Slurry stopping and plugging device

Abstract

The invention discloses a grout stopping and plugging device, which belongs to the technical field of grouting equipment and comprises a grout stopping and plugging module, a grouting control module and a monitoring control module. Pressure conduction connectors are arranged at the front end and the rear end of a grout stopping plug body of the grout stopping plugging module respectively. A grouting pump and a first electric control valve of the grouting control module are connected to a grouting pipeline in series, and a second electric control valve is arranged on a grout return pipeline. A front pressure sensor and a rear pressure sensor of the monitoring control module are coupled to corresponding interfaces, a flow sensor is installed on a grouting pipeline, and the three are connected to a controller. A pressure difference dynamic analysis algorithm is built in the controller, the front and back pressure difference is calculated in real time, and flow data are combined to generate signals to independently control the working pressure of the grouting pump, the grouting flow of the first electric control valve and the slurry return flow of the second electric control valve. The problems of plugging failure and slurry waste caused by lagging and extensive pressure control in the prior art are solved, and the accuracy, the reliability and the automation level of the grouting process are remarkably improved through intelligent closed-loop control of multi-parameter coupling.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of grouting equipment, and particularly relates to a grouting plugging device. BACKGROUND

[0002] In the fields of geotechnical engineering, mine exploitation, tunnel support and geological disaster prevention, pressure grouting is a widely used technical means, which aims to pour grout into rock mass fissures, drill holes or loose media, and achieve the effects of reinforcing strata, preventing water seepage, improving bearing capacity, etc. after the grout solidifies. The success of the grouting process depends largely on the effective control of grout pressure and flow during grouting, as well as the effective sealing and isolation of the grouting section, i.e. the grouting plugging operation.

[0003] A common method to achieve effective grouting plugging is to plug a grouting plugging device into the target grouting section in the drill hole. The basic principle is to make the plug body expand and tightly fit with the hole wall by mechanical or hydraulic means, forming a temporary plugging, so as to limit the grouting in the target section. However, in actual engineering applications, the stratum conditions are often complex and variable, and factors such as uneven development of rock mass fissures and rough and uneven hole wall can challenge the reliability of grouting plugging. Traditional grouting plugging devices rely on pre-set constant pressure grouting or simple manual experience to control the grouting process. The operator manually adjusts the pump pressure or valve according to the pressure gauge reading and the return grout, which has obvious limitations in open-loop control.

[0004] Firstly, due to the dynamic changes of stratum grouting rate and possible plugging failure (such as grout bypassing the plug and breaking through the fissure), the grouting pressure is a rapidly changing parameter. Manual monitoring and adjustment have the problem of response lag, and it is difficult to respond to sudden changes in pressure in time. If the pressure is too low, it may result in insufficient grouting range and failure to achieve the design effect; if the pressure is too high, it is easy to cause unnecessary waste of grout diffusion and stratum splitting damage, and even cause the sealing failure of the grouting plug, leading to the failure of the entire grouting operation.

[0005] Secondly, the existing device usually only focuses on the pressure or flow at the grouting end, and lacks synchronous and accurate monitoring and linkage analysis of the pressure state before and after the plugging section. It is impossible to obtain the key parameter representing the effectiveness of plugging, i.e. the pressure difference before and after the grouting plug, in real time. This makes the system unable to make a prediction and adjustment in the early stage of the decline of plugging performance (manifested as abnormal changes in pressure difference), and often discovers the problem when there is obvious return grout or pressure drop, which is too late.

[0006] In addition, the existing control strategy is relatively single, and usually cannot coordinate the management of grouting flow and return grout flow. When the pressure fluctuates, there is a lack of fine coordination of control instructions between multiple actuators (such as grouting pumps and multiple electric control valves), which easily leads to control overshoot or oscillation, further aggravating the instability of the process.

[0007] Therefore, there is an urgent need in the art for a new grouting sealing device that can accurately perceive the grouting sealing state in real time and automatically and intelligently adjust the grouting parameters based on the state, so as to overcome the above-mentioned disadvantages of response lag, extensive control and inability to make predictive adjustments, thereby improving the success rate, economy and safety of grouting operations. SUMMARY

[0008] The present application overcomes the problems of plugging failure and grout waste caused by pressure control lag and extensive control in the prior art grouting and plugging technology, and significantly improves the accuracy, reliability and automation level of the grouting process through intelligent closed-loop control of multiple parameters.

[0009] To achieve the above-mentioned purpose, the present application adopts the following scheme: The grouting sealing device comprises a grouting sealing module, a grouting control module and a monitoring control module; The grouting sealing module comprises a grouting plug body and an expansion sealing mechanism, the front end of the grouting plug body is provided with a front pressure conduction interface, and the rear end is provided with a rear pressure conduction interface; The grouting control module comprises a grouting pipeline, a return grouting pipeline, a grouting pump, a first electric control valve and a second electric control valve, the grouting pump and the first electric control valve are connected in series on the grouting pipeline, and the second electric control valve is arranged on the return grouting pipeline; The monitoring control module comprises a front pressure sensor, a rear pressure sensor, a flow sensor and a controller, the front pressure sensor is fixedly coupled with the front pressure conduction interface, the rear pressure sensor is fixedly coupled with the rear pressure conduction interface, and the flow sensor is installed on the grouting pipeline; The front pressure sensor, the rear pressure sensor and the flow sensor are signal connected with the signal input end of the controller, and the grouting pump, the first electric control valve and the second electric control valve are signal connected with the signal output end of the controller; The controller is built-in with a pressure difference dynamic analysis algorithm, the pressure difference dynamic analysis algorithm calculates the pressure difference value of the front pressure sensor and the rear pressure sensor in real time, generates a grouting pump pressure adjustment signal, a first electric control valve opening control signal and a second electric control valve opening control signal according to the real-time change characteristics of the pressure difference value and the flow data of the flow sensor, and outputs the grouting pump pressure adjustment signal to control the working pressure of the grouting pump, outputs the first electric control valve opening control signal to adjust the grouting flow, and outputs the second electric control valve opening control signal to adjust the return grouting flow.

