Building facility settlement monitoring method, device and equipment based on single radar and multiple targets

Abstract

The invention relates to the field of radar displacement monitoring, in particular to a building facility settlement monitoring method, device and equipment based on single radar and multiple targets. The method comprises the following steps: S1, monitoring building facilities by adopting a single micro-change monitoring radar, acquiring echo signal data and extracting displacement observation data and spatial position information of a plurality of monitoring targets; s2, determining a direction vector of each monitoring target relative to the radar according to the spatial position information; taking the direction vector and the displacement observation data as joint input, establishing a multi-source data association model capable of representing a corresponding relation between the monitoring target and the overall displacement, and performing fusion processing based on the model to obtain an overall three-dimensional displacement result of the building facility; and S3, outputting a vertical component of the overall three-dimensional displacement result as the settlement displacement of the building facility. According to the method, high-precision and automatic three-dimensional displacement monitoring of building facility settlement is realized by adopting a single micro-change monitoring radar, and the interference of transverse and longitudinal displacement on settlement measurement is effectively eliminated.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of radar displacement monitoring, in particular to a building facility settlement monitoring method, device and equipment based on single radar multi-target. BACKGROUND

[0002] During the long-term use of building facilities, they are prone to structural damage due to the combined effects of various factors, mainly including human factors and natural factors. Human factors include structural hazards in the design stage, material or process defects in the construction stage, and insufficient maintenance in the use and management stage. Natural factors not only include direct damage to the structure caused by extreme disasters such as earthquakes, typhoons, and heavy rains, but also include progressive damage caused by environmental effects such as temperature changes and rain erosion. The above factors may cause different degrees of settlement or deformation of building facilities, so it is of great significance to continuously and accurately monitor their health. The early monitoring method mainly relies on manual inspection supplemented by traditional displacement instruments, which not only has high labor intensity, but also is greatly affected by subjective factors, and the monitoring accuracy and timeliness are limited. With the development of sensor and signal processing technology, automated building facility health monitoring systems have gradually been applied. In recent years, micro-variation monitoring radar has become an important means of building structure vibration and displacement monitoring due to its advantages of high precision, non-contact, and all-weather monitoring. However, the existing settlement calculation method based on micro-variation monitoring radar assumes that the radial displacement measured by the radar is caused entirely by vertical settlement, and the settlement is obtained by angle conversion. When the building facility has lateral or longitudinal displacement, this assumption will introduce significant errors, resulting in deviation of the settlement monitoring result. SUMMARY

[0003] To solve the problem that the existing micro-variation monitoring radar settlement measurement cannot distinguish between lateral, longitudinal and vertical displacement, resulting in result errors, the present application provides a building facility settlement monitoring method, device and equipment based on single radar multi-target. This scheme uses a single micro-variation monitoring radar to collect displacement observation data and spatial position information of multiple monitoring targets, establishes a correlation model representing the correspondence between the multi-target observation data and the overall displacement, and performs data fusion processing based on the model to calculate the overall three-dimensional displacement result of the building facility, extracts the vertical component as the settlement displacement, and effectively eliminates the interference of lateral and longitudinal displacement, thereby significantly improving the accuracy and stability of settlement monitoring.

[0004] In a first aspect, the present application provides a building facility settlement monitoring method based on single radar multi-target, which can include: S1. A single micro-variation monitoring radar is used to monitor the building facility, to obtain echo signal data and extract displacement observation data and spatial position information of multiple monitoring targets; S2. Based on the spatial location information, determine the direction vector of each monitoring target relative to the radar; using the direction vector and displacement observation data as joint input, establish a multi-source data association model that can characterize the correspondence between the monitoring target and the overall displacement, and perform fusion processing based on the model to obtain the overall three-dimensional displacement result of the building facility; S3. Output the vertical component of the overall three-dimensional displacement result as the settlement displacement of the building facility.

[0005] According to some embodiments of this application, during the monitoring process of S1, the micro-change monitoring radar continuously samples the echo signal, calculates the phase change between the transmitted signal and the echo signal, and outputs high-precision displacement observation data of each monitoring target along the radial direction of the radar after phase demodulation and distance conversion processing, using the phase change and electromagnetic wave wavelength as input.

