Long-term monitoring method and system for building foundation settlement and stability

Abstract

The present invention discloses a method and system for long-term monitoring of building foundation settlement and stability. The method collects building settlement-related data through a distributed optical fiber sensing network, a tilt sensor array, and an earth pressure sensor; establishes a soil stress memory effect calculation model to calculate the effective stress taking into account the memory effect; constructs a total building foundation settlement model that includes the main consolidation settlement, creep settlement, and additional settlement caused by environmental factors; divides the risk level based on multi-level thresholds, calculates the early warning lead time, and generates an emergency response strategy, thereby realizing intelligent monitoring and early warning of building foundation settlement and having important engineering application value.

Description

Technical Field

[0001] The present invention belongs to the technical field of building stability monitoring, and in particular relates to a method and system for long-term monitoring of building foundation settlement and stability. Background Art

[0002] Building foundation settlement is a significant safety hazard in construction projects, significantly impacting the safety and structural stability of buildings. With the acceleration of urbanization and the extensive development of underground space, building settlement is becoming increasingly prominent. Traditional building settlement monitoring methods rely primarily on manual measurement and single-sensor data collection, resulting in limited accuracy and low efficiency, making it difficult to meet the needs of long-term continuous monitoring. Furthermore, existing monitoring systems often overlook the impact of soil stress memory effects on settlement deformation, resulting in significant deviations between predicted results and actual conditions.

[0003] Currently, research on building foundation settlement, both domestically and internationally, focuses primarily on settlement calculation models and monitoring technologies. Traditional settlement calculation methods, often based on Terzaghi's one-dimensional consolidation theory, fail to fully consider the impact of environmental factors on the settlement process and fail to establish interaction models between these factors, resulting in inaccurate predictions. Regarding monitoring technology, while various automated monitoring devices have been adopted, system integration is low, and data collection and analysis remain fragmented, making it difficult to effectively integrate and analyze multi-source data. Furthermore, existing building foundation settlement monitoring systems generally lack comprehensive early warning mechanisms. Most systems are limited to simple threshold determinations for a single monitoring indicator, failing to comprehensively assess and stratify multiple indicators, or effectively calculate early warning lead times. This results in delayed warnings and hinders the implementation of effective preventive measures.

[0004] Therefore, there is an urgent need to develop a building foundation settlement monitoring method and system that can achieve long-term continuous monitoring and has intelligent early warning functions. Summary of the Invention

[0005] To address the above issues, the present invention proposes a method and system for long-term monitoring of building foundation settlement and stability. The specific technical solutions are as follows:

[0006] In a first aspect, the present invention provides a method for long-term monitoring of building foundation settlement and stability, the method comprising the following steps:

[0007] Step S1: collect basic data related to building settlement based on deployed sensors and collect environmental data of the area where the building is located.

[0008] Furthermore, the collection of basic data related to building settlement includes: real-time collection of deformation data of each monitoring point of the building foundation through a distributed fiber optic sensing network, collection of building inclination angle data through a tilt sensor array, and collection of soil stress data at different depths of the building foundation through a soil pressure sensor; the environmental data includes at least temperature, humidity, groundwater level and rainfall.

[0009] Step S2: establishing a soil stress memory effect calculation model based on the soil stress data, calculating the effective stress considering the memory effect, and calculating the soil deformation response based on the effective stress.

[0010] Step S3: establishing a general model of building foundation settlement based on the main consolidation settlement, creep settlement and additional settlement caused by environmental factors according to the soil deformation response and combined with environmental data.

[0011] Furthermore, the overall model of building foundation settlement is: S(t) = S p (t)+S c (t)+S e (t), where S(t) is the total settlement at time t, Sp(t) is the main consolidation settlement considering stress memory effect, Sc(t) is the creep settlement, and Se(t) is the additional settlement caused by environmental factors. The unit of each item is millimeter.

[0012] Step S4, based on the total model calculation results of the building foundation settlement, combined with the deformation data and the tilt angle data, risk level classification is performed based on multi-level thresholds, the early warning lead time is calculated, and an emergency response strategy is generated.

