CN113139228B - Monitoring point arrangement optimization method for large-span foundation pit complex support system structure - Google Patents
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Abstract
The invention discloses a monitoring point arrangement optimization method for a large-span foundation pit complex supporting system structure. The traditional equidistant arrangement of monitoring points is only suitable for medium and small foundation pits with simple structural forms, the structural stress of a large-span foundation pit supporting system is complex due to the asymmetry and randomness of soil layers, structures and excavation, and the arrangement and selection of the monitoring points are very important. The method comprises the steps of obtaining modal parameters (frequency, damping ratio and basic vibration mode) of a supporting structure by means of modal analysis of a complex supporting system structure, constructing a displacement modal fitness function based on the modal parameters, judging an optimization standard of monitoring point positions according to the displacement modal fitness function, and finally performing overall global optimization on all monitoring point arrangement positions by adopting a particle swarm optimization algorithm. The method avoids the experience of the traditional monitoring point arrangement, carries out monitoring point arrangement aiming at the stress key weak link of the supporting structure, and can be used for optimizing the arrangement of the monitoring points of the large-span foundation pit complex supporting system structure.
Description
Technical Field
The invention relates to an optimal arrangement method of monitoring points of a large-span foundation pit. Belong to foundation ditch monitoring technology field in the foundation ditch engineering. The method is suitable for the optimized arrangement of the monitoring points of the foundation pit supporting system structure in the excavation process of the urban underground space and the urban tunnel open cut method.
Background
Since the 21 st century, the rapid development of our country has promoted the urbanization, the subways of high-rise buildings, large underground shopping malls and various large cities are indispensable basic constructions for urbanization, the foundation pit engineering construction of these projects not only needs to be excavated deeper and deeper, but also needs to be excavated in large areas, and the supporting system structure is more and more complex. The safety of foundation pit engineering is more and more taken into consideration, the influence range of foundation pit engineering accidents is wide, the loss is large, and the monitoring of the foundation pit engineering plays an important role in ensuring the safety of the foundation pit. The time for monitoring the foundation pit support is short, the standard is not much at home and abroad, and the research is not deep. Therefore, the safety risk degree of the foundation pit engineering is higher and higher, and how to ensure the safety of the foundation pit engineering is the most urgent problem in the building industry at present.
Regarding the research of the foundation pit supporting structure, Powrie w. and the like adopt a CRISP finite element program to research the stress and deformation of the foundation pit support structure, and indicate that when the wall rigidity is high, the deformation of the foundation pit is mainly controlled by the rigidity of the soil body instead of the bending rigidity of the wall body, and the influence of the lateral pressure coefficient of the soil body before excavation on the bending moment of the enclosure wall is high. Richards D.J. and the like research the influence of lateral soil pressure on the deformation of the support foundation pit in the reverse construction method, and indicate that the permanent support constructed at the top of the foundation pit is very effective in controlling the deformation in the early construction period; when the lateral pressure coefficient of the soil body is increased, the wall body bending moment and the supporting axial force are increased. The Longhai shore points out that the vertical supporting distance has great influence on the horizontal displacement of the wall body, and the small vertical supporting distance can effectively control the horizontal displacement of the diaphragm wall within a certain range. Considering the influence of the construction process on the deformation of the supporting structure, the Yangtze bloom provides an incremental method for calculating the stress and deformation of the multi-support supporting structure.
In recent years, a great deal of research and attempt has been made in the domestic engineering community on the technology and method for monitoring the foundation pit. The monitoring data of the deep foundation pit is managed by applying a deep foundation pit engineering monitoring data processing and predicting alarm system to the Hojordan and the plum blossom, a deformation prediction model is established by adopting a grey system theory, and the analysis, the judgment and the dangerous case prediction of the extreme state of the deep foundation pit engineering are carried out by adopting a plurality of qualitative and quantitative indexes. The Wangzheng and Liu Baoxin are combined with concrete engineering to deeply analyze the reasons of deformation and mutation generated by a technical method for monitoring a certain foundation pit supporting engineering and surrounding buildings, thereby explaining the significance of deformation monitoring in the construction process of large buildings. The Ningshixin and He Peng introduce various automatic instruments for sensing, measuring and monitoring in the safety monitoring system, advantages and disadvantages thereof, and current application situations at home and abroad, and summarize the development directions of advanced technologies, equipment and safety monitoring automatic systems in recent years.
