A method and system for automatically controlling cutting parameters of shield machine based on geological parameters

Abstract

The present invention relates to the field of automatic control technology, specifically a method and system for automatically controlling the cutting parameters of a shield machine based on geological parameters, comprising the following steps: collecting rock physical property data including density, porosity, and compressive strength, combining cutter head speed regulation and propulsion force adjustment, measuring the stress distribution and torque of the contact point, recording the force field change, and establishing initial force field model data. In the present invention, by integrating the data of rock physical properties and the analysis of cutter head behavior, the adaptability of the shield machine under complex geological conditions is improved, and the density, porosity, and compressive strength are monitored in real time. Combined with the dynamic data of stress distribution and torque, the shield machine can build an accurate force field model based on the current geological conditions, allowing for a more detailed nonlinear analysis of the dynamic reaction force of the cutter head, accurately adjusting the cutter head speed, torque, and propulsion force, and optimizing the cutting parameters. This adaptive adjustment strategy reduces mechanical failures caused by geological variations.

Description

Technical Field

[0001] The present invention relates to the field of automatic control technology, and in particular to a method and system for automatically controlling cutting parameters of a shield machine based on geological parameters. Background Art

[0002] The field of automatic control technology involves the use of automated systems to control and adjust the parameters of machinery, equipment or processes to optimize performance and efficiency. This technology is widely used in various industrial and technological fields, such as manufacturing, transportation, medical and energy management. Its core purpose is to reduce human intervention, improve accuracy and repeatability, while ensuring operational safety and system stability. Automatic control systems usually include sensors to monitor real-time data, controllers to make decisions and adjustments, and actuators to implement control commands. These components work together to ensure that the system operates automatically according to the predetermined goals.

[0003] Among them, the automatic control method of shield machine cutting parameters refers to the use of control technology to automatically adjust the shield machine's cutting parameters during tunnel excavation, such as cutter head speed, propulsion speed, and cutter head torque. The purpose of this method is mainly to optimize cutting efficiency and machine protection in real time according to changes in geological conditions to prevent machine damage and improve engineering efficiency. By automatically adjusting these parameters, the shield machine can more effectively adapt to different geotechnical conditions, reduce downtime, reduce maintenance costs, and improve the overall quality and speed of tunnel excavation.

[0004] Existing automatic control technologies are often insufficient in tunneling applications with variable geological environments, especially in terms of response speed and accuracy under highly variable geological conditions. These systems usually rely on preset operating parameters and lack the ability to respond immediately to sudden geological changes, which may cause shield machines to experience reduced efficiency or mechanical failure when encountering abnormally hard or loose formations. Delays in data processing and real-time feedback also increase equipment wear and affect project progress and safety. For example, if the cutting parameters are not adjusted in time, the shield machine may cause excessive wear of the cutterhead when operating in hard rock formations, which not only increases maintenance costs, but may also extend the completion time of the entire project. These shortcomings highlight the limitations of traditional technologies in dealing with complex geological conditions, which need to be improved through more sophisticated data integration and analysis. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a method and system for automatically controlling the cutting parameters of a shield machine based on geological parameters.

[0006] In order to achieve the above object, the present invention adopts the following technical solution: a method for automatically controlling cutting parameters of a shield machine based on geological parameters, comprising the following steps:

[0007] S1: Collect rock physical property data including density, porosity, and compressive strength, combine cutter head speed adjustment and propulsion force adjustment, measure stress distribution and torque at contact points, record force field changes, and establish initial force field model data;

[0008] S2: Based on the initial force field model data, a nonlinear dynamic analysis is performed to analyze the dynamic reaction force of the rock on the cutterhead, analyze the relationship between the physical properties of the rock and the performance of the cutterhead, identify changes in geological conditions and abnormal conditions, and obtain dynamic response analysis results;

[0009] S3: Calculate the optimal values ​​of the cutter head speed, torque and propulsion force according to the dynamic response analysis results, and adjust the cutter head speed, torque and propulsion force based on the optimal values ​​to match the changes in the geological environment, and obtain a cutting parameter adjustment plan;

[0010] S4: Apply the cutting parameter adjustment scheme to the control system of the shield machine, adjust the operating parameters of the shield machine, monitor the cutterhead vibration and equipment feedback, update the model prediction, and generate the execution parameters of the shield machine.

