Dual-block intelligent track panel fine-tuning equipment and fine-tuning method

Abstract

This invention relates to the field of railway system technology, specifically to a dual-block intelligent track panel fine-tuning device and method. The device includes a spatial data acquisition unit, a position adjustment mechanism, and a control unit. This invention acquires the spatial position information of track panel components through a non-contact spatial data acquisition unit, compares and analyzes the target position information with the spatial position information, decomposes it into directly executable lateral and vertical adjustment amounts, and then solves for the optimal coordinated action command of the position adjustment mechanism. Executing the coordinated action command completes high-precision adjustment. This invention eliminates the heavy reliance on manual measurement and operational experience in traditional methods, thereby improving the objectivity of positioning and the final adjustment accuracy, effectively ensuring the consistency of construction quality.

Description

Technical Field

[0001] This invention relates to the field of railway system technology, specifically to a dual-block intelligent track panel fine-tuning device and method, and more particularly to an intelligent positioning and adjustment system for laying ballastless railway tracks. Background Technology

[0002] The rapid development of high-speed railways and urban rail transit has placed extremely high demands on the smoothness and stability of railway lines. In railway construction, ballastless track is widely used due to its advantages such as good integrity, high stability, and low maintenance workload. Double-block ballastless track is an important form, and its construction process typically includes: after the concrete foundation base is poured, double-block sleepers (i.e., track panels) connected by steel trusses are laid on the base, and their spatial position (including elevation and centerline position) is precisely adjusted to the design tolerance range through fine-tuning operations. Finally, a second pour is performed for final fixation.

[0003] Traditional fine-tuning methods rely heavily on manual operation. Construction workers use hand tools such as crowbars and jacks, along with traditional surveying tools such as string lines, levels, and leveling rods. This method is labor-intensive, has relatively low construction efficiency, and exhibits high uncertainty in adjustment accuracy and quality.

[0004] With technological advancements, some semi-automated fine-tuning auxiliary equipment has emerged, reducing the labor intensity of workers to some extent and improving the objectivity of measurements. However, the closed-loop control of the entire adjustment process still relies on the operator's real-time judgment and manual intervention. The speed, magnitude, and final accuracy of the adjustment remain closely related to the operator's experience and responsiveness. Summary of the Invention

[0005] The technical problem to be solved by this invention is the high uncertainty in adjustment accuracy and quality. The purpose is to provide a dual-block intelligent track panel fine-tuning device and fine-tuning method, which improves efficiency and ensures the overall smoothness of the final track line.

[0006] This invention is achieved through the following technical solution:

[0007] A dual-block intelligent track panel fine-tuning device, comprising:

[0008] The spatial data acquisition unit is used to acquire the current spatial position information of the reference components on the dual-block track panel;

[0009] A position adjustment mechanism, which is connected to the double-block track, is used to adjust the spatial position of the reference component in two degrees of freedom, lateral and vertical.

[0010] The control unit is communicatively connected to the spatial data acquisition unit and the position adjustment mechanism. The control unit is configured to generate a control signal to drive the position adjustment mechanism to perform closed-loop adjustment of the position of the reference component based on the deviation between the current spatial position information obtained by the spatial data acquisition unit and the preset target position information.

[0011] Optionally, the double-block track panel includes: a foundation base, sleepers, a steel truss, and rails;

[0012] The lower side of the rail is fixedly connected to the sleeper, the steel truss is perpendicular to the rail and fixedly connected to the rail, and both ends of the steel truss are provided with force-bearing interfaces connected to the position adjustment mechanism. The force-bearing interfaces are used to bear and transmit the lateral and / or vertical adjustment forces from the position adjustment mechanism.

[0013] The spatial data acquisition unit is a total station, a 3D laser scanner, or an industrial vision system.

[0014] Optionally, the position adjustment mechanism includes:

[0015] A force-bearing component, which is detachably connected to the force-bearing interface;

[0016] A support structure that rests on the base during operation and provides a reaction force reference for adjustment;

[0017] A vertical adjustment actuator, which is installed on the support structure, is used to apply a vertical force to the load-bearing member to adjust the elevation position of the steel truss.

[0018] A lateral adjustment actuator, mounted on the support structure and / or the foundation base, is used to apply a lateral force to the load-bearing member to adjust the lateral position of the centerline of the steel truss.

[0019] Optionally, the vertical adjustment actuator and the horizontal adjustment actuator are lead screw drive mechanisms;

[0020] The lead screw transmission mechanism is provided with a drive interface, which is configured to be detachably connected to an external electric wrench to receive the rotational power input by the electric wrench and convert the rotational power into a linear force for achieving lateral or vertical adjustment.

