Visual grouting quality online evaluation and self-correction system and method

Abstract

The invention relates to the technical field of foundation engineering, in particular to a visual grouting quality online evaluation and self-correction system and method.The visual grouting quality online evaluation and self-correction system comprises a data acquisition module integrating various sensors; the data processing module is used for generating standardized grouting process data from the sensor data; the state analysis module evaluates the standardized data in real time by using a preset atlas analysis algorithm and an expert rule base, and identifies the grouting state and the quality condition; the geological information module generates a geological response map for auxiliary evaluation and control decision making; and the control execution module adjusts the operation parameters of the grouting equipment according to the evaluation result output by the state analysis module, and the operation parameters comprise valve opening and closing, the slurry flow speed and the grouting sequence, so that self-adaptive deviation correction control in the grouting process is achieved. According to the method, under-grouting, over-grouting and abnormal grout escape can be effectively avoided, grouting uniformity and construction quality are improved, manual intervention and misjudgment risks are reduced, and safety, efficiency and engineering reliability of grouting operation are remarkably improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of foundation engineering, in particular to a visual grouting quality online evaluation and self-correction system and method. BACKGROUND

[0002] Curtain grouting is a technique that injects cement slurry, chemical slurry and other materials into rock or soil through drilling to form a vertical or inclined continuous impermeable body (i.e. "curtain"), which is mainly used to block groundwater seepage, reinforce soft ground and prevent the spread of pollutants.

[0003] In the prior art, for foundation curtain grouting, consolidation grouting and other processes: most solutions only conduct survey or spot check before and after grouting, which cannot evaluate the diffusion and consolidation state of slurry in the target soil during the grouting process; even if pressure, flow and other online monitoring are introduced, they are usually used for recording or manual experience judgment, without forming a quantifiable "over-grouting" and "under-grouting" evaluation index system; existing visualization, digital twin or geophysical imaging solutions mostly focus on the visualization and effect evaluation of the whole project or the whole section, lack device-level closed-loop control on the single-hole or single-grouting segment scale, and cannot automatically perform actions such as supplementary grouting and pressure relief backfilling for correction; grouting parameters (pressure curve, termination criteria, etc.) mostly rely on pre-design and manual experience, and cannot adaptively optimize over-grouting / under-grouting criteria and control parameters according to historical data as the project progresses.

[0004] Therefore, there is a need for a device and method that can obtain working conditions and soil responses in real time during foundation grouting, online evaluate grouting quality, and automatically correct over-grouting and under-grouting states, so as to improve foundation consolidation quality, reduce slurry waste and the risk of disastrous spread. SUMMARY

[0005] Based on the above description, the present application provides a visual grouting quality online evaluation and self-correction device, which effectively avoids under-grouting, over-grouting and abnormal slurry escape, improves grouting uniformity and construction quality, reduces the risk of manual intervention and misjudgment, and significantly improves the safety, efficiency and engineering reliability of grouting operations.

[0006] In one aspect, the technical solution of the present application to solve the above technical problems is as follows: a visual grouting quality online evaluation and self-correction system, comprising a data acquisition module, a data processing module, a state analysis module, a geological information module and a control execution module; The data acquisition module integrates multiple sensors for real-time acquisition of pressure, flow, cumulative grouting volume, backfilling volume, slurry conductivity, and stratum vibration and pore pressure parameters during grouting; The data processing module calibrates and filters the data of each sensor and synchronizes the time to generate standardized grouting process data; The status analysis module uses a preset graph analysis algorithm and expert rule base to evaluate standardized data in real time and identify grouting status and quality. The geological information module associates historical geological survey data with real-time grouting data to generate geological response maps for auxiliary assessment and control decisions. The control execution module automatically adjusts the operating parameters of the grouting equipment, including valve opening and closing, grout flow rate and grouting sequence, based on the evaluation results output by the state analysis module, in order to achieve adaptive correction control of the grouting process.

[0007] The above technical solution integrates modules such as data acquisition, processing, analysis, geological correlation, and control execution to form a complete closed loop for grouting quality assessment and feedback, achieving intelligent management and control throughout the entire process. It collects grouting and formation response data in real time, combines map analysis and geological characteristics to determine the grouting status, and automatically adjusts grouting parameters and processes to effectively avoid under-grouting, over-grouting, and abnormal grout leakage, improve grouting uniformity and construction quality, reduce the risk of human intervention and misjudgment, and significantly improve the safety, efficiency, and reliability of grouting operations.

[0008] Based on the above technical solution, the present invention can be further improved as follows.

[0009] Furthermore, the data acquisition module includes pressure sensors, flow meters, slurry concentration or conductivity sensors, and slurry return metering devices installed in the grouting pipeline and borehole, as well as vibration acoustic sensors and pore water pressure sensors deployed in the grouting area, for acquiring multi-source data on grouting dynamics and formation response.

[0010] Through the above technical solution, the acoustic vibration sensor and pore water pressure sensor are buried in the borehole wall or nearby soil to monitor the formation filling response. They can capture information such as cavity closure, grout seepage path and structural response, and improve the ability to identify hidden problems such as under-grouting and grout leakage. This data acquisition solution has the advantages of modularity, scalability and strong adaptability. It can be applied to traditional single-hole grouting operations as well as complex scenarios such as multi-hole synchronous grouting and diaphragm walls. At the same time, its physical integration with the grouting equipment can realize integrated construction deployment, reduce the risk of wiring and misconnection, and significantly improve the practicality of the project and the stability of the system.

[0011] Furthermore, the data processing module includes a signal conditioning circuit, an A / D converter, and a data synchronization unit, which are used to amplify, filter, convert analog to digital, and align the raw signals from different sensors, and output the processed data in a predetermined format.

[0012] Through the above technical solutions, the data synchronization unit ensures the consistency of different parameters in the time dimension by using a timestamp-based or trigger-based synchronization mechanism, which is beneficial for multi-parameter correlation analysis. The data output in a unified format not only meets the input requirements of the subsequent state recognition module, but also enables advanced functions such as historical data comparison, map generation, and machine learning modeling. This module can also support edge computing deployment, avoiding excessive reliance on central server processing resources, enhancing the system's independent operation capability, and is particularly suitable for use in complex construction sites or areas with limited network signals such as tunnels and foundation pits, ensuring that the system has high stability and real-time response capabilities in actual engineering projects.

[0013] Furthermore, the status analysis module has a built-in expert rule base for the grouting process. The rule base contains threshold conditions and logical rules for judging under-grouting, over-grouting, blockage, and grout leakage. The status analysis module compares and calculates the real-time monitored pressure-flow curve and grouting volume change curve with the rule base. When a certain rule condition is met, the corresponding grouting status signal and alarm prompt are output.

[0014] The aforementioned technical solution, through preset multi-parameter threshold rules such as pressure, flow rate, and time, enables the system to determine in real time whether common problems such as under-grouting, over-grouting, blockage, and grout leakage exist, avoiding reliance on operator experience. The status recognition model uses standard spectral curves and historical patterns as references, and quickly outputs status labels and provides risk warnings by comparing real-time monitoring data with the rule base, thereby achieving "early warning and real-time control." In addition, this module has rule updatable capabilities, which can continuously optimize parameter thresholds based on historical data, enhancing the system's ability to adapt to different geological and grouting process conditions. This approach significantly improves recognition efficiency and automatic response capabilities, especially in multi-hole grouting, cross-strata, and long-term operations, significantly reducing the probability of construction accidents, material waste, and grouting quality deviations, and is a key technical support for the intelligent evolution of engineering sites.

[0015] Furthermore, the geological information module includes a database for storing geological profile information and a data fusion unit. The data fusion unit correlates the geological parameters at the corresponding location of the borehole with real-time grouting data to generate a geological response map. The state analysis module adjusts the grouting state discrimination criteria based on the geological response map, and the control execution module optimizes the control strategy for grouting pressure, flow rate, or sequence accordingly.

[0016] Through the above technical solutions, spatial matching with grouting hole locations or section data enables the binding of real-time grouting parameters with the geological characteristics of that section. During the state analysis process, the system can automatically correct the threshold judgment criteria based on the geological response map, such as relaxing the pressure upper limit in high-permeability sections and limiting the grouting rate in weak cementation sections, thereby avoiding misjudgment or over-control and improving the accuracy of identification. The control strategy can also be automatically optimized accordingly, such as prioritizing the densification of sealing sections and switching the order to seal high-permeability sections first, which helps to improve the uniformity of grouting and avoid grout leakage and injection along undesigned paths. This module is particularly suitable for areas with uneven stratification, interlocking soil and rock, or complex fracture development, significantly improving the intelligence level and regional adaptability of the entire system.

[0017] Furthermore, the control execution module includes an electric valve, an adjustable speed grouting pump, a grout mixing device controller, and a sequence control unit; When the status analysis module determines that the grouting status is normal, the control execution module runs according to the preset process parameters; When an abnormal state is detected, the control execution module automatically performs corrective measures, including starting and stopping the grouting pump, opening or closing valves to change the grout flow direction, adjusting the grout mix ratio, or switching grouting holes, in order to correct the abnormality and restore normal grouting.