[0011] As a further solution of the present invention, the step of obtaining the initial force field model data is specifically as follows:

[0012] S111: Collect rock physical property data of density, porosity and compressive strength using the formula:

[0013] ;

[0014] Calculate the stress value of each data point to generate a stress data point set;

[0015] in, represents density, represents the porosity, Represents compressive strength, represents the stress value, and It is the adjustment factor used to adjust the effect of porosity on stress;

[0016] S112: According to the rotation speed of the cutter head and propulsion The adjustment is made using the formula:

[0017] ;

[0018] Calculate the moment of the contact point and obtain a moment data point set;

[0019] in, represents the rotation speed, Represents propulsion;

[0020] Using the stress data point set and the moment data point set, the formula is used:

[0021] ;

[0022] Calculate the total moment at each contact point;

[0023] in, represents the torque, represents the total torque;

[0024] S113: Using the total torque and the recorded force field change data, the formula is:

[0025] ;

[0026] Calculate the average force field change at each time point to generate average force field change data;

[0027] in, represents the mean force field change, represents the force field change for a single data point, is the total number of data points, Indicates The total moment of the data points;

[0028] S114: Combining the average force field change data and rock physical properties, the formula is used:

[0029] ;

[0030] Optimize according to geological survey results and establish initial force field model data .

[0031] As a further solution of the present invention, the step of obtaining the dynamic response analysis result is specifically:

[0032] S211: Based on the initial force field model data, the dynamic reaction force of the rock on the cutter head is calculated using the formula:

[0033] ;

[0034] Generating Dynamic Reaction Force Results ;

[0035] in, represents the reaction force adjustment coefficient, is the intensity adjustment index, , are the adjustment coefficients of density and porosity to the reaction force, respectively;

[0036] S212: Using the dynamic reaction force, the formula:

[0037] ;

[0038] Calculate and generate cutterhead performance response results ;

[0039] in, , , is the adjustment factor, Adjust the base response level, , Adjust performance response based on dynamic reaction forces and compressive strength;

[0040] S213: Combining the cutterhead performance response and geological condition data, using the formula:

[0041] ;

[0042] Determine whether there is an abnormal situation and generate anomaly detection results ;

[0043] in, is the abnormality judgment threshold, Indicates geological condition data;

[0044] S214: Combining the abnormality detection result, the dynamic reaction force and the cutter head performance response, the formula is used:

[0045] ;

[0046] Calculate and generate dynamic response analysis results ;

[0047] in, Optimized parameters for analysis.

[0048] As a further solution of the present invention, the step of obtaining the optimal value is specifically as follows:

[0049] S311: Starting from the dynamic response analysis result, the optimal value of the cutter head rotation speed is calculated using the formula:

[0050] ;

[0051] Generate optimal speed results ;

[0052] in, represents the speed adjustment factor, is the speed normalization parameter, is the nonlinear adjustment parameter of the speed;

[0053] S312: Using the dynamic response analysis results , calculate the optimal value of torque, using the formula:

[0054] ;

[0055] Produces optimal torque results ;

[0056] in, is the torque adjustment factor, is the torque normalization parameter, is the nonlinear adjustment parameter of torque;

[0057] S313: Based on the dynamic response analysis result, the optimal value of the propulsion force is calculated using the formula:

[0058] ;

[0059] Integration generates optimal value results ;

[0060] in, is the propulsion adjustment coefficient, is the normalized parameter of propulsion force, Nonlinear adjustment parameter for propulsion force.

[0061] As a further solution of the present invention, the step of obtaining the cutting parameter adjustment solution is specifically as follows:

[0062] S321: From the optimal value result , , Starting from this, calculate the necessary amount of cutter head speed, torque and thrust adjustment using the formula:

[0063] ;

[0064] ;

[0065] ;

[0066] Generate adjustment results ;

[0067] in, Represent the adjusted target speed, torque and propulsion force respectively, is the sensitivity factor for multi-parameter adjustment;

[0068] S322: Based on the adjustment result , evaluate the impact of the adjustment, using the formula:

[0069] ;

[0070] Quantify the stability or performance changes after adjustment and generate adjustment impact assessment results ;

[0071] in, To estimate the coefficient of the adjusted effect, is the balance factor;

[0072] S323: According to the adjustment impact assessment result and the real-time data of the geological environment, the cutterhead operation optimization performance is adjusted using the formula:

[0073] ;

[0074] Adjust to match geological environment changes and generate cutting parameter adjustment plans ;

[0075] in, is the initial cutting performance score, is the adjustment factor, A smoothing factor for the adjustment effect.

[0076] As a further solution of the present invention, the steps of obtaining the execution parameters of the shield machine are specifically as follows:

[0077] S411: Apply the cutting parameter adjustment scheme to the control system of the shield machine to adjust the operating parameters, using the formula:

[0078] ;

[0079] Generate new operating parameters ;

[0080] in, Represents the new operation parameters, is the current operating parameter, , are the adjustment rate and adjustment sensitivity coefficient respectively;

[0081] S412: Based on the new operating parameters, monitor the vibration of the cutter head and the equipment feedback, using the formula:

[0082] ;

[0083] Calculate the device's response vibration and generate device feedback results ;

[0084] in, Represents real-time vibration data, , is the vibration sensitivity and adjustment factor;

[0085] S413: Update the model prediction according to the feedback result of the monitored device, using the formula:

[0086] ;

[0087] Generate TBM execution parameters ;

[0088] in, is the current model prediction value, , are the learning rate and smoothing coefficient respectively.

