House safety risk intelligent monitoring system and method based on Beidou and GIS platform

Abstract

The application relates to the technical field of electric digital data processing, and particularly discloses a house safety risk intelligent monitoring system and method based on Beidou and a GIS platform. The system is provided with an original deformation time sequence statistical module, an absolute deformation time sequence statistical module, a house safety early warning judgment module and a regionalized risk surface visualization module, obtains original deformation time sequences and absolute deformation time sequences, decomposes the absolute deformation time sequences, extracts net deformation, change rate, interlayer drift ratio, crack width growth rate and other features, carries out event detection and early warning judgment in combination with the original deformation time sequences and GIS grid factors, finally carries out quality weighted interpolation by taking the extracted features as input, generates a regionalized risk surface, superimposes the regionalized risk surface on a preset GIS base map, and automatically forms a geographic fence to realize visual delineation, and the regionalized risk surface and the geographic fence intuitively show where and how fast the change is, thereby facilitating linkage and control, work order distribution and path guidance.

Description

Technical Field

[0001] This invention relates to the field of electronic digital data processing technology, specifically to a building safety risk intelligent monitoring system and method based on the BeiDou and GIS platforms. Background Technology

[0002] Existing intelligent monitoring of building safety risks typically adopts an "edge-cloud" architecture: multi-source sensors are deployed at key components and potential hazard points, and connected to an edge gateway via LoRa / NB-IoT / 4G for clock synchronization, noise reduction / anomaly removal, and rapid alarm detection. The data is then uploaded to the cloud for feature extraction and fusion, and combined with standardized thresholds and data-driven methods to assess structural, environmental, and personal safety risks, triggering tiered alarms and work order closures. At the same time, BIM / digital twin visualization of trends and spatial distribution is used in conjunction with equipment health monitoring and OTA maintenance to reduce false alarms and missed alarms and support long-term online monitoring.

[0003] For example, Chinese invention patent CN118780622A discloses a building safety monitoring system and method based on sensor data fusion, which relates to the field of building monitoring and control technology. It collects building sensor fusion monitoring data, including building stress-strain data, relative settlement data, tilt data, and crack data; preprocesses the building sensor fusion monitoring data to obtain usable monitoring data, and divides the usable monitoring data into training and testing sets; analyzes and assesses the usable monitoring data to generate abnormal alarm signals; establishes a building safety level prediction model based on the testing set to generate a building safety level; and performs corresponding processing based on the abnormal alarm signals and the building safety level results.

[0004] For example, Chinese invention patent CN120318020A discloses a remote monitoring system for building structure safety based on multi-source data fusion using the Internet of Things. This system relates to the field of building structure monitoring technology. It divides the target building into different structural modules and deploys data acquisition terminals within these modules to collect multi-dimensional data. The system analyzes and determines whether the location of each data acquisition terminal is a structural risk point. If it is a structural risk point, it generates a simulated stress cloud map based on the correlation between the abnormal data items that caused the structural risk point and other parameter items, as well as other data acquisition terminals that are correlated with the data acquisition terminals at the location of the structural risk point. This allows the system to monitor potential risks to the building structure and assess other locations that may be affected by the identified structural risk point.

[0005] Based on the above technical solutions, it was found that existing building safety risk monitoring mostly relies on various on-site sensors for relative measurement and judgment within local coordinates. The output is mainly threshold alarms and safety levels, and the positioning depends on single-point positioning instruments. However, the coverage of the sensors is generally limited (point / line, difficult to form continuous area perception). Under extreme weather conditions such as strong winds, heavy rain, low temperature freezing, and high temperature exposure, they are easily affected by multipath propagation, water ingress, frost, temperature drift, and chain breaks, resulting in data loss or increased noise. In addition, there is a lack of regional spatial inference and a unified geodetic benchmark. The monitoring results are still at the level of local engineering coordinate system, making it difficult to intuitively see "where is changing and how fast it is changing". It is also difficult to directly and synchronously compare the deformation of different buildings or across seasons, thus limiting the granularity of linkage decision-making in building safety monitoring. Summary of the Invention

[0006] To address the shortcomings of existing technologies, this invention provides an intelligent monitoring system and method for building safety risks based on the BeiDou and GIS platforms, which can effectively solve the problems mentioned in the background technology.

[0007] To achieve the above objectives, the present invention provides the following technical solution: The first aspect of the present invention provides an intelligent monitoring system for building safety risks based on the BeiDou and GIS platforms, comprising: a raw deformation time series statistics module, used to construct a reference network in the building safety monitoring area according to the coordinates of a preset reference station and the coordinates of each building control point, extract the relative coordinates of each building control point relative to the reference station, and perform epoch difference statistics on the absolute coordinates to form the raw deformation time series of each building control point; and an absolute deformation time series statistics module, used to monitor the coordinates of each building control point based on the BeiDou monitoring terminal to obtain the absolute deformation time series of each building control point. The system performs epochal difference statistics on coordinates to form the absolute deformation time series of each building control point. The building safety early warning judgment module is used to decompose the absolute deformation time series into limiting terms and extract features from the decomposed absolute deformation time series to obtain the extracted features of the absolute deformation time series. Combined with the original deformation time series and GIS raster factors, the system performs event detection on building safety and determines whether to issue a building safety risk warning. The regional risk surface visualization module is used to generate regional risk surfaces based on the extracted features of the absolute deformation time series. The regional risk surfaces are then visualized as geofences on a preset GIS map of the building safety monitoring area to complete the intelligent monitoring of building safety risks.

[0008] The second aspect of this invention provides a method for intelligent monitoring of building safety risks based on BeiDou and GIS platforms, comprising: constructing a reference network in the building safety monitoring area according to the coordinates of a preset reference station and the coordinates of each building control point; extracting the relative coordinates of each building control point relative to the reference station and performing epoch difference statistics to form the original deformation time series of each building control point; monitoring the coordinates of each building control point based on the BeiDou monitoring terminal to obtain the absolute coordinates of each building control point; performing epoch difference statistics on the absolute coordinates to form the absolute deformation time series of each building control point; decomposing the absolute deformation time series into limiting terms and extracting features from the decomposed absolute deformation time series to obtain the extracted features of the absolute deformation time series; combining the original deformation time series and GIS raster factors to perform event detection on building safety and determine whether to issue a building safety risk warning; generating a regionalized risk surface based on the extracted features of the absolute deformation time series; visually delineating the regionalized risk surface as a geofence on a preset GIS map of the building safety monitoring area to complete the intelligent monitoring of building safety risks.

[0009] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects:

[0010] (1) This invention provides a building safety risk intelligent monitoring system and method based on Beidou and GIS platforms. A reference network is constructed according to the preset reference station and building control point coordinates. The relative coordinates of the control points relative to the reference station are extracted and epoch difference is performed to form the original deformation time series. The reference network unifies the spatiotemporal reference and provides multiple baseline redundancy to ensure that the relative quantities are reliable and traceable. At the same time, the absolute coordinates of the control points are obtained by the Beidou monitoring terminal and epoch difference is performed to form the absolute deformation time series. The absolute deformation can be compared across buildings and seasons under the unified reference to support spatial inference. The absolute deformation time series is decomposed into limiting terms and features such as net deformation, rate of change, inter-layer drift ratio, and crack width growth rate are extracted. Event detection and early warning judgment are carried out in combination with the original deformation time series and GIS raster factors. Finally, the extracted features are used as input for quality weighted interpolation to generate regional risk surfaces. These are superimposed on the preset GIS base map and automatically form a geofence to achieve visual delineation. The regional risk surfaces and geofence intuitively present "where is changing and how fast it is changing", which is convenient for linkage control, work order dispatch and path guidance.

[0011] (2) This invention determines the building safety risk score, and normalizes and weights features such as net deformation, growth rate, inter-story drift ratio, and crack growth rate according to quality and scenario factors to form an interpretable quantitative score, unifying the judgment criteria for different indicators and different buildings; the score can be smoothly tracked over time and entry / exit thresholds can be set, which not only increases the lead time but also suppresses fluctuations, making it easy to achieve graded response and precise resource allocation according to the score, and can be replayed and versioned to support auditing.