[0006] According to some embodiments of this application, the direction vector determination in S2 includes: taking the location of the radar as the origin of the coordinate system, reading the three-dimensional coordinate data of each monitored target, calculating the directional ratio of the monitored target relative to the radar in space, and storing the directional ratio as a direction vector for input to the subsequent multi-source data association model.

[0007] According to some embodiments of this application, the establishment of the multi-source data association model includes: taking the direction vector and radial displacement observation data of each monitored target as input, comparing the consistency of displacement response between different targets to form a data mapping relationship characterizing the overall motion characteristics of the building facility, and performing weighted combination based on the data mapping relationship to output a comprehensive observation matrix for fusion processing.

[0008] According to some embodiments of this application, the fusion process includes: taking the comprehensive observation matrix as input, calculating the overall three-dimensional displacement result of the building facility through a minimum deviation solution algorithm, wherein the direction vector of each monitored target is used as a weighting coefficient, the radial displacement of each target is linearly combined, and the overall three-dimensional displacement result of the building facility is output according to the principle of minimizing the sum of squared errors.

[0009] According to some embodiments of this application, before performing the fusion process, the displacement observation data of each monitoring target are cleaned and weighted, including removing abnormal data samples that exceed the confidence interval, smoothing and filtering noise interference signals, and setting different weighting parameters according to the target signal-to-noise ratio.

[0010] According to some embodiments of this application, when outputting the settlement displacement, trend fitting and threshold determination are performed on the time series monitoring data. When the settlement change rate exceeds the preset threshold, the system generates structural anomaly warning information and compares the settlement result with the historical monitoring curve to output the settlement change trend map of the building facility. Secondly, embodiments of this application provide a building settlement monitoring device based on a single radar targeting multiple targets, the device may include: The data acquisition module is used to receive echo signal data collected by a single micro-variable monitoring radar during the monitoring of building facilities, and to extract displacement observation data and spatial location information of multiple monitoring targets from the echo signal data; The data processing module is used to determine the direction vector of each monitoring target relative to the radar based on the spatial location information, and to establish a multi-source data association model that can characterize the correspondence between the monitoring target and the overall displacement using the direction vector and displacement observation data as joint input. Based on the association model, the module performs fusion processing to obtain the overall three-dimensional displacement result of the building facility. The result output module is used to output the vertical component of the overall three-dimensional displacement result as the settlement displacement of the building facility, and to provide the result to the structural health analysis system for building facility deformation assessment.

[0011] Thirdly, embodiments of this application provide a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the building settlement monitoring method based on a single radar and multiple targets described above.

[0012] The method, apparatus, and equipment for monitoring building settlement based on a single radar and multiple targets according to the present invention have at least the following beneficial effects: The present invention provides a method for monitoring the settlement of buildings and facilities based on a single radar and multiple targets. First, a single micro-variable monitoring radar is used to simultaneously observe multiple monitoring targets within the building and facility, reducing the complexity and cost of deploying multi-radar systems. Then, the direction vectors of each monitoring target relative to the radar are determined based on its spatial location information, thereby establishing a correlation model for the multi-source observation data. This model achieves geometric correspondence and unified expression of the observation data among different monitoring targets. Next, the multi-source observation data is fused based on the correlation model, and the radial displacement information of each target is jointly calculated to obtain the overall three-dimensional displacement result of the building and facility. Finally, the vertical component is extracted from the three-dimensional displacement result as the settlement displacement of the building and facility, achieving high-precision and automated monitoring of the settlement. By introducing multi-target collaborative observation and data fusion algorithms, the interference of lateral and longitudinal displacement components on settlement measurement is effectively eliminated, significantly improving the accuracy, stability, and robustness of the monitoring data, achieving the technical effect of high-precision settlement monitoring of buildings and facilities using a single radar device.

