Distributed spatial displacement measurement method, device, storage medium and system
By installing multiple tilt sensors on structures such as long-span bridges, and performing data filtering and fitting, the problems of high cost and low stability in traditional methods are solved, achieving high-precision distributed displacement monitoring, which is suitable for real-time monitoring in complex environments.
Patent Information
- Application Number
- CN202511176625.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-08-21
- Publication Date
- 2025-11-21
AI Technical Summary
Traditional displacement measurement methods are difficult to meet the long-term, dynamic, and high-precision monitoring needs of complex projects such as long-span bridges. They are also costly and have poor stability. Traditional methods are limited by environmental factors and cannot achieve distributed displacement monitoring.
A distributed spatial displacement measurement method is adopted. By setting multiple tilt sensors on the structure under test, the raw tilt data is acquired, filtered and fitted with cubic smooth splines to generate tilt curves, which are then integrated into deflection curves. Combined with Kalman filtering and deep Bayesian optimization algorithms, spatial displacement measurement is achieved.
It achieves high-precision, low-cost distributed displacement monitoring, improves the stability and adaptability of the system, and enables real-time monitoring of spatial displacement changes of structures in complex environments.
Smart Images
Figure CN120992137A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of spatial displacement measurement in the construction industry, and particularly to a distributed spatial displacement measurement method, device, storage medium, and system. Background Technology
[0002] In engineering mechanics and structural analysis, displacement is a key indicator for measuring the deformation of a structure under external forces. Currently, displacement is mainly measured through deflection measurement methods, where deflection refers to the vertical displacement of a structure (such as a beam or slab) when subjected to external forces. However, traditional deflection measurement methods are insufficient to fully meet the long-term, dynamic, and high-precision monitoring needs of complex projects such as long-span bridges. Currently, there are also tilt-based displacement calculation methods on the market, which are applied in engineering practice. However, their piecewise superposition calculation method leads to significant errors due to linear superposition, making it difficult to achieve high precision. Although various interpolation and fitting algorithms have been proposed to optimize displacement calculation, their high complexity makes real-time calculation difficult to implement in factory settings.
[0003] Furthermore, traditional displacement measurement methods generally only measure local deformation information of structures. To achieve distributed displacement monitoring of structures, multiple repeated measurements are required, which not only increases experimental costs but also reduces the reliability and long-term stability of sensors. At the same time, the installation and operation of traditional methods are limited by environmental factors such as weather, lighting, and vibration, further restricting their applicability in installation projects. Summary of the Invention
[0004] In order to overcome the shortcomings of the prior art, one of the objectives of this invention is to provide a distributed spatial displacement measurement method, which can solve the problems of high cost and poor stability of displacement measurement in engineering in the prior art.
[0005] The second objective of this invention is to provide a distributed spatial displacement measurement device that can solve the problems of high cost and poor stability in displacement measurement in existing technologies.
[0006] The third objective of this invention is to provide a computer-readable storage medium that can solve the problems of high cost and poor stability in displacement measurement in existing technologies.
[0007] The fourth objective of this invention is to provide a distributed spatial displacement measurement system that can solve the problems of high cost and poor stability in displacement measurement in existing technologies.
[0008] One of the objectives of this invention is achieved through the following technical solution:
[0009] Distributed spatial displacement measurement methods include:
[0010] Data acquisition steps: Obtain the original tilt angle data of multiple test points of the structure under test;
[0011] Preprocessing steps: Filter the raw tilt data of each measurement point to obtain the tilt value of each measurement point;
[0012] Inclination curve generation steps: The inclination curve of the structure under test is obtained by using a cubic smooth spline fitting algorithm to fit the inclination values of all test points.
[0013] Deflection curve generation steps: Numerical integration is performed on the tilt curve of the structure under test to obtain the deflection curve of the structure under test, and then the spatial displacement measurement value of any point of the structure under test is obtained based on the deflection curve of the structure under test.
[0014] Furthermore, the data acquisition step also includes: firstly, setting multiple test points on the structure according to a preset arrangement scheme of test points, then installing a corresponding tilt sensor at each test point, and configuring a network connection for each tilt sensor.
[0015] Then, data acquisition signals are sent to each tilt sensor at regular intervals to obtain the raw tilt data recorded by each tilt sensor; the test points are evenly distributed in the preset key areas of the structure to be tested;
[0016] Finally, the collected raw tilt data are grouped according to the data recording time to obtain multiple datasets. Then, based on each dataset, the raw tilt data of multiple test points of the structure under test are obtained. Each dataset includes the raw tilt data of each test point corresponding to the same data recording time.
