A loess roadbed side slope assembly type supporting structure deformation monitoring method and system

Abstract

The present application provides a kind of loess roadbed slope assembly type supporting structure deformation monitoring method and system, it is related to slope monitoring technical field.The method comprises: layout three-dimensional displacement sensor array;Obtain the panel specification parameter of the supporting panel;Obtain loess density;According to the panel specification parameter and the loess density, determine the adjacent sensor spacing of three-dimensional displacement sensor array;Obtain the node displacement vector of multiple nodes of multiple supporting panels;According to the node displacement vector and the adjacent sensor spacing, determine supporting structure local curvature distortion coefficient;According to the supporting structure local curvature distortion coefficient, the panel specification parameter and the node displacement vector, determine deformation early warning condition.According to the present application, adjacent sensor spacing can be adjusted, and supporting structure local curvature distortion and displacement vector angle are combined to monitor the deformation condition of supporting structure, improve the reliability and accuracy of deformation early warning, and reduce monitoring cost.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of slope monitoring, and particularly relates to a loess roadbed slope assembled supporting structure deformation monitoring method and system. BACKGROUND

[0002] In the related art, although the supporting deformation and the slope data can be monitored in real time, the sensor arrangement mode, the local curvature distortion of the supporting structure and the displacement vector angle are not considered, and the supporting structure deformation cannot be monitored by adjusting the adjacent sensor spacing and combining the local curvature distortion of the supporting structure and the displacement vector angle.

[0003] The information disclosed in the background section of this application is only intended to enhance the understanding of the general background of the application and should not be considered as recognition or any form of suggestion that this information forms the prior art that is known to those skilled in the art. SUMMARY

[0004] The present application provides a loess roadbed slope assembled supporting structure deformation monitoring method and system, which can solve the technical problem that the supporting structure deformation cannot be monitored by adjusting the adjacent sensor spacing and combining the local curvature distortion of the supporting structure and the displacement vector angle in the related art.

[0005] According to a first aspect of the present application, a loess roadbed slope assembled supporting structure deformation monitoring method is provided, comprising: arranging a three-dimensional displacement sensor array at a plurality of supporting panels of an assembled supporting structure, wherein the three-dimensional displacement sensor array is distributed in a rectangular grid form; obtaining panel specification parameters of the supporting panels, wherein the panel specification parameters include yield strength, panel elastic modulus and panel thickness; drilling a loess sample at a loess roadbed slope to obtain loess density; determining an adjacent sensor spacing of the three-dimensional displacement sensor array according to the panel specification parameters and the loess density; obtaining node displacement vectors of a plurality of nodes of a plurality of supporting panels according to the three-dimensional displacement sensor array; determining a local curvature distortion coefficient of the supporting structure according to the node displacement vectors and the adjacent sensor spacing; and determining a deformation warning condition according to the local curvature distortion coefficient of the supporting structure, the panel specification parameters and the node displacement vectors.

[0006] Further, determining the adjacent sensor spacing of the three-dimensional displacement sensor array according to the panel specification parameters and the loess density comprises: obtaining a slope inclination of a loess roadbed slope position where the plurality of supporting panels are located; and determining the adjacent sensor spacing of the three-dimensional displacement sensor array according to the slope inclination, the panel specification parameters and the loess density.

[0007] Furthermore, the adjacent sensor spacing of the three-dimensional displacement sensor array is determined according to the slope inclination, the panel specification parameters and the loess density, including: according to the formula Determine the adjacent sensor spacing of the three-dimensional displacement sensor array of the nth support panel , where E is the elastic modulus of the panel, H is the thickness of the panel, is the density of loess, is the acceleration due to gravity, is the slope inclination angle of the loess roadbed slope where the nth support panel is located.

[0008] Furthermore, the local curvature distortion coefficient of the support structure is determined based on the node displacement vector and the adjacent sensor spacing, including: determining the node displacement vector modulus of multiple nodes of multiple support panels based on the node displacement vector; determining the local curvature distortion coefficient of the support structure based on the node displacement vector modulus and the adjacent sensor spacing.

[0009] Furthermore, according to the node displacement vector modulus and the adjacent sensor spacing, the local curvature distortion coefficient of the support structure is determined, including: according to the formula Determine the local curvature distortion coefficient of the support structure at the node of the i-th row and j-th column of the n-th support panel ,in, is the displacement vector modulus of the node at the i-th row and j-th column of the n-th support panel, is the displacement vector modulus of the node at the i+1th row and jth column of the nth support panel, is the displacement vector modulus of the node at the i-th row and j+1-th column of the n-th support panel, is the adjacent sensor spacing of the three-dimensional displacement sensor array of the nth support panel, and n, i and j are all positive integers.

