Grouting construction quality intelligent monitoring method and system

Abstract

The application relates to the technical field of grouting construction, in particular to a grouting construction quality intelligent monitoring method and system, which comprises the following steps: acquiring a grouting pressure signal and a pore water pressure signal, and outputting a stratum action net pressure; synchronously acquiring at least two kinds of slurry state signals of different principles, and outputting anti-interference slurry concentration; judging slurry defects based on the stratum action net pressure, the anti-interference slurry concentration and the acquired grouting flow; constructing a comprehensive evaluation parameter based on the stratum action net pressure, the anti-interference slurry concentration, the slurry defects and the grouting flow, generating a process quality dynamic score; and executing corresponding construction parameter adjustment according to the process quality dynamic score and the type of the slurry defects. The application can solve the problem that monitoring data is distorted due to pore water pressure and underground water dilution, and then the problem that grouting construction quality cannot be accurately and real-timely controlled in a closed loop.

Description

Technical Field

[0001] This application relates to the technical field of grouting construction, and in particular to an intelligent monitoring method and system for grouting construction quality. Background Technology

[0002] Grouting technology is a key process in tunnel and underground engineering construction. Its core lies in reinforcing the surrounding rock and sealing water flow through grout injection to improve the safety and durability of the project. Especially in adverse geological conditions such as silty clay and water-rich fractured zones, accurate monitoring and quality control of grouting construction are crucial. Traditional monitoring methods rely heavily on limited manual point measurements and experience-based judgment, making it difficult to achieve real-time and comprehensive perception of the construction process. Furthermore, they cannot dynamically track and quantitatively evaluate key parameters such as grout diffusion, pressure distribution, and ground response, thus limiting the reliability of grouting effects and the ability to control engineering risks.

[0003] To improve the monitoring level of the grouting process, existing technologies have introduced solutions combining sensors and digital twin technology. For example, Chinese invention patent CN118364534B discloses the deployment criteria and intelligent optimization method and system for grouting construction twin sensors. It proposes a sensor deployment method that incorporates the structural characteristics of the working face, using acoustic and nanosensors, along with fluorescent markers and a dedicated delivery device, to achieve monitoring and data fusion of the grouting process. This technology aims to improve the targeting of sensor deployment and the completeness of data collection, providing a valuable attempt for the digital characterization of the grouting process.

[0004] However, when grouting is carried out in silty clay strata with poor permeability, active pore water pressure, and grout that is easily diluted by groundwater, the existing technical solution reveals a fundamental limitation: its system struggles to acquire highly reliable real-time parameters that truly and directly reflect the key interaction between the grout and the stratum. Specifically, this solution focuses on expanding the data acquisition coverage through optimized deployment, but fails to fully consider the fundamental interference caused by dynamic changes in the stratum on the sensor readings themselves. During grouting, fluctuations in pore water pressure are superimposed on the grouting pressure sensor readings in real time, resulting in the measured pressure value not being the net pressure of the grout acting on the soil skeleton; simultaneously, the mixing of groundwater alters the physicochemical properties of the grout, causing the concentration values ​​read by optical, conductivity, and other concentration sensors to deviate from the actual concentration of the grout itself. Due to the lack of an effective mechanism for real-time stripping and compensation of such dynamic interference, the pressure and concentration data collected and fused by the system are essentially superficial data containing multiple coupled interferences, rather than true parameters that can be used to accurately determine the construction status and quality. Based on this systematically biased data, no matter how advanced the subsequent data fusion algorithm or how complex the evaluation model, the identification of defects such as slurry segregation and bleeding will inevitably be delayed and unreliable. Consequently, any decision to adjust construction parameters will lack an accurate basis, making it impossible to form a timely and effective quality control loop. Therefore, the core problem of this existing technology is that in the specific construction scenario where silty clay and groundwater coexist, resulting in strong dynamic interference, its overall architecture cannot guarantee the authenticity and reliability of core monitoring parameters. Consequently, the perception, judgment, and execution of the entire intelligent monitoring system are all based on distorted data. Summary of the Invention

[0005] To address the problem of distorted monitoring data caused by pore water pressure and groundwater dilution, which prevents accurate real-time closed-loop control of grouting construction quality, this application provides an intelligent monitoring method and system for grouting construction quality.

[0006] Firstly, this application provides an intelligent monitoring method for grouting construction quality, which adopts the following technical solution: An intelligent monitoring method for grouting construction quality includes the following steps: The grouting pressure signal and pore water pressure signal are acquired, the friction loss and nozzle reflection loss of the grout along the force transmission path are determined, and the grouting pressure signal is dynamically calibrated by combining the friction loss, nozzle reflection loss and pore water pressure signal to output the net pressure of the formation. At least two initial slurry detection signals based on different principles are acquired simultaneously. The initial slurry detection signals are mapped to corresponding slurry state signals according to a preset non-Newtonian suspension detection model. Based on the formation interference level reflected by one of the slurry state signals, the other slurry state signal is compensated and fused to output an anti-interference slurry concentration. Based on the net pressure of the formation, the concentration of the anti-interference grout, and the obtained grouting flow rate, grout defects are determined in real time through multi-parameter collaborative analysis. A comprehensive evaluation parameter is constructed based on the net pressure of the formation, the concentration of the anti-interference grout, the grout defects, and the grouting flow rate. The weight ratio of each item in the comprehensive evaluation parameter is dynamically adjusted based on the real-time changes of the pore water pressure signal to generate a dynamic score for process quality. Based on the dynamic quality score of the process and the type of grout defect, the corresponding construction parameters are adjusted.

[0007] Optionally, the dynamic calibration further includes: Continuous monitoring of the net pressure acting on the formation; Based on the monitored continuous change characteristics, the working status of the sensors that collect the grouting pressure signal and the pore water pressure signal is determined: When the continuously changing characteristics exceed a preset drift threshold, it is determined to be sensor drift and dynamic compensation is triggered; When the difference between the grouting pressure signal and the pore water pressure signal exceeds a preset abnormal threshold, it is determined to be a sensor malfunction and a fault handling process including redundancy switching is triggered.

[0008] Optionally, the compensation and fusion include: Based on the first type of slurry state signal among the slurry state signals of the at least two principles, the groundwater dilution rate reflecting the degree of formation disturbance is estimated. The second type of slurry state signal among the at least two principles of slurry state signals is reverse-compensated based on the groundwater dilution rate to generate a compensated slurry state signal. Based on the comparison between the groundwater dilution rate and the preset dilution rate threshold, the fusion weights of the first type of slurry state signal and the compensated slurry state signal are dynamically allocated when generating the anti-interference slurry concentration.

[0009] Optionally, the real-time determination of slurry defects through multi-parameter collaborative analysis is based on multi-level logical verification rules, which include: When the change in the concentration of the anti-interference slurry meets the preset primary determination condition, the primary determination is triggered; When the primary determination is triggered, a further joint determination is made as to whether the change characteristics of the formation net pressure or the grouting flow rate exceed a preset correlation change threshold, so as to trigger an intermediate correlation determination. When the intermediate correlation determination is triggered, a final defect confirmation signal is generated based on whether the difference between the inlet slurry concentration and the outlet slurry concentration exceeds a preset concentration difference confirmation threshold. The final defect confirmation signal distinguishes between separation defects and bleeding defects based on the concentration change direction that triggered the primary determination.

[0010] Optionally, the primary determination criteria include: Based on the direction of change in the anti-interference slurry concentration, a primary judgment signal of the corresponding type is triggered. Specifically, when the direction of change is downward and its change characteristics exceed a preset first primary threshold, a primary judgment signal indicating segregation defects is triggered. When the direction of change is upward and its change characteristics exceed a preset second primary threshold, a primary judgment signal indicating a oozing defect is triggered.

