An abnormal deformation detection method and system for security engineering buildings

Abstract

This application relates to the field of building deformation detection technology, and discloses a method and system for detecting abnormal deformation in security engineering buildings, including the following steps: Step 1, embedding distributed optical fiber sensing elements inside the building to continuously acquire strain data within the building, and setting up Beidou high-precision positioning equipment around the building to continuously acquire the three-dimensional absolute coordinates of key building nodes; Step 2, constructing a mechanical coupling correlation model between local strain and overall displacement; Step 3, based on the continuously acquired strain data inside the building and the three-dimensional absolute coordinates of key building nodes, obtaining the building deformation rate and trend change rate through the mechanical coupling correlation model. By constructing a dual-modal synchronous sensing system of distributed optical fiber strain sensing and Beidou high-precision positioning, the spatiotemporal reference of multi-source data is unified, and a mechanical coupling correlation model between local strain and overall displacement is established.

Description

Technical Field

[0001] This application relates to the field of building deformation detection technology, specifically to an abnormal deformation detection method and system for security engineering buildings. Background Technology

[0002] Security engineering buildings (such as security equipment storage workshops, security towers, etc.) are core infrastructure that carries security equipment and ensures public safety. Long-term service is prone to deformation due to factors such as foundation settlement and material aging, requiring real-time and accurate detection and early warning. Since the deformation of building structures is generated by dynamic accumulation and has uncertainty in the time and amount of deformation, traditional monitoring instruments and methods are not easy to detect it. Currently, the construction industry uses professional testing instruments to measure the deformation of building structures such as bridges, houses, and tunnels. However, the monitoring accuracy is limited by the technical parameters of the purchased instruments, while manual on-site monitoring often lags behind the deformation. Therefore, this invention proposes an abnormal deformation detection method and system for security engineering construction to address the shortcomings of the prior art. Summary of the Invention

[0003] The purpose of this application is to provide an abnormal deformation detection method and system for security engineering construction, so as to solve the problems mentioned in the background art.

[0004] The objective of this application can be achieved through the following technical solutions: A method and system for detecting abnormal deformation in security engineering buildings, comprising the following steps: Step 1: Embed distributed fiber optic sensing elements inside the building to continuously acquire strain data within the building, and set up BeiDou high-precision positioning equipment around the building to continuously acquire the three-dimensional absolute coordinates of key building nodes. Step 2: Construct a mechanical coupling relationship model between local strain and overall displacement; Step 3: Based on the continuously acquired building strain data and the three-dimensional absolute coordinates of key building nodes, obtain the building deformation rate and trend change rate through a mechanical coupling correlation model; Step 4: Determine whether the building's deformation trend has changed significantly based on the obtained deformation rate and trend change rate. If the building's deformation trend has changed significantly, proceed to Step 5. If the building's deformation trend has not changed significantly, continue monitoring. Step 5: When a significant abrupt change occurs in the building deformation trend, a graded early warning is triggered, and the deformation source is traced.

[0005] Preferably, the method for performing step one is as follows: The key stress-bearing parts and easily deformable areas of the building are surveyed, and the embedding positions and laying paths of the distributed optical fiber sensing elements are pre-defined. Distributed fiber optic sensing elements are embedded in pre-defined locations within the building, ensuring a close fit between the distributed fiber optic sensing elements and the building structure. The BeiDou high-precision positioning equipment was deployed on the top of the building and in unobstructed areas on all sides. The distributed fiber optic sensing element and the Beidou high-precision positioning device are activated to continuously and synchronously acquire the building's internal strain data and the three-dimensional absolute coordinates of the Beidou high-precision positioning device's installation node.

[0006] Preferably, the method for performing step two is as follows: The acquired raw local strain data and key node three-dimensional absolute coordinate data are preprocessed to obtain initial strain reference values. and the three-dimensional displacement vector of key nodes Simultaneously obtain the elastic modulus of building materials ; Simulate the strain-displacement relationship of a building under different deformation states to obtain the structural stiffness matrix. Strain-displacement coupling coefficient ; Preset index correction coefficient Logarithmic correction factor for material properties , correction constant and error correction coefficient ; Based on the acquired and set parameters, a mechanical coupling correlation model is constructed.