[0021] A method for fine-tuning a dual-block intelligent track panel, based on the dual-block intelligent track panel fine-tuning device described above, the fine-tuning method comprising:

[0022] The position adjustment mechanism is installed on the double-block track panel, establishing a detachable mechanical connection between it and the stress interface on the steel truss; and the target position information, including track design parameters, is loaded into the control unit.

[0023] The spatial data acquisition unit is activated to measure the reference components on the dual-block track panel and obtain their current spatial position information in real time.

[0024] The current spatial position information is compared with the preset target position information to calculate the lateral and vertical deviations of the reference component, and a coordinated control command to drive the position adjustment mechanism is generated based on the deviation.

[0025] The coordinated action command is sent to the position adjustment mechanism to drive the vertical adjustment actuator and the horizontal adjustment actuator to coordinate their actions and adjust the spatial position of the reference component; and during the adjustment process, the current spatial position information after adjustment is continuously fed back until the deviation between the latest current spatial position information and the target position information is less than the preset accuracy threshold.

[0026] Optionally, the specific steps for obtaining its current spatial location information in real time include:

[0027] The reference component and its surrounding environment are scanned to obtain raw 3D point cloud data containing noise and outliers;

[0028] The original 3D point cloud data is filtered and segmented to remove outliers and extract a set of valid target point clouds that represent only the baseline components. ,in A three-dimensional point in the target point cloud;

[0029] Effective target point cloud Reference digital model with preset standard geometric shape Iterative registration is performed, and the target point cloud is determined by solving an optimization problem. Relative to the reference model The optimal rigid body transformation, and the objective function of the optimization problem are: ;

[0030] in:

[0031] Let be the optimal rotation matrix to be solved, representing the current spatial orientation of the steel truss;

[0032] Let be the optimal translation vector to be solved, representing the current spatial position of the steel truss;

[0033] In the reference digital model Above, and the transformed point The corresponding nearest point;

[0034] To assign point pairs The weights;

[0035] After the iteration converges, the optimal solution will be... and Combined into a homogeneous transformation matrix, the current spatial position information of the reference component is obtained.

[0036] Optionally, weight The calculation method is as follows: ,in, This is the preset maximum allowable distance threshold.

[0037] Optionally, the calculation steps for the lateral and vertical deviations of the reference component include:

[0038] Reference digital model of the benchmark component Above, a set of predefined common Local coordinate set of key control points ;

[0039] Using the optimal rotation matrix and optimal translation vector Calculate the current measurement position of each key control point in the global coordinate system. : ;

[0040] Based on the design and construction location of the benchmark component, the design target location corresponding to each critical control point is retrieved from the target location information. ;

[0041] Calculate the three-dimensional spatial error vector for each key control point. : ;

[0042] Obtain the orthogonal basis vectors of the local coordinate system of the orbit at the design target location. ;

[0043] Each three-dimensional spatial error vector By projecting onto the lateral and vertical basis vectors respectively, the lateral deviation components of each control point are obtained. and vertical deviation component ;

[0044] The final lateral deviation of the reference component is calculated by weighted average. and final vertical deviation : ;

[0045] in: The first Local coordinates, current measurement location, and design target location of each key control point;

[0046] For the first The three-dimensional spatial error vector of each control point;

[0047] These are the transverse basis vector, vertical basis vector, and longitudinal basis vector of the orbit, respectively.

[0048] To be assigned to the Preset weighting coefficients for each key control point.

[0049] Optionally, generating coordinated control commands for driving the position adjustment mechanism includes the following steps:

[0050] The control unit broadcasts a query signal and receives response signals from all installed and online vertical and horizontal adjustment actuators, thereby determining in real time the set of active actuators currently participating in the adjustment task. and their respective locations and types, among which This represents the total number of active actuators.

[0051] Based on the finite element mechanical model of the two-block track, the system influence matrix is ​​established. Matrix elements Indicates the first One active actuator When a unit displacement is generated, for the first The impact response caused by the pose of a key control point;

[0052] The three-dimensional spatial error vector of all key control points Combined into a total system error vector And calculate the cooperative displacement vector that can optimally compensate for the total system error with minimal adjustment cost. : ;

[0053] in: Here is the system influence matrix, where It represents the total number of error components monitored by the system.

[0054] The system's total error vector is composed of the error components of all control points;

[0055] For matrix Transpose of;

[0056] It is the identity matrix;

[0057] The regularization coefficient is used.

[0058] The optimal cooperative displacement vector Decomposed into individual active actuators The independent displacement command is sent as a cooperative control command to the corresponding actuator.

[0059] Optionally, the specific steps for continuous feedback and adjustment include:

[0060] During the movement of the position adjustment mechanism, the control unit repeatedly executes the measurement and deviation calculation steps, and updates the total system error vector in real time. ,in This is the current control cycle;

[0061] In each control cycle After completion, the control unit uses two conditional criteria to determine whether the adjustment process has converged and terminated. If either condition is not met, a new coordinated control command is generated and the next round of adjustment is initiated.