[0089] A shield machine cutting parameter automatic control system based on geological parameters, the shield machine cutting parameter automatic control system based on geological parameters is used to execute the above-mentioned shield machine cutting parameter automatic control method based on geological parameters, the system comprises:

[0090] The data acquisition module collects rock density, porosity, and compressive strength data, and records the stress distribution and torque changes at the cutterhead contact point, summarizes the data, reflects the current geological conditions, and constructs initial force field data;

[0091] The dynamic analysis module uses the initial force field data to analyze the dynamic reaction force of the rock on the cutterhead, identify abnormal conditions caused by changes in geological conditions, predict the interaction between rock physical properties and cutterhead performance, and generate dynamic response data;

[0092] The parameter optimization module uses the dynamic response data to calculate and set the optimal configuration of the cutter head speed, torque and propulsion force, adjusts the parameters to match the current geological environment, and generates optimized cutting parameters;

[0093] The control execution module applies the optimized cutting parameters, updates the parameters of the shield machine's control system, obtains execution feedback signals, monitors the vibration of the cutterhead and the operating status of the equipment, and provides continuous data feedback.

[0094] Compared with the prior art, the advantages and positive effects of the present invention are:

[0095] In the present invention, the adaptability of the shield machine under complex geological conditions is improved by integrating the data of rock physical properties and the analysis of cutterhead behavior. Real-time monitoring of density, porosity and compressive strength, combined with dynamic data of stress distribution and torque, enables the shield machine to build an accurate force field model based on the current geological conditions, allowing for a more detailed nonlinear analysis of the dynamic reaction force of the cutterhead, accurate adjustment of the cutterhead speed, torque and thrust, and optimization of cutting parameters. This adaptive adjustment strategy reduces mechanical failures caused by geological variations, improves operating efficiency and equipment life, while also reducing maintenance requirements and improving the speed and quality of tunnel excavation. BRIEF DESCRIPTION OF THE DRAWINGS

[0096] Figure 1 It is a schematic diagram of the workflow of the present invention;

[0097] Figure 2 This is a flow chart of the steps for obtaining the initial force field model data of the present invention;

[0098] Figure 3 A flowchart of the steps for obtaining the dynamic response analysis results of the present invention;

[0099] Figure 4 A flow chart of the steps for obtaining the optimal value of the present invention;

[0100] Figure 5 A flow chart of the steps for obtaining the cutting parameter adjustment scheme of the present invention;

[0101] Figure 6 This is a flow chart of the steps for obtaining the execution parameters of the shield machine of the present invention. DETAILED DESCRIPTION

[0102] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0103] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0104] Example 1: Please refer to Figure 1 The present invention provides a technical solution: a method for automatically controlling cutting parameters of a shield machine based on geological parameters, comprising the following steps:

[0105] S1: Collect rock physical property data including density, porosity, and compressive strength, combine cutter head speed adjustment and propulsion force adjustment, measure stress distribution and torque at contact points, record force field changes, and establish initial force field model data;

[0106] S2: Based on the initial force field model data, nonlinear dynamic analysis is used to analyze the dynamic reaction force of rock on the cutterhead, analyze the relationship between rock physical properties and cutterhead performance, identify changes and abnormal conditions in geological conditions, and obtain dynamic response analysis results;

[0107] S3: According to the results of dynamic response analysis, the optimal values ​​of the cutter head speed, torque and propulsion force are calculated, and the cutter head speed, torque and propulsion force are adjusted based on the optimal values ​​to match the changes in the geological environment and obtain the cutting parameter adjustment plan;

[0108] S4: Apply the cutting parameter adjustment scheme to the control system of the shield machine, adjust the operating parameters of the shield machine, monitor the cutterhead vibration and equipment feedback, update the model prediction, and generate the shield machine execution parameters.

[0109] The initial force field model data include density, porosity, compressive strength, stress distribution, torque, and force field changes. The dynamic response analysis results include the dynamic reaction force of rock on the cutterhead, the relationship between rock physical properties and cutterhead performance, the identification of changes in geological conditions, and the detection of abnormal conditions. The cutting parameter adjustment plan includes optimal speed, optimal torque, and optimal propulsion force. The shield machine execution parameters include the adjusted operating parameters and cutterhead vibration feedback.