[0007] Preferably, the method for performing step three is as follows: Extract building strain data obtained from distributed fiber optic sensing elements and three-dimensional absolute coordinates of key building nodes obtained from BeiDou high-precision positioning equipment; Preprocess the extracted periodic data; The processed strain data and the three-dimensional absolute coordinates of the key nodes are substituted into the established mechanical coupling relationship model of local strain and overall displacement for calculation. The building deformation rate and trend change rate are obtained from the calculation results.

[0008] Preferably, the method for obtaining the building deformation rate is as follows: The timestamp of each acquisition is recorded synchronously from the continuous synchronous acquisition of strain data and the three-dimensional absolute coordinates of key nodes within the building. This forms multiple time series; The strain data and three-dimensional displacement vectors of key nodes collected in each group Substitute the existing mechanical coupling and correlation model into the model to obtain the local strain vector of the building at the corresponding time point; Based on the local strain vector of the building, the three-dimensional displacement vector of the key nodes The time-dimension derivative is calculated, and the derivative deviation is corrected based on the time derivative of the local strain vector of the building to obtain the building deformation rate. ; For multiple sets of preliminary deformation rates Preprocessing is performed, and equipment and environmental errors are compensated for to obtain the building deformation rate. .

[0009] Preferably, the method for obtaining the trend mutation rate is as follows: Based on the obtained building deformation rate With corresponding collection timestamp This is used to create a continuous deformation rate time series. By fitting the continuous deformation rate sequence, the building deformation rate within each time period can be obtained. Find the trend fitting line and calculate the slope of the fitting line. ; Calculate the slope difference of the fitted lines of two adjacent sliding windows. and the slope difference Error compensation is performed to eliminate deviations caused by equipment interference and data fluctuations, thus obtaining the preliminary trend change rate. .

[0010] Set a threshold for determining trend mutations, and evaluate the initial trend mutation rate. The data is filtered to remove minor fluctuations below a threshold, while retaining valid mutation data exceeding the threshold, ultimately yielding a precise rate of change in building trends. .

[0011] Preferably, the method for performing step four is as follows: Preset building deformation rate safety threshold and trend mutation rate mutation threshold ; The obtained building deformation rate With deformation rate safety threshold Trend mutation rate With trend mutation rate mutation threshold Compare them separately; like and The building deformation trend was determined to have undergone a significant abrupt change; like or No significant mutations were found.

[0012] Preferably, the method for performing step five is as follows: Based on building safety standards, material properties, and the error range of the mechanical coupling correlation model, three levels of early warning thresholds are set, each corresponding to a different deformation rate. and trend mutation rate Critical value; The building deformation rate will be obtained. Trend mutation rate It accurately matches the preset three-level warning thresholds to determine the current corresponding warning level; Based on the matched warning level, the corresponding warning action will be triggered.

[0013] An abnormal deformation detection system for security engineering buildings, applicable to the aforementioned abnormal deformation detection method for security engineering buildings, includes the following modules: The data acquisition module acquires strain data within the building and the three-dimensional absolute coordinates of key building nodes through distributed fiber optic sensing elements and BeiDou high-precision positioning equipment, respectively. The model building module constructs a mechanically coupled model of local strain and overall displacement. The data analysis module uses periodically acquired building strain data and the three-dimensional absolute coordinates of key building nodes to obtain the building deformation rate and trend change rate through a mechanical coupling correlation model. The early warning judgment module determines whether there is a significant change in the deformation trend of the building based on the obtained building deformation rate and trend change rate. If there is a significant change in the deformation trend, a graded early warning is triggered.

[0014] The beneficial effects of this application are: 1. This application constructs a dual-modal synchronous sensing system combining distributed fiber optic strain sensing and BeiDou high-precision positioning to achieve unified spatiotemporal reference for multi-source data, establishes a mechanical coupling correlation model between local strain and overall displacement, and fully characterizes the full-scale deformation state of the structure. It abandons the traditional fixed-period acquisition and fixed-threshold over-limit alarm mode, adopting a deformation rate time-series analysis and trend change identification mechanism. It triggers graded early warnings only when a significant change in deformation trend occurs, accurately distinguishing between steady-state harmless deformation and catastrophic harmful deformation, significantly reducing the false alarm rate. Simultaneously, it achieves precise location of deformation sources and advanced prediction of deformation trends, providing reliable safety early warning and risk prevention support for high-level security engineering buildings.

