluation module, a primary support quality evaluation module, a secondary lining quality evaluation module and a whole-process construction quality evaluation module, wherein the data acquisition and preprocessing module is respectively connected with the excavation process quality evaluation module, the primary support quality evaluation module and the secondary lining quality evaluation module, and the excavation process quality evaluation module, the primary support quality evaluation module and the secondary lining quality evaluation module are all connected with the whole-process construction quality evaluation module.
2. The digital evaluation system for the whole-procedure construction quality of the tunnel according to claim 1, wherein the data acquisition and preprocessing module preprocesses the acquired three-dimensional point cloud data and transmits the three-dimensional point cloud data to the excavation procedure quality evaluation module, the primary support quality evaluation module and the secondary lining quality evaluation module; the excavation procedure quality evaluation module analyzes the point cloud data of the tunnel face excavation section after pretreatment and calculates the construction quality evaluation index of the excavation procedure section; the primary support quality evaluation module analyzes the point cloud data and the concrete strength data of the pretreated primary support section and calculates the construction quality evaluation index of the primary support section; the secondary lining quality evaluation module analyzes the point cloud data and the concrete strength data of the preprocessed secondary lining section and calculates the construction quality evaluation index of the secondary lining section; and the whole-process construction quality evaluation module comprehensively grades the quality evaluation indexes of all the processes according to the construction quality evaluation indexes of the excavation process section, the primary support section and the secondary lining section, and finally obtains the whole-process construction quality grade of the tunnel.
3. The digital evaluation system for the whole-procedure construction quality of the tunnel according to claim 2, wherein the data acquisition and preprocessing module comprises a laser scanning acquisition sub-module, a concrete strength acquisition sub-module and a data preprocessing sub-module, the laser scanning acquisition sub-module is connected with the data preprocessing sub-module, the data preprocessing sub-module is connected with the excavation procedure quality evaluation module, the primary support quality evaluation module and the secondary lining quality evaluation module respectively, and the concrete strength acquisition sub-module is connected with the primary support quality evaluation module and the secondary lining quality evaluation module respectively.
4. The digital evaluation system for tunnel whole-process construction quality according to claim 3, wherein the laser scanning acquisition sub-module performs whole-process scanning on a tunnel face and a tunnel contour between the tunnel face and a secondary lining by using a total-station scanner to acquire three-dimensional point cloud data under an earth absolute coordinate system; the concrete strength obtaining submodule utilizes an intelligent electronic resiliometer to measure concrete sprayed on the tunnel rock walls in the primary supporting section and the secondary lining section respectively, and obtains concrete spraying strength values of the primary supporting section and the secondary lining section; the data preprocessing submodule carries out scanning parameter setting, noise point data elimination and point cloud data segmentation on the three-dimensional point cloud data acquired by the laser scanning acquisition submodule, and respectively acquires point cloud data of a tunnel face excavation section, a primary support section and a secondary lining section; the types of the point cloud data are X coordinates, Y coordinates, Z coordinates and echo intensity values.
5. The digital evaluation system for the tunnel whole-process construction quality according to claim 3 or 4, wherein the excavation process quality evaluation module comprises a point cloud data analysis submodule, an undermining evaluation submodule and a blasting footage evaluation submodule, and the point cloud data analysis submodule is respectively connected with the undermining evaluation submodule and the blasting footage evaluation submodule;
the point cloud data analysis submodule sequentially selects M points from the boundary point cloud area in a clockwise or anticlockwise direction in the boundary point cloud area of the tunnel face and the peripheral outline through a man-machine interaction mode to form a closed polygonal area, and if the point cloud data of the excavation section is located in the closed polygonal area, the point cloud data of the tunnel face of the excavation section is regarded as the point cloud data of the tunnel face of the excavation section; otherwise, the point cloud data of the tunnel profile of the excavation section is regarded as point cloud data;
the super-under excavation evaluation submodule is used for carrying out super-under excavation analysis on point cloud data of the preprocessed tunnel outline of the excavation section, calculating the super-under excavation amount, comparing the super-under excavation amount with the super-under excavation control requirement, judging whether the tunnel outline of the excavation section meets the super-under excavation requirement or not, and evaluating the construction quality of the tunnel outline of the excavation section;
and the blasting footage evaluation submodule analyzes the point cloud data of the tunnel face of the preprocessed excavation section, calculates the actual blasting footage of the tunnel, and evaluates the construction quality of the tunnel face of the excavation section by taking the actual blasting footage/designed blasting footage as a footage rate.
6. The digital evaluation system for tunnel whole procedure construction quality according to claim 5, wherein the amount of overbreak and underexcavation is determined by the digital evaluation system
Figure FDA0003068763180000021
Wherein (x)axis,yaxis,zaxis) The method comprises the following steps of (1) obtaining an axial center point coordinate of an excavation section tunnel outline, (x, y, z) obtaining an outline point cloud coordinate of a tunnel section where the excavation section axial center point is located, and R is a tunnel design radius;
the blasting footage
Figure FDA0003068763180000022
Wherein j is 1,2, N,
Figure FDA0003068763180000023
cloud coordinates of face points of the tunnel excavation section, N is the cloud number of face points of the tunnel excavation section, dblastingAnd (5) blasting footage of the tunnel face of the tunnel excavation section.