[0018] Secondly, the technical solution of the present invention to solve the above-mentioned technical problems is as follows: A method for online evaluation and self-correction of grouting quality, comprising the following steps: Multi-parameter data acquisition: During the grouting process, real-time grouting data is collected by the deployed pressure, flow rate, grout return volume, concentration, conductivity, acoustic vibration, and pore pressure sensors. Real-time data processing; Synchronization and standardization of collected multi-source data, filtering out abnormal interference and converting the data into a unified time-series set of grouting parameters; Status identification and analysis: The processed data is input into the expert rule base for analysis and comparison. Combined with the grouting pattern characteristics, the current grouting status is identified, such as whether there is under-grouting, over-grouting, blockage or grout leakage, and evaluation results and prompt information are generated. Geological information fusion; the real-time assessment results are correlated with the pre-stored geological models and parameters to analyze the response characteristics of the current borehole section to grouting, thereby correcting or verifying the conclusions of state identification, and adjusting the assessment threshold when necessary. Automatic deviation control; adjusts grouting construction parameters in real time based on evaluation results, and automatically executes corresponding deviation control measures when an abnormality is detected, including pressure reduction, pump stoppage, change of grout formula or adjustment of grouting sequence; if the evaluation is normal, grouting continues according to optimized parameters until completion.

[0019] Compared with the traditional approach that relies solely on manual observation of pressure and flow rate, this method introduces multi-dimensional monitoring parameters such as grout volume, concentration, conductivity, acoustic vibration, and pore pressure. This elevates the grouting process from a rough assessment of "quantity and pressure" to a comprehensive evaluation of "grout behavior + formation response," significantly improving the sensitivity and reliability of problem identification. Through data synchronization and standardized processing, it ensures that the outputs of various sensors participate in the analysis under a unified time sequence and unified dimensions, avoiding misjudgments caused by different sampling frequencies and ranges. By combining expert rule base and map features for state identification, typical abnormal conditions such as under-grouting, over-grouting, blockage, and grout leakage can be detected in real time during the grouting process, and evaluation results with semantic information can be output. Geological information fusion further links the identification results with specific geological conditions, making the judgment more consistent with the actual geological environment and reducing "false anomalies" or over-control. Finally, automatic correction control transforms the analysis results into real-time adjustment of construction parameters, realizing closed-loop control of the entire process from "problem detection" to "automatic parameter adjustment", which significantly improves the intelligence, stability and controllability of grouting construction and grouting quality.

[0020] Furthermore, the real-time data processing specifically includes: using a two-way time window interpolation algorithm to perform timestamp alignment processing on the collected pressure, flow rate, slurry return volume, and conductivity multi-source data to ensure that each parameter has a corresponding value at the same time; Denoising the original signal based on moving average filtering or median filtering algorithms, smoothing abnormal fluctuations, and eliminating high-frequency interference; Three Sigma rules are used to remove outliers from abrupt or invalid data during the data acquisition process. A linear drift correction model is used to automatically correct sensor data with slow drift, thereby maintaining measurement stability. Different physical quantities are normalized according to their normal operating range to unify the data dimensions, so as to facilitate subsequent map construction and state identification.

[0021] The aforementioned technical solution, through outlier removal using the three sigma rule, can automatically identify failed or abrupt data points, preventing extreme erroneous data from skewing the overall judgment. The linear drift correction model provides an online correction method for sensor zero-point drift during long-term construction, ensuring stable and comparable data during long-term monitoring. The normalization transformation of different physical quantities eliminates dimensional differences, allowing subsequent spectral analysis and algorithm discrimination to be performed in a unified numerical space, significantly simplifying the complexity of the identification model and improving algorithm convergence. Overall, this claim, through a complete set of specific algorithmic processes, ensures that the data input to the state identification and control decision-making module is "clean, aligned, stable, and comparable," providing crucial underlying support for achieving high-precision online evaluation and reliable correction control.

[0022] Furthermore, the grouting status identification and analysis includes: A four-dimensional spectrum matrix of pressure-flow-time-concentration is generated using the processed grouting parameters. This matrix is ​​generated by a sliding window with a sampling frequency of ≥10Hz per second and serves as the basis for time series analysis. The system compares the spectral feature curves with a built-in expert rule base, which includes composite logical criteria based on experience. If the rate of decrease in flow rate ΔQ / Δt per unit time exceeds the set threshold Q t Furthermore, the rate of pressure increase ΔP / Δt is simultaneously greater than the threshold P. t If so, it is determined to be a blockage in the pipeline or a blockage in the orifice; If the pressure remains low for an extended period and the cumulative slurry volume is abnormally higher than the expected reference value, it is determined to be an overfilling or slurry leakage state. If the pressure rises rapidly and the grouting volume is far below the standard section value, it is judged as under-grouting or poor sealing. An adaptive dynamic threshold identification algorithm can be optionally introduced. This algorithm is based on statistical historical grouting data of similar strata or borehole sections, and automatically fits a reasonable range of key identification variables to improve the model's adaptability and accuracy to different geological conditions.

[0023] Through the above technical solutions, the four-dimensional spectral matrix serves as the basis for time-series analysis, which is beneficial for revealing the coupling relationship between pressure and flow rate, the concentration evolution law during the grouting process, and its comprehensive change trend over time, thereby forming visualized and quantifiable grouting behavior characteristics. By comparing these spectral characteristics with composite logical criteria in the built-in expert rule base, typical working conditions such as blockage, over-grouting, under-grouting, and poor sealing can be quickly and automatically identified based on physical mechanisms and engineering experience, realizing the transformation from "reading curves based on experience" to "automatic judgment based on rules". For the differences in parameter distribution caused by different strata and different construction methods, an adaptive dynamic threshold identification algorithm is introduced. By statistically analyzing historical similar working condition data, various threshold ranges are automatically fitted, so that the identification model no longer relies on fixed thresholds, but self-adjusts according to actual engineering and historical data. This significantly improves the model's adaptability and identification accuracy under multi-working-point and multi-stratum conditions, reduces false alarms and false negatives, and enhances the system's engineering universality and long-term use value.

[0024] Furthermore, the automatic deviation correction control includes the following implementable strategies: If the status recognition module outputs the "under-grouting" label, the system will increase the upper limit of grouting pressure by 10%–30% or extend the grouting duration to 150% of the original value through the control module, based on the formation permeability and design target of the corresponding borehole section, and at the same time activate the pressure stabilization compensation mode. If the status is identified as "overfilling" or "emergence," the system automatically executes pressure reduction and speed reduction logic, including: Reduce the grouting pump speed by 20%–50%. Lowering the water-cement ratio of the slurry improves its adhesion. And limit the cumulative amount of grouting in a single section to not exceed the safety threshold V. m ; If the status is identified as "blockage", the system will start the back pressure-unloading-pulsating unblocking procedure, sequentially performing short-term reverse unloading, opening the bypass valve to reduce the pressure difference, and periodically switching the main pump output at a frequency of 1~3Hz for pulsating excitation. All corrective actions are driven by an embedded working condition matching control rule table. This rule table combines real-time monitoring parameters and pre-stored geological response information to select the optimal control scheme and records the corrective process in real time for subsequent analysis and model retraining.

[0025] Through the above technical solutions, for situations of "over-grouting" or "grout overflow," the grouting pump speed is reduced by 20%–50%, the water-cement ratio is adjusted to improve the grout's cohesiveness, and a safety threshold V is applied to the cumulative grouting volume in a single section. m The upper limit effectively suppresses ineffective diffusion of grout and its escape into non-target areas, reducing material waste and risks to surrounding structures. For "blockage" conditions, a backpressure-unloading-pulsating unblocking procedure is used to achieve online unblocking of pipelines or ducts, avoiding process interruptions caused by simple and abrupt grouting shutdowns, while also reducing the risk of equipment or borehole wall damage due to overpressure. All strategies are uniformly managed by a condition-matching control rule table, automatically selecting the most suitable control combination based on real-time monitoring data and geological response information, and recording the execution process for subsequent optimization and model retraining. This quantitative and adaptive correction control mechanism not only significantly improves the system's speed and accuracy in handling abnormal conditions but also ensures that the grouting process achieves optimal quality and efficiency within safety boundaries, demonstrating the practical engineering value of this invention's method in intelligent construction control.

[0026] Compared with the prior art, the technical solution of this application has the following beneficial technical effects: 1. Achieving multi-source, full-scale sensing and high-quality data unification of the grouting process: By deploying various sensors such as pressure, flow rate, grout return volume, concentration, conductivity, acoustic vibration, and pore pressure in the grouting pipeline and formation, and configuring signal conditioning circuits, A / D conversion, and time synchronization units, the system can perform comprehensive, multi-scale real-time acquisition of the grouting process and formation response. Based on this, algorithms such as bidirectional time window interpolation, moving average / median filtering, three-sigma anomaly removal, linear drift correction, and normalization transformation are introduced to unify data from different sources, with different dimensions, and different sampling frequencies into a stable, clean, and aligned set of time-series parameters. This series of measures significantly improves the accuracy, continuity, and comparability of the data, providing a reliable foundation for subsequent map construction, state identification, and control decisions, and solving the key bottleneck of "disorganized and unusable data" in traditional grouting monitoring. 2. A high-precision grouting status identification system integrating expert experience and geological information is constructed. By generating a four-dimensional pressure-flow-time-concentration map matrix and accumulating it via a sliding window at a sampling frequency of ≥10Hz, the system can meticulously depict the dynamic evolution characteristics of the grouting process. Combined with composite logical criteria from the built-in expert rule base regarding under-grouting, over-grouting, blockage, and grout leakage, the system automatically identifies and classifies key abnormal states. Simultaneously, an adaptive dynamic threshold identification algorithm is introduced, automatically fitting a reasonable threshold range based on historical similar borehole segments or strata data, and associating real-time identification results with pre-stored geological models and parameters to form a geological response map, correcting or corroborating the identification conclusions. Through the combination of "map features + expert rules + dynamic threshold + geological fusion," the system significantly improves the identification accuracy and robustness under complex geological conditions and multiple working scenarios, reduces false alarms and false negatives, and upgrades grouting quality assessment from experience-based judgment to a calculable and transferable intelligent judgment. Attached Figure Description

[0027] Figure 1 This is a block diagram of the overall structure of the visualized online grouting quality assessment and self-correction system according to Embodiment 1 of the present invention; Figure 2 This is a schematic diagram of the structure of the visualized online grouting quality assessment and self-correction system of Embodiment 1 of the present invention; Figure 3 This is a hardware structure block diagram of the data acquisition and data processing module in Embodiment 1 of the present invention; Figure 4 This is a schematic diagram of the software functional structure of the state analysis module and the geological information module in Embodiment 1 of the present invention; Figure 5 This is a schematic diagram of the control execution module and grouting flow path in Embodiment 1 of the present invention; Figure 6 This is a flowchart of the online grouting quality assessment and self-correction method according to Embodiment 2 of the present invention; Figure 7 This is a schematic diagram of the grouting status identification and correction control logic in Embodiment 2 of the present invention.

