Tunneling parameter optimization and hob abnormal wear avoidance method based on shield cutterhead vibration

Abstract

The invention discloses a tunneling parameter optimization and hob abnormal wear avoidance method based on shield cutterhead vibration, and relates to the technical field of tunnel and underground engineering, and the method comprises the steps: collecting three-way vibration signals during tunneling of a shield cutterhead; driving the shield cutter head to execute an in-situ tunneling experiment, and synchronously calculating a vibration signal characteristic value by using the three-way vibration signal; carrying out bin opening detection and statistics on the abrasion type of each hob, and judging the abnormal damage level of the shield cutter head in combination with the material structure information of the hobs; extracting vibration intensity ranges when the shield cutter head is at different abnormal damage grades, and taking the corresponding vibration intensity range when the shield cutter head is at the lowest abnormal damage grade as a target tunneling range; and analyzing whether the vibration intensity of the shield cutter head is in the target tunneling range or not in real time during shield tunneling. According to the invention, the limitation of hysteresis of traditional geological exploration is broken through; hob breakage or eccentric wear accidents caused by geological sudden changes are avoided, and construction safety in complex stratums is remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of tunnel and underground engineering technology, and more specifically, to a method for optimizing tunneling parameters and avoiding abnormal cutter wear based on shield cutterhead vibration. Background Technology

[0002] With the rapid development of underground engineering, the shield tunneling method has been widely used in tunnel construction in complex and variable geological formations due to its advantages of high efficiency and safety. During the shield tunneling process, the cutterhead crushes the rock mass, and as a consumable material, it inevitably experiences wear.

[0003] However, due to the complex and variable geological conditions of long tunnels, the cutterhead is prone to stalling and uneven wear in softer strata, while in harder strata it is frequently subjected to impact loads, inducing fracture. Once abnormal wear occurs, the cutterhead's lifespan is drastically reduced, requiring immediate shutdown and cutterhead replacement. How to avoid abnormal wear during shield tunneling in complex strata is a common challenge and concern in the engineering community.

[0004] Based on the cutterhead vibration intensity signal, the current geological strength state can be determined. By comprehensively analyzing the cutterhead vibration intensity and cutter damage, and dynamically adjusting the tunneling parameters, cutter wear and breakage can be avoided in complex and variable geological formations. Therefore, it is necessary to propose a method for optimizing tunneling parameters and avoiding abnormal cutter wear based on cutterhead vibration, so as to avoid abnormal cutter wear during shield tunneling in complex and variable geological formations, reduce the number of cutterhead changes, and improve shield tunneling efficiency.

[0005] No effective solutions have yet been proposed to address the problems in the relevant technologies. Summary of the Invention

[0006] To address the problems in related technologies, this invention proposes a method for optimizing tunneling parameters and avoiding abnormal cutter wear based on shield cutterhead vibration, in order to overcome the aforementioned technical problems existing in the existing related technologies.

[0007] Therefore, the specific technical solution adopted by the present invention is as follows:

[0008] A method for optimizing tunneling parameters and avoiding abnormal cutter wear based on shield cutterhead vibration is provided. The method includes:

[0009] Based on the vibration sensors pre-installed inside the shield cutterhead, the three-dimensional vibration signals of the shield cutterhead during tunneling are collected;

[0010] By simulating actual geological conditions, the shield cutterhead was driven to perform in-situ tunneling experiments, and the characteristic values ​​of the vibration signals were calculated synchronously using triaxial vibration signals. When the in-situ tunneling experiment was completed, the wear type of each cutter was detected and statistically analyzed, and the abnormal damage level of the shield cutterhead was determined by combining the material and structural information of the cutter.

[0011] Based on the calculation results of the vibration signal feature values, the vibration intensity range of the shield cutterhead under different abnormal damage levels is extracted, and the vibration intensity range corresponding to the shield cutterhead under the lowest abnormal damage level is taken as the target tunneling range.

[0012] The system analyzes in real time whether the vibration intensity of the shield cutterhead is within the target tunneling range. If the vibration intensity is within the target tunneling range, the current tunneling parameters are maintained. If the vibration intensity is not within the target tunneling range, the tunneling parameters are optimized to adjust the vibration intensity to the target tunneling range in order to avoid the risk of abnormal wear of the cutterhead.

[0013] Furthermore, based on vibration sensors pre-installed inside the tunnel boring machine cutterhead, the three-dimensional vibration signals collected during tunnel boring machine cutterhead excavation include:

[0014] A magnetic vibration sensor is installed at the bearing position of the shield cutterhead to collect vibration acceleration data of the shield cutterhead during the tunneling process according to a preset sampling period.

[0015] All vibration sensors are wirelessly connected to a remote real-time vibration signal analysis system. The real-time vibration signal analysis system receives vibration acceleration data in real time and generates three-dimensional vibration waveforms of preset duration in the cutterhead excavation direction, horizontal direction, and vertical direction, respectively, according to preset waveform recording duration, as the three-dimensional vibration signals of the shield cutterhead.

[0016] Furthermore, by simulating actual geological conditions, an in-situ tunneling experiment was conducted by driving the tunnel boring machine cutterhead, and the characteristic values ​​of the vibration signals were synchronously calculated using three-dimensional vibration signals, including:

[0017] The actual geological conditions covering soil, rock and soil-rock composite layers were established, and the shield cutterhead was driven to carry out in-situ tunneling experiments according to the preset tunneling control parameters, including penetration depth, cutterhead rotation speed and tunneling mode.

[0018] Extract the maximum and minimum values ​​of vibration acceleration data from a preset number of triaxial vibration signals, and calculate the peak response of the triaxial vibration signal during the current sampling period;

[0019] The triaxial vibration signal is converted into time-domain sequence data, and the vibration acceleration data of all sample points in the time-domain sequence data are extracted and calculated to obtain the effective vibration value of the triaxial vibration signal at the current sampling period.

[0020] Based on the temporal distribution of time-series data, the response peaks and effective vibration values ​​in the same sampling period are spatiotemporally aligned and used as the vibration signal characteristic values ​​of the tunnel boring machine cutterhead in the current sampling period.

