Tunnel boring machine hob service life prediction method suitable for supergravity environment

Abstract

The invention discloses a tunnel boring machine hob service life prediction method suitable for a supergravity environment, and the method comprises the steps: firstly constructing a supergravity centrifugal experiment platform which comprises a supergravity rock-soil centrifugal machine and a model box disposed in a hanging basket of the supergravity rock-soil centrifugal machine, and the model box is internally provided with a rock-soil geological layer, a hydraulic servo system and a hob model; the hydraulic servo system is arranged in a rock-soil geological layer, the hob model is connected to the front end of the hydraulic servo system, and a data acquisition module in wireless communication connection with an external controller is arranged on the hob model; then, a hob service life prediction model is constructed, the hob service life prediction model comprises a wear prediction module and a service life prediction module, the wear prediction module is used for predicting the hob wear amount at the current moment, and the service life prediction module is used for predicting the hob remaining service life at the current moment. According to the hob service life prediction model constructed by the invention, coupling of the wear life and the fatigue life is carried out, the comprehensive damage of the hob is quantified, and the prediction precision and applicability are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of tunnel boring machines, in particular to a method for predicting the life of a cutter wheel for a tunnel boring machine suitable for a hypergravity environment. Background Art

[0002] Disc cutters are important cutting tools for full-face tunnel boring machines (TBMs) to crush hard rock and are widely used in geotechnical excavation for underground projects such as subways, railway tunnels, and water conservancy projects. The cutters directly bear high-intensity impact, abrasion, and cyclic loads by rotating and cutting the rock mass. Their lifespan directly affects the construction efficiency and cost of the TBM. The main forms of damage to the cutters include radial wear, cutter ring cracking, and material fatigue cracks, among which radial wear is the core indicator for life prediction. Due to the complex excavation environment (including hard rock, soft rock, mixed strata, groundwater, etc.), the prediction of cutter life requires comprehensive consideration of geological conditions, operating parameters, and material properties. Existing technologies mainly predict cutter life through experimental testing, numerical simulation, or empirical formulas, but the accuracy and adaptability are limited, especially under complex geological conditions.

[0003] In existing technologies, the life prediction of disc cutters mainly relies on the calculation of the radial wear coefficient and the estimation based on the operating parameters of the tunnel boring machine. However, existing methods have the following technical problems:

[0004] 1. Dynamic changes in geological conditions are not fully considered: Existing life prediction models are usually based on static or simplified geological parameters and cannot accurately reflect the impact of complex and changeable geological conditions (such as rock hardness, fault zones, groundwater seepage, etc.) on cutter wear during actual excavation.

[0005] 2. Ignoring material fatigue damage: Existing methods mainly focus on wear and fail to effectively quantify the fatigue damage of hob materials under high loads and cyclic stresses, resulting in life predictions that deviate from reality.

[0006] 3. Insufficient real-time data collection: Existing technologies lack the means to monitor the wear and stress of the hob in a hypergravity environment in real time, making it difficult to dynamically adjust the prediction model.

[0007] 4. Poor model adaptability: The existing radial wear coefficient model has poor adaptability to different types of hobs (such as single-edge, double-edge) or different sizes, and the prediction accuracy decreases as the hob structure changes. Summary of the Invention

[0008] The technical problem to be solved by the present invention is to provide a method for predicting the life of a roller cutter for a tunnel boring machine suitable for a hypergravity environment, construct a roller cutter life prediction model, couple the wear life and fatigue life, quantify the comprehensive damage of the roller cutter, and improve the prediction accuracy and applicability.

[0009] The technical solution of the present invention is:

[0010] A method for predicting the life of a cutter disc for a tunnel boring machine suitable for a hypergravity environment comprises the following steps:

[0011] (1) Constructing an ultra-gravity centrifuge experimental platform, comprising an ultra-gravity geotechnical centrifuge and a model box arranged in a hanging basket of the ultra-gravity geotechnical centrifuge, wherein a geotechnical stratum, a hydraulic servo system and a roller cutter model are arranged in the model box, wherein the hydraulic servo system is arranged in the geotechnical stratum and is used to simulate a tunnel boring machine, and the roller cutter model is connected to the front end of the hydraulic servo system and simulates the excavation operation of the geotechnical stratum under the drive of the hydraulic servo system, wherein the roller cutter model comprises a cutter disc and roller cutters arranged radially on the cutter disc, and a data acquisition module connected to an external controller by wireless communication is provided on the roller cutter model, wherein the data acquisition module comprises a laser wear sensor for collecting the wear amount of the roller cutter ring, a stress sensor for collecting the stress on the roller cutter, a temperature sensor for collecting the temperature of the roller cutter and a three-axis accelerometer for collecting the vibration frequency of the roller cutter;