[0028] Reference numerals: 101, Vibration acoustic sensor; 102, Pore water pressure sensor; 103, Grout concentration or conductivity sensor; 104, Pressure sensor; 105, Grout return metering device; 106, Grout return channel; 107, Main grouting pipeline. Detailed Implementation

[0029] To facilitate understanding of this application, a more complete description will be provided below with reference to the accompanying drawings, which illustrate embodiments of the present application. However, the present application can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided so that the disclosure of this application will be thorough and complete.

[0030] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application.

[0031] Example 1: refer to Figure 1 and Figure 5 In this embodiment, a visualized online grouting quality assessment and self-correction system mainly includes: a data acquisition module, a data processing module, a status analysis module, a geological information module, and a control execution module. Each module is connected through an industrial Ethernet or fieldbus to realize online monitoring, intelligent assessment, and automatic correction control of the grouting construction process.

[0032] I. Data Acquisition Module; The data acquisition module is deployed along the grouting pipeline, borehole opening, and grouting-affected area to acquire multi-source data on grouting dynamics and formation response. Specifically, it includes: 1. Pressure sensors on the main grouting pipeline are installed at the grouting pump outlet, near the orifice, and at the section pipeline where necessary, to collect the instantaneous pressure P(t) during the grouting process. The range is generally 0-5MPa or 0-10MPa depending on the design pressure. It is preferred to use a pressure transmitter with a flat diaphragm structure, such as the WIKA S-11 pressure sensor.

[0033] 2. The flow meter on the main grouting pipeline can be an electromagnetic flow meter or a volumetric flow meter, which outputs the instantaneous flow rate Q(t) and obtains the cumulative grouting volume V(t) by integration. The accuracy is preferably not less than ±1%. The main grouting flow meter is preferably an electromagnetic flow meter, such as the RF3301-SL type slurry electromagnetic flow meter or the Promag P300 type electromagnetic flow meter.

[0034] 3. A slurry return metering device is installed in the slurry return channel. It can be a slurry return tank with a weighing sensor or a volumetric metering device. It is used to measure the slurry return volume R(t) and record the slurry return start time and the flow rate change during the slurry return process. The slurry return metering device can be a weighing slurry return tank with a shear beam weighing sensor installed at the bottom of the tank, such as the SBK500-C6 sensor.

[0035] 4. A slurry concentration / conductivity sensor is installed at the outlet of the slurry mixing device or on the main grouting pipeline to monitor the slurry conductivity C(t) or concentration in real time, so as to reflect changes in the water-cement ratio, admixture dosage, and other proportions. The slurry concentration / conductivity sensor is preferably an inductive conductivity sensor, such as the Endress Hauser CLS54D sensor; an ultrasonic slurry density meter, such as the Rhosonics SDM slurry density meter, can also be used.

[0036] 5. Vibration acoustic sensors: Multiple vibration / acoustic emission sensors are deployed on the ground surface or around the monitoring borehole within the grouting influence range to collect response quantities A(t) such as formation vibration acceleration, spectral characteristics, or acoustic emission counts, in order to reflect the grout penetration and fracture filling process. The vibration acoustic sensors can be IEPE type piezoelectric accelerometers with a sensitivity of about 100mV / g and a frequency response of 0.5Hz to 10kHz or higher, such as the A26D100 type or similar products.

[0037] 6. Pore water pressure sensor: Pore water pressure gauges are installed in representative monitoring holes, observation holes or grouting hole sections to record changes in pore water pressure U(t) in order to determine the range and degree of influence of the seepage field and stress field; the pore water pressure sensor is preferably a vibrating wire piezometer, such as the GEOKON 4500 series vibrating wire pore water pressure gauge.

[0038] All of the above-mentioned sensors are connected to the signal input terminal of the data processing module via shielded cables or fieldbuses. The sampling frequency can be set to 1 to 50 Hz, preferably at a sampling frequency of not less than 10 Hz in the state identification stage, in order to meet the accuracy requirements of subsequent map construction and time series analysis.

[0039] 2. Data processing module; In a preferred embodiment, the data processing module is integrated into the field data acquisition terminal or industrial controller, and is further subdivided into a signal conditioning submodule, an analog-to-digital conversion (A / D) submodule, a data synchronization and caching submodule, and a communication management unit, for realizing the unified acquisition, shaping, digitization, and packet transmission of multi-source sensor signals.

[0040] (1) Signal conditioning submodule: The signal conditioning submodule designs channel circuits for different types of sensor output forms, including current type, voltage type, frequency type, and IEPE type vibration sensors, etc. Specifically, it may include: For the acquisition of 4–20mA current signals (such as pressure, flow, and pore water pressure sensors), it is preferable to use a precision sampling resistor (e.g., a 250Ω standard resistor) to convert the current into a 1–5V voltage, which is then amplified by an instrumentation amplifier. For 0–5V and 0–10V voltage signals (such as conductivity and displacement sensors), an input protection circuit and an adjustable gain amplification stage are set up, and a second-order or multi-order low-pass filter is configured. The cutoff frequency can be selected from 10 to 50Hz according to the sampling frequency to suppress high-frequency noise and achieve anti-aliasing. For IEPE type vibration / acoustic sensors, a constant current excitation source (e.g., 2-4mA) is configured, and a high-pass / band-pass filter is set in the signal path to extract vibration components within the target frequency band; For vibrating wire or similar sensors, a dedicated excitation and demodulation circuit can be configured to convert the vibrating wire frequency signal into an analog voltage or digital quantity proportional to the pressure. All channels are equipped with overvoltage protection and surge suppression devices (such as TVS diodes, surge absorbers, isolation amplifiers, etc.), and electrical isolation between the signal and the field high-voltage equipment is achieved through opto-isolation or magnetic isolation to ensure the system's anti-interference capability and safety.

[0041] After signal conditioning, the output of each channel is uniformly converted to standard analog quantities such as 0–5V or 4–20mA, and then sent to the analog-to-digital conversion submodule.

[0042] (2) Analog-to-Digital (A / D) Conversion Submodule: This submodule converts the conditioned analog signal into a digital signal. A multi-channel, high-resolution A / D converter or a multi-channel A / D module is preferred. Specifically, it may include: The A / D resolution is preferably no less than 16 bits, and more preferably a 24-bit Σ-Δ type A / D conversion chip is used to improve the ability to resolve minute changes in pressure, flow rate and pore pressure; The sampling frequency is set according to system requirements, generally 1 to 50 Hz, and preferably ≥10 Hz is set for the key channel sampling frequency during the grouting status identification stage; The channel configuration can adopt multi-channel synchronous sampling or multi-channel fast scanning + time correction. Key parameters (such as pressure and flow rate) can be sampled synchronously using A / D to reduce phase difference. The A / D module communicates with the fieldbus or CPU via SPI, I / O, etc. 2 C or parallel bus communication, after sampling, the instantaneous value of each channel is stored in the buffer.

[0043] (3) Data synchronization and caching submodule: This submodule is used to unify the time base of each channel, complete timestamp marking and data buffering, and specifically includes: The system clock, which uses a high-precision crystal oscillator as its core, serves as the time reference for all acquisition tasks. When necessary, it can be periodically synchronized via NTP on the host computer or via GPS / BeiDou timing module to ensure the stability of the clock during long-term operation. At the beginning of each sampling period, a unified timestamp is generated and assigned to all channel data collected within that period. For channels with different sampling periods or asynchronous sampling, the data synchronization unit uses interpolation and buffering mechanisms to resample or interpolate them onto a unified time axis; for a small number of lost data points, nearest neighbor or linear interpolation can be used to complete them; By using a circular buffer or double buffering mechanism to cache the collected data, when the host computer or communication bus is busy for a short period of time, the data can be cached locally for a certain period of time (e.g., 1 to 5 minutes) to avoid data loss. While writing data to the cache, basic data validity checks and anomaly marking are performed, such as detecting range overruns, fixed value jams, and sudden anomalies, providing markers for subsequent software filtering and three-sigma anomaly removal.