[0021] Furthermore, during the in-situ tunneling experiment, the wear types of each cutterhead were inspected and statistically analyzed. Combined with the material and structural information of the cutterheads, the abnormal damage levels existing on the shield cutterhead were determined, including:

[0022] When the shield cutterhead completes a single in-situ tunneling test, the shield tunneling is stopped and the cutterhead chamber door is opened in accordance with safety procedures. A spatial positioning reference is established by combining the cutterhead position number. Wear monitoring data is collected using multi-source sensors and associated with the marked cutterhead position information to form a wear monitoring dataset.

[0023] Based on the vision-current eddy current fusion detection technology, the hob is reconstructed in three dimensions and the wear characteristic parameters are calculated. Laser scanning is introduced to verify the wear amount in the hob body area and output the wear quantization matrix with position correlation.

[0024] Input the hob model into the hob material database to query the material structure information, construct a damage physics model by combining the temperature field distribution and wear characteristic parameters, perform causal analysis on the wear morphology, and output the wear failure attribution.

[0025] Based on the wear quantification matrix and wear failure attribution, the wear judgment threshold is dynamically adjusted according to the cutter position to determine and correct the wear type of the cutter, and to calculate the abnormal damage level of all cutters in the shield cutterhead.

[0026] Furthermore, the wear monitoring dataset includes visual images, eddy current thickness data, temperature field distribution, and hob position information; wear characteristic parameters include wear index, wear degree, and broken area ratio.

[0027] Furthermore, based on vision-eddy current fusion detection technology, the hob is subjected to three-dimensional contour reconstruction and wear characteristic parameter calculation. Laser scanning is introduced to verify the wear amount in the hob body area, and the output position-correlated wear quantization matrix includes:

[0028] Obtain the visual image and eddy current thickness data corresponding to a single hob, establish pixel-level coordinate alignment between the visual image and the eddy current thickness data through a spatial encoder, and dynamically map the pixel coordinates of the visual image and the measurement points in the eddy current thickness data to the same spatial coordinate system.

[0029] Extract the edge points of the hob profile from the visual image, combine them with the eddy current thickness data at the corresponding position in the spatial coordinate system to generate a feature point set with height attributes, and use an interpolation algorithm to construct a continuous surface with the feature point set as control points to fill the gaps between rows of the single-point scanning of the eddy current, and output the three-dimensional mesh model of the hob.

[0030] The regions in the 3D mesh model where the eddy current thickness data changes abruptly are marked as abnormal mutation regions. Laser verification is performed on the abnormal mutation regions. Based on the adjacent eddy current thickness data, the wear degree and wear index are calculated. The projected area of ​​the damaged area in the abnormal mutation region is calculated by computing the laser scanning points and compared with the total area of ​​the hob to obtain the damaged area ratio.

[0031] By integrating the 3D mesh model with the laser verification results, the wear degree, wear index and damage area ratio are used as wear characteristic parameters of a single cutter head. The wear characteristic parameters of all tested and verified cutters in the shield cutterhead are also integrated to generate a wear quantification matrix indexed by the cutterhead partition number.

[0032] Furthermore, the hob model is input into the hob material database to query material structure information. A damage physics model is constructed by combining temperature field distribution and wear characteristic parameters. Causal analysis of the wear morphology is performed, and the wear failure attribution is output, including:

[0033] Based on the hob model, query the hob material database to extract material structure information, including substrate type, hardness range, coating type, WC particle ratio, thermal stability threshold and fracture toughness.

[0034] Based on wear characteristic parameters and material structure information, a qualitative correlation rule between wear mode and material defects is established. The impact of different wear modes on the performance of the current hob is analyzed, the material failure threshold of the hob is generated, and the wear failure attribution is output.

[0035] Furthermore, based on the wear quantification matrix and wear failure attribution, and combined with the dynamic adjustment of the wear judgment threshold by the cutter position, the wear type of the cutter is determined and corrected, and the abnormal damage level of all cutters in the shield cutterhead is calculated, including:

[0036] The wear characteristic parameters of each hob are extracted from the wear quantization matrix, and wear classification rules are established based on the material failure threshold. Based on the wear classification rules, the wear type of each hob is preliminarily determined, and the wear type of the hob is output.

[0037] The shield cutterhead is divided into multiple annular zones according to the radius. Based on the zone position of the cutterhead, the position sensitivity coefficient is dynamically allocated. The material failure threshold and wear classification rules of the cutterhead in different zones are corrected according to the position sensitivity coefficient, and the wear type of the cutterhead is re-determined.

[0038] Using the polar coordinate system of the tunnel boring machine cutterhead as a reference, the corrected wear types are mapped to a gridded space in annular partitions. A continuous wear type heat map is generated by the color difference algorithm to show the spatial distribution of the wear types of the hobbing cutter.

[0039] Based on the wear distribution and location sensitivity coefficient of the roller cutter in the comprehensive wear type heat map, the overall damage index of the shield cutterhead is calculated by a partitioned weighted aggregation algorithm, and the abnormal damage level of the shield cutterhead is determined by combining the preset threshold.

[0040] Furthermore, the shield cutterhead is divided into multiple annular zones according to radius. Based on the zone positions of the cutterhead, a position sensitivity coefficient is dynamically allocated, including:

[0041] Based on the structural characteristics of the shield cutterhead and the theory of tunneling mechanics, the shield cutterhead is divided into a central area, a front area and an edge area distributed in a ring, and the load characteristics of each area are associated with the area. The area is automatically marked according to the position information of the roller cutter.

[0042] Based on the load characteristics of each zone, position sensitivity coefficients are assigned to different zones. The wear quantization matrix is ​​traversed, and position sensitivity coefficient labels are added to each hob and wear characteristic parameter according to the zone label.

[0043] Furthermore, based on the calculation results of the vibration signal feature values, the vibration intensity range of the shield cutterhead under different abnormal damage levels is extracted, and the vibration intensity range corresponding to the lowest abnormal damage level of the shield cutterhead is taken as the target tunneling range, including:

[0044] The test results of all in-situ tunneling experiments were reviewed, and the experimental group with the lowest abnormal damage level was selected as the target experimental group. The vibration signal feature values ​​corresponding to the target experimental group were selected as the vibration signal dataset. All vibration signal feature values ​​of the target experimental group were extracted, and the vibration effective value sequence and response peak sequence were separated.

[0045] The lower and upper quantiles of the effective vibration value sequence and the peak response sequence are calculated using quantile statistics to form a safe boundary range of vibration intensity, which serves as the target tunneling range. The calculated target tunneling range is then integrated to generate a standardized target tunneling range instruction set.