[0010] Furthermore, deformation warning conditions are determined based on the local curvature distortion coefficient of the support structure, the panel specification parameters and the node displacement vector, including: determining the local curvature distortion coefficient threshold of the support structure based on the panel specification parameters; determining the displacement vector angle based on the node displacement vector; and determining the deformation warning conditions based on the local curvature distortion coefficient of the support structure, the local curvature distortion coefficient threshold of the support structure and the displacement vector angle.

[0011] Further, according to the node displacement vector, the displacement vector angle is determined, including: according to the formula Determine the displacement vector angle of the node in the i-th row and j-th column of the n-th support panel ,in, is the displacement vector of the node at the i-th row and j-th column of the n-th support panel, a displacement vector of an (i+1)th row and jth column node of an nth supporting panel, a displacement vector of an ith row and (j+1)th column node of an nth supporting panel, and n, i and j are positive integers.

[0012] Further, according to the supporting structure local curvature distortion coefficient, the supporting structure local curvature distortion coefficient threshold and the displacement vector angle, a deformation early warning condition is determined, including: according to the formula determining a deformation early warning condition C, wherein, a supporting structure local curvature distortion coefficient of an (i+1)th row and jth column node of an nth supporting panel, a supporting structure local curvature distortion coefficient threshold, a displacement vector angle of an (i+1)th row and jth column node of an nth supporting panel, N is the number of supporting panels, I is the number of rows of the three-dimensional displacement sensor array, J is the number of columns of the three-dimensional displacement sensor array, n≤N, i≤I, j≤J, and n, i, j, N, I and J are positive integers.

[0013] According to a second aspect of the present application, a deformation monitoring system for a loess roadbed slope assembled supporting structure is provided, including: a three-dimensional displacement sensor array module for arranging a three-dimensional displacement sensor array at a plurality of supporting panels of the assembled supporting structure, wherein the three-dimensional displacement sensor array is distributed in a rectangular grid form; a panel specification parameter module for obtaining panel specification parameters of the supporting panels, wherein the panel specification parameters include yield strength, panel elastic modulus and panel thickness; a loess density module for obtaining loess density by drilling loess samples at a loess roadbed slope; an adjacent sensor spacing module for determining an adjacent sensor spacing of the three-dimensional displacement sensor array according to the panel specification parameters and the loess density; a node displacement vector module for obtaining node displacement vectors of a plurality of nodes of a plurality of supporting panels according to the three-dimensional displacement sensor array; a supporting structure local curvature distortion coefficient module for determining a supporting structure local curvature distortion coefficient according to the node displacement vectors and the adjacent sensor spacing; and a deformation early warning condition module for determining a deformation early warning condition according to the supporting structure local curvature distortion coefficient, the panel specification parameters and the node displacement vectors.

[0014] Technical effects: According to the present application, by arranging a three-dimensional displacement sensor array in a rectangular grid form at the plurality of supporting panels of the assembled supporting structure, the displacement of the supporting panels can be comprehensively monitored from three directions and multiple positions. By reasonably setting the adjacent sensor spacing according to the panel specification parameters of the supporting panel and the physical properties of the loess subgrade, the deformation characteristics of the supporting structure can be more accurately captured, the monitoring efficiency is improved, and the monitoring cost is reduced. The local curvature distortion coefficient can reflect the bending deformation degree of the local supporting structure, identify the potential sliding surface, determine the deformation warning condition combined with the displacement vector angle, reduce the limitations of single parameter judgment, improve the reliability and accuracy of deformation warning, and help to timely discover the abnormal deformation of the supporting structure. When determining the adjacent sensor spacing of the three-dimensional displacement sensor array, the adjacent sensor spacing of the three-dimensional displacement sensor array can be determined through the slope angle, the panel specification parameters, and the loess density. By setting a reasonable adjacent sensor spacing, the deformation of the supporting structure can be effectively monitored, while the excessive configuration of the number of sensors is reduced, and the monitoring cost is reduced. When determining the local curvature distortion coefficient of the supporting structure, the local curvature distortion coefficient of the supporting structure can be determined through the node displacement vector modulus and the adjacent sensor spacing. Through the displacement difference of the target node and the adjacent node in the horizontal and vertical directions, the bending and twisting deformation of the local supporting structure can be more comprehensively reflected. Through normalization processing, the influence of the size of the rectangular grid is eliminated, so that the data of different monitoring areas are comparable. Through dynamic spacing and normalization, the local curvature distortion coefficient of the supporting structure in the high-risk area at the top of the slope is amplified, which is consistent with the characteristics that the top of the slope is more prone to instability in actual engineering, and reduces the misjudgment. When determining the displacement vector angle, the displacement vector angle can be determined through the node displacement vectors of the adjacent three nodes. Through the analysis of the direction of the adjacent node displacement vectors, the dangerous phenomenon of overall sliding and the normal phenomenon of local deformation can be more accurately distinguished. Through the analysis of the spatial distribution of the displacement vector angle, the deformation incoordination area can be quickly located to provide a target for reinforcement design. When determining the deformation warning condition, whether the node enters the plastic stage can be judged by comparing the local curvature distortion coefficient of the supporting structure with the local curvature distortion coefficient threshold of the supporting structure, and the adjacent node displacement vector angle is combined to reduce invalid warning, further reduce the false positive rate, and improve the accuracy and comprehensiveness of the deformation warning condition.

