Microwave-assisted tunneling rock breaking parameter optimization method, tunneling method and system and tunneling machine

Abstract

The invention discloses a microwave-assisted tunneling rock breaking parameter optimization method, a tunneling method and system and a tunneling machine. The method comprises the following steps that S1, the confining pressure value borne by rock at the corresponding position is measured; s2, microwave pretreatment is conducted on the rock through microwave radiation equipment; s3, obtaining a rock thermal damage factor; s4, performing a hob rock breaking test on the rock pretreated in the step S2 and the control group rock which is not subjected to microwave treatment; s5, obtaining a microwave rock breaking energy consumption reduction coefficient and a microwave rock breaking degree gain coefficient; s6, establishing a microwave-assisted hob rock breaking benefit coefficient function model; and S7, taking the microwave-assisted hob rock breaking benefit coefficient function model as a target function, and obtaining optimized microwave parameters and hob rock breaking parameters. According to the method, the optimized microwave parameters and hob rock breaking parameters are finally obtained by establishing the microwave-assisted hob rock breaking benefit coefficient function model, so that the problem that parameter matching lacks a quantitative decision basis in the prior art is solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of tunneling, in particular, to a microwave-assisted tunneling rock breaking parameter optimization method, a tunneling method, a system and a tunneling machine. BACKGROUND

[0002] In tunnel engineering construction, tunneling is a key and complex construction link. The traditional tunneling method mainly relies on mechanical rock breaking tools such as milling cutters, which break the rock layer through physical action to realize the gradual advancement of the tunnel. However, with the development of tunnel engineering towards more complex geological conditions and higher construction requirements, the limitations of the traditional milling cutter rock breaking method gradually appear. For example, when encountering hard rock layers, the wear of the milling cutter intensifies, and the tunneling speed significantly decreases.

[0003] In recent years, the application of microwave technology in the field of geotechnical engineering has gradually attracted attention. Microwaves can pre-treat rock layers, change the physical properties of rock layers such as reducing the hardness and increasing the brittleness of rock layers through the thermal and electromagnetic effects of microwaves, thereby creating more favorable conditions for subsequent milling cutter rock breaking. However, at present, there is a lack of scientific quantitative decision basis for the matching between microwave parameters and milling cutter rock breaking parameters in actual construction. Construction personnel often adjust based on experience, making it difficult to achieve optimal tunneling results. This inaccurate parameter matching not only may lead to waste of microwave energy, but also may affect the service life of the milling cutter and the tunneling efficiency. SUMMARY

[0004] The present application aims to at least solve one of the technical problems existing in the prior art. To this end, the present application proposes a microwave-assisted tunneling rock breaking parameter optimization method, a tunneling method, a system and a tunneling machine.

[0005] To achieve the above-mentioned purpose, the technical solution adopted by the present application is as follows:

[0006] A microwave-assisted tunneling rock breaking parameter optimization method, comprising the following steps: S1, determining the confining pressure value σ c of the rock at the corresponding horizon and obtaining the physical and mechanical parameters of the rock; S2, using a microwave radiation device to pre-treat the rock with microwaves; S3, analyzing the rock sample after step S2 and obtaining the thermal damage factor of the rock; S4, performing a milling cutter rock breaking test on the rock pre-treated in step S2 and the control group rock without microwave treatment, and applying the confining pressure σ cAnd control the rock breaking parameters of the cutter, synchronously collect the vertical force of the cutter, the rolling force of the cutter, and the total volume of the broken rock chips in the test; S5, obtain the microwave rock breaking energy consumption reduction coefficient and the microwave rock breaking fragmentation gain coefficient; S6, establish a microwave auxiliary cutter rock breaking benefit coefficient function model; S7, take the microwave auxiliary cutter rock breaking benefit coefficient function model as a target function, and obtain the optimized microwave parameters and the rock breaking parameters of the cutter.

[0007] Further, step S3 specifically comprises: S31, obtaining a rock temperature rise coefficient α1 and a rock porosity gain rate α2 under microwave radiation through the following formula: α1 = μ1fε0E0 2 t m ; S32, obtaining a rock thermal damage factor α under microwave radiation through the following formula: α = ε1α1α2; wherein α1 is the rock temperature rise coefficient under microwave radiation, μ1 is the rock thermal expansion coefficient, f is the microwave irradiation frequency, ε0 is the rock dielectric constant, E0 is the microwave electric field intensity, t m is the microwave irradiation time; α2 is the rock porosity gain rate under microwave radiation, φ micro is the pore size of the rock after microwave treatment, φ T is the pore size of the rock without microwave treatment; α is the rock thermal damage factor, and ε1 is a proportional coefficient.