[0110] See also Figure 2 , the specific steps for obtaining the initial force field model data are:

[0111] S111: Collect rock physical property data of density, porosity and compressive strength using the formula:

[0112] ;

[0113] Calculate the stress value of each data point to generate a stress data point set;

[0114] in, represents density, represents the porosity, Represents compressive strength, represents the stress value, and It is the adjustment factor used to adjust the effect of porosity on stress;

[0115] S112: According to the rotation speed of the cutter head and propulsion The adjustment is made using the formula:

[0116] ;

[0117] Calculate the moment of the contact point and obtain a moment data point set;

[0118] in, represents the rotation speed, Represents propulsion;

[0119] Using the stress data point set and the moment data point set, the formula is:

[0120] ;

[0121] Calculate the total moment at each contact point;

[0122] in, represents the torque, represents the total torque;

[0123] S113: Using the total moment and recorded force field change data, the formula is:

[0124] ;

[0125] Calculate the average force field change at each time point to generate average force field change data;

[0126] in, represents the mean force field change, represents the force field change for a single data point, is the total number of data points, Indicates The total moment of the data points;

[0127] S114: Combining the mean force field variation data and rock physical properties, the formula is used:

[0128] ;

[0129] Optimize according to geological survey results and establish initial force field model data .

[0130] Formula and derivation of step 1;

[0131] formula:

[0132] ;

[0133] Parameter details:

[0134] : Density of rock (unit: ), assuming the value is .

[0135] : The porosity of the rock (ratio), assumed to be 0.1 (10%).

[0136] : The compressive strength of rock (unit: MPa), assuming the value is .

[0137] : Porosity adjustment coefficient, used to adjust the effect of porosity on stress.

[0138] Derivation process:

[0139] ;

[0140] This stress value ( ) represents the theoretical stress value of rock under given physical properties.

[0141] Formula and derivation of step 2;

[0142] formula:

[0143] ;

[0144] Parameter details:

[0145] : Propulsion force (unit: ), assuming the value is .

[0146] : Cutter speed (unit: rpm), assuming the value is .

[0147] Derivation process:

[0148] ;

[0149] This torque ( ) represents the theoretical torque at a given thrust and speed.

[0150] formula:

[0151] ;

[0152] Derivation process:

[0153] Assuming there are three data points, then:

[0154] ;

[0155] ;

[0156] This total torque Represents the cumulative moment at multiple contact points.

[0157] Formula and derivation for step 3

[0158] formula:

[0159]

[0160] Parameter details:

[0161] : The force field change at each data point, assuming the value is (Units not specified).

[0162] : The total moment at each data point, assumed to be consistent with the previous calculation.

[0163] Derivation process:

[0164] ;

[0165] This mean force field changes Represents the average force field influence at multiple time points.

[0166] Formula and derivation of step 4;

[0167] formula:

[0168] ;

[0169] Derivation process:

[0170] ;

[0171] This initial force field model data Represents the model value calculated under given parameters and is used to evaluate the simulation results of rock physical responses in actual engineering applications.

[0172] See also Figure 3 , the specific steps for obtaining the dynamic response analysis results are:

[0173] S211: Based on the initial force field model data, the dynamic reaction force of the rock on the cutterhead is calculated using the formula:

[0174] ;

[0175] Generating Dynamic Reaction Force Results ;

[0176] in, represents the reaction force adjustment coefficient, is the intensity adjustment index, , are the adjustment coefficients of density and porosity to the reaction force, respectively;

[0177] S212: Using dynamic reaction force, use the formula:

[0178] ;

[0179] Calculate and generate cutterhead performance response results ;

[0180] in, , , is the adjustment factor, Adjust the base response level, , Adjust performance response based on dynamic reaction forces and compressive strength;

[0181] S213: Combine the cutterhead performance response and geological condition data, using the formula:

[0182] ;

[0183] Determine whether there is an abnormal situation and generate anomaly detection results ;

[0184] in, is the abnormality judgment threshold, Indicates geological condition data;

[0185] S214: Comprehensive abnormality detection results, dynamic reaction force and cutter performance response, using the formula:

[0186] ;

[0187] Calculate and generate dynamic response analysis results ;

[0188] in, Optimized parameters for analysis.

[0189] Step 1: Dynamic Reaction Force Calculation of

[0190] formula:

[0191] ;

[0192] Parameter explanation and examples:

[0193] : Reaction force adjustment coefficient, assumed to be 1.5, which is a common adjustment coefficient used to enhance the sensitivity of the model.

[0194] : Strength adjustment index, assumed to be 0.05, used to adjust the contribution of the force field model to the results.

[0195] : Initial force field model data, assumed to be , which represents a moderately strong rock force field.

[0196] : Density adjustment factor, assumed to be 0.02, is used to consider the effect of rock density on the reaction force.

[0197] : Rock density, assumed to be , which is consistent with the common rock density range.

[0198] : Porosity adjustment factor, assumed to be 0.01.

