CN105631150A - Optimization method of shield excavation parameters under condition of compound stratum - Google Patents

Abstract

The invention discloses an optimization method of shield excavation parameters under the condition of a compound stratum. The method is characterized by comprising the following steps of (1) carrying out shield excavation orthogonal experimental design; (2) collecting excavation data; utilizing a data collection and storage system of a shield tunneling machine to collect and record experimental data; collecting the thrust, the rotating speed of a cutter, the excavation speed, the foam solution adding amount, the foam concentration and the cutter torque by the data collection system during the experiment process; collecting data at a time after excavating 20mm every time, wherein the experimental excavation length of each group is 1.6m; (3) building a shield excavation parameter mathematical model; designing an orthogonal experimental model according to the shield construction process, carrying out nonlinear regression analysis on data collected by the orthogonal experiment, respectively building an excavation speed model and a cutter torque model of earth pressure balance shield, confirming the reasonable excavation parameters under the condition of the compound stratum through resolving, and optimizing the excavation parameters, so that the safety of shield construction is improved, and the service life of the shield tunneling machine is prolonged.

Description

The optimization method of shield driving parameter in compound stratum situation

Technical field

The present invention relates to shield driving parameter selection technique field, particularly relate to the optimization method of shield driving parameter in a kind of compound stratum situation.

Background technology

Compound stratum shield driving state modulator is always up tunnel construction technology personnel's concern. In upper soft lower hard compound stratum tunneling process, maximum harm is that weak soil above easily causes backbreaks, and shield tunneling face external and internal pressure is uneven, causes that ground seriously settles, even has an accident owing to boring parameter selection is improper. So setting up the model of shield driving parameter in compound stratum and it being optimized, it is determined that optimum boring parameter, for ensureing that under compound stratum, the driving speed of shield-tunneling construction has great importance with safety.

The research and experiment that the boring parameter of shield has been correlated with by scholar both domestic and external. Prior art passes through model test and theoretical research, it is proposed that the computing formula of relation and cutter head torque between the mathematics physics model of earth pressure balanced shield, EPBS driving, parameters; Zhang Houmei etc. establish the mathematical model of boring parameter by earth pressure balanced shield, EPBS tunnels the analysis of test data; Jia Ke is by optimizing boring parameter and reasonable disposition cutter, solve smoothly shield when extremely hard rock stratum during tunneling construction owing to propulsive parameter and cutter arrange unreasonable, the problem that the tool wear caused is serious, tool changing is frequent, fltting speed is slow etc. affects construction speed.

As can be seen here, for the shield machine problem that the optimization of boring parameter is not only related to construction safety in compound stratum situation, it is also relate to the relevant issues such as efficiency of construction, shield machine service life, therefore, to those skilled in the art, development and Design is a kind of can be current urgent problem according to the method for compound stratum situation simulative optimization selection shield parameter.

Summary of the invention

The technical problem to be solved is to provide in a kind of compound stratum situation the optimization method of shield driving parameter, according to shield-tunneling construction Process Design orthogonal test model, and the data that orthogonal test gathered pass through nonlinear regression analysis, set up driving speed model and the cutter head torque model of earth pressure balanced shield, EPBS respectively, rational boring parameter under compound stratum is determined by resolving, boring parameter is optimized, it is effectively improved shield-tunneling construction safety, extend shield machine service life, improve efficiency of construction.

For solving above-mentioned technical problem, the technical solution used in the present invention is: the optimization method of shield driving parameter in a kind of compound stratum situation, it is characterised in that: comprise the steps:

The first step: shield driving Orthogonal Experiment and Design, jack thrust in shield tunneling process, cutterhead rotating speed, foam solution amount and consistency of foam are controlled, therefore, following orthogonal table is designed with jack thrust, cutterhead rotating speed, foam solution amount and consistency of foam for major parameter:

Test number	Thrust/KN	Rotating speed/r/min	Foam solution amount/m3	Consistency of foam/%
					1	24500	1.05	15	6
2	26500	1.05	11	5 1 -->
					3	28500	1.05	13	7
4	24500	1.15	13	5
					5	26500	1.15	15	7
6	28500	1.15	11	6
					7	24500	1.2	11	7
8	26500	1.2	13	6
					9	28500	1.2	15	5

Second step: tunneling data collection

The data acquisition storage system utilizing shield machine realizes collection and the record of test data, process of the test by data collecting system to thrust, cutterhead rotating speed, driving speed, add foam solution amount, consistency of foam, cutter head torque are acquired, often driving 20 collection one secondary data, often group test Excavation Length is 1.6m;