[0044] (4) Communication management and data packaging: The processed digital signals are packaged by the communication management unit according to a predetermined data structure to form standardized grouting process data frames. The preferred data structure is as follows: [Timestamp] + [Borehole Number / Segment Number] + [Pressure] + [Flow Rate] + [Cumulative Grouting Volume] + [Grouting Return Volume] + [Grouting Conductivity or Concentration] + [Vibration Amplitude / Characteristic Value] + [Pore Water Pressure] + [Status Mark / Quality Mark, etc.] The timestamp can be in UNIX time or in the format of "year-month-day hour:minute:second.millisecond", the hole number / hole segment number is used to distinguish different grouting locations, and the status flag field is used to record information such as whether the data has been filtered and whether there are any abnormal rejections.

[0045] The communication management unit can use an Ethernet controller or fieldbus interface module to send the aforementioned data frames to a host computer or central server according to TCP / IP, Modbus TCP, Profinet, or other industrial Ethernet protocols. For distributed monitoring points, data can also be uploaded via RS485 or other buses in Modbus RTU mode. To ensure transmission reliability, a CRC checksum or frame check field can be set in the data frame to perform error detection and retransmission control at the receiving end.

[0046] After the above processing and packaging, the standardized grouting process data can be directly used in the host computer for subsequent filtering and noise reduction, normalization, three-sigma anomaly removal, drift correction, and construction of a four-dimensional pressure-flow-time-concentration matrix, providing a consistent and reliable data foundation for the online evaluation of the state analysis module.

[0047] III. Status Analysis Module; In a preferred embodiment, the status analysis module is deployed in a host computer or industrial panel PC, using an industrial control computer as the running platform. This module can be divided into the following software components: a data access and caching unit, a graph construction and feature extraction unit, an expert rule base and rule reasoning unit, an adaptive threshold update unit, and a status output and alarm display unit, used to realize real-time graph analysis and grouting status identification of grouting process data.

[0048] (1) Data access and caching unit; The data access and caching unit communicates with the data processing module through industrial Ethernet or fieldbus and receives standardized grouting data frames at fixed intervals (e.g., 0.1s or 0.2s).

[0049] Each data frame includes at least: timestamp t, borehole number / segment number ID, pressure P(t), flow rate Q(t), cumulative grouting volume V(t), grout return volume R(t), conductivity / concentration C(t), vibration characteristic value A(t), pore water pressure U(t), and data quality identifier.

[0050] This unit establishes a cyclic buffer queue based on borehole number and borehole segment number, and maintains a data window for each grouting borehole segment for the most recent period (e.g., 5-30 minutes) to provide a data basis for subsequent sliding time window analysis.

[0051] When the received data quality is identified as abnormal (such as exceeding the range limit, failure point, etc.), the point is marked as "to be excluded" or "corrected" in the cache for subsequent algorithms to skip or interpolate.

[0052] (2) Map construction and feature extraction unit; The map construction and feature extraction unit uses cached data to generate various time series curves and multidimensional maps, and extracts key features.

[0053] ① Construction of curves and graphs: With time as the horizontal axis, plot the pressure-time curve P(t), flow rate-time curve Q(t), cumulative grouting volume-time curve V(t), grout return volume-time curve R(t), conductivity / concentration-time curve C(t), vibration amplitude-time curve A(t), and pore pressure-time curve U(t).

[0054] The time axis is divided into several windows by sliding time windows of fixed length, such as every 10 s or 30 s as an analysis window. A four-dimensional spectral matrix of pressure-flow-time-concentration is generated for each window. =[P,Q,C,t].

[0055] The four-dimensional map can be internally displayed using a three-dimensional surface overlay time index or compressed in pseudo-color mode to intuitively present the coupled changes of pressure, flow rate, and concentration over time.

[0056] ② Characteristic quantity calculation; Within each analysis time window, calculate the following characteristic quantities, for example: Pressure growth rate: ; Rate of change of flow: ; Cumulative grouting volume increase: ; Return slurry ratio: ; Where ε is a small constant to prevent the denominator from being zero; vibration energy or vibration RMS value: ; or integrate the energy of a specific frequency band in the frequency domain; pore pressure change rate: ; In addition, auxiliary features such as pressure-flow correlation coefficient, pressure plateau maintenance time, slurry return start time, and slurry return peak value can be calculated as needed to accurately identify different abnormal working conditions.

[0057] (3) Expert rule base and rule reasoning unit; The expert rule base and rule reasoning unit are the core of the state analysis module, used to map the above feature quantities to specific grouting states.

[0058] ① Rule base structure; the expert rule base can adopt a layered structure, including: Basic threshold table: Reference ranges for each characteristic quantity are preset according to stratum type (sand layer, clay layer, fractured rock layer, etc.), grouting purpose (curtain, seepage prevention and reinforcement, etc.), and borehole section design parameters (design pressure, design grouting volume, etc.). Permissible range Permissible range Reasonable range, reasonable range of ΔV, etc.

[0059] Composite logic rule set: Consists of rules in the form of "IF–THEN", which combine multiple feature quantities to determine a certain state. For example: If ≤-Q t and ,and If P is below the set value, it is inferred to be a "blockage"; if P remains below this value for an extended period... Furthermore, ΔV is significantly higher than the reference value within a given time period. If P increases rapidly within a short period of time and ΔV is significantly lower than the standard grouting volume at a certain depth in that borehole section, then it is inferred to be "over-grouting / grout leakage"; If so, it can be inferred that there is "under-irrigation"; Priority and conflict resolution rules: When multiple rules are triggered at the same time, conflict resolution is carried out by preset priority, confidence or weight. For example, "overfilling" with higher safety risk takes priority over "overfilling", and "clogging" with higher equipment risk takes priority over "underfilling".

[0060] Rule-based reasoning process The state analysis module executes the following reasoning process within each analysis window: Extract the feature vector corresponding to the time window from the cached data. ; For the current formation type of the borehole segment, obtain the corresponding threshold set for that formation from the basic threshold table. , , , , wait); The complex logic rule set is evaluated sequentially, rules that meet the conditions are marked, and the matching degree or confidence degree of each rule is calculated. If only one rule is triggered, the state corresponding to that rule is directly output as the current state. If multiple rules are triggered, a unique status label and its confidence level are obtained by combining the preset priority and matching degree.

[0061] Optionally, a simple scoring mechanism or fuzzy membership calculation can be superimposed during the rule reasoning process. That is, a membership function of "normal / under-irrigation / over-irrigation / blockage / slurry overflow" is constructed for each feature quantity. The membership degree of each state is calculated based on the actual value of the feature quantity. Finally, the state with the largest membership degree is selected as the discrimination result, and the membership degree value is used as the confidence level output.

[0062] (4) Adaptive threshold update unit; In order to enhance the adaptability of the system under different engineering and geological conditions, an adaptive threshold update unit is set in the state analysis module to dynamically correct some thresholds in the rule base during the engineering process.

[0063] The adaptive module periodically collects historical grouting data under the same stratum type and similar construction conditions, and calculates the statistical indicators (such as mean, standard deviation, quantiles, etc.) of each characteristic quantity under the condition that has been "verified as normal". Fine-tune the initial empirical thresholds in the basic threshold table, for example, adjust the thresholds under normal operating conditions. , The 95th percentile value will be used as the new upper / lower limit reference. The stable range is taken as the normal slurry return ratio range; The threshold adjustment process is subject to amplitude control, meaning that the adjustment range does not exceed a set proportion (e.g., 5% to 10%) to prevent excessive threshold drift due to individual abnormal data. Data segments identified by manual review as "typical under-irrigation" or "typical over-irrigation" can be used as training samples to correct the discrimination boundaries of the corresponding states.

[0064] Through the aforementioned adaptive updates, the system can gradually converge to a discrimination threshold that better suits the characteristics of this project, while ensuring a safety margin, thereby improving the accuracy and robustness of state recognition.

[0065] (5) Status output and alarm display unit, which is responsible for outputting the judgment result simultaneously in machine signal and visualization mode.

[0066] ① Status signal output: For each grouting hole section, the status analysis module periodically outputs the current status label (such as "normal", "under-grouting", "over-grouting", "grout leakage", "blockage", etc.) and confidence level; The status signal is sent to the control execution module via software interface or fieldbus, and the control execution module executes the corresponding correction logic (such as voltage regulation, speed reduction, switching of orifice section, etc.) accordingly. In the event of a severe anomaly (such as high-confidence slurry escape, severe blockage, etc.), the module simultaneously outputs an emergency stop or forced decompression command flag for the control execution module to respond quickly.

[0067] ② Visual alarms and color-coded indicators: Visual prompts can be displayed on the host computer interface in the following ways: In the real-time curve graph of each grouting hole, different colored sections are used to mark the current status, for example: green indicates normal, yellow indicates under-grouting, orange indicates over-grouting, and red indicates grout leakage or severe blockage. On the hole location plan or cross-sectional view, the current status of each hole is displayed as a dot or small icon. When an abnormal status occurs, the icon flashes or is surrounded by a red border. When an abnormality occurs, a pop-up window prompts the information, including: hole number, hole segment, status type, trigger time, and main characteristic parameters (such as current pressure, flow rate, grout return volume, and calculated characteristic values), to facilitate quick judgment by on-site technicians. Simultaneously, all status change events and alarm events are recorded, generating a time-sorted event log for subsequent quality analysis and construction review.