[0046] The beneficial effects of this invention are as follows:

[0047] 1. By using vibration sensors built into the shield cutterhead to collect vibration signals in the tunneling direction, horizontal and vertical directions in real time, and combining them with in-situ tunneling experimental data, a mapping relationship between vibration characteristic values ​​and stratum strength is constructed, breaking through the limitations of the lag in traditional geological exploration; the high-frequency sampling and wireless transmission technology of vibration signals enables dynamic updates to stratum condition identification, avoiding cutter breakage or uneven wear accidents caused by geological changes, and significantly improving construction safety in complex strata.

[0048] 2. By simulating various geological conditions such as soil, rock, and soil-rock composite layers, the shield tunneling machine was driven to perform in-situ tunneling experiments. Vibration signals and cutter wear data were collected simultaneously. For the first time, a quantitative correlation system was established between vibration intensity and abnormal cutter damage level. By selecting the vibration characteristic boundary of the lowest damage level experimental group as the target tunneling range, a reproducible safety benchmark was provided for parameter optimization, solving the problem of blindness in traditional empirical threshold setting.

[0049] 3. Based on the characteristic values ​​of vibration signals, including the peak response value and the effective value of vibration, the risk of abnormal damage to the hob is determined in real time, realizing a closed-loop control logic for vibration intensity over-limit warning and dynamic parameter adjustment; by comparing the current vibration intensity with the target range, the coordinated adjustment of speed and penetration is automatically triggered. If it is too high, the speed and penetration are reduced to prevent breakage; if it is insufficient, the speed is increased to increase penetration to prevent uneven wear, thereby avoiding abnormal failure modes such as hob impact breakage and uneven wear due to stoppage at the source.

[0050] 4. By integrating vibration characteristics, wear quantification matrix and material database, a decision model coupling location, material and abnormal damage is constructed; by dynamically allocating the location sensitivity coefficients of the center area and the edge area, the damage level of the cutter head is accurately corrected, which solves the defect of traditional methods that ignore spatial load distribution and material characteristics, and provides multi-dimensional basis for tunneling parameter optimization.

[0051] 5. By comparing the vibration intensity determination results with the target range in real time, a standardized tunneling parameter instruction set is generated and directly sent to the shield control system. This dynamic adjustment strategy is adaptable to complex working conditions such as uneven soft and hard strata and soil-rock composite layers, significantly reducing the intensity of manual intervention and providing a reusable technical paradigm for extending cutter life and improving construction efficiency under various geological conditions. Attached Figure Description

[0052] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0053] Figure 1 This is a flowchart of a method for optimizing tunneling parameters and avoiding abnormal cutter wear based on shield cutterhead vibration according to an embodiment of the present invention;

[0054] Figure 2 This is a diagram showing the installation of a field vibration sensor and analysis system according to an embodiment of the present invention;

[0055] Figure 3 These are the in-situ tunneling test parameters according to embodiments of the present invention;

[0056] Figure 4 These are the characteristic values ​​of the acceleration response in the X direction according to an embodiment of the present invention;

[0057] Figure 5 These are the characteristic values ​​of the acceleration response in the Y direction according to an embodiment of the present invention. Detailed Implementation

[0058] To further illustrate the various embodiments, the present invention provides accompanying drawings, which are part of the disclosure of the present invention. These drawings are mainly used to illustrate the embodiments and can be used in conjunction with the relevant descriptions in the specification to explain the operating principles of the embodiments. With reference to these drawings, those skilled in the art should be able to understand other possible implementation methods and the advantages of the present invention.

[0059] According to an embodiment of the present invention, a method for optimizing tunneling parameters and avoiding abnormal cutter wear based on shield cutterhead vibration is provided.

[0060] The present invention will now be further described in conjunction with the accompanying drawings and specific embodiments, such as... Figure 1 As shown, according to an embodiment of the present invention, a method for optimizing tunneling parameters and avoiding abnormal cutter wear based on shield cutterhead vibration is provided. The method includes:

[0061] S1. Based on the vibration sensors pre-installed inside the shield cutterhead, collect the three-dimensional vibration signals during shield cutterhead excavation.

[0062] In the description of this invention, the acquisition of three-dimensional vibration signals during tunnel boring machine (TBM) cutterhead excavation, based on vibration sensors pre-installed inside the TBM cutterhead, includes:

[0063] S11. Install magnetic vibration sensors at the bearing position of the shield cutterhead and collect vibration acceleration data of the shield cutterhead during the tunneling process according to the preset sampling period, such as collecting three-dimensional vibration waveforms every 15 minutes.

[0064] Specifically, such as Figure 2 As shown, Figure 2 The vibration acceleration sensor (i.e., vibration sensor) is installed on the cutter head bearing and is connected to the vibration analysis system (i.e., vibration signal real-time analysis system) via wireless communication.

[0065] S12. Establish a wireless communication connection between all vibration sensors and the remote real-time vibration signal analysis system. The real-time vibration signal analysis system receives vibration acceleration data in real time and generates three-dimensional vibration waveforms of preset duration in the cutterhead tunneling direction, horizontal direction, and vertical direction according to the preset waveform recording duration. For example, 2000 acceleration data are collected within 0.5s each time to form a waveform, which serves as the three-dimensional vibration signal of the shield cutterhead.

[0066] S2. By simulating actual geological conditions, the shield cutterhead is driven to perform in-situ tunneling experiments, and the characteristic values ​​of the vibration signals are calculated synchronously using three-dimensional vibration signals. During the in-situ tunneling experiment, the wear type of each cutter head is detected and statistically analyzed, and the abnormal damage level of the shield cutterhead is determined by combining the material and structural information of the cutter head.

[0067] In the description of this invention, by simulating actual geological conditions, the shield tunneling cutterhead is driven to perform in-situ tunneling experiments, and the characteristic values ​​of the vibration signals are synchronously calculated using three-dimensional vibration signals, including:

[0068] S21. Establish actual geological conditions covering soil, rock, and soil-rock composite layers, and drive the shield cutterhead to conduct in-situ tunneling experiments according to preset tunneling control parameters, including penetration depth, cutterhead rotation speed, and tunneling mode.

[0069] Specifically, in-situ tunneling tests include tests with varying cutterhead rotation speed, tests with varying penetration depth, and tests with different tunneling modes. The monitoring parameters for in-situ tunneling tests, including the shield cutterhead thrust, torque, penetration depth, and cutterhead rotation speed, also serve as tunneling parameters to control the shield cutterhead's construction operations. The monitored changes in each parameter are as follows: Figure 3 As shown.