[0008] Further, step S5 specifically comprises: S51, obtaining the dynamic rock breaking specific energy S w and the rock fractal dimension D w of the rock after microwave pretreatment in step S2; S52, obtaining the dynamic rock breaking specific energy S0 and the rock fractal dimension D0 of the rock without microwave treatment in the control group; S53, calculating the microwave rock breaking energy consumption reduction coefficient K1 and the microwave rock breaking fragmentation gain coefficient K2. The rock breaking specific energy refers to the energy consumed for breaking a unit volume of rock, which is an important indicator for measuring the rock breaking efficiency. The smaller the specific energy, the less energy is consumed for breaking a unit volume of rock, and the higher the rock breaking efficiency.

[0009] Further, the microwave rock breaking energy consumption reduction coefficient K1 is obtained through the following formula: The microwave rock breaking fragmentation gain coefficient K2 is obtained through the following formula: The microwave auxiliary cutter rock breaking benefit coefficient function model is: K = α·K1·K2.

[0010] Further, the dynamic rock breaking specific energy S w and the rock fractal dimension D w of the rock after microwave pretreatment are obtained through the following formula:

[0011]

[0012] S w is the specific energy of the rolling cutter cutting the microwave pretreated rock, F n1 is the vertical force of the rolling cutter of the microwave pretreatment group, F t1 is the rolling force of the rolling cutter of the microwave pretreatment group, v p1 is the penetration speed of the rolling cutter of the microwave pretreatment group, v c1 is the cutting speed of the rolling cutter of the microwave pretreatment group, V w1 is the total volume of the rock debris of the microwave pretreatment group; D w is the fractal dimension of the rock of the microwave pretreatment group, C1 is a correction coefficient of the fractal dimension of the rock of the microwave pretreatment group, and N1 is the number of the debris in the preset particle size interval of the microwave pretreatment group, d maxw1 / d minw1 is the particle size ratio of the debris of the microwave pretreatment group.

[0013] Further, the microwave parameters at least include a microwave electric field intensity E0, a microwave irradiation time t m , and a microwave frequency f; the geological parameters at least include a confining pressure value σ c ; and the rolling cutter parameters at least include a penetration speed and a cutting speed.

[0014] Further, the step S7 specifically comprises: S71, taking a microwave-assisted rolling cutter rock breaking efficiency coefficient function model as a target function, taking the geological parameters (a confining pressure value σ c ), the microwave parameters, and the rolling cutter parameters as decision variables, and setting a value range of each variable; S72, obtaining the optimized microwave parameters and the rolling cutter rock breaking parameters through an optimization algorithm.

[0015] The application further provides a tunneling method, which is constructed according to the optimized microwave parameters and the rolling cutter rock breaking parameters obtained by the microwave-assisted tunneling rock breaking parameter optimization method.

[0016] The application further provides a microwave-assisted rolling cutter rock breaking parameter optimization system for a tunnel, which is used for executing the microwave-assisted tunneling rock breaking parameter optimization method and comprises a measurement module for measuring a confining pressure value σ c, a physical and mechanical parameter acquisition module for acquiring physical and mechanical parameters of the rock; a microwave test data collection module for pre-treating the rock with a microwave radiation device; an analysis module for analyzing the rock sample after microwave treatment and obtaining a rock thermal damage factor; a collection module for performing a roller cutter rock breaking test on the rock pre-treated in step S2 and a control group of rocks without microwave treatment, and synchronously collecting vertical force of the roller cutter, rolling force of the roller cutter, and total volume of broken rock debris; a coefficient obtaining module for obtaining a microwave rock breaking energy consumption reduction coefficient and a microwave rock breaking fragmentation gain coefficient; a function model establishing module for establishing a microwave-assisted roller cutter rock breaking efficiency coefficient function model; and a parameter optimization module for taking the microwave-assisted roller cutter rock breaking efficiency coefficient function model as an objective function to obtain optimized microwave parameters and roller cutter rock breaking parameters.

[0017] The application also provides a tunnel boring machine for implementing the tunnel boring method.