[0017] Furthermore, the structure to be tested is a long-span bridge structure; the preset key areas include the geometrically abrupt change areas, the stress-complex node areas, the mid-span, the supports, and the cantilever ends of the structure to be tested.
[0018] Furthermore, the preset arrangement scheme of the test points is obtained by combining the finite element analysis model to simulate the different load conditions of the structure under test, determining the minimum number of test points and the distribution position of each test point based on the sensitivity of each tilt sensor, and then obtaining the optimized arrangement scheme of the test points.
[0019] Furthermore, the preprocessing step also includes:
[0020] Validity judgment steps: Determine whether the original dip angle data of each measurement point is valid. If not, delete the original dip angle data of that measurement point and then execute the backup data acquisition step; if yes, record the original dip angle data of the corresponding measurement point.
[0021] Backup data acquisition steps: Based on the installation location of the test point with invalid original tilt angle data, match the test candidate points from the system, obtain the original tilt angle data of the test candidate points and use it as the original tilt angle data of the test point;
[0022] Filtering steps: The original tilt angle data of each test point after the judgment is completed are filtered according to the Kalman filter algorithm to obtain the tilt angle value of each test point.
[0023] Furthermore, the tilt curve generation step specifically includes: firstly, performing cubic smooth spline fitting on the tilt values of all test points according to a pre-built polynomial model to obtain a fitting curve; then optimizing the fitting curve parameters according to a deep Bayesian optimization algorithm to obtain the tilt curve of the test structure.
[0024] Furthermore, it also includes: a visualization display step: displaying the tilt curve and deflection curve of the structure under test through a visualization display screen;
[0025] Statistical steps: The deflection curve of the structure under test is obtained by multiple calculations, and then the spatial displacement of the structure under test is analyzed over time based on the multiple deflection curves.
[0026] The second objective of this invention is achieved by the following technical solution:
[0027] The distributed spatial displacement measurement device includes a memory and a processor. The memory stores a spatial displacement measurement program that runs on the processor. The spatial displacement measurement program is a computer program. When the processor executes the spatial displacement measurement program, it implements the steps of the distributed spatial displacement measurement method as one of the objectives of this invention.
[0028] The third objective of this invention is achieved by the following technical solution:
[0029] A computer-readable storage medium storing a spatial displacement measurement program thereon, the spatial displacement measurement program being a computer program, which, when executed by a processor, implements the steps of a distributed spatial displacement measurement method as one of the objectives of this invention.
[0030] The fourth objective of this invention is achieved by the following technical solution:
[0031] A distributed spatial displacement measurement system includes a back-end data processing center, a local main control device, and multiple tilt sensors. The tilt sensors are distributed at preset measurement points on the structure under test to acquire tilt data at those points. Each tilt sensor is communicatively connected to the local main control device. The local main control device acquires the tilt data at each measurement point and sends it to the main control device, thereby enabling the local main control device to upload the collected tilt data to the back-end data processing center. The back-end data processing center executes the steps of the distributed spatial displacement measurement method as described in one of the objectives of this invention.
[0032] Compared with the prior art, the beneficial effects of the present invention are as follows:
[0033] This invention sets multiple test points on the structure under test and sets an independently operating tilt sensor at each test point to collect tilt angle data. The collected tilt angle data is then preprocessed and fitted into a tilt angle curve, which is then converted into a deflection curve, thereby measuring the spatial displacement of the structure under test. This invention features accurate measurement results and low cost. Attached Figure Description
[0034] Figure 1 A flowchart of the distributed spatial displacement measurement method provided by the present invention;
[0035] Figure 2 for Figure 1 The flowchart of step S2 in the text;
[0036] Figure 3 This is a schematic diagram showing the installation location of the tilt sensor provided by the present invention on a long-span bridge. Detailed Implementation
[0037] The present invention will now be further described in conjunction with the accompanying drawings and specific embodiments. It should be noted that, without conflict, the various embodiments or technical features described below can be arbitrarily combined to form new embodiments.
[0038] Example 1
[0039] To address the shortcomings of existing displacement measurement methods, this invention provides a preferred embodiment, such as... Figure 1 As shown, the distributed spatial displacement measurement method includes:
[0040] Step S1: Obtain the original tilt angle data of multiple test points of the structure under test.