[0070] During the cutterhead speed test, the cutterhead speed is adjusted step by step in the shield machine control room, typically within the range of 0.8 to 1.5 r / min. During the penetration test, the cutterhead speed is kept constant, and the penetration is changed by gradually adjusting the tunneling speed, typically within the range of 1 to 10 mm / r. During the tunneling mode test, the tunneling speed is kept constant. If the penetration is increased, the cutterhead speed is decreased, and if the penetration is decreased, the cutterhead speed is increased.

[0071] S22. Extract the maximum and minimum values ​​of vibration acceleration data of a preset number from the triaxial vibration signal, and calculate the peak response of the triaxial vibration signal during the current sampling period.

[0072] Specifically, to calculate the peak response value among the characteristic values ​​of the vibration signal, in order to minimize random errors in the data, four maximum values ​​(positive values) and four minimum values ​​(negative values) were selected from 2000 acceleration response values ​​(vibration acceleration data) to calculate the peak response value X. P Peak X P Take the following formula:

[0073]

[0074] In the formula, X m1 X m2 X m3 X m4 X represents the four maximum (positive) values ​​out of 2000 acceleration responses within 0.5s.n1 X n2 X n3 X n4 These are the four minimum (negative) values ​​among 2000 acceleration responses within 0.5s.

[0075] S23. Convert the triaxial vibration signal into time-domain sequence data, extract the vibration acceleration data of all sample points in the time-domain sequence data, perform calculations, and obtain the effective vibration value of the triaxial vibration signal at the current sampling period.

[0076] Specifically, the effective value X rms The energy used to describe the vibration signal can be used to characterize the energy level of the entire rock-breaking process of the roller cutter. The calculation formula is as follows:

[0077]

[0078] In the formula, x(n) is a time-domain sequence, n = 1, 2, ..., N; N is the number of acceleration sample points monitored. In this invention, the number of acceleration sample points within a monitoring period is 2000.

[0079] In addition, such as Figure 4 and Figure 5 As shown, Figure 4 The monitoring results of acceleration in the X-axis direction are shown, that is, the change in the characteristic value of the vibration signal as a function of the number of vibration monitoring cycles in the X-axis direction. Figure 5 The monitoring results of acceleration in the Y-axis direction are shown, that is, the change in the characteristic value of the vibration signal following the number of vibration monitoring in the Y direction.

[0080] S24. Based on the temporal distribution of time-series data, the response peak value and vibration effective value in the same sampling period are spatiotemporally aligned and used as the vibration signal characteristic value of the shield cutterhead in the current sampling period.

[0081] In the description of this invention, during the in-situ tunneling experiment, the wear type of each cutterhead is detected and statistically analyzed upon opening the tunnel boring machine (TBM), and the abnormal damage level of the TBM cutterhead is determined by combining the material and structural information of the cutterhead. This includes:

[0082] S25. When the shield cutterhead completes a single in-situ tunneling test, the shield tunneling is stopped and the cutterhead chamber door is opened in accordance with safety regulations. A spatial positioning reference is established in conjunction with the cutterhead position number. Wear monitoring data is collected using multi-source sensors and associated with the marked cutterhead position information to form a wear monitoring dataset. The wear monitoring dataset includes visual images, eddy current thickness data, temperature field distribution, and cutterhead position information.

[0083] Specifically, the safe opening and sensor positioning process includes: completing the soil chamber depressurization, ventilation, and harmful gas detection according to the standard shield tunneling opening procedure, and opening the chamber door after confirming safety. Dust-proof industrial cameras are deployed in designated areas of the cutterhead, and their position coordinates are automatically associated with the cutterhead's serial number labels. An eddy current sensor array is installed along the circumference of the cutterhead, and infrared temperature probes are simultaneously deployed to monitor the temperature gradient on the cutterhead surface in real time.

[0084] S26. Based on vision-current eddy current fusion detection technology, the hob is reconstructed in three dimensions and wear characteristic parameters are calculated. Laser scanning is introduced to verify the wear amount in the hob body area and output the wear quantification matrix associated with the position. The wear characteristic parameters include the wear index, wear degree and broken area ratio.

[0085] In the description of this invention, based on vision-current eddy current fusion detection technology, a three-dimensional contour reconstruction and wear characteristic parameter calculation are performed on the hob, and laser scanning is introduced to verify the wear amount in the hob body area. The output position-correlated wear quantization matrix includes:

[0086] S261. Obtain the visual image and eddy current thickness data corresponding to a single hob. Establish pixel-level coordinate alignment between the visual image and the eddy current thickness data through a spatial encoder. Dynamically map the pixel coordinates of the visual image and the measurement points in the eddy current thickness data to the same spatial coordinate system.

[0087] S262. Extract the edge points of the hob profile from the visual image, combine them with the eddy current thickness data at the corresponding positions in the spatial coordinate system, generate a feature point set with height attributes, and use an interpolation algorithm to construct a continuous surface with the feature point set as control points to fill the gaps between rows of the single-point scanning of the eddy current, and output the three-dimensional mesh model of the hob.

[0088] S263. Mark the regions in the 3D mesh model where the eddy current thickness data changes abruptly as abnormal mutation regions. Perform laser verification on the abnormal mutation regions. Calculate the wear degree and wear index based on the adjacent eddy current thickness data. Compare the projected area of ​​the damaged area within the abnormal mutation region using laser scanning points with the total area of ​​the hob to obtain the damaged area ratio.

[0089] S264. Integrate the three-dimensional mesh model with the laser verification results, and use the wear degree, wear index and damage area ratio as wear characteristic parameters of a single cutter head. Integrate the wear characteristic parameters of all tested and verified cutters head in the shield cutterhead to generate a wear quantification matrix indexed by the cutterhead partition number.

[0090] S27. Input the hob model into the hob material database to query the material structure information, construct a damage physics model by combining the temperature field distribution and wear characteristic parameters, perform causal analysis on the wear morphology, and output the wear failure attribution.

[0091] In the description of this invention, the hob model is input into the hob material database to query material structure information. A damage physics model is constructed by combining temperature field distribution and wear characteristic parameters. Causal analysis of wear morphology is performed, and the wear failure attribution is output, including:

[0092] S271. Query the hob material database according to the hob model and extract the material structure information, including substrate type, hardness range, coating type, WC particle ratio, thermal stability threshold and fracture toughness.