[0018] The application has the following beneficial effects:

[0019] The application provides a microwave-assisted tunnel boring rock breaking parameter optimization method, which has remarkable technical effects. By determining the confining pressure value of the rock corresponding to the layer (step S1) and combining microwave pre-treatment test (step S2) and rock thermal damage factor analysis (step S3), the change of the microwave on the physical properties of the rock can be accurately evaluated. By performing a roller cutter rock breaking test on the microwave pre-treated rock and the untreated rock (step S4), and synchronously collecting key data such as vertical force of the roller cutter, rolling force of the roller cutter, and total volume of broken rock debris, the influence of microwave pre-treatment on the effect of roller cutter rock breaking can be quantified. By calculating the microwave rock breaking energy consumption reduction coefficient and the microwave rock breaking fragmentation gain coefficient (step S5), and establishing a microwave-assisted roller cutter rock breaking efficiency coefficient function model (step S6), the scientific and quantitative matching between the microwave parameters and the roller cutter rock breaking parameters is realized. Finally, the optimized microwave parameters and roller cutter rock breaking parameters are obtained by taking the efficiency coefficient function model as an objective function (step S7), thereby solving the problem of lacking quantitative decision basis for parameter matching in the prior art. By using the method of the application, the tunnel boring efficiency can be significantly improved, the roller cutter wear can be reduced, the service life of the equipment can be prolonged, the waste of microwave energy can be reduced, and the safety and economy of the construction process can be improved. In addition, by optimizing the parameter matching, the construction cost can be effectively reduced, the tunnel construction period can be shortened, and strong technical support can be provided for tunnel engineering construction under complex geological conditions.

[0020] In addition to the objects, features, and advantages described above, the application has other objects, features, and advantages. The application will be described in further detail below with reference to the drawings. BRIEF DESCRIPTION OF DRAWINGS

[0021] The accompanying drawings, which form a part of this application, are included to provide a further understanding of the application, illustrate the preferred embodiments of the application and assist in

[0022] Figure 1 is a schematic diagram of the whole process of the present application;

[0023] Figure 2 is a schematic diagram of part of the process of the present application. DETAILED DESCRIPTION

[0024] It should be understood that the specific embodiments described herein merely exemplify the application and do not limit the application.

[0025] The technical solutions in the embodiments of the present application will be clearly and completely described with reference to the drawings of the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, but not all the embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0026] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present application are only used to explain the relative positional relationship, movement condition, etc. between components in a certain posture (as shown in the drawings), and if the certain posture changes, the directional indications also change accordingly.

[0027] In addition, the description of "first", "second" and the like in the present application is only for the purpose of description, and cannot be understood as indicating or implying the relative importance of the technical features indicated or the number of the technical features indicated. Therefore, the features defined as "first", "second" can explicitly or implicitly include at least one of the features. In addition, the technical solutions of each embodiment can be combined with each other, but it must be based on the realization of those skilled in the art, and when the combination of technical solutions contradicts each other or cannot be realized, it should be considered that the combination of technical solutions does not exist, and is not within the scope of protection required by the present application.

[0028] Please refer to Figure 1 In a preferred embodiment of the present application, a microwave-assisted tunneling rock breaking parameter optimization method is provided, which comprises steps S1, S2, S3, S4, S5, S6 and S7.

[0029] S1, measuring the confining pressure value σ of the rock corresponding to the layer c, the physical and mechanical parameters of the rock are obtained. The physical and mechanical parameters at least include the compressive strength of the rock, and in some embodiments, the physical and mechanical parameters can further include tensile strength, elastic modulus or other physical and mechanical parameters in order to consider the influence of other physical quantities on rock breaking.

[0030] S2, the rock is subjected to microwave pretreatment by using a microwave radiation device, and the thermal expansion coefficient of the rock and the dielectric constant of the rock can be obtained through experiments, and the microwave irradiation frequency, the microwave electric field intensity and the microwave irradiation time of the microwave radiation can be recorded.

[0031] S3, the rock sample treated in step S2 is analyzed, and the thermal damage factor of the rock is obtained.

[0032] S4, the rock pretreated in step S2 and the control group rock without microwave treatment are subjected to a cutter rock breaking test, and the confining pressure σ c and control the cutter rock breaking parameters, which are specifically the cutter penetration speed and the cutter cutting speed. The vertical force of the cutter, the rolling force of the cutter, and the total volume of the broken rock debris are synchronously collected in the test. The vertical force of the cutter and the rolling force of the cutter are the forces applied by the rock to the cutter during rock breaking.