[0013] The building settlement monitoring device based on a single radar and multiple targets provided by this invention first receives the echo signal from the micro-variable monitoring radar and extracts multi-target displacement observation data through a data acquisition module, ensuring the continuity and integrity of the monitoring information. Then, the data processing module determines the direction vector of the monitoring target based on spatial location information, establishes a multi-source data association model, and performs fusion calculation, thereby outputting the overall three-dimensional displacement result reflecting the true deformation state of the building facility. Subsequently, the result output module extracts the vertical component of the obtained result and outputs the data, realizing the automatic generation of building settlement information. Finally, the device can work in conjunction with a structural health analysis system to achieve long-term, dynamic monitoring and safety early warning of building settlement status. Through modular signal acquisition and calculation design, the device features convenient deployment, high calculation accuracy, and stable operation, achieving real-time, intelligent, and low-cost building settlement monitoring.

[0014] The computer device of the present invention realizes all the functions of the above method by running a corresponding computer program on a processor, enabling the building settlement monitoring process to be executed automatically in a computer environment, reducing manual intervention, improving system integration and data processing efficiency, thereby achieving high-precision, automated and long-term traceable monitoring of building settlement.

[0015] Other features and advantages of this application will be set forth in the following description and will be apparent in part from the description or may be learned by practicing the application. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating the steps of the building settlement monitoring method based on a single radar and multiple targets in Example 1. Figure 2 This is a schematic diagram of the single radar-multi-target deployment and the deployment of the monitored object in Example 2; Figure 3 This is a structural block diagram of the building settlement monitoring device based on a single radar and multiple targets, as described in Example 3. Detailed Implementation

[0017] The present application will now be described in further detail with reference to experimental examples and specific embodiments. However, this should not be construed as limiting the scope of the subject matter of the present application to the following embodiments. All technologies implemented based on the content of the present application fall within the scope of protection of the present application.

[0018] Unless otherwise specified, the use of terms such as "upper," "lower," "left," "right," "center," "inner," "outer," and "side" to indicate orientation or positional relationships in the description of specific embodiments of this application is based on the orientation or positional relationships shown in the accompanying drawings, or the orientation or positional relationship in which the product / equipment / device is usually placed during use. These terms are merely for the purpose of facilitating the description of the solution in this application or simplifying the description in specific embodiments, and for enabling those skilled in the art to quickly understand the solution, and do not indicate or imply that a particular device / component / element must have a specific orientation, or be constructed and operated in a specific positional relationship, and therefore should not be construed as a limitation of this application.

[0019] In the description of the embodiments of this application, technical terms such as "first" and "second" only distinguish one entity or operation from another, and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary or secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.

[0020] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a mutually exclusive, independent, or alternative embodiment. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0021] Example 1 During the research process, the applicant found that when using existing micro-change monitoring radar to monitor the settlement of building facilities, if it is desired to accurately obtain the settlement of building facilities using only a single radar device, it is necessary to strictly control the installation angle, distance and observation direction of the monitoring point, and to use complex methods such as multi-angle measurement or multi-radar joint deployment for data compensation. The process is cumbersome and the deployment cost is high. Moreover, when the site environment is limited, it is often only possible to obtain displacement information in one direction, and it is impossible to achieve effective separation of multi-directional displacement components.

[0022] In solving practical engineering problems, in order to achieve the technical goal of high-precision monitoring of building settlement under limited monitoring conditions, existing technologies cannot simultaneously balance monitoring accuracy, system simplification and data stability, and cannot meet the needs of long-term continuous monitoring of large building facilities.

[0023] Therefore, after in-depth research on this problem, the applicant proposed a method for monitoring building settlement based on a single radar and multiple targets. Addressing the technical challenge of single radar systems' inability to distinguish between lateral, longitudinal, and vertical displacements, leading to large settlement calculation errors, this method involves deploying multiple monitoring targets on the building. A multi-source data association model is established using the target spatial location information and radar observation data. Based on this model, a fusion calculation is performed to obtain the overall three-dimensional displacement of the building. The vertical component is then extracted as the settlement displacement, thus achieving high-precision, low-cost, and automated monitoring of building settlement using a single radar system, significantly improving the accuracy and stability of the monitoring results.