[0015] Of course, any product implementing this application does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a system module diagram of an abnormal deformation detection system for security engineering construction according to this application.

[0018] Figure 2 This is a flowchart illustrating the steps of an abnormal deformation detection method for security engineering buildings according to this application. Detailed Implementation

[0019] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0020] Please see Figure 1 As shown, this application discloses an abnormal deformation detection system for security engineering construction. The system includes a data acquisition module, a model building module, a data analysis module, and an early warning judgment module. The data acquisition module primarily uses distributed fiber optic sensors and BeiDou high-precision positioning equipment to acquire strain data within the building and the three-dimensional absolute coordinates of key building nodes, respectively. It continuously acquires strain data by embedding distributed fiber optic sensors within the building and continuously acquires the three-dimensional absolute coordinates of key building nodes by setting up BeiDou high-precision positioning equipment around the building. Specifically, a comprehensive survey is first conducted on key stress-bearing areas and easily deformable regions of the building to pre-determine the embedding positions and laying paths of the distributed fiber optic sensors. Then, the sensors are embedded in the pre-determined positions and tightly fitted to the building structure. Simultaneously, BeiDou high-precision positioning equipment is installed on the top and sides of the building... High-precision BeiDou positioning devices are deployed in areas with obstructions. Finally, both types of devices are activated to achieve continuous synchronous acquisition of strain data and three-dimensional absolute coordinates of key nodes inside the building. For example, in a security monitoring tower, after surveying, it was determined that the tower support and base are the key stress-bearing parts, and the middle section of the tower is a deformable area. Distributed fiber optic sensing elements are embedded along the preset paths of the support, base, and middle section of the tower and fitted to the tower structure. Four high-precision BeiDou positioning devices are deployed in open and unobstructed areas at the top of the tower and around the tower. After the devices are activated, the fiber optic elements continuously collect strain data of various parts of the tower, and the BeiDou devices continuously collect the three-dimensional absolute coordinates of key nodes such as the top of the tower and the middle section of the tower.

[0021] The model building module primarily constructs a mechanically coupled correlation model based on local strain and overall displacement. Specifically, it first preprocesses the raw local strain data collected by distributed fiber optic sensing elements and the three-dimensional absolute coordinate data of key nodes collected by BeiDou high-precision positioning equipment to extract initial strain reference values. 3D displacement vector of key nodes and the elastic modulus of building materials Then, by simulating different deformation states of the building, the structural stiffness matrix is ​​calibrated. Strain-displacement coupling coefficient Preset index correction coefficient Logarithmic correction factor for material properties , correction constant and error correction coefficient Finally, by integrating all parameters, a mechanically coupled correlation model is constructed: in, This represents the local strain vector of the building, acquired by distributed fiber optic sensors, and characterizes the strain level in easily deformable areas within the building. The structural stiffness matrix is ​​determined by the properties of building materials and structural dimensions, and characterizes the mechanical stiffness of the building structure. The three-dimensional displacement vectors of key building nodes are collected by BeiDou high-precision positioning equipment, representing the changes in the three-dimensional coordinates of the key nodes. The strain-displacement coupling coefficient is determined through finite element simulation and measured data to characterize the coupling strength between the two. The displacement gradient of key building nodes represents the rate of change of displacement space around the nodes. Exponential function term, This is the displacement correction exponent coefficient, calibrated to a value range of 0.1 to 0.5, used to correct nonlinear coupling relationships under large displacements. The absolute value of the displacement vector, to avoid the unreasonable use of negative exponents, is used as the denominator of the fraction. This is the logarithmic correction factor for material properties, with a value ranging from 0.001 to 0.01. The elastic modulus of building materials. This is a correction constant, set to a value of 1, used to correlate material properties with coupling relationships. This is the error correction factor, with a value ranging from 0.0001 to 0.001, used to compensate for errors caused by equipment data acquisition and environmental interference. This is the logarithmic error correction term. This is the initial strain reference value; Because of the displacement of critical building nodes There are variations of different orders of magnitude. Under large displacement conditions, the relationship between local strain and displacement exhibits nonlinear characteristics, resembling an exponential function. This can effectively correct such nonlinear deviations and ensure the accuracy of coupling relationships under different displacement magnitudes, due to the elastic modulus of building materials. The numerical range spans a large area. It can be compressed to a reasonable range to avoid [the following]: Excessive numerical differences lead to model calculation distortion; on the other hand... The choice of values ​​can avoid meaningless situations in logarithmic operations, and at the same time, through By correlating coefficients with material properties and coupling relationships, the model can be adapted to security buildings made of different material types. If it is a logarithmic error correction term, it can further compensate for equipment acquisition errors and environmental interference.