[0033] S5, the microwave rock breaking energy consumption reduction coefficient and the microwave rock breaking fragmentation gain coefficient are obtained.

[0034] S6, a microwave-assisted cutter rock breaking efficiency coefficient function model is established.

[0035] S7, the microwave-assisted cutter rock breaking efficiency coefficient function model is taken as the objective function, and the optimized microwave parameters and cutter rock breaking parameters are obtained.

[0036] The application provides a microwave-assisted tunneling rock breaking parameter optimization method, which has a significant technical effect. By measuring the confining pressure value of the corresponding layer rock (step S1), combining the microwave pretreatment test (step S2) and rock thermal damage factor analysis (step S3), the change of the microwave to the rock physical properties can be accurately evaluated. Further, by carrying out a cutter rock breaking test (step S4) on the microwave pretreated rock and untreated rock, and synchronously collecting key data such as cutter vertical force, cutter rolling force and total volume of broken rock debris, the influence of microwave pretreatment on the cutter rock breaking effect can be quantified. The application calculates the microwave rock breaking energy consumption reduction coefficient and the microwave rock breaking fragmentation gain coefficient (step S5), and establishes a microwave-assisted cutter rock breaking benefit coefficient function model (step S6), so as to realize the scientific and quantitative matching between the microwave parameters and the cutter rock breaking parameters. Finally, taking the benefit coefficient function model as the objective function, the optimized microwave parameters and cutter rock breaking parameters are obtained (step S7), thereby solving the problem of lacking quantitative decision basis for parameter matching in the prior art. By using the method of the application, the tunneling efficiency can be significantly improved, the cutter wear can be reduced, the service life of the equipment can be prolonged, the waste of microwave energy can be reduced, and the safety and economy of the construction process can be improved. In addition, by optimizing the parameter matching, the construction cost can be effectively reduced, the tunnel construction period can be shortened, and strong technical support can be provided for tunnel engineering construction under complex geological conditions. Different types of rocks can obtain optimized microwave parameters and cutter rock breaking parameters through the above method. Different types of rocks refer to rocks with different confining pressure values and physical and mechanical parameters. Of course, after many tests, the same type of rock encountered subsequently can use the microwave-assisted cutter rock breaking benefit coefficient function model obtained previously. In some embodiments, in order to reduce the number of tests, rocks with confining pressure values and various physical and mechanical parameters in the same preset range are classified as the same type of rock, for example, the confining pressure values of two rocks are in the same preset range, and the rock compressive strengths of the two rocks are also in the same preset range, so the rocks can be considered as the same type of rock; the same type of rock can use the same microwave-assisted cutter rock breaking benefit coefficient function model, so that rocks with similar physical and mechanical parameters do not have to repeat the test to obtain the microwave-assisted cutter rock breaking benefit coefficient function model. c The confining pressure value σ

[0037] Step S3 specifically includes steps S31 and S32.

[0038] S31, the rock temperature rise coefficient α1 and the microwave radiation rock porosity gain rate α2 are calculated by the following formula:

[0039] α1=μ1fε0E0 2 t m ;

[0040] S32, the rock thermal damage factor α under microwave radiation is calculated by the following formula:

[0041] α = ε1α1α2.

[0042] Wherein α1 is the temperature rise coefficient of the rock under microwave radiation, μ1 is the thermal expansion coefficient of the rock, f is the microwave irradiation frequency, ε0 is the dielectric constant of the rock, E0 is the microwave electric field intensity, t m is the microwave irradiation time; α2 is the porosity gain rate of the rock under microwave radiation, φ micro is the pore size of the rock after microwave treatment, φ T is the pore size of the rock without microwave treatment; α is the rock thermal damage factor, and ε1 is the proportional coefficient. The influence of microwave on rock expansion and porosity increase is obtained by the above formula, so as to obtain the rock thermal damage factor under microwave radiation, to reflect the damage of the rock under microwave radiation, and the difficulty of cutter rock breaking is reduced by the damage of the rock.

[0043] Referring to Figure 2 , step S5 specifically comprises:

[0044] S51, obtaining the dynamic rock breaking specific energy S w and the rock fractal dimension D w of the rock after microwave pretreatment in step S2.

[0045] S52, obtaining the dynamic rock breaking specific energy S0 and the rock fractal dimension D0 of the control group rock without microwave treatment.