[0015] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, but not limiting the present application. Other features and aspects of the present application will be more apparent from the following detailed description of exemplary embodiments with reference to the accompanying drawings. BRIEF DESCRIPTION OF DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description only show some embodiments of the present application, and for those skilled in the art, other embodiments can be obtained from these drawings without creative labor.

[0017] Figure 1 An exemplary flowchart of a loess subgrade slope assembled supporting structure deformation monitoring method according to an embodiment of the present application is shown.

[0018] Figure 2 An exemplary flowchart of calculating the distance between adjacent sensors according to an embodiment of the present application is shown.

[0019] Figure 3 An exemplary flowchart of calculating the local curvature distortion coefficient of the supporting structure according to an embodiment of the present application is shown.

[0020] Figure 4 An exemplary flowchart of determining the deformation early warning condition according to an embodiment of the present application is shown.

[0021] Figure 5 An exemplary block diagram of a loess subgrade slope assembled supporting structure deformation monitoring system according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0022] In order to make the objectives, technical solutions and advantages of the embodiments of the present application clearer, the following will combine the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the protection scope of the present application.

[0023] The technical solutions of the present application will be described in detail in the following specific embodiments. The following several specific embodiments can be combined with each other, and some embodiments may not be described again for the same or similar concepts or processes.

[0024] Figure 1An exemplary flowchart of a loess roadbed slope assembled supporting structure deformation monitoring method according to an embodiment of the present application is shown. The method comprises: step S1, arranging a three-dimensional displacement sensor array at a plurality of supporting panels of the assembled supporting structure, wherein the three-dimensional displacement sensor array is distributed in a rectangular grid form; step S2, obtaining panel specification parameters of the supporting panels, wherein the panel specification parameters comprise yield strength, panel elastic modulus and panel thickness; step S3, drilling a loess sample at the loess roadbed slope to obtain loess density; step S4, determining an adjacent sensor spacing of the three-dimensional displacement sensor array according to the panel specification parameters and the loess density; step S5, obtaining node displacement vectors of a plurality of nodes of a plurality of supporting panels according to the three-dimensional displacement sensor array; step S6, determining a local curvature distortion coefficient of the supporting structure according to the node displacement vectors and the adjacent sensor spacing; and step S7, determining a deformation warning condition according to the local curvature distortion coefficient of the supporting structure, the panel specification parameters and the node displacement vectors.

[0025] The loess roadbed slope assembled supporting structure deformation monitoring method according to the embodiment of the present application can comprehensively monitor the displacement of the supporting panels from three directions and multiple positions by arranging the three-dimensional displacement sensor array in the rectangular grid form at the plurality of supporting panels of the assembled supporting structure. The adjacent sensor spacing is reasonably set by the panel specification parameters of the supporting panels and the physical properties of the loess roadbed, so as to more accurately capture the deformation characteristics of the supporting structure, improve the monitoring efficiency and reduce the monitoring cost. The local curvature distortion coefficient can reflect the bending deformation degree of the local supporting structure, identify the potential sliding surface, determine the deformation warning condition in combination with the displacement vector angle, reduce the limitations of single parameter judgment, improve the reliability and accuracy of the deformation warning, and help to timely find the abnormal deformation of the supporting structure.

[0026] According to an embodiment of the present application, in step S1, the three-dimensional displacement sensor (for example, a total station, a GNSS receiver or a MEMS inertial unit) array is distributed in a rectangular grid form, that is, the supporting panels of the assembled supporting structure are divided into an I×J rectangular grid, I is the number of rows of the three-dimensional displacement sensor array, and J is the number of columns of the three-dimensional displacement sensor array, wherein the three-dimensional displacement sensor can be arranged at key positions of the supporting panels of the assembled supporting structure, for example, positions such as supporting panel connecting positions, structure edges and the like which are prone to deformation and bear greater pressure.

[0027] According to one embodiment of the present application, in step S2, according to the design drawing of the assembled support structure, the yield strength, the panel elastic modulus and the panel thickness of the support panel are obtained, the yield strength is the stress value at which the support panel material begins to deform plastically, the panel elastic modulus is a physical quantity that measures the ability of the support panel material to resist elastic deformation, for example, the yield strength of Q235 steel is 235 MPa, and the panel elastic modulus is 200 Gpa.

[0028] According to one embodiment of the present application, in step S3, a drilling point can be selected at the bottom of the loess subgrade slope, and when the drilling reaches a predetermined depth, drilling is stopped, and a soil sampler (such as a thin-walled soil sampler, a thick-walled soil sampler, etc.) is used to collect loess samples, so as to determine the loess density by the cutting ring method, for example, the loess density of the loess subgrade is close to 1.8 tons / cubic meter.

