Foundation pit quality monitoring method and system for constructional engineering

Abstract

The invention discloses a foundation pit quality monitoring method and system for constructional engineering, and relates to the technical field of safety monitoring of constructional engineering, and the monitoring method comprises the steps of data collection, space-time alignment, dynamic coupling analysis, grading early warning decision and block chain evidence storage. The method has the advantages that a multi-source sensor network space-time alignment method is combined with a soil-structure-water flow dynamic coupling model, cooperative monitoring and coupling analysis of displacement, soil pressure, underground water and the like are achieved, and sensor clock drift and space positioning errors are eliminated through the space-time alignment technology; the dynamic coupling model fully reflects complex responses of a foundation pit system under different working conditions through self-adaptive weight distribution in the construction stage, the limitation of traditional single-parameter monitoring is overcome, the monitoring result is more suitable for engineering practice, and the method is suitable for various geological conditions and foundation pit depth scenes.

Description

Technical Field

[0001] This invention relates to the field of building engineering safety monitoring technology, specifically to a method and system for monitoring the quality of foundation pits in building engineering. Background Technology

[0002] Foundation pit engineering is a critical link in building construction, and its quality and safety are directly related to the stability of the main structure and the safety of the surrounding environment. Currently, foundation pit monitoring mostly relies on the collection of single parameters or manual inspection, which has problems such as data fragmentation and insufficient real-time performance. It is difficult to fully reflect the dynamic coupling effect of soil pressure, groundwater and structural deformation under complex geological conditions, resulting in delayed risk warning.

[0003] Existing monitoring systems generally lack a spatiotemporal coordination mechanism for multi-source data. The accuracy of data fusion is greatly affected by sensor clock drift and spatial positioning deviation. At the same time, the warning thresholds are mostly fixed values, which cannot adapt to changes in the construction stage and are prone to false alarms or missed alarms. In addition, the manual recording mode of monitoring data is subject to tampering and cannot meet the needs of engineering quality traceability and responsibility determination. Therefore, we propose a method and system for monitoring the quality of foundation pits in building engineering. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for monitoring the quality of foundation pits in building construction projects.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a method for monitoring the quality of foundation pits in building construction, comprising a monitoring method, the monitoring method including the following steps:

[0006] Step 1: Data Acquisition: Deploy sensor nodes at the foundation pit support piles, edges, and groundwater level pipes to collect displacement, earth pressure, and water level data;

[0007] Step 2, Spatiotemporal Alignment: Time synchronization is achieved by using a temperature-compensated crystal oscillator (accuracy range ±0.05ppm to ±0.15ppm) and a UWB positioning module (accuracy range ±5cm to ±15cm), and spatial normalization is performed using a coordinate transformation matrix;

[0008] Step 3: Dynamic Coupling Analysis: Construct a dynamic coupling model of soil-structure-water flow, and assign parameter weights according to the construction stage (displacement weight 0.6, water pressure weight 0.3, earth pressure weight 0.1 during excavation; displacement weight 0.2, water pressure weight 0.7, earth pressure weight 0.1 during dewatering; displacement weight 0.4, water pressure weight 0.2, earth pressure weight 0.4 after foundation slab pouring).

[0009] Step 4, Tiered Early Warning Decision: Based on the benchmark threshold and dynamic adjustment coefficients (excavation depth coefficient k1 increases by 0.04 to 0.06 for every 1m of depth, 0.06 for soft soil and 0.04 for sandy soil, seepage sensitivity coefficient k2 is 0.002 to 0.004 for silt), calculate the early warning threshold and trigger the Level III response mechanism;

[0010] Step 5, Blockchain Evidence Storage: The original data, risk level, and timestamp are uploaded to the blockchain, and the integrity is verified by comparing the real-time data hash with the on-chain record through a smart contract.