[0199] : Porosity, assumed to be 0.15, which is a typical rock porosity.

[0200] Calculation process:

[0201] Calculate the exponential part: ;

[0202] calculate Index of: .

[0203] Calculate the final .

[0204] Step 2: Cutter Performance Response Calculation of

[0205] formula:

[0206] ;

[0207] Parameter explanation and examples:

[0208] : Basic response level adjustment coefficient, assumed to be 0.3.

[0209] : Dynamic reaction force adjustment coefficient, assumed to be 0.1.

[0210] : Calculated from step 1.

[0211] : Compressive strength adjustment coefficient, assumed to be 0.01.

[0212] : Compressive strength, assumed to be , which is in line with the compressive resistance range of general rocks.

[0213] Calculation process:

[0214] calculate (Use step 1 result).

[0215] Calculate the denominator: .

[0216] calculate :

[0217] ;

[0218] Step 3: Anomaly Detection Results Calculation of

[0219] formula:

[0220] ;

[0221] Parameter explanation and examples:

[0222] : Calculated from step 2.

[0223] : Geological condition data, assumed to be .

[0224] : Abnormal judgment threshold, assumed to be .

[0225] Calculation process:

[0226] calculate .

[0227] Check if the result is greater than 1.

[0228] Step 4: Dynamic Response Analysis Results Calculation of

[0229] formula:

[0230] ;

[0231] Parameter explanation and examples:

[0232] : Optimization parameter, assumed to be 10.

[0233] Calculation process:

[0234] calculate .

[0235] calculate .

[0236] Calculate the final :

[0237] ;

[0238] See also Figure 4 , the steps to obtain the optimal value are as follows:

[0239] S311: Based on the dynamic response analysis results, the optimal value of the cutter head speed is calculated using the formula:

[0240] ;

[0241] Generate optimal speed results ;

[0242] in, represents the speed adjustment factor, is the speed normalization parameter, is the nonlinear adjustment parameter of the speed;

[0243] S312: Using Dynamic Response Analysis Results , calculate the optimal value of torque, using the formula:

[0244] ;

[0245] Produces optimal torque results ;

[0246] in, is the torque adjustment factor, is the torque normalization parameter, is the nonlinear adjustment parameter of torque;

[0247] S313: Based on the dynamic response analysis results, calculate the optimal value of the propulsion force using the formula:

[0248] ;

[0249] Integration generates optimal value results ;

[0250] in, is the propulsion adjustment coefficient, is the normalized parameter of propulsion force, Nonlinear adjustment parameter for propulsion force.

[0251] Speed Calculation of

[0252] formula:

[0253] ;

[0254] Parameter explanation:

[0255] : Speed ​​adjustment coefficient;

[0256] : Speed ​​normalization parameter;

[0257] : Nonlinear adjustment parameter of speed;

[0258] : Dynamic response analysis result, assumed to be a specific value;

[0259] Calculation procedures and examples;

[0260] Assumptions:

[0261] (Dynamic response analysis results);

[0262] (Speed ​​adjustment factor);

[0263] (speed normalization parameter);

[0264] (nonlinear adjustment parameter of speed);

[0265] Insert these values ​​according to the formula:

[0266] ;

[0267] Result interpretation:

[0268] Optimum speed It is 33.33, which means that under the given dynamic response results and parameter settings, the cutter head should be adjusted to 33.33 revolutions per minute to achieve the best performance.

[0269] Torque Calculation of

[0270] formula;

[0271] ;

[0272] Parameter explanation:

[0273] Torque adjustment factor;

[0274] : Torque normalization parameter;

[0275] : Nonlinear adjustment parameter of torque;

[0276] : Dynamic response analysis results;

[0277] Calculation procedures and examples;

[0278] Assumptions:

[0279] ;

[0280] ;

[0281] ;

[0282] ;

[0283] Insert these values ​​according to the formula:

[0284] ;

[0285] Result interpretation:

[0286] Optimum torque It is 89.4, which means that under the current geological conditions and dynamic response, the optimal torque setting of the cutter disc is 89.4 Nm to optimize cutting efficiency and equipment safety.

[0287] Propulsion Calculation of

[0288] formula:

[0289] ;

[0290] Parameter explanation:

[0291] : propulsion force adjustment coefficient;

[0292] : propulsion force normalization parameter;

[0293] : Nonlinear adjustment parameter of propulsion force;

[0294] : Dynamic response analysis results;

[0295] Calculation procedures and examples;

[0296] Assumptions:

[0297] ;

[0298] ;

[0299] ;

[0300] ;

[0301] Insert these values ​​according to the formula:

[0302] ;

[0303] Result interpretation:

[0304] Optimal propulsion It is 136.36, which indicates that in order to match the changes in the geological environment and maximize the cutting efficiency, the thrust force should be set to 136.36 Newtons.