[0046] S53, calculating the microwave rock breaking energy consumption reduction coefficient K1 and the microwave rock breaking fragmentation degree gain coefficient K2.

[0047] The microwave rock breaking energy consumption reduction coefficient K1 is calculated by the following formula:

[0048]

[0049] The microwave rock breaking fragmentation degree gain coefficient K2 is calculated by the following formula:

[0050]

[0051] The microwave auxiliary cutter rock breaking benefit coefficient function model is K = α·K1·K2. Through the above formula, the influence of microwave on the energy consumption reduction of rock breaking and the influence on the rock fragmentation degree are obtained, and the influences are positive influences, which are used to evaluate the auxiliary gain evaluation of the microwave on the reduction of the cutter rock breaking ability.

[0052] The dynamic rock breaking specific energy S w and the rock fractal dimension Dw The dynamic rock breaking specific energy S of the rock pre-treated by microwaves is obtained by the following formula:

[0053]

[0054] S w F is the vertical force of the rolling cutter of the microwave pre-treatment group, F n1 F is the vertical force of the rolling cutter of the microwave pre-treatment group, F t1 v is the rolling force of the rolling cutter of the microwave pre-treatment group, v p1 v is the penetration speed of the rolling cutter of the microwave pre-treatment group, v c1 V is the cutting speed of the rolling cutter of the microwave pre-treatment group, V w1 D is the total volume of the rock debris broken by the microwave pre-treatment group; D w C1 is the correction coefficient of the fractal dimension of the rock of the microwave pre-treatment group, N1 is the number of debris in the preset particle size interval of the microwave pre-treatment group, N1 is the total number of debris particles in the preset particle size interval in the test of the statistical step S4 of the microwave pre-treatment group, which is the total number of particles here, which can be obtained by counting the particle size of the debris generated in step S4 test, and the preset particle size interval can be set according to the actual situation, such as setting the preset particle size interval to 1-2mm.d maxw1 / d minw1 d is the particle size ratio of the debris of the microwave pre-treatment group, d maxw1 d is the maximum particle size of the debris of the microwave pre-treatment group, d minw1 d is the minimum particle size of the debris of the microwave pre-treatment group, d maxw1 and d minw1 are in the preset particle size interval. Through the above formula, the dynamic rock breaking and the fractal dimension of the rock after microwave pre-treatment are obtained, thereby providing a calculation basis for the microwave rock breaking energy consumption reduction coefficient K1 and the microwave rock breaking fragmentation gain coefficient K2.

[0055] The dynamic rock breaking specific energy S0 of the control group of rocks without microwave treatment and the fractal dimension D0 of the rock are obtained by the following formula:

[0056]

[0057] F n0 F is the vertical force of the rolling cutter of the microwave pre-treatment group, F t0 v is the rolling force of the rolling cutter of the microwave pre-treatment group, v p0 v is the penetration speed of the rolling cutter of the microwave pre-treatment group, v c0 V is the cutting speed of the rolling cutter of the microwave pre-treatment group, V w0D0 is the fractal dimension of the rock in the non-microwave pretreatment group, C0 is the correction coefficient of the fractal dimension of the rock in the non-microwave pretreatment group, N0 is the number of the debris in the preset particle size interval in the non-microwave treatment control group, and N0 is the total number of the debris particles in the preset particle size interval in the non-microwave pretreatment group in the test of the statistical step S4. The particle size of the debris generated in the step S4 test can be counted and obtained.

[0058] d maxw0 / d minw0 D is the ratio of the particle size of the debris in the non-microwave treatment control group, d maxw0 D is the maximum particle size of the debris in the non-microwave treatment control group, d minw0 D is the minimum particle size of the debris in the non-microwave treatment control group, and t is time. maxw0 And d minw0 are in the preset particle size interval.

[0059] The microwave parameters at least include microwave electric field intensity E0, microwave irradiation time t m , and microwave frequency f; the geological parameters at least include confining pressure value s c ; and the cutter parameters at least include penetration speed and cutting speed.

[0060] The step S7 specifically includes:

[0061] S71, taking the microwave-assisted cutter rock breaking efficiency coefficient function model as the objective function, taking the geological parameters (confining pressure value s c and the physical and mechanical parameters of the rock itself), the microwave parameters, and the cutter parameters as the decision variables, and setting the value range of each variable.

[0062] S72, obtaining the corresponding optimized microwave parameters and cutter parameters through an optimization algorithm.