[0041] Specifically, in this embodiment, the structure under test is an object with a long span, such as a long-span bridge. Multiple test points are set on the structure under test, and tilt sensors or tilt monitoring devices are installed at each test point to collect tilt angle data. Figure 3 The diagram shows the installation location of the tilt sensor on a long-span bridge.
[0042] This invention involves setting a series of measurement points on the structure under test to collect the tilt angle data of each point. Then, the tilt angle measurements of all measurement points are fitted to an overall tilt angle deformation curve. Finally, the fitted overall tilt angle deformation curve is integrated to obtain the spatial displacement of any point on the structure under test. This method enables comprehensive monitoring of structures over a large area, especially for displacement measurement of structures with long spans, overcoming the limitation of existing displacement monitoring methods that only monitor partial displacements. Since long-span bridges primarily exhibit vertical displacement, this invention converts the measurement of bridge spatial displacement into the measurement of bridge vertical displacement. In spatial displacement, deflection represents the vertical displacement of a structure (such as a beam or slab) under external force. Therefore, in this embodiment, when applied to displacement measurement of long-span bridges, only the bridge deflection needs to be measured to determine the change in spatial displacement.
[0043] More preferably, in order to comprehensively acquire the displacement information of the structure under test, this embodiment also requires that the test points be evenly distributed on the structure under test. Specifically, test points are generally set at key parts of the structure to improve the detection accuracy. These key parts generally include areas of concentrated external loads, areas of concentrated stress, nodes with complex stress, mid-span, supports, and cantilever ends. By setting test points at these key parts, the monitoring accuracy of displacement measurement is improved. Specifically, multiple test points are set on the structure under test according to a preset arrangement scheme, and a corresponding tilt sensor is installed at each test point. A network connection is also configured for each tilt sensor. In this way, the tilt sensor at each test point will periodically record the original tilt data, and the data recording time is also recorded during the recording of the original tilt data.
[0044] Furthermore, to ensure data source synchronization among tilt sensors at multiple test points, this embodiment employs a local main control module during data acquisition. This module provides a unified clock source, ensuring clock synchronization among the tilt sensors at all test points. This guarantees that all tilt sensors record raw tilt data within a consistent time window. Simultaneously, during the transmission of the timing clock signal, feedback signals from multiple tilt sensors can be used to determine if the tilt sensor at the test point is in an abnormal state. If so, the tilt sensor at the corresponding candidate test point is activated promptly to record the tilt data. Simultaneously, any abnormal tilt sensors are reported to notify maintenance personnel for appropriate repairs. By setting up candidate test point tilt sensors, damage to abnormal tilt sensors that could affect tilt data acquisition is avoided, thus ensuring the system's normal and stable operation.
[0045] More specifically, the backend data processing center periodically sends data acquisition commands to the main control module to obtain the raw tilt angle data recorded by the tilt sensors at each test point. After acquiring the raw tilt angle data for each test point, the acquired data is grouped according to the data recording time to obtain multiple datasets. Each dataset then contains the raw tilt angle data for multiple test points of the structure under test.
[0046] More specifically, the arrangement scheme of the test points is determined by combining the finite element analysis model to simulate the different load conditions of the structure under test, and the minimum number of the structure under test and the distribution position of the test points are determined according to the sensitivity of each tilt sensor, thereby obtaining the optimized arrangement scheme of the test points.
[0047] In other words, a finite element analysis model is used to simulate different load conditions on the structure under test. Several test points are set within a preset key area, and tilt sensors are installed. Then, based on the sensitivity of the tilt sensors, the number of test points is gradually reduced, and the collected data is checked to see if the original tilt data within the preset key area can be completely captured. That is, while ensuring comprehensive data acquisition of the structure under test, the number of test points is minimized. By iteratively optimizing the above method, the minimum number of test points can be determined, and the distribution location of each test point can be determined. This invention, by optimizing the number of test points, can significantly reduce equipment costs without affecting monitoring accuracy.
[0048] Furthermore, this embodiment also sets up candidate points for some important key areas, using these candidate points as redundant measurement points to enhance the system's fault tolerance. This ensures that when some test points fail to measure or the tilt sensor of a test point malfunctions, a replacement point can be provided, allowing the system to maintain reliable and stable monitoring capabilities.