[0011] Optionally, the dynamic adjustment of the weighting of each item in the comprehensive evaluation parameters based on the real-time changes in the pore water pressure signal includes: Monitor the real-time variation characteristics of the pore water pressure signal and compare it with a preset formation state threshold; Based on the comparison results, the level of formation disturbance was determined; Based on the formation disturbance level, a weight adjustment instruction is generated, which is used to adjust the weight corresponding to the net pressure stability of formation action in the comprehensive evaluation parameters.

[0012] Optionally, after adjusting the corresponding construction parameters, a formation condition self-adaptation step is also included: Based on the slurry state signals according to the above at least two principles, a first evaluation index characterizing the reduction in the degree of formation disturbance is extracted. Based on the pore water pressure signal, a second evaluation index characterizing the release of formation pore water pressure is extracted. When the first evaluation index and the second evaluation index reach their respective optimization thresholds, the self-adaptation logic is activated. The self-adaptive logic is configured to execute simultaneously: progressively redirecting construction parameters to preset benchmark parameters, and restoring the weights of each item in the comprehensive evaluation parameters to preset benchmark weights.

[0013] Optionally, after initiating the self-adaptive logic, the process also includes effect verification and adaptive iteration steps: During the preset verification period, monitor the changes in the first evaluation indicator and the second evaluation indicator; When it is detected that the change of at least one of the evaluation indicators has not reached the corresponding expected optimization threshold, the enhanced adjustment of the construction parameters is triggered. If, after the enhancement and adjustment, the change in at least one evaluation indicator still does not reach the expected optimization threshold, then decision support information for requesting human intervention is generated. The decision support information includes at least key data trends, parameter adjustment history, and a list of items to be verified.

[0014] Optionally, the step of progressively redirecting the construction parameters to preset benchmark parameters is further configured as follows: The rate of the gradual callback is dynamically determined based on the improvement rate of the first evaluation index and the second evaluation index during the verification period. Based on the type of grout defect currently occurring, determine the priority callback item for the construction parameters; The priority callback items include: for segregation defects, priority callback of grouting flow rate; for bleeding defects, priority callback of grout water-cement ratio.

[0015] Secondly, the intelligent monitoring system for grouting construction quality provided in this application adopts the following technical solution: An intelligent monitoring system for grouting construction quality includes: The sensor array is configured to acquire grouting pressure signals, pore water pressure signals, initial grout detection signals based on at least two principles, and grouting flow rate; The processing control unit, connected to the sensor array, is configured to: receive signals from the sensor array; determine the friction loss and orifice reflection loss of the grout along the force transmission path, and dynamically calibrate the grouting pressure signal by combining the friction loss, the orifice reflection loss, and the pore water pressure signal, and output the net pressure of the formation; map the initial grout detection signal to grout state signals based on at least two principles according to a preset non-Newtonian suspension detection model, and perform compensation and fusion, outputting the anti-interference grout concentration; determine grout defects in real time through multi-parameter collaborative analysis based on the net pressure of the formation, the anti-interference grout concentration, and the grouting flow rate; construct comprehensive evaluation parameters based on the net pressure of the formation, the anti-interference grout concentration, the grout defects, and the grouting flow rate, and dynamically adjust the weight ratio of each item in the comprehensive evaluation parameters based on the real-time changes of the pore water pressure signal to generate a dynamic process quality score; and generate construction parameter adjustment instructions based on the dynamic process quality score and the type of grout defects. The parameter execution unit, connected to the processing control unit, is used to receive and execute the construction parameter adjustment instructions to adjust the grouting construction parameters.

[0016] In summary, this application includes the following beneficial technical effects: 1. This application uses dynamic calibration of grouting pressure signals to eliminate interference from pore water pressure and integrates grout state signals based on at least two principles to resist the effects of groundwater dilution. This allows for the acquisition of accurate and reliable net pressure of formation action and anti-interference grout concentration, effectively solving the core problem of data distortion caused by pore water pressure and groundwater dilution. This lays a solid foundation for achieving precise real-time closed-loop control of grouting construction quality.

[0017] 2. This application uses multi-parameter collaborative analysis based on formation net pressure, anti-interference grout concentration and grouting flow rate, and uses multi-level logical verification rules to determine grout segregation or bleeding defects in real time, which significantly improves the accuracy and timeliness of defect identification and avoids the problems of lag and high false alarm rate of traditional single index judgment.

[0018] 3. This application constructs a comprehensive evaluation system that can dynamically adjust weights according to changes in pore water pressure, generates a dynamic score for process quality, and performs targeted adjustments to construction parameters based on the score and defect type. At the same time, it introduces formation state self-adaptation logic to realize the gradual callback and weight restoration of construction parameters, thereby ensuring grouting quality while dynamically adapting to formation changes, improving construction efficiency and system self-adaptability. Attached Figure Description

[0019] Figure 1 This is a logical flowchart of the monitoring method; Figure 2 This is an architecture diagram of the monitoring system. Detailed Implementation

[0020] The following is in conjunction with the appendix Figure 1-2 This application will be described in further detail.

[0021] This application discloses an intelligent monitoring method for grouting construction quality. For example... Figure 1 As shown, an intelligent monitoring method for grouting construction quality is specifically designed for complex strata where silty clay and groundwater coexist. This method addresses the technical challenges of grouting pressure being affected by pore water pressure, grout concentration being diluted by groundwater leading to distorted monitoring data, and consequently, the inability to identify grout segregation / bleeding defects in real time and the difficulty in dynamically optimizing construction parameters. The following steps provide a detailed explanation: S1 Sensor Deployment and Initial Calibration This step involves the targeted deployment of multiple types of sensors and the completion of systematic initial calibration. This lays a solid foundation for the subsequent accurate acquisition of grouting pressure signals, pore water pressure signals, grout state signals, and grouting flow rates. It ensures that the initial data can accurately reflect the construction conditions and provides reliable data support for subsequent core processes such as dynamic calibration and signal compensation. This approach avoids data distortion caused by improper sensor deployment or initial deviations from the outset.

[0022] S11 sensor array deployment Considering the geological characteristics of silty clay, such as poor permeability, active pore water pressure, and slurry susceptibility to groundwater dilution, sensors are deployed in an orderly manner according to the following logic to form a complementary sensor array: A piezoresistive pressure sensor is installed at the grout inlet of the grouting pipe. This location can directly capture the pressure data at the moment of grouting, without being affected by pressure loss during grout transmission. This ensures the directness and authenticity of the grouting pressure signal acquisition to the greatest extent, providing accurate raw pressure data for subsequent stripping of pore water pressure interference.

[0023] A pore water pressure sensor was installed in the stratum 1 meter away from the grouting pipe. This distance was determined through multiple field tests and optimizations. It can accurately capture real-time changes in pore water pressure in the stratum, while avoiding physical damage to the sensor caused by direct impact during grouting pipe construction. This ensures the stability of pore water pressure signal acquisition and provides key reference data for the dynamic calibration of grouting pressure signals.

[0024] An optical concentration sensor, a conductivity concentration sensor, and a temperature sensor are installed in the middle section of the grouting pipe. The advantage of this middle section location is that it avoids concentration fluctuations caused by insufficient mixing of the grout at the inlet and reduces detection deviations caused by formation feedback interference with the outlet grout, thus achieving stable acquisition of grout status. The optical and conductivity sensors, based on different detection principles, can complement each other's data, while the temperature sensor corrects for the impact of temperature changes on concentration detection. The three sensors work together to provide multi-dimensional data support for subsequent calculations of the anti-interference grout concentration.

[0025] An electromagnetic flowmeter is installed next to the grout inlet of the grouting pipe. This installation location, close to the grouting pressure sensor, ensures the time synchronization of the grouting flow rate signal and the grouting pressure signal, avoiding deviations in subsequent multi-parameter collaborative analysis due to asynchronous data acquisition, and providing time-matched flow data for defect determination.

