Method and system for monitoring displacement of foundation pit support structure pile body and pile back soil body

Abstract

The invention relates to a foundation pit support structure pile body and pile back soil body displacement monitoring method and system. The system comprises an acquisition unit and a processing unit, the acquisition unit comprises a first optical fiber sensor and a second optical fiber sensor, and the processing unit can correct data information acquired by the first optical fiber sensor and the second optical fiber sensor and then comprehensively analyze the data information. The correction mode of the processing unit comprises the steps of directly correcting the data information acquired by the optical fiber sensor by using the first type of data acquired by the acquisition unit and correcting the data information acquired by the optical fiber sensor by using the second type of data corrected based on the first type of data. The method comprises the following steps: arranging an acquisition unit and acquiring data information; correcting the data information acquired by the optical fiber sensor by using the first type of data; correcting the data information acquired by the optical fiber sensor by using the second type of data corrected based on the first type of data; and comprehensively analyzing data information acquired by each optical fiber sensor to obtain a displacement analysis result.

Description

Technical Field

[0001] The present invention relates to the technical field of engineering construction, and in particular to a method and system for monitoring the displacement of a foundation pit retaining structure pile and soil behind the pile. Background Art

[0002] During the development of urban underground space, the design and construction of foundation pit retaining structures are crucial to ensuring project safety. The foundation pit retaining structure piles and the soil behind the piles are key components of the foundation pit project. They jointly bear the earth pressure and water pressure to ensure the stability of the foundation pit. Retaining piles are usually formed by driving or drilling into the ground, while the soil behind the piles refers to the soil behind the piles, and its stability directly affects the safety of the entire foundation pit project. In actual projects, due to the different support stiffness provided by the horizontal supports, retaining piles at different locations may produce different horizontal displacement distribution patterns, and the maximum horizontal displacement values ​​also have significant differences.

[0003] Displacement monitoring of foundation pit retaining structures is an important means of ensuring construction safety and quality control. Traditional displacement monitoring methods include inclinometer monitoring, static penetration testing, and load testing. These methods can effectively monitor the deep horizontal displacement of the pile and the pile side friction resistance ratio, thereby evaluating the stability and bearing capacity of the pile. The importance of displacement monitoring lies in its ability to promptly detect signs of instability in the foundation pit retaining structures, prevent accidents, control project quality, protect the surrounding environment, and optimize design and construction plans. For example, monitoring data can be used to evaluate whether the design of the support structure is reasonable and whether the construction quality meets the standards, and to optimize the design plan to improve construction efficiency and economy. In addition, displacement monitoring data can also help understand the impact of foundation pit excavation on surrounding buildings and underground pipelines, allowing necessary measures to be taken to prevent damage.

[0004] CN113358036A discloses a horizontal displacement monitoring device for the top of a foundation pit supporting pile, which includes a stable support, a support plate frame, a partition plate, a displacement monitoring device and an auxiliary correction component. The stable support is longitudinally fixed on a stable base surface and is arranged on the left and right sides of the supporting pile. The support plate frame is transversely connected and fixed to the left and right stable supports. The upper ends of the partition plates are vertically fixed on the lower side plates of the support plate frame. Multiple groups are arranged in a transverse linear manner, and adjacent partition plates and support plate frames form a displacement monitoring room; the lower ends of the partition plates are vertically connected to the middle and upper end surfaces of the two-way telescopic machine, and a displacement monitoring device is installed between the two-way telescopic machines in a group of the displacement monitoring rooms. A positioning early warning component is provided in the displacement monitoring device to monitor and warn the deformation displacement of the supporting pile, and an auxiliary correction component is installed inside the top of the supporting pile.

[0005] CN111764447A discloses a method for monitoring the horizontal displacement of foundation pit support pile tops, suitable for monitoring changes in the horizontal displacement of the tops of support structures surrounding the foundation pit during the excavation phase. The monitoring method includes the following steps: 1. Arrange plane control points, install small prisms, calculate plane coordinates, establish monitoring points, install small prisms, select base points for foundation pit monitoring, and set up a total station; 2. Measure and calculate the initial plane coordinates of each monitoring point using a multiple-round measurement method; 3. Repeat the measurement of each monitoring point at regular intervals to calculate the change in horizontal displacement; and 4. Perform statistical analysis on the change in horizontal displacement of each monitoring point.

[0006] CN118601060A discloses a novel method and system for monitoring the displacement of foundation pit support structures, comprising: obtaining monitoring items in a foundation pit construction project, and numerically simulating the construction process of the monitoring items to obtain the deformation characteristics and mechanical characteristics of particles during the construction process; arranging measurement points for the monitoring items based on the deformation characteristics and mechanical characteristics to obtain measurement point arrangement results; arranging monitoring instruments based on the measurement point arrangement results to perform monitoring and obtain monitoring results; and analyzing the monitoring results to determine the safety and stability of the foundation pit construction project.

[0007] However, existing technologies face a number of challenges in monitoring the displacement of piles and soil behind them in foundation pit retaining structures. First, fiber optic sensors can be affected by nonlinear factors such as temperature and strain in practical applications, resulting in nonlinear responses in the sensor output data. This directly impacts the accuracy of displacement measurements and, in turn, the assessment of foundation pit stability. Failure to accurately monitor displacement changes can lead to misjudgment of potential risks, increasing the risk of foundation pit collapse or structural damage. Second, external interference and noise can also affect sensor data, degrading the quality of the monitoring signal. For example, vibration and impact at the construction site can be misinterpreted by sensors as actual pile displacement, leading to erroneous engineering decisions. Finally, the interpretation of monitoring data is often influenced by the subjective judgment of analysts, which can lead to different interpretations of the same dataset by different engineers. This subjectivity can lead to inconsistent decisions and hinder the engineering team's shared understanding of foundation pit stability.