[0024] Please refer to Figure 1 , Figure 1 A schematic diagram illustrating the steps of a building settlement monitoring method based on a single radar and multiple targets provided in this application embodiment. This method may include: S1. A single micro-variable monitoring radar is used to monitor building facilities, acquire echo signal data, and extract displacement observation data and spatial location information of multiple monitoring targets; S2. Based on the spatial location information, determine the direction vector of each monitoring target relative to the radar; using the direction vector and displacement observation data as joint input, establish a multi-source data association model that can characterize the correspondence between the monitoring target and the overall displacement, and perform fusion processing based on the model to obtain the overall three-dimensional displacement result of the building facility; S3. Output the vertical component of the overall three-dimensional displacement result as the settlement displacement of the building facility.

[0025] This method first utilizes a single micro-variable monitoring radar to achieve simultaneous observation of multiple monitoring targets in a building facility, reducing system deployment complexity and equipment costs. Then, based on the spatial location information of each monitoring target, its direction vector relative to the radar is determined, establishing a correlation model for multi-source observation data to achieve geometric correspondence and unified expression of multi-target observation data. Next, based on the correlation model, the multi-source observation data is fused, and the radial displacement information of each target is jointly calculated to obtain the overall three-dimensional displacement result of the building facility. Finally, the vertical component is extracted from the three-dimensional displacement result as the settlement displacement of the building facility, achieving high-precision and automated monitoring of building facility settlement.

[0026] By introducing multi-target collaborative observation and data fusion algorithms, the interference of lateral and longitudinal displacement components on settlement measurement was effectively eliminated, significantly improving the accuracy, stability and robustness of monitoring data, and achieving the technical effect of high-precision settlement monitoring of building facilities with a single radar device.

[0027] In some specific embodiments, the building settlement monitoring method based on single radar and multiple targets may further include the following technical details: During the monitoring process of S1, the micro-variable monitoring radar continuously samples the echo signal, calculates the phase change between the transmitted signal and the echo signal, and uses the phase change and electromagnetic wave wavelength as input. After phase demodulation and range conversion processing, it outputs high-precision displacement observation data of each monitored target along the radar radial direction. In this way, the phase information of the radar signal can be converted into actual displacement, realizing high-resolution measurement of millimeter-level minute deformations and improving monitoring accuracy.

[0028] In step S2, determining the direction vector may include the following process: using the radar's location as the origin, reading the three-dimensional coordinate data of each monitored target, calculating the directional ratio of the monitored target relative to the radar in space, and storing this directional ratio as a direction vector for subsequent input to the multi-source data association model. This step establishes a spatial geometric correspondence between the radar and each monitored target, providing a clear directional reference for the subsequent data fusion process and ensuring the spatial accuracy of displacement calculations.

[0029] When establishing a multi-source data association model, the direction vectors and radial displacement observation data of each monitored target are used as input. By comparing the consistency of displacement responses among different targets, a data mapping relationship that reflects the overall motion characteristics of the building facility is formed. Based on this mapping relationship, a weighted combination is performed to output a comprehensive observation matrix for fusion processing. This process can transform scattered target observation data into a unified system expression, providing a mathematical basis for multi-target displacement fusion, thereby achieving unified modeling of the overall motion of the building facility.

[0030] During the fusion processing, the comprehensive observation matrix is ​​used as input, and the minimum deviation solution algorithm is employed to calculate the overall three-dimensional displacement of the building facilities. The direction vectors of each monitored target are used as weighting coefficients to linearly combine the radial displacements of each target, and the overall three-dimensional displacement result is output based on the principle of minimizing the sum of squared errors. This weighted optimization method effectively suppresses the propagation of single-target observation errors, improving the stability and accuracy of the overall solution.

[0031] Before performing the fusion process, the displacement observation data of each monitoring target can be cleaned and weighted. This includes removing outlier data samples that exceed the confidence interval, smoothing and filtering noise interference signals, and setting different weighting parameters according to the signal-to-noise ratio of the monitoring target. This preprocessing can significantly improve the quality of the input data, reduce the impact of noise and outlier data on the final displacement results, and ensure that the calculation results are more reliable.

