Displacement deviation control method and system of vertical point

Abstract

The invention relates to the related technical field of survey deviation control, in particular to a displacement deviation control method and system for a vertical point, and the method comprises the steps: deploying a three-axis laser displacement sensor at a target vertical point, collecting displacement deviation data and a vibration spectrum, and generating a deviation feature set; according to the method, key nodes are marked according to a building framework, a displacement compensation vector is configured, a weight coefficient and an action time sequence are corrected based on load mass distribution, and a hydraulic leveling mechanism is driven to perform deviation correction control on displacement deviation of a target vertical point, so that the technical problem that the displacement deviation precision of the building vertical point is insufficient due to the influence of foundation settlement and environmental factors is solved; the technical effects that the displacement deviation is accurately controlled by deploying the high-precision three-axis laser displacement sensor, collecting the displacement deviation data and the environment vibration frequency spectrum in the vertical direction in real time, configuring the displacement compensation vector and dynamically adjusting the weight coefficient, and then the safety and stability of the whole structure are improved are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field related to the control of survey deviation, and particularly to a method and system for controlling the displacement deviation of vertical points. Background Art

[0002] With the continuous development of modern engineering construction technology, the accuracy requirements for the displacement deviation of vertical points of buildings are getting higher and higher. Especially in projects such as high-rise buildings, large bridges, and reservoir dams, the stable control of parameters such as the verticality and horizontal displacement of buildings is directly related to the safety and service life of the project. Commonly, GPS measurement of vertical deflection requires the application of leveling measurement technology to obtain the difference in geoid undulation or the difference in height anomaly, and generally it is used in combination with a precise level. However, due to the limitation of the accuracy of the instrument itself, the measurement accuracy is not high.

[0003] In summary, there is a technical problem in the prior art that the displacement deviation accuracy of the vertical points of buildings is insufficient due to the influence of foundation settlement and environmental factors. Summary of the Invention

[0004] This application provides a displacement deviation control system for vertical points, aiming to solve the technical problem in the prior art that the displacement deviation accuracy of the vertical points of buildings is insufficient due to the influence of foundation settlement and environmental factors.

[0005] In view of the above problems, the technical solution of this application is as follows: On the one hand, this application provides a method for controlling the displacement deviation of vertical points. The method includes: deploying a three-axis laser displacement sensor at the target vertical point, collecting displacement deviation data and environmental vibration spectra in the vertical direction, and generating a deviation feature set; marking key pile foundation nodes and building core nodes according to the engineering building structure where the reference plane corresponding to the target vertical point is located, and configuring a first displacement compensation vector associated with the target vertical point and the key pile foundation node and a second displacement compensation vector associated with the target vertical point and the building core node in combination with the deviation feature set; based on the load mass distribution parameters of the engineering building structure, correcting the weight coefficients and action time sequences of the first displacement compensation vector and the second displacement compensation vector; driving a hydraulic leveling actuator according to the first displacement compensation vector, the second displacement compensation vector, and the correction result to correct the displacement deviation of the target vertical point.

[0006] On the other hand, the present application provides a displacement deviation control system for a vertical point. The system includes: a data acquisition module for deploying a three-axis laser displacement sensor at the target vertical point to collect displacement deviation data and environmental vibration spectra in the vertical direction and generate a deviation feature set; a compensation vector configuration module for marking key pile foundation nodes and building core nodes according to the engineering building structure where the reference plane corresponding to the target vertical point is located, and configuring a first displacement compensation vector associated with the target vertical point and the key pile foundation nodes and a second displacement compensation vector associated with the target vertical point and the building core nodes in combination with the deviation feature set; a correction module for correcting the weight coefficients and action time sequences of the first displacement compensation vector and the second displacement compensation vector based on the load mass distribution parameters of the engineering building structure; and a deviation correction control module for driving a hydraulic leveling actuator according to the first displacement compensation vector and the second displacement compensation vector and the correction result to perform deviation correction control on the displacement deviation of the target vertical point.

[0007] In summary, one or more technical solutions provided in the present application achieve the technical effect of deploying a high-precision three-axis laser displacement sensor to collect displacement deviation data and environmental vibration spectra in the vertical direction in real time, configuring displacement compensation vectors and dynamically adjusting weight coefficients, realizing precise control of displacement deviation, and further improving the safety and stability of the overall structure. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1 is a schematic flow chart of the displacement deviation control method for a vertical point provided by the present application; Figure 2 is a schematic structural diagram of the displacement deviation control system for a vertical point provided by the present application.

[0009] Description of reference numerals: data acquisition module M100, compensation vector configuration module M200, correction module M300, deviation correction control module M400. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0010] Embodiment 1 The present application will be specifically described below with reference to the accompanying drawings. As Figure 1 shown, the present application provides a displacement deviation control method for a vertical point. The method includes: S1: Deploy a three-axis laser displacement sensor at the target vertical point to collect displacement deviation data and environmental vibration spectra in the vertical direction and generate a deviation feature set; S2: Mark key pile foundation nodes and building core nodes according to the engineering building structure where the reference plane corresponding to the target vertical point is located, and configure a first displacement compensation vector associated with the target vertical point and the key pile foundation nodes and a second displacement compensation vector associated with the target vertical point and the building core nodes in combination with the deviation feature set.