[0011] As a further aspect of the present invention: the time synchronization algorithm in step two includes: extracting the timestamps of each sensor, calculating the median of the reference time, and applying a linear compensation model. ,in, The corrected time deviation, This is the original time deviation. For temperature coefficient, The value represents the temperature deviation, ranging from 0.00008 ppm / ℃ to 0.00012 ppm / ℃, which is the difference between the measured temperature and 25℃.

[0012] As a further aspect of the present invention: the spatial coordinate normalization in step two employs matrix transformation.

[0013] ;

[0014] in, The transformed target coordinates (unit: m) represent the normalized coordinates of the sensor data in the local coordinate system of the foundation pit. These are trigonometric function terms used to rotate the coordinates around the Z-axis. horn, The original coordinates collected by the sensor. Let the origin of the local coordinate system of the foundation pit be the origin. The angle between the main side of the foundation pit and true north.

[0015] As a further aspect of the present invention: the multiphysics coupling equation of the dynamic coupling model in step three is:

[0016] ;

[0017] in, For the displacement of the support piles, Pore ​​water pressure, For earth pressure, The horizontal displacement of the support pile (mm). The pore water pressure is (kPa). This represents the vertical earth pressure (kPa). Let be the internal friction angle of the soil (°). , This is the coupling coefficient (determined through calibration experiments).

[0018] As a further aspect of the present invention: the dynamic threshold calculation formula in step four is:

[0019] ;

[0020] in, The baseline threshold (mm, set according to the "Technical Specification for Foundation Pit Support"). This is the excavation depth coefficient (increases by 0.05 for every additional 1m of depth). The seepage sensitivity coefficient is 0.003 for silt and 0.01 for sand. The current excavation duration (h) is the soil creep time constant.

[0021] As a further aspect of the present invention: the blockchain evidence storage process in step five includes:

[0022] Original data is encrypted and hashed → Hash value and timestamp are stored on the chain → Smart contract compares new data hash with on-chain record in real time → Tampering alarm is triggered when inconsistency occurs;

[0023] Furthermore, the blockchain evidence storage process meets the data traceability requirements of the ISO 19650 standard.

[0024] The present invention also provides a foundation pit quality monitoring system for building engineering, comprising a monitoring system including the following modules:

[0025] Sensing layer: includes support pile inclination gauges (spacing 5m to 15m, burial depth -10m to -15m), earth pressure cells (5×5 grid arrangement at the bottom of the pit), water level gauges (arranged at the four corners and the midpoint of the long side), and built-in temperature-compensated crystal oscillator and UWB positioning module.

[0026] Analysis layer: includes spatiotemporal alignment unit (time synchronization algorithm, spatial coordinate normalization module), soil-structure-water coupling calculation unit (multiphysics coupling equation solving module), and adaptive threshold calculation unit (dynamic weight allocation submodule);

[0027] Decision-making level: Configure a Level III response module to execute Level I (displacement change rate > 0.5 mm / h) audible and visual alarms and construction suspension, Level II (displacement change rate 0.2 mm / h to 0.5 mm / h) SMS notifications, and Level III (displacement change rate < 0.2 mm / h) platform marking;

[0028] Blockchain evidence storage module: Stores raw sensor data and calibration record hashes, and uses smart contracts to provide real-time alerts for data tampering.

[0029] As a further aspect of the present invention: the soil-structure-water coupling calculation unit of the analysis layer has a built-in construction stage identification submodule, which automatically switches the weight allocation scheme by excavation depth and dewatering rate, and calls the finite element solver to calculate the coupling equation, with a solution error range of ≤±0.5mm (under the conditions of sensor positioning error ≤±1cm and finite element mesh size ≤0.5m).

[0030] As a further aspect of the present invention: the reference station of the sensing layer is set in a stable area outside the foundation pit, and a total station prism is configured to calibrate the drift error of the UWB positioning module. The calibration cycle is 24h to 48h, and the positioning accuracy is maintained within the range of ±5cm to ±15cm after calibration.