[0029] According to one embodiment of the present application, in step S4, according to the panel specification parameters and the loess density, the adjacent sensor spacing of the three-dimensional displacement sensor array is determined.

[0030] Figure 2 An exemplary flowchart of calculating the adjacent sensor spacing according to an embodiment of the present application is shown.

[0031] According to one embodiment of the present application, step S4 includes: step S41, obtaining the slope inclination of the loess subgrade slope position where the plurality of support panels are located; and step S42, determining the adjacent sensor spacing of the three-dimensional displacement sensor array according to the slope inclination, the panel specification parameters and the loess density.

[0032] According to one embodiment of the present application, the slope inclinations of the slope top and the slope foot of the loess subgrade slope are different, so the slope inclinations of the loess subgrade slope positions where different support panels are located are different, and the slope inclinations of the loess subgrade slope positions where the plurality of support panels are located can be measured by an electronic theodolite. The panel elastic modulus reflects the stiffness of the support structure, the greater the panel elastic modulus, the more difficult the structure is to deform, and the adjacent sensor spacing can be increased. For a support panel with a panel thickness H, the bending stiffness expression is wherein E is the panel elastic modulus, H is the panel thickness, is the Poisson's ratio of the material used for the support panel, in engineering applications, the influence of the Poisson's ratio is often ignored (i.e. ), which is simplified as Therefore, the bending stiffness is proportional to the cube of the panel thickness, the thicker the supporting panel, the stronger the anti-deformation ability, the adjacent sensor spacing can be appropriately increased, the loess density affects the self-weight stress of the slope, the greater the loess density, the greater the potential deformation, the adjacent sensor spacing needs to be reduced to improve the monitoring accuracy, the greater the slope angle, the higher the slip risk, and the adjacent sensor spacing needs to be reduced accordingly. The relationship between the above panel elastic modulus, panel thickness, loess density and adjacent sensor spacing can be used to determine the adjacent sensor spacing. Based on the setting mode of the three-dimensional displacement sensor array distributed in the form of a rectangular grid and the adjacent sensor spacing, the three-dimensional displacement sensors on each supporting panel are arranged.

[0033] According to one embodiment of the application, the adjacent sensor spacing of the three-dimensional displacement sensor array is determined according to the slope angle, the panel specification parameter and the loess density, comprising: determining the adjacent sensor spacing of the three-dimensional displacement sensor array of the nth supporting panel according to formula (1) ,

[0034] (1),

[0035] wherein E is the panel elastic modulus, H is the panel thickness, is the loess density, is the gravitational acceleration, is the slope angle of the loess subgrade slope position of the nth supporting panel.

[0036] According to one embodiment of the application, in formula (1), the numerator is the bending stiffness, the greater the bending stiffness, the stronger the anti-deformation ability of the supporting panel, and the adjacent sensor spacing needs to be increased, is the product of the loess density and the gravitational acceleration, which jointly determines the self-weight stress of the slope soil, the greater the density or the greater the gravity, the more intensive the sensor monitoring of the deformation caused by the soil pressure, and the denominator is the sliding force component of the loess subgrade slope position of the nth supporting panel, that is, the slope sliding load, the greater the slope sliding load, the more prone to shear slip, and the adjacent sensor spacing needs to be reduced. In order to unify the units on both sides of the equation, the is raised to the fourth power, that is, , the adjacent sensor spacing of the three-dimensional displacement sensor array can be obtained. The slope angles of the loess subgrade slope positions of different supporting panels are different, so the adjacent sensor spacing of the three-dimensional displacement sensor array on each supporting panel is different, and the adjacent sensor spacing of the three-dimensional displacement sensor array of the nth supporting panel needs to be obtained according to the slope angle of the loess subgrade slope position of the nth supporting panel.

[0037] In this way, the adjacent sensor spacing of the three-dimensional displacement sensor array can be determined by the slope angle, the panel specification parameter and the loess density, and by setting a reasonable adjacent sensor spacing, the effective monitoring of the deformation of the supporting structure can be realized, and meanwhile, the excessive configuration of the number of sensors is reduced, and the monitoring cost is reduced.

[0038] According to one embodiment of the present application, in step S5, the installation position of each three-dimensional displacement sensor represents a node, and the node can comprehensively reflect the deformation state of the supporting panel and is distributed in the form of a rectangular grid.

[0039] According to one embodiment of the present application, in step S6, the local curvature distortion coefficient of the supporting structure is determined according to the node displacement vector and the adjacent sensor spacing.

[0040] Figure 3 An exemplary flow chart for calculating the local curvature distortion coefficient of the supporting structure according to an embodiment of the present application is shown.