[0012] (2) Construct a hob life prediction model. The hob life prediction model includes a wear prediction module and a life prediction module. The wear prediction module is used to predict the hob wear amount at the current moment. The life prediction module is used to predict the wear life and fatigue life at the current moment based on the hob wear amount at the current moment, and select the minimum value from the wear life and fatigue life as the remaining life of the hob at the current moment.

[0013] The inner wall of the model box is provided with a polytetrafluoroethylene layer. The rock and soil geological layer includes granite, sandstone particles, clay and water. The water content of the rock and soil geological layer is 10-20%.

[0014] The bottom of the model box is provided with a discharge port connected to the rock and soil geological layer, and the top of the model box is provided with a feed port, and the density and composition of the rock and soil geological layer can be adjusted through the discharge port and the feed port.

[0015] The laser wear sensor is arranged on the cutter disc and located on the outer periphery of the hob ring, and uses laser ranging technology to measure the wear of the hob ring; the stress sensor is a strain gauge arranged on the inner ring of the hob, and the inner ring of the hob is fixedly connected to the drive shaft, and the hob is driven to rotate by the drive shaft; the temperature sensor is arranged on the surface of the hob; the three-axis accelerometer is arranged on the hob holder of the cutter disc, and the hob is connected to the hob holder when it rotates.

[0016] The processing process of the wear prediction module is specifically shown in the following formula (1):

[0017]

[0018] In formula (1), Wt Represents the wear prediction at the current time t;

[0019] W t-1 Represents the wear prediction at the previous moment t-1;

[0020] k t Represents the wear coefficient at the current time t, k t =k0+0.001a t +d1, k0 represents the initial wear coefficient, d1 represents the damage effect of the hypergravity environment on the hob model after one iteration, and the value is 0.00001, a t represents the crack length at the current time t;

[0021] F t Represents the thrust value provided by the hydraulic servo system;

[0022] S t Represents the sliding distance, k3 represents the influence coefficient of the hypergravity environment on the sliding distance of the hob model, and its value is 1.12-1.18. D represents the diameter of the hob model, N t represents the rotation speed of the hob model, which is determined by the hydraulic servo system, and Δt represents the time step of the model iteration;

[0023] H t Represents the hardness of the hob cutter ring, H t =K1H0·exp(-0.1·a t ), K1 represents the attenuation coefficient of the hob cutter ring hardness under hypergravity environment, with a value of 0.98-0.99, and H0 represents the initial hardness of the hob cutter ring.

[0024] a t represents the crack length at the current time t;

[0025] E a Represents activation energy, characterizing the effect of temperature on wear, E a =50kJ / mol;

[0026] R represents the gas constant, R = 8.314 J / (mol×K);

[0027] k1 represents the influence coefficient of temperature in hypergravity environment, and its value is 1.06;

[0028] T t Represents the temperature of the hob cutter ring in K, measured by the temperature sensor;

[0029] k2 represents the influence coefficient of hob wear in hypergravity environment, and its value is 1.08-1.16.

[0030] The crack length a t Calculated by the following formula (2):

[0031] a t =k4[a t-1 +C·(ΔK t ) m ·ΔN] (2);

[0032] In formula (2), a t represents the crack length at the current time t;

[0033] a t-1 Represents the crack length at the previous moment t-1;

[0034] C = 2.5 × 10 -1 , is the state constant, the material of the hob is H13 high-strength alloy steel, based on the fatigue characteristics of the hob material H13 steel;

[0035] ΔK t represents the stress intensity factor amplitude, σ t Represents the stress value of the hob measured by the stress sensor, Y(W t ) is the geometric correction factor, D is the diameter of the hob;

[0036] m = 3.0, which is dimensionless and represents the nonlinearity of crack growth;

[0037] ΔN represents the number of iterations of the model, ΔN = f t Δt, f t represents the vibration frequency of the hob measured by the triaxial accelerometer, and Δt represents the time step of the model iteration;

[0038] k4 represents the influence coefficient of the hypergravity environment on the surface cracks of the hob cutter ring, and its value is 1.04-1.08.