[0031] Compared with the prior art, the beneficial effects of the present invention by adopting the above technical solution are as follows:

[0032] 1. This invention combines a multi-source sensor network spatiotemporal alignment method with a soil-structure-water flow dynamic coupling model to achieve coordinated monitoring and coupled analysis of displacement, earth pressure, groundwater, etc. The spatiotemporal alignment technology eliminates sensor clock drift and spatial positioning errors. The dynamic coupling model fully reflects the complex response of the foundation pit system under different working conditions through adaptive weight allocation during the construction stage, overcoming the limitations of traditional single-parameter monitoring, making the monitoring results more consistent with engineering practice, and applicable to various geological conditions and foundation pit depth scenarios.

[0033] 2. The graded early warning decision system is based on a dynamic threshold algorithm, which comprehensively considers key factors such as excavation depth, seepage characteristics, and soil creep, and realizes real-time adjustment of the early warning threshold. The Level III response mechanism automatically triggers corresponding measures according to the risk level, which solves the problems of delayed early warning or high false alarm rate of fixed threshold. The system can quickly identify the deformation trend of the foundation pit, buy time for emergency response for engineers, effectively reduce the risk of collapse accidents, and ensure construction safety.

[0034] 3. The blockchain evidence storage module ensures the integrity and immutability of original monitoring data, analysis results, and timestamps through full-chain data on-chaining and smart contract verification. The data auditing process can be completed through hash comparison without human intervention, meeting the requirements of engineering quality supervision for data traceability. At the same time, it provides objective evidence for accident liability determination, improving the transparency and credibility of foundation pit engineering quality management. Attached Figure Description

[0035] Figure 1 This is a flowchart illustrating the method for monitoring the quality of foundation pits in building engineering according to the present invention.

[0036] Figure 2 This is a flowchart of the spatiotemporal alignment process of the present invention;

[0037] Figure 3This is a flowchart of the blockchain evidence storage process of the present invention. Detailed Implementation

[0038] The specific embodiments of the present invention will be further described below with reference to the accompanying drawings. It should be noted that the description of these embodiments is for the purpose of helping to understand the present invention, but does not constitute a limitation of the present invention.

[0039] Furthermore, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0040] Please see the appendix Figure 1 -Appendix Figure 3 This invention discloses a method for monitoring the quality of foundation pits in construction projects, comprising the following steps:

[0041] Step 1: Data Acquisition: Deploy sensor nodes at the foundation pit support piles, edges, and groundwater level pipes to collect displacement, earth pressure, and water level data;

[0042] Step 2, Spatiotemporal Alignment: Time synchronization is achieved by using a temperature-compensated crystal oscillator (accuracy range ±0.05ppm to ±0.15ppm) and a UWB positioning module (accuracy range ±5cm to ±15cm), and spatial normalization is performed using a coordinate transformation matrix;

[0043] Step 3: Dynamic Coupling Analysis: Construct a dynamic coupling model of soil-structure-water flow, and assign parameter weights according to the construction stage (displacement weight 0.6, water pressure weight 0.3, earth pressure weight 0.1 during excavation; displacement weight 0.2, water pressure weight 0.7, earth pressure weight 0.1 during dewatering; displacement weight 0.4, water pressure weight 0.2, earth pressure weight 0.4 after foundation slab pouring).

[0044] Step 4, Tiered Early Warning Decision: Calculate the early warning threshold based on the baseline threshold and dynamic adjustment coefficients (excavation depth coefficient k1 increases by 0.04 to 0.06 for every 1m of depth, and seepage sensitivity coefficient k2 is 0.002 to 0.004 for silt) and trigger the Level III response mechanism;

[0045] Step 5, Blockchain Evidence Storage: The original data, risk level, and timestamp are uploaded to the blockchain, and the integrity is verified by comparing the real-time data hash with the on-chain record through a smart contract.

[0046] In one embodiment of the present invention: the time synchronization algorithm in step two includes: extracting the timestamps of each sensor, calculating the median of the reference time, and applying a linear compensation model. ,in, The corrected time deviation, This is the original time deviation. For temperature coefficient, The value represents the temperature deviation, ranging from 0.00008 ppm / ℃ to 0.00012 ppm / ℃, which is the difference between the measured temperature and 25℃.