[0068] Through the aforementioned structural and algorithmic design, the state analysis module can perform real-time spectral analysis and quantitative feature extraction of multi-source monitoring data during grouting construction. Utilizing an expert rule base and adaptive thresholds, it accurately identifies typical working conditions such as under-grouting, over-grouting, blockage, and grout leakage. The analysis results are provided to the control execution module and on-site personnel in both standard signal and intuitive interface formats, providing a reliable decision-making basis for online evaluation and self-correcting control of the grouting process.

[0069] IV. Geological Information Module; In a preferred embodiment, the geological information module is set in a host computer or a dedicated server, and mainly consists of a geological profile database unit, a spatial index and borehole segment matching unit, a geological-grouting data fusion and geological response map generation unit, and a stratigraphic classification and threshold correction unit. It is used to realize the organic combination of engineering survey results and real-time grouting monitoring data, and to provide the state analysis module with the basis for adaptive judgment of geological conditions.

[0070] (1) Geological profile database unit. The geological profile database unit is used to store and manage various geological information obtained during the engineering exploration stage, and realize the standardized and structured description of geological information.

[0071] ① Data Sources and Content: Geological data from engineering survey reports are pre-imported into the database, including but not limited to: borehole columnar section: containing the borehole number, plane coordinates (X, Y), borehole elevation Z0, total borehole depth H, etc. for each borehole; stratigraphic information: stratigraphic layer number and top plate depth for each borehole according to depth. Bottom plate depth Rock and soil type: lithology name (e.g., silty clay, medium sand, gravel layer, strongly weathered granite, etc.), lithology code; permeability parameters: such as permeability coefficient k, gradient, permeability test results (Lugeon value, single-hole pumping test, etc.); mechanical properties: such as standard penetration test blow count N, cohesion c, internal friction angle φ, saturated uniaxial compressive strength, etc.; structural characteristics: location of fault fracture zone, degree of fracture development, joint spacing, distribution of weak interlayers, etc.; hydrogeological information: groundwater level depth, confined aquifer head, distribution of aquifers and impermeable layers; other auxiliary parameters: natural water content, void ratio, density, etc.

[0072] ② Database Structure: To facilitate rapid retrieval and integration with grouting well data, the geological profile database can adopt a relational database structure or an object-oriented database structure. Typical table structures include: "Basic Information Sheet for Boreholes": Records borehole number, coordinates, elevation, total borehole depth, exploration date, etc. "Borehole Stratification Information Table": Fields include borehole number, layer number, top / bottom depth, lithology code, k value, N value, fracture index, etc. "Fault Fracture Zone Information Table": Records fault name, spatial location, dip angle, width, filling material, etc. "Hydrogeological Information Sheet": Records the regional groundwater level, the top and bottom plates of the aquifer, and the confined water head, etc.

[0073] Each table is linked by key values ​​such as borehole number, layer number, and spatial coordinates, and indexes are created to enable fast queries by borehole number, depth, or stratigraphic type.

[0074] (2) Spatial index and borehole-hole segment matching unit The spatial indexing and matching unit is responsible for establishing a spatial association between the construction grouting holes and the exploration hole database, so as to achieve rapid matching of "grouting holes - geological profiles".

[0075] ① Grouting hole parameter input: During the construction preparation stage, the design information of each grouting hole is entered into the system, including: grouting hole number, plane coordinates, hole opening elevation, design hole depth, hole segment division (start and end depth of each segment), etc.

[0076] ② Spatial matching method: Depending on the engineering accuracy requirements, spatial matching can adopt one or a combination of the following methods: Nearest Neighbor Borehole Matching: Using the plane coordinates of the grouting borehole as the center, the nearest exploration borehole is retrieved, and the columnar section of that exploration borehole is used as the reference geological profile for the grouting borehole; Linear Interpolation Matching: For grouting boreholes located between two exploration lines, linear interpolation or weighted averaging can be performed on the same strata of two or more adjacent exploration boreholes to construct a virtual geological profile; Zonal Matching: When the geological exploration has divided the area into several geological zones, the geological zone where the grouting borehole is located can be determined first, and then representative boreholes or combinations within the zone can be selected as references.

[0077] ③ Hole Section-Structural Unit Division: After establishing the association between grouting holes and exploration holes or virtual profiles, each grouting hole section (e.g., a 2 m to 5 m section) is divided into "hole section-structural units": For a certain depth range [D1, D2] of a borehole section, find one or more stratigraphic horizons within that depth range in the corresponding geological profile; If the borehole section falls entirely within a single stratum, then the stratum code for that borehole section is the lithology code and corresponding parameters of that stratum; If a borehole segment spans multiple strata, it is divided into several sub-units based on the length or weight calculation method, or based on the main stratum (the stratum with the largest proportion) with secondary strata information.

[0078] Finally, one or more "stratigraphic units" records are established for each grouting hole section, including parameters such as depth, lithology, permeability coefficient, and fracture degree, as static inputs for subsequent fusion calculations.

[0079] (3) Geological-grouting data fusion and geological response map generation unit This unit is used to correlate real-time grouting data with the aforementioned static geological information to construct a geological response map that reflects the relationship between "strata-grouting parameters-strata response".

[0080] ① Real-time data association: During the grouting process, each real-time grouting data frame contains the borehole number, borehole segment number, or current grouting depth information. The geological information module uses these identifiers to: Locate the geological profile corresponding to the grouting hole based on the hole number; Find the corresponding stratigraphic unit record based on the current grouting depth or borehole segment number; The grouting parameters at that moment (such as P, Q, V, R, C, A, U, etc.) are bound to the static parameters (lithology, k value, N value, fracture index, etc.) in that stratigraphic unit to form a "geology-grouting" fusion record.

[0081] ② Geological response map generation: After grouting or during construction, the system can generate geological response maps at different scales in the following ways: Longitudinal geological response map inside the borehole: The distribution of strata is drawn along the borehole section with depth as the vertical axis. Parameters such as grouting pressure, cumulative grouting volume, grout return ratio, and borehole pressure change are superimposed on each borehole section and presented in different colors or symbols to form a comprehensive profile of "depth-strata-grouting effect". Geological response map of curtain line profile: Along the curtain axis, with distance as the horizontal axis and depth as the vertical axis, the stratum distribution of multiple grouting holes is spliced ​​into a 2D profile. The statistical values ​​of grouting parameters (such as grouting volume per unit length, final pressure, grout return, etc.) are superimposed at the corresponding hole sections to evaluate the overall continuity and compactness of the curtain. Stratigraphic Category Response Map: The average pressure-flow rate curve, average unit grouting volume, and typical pore pressure response curve of each grouting hole section in a stratigraphic category are statistically analyzed to form a "typical geological response template" for a certain type of stratigraphic category.

[0082] These geological response maps can be displayed graphically on the host computer interface or provided to the state analysis module in the form of data tables as the basis for threshold adjustment and model training.

[0083] (4) Stratigraphic classification and threshold correction unit: The stratigraphic classification and threshold correction unit is used to convert geological information into classification labels and parameter correction coefficients that can be directly used by the state analysis module, so as to realize the adaptive adjustment of geological conditions to the state identification criteria.

[0084] ① Formation classification rules: Based on information such as lithology, permeability coefficient k, and fracture index in the geological profile database, the formation is divided into several standard categories. For example: High-permeability gravel layer: k≥k1, loose structure, good pore connectivity; Medium-permeability sandy soil layer: k2≤k<k1; Low-permeability clay layer: k<k2, or high N value and small porosity ratio; Fracture-developed hard rock layer: lithology is rock and high fracture index, joints are developed; Fault fracture zone and weak interlayer: extremely fractured structure, may be high-permeability but unstable formation.

[0085] Each type of formation corresponds to a set of "recommended grouting parameter ranges" and "state recognition sensitivity parameters", such as the upper limit of allowable pressure, target grouting volume per unit length, allowable slurry return ratio range, pressure / flow rate change rate threshold, etc.

[0086] ② Threshold correction mechanism: When the state analysis module conducts state recognition on a certain hole section, the geological information module provides the formation category of this hole section and the corresponding threshold correction coefficient. For example: For the high-permeability gravel layer, appropriately relax the upper limit threshold of the cumulative grouting volume , allowing a relatively higher grouting volume; reduce the sensitivity to the flow rate decrease, but increase the monitoring weight for the slurry return ratio and slurry leakage signs; For the low-permeability clay layer or weakly weathered rock layer, appropriately lower the upper limit of pressure and the pressure increase rate threshold P t , enabling the system to respond to sudden pressure increases earlier and preventing overpressure and local damage; For the fracture-developed hard rock layer or fault fracture zone, rely more on the changes in vibration energy, acoustic response, and pore pressure in adjacent holes, and increase the weights of these indicators to judge the risk of fracture penetration and slurry leakage.

[0087] Threshold correction can be achieved by multiplicative coefficient or additive offset methods. For example: ; where is the correction coefficient determined by the formation category.

[0088] Through this mechanism, the state analysis module adopts different discrimination criteria under different formation conditions, avoiding misjudging "normal large grouting volume in high-permeability layers" as over-grouting and also avoiding missing the detection of "slight pressure anomalies in low-permeability layers".

[0089] (5) Provide support for the state analysis module and adaptive algorithm; The geological information module not only provides the formation category and correction threshold for the state analysis module in a single discrimination, but also provides a statistical basis for the subsequent adaptive algorithm.