[0011] Specifically, deploying a three-axis laser displacement sensor at the target vertical point means installing a high-precision sensor that can measure displacements in three directions (X, Y, Z) simultaneously at the key vertical points of a building. It can collect displacement deviation data in the vertical direction. At the same time, it records the environmental vibration spectrum and generates a deviation feature set. The deviation feature set is a multi-dimensional data set that includes time series data of displacement deviation and vibration spectrum features for subsequent analysis and compensation; marking the key nodes of the pile foundation and the core nodes of the building means determining the key positions of the pile foundation and the core structure related to the vertical point on the reference plane of the building, which are the key points for the structural stability of the building; the displacement compensation vector represents the direction and magnitude of the displacement adjustment that needs to be applied.

[0012] Execution steps: Install a three-axis laser displacement sensor at the vertical point of the building, which can collect displacement deviation data in the vertical direction and the environmental vibration spectrum in real time. For example, in a high-rise building, the sensor collects data at a sampling rate of 10 Hz and generates a deviation feature set that includes the time series of displacement deviation and vibration spectrum features; according to the reference plane of the building, mark the key nodes of the pile foundation (such as the top and bottom of the pile foundation) and the core nodes of the building (such as the core tube, shear wall), which are the key points for the structural stability of the building and can reflect the overall displacement trend of the building.

[0013] Combined with the deviation feature set, configure displacement compensation vectors for each target vertical point, key pile foundation node, and core building node. Further, through the displacement deviation time series and vibration spectrum features in the deviation feature set, calculate the first displacement compensation vector associated with the key pile foundation node and the second displacement compensation vector associated with the core building node. The first and second displacement compensation vectors can accurately describe the adjustment direction and magnitude of the displacement deviation. Preferably, the high-precision measurement ability of the three-axis laser displacement sensor can capture tiny displacement deviations and environmental vibration spectra, and the generation of the deviation feature set provides a data basis for subsequent intelligent compensation; the marking of the key pile foundation nodes and core building nodes can ensure that the configuration of the compensation vectors is targeted and improve the accuracy of the deviation correction control.

[0014] S3: Based on the load mass distribution parameters of the engineering building structure, correct the weight coefficients and action timings of the first displacement compensation vector and the second displacement compensation vector; S4: According to the first displacement compensation vector and the second displacement compensation vector, combined with the correction results, drive the hydraulic leveling actuator to perform deviation correction control on the displacement deviation of the target vertical point.

[0015] Specifically, the load mass distribution parameter refers to the mass distribution of a building at different structural points, usually represented in the form of a mass matrix or distribution map; the weight coefficient is a parameter in the displacement compensation vector used to adjust the influence of the compensation vector; the action time sequence refers to the application order and duration of the compensation vector over time; the hydraulic leveling actuator is a mechanical device that can adjust the vertical point position of a building according to a control signal and is usually used for deviation correction control.

[0016] Execution steps: Dynamically adjust the weight coefficients and action time sequences of the first displacement compensation vector and the second displacement compensation vector according to the load mass distribution parameter of the building. Further, if a certain area of the building has a heavy load, increase the weight coefficient of the compensation vector in that area and at the same time adjust the action time sequence to ensure the compensation effect; if the load mass distribution parameter shows that the top of the building has a heavy load, adjust the weight coefficient of the top compensation vector from 0.5 to 0.7 and at the same time advance the action time sequence by 10 milliseconds to respond more quickly to displacement deviation.

[0017] Drive the hydraulic leveling actuator to perform deviation correction control on the displacement deviation of the target vertical point according to the corrected displacement compensation vector. The hydraulic leveling actuator precisely adjusts the position of the vertical point according to the direction and magnitude of the compensation vector; the analysis of the load mass distribution parameter can provide detailed information about the building load, enabling the weight coefficients and action time sequences of the compensation vector to be dynamically adjusted according to the actual load situation, and the high-precision control ability of the hydraulic leveling actuator ensures the accuracy and stability of the deviation correction operation.

[0018] Furthermore, the method further includes: Symmetrically arrange dual-frequency laser interferometers at the four corners of the reference plane; based on the dual-frequency laser interferometers, set the first data synchronization constraint condition; wherein, under the condition of a preset sampling rate interval, the time alignment error under the first data synchronization constraint condition meets the preset stability requirement.

[0019] Specifically, a dual-frequency laser interferometer is a high-precision measuring instrument that can simultaneously emit two different frequencies of laser light and is used to measure physical quantities such as displacement and vibration; the reference plane is a reference plane of the building used to locate and measure the positions of other points; the data synchronization constraint condition refers to the condition for ensuring the time alignment of data from different sensors during the data acquisition process; the time alignment error refers to the time difference between data from different sensors, and the stability requirement refers to the accuracy requirement that the time alignment error after data synchronization must meet.