[0010] As a preferred, the pressure difference dynamic analysis algorithm comprises a data validity verification step, which judges the reliability of the pressure data by comparing the correlation between the reading change trend of the front pressure sensor and the rear pressure sensor and the flow change trend of the flow sensor; When the instantaneous change amount of the pressure difference between the current pressure sensor and the rear pressure sensor and the flow change amount do not satisfy the preset correlation relationship, a data correction mode is enabled, the latest reliable pressure data and real-time flow data are used for weighted calculation to generate a substitute pressure difference value; the controller maintains the output of the grouting pump pressure regulation signal, the first electric control valve opening control signal and the second electric control valve opening control signal in the data correction mode, and sends a command to keep the current working pressure to the grouting pump until the pressure sensor data returns to normal correlation.

[0011] Preferably, the data correction mode includes a dynamic weight adjustment unit, which calculates a weighting coefficient according to the duration of abnormal pressure sensor data and the reliability of flow sensor data; The dynamic weight adjustment unit monitors the recovery of the readings of the front pressure sensor and the rear pressure sensor in real time, adjusts the weighting proportion of the latest reliable pressure data and real-time flow data when any sensor data returns to normal, continuously compares the correlation between the instantaneous change amount of the pressure difference and the flow change amount in the data correction mode, and exits the data correction mode when the correlation is detected to return to the preset threshold; after exiting the data correction mode, the controller generates a mode switching instruction and transmits it to the grouting pump and the electric control valve, and restores the grouting pump pressure regulation signal and the electric control valve opening control signal to the normal control mode.

[0012] Preferably, the dynamic weight adjustment unit includes a transition interval controller, which establishes a gradual transition interval between the data correction mode and the normal control mode; the transition interval controller monitors the change rate of the weighting coefficient, and enables a gradual adjustment mechanism when the change rate of the weighting coefficient exceeds a set value; the gradual adjustment mechanism uses a piecewise linear interpolation algorithm to gradually adjust the output values of the grouting pump pressure regulation signal and the electric control valve opening control signal to target values within a preset time window; the transition interval controller compares the correlation between the instantaneous change amount of the pressure difference and the flow change amount in real time, and starts a mode switching preparation program when the correlation enters a stable interval; the mode switching preparation program sends a ready signal to the controller, and the controller receives the ready signal and gradually restores the operation weight of the normal control algorithm while removing the control parameters of the data correction mode in stages until it completely switches to the normal control mode.

[0013] As preferred, the inflation sealing mechanism comprises a ring-shaped array of pressure chambers, each pressure chamber being provided with an independent pressure conduction channel; the pressure conduction channels form a communication loop with the front and rear pressure conduction interfaces; a flexible partition layer made of elastic material is arranged between the pressure chambers; the front and rear pressure sensors are coupled with the pressure conduction channels; the controller receives multi-point pressure data of the front and rear pressure sensors, calculates the pressure difference values between the pressure chambers through a pressure differential dynamic analysis algorithm; the controller generates a grouting pump pressure adjustment signal according to the calculated pressure difference values, the grouting pump pressure adjustment signal including independent pressure adjustment parameters for each pressure chamber.

[0014] As preferred, the controller comprises a pressure-flow coupling analysis unit, which receives the pressure difference value signals of the front and rear pressure sensors and the real-time flow signals of the flow sensor; the pressure-flow coupling analysis unit performs time sequence alignment processing on the pressure difference value signals and the flow signals to generate a synchronous monitoring data set; the controller calculates a reference working pressure value of the grouting pump according to the pressure-flow correlation characteristics in the synchronous monitoring data set, converts the reference working pressure value into a pulse width modulation signal and transmits it to the motor driver of the grouting pump; the motor driver adjusts the armature voltage of the grouting pump according to the pulse width modulation signal to control the output pressure of the grouting pump; at the same time, the pressure-flow coupling analysis unit generates an opening correction coefficient of the first electric control valve according to the deviation value of the real-time flow signal from the preset reference flow and controls the opening of the first electric control valve.

[0015] As preferred, the monitoring control module comprises a data verification unit, which receives the original monitoring data of the front and rear pressure sensors and the flow sensor; the data verification unit comprises three independent data processing channels, each corresponding to a sensor signal; each data processing channel comprises a signal filtering circuit and an analog-to-digital conversion module, the signal filtering circuit uses a second-order Butterworth filter, and the analog-to-digital conversion module uses a 16-bit precision converter; the output ends of the three data processing channels are connected to a data comparator, which simultaneously receives the expected data range value issued by the controller; the data comparator performs real-time comparison between the sensor data processed by the data processing channels and the expected data range value, and sends a data anomaly flag signal to the controller when any sensor data exceeds the expected data range; after receiving the data anomaly flag signal, the controller automatically switches to a backup control mode, takes the historical data mean value within the latest reliable time window as a control reference value, and maintains the output of the grouting pump pressure adjustment signal and the electric control valve opening control signal according to the control reference value.

[0016] As preferred, the data checking unit comprises a historical data tracing program, which retrieves a historical data storage area within a recent reliable time window upon receiving the data abnormality flag signal; the historical data storage area adopts a ring buffer structure to store the monitoring data of the front pressure sensor, the rear pressure sensor and the flow sensor in chronological order; the historical data tracing program filters the historical data in the buffer through a data quality evaluation algorithm, which calculates a smoothness index of the monitoring data at each time point and the data at adjacent time points; the data quality evaluation algorithm selects a continuous time segment with the optimal smoothness index, and calculates the weighted average value of the sensor data in the segment; the controller adopts the weighted average value as the control basis in the standby control mode to generate the grouting pump pressure regulating signal and the electrically controlled valve opening control signal, while continuously monitoring whether the sensor data returns to normal.