[0032] When outputting settlement displacement, the system can further perform trend fitting and threshold determination on the time series monitoring data. When the settlement change rate exceeds a preset threshold, the system automatically generates a structural anomaly warning and compares the current settlement result with historical monitoring curves to output a settlement change trend map of the building facility. This output mechanism not only enables real-time assessment of the settlement status of the building facility but also allows for early detection of potential structural anomalies through trend comparison, thereby improving the system's safety early warning capabilities.

[0033] The building settlement monitoring method based on a single radar and multiple targets provided in this application can be applied to various engineering monitoring fields, such as bridge settlement monitoring, tunnel lining deformation monitoring, dam displacement monitoring, and communication base station foundation settlement monitoring. In the above implementation, when collecting and analyzing displacement data of buildings or large structures in real time, a single micro-variable monitoring radar can simultaneously acquire echo signals from multiple monitoring targets; geometric unification of multi-target observation data can be achieved through the calibration of target spatial location information and the determination of direction vectors; and high-precision inversion of the overall three-dimensional displacement of the building can be achieved by establishing a multi-source data association model and performing fusion calculations. This achieves automated, high-precision, and long-term continuous monitoring of structural settlement and deformation under conditions of simple equipment deployment and low cost.

[0034] Example 2 As a further optimization of the preceding embodiments, this paper presents a specific implementation of a building settlement monitoring method based on a single radar and multiple targets. This method employs millimeter-wave radar and phase ranging technology, utilizing a micro-variable monitoring radar to perform real-time monitoring of multiple targets deployed at key locations within the building facility, acquiring high-precision radial displacement data for each target. Then, by combining the precise spatial position of each monitoring target relative to the radar, the multi-source observation data is fused and calculated to ultimately obtain accurate measurement results of the building facility's settlement displacement.

[0035] The method includes the following steps: S1. N targets are deployed at key locations within the building infrastructure, ensuring that the radial distances between each target and the radar are as follows: Furthermore, the difference in radial distances corresponding to the targets must exceed the range resolution capability of the micro-variable radar.

[0036] like Figure 2 As shown, it is assumed that the displacement of each target point is consistent when installing the monitoring targets. If there are differences in the displacement between different targets, it will introduce errors into the final calculation results. Therefore, when deploying monitoring targets, the principle of displacement consistency should be fully considered, and the selection of locations should be based on ensuring that the displacement response of each target is consistent.

[0037] S2. Measure the precise positions of N targets. Precise measurements are performed using the radar as the zero point of the coordinate system, for each target... Precise three-dimensional position .

[0038] The precise positions of N targets were measured on-site. Precise measurements were taken using the radar as the zero point of the coordinate system, for each target... The precise three-dimensional position in three-dimensional Euclidean space In a vector matrix, the position of any point in space (or the vector representing that point, i.e., the vector pointing from the origin to that point) can be uniquely determined by its projection components onto the x, y, and z coordinate axes. There are two common forms of matrix representation of vectors: one is a row vector. One type is column vectors If the original matrix is ​​a row vector, it needs to be transposed, i.e., the rows and columns are interchanged, to obtain a column vector (3×1 dimension). The column vector is... Where T represents the column vector obtained by transposing the row vector. Indicates the first The position vectors of the points.

[0039] S3. Precisely measure the displacement of each target using micro-variable radar. .

[0040] By using micro-variable radar, all-weather, non-contact, micron-level precision measurements can be performed on each target positioned in different locations, measuring the high-precision displacement of each target. S represents a set, sequence, or vector, indicating the collection of echo signals from multiple targets. It is the radar scattering signal or displacement measurement of the first target. It consists of the n elements that make up the set, that is, the echo intensity or displacement change of the n targets.

[0041] S4. Calculate the direction vector of each target relative to the radar. The formula is

[0042] in: .

