Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides a rapid method for optimizing the tunneling parameters of an earth pressure balanced type shield tunneling machine, which is used for quantitatively optimizing the tunneling parameters of the earth pressure balanced type shield tunneling machine and taking the ratio of the tunneling speed to the cutter head torque as an optimized analysis objective function and specifically comprises the following steps:
step one, establishing a tunneling efficiency statistical sample
The tunneling efficiency β is defined as the tunneling rate v divided by the cutterhead torque T, as formula (1). T directly reflects the operating state of the equipment, and β reflects the relationship between the tunneling rate and the loading capacity of the cutterhead drive motor.
And combining the tunneling parameters automatically recorded by the shield tunneling machine during the trial tunneling of the tunnel and the tunneling parameter data of the previous engineering, taking the tunneling speed v, the cutter torque T, the effective thrust F, the soil bin pressure p and the cutter rotating speed n which are actually measured at the same moment as a group of tunneling parameters, and taking β, F, p and n at each recording moment in the trial tunneling stage as a tunneling efficiency statistical sample.
Step two, obtaining a tunneling efficiency prediction equation for the limited sample through symbolic regression and linear regression
Uniaxial compressive strength R to formation saturationcPerforming symbolic regression on the tunneling efficiency β of the shield tunneling machine in different strata respectively, and running the symbolic regression algorithm on the computer with the computation time of less than 1 minute and the fitting precision r2Fitting equations for β above 0.7 are candidate equations.
Counting candidate equations of each stratum, independent variable n2P, np, pF all co-exist in at least one of the candidate equations for each formation, thus in n2P, np and pF are used as independent variables of the tunneling efficiency prediction equation under the limited sample, as shown in formula (2), linear regression is carried out again on the tunneling efficiency statistical sample through the tunneling efficiency prediction equation under the limited sample, and equation coefficients belonging to each stratum are obtained;
β is the predicted value of tunneling efficiency under limited samples.
β*=a1n2+a2p+a3np+a4pF+a5(2)
Step three tunneling efficiency prediction equation continuation
The equation coefficients in the formula (2) obtained under the condition of the limited samples are discrete equation coefficients for the limited kinds of strata, and the equations corresponding to the discrete equation coefficients need to be extended to obtain the equations suitable for the general strata.
Taking coefficients of prediction equations of the tunneling efficiency in different tunneling strata under the limited samples obtained in the step one as dependent variables, and taking the saturated uniaxial compressive strength R of the tunneling strata ascLinear and nonlinear regression for independent variables to obtain equation coefficients with RcThe continuous function of the change is shown as formula (3), formula (4), formula (5), formula (6) and formula (7). Because the samples are all obtained from hard rocks, the continuation of the tunneling efficiency prediction equation is also in the hard rock range, namely Rc≥30MPa。
a1=116.588-99.614Rc 0.038,Rc≥30MPa (3)
a2=46.522-12.532Rc 0.313,Rc≥30MPa (4)
a3=0.093Rc-4.414,Rc≥30MPa (5)
a4=1.135×10-6Rc-6.976×10-5,Rc≥30MPa (6)
According to the formula (8), the formula (3), the formula (4), the formula (5), the formula (6) and the formula (7) are substituted into the formula (2), so that a tunneling efficiency prediction equation suitable for the soil pressure balance type shield tunneling hard rock is obtained, and β is a tunneling efficiency prediction value of the soil pressure balance type shield tunneling hard rock.
Step four, determining an optimized calculation formula and boundary conditions
The optimal calculation formula of the tunneling parameter is shown as a formula (9), pΩ、ΘΩ、ΨΩRespectively reflects the allowable fluctuation range of the soil bin pressure, the effective thrust and the cutter head rotating speed when the stratum is normally tunneled omega, namely [ pmin,pmax]、[Fmin,Fmax]、[nmin,nmax]。
Step five-step dot method to calculate β larger value
Influence factors of the optimization problem are quantized, the boundary is clear, linear equal division is adopted to obtain the optimal value grid of the tunneling parameters to be selected, and step-by-step point-taking method gradual operation is carried out on grid nodes.
P is to beΩ、ΘΩ、ΨΩRespectively as emptyAnd defining domains on the X, Y and Z coordinate axes which are mutually orthogonal in the rectangular coordinate system are obtained, and β -star space defining domains are obtained.