[0012] (3) In this embodiment of the invention, the original deformation is used for quality inspection and gap segmentation, the absolute deformation is used for cross-target alignment and spatial expression, and the GIS raster factor is used for contextual correction and spatial constraints. These parameters are repeatedly reused in the solution-decomposition-detection-scoring-interpolation stages to form a data closed loop. Thus, without adding additional sensors, the anti-defect detection capability and robustness are improved, the operation and maintenance cost is reduced, and the consistency and comparability between different modules are maintained.

[0013] (4) The embodiments of the present invention upgrade the point monitoring of traditional local coordinates combined with threshold alarms to a regional risk surface expression of unified benchmark combined with Beidou time and GIS; introduce limiting term decomposition, non-gap derivative and contextual threshold to make the judgment more stable and less false alarm; through the multi-baseline redundancy of the benchmark network and the linkage of geofence, higher resilience, more intuitive visualization and more efficient handling loop are achieved, significantly improving the early warning timeliness and decision granularity. Attached Figure Description

[0014] The present invention will be further described with reference to the accompanying drawings, but the embodiments in the drawings do not constitute any limitation on the present invention. For those skilled in the art, other drawings can be obtained based on the following drawings without creative effort.

[0015] Figure 1 This is a schematic diagram of the system module connections of the present invention.

[0016] Figure 2 This is a schematic diagram of the method steps of the present invention.

[0017] Figure 3 This is the real-time situation overview interface of the Housing Safety Intelligent Monitoring Platform.

[0018] Figure 4 This is the overview interface of the buildings belonging to the Housing Safety Intelligent Monitoring Platform. Detailed Implementation

[0019] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0020] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0021] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning.

[0022] In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0023] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0024] In the application of BeiDou and GIS platforms in intelligent monitoring of building safety risks, BeiDou typically provides precise location and unified time, while GIS provides spatial organization and spatiotemporal analysis. The combination of the two transforms the measured risks into actionable decisions on a map, upgrading building safety monitoring from point data to a visible, analyzable, and interconnected spatiotemporal risk management system.

[0025] Reference Figure 1 As shown, the first aspect of this invention provides a building safety risk intelligent monitoring system based on the BeiDou and GIS platforms, including: a raw deformation time series statistics module, an absolute deformation time series statistics module, a building safety early warning judgment module, a regionalized risk surface visualization module, and a risk monitoring management library. The risk monitoring management library is used to store preset values ​​for various parameters.

[0026] The preset relationship acquisition process involved in this embodiment includes, but is not limited to, predefined acquisition, matching, and mapping. Specifically, taking the mapping relationship between the maximum span and the weight parameter corresponding to the predefined maximum span as an example, let's first denote the maximum span as L. 区 Then determine the benchmark span L that meets the accuracy and communication requirements for similar projects. 0,区 (Based on targets such as reference station density, baseline length, interpolation error, and communication delay), a span ratio r=L is formed. 区 / L 0,区Subsequently, a monotonic, amplitude-limited weight curve is constructed through three-source calibration: ① baseline network simulation (the growth law of geometric accuracy, interpolation error, and time delay with r under different regional spans); ② historical project statistics (the change of false alarms / missed alarms and handling timeliness with r in large-span areas); ③ expert rules (the risk weight should be increased when it exceeds a certain multiple). Based on this, several anchor points are set and piecewise linear or monotonic spline fitting is performed, constrained to not decrease with r, smooth transition, and maximum value limit, to obtain the mapping set w(r) in the library (e.g., r less than or equal to 1 maps to w=1, r equal to 1.5 maps to w=1.2, r equal to 2 maps to w=1.5, r greater than or equal to 3 maps to w=1.8; the values ​​are recalibrated according to the project). During runtime, only r of the current region needs to be calculated, and the weight parameter corresponding to the maximum span of the region is obtained by looking up / interpolating in the mapping set, which is used for the construction of the baseline network.

[0027] The original deformation time series statistics module is connected to the absolute deformation time series statistics module. The absolute deformation time series statistics module is connected to the building safety early warning judgment module. The building safety early warning judgment module is connected to the regional risk surface visualization module. The original deformation time series statistics module, the absolute deformation time series statistics module, the building safety early warning judgment module, and the regional risk surface visualization module are all connected to the risk monitoring and management database.

[0028] Before conducting on-site monitoring of the monitoring area, the benchmark unification of the monitoring area is first completed: the National Geodetic Coordinate System and the National Elevation Benchmark are selected as the sole references, parallel reference stations and building control points are set up, and the latitude, longitude, and altitude output by each monitoring device are uniformly converted to plane coordinates under the selected projection (such as Gauss-Kruger), and the ellipsoidal height is converted to normal height using a geoid model; at the same time, horizontal and vertical integrated constraints are completed through leveling and network adjustment, forming a unified regional coordinate and elevation framework starting from the benchmark epoch. After completion, elements such as building outlines, topography, roads, pipelines, reference stations, and control points are collected to generate the basic GIS layer and metadata of the monitoring area (including benchmark, epoch, accuracy indicators, and quality identifiers), clarifying the plane and elevation accuracy requirements (such as centimeter-level plane and millimeter-level vertical), and establishing coordinate services and layer publishing, so that all subsequent displacement, drift ratio, risk surface calculations and visualizations can be directly compared, superimposed, and traced under the same benchmark.

[0029] This embodiment targets multiple buildings within the monitoring area, selecting one as a demonstration object for intelligent safety risk monitoring: Under unified coordinates and national elevation datum, building control points are deployed on the roof and key components of the building using existing reference stations. Continuous data acquisition is initiated, and time, coordinate, and elevation are unified. The epoch data undergoes quality checks and elimination to establish an original deformation sequence, which is then decomposed to obtain core indicators such as net deformation, rate of change, and inter-layer drift ratio. Threshold adaptation and risk scoring are performed in conjunction with scenario factors such as wind, rain, and earthquakes. Automatic judgment is made according to four levels: information, early warning, alarm, and emergency, and fences and disposal suggestions are generated on the map. Simultaneously, work orders, verification, and report export are linked to form a closed loop. The above process and parameters can be replicated to other buildings in the area in the same way to achieve parallel monitoring of multiple buildings and regionalized risk surface expression without limiting the protection scope.

[0030] The specific security risk monitoring process in this embodiment of the invention is implemented based on the Housing Safety Intelligent Monitoring Platform, as follows: Figure 3 As shown, Figure 3 This is the real-time situation overview interface of the Housing Safety Intelligent Monitoring Platform, providing situational awareness and dispatch for command and control across the entire region. It summarizes online rate, number of anomalies, real-time risk score, and system status, overlaying environmental background such as wind, rain, and earthquakes, as well as the health of reference stations. This helps to quickly grasp the overall risk level and the reliability of the baseline network, enabling tiered responses, resource allocation, and threshold strategy adjustments—solving the question of "where is the overall risk, and where should we focus our efforts first?"

[0031] The original deformation time series statistics module is used to construct a baseline network in the building safety monitoring area according to the preset coordinates of the reference station and the coordinates of each building control point. It extracts the relative coordinates of each building control point relative to the reference station, performs epoch difference statistics on the absolute coordinates, and forms the original deformation time series of each building control point.

[0032] The aforementioned reference station refers to one or a few fixed BeiDou reference points set up on open, stable ground. Their three-dimensional coordinates have been measured with high precision under the national geodetic coordinate / elevation datum and remain stationary for a long period. It continuously collects satellite observations and produces differential information required for ephemeris / clock error correction and baseline calculation, while also providing unified time synchronization and coordinate transformation parameters. Its function is to "nail" the entire monitoring area to a unified, traceable spatiotemporal reference: providing RTK / PPP references and corrections for each building's measuring points, ensuring comparability of deformation across buildings / seasons, monitoring its own stability to identify systematic drift, and acting as an "anchor point" for data and time under extreme conditions.