[0063] Specifically, the optimization algorithm is a multi-objective genetic initialization algorithm, which specifically includes:

[0064] A multi-objective genetic initialization algorithm is written, the coding scheme is determined, each decision variable is converted into a gene string, and a population initialization strategy is set. According to different objectives, a fitness function is designed, and the trade-off between multiple objectives is considered. The fitness evaluation and non-dominated sorting of the microwave-assisted cutter rock breaking efficiency coefficient K are performed, and a geological parameter self-adaptive mechanism is written to optimize the algorithm iteration. Based on the initial parameters such as the confining pressure value s c in the geological report, and through iterative optimization, the parameter matching effect is gradually improved, the specific value range of the decision variables such as the microwave parameters and the cutter parameters under the related geological conditions is obtained, and the global optimal solution set of the microwave-assisted cutter rock breaking efficiency coefficient K is output, which provides a reference for the microwave-assisted cutter rock breaking parameter matching decision.

[0065] Of course the optimization algorithm can also be a particle swarm optimization algorithm, simulated annealing algorithm, differential evolution algorithm, and of course a hybrid optimization algorithm can be used, combining various optimization algorithms to give full play to their respective advantages to improve the optimization effect. For example, genetic algorithm and simulated annealing algorithm can be combined, first using genetic algorithm for global search, and then using simulated annealing algorithm for local search.

[0066] The application also provides a tunneling method, which uses the optimized microwave parameters and the cutter rock breaking parameters obtained by the microwave-assisted tunneling rock breaking parameter optimization method to perform tunneling construction.

[0067] The application also provides a tunneling microwave-assisted cutter rock breaking parameter optimization system for performing the microwave-assisted tunneling rock breaking parameter optimization method, which comprises a measuring module for measuring the surrounding pressure value σ c and obtaining the physical and mechanical parameters of the rock; a microwave test data collection module for using a microwave radiation device to pre-treat the rock; an analysis module for analyzing the rock sample after microwave treatment and obtaining the thermal damage factor of the rock; a collection module for performing cutter rock breaking tests on the rock pre-treated in step S2 and the control group rock without microwave treatment, and synchronously collecting the cutter vertical force, cutter rolling force and total volume of broken rock chips in the test; a coefficient obtaining module for obtaining the microwave rock breaking energy consumption reduction coefficient and the microwave rock breaking fragmentation gain coefficient; a function model establishing module for establishing a microwave-assisted cutter rock breaking benefit coefficient function model; and a parameter optimization module for taking the microwave-assisted cutter rock breaking benefit coefficient function model as the objective function to obtain the optimized microwave parameters and cutter rock breaking parameters.

[0068] The application also provides a tunnel boring machine comprising a device for implementing the tunneling method.

[0069] The above is only a preferred embodiment of the application and is not used to limit the application. For those skilled in the art, the application can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the application shall be included in the protection scope of the application.

Claims

1. A method for optimizing parameters of rock breaking by microwave-assisted tunneling, characterized in that, The method comprises the following steps: S1, measure the confining pressure value σ of the corresponding layer position rock c and obtain the physical and mechanical parameters of the rock; S2, microwave pretreatment of the rock is performed by using a microwave radiation device; S3, analysis is performed on the rock sample after the step S2 treatment, and a rock thermal damage factor is obtained; S4, the rock pretreated in step S2 and the control group rock without microwave treatment are subjected to a rock breaking test by a rolling cutter, and the rock is subjected to the confining pressure σ determined in step S1 in the test c and the rolling cutter rock breaking parameters are controlled, and the vertical force of the rolling cutter, the rolling force of the rolling cutter and the total volume of the broken rock debris in the test are synchronously collected. S5, a microwave rock breaking energy consumption reduction coefficient and a microwave rock breaking fragmentation gain coefficient are obtained; S6, a microwave auxiliary cutter rock breaking benefit coefficient function model is established; S7, the microwave auxiliary cutter rock breaking benefit coefficient function model is taken as a target function, and optimized microwave parameters and cutter rock breaking parameters are obtained.