[0017] As preferred, the expected data range value is generated by a data learning module, which continuously collects the monitoring data of the front pressure sensor, the rear pressure sensor and the flow sensor under normal working conditions to establish a sensor data feature library; the data learning module statistically analyzes the data in the feature library using a sliding time window method to calculate the mean value and the standard deviation of each sensor data; the expected data range value is dynamically determined according to the mean value and the standard deviation, with the upper limit being the mean value plus three times the standard deviation and the lower limit being the mean value minus three times the standard deviation; the data learning module updates the expected data range value every five minutes and transmits the updated value to the data comparator; the data comparator compares the real-time sensor data with the dynamically updated expected data range value, and sends a data abnormality flag signal to the controller when the data is out of range.

[0018] As preferred, the pressure difference dynamic analysis algorithm comprises a change rate calculation program and a segmented control mechanism; the change rate calculation program calculates the change amount per unit time of the pressure difference between the front pressure sensor and the rear pressure sensor in real time, and triggers the segmented control mechanism when the change amount per unit time exceeds a set threshold; the segmented control mechanism divides the control process into three consecutive stages according to the numerical range of the change amount per unit time: in the first stage, the grouting pump pressure regulating signal is adjusted to make the grouting pump output pressure decrease according to a linear law; in the second stage, the first electrically controlled valve opening control signal is controlled to make the opening of the first electrically controlled valve decrease according to a parabolic law; in the third stage, the second electrically controlled valve opening control signal and the grouting pump pressure regulating signal are simultaneously adjusted to make the return slurry flow rate and the grouting flow rate maintain a predetermined proportional relationship.

[0019] The present invention has at least the following beneficial effects: (1) By real-time monitoring of multiple parameters of the front and rear pressure sensors and flow sensors, and combined with the algorithm built into the controller for comprehensive analysis, independent and precise closed-loop control of grouting pressure, grouting flow and return flow is realized, so that the entire grouting process can maintain higher stability and controllability under complex geological conditions; (2) Through data validity verification and data correction mode, the system can perform weighted calculation based on historical reliable data and maintain control when sensor data shows a brief abnormality, avoiding unplanned shutdown or sudden change in control command caused by this, ensuring the continuous operation of grouting, and improving the reliability and robustness of the device; (3) By setting a transition range controller and a gradual adjustment mechanism, it is ensured that the system can recover from the correction after data abnormality repair. The system smoothly and seamlessly switches back to the normal control mode, effectively avoiding pressure shocks or system oscillations caused by control command jumps, further ensuring equipment safety and process stability; (4) The multi-pressure chamber design and independent monitoring and control enable the grout plug to expand more evenly and fit against the borehole wall, and can compensate for local pressure loss, greatly improving the sealing effectiveness and plugging quality in irregular boreholes or fractured formations, and reducing leakage risk; (5) Through data verification, historical data tracing and dynamic expectation range setting based on self-learning, the system can more intelligently identify the validity of sensor data, automatically activate the backup control strategy when the data is abnormal, and dynamically adjust the normal value range to reduce false alarms, achieving earlier and more accurate fault warning and more intelligent fault tolerance processing capabilities. Attached Figure Description

[0020] Figure 1 This is a schematic diagram of the main structure of the grout sealing device provided by the present invention.

[0021] In the diagram: 1. Grout stop plug body; 2. Grouting pipeline; 3. Return grout pipeline; 4. Front pressure sensor; 5. Rear pressure sensor; 6. Expansion sealing mechanism. Detailed Implementation

[0022] The present invention will now be described in further detail with reference to the accompanying drawings, so that those skilled in the art can implement it based on the description.

[0023] like Figure 1 As shown, the grout sealing device provided by the present invention includes a grout sealing module, a grouting control module, and a monitoring control module; The grout sealing module includes a grout plug body 1 and an expansion sealing mechanism 6. The grout plug body 1 has a front pressure transmission interface at the front end and a rear pressure transmission interface at the rear end. The grouting control module comprises a grouting pipeline 2, a return grouting pipeline 3, a grouting pump, a first electric control valve and a second electric control valve, the grouting pump and the first electric control valve are arranged in series on the grouting pipeline 2, and the second electric control valve is arranged on the return grouting pipeline 3; The monitoring control module comprises a front pressure sensor 4, a rear pressure sensor 5, a flow sensor and a controller, the front pressure sensor 4 is fixedly coupled with the front pressure conducting interface, the rear pressure sensor 5 is fixedly coupled with the rear pressure conducting interface, and the flow sensor is installed on the grouting pipeline 2; The front pressure sensor 4, the rear pressure sensor 5 and the flow sensor are signal-connected with a signal input end of the controller, and the grouting pump, the first electric control valve and the second electric control valve are signal-connected with a signal output end of the controller; The controller is internally provided with a pressure difference dynamic analysis algorithm, which calculates a pressure difference value of the front pressure sensor 4 and the rear pressure sensor 5 in real time, generates a grouting pump pressure regulating signal, a first electric control valve opening degree control signal and a second electric control valve opening degree control signal according to real-time change characteristics of the pressure difference value and flow data of the flow sensor, outputs the grouting pump pressure regulating signal to control the working pressure of the grouting pump, outputs the first electric control valve opening degree control signal to regulate the grouting flow, and outputs the second electric control valve opening degree control signal to regulate the return grouting flow.