[0020] Execution steps: Dual-frequency laser interferometers are symmetrically arranged at the four corners of the reference plane to ensure that each corner can be accurately measured. The symmetrical arrangement can provide comprehensive displacement and vibration data, improving the accuracy and reliability of the measurement. Exemplarily, for a square reference plane with a side length of 10 meters, dual-frequency laser interferometers are arranged at each corner to cover the measurement requirements of the entire plane; based on the dual-frequency laser interferometers, a first data synchronization constraint condition is set to ensure that within a preset sampling rate interval, the time alignment error meets the preset stability requirements. Preferably, the preset sampling rate is 100 Hz, and the time alignment error needs to be controlled within 1 millisecond to ensure data synchronization and stability. Through precise time alignment, data deviation between different sensors is eliminated, improving the overall measurement accuracy; the high-precision measurement ability of the dual-frequency laser interferometers can provide accurate displacement and vibration data, and the data synchronization constraint condition ensures the time consistency of multi-sensor data, thereby improving the measurement accuracy and reliability of the entire system.

[0021] Furthermore, the method further includes: Based on the reference plane, a capacitive micro-displacement probe is configured along the vertical axis direction; based on the capacitive micro-displacement probe, a second data synchronization constraint condition is set; wherein, under the condition of a preset resolution interval, the frequency-domain aliasing suppression ratio defined by the second data synchronization constraint condition meets the preset accuracy requirements.

[0022] Specifically, the capacitive micro-displacement probe detects minute displacements through capacitance changes; the reference plane is a reference surface of a building used for positioning and measuring the positions of other points; the data synchronization constraint condition refers to the condition for ensuring the time alignment of data from different sensors during data acquisition; the frequency-domain aliasing suppression ratio refers to the ability to suppress aliasing phenomena in frequency-domain analysis, and the aliasing phenomenon is the misjudgment of high-frequency signals as low-frequency signals due to insufficient sampling rate; the preset accuracy requirement refers to the accuracy requirement that the frequency-domain aliasing suppression ratio must meet after data synchronization.

[0023] Execution steps: On the reference plane, a capacitive micro-displacement probe is configured along the vertical axis direction to measure minute displacement changes in the vertical direction and output high-resolution displacement data; based on the capacitive micro-displacement probe, a second data synchronization constraint condition is set to ensure that within a preset resolution interval, the frequency-domain aliasing suppression ratio meets the preset accuracy requirements. Preferably, the preset resolution is 0.1 micrometer, and the frequency-domain aliasing suppression ratio needs to reach above 40 dB to ensure data reliability and accuracy; through precise frequency-domain aliasing suppression, the influence of high-frequency noise can be eliminated, improving data accuracy; the high-resolution measurement ability of the capacitive micro-displacement probe can capture minute displacement changes, and the data synchronization constraint condition ensures the time consistency of multi-sensor data, thereby improving the measurement accuracy and reliability of the entire system.

[0024] Furthermore, configure a first displacement compensation vector associated with the target vertical point and the key pile foundation nodes. The method includes: Perform spatial grid pre-partitioning on the reference plane through the target vertical point and the key pile foundation nodes to obtain a plurality of first pre-partitioned spatial grids; based on the plurality of first pre-partitioned spatial grids, perform multi-scale association with the deviation feature set to configure the first displacement compensation vector.

[0025] Specifically, the target vertical point is a key point in the building where displacement deviation control is required; the key pile foundation nodes are important nodes in the building pile foundation structure and are usually closely related to the displacement deviation of the vertical point; the reference plane is a reference plane of the building used to locate and measure the positions of other points; spatial grid pre-partitioning refers to dividing the reference plane into multiple small spatial units for more accurate analysis and data processing; the deviation feature set is a multi-dimensional data set containing time series data of displacement deviation and vibration spectrum features; multi-scale association refers to analyzing the correlation between data at different scales (such as time scale and spatial scale); the displacement compensation vector is a mathematical model for deviation correction, indicating the direction and magnitude of the displacement adjustment to be applied.

[0026] Execute the steps: Perform spatial grid pre-partitioning on the reference plane through the target vertical point and the key pile foundation nodes to obtain a plurality of first pre-partitioned spatial grids. For example, in a high-rise building, the reference plane can be divided into a 10×10 grid, and each grid cell represents a specific spatial area. This division can help more accurately locate and analyze the source of displacement deviation; by analyzing the displacement deviation time series and vibration spectrum features in the deviation feature set and combining with the position information of the spatial grid, calculate the displacement compensation requirements for each grid cell. Further, if the displacement deviation of a certain grid cell is 3 millimeters and the vibration spectrum shows a vibration with a dominant modal frequency of 15 Hz, a compensation vector can be configured with a direction opposite to the offset direction and a compensation amount of 3 millimeters. At the same time, considering the influence of the vibration frequency, adjust the timing and amplitude of the compensation vector. Spatial grid pre-partitioning can decompose complex displacement deviation problems into problems of multiple small regions, making the analysis and processing more accurate; multi-scale association analysis can comprehensively consider time and space factors, improving the accuracy and effectiveness of the displacement compensation vector.