[0022] Constructing a mechanically coupled correlation model can compensate for the inability of a simple linear model to adapt to the nonlinear characteristics of building deformation, and correlate local strain with overall displacement.

[0023] For example, taking a common concrete structure for a security factory as an example: the parameters are as follows. , , , , , , , , , ; but, Therefore, the local strain vector of this security plant is .

[0024] The data analysis module, based on periodically acquired building strain data and the three-dimensional absolute coordinates of key building nodes, obtains the building deformation rate and trend change rate through a mechanical coupling correlation model. Specifically, the building deformation rate refers to the displacement change of key building nodes per unit time. Firstly, the timestamp of each acquisition is synchronously recorded from the continuously and synchronously acquired building strain data and the three-dimensional absolute coordinates of key nodes. This ensures that each set of strain data and three-dimensional absolute coordinates corresponds to a unique acquisition time, ultimately forming multiple time series, i.e. ( , , ), ( , , )……( , , ),in , ... These are the timestamps collected sequentially. , ... These are the original strain data inside the building at the corresponding time points.

[0025] The raw strain data consists of the original dynamic strain values ​​of the building structure acquired in real time by distributed fiber optic sensing elements. These raw strain data represent the actual stress generated by the building structure. They are primarily used for real-time calibration and verification of the theoretically coupled strain output by the model, achieving mechanical constraint coupling between the actual local deformation and the overall nodal displacement of the building. Simultaneously, they are used for dual error verification during deformation rate calculation, distinguishing between spurious deformation caused by environmental interference and the actual structural deformation of the building. The original time-series data is also retained, providing original measured data for subsequent verification of deformation trend changes, early warning trigger verification, and deformation source tracing analysis. This data is used to obtain the local strain vector of the building. Next, the local strain vector of the building Compare the difference with the original strain: a small deviation indicates that the model calculation is accurate and the building deformation is normal; an excessive deviation indicates that there is environmental interference, sensor drift, or model parameter offset, and some coefficients need to be adjusted for correction.

[0026] , ... The three-dimensional displacement vector of the key building nodes at the corresponding time point is calculated from the three-dimensional absolute coordinates collected by the BeiDou high-precision positioning equipment, i.e., the difference between the current coordinates and the initial coordinates. Then, the multiple sets of time series formed in the first step are successively substituted into the mechanical coupling correlation model constructed in the second step for calculation, and the corresponding time point can be obtained. Local strain vector of building Based on the obtained local strain vector of the building Local strain vector It needs to be compared with the original strain data at the corresponding time point. Perform correlation verification to ensure that the model calculation results match the actual strain state of the building at that point in time.

[0027] Three-dimensional displacement vectors of key nodes Perform the derivative operation in the time dimension, that is... The initial displacement rate of key building nodes, i.e., the preliminary value of the building deformation rate, was obtained. .

[0028] Because of the strong nonlinear coupling between local strain and overall displacement during building deformation, a single pair of displacement vectors... Taking the derivative will neglect the effect of strain change on displacement rate, leading to calculation errors. Therefore, it is necessary to calculate the local strain vector of the building simultaneously. The time derivative is Combining the coupling relationship logic between strain and displacement in the mechanical coupling correlation model, using right The result is corrected to eliminate the derivative bias caused by nonlinear coupling, and the corrected preliminary deformation rate is obtained. Finally, the obtained preliminary deformation rates were analyzed. Preprocessing is performed by using wavelet denoising to remove abnormal fluctuations in the velocity data, and smoothing is also applied to obtain a more stable velocity sequence. Then, the error correction term in the mechanical coupling correlation model is used... Error compensation is performed on the smoothed rate sequence to compensate for the acquisition errors of the distributed fiber optic sensing elements and BeiDou high-precision positioning equipment, as well as the calculation deviations caused by environmental interference such as temperature and vibration, ultimately yielding an accurate and stable building deformation rate. ; Taking a concrete security equipment factory as an example: This factory is mainly used to store security equipment. The building is 12m high and 18m wide. The key load-bearing parts are the beam-column joints and the roof support structure. The easily deformable area is the middle of the roof. Distributed fiber optic sensing elements and Beidou high-precision positioning equipment are used to collect data in collaboration. The specific acquisition process is as follows: Six sets of data were continuously collected, and timestamps and corresponding data were recorded synchronously. The time series is as follows: =0min, =0.0012, =0.0015m; =10min, =0.0015, =0.0018m; =20min, =0.0018, =0.0021m; =30min, =0.0021, =0.0024m; =40min, =0.0024, =0.0027m; =50min, =0.0027, =0.0030m.