[0049] Meanwhile, the multiple tilt sensors installed on the structure under test in this invention are independent of each other and do not require physical connection, which significantly improves the adaptability and application flexibility of the system, enabling it to adapt to the monitoring needs of different working conditions and various structural types, and is especially suitable for complex and dynamic monitoring environments.
[0050] More specifically, this invention uses an inclination sensor to monitor data at the point of measurement. Because inclination sensors are lightweight, inexpensive, and easy to install, combined with their excellent low-frequency characteristics and transient response, they are ideally suited for comprehensive displacement measurement of complex structures such as long-span bridges.
[0051] Step S2: Filter the raw tilt angle data of each test point to obtain the tilt angle value of each test point.
[0052] Specifically, when preprocessing the raw dip angle data, the present invention also includes verifying the legality of the raw dip angle data to ensure that the collected raw dip angle data is legal.
[0053] Preferably, such as Figure 2 As shown, step S2 further includes:
[0054] Step S21: Determine whether the original dip angle data of each test point is valid. If yes, record the original dip angle data of the corresponding test point; otherwise, delete the original dip angle data of the corresponding test point and proceed to step S22.
[0055] Step S22: Based on the installation location of the test point with invalid original tilt angle data, match the test candidate points from the system, obtain the original tilt angle data of the test candidate points and use it as the original tilt angle data of the test point.
[0056] Step S23: Filter the original tilt angle data of each test point after the judgment is completed using the Kalman filter algorithm to obtain the tilt angle value of each test point.
[0057] Specifically, if the raw tilt angle data collected does not conform to standard specifications due to reasons such as tilt sensor malfunction, it is necessary to discard the raw tilt angle data that does not conform to standard specifications in order to ensure the accuracy of subsequent calculations. The criteria for determining validity can be set based on practical experience. For example, the raw tilt angle data collected for each test point can be set to meet a certain reasonable range. If the collected data does not meet this range, the raw tilt angle data of the test point is considered unqualified, and the raw tilt angle data of the candidate test points can be started.
[0058] Once the original dip angle data for each measurement point is valid, a Kalman filter algorithm is used to filter the dip angle data for that point to obtain its value. Simultaneously, during Kalman filtering, initial state estimates and initial error covariance matrices are set, and appropriate process noise and measurement noise covariances are selected to smooth and optimize the original dip angle data. The Kalman filter algorithm is a recursive algorithm that combines predicted values with new predicted values to recursively update the state estimate, thus converting the original dip angle data into dip angle values. By employing the Kalman filter algorithm, the influence of noise can be effectively suppressed, improving data quality and system robustness.
[0059] Step S3: Use a cubic smooth spline fitting algorithm to perform curve fitting on the inclination angle values of all test points to obtain the inclination angle curve of the structure under test.
[0060] Specifically, a cubic smooth spline fitting is performed on the tilt angle values of all test points based on a pre-built polynomial model to obtain a fitted curve. Then, the fitted curve is optimized using a deep Bayesian optimization algorithm to obtain the tilt angle curve of the test structure. Specifically, during the cubic smooth spline fitting, a deep Bayesian optimization algorithm is used to determine the loss function and objective function that minimize the fitted curve, determine the fitting parameters, and optimize the fitting by constructing a surrogate model of the objective function to obtain the tilt angle curve of the test structure.
[0061] This embodiment also provides the specific formula for the cubic polynomial model as follows:
[0062] f(x i ) = a i +b i (xx i )+c i (xx i ) 2 +d i (xx i ) 3 (1);
[0063] Among them, a i b i ci d i The coefficients of the polynomial are derived empirically.
[0064] f(x i () represents the inclination angle of the point to be measured; x i is the x-coordinate of the i-th point to be measured, and x is the lateral position coordinate of the beam (along the length direction of the beam axis). The coordinate system XOY is constructed with the direction of the beam as the x-axis and the direction perpendicular to the beam as the y-axis.
[0065] By substituting the position coordinates and inclination angle of each test point into formula (1), a polynomial formula for the test point is obtained. Then, a curve fit is performed on the polynomial formulas of all test points according to cubic smooth spline fitting to obtain the inclination curve of the structure under test. Specifically, x∈[x i x i+1 ] and the function value f(x)∈[f(x) i ), f(x) i+1 Substituting into formula (1), we get the interval [x] i x i+1 The expression for the tilt angle function within [].