[0027] Furthermore, based on the plurality of first pre-partitioned spatial grids, perform multi-scale association with the deviation feature set to configure the first displacement compensation vector. The method includes: Based on the deviation feature set, a bidirectional LSTM network is used to extract the long-term dependence features of the displacement deviation time series, where the number of hidden layer nodes of the bidirectional LSTM network is N; based on multiple first pre-partitioned spatial grids, a three-dimensional convolution kernel is used to capture the spatial correlation pattern, and the feature channels are extended to M dimensions, where M < N; according to the long-term dependence features of the displacement deviation time series, combined with the spatial correlation pattern, a gated attention mechanism is set up to perform prominent deviation correction control on the first displacement compensation vector with attention coefficients.

[0028] Specifically, the deviation feature set is a multi-dimensional data set containing time series data of displacement deviation and vibration spectrum features for subsequent analysis and compensation; the bidirectional LSTM network (Bidirectional Long Short-Term Memory Network) is a neural network that can simultaneously process the forward and reverse information of time series data and is suitable for extracting long-term dependence features; the number of hidden layer nodes refers to the number of nodes in the hidden layer of the neural network, which determines the complexity and processing ability of the network; the three-dimensional convolution kernel is a convolution kernel used to capture the three-dimensional spatial data correlation pattern and is commonly used in image and spatial data processing; feature channel expansion refers to expanding the feature data to a higher dimension to enhance the feature expression ability; the gated attention mechanism is a mechanism that dynamically adjusts the feature weights through a gated unit and attention coefficients and is used to highlight important features; the attention coefficient is a weight value used to measure the importance of features, and a higher attention coefficient indicates that the feature is more important in the current task.

[0029] Execute the steps: Based on the deviation feature set, use a bidirectional LSTM network to extract the long-term dependence features of the displacement deviation time series. The bidirectional LSTM network can simultaneously process the forward and reverse information of the time series, capture more comprehensive features, and thus more accurately predict the trend of displacement deviation; based on multiple first pre-partitioned spatial grids, use a three-dimensional convolution kernel to capture the spatial correlation pattern. The three-dimensional convolution kernel can analyze the correlation of the spatial grids in three dimensions, such as the displacement correlation in the X, Y, and Z directions, and extend the feature channels to M dimensions. Preferably, M < N, which can more efficiently express the spatial features.

[0030] According to the long-term dependence characteristics and spatial correlation patterns of the displacement deviation time series, a gated attention mechanism is set. The gated attention mechanism dynamically adjusts the weight of the first displacement compensation vector through the attention coefficient, highlighting the deviation correction characteristics. If the displacement deviation characteristics of a certain spatial grid show strong long-term dependence in the time series, the gated attention mechanism will assign a higher attention coefficient to enhance the influence of this feature in the compensation vector. The powerful time series processing ability of the bidirectional LSTM network can capture the long-term trend of the displacement deviation, the spatial analysis ability of the three-dimensional convolution kernel can extract the correlation patterns of the spatial grid, and the gated attention mechanism can dynamically adjust the feature weights to highlight the important deviation correction features.

[0031] Furthermore, the method includes: Based on multiple first pre-divided spatial grids, extract the dominant modal frequency in the vibration spectrum; when the frequency offset between the dominant modal frequency and the natural frequency is less than the set frequency threshold, activate the dynamic vibration absorber, and the position of the mass block of the dynamic vibration absorber is adjusted in real time by a servo motor.

[0032] Specifically, the vibration spectrum is a representation method for describing the vibration characteristics of an object. Usually, the time-domain signal is converted into a frequency-domain signal through Fourier transform to display the amplitudes of different frequency components; in the vibration spectrum, the frequency component with the largest amplitude is the dominant modal frequency; the natural vibration frequency of the structure without external force, the natural frequency is determined by the physical characteristics of the structure (such as mass, stiffness); the frequency offset refers to the difference between the current vibration frequency and the natural frequency; the set frequency threshold is a pre-set frequency difference value, when the actual frequency offset is less than this threshold, a specific control action is triggered; the dynamic vibration absorber is a device that can absorb vibrations of a specific frequency by adjusting its own parameters (such as mass, stiffness, damping); the servo motor is a motor that can accurately control position, speed and acceleration, and is used in occasions that require high-precision adjustment.

[0033] Execute the steps: Based on multiple first pre-divided spatial grids, analyze the vibration spectrum and extract the dominant modal frequency therein. Specifically, in a high-rise building, by analyzing the vibration spectra of different spatial grids, it is found that the dominant modal frequency is 10 Hz, which indicates that the building vibrates most significantly at this frequency; calculate the frequency offset between the dominant modal frequency and the natural frequency of the building. If the natural frequency is 10.2 Hz and the dominant modal frequency is 10 Hz, then the frequency offset is 0.2 Hz; when the frequency offset is less than the set frequency threshold (such as 0.3 Hz), activate the dynamic vibration absorber, and the dynamic vibration absorber changes its resonant frequency by adjusting the position of its own mass block to match the external excitation frequency, thereby absorbing vibration energy.