[0039] The initial wear coefficient k0 is calibrated based on the actual wear value collected by the laser wear sensor. The specific calibration steps are as follows:

[0040] a. Data collection at the initial stage of the experiment: On the ultra-gravity centrifuge experimental platform, a laser wear sensor was used to measure the actual wear value of the hob cutter ring at the initial stage of the experiment.

[0041] b. Calculation of initial wear coefficient: Let W t-1 =0,H t =H0,T t =T0, T0 represents the initial temperature of the hob cutter ring, and the wear prediction value W at the initial stage of the experiment is calculated by formula (1): t ;

[0042] c. Adjustment of wear coefficient: First calculate the actual wear value and wear prediction value W t The difference between When the error ρ is greater than the set maximum error, the initial wear coefficient is optimized by minimizing the error. The optimization formula is: The initial setting k0=0.005, when the error ρ is not greater than the set maximum error, the initial wear coefficient is not optimized;

[0043] d. Repeat the above steps ac under different geological conditions and working conditions on the gravity centrifuge experimental platform to collect multiple groups of Calculate and update the corresponding k0, and finally take the average or weighted average as the final initial wear coefficient.

[0044] The prediction process of the wear life at the current moment is shown in the following formula (3):

[0045]

[0046] In formula (3), L w Represents the wear life at the current moment;

[0047] W max =5mm, representing the maximum allowable wear;

[0048] W t Represents the wear prediction at the current time t;

[0049] R w represents the wear rate, Δt=60s.

[0050] A w Represents the damage safety factor, with a value of 0.7-0.8.

[0051] The fatigue life prediction process at the current moment is shown in the following formula (4):

[0052]

[0053] In formula (4), L f Represents the fatigue life at the current moment;

[0054] a t represents the crack length at the current time t;

[0055] a c =2mm, represents the critical crack length of the hob, based on the fracture toughness of the hob material H13 steel;

[0056] represents the crack growth rate, C = 2.5 × 10 -1 , is the state constant, based on the fatigue characteristics of the hob material H13 steel, ΔK t represents the stress intensity factor amplitude, m = 3.0;

[0057] f t represents the hob vibration frequency measured by the triaxial accelerometer;

[0058] A f Represents the fatigue safety factor, with a value of 0.6-0.7.

[0059] The minimum value between the wear life and the fatigue life is selected as the remaining life of the hob at the current moment, as shown in the following formula (5):

[0060] L d =min(L w ,L f ) (5);

[0061] In formula (5), L d Represents the remaining life of the hob at the current moment.

[0062] Advantages of the present invention:

[0063] The cutter life prediction model constructed by the present invention quantifies the dynamic interaction between wear (radial wear) and fatigue (crack propagation) of the cutter during excavation in a hypergravity environment through an iterative algorithm, and comprehensively considers the effects of temperature, stress concentration and material degradation on damage. The model outputs the damage life of the cutter based on the data (stress, temperature, vibration frequency) collected in real time by various sensors of the data acquisition module, the operating data (thrust, speed) of the hydraulic servo system, geological parameters (CAI) and material parameters, greatly improving the accuracy and applicability of the prediction. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 It is a structural schematic diagram of the model box of the present invention.

[0065] Figure 2 It is a structural schematic diagram of the hob model of the present invention.

[0066] Figure 3 Flowchart of one-time iterative optimization of the hob life prediction model of the present invention.