[0013] Furthermore, the calculation formula of the stress memory kernel function K(t) in step S2 is:

[0014] K(t)=de -ut +(1-d)e -γt ; Wherein, d is the stress memory distribution coefficient, which represents the weight ratio of the two memory components, and its value range is [0, 1]; u is the fast memory decay coefficient, which represents the decay rate of the short-term stress memory effect, and its unit is 1 / day; γ is the slow memory decay coefficient, which represents the decay rate of the long-term stress memory effect, and its unit is 1 / day; t is the time variable, which represents the time interval from the start of loading to the current time, and its unit is day;

[0015] The calculation formula of effective stress σm(t) considering memory effect is:

[0016] Wherein, σm(t) is the effective stress considering the memory effect, in kPa; σ(τ) is the actual stress at the historical moment τ, in kPa; τ is the integral variable, representing the historical moment, in days.

[0017] Furthermore, the main consolidation settlement calculation model is as follows:

[0018] where Hi is the thickness of the i-th soil layer, with the unit of m; n is the total number of monitored soil layers, e0 is the initial void ratio, dimensionless; C c is the compression index, dimensionless; Δp is the additional stress increment, with the unit of kPa.

[0019] Furthermore, the creep settlement calculation model is as follows:

[0020] where a is the initial deformation parameter, with the unit of day / mm; b is the long-term deformation parameter, with the unit of 1 / mm.

[0021] Furthermore, the calculation model for the additional settlement caused by the environmental factors is as follows:

[0022] where f i (E i (t)) is the influence function value of the i-th environmental factor, k i is the influence coefficient of the i-th environmental factor, m is the number of environmental factors, is the reference value of the i-th environmental factor, taking the historical average; g i (E i (t) is the non-linear interaction effect value of the i-th environmental factor, λ i is the interaction coefficient, characterizing the coupling strength between environmental factors, and satisfying 0 ≤ λ i ≤ 1 and ∑λi = 1; α i is the weight coefficient of the i-th environmental factor, β is the comprehensive influence coefficient of the environmental factor interaction, and the value range is [0.1, 0.5].[[]END]]

[0023] Furthermore, the risk level classification in step S4 includes:

[0024] Based on the comprehensive evaluation of the total settlement S(t), the deformation amount D(t), and the tilt angle θ(t), the building foundation settlement risk is divided into four levels:

[0025] Level I indicates safety: when the total settlement S(t) ≤ S1 and the deformation amount D(t) ≤ D1 and the tilt angle θ(t) ≤ θ1;

[0026] Level II indicates warning: when S1 < S(t) ≤ S2 or D1 < D(t) ≤ D2 or θ1 < θ(t) ≤ θ2;

[0027] Level III indicates danger: when S2 < S(t) ≤ S3 or D2 < D(t) ≤ D3 or θ2 < θ(t) ≤ θ3;

[0028] Level IV indicates emergency: when S(t) > S3 or D(t) > D3 or θ(t) > θ3;

[0029] Among them, S1, S2, and S3 are settlement thresholds in millimeters; D1, D2, and D3 are deformation thresholds in millimeters; θ1, θ2, and θ3 are tilt angle thresholds in degrees.

[0030] Furthermore, the specific steps for calculating the early warning lead include:

[0031] Based on historical monitoring data, use the sliding time window method to establish prediction models for the settlement S(t), deformation D(t), and tilt angle θ(t), and set the time window length L and prediction step h; conduct trend analysis on the data within each time window;

[0032] Calculate the time when each monitoring index reaches the early warning threshold:

[0033] Among them, t s is the earliest time point when the settlement reaches the early warning threshold, t i is the predicted time series point, S(t i ) is the predicted settlement value at time t i ; S k is the settlement threshold corresponding to the risk level k, where k = 1, 2, 3, corresponding to the three levels of warning, danger, and emergency respectively; t d is the earliest time point when the deformation reaches the early warning threshold, D(t i ) is the predicted deformation value at time t i , D k is the deformation threshold corresponding to the risk level k, t θ is the earliest time point when the tilt angle reaches the early warning threshold, θ(t i ) is the predicted tilt angle value at time t i , θ k is the tilt angle threshold corresponding to the risk level k;

[0034] Comprehensively determine the early warning lead: T w = min(t s , t d , t θ ) - t0; Among them, T w is the early warning lead, indicating the time interval from the current moment to the earliest time to reach the early warning state, min(t s , t d , t θ) is the earliest time point when the three monitoring indicators reach the warning threshold, and t0 is the current time.