[0033] The aforementioned building control points refer to BeiDou measuring points or coordinate-calibrated measuring markers deployed at key locations of each building (such as roof, parapet wall, core tube, foundation edge, etc.). When necessary, they are installed adjacent to and jointly calibrated with inclinometers, hydrostatic levels, crack gauges, etc. Their coordinates are unified to the national benchmark through reference stations / PPP and continuously updated in a time series. Serving as the "deformation anchor point and fusion hub" for each building, it directly outputs the building's absolute displacement / settlement / tilt sequence, integrates and calibrates load-bearing and relative sensors, supports spatial inference within / between buildings and risk surface generation, and accurately locates alarms and work orders to floors / components, enabling coordinated decision-making for individual buildings and regions.

[0034] Specifically, the coordinates of the reference station and the coordinates of the control points of each building are analyzed as follows:

[0035] The maximum span and openness of the building safety monitoring area are obtained and coupled together to obtain the construction feature value of the building safety monitoring area. Specifically, the maximum span of the building safety monitoring area is multiplied by a predefined weight parameter corresponding to the maximum span to obtain the first component of the construction feature of the building safety monitoring area. The openness of the building safety monitoring area is multiplied by a predefined weight parameter corresponding to the openness to obtain the second component of the construction feature of the building safety monitoring area. The first component and the second component of the construction feature of the building safety monitoring area are added together to obtain the construction feature value of the building safety monitoring area. It should be noted that the above coupling process is based on the normalized results of the maximum span and openness of the building safety monitoring area. The weight parameters are all extracted from the risk monitoring management database.

[0036] The maximum span can be extracted from the monitoring records of the building safety monitoring area. Openness indicates the visibility of the sky within the building safety monitoring area or reflects the degree of surrounding obstruction; a higher value indicates greater openness and less obstruction. This is achieved by capturing fisheye panoramic images from several points within the building safety monitoring area. The average percentage of sky / obstacle pixels in the fisheye panoramic images at these points represents the openness.

[0037] The construction characteristic values ​​of the building safety monitoring area are matched with the number of reference stations corresponding to each predefined construction characteristic value interval in the risk monitoring management database to determine the interval to which the construction characteristic values ​​of the building safety monitoring area belong, and the number of reference stations corresponding to that interval is obtained. The number of reference stations is recorded as the reference station deployment matching number.

[0038] The number of reference station deployment adapters increases monotonically with the construction characteristic value; that is, the larger the construction characteristic value, the more reference station deployment adapters are required. A larger construction characteristic value indicates that it is more difficult to maintain the solution quality under constraints such as baseline length limitations, coverage redundancy, geometric accuracy, and damage resistance zoning (cross-zoning deployment). Therefore, a higher density and a larger number of reference stations are needed to ensure spatiotemporal reference stability, controlled interpolation errors, and link redundancy.

[0039] The maximum elevation value of the building is obtained, which can be extracted from the building's basic information record. This elevation value is then weighted and coupled with the construction characteristic values ​​of the building's safety monitoring area to obtain the building's structural influence. Specifically, the coupling involves multiplying the building's maximum elevation value by a predefined weight parameter corresponding to the maximum elevation value in the risk monitoring management database to obtain the first component of the building's structural influence; multiplying the construction characteristic values ​​of the building's safety monitoring area by a predefined weight parameter corresponding to the construction characteristic values ​​to obtain the second component of the building's structural influence; and finally, adding the first and second components of the building's structural influence to obtain the total structural influence.

[0040] The structural influence of the building is matched with the number of building control points corresponding to each predefined structural influence interval to determine the specific interval of the structural influence of the building, and the number of building control points corresponding to the interval is obtained. The obtained number of building control points is recorded as the number of building control point placement matching.

[0041] The number of building control points should monotonically increase with the structural influence of the building; that is, the greater the structural influence, the more building control points should be deployed. A greater structural influence indicates a more irregular plan or elevation, and more complex or critical components (large cantilever, transfer floor, concave / convex and eccentric structures, weak stories, expansion joints, multi-tower interconnections, foundation differences, etc.). This makes the deformation field more likely to exhibit a non-uniform and torsional pattern. To reliably identify differential settlement, inter-story relative displacement, and torsional components and perform cross-checking, it is necessary to improve the spatial resolution and redundancy of observations. Therefore, the number of building control points should monotonically increase with the structural influence.

[0042] The number of reference stations to be adapted, the number of building control points to be adapted, and the preset set of layout constraints are input into the mixed integer linear programming algorithm, and the coordinates of the reference stations and the coordinates of each building control point are output.

[0043] Using the number of reference stations, the number of control points for each building, and the preset layout constraint set as input, a mixed-integer linear programming problem is constructed. Under a unified coordinate system, the layout coordinates of reference stations and control points for each building are automatically filtered from a pre-selected candidate point set and output. The constraint set can simultaneously include: quantity constraints (total number of reference stations, number of control points per building, not less than three points and not collinear), coverage and redundancy constraints (each control point is served by at least two reference stations, and the monitoring grid is covered by at least a certain number of reference stations), baseline constraints (the distance from the reference station to the control point falls within a given interval and has line of sight), geometric and signal quality constraints (sky openness is not less than the threshold, and the carrier-to-noise ratio and geometric accuracy scores meet the lower / upper limit requirements), minimum spacing and azimuth distribution constraints (the spacing between points on the same roof is not less than the limit value, and the control points are distributed in at least three azimuth sectors), zonal damage resistance constraints (reference stations are distributed in different power supply or communication zones, and each zone has not less than the specified number), and construction and safety constraints (avoiding prohibited buffer zones, prioritizing the location of key components such as the core tube / corners / transition layers). The coordinate results are directly given after solving.

[0044] For example, output the east coordinates, north coordinates, and normal altitude of the reference station and control point respectively.

[0045] Reference station 1: East coordinates 345120.0 meters, North coordinates 2975430.0 meters, Normal elevation 42.38 meters.

[0046] Building A: Control Point 1: East coordinates 345185.6 meters, North coordinates 2975488.2 meters, Normal height 39.92 meters.

[0047] A baseline network is constructed based on the coordinates of the reference station and the coordinates of the control points of each building.

[0048] In this embodiment, a benchmark network is constructed, forming a spatiotemporally integrated and redundantly constrained monitoring framework under unified geodetic coordinates and national elevation benchmarks. On the one hand, it continuously provides high-precision corrections and unified time synchronization for all measuring points, significantly improving the accuracy and comparability of indicators such as absolute displacement and inter-layer drift ratio (direct alignment across buildings and seasons), and reducing false alarms / missed alarms caused by multipath, occlusion, and instrument drift. On the other hand, through multi-baseline redundancy and automatic quality checks within the network (baseline closure error, coordinate stability, and mutual monitoring of reference stations), it achieves resilience and self-diagnosis, maintaining stable solutions and traceable results even if a single station is abnormal. At the same time, it provides a uniform and reliable control framework for GIS risk surface interpolation, making "where it is changing and how fast it is changing" more intuitive and credible, and supporting the linkage of construction layout, verification, and emergency communication (short messages), ultimately achieving a comprehensive effect of shortened deployment cycle, reduced operation and maintenance costs, more timely early warning, and finer decision granularity.

[0049] The aforementioned benchmark network construction specifically involves building the overall framework of the monitoring buildings, as detailed below. Figure 4As shown, Figure 4 This is the building overview interface of the Housing Safety Intelligent Monitoring Platform, designed for refined diagnosis and handling of individual buildings. It intuitively presents the 3D layout and surrounding environment, and, together with recent key feature curves (such as net deformation), allows you to pinpoint which building and which point is changing, determine whether it is continuous or sudden, and initiate review, adjust fences, or export individual building reports—solving the question of "what exactly happened to this building and how quickly it changed."