2. The method of claim 1, wherein, The step S3 specifically comprises: S31, the rock temperature rise coefficient a1 and the rock porosity gain rate a2 under microwave radiation are calculated by the following formula: a1 = μ1fε0E0 2 t m ; S32, the rock thermal damage factor a under microwave radiation is calculated by the following formula: a = e1a1a2. wherein a1 is the temperature rise coefficient of rock under microwave irradiation, μ1 is the thermal expansion coefficient of rock, f is the microwave irradiation frequency, ε0 is the dielectric constant of rock, E0 is the microwave electric field intensity, t m is the microwave irradiation time; a2 is the porosity gain rate of rock under microwave irradiation, φ micro is the pore size of rock after microwave treatment, φ T is the pore size of rock without microwave treatment; a is the thermal damage factor of rock, ε1 is the proportional coefficient.

3. The method of claim 1, wherein, The step S5 specifically comprises: S51, obtaining the dynamic rock breaking specific energy S of the rock after the microwave pretreatment in step S2 w , fractal dimension D of the rock w ; S52, the dynamic rock breaking specific energy S0 of the control group rock without microwave treatment and the rock fractal dimension D0 are obtained; S53, a microwave rock breaking energy consumption reduction coefficient K1 and a microwave rock breaking fragmentation gain coefficient K2 are calculated.

4. The method of claim 3, wherein, The microwave rock breaking energy consumption reduction coefficient K1 is calculated by the following formula: The microwave rock breaking fragmentation gain coefficient K2 is calculated by the following formula: The microwave auxiliary cutter rock breaking benefit coefficient function model is K = aK1K2.

5. The method of claim 3, wherein, The dynamic rock breaking specific energy S of the rock after the microwave pretreatment w The rock fractal dimension D w is obtained by the following formula: S w The specific energy of the rolling cutter for cutting the microwave pretreated rock, F n1 The vertical force of the rolling cutter for the microwave pretreatment group, F t1 The rolling force of the rolling cutter for the microwave pretreatment group, v p1 The penetration speed of the rolling cutter for the microwave pretreatment group, v c1 The cutting speed of the rolling cutter for the microwave pretreatment group, V w1 The total volume of the rock debris for the microwave pretreatment group; D w The fractal dimension of the rock for the microwave pretreatment group, C1 is the correction coefficient of the fractal dimension of the rock for the microwave pretreatment group, N1 is the number of debris in the preset particle size interval of the microwave pretreatment group, d maxw1 / d minw1 The particle size ratio of the debris for the microwave pretreatment group.

6. The method of claim 1, wherein, The microwave parameters at least include microwave electric field intensity E0, microwave irradiation time t m , microwave frequency f; the geological parameters at least include confining pressure value σ c ; the roller cutter parameters at least include penetration speed and cutting speed.

7. The method of claim 1, wherein, The step S7 specifically comprises: S71, the microwave auxiliary cutter rock breaking benefit coefficient function model is taken as a target function, the geological parameters, the microwave parameters and the cutter parameters are taken as decision variables, and the value ranges of the variables are set; S72, the corresponding optimized microwave parameters and cutter rock breaking parameters are obtained by an optimization algorithm.

8. A method of tunneling, characterized by, The optimized microwave parameters and cutter rock breaking parameters obtained by the microwave auxiliary tunneling rock breaking parameter optimization method according to any one of claims 1 to 7 are used for tunneling construction.

9. A system for optimizing parameters of microwave-assisted rock breaking for tunneling with a rolling cutter, for performing the method of optimizing parameters of microwave-assisted rock breaking for tunneling according to any one of claims 1 to 7, characterized in that, It comprises: A measuring module is arranged to measure the confining pressure value σ of the rock at the corresponding horizon c and obtain the physical and mechanical parameters of the rock. a microwave test data collection module, which is used for microwave pretreatment of the rock by using a microwave radiation device; an analysis module, which is used for analysis on the rock sample after the microwave treatment, and obtaining a rock thermal damage factor; a collection module, which is used for cutter rock breaking tests on the rock pretreated in the step S2 and the control group rock without microwave treatment, and simultaneously collecting the cutter vertical force, the cutter rolling force and the total volume of broken rock debris in the tests; a coefficient obtaining module, which is used for obtaining a microwave rock breaking energy consumption reduction coefficient and a microwave rock breaking fragmentation gain coefficient; a function model establishing module, which is used for establishing a microwave auxiliary cutter rock breaking benefit coefficient function model; a parameter optimization module, which is used for taking the microwave auxiliary cutter rock breaking benefit coefficient function model as a target function, and obtaining optimized microwave parameters and cutter rock breaking parameters.

10. A tunnel boring machine characterized by, The tunneling method according to claim 8 is used for implementation.

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