[0066] In performing cubic smoothing spline fitting, this embodiment also controls the degree of fitting by setting weights, smoothing factors, and penalty factors to reduce fluctuations in the data; meanwhile, the objective function during fitting is:
[0067]
[0068] Where, ω i Let λ be the weight, λ be the smoothing factor, β be the penalty factor, and y be the weight. i For the target value to be fitted, f″(x) i ) is the function f(x) i The second derivative of f'(x1) is given by the natural boundary conditions f'(x1) = 0 and f'(x2) = 0. n =0. By setting the above objective function and parameters, the smoothness of the fitted curve at the boundaries is ensured, thereby improving the overall fitting effect and physical meaning.
[0069] This invention employs a deep Bayesian optimization method to automatically select the optimal smoothing factor, penalty factor, and Bayesian optimization dynamic tuning parameters to minimize the loss function (such as mean squared error) of the fitted curve. By establishing a surrogate model of the objective function, it significantly improves the accuracy of spline fitting, enabling the fitted curve to better reflect the characteristics of the real data.
[0070] Step S4: Perform numerical integration on the tilt curve of the structure under test to obtain the deflection curve of the structure under test, and then obtain the spatial displacement measurement value of any point of the structure under test based on the deflection curve of the structure under test.
[0071] Specifically, this embodiment calculates the deflection curve using the conjugate beam-integral method. The conjugate beam method is a simplified approach to calculating the deflection and rotation of an actual beam (real beam) under load. By constructing a virtual "conjugate beam" and analyzing its stress characteristics, the deflection characteristics of the real beam can be derived. The conjugate beam includes a virtual beam (i.e., a virtual beam) and a real beam. The conjugate beam-integral method utilizes the similarity relationships between two pairs of physical quantities: load-shear force-bending moment and curvature-rotation-deflection. The core idea of the conjugate beam method is to map the curvature of the actual beam to the load distribution of a virtual beam, so that the mechanical properties (bending moment, shear force, etc.) of the virtual beam have a certain mathematical relationship with the deformation characteristics such as deflection and rotation of the real beam. By analyzing the shear force and bending moment of the virtual beam, the deflection of the real beam can be directly obtained.
[0072] The virtual beam corresponds to the knowledge of internal mechanics, that is: the specific formulas for load, shear force, and bending moment are as follows:
[0073]
[0074] For a solid beam, the corresponding structural mechanics knowledge is as follows: The specific formula for curvature-rotation-deflection is:
[0075]
[0076] In the formula: q is the distributed load; Q is the shear force; M is the bending moment; θ is the rotation angle; w is the deflection; EI is the bending stiffness of the beam section; E is the elastic modulus of the elastic material; I is the moment of inertia of the section; and x is the transverse position coordinate of the beam (along the length direction of the beam axis).
[0077] From the above formulas (2) and (3), it can be seen that the curvature distribution of the solid beam is equivalent to the load distribution of the conjugate beam, and the shear force distribution of the conjugate beam is obtained by integrating the load distribution of the conjugate beam, while the bending moment distribution of the conjugate beam is obtained by further integrating the shear force distribution of the conjugate beam. Therefore, if the rotation angle data on the structure to be measured (i.e., the solid beam) is known, the known rotation angle distribution of the solid beam can be used as the load distribution of the conjugate beam, and the shear force distribution of the conjugate beam can be obtained by integration. Among them, the shear force distribution of the conjugate beam is numerically equivalent to the deflection distribution of the solid beam. Therefore, in this embodiment, the obtained tilt angle curve of the structure to be measured can be directly numerically integrated to obtain the deflection curve of the structure to be measured, and the spatial displacement measurement value of any point on the structure to be measured can be obtained based on the deflection curve of the structure to be measured.
[0078] Furthermore, the present invention also includes: displaying the tilt curve and deflection curve of the structure under test through a visualization display screen, so as to more intuitively observe the changes of various values through the curves.
[0079] The study also statistically analyzed the deflection curves of the structure under test obtained from multiple calculations. Based on these multiple deflection curves, a trend diagram of the spatial displacement of the structure over time was derived. By comparing the changes in tilt and deflection data of the structure at different time periods, the spatial displacement of the entire structure under test could be assessed. Furthermore, the analysis results were clearly presented through visualization, providing data support for the health monitoring and assessment of the structure under test.