[0041] According to one embodiment of the present application, step S6 comprises: step S61, determining the node displacement vector modulus of a plurality of nodes of a plurality of supporting panels according to the node displacement vector; and step S62, determining the local curvature distortion coefficient of the supporting structure according to the node displacement vector modulus and the adjacent sensor spacing.

[0042] According to one embodiment of the present application, the node displacement vector is used to describe the displacement of a node on a supporting panel in a three-dimensional space, and is generally represented as wherein, is the node displacement vector, , and are displacement components of the node in X, Y and Z coordinate axis directions, respectively, and the displacement components can be acquired and processed by the three-dimensional displacement sensor array. The node displacement vector modulus is wherein, is the node displacement vector modulus. On the supporting panel, according to the arrangement of the three-dimensional displacement sensor array, a node and the nodes laterally adjacent and longitudinally adjacent to the node form a local node group, and the local curvature distortion coefficient of the supporting structure is determined according to the adjacent three node displacement vector moduli and the adjacent sensor spacing.

[0043] According to one embodiment of the present application, the local curvature distortion coefficient of the supporting structure is determined according to the node displacement vector modulus and the adjacent sensor spacing, and comprises: determining the local curvature distortion coefficient of the node in the i-th row and the j-th column of the n-th supporting panel according to formula (2) ,

[0044] (2),

[0045] wherein, is a displacement vector modulus of an i row j column node of the n support panel, is a displacement vector modulus of an i+1 row j column node of the n support panel, is a displacement vector modulus of an i row j+1 column node of the n support panel, is a distance between adjacent sensors of a three-dimensional displacement sensor array of the n support panel, and n, i and j are positive integers.

[0046] According to one embodiment of the present application, in formula (2), is a difference between the displacement vector modulus of the i row j column node (target node) of the n support panel and the displacement vector modulus of the i+1 row j column node of the n support panel, indicating a displacement difference along the transverse direction of the support panel, is a difference between the displacement vector modulus of the i row j column node of the n support panel and the displacement vector modulus of the i row j+1 column node of the n support panel, indicating a displacement difference along the longitudinal direction of the support panel, and the sum of the above two indicates the total displacement difference of the node, the greater the total displacement difference, the more serious the local curvature distortion of the support structure, and the more likely the potential slip surface is found through bidirectional (transverse + longitudinal) displacement difference analysis, reducing misjudgment. is a ratio of the total displacement difference to the square of the distance between adjacent sensors, indicating the displacement change rate per unit area, i.e., the local curvature distortion coefficient of the support structure, which is normalized to eliminate the influence of the size of the rectangular grid, making the data of different monitoring areas comparable, and the greater the local curvature distortion coefficient of the support structure, the more serious the local curvature distortion, indicating the formation of a slip surface, and the local curvature distortion coefficient of the support structure close to 0 indicates uniform displacement distribution and stable structure.

[0047] In this way, the local curvature distortion coefficient of the support structure can be determined through the node displacement vector modulus and the distance between adjacent sensors, the displacement difference between the target node and the adjacent nodes in the transverse and longitudinal directions can more comprehensively reflect the bending and twisting deformation of the local support structure, the normalized processing eliminates the influence of the size of the rectangular grid, making the data of different monitoring areas comparable, and the local curvature distortion coefficient of the high-risk area of the slope top is amplified through dynamic distance and normalization, which is consistent with the characteristics of the slope top being more prone to instability in actual engineering, reducing misjudgment.

[0048] According to one embodiment of the present application, in step S7, a deformation warning condition is determined according to the local curvature distortion coefficient of the support structure, the panel specification parameter and the node displacement vector.

[0049] Figure 4An exemplary flow chart of determining a deformation early warning condition according to an embodiment of the present application is shown.

[0050] According to an embodiment of the present application, the step S7 comprises: a step S71 of determining a local curvature distortion coefficient threshold of the support structure according to the panel specification parameters; a step S72 of determining a displacement vector angle according to the node displacement vectors; and a step S73 of determining a deformation early warning condition according to the local curvature distortion coefficient of the support structure, the local curvature distortion coefficient threshold of the support structure and the displacement vector angle.

[0051] According to an embodiment of the present application, if a cross section perpendicular to the neutral axis before bending remains planar and perpendicular to the neutral axis after bending. The strain of an arbitrary point on the cross section is wherein, is the strain of an arbitrary point on the cross section, y is the vertical distance from the stress point to the neutral axis, the maximum value of y is H / 2, H is the thickness of the panel, R is the radius of curvature, K is the curvature, and the Hook's law is combined , and the maximum stress is wherein, is the stress, E is the elastic modulus of the panel, when the maximum stress reaches the yield strength, the support structure starts to yield, i.e., plastic deformation occurs. Therefore, and , the local curvature distortion coefficient threshold of the support structure is wherein, is the maximum stress, is the yield strength, is the maximum vertical distance from the stress point to the neutral axis. The displacement vector angle reflects the relative change of the displacement direction between adjacent nodes.