[0047] In one embodiment of the present invention: spatial coordinate normalization in step two employs matrix transformation.

[0048] ;

[0049] in, The transformed target coordinates (unit: m) represent the normalized coordinates of the sensor data in the local coordinate system of the foundation pit. These are trigonometric function terms used to rotate the coordinates around the Z-axis. horn, The original coordinates collected by the sensor. Let the origin of the local coordinate system of the foundation pit be the origin. The angle between the main side of the foundation pit and true north.

[0050] In one embodiment of the present invention: the multiphysics coupling equation of the dynamic coupling model in step three is:

[0051] ;

[0052] in, For the displacement of the support piles, Pore ​​water pressure, For earth pressure, The horizontal displacement of the support pile (mm). The pore water pressure is (kPa). This represents the vertical earth pressure (kPa). Let be the internal friction angle of the soil (°). , This is the coupling coefficient (determined through calibration experiments).

[0053] In one embodiment of the present invention: the dynamic threshold calculation formula in step four is:

[0054] ;

[0055] in, The baseline threshold (mm, set according to the "Technical Specification for Foundation Pit Support"). This is the excavation depth coefficient (increases by 0.05 for every additional 1m of depth). The seepage sensitivity coefficient is 0.003 for silt and 0.01 for sand. The current excavation duration (h) is the soil creep time constant.

[0056] In one embodiment of the present invention: the blockchain evidence storage process in step five includes:

[0057] Original data is encrypted and hashed → Hash value and timestamp are stored on the chain → Smart contract compares new data hash with on-chain record in real time → Tampering alarm is triggered when inconsistency occurs;

[0058] Furthermore, the blockchain evidence storage process meets the data traceability requirements of the ISO 19650 standard.

[0059] The present invention also provides a foundation pit quality monitoring system for building engineering, including a monitoring system comprising the following modules:

[0060] Sensing layer: includes support pile inclination gauges (spacing 5m to 15m, burial depth -10m to -15m), earth pressure cells (5×5 grid arrangement at the bottom of the pit), water level gauges (arranged at the four corners and the midpoint of the long side), and built-in temperature-compensated crystal oscillator and UWB positioning module.

[0061] Analysis layer: includes spatiotemporal alignment unit (time synchronization algorithm, spatial coordinate normalization module), soil-structure-water coupling calculation unit (multiphysics coupling equation solving module), and adaptive threshold calculation unit (dynamic weight allocation submodule);

[0062] Decision-making level: Configure a Level III response module to execute Level I (displacement change rate > 0.5 mm / h) audible and visual alarms and construction suspension, Level II (displacement change rate 0.2 mm / h to 0.5 mm / h) SMS notifications, and Level III (displacement change rate < 0.2 mm / h) platform marking;

[0063] Blockchain evidence storage module: Stores raw sensor data and calibration record hashes, and uses smart contracts to provide real-time alerts for data tampering.

[0064] In one embodiment of the present invention: the soil-structure-water coupling calculation unit of the analysis layer has a built-in construction stage identification submodule, which automatically switches the weight allocation scheme by excavation depth and dewatering rate, and calls the finite element solver to calculate the coupling equation, with a solution error range of ≤ ±0.5mm.

[0065] In one embodiment of the present invention: the reference station of the sensing layer is set in a stable area outside the foundation pit, and a total station prism is configured to calibrate the drift error of the UWB positioning module. The calibration cycle is 24h to 48h, and the positioning accuracy is maintained within the range of ±5cm to ±15cm after calibration.

[0066] Example 1: Application of Multi-parameter Collaborative Monitoring System for Deep Foundation Pit in Soft Soil Strata

[0067] Project Overview: This example is applied to a deep foundation pit project in soft soil strata in a coastal city. The foundation pit is 28m deep and 450m in circumference. It adopts a "diaphragm wall + internal support" support structure. Existing buildings and subway lines are distributed within a 50m radius. The construction risk level is Level I.