Establishing a first step grid, and respectively connecting p
Ω、Θ
Ω、Ψ
ΩAs m
1Dividing equally and making normal planes of coordinate axes of the equally divided points at all equally divided points, wherein the normal planes are intersected to form β -x space definition domain first step grid, and any one first step grid node
Satisfies the formulas (10), (11) and (12). Determining tunneling stratum R according to stratum investigation data
cThen, the points are put
And (3) substituting the formula (8) to obtain β corresponding to each first step grid node in the spatial definition domain of β, arranging β corresponding to each first step grid node in the spatial definition domain of β in descending order of magnitude to obtain a first step grid node β number sequence, and taking the grid nodes corresponding to β which is the first 20% of the maximum in the first step grid nodes β as the first step grid dominant points.
Establishing a second step grid, and taking the dominant point of each first step grid as a body center and the projection lengths of the dominant point in the x axis, the y axis and the z axis as
The sides of the cuboid are m
2Dividing equally, making normal planes of coordinate axes of all equally divided points, and intersecting all normal planes to form second grid dominant points of the first stepStep grid, any second step grid node
Satisfies the formulas (13), (14) and (15). Determining tunneling stratum R according to stratum investigation data
cThen, the points are put
Formula (8) was substituted to obtain β × corresponding to all second-step grid nodes.
β corresponding to the first step grid dominant point and β corresponding to all the second step grid nodes are collected, and the grid nodes corresponding to the first 10% of the maximum β are taken as initial selection optimization parameter points.
And sixthly, checking the tunneling rate.
The positive hob and the side hob are distributed on the cutter head, the positive hob is installed in parallel to the tunneling direction, and a non-zero side hob installation angle exists between the side hob and the tunneling direction. The effective thrust is approximately evenly distributed to each hob, the force parallel to the tunneling direction is F/N, the forces borne by the positive hob and the side hob and parallel to the tunneling direction are approximately evenly F/N, and the number of the positive hobs is NfcWith a number of edge cutters of NlcThe total number of the cutters is N, and the formula (16) shows. According to the balance of forces, the resultant force of the stratum resistance borne by the cutter head is equal to the resultant force of the effective thrust, the torque of the cutter head is equal to the resultant moment of the stratum resistance to the main shaft of the cutter head, and according to the Saint-Venn principle, the sum of the cutter head torques borne by the positive hob is approximate to that of the cutter headIs λ μ (FN)fcR/N) R/2, the cutter head torque can be approximate to the resultant torque of the occlusal force and the frictional resistance generated between the cutter and the rock on the face by the effective thrust, as shown in formula (17), R is the maximum installation radius of the positive hob, and R iswThe mounting radius of the w-th edge hob, thetawThe w-th installation angle of the edge roller cutter is shown, mu is the friction coefficient between steel and the stratum, and lambda is the empirical correction coefficient.
N=Nfc+Nlc(16)
According to the formula (8), the tunneling rate to-be-determined value v is represented by the formula (18).
And substituting the cutter head rotating speed n, the soil bin pressure p and the effective thrust F of the primarily selected optimization parameter points into a formula (18) to obtain v corresponding to the points, calculating the v corresponding to each primarily selected optimization parameter point one by one, and taking the tunneling parameter of the primarily selected optimization parameter point when v is the maximum as the optimized tunneling parameter.
Further, in the step one: v, T, F, p and n are respectively in units of mm/min and 106Nm、kN、Bar、r/min。
Further, in the sixth step, λ is an empirical correction coefficient, and λ can be 0.24, 0.21, and 0.2 in a granite formation, an andesite formation, and a limestone formation, respectively.
Detailed description of the invention
Aiming at the defects of the prior art, the invention provides a rapid method for optimizing the tunneling parameters of an earth pressure balance type shield tunneling machine, which comprises the following steps:
when the shield tunnels different types of stratums, namely tunnel face stratum distribution is changed, the shield tunneling speed and cutter head torque are changed accordingly. The tunneling speed is larger, the construction period is shorter, but the cutter head torque is also increased, and the cutter head torque is the most main control parameter of the integrity of equipment and reflects the working state of a cutter head main shaft. In order to meet the requirements of construction period and equipment completeness, balance needs to be obtained between the tunneling rate and the cutter head torque, so that the potential of the equipment is excavated to the maximum extent under the condition that the equipment is guaranteed to be complete, and the tunneling rate is effectively improved. Therefore, the shield tunneling parameter control optimization method based on the geological segmentation is provided, and the shield tunneling parameter dynamic optimization control based on the tunneling stratum parameters is realized.