[0052] According to an embodiment of the present application, the displacement vector angle is determined according to the node displacement vectors, comprising: determining the displacement vector angle of the node in the i-th row and the j-th column of the n-th support panel according to formula (3) ,

[0053] (3),

[0054] wherein, is the displacement vector of the node in the i-th row and the j-th column of the n-th support panel, is the displacement vector of the node in the i+1-th row and the j-th column of the n-th support panel, is the displacement vector of the node in the i-th row and the j+1-th column of the n-th support panel, and n, i and j are positive integers.

[0055] According to an embodiment of the present application, in formula (3), a relative displacement vector of a node in the i th row and the j th column of the n th support panel and a node in the i th row and the j th column of the n th support panel, a relative displacement vector of a node in the i th row and the j th column of the n th support panel and a node in the i th row and the j th column of the n th support panel, a cosine value of an angle between the two relative displacement vectors, the smaller the cosine value, the larger the angle between the displacement vectors, and the larger the difference between the directions of the two relative displacement vectors. , indicating that the displacement directions are almost the same, and indicating a coordinated deformation (for example, temperature expansion, which is a normal phenomenon), , indicating that the displacement directions are quite different, and indicating a non-coordinated deformation (for example, slippage or structural damage, which is a dangerous phenomenon), , indicating that the displacement directions are orthogonal, and indicating a shear deformation (for example, support panel dislocation, which is a dangerous phenomenon).

[0056] In this way, the angle between the displacement vectors can be determined through the node displacement vectors of the adjacent three nodes, the dangerous phenomenon of overall slippage and the normal phenomenon of local deformation can be more accurately distinguished through the direction analysis of the adjacent node displacement vectors, and the deformation non-coordinated area can be quickly located through the analysis of the spatial distribution of the angle between the displacement vectors, thereby providing a target for reinforcement design.

[0057] According to one embodiment of the present application, the deformation warning condition is determined according to the local curvature distortion coefficient of the support structure, the local curvature distortion coefficient threshold of the support structure, and the angle between the displacement vectors, and includes: determining the deformation warning condition C according to formula (4),

[0058] (4),

[0059] wherein, the local curvature distortion coefficient of the node in the i th row and the j th column of the n th support panel, the local curvature distortion coefficient threshold of the support structure, the angle between the displacement vectors of the node in the i th row and the j th column of the n th support panel, N is the number of support panels, I is the number of rows of the three-dimensional displacement sensor array, J is the number of columns of the three-dimensional displacement sensor array, n≤N, i≤I, j≤J, and n, i, j, N, I and J are all positive integers.

[0060] According to one embodiment of the present application, in formula (4), the local curvature distortion coefficient of the node in the i th row and the j th column of the n th support panel is greater than the local curvature distortion coefficient threshold of the support structure, indicating that the support structure has entered a plastic deformation stage and has a risk of instability, The displacement vector angle of the nth supporting panel, the ith row, and the jth column node is greater than 60°, which indicates that the displacement direction difference of adjacent nodes is large, and the overall slip may occur. When only is satisfied, it only indicates that the local curvature distortion coefficient of the supporting structure of the node exceeds the threshold value due to local impact, and cannot represent the overall instability of the supporting structure. When only is satisfied, it is the displacement direction difference, which may be caused by non-destructive factors (for example, vibration), that is, elastic deformation, and the supporting structure does not occur plastic deformation. At this time, the supporting structure is still in a safe state, which indicates that the local curvature distortion coefficient of the supporting structure is greater than the local curvature distortion coefficient threshold of the supporting structure, and the displacement vector angle is greater than 60°, which indicates that the local curvature distortion coefficient and the displacement vector angle of a certain node satisfy and that is, the local curvature distortion of the supporting structure is out of limit and the displacement direction difference is large (for example, slope slip, supporting structure fracture), it is determined that the assembled supporting structure of the loess subgrade slope needs to be deformed.

[0061] In this way, by comparing the local curvature distortion coefficient of the supporting structure with the local curvature distortion coefficient threshold of the supporting structure, it can be judged whether the node enters the plastic stage, and the displacement vector angle of the adjacent node is combined to reduce invalid early warning, further reduce the false positive rate, and improve the accuracy and comprehensiveness of the deformation early warning condition.