[0035] Furthermore, the method for deploying the distributed fiber optic sensing network includes: deploying fiber optic sensors in the horizontal and vertical directions at key locations of the building foundation, with a horizontal deployment spacing of 3-5 meters and a vertical deployment depth of 10-15 meters below the foundation bottom surface; deploying the tilt sensor array at the corners and middle of the building, with a spacing of no more than 20 meters; and deploying the soil pressure sensor at a measurement point every 5 meters under the building foundation, with a total depth of no less than 20 meters.

[0036] In the second aspect, the present invention provides a long-term monitoring system for building foundation settlement and stability, which is used to execute the method described in the first aspect. The system includes: a data acquisition module, a memory effect calculation module, a settlement total model calculation module and an early warning response module connected in sequence.

[0037] Furthermore, the data acquisition module is used to collect basic data related to building settlement based on the deployed sensors and collect environmental data of the area where the building is located.

[0038] Furthermore, the memory effect calculation module is used to establish a soil stress memory effect calculation model based on the soil stress data and calculate the effective stress considering the memory effect, and calculate the soil deformation response based on the effective stress.

[0039] Furthermore, the settlement total model calculation module is used to establish a total model of building foundation settlement based on the main consolidation settlement, creep settlement and additional settlement caused by environmental factors according to the soil deformation response and combined with environmental data.

[0040] Furthermore, the early warning response module is used to divide the risk level based on the total model calculation results of the building foundation settlement, combined with the deformation data and the tilt angle data, based on the multi-level threshold, calculate the early warning lead time, and generate an emergency response strategy.

[0041] Furthermore, the system also includes a data communication module and a system maintenance module.

[0042] The data communication module is used for real-time collection and transmission of on-site monitoring data, remote transmission and sharing of monitoring data, and integration and synchronization of multi-source data.

[0043] The system maintenance module is used for regular calibration of various sensors, validity verification of monitoring data, and system operation status monitoring and fault handling.

[0044] Compared with the prior art, the present invention has the following beneficial effects:

[0045] The present invention introduces a soil stress memory effect calculation model and combines it with real-time monitoring data from a distributed optical fiber sensor network to establish an overall model that includes main consolidation settlement, creep settlement, and additional settlement caused by environmental factors. This allows for a comprehensive assessment of the building settlement process and, combined with the calculation of early warning lead times, enables accurate early warning. The present invention significantly improves the accuracy of settlement prediction. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 This is a flow chart of the long-term monitoring method for building foundation settlement and stability of the present invention.

[0047] Figure 2 It is a schematic diagram of the composition of the long-term monitoring system for building foundation settlement and stability of the present invention. DETAILED DESCRIPTION

[0048] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention are described clearly and completely below. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts are within the scope of protection of the present invention.

[0049] Example 1

[0050] like Figure 1 FIG. 1 is a flow chart of a method for long-term monitoring of building foundation settlement and stability according to the present invention, and the method comprises the following steps:

[0051] Step S1: collect basic data related to building settlement based on deployed sensors and collect environmental data of the area where the building is located.

[0052] The collection of basic data related to building settlement includes: real-time collection of deformation data of each monitoring point of the building foundation through a distributed fiber optic sensing network, collection of building inclination angle data through a tilt sensor array, and collection of soil stress data at different depths of the building foundation through a soil pressure sensor; the environmental data includes at least temperature, humidity, groundwater level and rainfall.

[0053] The method for deploying the distributed fiber optic sensing network includes: deploying fiber optic sensors horizontally and vertically at key locations on a building foundation, with a horizontal spacing of 3-5 meters and a vertical depth of 10-15 meters below the foundation bottom surface; deploying an array of tilt sensors at corners and in the middle of the building, with a spacing of no more than 20 meters; and deploying soil pressure sensors at a depth of no less than 5 meters under the building foundation, with a total depth of no less than 20 meters.

[0054] Step S2: establishing a soil stress memory effect calculation model based on the soil stress data, calculating the effective stress considering the memory effect, and calculating the soil deformation response based on the effective stress.