[0062] The two conditional criteria are:

[0063] The Euclidean norm of the current system's total error vector is less than the preset position accuracy threshold. : ;

[0064] Between two consecutive control cycles, the change in the system's total error norm is less than the preset dynamic stability threshold. , ;

[0065] in: They were respectively in the second and the The total system error vector for each control cycle;

[0066] These are the preset position accuracy threshold and the dynamic stability threshold, respectively.

[0067] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0068] This invention acquires the spatial position information of track panel components through a non-contact spatial data acquisition unit, compares and analyzes the target position information with the spatial position information, decomposes it into directly executable lateral and vertical adjustment amounts, and then solves for the optimal coordinated action command of the position adjustment mechanism. Executing the coordinated action command completes high-precision adjustment. This invention eliminates the heavy reliance on manual measurement and operational experience in traditional methods, thereby improving the objectivity of positioning and the final adjustment accuracy, and effectively ensuring the consistency of construction quality. Attached Figure Description

[0069] The accompanying drawings illustrate exemplary embodiments of the present invention and, together with the description thereof, serve to explain the principles of the invention. These drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, but do not constitute a limitation on the embodiments of the present invention.

[0070] Figure 1 This is a structural schematic diagram of the dual-block intelligent track panel fine-tuning device according to the present invention.

[0071] Figure 2 This is a physical image of the dual-block intelligent track panel fine-tuning device according to the present invention.

[0072] Figure 3 This is a flowchart illustrating the dual-block intelligent track panel fine-tuning method according to the present invention.

[0073] Reference numerals: 1-Spatial data acquisition unit, 2-Foundation base, 3-Sleeper, 4-Steel truss, 5-Rail, 6-Strengthening component, 7-Supporting structure, 8-Vertical adjustment actuator, 9-Horizontal adjustment actuator. Detailed Implementation

[0074] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the invention.

[0075] It should also be noted that, for ease of description, only the parts relevant to the present invention are shown in the accompanying drawings.

[0076] Where there is no conflict, the embodiments and features described in the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0077] Example 1

[0078] like Figure 1 and Figure 2 As shown, this embodiment provides a dual-block intelligent track panel fine-tuning device, including: a spatial data acquisition unit 1, a position adjustment mechanism, and a control unit.

[0079] The spatial data acquisition unit 1 is used to acquire the current spatial position information of the reference components on the double-block track panel; and to capture and quantify the current spatial position information of a pre-selected reference component (such as a specific marker point or structural feature on the steel truss 4) on the double-block track panel in real time.

[0080] The position adjustment mechanism is connected to the double-block track and is used to adjust the spatial position of the reference component in two degrees of freedom, lateral and vertical. The position adjustment mechanism is physically connected to the double-block track and has the ability to apply controllable displacement in at least two orthogonal directions, namely lateral (left and right movement perpendicular to the direction of track movement) and vertical (up and down movement perpendicular to the ground).

[0081] The control unit is communicatively connected to the spatial data acquisition unit 1 and the position adjustment mechanism. The control unit is configured to generate a control signal to drive the position adjustment mechanism to perform closed-loop adjustment of the position of the reference component based on the deviation between the current spatial position information acquired by the spatial data acquisition unit 1 and the preset target position information.

[0082] The operating logic of the control unit is as follows:

[0083] Data reception: Obtain current spatial location information of the reference component from the spatial data acquisition unit 1 via a communication connection.

[0084] Deviation calculation: The ideal position of the reference component in the design blueprint is pre-stored internally, i.e., "preset target position information". The control unit will mathematically compare the current position received in real time with this target position to calculate the deviation between the two in the horizontal and vertical directions.

[0085] Command generation and transmission: Based on the calculated magnitude and direction of the deviation, the control unit generates corresponding control signals and sends these signals to the position adjustment mechanism.

[0086] Closed-loop adjustment: While the position adjustment mechanism is in operation, the spatial data acquisition unit 1 continues to measure the new position of the reference component, and the control unit continuously calculates the new deviation and updates the control signal accordingly. The "measurement-calculation-adjustment" process is executed in a loop until the deviation is eliminated or reduced to within the preset accuracy range.

[0087] Example 2

[0088] This embodiment is a further refinement of the solution described in Embodiment 1.

[0089] The dual-block track panel adapted in this embodiment includes: a foundation base 2, a sleeper 3, a steel truss 4, and a rail 5.

[0090] The lower side of the rail 5 is fixedly connected to the sleeper 3. The steel truss 4 is perpendicular to the rail 5 and fixedly connected to the rail 5. Both ends of the steel truss 4 are provided with force-bearing interfaces connected to the position adjustment mechanism. The force-bearing interfaces are used to bear and transmit the lateral and / or vertical adjustment forces from the position adjustment mechanism.