[0034] The position of the mass block of the dynamic vibration absorber is adjusted in real time by a servo motor. The servo motor precisely adjusts the position of the mass block according to the control signal to ensure that the resonant frequency of the dynamic vibration absorber is consistent with the current vibration frequency. Vibration spectrum analysis can accurately identify the dominant modal frequency, and frequency offset detection ensures that measures are taken in a timely manner when approaching the natural frequency. The combined use of the dynamic vibration absorber and the servo motor can adjust the parameters of the vibration absorber in real time and effectively suppress vibration.

[0035] Furthermore, the position of the mass block of the dynamic vibration absorber is adjusted in real time by a servo motor, and the method includes: Through PID control, determine the target displacement of the mass block, where the integral term weight coefficient is negatively correlated with the absolute value of the frequency offset; drive the servo motor to move the mass block to the coordinate position corresponding to the target displacement, and combine the energy decay rate to inversely optimize the amplitude-phase parameters of the target displacement until the resonant frequency of the dynamic vibration absorber matches the external excitation frequency.

[0036] Specifically, PID control (Proportional-Integral-Derivative Control) is a commonly used feedback control algorithm that adjusts the output of the system through three terms: proportional, integral, and derivative; the integral term weight coefficient refers to the weight coefficient of the integral term in PID control, which is used to adjust the influence of the integral term on the control output; the absolute value of the frequency offset: the absolute value of the difference between the current vibration frequency and the target frequency; a servo motor is a motor that can precisely control position, speed, and acceleration; the target displacement refers to the displacement that the mass block of the dynamic vibration absorber needs to move to; the energy decay rate refers to the speed at which the vibration energy decays over time, which is usually used to evaluate the vibration suppression effect; the amplitude-phase parameters refer to the parameters that describe the amplitude and phase of the vibration signal and are used to optimize the performance of the dynamic vibration absorber.

[0037] Execute the steps: Through the PID control algorithm, determine the target displacement of the mass block according to the absolute value of the frequency offset, where the integral term weight coefficient is negatively correlated with the absolute value of the frequency offset, that is, the smaller the frequency offset, the lower the weight coefficient of the integral term. Specifically, if the frequency offset is 0.2 Hz, the integral term weight coefficient is set to 0.5; if the frequency offset is reduced to 0.1 Hz, the integral term weight coefficient is reduced to 0.3. This negative correlation ensures that when approaching the target frequency, the control action is smoother and over-adjustment is avoided.

[0038] Based on the target displacement determined by PID control, drive the servo motor to move the mass block to the corresponding target position. The servo motor can adjust the position of the mass block with high precision (such as 0.01 mm) to ensure that the resonant frequency of the dynamic vibration absorber matches the external excitation frequency; combined with the energy attenuation rate, reverse-optimize the amplitude and phase parameters of the target displacement. The energy attenuation rate reflects the reduction speed of vibration energy. By optimizing the amplitude and phase parameters, further improve the performance of the dynamic vibration absorber. By optimizing the amplitude and phase parameters, the energy attenuation rate can be increased, thereby suppressing vibration faster. PID control can dynamically adjust the target displacement of the mass block to ensure that the resonant frequency of the dynamic vibration absorber matches the external excitation frequency. The high-precision adjustment ability of the servo motor ensures the accurate movement of the mass block, and the optimization of the energy attenuation rate further improves the vibration suppression effect.

[0039] - Further, configure a second displacement compensation vector associated with the target vertical point and the building core node. The method includes: Perform spatial grid pre-partitioning on the reference plane through the target vertical point and the building core node to obtain a plurality of second pre-partitioned spatial grids; based on the plurality of second pre-partitioned spatial grids, perform multi-scale association with the deviation feature set to configure the second displacement compensation vector.

[0040] Specifically, the target vertical point refers to the key point in the building where displacement deviation control is required; the building core node refers to the key point of the building's core structure, which is usually closely related to the stability and deformation of the structure; the reference plane refers to a reference plane of the building for positioning and measuring the positions of other points; spatial grid pre-partitioning refers to dividing the reference plane into multiple small spatial units for more accurate analysis and data processing; the deviation feature set includes the time series data of displacement deviation and the multi-dimensional data set of vibration spectrum features; the displacement compensation vector is a mathematical model for deviation correction, representing the direction and magnitude of the displacement adjustment that needs to be applied.

[0041] Execute the steps: perform spatial grid pre-partitioning on the reference plane through the target vertical point and the building core node to obtain a plurality of second pre-partitioned spatial grids, and each second pre-partitioned spatial grid represents a specific spatial area; based on the divided second pre-partitioned spatial grids, perform multi-scale association with the deviation feature set to configure the second displacement compensation vector. Specifically, by analyzing the displacement deviation time series and vibration spectrum features in the deviation feature set, combined with the position information of the spatial grid, calculate the displacement compensation requirements of each grid unit, and at the same time consider the influence of the vibration frequency to adjust the timing and amplitude of the compensation vector. Spatial grid pre-partitioning can decompose complex displacement deviation problems into problems of multiple small regions, making the analysis and processing more accurate. Multi-scale association analysis can comprehensively consider time and space factors to improve the accuracy and effectiveness of the displacement compensation vector.