[0093] Simultaneously, the position label of the hob in the cutter head is associated, and a typical load spectrum (composite load) of the region is loaded to provide basic material science parameters for subsequent damage attribution.

[0094] S272. Based on wear characteristic parameters and material structure information, establish qualitative correlation rules between wear mode and material defects, analyze the impact of different wear modes on the performance of the current hob, generate the material failure threshold of the hob, and output the wear failure attribution.

[0095] Specifically, combining the wear characteristic parameters in the wear quantification matrix with the extracted material parameters, the wear characteristic parameters include the eccentric wear index B and the broken area ratio F. r Degree of wear W, establish qualitative correlation rules:

[0096] Attribution of uneven wear: If B≥0.3 and WC particle ratio<70%, it is determined that the uneven wear is caused by insufficient coating wear resistance, as the edge hob is more sensitive; if a local temperature rise>15℃ and substrate hardness<400HV are detected at the same time, the combined attribution is that thermal softening aggravates uneven wear, as the center hob has a significant temperature rise due to impact.

[0097] Attribution of fracture: If F r >10% and no significant temperature rise, temperature difference ΔT < temperature threshold, attributed to impact overload brittle fracture, i.e., the central hob is subjected to high impact load; if F r >10% accompanied by a temperature rise gradient >20℃ / cm and a substrate hardness >500HV, is attributed to thermal fatigue-induced matrix cracking due to thermal stress concentration in high-hardness materials.

[0098] Based on the above rules, a material failure threshold is generated, and a wear failure attribution report including primary and secondary causes is output, such as the wear exceedance threshold W for alloy steel. max =8mm, coating fracture sensitive temperature T critical =600℃, then the output will be "Edge hob R9: Main cause - insufficient coating wear resistance, secondary cause - local temperature rise of 18℃".

[0099] S28. Based on the wear quantification matrix and wear failure attribution, and combined with the dynamic adjustment of the wear judgment threshold by the cutter position, the wear type of the cutter is determined and corrected, and the abnormal damage level of all cutters in the shield cutterhead is calculated.

[0100] In the description of this invention, based on the wear quantification matrix and wear failure attribution, and combined with the dynamic adjustment of the wear judgment threshold by the cutter position, the wear type of the cutter is determined and corrected, and the abnormal damage level of all cutters in the shield cutterhead is calculated, including:

[0101] S281. Extract the wear characteristic parameters of each hob from the wear quantization matrix, and establish wear classification rules based on the material failure threshold. Based on the wear classification rules, make a preliminary determination of the wear type of each hob and output the wear type of the hob; according to the actual scenario, each hob can be divided into normal wear hob, wear exceeding the limit hob, uneven wear hob, and fracture hob.

[0102] Specifically, based on the characteristic parameters in the wear quantification matrix (wear index B, damage area ratio F) r Based on the wear level (W) and the material failure threshold, the damage type of each hob is initially determined, and four labels are output: "normal wear / wear exceeding limit / uneven wear / fracture", providing a data source for individual damage in the heat map.

[0103] The following aspects can be considered when formulating classification rules: 1. Normal wear (grade 0): W≤8mm or ≤15mm and B<0.1, no structural damage (F r ≤5%); 2. Excessive wear (Level 1): W>8mm or>15mm, but uniform wear (B<0.1); 3. Uneven wear (Level 2): ​​B≥0.3 or local thickness abrupt change>3mm, regardless of the amount of wear; 4. Fracture (Level 3): F r >10% or there may be broken blade rings or stuck bearings.

[0104] S282. Divide the shield cutterhead into multiple annular zones according to the radius. Based on the zone position of the cutterhead on the shield cutterhead, dynamically allocate position sensitivity coefficients. Then, based on the position sensitivity coefficients, correct the material failure threshold and wear classification rules of the cutterhead in different zones, and re-determine the wear type of the cutterhead.

[0105] In the description of this invention, the shield cutterhead is divided into multiple annular sections according to radius, and the position sensitivity coefficient is dynamically allocated based on the section position of the cutterhead on the shield cutterhead, including:

[0106] S2821. Based on the structural characteristics of the shield cutterhead and the theory of tunneling mechanics, the shield cutterhead is divided into a central area, a front area and an edge area distributed in a ring, and the load characteristics of each area are associated with the area. The area to which the cutterhead belongs is automatically marked according to the cutterhead position information.

[0107] Specifically, based on the structural characteristics of the cutterhead and the tunneling mechanics model, the cutterhead is divided into three typical regions: the central region, the frontal region, and the edge region. The load characteristics of each region are associated with the load characteristics, including impact load, composite load, and shear load, to provide a mechanical basis for the allocation of position influence factors.

[0108] The specific structural zoning definitions can be found below: 1. Central zone (R1-R3): 0-30% radius area, dominated by frontal impact loads of the rock mass, with the cutter bearing high-frequency impact force; 2. Frontal zone (R4-R6): 30%-70% radius area, subjected to combined thrust and torque loads, with the cutter bearing medium-frequency alternating force; 3. Edge zone (R7-R9): 70%-100% radius area, subjected to lateral shear loads of the soil, with the cutter bearing continuous shear force.

[0109] S2822. Based on the load characteristics of each partition, assign position sensitivity coefficients to different partitions, traverse the wear quantization matrix, and add position sensitivity coefficient labels to each hob and wear characteristic parameter according to the partition label.

[0110] Specifically, based on the regional load characteristics, different zones are assigned damage sensitivity coefficients (α). c / α p / α e This method quantifies the differences in the sensitivity of location to abnormal damage, breaking through the limitation of ignoring the spatial mechanical distribution by using a fixed threshold.

[0111] The sensitivity coefficient allocation rules are as follows: 1. Central region (impact sensitive): Assign a fracture sensitivity coefficient α c =1.2, indicating that impact load exacerbates the risk of blade ring breakage; 2. Edge region (sensitive to uneven wear): assigns an uneven wear sensitivity coefficient α e =1.5, characterizing shear load-accelerated unilateral wear; 3. Front area (reference): assigns a composite sensitivity coefficient α p =1.0, which means maintaining the default threshold.