[0068] System Deployment:

[0069] 1. Sensor Network Construction: A set of "triaxial accelerometer + fiber optic strain gauge" combined sensor is deployed every 15m around the foundation pit, with a total of 30 monitoring points. 20 sets of pore water pressure gauges and soil pressure cells are buried in the soil at the bottom of the pit and around it. The sampling frequency is set to 1Hz. All sensors are connected to the edge computing gateway via the LoRaWAN wireless protocol. The gateway is deployed in the monitoring room around the foundation pit and has a built-in temperature-compensated crystal oscillator module to achieve time synchronization (synchronization error ≤5ms).

[0070] 2. Data processing unit: An industrial-grade server (configured with an Intel Xeon E5 processor and a 1TB SSD) is used to deploy a spatiotemporal alignment algorithm and a dynamic coupling model. The spatiotemporal alignment corrects the sensor timestamp deviation through a temperature compensation formula and unifies the original coordinates in different coordinate systems to the local coordinate system of the foundation pit (the origin is set to the northwest corner) through a rotation transformation matrix.

[0071] 3. Early warning and evidence storage module: The early warning terminal is equipped with a 12-inch touch screen to display the monitoring data curve and risk level in real time. The blockchain node adopts a consortium blockchain architecture and is deployed in the server of the project supervision unit. The raw data hash value is automatically uploaded to the chain every day. The data on the chain includes sensor ID, collection time, monitoring value and verification code.

[0072] Implementation steps:

[0073] 1. Initialization Phase (7 days before construction): Complete sensor calibration (determined through constant temperature chamber testing). The value is 0.0001ppm / ℃), coordinate system calibration (using a total station to measure the angle between the principal side of the foundation pit and true north). =15.3°) and the parameter settings of the coupling model (initial weights: displacement 40%, earth pressure 30%, pore water pressure 30%).

[0074] 2. Construction period monitoring: During earthwork excavation, the system generates a multi-parameter fusion report every hour. When the excavation reaches the 10th layer (18m deep), the sensor on the east side of the foundation pit collects a horizontal displacement rate of 0.8mm / h. At the same time, the corresponding area soil pressure suddenly increases by 20kPa. The system temporarily increases the displacement weight to 60% through the dynamic coupling model, triggering a Level II warning (the warning threshold is dynamically adjusted to 1.0mm / h according to the excavation depth).

[0075] 3. Emergency Response: The early warning information is pushed to the project manager, supervising engineer and monitoring unit via SMS, and the suggested measures ("Stop excavation on the east side and increase the prestress of the steel support to 300kN") are displayed on the terminal at the same time. Two hours after the measures are implemented, the displacement rate drops to 0.3mm / h, and the system automatically cancels the early warning.

[0076] Example 2: Application of a hierarchical early warning system based on dynamic thresholds in subway excavation pits

[0077] Project Overview: This example is applied to a deep foundation pit project along Metro Line 3 in the city. The minimum clearance between the foundation pit and the metro tunnel is only 8m. The tunnel structure safety control level is special grade, and the impact of foundation pit construction on the tunnel needs to be strictly controlled (the maximum horizontal displacement of the tunnel is allowed to be ≤5mm).

[0078] System innovations:

[0079] 1. Dynamic threshold algorithm design: A threshold adjustment model is constructed based on the three-dimensional parameters of "construction stage - geological conditions - tunnel depth". For example, when the foundation pit is excavated to within 5m above the top of the tunnel (risk-sensitive stage), the horizontal displacement warning threshold is lowered from the usual 10mm to 4mm. When the water content of the soil around the tunnel is detected to exceed 25%, the threshold is further triggered to tighten dynamically (reduced by 15%).

[0080] 2. Level III Early Warning Response Mechanism:

[0081] Level I Warning (Warning value = 0.7 × threshold): The system automatically pushes risk alerts to construction teams, and it is recommended to increase the monitoring frequency to 15 minutes / time.