[0024] The grouting stopping and plugging module is a core component of the grouting stopping and plugging device, and is used for realizing physical plugging and pressure conduction of a grouting area. The module comprises a grouting stopping plug body 1 and an expansion sealing mechanism 6. The grouting stopping plug body 1 is usually made of high-strength elastic material, the front end of the grouting stopping plug body 1 is provided with a front pressure conducting interface, the rear end of the grouting stopping plug body 1 is provided with a rear pressure conducting interface, and the interfaces are connected with external sensors through metal or high-strength plastic pipelines. The expansion sealing mechanism 6 usually comprises a plurality of cavities that can be inflated, and is inflated through grouting pressure, so as to realize close fitting with a hole wall and prevent leakage of grout. The front pressure conducting interface is used for sensing pressure change in front of the grouting area, and the rear pressure conducting interface is used for sensing rear pressure, and the two interfaces jointly form a double-end pressure monitoring point, and provide a key pressure difference signal for a subsequent control system. In actual use, the grouting pump is used to inject grout into the expansion sealing mechanism 6, so that the expansion sealing mechanism 6 is inflated and closely fitted with the hole wall, and a temporary but reliable sealing barrier is formed.

[0025] The grouting control module is responsible for the delivery and reflux control of the slurry, ensuring the stability and adjustability of the grouting process. The module includes a grouting pipeline 2, a return slurry pipeline 3, a grouting pump, a first electric control valve, and a second electric control valve. The grouting pump is usually a plunger or screw pump, with its outlet connected to the stopper body 1 through the grouting pipeline 2 for delivering the slurry. The first electric control valve is installed on the grouting pipeline 2 for adjusting the grouting flow rate; the second electric control valve is installed on the return slurry pipeline 3 for controlling the discharge of the reflux slurry. The grouting pump and the first electric control valve are arranged in series to achieve double regulation of the grouting process. The return slurry pipeline 3 is used to guide the excess slurry back to the slurry tank to maintain system pressure balance. In actual operation, the grouting pump adjusts the output pressure according to the control signal, the first electric control valve precisely controls the grouting flow rate by changing the opening degree, and the second electric control valve adjusts the return slurry flow rate according to the system pressure, all working together to ensure that the grouting process is both efficient and safe.

[0026] The monitoring control module is the intelligent decision-making center of the entire device, responsible for real-time data acquisition and issuing control instructions. The module includes a front pressure sensor 4, a rear pressure sensor 5, a flow sensor, and a controller. The front pressure sensor 4 is coupled with the front pressure transmission interface for monitoring the pressure at the front end of the grouting area; the rear pressure sensor 5 is coupled with the rear pressure transmission interface for monitoring the rear-end pressure. The flow sensor is installed on the grouting pipeline 2 for real-time measurement of the grouting flow rate. All sensors are connected to the signal input end of the controller to ensure high-frequency data acquisition and transmission. The controller is usually an embedded industrial computer or PLC with built-in special control algorithms that can quickly process input signals and output control instructions. The grouting pump, the first electric control valve, and the second electric control valve are all connected to the output end of the controller to achieve closed-loop control.

[0027] The pressure differential dynamic analysis algorithm built into the controller is the key to the intelligent control of the device. This algorithm calculates the pressure difference between the front and rear pressure sensors 5 in real time and, combined with the data from the flow sensor, comprehensively analyzes the grouting state. For example, when the pressure difference suddenly increases, it may indicate that the plugging has failed or the grouting pressure is too high, at which point the algorithm will generate corresponding adjustment signals. Specifically, the controller will output pressure adjustment signals for the grouting pump to control its working pressure, output opening control signals for the first electric control valve to adjust the grouting flow rate, and output opening control signals for the second electric control valve to adjust the return slurry flow rate. These signals are usually output in the form of PWM (Pulse Width Modulation) or 4-20mA current signals to ensure that the actuators can respond quickly. The algorithm can also adaptively adjust control parameters according to actual working conditions, such as adopting a more conservative control strategy when the pressure fluctuates greatly, and increasing the response speed during the stable stage.

[0028] The three modules of the grout stopping plugging module, the grouting control module and the monitoring control module work cooperatively to form a complete intelligent grouting control system. First, the grout stopping plugging module realizes preliminary plugging through the expansion sealing mechanism 6; then, the grouting control module starts grouting, and the monitoring control module collects real-time pressure and flow data; the controller dynamically analyzes the grouting state according to the data and generates control instructions through an algorithm to adjust the working state of the grouting pump and the electric control valve. The whole process realizes closed-loop control from data collection, analysis to execution, significantly improving the accuracy and reliability of the grouting process. Compared with the traditional grout stopping plugging device, the present scheme realizes real-time dynamic adjustment of the grouting process by introducing multi-sensor monitoring and intelligent control algorithm, significantly improving the reliability of plugging and the efficiency of grouting. The traditional device relies on manual experience or simple mechanical control, and it is difficult to deal with pressure fluctuations and flow changes under complex geological conditions, and problems such as loose plugging, waste of grout or out-of-control grouting pressure are prone to occur. While the device can maintain stable grouting state under different working conditions through automatic pressure difference analysis and multi-parameter collaborative control, reducing human intervention and reducing operation difficulty, while improving the adaptability and safety of the system. Overall, the device has obvious advantages in intelligence and automation, and is suitable for efficient and accurate plugging requirements in various grouting projects.

[0029] In another technical solution, the pressure difference dynamic analysis algorithm includes a data validity verification step, which compares the correlation between the change trend of the readings of the front pressure sensor 4 and the rear pressure sensor 5 and the change trend of the flow of the flow sensor to determine the reliability of the pressure data. When the instantaneous change amount of the pressure difference value of the front pressure sensor 4 and the rear pressure sensor 5 and the flow change amount do not satisfy the preset correlation, the data correction mode is enabled, the latest reliable pressure data and real-time flow data are weighted to generate a substitute pressure difference value; the controller maintains the output of the grouting pump pressure adjustment signal, the first electric control valve opening control signal and the second electric control valve opening control signal in the data correction mode, and sends a command to the grouting pump to keep the current working pressure until the pressure sensor data returns to normal correlation.