[0043] After the system collects data on the target points, it calculates the direction vector of each target relative to the radar. In the monitoring system, This represents the displacement vector of the i-th monitoring point. The displacement vector is a vector representation of the object's displacement changes in three-dimensional space, used to encapsulate and describe its displacement components in the x, y, and z directions. Magnitude This is the cumulative displacement at that point, used to correspond one-to-one with the target, allowing the micro-variable radar to calculate the displacement point by point through phase interferometry. Then, they are stitched together to form a full-field displacement diagram.

[0044] S5. Assuming that the actual settlement displacement, lateral displacement, and longitudinal displacement of each target are the same, .in, These represent settlement displacement, lateral displacement, and longitudinal displacement, respectively. Therefore, we have...

[0045] in, .

[0046] Assuming that the actual settlement displacement, lateral displacement, and longitudinal displacement of each target are the same, the displacement vector can be expressed as: Observation vector S Include N Each observation data point (such as the coordinates of an image point) is denoted as: Design Matrix L Let be the influence coefficient of displacement on the observed value, for the j For each observation (j=1,2,…,N), the change in the observed value is determined by the displacement. h The three components ( The values ​​are multiplied by their respective influence coefficients, thus L is a 3×N matrix. A linear relationship between displacement and observations is established, for the ... j The first observation value i Each component, its observed value Displacement and influence coefficient The product determines By arranging the relationships of all observed components by rows (corresponding to displacement components) and columns (corresponding to observation sequence numbers), a linear equation in matrix form can be constructed. Here, the displacement vector h is a 3×1 column vector, the design matrix L is a 3×N matrix, and the product hL has a dimension of 3×N, consistent with the dimension of the observed value vector s. Based on the linear influence of displacement on the observed data, and combined with the matrix multiplication rules, a linear relationship can be obtained between the displacement vector h, the design matrix L, and the observed value vector s. .

[0047] S6. The settlement displacement can be obtained by solving using the least squares method.

[0048] Settlement displacement can be obtained using the least squares method. Here, h represents the settlement displacement to be determined, which can be understood as the actual displacement of the target monitored by the millimeter-wave radar; s represents the noisy observation data acquired by the radar, including information such as the echo time delay, phase difference, and amplitude; and L is the system matrix. In the noisy measurement environment of millimeter-wave radar, the least squares method combined with the system model L is used to solve for the noisy observation data s, yielding high-precision settlement displacement results, providing reliable data support for applications such as deformation monitoring and target location. This process is essentially an organic combination of mathematical solution methods, radar physical models, and noise robustness processing, thereby significantly improving the measurement accuracy and result stability of the equipment.

[0049] Phase ranging technology is a technique for high-precision distance measurement based on electromagnetic wave phase information. Its core principle is to measure the phase difference between the radar's transmitted signal and the received reflected signal, and then invert the target distance by combining the propagation characteristics and wavelength parameters of electromagnetic waves. This technology overcomes the resolution limitations of traditional pulse ranging, achieving millimeter-level or even sub-millimeter-level measurement accuracy, thus effectively solving the challenges of high-precision dynamic distance measurement.

[0050] Based on phase ranging technology, this invention proposes a multi-target fusion micro-variable radar monitoring scheme. This scheme deploys multiple monitoring targets on the surface of the monitored object, simultaneously acquires the echo signals of each target using a single micro-variable monitoring radar, and combines this with a multi-source data fusion algorithm to achieve high-precision calculation of the target's three-dimensional displacement. Compared with traditional single-radar single-target monitoring methods, this scheme utilizes the spatial distribution characteristics of multiple targets to simultaneously acquire radial, lateral, and longitudinal displacement information, significantly improving the completeness and accuracy of displacement measurement. Compared with multi-radar collaborative measurement methods, since the cost of adding monitoring target points is far lower than the cost of deploying multiple radars, this scheme significantly reduces system deployment and maintenance costs while maintaining high measurement accuracy.