[0067] Figure numerals: 11 - model box, 12 - rock and soil geological layer, 13 - hydraulic servo system, 14 - hob model, 15 - discharge port, 16 - feed port, 41 - cutterhead, 42 - hob, 43 - laser wear sensor, 44 - stress sensor, 45 - temperature sensor, 46 - three-axis accelerometer. DETAILED DESCRIPTION

[0068] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0069] A method for predicting the life of a cutter disc for a tunnel boring machine suitable for a hypergravity environment comprises the following steps:

[0070] (1) Construct a high-gravity centrifuge experimental platform, including a high-gravity geotechnical centrifuge and a model box (made of stainless steel) arranged in the hanging basket of the high-gravity geotechnical centrifuge;

[0071] See Figure 1 The inner wall of the model box 11 is provided with a polytetrafluoroethylene layer to reduce friction. A rock and soil geological layer 12, a hydraulic servo system 13 and a hob model 14 are provided in the model box 11. The rock and soil geological layer 12 includes granite, sandstone particles (particle size 0.5-2mm), clay (plasticity index 15-20) and water. The moisture content of the rock and soil geological layer 12 is 10-20%. The hydraulic servo system 13 is provided in the rock and soil geological layer 12, providing a maximum thrust of 100kN and a torque of 500N·m. It is equipped with a high-precision encoder (resolution 0.01°) for simulating A tunnel boring machine (thrust 50 kN, rotation speed 10 rpm) is controlled in a closed loop by a programmable logic controller (PLC). A roller cutter model 14 is connected to the front end of a hydraulic servo system 13. Driven by the hydraulic servo system 13, the roller cutter model 14 simulates the tunneling operation of a rock and soil geological layer 11. A discharge port 15 is provided at the bottom of the model box 11, communicating with the rock and soil geological layer 12. Two feed ports 16 are provided at the top of the model box 11. The two feed ports 16 are respectively loaded with sand particles of different grades. The density and composition of the rock and soil geological layer 12 are adjusted through the discharge port 15 and the two feed ports 16.

[0072] See Figure 2The cutter model 14 includes a cutter head 41 and cutters 42 arranged radially on the cutter head 41. The volume ratio of the cutter model 14 to the cutter used in the tunnel boring machine is 1:50. The cutter 42 is made of H13 high-strength alloy steel (hardness HRC 58-62, yield strength 1400-1500MPa), the hob cutter ring has a diameter of 8.6mm and a thickness of 2mm, a single-edge design, and a 0.5mm wear-resistant coating on the surface. The hob cutter model is provided with a data acquisition module that is wirelessly connected to an external controller. The data acquisition module includes a laser wear sensor 43, a stress sensor 44, a temperature sensor 45, and a three-axis accelerometer 46. The laser wear sensor 43 is provided on the cutter head 41 and is located on the outer periphery of the cutter ring of the hob cutter 42. It uses laser ranging technology to measure the wear of the hob cutter ring; the stress sensor 44 is a strain gauge provided on the inner ring of the hob cutter. The inner ring of the hob cutter is fixedly connected to the drive shaft, and the hob cutter is driven to rotate by the drive shaft; the temperature sensor 45 is a thermocouple and is provided on the surface of the hob cutter 42; the three-axis accelerometer 46 is provided on the hob cutter holder of the cutter head 41. The hob cutter 42 is rotatably connected to the hob cutter holder;

[0073] (2) See Figure 3 , constructing a hob life prediction model, the hob life prediction model includes a wear prediction module and a life prediction module, the wear prediction module is used to predict the hob wear amount at the current moment t, the life prediction module is used to predict the wear life and fatigue life at the current moment based on the hob wear amount at the current moment t, and select the minimum value from the wear life and fatigue life as the remaining life of the hob at the current moment;

[0074] S11, the processing process of the wear prediction module is specifically shown in the following formula (1):

[0075]

[0076] In formula (1), W t Represents the wear prediction at the current time t;

[0077] W t-1 Represents the wear prediction at the previous moment t-1;

[0078] k t Represents the wear coefficient at the current time t, k t =k0+0.001a t +d1, k0 represents the initial wear coefficient, d1 represents the damage effect of the hypergravity environment on the hob model after one iteration, and the value is 0.00001, a t represents the crack length at the current time t;

[0079] F t Represents the thrust value provided by the hydraulic servo system;

[0080] S t Represents the sliding distance, k3 represents the influence coefficient of the hypergravity environment on the sliding distance of the hob model, and its value is 1.12-1.18. D represents the diameter of the hob model, N t represents the rotation speed of the hob model, which is measured by a precision encoder on the hydraulic servo system and installed on the motor shaft of the hydraulic servo system. Δt represents the time step of the model iteration, Δt = 60 seconds;

[0081] H t Represents the hardness of the hob cutter ring, H t =K1H0·exp(-0.1·a t ), K1 represents the attenuation coefficient of the hob cutter ring hardness under hypergravity environment, with a value of 0.98-0.99, and H0 represents the initial hardness of the hob cutter ring.