[0042] Furthermore, based on multiple second pre-partitioned spatial grids, perform multi-scale association with the deviation feature set and configure a second displacement compensation vector. The method includes: Construct a topological relationship graph of the building core nodes, where each node in the topological relationship graph represents a building core structure point, and each edge in the topological relationship graph represents the structural connection stiffness; extract features from the topological relationship graph to generate a structural topology embedding pointer; perform cross-modal fusion of the structural topology embedding pointer and the deviation feature set, and assign association weights corresponding to multiple second pre-partitioned spatial grids; generate a second displacement compensation vector based on the multi-scale features after cross-modal fusion; the compensation direction of the second displacement compensation vector is reversely matched with the structural deformation trend of the building core nodes.

[0043] Specifically, a building core node refers to a key point of the core structure of a building, which is usually closely related to the stability and deformation of the structure; the topological relationship graph is used to represent the connection relationship and stiffness between building core nodes; the structural connection stiffness is used to describe the rigidity degree of the connection between building core nodes, usually represented by a numerical value; the association weight represents the importance of different spatial grids in the fused features; the compensation direction is the direction of the displacement compensation vector, which is used for rectification; the structural deformation trend refers to the deformation direction and degree of the building core nodes under force or vibration.

[0044] Execute the steps: construct a topological relationship graph of the building core nodes, where the nodes represent building core structure points and the edges represent structural connection stiffness. Specifically, in high-rise buildings, key structural points such as core tubes and shear walls are used as nodes, and the connection stiffness between the nodes is used as the weight of the edges to construct the topological relationship graph of the building core nodes, visually representing the connection relationship and stiffness distribution of the building core structure; extract features from the topological relationship graph to generate a structural topology embedding pointer. Further, each node in the topological relationship graph represents a building core structure point, and each edge in the topological relationship graph represents the structural connection stiffness, and is converted into an embedding pointer through a graph neural network (GNN).

[0045] Perform cross-modal fusion of the structural topology embedding pointer and the deviation feature set, and assign association weights corresponding to multiple second pre-partitioned spatial grids. Specifically, through the attention mechanism, weights are assigned to each spatial grid according to the correlation between the topological features and the deviation features, and the grids with higher weights play a greater role in compensation; based on the multi-scale features after cross-modal fusion, generate a second displacement compensation vector. The compensation direction is reversely matched with the structural deformation trend of the building core node to ensure that the compensation vector can effectively correct the structural deformation. The topological relationship graph can accurately represent the connection and stiffness distribution of the building core structure, and feature extraction and embedding pointer generation enable the topological information to be fused with the deviation feature set. Cross-modal fusion and weight assignment ensure the pertinence and effectiveness of the compensation vector.

[0046] In summary, the beneficial effects of the embodiments of the present application are as follows: By deploying a three-axis laser displacement sensor at the target vertical point, collecting displacement deviation data and environmental vibration spectra in the vertical direction to generate a deviation feature set; marking the pile foundation key nodes and building core nodes according to the engineering building structure where the reference plane corresponding to the target vertical point is located, and configuring a first displacement compensation vector associated with the target vertical point and the pile foundation key node, and a second displacement compensation vector associated with the target vertical point and the building core node; based on the load mass distribution parameters of the engineering building structure, correcting the weight coefficients and action time sequences of the first displacement compensation vector and the second displacement compensation vector; according to the first displacement compensation vector and the second displacement compensation vector, combined with the correction results, driving the hydraulic leveling actuator to perform deviation correction control on the displacement deviation of the target vertical point. The present application provides a displacement deviation control method and system for the vertical point. By deploying a high-precision three-axis laser displacement sensor, real-time collecting displacement deviation data and environmental vibration spectra in the vertical direction, configuring displacement compensation vectors and dynamically adjusting weight coefficients, the precise control of the displacement deviation is realized, thereby improving the technical effects of the safety and stability of the overall structure.

[0047] Embodiment 2 Based on the same inventive concept as the vertical point displacement deviation control method in the foregoing embodiment, as Figure 2 shown, the embodiments of the present application provide a vertical point displacement deviation control system, wherein the system includes: A data acquisition module M100, configured to deploy a three-axis laser displacement sensor at the target vertical point, collect displacement deviation data and environmental vibration spectra in the vertical direction, and generate a deviation feature set.

[0048] The compensation vector configuration module M200 is used to mark the key pile foundation nodes and the building core nodes according to the engineering building structure where the reference plane corresponding to the target vertical point is located, and configure a first displacement compensation vector associated with the target vertical point and the key pile foundation nodes and a second displacement compensation vector associated with the target vertical point and the building core nodes in combination with the deviation feature set.

[0049] The correction module M300 is used to correct the weight coefficients and action time sequences of the first displacement compensation vector and the second displacement compensation vector based on the load mass distribution parameters of the engineering building structure.

[0050] The deviation correction control module M400 is used to drive the hydraulic leveling actuator to perform deviation correction control on the displacement deviation of the target vertical point according to the first displacement compensation vector, the second displacement compensation vector and in combination with the correction result.