[0051] In engineering applications, safety monitoring of critical infrastructure such as large buildings, dams, bridges, communication base stations, and power transmission towers typically requires long-term, high-precision tracking of minute deformations or displacements in the structure. Traditional monitoring methods are limited by spatial resolution, environmental adaptability, and cost factors, making it difficult to meet the demands for high-frequency, continuous, and precise monitoring. This invention utilizes micro-variable radar and multi-target fusion technology to achieve high-sensitivity and high-resolution observation of building structures. It can capture minute displacements that are difficult to identify using traditional methods and, through long-term data accumulation and analysis, identify potential safety hazards in advance, such as crack propagation or abnormal foundation settlement. This method provides reliable data support for facility maintenance decisions and safety management, and has significant engineering application value for ensuring public safety, extending facility lifespan, and reducing operation and maintenance costs.

[0052] In summary, this method, by introducing millimeter-wave radar and phase ranging technology, achieves high-precision monitoring of building settlement, effectively overcoming the measurement errors caused by the coupling of lateral and longitudinal displacements in traditional settlement measurement algorithms. Relying on the high resolution and all-weather operation of micro-variable monitoring radar, this method can operate stably in complex environments, continuously outputting high-precision observation data. Through the fusion processing of multi-target data, it directly calculates the three-dimensional high-precision displacement results of the building facility in the settlement, lateral, and longitudinal directions, fundamentally eliminating the interference of lateral and longitudinal displacement components on settlement calculations in traditional measurement methods, significantly improving the accuracy and reliability of monitoring results. This technical solution has good engineering applicability and can be widely applied to the settlement and deformation monitoring of infrastructure such as roads, bridges, communication base stations, and dams, providing strong data support for structural safety assessment and operation and maintenance management.

[0053] Example 3 As a further optimization of the preceding embodiments, this application provides a building settlement monitoring device based on a single radar and multiple targets, such as... Figure 3 As shown, Figure 3The structural block diagram of a building settlement monitoring device based on a single radar and multiple targets includes the following modules: The data acquisition module is used to receive echo signal data collected by a single micro-change monitoring radar during the monitoring of building facilities, and to extract displacement observation data and spatial location information of multiple monitoring targets from the echo signal data. By completing the echo signal acquisition and information extraction of multiple monitoring targets with a single micro-change monitoring radar, the synchronous acquisition of multi-point displacement of building facilities is realized, reducing the complexity of multi-device deployment and ensuring the integrity and real-time performance of the observation data.

[0054] The data processing module is used to determine the direction vector of each monitoring target relative to the radar based on the spatial location information, and to establish a multi-source data association model that can characterize the correspondence between the monitoring target and the overall displacement using the direction vector and displacement observation data as joint input. Based on the association model, fusion processing is performed to obtain the overall three-dimensional displacement result of the building facility. By determining the direction vector and modeling the association with multi-source data, the observation data of different monitoring targets are fused and calculated in a unified spatial coordinate system, which can accurately reflect the overall three-dimensional displacement state of the building facility and improve the accuracy and anti-interference capability of displacement calculation.

[0055] The result output module is used to output the vertical component of the overall three-dimensional displacement result as the settlement displacement of the building facility, and provide the result to the structural health analysis system for building facility deformation assessment; by extracting and outputting the components of the three-dimensional displacement result obtained by fusion calculation, the automatic identification of building facility settlement displacement and structural deformation assessment are realized, which facilitates the subsequent monitoring system to perform trend analysis and safety early warning.

[0056] It should be understood that the various modules of the building settlement monitoring device based on a single radar and multiple targets provided in the above embodiments are only illustrated by the division of the functional modules in the above description when monitoring building settlement. In practical applications, the above functions can be assigned to different functional modules as needed. That is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0057] The functional modules in the above embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of the embodiments of this application.

[0058] Based on the same concept, embodiments of this application also provide a computer device, which may include a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the building settlement monitoring method based on a single radar and multiple targets as described above.

[0059] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects.

[0060] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0061] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for monitoring building settlement based on a single radar targeting multiple targets, characterized in that, include: S1. A single micro-variable monitoring radar is used to monitor building facilities, acquire echo signal data, and extract displacement observation data and spatial location information of multiple monitoring targets; S2. Based on the spatial location information, determine the direction vector of each monitoring target relative to the radar; using the direction vector and displacement observation data as joint input, establish a multi-source data association model that can characterize the correspondence between the monitoring target and the overall displacement, and perform fusion processing based on the model to obtain the overall three-dimensional displacement result of the building facility; S3. Output the vertical component of the overall three-dimensional displacement result as the settlement displacement of the building facility.