[0026] S12 sensor initial calibration Before the official commencement of construction, initial calibration was completed according to sensor function categories. The calibration process strictly followed engineering testing standards to ensure that the sensor acquisition accuracy met the requirements of subsequent analysis. The specific operations are as follows: The piezoresistive pressure sensor was calibrated. A 0.01-grade standard pressure source was selected for zero-point calibration. This accuracy level of the standard pressure source can meet the requirements for accurate acquisition of pressure signals in silty clay and groundwater formations, avoiding calibration deviations caused by insufficient accuracy of the standard source. Three standard pressure values—0 MPa, 0.5 MPa, and 1.0 MPa—were sequentially output from the standard pressure source. These three values ​​cover the conventional pressure range for grouting construction in this formation. The corresponding sensor readings were recorded, and the sensor zero-point parameters were adjusted successively until the error between the sensor reading and the standard pressure value was controlled within ±0.5%. This error threshold comprehensively considers the formation pressure fluctuation range and the compensation capability of subsequent dynamic calibration, ensuring the accuracy of the initial data without increasing the difficulty of on-site implementation due to excessively high requirements.

[0027] Calibrate the pore water pressure sensor. After starting the pore water pressure sensor, continuously acquire initial formation pore water pressure data three times at 1-minute intervals. The 1-minute interval is chosen to reduce random errors from a single acquisition; three acquisitions effectively filter out random interference. The arithmetic mean of the three data points is taken as the initial pore water pressure reference value (denoted as ). This benchmark value is crucial for understanding the interference of initial pore water pressure on grouting pressure signals during subsequent stripping, and its reliability directly affects the accuracy of calculating net pressure from formation action.

[0028] Calibrate the optical and conductivity concentration sensors. Prepare a standard grout with the same concentration as the design grout (denoted as...). Dimensions: g / cm 3 The concentration value of the standard grout serves as a reference for concentration detection, ensuring that the calibration process matches the actual construction conditions. The standard grout is brought into full contact with the detection ends of both sensors, and the sensor sensitivity parameters are adjusted until the errors between the readings of both sensors and the standard grout concentration value do not exceed ±1%. This error threshold is determined based on the degree of influence of grout concentration changes on defect judgment; only by controlling it within this range can the accuracy of subsequent anti-interference grout concentration calculations be guaranteed, meeting the requirements for defect identification.

[0029] Calibrate the electromagnetic flowmeter. Calibration is performed using the standard volume method. A standard container of known volume is selected and its volume value is recorded. The grout is controlled to flow through the flowmeter at a stable velocity. Simultaneously, grout is collected in the standard container for a fixed period of time. The actual flow rate is calculated using the container volume and collection time. Adjust the flowmeter parameters until the error between the flow rate displayed by the flowmeter and the actual flow rate does not exceed ±2%. This error threshold comprehensively considers the normal fluctuation range of flow rate during grouting construction and the accuracy requirements of multi-parameter collaborative analysis for flow data, ensuring the reliability of flow signal acquisition and providing accurate flow parameters for defect identification.

[0030] S2 Formation Net Pressure Dynamic Calibration This step closely follows the sensor deployment and initial calibration results of S1. By acquiring pressure signals in real time, performing dynamic calibration calculations, and continuously monitoring the sensor's working status, it accurately eliminates the interference of pore water pressure on the grouting pressure signal, obtains net pressure data that truly reflects the grout's effect on the formation soil skeleton, and ensures the continuity and reliability of sensor operation, providing accurate and stable pressure parameter support for subsequent grout defect determination.

[0031] S21 Real-time Pressure Signal Acquisition After the grouting operation is started, the grouting pressure signal from the piezoresistive pressure sensor is synchronously acquired at a frequency of 3 minutes per acquisition (denoted as grouting pressure signal). (dimensions in MPa) and the pore water pressure signal from the pore water pressure sensor (denoted as ). (Dimension: MPa). The sampling frequency was set through extensive field testing, perfectly matching the 2-3 minute variation cycle of pore water pressure in silty clay formations. This ensures the complete capture of the dynamic fluctuations in the pressure signal without increasing the data processing load due to excessively frequent sampling, effectively guaranteeing the timeliness and completeness of the pressure data. During the sampling process, a synchronous triggering mechanism ensures that the signal acquisition times of the two sensors are completely consistent, thoroughly eliminating the interference of time differences on subsequent calibration calculations.

[0032] Calculation of net pressure acting on the S22 formation The grouting pressure sensor is installed at the grout inlet. The grouting pressure signal it collects is significantly affected by non-Newtonian fluid characteristics during transmission to the formation soil skeleton, resulting in substantial force transmission path loss and interference from the superimposed pore water pressure. Direct use of this data leads to data distortion and fails to reflect the true effect of the grout on the formation. Based on the initial pore water pressure benchmark value... Combining the friction loss along the slurry and the reflection loss at the nozzle, the formula for calculating the net pressure acting on the formation is derived: set up This represents the real-time measured value (MPa) from the grouting pressure sensor. This is the real-time value (MPa) collected by the pore water pressure sensor. The initial pore water pressure reference value (MPa); The Bingham fluid flow calculation model is introduced to calculate the friction loss (denoted as ) along the pipe based on the real-time grouting flow rate and the geometric parameters of the grouting pipeline. (dimensions in MPa), and the pipe outlet reflection loss coefficient is set according to the abrupt change characteristics of the grouting pipe outlet cross section. Calculate the reflection loss at the nozzle. ; The change in real-time pore water pressure relative to the initial state is ( This change is the dynamic interference value superimposed on the grouting pressure signal, with the dimension MPa; Furthermore, the solution for the net pressure of the formation action in this application is based on the Terzaghi effective stress principle, and its applicable conditions are limited to: the grouting target formation is in a state of groundwater saturation, and the formation pore connectivity allows for the instantaneous transmission and response of pore water pressure signals.

[0033] Under these conditions, by successively subtracting friction loss, nozzle reflection loss, and dynamic interference values ​​of pore water pressure from the grouting pressure signal, the net ground pressure acting on the soil skeleton on the same mechanically closed surface (denoted as ) is obtained. (dimensions in MPa), the calculation formula is: .

[0034] This formula compensates for the hydrodynamic attenuation along the force transmission path and eliminates interference from pore water pressure, thereby improving the mechanical rationality and reliability of the pressure data.

[0035] S23 Sensor Operating Status Determination and Handling The calculated net pressure of the formation Continuous monitoring is conducted to indirectly determine the operating status of piezoresistive pressure sensors and pore water pressure sensors by analyzing their changing characteristics, enabling timely handling of drift or malfunction issues and ensuring continuous and reliable data acquisition. A drift threshold of 3% was set. In silty clay strata, the sensor is affected by environmental factors such as temperature fluctuations and changes in pore water pressure, resulting in slight drift. Statistically, this drift range usually does not exceed 3%, therefore 3% was set as the drift threshold. When two adjacent data acquisitions... Difference compared to the previous When the ratio exceeds 3%, it is determined to be sensor drift. At this time, the dynamic compensation process is immediately triggered, calling the temperature-pore water pressure compensation algorithm. The current ambient temperature and pore water pressure change are input, and the zero-point parameters of the piezoresistive sensor are adjusted accordingly to quickly correct the reading deviation and ensure the accuracy of the pressure data. The abnormal threshold is set at 10%. During normal construction, the difference between the grouting pressure signal and the pore water pressure signal should be within a relatively stable range. Considering the construction characteristics of silty clay and groundwater strata, when ( )and When the ratio exceeds 10%, it falls outside the reasonable difference range and is judged as a sensor malfunction. At this time, the fault handling procedure is triggered. First, high-pressure air is used to purge the sensor probe to clear blockages. After clearing the blockages, data is collected again after an interval of 1 minute. If the data is still within the abnormal range, the system automatically switches to the backup sensor to ensure uninterrupted pressure data acquisition and provide continuous support for subsequent monitoring work.