[0112] In the description of this invention, the wear type of the hob is re-determined according to the material failure threshold and wear classification rules of the hob with different position sensitivity coefficients, based on the following: 1. Hob in the center area: Due to the concentrated impact load, according to the fracture sensitivity coefficient α of the center area... c =1.2, lowering the material failure threshold for fracture determination by 20%, that is, when the damaged area is greater than F r >α c -1 ×10% upgrades to fracture wear; 2. Edge zone hobbing: Because lateral shear force easily induces uneven wear, the material failure threshold for determining the uneven wear index is reduced to B≥0.25, that is, the original threshold of 0.3×α e -1Simultaneously, the wear threshold is compressed; 3. Front area hobbing cutter: Maintain the default material failure threshold, such as wear index B≥0.3, fracture area ratio F r >10%.

[0113] S283. Using the polar coordinate system of the shield cutterhead as a reference, the corrected wear types are mapped to the gridded space in annular partitions. A continuous wear type heat map is generated through the color difference algorithm to show the spatial distribution of the cutterhead wear types.

[0114] Specifically, a polar coordinate system is established with the center of the shield cutterhead as the origin. The cutterhead is divided into three annular regions with equal radius, and circumferential sectors are divided at 30° intervals to form gridded spatial units. The wear type data of the roller cutters in each grid unit is traversed, the proportion of roller cutters with different wear types in each unit is counted, and the wear type distribution gradient of adjacent grid units is smoothed by cubic spline interpolation algorithm to generate a continuous two-dimensional damage density distribution surface.

[0115] Finally, based on the preset color mapping rules, the surface is rendered with colors to output a heat map that intuitively displays the spatial clustering characteristics of wear types. The color transition areas reflect the gradual trend of wear risk, such as dark green indicating that the proportion of normal wear is ≥90%, orange indicating that the proportion of uneven wear is >30%, and red indicating that the proportion of fracture is >15%.

[0116] S284. The wear distribution and location sensitivity coefficient of the roller cutter in the comprehensive wear type heat map are used to calculate the overall damage index of the shield cutterhead through a partitioned weighted aggregation algorithm, and the abnormal damage level of the shield cutterhead is determined by combining the preset threshold.

[0117] Specifically, the wear type distribution weights for each region are extracted according to the annular partition, with the central region focusing on fracture damage (assigned a weighting coefficient ω). c =1.5), edge area eccentric wear damage (ω) e =1.8), the front area combines all types (ω) p =1.0).

[0118] The calculation of the zonal damage index includes the following aspects: 1. Central zone index D c = (Number of Level 3 Fracture Hobs × ω) c +2 number of grade 2 uneven grinding hobs) / total number of hobs; 2. Edge zone index D e = (Number of level 2 uneven grinding hobs × ω) e +3 number of fractured hobs) / total number of hobs; 3. Front area index D p =Σ(Number of hobs at each damage level × ω) p ) / Total number of hobbing cutters.

[0119] Using the weighted aggregation formula D index=0.4×max(D c D e )+0.6×D p The overall damage index is obtained, and the damage level is determined based on a threshold, for example: D. index <0.15 is Level I (normal), 0.15-0.30 is Level II (mild), 0.30-0.45 is Level III (moderate), and ≥0.45 is Level IV (severe). This level is directly related to maintenance decisions.

[0120] S3. Based on the calculation results of the vibration signal feature values, extract the vibration intensity range when the shield cutterhead is under different abnormal damage levels, and take the vibration intensity range corresponding to the lowest abnormal damage level of the shield cutterhead as the target tunneling range.

[0121] In the description of this invention, based on the calculation results of vibration signal feature values, the vibration intensity range of the shield cutterhead under different abnormal damage levels is extracted, and the vibration intensity range corresponding to the lowest abnormal damage level of the shield cutterhead is taken as the target tunneling range, including:

[0122] S31. Traverse all in-situ tunneling test results, select the experimental group with the lowest abnormal damage level as the target experimental group, select the vibration signal feature value corresponding to the target experimental group as the vibration signal dataset, and extract all vibration signal feature values ​​in the target experimental group to separate the vibration effective value sequence and the response peak sequence.

[0123] S32. Calculate the lower and upper quantiles of the vibration effective value sequence and the response peak sequence using quantile statistics to form the safe boundary range of vibration intensity, which serves as the target tunneling range. Integrate the calculated target tunneling ranges to generate a standardized target tunneling range instruction set.

[0124] Specifically, the response peak sequences are also arranged in ascending order, and the 10th percentile (P10) is taken. Peak Using 90% quantile as the lower limit, we take the 90th percentile (P90). Peak ) serves as the upper limit, forming the response peak safety boundary Peak∈[P10] Peak P90 Peak ].

[0125] The effective vibration value sequence is arranged in ascending order, and the 10th percentile (P10) is taken. RMs As the lower limit of the safety range, the 90th percentile (P90) is used. RMs As the upper limit of the safety range, the effective vibration value safety boundary RMS∈[P10] is formed. RMs P90 RMs ].

[0126] The physical rationality of boundary values ​​is verified based on engineering safety principles: if the upper limit of RMS exceeds the material limit of the alloy steel hob, the limit is forcibly truncated to RMS. max =6m / s 2 If the Peak lower limit is lower than the sensor noise level, then adjust to Peak. min =0.5m / s 2 Finally, the validated boundary parameters are integrated to generate a standardized target tunneling range instruction set, which is stored in a structured data format, including the upper and lower limits of the effective vibration value (RMS). min RMS max ) and peak response upper and lower limits (Peak) min Peak max The data is then written into the shield tunneling control parameter database via the PLC system.

[0127] S4. Real-time analysis of whether the vibration intensity of the shield cutterhead is within the target tunneling range during shield tunneling. If the vibration intensity is within the target tunneling range, the current tunneling parameters are maintained. If the vibration intensity is not within the target tunneling range, the tunneling parameters are optimized to adjust the vibration intensity to the target tunneling range in order to avoid the risk of abnormal wear of the cutterhead.

[0128] Specifically, when the vibration intensity is not within the target tunneling range, if the tunneling vibration intensity is greater than the target tunneling range, reduce the cutterhead speed or penetration depth to reduce the vibration intensity to the target tunneling range and avoid cutter breakage; if the tunneling vibration intensity is less than the target tunneling range, increase the cutterhead speed or penetration depth to increase the vibration intensity to the target tunneling range and avoid cutter wear.