[0030] The pressure difference dynamic analysis algorithm compares the correlation between the change trend of the readings of the front and rear pressure sensors 5 and the change trend of the flow rate of the flow sensor to determine the reliability of the current pressure data. For example, during normal grouting, there is usually a certain physical correlation between the pressure difference and the flow rate, such as when the flow rate increases, the pressure difference may also increase accordingly. The system will preset a correlation, which may be based on historical data or a theoretical model, for example, it is set that within a certain time window, the rate of change of the pressure difference and the rate of change of the flow rate should be within a certain range, such as for every percentage point increase in the rate of change of the pressure difference, the rate of change of the flow rate should increase by three to eight percentage points, and this range can be adjusted according to the specific working conditions. If the instantaneous change in the pressure difference and the flow rate in the real-time data does not conform to the preset correlation, it is determined that the data is abnormal, which may be caused by temporary interference, blockage of the sensor or sudden change in the properties of the fluid.

[0031] When the data is abnormal, the system will enable the data correction mode. In this mode, the controller no longer directly uses the abnormal real-time pressure data, but instead uses the historical pressure data within a certain reliable time window and the current real-time flow rate data to perform weighted calculation to generate a substitute pressure difference value for control. In the weighted calculation, the weight of the historical data may be higher, for example, accounting for seventy to ninety percent, and the real-time flow rate data is used for fine tuning to ensure that the system can still operate based on reasonable speculation when the sensor is temporarily abnormal. At the same time, the controller sends instructions to the grouting pump to maintain the current working pressure, avoiding sudden changes in pressure caused by false data, which can cause plugging failure or waste of grout, until the system detects the normal correlation between the pressure sensor data and the flow rate change. This scheme significantly improves the robustness and fault tolerance of the control system when the sensor data is abnormal. Compared with the traditional system which is prone to misjudgment or protective shutdown when the data is abnormal, this design enables the device to smoothly transition and maintain stable operation for a period of time without interrupting the grouting process, thereby reducing production interruptions and efficiency losses caused by temporary data interference and improving the continuity and reliability of the entire grouting process.

[0032] The data correction mode includes a dynamic weight adjustment unit that calculates the weighting coefficient based on the duration of the pressure sensor data abnormality and the reliability of the flow sensor data; The dynamic weight adjustment unit monitors the recovery of the readings of the front pressure sensor 4 and the rear pressure sensor 5 in real time, and adjusts the weighting proportion of the latest reliable pressure data and real-time flow data when the data of any sensor returns to normal; the controller continuously compares the correlation of the instantaneous change of the pressure difference and the change of the flow in the data correction mode, and exits the data correction mode when the correlation is detected to return to a preset threshold; after exiting the data correction mode, the controller generates a mode switching instruction and transmits it to the grouting pump and the electric control valve, and restores the grouting pump pressure adjustment signal and the electric control valve opening control signal to the normal control mode.

[0033] The dynamic weight adjustment unit is used to more finely manage the generation of control signals during data anomalies. The unit calculates the weighting coefficient according to two main factors: one is the duration of pressure sensor data anomaly, for example, the longer the anomaly time, the higher the weight of historical data, which can be gradually increased from 60% to 95% over time; the other is the reliability of flow sensor data, if the flow data itself fluctuates little and meets expectations, its weight will also be increased accordingly. The dynamic weight adjustment unit continuously monitors the recovery of the readings of the front and rear pressure sensors 5, and immediately adjusts the weighting proportion and gradually increases the weight of real-time pressure data as soon as it finds that the data of any sensor returns to normal, for example, the readings re-enter a reasonable range and match the flow change trend. For example, the weight of real-time data is increased by 5% every second until it returns to the normal calculation mode.

[0034] The controller continuously compares the correlation of the instantaneous change of the pressure difference and the change of the flow in the data correction mode, which can be achieved by calculating the correlation coefficient in the moving window. A threshold value of 0.7 or higher is considered to be normal. When the correlation returns to the preset threshold, the system exits the data correction mode. When exiting, the controller generates a mode switching instruction and transmits it to the grouting pump and the electric control valve. The instruction does not immediately switch, but includes a gradual recovery process, for example, the grouting pump pressure adjustment signal and the electric control valve opening control signal are gradually adjusted to the target value in the normal control mode within two to three seconds, avoiding pressure shocks caused by sudden changes in output.

[0035] This scheme realizes smooth and stable transition between anomaly handling and normal control. Compared with the mode switching oscillation or control instruction jump that may occur in traditional systems, this dynamic weight adjustment and orderly recovery mechanism significantly improves the control quality and response continuity of the system, ensuring that the grouting process maintains high stability and predictability before and after data anomalies.

[0036] The dynamic weight adjustment unit includes a transition interval controller that establishes a gradual transition interval between the data correction mode and the normal control mode; the transition interval controller monitors the change rate of the weighting coefficient, and when the change rate of the weighting coefficient exceeds a set value, a gradual adjustment mechanism is enabled; the gradual adjustment mechanism uses a piecewise linear interpolation algorithm to gradually adjust the output values of the grouting pump pressure regulation signal and the electric control valve opening control signal to the target values within a preset time window; the transition interval controller compares the correlation degree of the instantaneous change amount of the pressure difference value and the flow change amount in real time, and when the correlation degree enters a stable interval, a mode switching preparation program is started; the mode switching preparation program sends a ready signal to the controller, and after the controller receives the ready signal, the control parameters of the data correction mode are removed in stages, and the operation weight of the normal control algorithm is gradually restored until the normal control mode is completely switched.

[0037] The transition interval controller is used to manage the switching process between the data correction mode and the normal control mode, to ensure that the system control signal does not change abruptly. The controller establishes a gradual transition interval between the two modes, which may last for several seconds to tens of seconds, and the specific time length can be set according to the actual system response speed, for example, five to ten seconds. The transition interval controller continuously monitors the change rate of the weighting coefficient in the dynamic weight adjustment unit, and if the rate exceeds a set value, for example, the weight changes more than fifteen percent per second, a gradual adjustment mechanism is enabled to prevent the control instruction from changing too fast.