[0036] S3 Anti-interference slurry concentration compensation and fusion This step closely follows the pressure signal acquisition rhythm of S2. Relying on the optical concentration sensor, conductivity concentration sensor and temperature sensor that have been calibrated in S1, it systematically eliminates the interference of groundwater dilution on slurry concentration detection by synchronously acquiring multi-dimensional state signals of slurry, accurately estimating groundwater dilution rate, reverse compensating for concentration deviation, and dynamically fusing multi-source data. Finally, it obtains an anti-interference slurry concentration that can truly reflect the physicochemical properties of the slurry itself, providing reliable concentration parameter support for the accurate determination of subsequent slurry defects.

[0037] S31 slurry status signal synchronous acquisition During grouting, the optical concentration signal from the optical concentration sensor (denoted as ) is simultaneously acquired at a frequency of 3 minutes / time, consistent with the S2 pressure signal acquisition. Dimensions: g / cm 3 ), the conductivity concentration signal of the conductivity-type concentration sensor (denoted as ), Dimensions: g / cm 3 ) and the slurry temperature signal from the temperature sensor (denoted as ) (Dimension: °C). This synchronous acquisition strategy is not simply about unifying the frequency, but rather about ensuring that the concentration and pressure signals are completely aligned in the time dimension, thus removing time synchronization obstacles for subsequent multi-parameter collaborative analysis. A frequency of 3 minutes per acquisition has been verified through extensive field tests. This approach can fully capture the dynamic characteristics of slurry concentration changes in silty clay strata due to groundwater disturbance, while avoiding data redundancy and increased processing load caused by overly frequent acquisitions, achieving a balance between data acquisition efficiency and effectiveness.

[0038] S32 Groundwater Dilution Rate Estimation First, based on the calibration equations for conductivity and solid content, the initial detection signal acquired by the conductivity sensor is mapped, and temperature compensation is performed. Cement slurry, as a non-Newtonian suspension containing solids, has its calibration equations pre-established:

[0039] in This is the real-time conductivity measurement value output by the sensor. For calibration constants, The mapped reference conductivity concentration signal (dimensions g / cm) 3 ).

[0040] Then, the slurry temperature was utilized. (°C) Temperature compensation is performed. The detection values ​​of the conductivity sensor show a significant correlation with the grout temperature, determined by the temperature effect of the electrolyte solution's conductivity. Within the grouting temperature range (10℃-40℃) of silty clay and groundwater strata, the temperature coefficient of conductivity... Approximately 2% / ℃. Based on a standard reference temperature of 25℃, a linear compensation model is adopted:

[0041] Will Substituting the values, the calculation formula is:

[0042] After calibration and compensation, the impact of the environment on the test results can be controlled within ±1.5%, providing a reliable data basis for subsequent dilution rate estimation.

[0043] Based on the compensated true conductivity concentration With known initial slurry concentration Estimate the groundwater dilution rate (denoted as ). (dimensionless) When groundwater mixes with the slurry, it dilutes the concentration of electrolytes, leading to... Below The difference between the two directly reflects the degree of groundwater dilution; groundwater dilution rate The value range is 0-1, and the calculation formula is:

[0044] This estimation method is based on a well-defined solids content calibration equation, which quantifies the impact of formation disturbances on slurry concentration.

[0045] S33 Optical Concentration Signal Reverse Compensation After the optical concentration sensor acquires the initial optical signal, a Mie scattering correction model is pre-introduced to map the light intensity attenuation for non-Newtonian suspension particle distribution to the optical concentration signal. Mapped optical concentration signal Also affected by groundwater dilution, the measured values ​​only reflect the apparent concentration of the diluted slurry and cannot be directly used for defect determination. They must be based on the estimated groundwater dilution rate. Perform reverse compensation: The core logic of dilution is: concentration after dilution = true concentration × (1 - dilution rate), therefore, true concentration = concentration after dilution / (1 - dilution rate). The compensated optical concentration (denoted as) is derived. Dimensions: g / cm 3 The calculation formula is:

[0046] The method of introducing an optical scattering model and performing reverse compensation can effectively restore the true concentration of slurry undisturbed by groundwater. The deviation between the compensated data and the actual concentration can be controlled within 5%, thus improving the reliability of the optical concentration signal.

[0047] S34 concentration signal dynamic fusion The preset dilution rate threshold is 10%, which is based on a large amount of field test data. When the groundwater dilution rate is less than 10%, the groundwater interference is less severe, the optical concentration sensor is more sensitive to the distribution of slurry particles, and the data stability and accuracy are better. When the dilution rate is higher than or equal to 10%, the groundwater interference is significantly enhanced, and the conductivity concentration sensor has better anti-interference ability and data stability after temperature compensation.

[0048] Based on groundwater dilution rate The results of comparison with the dilution rate threshold are dynamically allocated. and The fusion weight is used to generate the anti-interference slurry concentration (denoted as ). Dimensions: g / cm 3 ): when When <10%, assign A weight of 0.6 is assigned to With a weight of 0.4, the fusion formula is as follows: ; when When ≥10%, assign A weight of 0.5 is assigned to With a weight of 0.5, the fusion formula is as follows: ; This dynamic weight allocation strategy overcomes the limitations of traditional single-sensor or fixed-weight fusion methods. It automatically selects the most reliable data source based on the degree of groundwater interference, fully leveraging the complementary advantages of two sensors with different detection principles. Experimental results show that the final anti-interference slurry concentration detection accuracy is improved by more than 15% compared to a single sensor, effectively solving the industry pain point of slurry concentration detection in silty clay and groundwater strata being easily affected by dilution interference.

[0049] S4 Slurry Defect Multi-Parameter Collaborative Judgment This step deeply integrates the net formation pressure output by S2. The concentration of the anti-interference slurry generated by S3 The grouting flow data collected by S1, through a three-level progressive logic verification rule, enables real-time and accurate determination of grout segregation and bleeding defects. This overcomes the problems of lag and high false alarm rate in traditional single-indicator determination, and provides clear and reliable defect basis for targeted adjustment of subsequent construction parameters.

[0050] S41 Grouting Flow Data Preprocessing The grouting flow signal collected by the electromagnetic flowmeter in S1 (denoted as...) The readings (in L / min) are pre-processed to filter out abnormal values ​​caused by momentary equipment vibration. In complex construction environments involving silty clay and groundwater strata, electromagnetic flowmeters are susceptible to pipeline vibration and uneven slurry flow, resulting in momentary abnormal readings that do not match the actual construction conditions. Directly using these readings for defect determination would severely interfere with the accuracy of the results.

[0051] The preprocessing standard has been determined through extensive field testing: when a single data collection... With the three adjacent data collections When the difference between the average and average values ​​exceeds 10%, the data is considered an outlier. 10% was chosen as the criterion because the normal fluctuation range of flow rate during grouting in this formation is statistically no more than 8%. The 10% threshold effectively filters out outlier data caused by equipment vibration without mistakenly deleting normal flow rate fluctuation data. Outlier data is handled by comparing three consecutive data acquisitions. The average value is used to replace the outlier. This smoothing process ensures the stability and reliability of the grouting flow rate data, providing high-quality flow parameter support for subsequent intermediate correlation determination.

[0052] S42 Initial Judgment Trigger Anti-interference slurry concentration obtained based on S3 The changing characteristics are used to set initial judgment conditions, accurately capturing the initial signals of slurry defects. The core characteristic of slurry segregation is the rapid settling of solid particles, which leads to... A continuous decline; the core characteristic of slurry bleeding is the rapid precipitation of water, which leads to... These two characteristics, both of which are continuously rising, are key to distinguishing defects from normal concentration fluctuations.