[0082] a t represents the crack length at the current time t;

[0083] E a Represents activation energy, characterizing the effect of temperature on wear, E a =50kJ / mol;

[0084] R represents the gas constant, R = 8.314 J / (mol×K);

[0085] k1 represents the influence coefficient of temperature in hypergravity environment, and its value is 1.06;

[0086] T t Represents the temperature of the hob cutter ring in K, measured by the temperature sensor;

[0087] k2 represents the influence coefficient of hob wear in hypergravity environment, and its value is 1.08-1.16;

[0088] Among them, the crack length a t Calculated by the following formula (2):

[0089] a t =k4[a t-1 +C·(ΔK t ) m ·ΔN] (2);

[0090] In formula (2), a t represents the crack length at the current time t;

[0091] a t-1 Represents the crack length at the previous moment t-1;

[0092] C = 2.5 × 10 -11, is the state constant, based on the fatigue characteristics of the hob material H13 steel;

[0093] ΔK t represents the stress intensity factor amplitude, σ t Represents the stress value of the hob measured by the stress sensor, Y(W t ) is the geometric correction factor, D is the diameter of the hob;

[0094] m = 3.0, which is dimensionless and represents the nonlinearity of crack growth;

[0095] ΔN represents the number of iterations of the model, ΔN = f t Δt, f t represents the vibration frequency of the hob measured by the triaxial accelerometer, Δt represents the time step of the model iteration, Δt = 60 seconds;

[0096] k4 represents the influence coefficient of hypergravity environment on the surface cracks of the hob cutter ring, and its value is 1.04-1.08;

[0097] The initial wear coefficient k0 is calibrated based on the actual wear value collected by the laser wear sensor. The specific calibration steps are as follows:

[0098] a. Data collection at the initial stage of the experiment: On the ultra-gravity centrifuge experimental platform, a laser wear sensor was used to measure the actual wear value of the hob cutter ring at the initial stage of the experiment.

[0099] b. Calculation of initial wear coefficient: Let W t-1 =0,H t =H0,T t =T0, T0 represents the initial temperature of the hob cutter ring, and the wear prediction value W at the initial stage of the experiment is calculated by formula (1): t ;

[0100] c. Adjustment of wear coefficient: First calculate the actual wear value and wear prediction value W t The difference between When the error ρ is greater than the set maximum error, the initial wear coefficient is optimized by minimizing the error. The optimization formula is: The initial setting k0=0.005, when the error ρ is not greater than the set maximum error, the initial wear coefficient is not optimized;

[0101] d. Repeat the above steps ac under different geological conditions and working conditions on the gravity centrifuge experimental platform to collect multiple groups of Calculate and update the corresponding k0, and finally take the average or weighted average as the final initial wear coefficient;

[0102] S12. The prediction process of wear life at the current moment is shown in the following formula (3):

[0103]

[0104] In formula (3), L w Represents the wear life at the current moment;

[0105] W max =5mm, representing the maximum allowable wear;

[0106] W t Represents the wear prediction at the current time t;

[0107] R w represents the wear rate, Δt=60s.

[0108] A w represents the damage safety factor, with a value of 0.7-0.8;

[0109] S13. The prediction process of fatigue life at the current moment is shown in the following formula (4):

[0110]

[0111] In formula (4), L f Represents the fatigue life at the current moment;

[0112] a t represents the crack length at the current time t;

[0113] a c =2mm, represents the critical crack length of the hob, based on the fracture toughness of the hob material H13 steel;

[0114] represents the crack growth rate, C = 2.5 × 10 -1 , is the state constant, based on the fatigue characteristics of the hob material H13 steel, Δk t represents the stress intensity factor amplitude, m = 3.0;

[0115] f t represents the hob vibration frequency measured by the triaxial accelerometer;

[0116] A f represents the fatigue safety factor, with a value of 0.6-0.7;

[0117] S14. Select the minimum value from the wear life and fatigue life as the remaining life of the hob at the current moment, as shown in the following formula (5):

[0118] L d =min(L w ,L f ) (5);

[0119] In formula (5), L d Represents the remaining life of the hob at the current moment.