[0055] The calculation formula of stress memory kernel function K(t) is:

[0056] K(t)=de -ut +(1-d)e -γt ; Wherein, d is the stress memory distribution coefficient, which represents the weight ratio of the two memory components, and its value range is [0, 1]; u is the fast memory decay coefficient, which represents the decay rate of the short-term stress memory effect, and its unit is 1 / day; γ is the slow memory decay coefficient, which represents the decay rate of the long-term stress memory effect, and its unit is 1 / day; t is the time variable, which represents the time interval from the start of loading to the current time, and its unit is day;

[0057] The calculation formula of effective stress σm(t) considering memory effect is:

[0058] Wherein, σm(t) is the effective stress considering the memory effect, in kPa; σ(τ) is the actual stress at the historical moment τ, in kPa; τ is the integral variable, representing the historical moment, in days.

[0059] Step S3: establishing a general model of building foundation settlement based on the main consolidation settlement, creep settlement and additional settlement caused by environmental factors according to the soil deformation response and combined with environmental data.

[0060] The overall model of building foundation settlement is: S(t) = S p (t)+S c (t)+S e (t), where S(t) is the total settlement at time t, Sp(t) is the main consolidation settlement considering stress memory effect, Sc(t) is the creep settlement, and Se(t) is the additional settlement caused by environmental factors. The unit of each item is millimeter.

[0061] The calculation model of the main consolidation settlement is:

[0062] Where Hi is the thickness of the i-th soil layer, in meters; n is the total number of monitored coatings; e0 is the initial porosity, dimensionless; C c is the compression index, dimensionless; Δp is the additional stress increment, unit is kPa.

[0063] The calculation method of additional stress increment Δp is:

[0064] Δp=η∑(q i ×I i);where: η is the stress diffusion coefficient, which is related to the soil type and has a value range of [0.8, 1.2]; q i is the additional ground pressure generated by the i-th load source, in kPa; I i is the stress influence coefficient of the i-th load source on the calculation point, which is calculated by the Boussinesq solution:

[0065] I i =1 / (2π)[3z 3 / (R 2 +z 2 )(5 / 2)]; where: z is the depth of the calculation point from the ground, in m; R is the horizontal distance from the calculation point to the load application point, in m.

[0066] The creep settlement calculation model is:

[0067] Where a is the initial deformation parameter, in days / mm; b is the long-term deformation parameter, in 1 / mm.

[0068] The calculation model for additional settlement caused by environmental factors is:

[0069] Among them, f i (E i (t)) is the impact function value of the i-th environmental factor, k i is the influence coefficient of the i-th environmental factor, m is the number of environmental factors, is the baseline value of the i-th environmental factor, taking the historical average value; g i (E i (t) is the nonlinear interaction effect value of the i-th environmental factor, λ i is the interaction coefficient, which characterizes the coupling strength between environmental factors and satisfies 0≤λ i ≤1 and ∑λi=1;α i is the weight coefficient of the i-th environmental factor, and β is the comprehensive influence coefficient of the interaction of environmental factors, with a value range of [0.1, 0.5].

[0070] Step S4, based on the total model calculation results of the building foundation settlement, combined with the deformation data and the tilt angle data, risk level classification is performed based on multi-level thresholds, the early warning lead time is calculated, and an emergency response strategy is generated.

[0071] The risk classification includes: Based on the comprehensive evaluation of total settlement S(t), deformation D(t) and tilt angle θ(t), the building foundation settlement risk is divided into four levels:

[0072] Level I indicates safety: when the total settlement S(t) ≤ S1, the deformation D(t) ≤ D1, and the tilt angle θ(t) ≤ θ1;

[0073] Level II indicates warning: when S1 < S(t) ≤ S2 or D1 < D(t) ≤ D2 or θ1 < θ(t) ≤ θ2;

[0074] Level III indicates danger: when S2 < S(t) ≤ S3 or D2 < D(t) ≤ D3 or θ2 < θ(t) ≤ θ3;

[0075] Level IV indicates emergency: when S(t) > S3 or D(t) > D3 or θ(t) > θ3;

[0076] Among them, S1, S2, and S3 are settlement thresholds in millimeters; D1, D2, and D3 are deformation thresholds in millimeters; θ1, θ2, and θ3 are tilt angle thresholds in degrees.

[0077] These thresholds are set based on engineering practice experience, and a specific value is given:

[0078] Total settlement thresholds (S1, S2, S3): S1 = 30mm: the normal settlement range allowed for general buildings; S2 = 50mm: the warning value that requires close attention; S3 = 80mm: the dangerous value that may cause building damage.