[0082] Level II Warning (Warning value = 0.9 × threshold): Activate the on-site emergency response team, suspend operations in the dangerous area, and reinforce the soil around the tunnel using a miniature grouting machine.

[0083] Level III Warning (Warning value ≥ threshold): Immediately activate the emergency response plan for the foundation pit, call up the backup steel supports, and report to the housing and construction department.

[0084] Key implementation details:

[0085] Tunnel deformation monitoring: Ten high-precision tilt sensors (measurement accuracy 0.001°) are deployed on the tunnel segments. The tilt data is converted into the longitudinal displacement curve of the tunnel using the coordinate transformation formula in claim 4, and analyzed in conjunction with the pit monitoring data.

[0086] Threshold verification experiment: Before construction, 20 risk conditions were simulated using numerical simulation (FLAC3D software) to determine the dynamic threshold adjustment coefficient library. For example, "for every 0.5m / d increase in excavation speed in sandy soil, the threshold is lowered by 0.8mm".

[0087] Example 3: Application of Blockchain Evidence Storage in Cross-Regional Foundation Pit Engineering Data Management

[0088] Project Overview: This example is applied to a cross-regional foundation pit engineering management platform of a construction group, involving 5 projects under construction in 3 cities (including various geological conditions such as soft soil, rock, and fill), and requires the realization of cross-entity sharing and supervision and traceability of monitoring data.

[0089] 1. Blockchain System Architecture:

[0090] Node setup: Six consortium blockchain nodes are deployed, controlled by the construction unit, construction company, supervision unit, monitoring agency, design unit, and government regulatory department, respectively. Data synchronization between nodes is achieved through the PBFT consensus mechanism (consensus efficiency 300 transactions / second).

[0091] 2. Smart Contract Design:

[0092] The storage contract automatically verifies the monitoring data format (such as sensor ID, sampling timestamp, and numerical range), and generates a unique hash value to write to the block after verification.

[0093] Audit Contract: Regulatory authorities can trigger a data audit process. The contract automatically compares the original data with the on-chain hash value and outputs an integrity report.

[0094] Access control contracts: Data access permissions are assigned based on roles (e.g., construction companies can only view real-time data for their own project, while regulatory authorities can access historical data for all projects).

[0095] Data flow process:

[0096] 1. Data Acquisition Layer: Sensor data from each project is encrypted by the edge gateway (AES-256 algorithm) and then transmitted to the group's cloud platform via VPN.

[0097] 2. On-chain layer: The cloud platform automatically calls the evidence storage contract at 3:00 AM every day to upload the original data summary of the previous 24 hours (generating a data block every 10 minutes) to the chain. The on-chain data includes the project ID, time range, data hash and gateway MAC address.

[0098] 3. Application Layer: The supervision unit periodically checks the data integrity through audit contracts. For example, during the excavation of a foundation pit in a project, the supervisor found that data was missing during a certain period from 14:00 to 15:00. This triggered the contract to automatically trace back and locate the cause as a power outage in the gateway. After the retransmitted data was verified to be consistent by hash, the on-chain update was completed.

[0099] While the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the invention. Any variations and modifications can be made by those skilled in the art without departing from the spirit and scope of the invention. Therefore, any modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of the present invention, without departing from the scope of the invention, fall within the protection scope defined by the claims of the present invention.

Claims

1. A method for monitoring the quality of foundation pits in building construction, comprising a monitoring method, characterized in that: The monitoring method includes the following steps: Step 1: Data Acquisition: Deploy sensor nodes at the foundation pit support piles, edges, and groundwater level pipes to collect displacement, earth pressure, and water level data; Step 2, Spatiotemporal Alignment: Time synchronization is achieved through a temperature-compensated crystal oscillator and a UWB positioning module, and spatial normalization is performed using a coordinate transformation matrix; Step 3: Dynamic Coupling Analysis: Construct a dynamic coupling model of soil-structure-water flow and assign parameter weights according to the construction stage; Step 4, Tiered Early Warning Decision-Making: Calculate the early warning threshold based on the baseline threshold and dynamic adjustment coefficient, and trigger the Level III response mechanism; Step 5, Blockchain Evidence Storage: The original data, risk level, and timestamp are uploaded to the blockchain, and the integrity is verified by comparing the real-time data hash with the on-chain record through a smart contract.