[0305] See also Figure 5 , the specific steps for obtaining the cutting parameter adjustment plan are:

[0306] S321: From the optimal value results , Starting from this, calculate the necessary amount of cutter head speed, torque and thrust adjustment using the formula:

[0307] ;

[0308] ;

[0309] ;

[0310] Generate adjustment results ;

[0311] in, Represent the adjusted target speed, torque and propulsion force respectively, is the sensitivity factor for multi-parameter adjustment;

[0312] S322: According to the adjustment result , evaluate the impact of the adjustment, using the formula:

[0313] ;

[0314] Quantify the stability or performance changes after adjustment and generate adjustment impact assessment results ;

[0315] in, To estimate the coefficient of the adjusted effect, is the balance factor;

[0316] S323: Adjust the cutterhead operation to optimize performance based on the adjustment impact assessment results and real-time data of the geological environment, using the formula:

[0317] ;

[0318] Adjust to match geological environment changes and generate cutting parameter adjustment plans ;

[0319] in, is the initial cutting performance score, is the adjustment factor, A smoothing factor for the adjustment effect.

[0320] Step 1: Calculate the optimal speed ;

[0321] formula:

[0322] ;

[0323] Parameter explanation:

[0324] : Speed ​​adjustment coefficient, used to adjust the speed to adapt to changes in geological conditions.

[0325] : Dynamic response analysis results, indicating the comprehensive impact of geological feedback on equipment performance.

[0326] : Speed ​​normalization parameter, used to keep the speed within a reasonable range.

[0327] : Nonlinear adjustment parameter of the rotation speed, used to adjust the sensitivity of the rotation speed according to geological feedback.

[0328] Calculation example:

[0329] Assumptions .

[0330] Calculation process:

[0331] ;

[0332] Result interpretation:

[0333] Calculated optimal speed A value of 2 indicates that under the current geological feedback and the set adjustment coefficient, the equipment should adjust its speed to 2 to best adapt to the geological conditions.

[0334] Step 2: Calculate the optimal torque ;

[0335] formula:

[0336] ;

[0337] Parameter explanation:

[0338] : Torque adjustment coefficient.

[0339] : Torque normalization parameter.

[0340] Nonlinear adjustment parameter for torque.

[0341] Calculation example:

[0342] Assumptions .

[0343] Calculation process:

[0344] ;

[0345] Result interpretation:

[0346] Optimum torque The calculation is 17.89, which is to adjust the torque to maintain equipment performance under given geological conditions and feedback.

[0347] Step 3: Calculate the optimal propulsion force ;

[0348] formula:

[0349] ;

[0350] Parameter explanation:

[0351] : Propulsion force adjustment coefficient.

[0352] : Normalized parameter of propulsion force.

[0353] : Nonlinear adjustment parameter of propulsion force.

[0354] Calculation example:

[0355] Assumptions .

[0356] Calculation process:

[0357] ;

[0358] Result interpretation:

[0359] Calculated optimal propulsion force It is 114285.71, which indicates that under the current dynamic response of the equipment and the set adjustment parameters, the propulsion force needs to be adjusted to this value to optimize the adaptation of the equipment performance to the geological conditions.

[0360] See also Figure 6 , the specific steps for obtaining the execution parameters of the shield machine are:

[0361] S411: Apply the cutting parameter adjustment scheme to the control system of the shield machine to adjust the operating parameters, using the formula:

[0362] ;

[0363] Generate new operating parameters ;

[0364] in, Represents the new operation parameters, is the current operating parameter, , are the adjustment rate and adjustment sensitivity coefficient respectively;

[0365] S412: Based on the new operating parameters, monitor the cutter vibration and equipment feedback, using the formula:

[0366] ;

[0367] Calculate the device's response vibration and generate device feedback results ;

[0368] in, Represents real-time vibration data, , is the vibration sensitivity and adjustment factor;

[0369] S413: Update the model prediction based on the feedback from the monitored equipment, using the formula:

[0370] ;

[0371] Generate TBM execution parameters ;

[0372] in, is the current model prediction value, , are the learning rate and smoothing coefficient respectively.

[0373] Step 1: Formula for adjusting operating parameters;

[0374] formula:

[0375] ;

[0376] Parameter details:

[0377] : Current operating parameters, assumed to be 100 units.

[0378] : The target parameter obtained from the cutting parameter adjustment plan, assumed to be 120 units.

[0379] : Adjustment rate, assuming it is 0.5, which indicates the speed or step size of the adjustment.

[0380] : Adjustment sensitivity coefficient, assumed to be 0.1, indicating the sensitivity of the adjustment.

[0381] Calculation process:

[0382] Calculate the difference between the target parameter and the current parameter: .

[0383] Calculate the denominator part of the adjustment: .

[0384] Calculate the adjustment step size: .

[0385] Apply adjustment rate: Adjust step size .

[0386] Calculate new operating parameters: Adjustment results .

[0387] Result interpretation:

[0388] The resulting new operating parameters It is 103.33, which indicates that at a given adjustment rate and sensitivity, the system approaches the target parameters after one adjustment.

[0389] Step 2: Formula for monitoring device feedback;

[0390] formula:

[0391] ;

[0392] Parameter details:

[0393] : New operating parameter obtained from step 1, 103.33.

[0394] : Real-time data obtained from the vibration sensor, assumed to be 95 units.

[0395] : Vibration sensitivity coefficient, assumed to be 2.

[0396] : Adjustment coefficient, assumed to be 0.05.

[0397] Calculation process:

[0398] Calculate the square of the difference in vibration data: .

[0399] Weighted vibration raw data: .

[0400] Compute the square root of a sum of squares: .

[0401] Apply vibration sensitivity: .

[0402] Result interpretation:

[0403] The vibration value of the equipment feedback It is 17.32, which indicates the response level of the current adjusted system.

[0404] Step 3: Update the model prediction formula;

[0405] formula:

[0406] ;

[0407] Parameter details:

[0408] : The current model prediction value, assumed to be 50 units.

[0409] : The device feedback value obtained from step 2, 17.32.

[0410] : Learning rate, assumed to be 0.3.

[0411] : Smoothing coefficient, assumed to be 0.2.

[0412] Calculation process:

[0413] Calculate the difference between the feedback and the current prediction: .

[0414] Calculate the smoothing adjusted denominator: .

[0415] Calculate the adjustment: .

[0416] Apply learning rate: Adjustment amount .

[0417] Update the model predictions: Adjustment results .

[0418] Result interpretation:

[0419] Updated model predictions It is 48.7, which reflects the current status of the equipment and its performance after adjustment.

[0420] A shield machine cutting parameter automatic control system based on geological parameters, the shield machine cutting parameter automatic control system based on geological parameters is used to execute the above-mentioned shield machine cutting parameter automatic control method based on geological parameters, the system includes:

[0421] The data acquisition module collects rock density, porosity, and compressive strength data, and records the stress distribution and torque changes at the cutterhead contact point, summarizes the data, reflects the current geological conditions, and constructs initial force field data;

[0422] The dynamic analysis module uses the initial force field data to analyze the dynamic reaction force of the rock on the cutterhead, identify abnormal conditions caused by changes in geological conditions, predict the interaction between rock physical properties and cutterhead performance, and generate dynamic response data;

[0423] The parameter optimization module uses dynamic response data to calculate and set the optimal configuration of cutter head speed, torque and thrust, adjusts the parameters to match the current geological environment, and generates optimized cutting parameters;

[0424] The control execution module optimizes cutting parameters, updates the parameters of the shield machine's control system, obtains execution feedback signals, monitors the vibration of the cutterhead and the operating status of the equipment, and provides continuous data feedback.

[0425] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A method for automatically controlling cutting parameters of a shield machine based on geological parameters, characterized in that: The following steps are involved: Collect rock physical property data including density, porosity, and compressive strength, combine cutter head speed adjustment and propulsion force adjustment, measure stress distribution and torque at contact points, record force field changes, and establish initial force field model data; The steps for obtaining the initial force field model data are specifically as follows: Collect rock physical property data of density, porosity, and compressive strength using the formula: ； Calculate the stress value of each data point to generate a stress data point set; in, represents density, represents the porosity, Represents compressive strength, represents the stress value, and the 0.05 in the denominator is the adjustment coefficient used to adjust the effect of porosity on stress; According to the blade speed and propulsion The adjustment is made using the formula: ； Calculate the moment of the contact point and obtain a moment data point set; in, represents the rotation speed, Represents propulsion; Using the stress data point set and the moment data point set, the formula is used: ； Calculate the total moment at each contact point; in, represents the torque, represents the total torque; Using the total moment and the recorded force field change data, the formula is used: ； Calculate the average force field change at each time point to generate average force field change data; in, represents the mean force field change, represents the force field change for a single data point, is the total number of data points, Indicates The total moment of the data points; Combining the average force field change data and rock physical properties, the formula is adopted: ； Optimize according to geological survey results and establish initial force field model data ; Based on the initial force field model data, a nonlinear dynamic analysis is used to analyze the dynamic reaction force of the rock on the cutterhead, analyze the relationship between the physical properties of the rock and the performance of the cutterhead, identify changes in geological conditions and abnormal conditions, and obtain dynamic response analysis results; The steps for obtaining the dynamic response analysis results are specifically as follows: Based on the initial force field model data, the dynamic reaction force of the rock on the cutterhead is calculated using the formula: ； Generating Dynamic Reaction Force Results ; in, represents the reaction force adjustment coefficient, is the intensity adjustment index, , are the adjustment coefficients of density and porosity to the reaction force, respectively; Using the dynamic reaction force, the formula is used: ； Calculate and generate cutterhead performance response results ; in, , , is the adjustment factor, Adjust the base response level, , Adjust performance response based on dynamic reaction forces and compressive strength; Combining the cutterhead performance response and rock physical properties, the formula is used: ； Determine whether there is an abnormal situation and generate anomaly detection results ; in, is the abnormality judgment threshold, Indicates rock physical properties; Combining the abnormality detection result, the dynamic reaction force and the cutter head performance response, the formula is adopted: ； Calculate and generate dynamic response analysis results ; in, Optimization parameters for analysis; According to the dynamic response analysis results, the optimal values ​​of the cutter head speed, torque and propulsion force are calculated, and the cutter head speed, torque and propulsion force are adjusted based on the optimal values ​​to match the changes in the geological environment, thereby obtaining a cutting parameter adjustment plan; The steps for obtaining the optimal value are specifically as follows: Based on the dynamic response analysis results, the optimal value of the cutter head speed is calculated using the formula: ； Generate optimal speed results ; in, represents the speed adjustment factor, is the speed normalization parameter, is the nonlinear adjustment parameter of the speed; Using the dynamic response analysis results , calculate the optimal value of torque, using the formula: ； Produces optimal torque results ; in, is the torque adjustment factor, is the torque normalization parameter, is the nonlinear adjustment parameter of torque; Based on the dynamic response analysis results, the optimal value of the propulsion force is calculated using the formula: ； The optimal value of the combined thrust generation results ; in, is the propulsion adjustment coefficient, is the normalized parameter of propulsion force, Nonlinear adjustment parameters for propulsion force; The steps for obtaining the cutting parameter adjustment scheme are specifically as follows: The optimal value results from , , Starting from this, calculate the necessary amount of cutter head speed, torque and thrust adjustment using the formula: ； ； ； Generate adjustment results , , ; in, , , They represent the adjusted target speed, torque and propulsion force respectively; According to the adjustment result , , , evaluate the impact of the adjustment, using the formula: ； Quantify the stability or performance changes after adjustment and generate adjustment impact assessment results ; in, To estimate the coefficient of the adjusted effect, is the balance factor; According to the adjustment impact assessment results and the real-time data of the geological environment, the cutterhead operation is adjusted to optimize performance, using the formula: ； Adjust to match geological environment changes and generate cutting parameter adjustment plans ; in, is the initial cutting performance score, is the adjustment factor, is the smoothing factor for the adjustment effect; Applying the cutting parameter adjustment scheme to the control system of the shield machine, adjusting the operating parameters of the shield machine, monitoring the vibration of the cutterhead and the feedback of the equipment, updating the model prediction, and generating the execution parameters of the shield machine; The steps for obtaining the execution parameters of the shield machine are specifically as follows: The cutting parameter adjustment scheme is applied to the control system of the shield machine to adjust the operating parameters, using the formula: ； Generate new operating parameters ; in, Represents the new operation parameters, is the current operating parameter, , are the adjustment rate and adjustment sensitivity coefficient respectively; Based on the new operating parameters, monitoring cutterhead vibration and equipment feedback, the formula is used: ； Calculate the device's response vibration and generate device feedback results ; in, Represents real-time vibration data, , is the vibration sensitivity and adjustment factor; According to the feedback results of the monitored equipment, the model prediction is updated using the formula: ； Generate TBM execution parameters ; in, is the current model prediction value, , are the learning rate and smoothing coefficient respectively.

2. An automatic control system for shield machine cutting parameters based on geological parameters, characterized in that: According to the method for automatically controlling shield machine cutting parameters based on geological parameters according to claim 1, the system comprises: The data acquisition module collects rock density, porosity, and compressive strength data, and records the stress distribution and torque changes at the cutterhead contact point, summarizes the data, reflects the current geological conditions, and constructs initial force field data; The dynamic analysis module uses the initial force field data to analyze the dynamic reaction force of the rock on the cutterhead, identify abnormal conditions caused by changes in geological conditions, predict the interaction between rock physical properties and cutterhead performance, and generate dynamic response data; The parameter optimization module uses the dynamic response data to calculate and set the optimal configuration of the cutter head speed, torque and propulsion force, adjusts the parameters to match the current geological environment, and generates optimized cutting parameters; The control execution module applies the optimized cutting parameters, updates the parameters of the shield machine's control system, obtains execution feedback signals, monitors the vibration of the cutterhead and the operating status of the equipment, and provides continuous data feedback.

Images