Step one, establishing a statistical sample of tunneling efficiency
The tunneling efficiency β is defined as the tunneling rate v divided by the cutterhead torque T, as formula (1). T directly reflects the operating state of the equipment, and β reflects the relationship between the tunneling rate and the loading capacity of the cutterhead drive motor.
Combining tunneling parameters automatically recorded by a shield machine during trial tunneling of a tunnel and tunneling parameter data of a previous project, taking a tunneling rate v, a cutter torque T, an effective thrust F, a soil bin pressure p and a cutter rotating speed n which are actually measured at the same moment as a group of tunneling parameters, and taking β, F, p and n at each recording moment in a trial tunneling stage as a tunneling efficiency statistical sample;
v, T, F, p, n are in mm/min (millimeter per minute), 106Nm, kN, Bar, r/min (circles per minute).
Step two, obtaining a prediction equation of the tunneling efficiency for the limited sample through symbolic regression and linear regression to obtain the saturated uniaxial compressive strength R of the stratumcβ of the shield machine in different strata are respectively subjected to symbolic regression, the operation time of a computer running a symbolic regression algorithm in the background is less than 1 minute, and the fitting precision r2Fitting equations for β above 0.7 are candidate equations.
Counting candidate equations of each stratum, independent variable n2P, np, pF allCo-existing in at least one of the candidate equations of the respective formations, thus in n2P, np and pF are used as independent variables of the tunneling efficiency prediction equation under the limited sample, as shown in formula (2), linear regression is carried out again on the tunneling efficiency statistical sample through the tunneling efficiency prediction equation under the limited sample, and equation coefficients belonging to each stratum are obtained, and are shown in table 1;
β is the predicted value of tunneling efficiency under limited samples.
β*=a1n2+a2p+a3np+a4pF+a5(2)
TABLE 1 prediction equation coefficient of tunneling efficiency of different saturated uniaxial compressive strength strata
Step three tunneling efficiency prediction equation continuation
Table 1 shows equation coefficients obtained by equation (2) under discrete finite sample conditions (the saturated uniaxial compressive strengths of the formation are 42MPa, 54MPa, 62MPa, 90MPa, and 118MPa, respectively), and the equation corresponding to the discrete equation coefficients under the finite sample conditions needs to be extended to obtain the equation coefficients suitable for general formations (the saturated uniaxial compressive strength is different from the sample value), that is, the equation can be applied to the cases when the saturated uniaxial compressive strength of the formation is not equal to 42MPa, 54MPa, 62MPa, 90MPa, and 118 MPa.
Taking coefficients of prediction equations of the tunneling efficiency in different tunneling strata under the limited samples obtained in the step one as dependent variables, and taking the saturated uniaxial compressive strength R of the tunneling strata ascLinear and nonlinear regression for the independent variables, i.e. for the scatter points in FIG. 1, the equation coefficients are obtained as a function of RcThe continuous function of the change is shown as formula (3), formula (4), formula (5), formula (6) and formula (7). Because the samples are all obtained from hard rocks, the continuation of the tunneling efficiency prediction equation is also in the hard rock range, namely Rc≥30MPa。
a1=116.588-99.614Rc 0.038,Rc≥30MPa (3)
a2=46.522-12.532Rc 0.313,Rc≥30MPa (4)
a3=0.093Rc-4.414,Rc≥30MPa (5)
a4=1.135×10-6Rc-6.976×10-5,Rc≥30MPa (6)
According to the formula (8), the formula (3), the formula (4), the formula (5), the formula (6) and the formula (7) are substituted into the formula (2), so that a tunneling efficiency prediction equation suitable for the soil pressure balance type shield tunneling hard rock is obtained, and β is a tunneling efficiency prediction value of the soil pressure balance type shield tunneling hard rock.