At present, the technical means of foundation pit monitoring is continuously promoted, but effective monitoring, effective evaluation and effective early warning are achieved for how to realize the optimal arrangement of monitoring points, and deep research is not yet carried out. The monitoring of the present overwhelming majority foundation ditch engineering adopts traditional monitoring stationing mode, and the basic requirement in the foundation ditch monitoring standard only can be satisfied in arranging of monitoring point, and to some spans are big, the complicated foundation ditch engineering of support system, and these data that the monitoring point that arrange according to traditional stationing mode obtained do not have the representativeness to the most unfavorable position of foundation ditch safety, can't carry out the guidance of foundation ditch engineering construction through the monitoring achievement, ensure foundation ditch safety. Therefore, an effective monitoring point optimal arrangement method of the foundation pit supporting structure is found, and the method has important significance for guiding the foundation pit construction safety.
Disclosure of Invention
The technical problem is as follows: the invention aims to provide a monitoring point arrangement optimization method for a large-span foundation pit complex support system structure. According to the method, based on the mechanical characteristics of the large-span complex foundation pit supporting structure, a displacement modal fitness function based on modal parameters is constructed by means of modal analysis of the complex supporting system structure, the optimization standard of the position of the monitoring point is judged according to the displacement modal fitness function, the experience of the traditional monitoring point arrangement is avoided, and the problem of optimization arrangement of the monitoring points of the large-span complex foundation pit supporting system structure is solved.
The technical scheme is as follows: due to asymmetry and randomness of soil layers, structures and excavation in the construction process of the large-span foundation pit, the structure of the large-span foundation pit supporting system is stressed complexly, and the arrangement and selection of monitoring points are of great importance; the traditional foundation pit monitoring method adopts the equidistant arrangement of monitoring points, is only suitable for medium and small foundation pits with simple structural forms, and can not meet the monitoring requirements of complex foundation pits of large urban underground complex and large-span tunnel foundation pit supporting structures of urban open cut method. The invention provides a monitoring point arrangement optimization method for a large-span foundation pit complex support system structure, which comprises the following steps: firstly, carrying out modal analysis on a large-span foundation pit complex support system structure to obtain the frequency, the damping ratio and the basic vibration mode modal parameters of the complex support system structure, then constructing a displacement modal fitness function based on the modal parameters, using the displacement modal fitness function as an optimization standard for judging whether the position of a monitoring point is proper or not, and finally carrying out overall global optimization on the position of the monitoring point on the complex support system by adopting a particle swarm optimization algorithm and combining the displacement modal fitness function.
The optimization method comprises the following specific steps:
the method comprises the following steps: selecting a modal analysis mode, wherein the modal analysis method comprises numerical modal analysis and test modal analysis, and one of the numerical modal analysis method and the test modal analysis method can be selected as a modal analysis method;
step two: modal analysis and parametrizationPerforming number identification, performing modal analysis on a complex support system structure, and obtaining a modal vibration mode of the complex support system structure on the assumption that the support structure is undamped to vibrate
Step three: calculating the stiffness influence coefficient of the structural member, the stiffness influence coefficient k rs According to the following formula:
e is the elastic modulus of the component material, A is the sectional area of the component, l is the length of the component, r and s are the end point labels of the component, and gamma is the included angle between the component coordinate system and the structure coordinate system;
step four: selecting a fitness function, wherein the fitness value f is based on a displacement mode, the value of f is the magnitude of the accumulated displacement strain value of the monitoring point, and the larger the value of f is, the monitoring point can reflect the structural deformation; a mode shape matrix Φ obtained by modal analysis:
n order mode in phi
Determining that the freedom of a support system structure is N, the number of monitoring points is m, and defining a fitness function based on a displacement mode as follows:
in the formula (I), the compound is shown in the specification,
is the r-th component of the ith mode shape,
is the s component of the j-th mode rs Representing the stiffness of the member between the end points r and sCoefficient of influence, i, j ∈ [1, n ]]R, s ∈ m indicates that r and s are limited to all measurement points;
step five: a monitoring point position optimization algorithm based on a particle swarm algorithm;
step six: and (3) selecting the monitoring point arrangement scheme, selecting the fundamental frequency of the supporting structure and the vibration mode of the first 16 orders to participate in calculation after the particle swarm optimization layout program normally runs, and generating the optimal monitoring point arrangement scheme under the vibration mode of the corresponding order.