[0080] This invention achieves comprehensive monitoring of the deformation of the structure under test by deploying multiple nodes equipped with tilt sensors at different locations in a distributed manner. This effectively overcomes the limitations of traditional methods that can only obtain local displacement information, significantly improving the ability to perceive the overall deformation of the structure. Furthermore, this embodiment also incorporates fault-tolerant functionality by setting candidate measurement points. This ensures that even if the sensor modules at some measurement points malfunction, other measurement points can still operate normally, guaranteeing the stability and reliability of the monitoring process and enhancing the robustness of the system.
[0081] Meanwhile, during data acquisition, a synchronous data source is used to ensure the synchronous acquisition and processing of data from each test point. This effectively reduces the communication latency and bandwidth burden of transmitting raw data to the central server. Furthermore, it can respond and process quickly when test point data fails or becomes abnormal, significantly improving the system's real-time performance and reliability.
[0082] This invention also employs a high-performance inclinometer with excellent low-frequency characteristics and transient response capabilities, resulting in high angle measurement accuracy. It can be directly deployed on the bridge deck without the need for a stationary reference point, making installation simple and efficient and significantly shortening bridge closure time. Therefore, it has significant advantages over other sensors, especially for displacement measurement of large-span structures such as cross-sea bridges.
[0083] Example 2
[0084] Based on Embodiment 1, the present invention also provides another embodiment, a distributed spatial displacement measurement device, including a memory and a processor. The memory stores a spatial displacement measurement program that runs on the processor. The spatial displacement measurement program is a computer program. When the processor executes the spatial displacement measurement program, it performs the following steps:
[0085] Data acquisition steps: Obtain the original tilt angle data of multiple test points of the structure under test;
[0086] Preprocessing steps: Filter the raw tilt data of each measurement point to obtain the tilt value of each measurement point;
[0087] Inclination curve generation steps: The inclination curve of the structure under test is obtained by using a cubic smooth spline fitting algorithm to fit the inclination values of all test points.
[0088] Deflection curve generation steps: Numerical integration is performed on the tilt curve of the structure under test to obtain the deflection curve of the structure under test, and then the spatial displacement measurement value of any point of the structure under test is obtained based on the deflection curve of the structure under test.
[0089] Furthermore, the data acquisition steps also include: firstly, setting multiple test points on the structure according to a preset layout scheme of test points, then installing a corresponding tilt sensor at each test point, and configuring a network connection for each tilt sensor.
[0090] Then, data acquisition signals are sent to each tilt sensor at regular intervals to obtain the raw tilt data recorded by each tilt sensor; the test points are evenly distributed in the preset key areas of the structure to be tested;
[0091] Finally, the collected raw tilt data are grouped according to the data recording time to obtain multiple datasets. Then, based on each dataset, the raw tilt data of multiple test points of the structure under test are obtained. Each dataset includes the raw tilt data of each test point corresponding to the same data recording time.
[0092] Furthermore, the structure to be tested is a long-span bridge structure; the key areas are pre-defined as the geometrically abrupt change areas, the stress-complex node areas, the mid-span, the supports, and the cantilever ends of the structure to be tested.
[0093] Furthermore, the preset arrangement scheme of the test points is determined by combining the finite element analysis model to simulate the different load conditions of the structure under test, and the minimum number of test points and the distribution position of each test point are determined according to the sensitivity of each tilt sensor, thereby obtaining the optimized arrangement scheme of the test points.
[0094] Furthermore, the preprocessing steps also include:
[0095] Validity judgment steps: Determine whether the original dip angle data of each measurement point is valid. If not, delete the original dip angle data of that measurement point and then execute the backup data acquisition step; if yes, record the original dip angle data of the corresponding measurement point.
[0096] Backup data acquisition steps: Based on the installation location of the test point with invalid original tilt angle data, match the test candidate points from the system, obtain the original tilt angle data of the test candidate points and use it as the original tilt angle data of the test point;
[0097] Filtering steps: The original tilt angle data of each test point after the judgment is completed are filtered according to the Kalman filter algorithm to obtain the tilt angle value of each test point.
[0098] Furthermore, the steps for generating the tilt curve specifically include: firstly, performing cubic smooth spline fitting on the tilt values of all test points based on a pre-built polynomial model to obtain the fitted curve; then, optimizing the parameters of the fitted curve using a deep Bayesian optimization algorithm to obtain the tilt curve of the test structure.
[0099] Furthermore, it also includes: a visualization display step: displaying the tilt curve and deflection curve of the structure under test through a visualization display screen;
[0100] Statistical steps: Calculate the deflection curve of the structure under test multiple times, and then analyze the spatial displacement trend of the structure under test over time based on the multiple deflection curves.