[0129] In summary, by utilizing the technical solutions described above, the shield tunneling machine (TBM) uses a built-in vibration sensor to collect vibration signals in the tunneling direction, horizontal and vertical directions in real time. Combined with in-situ tunneling experimental data, a mapping relationship between vibration characteristic values ​​and stratum strength is constructed, overcoming the limitations of traditional geological exploration's lag. High-frequency sampling and wireless transmission of vibration signals enable dynamic updates to stratum condition identification, preventing cutter breakage or uneven wear accidents caused by sudden geological changes, and significantly improving construction safety in complex strata. By simulating various strata conditions such as soil, rock, and soil-rock composite layers, the TBM is driven to perform in-situ tunneling experiments, simultaneously collecting vibration signals and cutter wear data. For the first time, a quantitative correlation system linking vibration intensity and abnormal cutter damage levels is established. By selecting the vibration characteristic boundary of the lowest damage level experimental group as the target tunneling range, a reproducible safety benchmark is provided for parameter optimization, solving the problem of blindly setting traditional empirical thresholds. Based on vibration signal characteristic values, including peak response and effective vibration value, the risk of abnormal cutter damage is determined in real time, realizing a closed-loop control logic for vibration intensity over-limit early warning and dynamic parameter adjustment. By comparing the current vibration intensity with the target range, the rotation speed and penetration are automatically adjusted in a coordinated manner. If the vibration intensity is too high, the speed and penetration are reduced to prevent fracture; if the vibration intensity is insufficient, the speed and penetration are increased to prevent uneven wear. This fundamentally avoids abnormal failure modes such as cutter impact fracture and uneven wear due to rotation stoppage. By integrating vibration characteristics, wear quantification matrix, and material database, a decision model coupling location, material, and abnormal damage is constructed. By dynamically allocating the location sensitivity coefficients of the center and edge areas, the cutter damage level is accurately corrected, overcoming the shortcomings of traditional methods that ignore spatial load distribution and material characteristics, and providing multi-dimensional basis for tunneling parameter optimization. By comparing the vibration intensity determination results with the target range in real time, a standardized set of tunneling parameter instructions is generated and directly sent to the shield control system. This dynamic adjustment strategy is adaptable to complex working conditions such as uneven soft and hard strata and soil-rock composite layers, significantly reducing the intensity of manual intervention and providing a reusable technical paradigm for extending cutter life and improving construction efficiency under various geological conditions.

[0130] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for optimizing tunneling parameters and avoiding abnormal cutter wear based on shield cutterhead vibration, characterized in that, The method includes: Based on the vibration sensors pre-installed inside the shield cutterhead, the three-dimensional vibration signals of the shield cutterhead during tunneling are collected; By simulating actual geological conditions, the shield cutterhead was driven to perform in-situ tunneling experiments, and the characteristic values ​​of the vibration signals were calculated synchronously using triaxial vibration signals. When the in-situ tunneling experiment was completed, the wear type of each cutter was detected and statistically analyzed, and the abnormal damage level of the shield cutterhead was determined by combining the material and structural information of the cutter. Based on the calculation results of the vibration signal feature values, the vibration intensity range of the shield cutterhead under different abnormal damage levels is extracted, and the vibration intensity range corresponding to the shield cutterhead under the lowest abnormal damage level is taken as the target tunneling range. The system analyzes in real time whether the vibration intensity of the shield cutterhead is within the target tunneling range. If the vibration intensity is within the target tunneling range, the current tunneling parameters are maintained. If the vibration intensity is not within the target tunneling range, the tunneling parameters are optimized to adjust the vibration intensity to the target tunneling range in order to avoid the risk of abnormal wear of the cutterhead.

2. The method for optimizing tunneling parameters and avoiding abnormal cutter wear based on shield cutterhead vibration according to claim 1, characterized in that, The method of collecting three-dimensional vibration signals during shield tunneling based on vibration sensors pre-installed inside the shield cutterhead includes: A magnetic vibration sensor is installed at the bearing position of the shield cutterhead to collect vibration acceleration data of the shield cutterhead during the tunneling process according to a preset sampling period. All vibration sensors are wirelessly connected to a remote real-time vibration signal analysis system. The real-time vibration signal analysis system receives vibration acceleration data in real time and generates three-dimensional vibration waveforms of preset duration in the cutterhead tunneling direction, horizontal direction, and vertical direction, respectively, according to preset waveform recording duration, as the three-dimensional vibration signals of the shield cutterhead.

3. The method for optimizing tunneling parameters and avoiding abnormal cutter wear based on shield cutterhead vibration according to claim 1, characterized in that, The process of simulating actual geological conditions to drive the tunnel boring machine cutterhead to perform in-situ tunneling experiments, and synchronously calculating the vibration signal characteristic values ​​using three-dimensional vibration signals, includes: The actual geological conditions covering soil, rock and soil-rock composite layers were established, and the shield cutterhead was driven to carry out in-situ tunneling experiments according to the preset tunneling control parameters, including penetration depth, cutterhead rotation speed and tunneling mode. Extract the maximum and minimum values ​​of vibration acceleration data from a preset number of triaxial vibration signals, and calculate the peak response of the triaxial vibration signal during the current sampling period; The triaxial vibration signal is converted into time-domain sequence data, and the vibration acceleration data of all sample points in the time-domain sequence data are extracted and calculated to obtain the effective vibration value of the triaxial vibration signal at the current sampling period. Based on the temporal distribution of time-series data, the response peaks and effective vibration values ​​in the same sampling period are spatiotemporally aligned and used as the vibration signal characteristic values ​​of the tunnel boring machine cutterhead in the current sampling period.

4. The method for optimizing tunneling parameters and avoiding abnormal cutter wear based on shield cutterhead vibration according to claim 3, characterized in that, During the in-situ tunneling experiment, the wear type of each cutterhead was detected and statistically analyzed upon opening the tunnel boring machine (TBM) chamber. Combined with the material and structural information of the cutterheads, the abnormal damage level of the TBM cutterhead was determined, including: When the shield cutterhead completes a single in-situ tunneling test, the shield tunneling is stopped and the cutterhead chamber door is opened in accordance with safety procedures. A spatial positioning reference is established by combining the cutterhead position number. Wear monitoring data is collected using multi-source sensors and associated with the marked cutterhead position information to form a wear monitoring dataset. Based on the vision-current eddy current fusion detection technology, the hob is reconstructed in three dimensions and the wear characteristic parameters are calculated. Laser scanning is introduced to verify the wear amount in the hob body area and output the wear quantization matrix with position correlation. Input the hob model into the hob material database to query the material structure information, construct a damage physics model by combining the temperature field distribution and wear characteristic parameters, perform causal analysis on the wear morphology, and output the wear failure attribution. Based on the wear quantification matrix and wear failure attribution, the wear judgment threshold is dynamically adjusted according to the cutter position to determine and correct the wear type of the cutter, and to calculate the abnormal damage level of all cutters in the shield cutterhead.