[0029] Meanwhile, the parameters of the mechanical coupling correlation model are as follows: =2.8×10³, =0.75, =0.35, =0.004, =3.2×10 4 , =1, =0.0004, =0.001, displacement gradient u =0.0012 / m; Substituting the six sets of data one by one, the local strain vectors at the corresponding time points are obtained as follows: ≈1.0023 ≈1.0379 ≈1.0735 ≈1.1091、 ≈1.1447 ≈1.1803, Three-dimensional displacement vectors of key nodes Perform time differentiation ,by to For example, That is, the initial rate =0.00003; Simultaneously calculate the local strain vector The time derivative is Subsequently through right The correction is made, and the correction formula is: Following the above method, the preliminary deformation rate of the 6 sets of data was calculated and corrected to obtain the corrected preliminary deformation rate sequence: , , , , , .

[0030] Subsequently, through the error correction term Compensation is applied to the initial deformation rate of each group: According to the error correction term Compensation is applied to each initial deformation rate: Therefore, the average value of this sequence is taken as the final building deformation rate. ,Right now: .

[0031] The method described above for obtaining building deformation rate can meet the complexity and accuracy requirements of building deformation detection in security engineering, and make up for the limitations of traditional rate acquisition methods.

[0032] Trend abrupt change rate refers to the trend and magnitude of change in the building deformation rate, reflecting how fast the building deformation rate changes per unit time. Its core function is to determine whether there is a significant abrupt change in the building deformation trend. It is obtained through the following steps: Based on the obtained building deformation rate... Combined with the corresponding collection timestamp Construct a time series of deformation rates, i.e. ( , ), ( , )……( , ),in , ... The precise building deformation rate after preprocessing and error compensation. , ... To correspond to the acquisition timestamps, a sliding window fitting method was then used to perform trend fitting on the processed continuous deformation rate sequence. The size of the sliding window was set according to the acquisition period, preferably selecting 3 to 5 consecutive acquisition periods as a window. For example, if the acquisition period was 10 minutes, the window size was set to 3 periods, i.e., 30 minutes. Then, linear fitting was performed on the deformation rate data within each sliding window to obtain the trend fitting line of the deformation rate within that window. The slope of the fitting line was... This represents the trend of deformation rate over the given time period. A positive slope indicates that the deformation rate is gradually increasing; a negative slope indicates that the deformation rate is gradually decreasing; and a slope approaching 0 indicates that the deformation rate remains stable. Using a sliding window fitting method effectively avoids the influence of fluctuations in a single data point on trend analysis, and more accurately reflects the overall trend of deformation rate change.

[0033] Then calculate the slope difference of the fitted lines of two adjacent sliding windows. ,Right now , The slope of the fitted line in the previous window. The slope of the fitted line for the next window, and the slope difference. The magnitude of the difference directly reflects the difference in the deformation rate trend between two adjacent time periods. The larger the difference, the more drastic the deformation rate trend, and the closer it is to a sudden change. However, since the slope calculation may still be affected by equipment errors and environmental interference, leading to deviations in the slope difference, it is necessary to combine the error correction term of the mechanical coupling correlation model. For slope difference Error compensation is performed to eliminate deviations caused by equipment interference and data fluctuations, thus obtaining the preliminary trend change rate. This ensures the accuracy of the trend mutation rate.