[0091] The spatial data acquisition unit 1 can be a total station, a 3D laser scanner, or an industrial vision system. A total station can accurately measure the 3D coordinates of a specific target point (such as a prism); a 3D laser scanner can quickly acquire massive amounts of 3D point cloud data of an object's surface to form a complete digital model; an industrial vision system can use a high-resolution camera and image processing algorithms to identify specific markers and calculate their spatial positions.

[0092] In this embodiment, the position adjustment mechanism is designed as a modular mechanical assembly, which includes: a force-bearing component 6, a support structure 7, a vertical adjustment actuator 8, and a horizontal adjustment actuator 9.

[0093] The load-bearing component 6 is detachably connected to the load-bearing interface. The load-bearing component 6 is connected to the load-bearing interface on the aforementioned steel truss 4 through a quick-release joint (e.g., flange and flange bolt).

[0094] The support structure 7 is supported on the base 2 during operation and provides a reaction force reference for adjustment; it provides a stable reference reference for the entire adjustment process, through which all adjustment forces will obtain a reliable reaction force reference.

[0095] A vertical adjustment actuator 8 is installed on the support structure 7 to apply a vertical force to the force-bearing member 6 in order to adjust the elevation position of the steel truss 4.

[0096] The lateral adjustment actuator 9 is installed on the support structure 7 and / or the foundation base 2 to apply a lateral force to the force-bearing member 6 in order to adjust the lateral position of the centerline of the steel truss 4.

[0097] In order to achieve precise and labor-saving fine-tuning, this embodiment preferably designs the vertical adjustment actuator 8 and the horizontal adjustment actuator 9 as a lead screw transmission mechanism. By utilizing the helical motion of the screw (i.e., the lead screw), the input rotational motion can be converted into linear motion, and it usually has a self-locking function, that is, it can maintain its position when no power is applied.

[0098] To drive the lead screw transmission mechanism, a drive interface (e.g., a standard-sized hexagonal head or square tenon) is provided on the lead screw transmission mechanism. The drive interface is configured to be detachably connected to an external electric wrench to receive the rotational power input by the electric wrench and convert the rotational power into a linear force for achieving lateral or vertical adjustment.

[0099] Example 3

[0100] like Figure 3As shown, this embodiment discloses a dual-block intelligent track panel fine-tuning method based on the dual-block intelligent track panel fine-tuning device described above. This method upgrades the traditional discrete adjustment operation that relies on manual experience into a standardized closed-loop control process driven by data. The fine-tuning method mainly includes the following four key steps:

[0101] Step 1: Installation and initialization.

[0102] The position adjustment mechanism is installed on the double-block track panel, establishing a detachable mechanical connection between it and the stress interface on the steel truss; and the target position information, including track design parameters, is loaded into the control unit.

[0103] The preparation phase before the operation begins includes two aspects: physical installation and data loading. First, the load-bearing components of the position adjustment mechanism are detachably mechanically connected to the pre-set load-bearing interfaces on the steel truss to ensure a stable working relationship between the equipment and the track panel. At the same time, the digital design blueprint containing information such as the global coordinates, elevation, and geometric parameters of the track line, i.e., the target position information, is loaded into the memory of the control unit through the data interface.

[0104] Step 2: Real-time measurement.

[0105] The spatial data acquisition unit is activated to measure the reference components on the dual-block track panel and obtain their current spatial position information in real time.

[0106] After initialization, the spatial data acquisition unit is activated to continuously scan or measure the reference components on the track panel, and to obtain the current spatial position information of the reference components in the construction coordinate system in real time.

[0107] Step 3: Comparison and decision-making.

[0108] The current spatial position information is compared with the preset target position information to calculate the lateral and vertical deviations of the reference component, and a coordinated control command to drive the position adjustment mechanism is generated based on the deviation.

[0109] The control unit performs a mathematical comparison between the "current spatial position information" acquired in real time in the second step and the "preset target position information" loaded in the first step. This comparison calculates the specific deviations of the reference component from the design target in both the horizontal and vertical dimensions. Based on these quantified deviations, the control unit then uses its internal control algorithm to generate a set of coordinated control commands to drive the position adjustment mechanism to perform corrective actions.

[0110] Step 4: Drive execution and closed-loop feedback.

[0111] The coordinated action command is sent to the position adjustment mechanism to drive the vertical adjustment actuator and the horizontal adjustment actuator to coordinate their actions and adjust the spatial position of the reference component; and during the adjustment process, the current spatial position information after adjustment is continuously fed back until the deviation between the latest current spatial position information and the target position information is less than the preset accuracy threshold.

[0112] The control unit sends the generated coordinated control command to the position adjustment mechanism, instructing its internal vertical and horizontal adjustment actuators to start coordinated action, thereby pushing or lifting the reference component and moving its spatial position toward the target point.