3rd step: shield driving parameter mathematical model is set up

(1) Multiple Non Linear Regression of driving speed

9 groups of measured test data are carried out regression analysis by the method adopting Multiple Non Linear Regression, and the multinomial nonlinear regression model (NLRM) of employing is:

V=��₀+��₁x₁+��₂x₂+��₃x₃+��₄x₄+��₅x₁ ²+��₆x₁x₂+��₇x₁x₃+��₈x₁x₄+��₉x₂ ²+��₁₀x₂x₃+��₁₁x₂x₄+��₁₂x₃ ²+��₁₃x₃x₄+��₁₄x₄ ²+��₁₅x₁ ³+...+��

Wherein �� is N (0, ��²);

In formula, V is driving speed (/min); x₁For thrust (KN); x₂For cutterhead rotating speed (r/min); x₃For foam solution amount (m³); x₄For consistency of foam (%), ��₀����₁����₂����₄It is regression coefficient;

Adopting SPSS software to carry out test data regression treatment, regression result is as follows:

V=26.499+0.002 �� x₁-23.970��x₂-148.630��x₃+9.989��x₄-6.623E^-8x₁ ²+����

Driving speed regression model collects such as following table:

Model	R	R side	Adjust R side	Standard error of estimate
					1	.843a	.711	.700	1.837
2	.833a	.693	.684	1.542

(2) Multiple Non Linear Regression of cutter head torque

To thrust, cutterhead rotating speed, add the relation of foam volume, consistency of foam and cutter head torque value, nonlinear regression model (NLRM) is adopted to be fitted processing, extract and 9 groups of experimental datas do not have 20 records real data result once carry out regression analysis, adopting SPSS software to carry out experimental data processing, regression result is as follows:

T=-1596.541+0.111 �� X₁+20353.209��X₃+1485.097��X₄-1.193E-6��X₁ ²����

In formula, T is cutter head torque (KN m), X₁For thrust (KN), X₂For cutterhead rotating speed (r/min), X₃For foam solution amount (m³), X₄For consistency of foam (%);

Cutter head torque regression model collects such as following table:

Model	R	R side	Adjust R side	Standard error of estimate
					3	.652	.425	.404	677.253638
4	.530a	.281	.259	642.388588

3rd step: the optimization of shield driving parameter

Shield driving parameter optimization belongs to nonlinear bounded programming problem:

Its mathematical model is:

minF(x)

s.tG_i(x)��0i=1 ..., m

G_j(x)=0j=m+1 ..., n

x_l��x��x_u

Wherein F (x) is polynary real-valued function, G (x) is vector valued function, in nonlinear bounded programming problem, generally this problem is converted to simpler subproblem, subproblem can in the hope of and as the basis of iterative process, the method being based on K-T solution of equation, K-T equation can be expressed as:

$f\left(x^{*}\right)+\underset{i=1}{\overset{n}{\Σ}}{\mathrm{\λ}}_i^{*}\·\▿G_i\left(x^{*}\right)=0$

$\▿G_i=0,i=1,...m$

��_i=>=0, i=m+1 ..., n

Utilizing matlba software programming, respectively driving speed and cutter head torque are optimized, wherein, cutterhead thrust range is 24000KN-28450KN, and cutterhead rotating speed is 0.89r/min-1.28r/min, and every 20 distances add foam volume and range for 0.1m³-0.22m³, consistency of foam scope is at 5%-7%, and the initial value optimizing process is thrust=28450KN, and cutterhead rotating speed=1.19r/min adds foam solution amount=0.2m³, consistency of foam=7%, optimum results is following table such as:

Adopt and have the beneficial effects that produced by technique scheme: according to shield-tunneling construction Process Design orthogonal test model, and the data that orthogonal test gathered pass through nonlinear regression analysis, set up driving speed model and the cutter head torque model of earth pressure balanced shield, EPBS respectively, rational boring parameter under compound stratum is determined by resolving, boring parameter is optimized, it is effectively improved shield-tunneling construction safety, extends shield machine service life, improve efficiency of construction.

Accompanying drawing explanation

Fig. 1 is that thrust is with number of rings variation diagram;

Fig. 2 is that rotating speed is with number of rings variation diagram;

Fig. 3 is that foam solution amount is with number of rings variation diagram;

Fig. 4 is that foam solution concentration is with number of rings variation diagram;

Fig. 5 is driving speed fitted figure;

Fig. 6 is suppressing exception data driving speed fitted figure;

Fig. 7 is moment of torsion fitted figure;

Fig. 8 is suppressing exception data moment of torsion fitted figure.

Detailed description of the invention

Below in conjunction with the drawings and specific embodiments, the present invention is further detailed explanation.