[0062] The loess roadbed slope assembled supporting structure deformation monitoring method according to the embodiment of the present application can comprehensively monitor the displacement conditions of the supporting panel from three directions and multiple positions by arranging the three-dimensional displacement sensor array in the form of a rectangular grid at the multiple supporting panels of the assembled supporting structure. The adjacent sensor spacing is reasonably set through the panel specification parameters of the supporting panel and the physical properties of the loess roadbed, so that the deformation characteristics of the supporting structure are more accurately captured, the monitoring efficiency is improved, and the monitoring cost is reduced. The local curvature distortion coefficient can reflect the bending deformation degree of the local supporting structure, identify the potential sliding surface, determine the deformation warning condition in combination with the displacement vector angle, reduce the limitations of single parameter judgment, improve the reliability and accuracy of the deformation warning, and help to timely discover the abnormal deformation of the supporting structure. When determining the adjacent sensor spacing of the three-dimensional displacement sensor array, the adjacent sensor spacing of the three-dimensional displacement sensor array can be determined through the slope inclination, the panel specification parameters, and the loess density. By setting a reasonable adjacent sensor spacing, the deformation of the supporting structure can be effectively monitored, the excessive configuration of the number of sensors is reduced, and the monitoring cost is reduced. When determining the local curvature distortion coefficient of the supporting structure, the local curvature distortion coefficient of the supporting structure can be determined through the node displacement vector modulus and the adjacent sensor spacing. Through the displacement difference of the target node and the adjacent node in the horizontal direction and the vertical direction, the bending and twisting deformation conditions of the local supporting structure can be more comprehensively reflected. Through normalization processing, the influence of the size of the rectangular grid is eliminated, the data of different monitoring areas are comparable, the local curvature distortion coefficient of the supporting structure in the high-risk area at the top of the slope is magnified through the dynamic spacing and normalization, which conforms to the characteristics that the top of the slope is more prone to instability in actual engineering, and reduces the misjudgment. When determining the displacement vector angle, the displacement vector angle can be determined through the node displacement vectors of the adjacent three nodes. Through the analysis of the directions of the adjacent node displacement vectors, the dangerous phenomenon of overall sliding and the normal phenomenon of local deformation can be more accurately distinguished. Through the analysis of the spatial distribution of the displacement vector angle, the deformation incoordination area can be quickly located to provide a target for reinforcement design. When determining the deformation warning condition, whether the node enters the plastic stage can be judged by comparing the local curvature distortion coefficient of the supporting structure with the local curvature distortion coefficient threshold of the supporting structure. In combination with the adjacent node displacement vector angle, the invalid warning is reduced, the false positive rate is further reduced, and the accuracy and comprehensiveness of the deformation warning condition are improved.

[0063] Figure 5An example of a block diagram of a loess roadbed slope assembled supporting structure deformation monitoring system according to an embodiment of the application is shown, the system comprising: a three-dimensional displacement sensor array module for arranging a three-dimensional displacement sensor array at a plurality of supporting panels of the assembled supporting structure, wherein the three-dimensional displacement sensor array is distributed in a rectangular grid form; a panel specification parameter module for obtaining panel specification parameters of the supporting panels, wherein the panel specification parameters include yield strength, panel elastic modulus and panel thickness; a loess density module for obtaining loess density by drilling loess samples at a loess roadbed slope; an adjacent sensor spacing module for determining the adjacent sensor spacing of the three-dimensional displacement sensor array according to the panel specification parameters and the loess density; a node displacement vector module for obtaining the node displacement vector of a plurality of nodes of a plurality of supporting panels according to the three-dimensional displacement sensor array; a supporting structure local curvature distortion coefficient module for determining the supporting structure local curvature distortion coefficient according to the node displacement vector and the adjacent sensor spacing; and a deformation early warning condition module for determining the deformation early warning condition according to the supporting structure local curvature distortion coefficient, the panel specification parameters and the node displacement vector.

[0064] The present application can be a method, an apparatus, a system, and / or a computer program product. The computer program product can include a computer readable storage medium (or media) having computer readable program instructions thereon for performing various aspects of the present application.

[0065] Those skilled in the art will understand that the embodiments of the application described above and shown in the drawings are merely illustrative and that numerous other variations and modifications can be possible without departing from the true spirit and scope of the application. The object of the application has been fully and effectively achieved. The functional and structural principles of the application have been shown and described in the embodiments, and the embodiments of the application can be modified or changed in any way without departing from the principles.

Claims

1. A method for monitoring deformation of an assembled support structure for a loess roadbed slope, characterized in that: include: Arrange a three-dimensional displacement sensor array at multiple support panels of an assembled support structure, wherein the three-dimensional displacement sensor array is distributed in a rectangular grid; obtain panel specification parameters of the support panel, wherein the panel specification parameters include yield strength, panel elastic modulus, and panel thickness; obtain loess samples by drilling holes in the loess roadbed slope to obtain loess density; determine the adjacent sensor spacing of the three-dimensional displacement sensor array based on the panel specification parameters and the loess density; obtain node displacement vectors of multiple nodes of multiple support panels based on the three-dimensional displacement sensor array; determine the local curvature distortion coefficient of the support structure based on the node displacement vectors and the adjacent sensor spacing; determine deformation warning conditions based on the local curvature distortion coefficient of the support structure, the panel specification parameters, and the node displacement vectors; Determining the spacing between adjacent sensors of the three-dimensional displacement sensor array based on the panel specifications and the loess density, including: obtaining the slope inclination angle of the loess roadbed slope position where the plurality of support panels are located; determining the spacing between adjacent sensors of the three-dimensional displacement sensor array based on the slope inclination angle, the panel specifications and the loess density; According to the slope inclination, the panel specification parameters and the loess density, the adjacent sensor spacing of the three-dimensional displacement sensor array is determined, including: according to the formula Determine the adjacent sensor spacing L of the three-dimensional displacement sensor array of the nth support panel n , where E is the elastic modulus of the panel, H is the thickness of the panel, ρ is the density of loess, g is the acceleration of gravity, θ n is the slope inclination angle of the loess roadbed slope where the nth support panel is located; Determining a local curvature distortion coefficient of the support structure according to the node displacement vector and the adjacent sensor spacing, including: determining a node displacement vector modulus of a plurality of nodes of a plurality of support panels according to the node displacement vector; determining a local curvature distortion coefficient of the support structure according to the node displacement vector modulus and the adjacent sensor spacing; Determine the local curvature distortion coefficient of the support structure according to the node displacement vector modulus and the adjacent sensor spacing, including: according to the formula Determine the local curvature distortion coefficient K of the support structure at the node of the i-th row and j-th column of the n-th support panel n，i，j , where Δu n，i，j is the displacement vector modulus of the node at the i-th row and j-th column of the n-th support panel, Δu n，i+1，j is the displacement vector modulus of the node at the i+1th row and jth column of the nth support panel, Δu n，i，j+1 is the displacement vector modulus of the node at the i-th row and j+1-th column of the n-th support panel, L n is the adjacent sensor spacing of the three-dimensional displacement sensor array of the nth support panel, and n, i and j are all positive integers.

2. The deformation monitoring method of the assembled support structure of loess roadbed slope according to claim 1 is characterized in that: Deformation warning conditions are determined based on the local curvature distortion coefficient of the support structure, the panel specification parameters and the node displacement vector, including: determining the local curvature distortion coefficient threshold of the support structure based on the panel specification parameters; determining the displacement vector angle based on the node displacement vector; and determining the deformation warning conditions based on the local curvature distortion coefficient of the support structure, the local curvature distortion coefficient threshold of the support structure and the displacement vector angle.

3. The deformation monitoring method of the loess roadbed slope prefabricated support structure according to claim 2 is characterized in that: According to the node displacement vector, determining the displacement vector angle includes: according to the formula Determine the displacement vector angle α of the node in the i-th row and j-th column of the n-th support panel n，i，j , where ΔU n，i，j is the displacement vector of the node at the i-th row and j-th column of the n-th support panel, ΔU n，i+1，j is the displacement vector of the node at the i+1th row and jth column of the nth support panel, ΔU n，i，k+1 is the displacement vector of the node in the i-th row and j+1-th column of the n-th support panel, and n, i and j are all positive integers.

4. The deformation monitoring method of the assembled support structure of loess roadbed slope according to claim 3 is characterized in that: Determine the deformation warning condition according to the local curvature distortion coefficient of the support structure, the local curvature distortion coefficient threshold of the support structure and the displacement vector angle, including: according to the formula Determine the deformation warning condition C, where K n，i，j is the local curvature distortion coefficient of the support structure at the node of the i-th row and j-th column of the n-th support panel, K P is the local curvature distortion coefficient threshold of the support structure, α n，i，j is the displacement vector angle of the node in the i-th row and j-th column of the n-th support panel, N is the number of support panels, I is the number of rows of the three-dimensional displacement sensor array, J is the number of columns of the three-dimensional displacement sensor array, n≤N, i≤I, j≤J, and n, i, j, N, I and J are all positive integers.

5. A deformation monitoring system for a loess roadbed slope prefabricated support structure, used to implement the deformation monitoring method for a loess roadbed slope prefabricated support structure according to any one of claims 1 to 4, characterized in that: include: a three-dimensional displacement sensor array module, for arranging a three-dimensional displacement sensor array at multiple support panels of an assembled support structure, wherein the three-dimensional displacement sensor array is distributed in a rectangular grid; a panel specification parameter module, for obtaining the panel specification parameters of the support panel, wherein the panel specification parameters include yield strength, panel elastic modulus and panel thickness; a loess density module, for drilling holes in the loess roadbed slope to obtain loess samples and obtain loess density; an adjacent sensor spacing module, for determining the adjacent sensor spacing of the three-dimensional displacement sensor array based on the panel specification parameters and the loess density; a node displacement vector module, for obtaining the node displacement vectors of multiple nodes of multiple support panels based on the three-dimensional displacement sensor array; a support structure local curvature distortion coefficient module, for determining the local curvature distortion coefficient of the support structure based on the node displacement vector and the adjacent sensor spacing; a deformation warning condition module, for determining the deformation warning condition based on the local curvature distortion coefficient of the support structure, the panel specification parameters and the node displacement vector.

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