[0113] Throughout the actuator's operation, the system remains in a closed-loop state, meaning that the second step, "real-time measurement," and the third step, "comparison and decision-making," are continuously performed. The system continuously provides feedback on the adjusted spatial position information and updates instructions until the control unit determines that the deviation between the latest position and the target position is less than a preset accuracy threshold, at which point the entire adjustment process automatically stops.

[0114] Example 4

[0115] This embodiment provides a detailed description of the specific steps for acquiring its current spatial location information in real time, including:

[0116] Spatial data acquisition units (such as 3D laser scanners) scan the reference component and its surrounding environment to obtain raw 3D point cloud data containing noise and outliers; a point cloud refers to a 3D coordinate dataset composed of tens of thousands of sampling points on the surface of a target.

[0117] The original point cloud inevitably contains noise points caused by measurement errors and outliers such as background points that do not belong to the target object. Therefore, the original 3D point cloud data is filtered and segmented to remove outliers and extract a set of valid target point clouds that only represent the reference components. ,in A point in a three-dimensional space within the target point cloud.

[0118] Effective target point cloud Reference digital model with preset standard geometric shape Iterative registration is performed by solving a mathematical optimization problem, namely, finding an optimal rigid body transformation. A rigid body transformation refers to a transformation in three-dimensional space that changes only the position and orientation of an object without altering its shape and size. It consists of a combination of rotation and translation. Therefore, the system continuously adjusts the mounting matrix and translation matrix to find the optimal solution that minimizes the objective function value.

[0119] That is, solving the optimization problem to determine the target point cloud. Relative to the reference model The optimal rigid body transformation, and the objective function of the optimization problem are: ;

[0120] in:

[0121] Let be the optimal rotation matrix to be solved, representing the current spatial orientation of the steel truss;

[0122] Let be the optimal translation vector to be solved, representing the current spatial position of the steel truss;

[0123] In the reference digital model Above, and the transformed point The corresponding nearest point;

[0124] To assign point pairs The weights; to improve the robustness and accuracy of the registration algorithm, the weights... The calculation method is as follows: ,in, This is the preset maximum allowable distance threshold.

[0125] By setting a maximum allowed distance threshold, when a pair of matching points... When the distance between points exceeds the threshold, the system determines that the match may be due to noise or incorrect segmentation and is an unreliable "outlier pair," assigning a weight of 0. For "trustworthy pairs" where the distance is within the threshold, the weight increases as the distance between the pairs decreases.

[0126] After iterative convergence (i.e., the objective function value no longer decreases significantly), the optimal solution is... and Combined into a homogeneous transformation matrix, the current spatial position information of the reference component is obtained.

[0127] Example 5

[0128] This embodiment illustrates how, after obtaining the precise current spatial position information of the reference component, it is compared with the design target, and the lateral and vertical deviations of the reference component are calculated. The specific calculation steps include:

[0129] To perform detailed deviation analysis, a reference digital model of the benchmark component is used. Above, a set of predefined common Local coordinate set of key control points These points are usually selected at the geometric features of the component or at key stress locations, such as the corners of steel trusses or the connection points of sleepers.

[0130] Using the optimal rotation matrix and optimal translation vector Calculate the current measurement position of each key control point in the global coordinate system. : .

[0131] Based on the design and construction location of the reference components, the design target location corresponding to each critical control point is retrieved from the loaded "target location information" (i.e., the digital blueprint of the track design). ;

[0132] Calculate the three-dimensional spatial error vector for each key control point. : ; indicates that the first one needs to be... How can a key control point be moved from its current position in which direction and how far to reach its ideal target position?

[0133] Obtain the orthogonal basis vectors of the local coordinate system of the orbit at the design target location. By using the mathematical operation of vector dot product, each three-dimensional spatial error vector is... By projecting onto the lateral and vertical basis vectors respectively, the lateral deviation components of each control point are obtained. and vertical deviation component .

[0134] After obtaining the lateral and vertical deviation components of each key control point, in order to obtain a unified adjustment command that can guide the overall movement of the entire reference component, the final lateral deviation of the reference component is calculated by weighted averaging. and final vertical deviation : ;

[0135] in: The first Local coordinates, current measurement location, and design target location of each key control point;

[0136] For the first The three-dimensional spatial error vector of each control point;

[0137] These are the transverse basis vector, vertical basis vector, and longitudinal basis vector of the orbit, respectively.

[0138] To be assigned to the The preset weight coefficients of each key control point reflect the importance of that point in ensuring the overall smoothness of the track (for example, the closer a point is to the bottom of the rail, the higher its weight may be).

[0139] Example 6

[0140] In actual ballastless track laying projects, considering factors such as construction efficiency, equipment costs, and operational flexibility, construction units typically do not, and do not need to, install position adjustment mechanisms on every steel truss along a several-kilometer-long track.