The present invention provides the optimization method of shield driving parameter in a kind of compound stratum situation, it is characterised in that: comprise the steps:

The first step: shield driving Orthogonal Experiment and Design, jack thrust in shield tunneling process, cutterhead rotating speed, foam solution amount and consistency of foam are controlled, therefore, following orthogonal table is designed with jack thrust, cutterhead rotating speed, foam solution amount and consistency of foam for major parameter:

Test number	Thrust/KN	Rotating speed/r/min	Foam solution amount/m3	Consistency of foam/%
					1	24500	1.05	15	6
2	26500	1.05	11	5
					3	28500	1.05	13	7
4	24500	1.15	13	5
					5	26500	1.15	15	7
6	28500	1.15	11	6
					7	24500	1.2	11	7
8	26500	1.2	13	6
					9	28500	1.2	15	5

The data acquisition storage system utilizing shield realizes collection and the record of test data, process of the test by data collecting system to thrust, cutterhead rotating speed, driving speed, add the parameters such as foam solution amount, consistency of foam, cutter head torque and carry out data acquisition with the frequency often tunneling 20mm distance, often group test Excavation Length 1.6m. 9 groups of tests are arranged altogether according to orthogonal test designs table. Due to process of the test thrust, adding the parameters such as foam solution amount and be difficult to accurately control by pre-determined level completely, the design load of actually measured value and orthogonal table has certain difference. Fig. 1-4 is that in test, thrust, cutterhead rotating speed add foam solution amount, four parameters of consistency of foam with the change curve of number of rings.

Second step: tunneling data collection

The data acquisition storage system utilizing shield machine realizes collection and the record of test data, process of the test by data collecting system to thrust, cutterhead rotating speed, driving speed, add foam solution amount, consistency of foam, cutter head torque are acquired, often driving 20 collection one secondary data, often group test Excavation Length is 1.6m;

3rd step: shield driving parameter mathematical model is set up

(1) Multiple Non Linear Regression of driving speed

9 groups of measured test data are carried out regression analysis by the method adopting Multiple Non Linear Regression, and the multinomial nonlinear regression model (NLRM) of employing is:

V=��₀+��₁x₁+��₂x₂+��₃x₃+��₄x₄+��₅x₁ ²+��₆x₁x₂+��₇x₁x₃+��₈x₁x₄+��₉x₂ ²+��₁₀x₂x₃+��₁₁x₂x₄+��₁₂x₃ ²+��₁₃x₃x₄+��₁₄x₄ ²+��₁₅x₁ ³+...+��

Wherein �� is N (0, ��²);

In formula, V is driving speed (/min); x₁For thrust (KN); x₂For cutterhead rotating speed (r/min); x₃For foam solution amount (m³); x₄For consistency of foam (%), ��₀����₁����₂����₄It is regression coefficient;

Adopting SPSS software to carry out test data regression treatment, regression result is as follows:

V=26.499+0.002 �� x₁-23.970��x₂-148.630��x₃+9.989��x₄-6.623E^-8x₁ ²+����

Driving speed regression model collects such as following table:

Model	R	R side	Adjust R side	Standard error of estimate
					1	.843a	.711	.700	1.837
2	.833a	.693	.684	1.542

Coefficient of multiple correlation R is the index weighing dependent variable with independent variable degree of correlation, and the value of coefficient of multiple correlation R is closer to 1, it was shown that their degree of correlation is more close, driving speed moment of torsion regression model R=0.843 in table, it was shown that degree of correlation is higher, coefficient R²=0.711, represent that plan goodness is higher. Standard error of estimate is 1.837. Through inspection, driving speed modular form generally there are notable linear relationship. In 742 groups of sample datas (non-rejecting abnormalities data), driving speed test value is shown in Fig. 5-6. with match value contrast

In Fig. 5, about 80 groups of data are a ring, when every time driving starts, thrust is only small, but can driving speed quickly, this is because, often tunnel a ring, it is necessary to segment assembly, it is necessary to the longer time, soil penetrates in ground therewith containing a large amount of muddy water in storehouse, completely decomposed rock meets the feature that namely water changed, and causes that time every time from new driving, driving speed is fast, and this embodies in the drawings to some extent. Need when being optimized to reject these abnormal datas. The driving speed test value of rejecting abnormalities data and match value correlation curve are shown in Fig. 6. As seen from Figure 6, after rejecting abnormalities data, standard error of estimate is reduced to 1.542 by 1.837, and error reduces to some extent.