[0034] Continuing with the aforementioned case study of a concrete security factory, and combining the already obtained building deformation rate data, we further obtain the trend abrupt change rate: Based on the obtained precise building deformation rate Combined with the corresponding timestamps, a deformation rate time series is formed: =0min, =0.00003002, =10min, =0.00003001, =20min, =0.00003002, =30min, =0.00002999, =40min, =0.00003003、 =50min, =0.00003001.

[0035] The sliding window size was set to 3 acquisition cycles (30 minutes), meaning each window contained 3 sets of data, forming a total of 4 sliding windows. The data within each window were fitted to obtain the line slope. : Window 1 ( ~ (0~20min): Data are (0, 0.00003002), (10, 0.00003001), (20, 0.00003002). After linear fitting, the slope of the fitted line is... The slope approaches 0, indicating that the deformation rate is stable during this period; Window 2 ( ~ (10–30 min): Data are (10, 0.00003001), (20, 0.00003002), and (30, 0.00002999). After linear fitting, the slope of the fitted line is... The slope approaches 0, and the deformation rate is stable; Window 3 ( ~ (20–40 min): Data are (20, 0.00003002), (30, 0.00002999), and (40, 0.00003003). After linear fitting, the slope of the fitted line is... ≈0.00000002, the slope approaches 0, and the deformation rate is stable; Window 4 ( ~ 30–50 min): Data are (30, 0.00002999), (40, 0.00003003), (50, 0.00003001). After linear fitting, the slope of the fitted line is... ≈0.00000001, the slope approaches 0, and the deformation rate is stable; Slope difference calculation and error compensation: Calculate the slope difference between two adjacent windows. According to the error correction term Error compensation is performed. After compensation ; After compensation ; After compensation .

[0036] The early warning judgment module determines whether there is a significant change in the building's deformation trend based on the acquired building deformation rate and trend change rate. If a significant change in the deformation trend occurs, a tiered early warning is triggered. Specifically, a safe threshold for the building deformation rate is set according to the safety standards for concrete safety workshops. Threshold for determining trend mutation In this application, the building deformation rate safety threshold The value is 0.0001, which is the threshold for determining a sudden trend change. The value is 0.000005. Using the aforementioned distance, the final building deformation rate is calculated. Safety threshold for building deformation rate By comparison, the initial trend mutation rate will be determined. , , and By comparison, the building deformation rate was found. Less than the building deformation rate safety threshold , , , All three are smaller than Therefore, after eliminating these minor fluctuations, it was determined that the deformation rate of the concrete security plant remained stable during this period without any significant abrupt changes, and continued monitoring was required.

[0037] If the deformation rate of the factory building suddenly increases due to foundation settlement, assuming the deformation rate data for a certain period of time becomes: ( =60min, =0.00005), ( =70min, =0.00008), ( =80min, =0.00011), 5 new windows added ( ~ (40-60 minutes) Then the fitted slope ≈0.000001, After compensation still smaller If more data is collected ( =90min, =0.0002), Window 6 ( ~ (50-70 min) Fitting slope , After compensation greater than At this point, the trend mutation rate is obtained after screening. The value ≈0.0000079 indicates a significant abrupt change in the building deformation trend, requiring the triggering of a tiered early warning system. This application sets the three-tiered early warning thresholds as follows: Level 1 Warning: Building Deformation Rate: 0.5 × ≤ <0.8× That is, 0.00005≤ <0.00008, trend mutation rate: 0.5× ≤ <0.8× That is, 0.0000025≤ <0.000004, at this point the deformation rate is close to 50%-80% of the safety threshold, the trend change amplitude is small, and there are no obvious signs of accelerated deformation. At this point, the acquisition cycle is reduced, the data acquisition density is increased, the focus is on monitoring the trend of deformation rate change, and the deformation rate and trend change rate are reviewed daily. The original strain data are compared with the model output value to check for slight equipment drift or environmental interference. Then, the warning trigger time, rate data, and environmental parameters are recorded to form a basic warning file, without the need to initiate on-site investigation.

[0038] Level II Warning: Building Deformation Rate: 0.8 × ≤ < That is, 0.00008≤ <0.0001, trend mutation rate: 0.8× ≤ < That is, 0.000004≤ <0.000005, at this point the deformation rate is close to the upper limit of the safety threshold, the trend change amplitude is significantly increased, there is a potential risk of accelerated deformation, it is necessary to organize professional inspection personnel to rush to the site to check whether there are any abnormalities such as slight cracks or loosening in the key parts of the building, to fully calibrate the distributed fiber optic sensing elements and Beidou positioning equipment, to eliminate the false alarm caused by equipment errors, and to closely monitor the deformation rate and trend change, report the warning information to the security engineering management department, and simultaneously inform the on-site operation and maintenance personnel to make emergency preparations.