[0120] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A method for predicting the life of a cutter disc for a tunnel boring machine suitable for use in a hypergravity environment, characterized by: The specific steps include: (1) Constructing an ultra-gravity centrifuge experimental platform, comprising an ultra-gravity geotechnical centrifuge and a model box arranged in a hanging basket of the ultra-gravity geotechnical centrifuge, wherein a geotechnical stratum, a hydraulic servo system and a roller cutter model are arranged in the model box, wherein the hydraulic servo system is arranged in the geotechnical stratum and is used to simulate a tunnel boring machine, and the roller cutter model is connected to the front end of the hydraulic servo system and simulates the excavation operation of the geotechnical stratum under the drive of the hydraulic servo system, wherein the roller cutter model comprises a cutter disc and roller cutters arranged radially on the cutter disc, and a data acquisition module connected to an external controller by wireless communication is provided on the roller cutter model, wherein the data acquisition module comprises a laser wear sensor for collecting the wear amount of the roller cutter ring, a stress sensor for collecting the stress on the roller cutter, a temperature sensor for collecting the temperature of the roller cutter and a three-axis accelerometer for collecting the vibration frequency of the roller cutter; (2) Construct a hob life prediction model. The hob life prediction model includes a wear prediction module and a life prediction module. The wear prediction module is used to predict the hob wear amount at the current moment. The life prediction module is used to predict the wear life and fatigue life at the current moment based on the hob wear amount at the current moment, and select the minimum value from the wear life and fatigue life as the remaining life of the hob at the current moment.

2. The method for predicting the life of a cutter disc for a tunnel boring machine suitable for a hypergravity environment according to claim 1, wherein: The inner wall of the model box is provided with a polytetrafluoroethylene layer. The rock and soil geological layer includes granite, sandstone particles, clay and water. The water content of the rock and soil geological layer is 10-20%.

3. The method for predicting the life of a cutter disc for a tunnel boring machine suitable for a hypergravity environment according to claim 2, wherein: The bottom of the model box is provided with a discharge port connected to the rock and soil geological layer, and the top of the model box is provided with a feed port, and the density and composition of the rock and soil geological layer can be adjusted through the discharge port and the feed port.

4. The method for predicting the life of a cutter disc for a tunnel boring machine suitable for a hypergravity environment according to claim 1, wherein: The laser wear sensor is arranged on the cutter disc and located on the outer periphery of the hob ring, and uses laser ranging technology to measure the wear of the hob ring; the stress sensor is a strain gauge arranged on the inner ring of the hob, and the inner ring of the hob is fixedly connected to the drive shaft, and the hob is driven to rotate by the drive shaft; the temperature sensor is arranged on the surface of the hob; the three-axis accelerometer is arranged on the hob holder of the cutter disc, and the hob is connected to the hob holder when it rotates.

5. The method for predicting the life of a cutter disc for a tunnel boring machine suitable for a hypergravity environment according to claim 1, wherein: The processing process of the wear prediction module is specifically shown in the following formula (1): In formula (1), W t Represents the wear prediction at the current time t; W t-1 Represents the wear prediction at the previous moment t-1; k t Represents the wear coefficient at the current time t, k t =k0+0.001a t +d1, k0 represents the initial wear coefficient, d1 represents the damage effect of the hypergravity environment on the hob model after one iteration, and the value is 0.00001, a t represents the crack length at the current time t; F t Represents the thrust value provided by the hydraulic servo system; S t Represents the sliding distance, k3 represents the influence coefficient of the hypergravity environment on the sliding distance of the hob model, and its value is 1.12-1.

18. D represents the diameter of the hob model, N t represents the rotation speed of the hob model, which is determined by the hydraulic servo system, and Δt represents the time step of the model iteration; H t Represents the hardness of the hob cutter ring, H t =K1H0·exp(-0.1·a t ), K1 represents the attenuation coefficient of the hob cutter ring hardness under hypergravity environment, with a value of 0.98-0.99, H0 represents the initial hardness of the hob cutter ring, a t represents the crack length at the current time t; E a Represents activation energy, characterizing the effect of temperature on wear, E a =50kJ / mol; R represents the gas constant, R = 8.314 J / (mol×K); k1 represents the influence coefficient of temperature in hypergravity environment, and its value is 1.06; T t Represents the temperature of the hob cutter ring in K, measured by the temperature sensor; k2 represents the influence coefficient of hob wear in hypergravity environment, and its value is 1.08-1.