[0141] A more common and economical operating model is a "segmented mobile" construction process. This involves the construction team using a limited number of positioning mechanisms (e.g., enough to cover a 20- or 30-meter work section). During construction, the team centrally installs these mechanisms onto the steel truss within the section currently undergoing fine-tuning. After completing the fine-tuning of that section and initially fixing the track panel position, the team disassembles these mechanisms and moves them in a "leapfrog" fashion to the next section to be constructed for a new round of installation and work.

[0142] This "selective installation" and "leapfrog" work mode leads to a critical practical problem: for the control unit, the set of actuators it needs to control at any given time is not fixed, but dynamically changes as construction progresses and mechanisms are relocated. A control program with preset fixed actuator addresses and numbers will be completely unable to adapt to such flexible and changing field conditions, and may issue invalid commands to locations where mechanisms are not installed, resulting in system errors or work interruptions.

[0143] This embodiment describes a specific method for generating coordinated control commands based on deviation to drive the position adjustment mechanism. First, all currently available adjustment resources (i.e., online actuators) are identified. Then, a mathematical model is used to calculate a set of optimal coordinated actions that can correct the overall system error with minimal adjustment cost and maximum efficiency. Specifically, the method includes the following steps:

[0144] Before initiating any adjustment action, the control unit first broadcasts a query signal to all nodes where adjustment actuators may be present. Upon receiving this signal, each installed and powered-on actuator sends a response signal back to the control unit containing its unique identifier, location, and type (vertical or horizontal). By collecting and parsing these responses, the set of active actuators currently participating in the adjustment task is determined in real time. and their respective locations and types, among which This refers to the total number of active actuators; that is, to know precisely which actuators are currently active, their locations, and whether they can receive instructions.

[0145] Based on the finite element mechanical model of the two-block track, the system influence matrix is ​​established. This matrix is ​​typically obtained based on finite element mechanical model simulation analysis of a bi-block track structure or through experimental calibration. The elements of the matrix... Indicates the first One active actuator When a unit displacement is generated, for the first The impact response caused by the pose of a key control point;

[0146] The three-dimensional spatial error vector of all key control points Combined into a total system error vector The control system calculates the cooperative displacement vector that optimally compensates for the total system error with minimal adjustment cost by solving a least-squares optimization problem with a regularization term. : ;

[0147] in: Here is the system influence matrix, where It represents the total number of error components monitored by the system.

[0148] The system's total error vector is composed of the error components of all control points;

[0149] For matrix Transpose of;

[0150] It is the identity matrix;

[0151] The regularization coefficient is used.

[0152] The optimal cooperative displacement vector Decomposed into individual active actuators Independent displacement commands (e.g., commanding actuator a1 to move vertically by -2.5mm, commanding actuator a2 to move laterally by +1.8mm, etc.) are sent as coordinated control commands to the corresponding actuators.

[0153] Example 7

[0154] This embodiment provides specific steps for continuous feedback adjustment, including:

[0155] During the movement of the position adjustment mechanism, the control unit repeatedly executes the measurement and deviation calculation steps, and updates the total system error vector in real time. ,in This is the current control cycle;

[0156] In each control cycle After completion, the control unit uses two conditional criteria to determine whether the adjustment process has converged and terminated. If either condition is not met, a new coordinated control command is generated and the next round of adjustment is initiated.

[0157] The two conditional criteria are:

[0158] Static accuracy condition: The Euclidean norm of the current system's total error vector is less than a preset position accuracy threshold. : This condition is only satisfied when the absolute magnitude of the error falls within the accuracy range required by the engineering requirements.

[0159] Dynamic stability condition: Between two consecutive control cycles, the change in the system's total error norm is less than the preset dynamic stability threshold. , This condition is only satisfied when the magnitude of the error itself no longer changes drastically and tends to stabilize.

[0160] in: They were respectively in the second and the The total system error vector for each control cycle; These are the preset position accuracy threshold and the dynamic stability threshold, respectively.

[0161] The control unit performs a logical AND operation on the results of the two criteria mentioned above. If both conditions are true, the control unit determines that the fine-tuning task has been completed with high quality and immediately stops all adjustment actions. Conversely, if either condition is not met, it indicates that the system has not yet reached the ideal precise and stable state, and the control unit will return to the instruction generation step described in the previous embodiment (such as Embodiment Six), generate new cooperative control instructions based on the latest error vector, and initiate the next round of adjustment.

[0162] Example 8

[0163] A dual-block intelligent track panel fine-tuning terminal includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the aforementioned dual-block intelligent track panel fine-tuning method.

[0164] Memory is used to store software programs and modules. The processor executes various terminal functions and data processing by running the software programs and modules stored in memory. Memory can mainly consist of a program storage area and a data storage area. The program storage area can store the operating system, at least one executable program required for a given function, etc.