[0050] Furthermore, the original deformation time sequence of each building control point is formed, and the specific analysis process is as follows:

[0051] At each epoch, the relative coordinates of each building control point of the house relative to the reference station are extracted and recorded as the relative coordinates of each building control point of the house at each epoch. The epoch point represents the sampling time point or sampling moment of the relative coordinates.

[0052] The epoch point where the relative coordinates are initially extracted is recorded as the reference epoch point. The relative coordinates of each building control point under the current epoch point are processed by the difference between the relative coordinates of the corresponding building control points under the reference epoch point to obtain the relative coordinate deviation of each building control point under the epoch point. The epoch difference is represented by the relative coordinate difference between the current epoch point and the reference epoch point respectively.

[0053] The relative coordinate deviations of each building control point under the statistical epoch difference point are sorted according to the relative epoch point sequence to obtain the original deformation time series of each building control point.

[0054] In this embodiment, the original deformation time series is obtained and can be used as the "foundation data" for the whole-link judgment. It is not only used for quality inspection and anomaly identification (cycle slip, false fixation, missing measurement, geometric deterioration, multipath / water ingress, etc.), timely marking and removing inferior epoch points, but also provides reliable weights and covariance priors for multi-source fusion, reducing the pull of inferior observations on the results and significantly reducing false alarms / missed alarms. It can also support the stripping of baseline / seasonal / temperature terms, thereby stably obtaining net deformation, slope and acceleration, improving the sensitivity and reliability of trend and sudden judgment. Furthermore, it can serve as an emergency backup and verification basis in extreme operating conditions or algorithm anomalies, ensuring that the entire monitoring-early warning-response chain is interpretable, replayable, and verifiable.

[0055] The absolute deformation time series statistics module is used to monitor the coordinates of each building control point based on the Beidou monitoring terminal, obtain the absolute coordinates of each building control point, perform epoch difference statistics, and form the absolute deformation time series of each building control point.

[0056] Specifically, the absolute deformation time sequence of each building control point is formed, and the specific analysis process is as follows:

[0057] The Beidou monitoring terminal monitors the absolute coordinates of each building control point in real time, obtaining the absolute coordinates of each building control point at each epoch.

[0058] The absolute coordinates of each building control point at each epoch are optimized, specifically as follows:

[0059] The GIS platform receives absolute coordinate monitoring data transmitted from the BeiDou monitoring terminal in real time, extracts the transmission carrier-to-noise ratio (TCN) and phase cycle slip of the BeiDou monitoring terminal at each epoch, and combines these with the quality assessment influencing factors of the openness of the building safety monitoring area to obtain the coordinate quality assessment parameters at each epoch. The TCN and phase cycle slip can be extracted from the received records on the GIS platform.

[0060] The specific coupling process is as follows:

[0061] The monitoring openness of the building safety monitoring area is matched with the quality assessment impact elements corresponding to each predefined monitoring openness interval in the risk monitoring management database to determine the specific interval of the monitoring openness of the building safety monitoring area and obtain the quality assessment impact element corresponding to the interval.

[0062] Among them, the quality assessment influencing factor monotonically increases with the openness; the larger the openness, the larger the quality assessment influencing factor. A high openness means more visible satellites, a higher carrier-to-noise ratio, better geometric accuracy, fewer cycle slips and multipaths, and more stable timing, thereby improving the overall quality of coordinate and deformation calculations.

[0063] The transmission carrier-to-noise ratio and phase cycle slip of the BeiDou monitoring terminals at each epoch were normalized. The normalized results were then weighted and aggregated with the quality assessment influencing factors to obtain the coordinate quality assessment parameters at each epoch, specifically:

[0064]

[0065] In the formula, QAy is the coordinate quality assessment parameter at the y-th epoch, and y is the number of each epoch. Y represents the total number of epochs, CN0 y Let GF be the transmission carrier-to-noise ratio of the BeiDou monitoring terminal at the y-th epoch. y Let d1 be the phase cycle slip of the BeiDou monitoring terminal at the y-th epoch, Q be the quality assessment impact element, d1 be the weighting factor corresponding to the transmission carrier-to-noise ratio predefined in the risk monitoring management library, and d2 be the weighting factor corresponding to the phase cycle slip predefined in the risk monitoring management library.

[0066] It should be explained that the aforementioned carrier-to-noise ratio (CNR) is a core indicator for measuring the strength of the BeiDou signal relative to its noise level. A higher CNR indicates stronger signal power relative to noise, resulting in smaller errors in the observed data. Phase slips are instantaneous jumps in carrier phase observations, directly causing positioning errors.

[0067] The coordinate quality assessment parameters at each epoch are compared with the predefined coordinate quality assessment benchmark parameters. If the coordinate quality assessment parameters at each epoch are all greater than or equal to the coordinate quality assessment benchmark parameters, then there is no need to optimize the absolute coordinates. If there is a coordinate quality assessment parameter at a certain epoch that is less than the coordinate quality assessment benchmark parameter, then the absolute coordinates of each building control point at that epoch are removed, thus completing the optimization of the absolute coordinates of each building control point at each epoch.

[0068] After statistical optimization, the absolute coordinates of each building control point under several epochs are denoted as the effective absolute coordinates of each building control point under each epoch. The effective absolute coordinates correspond to each epoch, forming an absolute epoch sequence according to the sampling order.

[0069] Based on the effective absolute coordinates of each building control point under each epoch, the epoch first in the absolute epoch sequence is designated as the standard epoch. The effective absolute coordinates of each building control point under each epoch are then compared with the effective absolute coordinates of each building control point under the standard epoch to obtain the absolute deformation time series of each building control point. The order of the absolute deformation time series is sorted according to the absolute epoch sequence.

[0070] In this embodiment, absolute deformation time series is obtained (unified to national geodetic coordinates and elevation datum, and after quality inspection and decomposition purification). All monitoring points are "nailed" to the same scale, and deformations across buildings, seasons, and equipment can be directly compared. Thresholds and classification standards are unified, and the false alarm rate is reduced. It can robustly calculate trends / rates / accelerations and inter-layer drift ratios, supporting early warning and residual risk assessment. It also provides reliable input for GIS to generate regionalized risk surfaces and settlement gradients, intuitively showing "where is changing and how fast it is changing," and linking fencing and disposal. Moreover, it is easy to perform contextualized threshold adaptation and multi-source fusion (tilt angle, cracks, acceleration) with factors such as meteorology and load, improving the credibility of judgments, forming a traceable evidence chain and a basis for compliant reports, serving equipment health diagnosis, operation and maintenance decisions, and review, thereby improving the overall monitoring accuracy, early warning timeliness, and command decision granularity.

[0071] Furthermore, optimizing the absolute coordinates of each building control point at each epoch also includes:

[0072] Extract the time interval between several adjacent epochs in the absolute epoch sequence, and denote it as the gap between each adjacent epoch.

[0073] The gaps of each adjacent epoch point are compared with the gaps defined by the predefined epoch point to obtain the gap comparison results. Based on the gap comparison results, the GIS platform determines whether the gaps of each adjacent epoch point should be discarded.

[0074] The gap comparison results include the first gap comparison result and the second gap comparison result.

[0075] The first result of the gap comparison is that the gaps of all adjacent epochs are smaller than the epoch-bound gap. The second result of the gap comparison is that there exists an adjacent epoch gap that is greater than or equal to the epoch-bound gap.

[0076] If the gap comparison result shows the first result, the GIS platform determines that the gaps of adjacent epochs are not discarded, indicating that the adjacent epochs meet the feature extraction constraints. If the gap comparison result shows the second result, the GIS platform determines that the gaps of adjacent epochs are discarded, and the gaps of adjacent epochs are marked as missing on the coordinate monitoring time axis, indicating that the adjacent epochs do not meet the feature extraction constraints.