[0101] Example 3
[0102] Based on Embodiment 1, the present invention also provides Embodiment 3, a computer-readable storage medium storing a spatial displacement measurement program thereon. The spatial displacement measurement program is a computer program, and when executed by a processor, the spatial displacement measurement program performs the following steps:
[0103] Data acquisition steps: Obtain the original tilt angle data of multiple test points of the structure under test;
[0104] Preprocessing steps: Filter the raw tilt data of each measurement point to obtain the tilt value of each measurement point;
[0105] Inclination curve generation steps: The inclination curve of the structure under test is obtained by using a cubic smooth spline fitting algorithm to fit the inclination values of all test points.
[0106] Deflection curve generation steps: Numerical integration is performed on the tilt curve of the structure under test to obtain the deflection curve of the structure under test, and then the spatial displacement measurement value of any point of the structure under test is obtained based on the deflection curve of the structure under test.
[0107] Furthermore, the data acquisition steps also include: firstly, setting multiple test points on the structure according to a preset layout scheme of test points, then installing a corresponding tilt sensor at each test point, and configuring a network connection for each tilt sensor.
[0108] Then, data acquisition signals are sent to each tilt sensor at regular intervals to obtain the raw tilt data recorded by each tilt sensor; the test points are evenly distributed in the preset key areas of the structure to be tested;
[0109] Finally, the collected raw tilt data are grouped according to the data recording time to obtain multiple datasets. Then, based on each dataset, the raw tilt data of multiple test points of the structure under test are obtained. Each dataset includes the raw tilt data of each test point corresponding to the same data recording time.
[0110] Furthermore, the structure to be tested is a long-span bridge structure; the key areas are pre-defined as the geometrically abrupt change areas, the stress-complex node areas, the mid-span, the supports, and the cantilever ends of the structure to be tested.
[0111] Furthermore, the preset arrangement scheme of the test points is determined by combining the finite element analysis model to simulate the different load conditions of the structure under test, and the minimum number of test points and the distribution position of each test point are determined according to the sensitivity of each tilt sensor, thereby obtaining the optimized arrangement scheme of the test points.
[0112] Furthermore, the preprocessing steps also include:
[0113] Validity judgment steps: Determine whether the original dip angle data of each measurement point is valid. If not, delete the original dip angle data of that measurement point and then execute the backup data acquisition step; if yes, record the original dip angle data of the corresponding measurement point.
[0114] Backup data acquisition steps: Based on the installation location of the test point with invalid original tilt angle data, match the test candidate points from the system, obtain the original tilt angle data of the test candidate points and use it as the original tilt angle data of the test point;
[0115] Filtering steps: The original tilt angle data of each test point after the judgment is completed are filtered according to the Kalman filter algorithm to obtain the tilt angle value of each test point.
[0116] Furthermore, the steps for generating the tilt curve specifically include: firstly, performing cubic smooth spline fitting on the tilt values of all test points based on a pre-built polynomial model to obtain the fitted curve; then, optimizing the parameters of the fitted curve using a deep Bayesian optimization algorithm to obtain the tilt curve of the test structure.
[0117] Furthermore, it also includes: a visualization display step: displaying the tilt curve and deflection curve of the structure under test through a visualization display screen;
[0118] Statistical steps: Calculate the deflection curve of the structure under test multiple times, and then analyze the spatial displacement trend of the structure under test over time based on the multiple deflection curves.
[0119] Example 4
[0120] Based on Embodiment 1, the present invention also provides Embodiment 4, a distributed spatial displacement measurement system, including a background data processing center, a local main control device, and multiple tilt sensors; the multiple tilt sensors are distributed on preset test points of the structure under test, used to acquire tilt data of the test points; each tilt sensor is communicatively connected to the local main control device; the local main control device is used to acquire the tilt data of each test point and send it to the main control device, thereby enabling the local main control device to upload the acquired tilt data to the background data processing center; the background data processing center is used to execute the steps of the distributed spatial displacement measurement method provided by the present invention.
[0121] The above embodiments are merely preferred embodiments of the present invention and should not be construed as limiting the scope of protection of the present invention. Any non-substantial changes and substitutions made by those skilled in the art based on the present invention shall fall within the scope of protection claimed by the present invention.