[0039] Level 3 Warning: Building Deformation Rate ≥ ,Right now ≥0.0001, trend mutation rate: ≥ ,Right now If the deformation rate is ≥0.000005, exceeding the safety threshold, and the trend abruptly changes significantly, the building exhibits obvious accelerated deformation, potentially posing a structural safety hazard. Immediately evacuate all on-site personnel and equipment to a safe area, prohibit unauthorized personnel from entering the site, activate a specialized testing team, and use professional equipment to conduct a comprehensive inspection of the building structure to determine the cause of the deformation (such as foundation settlement, structural cracking, etc.). Coordinate with the emergency management department, activate the emergency response plan for security buildings, and take temporary reinforcement and support measures to curb further deformation. Report the incident to the security engineering management unit, emergency management department, and housing and construction department at each level as soon as possible, simultaneously pushing real-time rate data and on-site testing information to facilitate subsequent handling.

[0040] Please see Figure 2 As shown, this application also provides a method for detecting abnormal deformation in security engineering buildings, characterized by comprising the following steps: Step 1: Embed distributed fiber optic sensing elements inside the building to continuously acquire strain data within the building, and set up BeiDou high-precision positioning equipment around the building to continuously acquire the three-dimensional absolute coordinates of key building nodes. Step 2: Construct a mechanical coupling relationship model between local strain and overall displacement; Step 3: Based on the continuously acquired building strain data and the three-dimensional absolute coordinates of key building nodes, obtain the building deformation rate and trend change rate through a mechanical coupling correlation model; Step 4: Determine whether the building's deformation trend has changed significantly based on the obtained deformation rate and trend change rate. If the building's deformation trend has changed significantly, proceed to Step 5. If the building's deformation trend has not changed significantly, continue monitoring. Step 5: When a significant abrupt change occurs in the building deformation trend, a graded early warning is triggered, and the deformation source is traced.

[0041] The above description is merely an example and illustration of the concept of this application. 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 inventive concept or exceed the scope defined in the claims, they should all fall within the protection scope of this application.

Claims

1. A method for detecting abnormal deformation in security engineering construction, characterized in that, Includes the following steps: Step 1: Embed distributed fiber optic sensing elements inside the building to continuously acquire strain data within the building, and set up BeiDou high-precision positioning equipment around the building to continuously acquire the three-dimensional absolute coordinates of key building nodes. Step 2: Construct a mechanical coupling relationship model between local strain and overall displacement; Step 3: Based on the continuously acquired building strain data and the three-dimensional absolute coordinates of key building nodes, obtain the building deformation rate and trend change rate through a mechanical coupling correlation model; Step 4: Determine whether the building's deformation trend has changed significantly based on the obtained deformation rate and trend change rate. If the building's deformation trend has changed significantly, proceed to Step 5. If the building's deformation trend has not changed significantly, continue monitoring. Step 5: When a significant abrupt change occurs in the building deformation trend, a graded early warning is triggered, and the deformation source is traced.

2. The method for detecting abnormal deformation in security engineering construction according to claim 1, characterized in that, The method for performing step one is as follows: The key stress-bearing parts and easily deformable areas of the building are surveyed, and the embedding positions and laying paths of the distributed optical fiber sensing elements are pre-defined. Distributed fiber optic sensing elements are embedded in pre-defined locations within the building, ensuring a close fit between the distributed fiber optic sensing elements and the building structure. The BeiDou high-precision positioning equipment was deployed on the top of the building and in unobstructed areas on all sides. The distributed fiber optic sensing element and the Beidou high-precision positioning device are activated to continuously and synchronously acquire the building's internal strain data and the three-dimensional absolute coordinates of the Beidou high-precision positioning device's installation node.