[0038] The gradual adjustment mechanism uses a piecewise linear interpolation algorithm, for example, the entire transition interval is divided into several sub-stages, and the output values of the grouting pump pressure regulation signal and the electric control valve opening control signal are gradually adjusted to the target values in each stage. For example, first adjust the grouting pump pressure signal by thirty percent in the first second, and then adjust by twenty percent per second until the target is reached. At the same time, the transition interval controller continuously compares the correlation degree of the instantaneous change amount of the pressure difference value and the flow change amount, and when the correlation degree enters a stable interval, for example, the correlation coefficient is maintained above 0.8 for one second, the mode switching preparation program is started. The program sends a ready signal to the controller, and after the controller receives it, the control parameters of the data correction mode are removed in stages, for example, the pressure calculation weight is restored first, then the flow correction coefficient is restored, and at the same time the operation weight of the normal control algorithm is gradually restored until it is finally completely switched back to the normal control mode. This design improves the stability and safety of the system during mode switching. By establishing a gradual transition interval and a segmented adjustment mechanism, pressure fluctuations or mechanical shocks caused by sudden changes in control instructions are effectively avoided, making the entire grouting and plugging device exhibit higher smoothness and reliability during data anomaly handling and recovery, reducing equipment wear and process risk.

[0039] In another technical solution, the inflation sealing mechanism 6 comprises a ring-arranged pressure chamber group, each pressure chamber being provided with an independent pressure conduction channel; the pressure conduction channel forms a communication loop with the front and rear pressure conduction interfaces; a flexible partition layer made of elastic material is arranged between the pressure chambers; the front and rear pressure sensors 4 and 5 are coupled with the pressure conduction channel; the controller receives the multi-point pressure data of the front and rear pressure sensors 4 and 5, calculates the pressure difference value between each pressure chamber through a pressure differential dynamic analysis algorithm; the controller generates a grouting pump pressure adjustment signal according to the calculated pressure difference value, and the grouting pump pressure adjustment signal includes an independent pressure adjustment parameter for each pressure chamber.

[0040] The inflation sealing mechanism 6 adopts a ring-arranged pressure chamber group structure, each pressure chamber is usually composed of a high-elastic and wear-resistant material (such as polyurethane or reinforced rubber), and is distributed in a ring shape to jointly wrap the periphery of the grouting plug body 1. Each pressure chamber is provided with an independent pressure conduction channel, and an independent opening adjustment valve is arranged for independent pressure adjustment. These channels can be realized by small-diameter pipelines embedded in the grouting plug body 1, and the diameter can be between one to three millimeters, and the specific size can be adjusted according to the actual grouting pressure and the characteristics of the slurry. All these independent pressure conduction channels are finally connected with the front and rear pressure conduction interfaces respectively, forming a complete pressure conduction loop, so that the grouting pressure can be uniformly and independently transmitted to each chamber, and at the same time, it also provides a multi-point collection physical basis for front and rear pressure monitoring.

[0041] Between adjacent pressure chambers, a flexible partition layer made of elastic material is arranged. The role of the partition layer is to prevent pressure interference between chambers, and to allow the chamber to have a certain independent deformation ability when inflated, so as to better adapt to the shape of irregular hole wall and improve the sealing fit and reliability. The front and rear pressure sensors 4 and 5 are fixed with these pressure conduction channels through mechanical coupling or threaded connection, and real-time acquisition of the pressure value in each channel is realized, so as to obtain the pressure data of multiple measurement points.

[0042] The controller receives multi-point pressure data from the front and rear pressure sensors 5 and calculates the pressure difference values between the individual pressure chambers using a pressure differential dynamic analysis algorithm. For example, if the pressure in a certain chamber is significantly lower than that in other chambers, it may indicate a risk of leakage or blockage. Based on these calculated pressure difference values, the controller generates a grouting pump pressure regulation signal containing independent pressure adjustment parameters for each pressure chamber. In actual operation, the grouting pump can compensate for the specific chamber through multi-output or time-sharing control according to these independent parameters, thereby achieving fine balancing of the pressure between the chambers and ensuring uniform expansion of the annular sealing ring, effectively improving the integrity and safety of the plugging. This significantly improves the adaptability and sealing reliability of the plugging device under complex or irregular drilling conditions. By independently monitoring and controlling multiple pressure chambers, this design can achieve more accurate pressure balancing and more uniform radial expansion, avoiding the sealing failure problems that may occur due to local pressure deficiency or excessive pressure in traditional single-chamber structures, greatly enhancing the plugging effect and long-term stability of the device under harsh geological conditions.

[0043] In another technical solution, the controller includes a pressure-flow coupling analysis unit that receives the pressure difference value signals from the front and rear pressure sensors 4 and 5 and the real-time flow signals from the flow sensor; the pressure-flow coupling analysis unit processes the pressure difference value signals and the flow signals in time series alignment to generate a synchronized monitoring data set; the controller calculates the reference working pressure value of the grouting pump based on the pressure-flow correlation characteristics in the synchronized monitoring data set, converts the reference working pressure value into a pulse width modulation signal and transmits it to the motor driver of the grouting pump; the motor driver adjusts the armature voltage of the grouting pump according to the pulse width modulation signal to control the output pressure of the grouting pump; at the same time, the pressure-flow coupling analysis unit generates the opening correction coefficient of the first electric control valve based on the deviation value of the real-time flow signal from the preset reference flow and controls the opening of the first electric control valve.

[0044] The pressure-flow coupling analysis unit is introduced into the controller, which is a software function module or a special processing circuit inside the controller. Its core function is to receive the pressure difference value signals from the front and rear pressure sensors 5 and the real-time flow signals from the flow sensor. Since these signals come from different sensors and may have different collection times, the unit first processes them in time series alignment, such as using timestamp matching or interpolation algorithms, to combine the pressure difference value and flow value at the same time into a complete data record, thereby generating a synchronized monitoring data set to lay the foundation for subsequent correlation analysis.