[0077] The building safety early warning determination module is used to decompose the absolute deformation time series into limiting terms, extract features from the decomposed absolute deformation time series, obtain the extracted features of the absolute deformation time series, and combine the original deformation time series and GIS raster factors to perform event detection on building safety and determine whether to issue a building safety risk warning.

[0078] The aforementioned constraint decomposition specifically involves a constrained physical decomposition of the absolute deformation time series: first, a quality check and gap segmentation are performed, retaining only valid epochs; then, the curve is represented by a small number of interpretable constraints—including slow-changing trends (applied smoothing and slope upper limits), diurnal and seasonal cycles (only a few harmonics are taken and their amplitudes are constrained), and temperature effects (including time lags and quadratic terms, with upper and lower bounds for coefficients), with rainfall lags and known event steps added if necessary; each component is estimated under a quality-weighted fitting, and the absolute deformation is successively subtracted from the periodic term, temperature term, rainfall-induced term, and step term to obtain the net deformation; finally, the rate of change and acceleration are calculated only from the net deformation over continuous time periods, without crossing gaps. This removes reversible fluctuations and avoids overfitting, making subsequent threshold determination, trend warning, and regional risk assessment more stable, comparable, and traceable.

[0079] Specifically, feature extraction is performed on the decomposed absolute deformation time series to obtain the extracted features of the absolute deformation time series. The specific extraction process is as follows:

[0080] The decomposed absolute deformation time series is denoted as the net deformation time series. The net deformation of the house at the adjacent epoch is obtained. Then, according to the net deformation time series, the net deformation of the current epoch is differentiated from the net deformation of the previous epoch to obtain the house deformation growth rate at the adjacent epoch.

[0081] Extract the net deformation of the current epoch on the Z-axis and the net deformation of the previous epoch on the Z-axis, perform difference processing, and obtain the deformation displacement of adjacent epochs on the Z-axis.

[0082] The adjacent floor heights of a building can be obtained, which can be extracted from the building's basic information records. A finite difference approximation is then performed on these adjacent floor heights and their deformation displacements along the Z-axis to obtain the inter-floor drift ratio at adjacent epochs. The finite difference approximation can be substituted into the following formula:

[0083]

[0084] In the formula, Let u(z) be the inter-story drift ratio between adjacent epochs, which can be understood as the average shear deformation rate / rotation angle of that story. u(z) represents the lateral displacement of the story along a certain horizontal direction, a function of height z, where z is the vertical height coordinate. i , z i-1 The elevations of the floors above and below this level are given, where H represents the height of adjacent floors in the building, and u(z) represents the floor level above and below this level. i ), u(z) i-1 These represent the lateral displacements at the upper and lower floors, respectively. This represents the interlayer relative displacement of this layer.

[0085] The extracted features of the absolute deformation time series include the net deformation of houses at adjacent epochs, the deformation growth rate of houses at adjacent epochs, and the inter-story drift ratio of houses at adjacent epochs.

[0086] Furthermore, the specific process for determining whether to issue a building safety risk warning is as follows:

[0087] Extracted features of the original deformation time series are obtained, including the original net deformation of the house at adjacent epochs, the original deformation growth rate of the house at adjacent epochs, and the original inter-story drift ratio of the house at adjacent epochs.

[0088] Based on the original net deformation of the house at adjacent epochs, a net deformation threshold adjustment element is obtained. Specifically, the original net deformation of the house at adjacent epochs is matched with the net deformation threshold adjustment element corresponding to each predefined original net deformation interval of the house in the risk monitoring and management database to determine the specific interval of the original net deformation of the house at adjacent epochs. The net deformation threshold adjustment element corresponding to this interval is obtained and coupled with the predefined net deformation benchmark threshold. Specifically, the net deformation threshold adjustment element is multiplied by the net deformation benchmark threshold to obtain the net deformation reference threshold.

[0089] The original deformation growth rate of houses at adjacent epochs is matched to obtain the deformation growth rate threshold adjustment element. Specifically, the original deformation growth rate of houses at adjacent epochs is matched with the deformation growth rate threshold adjustment element corresponding to each predefined original deformation growth rate interval of houses in the risk monitoring and management database to determine the specific interval of the original deformation growth rate of houses at adjacent epochs. The deformation growth rate threshold adjustment element corresponding to this interval is obtained and coupled with the predefined deformation growth rate benchmark threshold. Specifically, the deformation growth rate threshold adjustment element is multiplied by the deformation growth rate benchmark threshold to obtain the deformation growth rate reference threshold.

[0090] The original inter-story drift ratios of houses at adjacent epochs are matched to obtain drift ratio threshold adjustment elements. Specifically, the original inter-story drift ratios of houses at adjacent epochs are matched with the drift ratio threshold adjustment elements corresponding to the predefined intervals of original inter-story drift ratios of houses in the risk monitoring and management database to determine the specific intervals of the original inter-story drift ratios of houses at adjacent epochs. The drift ratio threshold adjustment element corresponding to this interval is obtained and coupled with the predefined inter-story drift ratio benchmark threshold to obtain the inter-story drift ratio reference threshold.

[0091] It should be explained that the above-mentioned net deformation threshold adjustment element, deformation growth rate threshold adjustment element, and drift ratio threshold adjustment element all decrease as the original net deformation of the building, the original deformation growth rate of the building, and the original inter-story drift ratio of the building increase. The larger the original net deformation of the building, the original deformation growth rate of the building, and the original inter-story drift ratio of the building, the higher the potential safety risk of the building, and the threshold should be tightened to improve sensitivity.

[0092] The preset GIS raster factor is extracted and coupled with the inter-layer drift ratio reference threshold to obtain the inter-layer drift ratio adaptation threshold.

[0093] The coupling between the preset GIS raster factor and the inter-layer drift ratio reference threshold is specifically obtained by substituting the contextualized threshold adjustment formula:

[0094]

[0095] In the formula, To adapt the threshold for interlayer drift ratio, The interlayer drift ratio is the reference threshold. To preset the GIS raster factor, g This is a working condition correction function that adjusts the threshold value either upwards or downwards based on the current environment. These are wind / rain / earthquake intensity factors, which normalize wind speed, rainfall intensity, earthquake (PGA / intensity) and other physical quantities to 0–1.

[0096] When things are stable: ≈0, g≈1, at this point, the interlayer drift ratio is used as the reference threshold. .

[0097] Extreme operating conditions: If we increase the value of g and set g < 1, the interlayer drift will be smaller than the baseline threshold, making the judgment more sensitive (earlier warning).

[0098] The net deformation of the house at adjacent epochs, the growth rate of the house deformation at adjacent epochs, and the inter-story drift ratio of the house at adjacent epochs are compared with the reference thresholds for net deformation, growth rate, and inter-story drift ratio, respectively. If any extracted feature of the absolute deformation time series is greater than the corresponding threshold, it is determined to be an instantaneous risk event; otherwise, it is determined to be a continuous static event.

[0099] If the building safety risk monitoring is an instantaneous risk event, then an early warning will be issued in real time. If the building safety risk monitoring is a continuous static event, then the building safety risk will be continuously monitored, and a building safety risk score will be determined.

[0100] In this embodiment, a dual-track strategy combining instantaneous event early warning with continuous event monitoring and scoring is adopted. This strategy can simultaneously improve timeliness and stability. For sudden risks (such as strong wind vibration, impact, and abnormal acceleration), real-time early warning prompts are provided, significantly reducing the detection-response delay and triggering encrypted sampling, evidence preservation, and personnel reminders, thereby reducing missed reports and secondary risks. For slowly changing risks (such as gradual settlement and slow crack propagation), net deformation, rate, and interlayer drift ratio are continuously tracked and risk scores are calculated. Short-term noise is filtered out, false alarms are suppressed, and a comparable and traceable quantitative classification is formed, which facilitates the formulation of disposal and maintenance plans according to priority. Overall, this approach ensures that "urgent events are seen early" and "slow changes are accurately observed," thereby increasing the lead time for early warnings, reducing false alarms and missed reports, optimizing resource allocation, and supporting more granular coordinated decision-making and emergency command.