Wherein the content of the first and second substances,
the specific method of the second step is as follows:
step 1: simplifying the enclosure structure of the large-span foundation pit according to a wall structure, simplifying the support system structure of the large-span foundation pit according to a rod system structure, and establishing a finite element analysis model of the complex support system structure of the large-span foundation pit;
step 2: determining the degree of freedom N of the structure according to the finite element analysis model;
and 3, step 3: establishing a mass matrix M and a rigidity matrix K according to the material parameters of the finite element analysis model; and 4, step 4: establishing a modal analysis system equation:
wherein: [K] -stiffness matrix
ω i The natural frequency of the i-th order mode, i.e. the characteristic value
[ M ] -quality matrix
And 5, step 5: and solving modal parameters of the complex support system structure by adopting a finite element subspace Jacobi iterative algorithm.
And step 5: and (3) solving modal parameters of the complex support system structure by adopting a finite element subspace Jacobi iterative algorithm, wherein the modal parameters comprise frequency, damping ratio and basic mode shape.
The monitoring point position optimization algorithm based on the particle swarm optimization specifically comprises the following steps:
step 1: initializing a particle swarm, setting the scale of the particle swarm g, and generally taking 20-40 particles;
step 2: setting the dimension D of a single particle, wherein the dimension D is the number of the arranged monitoring points;
and 3, step 3: setting the position range of the particles [ -x [ ] max ,x max ]Wherein x is max The position range of the particles is the monitoring point arrangement range of the foundation pit model under the space rectangular coordinate system;
and 4, step 4: setting individual particle velocity range [ -v ] max ,v max ]Wherein v is max For the maximum velocity of the particles, v is usually set max ＝k·x max Wherein k is a constant, usually 0.1. ltoreq. k.ltoreq.1;
and 5, step 5: setting the acceleration constant c of a single particle 1 And c 2 Definition of c 1 And c 2 Equal and range of values of [0, 4 ]]；
And 6, step 6: setting an inertia weight w, wherein the inertia weight enables a single particle to keep moving inertia, so that the single particle has the tendency of expanding and exploring space, and the value range is usually [0.2, 1.2 ];
and 7, step 7: setting the maximum iteration times of the algorithm, wherein the maximum iteration times are generally taken as [100,200 ];
and 8, step 8: setting the initial position and initial velocity of a single particle, the initial position x td Is the position of the particle t in d dimension, x td ＝2x max Rand()-x max Initial velocity v td Velocity of the particle t in d dimension, v td ＝2v max Rand()-v max Wherein Rand () is [0,1 ]]Uniformly distributed random number generating functions;
step 9: calculating the fitness, namely calculating the vibration mode of the node where each dimension of the particle is located according to the step four
And a stiffness influence coefficient k rs In the belt-in type, calculating a fitness value f of a particle;
step 10: comparing the fitness value f of each particle, and finding the historically optimal position information of each particle as an individual extreme value p td ，p td The historical maximum value of the particle t appears on the d dimension, a global optimal solution is found from the individual historical optimal solutions, the global optimal solution is compared with the historical optimal solution, and the optimal solution is selected as the current historical optimal solution p gd ，p gd A large historical maximum value appears on the d dimension for the particle swarm g;
and 11, step 11: and updating the position and the speed of the particles, wherein the calculation formula is as follows:
v td+1 ＝wv td +c 1 ×Rand()×(p td -x td )+c 2 ×Rand()×(p gd -x td )
x td+1 ＝x td +v td
in the formula: v. of td+1 Is the velocity v of the particle td Updated next generation speed, x td+1 As particle position x td Updated next generation position, Rand () is [0,1 ]]Uniformly distributed random number generating function, c 1 、c 2 Is the acceleration constant, w is the inertial weight;
step 12: if the set maximum iteration times is reached, ending; otherwise loop from step 9.