[0053] The first primary threshold was set at 6% / min. This threshold was derived from a large amount of field test data: in silty clay and groundwater strata, when substantial segregation of the grout occurs, The relative decrease rate is usually not less than 6% / min. A decrease in concentration below this rate is generally a normal homogenization process of the slurry and will not lead to segregation defects. The formula for calculating the relative decrease rate is: Relative decrease rate = [(previous decrease rate)] / [min]. -current ) / Previous [×100% / time interval, where the time interval is the acquisition interval of 3 minutes. When the relative decrease rate is ≥6% / min, the system triggers a primary judgment signal indicating segregation defects.]

[0054] The second primary threshold was set at 4% (per 10-minute intervals). This threshold was also based on field test results: when slurry bleeds, water separation causes... The concentration shows a clear upward trend within 10 minutes, and the increase is usually not less than 4%. Increases below this range are mostly due to redistribution of moisture within the slurry and do not constitute bleeding defects. The formula for calculating the increase range is: Increase Range = (Current Concentration + Increase Rate) / Increase Rate. -10min ago ) / 10min ago ×100%, when the increase is ≥4%, the system triggers a primary judgment signal indicating a bleeding defect.

[0055] S43 Intermediate Association Decision After the primary determination signal is triggered, it is further combined with S2. Or the grouting flow rate after S41 pretreatment By analyzing the changing characteristics, intermediate-level correlation judgments are performed to effectively filter out false trigger signals from primary judgments and improve the rigor of defect judgment.

[0056] set up The fluctuation threshold is 12%. The logic behind setting this threshold is that slurry segregation leads to uneven particle distribution, which in turn causes unstable grouting pressure transmission and triggers... Fluctuations, under normal construction conditions The fluctuation range is statistically determined to be no more than 12%. A range exceeding this is strongly correlated with segregation defects. The formula for calculating the fluctuation range is: Fluctuation Range = (Last 5 fluctuations) / (The fluctuation range of the last 5 fluctuations in the segregation rate). Maximum value - last 5 times (Minimum value) / Last 5 times The average value is multiplied by 100%. When the primary signal of segregation defect is triggered and the fluctuation range is ≥12%, the intermediate correlation judgment signal is triggered.

[0057] set up The reduction rate threshold is 5%. The logic behind setting this threshold is that grout bleeding leads to a reduction in the effective grouting volume, directly causing... Descending, under normal construction conditions The natural reduction rate should not exceed 5%; if it exceeds this range, it is highly likely related to urination defects. The formula for calculating the reduction rate is: Reduction rate = (Initial...) -current ) / initial ×100%, when the primary signal of oozing defect is triggered and the reduction rate is ≥5%, the intermediate correlation judgment signal is triggered.

[0058] This multi-parameter correlation verification method breaks through the limitations of traditional single concentration index judgment and significantly reduces the probability of misjudgment caused by accidental factors.

[0059] S44 Final Defect Confirmation An S12-calibrated optical concentration sensor is deployed at the outlet of the grouting pipe to collect the outlet slurry concentration (denoted as ). Dimensions: g / cm 3 ), and use the S3 compensation and fusion method to process This ensures the consistency and accuracy of outlet concentration data with inlet concentration data, providing a reliable basis for comparing inlet and outlet concentrations.

[0060] The concentration difference confirmation threshold is set at 8%. This threshold is based on engineering practice: during normal construction, the grout will experience slight concentration changes due to minor adsorption and penetration during transport, but the concentration difference between the inlet and outlet usually does not exceed 8%. Exceeding this threshold indicates a significant change in the grout composition, constituting a substantial defect. The formula for calculating the concentration difference is: Concentration Difference = |Current... -After processing Current ×100%, when the intermediate correlation determination signal is triggered, the concentration difference is calculated.

[0061] If the concentration difference is ≥8% and the initial judgment signal is a segregation defect, a final confirmation signal for the segregation defect is generated; if the concentration difference is ≥8% and the initial judgment signal is a bleeding defect, a final confirmation signal for the bleeding defect is generated. Through the final verification of the inlet real-time anti-interference concentration and the outlet concentration, a three-level logical closed loop of "initial capture - intermediate correlation - final confirmation" is completed, ensuring the accuracy of defect judgment and providing a clear basis for subsequent adjustments to construction parameters.

[0062] S5 Process Quality Dynamic Scoring This step deeply integrates the net formation pressure output by S2. The concentration of the anti-interference slurry generated by S3 The results of grout defect determination by S4 and the grouting flow rate collected by S1 The data is used to construct a comprehensive evaluation parameter system covering the core dimensions of quality. By dynamically adjusting the weights of various indicators in conjunction with real-time changes in pore water pressure, a dynamic process quality score that fits the actual working conditions of the formation is generated, providing a quantitative and accurate quality basis for subsequent adjustments to construction parameters.

[0063] S51 Comprehensive Evaluation Parameter Construction A comprehensive evaluation parameter system comprising four core indicators was constructed. The initial weights of each indicator were determined based on the importance analysis of construction quality influencing factors in silty clay and groundwater strata, ensuring that the evaluation is comprehensive and closely aligned with the specific requirements of the scenario. The stability of net pressure on the formation is initially weighted at 35%. This indicator directly determines the effectiveness of the grout on the formation and is the core of ensuring the compactness of the grout. In complex formations with active pore water pressure, whether the pressure is stable or not directly affects the diffusion and filling effect of the grout, so it is given the highest weight. The consistency of grout concentration is evaluated against interference, with an initial weight of 30%. Concentration stability is directly related to the strength and durability of the grout after solidification. Groundwater dilution can easily lead to concentration fluctuations. This indicator can accurately reflect the stability of the grout's inherent properties and is crucial for quality control. Grout defect incidence rate, initial weight 25%. Segregation and bleeding defects directly damage the grout structure and reduce the integrity of the grout body. In silty clay, these defects are easily aggravated by particle sedimentation and water exudation, and need to be focused on control, so they are given a higher weight. Grouting flow uniformity, with an initial weight of 10%. Flow uniformity affects the grout diffusion range and filling uniformity, and is an important indicator to help ensure grouting quality. Its influence is relatively weaker than the first three items, so its weight is relatively low but indispensable.

[0064] The four indicators have a total weight of 100%, comprehensively covering the core dimensions that affect the quality of grouting construction. They highlight key points while taking into account the overall situation, ensuring the scientific and targeted nature of the evaluation.

[0065] S52 Stratigraphic Disturbance Level Classification Continuous monitoring of pore water pressure sensor data in S1 Combine it with the one determined by S12 A comparison was conducted, and the formation disturbance levels were classified based on the comparison results. The preset formation state thresholds were determined based on a large number of field tests. When the formation disturbance coefficient is ≤10%, it is judged as a low-disturbance formation. The formula for calculating the formation disturbance coefficient is: At this point, the formation pore water pressure changes gradually, the formation condition is stable, there is no obvious risk of deformation, and the quality evaluation can maintain the conventional weight. When 10% < formation disturbance coefficient ≤ 30%, it is judged as a medium-level disturbance in the formation. At this time, the formation is affected by grouting and fluctuates to a certain extent, but it is still within a controllable range. The evaluation weight of pressure stability needs to be appropriately increased. When the formation disturbance coefficient exceeds 30%, it is classified as a high-disturbance formation. The pore water pressure change corresponding to this coefficient is close to the bearing capacity limit of the silty clay formation, and the formation faces the risk of deformation. Pressure stability becomes the primary objective of quality control.

[0066] By quantifying the degree of formation disturbance through changes in pore water pressure, an intuitive and quantifiable basis is provided for subsequent dynamic adjustment of weights, enabling quality assessment to adapt to changes in formation condition in real time.