[0101] Specifically, continuous monitoring of building safety risks is conducted, and the specific monitoring process is as follows:

[0102] Based on the extracted features of the absolute deformation time series, the building safety risk score is determined in real time.

[0103] The building safety risk score is compared with predefined risk score intervals, which include a first risk score interval, a second risk score interval, a third risk score interval, and a fourth risk score interval. Each risk score interval is assigned sequentially, increasing the building risk level.

[0104] Example: Let t1 be the threshold for the first risk score interval, t2 be the threshold for the second risk score interval, t3 be the threshold for the third risk score interval, and t4 be the threshold for the fourth risk score interval. Where t1... <t2<t3<t4。

[0105] If the building safety risk score falls within the first risk score interval, the building safety will be continuously monitored. At the same time, based on the building safety risk score, the adjacent epoch time interval factor will be matched. Specifically, the adjacent epoch time interval factor corresponding to the first risk score interval will be extracted and coupled with the currently set adjacent epoch time interval. Specifically, the adjacent epoch time interval factor will be multiplied by the adjacent epoch time interval to obtain the adjacent epoch adaptation time interval, which will be used to update the adjacent epoch time interval and configure the next round of monitoring.

[0106] If the building safety risk score falls within the second risk score range, the GIS platform initiates a rapid review command to extract the deformation direction and deformation amplitude of adjacent building control points. The deformation direction and deformation amplitude can be obtained from the monitoring records of the GIS platform. It is then determined whether the deformation direction and deformation amplitude of adjacent building control points are consistent. If all adjacent building control points are consistent, the building safety is continuously monitored. If a certain building control point is inconsistent, the weight factor of the extracted features of that building control point in the building safety risk score is reduced until the weight factor is defined, and the building safety is continuously monitored again.

[0107] The determination of consistency specifically means that the two points are governed by the same load and the same structural working mode (translation / slight torsion of the same rigid block, or approximately consistent response of the same component under low curvature bending) and there is no abnormal local differential deformation.

[0108] If the building safety risk score falls within the third risk score range, a zone inspection is triggered. At the same time, the GIS platform reports a redundant BDS short message, including the building coordinates, building safety risk score, trigger factor, and suggestion code.

[0109] If the building safety risk score belongs to the fourth risk score interval, a risk warning for building safety will be issued, all original monitoring data will be retained, a geofence will be formed on the preset GIS map, and a transmission carrier-to-noise ratio (TCN) reference threshold correction element will be matched according to the building safety risk score. Specifically, the TCN reference threshold correction element corresponding to the fourth risk score interval will be extracted and coupled with the preset TCN. Specifically, the TCN reference threshold correction element will be multiplied by the preset TCN to obtain the TCN boundary threshold.

[0110] The optimization of the absolute coordinates of each building control point at each epoch also includes comparing the transmission carrier-to-noise ratio (TCN) of the monitoring terminal at each epoch with a TCN threshold. If the TCN of the monitoring terminal at any epoch is less than the TCN threshold, the corresponding absolute coordinate data at that epoch is discarded and not included in the construction of the absolute deformation time series for each building control point. If the TCN of the monitoring terminal at each epoch is greater than or equal to the TCN threshold, the absolute coordinate data at each epoch is retained.

[0111] In this embodiment, the implementation of a risk warning combined with a tiered response mechanism can simultaneously improve timeliness and reliability: sudden anomalies are quickly identified and immediately alerted, significantly shortening the time from discovery to handling; gradually changing risks are presented through continuous monitoring and quantitative scoring, suppressing short-term noise and reducing false alarms and missed alarms; sampling, fencing, verification, and handling are linked according to information, warning, alarm, and emergency levels, enabling precise resource allocation based on the severity of risk; evidence and parameter write-back are retained throughout the process, forming a traceable and adaptive closed loop, improving the granularity and executability of command and decision-making.

[0112] Furthermore, a building safety risk score is determined, and the specific determination process is as follows:

[0113] The extracted features of the absolute deformation time series also include the growth rate of the house crack width at adjacent epochs.

[0114] Extract the original growth rate of house crack width at adjacent epochs and match it to obtain the crack width growth rate threshold adjustment element. Specifically, match the original growth rate of house crack width at adjacent epochs with the crack width growth rate threshold adjustment element corresponding to each predefined original growth rate interval of house crack width in the risk monitoring and management database to determine the interval to which the original growth rate of house crack width at adjacent epochs belongs, and obtain the crack width growth rate threshold adjustment element corresponding to the interval. Couple it with the predefined crack width benchmark growth rate. Specifically, multiply the crack width growth rate threshold adjustment element with the crack width benchmark growth rate to obtain the crack width reference growth rate.

[0115] The threshold adjustment element for crack width growth rate decreases monotonically with the original crack width growth rate; the larger the original crack width growth rate, the smaller the resulting threshold adjustment element. When the measured crack growth rate is larger and the risk is higher, the threshold should be tightened to improve sensitivity; therefore, the adjustment element should decrease as the growth rate increases.

[0116] The net deformation, deformation growth rate, inter-story drift ratio, and crack width growth rate of adjacent epochs are compared with the reference thresholds for net deformation, deformation growth rate, inter-story drift ratio, and crack width growth rate, respectively. Weighting factors are then introduced to sequentially weight and aggregate the deviation results to obtain the building safety risk score. The specific analysis method is as follows:

[0117]

[0118] In the formula, R represents the building safety risk score. H represents the net deformation of the house at adjacent epochs. The net deformation reference threshold is used. This represents the rate of increase in house deformation at adjacent epochs. The deformation growth rate is set as a reference threshold, and V is the inter-story drift ratio between adjacent epochs. The inter-layer drift ratio is the adaptation threshold, and W is the rate of increase in house crack width between adjacent epochs. The reference growth rate of crack width is denoted as a1, which is the weighting factor corresponding to the predefined net deformation of the building in the risk monitoring and management database. a2 is the weighting factor corresponding to the predefined deformation growth rate of the building in the risk monitoring and management database. a3 is the weighting factor corresponding to the predefined inter-story drift ratio of the building in the risk monitoring and management database. a4 is the weighting factor corresponding to the predefined crack width growth rate of the building in the risk monitoring and management database.

[0119] The system pre-defines the correspondence between indicators and weights in the risk monitoring and management database. First, it establishes a mapping set for indicators such as net deformation, deformation growth rate, inter-story drift ratio, and crack width growth rate. During runtime, the system simply substitutes the real-time indicator values ​​into their corresponding mappings to directly read the weights for net deformation, growth rate, inter-story drift ratio, and crack growth rate. This mapping set is based on historical monitoring and event samples, combined with structural type and importance level. It groups and statistically analyzes different operating conditions (wind, rain, earthquake, etc.), performs binning and monotonic constraint fitting (or piecewise linear / spline interpolation) according to expert thresholds and empirical upper / lower limits, and then uses playback and cross-validation to calibrate false alarms / false negatives before being fixed into the database and managed in a versioned manner. This ensures consistency while also allowing for scenario adaptation.

[0120] In this embodiment, multivariate analysis is used to analyze the net deformation, deformation growth rate, inter-story drift ratio, and crack width growth rate of the building. Specifically, the correlation of these parameters is considered. Net deformation is the displacement state, and the deformation growth rate is its first difference (difference in displacement between adjacent epochs / time), reflecting "how fast it changes." The inter-story drift ratio is the normalized difference in displacement between adjacent floors (divided by story height), equal to the spatial gradient of horizontal displacement. The crack width growth rate is driven by both the drift ratio and the growth rate, often exhibiting a lagged increase. In the small deformation stage, these quantities should be consistent in direction and their amplitudes should be smooth over time. When the growth rate / drift ratio exceeds the threshold or positive acceleration occurs at consecutive epochs, the crack growth rate rises accordingly and feedback reduces the stiffness of the components, causing the net deformation and drift ratio to be further amplified under the same external load, forming a closed loop of displacement, rate, crack, stiffness degradation, and larger displacement. Therefore, engineering judgments need to check the consistency of direction / amplitude / correlation within the same time window and not calculate across gaps to distinguish between real evolution and noise jumps.