Claims
1. A distributed spatial displacement measurement method, characterized in that, include: Data acquisition steps: Obtain the original tilt angle data of multiple test points of the structure under test; Preprocessing steps: Filter the raw tilt data of each measurement point to obtain the tilt value of each measurement point; Inclination curve generation steps: The inclination curve of the structure under test is obtained by using a cubic smooth spline fitting algorithm to fit the inclination values of all test points. Deflection curve generation steps: Numerical integration is performed on the tilt curve of the structure under test to obtain the deflection curve of the structure under test, and then the spatial displacement measurement value of any point of the structure under test is obtained based on the deflection curve of the structure under test.
2. The distributed spatial displacement measurement method according to claim 1, characterized in that, The data acquisition step further includes: firstly, setting multiple test points on the structure according to a preset test point layout scheme, then installing a corresponding tilt sensor at each test point, and configuring a network connection for each tilt sensor. Then, data acquisition signals are sent to each tilt sensor at regular intervals to obtain the raw tilt data recorded by each tilt sensor; the test points are evenly distributed in the preset key areas of the structure to be tested; Finally, the collected raw tilt data are grouped according to the data recording time to obtain multiple datasets. Then, based on each dataset, the raw tilt data of multiple test points of the structure under test are obtained. Each dataset includes the raw tilt data of each test point corresponding to the same data recording time.
3. The distributed spatial displacement measurement method according to claim 2, characterized in that, The structure to be tested is a long-span bridge structure; the preset key areas include the geometrically abrupt change areas, the stress-complex node areas, the mid-span, the supports, and the cantilever ends of the structure to be tested.
4. The distributed spatial displacement measurement method according to claim 2, characterized in that, The preset arrangement scheme of the test points is determined by combining the finite element analysis model to simulate the different load conditions of the structure under test, and then determining the minimum number of test points and the distribution position of each test point based on the sensitivity of each tilt sensor, thereby obtaining the optimized arrangement scheme of the test points.
5. The distributed spatial displacement measurement method according to claim 1, characterized in that, The preprocessing step further includes: Validity judgment steps: Determine whether the original dip angle data of each measurement point is valid. If not, delete the original dip angle data of that measurement point and then execute the backup data acquisition step; if yes, record the original dip angle data of the corresponding measurement point. Backup data acquisition steps: Based on the installation location of the test point with invalid original tilt angle data, match the test candidate points from the system, obtain the original tilt angle data of the test candidate points and use it as the original tilt angle data of the test point; Filtering steps: The original tilt angle data of each test point after the judgment is completed are filtered according to the Kalman filter algorithm to obtain the tilt angle value of each test point.
6. The distributed spatial displacement measurement method according to claim 1, characterized in that, The steps for generating the tilt curve specifically include: first, performing cubic smooth spline fitting on the tilt values of all test points according to a pre-built polynomial model to obtain a fitting curve; then, optimizing the fitting curve parameters according to a deep Bayesian optimization algorithm to obtain the tilt curve of the test structure.
7. The distributed spatial displacement measurement method according to claim 1, characterized in that, Also includes: Visualization display step: Display the tilt curve and deflection curve of the structure under test through a visualization display screen; Statistical steps: The deflection curve of the structure under test is obtained by multiple calculations, and then the spatial displacement of the structure under test is analyzed over time based on the multiple deflection curves.
8. A distributed spatial displacement measurement device, comprising a memory and a processor, characterized in that, The memory stores a spatial displacement measurement program that runs on the processor. The spatial displacement measurement program is a computer program. When the processor executes the spatial displacement measurement program, it implements the steps of the distributed spatial displacement measurement method as described in any one of claims 1-7.
9. A computer-readable storage medium storing a spatial displacement measurement program thereon, characterized in that, The spatial displacement measurement program is a computer program, and when the spatial displacement measurement program is executed by the processor, it implements the steps of the distributed spatial displacement measurement method as described in any one of claims 1-7.
10. A distributed spatial displacement measurement system, characterized in that, The system includes a background data processing center, a local main control device, and multiple tilt sensors. These tilt sensors are distributed at preset measurement points on the structure under test to acquire tilt data at those points. Each tilt sensor is communicatively connected to the local main control device. The local main control device acquires tilt data from each measurement point and sends it to the main control device, thereby enabling the local main control device to upload the collected tilt data to the background data processing center. The background data processing center executes the steps of the distributed spatial displacement measurement method as described in any one of claims 1-7.