[0090] When performing statistical analysis on historical data, the adaptive threshold update unit (located inside the state analysis module) can group the data by formation type and statistically analyze the distribution characteristics of indicators such as pressure growth rate, flow rate change, grouting volume per unit length, and grout return ratio under normal working conditions in each formation type, thereby correcting the basic threshold table corresponding to each formation type. For confirmed working conditions such as "typical under-irrigation", "typical over-irrigation / slurry leakage" and "typical blockage", they can also be archived according to stratigraphic categories to form a set of anomalous samples with geological labels, which can be used as a training dataset for subsequent optimization of expert rules or introduction of machine learning to assist in identification. The "typical geological response template" formed in the geological response map can serve as a benchmark for rapid comparison during construction. When the real-time grouting response of a certain borehole section deviates significantly from the typical template of the same type of strata, it can be regarded as a potential anomaly, triggering an early warning.

[0091] Through the above structural and functional design, the geological information module closely integrates static engineering geological survey results with dynamic grouting monitoring data, transforming complex stratigraphic differences into quantifiable and callable parameters and classification information. This provides the state analysis module with a basis for adaptive judgment of geological conditions, ensuring that under-grouting, over-grouting, blockage, and grout leakage can be more accurately identified and distinguished under different stratigraphic conditions. This significantly improves the reliability and engineering applicability of the online grouting quality assessment and self-correction system of this invention.

[0092] V. Control Execution Module; In a preferred embodiment, the control execution module is installed near the electrical control cabinet and field valve group of the grouting equipment. It consists of a grouting pump frequency conversion control unit, a valve and flow direction switching unit, a grout mixing control unit, a sequence control and working condition management unit, and a safety interlock and manual intervention unit. It is used to receive the grouting status signal output by the status analysis module, automatically adjust the pressure, flow rate, mixing ratio and grouting sequence of the grouting process, and realize real-time self-correction control of the grouting process.

[0093] (1) Grouting pump and frequency conversion control unit: The grouting pump and frequency conversion control unit are used to achieve fine adjustment of the grout delivery pressure and flow rate.

[0094] The grouting pump can be a high-pressure grout pump such as a plunger pump or a screw pump, and the rated pressure and flow rate are selected according to the scale of the project. The pump motor adopts a three-phase asynchronous motor or a permanent magnet synchronous motor, and is equipped with a frequency converter to achieve stepless speed regulation control; The frequency converter control unit receives a given signal (such as 0–10V or communication setting frequency) from the controller inside the control execution module, so as to realize the continuous adjustment of the pump speed within the set range; A simple closed-loop control loop is constructed using feedback signals from a pressure sensor: Under normal operating conditions, pressure closed-loop control is employed to stabilize the orifice pressure at the target pressure given by the state analysis module or process parameters. nearby; When flow rate is the primary control variable, the system can switch to flow closed-loop or dual-constraint control mode of "pressure limiting + flow priority". Under different conditions such as under-irrigation, over-irrigation, and blockage, the sequential control unit issues speed-up, speed-down, or shutdown commands to the frequency converter to automate pump start-up, shutdown, and speed adjustment.

[0095] To ensure safety, when the status analysis module outputs a "severe overpressure" or "severe blockage" status and the pressure exceeds the safety limit, the system will take appropriate action. At this time, the frequency converter control unit has a hardware emergency stop input, which cuts off the pump motor running command through a relay to achieve rapid pump stop.

[0096] (2) Valve and flow direction switching unit: The valve and flow direction switching unit is installed on the main grouting pipeline, branch pipeline and bypass grout return pipeline to realize the grouting flow direction, flow distribution and rapid pressure relief.

[0097] An electric regulating valve is installed on the main grouting pipeline for precise adjustment of the main flow rate and pressure. Electric switching valves (electric ball valves, butterfly valves, or shut-off valves) are installed before each grouting hole or branch of each hole section to select the current grouting hole or hole section and realize automatic switching of multiple holes and multiple sections. A bypass grout return electric valve is installed between the main grouting trunk line and the grout return pipeline. When pressure reduction, unloading or blockage clearing procedures are required, the bypass can be opened to guide part of the grout back to the grout return container or circulation tank. The valve actuator is preferably an electric actuator or an electric / pneumatic integrated actuator, which supports on / off control and analog (opening degree) control, and has a valve position feedback signal; The actions of valves and pumps are coordinated by a sequence control unit to ensure that the switching process avoids shocks and accidental spraying caused by "switching under pressure" or accidental opening or closing.

[0098] In the "overfill / slurry overflow" state, the control logic can execute: appropriately close the main regulating valve, open the bypass slurry return valve, or reduce the slurry supply time of a certain orifice section. In the "blockage" state, the downstream valve can be temporarily closed, the bypass unloading valve can be opened, and the frequency converter can be used to execute a pulsed pressure sequence to reduce the risk of blockage and perform unblocking.

[0099] (3) Slurry preparation control unit: The slurry preparation control unit is specifically responsible for the automatic control of slurry ratio, water-cement ratio and admixture dosage, and can dynamically adjust the formula according to the state analysis results.

[0100] The slurry preparation device includes a clear water tank, a water metering unit, a cement (or powder) metering unit, an admixture metering unit, and a mixing device. Each metering unit is controlled by actuators such as electric valves, variable frequency screw conveyors, or metering pumps. The slurry mixing controller calculates the water-cement ratio, cement dosage, and admixture dosage based on the preset formula table, and issues control commands such as adding water, powder, and admixtures in the set formula sequence. When the status analysis module determines that the grouting is "under-filled" and that the permeability needs to be improved, the grouting controller can be instructed to switch to a formula with higher permeability (e.g., appropriately increasing the water-cement ratio or adjusting the type and dosage of admixtures). In the "overfilling / excessive grouting" state, you can switch to a formula with higher viscosity or faster setting (reduce the water-cement ratio, use quick-setting or high-binder) to enhance the sealing ability and quickly form a grout stop. Key parameters during the slurry preparation process (water addition, powder addition, and stirring time) can be uploaded to a host computer for comparison with conductivity / concentration sensor data to ensure the accuracy of formula execution.

[0101] By linking the grout mixing control unit with the status analysis module, the system can not only adjust the grouting pressure and flow rate, but also perform "soft adjustment" at the mixing ratio level, thereby achieving more fundamental control over the grouting effect.

[0102] (4) Sequence control and working condition management unit: The sequence control and working condition management unit is the core logic layer of the control execution module. It is used to manage the construction sequence of multi-hole and multi-segment grouting and coordinate the coordinated actions of pumps, valves and grouting.

[0103] ① Construction sequence management: Pre-set the grouting hole list, hole segment division and design sequence in the system, such as from upstream to downstream, from shallow to deep or in a symmetrical order; The sequence control unit dynamically updates the grouting queue based on the status of completed borehole segments (normal completion, under-grouting supplementation, over-grouting early termination, etc.); For borehole sections that require re-irrigation or supplemental irrigation, the corresponding "re-irrigation task" can be inserted into the queue and automatically scheduled for execution at an appropriate position in the main sequence.

[0104] ② Operating mode management: The sequence control unit supports multiple operating modes, including: Automatic mode: Driven by the status analysis module, the system automatically completes the entire process of pump start-up, valve opening, grouting, pump stop-up, and recording according to preset strategies; Semi-automatic mode: Key switching actions (such as borehole section switching and formula switching) require manual confirmation, while other parameters are automatically adjusted by the system; Manual mode: Provides only status monitoring and auxiliary protection, allowing operators to directly control the pumps and valves, suitable for commissioning or special operating conditions.

[0105] In automatic mode, the sequence control unit executes cyclically according to the following logic: Select the current target borehole section → Check the status of the corresponding valves and the grout preparation status → Start the grouting pump and open the corresponding branch valves → Perform grouting according to the design parameters → Adjust parameters in real time based on the output of the status analysis module and determine the termination conditions → Automatically stop the pump, close the valves and record the results after grouting is completed → Jump to the next borehole section or perform the re-grouting task.

[0106] (5) Status linkage and correction control logic: The control execution module maps the status labels (normal, under-irrigation, over-irrigation, slurry overflow, blockage, etc.) output by the status analysis module into specific control action combinations.

[0107] Normal state: The grouting pump operates in closed loop according to the target pressure or flow rate; the valves maintain the current opening and flow direction; the grouting control maintains the current formula; the sequence control proceeds according to the design rhythm until the design grouting volume or termination criterion is reached.

[0108] Under-grouting status: Issue a command to the frequency converter to increase the speed or pressure limit, thereby increasing the target pressure limit by 10% to 30% (within the safe range); extend the grouting time for this section of the hole or set a new target cumulative grouting volume; the grouting control can be commanded to switch to a more permeable formula; if it is still judged as under-grouting after multiple adjustments, it can be automatically added to the "re-grouting task" and re-grouted in subsequent construction.

[0109] Overfilling / Grouting Excess: Send a speed reduction command to the frequency converter to reduce the pump speed by approximately 20%–50%, thereby reducing the rate of increase in flow and pressure; appropriately close the main regulating valve or temporarily shut off the branch valve of the current borehole section; open the bypass grout return valve as needed to release some pressure and limit the cumulative grouting volume of a single borehole section to not exceed the safety threshold. The instruction to switch the slurry preparation control to a high-viscosity or rapid-setting formula promotes rapid sealing of potential slurry leakage channels.