[0051] Furthermore, the data acquisition module M100 is also used to execute the following method: Dual-frequency laser interferometers are symmetrically arranged at the four corners of the reference plane; based on the dual-frequency laser interferometers, a first data synchronization constraint condition is set; wherein, under the condition of a preset sampling rate interval, the time alignment error limited by the first data synchronization constraint condition meets the preset stability requirement.

[0052] Furthermore, the data acquisition module M100 is also used to execute the following method: Capacitive micro displacement probes are arranged along the vertical axis direction based on the reference plane; based on the capacitive micro displacement probes, a second data synchronization constraint condition is set; wherein, under the condition of a preset resolution interval, the frequency domain aliasing suppression ratio limited by the second data synchronization constraint condition meets the preset accuracy requirement.

[0053] Furthermore, the compensation vector configuration module M200 is used to execute the following method: The reference plane is pre-divided into a plurality of first pre-divided spatial grids through the target vertical point and the key pile foundation nodes; based on the plurality of first pre-divided spatial grids, multi-scale association is performed with the deviation feature set to configure the first displacement compensation vector.

[0054] Furthermore, the compensation vector configuration module M200 is also used to execute the following method: Based on the deviation feature set, a bidirectional LSTM network is used to extract the long-term dependence features of the displacement deviation time series, where the number of hidden layer nodes of the bidirectional LSTM network is N; based on multiple first pre-partitioned spatial grids, a three-dimensional convolution kernel is used to capture the spatial association pattern, and the feature channels are extended to M dimensions, where M < N; according to the long-term dependence features of the displacement deviation time series, combined with the spatial association pattern, a gated attention mechanism is set to perform prominent deviation correction control on the first displacement compensation vector with attention coefficients.

[0055] Further, the compensation vector configuration module M200 is further configured to execute the following method: Based on multiple first pre-partitioned spatial grids, the dominant modal frequency in the vibration spectrum is extracted; when the frequency offset between the dominant modal frequency and the natural frequency is less than the set frequency threshold, the dynamic vibration absorber is activated, and the position of the mass block of the dynamic vibration absorber is adjusted in real time by a servo motor.

[0056] Further, the compensation vector configuration module M200 is further configured to execute the following method: Through PID control, the target displacement of the mass block is determined, where the integral term weight coefficient is negatively correlated with the absolute value of the frequency offset; the servo motor is driven to move the mass block to the coordinate position corresponding to the target displacement, and in combination with the energy attenuation rate, the amplitude-phase parameters of the target displacement are reversely optimized until the resonance frequency of the dynamic vibration absorber matches the external excitation frequency.

[0057] Further, the compensation vector configuration module M200 is configured to execute the following method: Through the target vertical point and the building core node, the reference reference plane is pre-partitioned into spatial grids to obtain multiple second pre-partitioned spatial grids; based on the multiple second pre-partitioned spatial grids, multi-scale association is performed with the deviation feature set to configure a second displacement compensation vector.

[0058] Further, the compensation vector configuration module M200 is further configured to execute the following method: Construct a topological relationship graph of the building core node, where each node in the topological relationship graph represents a building core structure point, and each edge in the topological relationship graph represents the structural connection stiffness; feature extraction is performed on the topological relationship graph to generate a structural topology embedding pointer; the structural topology embedding pointer is cross-modally fused with the deviation feature set to assign association weights corresponding to multiple second pre-partitioned spatial grids; based on the multi-scale features after cross-modal fusion, a second displacement compensation vector is generated; the compensation direction of the second displacement compensation vector is reversely matched with the structural deformation trend of the building core node.

[0059] In summary, any step can be stored as computer instructions or programs in an unrestricted computer memory and can be called and recognized by an unrestricted computer processor, without any additional restrictions here.

[0060] Furthermore, the above technical solutions only reflect the preferred technical solutions of the technical solutions of the embodiments of the present application. Some changes that those skilled in the art may make to some parts thereof all reflect the principles of the novelty of the embodiments of the present application. Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the scope of the present application.

Claims

1. A method for controlling the displacement deviation of a vertical point, characterized in that, The method includes: Deploy a three-axis laser displacement sensor at the target vertical point to collect displacement deviation data and environmental vibration spectra in the vertical direction, and generate a deviation feature set; According to the engineering building structure where the reference plane corresponding to the target vertical point is located, mark the key pile foundation nodes and the core building nodes, and configure a first displacement compensation vector associated with the target vertical point and the key pile foundation nodes, and a second displacement compensation vector associated with the target vertical point and the core building nodes in combination with the deviation feature set; Based on the load mass distribution parameters of the engineering building structure, correct the weight coefficients and action time sequences of the first displacement compensation vector and the second displacement compensation vector; According to the first displacement compensation vector and the second displacement compensation vector, and in combination with the correction result, drive the hydraulic leveling actuator to perform deviation correction control on the displacement deviation of the target vertical point.