7. The digital evaluation system for the tunnel whole-process construction quality according to claim 5, wherein the primary support quality evaluation module comprises an arch construction quality evaluation submodule, an anchor rod construction quality evaluation submodule and a spraying quality evaluation submodule, the data preprocessing submodule is respectively connected with the arch construction quality evaluation submodule and the anchor rod construction quality evaluation submodule, and the concrete strength acquisition submodule is connected with the spraying quality evaluation submodule;
the arch center construction quality evaluation submodule analyzes and refines the point cloud data of the preprocessed primary support sectionThe number and the position coordinates of arches of the primary support section of the tunnel are identified, and the distance between the arches of the primary support section of the tunnel is calculated; calculating the arch spacing deviation value delta d ═ d-d by comparing the calculated distance between two adjacent arches with the distance between the designed adjacent archesdesign|，ddesignThe distance between adjacent arch frames is designed so as to judge whether the construction quality of the arch frames meets the field requirement;
the anchor rod construction quality evaluation submodule analyzes point cloud data of a pre-processed primary support section and accurately identifies the number and position coordinates of anchor rods of the primary support section of the tunnel; taking the ratio of the actual number of the anchor rods to the designed number of the anchor rods as an evaluation index, and judging whether the number of the anchor rods meets the design requirement during primary support;
and the spraying quality evaluation submodule compares the actual measured strength of the concrete of the primary support section measured by the concrete strength acquisition submodule with the design strength and judges whether the strength of the concrete sprayed on the wall surface of the tunnel meets the construction requirements or not.
8. The digital evaluation system for tunnel whole-process construction quality according to claim 7, wherein the identification of the arch of the tunnel primary supporting section is carried out by counting the echo intensity range [ intensity ] of the point cloud data corresponding to the surface of the arch1,intensity2]Filtering the preprocessed point cloud data of the primary support section, and if the echo intensity of the point cloud data is within the threshold range [ intensity ]1,intensity2]If the data is internal, the data is regarded as arch center point cloud data, so that the preliminary identification of the arch center is realized; clustering the preliminarily identified arch point cloud data by using a DBSCAN clustering method, and calculating the density of the preliminarily identified arch point cloud data to regard arches with different point cloud densities as different clustering categories to finally obtain point cloud data [ arch ] under different arch category1,arch2,···,archm]M is the number of identification arches; the actual distance between two adjacent arch frames passes through
Figure FDA0003068763180000031
j is more than i and less than or equal to m, and i-j is calculated to be 1，
Figure FDA0003068763180000032
Respectively point cloud data of surfaces of adjacent i-th and j-th arches, wherein d is an actual distance between the adjacent i-th and j-th arches;
the identification of the anchor rod at the primary support section of the tunnel is realized by counting the echo intensity range of the corresponding point cloud data on the surface of the anchor rod3,intensity4]Filtering the preprocessed point cloud data of the primary support section, and if the echo intensity of the point cloud data is within the threshold range [ intensity ]3,intensity4]If the point cloud data is not the anchor rod point cloud data, the anchor rod is identified preliminarily; clustering the preliminarily identified anchor rod point cloud data by using a DBSCAN clustering method, and calculating the density of the preliminarily identified anchor rod point cloud data to regard anchor rods with different point cloud densities as different clustering categories to finally obtain point cloud data [ Bolt ] under different anchor rod categories1,Bolt2,···,Boltn]And n is the number of identification arches.
9. The digital evaluation system for the tunnel whole-process construction quality according to claim 7, wherein the secondary lining quality evaluation module comprises a cavity detection submodule, a concrete thickness evaluation submodule and a wall construction quality evaluation submodule, the data preprocessing submodule is respectively connected with the cavity detection submodule and the concrete thickness evaluation submodule, and the concrete strength acquisition submodule is connected with the wall construction quality evaluation submodule;
the cavity detection submodule analyzes the point cloud data of the preprocessed tunnel secondary lining section, accurately identifies the height value of the cavity, and judges whether the concrete construction meets the construction requirement or not by comparing the control requirement with the control requirement of the height value of the cavity of the secondary lining section;
the concrete thickness evaluation submodule analyzes the point cloud data of the preprocessed secondary lining section, calculates the spraying thickness of the concrete of the secondary lining section, and judges whether the concrete thickness meets the construction requirement or not by comparing the spraying thickness with the spraying thickness designed by the concrete of the secondary lining section;
the wall construction quality evaluation submodule compares the actual concrete measurement strength of the secondary lining section measured by the concrete strength acquisition submodule with the design strength, and judges whether the concrete strength sprayed by the wall of the secondary lining section of the tunnel meets the construction requirements.