[0110] Blockage status: Immediately execute the "back pressure-unloading-pulse unblocking procedure": briefly stop the pump or reduce the pressure, close the downstream valve, open the bypass unloading valve, and reduce the pipeline pressure to a safe level; then periodically switch the pump output status at a frequency of 1 to 3 Hz (e.g., switching between set high pressure / low pressure) to create pressure pulsations impacting the blockage site; after the procedure is executed a limited number of times (e.g., 3 to 5 cycles), reassess the status. If the blockage is cleared, normal operation is restored; if a serious blockage still exists, the pump is stopped and a manual maintenance prompt is issued, and grouting of that section is no longer automatically resumed.

[0111] All of the above actions are recorded with state information before and after execution. The control execution module will upload the occurrence time, control command and execution result of each correction to the host computer log for later analysis and rule base optimization.

[0112] (6) Safety Interlock and Manual Intervention Unit: Considering the complexity and safety of the construction site, the control execution module also includes a multi-level safety interlock and manual intervention mechanism: Hardware Interlock: Emergency stop button, mechanical limit switch, pressure limit switch, etc. are set. When extreme overpressure, pump overload, motor overheating, etc. are detected, the operation command of the pump and key valve can be directly cut off by bypassing the upper computer logic; Software Interlock: Multiple condition judgments are set in the control program, such as when the status analysis is a serious abnormality and the pressure exceeds If the pore pressure exceeds the design limit, the system will force the pump to stop and depressurize even if the operator does not issue a stop command; Manual priority mechanism: When the operator selects to enter manual or semi-automatic mode, manual operation commands take precedence over automatic control logic, but key safety interlocks are retained and not bypassed to avoid accidents caused by misoperation; Access control and recording: For sensitive operations such as changing the formula and adjusting the pressure limit, access control can be set up, and key operations of each operator can be recorded to facilitate quality traceability and responsibility division.

[0113] Through the aforementioned structure and control logic, the control execution module can form a closed loop with the state analysis module without altering the traditional grouting process. This enables fully automatic adjustment of grouting pressure, flow rate, grout mix ratio, and construction sequence. While ensuring safety, it provides timely and targeted self-corrective control for abnormal conditions such as under-grouting, over-grouting, grout leakage, and blockage, significantly improving the controllability of grouting quality and the level of automation in engineering construction.

[0114] Example 2: Based on the above system, this embodiment provides a method for online evaluation and self-correction of grouting quality, using single-hole or single-section grouting as an example.

[0115] The method includes the following steps: Step S1, Multi-parameter data acquisition: Before the grouting operation begins, the operator inputs the design parameters into the host computer, including the design grouting pressure range, design grouting volume, allowable grout return volume, target permeability index, etc. At the same time, the system retrieves the corresponding stratum type and parameters for this borehole section from the geological information module.

[0116] During the grouting process, the data acquisition module continuously collects the following data at a sampling frequency of no less than 10Hz: grouting orifice pressure P(t), instantaneous flow rate Q(t) and the cumulative grouting volume V(t) obtained by integration, return grout volume R(t) and its time process, grout conductivity or concentration C(t), formation vibration and acoustic response A(t), and pore water pressure U(t).

[0117] The aforementioned real-time data is sent to the data processing module in chronological order.

[0118] Step S2, Real-time Data Processing: The data processing module performs synchronization and standardization processing on the collected multi-source data, specifically including: 1. Timestamp alignment: Using a two-way time window interpolation algorithm, time correction is performed on discrete sampling points of different channels. For a target time point t0, several sampling points before and after it are taken to form a time window. The consistent values ​​of each parameter at time t0 are obtained by linear or spline interpolation, thereby ensuring that pressure, flow rate, slurry return, conductivity, etc. have corresponding data at a unified time.

[0119] 2. Noise reduction and smoothing: Apply moving average filtering or median filtering algorithms to the original signals of each channel to eliminate high-frequency noise and occasional spikes. For example, replace the current value with the arithmetic mean of the most recent N sampling points, or select the median to suppress isolated outliers.

[0120] 3. Outlier removal: Within each time window, the mean and standard deviation of the signal are statistically analyzed. The three sigma rule (three times the standard deviation method) is used to remove jump data and invalid data points that deviate significantly from the normal range, and the data is then filled in by interpolation or nearby valid values.

[0121] 4. Drift correction: For sensor data exhibiting slow drift (such as pressure and flow), establish a linear drift correction model. For example, determine the reference using periodic zeroing or static load processes. The slow-varying offset is compensated in a manner that maintains the stability of long-term monitoring.

[0122] 5. Normalization processing: Normalize each physical quantity according to its normal operating range, such as using the range [0,1] or [-1,1] mapping, to convert pressure, flow rate, grout return volume, conductivity, vibration amplitude, pore pressure, etc. into dimensionless quantities, which facilitates the subsequent construction of a grouting map of a unified scale and the identification of the state.

[0123] After processing, a set of grouting parameters with a unified time sequence is formed, which serves as the input for subsequent steps S3 and S4.

[0124] Step S3: Grouting Status Identification and Analysis In step S3, the state analysis module constructs a map and determines the state based on the processed data.

[0125] 1. A four-dimensional spectral matrix is ​​constructed, with time as the main axis. Key variables such as pressure (P), flow rate (Q), and concentration / conductivity (C) are selected and accumulated according to a set sliding time window (e.g., every 10 s or 30 s) to generate a four-dimensional spectral matrix of pressure-flow rate-time-concentration. This matrix not only preserves the temporal evolution information but also presents the joint changes of multiple parameters within the same time window.

[0126] 2. Rule base comparison: The system compares the change rates of the graph feature curves and key variables with the expert rule base. Typical composite logic criteria include: Congestion detection: If the flow rate decrease ΔQ / Δt per unit time exceeds a set threshold Q... t Furthermore, the rate of pressure rise ΔP / Δt is simultaneously greater than the threshold P. t If the grout return volume does not increase significantly, it is determined to be a blockage in the pipeline or borehole section; Over-grouting / grout leakage judgment: If the pressure remains at a relatively low level or far below the lower limit of the design pressure for a long time, while the cumulative grout volume is significantly higher than the target reference value, and the grout return volume increases or the pore pressure of adjacent boreholes rises abnormally, it is determined to be an over-grouting or grout leakage state; Under-grouting judgment: If the pressure rises rapidly to approach or exceed the upper limit, while the cumulative grouting volume is significantly lower than the corresponding design section value, and the formation vibration or pore pressure response is weak, it is determined to be under-grouting or poor curtain sealing; By combining acoustic vibration and pore pressure characteristics, a comprehensive judgment is made on complex situations such as sudden fracture penetration and long-distance grout leakage.

[0127] 3. Adaptive Dynamic Threshold: To improve identification accuracy under different geological conditions, an adaptive dynamic threshold identification algorithm can be optionally introduced. Based on grouting data samples from the same or similar strata in historical projects (provided by the geological information module), the statistical distribution of key parameters such as ΔQ / Δt, ΔP / Δt, cumulative grouting volume V, and backfill volume R are analyzed, and a reasonable threshold range for discrimination is automatically fitted. During the identification process, the system dynamically adjusts Q according to the geological category of the current borehole section. t P t Thresholds such as V reference value are used to improve the model's adaptability and accuracy to different formations and borehole sections.

[0128] By comparing the above rules, the status analysis module obtains the current grouting status label (such as "normal", "under-grouting", "over-grouting", "grout overflow", "blockage", etc.) and the corresponding confidence level in each time window, and outputs the evaluation results and prompt information.

[0129] Step S4: Geological information fusion and threshold correction. The geological information module fuses the geological profile and parameters of the borehole location with the above evaluation results: If the current borehole section is a high-permeability gravel layer, the system allows for a larger cumulative grouting volume and a higher flow rate limit, and the threshold for judging "over-grouting / excess grouting" is relaxed accordingly. If it is a low-permeability clay layer or a weakly weathered rock layer, the threshold for "overfilling / excessive grouting" should be appropriately tightened to increase the sensitivity to sudden pressure increases. If the rock layer is a hard rock layer with well-developed fractures, more attention should be paid to vibration energy, acoustic emission count, and pore pressure response to determine the fracture filling status and curtain integrity.

[0130] In this way, the real-time assessment results are not only based on the current monitoring data, but also combined with the pre-stored geological model to correct or corroborate the original judgment conclusions, and automatically adjust the assessment threshold when necessary, so that the identification results are more in line with the actual geological environment.

[0131] Step S5: Automatic Correction Control; In step S5, the control execution module automatically adjusts the grouting construction parameters based on the final evaluation results to achieve self-correction control. Specifically, the following strategies can be adopted: 1. Under-irrigation correction strategy: When the state analysis module outputs an "under-irrigation" label, the system automatically executes the following based on the formation permeability and design target of the corresponding borehole section: Increase the upper limit of the grouting pressure in this section by about 10% to 30%, and increase the pump speed by using a frequency converter or adjust the valve opening to stabilize the actual pressure near the new upper limit. The grouting duration of this section of the borehole can be appropriately extended, for example, to 150% of the original set time, and the grouting process can be put into a pressure stabilization compensation mode, that is, the pressure at the borehole opening can be kept stable within a small range of fluctuation through closed-loop control, thereby ensuring that the grout can fully penetrate and diffuse.