16.

6. The method for predicting the life of a cutter disc for a tunnel boring machine suitable for a hypergravity environment according to claim 5, characterized in that: The crack length a t Calculated by the following formula (2): a t =k4[a t-1 +C·(ΔK t ) m ·ΔN] (2); In formula (2), a t represents the crack length at the current time t; a t-1 Represents the crack length at the previous moment t-1; C = 2.5 × 10 -1 , is the state constant, the material of the hob is H13 high-strength alloy steel, based on the fatigue characteristics of the hob material H13 steel; ΔK t represents the stress intensity factor amplitude, σ t Represents the stress value of the hob measured by the stress sensor, Y(W t ) is the geometric correction factor, D is the diameter of the hob; m = 3.0, which is dimensionless and represents the nonlinearity of crack growth; ΔN represents the number of iterations of the model, ΔN = f t Δt, f t represents the vibration frequency of the hob measured by the triaxial accelerometer, and Δt represents the time step of the model iteration; k4 represents the influence coefficient of the hypergravity environment on the surface cracks of the hob cutter ring, and its value is 1.04-1.

08.

7. The method for predicting the life of a cutter disc for a tunnel boring machine suitable for a hypergravity environment according to claim 5, characterized in that: The initial wear coefficient k0 is calibrated based on the actual wear value collected by the laser wear sensor. The specific calibration steps are as follows: a. Data collection at the initial stage of the experiment: On the ultra-gravity centrifuge experimental platform, a laser wear sensor was used to measure the actual wear value of the hob cutter ring at the initial stage of the experiment. b. Calculation of initial wear coefficient: Let W t-1 =0,H t =H0,T t =T0, T0 represents the initial temperature of the hob cutter ring, and the wear prediction value W at the initial stage of the experiment is calculated by formula (1): t ; c. Adjustment of wear coefficient: First calculate the actual wear value and wear prediction value W t The difference between When the error ρ is greater than the set maximum error, the initial wear coefficient is optimized by minimizing the error. The optimization formula is: The initial setting k0=0.005, when the error ρ is not greater than the set maximum error, the initial wear coefficient is not optimized; d. Repeat the above steps ac under different geological conditions and working conditions on the gravity centrifuge experimental platform to collect multiple groups of Calculate and update the corresponding k0, and finally take the average or weighted average as the final initial wear coefficient.

8. The method for predicting the life of a cutter disc for a tunnel boring machine suitable for a hypergravity environment according to claim 6, wherein: The prediction process of the wear life at the current moment is shown in the following formula (3): In formula (3), L w Represents the wear life at the current moment; W max =5mm, representing the maximum allowable wear; W t Represents the wear prediction at the current time t; R w represents the wear rate, Δt=60s. A w Represents the damage safety factor, with a value of 0.7-0.

8.

9. The method for predicting the life of a cutter disc for a tunnel boring machine suitable for a hypergravity environment according to claim 8, characterized in that: The fatigue life prediction process at the current moment is shown in the following formula (4): In formula (4), L f Represents the fatigue life at the current moment; a t represents the crack length at the current time t; a c =2mm, represents the critical crack length of the hob, based on the fracture toughness of the hob material H13 steel; represents the crack growth rate, C = 2.5 × 10 -10 , is the state constant, based on the fatigue characteristics of the hob material H13 steel, ΔK t represents the stress intensity factor amplitude, m = 3.0; f t represents the hob vibration frequency measured by the triaxial accelerometer; A f Represents the fatigue safety factor, with a value of 0.6-0.

7.

10. The method for predicting the life of a cutter disc for a tunnel boring machine suitable for a hypergravity environment according to claim 9, characterized in that: The minimum value between the wear life and the fatigue life is selected as the remaining life of the hob at the current moment, as shown in the following formula (5): L d =min(L w ,L f ) (5); In formula (5), L d Represents the remaining life of the hob at the current moment.

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