5. The method for optimizing tunneling parameters and avoiding abnormal cutter wear based on shield cutterhead vibration according to claim 4, characterized in that, The wear monitoring dataset includes visual images, eddy current thickness data, temperature field distribution, and hob position information; the wear characteristic parameters include wear index, wear degree, and broken area ratio.

6. The method for optimizing tunneling parameters and avoiding abnormal cutter wear based on shield cutterhead vibration according to claim 4, characterized in that, The vision-eddy current fusion detection technology reconstructs the three-dimensional contour of the hob and calculates its wear characteristic parameters. Laser scanning is then introduced to verify the wear amount in the hob body area. The output wear quantization matrix, associated with the location, includes: Obtain the visual image and eddy current thickness data corresponding to a single hob, establish pixel-level coordinate alignment between the visual image and the eddy current thickness data through a spatial encoder, and dynamically map the pixel coordinates of the visual image and the measurement points in the eddy current thickness data to the same spatial coordinate system. Extract the edge points of the hob profile from the visual image, combine them with the eddy current thickness data at the corresponding position in the spatial coordinate system to generate a feature point set with height attributes, and use an interpolation algorithm to construct a continuous surface with the feature point set as control points to fill the gaps between rows of the single-point scanning of the eddy current, and output the three-dimensional mesh model of the hob. The regions in the 3D mesh model where the eddy current thickness data changes abruptly are marked as abnormal mutation regions. Laser verification is performed on the abnormal mutation regions. Based on the adjacent eddy current thickness data, the wear degree and wear index are calculated. The projected area of ​​the damaged area in the abnormal mutation region is calculated by computing the laser scanning points and compared with the total area of ​​the hob to obtain the damaged area ratio. By integrating the 3D mesh model with the laser verification results, the wear degree, wear index and damage area ratio are used as wear characteristic parameters of a single cutter head. The wear characteristic parameters of all tested and verified cutters in the shield cutterhead are also integrated to generate a wear quantification matrix indexed by the cutterhead partition number.

7. The method for optimizing tunneling parameters and avoiding abnormal cutter wear based on shield cutterhead vibration according to claim 4, characterized in that, The process involves inputting the hob model into the hob material database to query material structure information, constructing a damage physics model by combining temperature field distribution and wear characteristic parameters, performing causal analysis on wear morphology, and outputting wear failure attribution, including: Based on the hob model, query the hob material database to extract material structure information, including substrate type, hardness range, coating type, WC particle ratio, thermal stability threshold and fracture toughness. Based on wear characteristic parameters and material structure information, a qualitative correlation rule between wear mode and material defects is established. The impact of different wear modes on the performance of the current hob is analyzed, the material failure threshold of the hob is generated, and the wear failure attribution is output.

8. The method for optimizing tunneling parameters and avoiding abnormal cutter wear based on shield cutterhead vibration according to claim 4, characterized in that, The method, based on the wear quantification matrix and wear failure attribution, dynamically adjusts the wear judgment threshold according to the cutter position to determine and correct the wear type of the cutter, and calculates the abnormal damage level of all cutters in the shield cutterhead, including: The wear characteristic parameters of each hob are extracted from the wear quantization matrix, and wear classification rules are established based on the material failure threshold. Based on the wear classification rules, the wear type of each hob is preliminarily determined, and the wear type of the hob is output. The shield cutterhead is divided into multiple annular zones according to the radius. Based on the zone position of the cutterhead, the position sensitivity coefficient is dynamically allocated. The material failure threshold and wear classification rules of the cutterhead in different zones are corrected according to the position sensitivity coefficient, and the wear type of the cutterhead is re-determined. Using the polar coordinate system of the tunnel boring machine cutterhead as a reference, the corrected wear types are mapped to a gridded space in annular partitions. A continuous wear type heat map is generated by the color difference algorithm to show the spatial distribution of the wear types of the hobbing cutter. Based on the wear distribution and location sensitivity coefficient of the roller cutter in the comprehensive wear type heat map, the overall damage index of the shield cutterhead is calculated by a partitioned weighted aggregation algorithm, and the abnormal damage level of the shield cutterhead is determined by combining the preset threshold.

9. The method for optimizing tunneling parameters and avoiding abnormal cutter wear based on shield cutterhead vibration according to claim 8, characterized in that, The process of dividing the shield cutterhead into multiple annular zones according to radius, and dynamically allocating position sensitivity coefficients based on the zone positions of the cutterhead on the shield cutterhead, includes: Based on the structural characteristics of the shield cutterhead and the theory of tunneling mechanics, the shield cutterhead is divided into a central area, a front area and an edge area distributed in a ring, and the load characteristics of each area are associated with the area. The area is automatically marked according to the position information of the roller cutter. Based on the load characteristics of each zone, position sensitivity coefficients are assigned to different zones. The wear quantization matrix is ​​traversed, and position sensitivity coefficient labels are added to each hob and wear characteristic parameter according to the zone label.

10. The method for optimizing tunneling parameters and avoiding abnormal cutter wear based on shield cutterhead vibration according to claim 1, characterized in that, The calculation results based on the vibration signal feature values ​​are used to extract the vibration intensity range of the shield cutterhead under different abnormal damage levels, and the vibration intensity range corresponding to the lowest abnormal damage level of the shield cutterhead is taken as the target tunneling range, including: The test results of all in-situ tunneling experiments were reviewed, and the experimental group with the lowest abnormal damage level was selected as the target experimental group. The vibration signal feature values ​​corresponding to the target experimental group were selected as the vibration signal dataset. All vibration signal feature values ​​of the target experimental group were extracted, and the vibration effective value sequence and response peak sequence were separated. The lower and upper quantiles of the effective vibration value sequence and the peak response sequence are calculated using quantile statistics to form a safe boundary range of vibration intensity, which serves as the target tunneling range. The calculated target tunneling range is then integrated to generate a standardized target tunneling range instruction set.

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