[0165] The storage data area can store data created based on the use of the terminal. Furthermore, the memory can include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory, or other volatile solid-state storage devices.

[0166] A computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described dual-block intelligent track panel fine-tuning method.

[0167] Without loss of generality, computer-readable media can include computer storage media and communication media. Computer storage media includes volatile and non-volatile, removable and non-removable media implemented using any method or technology for storing information such as computer-readable instruction data structures, program modules, or other data. Computer storage media includes RAM, ROM, EPROM, EEPROM, flash memory or other solid-state storage technologies, CD-ROM, DVD or other optical storage, magnetic tape cassettes, magnetic tape, disk storage, or other magnetic storage devices. Of course, those skilled in the art will recognize that computer storage media are not limited to the above-mentioned types. The aforementioned system memories and mass storage devices can be collectively referred to as memory.

[0168] A computer program product includes a computer program / instructions that, when executed by a processor, implement the steps of the dual-block intelligent track fine-tuning method described above.

[0169] Computer program products include computer programs or instruction sets used to perform specific tasks or achieve specific functions. These programs or instructions are designed to be executed by a processor to implement a series of predefined steps or operations. The program product may be stored in various forms of computer storage media, such as memory, hard disks, solid-state drives, optical discs, or other forms of digital storage devices. It may exist in the form of compiled binary code or in the form of scripts or bytecode that can be executed by an interpreter. Through carefully designed algorithms and logical instructions, the program product enables the processor to process data in a specific order and manner, performing various functions such as data analysis, user interaction, and device control.

[0170] In the description of this specification, the references to terms such as "one embodiment / mode," "some embodiments / modes," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment / mode or example is included in at least one embodiment / mode or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment / mode or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments / modes or examples. Furthermore, without contradiction, those skilled in the art can combine and integrate the different embodiments / modes or examples described in this specification, as well as the features of different embodiments / modes or examples.

[0171] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0172] Those skilled in the art should understand that the above embodiments are merely for illustrating the present invention and are not intended to limit the scope of the invention. Those skilled in the art can make other changes or modifications based on the above invention, and these changes or modifications still fall within the scope of the present invention.

Claims

1. A method for fine-tuning a dual-block intelligent track panel, characterized in that, A dual-block intelligent track panel fine-tuning device is based on which the fine-tuning device includes: The spatial data acquisition unit (1) is used to acquire the current spatial position information of the reference component on the dual-block track panel; A position adjustment mechanism, which is connected to the double-block track, is used to adjust the spatial position of the reference component in two degrees of freedom, lateral and vertical. The control unit is communicatively connected to the spatial data acquisition unit (1) and the position adjustment mechanism. The control unit is configured to generate a control signal to drive the position adjustment mechanism to perform closed-loop adjustment of the position of the reference component based on the deviation between the current spatial position information obtained by the spatial data acquisition unit (1) and the preset target position information. The fine-tuning method includes: The position adjustment mechanism is installed on the double-block track panel, establishing a detachable mechanical connection between it and the stress interface on the steel truss; and the target position information, including track design parameters, is loaded into the control unit. The spatial data acquisition unit is activated to measure the reference components on the dual-block track panel and obtain their current spatial position information in real time. The current spatial position information is compared with the preset target position information to calculate the lateral and vertical deviations of the reference component, and a coordinated control command to drive the position adjustment mechanism is generated based on the deviation. The coordinated action command is sent to the position adjustment mechanism to drive the vertical adjustment actuator and the horizontal adjustment actuator to coordinate their actions and adjust the spatial position of the reference component; and during the adjustment process, the current spatial position information after adjustment is continuously fed back until the deviation between the latest current spatial position information and the target position information is less than the preset accuracy threshold. The coordinated control command for generating the driving position adjustment mechanism based on the deviation specifically includes the following steps: The control unit broadcasts a query signal and receives response signals from all installed and online vertical and horizontal adjustment actuators, thereby determining in real time the set of active actuators currently participating in the adjustment task. and their respective locations and types, among which This represents the total number of active actuators. Based on the finite element mechanical model of the two-block track, the system influence matrix is ​​established. Matrix elements Indicates the first One active actuator When a unit displacement is generated, for the first The impact response caused by the pose of a key control point; The three-dimensional spatial error vector of all key control points Combined into a total system error vector And calculate the cooperative displacement vector that can optimally compensate for the total system error with minimal adjustment cost. : ; in: This is the system influence matrix; The system's total error vector is composed of the error components of all control points; For matrix Transpose of; It is the identity matrix; The regularization coefficient is used. The optimal cooperative displacement vector Decomposed into individual active actuators The independent displacement command is sent as a cooperative control command to the corresponding actuator.