[0121] The regionalized risk surface visualization module is used to generate regionalized risk surfaces based on the extracted features of absolute deformation time series. The regionalized risk surfaces are then visualized and delineated on a preset GIS map of the building safety monitoring area to complete the intelligent monitoring of building safety risks.

[0122] Under a unified coordinate system and national elevation datum, comparable features (such as net deformation, rate of change, inter-layer drift ratio, crack growth rate, etc.) are extracted from the absolute deformation time series of each monitoring point according to the current time window. After masking inferior epoch points and gaps by combining quality weights and contextual thresholds, the point features are generated into a continuous regionalized risk surface through quality-weighted interpolation (such as inverse distance or kriging). Subsequently, the risk surface is rasterized and contour lines are extracted according to the graded thresholds. Connectivity aggregation, smoothing and topology correction are performed to obtain a set of over-limit area polygons. These polygons are superimposed on the preset basic GIS layer of the building safety monitoring area and attributes such as level, feature source, time window and confidence level are written to form a visualized geofence, which is refreshed with new data to achieve dynamic delineation and linkage control of "where is changing and how fast it is changing".

[0123] Reference Figure 2 As shown, the second aspect of the present invention provides a method for intelligent monitoring of building safety risks based on Beidou and GIS platforms, including: constructing a reference network in the building safety monitoring area according to the coordinates of a preset reference station and the coordinates of each building control point; extracting the relative coordinates of each building control point relative to the reference station and performing epoch difference statistics to form the original deformation time sequence of each building control point.

[0124] Based on the BeiDou monitoring terminal, coordinate monitoring is performed on the control points of each building to obtain the absolute coordinates of each control point. The absolute coordinates are then statistically analyzed using epoch difference to form the absolute deformation time series of each control point.

[0125] The absolute deformation time series is decomposed into limiting terms, and features are extracted from the decomposed absolute deformation time series to obtain the extracted features of the absolute deformation time series. Combined with the original deformation time series and GIS raster factors, event detection is performed on building safety to determine whether to issue a building safety risk warning.

[0126] Based on the extracted features of the absolute deformation time series, regional risk surfaces are generated. These regional risk surfaces are then visualized and delineated on a preset GIS map of the building safety monitoring area, thus completing the intelligent monitoring of building safety risks.

[0127] The above description is merely an example and illustration of the structure of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the structure of the invention or exceed the scope defined by the present invention, they should all fall within the protection scope of the present invention.

Claims

1. A building safety risk intelligent monitoring system based on BeiDou and GIS platforms, characterized in that: include: The original deformation time series statistics module is used to construct a reference network in the building safety monitoring area according to the preset coordinates of the reference station and the coordinates of each building control point. It extracts the relative coordinates of each building control point relative to the reference station and performs epoch difference statistics to form the original deformation time series of each building control point. The absolute deformation time series statistics module is used to monitor the coordinates of each building control point of the building based on the Beidou monitoring terminal, obtain the absolute coordinates of each building control point, perform epoch difference statistics on the absolute coordinates, and form the absolute deformation time series of each building control point. The building safety early warning judgment module is used to decompose the absolute deformation time series into limiting factors and extract features from the decomposed absolute deformation time series to obtain the extracted features of the absolute deformation time series. Combined with the original deformation time series and GIS raster factors, the module performs event detection on building safety and determines whether to issue a building safety risk warning. The regionalized risk surface visualization module is used to generate regionalized risk surfaces based on the extracted features of the absolute deformation time series. The regionalized risk surfaces are then visualized on the preset GIS map of the building safety monitoring area to form a geofence, thus completing the intelligent monitoring of building safety risks. The specific analysis process for the original deformation time sequence of each building control point is as follows: At each epoch, the relative coordinates of each building control point of the house relative to the reference station are extracted and recorded as the relative coordinates of each building control point of the house at each epoch. The epoch point represents the sampling time point or sampling moment of the relative coordinates. The epoch point where the relative coordinates are initially extracted is recorded as the reference epoch point. The relative coordinates of each building control point under the current epoch point are compared with the relative coordinates of the corresponding building control point under the reference epoch point to obtain the relative coordinate deviation of each building control point under the epoch point. The epoch difference is represented by the relative coordinate difference between the current epoch point and the reference epoch point respectively. The relative coordinate deviations of each building control point under the statistical epoch difference point are sorted according to the relative epoch point sequence to obtain the original deformation time series of each building control point.

2. The intelligent monitoring system for building safety risks based on BeiDou and GIS platforms according to claim 1, characterized in that: The specific analysis process for the coordinates of the reference station and the coordinates of the control points of each building is as follows: The maximum span and the openness of the building safety monitoring area are obtained and coupled together to obtain the construction characteristic value of the building safety monitoring area; The construction characteristic values ​​of the building safety monitoring area are matched with the number of reference stations deployed corresponding to each predefined construction characteristic value interval, and the result is recorded as the number of reference station deployments. The maximum elevation value of the building is obtained and coupled with the construction characteristic value of the building safety monitoring area to obtain the structural influence of the building. The structural influence of the building is matched with the number of building control points corresponding to each predefined structural influence interval, and the resulting number of building control points is recorded as the number of building control point matching points. Input the number of reference station deployment adapters, the number of building control point deployment adapters, and the preset deployment constraint set into the mixed integer linear programming algorithm, and output the coordinates of the reference station deployment and the coordinates of each building control point. A baseline network is constructed based on the coordinates of the reference station and the coordinates of the control points of each building.

3. The intelligent monitoring system for building safety risks based on BeiDou and GIS platforms according to claim 1, characterized in that: The specific analysis process for the absolute deformation time sequence of each building control point is as follows: The Beidou monitoring terminal monitors the absolute coordinates of each building control point in real time, and obtains the absolute coordinates of each building control point at each epoch. The absolute coordinates of each building control point at each epoch are optimized, specifically as follows: The GIS platform receives absolute coordinate monitoring data transmitted by the Beidou monitoring terminal in real time, extracts the transmission carrier-to-noise ratio and phase cycle slip of the Beidou monitoring terminal at each epoch, and combines them with the quality assessment influencing element of the openness of the building safety monitoring area to obtain the coordinate quality assessment parameter at each epoch. The coordinate quality assessment parameters at each epoch are compared with the predefined coordinate quality assessment benchmark parameters. If the coordinate quality assessment parameters at each epoch are all greater than or equal to the coordinate quality assessment benchmark parameters, then there is no need to optimize the absolute coordinates. If there is a coordinate quality assessment parameter at a certain epoch that is less than the coordinate quality assessment benchmark parameter, then the absolute coordinates of each building control point at that epoch are removed, thus completing the optimization of the absolute coordinates of each building control point at each epoch. After statistical optimization, the absolute coordinates of each building control point of the house at several epochs are recorded as the effective absolute coordinates of each building control point of the house at each epoch. The effective absolute coordinates correspond to each epoch, forming an absolute epoch sequence according to the sampling order. Based on the effective absolute coordinates of each building control point under each epoch, the epoch first in the absolute epoch sequence is designated as the standard epoch. The effective absolute coordinates of each building control point under each epoch are then compared with the effective absolute coordinates of each building control point under the standard epoch to obtain the absolute deformation time series of each building control point. The order of the absolute deformation time series is sorted according to the absolute epoch sequence.