[0132] 2. Overfill / Escape Correction Strategy: When the status is identified as "overfill" or "escape," the system automatically executes pressure reduction and speed reduction logic, including: Reduce the grouting pump speed by about 20% to 50% from the current value to reduce the instantaneous flow rate and pressure increase rate; The water-cement ratio is adjusted by the slurry mixing device controller to reduce the water-cement ratio (i.e., the slurry increases its binding and viscosity), thereby enhancing the slurry's sealing ability and inhibiting long-distance escape. At the same time, a safe threshold V for the cumulative grouting volume per section is set for the current borehole section. m When the cumulative grouting volume approaches or reaches V m The system automatically limits continued grouting and issues a warning.

[0133] 3. Blockage Clearing Strategy: When the status is identified as "blocked," the system initiates the "back pressure – unloading – pulse clearing program," which can be executed sequentially: Short-term reverse unloading: By quickly closing the main valve and opening the bypass valve, the high-pressure slurry in the hole is released, causing a sudden drop in pressure to relieve stress at the blockage site; Bypass pressure relief: Maintaining a certain opening of the bypass valve allows some slurry to flow back, reducing the pipeline pressure difference; Pulsating excitation: The main pump output status is periodically switched at a frequency of 1–3 Hz (such as switching between high pressure / low pressure or slurry supply / unloading modes), forming periodic pressure pulses to mechanically oscillate and clear the blockage site.

[0134] If the blockage cannot be cleared after the above procedures, the system will automatically stop the pump and issue a manual maintenance prompt to avoid equipment damage and overpressure accidents.

[0135] 1. The embedded working condition matching control rule table and data records drive all the aforementioned corrective actions. This rule table takes grouting status labels, real-time monitoring parameters, and geological response information as input and outputs the corresponding optimal control scheme. The triggering conditions, execution parameters, and result evaluation of each corrective process are automatically recorded by the system for subsequent engineering analysis and retraining and optimization of the rule base and adaptive threshold model.

[0136] 2. Normal operating condition control: When the evaluation result is "normal," the system continues grouting according to the optimized process parameters until the designed grouting volume or termination criterion is reached, and then automatically switches to the next hole or the next hole section for construction. Operators can take over the system for manual control at any time, ensuring that the system has safety redundancy for manual intervention.

[0137] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A visualized online grouting quality assessment and self-correction system, characterized in that, It includes a data acquisition module, a data processing module, a status analysis module, a geological information module, and a control execution module; The data acquisition module integrates multiple sensors to acquire in real time the pressure, flow rate, cumulative grouting volume, return grout volume, grout conductivity, as well as formation vibration and pore pressure parameters during the grouting process. The data processing module calibrates, filters, and synchronizes the data from each sensor to generate standardized grouting process data. The status analysis module uses a preset graph analysis algorithm and expert rule base to evaluate standardized data in real time and identify grouting status and quality. The geological information module associates historical geological survey data with real-time grouting data to generate geological response maps for auxiliary assessment and control decisions. The control execution module automatically adjusts the operating parameters of the grouting equipment, including valve opening and closing, grout flow rate and grouting sequence, based on the evaluation results output by the state analysis module, in order to achieve adaptive correction control of the grouting process.

2. The visualized online grouting quality assessment and self-correction system according to claim 1, characterized in that, The data acquisition module includes pressure sensors, flow meters, slurry concentration or conductivity sensors, and slurry return metering devices installed in the grouting pipeline and borehole, as well as vibration acoustic sensors and pore water pressure sensors deployed in the grouting area, for acquiring multi-source data on grouting dynamics and formation response.

3. The visualized online grouting quality assessment and self-correction system according to claim 1, characterized in that, The data processing module includes a signal conditioning circuit, an A / D converter, and a data synchronization unit, which are used to amplify, filter, convert analog to digital, and align the raw signals from different sensors, and output the processed data in a predetermined format.

4. The visualized online grouting quality assessment and self-correction system according to any one of claims 1-3, characterized in that, The status analysis module has a built-in expert rule base for the grouting process. The rule base contains threshold conditions and logical rules for judging under-grouting, over-grouting, blockage, and grout leakage. The status analysis module compares and calculates the real-time monitored pressure-flow curve and grouting volume change curve with the rule base. When a certain rule condition is met, the corresponding grouting status signal and alarm prompt are output.

5. The visualized online grouting quality assessment and self-correction system according to any one of claims 1-3, characterized in that, The geological information module includes a database for storing geological profile information and a data fusion unit. The data fusion unit correlates the geological parameters at the corresponding location of the borehole with real-time grouting data to generate a geological response map. The state analysis module adjusts the grouting state discrimination criteria based on the geological response map, and the control execution module optimizes the control strategy for grouting pressure, flow rate, or sequence accordingly.

6. The visualized online grouting quality assessment and self-correction system according to any one of claims 1-3, characterized in that, The control execution module includes an electric valve, an adjustable speed grouting pump, a grout mixing device controller, and a sequence control unit. When the status analysis module determines that the grouting status is normal, the control execution module runs according to the preset process parameters; When an abnormal state is detected, the control execution module automatically performs corrective measures, including starting and stopping the grouting pump, opening or closing valves to change the grout flow direction, adjusting the grout mix ratio, or switching grouting holes, in order to correct the abnormality and restore normal grouting.

7. A method for online evaluation and self-correction of grouting quality, characterized in that, Includes the following steps: Multi-parameter data acquisition: During the grouting process, real-time grouting data is collected by the deployed pressure, flow rate, grout return volume, concentration, conductivity, acoustic vibration, and pore pressure sensors. Real-time data processing; Synchronization and standardization of collected multi-source data, filtering out abnormal interference and converting the data into a unified time-series set of grouting parameters; Status identification and analysis: The processed data is input into the expert rule base for analysis and comparison. Combined with the grouting pattern characteristics, the current grouting status is identified, such as whether there is under-grouting, over-grouting, blockage or grout leakage, and evaluation results and prompt information are generated. Geological information fusion; the real-time assessment results are correlated with the pre-stored geological models and parameters to analyze the response characteristics of the current borehole section to grouting, thereby correcting or verifying the conclusions of state identification, and adjusting the assessment threshold when necessary. Automatic deviation control; adjusts grouting construction parameters in real time based on evaluation results, and automatically executes corresponding deviation control measures when an abnormality is detected, including pressure reduction, pump stoppage, change of grout formula or adjustment of grouting sequence; if the evaluation is normal, grouting continues according to optimized parameters until completion.

8. The method for online evaluation and self-correction of grouting quality according to claim 7, characterized in that, The real-time data processing specifically includes: A two-way time window interpolation algorithm is used to perform timestamp alignment processing on the collected multi-source data of pressure, flow rate, slurry return, and conductivity to ensure that each parameter has a corresponding value at the same time. Denoising the original signal based on moving average filtering or median filtering algorithms, smoothing abnormal fluctuations, and eliminating high-frequency interference; Three Sigma rules are used to remove outliers from abrupt or invalid data during the data acquisition process. A linear drift correction model is used to automatically correct sensor data with slow drift, thereby maintaining measurement stability. Different physical quantities are normalized according to their normal operating range to unify the data dimensions, so as to facilitate subsequent map construction and state identification.

9. The method for online evaluation and self-correction of grouting quality according to any one of claims 7-8, characterized in that, The grouting status identification and analysis includes: A four-dimensional spectrum matrix of pressure-flow-time-concentration is generated using the processed grouting parameters. This matrix is ​​generated by a sliding window with a sampling frequency of ≥10Hz per second and serves as the basis for time series analysis. The system compares the spectral feature curves with a built-in expert rule base, which includes composite logical criteria based on experience. If the rate of decrease in flow rate ΔQ / Δt per unit time exceeds the set threshold Q t Furthermore, the rate of pressure increase ΔP / Δt is simultaneously greater than the threshold P. t If so, it is determined to be a blockage in the pipeline or a blockage in the orifice; If the pressure remains low for an extended period and the cumulative slurry volume is abnormally higher than the expected reference value, it is determined to be an overfilling or slurry leakage state. If the pressure rises rapidly and the grouting volume is far below the standard section value, it is judged as under-grouting or poor sealing. An adaptive dynamic threshold identification algorithm can be optionally introduced. This algorithm is based on statistical historical grouting data of similar strata or borehole sections, and automatically fits a reasonable range of key identification variables to improve the model's adaptability and accuracy to different geological conditions.

10. The method for online evaluation and self-correction of grouting quality according to any one of claims 7-8, characterized in that, The automatic correction control includes the following implementable strategies: If the status recognition module outputs the "under-grouting" label, the system will increase the upper limit of grouting pressure by 10%–30% or extend the grouting duration to 150% of the original value through the control module, based on the formation permeability and design target of the corresponding borehole section, and at the same time activate the pressure stabilization compensation mode. If the status is identified as "overfilling" or "emergence," the system automatically executes pressure reduction and speed-down logic, including: Reduce the grouting pump speed by 20%–50%. Lowering the water-cement ratio of the slurry improves its adhesion. And limit the cumulative amount of grouting in a single section to not exceed the safety threshold V. m ; If the status is identified as "blockage", the system will start the back pressure-unloading-pulsating unblocking procedure, sequentially performing short-term reverse unloading, opening the bypass valve to reduce the pressure difference, and periodically switching the main pump output at a frequency of 1~3Hz for pulsating excitation. All corrective actions are driven by an embedded working condition matching control rule table. This rule table combines real-time monitoring parameters and pre-stored geological response information to select the optimal control scheme and records the corrective process in real time for subsequent analysis and model retraining.

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