[0067] S53 weight dynamic adjustment Based on the formation disturbance levels classified in S52, a weight adjustment instruction is generated, focusing on adjusting the weight of the net pressure stability of formation action in the comprehensive evaluation parameters. The weights of other indicators are reduced synchronously according to their original proportions to ensure that the sum of the weights of the four indicators is always 100%. When the formation is at a low disturbance level, the initial weight for maintaining the net pressure stability of the formation is 35%, and the weights of various indicators remain unchanged, which meets the quality evaluation requirements when the formation is stable. When the formation is at a medium level of disturbance, the weight of net pressure stability of the formation is adjusted to 38%. By appropriately increasing the weight of this indicator, the evaluation weight of pressure stability is enhanced, guiding subsequent parameter adjustments to focus on pressure control. When the formation is under high disturbance, the weight of net pressure stability of the formation is adjusted to 40%. At this time, the formation faces the risk of deformation, and pressure stability becomes the core of ensuring quality. Its importance is highlighted by giving it the highest weight, ensuring that the quality score can accurately reflect the key control objectives.

[0068] This dynamic weight adjustment strategy breaks through the limitations of traditional fixed-weight evaluation, enabling the quality score to adapt to changes in formation conditions in real time. It solves the problem of the traditional evaluation method being out of touch with the actual working conditions of complex formations, and improves the objectivity and pertinence of the evaluation.

[0069] S54 Dynamic Scoring Calculation The process quality dynamic score is calculated at a frequency of 2 minutes per calculation, with a full score of 100 points. This frequency can capture changes in construction quality in a timely manner without causing data redundancy due to excessive frequency. The scoring calculation methods for each indicator are as follows: Formation net pressure stability: calculation within the last 5 minutes The standard deviation, and the average deviation within the last 5 minutes. The full score for the current weight is obtained if the ratio of the average value to the average value is ≤2%. The 2% threshold is determined based on the pressure fluctuation range during normal construction in this formation. Exceeding this ratio indicates insufficient pressure stability. For every 1% exceeding this value, 1 / 7 of the current weight score is deducted (e.g., when the current weight is 35%, 5 points are deducted for every 1% exceeding this value), ensuring that the deduction gradient is reasonable and can accurately reflect the impact of pressure fluctuations on quality. Anti-interference slurry concentration consistency: calculation and The difference accounts for The percentage is ≤5%, and 30 points are awarded. The 5% threshold takes into account the concentration fluctuation range of slight groundwater disturbance and normal homogenization process of slurry. 4 points are deducted for each 1% exceeding the threshold, which strictly controls the concentration deviation while avoiding excessive criticism of normal fluctuations. Grout defect incidence rate: The number of grout defects occurring in the past 10 minutes is counted, with 0 defects scoring 25 points. The 10-minute statistical period balances defect response speed and evaluation stability. Each additional defect deducts 12 points, and the higher deduction rate strengthens defect control and guides timely handling of potential quality problems. Grouting flow uniformity: Calculated within the last 5 minutes The coefficient of variation (the ratio of standard deviation to mean) is used to calculate the variability. A coefficient of variation ≤ 5% earns 10 points. The 5% threshold is within the normal fluctuation range of grouting flow rate for this formation. For every 1% exceeding this threshold, 2 points are deducted to ensure that the impact of flow rate uniformity on quality can be reasonably quantified.

[0070] After each scoring calculation is completed, the scoring results are updated in real time to ensure that the output quality status can reflect the changes in construction in a timely manner, providing the latest and most accurate quantitative basis for subsequent adjustments to construction parameters.

[0071] S6 Construction Parameter Adjustment and Formation Self-Adaptation This step closely integrates the dynamic quality scoring of S5 with the grout defect judgment results of S4. It implements targeted adjustments to construction parameters for different quality risk levels, and forms a complete closed loop through quantitative assessment of formation conditions, self-adaptive logic, and effect verification. This ensures continuous optimization of grouting quality and dynamic adaptation to changes in formation conditions, balancing construction quality and efficiency.

[0072] S61 Adjusts trigger conditions and priorities Based on the dynamic scoring results of S5, the defect confirmation signal of S4, and the formation disturbance level of S52, a three-level adjustment priority is set, and the triggering conditions are clarified to ensure that the adjustment actions are accurately matched with the quality risks: Priority 1 (Severe Risk): When the dynamic score is ≤70 points, or the formation disturbance level is high disturbance, an emergency shutdown and adjustment will be triggered. The threshold of 70 points is determined based on the weight distribution of the four core evaluation indicators and the quality qualification standard. At this time, at least two core indicators are seriously substandard, and there is a major hidden danger to the grouting quality. The high disturbance level corresponds to a formation disturbance coefficient >30%, and the formation faces the risk of deformation. Both require emergency treatment to avoid safety and quality accidents. Priority 2 (General Risk): Automatic parameter adjustment is triggered when 70 points < dynamic score < 80 points, or when a final confirmation signal for slurry defects is generated. This score range indicates that there are obvious hidden quality risks but they do not endanger formation safety. The defect confirmation signal directly indicates that there are substantial problems such as segregation or bleeding in the slurry, and the hidden risks need to be eliminated in time through automatic adjustment. Priority 3 (Optimization Requirement): When 80 points ≤ Dynamic Score < 90 points, progressive parameter optimization is triggered. A score above 80 points indicates that all quality indicators meet the standards. This priority adjustment aims to slightly optimize parameters to improve construction efficiency without affecting quality, and avoids quality fluctuations caused by excessive adjustments.

[0073] S62 parameter adjustment execution at different priorities S621 Priority 1 (Severe Risk) Adjustment Immediately stop the grouting pump and close the main valve of the grouting pipe. This operation can quickly block the backflow of groundwater, prevent the grout from being contaminated or damaged by scaling inside the grouting equipment, and prevent further expansion of quality and safety risks. All pressure and concentration sensors were cleaned with high-pressure air. In complex geological formations, sensor probes are easily clogged by slurry or clay particles. After cleaning, the initial calibration procedure of S12 was repeated to quickly restore the sensor's detection accuracy and provide reliable data support for subsequent adjustments. Grout samples were extracted from the grouting pipe and sent to the on-site laboratory for testing of their actual concentration and segregation rate. The test results were compared with those of S3. The defect judgment results of S4 are compared to verify the accuracy of the monitoring data, providing a direct reference for the precise formulation of subsequent adjustment plans.

[0074] S622 Priority 2 (General Risk) Adjustment Segregation defect adjustment: Prioritize adjusting the grouting flow rate. The formula for calculating the segregation rate is: The adjusted flow rate (denoted as The calculation formula is: . The minimum value is set at 5L / min. This value has been verified by multiple field tests and can effectively prevent the slurry from depositing and clogging in the pipeline due to excessively low flow rate. When the segregation rate is ≥10%, the bentonite content in the slurry is increased from 3% to 5%. The gradient increase in the bentonite content can specifically improve the thixotropy of the slurry, inhibit the sedimentation of solid particles, and alleviate the segregation problem from the root. Bleeding defect adjustment: Prioritize adjusting the water-cement ratio of the slurry. The formula for calculating the bleeding rate is: The adjusted water-cement ratio (denoted as ) The calculation formula is: . The minimum value is set to 0.8. This value can ensure that the grout has sufficient fluidity and avoid bleeding, which will cause the grout to dry and fail to spread evenly. When the bleeding rate is ≥8%, the micro circulation pump is started to pump the bleeding grout in the grouting pipe back to the mixing tank for re-stirring. Each stirring time lasts for 3 minutes. By circulating and stirring, the water distribution of the grout is redistributed evenly, and the bleeding defect is quickly eliminated. Pressure fluctuation adjustment: when When the fluctuation range is ≥12%, open the miniature pressure relief valve located 1.5m around the grouting pipe, and control the release volume to within [a certain range]. Within 10% of the corresponding pore water volume, this release amount has been verified by experiments to effectively relieve pressure without causing formation subsidence; the grouting pump is switched from constant pressure mode to variable pressure mode, the pressure is first reduced by 10%, and then gradually increased at a rate of 0.05MPa / min, and the formation stress is smoothly released through gradient pressure adjustment to reduce pressure fluctuations.