4. The intelligent monitoring system for building safety risks based on BeiDou and GIS platforms according to claim 3, characterized in that: The optimization of the absolute coordinates of each building control point at each epoch also includes: Extract the time interval between several adjacent epochs in the absolute epoch sequence, and denote it as the gap between each adjacent epoch; The gaps between adjacent epochs are compared with the gaps defined by predefined epochs to obtain the gap comparison results. Based on the gap comparison results, the GIS platform determines whether to discard the gaps between adjacent epochs. The gap comparison results include a first gap comparison result and a second gap comparison result; The first result of the gap comparison is that the gaps of each adjacent epoch point are all smaller than the epoch point boundary gap, and the second result of the gap comparison is that there are adjacent epoch point gaps that are greater than or equal to the epoch point boundary gap. If the gap comparison result shows the first result, the GIS platform determines that the gaps of adjacent epochs are not discarded, indicating that the adjacent epochs meet the feature extraction constraints. If the gap comparison result shows the second result, the GIS platform determines that the gaps of adjacent epochs are discarded, and the gaps of adjacent epochs are marked as missing on the coordinate monitoring time axis, indicating that the adjacent epochs do not meet the feature extraction constraints.

5. The intelligent monitoring system for building safety risks based on BeiDou and GIS platforms according to claim 1, characterized in that: The decomposed absolute deformation time series is subjected to feature extraction to obtain the extracted features of the absolute deformation time series. The specific extraction process is as follows: The decomposed absolute deformation time series is denoted as the net deformation time series. The net deformation of the house at the adjacent epoch is obtained. According to the net deformation time series, the net deformation of the current epoch is differentiated from the net deformation of the previous epoch to obtain the house deformation growth rate at the adjacent epoch. Extract the net deformation of the current epoch on the Z-axis and the net deformation of the previous epoch on the Z-axis, perform difference processing, and obtain the deformation displacement of adjacent epochs on the Z-axis. Obtain the adjacent floor heights of the building and perform finite difference approximation calculations on the deformation displacement of adjacent epochs along the Z-axis to obtain the inter-floor drift ratio of the building at adjacent epochs. The extracted features of the absolute deformation time series include the net deformation of the house at adjacent epochs, the house deformation growth rate at adjacent epochs, and the house inter-story drift ratio at adjacent epochs.

6. The intelligent monitoring system for building safety risks based on BeiDou and GIS platforms according to claim 1, characterized in that: The specific determination process for whether to issue a warning about housing safety risks is as follows: Extracted features of the original deformation time series are obtained, including the original net deformation of the house at adjacent epochs, the original deformation growth rate of the house at adjacent epochs, and the original inter-story drift ratio of the house at adjacent epochs. Based on the original net deformation of the house at adjacent epochs, a net deformation threshold adjustment element is obtained by matching it, and coupled with a predefined net deformation reference threshold to obtain a net deformation reference threshold. The original deformation growth rate of houses at adjacent epochs is matched to obtain the deformation growth rate threshold adjustment element, which is then coupled with the predefined deformation growth rate benchmark threshold to obtain the deformation growth rate reference threshold. The original inter-story drift ratios of houses at adjacent epochs are matched to obtain a drift ratio threshold adjustment element, which is then coupled with a predefined inter-story drift ratio reference threshold to obtain an inter-story drift ratio reference threshold. The preset GIS raster factor is extracted and coupled with the inter-layer drift ratio reference threshold to obtain the inter-layer drift ratio adaptation threshold; The net deformation of the house at adjacent epochs, the growth rate of the house deformation at adjacent epochs, and the inter-story drift ratio of the house at adjacent epochs are compared with the net deformation reference threshold, the growth rate of the house deformation reference threshold, and the inter-story drift ratio adaptation threshold, respectively. If any extracted feature of the absolute deformation time series is greater than the corresponding threshold, it is determined to be an instantaneous risk event; otherwise, it is determined to be a continuous static event. If the building safety risk monitoring is an instantaneous risk event, then an early warning will be issued in real time. If the building safety risk monitoring is a continuous static event, then the building safety risk will be continuously monitored, and a building safety risk score will be determined.

7. The intelligent monitoring system for building safety risks based on BeiDou and GIS platforms according to claim 6, characterized in that: The specific monitoring process for continuous monitoring of building safety risks is as follows: Based on the extracted features of the absolute deformation time series, the building safety risk score is determined in real time; The building safety risk score is compared with predefined risk score intervals, which include a first risk score interval, a second risk score interval, a third risk score interval, and a fourth risk score interval. Each risk scoring interval is defined sequentially according to the numerical sequence, and the risk level of the house increases accordingly. If the building safety risk score belongs to the first risk score range, the building safety will be continuously monitored. At the same time, based on the building safety risk score, the adjacent epoch time interval factor will be matched and coupled with the currently set adjacent epoch time interval to obtain the adjacent epoch adaptation time interval, which will be used to update the adjacent epoch time interval and configure the next round of monitoring. If the building safety risk score falls within the second risk score range, the GIS platform initiates a rapid review command, extracts the deformation direction and deformation amplitude of adjacent building control points, and determines whether the deformation direction and deformation amplitude of adjacent building control points are consistent. If all adjacent building control points are consistent, the building safety is continuously monitored. If a certain building control point is inconsistent, the weight factor of the extracted features of that building control point in the building safety risk score is reduced until the weight factor is defined, and the building safety is continuously monitored again. If the building safety risk score falls within the third risk score range, a zone inspection will be triggered. At the same time, the GIS platform will report a redundant BDS short message, including the building coordinates, building safety risk score, trigger factor, and suggestion code. If the building safety risk score belongs to the fourth risk score range, a risk warning will be issued for the building safety, all original monitoring data will be retained, a geofence will be formed on the preset GIS map, and at the same time, according to the building safety risk score, a transmission carrier-to-noise ratio reference threshold correction element will be matched and coupled with the preset transmission carrier-to-noise ratio to obtain the transmission carrier-to-noise ratio definition threshold. The optimization of the absolute coordinates of each building control point at each epoch also includes comparing the transmission carrier-to-noise ratio (RCN) of the monitoring terminal at each epoch with the RCN threshold. If the RCN of the monitoring terminal at a certain epoch is less than the RCN threshold, the absolute coordinate data corresponding to that epoch will be removed and will not participate in the construction of the absolute deformation time series of each building control point.

8. The intelligent monitoring system for building safety risks based on BeiDou and GIS platforms according to claim 7, characterized in that: The specific process for determining the building safety risk score is as follows: The extracted features of the absolute deformation time series also include the growth rate of the house crack width at adjacent epochs. Extract the original growth rate of house crack width at adjacent epochs, match it to obtain the crack width growth rate threshold adjustment element, and couple it with the predefined crack width benchmark growth rate to obtain the crack width reference growth rate. The net deformation of the house at adjacent epochs, the growth rate of the house deformation at adjacent epochs, the inter-story drift ratio of the house at adjacent epochs, and the growth rate of the house crack width at adjacent epochs are deviated from the reference thresholds for net deformation, deformation growth rate, inter-story drift ratio, and crack width. Weighting factors are introduced to aggregate the deviation results in sequence to obtain the house safety risk score.

9. A method for intelligent monitoring of building safety risks based on BeiDou and GIS platforms, applied to the intelligent monitoring system for building safety risks based on BeiDou and GIS platforms as described in any one of claims 1-8, characterized in that: include: In the building safety monitoring area, a baseline network is constructed according to the preset coordinates of the reference station and the coordinates of each building control point. The relative coordinates of each building control point relative to the reference station are extracted and epoch difference statistics are performed to form the original deformation time series of each building control point. Based on the BeiDou monitoring terminal, coordinate monitoring is performed on the control points of each building to obtain the absolute coordinates of each building control point. The absolute coordinates are then statistically analyzed using epoch difference to form the absolute deformation time series of each building control point. The absolute deformation time series is decomposed into limiting terms, and the features of the decomposed absolute deformation time series are extracted to obtain the extracted features of the absolute deformation time series. Combined with the original deformation time series and GIS raster factors, event detection is performed on building safety to determine whether to issue a building safety risk warning. Based on the extracted features of the absolute deformation time series, regional risk surfaces are generated. These regional risk surfaces are then visualized and delineated on a preset GIS map of the building safety monitoring area, thus completing the intelligent monitoring of building safety risks.

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