2. The method for controlling the displacement deviation of the vertical point according to claim 1, wherein The method further includes: Symmetrically arrange dual-frequency laser interferometers at the four corners of the reference plane; Based on the dual-frequency laser interferometers, set a first data synchronization constraint condition; Among them, under the condition of a preset sampling rate interval, the time alignment error under the limitation of the first data synchronization constraint condition meets the preset stability requirement.

3. The method for controlling the displacement deviation of the vertical point according to claim 2, wherein The method further includes: Configure capacitive micro displacement probes along the vertical axis direction based on the reference plane; Based on the capacitive micro displacement probes, set a second data synchronization constraint condition; Among them, under the condition of a preset resolution interval, the frequency domain aliasing suppression ratio under the limitation of the second data synchronization constraint condition meets the preset accuracy requirement.

4. The method for controlling the displacement deviation of the vertical point according to claim 3, characterized in that Configure a first displacement compensation vector associated with the target vertical point and the key pile foundation nodes. The method includes: Perform spatial grid pre-partitioning on the reference plane through the target vertical point and the key pile foundation nodes to obtain a plurality of first pre-partitioned spatial grids; Based on the plurality of first pre-partitioned spatial grids, perform multi-scale association with the deviation feature set to configure the first displacement compensation vector.

5. The displacement deviation control method of the vertical point according to claim 4, characterized in that, Based on the plurality of first pre-partitioned spatial grids, perform multi-scale association with the deviation feature set to configure the first displacement compensation vector. The method includes: Based on the deviation feature set, use a bidirectional LSTM network to extract the long-term dependence features of the displacement deviation time series, where the number of hidden layer nodes of the bidirectional LSTM network is N; Based on the plurality of first pre-partitioned spatial grids, use a three-dimensional convolution kernel to capture the spatial association pattern and expand the feature channels to M dimensions, where M < N; According to the long-term dependence features of the displacement deviation time series, in combination with the spatial association pattern, set a gated attention mechanism to perform prominent deviation correction control on the first displacement compensation vector with attention coefficients.

6. The method for controlling the displacement deviation of the vertical point according to claim 5, wherein The method includes: Extract the dominant modal frequency in the vibration spectrum based on the plurality of first pre-partitioned spatial grids; When the frequency offset between the dominant modal frequency and the natural frequency is less than the set frequency threshold, activate the dynamic vibration absorber, and the position of the mass block of the dynamic vibration absorber is adjusted in real time by a servo motor.

7. The method for controlling the displacement deviation of the vertical point according to claim 6, wherein, The position of the mass block of the dynamic vibration absorber is adjusted in real time by a servo motor. The method includes: Determine the target displacement of the mass block through PID control, where the integral term weight coefficient is negatively correlated with the absolute value of the frequency offset; Drive the servo motor to move the mass block to the coordinate position corresponding to the target displacement, and combine the energy attenuation rate to reversely optimize the amplitude-phase parameters of the target displacement until the resonance frequency of the dynamic vibration absorber matches the external excitation frequency.

8. The method for controlling the displacement deviation of the vertical point according to claim 4, wherein Configure a second displacement compensation vector associated with the target vertical point and the building core node. The method includes: Perform spatial grid pre-partitioning on the reference plane through the target vertical point and the building core node to obtain a plurality of second pre-partitioned spatial grids; Based on the plurality of second pre-partitioned spatial grids, perform multi-scale association with the deviation feature set to configure the second displacement compensation vector.

9. The method for controlling the displacement deviation of the vertical point according to claim 8, characterized in that, Based on the plurality of second pre-partitioned spatial grids, perform multi-scale association with the deviation feature set to configure the second displacement compensation vector. The method includes: Construct a topological relationship graph of the building core node, where each node in the topological relationship graph represents a building core structure point, and each edge in the topological relationship graph represents the structural connection stiffness; Extract features from the topological relationship graph to generate a structural topology embedding pointer; Perform cross-modal fusion of the structural topology embedding pointer and the deviation feature set, and assign association weights corresponding to the plurality of second pre-partitioned spatial grids; Generate a second displacement compensation vector based on the multi-scale features after cross-modal fusion; The compensation direction of the second displacement compensation vector is reversely matched with the structural deformation trend of the building core node.

10. A vertical point displacement deviation control system, characterized in that For implementing the vertical point displacement deviation control method according to any one of claims 1-9, the system includes: A data acquisition module for deploying a three-axis laser displacement sensor at the target vertical point to collect displacement deviation data and environmental vibration spectra in the vertical direction and generate a deviation feature set; A compensation vector configuration module for marking the key pile foundation nodes and building core nodes according to the engineering building structure where the reference plane corresponding to the target vertical point is located, and combining the deviation feature set to configure a first displacement compensation vector associated with the target vertical point and the key pile foundation node, and a second displacement compensation vector associated with the target vertical point and the building core node; A correction module for correcting the weight coefficients and action timings of the first displacement compensation vector and the second displacement compensation vector based on the load mass distribution parameters of the engineering building structure; A deviation correction control module for driving a hydraulic leveling actuator to perform deviation correction control on the displacement deviation of the target vertical point according to the first displacement compensation vector, the second displacement compensation vector, and the correction result.

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