(2) Multiple Non Linear Regression of cutter head torque

To thrust, cutterhead rotating speed, add the relation of foam volume, consistency of foam and cutter head torque value, nonlinear regression model (NLRM) is adopted to be fitted processing, extract and 9 groups of experimental datas do not have 20 records real data result once carry out regression analysis, adopting SPSS software to carry out experimental data processing, regression result is as follows:

T=-1596.541+0.111 �� X₁+20353.209��X₃+1485.097��X₄-1.193E-6��X₁ ²����

In formula, T is cutter head torque (KN m), X₁For thrust (KN), X₂For cutterhead rotating speed (r/min), X₃For foam solution amount (m³), X₄For consistency of foam (%);

Cutter head torque regression model collects such as following table:

Model	R	R side	Adjust R side	Standard error of estimate
					3	.652	.425	.404	677.253638
4	.530a	.281	.259	642.388588

From upper data it can be seen that time each ring starts to tunnel torque value very low, along with the increase of distance, moment of torsion is in certain scope fluctuation. Owing under compound stratum, torque change rule is complicated, sometimes up and down, so needing shield machine boring parameter is rationally arranged in driving. The torsional moment test value of rejecting abnormalities data is with match value correlation curve as shown in Figure 8. As seen from Figure 8, after rejecting abnormalities data, standard error of estimate is reduced to 642.388588 by 677.253638, and error reduces to some extent.

3rd step: the optimization of shield driving parameter

Shield driving parameter optimization belongs to nonlinear bounded programming problem:

Its mathematical model is:

minF(x)

s.tG_i(x)��0i=1 ..., m

G_j(x)=0j=m+1 ..., n

x_l��x��x_u

Wherein F (x) is polynary real-valued function, G (x) is vector valued function, in nonlinear bounded programming problem, generally this problem is converted to simpler subproblem, subproblem can in the hope of and as the basis of iterative process, the method being based on K-T solution of equation, K-T equation can be expressed as:

$f\left(x^{*}\right)+\underset{i=1}{\overset{n}{\Σ}}{\mathrm{\λ}}_i^{*}\·\▿G_i\left(x^{*}\right)=0$

$\▿G_i=\left(x^{*}\right)0,i=1,...m$

��_i>=0, i=m+1 ..., n

Utilizing matlba software programming, respectively driving speed and cutter head torque are optimized, wherein, cutterhead thrust range is 24000KN-28450KN, and cutterhead rotating speed is 0.89r/min-1.28r/min, and every 20 distances add foam volume and range for 0.1m³-0.22m³, consistency of foam scope is at 5%-7%, and the initial value optimizing process is thrust=28450KN, and cutterhead rotating speed=1.19r/min adds foam solution amount=0.2m³, consistency of foam=7%, optimum results is following table such as:

Solving result from above: maximum driving speed occurs in cutterhead thrust at 28449.999kN, cutterhead rotating speed 1.280r/min, and foam solution amount is 0.100m³, when consistency of foam is 5.024%, it is seen that when thrust arranges higher value in the scope of test value, cutterhead rotating speed arranges relatively big, and the optimal value obtaining driving speed is 13.851mm/min; It is 24000kN that minimal torque occurs in cutterhead thrust, and cutterhead rotating speed is 1.277r/min foam solution amount is 0.220m³, obtaining optimal value during consistency of foam 7%, it is seen that when thrust takes minima in the scope of test value, during foam solution amount maximum, the optimal value obtaining cutter head torque is 3260.006kN m. It is consistent with practice of construction situation, it was demonstrated that the reasonability of optimum results.

In a word, adopt orthogonal test technology herein, by the boring parameter data of field measurement, to thrust, cutterhead rotating speed, add the main boring parameter such as foam volume, consistency of foam the affecting laws of driving speed, cutter head torque has been studied. Show that Main Conclusions is as follows:

(1) by the shield driving speed model to cutter head torque it can be seen that driving speed is directly proportional to thrust, cutterhead rotating speed, when cutterhead thrust is less, cutterhead rotating speed is increased the effect improving driving speed is less; Cutter head torque is directly proportional to thrust, and when increasing cutterhead thrust, the moment of torsion of cutterhead can increase therewith.

(2) binding tests data analysis and practice of construction situation, is proposed with the low thrust slow-speed of revolution, and adopts high thrust height speed combination in soft rock during driving, it is possible to effectively improve drivage efficiency in when the weak soil in compound stratum tunnels.

(3) shown by the optimization of boring parameter, combination boring parameter suitable within the specific limits, can obtaining maximum driving speed and minimum moment of torsion, the boring parameter setting for compound stratum construction provides theoretical basis, has important construction value.