[0075] S623 Priority 3 (Optimization Requirements) Adjustment Based on the current construction parameters and the dynamic score of S5, the grouting flow rate is fine-tuned and optimized. The flow rate is increased by no more than 5% from the current level; this adjustment has been verified through extensive testing and will not affect [the project's performance]. Stability and Consistency; after adjustment, continuous monitoring for 2 minutes. If the dynamic score does not decrease, the adjusted parameters are maintained. If the score decreases, the original parameters are immediately restored to ensure that construction efficiency is maximized while meeting quality standards.

[0076] S63 Formation State Self-Adaptation S631 Evaluation Indicator Extraction Based on the slurry state signal of S3 and the pore water pressure signal of S2, two formation state assessment indicators are extracted to accurately quantify the degree of formation disturbance and pressure release: First assessment indicator: The rate of decrease in groundwater dilution rate (denoted as...) The calculation formula is: , The larger the negative value and the larger the absolute value, the lower the degree of dilution interference of groundwater on the slurry, and the better the compatibility between the formation and the slurry. Second evaluation indicator: Pore water pressure release rate (denoted as...) The calculation formula is: , The larger the value, the more fully the formation pore water pressure is released, and the more stable the formation condition.

[0077] S632 self-adaptive logic startup and execution Preset optimization threshold: ≤-5%, ≥20%. This threshold was determined through field tests. At this point, groundwater dilution disturbance has been significantly reduced, formation pore water pressure has been released to a relatively stable range, formation conditions tend to be stable, and the conditions for parameter self-adaptation are met.

[0078] When both evaluation metrics reach the optimization threshold, the self-adaptive logic is activated, and two operations are performed simultaneously: Gradual pullback of construction parameters: based on and The rate of improvement (average rate of change in the last 5 minutes) is used to dynamically determine the rate of correction. The faster the rate of improvement, the higher the rate of correction. However, the magnitude of each correction does not exceed 10% of the initial benchmark parameter to avoid parameter mutations affecting the grouting quality. The priority correction item is determined according to the type of grout defect that has occurred. For segregation defects, the grouting flow rate is prioritized for correction. For bleeding defects, the water-cement ratio of the grout is prioritized for correction. The construction parameters are gradually corrected back to the preset benchmark parameters. Weight Restoration: The weights of each indicator in the comprehensive evaluation parameters are restored to the initial benchmark weights of S51, so that the quality score returns to the conventional evaluation standard, balances quality control and construction efficiency, and avoids excessive emphasis on a single indicator, which leads to waste of resources.

[0079] S64 Performance Verification and Adaptive Iteration S641 Verification Period Monitoring The preset verification period is 5 minutes. This duration has been experimentally verified to ensure that the grout state and formation response reach a completely stable state after the construction parameters are adjusted. During the verification period, the first evaluation index is continuously monitored. Compared with the second evaluation indicator Changes are recorded synchronously. , Real-time data on core parameters provides a comprehensive basis for judging the adjustment effect.

[0080] S642 Enhanced Adjustment Trigger Preset expected optimization threshold: ≤-8%, ≥25%. When at least one evaluation indicator is detected to have changed below the corresponding expected optimization threshold, a strengthened adjustment to the construction parameters is triggered. Segregation defects: Based on the original adjustments, the grouting flow rate is reduced by an additional 10%, and the bentonite content is increased to 6% to further improve the thixotropy of the grout and enhance the inhibition effect on the settling of solid particles. Bleeding defect: Reduce the water-cement ratio of the slurry to 0.85 and extend the circulation stirring time to 5 minutes to enhance the uniformity of slurry moisture and completely eliminate the risk of bleeding; Pressure fluctuations: Increase the opening degree of the pressure relief valve by 5% and adjust the pressure recovery rate to 0.03 MPa / min to release formation stress more smoothly and stabilize the formation. .

[0081] S643 Human-Assisted Decision Support If, after the adjustments, the change in at least one evaluation indicator still fails to reach the expected optimization threshold, then a decision support message requesting human intervention is generated. This message contains three core parts: Key data trends: within the last 10 minutes , , , The curves show the changes in quality and formation state, with abnormal fluctuation points and corresponding time points marked to visually present the changes in quality and formation state. Parameter adjustment history: The system records in detail the triggering conditions, adjustment time, adjustment parameters, and adjustment range of this adjustment, clearly presenting the adjustment trajectory; List of items to be verified: whether there are unexplored weak interlayers in the strata, whether the grout formula complies with the GB 175-2023 standard for general silicate cement, and whether the sensor has shifted due to vibration of the grouting pipe (shift ≥2cm will affect data accuracy). Clarify the direction of manual verification and improve decision-making efficiency.

[0082] The implementation principle of the intelligent monitoring method for grouting construction quality in this application embodiment is as follows: By dynamically calibrating the grouting pressure signal to remove interference from pore water pressure and integrating grout state signals from at least two principles to resist the dilution effect of groundwater, a true and reliable net pressure of the formation and the anti-interference grout concentration are obtained. Based on this, multi-parameter collaborative analysis and multi-level logical verification are performed in conjunction with the grouting flow rate to achieve accurate real-time judgment of defects such as grout segregation and bleeding. Furthermore, a comprehensive evaluation system that can dynamically adjust weights according to changes in pore water pressure is constructed, generating a dynamic score for process quality. Based on the score and defect type, targeted adjustments to construction parameters are executed, forming a closed-loop control from perception and judgment to execution. This method effectively solves the problem of monitoring data distortion caused by the superposition of pore water pressure and grout dilution in strata where silty clay and groundwater coexist. It achieves accurate, real-time, and adaptive control of grouting construction quality, improving the reliability of grouting technology and the ability to control engineering risks under complex geological conditions.

[0083] This application also discloses an intelligent monitoring system for grouting construction quality. For example... Figure 2 As shown, an intelligent monitoring system for grouting construction quality is used to implement the aforementioned intelligent monitoring method for grouting construction quality. Through the coordinated operation of a sensor array, a processing control unit, and a parameter execution unit, a complete closed loop of "acquisition-processing-execution" is constructed, accurately adapting to the construction needs of complex strata where silty clay and groundwater coexist. The specific implementation is as follows: The sensor array is deployed according to the principle of functional complementarity to ensure accurate acquisition of key parameters: it acquires grouting pressure and pore water pressure signals to provide raw data support for the dynamic calibration of net pressure acting on the formation; it acquires grout state signals and grout temperature signals based on both optical and electrical conductivity principles to meet the compensation and fusion requirements for anti-interference grout concentration; and it acquires grouting flow rate signals to provide flow rate basis for multi-parameter collaborative judgment and construction parameter adjustment. All sensors have undergone initial calibration using the aforementioned methods to ensure the reliability and consistency of the acquired data, laying a solid data foundation for subsequent system processing.

[0084] The processing and control unit, as the core of the system, communicates bidirectionally with the sensor array and sequentially performs the following key operations: receiving various acquired signals; dynamically calibrating the grouting pressure signal based on the pore water pressure signal; removing pore water pressure interference; and outputting the net pressure of the formation action; estimating the groundwater dilution rate based on grout state signals from two principles; dynamically allocating fusion weights after reverse compensation for one type of signal; and outputting the anti-interference grout concentration; combining the net pressure of the formation action, the anti-interference grout concentration, and the grouting flow rate; and using multi-level logical verification rules to determine grout defects such as segregation and bleeding in real time; constructing a comprehensive evaluation parameter system; dynamically adjusting the index weights based on real-time changes in pore water pressure; and generating a dynamic score for process quality; and generating targeted construction parameter adjustment instructions based on the dynamic score and defect type to ensure the accuracy and timeliness of adjustment decisions. This unit, by integrating core functions such as dynamic calibration, multi-source fusion, and intelligent judgment, overcomes the limitations of traditional systems in terms of slow data processing and weak anti-interference capabilities, highlighting the system's intelligent advantages.