The acceleration constant c of the single particle 1 And c 2 Usually take c 1 ＝c 2 ＝2。
The maximum iteration number is usually 100, so that the convergence requirement of the algorithm can be met.
Has the advantages that: the traditional method for arranging the foundation pit monitoring points is usually to select the arrangement positions of the foundation pit monitoring points according to the actual working conditions of engineering and past engineering experiences, and is only suitable for medium and small foundation pits with small span and simple structural forms. The method avoids the experience of the traditional foundation pit monitoring distribution point arrangement, obtains modal parameters (frequency, damping ratio and basic vibration mode) of a supporting structure by virtue of modal analysis of a complex supporting system structure from the structural mechanical characteristics of a large-span complex foundation pit support, constructs a displacement modal fitness function based on the modal parameters, judges the optimization standard of the monitoring point position according to the displacement modal fitness function, and finally performs overall global optimization on all the monitoring point arrangement positions by adopting a particle swarm optimization algorithm. The method can realize the optimal arrangement of the monitoring points, improves the effectiveness of the monitoring points, ensures the construction safety of the large-span foundation pit, and can be used for the optimal arrangement of the monitoring points of the large-span foundation pit supporting system structure in the excavation process of the urban underground space and the urban tunnel open cut method.
Drawings
FIG. 1 is a flow chart of a monitoring point arrangement optimization method of the present invention.
Fig. 2 is a schematic view of a space bar unit. In the figure Y r e V r e The superscript e represents the element, the subscript r represents the end of the element r, Y, Z, X are rod end force components, and u, v, w are rod end displacement components.
Detailed Description
The technical solution of the present invention is described in detail below by way of example:
the invention discloses a monitoring point arrangement optimization method for a large-span foundation pit complex support system structure, which comprises the following steps:
the method comprises the following steps: and selecting a mode of modal analysis, wherein the modal analysis comprises numerical modal analysis and test modal analysis, and selecting a proper mode of modal analysis according to the requirement of arrangement of monitoring points of the foundation pit maintenance supporting structure.
1. The numerical modal analysis is to determine the unit type of the structure according to the characteristics of the foundation pit enclosure support structure, establish a geometric model of the structure by using finite element software, input the properties of materials, divide the grid units of the geometric model according to the actual analysis requirements, and perform modal analysis through the finite element model.
2. And carrying out test modal analysis on the scale-reduced model of the large-span foundation pit support structure by using a vibration table test.
Step 1: and establishing a test system, namely determining a test object, selecting an excitation mode, and calibrating the whole test system.
Step 2: the response data of the tested system is measured, which is a key step of the test mode, and the accuracy and reliability of the measured data directly influence the result of the mode test. Once the tested system is excited under the action of a certain excitation force, the time domain signal of the excitation force or response can be obtained through measurement of a testing instrument, and the time domain signal is converted into a frequency domain signal through a mathematical means, so that the average estimation of a system frequency response function can be obtained.
And 3, step 3: performing modal parameter estimation, and estimating modal parameters by using a measured frequency response function or time history, wherein the method comprises the following steps: natural frequency, modal shape, modal damping, etc.
And 4, step 4: and the modal model verification is to verify the correctness of the result obtained by the modal parameter estimation.
Step two: modal analysis and parameter identification, modal analysis is carried out on the complex support system structure, and the modal vibration mode is obtained on the assumption that the support structure is undamped vibration
Step 1: and simplifying the enclosure structure of the large-span foundation pit according to the wall structure, simplifying the support system structure of the large-span foundation pit according to the rod system structure, and establishing a finite element analysis model of the complex support system structure of the large-span foundation pit.
Step 2: and determining the freedom degree N of the structure according to the finite element analysis model.
And 3, step 3: and establishing a mass matrix M and a rigidity matrix K according to the material parameters of the finite element analysis model.
And 4, step 4: establishing a modal analysis system equation:
wherein: [K] -stiffness matrix
ω i The natural frequency of the i-th order mode, i.e. the characteristic value
[ M ] -quality matrix
And 5, step 5: and (3) solving modal parameters (frequency, damping ratio and basic mode shape) of the complex support system structure by adopting a finite element subspace Jacobi iterative algorithm.