10. The digital evaluation system for tunnel whole-process construction quality according to claim 9, characterized in that the identification of the cavities is performed with cylindrical surface fitting on the point cloud data of the preprocessed tunnel secondary lining section by a least square fitting method to obtain a cylindrical surface where the point cloud data of the tunnel secondary lining section is located; if the point cloud data is not in the fitting cylinder, the point cloud data is regarded as a hole area; height value of the cavity
Figure FDA0003068763180000041
(xhole,yhole,zhole) Is the cloud coordinates of points in the hollow area,
Figure FDA0003068763180000042
the coordinates of the tunnel axis point corresponding to the cavity area are obtained, and R is the design radius of the tunnel;
the thickness of the coating
Figure FDA0003068763180000043
(xaxis,yaxis,zaxis) Is the axial center point coordinate of the tunnel contour of the secondary lining section, (x)lining,ylining,zlining) And (3) carrying out point cloud coordinate of the profile of the tunnel section where the axis center point of the secondary lining section is located, wherein eta is the design thickness of concrete sprayed on the primary support section of the tunnel, and R is the design radius of the tunnel.
11. The digital evaluation system for the whole-process construction quality of the tunnel according to claim 9, wherein the whole-process construction quality evaluation module is respectively connected with an undermining evaluation submodule, a blasting footage evaluation submodule, an arch construction quality evaluation submodule, an anchor rod construction quality evaluation submodule, a spraying quality evaluation submodule, a cavity detection submodule, a concrete thickness evaluation submodule and a wall construction quality evaluation submodule.
12. The digital evaluation system for the whole tunnel process construction quality according to claim 11, wherein the whole process construction quality evaluation module can comprehensively grade the influence of the quality evaluation indexes of each process on the whole process construction quality, and finally obtain the whole tunnel process construction quality grade, and the implementation steps are as follows:
s5.1, selecting the lowest scores of the undermining evaluation submodule and the blasting footage evaluation submodule in the excavation procedure construction quality evaluation module as the scores of the excavation procedure construction quality evaluation module;
s5.2, selecting the lowest scores of an arch construction quality evaluation submodule, an anchor rod construction quality evaluation submodule and a spraying quality evaluation submodule in the primary support quality evaluation module as the scores of the primary support quality evaluation module;
s5.3, selecting the lowest scores of a cavity detection submodule, a concrete thickness evaluation submodule and a wall construction quality evaluation submodule in the secondary lining quality evaluation module as the scores of the secondary lining quality evaluation module;
and S5.4, accumulating and summing scores of the excavation procedure construction quality evaluation module, the primary support quality evaluation module and the secondary lining quality evaluation module to serve as a total score of the whole procedure construction quality evaluation module, and if the total score is within the range of 0-180, 180-225, 225-270 and 270-300, sequentially evaluating the whole procedure construction quality grades of the tunnel as excellent, good, passing and failing.
13. A digital evaluation method for tunnel whole-process construction quality is characterized by comprising the following steps:
after blasting excavation is finished, scanning the tunnel face and the tunnel profile between the tunnel face and the secondary lining in the whole process by using a laser scanner to obtain three-dimensional point cloud data;
extracting point cloud data of tunnel face excavation sections, and calculating construction quality evaluation indexes in an excavation procedure;
extracting point cloud data of the primary support section, and calculating construction quality evaluation indexes of the primary support section;
extracting point cloud data of the secondary lining section, and calculating a construction quality evaluation index of the secondary lining section;
and comprehensively grading the influence of the quality evaluation indexes of the working procedures on the construction quality of the whole working procedure according to the quality evaluation indexes of the excavation working procedure section, the primary support section and the secondary lining section, and finally obtaining the construction quality grade of the whole working procedure of the tunnel.
14. The digitized evaluation method for tunnel whole-process construction quality according to claim 13, wherein the evaluation indexes for construction quality in the excavation process comprise the out-of-cut amount and the ratio of the actual blasting footage to the designed blasting footage of the tunnel; the construction quality evaluation indexes of the primary support section comprise the distance between adjacent arch frames, the ratio of the actual number of anchor rods to the designed number of anchor rods and the actual measured concrete strength of the primary support section; the construction quality evaluation indexes of the secondary lining section comprise the height value of the cavity, the spraying thickness of the concrete of the secondary lining section and the actual measurement strength of the concrete of the secondary lining section.
15. The method for digitally evaluating the construction quality of the whole tunnel process according to claim 13 or 14, wherein the comprehensive rating includes evaluating the construction quality of the whole tunnel wall surface, and the method includes: the method comprises the steps of measuring tunnel wall surface concrete of a primary supporting section and a secondary lining section by using an intelligent electronic resiliometer, respectively obtaining concrete strength of the primary supporting section and the secondary lining section, comparing the obtained concrete strength with concrete design strength, and determining the whole-process construction quality score of the tunnel wall surface, so as to judge whether the concrete strength sprayed by the wall surface meets construction requirements.
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