[0045] The controller calculates based on the pressure-flow correlation characteristics in the synchronization data set, analyzes the dynamic coupling relationship between the two in the grouting process. For example, in the normal grouting stage, the increase of flow is usually accompanied by the increase of pressure difference, but the proportional relationship will change due to the viscosity of slurry, stratum absorption rate and other factors. By identifying this correlation feature, the unit can calculate the reference working pressure value of the grouting pump, which is a theoretical optimal value that meets the current working condition requirements. The reference working pressure value will be converted into a pulse width modulation (PWM) signal, such as a square wave signal with a frequency of 1 kHz to 5 kHz and adjustable duty cycle, which is transmitted to the motor driver of the grouting pump. The motor driver adjusts the armature voltage supplied to the motor of the grouting pump according to the duty cycle of the PWM signal, and then steplessly adjusts the output pressure of the grouting pump, forming a closed pressure control loop.

[0046] At the same time, the pressure-flow coupling analysis unit also compares the real-time flow signal with a preset reference flow value and calculates the deviation value. The reference flow may be set according to the design grouting rate, such as a value between 10 liters and 50 liters per minute. According to the size and direction of the deviation, the unit generates a coefficient for correcting the opening of the first electric control valve, such as a multiplication factor between 0.8 and 1.2. The coefficient is applied to the opening control algorithm of the first electric control valve, so that the opening of the valve increases or decreases, thereby dynamically adjusting the actual grouting flow to approximate the preset reference value, achieving precise closed-loop control of the grouting flow. The scheme realizes high-precision collaborative control of the two key parameters of grouting pressure and flow. Through the coupling analysis of pressure and flow and independent closed-loop regulation circuit, the system can automatically adapt to the changes of stratum resistance and slurry characteristics in the grouting process, significantly improving the stability and control accuracy of the grouting process, avoiding the process fluctuations and material waste problems caused by the disconnection of pressure and flow control in traditional methods, and making the entire grouting and plugging process more efficient and reliable.

[0047] In another technical solution, the monitoring control module comprises a data verification unit, which receives the original monitoring data of the front pressure sensor 4, the rear pressure sensor 5 and the flow sensor; the data verification unit comprises three independent data processing channels, each of which corresponds to a sensor signal; each data processing channel comprises a signal filtering circuit and an analog-to-digital conversion module, the signal filtering circuit adopts a second-order Butterworth filter, and the analog-to-digital conversion module adopts a 16-bit precision converter; the output ends of the three data processing channels are connected to a data comparator, which simultaneously receives the expected data range value issued by the controller; the data comparator compares the sensor data processed by the data processing channel with the expected data range value in real time, and sends a data abnormality flag signal to the controller when any sensor data exceeds the expected data range; after receiving the data abnormality flag signal, the controller automatically switches to a backup control mode, takes the historical data mean value in the latest reliable time window as a control reference value, and maintains the output of the grouting pump pressure adjustment signal and the electric control valve opening control signal according to the control reference value.

[0048] The monitoring control module introduces a data verification unit, which is a key component for achieving high-reliability data acquisition and processing. The data verification unit is responsible for receiving the original monitoring data from the front pressure sensor 4, the rear pressure sensor 5 and the flow sensor, which are usually continuous analog voltage or current signals. To ensure independent and accurate processing of each sensor signal, the unit contains three completely independent data processing channels, each of which corresponds to a sensor signal. Within each data processing channel, the signal is first processed by a signal filtering circuit, which can be designed as a second-order Butterworth low-pass filter, for example, with a cutoff frequency set between 10 Hz and 50 Hz, aiming to effectively filter out high-frequency noise from the field power equipment, random electromagnetic interference, etc. The filtered analog signal is then sent to an analog-to-digital conversion module, which can use a 16-bit precision ADC converter to convert the analog signal to a digital value, with a sampling rate of more than 100 times per second, thus ensuring accuracy while capturing rapid changes in pressure.

[0049] The outputs of the three data processing channels are finally connected to a logic unit called data comparator. The data comparator receives from the controller a real-time issued expected data range value, which is set as the reasonable upper and lower limits of the readings of the sensors under the current working condition. The data comparator continuously compares the filtered and digitized sensor data with the dynamic expected range in real time. For example, the reading range of the front pressure sensor 4 may fluctuate between 5 MPa and 20 MPa, and the specific value is dynamically set by the control system according to the grouting stage. When the data comparator detects that the real-time data of any sensor continuously exceeds the expected range, for example, the reading of the rear pressure sensor 5 suddenly drops below 1 MPa or soars above 25 MPa, and continues to exceed a very short time window (such as 100 milliseconds), it will send a digital data anomaly flag signal to the controller.

[0050] After receiving the data anomaly flag signal, the controller will immediately start the pre-set fault-tolerant processing mechanism and automatically switch from the normal control mode to the backup control mode. In this mode, the controller no longer relies on the real-time sensor data that is judged to be abnormal, but instead calls its stored historical data. It will take the historical data in the last reliable time window, for example, the data in the past 5 to 10 seconds, calculate the moving average of these historical data, and use the average as the reference value for the current control cycle. Based on this historical reference value, the controller continues to generate the grouting pump pressure regulation signal and the electrically controlled valve opening control signal, so as to maintain the system in a relatively stable and safe state to continue running, while continuously monitoring whether the abnormal sensor data returns to normal in the background, preparing for switching back to the normal mode. This design greatly enhances the data reliability and decision safety of the entire control system in the face of sensor failure or strong interference. Through independent channel processing, real-time data validity verification, and seamless switching to backup control strategy, the system can effectively avoid control failure or system shutdown caused by single-point data error, and significantly improve the anti-interference ability and continuous running stability of the device in complex industrial environments.