2. The method for monitoring the quality of foundation pits in building construction according to claim 1, characterized in that: The time synchronization algorithm in step two includes: extracting the timestamps of each sensor, calculating the median of the reference time, and applying a linear compensation model. ,in, The corrected time deviation, This is the original time deviation. For temperature coefficient, The value represents the temperature deviation, ranging from 0.00008 ppm / ℃ to 0.00012 ppm / ℃, which is the difference between the measured temperature and 25℃.

3. The method for monitoring the quality of foundation pits in building construction projects according to claim 2, characterized in that: In step two, spatial coordinate normalization employs matrix transformation: ； in, The transformed target coordinates represent the normalized coordinates of the sensor data in the local coordinate system of the foundation pit. These are trigonometric function terms used to rotate the coordinates around the Z-axis. horn, The original coordinates collected by the sensor. Let the origin of the local coordinate system of the foundation pit be the origin. The angle between the main side of the foundation pit and true north.

4. The method for monitoring the quality of foundation pits in building construction projects according to claim 1, characterized in that: The multiphysics coupling equations of the dynamic coupling model in step three are as follows: ； in, For the displacement of the support piles, Pore ​​water pressure, For earth pressure, For the horizontal displacement of the support piles, Pore ​​water pressure, This is the vertical earth pressure. The internal friction angle of the soil. , is the coupling coefficient.

5. The method for monitoring the quality of foundation pits in building construction projects according to claim 1, characterized in that: The formula for calculating the dynamic threshold in step four is as follows: ； in, As the baseline threshold, This is the excavation depth coefficient. The seepage sensitivity coefficient, For the current excavation duration, is the soil creep time constant.

6. The method for monitoring the quality of foundation pits in building construction according to claim 1, characterized in that: The blockchain evidence storage process in step five includes: Original data is encrypted and hashed → Hash value and timestamp are stored on the chain → Smart contract compares new data hash with on-chain record in real time → Tampering alarm is triggered when inconsistency occurs; Furthermore, the blockchain evidence storage process meets the data traceability requirements of the ISO 19650 standard.

7. A foundation pit quality monitoring system for building construction projects according to any one of claims 1-6, comprising a monitoring system, characterized in that: The monitoring system includes the following modules: Sensing layer: includes support pile inclination gauge, earth pressure cell, water level gauge, and built-in temperature compensated crystal oscillator and UWB positioning module; Analysis layer: includes spatiotemporal alignment unit, soil-structure-water coupled calculation unit, and adaptive threshold calculation unit; Decision-making level: Configure a Level III response module to execute Level I audible and visual alarms and construction suspension, Level II SMS notifications, and Level III platform marking; Blockchain evidence storage module: Stores raw sensor data and calibration record hashes, and uses smart contracts to provide real-time alerts for data tampering.

8. The foundation pit quality monitoring system for building construction according to claim 7, characterized in that: The soil-structure-water coupling calculation unit of the analysis layer has a built-in construction stage identification submodule. It automatically switches the weight allocation scheme by excavation depth and dewatering rate, and calls the finite element solver to calculate the coupling equations. The solution error range is ≤ ±0.5mm.

9. A foundation pit quality monitoring system for building construction according to claim 8, characterized in that: The reference station of the sensing layer is set in a stable area outside the foundation pit and equipped with a total station prism to calibrate the drift error of the UWB positioning module. The calibration cycle is 24h to 48h, and the positioning accuracy is maintained within the range of ±5cm to ±15cm after calibration.

Images