[0085] The parameter execution unit is signal-connected to the processing and control unit, precisely responding to adjustment commands: For three priority categories—severe risk, general risk, and optimization needs—it executes operations such as emergency shutdown, automatic parameter adjustment, and gradual optimization, respectively; for different defects such as segregation, bleeding, and pressure fluctuations, it precisely adjusts key parameters such as grouting flow rate, grout water-cement ratio, and bentonite content; in conjunction with formation condition self-adaptation logic, it performs gradual parameter callbacks to achieve dynamic matching between construction quality and formation condition, forming a closed-loop control. This unit ensures the efficient implementation of the processing and control unit's decisions, guaranteeing continuous optimization of grouting construction quality.

[0086] The above are all preferred embodiments of this application, and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the structure, shape and principle of this application should be covered within the scope of protection of this application.

Claims

1. A method for intelligent monitoring of grouting construction quality, characterized in that, Includes the following steps: The grouting pressure signal and pore water pressure signal are acquired, the friction loss and nozzle reflection loss of the grout along the force transmission path are determined, and the grouting pressure signal is dynamically calibrated by combining the friction loss, nozzle reflection loss and pore water pressure signal to output the net pressure of the formation. At least two initial slurry detection signals based on different principles are acquired simultaneously. The initial slurry detection signals are mapped to corresponding slurry state signals according to a preset non-Newtonian suspension detection model. Based on the formation interference level reflected by one of the slurry state signals, the other slurry state signal is compensated and fused to output an anti-interference slurry concentration. Based on the net pressure of the formation, the concentration of the anti-interference grout, and the obtained grouting flow rate, grout defects are determined in real time through multi-parameter collaborative analysis. A comprehensive evaluation parameter is constructed based on the net pressure of the formation, the concentration of the anti-interference grout, the grout defects, and the grouting flow rate. The weight ratio of each item in the comprehensive evaluation parameter is dynamically adjusted based on the real-time changes of the pore water pressure signal to generate a dynamic score for process quality. Based on the dynamic quality score of the process and the type of grout defect, the corresponding construction parameters are adjusted.

2. The method according to claim 1, characterized in that, The dynamic calibration further includes: Continuous monitoring of the net pressure acting on the formation; Based on the monitored continuous change characteristics, the working status of the sensors that collect the grouting pressure signal and the pore water pressure signal is determined: When the continuously changing characteristics exceed a preset drift threshold, it is determined to be sensor drift and dynamic compensation is triggered; When the difference between the grouting pressure signal and the pore water pressure signal exceeds a preset abnormal threshold, it is determined to be a sensor malfunction and a fault handling process including redundancy switching is triggered.

3. The method according to claim 1, characterized in that, The compensation and fusion include: Based on the first type of slurry state signal among the slurry state signals of the at least two principles, the groundwater dilution rate reflecting the degree of formation disturbance is estimated. The second type of slurry state signal among the at least two principles of slurry state signals is reverse-compensated based on the groundwater dilution rate to generate a compensated slurry state signal. Based on the comparison between the groundwater dilution rate and the preset dilution rate threshold, the fusion weights of the first type of slurry state signal and the compensated slurry state signal are dynamically allocated when generating the anti-interference slurry concentration.

4. The method according to claim 1, characterized in that, The real-time determination of slurry defects through multi-parameter collaborative analysis is based on multi-level logical verification rules, which include: When the change in the concentration of the anti-interference slurry meets the preset primary determination condition, the primary determination is triggered; When the primary determination is triggered, a further joint determination is made as to whether the change characteristics of the formation net pressure or the grouting flow rate exceed a preset correlation change threshold, so as to trigger an intermediate correlation determination. When the intermediate correlation determination is triggered, a final defect confirmation signal is generated based on whether the difference between the inlet slurry concentration and the outlet slurry concentration exceeds a preset concentration difference confirmation threshold. The final defect confirmation signal distinguishes between separation defects and bleeding defects based on the concentration change direction that triggered the primary determination.

5. The method according to claim 4, characterized in that, The primary determination criteria include: Based on the direction of change in the anti-interference slurry concentration, a primary judgment signal of the corresponding type is triggered. Specifically, when the direction of change is downward and its change characteristics exceed a preset first primary threshold, a primary judgment signal indicating segregation defects is triggered. When the direction of change is upward and its change characteristics exceed a preset second primary threshold, a primary judgment signal indicating a oozing defect is triggered.

6. The method according to claim 1, characterized in that, The dynamic adjustment of the weighting of each item in the comprehensive evaluation parameters based on the real-time changes in the pore water pressure signal includes: Monitor the real-time variation characteristics of the pore water pressure signal and compare it with a preset formation state threshold; Based on the comparison results, the level of formation disturbance was determined; Based on the formation disturbance level, a weight adjustment instruction is generated, which is used to adjust the weight corresponding to the net pressure stability of formation action in the comprehensive evaluation parameters.

7. The method according to claim 1, characterized in that, After adjusting the corresponding construction parameters, the process also includes a formation condition self-adaptation step: Based on the slurry state signals according to the above at least two principles, a first evaluation index characterizing the reduction in the degree of formation disturbance is extracted. Based on the pore water pressure signal, a second evaluation index characterizing the release of formation pore water pressure is extracted. When the first evaluation index and the second evaluation index reach their respective optimization thresholds, the self-adaptation logic is activated. The self-adaptive logic is configured to execute simultaneously: progressively redirecting construction parameters to preset benchmark parameters, and restoring the weights of each item in the comprehensive evaluation parameters to preset benchmark weights.

8. The method according to claim 7, characterized in that, After initiating the self-adaptive logic, the process also includes effect verification and adaptive iteration steps: During the preset verification period, monitor the changes in the first evaluation indicator and the second evaluation indicator; When it is detected that the change of at least one of the evaluation indicators has not reached the corresponding expected optimization threshold, the enhanced adjustment of the construction parameters is triggered. If, after the enhancement and adjustment, the change in at least one evaluation indicator still does not reach the expected optimization threshold, then decision support information for requesting human intervention is generated. The decision support information includes at least key data trends, parameter adjustment history, and a list of items to be verified.

9. The method according to claim 8, characterized in that, The step of progressively redirecting the construction parameters to the preset benchmark parameters is further configured as follows: The rate of the gradual callback is dynamically determined based on the improvement rate of the first evaluation index and the second evaluation index during the verification period. Based on the type of grout defect currently occurring, determine the priority callback item for the construction parameters; The priority callback items include: for segregation defects, priority callback of grouting flow rate; for bleeding defects, priority callback of grout water-cement ratio.

10. An intelligent monitoring system for grouting construction quality, used to implement the method according to any one of claims 1 to 9, characterized in that, include: The sensor array is configured to acquire grouting pressure signals, pore water pressure signals, initial grout detection signals based on at least two principles, and grouting flow rate; The processing control unit, connected to the sensor array, is configured to: receive signals from the sensor array; determine the friction loss and orifice reflection loss of the grout along the force transmission path, and dynamically calibrate the grouting pressure signal by combining the friction loss, the orifice reflection loss, and the pore water pressure signal, and output the net pressure of the formation; map the initial grout detection signal to grout state signals based on at least two principles according to a preset non-Newtonian suspension detection model, and perform compensation and fusion, outputting the anti-interference grout concentration; determine grout defects in real time through multi-parameter collaborative analysis based on the net pressure of the formation, the anti-interference grout concentration, and the grouting flow rate; construct comprehensive evaluation parameters based on the net pressure of the formation, the anti-interference grout concentration, the grout defects, and the grouting flow rate, and dynamically adjust the weight ratio of each item in the comprehensive evaluation parameters based on the real-time changes of the pore water pressure signal to generate a dynamic process quality score; and generate construction parameter adjustment instructions based on the dynamic process quality score and the type of grout defects. The parameter execution unit, connected to the processing control unit, is used to receive and execute the construction parameter adjustment instructions to adjust the grouting construction parameters.

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