Claims (1)

1. the optimization method of shield driving parameter in a compound stratum situation, it is characterised in that: comprise the steps:

The first step: shield driving Orthogonal Experiment and Design, jack thrust in shield tunneling process, cutterhead rotating speed, foam solution amount and consistency of foam are controlled, therefore, following orthogonal table is designed with jack thrust, cutterhead rotating speed, foam solution amount and consistency of foam for major parameter:

Test number Thrust/KN Rotating speed/r/min Foam solution amount/m³ Consistency of foam/% 1 24500 1.05 15 6 2 26500 1.05 11 5 3 28500 1.05 13 7 4 24500 1.15 13 5 5 26500 1.15 15 7 6 28500 1.15 11 6 7 24500 1.2 11 7 8 26500 1.2 13 6 9 28500 1.2 15 5

Second step: tunneling data collection

The data acquisition storage system utilizing shield machine realizes collection and the record of test data, process of the test by data collecting system to thrust, cutterhead rotating speed, driving speed, add foam solution amount, consistency of foam, cutter head torque are acquired, often driving 20 collection one secondary data, often group test Excavation Length is 1.6m;

3rd step: shield driving parameter mathematical model is set up

(1) Multiple Non Linear Regression of driving speed

9 groups of measured test data are carried out regression analysis by the method adopting Multiple Non Linear Regression, and the multinomial nonlinear regression model (NLRM) of employing is:

V=��₀+��₁x₁+��₂x₂+��₃x₃+��₄x₄+��₅x₁ ²+��₆x₁x₂+��₇x₁x₃+��₈x₁x₄+��₉x₂ ²+��₁₀x₂x₃+��₁₁x₂x₄+��₁₂x₃ ²+��₁₃x₃x₄+��₁₄x₄ ²+��₁₅x₁ ³+��+��

Wherein �� is N (0, ��²);

In formula, V is driving speed (/min); x₁For thrust (KN); x₂For cutterhead rotating speed (r/min); x₃For foam solution amount (m³); x₄For consistency of foam (%), ��₀����₁����₂����₄It is regression coefficient;

Adopting SPSS software to carry out test data regression treatment, regression result is as follows:

V=26.499+0.002 �� x₁-23.970��x₂-148.630��x₃+9.989��x₄-6.623E^-8x₁ ²+����

Driving speed regression model collects such as following table:

Model R R side Adjust R side Standard error of estimate 1 .843^a .711 .700 1.837 2 .833^a .693 .684 1.542

(2) Multiple Non Linear Regression of cutter head torque

To thrust, cutterhead rotating speed, add the relation of foam volume, consistency of foam and cutter head torque value, nonlinear regression model (NLRM) is adopted to be fitted processing, extract and 9 groups of experimental datas do not have 20 records real data result once carry out regression analysis, adopting SPSS software to carry out experimental data processing, regression result is as follows:

T=-1596.541+0.111 �� X₁+20353.209��X₃+1485.097��X₄-1.193E-6��X₁ ²����

In formula, T is cutter head torque (KN m), X₁For thrust (KN), X₂For cutterhead rotating speed (r/min), X₃For foam solution amount (m³), X₄For consistency of foam (%);

Cutter head torque regression model collects such as following table:

Model R R side Adjust R side Standard error of estimate 3 .652 .425 .404 677.253638 4 .530a .281 .259 642.388588

3rd step: the optimization of shield driving parameter

Shield driving parameter optimization belongs to nonlinear bounded programming problem:

Its mathematical model is:

minF(x)

s.tG_i(x)��0i=1 ..., m

G_j(x)=0j=m+1 ..., n

x₁��X��x_u

Wherein F (x) is polynary real-valued function, G (x) is vector valued function, in nonlinear bounded programming problem, generally this problem is converted to simpler subproblem, subproblem can in the hope of and as the basis of iterative process, the method being based on K-T solution of equation, K-T equation can be expressed as:

$f\left(x^{*}\right)+\underset{i=1}{\overset{n}{\Σ}}{\mathrm{\λ}}_i^{*}\·\▿G_i\left(x^{*}\right)=0$

$\▿G_i\left(x^{*}\right)=0,i=1,...m$

��_i>=0, i=m+1 ..., n

Utilizing matlba software programming, respectively driving speed and cutter head torque are optimized, wherein, cutterhead thrust range is 24000KN-28450KN, and cutterhead rotating speed is 0.89r/min-1.28r/min, and every 20 distances add foam volume and range for 0.1m³-0.22m³, consistency of foam scope is at 5%-7%, and the initial value optimizing process is thrust=28450KN, and cutterhead rotating speed=1.19r/min adds foam solution amount=0.2m³, consistency of foam=7%, optimum results is following table such as: