Intelligent positioning method for TBM disassembly supporting tool

Abstract

The invention discloses an intelligent positioning method for a TBM disassembly supporting tool, and the method comprises the steps: installing laser ranging sensors at four corners of a supporting tool frame, forming space projection mapping with a shield body four-quadrant reflection target, collecting target distance data, comparing the target distance data with a pre-stored shield body theoretical axis model, and calculating a deviation value; the controller converts the axial deviation into a hydraulic cylinder stroke instruction to drive the four supporting hydraulic cylinders to conduct cooperative adjustment, when the pressure sensor monitors that the pressure difference exceeds 0.8 MPa, the compensation amount is recalculated, and historical ovality data is called to calculate an inclination angle correction value; the double-inclination-angle adjusting oil cylinder is controlled for compensation and secondary verification, and if the radial deviation range is exceeded, adjustment is returned; after three times of cross validation are completed, a hydraulic cylinder self-locking mechanism and a positioning pin are locked, positioning parameters are encrypted and stored, and a completion signal is triggered. The method is used for improving the positioning precision and efficiency of shield tunneling machine disassembling operation, effectively reduces the contact damage risk between the supporting tool and the shield body, and is particularly suitable for large shield tunneling machine disassembling engineering with the diameter larger than 8 m.

Description

Technical Field

[0001] The present invention relates to the technical field of tunnel engineering construction equipment, and more specifically, to an intelligent positioning method for TBM dismantling support tooling. Background Art

[0002] In the dismantling operation of tunnel engineering equipment, the existing support tooling positioning method has the dual defects of insufficient axial alignment accuracy and poor radial adaptability.

[0003] Traditional mechanical positioning devices rely on manual experience to adjust the hydraulic support points. It is difficult to overcome the problem of uneven contact surface pressure caused by the elliptical deformation of the shield due to long-term use, and there is a lack of multi-dimensional verification mechanism after positioning, and the secondary positioning rate is more than 30%; at the same time, there is a lack of effective integration means between the theoretical axis model of the shield and the actual axis deviation under dynamic conditions. During the positioning process, the cumulative error caused by the overshoot of the hydraulic system and the elastic deformation of the frame often leads to local interference between the support tooling and the shield, resulting in frequent contact surface damage accidents. This phenomenon is particularly evident in the dismantling operation of shield machines with a diameter of more than 8 meters. The fundamental reason is that the existing technology has failed to establish a collaborative control mechanism for real-time data closed-loop feedback and multi-physical field coupling compensation. Summary of the invention

[0004] An object of the present invention is to provide a method for intelligently positioning a TBM dismantling support tool, comprising: Four laser distance measuring sensors are installed at the four corners of the supporting tooling frame, with their laser directions parallel to the tunnel axis and the installation plane coincident with the geometric center plane of the supporting tooling frame. Four laser reflection targets that form spatial projection mapping with the sensors are fixed at the symmetrical points of the four quadrants of the shield; The distance data of the four targets obtained by the laser ranging sensor are compared with the pre-stored theoretical axis model of the shield body to calculate the axial deviation and radial offset component of each ranging channel; The controller converts the axial deviation into a hydraulic cylinder stroke command, and drives the four supporting hydraulic cylinders to adjust in coordination. During the adjustment, the contact pressure is monitored by the pressure sensor at the end of the supporting hydraulic cylinder. When the adjacent pressure difference exceeds 0.8 MPa, the adjustment is suspended and the compensation amount is recalculated. When the values of the four pressure sensors reach 7±0.3 MPa synchronously and remain stable for 5 seconds, the shield's historical ovality data and the current radial offset component are called to calculate the inclination correction value. The dual tilt adjustment cylinders located in the middle of the support tooling frame are controlled to make step compensation according to the tilt correction value. The laser ranging data is verified twice after each step of 0.3 mm. If the radial offset extreme error exceeds 1.2 mm, the system returns to the hydraulic cylinder adjustment stage. After completing the inclination compensation, start the four laser rangefinder sensors alternately for three cross-verifications. When the maximum axial deviation ≤ 0.5 mm and the maximum radial offset ≤ 0.8 mm, lock the self-locking mechanism of the hydraulic cylinder and the positioning pin of the inclination adjustment cylinder. Encrypt the verified positioning parameters and write them into the non-volatile memory of the tooling control system, and trigger the audible and visual completion signal.

[0005] Preferably, the method for constructing the theoretical axis model of the shield body includes: In the shutdown state of the shield body, collect the center coordinates of the flange plates at both ends of the shield body and the ovality data of the middle three cross-sections through a laser tracker. With the connection line of the head and tail centers as the reference axis, generate a theoretical axis model including a three-dimensional coordinate system based on the least squares method.

[0006] Preferably, the coordinated adjustment of the support hydraulic cylinders includes a dynamic load distribution step, which includes: Set the support hydraulic cylinder with the largest axial deviation as the main adjustment cylinder. The other three support hydraulic cylinders generate compensation coefficients according to the deviation ratio of their corresponding ranging channels. For every 1 mm of travel of the main adjustment cylinder, the slave adjustment cylinders synchronously perform a follow-up compensation of 0.6 - 0.8 times the travel.

[0007] Preferably, the method for updating the historical ovality data of the shield body includes: After each positioning is completed, control the support tooling frame to move axially along the shield body to three preset detection positions. Start the laser rangefinder sensor for circumferential scanning at each detection position, and update the cross-sectional ovality data obtained by scanning to the historical database according to the time stamp.

[0008] Preferably, the dynamic verification of the theoretical axis model includes: At the start of each positioning, reverse-scan the profiles of the head and tail flange plates of the shield body through four laser rangefinder sensors, extract the real-time center coordinates and perform deviation analysis with the theoretical center coordinates in the model. If the axial deviation > 1.5 mm or the radial offset > 2 mm, trigger the model reconstruction program: re-fit the reference axis based on the real-time center coordinates and the latest updated middle cross-sectional ovality data to generate an updated theoretical axis model, and mark the original model as a historical version for storage.

[0009] Preferably, the three cross-verifications adopt a time-division multiplexing verification mode, which includes: For the first verification, only the first and third laser rangefinder sensors are enabled. For the second verification, the second and fourth laser rangefinder sensors are enabled. For the third verification, all four sensors are enabled for full-channel data fusion verification. If any verification stage fails to meet the standard, trigger the calibration program for the corresponding sensor channel.

[0010] Preferably, the locking process of the hydraulic cylinder self-locking mechanism includes pre-tightening force detection, which includes: Apply a sinusoidal alternating test load with a frequency of 3 Hz and an amplitude of 10% of the rated pressure to the four hydraulic cylinders through the servo valve. After 6 cycles, count the pressure fluctuation data of the last three cycles. If the fluctuation difference between any two diagonal pressure sensors > 8% of the rated value or the fluctuation phase difference > 30°, trigger the unlocking mechanism and return to the hydraulic cylinder adjustment stage.

[0011] Preferably, the non-volatile memory adopts a data integrity protection mechanism, including: When encrypting and storing the positioning parameters, generate a digital fingerprint synchronously. Before each call of the positioning parameters, verify the matching of the digital fingerprint and the stored data first. If the verification fails, call the backup positioning parameters of the adjacent workstations for data repair.

[0012] Preferably, when the cross-sectional ovality data is updated, the credibility verification is performed synchronously, which includes: When the deviation between the newly obtained ovality data and the average value of the historical data > 15%, trigger the shield surface anomaly detection program, control the support tooling frame to move along the axis to the adjacent detection position for three repeated scans, and use the middle value of the three scan results as the effective update data.

[0013] Preferably, the model reconstruction program further includes a deformation pre-compensation step: Before re-fitting the reference axis, dynamically correct the theoretical axis model according to the material elastic modulus parameter of the support tooling frame and the real-time collected ambient temperature data. Real-time monitor the deformation compensation amount through the strain gauge array attached to the frame surface, and pre-inject the compensation amount into the initial stroke command of the main adjustment cylinder. The compensation direction is opposite to the frame deformation direction.

[0014] The present invention has at least the following beneficial effects: First, through the real-time comparison between the laser distance sensor and the theoretical axis model, combined with the dynamic cooperative adjustment of the four hydraulic cylinders and the inclination compensation mechanism, the present invention realizes high-precision positioning with an axial deviation ≤ 0.5 mm and a radial offset ≤ 0.8 mm, significantly reduces the secondary positioning rate, shortens the adjustment time, and adapts to the complex deformation conditions of large-diameter shields.

[0015] Second, through the double guarantee of the pressure difference threshold and the dynamic detection of the pre-tightening force of the self-locking mechanism, the present invention effectively avoids the risks of local overload and false locking. The ovality data credibility verification and the model dynamic reconstruction mechanism ensure the pressure uniformity of the contact surface between the support tooling and the shield.

[0016] Second, through the integration of multi-sensor data fusion (three - time cross - validation), deformation pre - compensation (strain gauge array + temperature correction), and encrypted storage technology, the present invention forms a closed - loop system of real - time feedback - compensation - verification, enhancing the system's resistance to interferences such as vibration and temperature drift, and is applicable to the tunnel construction environment with high dust and strong electromagnetic interference.

[0017] Other advantages, objectives, and features of the present invention will be partially reflected by the following description and partially understood by those skilled in the art through the research and practice of the present invention. Detailed implementation manners

[0018] The following further detailed description of the present invention is provided to enable those skilled in the art to implement it with reference to the text of the specification.

[0019] It should be noted that, unless otherwise specified, the experimental methods described in the following implementation schemes are all conventional methods, and the reagents and materials, unless otherwise specified, can all be obtained from commercial channels; in the description of the present invention, the orientation or positional relationship indicated by the terms is based on the shown orientation or positional relationship, and is 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 a limitation to the present invention.

[0020] The present invention provides an intelligent positioning method for the TBM disassembly support tooling, including: Install four laser range - finding sensors at the four corners of the support tooling frame. The laser directions are parallel to the tunnel axis, and the installation planes coincide with the geometric center plane of the support tooling frame. Fix four laser reflection targets at the symmetric points of the four quadrants of the shield body to form a spatial projection mapping with the sensors; Compare the four target distance data obtained by the laser range - finding sensors with the pre - stored theoretical axis model of the shield body, and calculate the axial deviation amount and radial offset component of each ranging channel; The controller converts the axial deviation amount into a hydraulic cylinder stroke command to drive the four support hydraulic cylinders to adjust collaboratively. During the adjustment, monitor the contact pressure through the pressure sensors at the ends of the support hydraulic cylinders. When the adjacent pressure difference exceeds 0.8 MPa, pause the adjustment and recalculate the compensation amount. When the values of the four pressure sensors reach 7 ± 0.3 MPa synchronously and are stable for 5 seconds, call the historical ellipticity data of the shield body and calculate the inclination correction value with the current radial offset component; Control the double - inclination adjustment oil cylinder installed in the middle of the support tooling frame to step - by - step compensate according to the inclination correction value. After each step of 0.3 mm, verify the laser range - finding data for the second time. If the radial offset range difference exceeds 1.2 mm, return to the hydraulic cylinder adjustment stage; After completing the inclination compensation, start the four laser ranging sensors alternately for three cross-verifications. When the maximum axial deviation ≤ 0.5 mm and the maximum radial deviation ≤ 0.8 mm, lock the self-locking mechanism of the hydraulic cylinder and the positioning pin of the inclination adjustment cylinder; Encrypt and write the verified positioning parameters into the non-volatile memory of the tooling control system and trigger the audible and visual completion signal.

[0021] In the above technical solution, the main structure of the support tooling frame can be welded and formed with low-alloy high-strength steel. The laser ranging sensor can be an industrial-grade two-dimensional laser displacement meter, installed on the L-shaped mounting bases welded at the four corners of the support tooling frame. The laser reflection target can be a high-reflectivity ceramic composite target plate, fixed on the machined positioning reference surface on the shield surface by high-strength bolts. The controller can be a programmable logic controller with an EtherCAT bus, with a built-in multi-axis motion control module, connected to the hydraulic servo system through the field bus; When installing laser ranging sensors at the four corners of the supporting tooling frame, suitable mounting holes can be opened at the four top corners of the frame, and the sensors can be fixed therein by bolts to ensure that the laser direction is parallel to the tunnel axis and the mounting plane coincides with the geometric center plane of the supporting tooling frame; laser reflection targets are fixed at the symmetrical points of the four quadrants of the shield body, and the targets can be adhered to the surface of the shield body with a strong adhesive, or the targets can be firmly mounted at the corresponding positions of the shield body by welding a small fixing frame, and the target distance data obtained by the laser ranging sensor is transmitted to the controller. The controller can be an industrial-grade programmable logic controller with data processing and command output functions, which can compare the received data with the pre-stored theoretical axis model of the shield body, and calculate the axial deviation and radial offset component of each ranging channel. After the controller calculates the axial deviation, it converts it into a hydraulic cylinder stroke command to drive the four supporting hydraulic cylinders to adjust in coordination. The supporting hydraulic cylinder can use a servo hydraulic cylinder with a high-precision displacement control function. A pressure sensor is installed at the end of the hydraulic cylinder. The pressure sensor can use a high-precision strain gauge pressure sensor to monitor the contact pressure. When the adjacent pressure difference exceeds 0.8 MPa, the controller suspends adjustment and recalculates the compensation amount. After a large number of simulation experiments and actual engineering tests, the pressure difference threshold of 0.8 MPa can effectively avoid damage to the shield or supporting tooling due to excessive local pressure while ensuring the adjustment efficiency. When the pressure difference exceeds this threshold, the uneven force on the supporting structure may affect the positioning accuracy and equipment safety, so the compensation amount needs to be recalculated. When the values of the four pressure sensors reach 7±0.3 MPa synchronously and remain stable for 5 seconds, the controller calls the historical ovality data of the shield and the current radial offset component to calculate the inclination correction value.Control the double-inclination adjustment oil cylinder located in the middle of the support tooling frame to perform step-by-step compensation according to the inclination correction value. The double-inclination adjustment oil cylinder can be an electric push-rod type oil cylinder that can achieve precise angle adjustment. After each step of 0.3 mm, obtain data again through the laser distance sensor for secondary verification. If the radial offset range exceeds 1.2 mm, return to the hydraulic cylinder adjustment stage. After completing the inclination compensation, alternately start the four laser distance sensors for three-way cross-verification. When the maximum axial deviation ≤ 0.5 mm and the maximum radial offset ≤ 0.8 mm, lock the self-locking mechanism of the hydraulic cylinder and the positioning pin of the inclination adjustment oil cylinder. The self-locking mechanism can be a mechanical plug-type self-locking device, and the positioning pin can be a cylindrical pin. Encrypt and write the verified positioning parameters into the non-volatile memory of the tooling control system. The non-volatile memory can be a flash memory chip. After writing is completed, trigger the sound and light completion signal. The sound and light device can be a combination of an ordinary buzzer and an LED indicator light; through multi-sensor data fusion and closed-loop control, the technical indicators of axial alignment accuracy ≤ 0.5 mm and radial adaptation deviation ≤ 0.8 mm are achieved, effectively reducing the incidence rate of contact surface damage accidents. The setting of the pressure difference threshold balances the adjustment efficiency and the system stability requirements. The three-step verification mechanism controls the secondary positioning rate below 5%. The double-inclination compensation mechanism solves the local interference problem caused by the elliptical deformation of the large-diameter shield body. The mechanical self-locking device ensures the structural rigidity after positioning.

[0022] In another technical solution, the method for constructing the theoretical axis model of the shield body includes: In the shield body shutdown state, the center coordinates of the flange plates at both ends of the shield body and the ovality data of the three middle cross-sections are collected by a laser tracker. Taking the line connecting the center points at both ends as the reference axis, a theoretical axis model including a three-dimensional coordinate system is generated by fitting based on the least squares method. Specifically, for the construction of the theoretical axis model of the shield body, an industrial-grade laser tracker can be used to complete data collection. In the shield body shutdown state, the operator can arrange five measurement cross-sections along the axial direction of the shield body. The two cross-sections at both ends are respectively aligned with the machined end faces of the front and rear flange plates of the shield body, and the three middle cross-sections are distributed in the middle of the shield body according to the equal-spacing principle. Eight equally divided measurement points can be arranged on each cross-section, and three-dimensional coordinate data is obtained through the contact measurement of the target ball of the laser tracker. During data collection, the center coordinates of the end faces of the front and rear flange plates can be measured preferentially, and the center position is determined by the three-point circle fitting method. The ovality data of the three middle cross-sections can be obtained by the polar coordinate measurement method, and the measurement points are arranged at an interval of 45-degree angles. The measurement data can be uploaded to the modeling workstation in real time through a wireless transmission module. The modeling software can select engineering analysis software with point cloud processing functions. The generation of the theoretical axis model can adopt a spatial straight line fitting algorithm. Taking the line connecting the center points of the front and rear flanges as the initial reference line, the ovality distribution weight of the middle cross-section is optimized by the least squares method, and finally a digital model including the X / Y / Z three-direction coordinate offsets is generated. During model verification, the theoretical axis can be mapped to the actual shield body surface by the reverse projection method, and the deviation between the actual coordinates and the theoretical coordinates of the key points is re-measured by the laser tracker. When the axial projection deviation exceeds 0.15 mm or the radial ovality deviation exceeds 0.3 mm, the data can be re-collected and the model parameters can be iteratively optimized. The completed and verified theoretical axis model can be stored as a STEP format file and imported into the tooling control system after being encrypted by a digital signature. This modeling method controls the axis fitting error within the range of ±0.1 mm, and the established model can be compatible with the dynamic deformation characteristics during the actual operation of the shield body. This axis model construction method improves the matching degree between the theoretical model and the actual working conditions to more than 98% through multi-cross-section data fusion and weighted optimization. The layout design of the five-point measurement cross-section effectively captures the axial deformation characteristics of the shield body. The application of the least squares method eliminates the influence of local measurement errors on the overall axis. The deviation threshold setting in the model verification stage ensures the safety of engineering applications, and the digital signature encryption guarantees the integrity of the model data. This method provides a high-precision reference for subsequent intelligent positioning. Especially when dealing with a shield body with a diameter exceeding 8 meters, it can effectively compensate for the axis offset caused by gravity deformation.

[0023] In another technical solution, the coordinated adjustment of the support hydraulic cylinders includes a dynamic load distribution step, which includes: The support hydraulic cylinder with the largest axial deviation is set as the main adjustment cylinder. The other three support hydraulic cylinders generate compensation coefficients according to the deviation ratio of their corresponding ranging channels. For every 1 mm of travel of the main adjustment cylinder, the slave adjustment cylinders perform a follow-up compensation of 0.6 - 0.8 times the travel synchronously. Specifically, the dynamic load distribution step can be achieved through a multi-axis motion controller, which can select a servo control system with EtherCAT bus communication function. The main adjustment cylinder can select a servo hydraulic cylinder with an absolute encoder. The slave adjustment cylinders can be equipped with proportional flow valves to achieve accurate travel following. The compensation coefficient calculation module can be integrated into the motion planning algorithm of the controller to receive the laser ranging deviation data corresponding to each hydraulic cylinder in real time. The piston rod of the support hydraulic cylinder can be made of alloy steel and surface-hardened by chromium plating. The measuring diaphragm of the pressure sensor can be made of stainless steel. The execution period of the dynamic compensation algorithm can be set to 10 ms. The displacement command of the main adjustment cylinder is distributed to the slave adjustment cylinders in real time through the CANopen protocol. The main adjustment cylinder is determined by comparing the axial deviations of the four ranging channels in real time. When the maximum deviation ≥ 0.3 mm, the dynamic load distribution mode is triggered, and the compensation coefficient is automatically generated according to the deviation ratio. The specific calculation formula is K i =(Δ i / ΣΔ)×0.7±0.1, where Δ i is the deviation of each slave cylinder. The follow-up compensation travel range is limited to 0.6 - 0.8 times the displacement of the master cylinder. When the pressure difference between adjacent hydraulic cylinders exceeds 0.8 MPa, it automatically switches to the independent adjustment mode. The displacement synchronization accuracy is ensured by closed-loop PID control, and the position following error threshold is set to ±0.05 mm. Through the master-slave collaborative adjustment mechanism, this method effectively balances the load distribution at each support point, reduces the local stress concentration coefficient to below 1.2. The setting of the dynamic compensation coefficient range of 0.6 - 0.8 takes into account both the adjustment efficiency and system stability. The dual judgment mechanism of the pressure difference threshold avoids over-compensation. The multi-axis synchronous control technology shortens the collaborative positioning time of the hydraulic cylinders and improves the pressure uniformity of the support surface at the same time. This implementation method is particularly suitable for complex working conditions with foundation settlement or shield eccentric load, and can effectively prevent structural damage caused by single-point overload.

[0024] In another technical solution, the method for updating the historical ellipticity data of the shield body includes: After each positioning is completed, control the support tooling frame to move axially along the shield body by three preset detection positions. At each detection position, start the laser ranging sensor for circumferential scanning, and update the cross-sectional ovality data obtained by scanning to the historical database according to the time stamp. Specifically, the update of the shield body's historical ovality data can be achieved by configuring an axial movement mechanism, which can be a ball screw slide driven by a servo motor. The spacing of the three preset detection positions can be set to 1 / 4 of the total length of the shield body, and the specific interval distance is adjusted according to the shield body diameter. For an 8-meter diameter shield body, the spacing can be set to 500 ± 5 mm. The circumferential scanning mechanism can be a rotating platform with a harmonic reducer, and the rotation angle resolution is ≤ 0.01°. The laser ranging sensor can be upgraded to a 2D laser scanner, installed on a 360° rotatable cloud platform, and the scanning frequency is ≥ 100 Hz. The data storage system can be an industrial-grade time series database, and the storage period is set to automatically back up every work shift. The ovality calculation module can be integrated with an edge computing gateway, and the minimum zone method is used to evaluate the ovality error. When the historical database is updated, the moving average value of the recent five measurement data can be compared. When the deviation exceeds 0.5 mm, data validity verification is triggered. The axial movement guide rails of the support tooling frame can be arranged in parallel on both sides of the shield body axis, and the guide rail surface can be sprayed with a tungsten carbide wear-resistant coating. The detection position positioning uses an absolute grating scale for feedback, and the in-place repeatability accuracy is controlled within ± 0.1 mm. During circumferential scanning, the laser scanner performs a full-circle measurement at an angular velocity of 5° / s, and a set of cross-sectional profile data is collected at every 0.5° interval. The updated ovality data is stored in the format of "time stamp - cross-sectional position - polar coordinate data", and at the same time, the ambient temperature and hydraulic system pressure parameters are recorded. This method improves the update frequency of the ovality data to once per operation cycle through multi-section dynamic detection. The arrangement of the three detection positions covers the key deformation areas of the shield body, and the evaluation by the minimum zone method ensures that the ovality calculation complies with ISO standards. The coordinated control of the axial movement mechanism and the rotary scanning shortens the single full-circle measurement time to within 3 minutes. The historical data comparison mechanism effectively identifies abnormal measurement values and avoids incorrect data entry into the database. The ovality evolution model established by this implementation method can provide deformation trend prediction for subsequent positioning, especially when dealing with long-term service shield bodies, and can effectively compensate for geometric deviations caused by material creep.

[0025] In another technical solution, the dynamic verification of the theoretical axis model includes: At each positioning startup, the four laser ranging sensors are used to scan the profiles of the head and tail flange plates of the shield body in reverse, extract the real-time center coordinates, and perform deviation analysis with the theoretical center coordinates in the model. If the axial deviation > 1.5 mm or the radial offset > 2 mm, the model reconstruction program is triggered: based on the real-time center coordinates and the latest updated ellipticity data of the middle section, a new reference axis is refitted to generate an updated theoretical axis model, and the original model is marked as a historical version for storage; specifically, the dynamic verification of the theoretical axis model can be achieved by configuring a dedicated scanning program. The laser ranging sensors can be upgraded to two-dimensional laser profilers with rotating pan-tilt units, the scanning angular resolution ≤ 0.1°, and the flange plate profile scanning adopts a spiral path planning. Starting from the bolt holes on the flange end face, radial involute scanning is performed at a 0.5 mm interval. The circle fitting method of Random Sample Consensus (RANSAC) can be selected as the algorithm for extracting the center coordinates. This is an algorithm that filters out the optimal model parameters from a dataset containing outliers through random sampling and model fitting. In this solution, it is used to accurately extract the center coordinates from the flange plate profile scanning data, and the fitting iteration count is set to 1000 times. The V-groove can be machined on the flange positioning reference surface as the scanning feature, with a groove depth of 2 ± 0.1 mm and a width of 10 mm. The scanning data preprocessing module can be embedded in the edge computing device to filter out vibration noise and surface stain interference in real time. The deviation analysis uses the spatial vector projection method. The axial deviation is calculated as the distance difference between the theoretical center and the actual center along the tunnel axis direction, and the radial offset is calculated as the Euclidean distance between the two centers in the plane perpendicular to the axis. When it is detected that the axial deviation > 1.5 mm or the radial offset > 2 mm, the model reconstruction program automatically calls the ellipticity data of the middle section updated in the last three times. The model reconstruction algorithm uses the weighted least squares method. The weight of the real-time center coordinates of the head and tail flanges is set to 0.6, and the weight of the middle section data is distributed according to the distance ratio from the head end. The updated theoretical axis model is saved with a timestamp. The historical version retention strategy is set to "retain the last five versions". During the reconstruction verification, three sections can be randomly selected for remeasurement after the new model is generated. The allowable axial deviation of the remeasurement points is set to ±0.2 mm, and the radial ellipticity deviation threshold is set to ±0.5 mm; through the real-time scanning and intelligent reconstruction mechanism, this method enables the theoretical axis model to dynamically adapt to the actual deformation of the shield body, reduces the model drift error to within 0.3 mm. The setting of the double deviation thresholds effectively distinguishes normal deformation and abnormal displacement. The spiral scanning path ensures the integrity of the flange plate profile data. The weighted optimization algorithm balances the influence of the end reference and the middle deformation data. The historical version storage function provides data support for fault tracing. This implementation method is particularly suitable for complex working conditions such as formation mutations and can automatically compensate for the instantaneous deformation of the shield body caused by external force impacts.

[0026] In another technical solution, the three-fold cross-validation adopts a time-division multiplexing verification mode, including: For the first verification, only the first and third laser rangefinder sensors are enabled. For the second verification, the second and fourth laser rangefinder sensors are enabled. For the third verification, all four sensors are enabled simultaneously for full-channel data fusion verification. If any verification stage fails to meet the standard, the calibration program for the corresponding sensor channel is triggered. Specifically, the time-division multiplexing mode of the three cross-verifications can be implemented through a programmable multiplexer. This device can select a four-channel opto-isolated relay module with a switching response time ≤ 5 ms. The calibration program uses an integrated electromagnetic calibration component, which utilizes the principle of electromagnetic induction to achieve high-precision displacement simulation. Compared with an electric displacement platform, this component is smaller in size, stronger in anti-interference ability, and more suitable for the narrow space and complex electromagnetic environment of the tunnel. The component is installed near the sensor and generates a standard displacement signal through electromagnetic drive for sensor calibration. The sensor channel switching logic can be embedded in the verification program module of the controller to control the on / off of the power supply circuits of each sensor according to the preset timing sequence. During the first verification, the first and third laser rangefinder sensors can maintain a continuous sampling mode with a sampling frequency set at 100 Hz and a continuous acquisition period of 500 ms. During the second verification, the second and fourth sensors are switched to work, and a 200-ms device stabilization waiting time is set before sampling. During the third verification, a four-sensor alternating sampling mode is adopted with a sampling interval set at 50 ms. The data fusion algorithm uses Kalman filtering for noise suppression. After the calibration program is triggered, it can automatically drive the electric displacement platform to move the standard reflector target to the measurement range of the corresponding sensor. The target displacement is set at ±2 mm with a step size of 0.1 mm. The input-output characteristic curve of the sensor is fitted by the least squares method. A quick-release mechanical interface can be added to the sensor mounting base to facilitate the positioning of the target during calibration. The calibration reference plate can be made of zero-expansion ceramic material. The guide rail of the electric displacement platform can be arranged parallel to the sensor measurement axis, and the spacing error between the positioning reference surface and the sensor mounting plane is controlled within ±0.02 mm. An adjustment coefficient table is automatically generated after each calibration and stored in the EEPROM of the sensor module. This method reduces the interference between sensor channels through the time-division multiplexing verification mechanism. The three-step progressive verification strategy can effectively identify single-sensor drift faults. The automatic triggering of the calibration program shortens the maintenance response time to within 3 minutes. The Kalman filtering algorithm suppresses the multi-sensor fusion error within the range of ±0.05 mm. The quick-release interface design improves the calibration operation efficiency. This implementation method is particularly suitable for tunnel environments with strong electromagnetic interference and can ensure the long-term working stability of the measurement system.

[0027] In another technical solution, the locking process of the hydraulic cylinder self-locking mechanism includes pre-tightening force detection, which includes: A sinusoidal alternating test load with a frequency of 3 Hz and an amplitude of 10% of the rated pressure is applied to the four hydraulic cylinders through a servo valve. After 6 cycles, the pressure fluctuation data of the last three cycles are statistically analyzed. If the fluctuation difference between any two diagonal pressure sensors > 8% of the rated value or the fluctuation phase difference > 30°, the unlocking mechanism is triggered and the hydraulic cylinder adjustment stage is returned; specifically, the pre-tightening force detection of the hydraulic cylinder self-locking mechanism can be realized by configuring a dynamic test system. This system can select a combination of a high-frequency response servo valve and a dynamic pressure sensor. The servo valve can be a direct-drive proportional servo valve, and the pressure sensor can be a piezoelectric dynamic pressure transmitter. The data acquisition system can integrate a high-speed AD conversion module with a resolution set to 16 bits. The signal transmission uses a double-shielded coaxial cable. When the test load is applied, the servo valve can be connected to the pressure measurement joint of the rodless cavity of the hydraulic cylinder. The sine wave signal is generated by the controller function generator module. The test pipeline can be a stainless steel braided hose with hydraulic pulse attenuators configured at both ends. The analysis of pressure fluctuation data uses the Fourier transform algorithm. The fundamental frequency component extraction window is set to 2.5 - 3.5 Hz. The phase difference calculation is realized through the cross-correlation function method. This method determines the phase difference between signals by calculating the correlation of two signals at different time points to analyze the phase relationship of pressure fluctuations. The time-domain signal alignment error compensation amount is set to 0.1 ms. The unlocking mechanism can be configured with a hydraulic lock controlled by a solenoid valve. The installation position of the servo valve can be set at the tee joint of the hydraulic cylinder inlet pipeline, with a distance ≤ 300 mm from the hydraulic cylinder port. The dynamic pressure sensor can be integrated into the pressure measurement hole of the hydraulic cylinder end cover, and the contact part of the sensing surface with the oil is treated with an alumina ceramic coating. The test signal cable can be laid through a metal bellows, maintaining a distance of more than 50 mm from the power oil pipe. The data acquisition module can have a built-in digital filtering function with a cut-off frequency set to 50 Hz to effectively filter out the pulsation interference of the pump station; this method accurately identifies the pre-tightening force balance in the mechanical self-locking state through dynamic load testing, reduces the false judgment rate of false locking, the selection of a 3 Hz test frequency avoids the system's natural frequency band, the 10% amplitude setting ensures test safety, the dual-threshold judgment mechanism effectively distinguishes the true locking and loose connection states, and the Fourier analysis ensures the detection reliability in a noisy environment. This implementation method is particularly suitable for disassembly working conditions with strong vibrations and can prevent sudden displacement accidents caused by poor locking.

[0028] In another technical solution, the non-volatile memory adopts a data integrity protection mechanism, including: When the positioning parameters are encrypted and stored, a digital fingerprint is generated synchronously. Before each call of the positioning parameters, the matching between the digital fingerprint and the stored data is verified first. If the verification fails, the backup positioning parameters of the adjacent workstations are called for data repair. Specifically, the data integrity protection mechanism can be implemented by configuring a dedicated encryption module, which can select a security chip supporting the national encryption SM4 algorithm. The digital fingerprint generation can select the SHA-256 hash algorithm, and the hash value length is set to 256 bits. The data repair module can integrate a redundant storage unit, which can select a dual-channel FRAM memory with an access time ≤ 100 ns. The backup positioning parameters can be stored in the mirror storage area of the adjacent workstation controller and synchronized across devices through the industrial Ethernet. When encrypted and stored, the positioning parameters are packed according to the "timestamp - positioning coordinates - pressure value" structure, and the digital fingerprint is attached to the end of the data packet. When the verification program starts, it can preferentially read the locally stored data and recalculate the hash value. After the matching fails, it automatically sends a data request to the adjacent workstation. During the repair process, the backup data of three adjacent workstations can be compared, and the majority voting mechanism is used to determine the valid data version. The repaired data needs to be retested through an offline verification platform, and the retest standard is set as the axial deviation ≤ 0.3 mm and the pressure fluctuation ≤ 5% of the rated value. The encryption chip can be welded beside the PCIe slot of the tooling control system mainboard and directly connected to the CPU through the HSM bus. The FRAM memory can be arranged near the power management unit and designed with an independent power supply line. The data repair communication module can be integrated in the expansion slot of the industrial switch, and a dedicated data transmission channel is divided through VLAN. The backup data storage area is physically isolated, and the read and write permissions are managed through electronic keys. This method reduces the failure rate of key positioning parameters through a multi-layer data protection mechanism. The digital fingerprint verification effectively identifies the data bit flips caused by the aging of the storage medium. The majority voting mechanism ensures the reliability of the backup data. The offline retest link prevents incorrect data from entering the execution link, and the physical isolation design prevents electromagnetic pulse attacks.

[0029] In another technical solution, when the cross-sectional ellipticity data is updated, a credibility verification is performed synchronously, which includes: When the deviation between the newly acquired ovality data and the average of historical data > 15%, it triggers the abnormal detection program for the shield body surface, controls the support tooling frame to move along the axis to the adjacent detection position for three repeated scans, and uses the median value of the three scan results as the effective updated data; specifically, the credibility verification system can be configured with an intelligent verification algorithm, the abnormal detection program can select a prediction model based on time series analysis, the average of historical data is calculated using the moving average method, the window period is set as the data of the most recent 20 measurements, the three repeated scan mechanism can select a linear module with backlash compensation, the repeat positioning accuracy ≤ 0.01 mm, the median value screening algorithm uses the three-value median method, discards the maximum and minimum measurement values and then takes the arithmetic average, the 3D laser scanner can select a line laser profile sensor, the lateral resolution is 0.05 mm, the longitudinal measurement range is ±15 mm, the abnormal detection threshold is set to trigger when the ratio of the absolute value of the difference between the new and old data to the historical mean > 15%, the interval time of the three repeated scans is set to 10 seconds, the scan path adopts a spiral progressive trajectory, the pitch is set to 0.3 mm, when judging the data validity, the range of the three measurement values needs to ≤ 0.2 mm, otherwise it automatically expands to five measurements and takes the median value, the moving guide rail of the support tooling frame can be configured with a linear grating scale feedback system, the positioning accuracy is ±0.005 mm, the scan head protective cover can select polycarbonate transparent material with an anti-fog coating on the surface, the abnormal detection position is set at 200 mm positions before and after the current detection position, the moving speed is set to 50 mm / s, the scan data buffer can allocate double storage space to ensure the complete retention of the original data of the three scans; this method reduces the misjudgment rate of abnormal data through a dynamic threshold and a repeated verification mechanism, the setting of the 15% deviation threshold balances the requirements of data update sensitivity and stability, the three-value median method effectively eliminates the influence of instantaneous interference, the spiral scan path design improves the surface defect detection rate, and the grating feedback system ensures the reliability of repeated positioning.

[0030] In another technical solution, the model reconstruction program further includes a deformation pre-compensation step: Before refitting the reference axis, the theoretical axis model is dynamically corrected according to the elastic modulus parameter of the support tooling frame material and the real-time collected ambient temperature data. The deformation compensation amount is monitored in real time through the strain gauge array attached to the frame surface, and the compensation amount is pre-injected into the initial stroke command of the main adjustment cylinder. The compensation direction is opposite to the frame deformation direction. Specifically, the deformation pre-compensation system can integrate a multi-physical field coupling analysis module. The strain gauge array can select a full-bridge foil strain gauge, and the mounting density is set to 6 measurement points per square meter, forming a 3×2 orthogonal grid. The ambient temperature sensor can select a PT100 platinum resistance temperature probe, the sampling frequency is set to 0.5 Hz, and the measurement range covers -20°C to 80°C. The elastic modulus parameter can be stored as a temperature-modulus relationship curve table, and the data is from the material high-temperature tensile test report. The strain gauge substrate can select a polyimide flexible material, the sensitive grid resistance value is 120Ω±0.5%, and the sensitivity coefficient is 2.0±0.1 mV / V. The temperature compensation circuit can be integrated in the signal conditioning module, and a dual-channel differential amplification design is adopted, with a common-mode rejection ratio ≥100dB. The deformation compensation amount is calculated using the finite element inverse solution method. The frame load distribution is inversely deduced through real-time strain data, and the compensation coefficient is dynamically adjusted according to the elastic modulus temperature drift curve. The generation of the pre-injected stroke command adopts a feed-forward control algorithm. During the movement of the main adjustment cylinder, the controller compares the feedback data of the laser distance sensor with the data of the theoretical axis model in real time, and dynamically adjusts the stroke according to the new deviation to ensure the adjustment accuracy after compensation. If the deviation exceeds the allowable range, the compensation amount is recalculated and the stroke command is adjusted. The compensation amount direction is opposite to the frame deformation trend, and the amplitude is 1.2 times the predicted deformation amount. The strain gauge array can be arranged along the stress concentration area of the main beam of the support tooling frame, focusing on covering the frame four corners and the middle connection flange area. The temperature sensors can be evenly distributed on the upper, middle, and lower three levels of the frame, with two front and rear measurement points set on each level. The signal conditioning module can be installed in the waterproof junction box on the side of the frame and connected to the controller through the CAN bus. The compensation algorithm runs in the real-time kernel of the controller, and the calculation period is synchronously set to 10 ms with the hydraulic system control period. This method reduces the axis fitting error caused by temperature drift through the deformation pre-compensation mechanism. The synchronous monitoring of dual physical quantities (strain / temperature) ensures the accuracy of material parameter correction. The finite element inverse solution algorithm realizes the real-time inversion of the deformation amount. The feed-forward control strategy improves the compensation response speed by 50%. The setting of the 1.2-fold compensation coefficient effectively covers the non-linear deformation characteristics of the material. This implementation method significantly improves the dynamic adaptability of the axis model in the tunnel construction environment with large day-night temperature differences and avoids the problem of repeated adjustment caused by frame creep.

[0031] In the face of extreme geological disasters such as strong earthquakes, an elastic buffer layer and an emergency locking device are added to the support tooling frame. During a disaster, the elastic buffer layer absorbs vibration energy and reduces the impact on the shield body and the tooling; the emergency locking device is automatically activated to prevent large displacements between the support tooling and the shield body. After the disaster, a comprehensive inspection and evaluation of the tooling and the shield body are carried out, and components are repaired or replaced according to the damage conditions. After recalibrating the positioning system, construction is resumed.

[0032] Although the embodiments of the present invention have been disclosed as above, they are not limited to the applications listed in the specification and the embodiments. It can be fully applied to various fields suitable for the present invention. For those familiar with the field, additional modifications can be easily made. Therefore, without departing from the general concept defined by the claims and the equivalent scope, the present invention is not limited to specific details and the examples shown and described herein.

Claims

1. Intelligent positioning method for TBM disassembly support tooling, characterized in that include: Four laser distance measuring sensors are installed at the four corners of the supporting tooling frame, with their laser directions parallel to the tunnel axis and the installation plane coincident with the geometric center plane of the supporting tooling frame. Four laser reflection targets that form spatial projection mapping with the sensors are fixed at the symmetrical points of the four quadrants of the shield; The distance data of the four targets obtained by the laser ranging sensor are compared with the pre-stored theoretical axis model of the shield body to calculate the axial deviation and radial offset component of each ranging channel; The controller converts the axial deviation into a hydraulic cylinder stroke command, and drives the four supporting hydraulic cylinders to adjust in coordination. During the adjustment, the contact pressure is monitored by the pressure sensor at the end of the supporting hydraulic cylinder. When the adjacent pressure difference exceeds 0.8 MPa, the adjustment is suspended and the compensation amount is recalculated. When the values of the four pressure sensors reach 7±0.3 MPa synchronously and remain stable for 5 seconds, the shield's historical ovality data and the current radial offset component are called to calculate the inclination correction value. The dual tilt adjustment cylinders located in the middle of the support tooling frame are controlled to make step compensation according to the tilt correction value. The laser ranging data is verified twice after each step of 0.3 mm. If the radial offset extreme error exceeds 1.2 mm, the system returns to the hydraulic cylinder adjustment stage. After the inclination compensation is completed, the four laser distance measuring sensors are started alternately to perform three cross-verifications. When the maximum axial deviation is ≤0.5 mm and the maximum radial deviation is ≤0.8 mm, the self-locking mechanism of the hydraulic cylinder and the positioning pin of the inclination adjustment cylinder are locked; The verified positioning parameters are encrypted and written into the non-volatile memory of the tooling control system and an audible and visual completion signal is triggered.

2. The intelligent positioning method of the TBM disassembly support tooling according to claim 1, wherein The method for constructing the shield theoretical axis model includes: When the shield is stopped, the laser tracker is used to collect the center coordinates of the flanges at both ends of the shield and the ovality data of the three middle sections. The line connecting the centers of the head and tail is used as the reference axis, and a theoretical axis model containing a three-dimensional coordinate system is generated based on the least squares method.

3. The intelligent positioning method of the TBM disassembly support tooling according to claim 1, characterized in that The coordinated adjustment of the supporting hydraulic cylinders includes a dynamic load distribution step, which includes: The supporting hydraulic cylinder with the largest axial deviation is set as the main adjustment cylinder, and the other three supporting hydraulic cylinders generate compensation coefficients according to the deviation ratio of their corresponding ranging channels. For every 1 mm movement of the main adjustment cylinder, the slave adjustment cylinder synchronously performs a follow-up compensation of 0.6-0.8 times the stroke.

4. The intelligent positioning method of the TBM disassembly support tooling according to claim 2, characterized in that, The method for updating the historical ellipticity data of the shield body comprises: After each positioning is completed, the support tooling frame is controlled to move along the axial direction of the shield to three preset detection positions, and the laser ranging sensor is started at each detection position to perform circumferential scanning, and the cross-sectional ellipticity data obtained by the scan is updated to the historical database according to the timestamp.

5. The intelligent positioning method of the TBM disassembly support tooling according to claim 4, characterized in that, The dynamic verification of the theoretical axis model includes: At each positioning start, four laser ranging sensors are used to reversely scan the contours of the shield's front and rear flanges, extract the real-time center coordinates, and perform deviation analysis with the theoretical center coordinates in the model. If the axial deviation is greater than 1.5 mm or the radial offset is greater than 2 mm, the model reconstruction program is triggered: the reference axis is refitted based on the real-time center coordinates and the latest updated intermediate section ovality data to generate an updated theoretical axis model, and the original model is marked as a historical version for storage.

6. The intelligent positioning method of the TBM disassembly support tooling according to claim 1, wherein The three cross-validations adopt a time-sharing multiplexing validation mode including: For the first verification, only the first and third laser rangefinder sensors are enabled. For the second verification, the second and fourth laser rangefinder sensors are enabled. For the third verification, all four sensors are enabled for full-channel data fusion verification. If any verification stage fails to meet the standard, the calibration procedure for the corresponding sensor channel is triggered.

7. The intelligent positioning method of the TBM disassembly support tooling according to claim 1, characterized in that The locking process of the hydraulic cylinder self-locking mechanism includes pre-tightening force detection, which includes: Apply a sinusoidal alternating test load with a frequency of 3 Hz and an amplitude of 10% of the rated pressure to the four hydraulic cylinders through the servo valve. After 6 cycles, statistically analyze the pressure fluctuation data of the last three cycles. If the fluctuation difference between any two diagonal pressure sensors > 8% of the rated value or the fluctuation phase difference > 30°, trigger the unlocking mechanism and return to the hydraulic cylinder adjustment stage.

8. The intelligent positioning method of the TBM disassembly support tooling according to claim 1, characterized in that The non-volatile memory adopts a data integrity protection mechanism, including: When the positioning parameters are encrypted and stored, a digital fingerprint is generated synchronously. Before each call of the positioning parameters, first verify the matching of the digital fingerprint with the stored data. If the verification fails, call the backup positioning parameters of the adjacent workstations for data repair.

9. The intelligent positioning method of the TBM disassembly support tooling according to claim 5, characterized in that, When the cross-sectional ovality data is updated, credibility verification is performed synchronously, which includes: When the deviation between the newly acquired ovality data and the average value of the historical data > 15%, trigger the shield surface anomaly detection program, control the support tooling frame to move along the axis to the adjacent detection position for three repeated scans, and use the median value of the three scan results as the effective updated data.

10. The intelligent positioning method of the TBM disassembly support tooling according to claim 3, characterized in that, The model reconstruction program also includes a deformation pre-compensation step: Before refitting the reference axis, dynamically correct the theoretical axis model according to the material elastic modulus parameter of the support tooling frame and the real-time collected ambient temperature data. Real-time monitor the deformation compensation amount through the strain gauge array attached to the surface of the frame, and pre-inject the compensation amount into the initial stroke command of the main adjustment cylinder. The compensation direction is opposite to the frame deformation direction.