Step three: calculating the rigidity influence coefficient of the structural member, regarding the foundation pit supporting structure, the rod units can be regarded as axial stress rod pieces, each rod unit has 6 degrees of freedom, and if the two sides of the rod unit are respectively r and s, the two sides of the rod unit should be u r 、v r 、w r 、u s 、v s 、w s As shown in fig. 2:
let unit coordinate axes
The included angles with the integral coordinate axes x, y and z are respectively alpha, beta and gamma.
The formula for deriving the stiffness coefficient is:
wherein E is the elastic modulus of the member material, A is the sectional area of the member, l is the length of the member, r and s are end point labels of the member, and gamma is the included angle between the member coordinate system and the structure coordinate system.
Step four: and selecting a fitness function, wherein the fitness f is based on a displacement mode, the value of f is the magnitude of the accumulated displacement strain value of the monitoring point, and the larger the value of f is, the monitoring point can reflect the structural deformation. A mode shape matrix Φ obtained by modal analysis:
n order mode in phi
Determining that the freedom of a support system structure is N, the number of monitoring points is m, and defining a fitness function based on a displacement mode as follows:
in the formula (I), the compound is shown in the specification,
is the r-th component of the ith mode shape,
is the s component of the j-th mode rs Representing the stiffness influence coefficient of the member between the endpoint r and the endpoint s, i, j epsilon [1, n ∈ ]]And r, s e m indicates that r and s are limited to all stations.
Step five: the monitoring point position optimization algorithm based on the particle swarm optimization algorithm is characterized in that firstly, parameter setting is carried out on the particle swarm optimization algorithm, wherein the parameter setting comprises particle population size, particle dimension, particle position range, particle speed range, particle acceleration constant, inertia weight, maximum iteration number and the like, and aiming at specific optimization problems, in order to obtain stable and reliable results, optimal parameter setting can be obtained through multiple times of program operation. The method comprises the following specific steps:
step 1: initializing a particle swarm, setting the scale of the particle swarm g, and generally taking 20-40 particles;
step 2: setting the dimension D of a single particle, wherein the dimension D is the number of the arranged monitoring points;
and 3, step 3: setting the position range of the particles [ -x [ ] max ,x max ]Wherein x is max The position range of the particles is the monitoring point arrangement range of the foundation pit model under the space rectangular coordinate system;
and 4, step 4: setting individual particle velocity range [ -v ] max ,v max ]Wherein v is max For the maximum velocity of the particles, v is usually set max ＝k·x max Wherein k is a constant, usually 0.1. ltoreq. k.ltoreq.1;
and 5, step 5: is provided withAcceleration constant c of single particle 1 And c 2 Definition of c 1 And c 2 Equal and a value range of [0, 4 ]]。
And 6, step 6: setting an inertia weight w, wherein the inertia weight enables a single particle to keep moving inertia, so that the single particle has the tendency of expanding and exploring space, and the value range is usually [0.2, 1.2 ];
and 7, step 7: the maximum number of iterations of the algorithm is set, typically to a value of [100,200 ].
And 8, step 8: setting the initial position and initial velocity of a single particle, the initial position x td Is the position of the particle t in d dimension, x td ＝2x max Rand()-x max Initial velocity v td Velocity of the particle t in d dimension, v td ＝2v max Rand()-v max Wherein Rand () is [0,1 ]]Uniformly distributed random number generating functions;
step 9: calculating the fitness, namely calculating the vibration mode of the node where each dimension of the particle is located according to the step four
And a stiffness influence coefficient k rs In the belt-in type, calculating a fitness value f of a particle;
step 10: comparing the fitness value f of each particle, and finding the historically optimal position information of each particle as an individual extreme value p td ，p td The historical maximum value of the particle t appears on the d dimension, a global optimal solution is found from the individual historical optimal solutions, the global optimal solution is compared with the historical optimal solution, and the optimal solution is selected as the current historical optimal solution p gd ，p gd A large historical maximum value appears on the d dimension for the particle swarm g;
and 11, step 11: and updating the position and the speed of the particles, wherein the calculation formula is as follows:
v td+1 ＝wv td +c 1 ×Rand()×(p td -x td )+c 2 ×Rand()×(p gd -x td )
x td+1 ＝x td +v td
in the formula: v. of td+1 Is the velocity v of the particle td Updated next generation speed, x td+1 As particle position x td Updated next generation position, Rand () is [0,1 ]]Uniformly distributed random number generating function, c 1 、c 2 W is the inertial weight for the acceleration constant.