2. The method for monitoring building settlement based on a single radar and multiple targets according to claim 1, characterized in that, During the monitoring process of S1, the micro-change monitoring radar continuously samples the echo signal, calculates the phase change between the transmitted signal and the echo signal, and outputs high-precision displacement observation data of each monitoring target along the radial direction of the radar after phase demodulation and distance conversion processing, using the phase change and electromagnetic wave wavelength as input.

3. The method for monitoring building settlement based on a single radar and multiple targets according to claim 1, characterized in that, The direction vector determination in S2 includes: taking the location of the radar as the origin of the coordinate system, reading the three-dimensional coordinate data of each monitored target, calculating the directional ratio of the monitored target relative to the radar in space, and storing the directional ratio as a direction vector for use as input to the subsequent multi-source data association model.

4. The method for monitoring building settlement based on a single radar and multiple targets according to claim 1, characterized in that, The establishment of the multi-source data association model includes: taking the direction vector and radial displacement observation data of each monitoring target as input, comparing the consistency of displacement response between different targets to form a data mapping relationship that characterizes the overall motion characteristics of the building facilities, and performing weighted combination based on the data mapping relationship to output a comprehensive observation matrix for fusion processing.

5. The method for monitoring building settlement based on a single radar and multiple targets according to claim 4, characterized in that, The fusion processing includes: taking the comprehensive observation matrix as input, calculating the overall three-dimensional displacement result of the building facility through the minimum deviation solution algorithm, wherein the direction vector of each monitored target is used as a weighting coefficient, the radial displacement of each target is linearly combined, and the overall three-dimensional displacement result of the building facility is output according to the principle of minimizing the sum of squared errors.

6. The method for monitoring building settlement based on a single radar and multiple targets according to claim 1, characterized in that, Before performing the fusion process, the displacement observation data of each monitoring target are cleaned and weighted, including removing abnormal data samples that exceed the confidence interval, smoothing and filtering noise interference signals, and setting different weighting parameters according to the target signal-to-noise ratio.

7. The method for monitoring building settlement based on a single radar and multiple targets according to claim 1, characterized in that, When outputting the settlement displacement, the system performs trend fitting and threshold determination on the time series monitoring data. When the settlement change rate exceeds the preset threshold, the system generates a structural anomaly warning information and compares the settlement result with the historical monitoring curve to output a settlement change trend map of the building facility.

8. A building settlement monitoring device based on a single radar and multiple targets, characterized in that, include: The data acquisition module is used to receive echo signal data collected by a single micro-variable monitoring radar during the monitoring of building facilities, and to extract displacement observation data and spatial location information of multiple monitoring targets from the echo signal data; The data processing module is used to determine the direction vector of each monitoring target relative to the radar based on the spatial location information, and to establish a multi-source data association model that can characterize the correspondence between the monitoring target and the overall displacement using the direction vector and displacement observation data as joint input. Based on the association model, the module performs fusion processing to obtain the overall three-dimensional displacement result of the building facility. The result output module is used to output the vertical component of the overall three-dimensional displacement result as the settlement displacement of the building facility, and to provide the result to the structural health analysis system for building facility deformation assessment.

9. The building settlement monitoring device based on a single radar and multiple targets according to claim 8, characterized in that, The data processing module includes a fusion calculation unit, which takes the direction vector and radial displacement data of each monitored target as input, establishes a linear correspondence between the multi-target observation data and the overall three-dimensional displacement of the building facility, performs fusion calculation through the minimum deviation solution algorithm, outputs the overall three-dimensional displacement result of the building facility, and filters and weights abnormal observation data during the calculation process to improve the stability and accuracy of displacement calculation.

10. A computer device, characterized in that, The computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the building settlement monitoring method based on a single radar and multiple targets as described in any one of claims 1 to 7.

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