[0008] In addition, on the one hand, there are differences in understanding among those skilled in the art; on the other hand, the applicant studied a large number of documents and patents when making the present invention, but due to space limitations, not all details and contents are listed in detail. However, this does not mean that the present invention does not have the characteristics of these prior arts. On the contrary, the present invention already has all the characteristics of the prior art, and the applicant reserves the right to add relevant prior art to the background technology. Summary of the Invention

[0009] In view of the deficiencies of the existing technology, the present invention provides a method and system for monitoring the displacement of foundation pit retaining structure piles and pile back soil to solve at least some of the above technical problems.

[0010] The present invention discloses a displacement monitoring system for piles and soil behind piles of a foundation pit retaining structure, comprising: an acquisition unit for acquiring data information related to the piles and / or soil behind piles; and a processing unit for analyzing and calculating the data information acquired by the acquisition unit to obtain a displacement assessment result. The acquisition unit comprises a first fiber optic sensor for acquiring data information related to the piles and a second fiber optic sensor for acquiring data information related to soil behind piles. The processing unit is capable of correcting the data information acquired by the first and second fiber optic sensors before performing a comprehensive analysis. The correction method of the processing unit includes directly correcting the data information acquired by the fiber optic sensors using the first type of data acquired by the acquisition unit, and correcting the data information acquired by the fiber optic sensors using the second type of data corrected based on the first type of data.

[0011] The displacement monitoring system for piles and soil behind piles of foundation pit retaining structure of the present invention realizes accurate monitoring of the displacement of piles and soil behind piles by integrating an acquisition unit and a processing unit. The first optical fiber sensor and the second optical fiber sensor equipped with the acquisition unit collect data for the pile body and soil behind piles respectively, ensuring the comprehensiveness and pertinence of the monitoring data. The processing unit corrects and comprehensively analyzes these data, and by introducing a correction mechanism, compensates for environmental influences that the optical fiber sensor may be subject to, such as temperature and humidity changes and external disturbances, thereby improving the accuracy of the displacement assessment results. This correction method includes direct correction and correction of the second type of data based on the correction of the first type of data, which enhances the adaptability and robustness of the system. Through this refined data processing, the system can provide more reliable displacement assessment results, providing strong data support for the safety and stability of foundation pit projects.

[0012] According to a preferred embodiment, the first type of data can be obtained by the temperature and humidity sensor configured by the acquisition unit, so that the processing unit can use the current temperature and humidity data of the pile body and its surrounding soil as the first type of data to generate a temperature and humidity distribution cloud map, and perform temperature and humidity compensation on the data information obtained by each optical fiber sensor based on the overall temperature and humidity conditions of the current area.

[0013] The system uses temperature and humidity sensors to capture the first type of data, enabling the processing unit to generate a temperature and humidity distribution cloud map and obtain an overall picture of the temperature and humidity in the current area. Using this data, the processing unit applies temperature and humidity compensation to the data captured by the fiber optic sensors, correcting for measurement errors caused by changes in ambient temperature and humidity. This compensation mechanism accounts for the combined effects of temperature and humidity on the performance of the fiber optic sensors. Through precise temperature and humidity compensation, the system can provide more accurate displacement monitoring data, enhancing the reliability and practicality of the monitoring results.

[0014] According to a preferred embodiment, when the processing unit uses the first type of data to perform temperature and humidity compensation, it can introduce a temperature and humidity interaction compensation coefficient and an interaction term into the compensation model in a manner that takes into account the coupling effect of temperature and humidity.

[0015] The processing unit further refines the accuracy of temperature and humidity compensation by introducing temperature and humidity interaction compensation coefficients and interaction terms into the compensation model. This model not only considers the individual effects of temperature and humidity, but also the coupling effect between them, thereby more accurately predicting and correcting the impact of environmental factors on fiber optic sensor performance. This advanced compensation strategy enables a higher level of data correction and provides more accurate displacement monitoring results, which is of great significance for ensuring the safety of foundation pit projects and optimizing the construction process.

[0016] According to a preferred embodiment, the second type of data can be acquired by a vibration monitoring device configured by the acquisition unit, so that the processing unit can use a cross-correlation analysis method to align the signal of the optical fiber sensor within a specific time window with the signal of the vibration monitoring device to determine their consistency, wherein the vibration signal acquired by the vibration monitoring device can be corrected by the temperature and humidity data as the first type of data when serving as the second type of data.

[0017] The system utilizes vibration monitoring components to capture secondary data, capturing vibration signals generated by vibration sources in the surrounding environment. The processing unit uses cross-correlation analysis to align and determine consistency between these signals, helping to distinguish actual displacement from unrealistic displacement caused by vibration. Furthermore, when using vibration signals as secondary data, they can be corrected using temperature and humidity data, further improving their accuracy. This comprehensive analysis method provides more accurate displacement monitoring results, helping to identify and prevent potential structural risks.

[0018] According to a preferred embodiment, the processing unit is capable of introducing a propagation model to correct the vibration signal to take into account the influence of the properties of the propagation medium on the propagation of the vibration signal, wherein the propagation medium includes piles and / or soil, and the properties of the propagation medium include type and temperature and humidity distribution.

[0019] The processing unit incorporates a propagation model to correct vibration signals, taking into account the impact of the propagation medium's properties, such as pile and soil type, and temperature and humidity distribution. This model more accurately simulates the propagation characteristics of vibration signals in different media, including attenuation and phase delay, thereby improving the accuracy of vibration signal correction. This advanced signal processing enables the system to provide more reliable displacement monitoring data, enhancing its adaptability and robustness.

[0020] According to a preferred embodiment, the attenuation coefficient related to the properties of the propagation medium of the propagation path introduced by the processing unit in the propagation model can be obtained by dividing the propagation path into multiple local paths according to the type and / or temperature and humidity of the propagation medium, and calculating the attenuation coefficient of each local path separately, thereby being comprehensively calculated based on the distance of each local path.

[0021] By dividing the propagation path into multiple localized segments based on the type of propagation medium and / or temperature and humidity, and calculating the attenuation coefficient for each segment separately, the processing unit can more accurately calculate the overall attenuation coefficient. This approach considers the impact of different propagation media on the propagation characteristics of vibration signals, providing more precise vibration signal correction. Through this refined attenuation coefficient calculation, the system can provide more accurate vibration signal correction results, thereby improving the accuracy and reliability of displacement monitoring.

[0022] According to a preferred embodiment, the first optical fiber sensor can be arranged in the horizontal direction at positions of different heights within the pile body, wherein the positions of different heights within the pile body include the pile top, the pile body, and the pile bottom.

[0023] The first fiber optic sensor is positioned horizontally at different heights within the pile, providing displacement data at varying heights. This arrangement enables the system to capture changes in pile displacement at various heights, providing more comprehensive information. This multi-height monitoring allows the system to more accurately assess the overall stability and bearing capacity of the pile, providing strong data support for foundation pit engineering safety.

[0024] According to a preferred embodiment, the second optical fiber sensor can be arranged at intervals in the soil behind the pile in a "gradient arrangement" or "layered arrangement" manner, wherein the soil behind the pile can be divided into upper soil, middle soil, and lower soil along its depth direction. The second optical fiber sensor has different configuration densities in different layers of soil, and the second optical fiber sensor can be arranged at key positions of each layer of soil.

[0025] The second fiber optic sensor is placed at intervals within the soil behind the pile in a "gradient" or "layered" arrangement, providing monitoring data at varying densities at different soil levels. This arrangement enables the system to capture the displacement and strain characteristics of the soil at various depths, particularly at key locations, providing more accurate soil displacement information. Through this refined soil monitoring, the system can more accurately assess the stability and bearing capacity of the soil behind the pile, providing crucial data support for the safety and optimized design of foundation pit projects.

[0026] The present invention also discloses a method for monitoring the displacement of a foundation pit retaining structure pile and soil behind the pile, which comprises:

[0027] Deploy acquisition units and obtain data information related to the pile body and / or the soil behind the pile;

[0028] The first type of data obtained by the acquisition unit is used to directly correct the data information obtained by the optical fiber sensor;

[0029] When the acquisition unit acquires the second type of data, the data information acquired by the optical fiber sensor is corrected using the second type of data corrected based on the first type of data;

[0030] The data information obtained by each optical fiber sensor is comprehensively analyzed to obtain the displacement analysis results.

[0031] This displacement monitoring method provides a systematic monitoring solution by deploying acquisition units to acquire data related to the pile and the soil behind the pile. The first type of data is used to directly correct the data acquired by the fiber optic sensors. When the second type of data is acquired, the second type of data, corrected based on the first type of data, is used to correct the data acquired by the fiber optic sensors. This method provides more accurate displacement monitoring results. The data acquired by each fiber optic sensor is comprehensively analyzed to obtain displacement analysis results. This comprehensive analysis method provides more comprehensive displacement monitoring data, helping to identify and prevent potential structural risks.

[0032] According to a preferred embodiment, when laying out the collection unit, the first optical fiber sensor is set in the pile body, the second optical fiber sensor is set in the soil behind the pile, and a temperature and humidity sensor for obtaining temperature and humidity data as the first type of data and a vibration monitoring component for obtaining vibration signals from the vibration source as the second type of data are further provided.

[0033] The displacement monitoring method and system of the present invention are particularly suitable for scenarios with strict requirements on displacement monitoring accuracy, for example, high-risk foundation pit projects: foundation pit projects carried out in urban centers or densely populated areas, any structural failure may lead to significant loss of life and property; complex geological conditions: when foundation pit projects are carried out in areas with complex geological conditions, large changes in groundwater levels or uneven distribution of soil layers, traditional monitoring methods may not be able to provide sufficient accuracy and reliability; important infrastructure: for important infrastructure projects, such as nuclear power plants, large dams, high-rise buildings, etc., structural stability is of vital importance; sensitive environment monitoring: in construction projects that need to protect historical relics, sensitive ecological areas or minimize environmental impacts, high-precision displacement monitoring can reduce interference with the environment while ensuring construction safety. In the above scenarios, the requirements for monitoring accuracy far exceed the cost constraints. Although the initial investment is high, the safety improvements, risk prevention and long-term stability guarantees it brings far outweigh the cost considerations. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 This is a hardware connection diagram of a displacement monitoring system according to a preferred embodiment of the present invention;

[0035] Figure 2 This is a schematic diagram of the layout of a first optical fiber sensor according to a preferred embodiment of the present invention;

[0036] Figure 3 This is a schematic diagram of the layout of a second optical fiber sensor according to a preferred embodiment of the present invention;

[0037] Figure 4 It is a flow chart of the steps of a displacement monitoring method according to a preferred embodiment of the present invention.

[0038] Reference Signs List

[0039] 100: acquisition unit; 110: first optical fiber sensor; 120: second optical fiber sensor; 130: temperature and humidity sensor; 140: vibration monitoring element; 200: processing unit; 210: compensation model; 220: propagation model. DETAILED DESCRIPTION

[0040] The following is a detailed description with reference to the accompanying drawings.

[0041] In foundation pit construction, piles and backfill soil are crucial components of the retaining structure. A pile is a long, cylindrical member typically made of concrete, steel, or other materials that supports and bears the weight of the superstructure. Piles are driven or drilled deep into the soil to provide the necessary load-bearing capacity. The main functions of a pile include: bearing load, transferring the load of the superstructure to deeper soil layers to reduce foundation settlement and ensure safety; providing stability, helping to maintain the stability of the surrounding soil during excavation and prevent collapse. Backfill soil refers to the soil layer in contact with the pile, typically the soil behind and around the pile. The quality and properties of the backfill soil directly affect the pile's bearing capacity and displacement. The main functions of the backfill soil include: providing lateral support, preventing displacement and deformation during excavation; and influencing bearing properties, namely, soil strength, deformation properties, and water level fluctuations, which can all affect the pile's bearing capacity and stability. The interaction between the pile and the soil behind it is a critical factor in foundation pit engineering. Changes in either aspect can affect the safety and stability of the entire retaining structure. Therefore, during the design and construction process, the bearing capacity of the pile, the properties of the soil behind it, and their interaction must be fully analyzed and monitored to ensure construction safety and protect the surrounding environment.

[0042] The displacement of the pile and the soil behind the pile refers to their change relative to their original position under load. Pile displacement refers to the vertical and / or lateral displacement of the pile after it bears the load of the superstructure. Vertical displacement refers to the settlement or uplift of the pile due to load; lateral displacement refers to the deflection of the pile under lateral forces (such as soil pressure or water pressure). Excessive pile displacement can lead to structural instability or damage. The displacement of the soil behind the pile refers to the deformation and displacement of the soil in contact with the pile due to the pile load. It usually manifests as soil settlement and / or lateral displacement. Soil settlement refers to the settlement of the soil behind the pile due to compaction when the pile bears the load; lateral displacement refers to the lateral movement of the surrounding soil under the load of the pile. The displacement of the pile and the soil behind the pile are interrelated. Pile displacement causes changes in the stress state of the soil behind the pile, and vice versa. Monitoring the displacement of these two components can help assess the overall safety and stability of the retaining structure.

[0043] Example 1

[0044] like Figure 1 As shown, the present invention discloses a displacement monitoring system for piles and soil behind piles of a foundation pit retaining structure, which includes: an acquisition unit 100 for acquiring data information related to the piles and / or soil behind piles; and a processing unit 200 for analyzing and calculating the data information acquired by the acquisition unit 100 to obtain a displacement assessment result.

[0045] Preferably, the acquisition unit 100 may include a first fiber optic sensor 110 for acquiring data and information related to the pile body, and a second fiber optic sensor 120 for acquiring data and information related to the soil behind the pile. Both the first fiber optic sensor 110 and the second fiber optic sensor 120 utilize fiber optic technology for measurement and monitoring, relying on the propagation characteristics of light to sense changes in physical quantities such as temperature, strain, pressure, and displacement. Preferably, the first fiber optic sensor 110 and the second fiber optic sensor 120 have high sensitivity to minute physical changes and are capable of detecting very small changes in physical quantities (e.g., strain, temperature, displacement, etc.). Furthermore, they are unaffected by electromagnetic interference and are well suited for use in environments with high electromagnetic noise. Furthermore, they have good corrosion resistance to chemicals and are suitable for operation in harsh environments. Furthermore, they are relatively lightweight, easy to install and deploy, and adaptable to a variety of application scenarios. Preferably, the first fiber optic sensor 110 can be configured as a distributed fiber optic sensor, capable of continuous monitoring at any location along the fiber, suitable for measuring physical quantities over a wide range. The second fiber optic sensor 120 can be configured as a point fiber optic sensor, which can be composed of an optical fiber and a sensor element and performs measurements at a specific location.

[0046] Preferably, if Figure 2 As shown, the first optical fiber sensor 110 can be set at different positions in the pile body, and especially arranged at different heights in the pile body along the horizontal direction, wherein the different heights in the pile body can include the pile top, pile body, and pile bottom.

[0047] Preferably, if Figure 3As shown, the second optical fiber sensors 120 can be disposed within the soil behind the pile, and in particular, can be arranged at intervals within the soil behind the pile in a "gradient layout" or "layered layout" manner to ensure that the displacement and strain characteristics of the soil are fully captured. Specifically, second optical fiber sensors 120 of varying densities can be deployed in different layers of soil along the depth direction of the soil behind the pile, where the soil behind the pile can be divided into an upper soil layer, a middle soil layer, and a lower soil layer. Furthermore, the upper soil layer is usually loose topsoil with relatively low bearing capacity, which is greatly affected by external loads and prone to settlement and displacement. Therefore, a relatively higher density of sensors (e.g., spacing of 0.5 meters) can be configured to ensure sensitive monitoring of initial displacement and strain. The middle soil layer may contain relatively uniform soil layers and generally have a strong bearing capacity. Therefore, the sensor density can be set to a medium level (e.g., spacing of 1 meter) and can be adjusted according to actual conditions and project requirements. The lower soil layer is usually hard soil or rock layer with small deformation and a greater impact on the bearing capacity of the pile foundation. Therefore, its sensor density can be relatively low (e.g., spacing of 1.5 meters or 2 meters). Furthermore, preferably, the key positions of each layer of soil can be determined first to flexibly adjust the sensor density to capture significant deformation or stress concentration areas. Among them, since the pile foundation load will be transmitted downward, the soil near the pile bottom is usually subjected to higher stress. Therefore, when deploying the second optical fiber sensor 120 in the lower soil layer, it is necessary to accurately locate each key position, and focus on locating the key positions to ensure comprehensive monitoring. Preferably, the key locations mentioned above may include: the pile bottom area, i.e., the point where the soil contacts the pile foundation and bears the maximum load; the load transfer path, i.e., the area above the pile foundation and within the underlying soil layer intersecting the pile body; the potential instability area, i.e., soil areas identified based on geological survey results as potentially at risk of liquefaction, landslide, or subsidence; the contact surface between the pile and the soil, especially the section bordering different soil layers; areas subject to high stress or significant deformation, such as areas where stress or displacement changes may be significant due to changes in groundwater levels or construction impacts; the topsoil layer; and the location of the first fiber optic sensor 110 at the same depth. By implementing gradient or layered point-type fiber optic sensors in the soil behind the pile, the sensors can accurately capture deformation patterns, allowing monitoring data at different depths and locations to accurately identify the deformation characteristics of the soil under the influence of the pile foundation. By monitoring changes in bearing capacity in real time, the sensors can provide strain and displacement data of the soil surrounding the pile foundation, thereby promptly identifying potential changes in bearing capacity. In addition, the established hierarchical monitoring network ensures the hierarchy and continuity of data, so that data obtained from different depths and locations form an effective reference.

[0048] The reason why the two fiber optic sensors of the acquisition unit 100 adopt this layout strategy is that the strain and displacement of the soil are not uniformly distributed, but are affected by multiple factors such as the load imposed by the pile foundation, the construction process, and environmental changes. Therefore, multi-point sensors are needed to capture the change information at different depths and positions. After achieving comprehensive monitoring of the pile body and the soil behind the pile, the reliability and accuracy of the monitoring data can be effectively improved, providing a scientific basis for the safety assessment and maintenance of the construction project. In addition, the combination of distributed fiber optic sensors and multi-point fiber optic sensors enables high-density, real-time, and continuous monitoring over a large area, thereby comprehensively evaluating the stability of the pile foundation and the surrounding soil, and discovering potential structural risks in advance.

[0049] Preferably, the optical parameters such as reflected light intensity, phase, or wavelength collected by the two optical fiber sensors of the acquisition unit 100 can be sent to the processing unit 200 for data analysis and calculation. The processing unit 200 can calculate the strain value based on the relationship between the optical parameter changes and the strain. The strain is then converted into displacement using the principles of material mechanics, thereby determining the displacement of the pile and the soil behind the pile. Furthermore, the measurement accuracy of optical fiber sensors is often affected by temperature. This is because the refractive index of the optical fiber changes with temperature, affecting the propagation speed of the optical signal in the fiber and, consequently, the measurement results. For example, an increase in temperature causes a decrease in the refractive index, which in turn affects the phase and intensity of the optical signal. Optical fiber materials undergo thermal expansion or contraction under temperature fluctuations. This physical change affects the geometry and length of the optical fiber, and thus the transmission characteristics of the optical signal. Therefore, temperature compensation is often performed to improve measurement accuracy. However, humidity, a less studied issue, can also affect the sampling accuracy of optical fiber sensors. This is because optical fibers are typically made of glass or polymer materials, whose refractive index and physical properties are affected by humidity fluctuations. For example, polymer optical fibers absorb moisture, which changes the refractive index and, in turn, affects the propagation of the optical signal. Furthermore, due to the coupled effects of temperature and humidity, changes in temperature and humidity will cause optical signals to attenuate, especially over long distances. Signal attenuation will cause the signal strength received by the receiver to decrease, thereby reducing measurement accuracy.

[0050] Preferably, the acquisition unit 100 may also include a temperature and humidity sensor 130 for obtaining current temperature and humidity data, wherein the current temperature and humidity data mainly refer to the real-time sampling values ​​of the temperature and humidity of the pile body and the soil around it. Furthermore, the acquisition unit 100 may be provided with a plurality of temperature and humidity sensors 130 in a dispersed manner in the pile body and the soil around it in the form of a ring or matrix, wherein the temperature and humidity sensors 130 may be arranged based on the arrangement of the optical fiber sensors to determine the arrangement position, so as to ensure that the temperature and humidity conditions in the current area are monitored at different directions and distances. Preferably, the temperature and humidity data acquired by the temperature and humidity sensor 130 may be sent to the processing unit 200, so that the processing unit 200 may generate a temperature and humidity distribution cloud map in real time based on these data, thereby displaying the overall temperature and humidity conditions in the current area.

[0051] Preferably, the processing unit 200 can establish a compensation model 210 based on the relationship between the acquired temperature and humidity and the displacement measurement results. In addition to compensating for the effects of temperature and humidity in isolation, the processing unit 200 of the present invention also introduces a temperature-humidity interaction compensation coefficient. Furthermore, the compensation model 210 established by the processing unit 200 is:

[0052] D′=D+k T (T-T0)+k H (H-H0)+k TH (T-T0) (H-H0),

[0053] Where D′ is the displacement value after compensation, D is the original measured displacement value, T is the current temperature, H is the current humidity, T0 is the reference temperature, H0 is the reference humidity, k T is the temperature compensation coefficient, k H is the humidity compensation coefficient, k TH is the temperature and humidity interaction compensation coefficient.

[0054] In the compensation model 210, the reference temperature and reference humidity can be reference values ​​obtained by collecting temperature and humidity data over a period of time and taking the average value under normal operating conditions, or by conducting experiments under different environmental conditions, recording the corresponding displacement and temperature and humidity, and selecting the temperature and humidity under undisturbed or specific stable conditions as the reference values.

[0055] In the compensation model 210, the temperature compensation coefficient, humidity compensation coefficient, and temperature-humidity interaction compensation coefficient can be obtained through multiple measurements during the experimental phase. Displacement data is recorded under different temperature and humidity conditions, and the corresponding compensation coefficients can be fitted through linear regression analysis or other statistical methods. Preferably, when fitting the compensation coefficients, the processing unit 200 needs to pay special attention to data quality, model selection, and data preprocessing. Ensure that the collected sample data is accurate, consistent, and has a wide coverage, and standardize the input variables to reduce the impact of magnitude differences. The processing unit 200 can select an appropriate data fitting model. For example, when linear regression is performed, multicollinearity should be considered, which can be assessed by calculating the variance inflation factor (VIF). In addition, the processing unit 200 can use cross-validation techniques to evaluate model performance, perform residual analysis to test the effectiveness of the model fit, and use the coefficient of determination R2 and adjusted R2 to assess the goodness of fit. After introducing the interaction term (T-T0)(H-H0), the processing unit 200 can evaluate whether it is significant to ensure that it provides additional information to the model.

[0056] In compensation model 210, the temperature compensation coefficient, humidity compensation coefficient, and temperature-humidity interaction compensation coefficient can be calibrated through a multi-factor full-factor experiment in a climate simulation chamber during the experimental phase. The climate simulation chamber can adopt a 15m×8m×6m cabin structure and integrate a temperature control module (accuracy ±0.5°C) and a humidity control module (accuracy ±3%RH). Processing unit 200 designs 27 sets of standard experimental samples based on the three-factor three-level response surface methodology and adds 4 sets of extreme condition test samples to cover typical operating conditions. When fitting each compensation coefficient, processing unit 200 obtains displacement data through a monitoring network consisting of a vibrating wire displacement meter and a distributed fiber optic sensor. A ridge regression algorithm (regularization parameter λ = 0.01) is used to construct a multivariate regression model including interaction terms. The variance inflation factor (VIF) is also calculated to assess the impact of multicollinearity. The multivariate regression model is shown below:

[0057]

[0058] Among them, ΔD1, ΔD2, ..., ΔD n is the displacement change, ΔT1, ΔT2, …, ΔT n is the temperature change, ΔH1, ΔH2, …, ΔH n is the humidity change, ΔT1ΔH1, ΔT2ΔH2, …, ΔT n ΔH n is the interactive change of temperature and humidity, k T is the temperature compensation coefficient, k H is the humidity compensation coefficient, k TH is the temperature and humidity interaction compensation coefficient, ∈1, ∈2, …, ∈ nis the error term.

[0059] The model validation module built into the processing unit 200 uses the holdout method to divide the training set and the test set (8:2 ratio), and based on the adjusted coefficient of determination R 2 The model's effectiveness is evaluated using the criteria of ≥0.85 and mean absolute percentage error (MAPE) ≤3%. Preferably, the processing unit 200 performs daily sensor zero-point calibration during the experimental phase, establishes a displacement reference system through a laser interferometer, and calculates the moving range (MR) value in real time during the data acquisition process. When three consecutive data points exceed the 2σ control limit, an abnormal alarm mechanism is triggered. Furthermore, after completing laboratory calibration, the processing unit 200 can connect to the temperature and humidity sensors 130 and vibration monitoring components 140 at the project site through the field verification module. Combined with real-time data from the wind load sensor and pore water pressure gauge, the compensation model 210 is dynamically modified to adapt to the influence of uncontrolled environmental variables.

[0060] When vibrations generated by vibration sources in the surrounding environment of the foundation pit propagate through the soil and / or piles to the location where the fiber optic sensor is installed, the vibrations cause slight displacements or deformations in the fiber optic cable. This displacement can cause a phase change in the optical signal in the fiber optic cable. For example, the vibration sources in the surrounding environment can be construction activities and / or traffic. Construction activities such as drilling, piling, or heavy machinery operation generate ground vibrations, which can propagate through the soil to the surrounding area. Traffic-induced vibrations primarily originate from the movement of motor vehicles, trains, and other transportation vehicles. For example, the movement of cars, public transportation, and heavy vehicles on the road generates ground vibrations due to tire contact with the ground, acceleration, braking, and turning. These vibrations can propagate through the soil and buildings, affecting the surrounding environment and structures. When the fiber optic cable is vibrated, if a portion of the fiber optic cable is displaced, the light propagation path will change. However, not all vibrations generated by vibration sources will cause displacement of the pile or the soil behind the pile. In particular, low-intensity vibrations can affect the fiber optic sensor but may not cause actual displacement, leading to measurement errors.

[0061] Preferably, the acquisition unit 100 may also be provided with a vibration monitoring device 140 for capturing vibration data. The vibration monitoring device 140 may be configured as an accelerometer or vibration sensor with an appropriate frequency response range to capture changes in the target vibration frequency. Preferably, the vibration monitoring device 140 may be installed in areas with frequent construction activities and / or traffic to capture vibrations generated by vibration sources in the surrounding environment. Preferably, the vibration signals acquired by the vibration monitoring device 140 may be transmitted to the processing unit 200 for analysis and calculation of the vibration signals.

[0062] Preferably, the processing unit 200 can pre-process the signals collected by the vibration monitoring device 140, including denoising and filtering. Specifically, the processing unit 200 can use a bandpass filter to extract vibration signals within a specific frequency range. Preferably, the processing unit 200 can use a wavelet transform or a fast Fourier transform (FFT) to perform frequency domain analysis to remove high-frequency noise.

[0063] Preferably, the processing unit 200 can select a specific time window to ensure that within this window, the data from the vibration monitoring device 140 located around the vibration source and the optical fiber sensor located in the pile body and the soil behind the pile can both capture the same vibration event. Furthermore, the processing unit 200 can use a cross-correlation analysis method to align the signal from the optical fiber sensor with the signal from the vibration monitoring device 140 to determine their consistency, wherein the cross-correlation function built into the processing unit 200 is:

[0064]

[0065] Where R xy (τ) is the cross-correlation function, x(t) is the signal collected by the optical fiber sensor, y(t) is the signal collected by the vibration monitoring component 140, t is time, and τ is the time delay.

[0066] Preferably, the present invention considers the impact of the properties of the propagation medium on vibration signal propagation and introduces a propagation model 220 to correct the vibration signal. The propagation medium may include piles and / or soil, and the properties of the propagation medium include type (i.e., material), temperature and humidity distribution, etc. Preferably, the temperature and humidity distribution of the propagation medium can be obtained by processing unit 200 based on data information obtained by temperature and humidity sensor 130. When vibration generated by the same vibration source propagates along different propagation paths to fiber optic sensors at different locations, it will be affected by varying degrees of attenuation and phase delay. For example, some propagation paths may include a single propagation medium, while others may include multiple different types of propagation media, such as both pile propagation and soil propagation. The soil may also include more subdivided types (such as clay, sand, or gravel). Different subdivided types of soil may also serve as different types of propagation media. Propagation paths composed of different types of propagation media may have varying degrees of impact on vibration propagation. For another example, multiple propagation paths with the same propagation medium may have varying degrees of impact on vibration propagation due to the different temperatures and humidity levels of the propagation media they contain. Therefore, different propagation paths may have different vibration sensitivities, so that the signals detected by optical fiber sensors at different locations for the vibration generated by the same vibration source are substantially different. Preferably, the corrected vibration signal can be represented by the following propagation model 220:

[0067] y corrected (t) = e-αd y(t-δ)+ε(t),

[0068] Where y corrected (t) is the corrected vibration signal, α is the attenuation coefficient, d is the propagation distance, δ is the phase delay caused by the propagation medium, and ε(t) is the noise term.

[0069] Preferably, the attenuation coefficient is related to the properties of the propagation medium of the propagation path. The propagation path can be divided into multiple local paths according to the type and / or temperature and humidity of the propagation medium, so as to calculate the attenuation coefficient of each local path separately, and thus calculate the comprehensive attenuation coefficient based on the distance of each local path.

[0070] Preferably, the phase delay caused by the propagation medium can be calculated by using a wave equation and material properties, or can be obtained through experimental measurement, numerical simulation, or empirical formula.

[0071] Preferably, after introducing the propagation model 220, the improved cross-correlation function can be expressed as:

[0072]

[0073] Preferably, when calculating the cross-correlation function R xy (τ), the processing unit 200 can determine the consistency according to the preset threshold, wherein, if the calculated cross-correlation function R xy If the maximum value of (τ) is greater than the preset threshold, the signals are considered to be consistent; otherwise, there are significant differences between the signals.

[0074] By introducing the propagation model 220 and taking into account the influence of the soil or pile, the processing unit 200 of the present invention can more accurately determine the relationship between the vibration signal of the vibration source and the signal collected by the optical fiber sensor, thereby improving the accuracy of the cross-correlation analysis. At the same time, the processing unit 200 performs consistency judgment based on the set threshold, which can effectively reduce the possibility of misjudgment and enhance the reliability of the signal consistency judgment. The parameterized propagation model 220 adapts to different soil and pile types and can be calibrated under different temperature and humidity conditions, thereby improving the versatility of the system. In addition, the introduction of the noise term helps to better handle the interference signals present in the actual measurement, making the cross-correlation analysis less susceptible to external noise. Overall, this improved solution provides more accurate correction, can improve the measurement accuracy of the optical fiber sensor in complex environments, adapt to different environmental conditions, improve the reliability and applicability of the system, and ultimately reduce the errors caused by environmental factors through a more reasonable signal processing and judgment mechanism, making the measurement results more reliable.

[0075] Preferably, when the processing unit 200 determines that the vibration signal of the vibration source is consistent with the signal collected by the optical fiber sensor, it can correct the signal collected by the optical fiber sensor to avoid interference with the monitored displacement data.

[0076] Preferably, the processing unit 200 can calibrate the vibration signal and temperature and humidity data for the first fiber optic sensor 110 and the second fiber optic sensor 120, respectively, and fuse the data acquired by each sensor using methods such as weighted averaging to comprehensively evaluate the interaction between the pile and the soil behind the pile. Furthermore, the processing unit 200 can establish a state-space model, using the sensor data as observations to update the state estimate. This state estimate can then be used to track changes in displacement and strain in real time. For nonlinear systems, an extended Kalman filter is used for state estimation and data fusion.

[0077] Preferably, the processing unit 200 can import the monitoring data into the established pile body and pile back soil model to perform dynamic analysis to simulate the displacement response under different loads (such as static load and dynamic load), and compare it with the on-site monitoring data to obtain the displacement analysis results related to the pile body and pile back soil. Furthermore, by comparing the simulation results with the actual monitoring data, the source of the error can be analyzed, and the model parameters (such as the elastic modulus and damping ratio of the soil) can be adjusted according to the monitoring results to improve the accuracy of the model. Furthermore, the processing unit 200 can continuously optimize the model through repeated correction and verification to make it more in line with the actual situation.

[0078] Example 2

[0079] This embodiment is a further improvement of embodiment 1, and repeated contents will not be repeated here.

[0080] The present invention discloses a method for monitoring the displacement of a foundation pit retaining structure pile and the soil behind the pile, which can be implemented using the displacement monitoring system as described in Example 1. Preferably, Figure 4 As shown, the displacement monitoring method may include one or more of the following steps:

[0081] Deploy the acquisition unit 100 and acquire data information related to the pile body and / or the soil behind the pile;

[0082] The first type of data acquired by the acquisition unit 100 is used to directly correct the data information acquired by the optical fiber sensor;

[0083] When the acquisition unit 100 acquires the second type of data, the data information acquired by the optical fiber sensor is corrected using the second type of data corrected based on the first type of data;

[0084] The data information obtained by each optical fiber sensor is comprehensively analyzed to obtain the displacement analysis results.

[0085] Preferably, when deploying the acquisition unit 100, the first optical fiber sensor 110 is set in the pile body, the second optical fiber sensor 120 is set in the soil behind the pile, and a temperature and humidity sensor 130 for obtaining temperature and humidity data as the first type of data and a vibration monitoring component 140 for obtaining the vibration signal of the vibration source as the second type of data are further provided.

[0086] It should be noted that the above-mentioned specific embodiments are exemplary, and those skilled in the art can come up with various solutions inspired by the disclosure of the present invention, and these solutions also belong to the disclosure scope of the present invention and fall within the protection scope of the present invention. Those skilled in the art should understand that the present invention specification and its drawings are illustrative and do not constitute a limitation on the claims. The scope of protection of the present invention is defined by the claims and their equivalents. The present invention specification contains multiple inventive concepts, such as "preferably" or "according to a preferred embodiment", which means that the corresponding paragraph discloses an independent concept, and the applicant reserves the right to file a divisional application based on each inventive concept. Throughout the text, the features guided by "preferably" are only an optional method and should not be understood as having to be set. Therefore, the applicant reserves the right to abandon or delete the relevant preferred features at any time.

Claims

1. A system for monitoring the displacement of foundation pit retaining structure piles and pile back soil, characterized in that: It includes: A collection unit (100) is used to obtain data information related to the pile body and / or the soil behind the pile; The processing unit (200) is used to analyze and calculate the data information obtained by the acquisition unit (100) to obtain a displacement evaluation result. The acquisition unit (100) comprises a first optical fiber sensor (110) for acquiring data information related to a pile body and a second optical fiber sensor (120) for acquiring data information related to soil behind the pile. The processing unit (200) is capable of correcting the data information acquired by the first optical fiber sensor (110) and the second optical fiber sensor (120) and then performing a comprehensive analysis. The correction method of the processing unit (200) comprises directly correcting the data information acquired by the optical fiber sensor using the first type of data acquired by the acquisition unit (100) and correcting the data information acquired by the optical fiber sensor using the second type of data corrected based on the first type of data.

2. The displacement monitoring system according to claim 1, characterized in that: The first type of data can be acquired by a temperature and humidity sensor (130) configured by the acquisition unit (100), so that the processing unit (200) can use the current temperature and humidity data of the pile body and the surrounding soil as the first type of data to generate a temperature and humidity distribution cloud map, and perform temperature and humidity compensation on the data information acquired by each optical fiber sensor based on the overall temperature and humidity conditions of the current area.

3. The displacement monitoring system according to claim 1 or 2, characterized in that: When the processing unit (200) uses the first type of data to perform temperature and humidity compensation, it can introduce a temperature and humidity interaction compensation coefficient and an interaction term into the compensation model (210) in a manner that takes into account the coupling effect of temperature and humidity.

4. The displacement monitoring system according to any one of claims 1 to 3, characterized in that: The second type of data can be acquired by a vibration monitoring component (140) configured by the acquisition unit (100), so that the processing unit (200) can align the signal of the optical fiber sensor within a specific time window with the signal of the vibration monitoring component (140) using a cross-correlation analysis method to determine their consistency, wherein the vibration signal acquired by the vibration monitoring component (140) can be corrected by the temperature and humidity data as the first type of data when serving as the second type of data.

5. The displacement monitoring system according to any one of claims 1 to 4, characterized in that: The processing unit (200) can introduce a propagation model (220) to correct the vibration signal to take into account the influence of the properties of the propagation medium on the propagation of the vibration signal, wherein the propagation medium includes a pile and / or soil, and the properties of the propagation medium include type and temperature and humidity distribution.

6. The displacement monitoring system according to any one of claims 1 to 5, characterized in that: The attenuation coefficient related to the properties of the propagation medium of the propagation path introduced by the processing unit (200) in the propagation model (220) can be obtained by dividing the propagation path into multiple local paths according to the type and / or temperature and humidity of the propagation medium, and calculating the attenuation coefficient of each local path separately, thereby comprehensively calculating the distance of each local path.

7. The displacement monitoring system according to any one of claims 1 to 6, characterized in that: The first optical fiber sensor (110) can be arranged in a horizontal direction at positions of different heights within the pile body, wherein the positions of different heights within the pile body include the pile top, the pile body, and the pile bottom.

8. The displacement monitoring system according to any one of claims 1 to 7, characterized in that: The second optical fiber sensors (120) can be arranged at intervals in the soil behind the pile in a "gradient arrangement" or "layered arrangement" manner, wherein the soil behind the pile can be divided into an upper soil layer, a middle soil layer, and a lower soil layer along its depth direction, the second optical fiber sensors (120) have different configuration densities in different layers of soil, and the second optical fiber sensors (120) can be arranged at key positions of each layer of soil.

9. A method for monitoring the displacement of a foundation pit retaining structure pile and the soil behind the pile, characterized in that: It includes: Deploying a collection unit (100) and acquiring data information related to the pile body and / or the soil behind the pile; Directly correcting data information acquired by the optical fiber sensor using the first type of data acquired by the acquisition unit (100); When the acquisition unit (100) acquires the second type of data, the data information acquired by the optical fiber sensor is corrected using the second type of data corrected based on the first type of data; The data information obtained by each optical fiber sensor is comprehensively analyzed to obtain the displacement analysis results.

10. The displacement monitoring method according to claim 9, characterized in that: When the acquisition unit (100) is arranged, a first optical fiber sensor (110) is arranged in the pile body, a second optical fiber sensor (120) is arranged in the soil behind the pile, and a temperature and humidity sensor (130) for acquiring temperature and humidity data as first-type data and a vibration monitoring element (140) for acquiring vibration signals of a vibration source as second-type data are further provided.

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