2. The dual-block intelligent track panel fine-tuning method according to claim 1, characterized in that, The specific steps for obtaining its current spatial location information in real time include: The reference component and its surrounding environment are scanned to obtain raw 3D point cloud data containing noise and outliers; The original 3D point cloud data is filtered and segmented to remove outliers and extract a set of valid target point clouds that represent only the baseline components. ,in A three-dimensional point in the target point cloud; Effective target point cloud Reference digital model with preset standard geometric shape Iterative registration is performed, and the target point cloud is determined by solving an optimization problem. Relative to the reference model The optimal rigid body transformation, and the objective function of the optimization problem are: ; in: Let be the optimal rotation matrix to be solved; For all rotation matrices; Let be the optimal translation vector to be solved; For all translation vectors; In the reference digital model Above, and the transformed point The corresponding nearest point; To assign point pairs The weights; After the iteration converges, the optimal solution will be... and Combined into a homogeneous transformation matrix, the current spatial position information of the reference component is obtained.

3. The dual-block intelligent track panel fine-tuning method according to claim 2, characterized in that, Weight The calculation method is as follows: ,in, This is the preset maximum allowable distance threshold.

4. The dual-block intelligent track panel fine-tuning method according to claim 2, characterized in that, The calculation steps for the lateral and vertical deviations of the reference component include: Reference digital model of the benchmark component Above, a set of predefined common Local coordinate set of key control points ; Using the optimal rotation matrix and optimal translation vector Calculate the current measurement position of each key control point in the global coordinate system. : ; Based on the design and construction location of the benchmark component, the design target location corresponding to each critical control point is retrieved from the target location information. ; Calculate the three-dimensional spatial error vector for each key control point. : ; Obtain the orthogonal basis vectors of the local coordinate system of the orbit at the design target location. ; Each three-dimensional spatial error vector By projecting onto the lateral and vertical basis vectors respectively, the lateral deviation components of each control point are obtained. and vertical deviation component ; The final lateral deviation of the reference component is calculated by weighted average. and final vertical deviation : ; in: The first Local coordinates, current measurement location, and design target location of each key control point; For the first The three-dimensional spatial error vector of each control point; These are the transverse basis vector, vertical basis vector, and longitudinal basis vector of the orbit, respectively. To be assigned to the Preset weighting coefficients for each key control point.

5. The dual-block intelligent track panel fine-tuning method according to claim 1, characterized in that, The specific steps for continuous feedback and adjustment include: During the movement of the position adjustment mechanism, the control unit repeatedly executes the measurement and deviation calculation steps, and updates the total system error vector in real time. ,in This is the current control cycle; In each control cycle After completion, the control unit uses two conditional criteria to determine whether the adjustment process has converged and terminated. If either condition is not met, a new coordinated control command is generated and the next round of adjustment is initiated. The two conditional criteria are: The Euclidean norm of the current system's total error vector is less than the preset position accuracy threshold. : ; Between two consecutive control cycles, the change in the system's total error norm is less than the preset dynamic stability threshold. , ; in: They were respectively in the second and the The total system error vector for each control cycle; These are the preset position accuracy threshold and the dynamic stability threshold, respectively.

6. The dual-block intelligent track panel fine-tuning method according to claim 1, characterized in that, The double-block track panel includes: a foundation base (2), sleepers (3), steel trusses (4), and rails (5); The lower side of the rail (5) is fixedly connected to the sleeper (3), the steel truss (4) is perpendicular to the rail (5) and fixedly connected to the rail (5), and the two ends of the steel truss (4) are provided with force-bearing interfaces connected to the position adjustment mechanism. The force-bearing interfaces are used to bear and transmit the lateral and / or vertical adjustment forces from the position adjustment mechanism. The spatial data acquisition unit (1) is a total station, a 3D laser scanner, or an industrial vision system.

7. The dual-block intelligent track panel fine-tuning method according to claim 6, characterized in that, The position adjustment mechanism includes: The force-bearing component (6) is detachably connected to the force-bearing interface; The support structure (7) is supported on the base base (2) during operation and provides a reaction force reference for adjustment; A vertical adjustment actuator (8) is installed on the support structure (7) to apply a vertical force to the force-bearing member (6) to adjust the elevation position of the steel truss (4); A lateral adjustment actuator (9), which is installed on the support structure (7) and / or the base (2), is used to apply a lateral force to the force-bearing member (6) to adjust the lateral position of the centerline of the steel truss (4).

8. The dual-block intelligent track panel fine-tuning method according to claim 7, characterized in that, The vertical adjustment actuator (8) and the horizontal adjustment actuator (9) are screw drive mechanisms; The lead screw transmission mechanism is provided with a drive interface, which is configured to be detachably connected to an external electric wrench to receive the rotational power input by the electric wrench and convert the rotational power into a linear force for achieving lateral or vertical adjustment.

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