Step four, determining an optimized calculation formula and boundary conditions
The optimal calculation formula of the tunneling parameter is shown as a formula (9), pΩ、ΘΩ、ΨΩRespectively reflects the allowable fluctuation range of the soil bin pressure, the effective thrust and the cutter head rotating speed when the stratum is normally tunneled omega, namely [ pmin,pmax]、[Fmin,Fmax]、[nmin,nmax]。
Taking Shenzhen subway certain tunnel interval as an example, the saturated uniaxial compressive strength R of the tunneling stratumcAnd the pressure is 64.5MPa, the heading efficiency prediction equation corresponding to the stratum is obtained according to the formula (8) and is β ═ 0.115n2+0.346p+1.585np+3.448×10- 6pF +2.739, and according to engineering experience, during normal tunneling, the allowable fluctuation range p of the pressure of the soil bin in the stratumΩIs [0.05,0.4 ]]Allowable fluctuation range psi of cutter head rotation speedΩIs [0.8,2.2 ]]Effective thrust allowable fluctuation range thetaΩIs [6000,15000 ]]。
Step five-step dot method to calculate β larger value
Influence factors of the optimization problem are quantized, the boundary is clear, linear equal division is preferably adopted to obtain a mesh with the optimal value of the tunneling parameter to be selected, and step-by-step point taking method gradual operation is carried out on mesh nodes, so that influence of initial value selection on a calculation result is avoided.
P is to beΩ、ΘΩ、ΨΩAnd β x space domain is obtained as the domain defined on the mutually orthogonal x, y and z coordinate axes of the space rectangular coordinate system.
Establishing a first step grid, and respectively connecting p
Ω、Θ
Ω、Ψ
ΩAs m
1Dividing equally and making normal planes of coordinate axes of the equally divided points at all equally divided points, wherein the normal planes are intersected to form β -x space definition domain first step grid, and any one first step grid node
Satisfies the formulas (10), (11) and (12). Determining tunneling stratum R according to stratum investigation data
cThen, the points are put
And (3) substituting the formula (8) to obtain β corresponding to each first step grid node in the spatial definition domain of β, arranging β corresponding to each first step grid node in the spatial definition domain of β in descending order of magnitude to obtain a first step grid node β number sequence, and taking the grid nodes corresponding to β which is the first 20% of the maximum in the first step grid nodes β as the first step grid dominant points.
Establishing a second step grid, and taking the dominant point of each first step grid as a body center and the projection lengths of the dominant point in the x axis, the y axis and the z axis as
The sides of the cuboid are m
2Dividing equally, making normal planes of coordinate axes of all equally divided points, intersecting all normal planes to form second step grid of the first step grid dominant point, any one second step grid node
Satisfies the formulas (13), (14) and (15). Determining tunneling stratum R according to stratum investigation data
cThen, the points are put
Formula (8) was substituted to obtain β × corresponding to all second-step grid nodes.
β corresponding to the first step grid dominant point and β corresponding to all the second step grid nodes are collected, and the grid nodes corresponding to the first 10% of the maximum β are taken as initial selection optimization parameter points.
Step six tunneling rate check
As shown in figure 2, a positive hob and an edge hob are distributed on the cutterhead, the positive hob is installed in parallel with the tunneling direction, and the edge hob does not exist between the tunneling direction and the edge hobAnd the installation angle of the edge hob is zero. The effective thrust is approximately evenly distributed to each hob, the force parallel to the tunneling direction is F/N, the forces borne by the positive hob and the side hob and parallel to the tunneling direction are approximately evenly F/N, and the number of the positive hobs is NfcWith a number of edge cutters of NlcThe total number of the cutters is N, and the formula (16) shows. According to the balance of forces, the resultant force of the stratum resistance borne by the cutter head is equal to the resultant force of the effective thrust, the torque of the cutter head is equal to the resultant moment of the stratum resistance to the main shaft of the cutter head, and the sum of the torques of the cutter head borne by the positive hob is approximate to lambda mu (FN) according to the Saint-Venn principlefcR/N) R/2, the cutter head torque can be approximate to the resultant torque of the occlusal force and the frictional resistance generated between the cutter and the rock on the face by the effective thrust, as shown in formula (17), R is the maximum installation radius of the positive hob, and R iswThe mounting radius of the w-th edge hob (the distance between the contact point between the hob and the tunnel face and the normal line of the cutterhead plane passing through the center of the cutterhead), thetawThe w-th installation angle of the edge hob is set, mu is the friction coefficient between steel and the stratum, lambda is the empirical correction coefficient, and lambda can be respectively 0.24, 0.21 and 0.2 in the granite stratum, the andesite stratum and the limestone stratum.
N=Nfc+Nlc(16)
According to the formula (8), the tunneling rate to-be-determined value v is represented by the formula (18).
And substituting the cutter head rotating speed n, the soil bin pressure p and the effective thrust F of the primarily selected optimization parameter points into a formula (18) to obtain v corresponding to the points, calculating the v corresponding to each primarily selected optimization parameter point one by one, and taking the tunneling parameter of the primarily selected optimization parameter point when v is the maximum as the optimized tunneling parameter.