Step 12: if the set maximum iteration times is reached, ending; otherwise loop from step 9.
Step six: and (3) selecting the monitoring point arrangement scheme, selecting the fundamental frequency of the supporting structure and the vibration mode modes of 6 orders of the first 8 orders, the first 16 orders, the first 24 orders, the first 32 orders and the first 40 orders to participate in calculation after the particle swarm optimization layout program normally runs, and generating the optimal monitoring point arrangement scheme under the vibration mode of the corresponding order. According to data analysis, only the first few lowest structural natural vibration frequencies and vibration modes have influence on the engineering, and generally ten lowest natural vibration frequencies are taken for structural dynamic analysis, so that the requirement on engineering design precision can be met. Therefore, the first 16-order matrix types can be preliminarily selected for calculation, the accuracy requirement can be met only by specifically selecting how many orders of modes to participate in calculation, and the accuracy requirement can be further determined according to specific engineering.
Claims (6)
1. A monitoring point arrangement optimization method for a large-span foundation pit complex support system structure is characterized by firstly carrying out modal analysis on the large-span foundation pit complex support system structure to obtain the frequency, the damping ratio and the basic vibration mode modal parameters of the complex support system structure, then constructing a displacement modal fitness function based on the modal parameters, using the displacement modal fitness function as an optimization standard for judging whether the position of a monitoring point is proper or not, and finally carrying out overall global optimization on the position of the monitoring point on the complex support system by adopting a particle swarm optimization algorithm and combining the displacement modal fitness function, wherein the optimization method specifically comprises the following steps:
the method comprises the following steps: selecting a modal analysis mode, wherein the modal analysis method comprises numerical modal analysis and test modal analysis, and one of the numerical modal analysis method and the test modal analysis method can be selected as a modal analysis method;
step two: modal analysis and parameter identification, modal analysis is carried out on the complex support system structure, and the modal vibration mode is obtained on the assumption that the support structure is undamped vibration
Step three: calculating the stiffness influence coefficient of the structural member, the stiffness influence coefficient k rs According to the following formula:
e is the elastic modulus of the component material, A is the sectional area of the component, l is the length of the component, r and s are the end point labels of the component, and gamma is the included angle between the component coordinate system and the structure coordinate system;
step four: selecting a fitness function, wherein the fitness value f is based on a displacement mode, the value of f is the magnitude of the accumulated displacement strain value of the monitoring point, and the larger the value of f is, the monitoring point can reflect the structural deformation; a mode shape matrix Φ obtained by modal analysis:
n order mode in phi
Determining that the freedom of a support system structure is N, the number of monitoring points is m, and defining a fitness function based on a displacement mode as follows:
in the formula (I), the compound is shown in the specification,
is the r-th component of the ith mode shape,
is the s component of the j-th mode rs Representing the member stiffness influence coefficient between the member endpoint r and the endpoint s, i, j epsilon [1, n ∈]R, s ∈ m indicates that r and s are limited to all measurement points;
step five: a monitoring point position optimization algorithm based on a particle swarm algorithm;
step six: and (3) selecting the monitoring point arrangement scheme, selecting the fundamental frequency of the supporting structure and the vibration mode of the first 16 orders to participate in calculation after the particle swarm optimization layout program normally runs, and generating the optimal monitoring point arrangement scheme under the vibration mode of the corresponding order.
2. The method for optimizing the arrangement of the monitoring points of the large-span foundation pit complex support system structure according to claim 1, wherein the specific method in the second step is as follows:
step 1: simplifying the enclosure structure of the large-span foundation pit according to a wall structure, simplifying the support system structure of the large-span foundation pit according to a rod system structure, and establishing a finite element analysis model of the complex support system structure of the large-span foundation pit;
step 2: determining the degree of freedom N of the structure according to the finite element analysis model;
and 3, step 3: establishing a mass matrix M and a rigidity matrix K according to the material parameters of the finite element analysis model;
and 4, step 4: establishing a modal analysis system equation:
wherein: [K] -stiffness matrix
ω i The natural frequency of the i-th order mode, i.e. the characteristic value
[ M ] -quality matrix
And 5, step 5: and solving modal parameters of the complex support system structure by adopting a finite element subspace Jacobi iterative algorithm.
3. The method for optimizing the arrangement of the monitoring points of the large-span foundation pit complex support system structure according to claim 2, wherein the 5 th step: and (3) solving modal parameters of the complex support system structure by adopting a finite element subspace Jacobi iterative algorithm, wherein the modal parameters comprise frequency, damping ratio and basic mode shape.
4. The method for optimizing the arrangement of the monitoring points of the large-span foundation pit complex support system structure according to claim 1, wherein the monitoring point position optimizing algorithm based on the particle swarm optimization in the fifth step comprises the following specific steps:
step 1: initializing a particle swarm, setting the scale of the particle swarm g, and taking 20-40 particles;
step 2: setting the dimension D of a single particle, wherein the dimension D is the number of the arranged monitoring points;
and 3, step 3: setting the position range of the particles [ -x [ ] max ,x max ]Wherein x is max The position range of the particles is the monitoring point arrangement range of the foundation pit model under the space rectangular coordinate system;
and 4, step 4: setting individual particle velocity range [ -v ] max ,v max ]Wherein v is max For the maximum velocity of the particles, set v max ＝k·x max Wherein k is a constant, and the value of k is more than or equal to 0.1 and less than or equal to 1;
and 5, step 5: setting the acceleration constant c of a single particle 1 And c 2 Definition of c 1 And c 2 Equal and a value range of [0, 4 ]]；
And 6, step 6: setting an inertia weight w, wherein the inertia weight enables a single particle to keep moving inertia, so that the single particle has the tendency of expanding and exploring space, and the value range is [0.2, 1.2 ];
and 7, step 7: setting the maximum iteration times of the algorithm, and taking the maximum iteration times as values of [100,200 ];
and 8, step 8: setting the initial position and initial velocity of a single particle, the initial position x td Is the position of the particle t in d dimension, x td ＝2x max Rand()-x max Initial velocity v td Velocity of the particle t in d dimension, v td ＝2v max Rand()-v max Wherein Rand () is [0,1 ]]Uniformly distributed random number generating functions;
step 9: calculating the fitness, namely calculating the vibration mode of the node where each dimension of the particle is located according to the fourth step
And a stiffness influence coefficient k rs In the belt-in type, calculating a fitness value f of a particle;
step 10: comparing the fitness value f of each particle, and finding the historically optimal position information of each particle as an individual extreme value p td ，p td The historical maximum value of the particle t appears on the d dimension, a global optimal solution is found from the individual historical optimal solutions, the global optimal solution is compared with the historical optimal solution, and the optimal solution is selected as the current historical optimal solution p gd ，p gd The historical maximum value of the particle swarm g appearing on the d dimension is taken as the maximum value;
and 11, step 11: and updating the position and the speed of the particles, wherein the calculation formula is as follows:
v td+1 ＝wv td +c 1 ×Rand()×(p td -x td )+c 2 ×Rand()×(p gd -x td )
x td+1 ＝x td +v td
in the formula: v. of td+1 Is the velocity v of the particle td Updated next generation speed, x td+1 At particle position x td Updated next generation position, Rand () is [0,1 ]]Uniformly distributed random number generating function, c 1 、c 2 Is the acceleration constant, w is the inertial weight;
step 12: if the set maximum iteration times is reached, ending; otherwise loop from step 9.
5. The method for optimizing the arrangement of monitoring points of the large-span foundation pit complex support system structure according to claim 4, wherein the method comprisesCharacterised by the acceleration constant c of said single particle 1 And c 2 Taking c 1 ＝c 2 ＝2。
6. The method for optimizing the arrangement of the monitoring points of the large-span foundation pit complex support system structure according to claim 4, wherein the maximum iteration number is 100, so that the convergence requirement of the algorithm can be met.
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