3. The method for detecting abnormal deformation in security engineering construction according to claim 1, characterized in that, The method for performing step two is as follows: The acquired raw local strain data and key node three-dimensional absolute coordinate data are preprocessed to obtain initial strain reference values. and the three-dimensional displacement vector of key nodes Simultaneously obtain the elastic modulus of building materials ; Simulate the strain-displacement relationship of a building under different deformation states to obtain the structural stiffness matrix. Strain-displacement coupling coefficient ; Preset index correction coefficient Logarithmic correction factor for material properties , correction constant and error correction coefficient ; Based on the acquired and set parameters, a mechanical coupling correlation model is constructed.

4. The method for detecting abnormal deformation in security engineering construction according to claim 1, characterized in that, The method for performing step three is as follows: Extract building strain data obtained from distributed fiber optic sensing elements and three-dimensional absolute coordinates of key building nodes obtained from BeiDou high-precision positioning equipment; Preprocess the extracted periodic data; The processed strain data and the three-dimensional absolute coordinates of the key nodes are substituted into the established mechanical coupling relationship model of local strain and overall displacement for calculation. The building deformation rate and trend change rate are obtained from the calculation results.

5. The method for detecting abnormal deformation in security engineering construction according to claim 4, characterized in that, The method for obtaining the building deformation rate is as follows: The timestamp of each acquisition is recorded synchronously from the continuous synchronous acquisition of strain data and the three-dimensional absolute coordinates of key nodes within the building. This forms multiple time series; The strain data and three-dimensional displacement vectors of key nodes collected in each group Substitute the existing mechanical coupling and correlation model into the model to obtain the local strain vector of the building at the corresponding time point; Based on the local strain vector of the building, the three-dimensional displacement vector of the key nodes The time-dimension derivative is calculated, and the derivative deviation is corrected based on the time derivative of the local strain vector of the building to obtain the building deformation rate. ; For multiple sets of preliminary deformation rates Preprocessing is performed, and equipment and environmental errors are compensated for to obtain the building deformation rate. .

6. The method for detecting abnormal deformation in security engineering construction according to claim 5, characterized in that, The method for obtaining the trend mutation rate is as follows: Based on the obtained building deformation rate With corresponding collection timestamp This is used to create a continuous deformation rate time series. By fitting the continuous deformation rate sequence, the building deformation rate within each time period can be obtained. Find the trend fitting line and calculate the slope of the fitting line. ; Calculate the slope difference of the fitted lines of two adjacent sliding windows. and the slope difference Error compensation is performed to eliminate deviations caused by equipment interference and data fluctuations, thus obtaining the preliminary trend change rate. . Set a threshold for determining trend mutations, and evaluate the initial trend mutation rate. The data is filtered to remove minor fluctuations below a threshold, while retaining valid mutation data exceeding the threshold, ultimately yielding a precise rate of change in building trends. .

7. The method for detecting abnormal deformation in security engineering construction according to claim 1, characterized in that, The method for performing step four is as follows: Preset building deformation rate safety threshold and trend mutation rate mutation threshold ; The obtained building deformation rate With deformation rate safety threshold Trend mutation rate With trend mutation rate mutation threshold Compare them separately; like and The building deformation trend was determined to have undergone a significant abrupt change; like or No significant mutations were found.

8. The method for detecting abnormal deformation in security engineering construction according to claim 1, characterized in that, The method for performing step five is as follows: Based on building safety standards, material properties, and the error range of the mechanical coupling correlation model, three levels of early warning thresholds are set, each corresponding to a different deformation rate. and trend mutation rate Critical value; The building deformation rate will be obtained. Trend mutation rate It accurately matches the preset three-level warning thresholds to determine the current corresponding warning level; Based on the matched warning level, the corresponding warning action will be triggered.

9. An abnormal deformation detection system for security engineering construction, applicable to the abnormal deformation detection method for security engineering construction according to claims 1-8, characterized in that, Includes the following modules: The data acquisition module acquires strain data within the building and the three-dimensional absolute coordinates of key building nodes through distributed fiber optic sensing elements and BeiDou high-precision positioning equipment, respectively. The model building module constructs a mechanically coupled model of local strain and overall displacement. The data analysis module uses periodically acquired building internal strain data and the three-dimensional absolute coordinates of key building nodes to obtain the building deformation rate and trend change rate through a mechanical coupling correlation model. The early warning judgment module determines whether the building deformation trend has changed significantly based on the acquired building deformation rate and trend change rate. If the deformation trend changes significantly, a graded early warning is triggered.

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