[0079] Deformation thresholds (D1, D2, D3): D1 = 20mm: the normal differential settlement range; D2 = 35mm: the warning value of differential settlement that needs attention; D3 = 60mm: the dangerous value of differential settlement that may cause structural problems.

[0080] Tilt angle thresholds (θ1, θ2, θ3): θ1 = 0.3 degrees: the normal tilt range (about 1 / 200); θ2 = 0.6 degrees: the warning tilt value (about 1 / 100); θ3 = 1.0 degrees: the dangerous tilt value (about 1 / 60).

[0081] The specific steps for calculating the early warning lead include:

[0082] Based on historical monitoring data, a prediction model for settlement S(t), deformation D(t), and tilt angle θ(t) is established using the sliding time window method, and the time window length L and prediction step h are set; trend analysis is performed on the data within each time window; multi-time scale predictions are made.

[0083] Short-term prediction: Predict the change trend in the next 1 - 7 days;

[0084] Medium-term prediction: Predict the change trend in the next 8 - 30 days;

[0085] Long-term forecast: predict the changing trend in the next 31-90 days.

[0086] For any monitoring indicator y(t) (which can be settlement S(t), deformation D(t) or tilt angle θ(t)), its prediction model is: Where, l(t) is the horizontal component at time t;

[0087] l(t)=α 1 y(t)+(1-α 1 )[l(t-1)+b(t-1)]; where a 1 is the smoothing coefficient of the horizontal component, ranging from [0, 1]; b(t) is the trend component at time t:

[0088] b(t)=α 2 [l(t)-l(t-1)]+(1-α 2 )b(t-1); where α 2 is the smoothing coefficient of the trend component, ranging from [0, 1]; s(t) is the seasonal component at time t:

[0089] s(t)=α 3 [(t)-l(t)]|+(1-α 3 )s(tp)

[0090] Where α3 is the smoothing coefficient of the seasonal component, and its value range is [0, 1]; p is the seasonal period, for example, when sampling by day, p = 24 means one day is the period, a 1 、a 2 , α 3 is the weight coefficient of each component, and satisfies: a 1 +a 2 +α 3 =1; the value needs to be calibrated according to the actual monitoring data; h is the prediction step, which is set according to the prediction scale: short-term prediction: h∈[1,7]; medium-term prediction: h∈[8,30]; long-term prediction: h∈[31,90].

[0091] Calculate the time when each monitoring indicator reaches the warning threshold:

[0092] Among them, t s is the earliest time point when the settlement reaches the warning threshold, t i is the predicted time series point, S(t i ) is t i The predicted settlement value at the moment; S k is the settlement threshold corresponding to risk level k, k = 1, 2, 3, corresponding to warning, danger, and emergency levels respectively; t d is the earliest time point when the deformation reaches the warning threshold, D(ti ) is t i The predicted deformation value at the moment, D k is the deformation threshold corresponding to risk level k, t θ is the earliest time point when the tilt angle reaches the warning threshold, θ(t i ) is t i The predicted tilt angle value at the moment, θ k is the tilt angle threshold corresponding to risk level k;

[0093] Comprehensively determine the warning lead time: T w =min(t s , t d , t θ )-t0; where T w is the warning lead time, which means the time interval from the current moment to the earliest warning state, min(t s , t d , t θ ) is the earliest time point when the three monitoring indicators reach the warning threshold, and t0 is the current time.

[0094] Emergency response strategies include: Level I response: continue routine monitoring and maintain the existing monitoring frequency; Level II response: intensify monitoring frequency, increase patrol frequency, and analyze disaster-causing factors; Level III response: activate emergency plans, add temporary support, and formulate reinforcement plans; Level IV response: immediately evacuate personnel, take emergency reinforcement measures, and initiate emergency response.

[0095] Example 2

[0096] like Figure 2 As shown, it is a schematic diagram of the composition of the long-term monitoring system for building foundation settlement and stability of the present invention, which is used to execute the method described in Example 1. The system includes: a data acquisition module, a memory effect calculation module, a settlement total model calculation module and an early warning response module connected in sequence.

[0097] The data acquisition module is used to collect basic data related to building settlement based on the deployed sensors and collect environmental data of the area where the building is located.

[0098] The memory effect calculation module is used to establish a soil stress memory effect calculation model based on the soil stress data and calculate the effective stress considering the memory effect, and calculate the soil deformation response based on the effective stress.

[0099] The settlement total model calculation module is used to establish a total model of building foundation settlement based on the main consolidation settlement, creep settlement and additional settlement caused by environmental factors according to the soil deformation response and combined with environmental data.

[0100] The early warning response module is used to divide the risk level based on the total model calculation results of the building foundation settlement, combined with the deformation data and the tilt angle data, based on the multi-level threshold, calculate the early warning lead time, and generate an emergency response strategy.

[0101] The system also includes a data communication module and a system maintenance module.

[0102] The data communication module is used for real-time collection and transmission of on-site monitoring data, remote transmission and sharing of monitoring data, and integration and synchronization of multi-source data.

[0103] The system maintenance module is used for regular calibration of various sensors, validity verification of monitoring data, and system operation status monitoring and fault handling.

[0104] Establish monitoring data quality control for multi-source data fusion; pre-process the raw data collected by sensors: remove outliers, use the triple standard deviation method or box plot method to identify and eliminate abnormal data; smooth data, use sliding average or wavelet transform to eliminate data noise; interpolate data, use linear interpolation or spline interpolation method to repair missing data.

[0105] Establish a data quality evaluation index system, including data integrity index to evaluate the missing rate and validity of data; data accuracy index to evaluate the precision and reliability of data; data timeliness index to evaluate data collection delay and transmission delay;

[0106] Realize the collaborative verification of multi-source data, based on the cross-validation of fiber optic sensing and tilt sensing data; based on the correlation analysis of deformation data and earth pressure data; and based on the correction of monitoring data based on environmental data.

[0107] The regular calibration and maintenance plan includes: sensor calibration every 6 months; performance testing of data acquisition equipment every 3 months; and connectivity testing of the communication system every month.

[0108] Establish an equipment fault diagnosis model to realize automatic fault identification; formulate a hierarchical fault handling plan, determine the fault response process, set up backup monitoring equipment, and ensure the continuous operation of the system; dynamically adjust the data collection frequency to optimize system resource utilization; optimize the data transmission strategy to improve the real-time performance of the system; update the early warning model parameters to improve the accuracy of the early warning.

[0109] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A long-term monitoring method for building foundation settlement and stability, characterized in that: The method comprises the following steps: Step S1, collecting basic data related to building settlement based on deployed sensors and collecting environmental data of the area where the building is located; The collection of basic data related to building settlement includes: real-time collection of deformation data of each monitoring point of the building foundation through a distributed optical fiber sensing network, collection of building inclination angle data through a tilt sensor array, and collection of soil stress data at different depths of the building foundation through an earth pressure sensor; the environmental data includes at least temperature, humidity, groundwater level and rainfall; Step S2, establishing a soil stress memory effect calculation model based on the soil stress data and calculating the effective stress considering the memory effect, and calculating the soil deformation response based on the effective stress; Stress memory kernel function The calculation formula is: ;in, is the stress memory distribution coefficient, which represents the weight ratio of the two memory components and has a value range of [0, 1]; is the fast memory decay coefficient, which characterizes the decay rate of the short-term stress memory effect, with the unit of 1 / day; is the slow memory decay coefficient, which characterizes the decay rate of the long-term stress memory effect, and the unit is 1 / day; is a time variable, indicating the time interval from the start of loading to the current time, in days; Effective stress considering memory effect The calculation formula is: ;in, The effective stress considering the memory effect is in kPa; For historical moments The actual stress in kPa; is the integral variable, representing the historical moment, the unit is day; Step S3, establishing a general model of building foundation settlement based on the soil deformation response and environmental data, which is composed of the main consolidation settlement, creep settlement and additional settlement caused by environmental factors; The overall model of building foundation settlement is: ,in, for The total settlement at time To consider the main consolidation settlement of stress memory effect, is the creep settlement, is the additional settlement caused by environmental factors, and the unit of each item is millimeter; The calculation model of the main consolidation settlement is: ;in, For the Thickness of soil layer, in m; is the total number of coatings monitored, is the initial void ratio, dimensionless; is the compression index, dimensionless; is the additional stress increment, in kPa; The creep settlement calculation model is: ;in, is the initial deformation parameter, in day / mm; is the long-term deformation parameter, the unit is 1 / mm; The calculation model for additional settlement caused by environmental factors is: ;in, For the The impact function value of each environmental factor, ; For the The environmental factor influence coefficient, is the number of environmental factors, is the baseline value of the i-th environmental factor, taking the historical average value; For the The nonlinear interaction effect value of environmental factors, ; is the interaction coefficient, which characterizes the coupling strength between environmental factors and satisfies and ; For the The weight coefficient of each environmental factor, is the comprehensive influence coefficient of the interaction of environmental factors, and its value range is [0.1, 0.5]; Step S4, based on the total model calculation results of the building foundation settlement, combined with the deformation data and the tilt angle data, risk level classification is performed based on multi-level thresholds, the early warning lead time is calculated, and an emergency response strategy is generated.

2. The long-term monitoring method for building foundation settlement and stability according to claim 1, characterized in that: The risk level classification in step S4 includes: Based on total settlement , shape variable and tilt angle Based on the comprehensive assessment, the building foundation settlement risk is divided into four levels: Level I means safety: when the total settlement And the deformation And the tilt angle hour; Level II means warning: When or or hour; Level III indicates danger: or or hour; Level IV means emergency: or or hour; in, 、 、 is the settlement threshold, in millimeters; 、 、 is the deformation threshold, in millimeters; 、 、 is the tilt angle threshold in degrees.

3. The long-term monitoring method for building foundation settlement and stability according to claim 2, characterized in that: The specific steps for calculating the early warning lead time include: Based on historical monitoring data, the sliding time window method is used to establish the settlement , shape variable and tilt angle Prediction model, set the time window length and prediction step length ;Perform trend analysis on data within each time window; Calculate the time when each monitoring indicator reaches the warning threshold: ;in, The earliest time point when the settlement reaches the warning threshold, is the predicted time series point, for The predicted settlement value at each moment; is the settlement threshold corresponding to risk level k, k = 1, 2, 3, corresponding to warning, danger, and emergency levels respectively; is the earliest time point when the deformation variable reaches the warning threshold, for The predicted shape value at the moment, is the deformation threshold corresponding to risk level k, The earliest time point when the tilt angle reaches the warning threshold, for The predicted tilt angle value at the moment, is the tilt angle threshold corresponding to risk level k; Comprehensively determine the advance warning amount: ;in, is the warning lead time, which means the time interval from the current moment to the earliest warning state. The earliest time point when the three monitoring indicators reach the warning threshold, For the current moment.

4. The long-term monitoring method for building foundation settlement and stability according to claim 3, characterized in that: The method for deploying the distributed fiber optic sensing network includes: deploying fiber optic sensors horizontally and vertically at key locations on a building foundation, with a horizontal spacing of 3-5 meters and a vertical depth of 10-15 meters below the foundation bottom surface; deploying an array of tilt sensors at corners and in the middle of the building, with a spacing of no more than 20 meters; and deploying soil pressure sensors at a depth of no less than 5 meters under the building foundation, with a total depth of no less than 20 meters.

5. A long-term monitoring system for building foundation settlement and stability, used to implement the method according to any one of claims 1 to 4, characterized in that: The system includes: a data acquisition module, a memory effect calculation module, a settlement total model calculation module and an early warning response module connected in sequence; The data acquisition module is used to collect basic data related to building settlement based on the deployed sensors and collect environmental data of the area where the building is located; The memory effect calculation module is used to establish a soil stress memory effect calculation model based on the soil stress data and calculate the effective stress considering the memory effect, and calculate the soil deformation response based on the effective stress; The settlement total model calculation module is used to establish a total model of building foundation settlement based on the main consolidation settlement, creep settlement and additional settlement caused by environmental factors according to the soil deformation response and combined with environmental data; The early warning response module is used to divide the risk level based on the total model calculation results of the building foundation settlement, combined with the deformation data and the tilt angle data, based on the multi-level threshold, calculate the early warning lead time, and generate an emergency response strategy.

6. The long-term monitoring system for building foundation settlement and stability according to claim 5, characterized in that: The system also includes a data communication module and a system maintenance module; The data communication module is used for real-time collection and transmission of on-site monitoring data, remote transmission and sharing of monitoring data, and integration and synchronization of multi-source data; The system maintenance module is used for regular calibration of various sensors, validity verification of monitoring data, and system operation status monitoring and fault handling.

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