[0051] The data verification unit comprises a historical data tracing program, which, upon receiving the data anomaly flag signal, searches the historical data storage area within the most recent reliable time window; the historical data storage area adopts a ring buffer structure and stores the monitoring data of the front pressure sensor 4, the rear pressure sensor 5 and the flow sensor in chronological order; the historical data tracing program filters the historical data in the buffer area through a data quality evaluation algorithm, which calculates the smoothness index of the monitoring data at each time point and the data at adjacent time points; the data quality evaluation algorithm selects a continuous time segment with the optimal smoothness index, and calculates the weighted average of the sensor data in the segment; the controller uses the weighted average as the control basis in the standby control mode to generate the grouting pump pressure regulating signal and the electrically controlled valve opening control signal, while continuously monitoring whether the sensor data has returned to normal.

[0052] The data verification unit uses a historical data tracing program, which is activated immediately upon receiving the data anomaly flag signal from the data comparator. Its primary task is to search for the recent valid data stored in a specific historical data storage area, which usually adopts a ring buffer (or circular buffer) data structure. The buffer occupies a fixed-size continuous space in the memory, and its capacity may be designed to store sensor data for the last 30 seconds to several minutes. The data is sequentially stored according to the millisecond or centisecond timestamp, and when the buffer is full, the newest data will overwrite the oldest data, achieving continuous rolling update.

[0053] The historical data tracing program does not simply use all the data in the buffer, but intelligently filters the historical data within a specific time window through a data quality evaluation algorithm. The algorithm calculates the rate of change or derivative of the monitoring data at each time point in the buffer and its adjacent time points, and then obtains a "smoothness index" to quantify the reliability of the data point. Because a sudden rise or fall in the smoothness of the data point may be caused by interference. The algorithm scans the buffer to find a continuous time segment with the optimal smoothness index, such as the most stable 5 seconds of data in the past 10 seconds. Then, the program calculates the weighted average of the sensor data in the high-quality segment, and the data points closer to the current time may be given higher weights, such as exponential weighted average, to obtain a reliable estimate value that better reflects the recent trend.

[0054] In the backup control mode, the controller uses this calculated weighted average as the core control basis. It uses this value to generate the grouting pump pressure regulation signal and the electric control valve opening control signal, so that the action of the actuator is based on a reliable historical trend rather than invalid instantaneous values, thereby avoiding the sharp jump of control instructions. Throughout the process, the controller continues to monitor the sensor data stream marked as abnormal in the background, and once it finds that its readings re-enter the expected range and remain stable for more than a set period of time, it will initialize the program to exit the backup mode, gradually restore trust in real-time data, and smoothly transition back to normal control mode. This scheme provides higher-level intelligent fault-tolerant control capabilities. It extracts and analyzes high-quality information from historical data, enabling the system to make near-optimal decisions even in the presence of partial sensor data distortion, greatly reducing the probability of unplanned downtime, ensuring high continuity of the process, and improving the system's resilience and self-maintenance capabilities in the face of unexpected abnormal states.

[0055] The expected data range value is generated by a data learning module, which continuously collects monitoring data of the front pressure sensor 4, the rear pressure sensor 5 and the flow sensor under normal working conditions to establish a sensor data feature library. The data learning module uses a sliding time window method to statistically analyze the data in the feature library and calculates the mean and standard deviation of each sensor data. The expected data range value is dynamically determined based on the mean and standard deviation, with the upper limit being the mean plus three times the standard deviation and the lower limit being the mean minus three times the standard deviation. The data learning module updates the expected data range value every five minutes and transmits the updated value to the data comparator. The data comparator compares the real-time sensor data with the dynamically updated expected data range value, and immediately sends a data abnormality flag signal to the controller when the data is out of range.

[0056] By introducing the data learning module, the system has self-learning and self-adaptive capabilities, rather than relying on fixed, pre-set data ranges. The data learning module is a software process that runs continuously in the background of the controller, which continuously collects monitoring data of the front pressure sensor 4, the rear pressure sensor 5, and the flow sensor under the system being confirmed as normal working conditions (such as manual confirmation or through other indicators). These massive time series data are stored and built into a growing sensor data feature library for learning normal data patterns under different grouting stages and different geological conditions. The module uses a sliding time window to statistically analyze the data in the feature library. For example, it may always take the "normal" data in the last 24 hours as the analysis sample. For each sensor, it periodically (such as every minute) calculates the arithmetic mean and standard deviation of all data in the sliding window. Subsequently, it dynamically determines the expected reasonable data range for each sensor based on classical statistical principles, usually setting the upper limit value to the mean plus several times the standard deviation, and the lower limit value to the mean minus several times the standard deviation. This multiple can be 2 times, 3 times, or other values, for example, using 3 times the standard deviation means that theoretically 99.7% of normal data should fall within this range. These dynamically calculated range values (for example, the front pressure range may be updated to [7.2MPa, 18.5MPa]) will be updated every fixed period, for example, every five minutes, and transmitted to the data comparator.

[0057] After receiving the updated expected data range values, the data comparator immediately uses them as the benchmark for the next round of comparison. It compares the real-time collected and pre-processed sensor data with these latest, dynamic ranges. Since these range values are learned based on the system's own recent running history, they can more accurately reflect the current actual working conditions, for example, in the initial, stable, and end stages of grouting, the pressure range itself has a large difference. Once the real-time data exceeds this dynamic range, the data comparator will be very sensitive and immediately send a data anomaly flag signal to the controller, thereby achieving early and accurate warning of abnormal conditions. The system has significantly improved its intelligent level and self-adaptive capability. By continuously learning normal conditions, the system can automatically adjust its "normal" benchmark for monitoring, making the abnormal judgment more accurate, effectively reducing false alarms due to normal changes in working conditions, while being able to timely detect real abnormal signs, greatly enhancing the reliability of state monitoring and the effectiveness of early warning, making the entire device more intelligent and more in line with actual production needs.

[0058] In another technical solution, the pressure difference dynamic analysis algorithm includes a rate of change calculation program and a segmented control mechanism; the rate of change calculation program calculates the change in the pressure difference between the front pressure sensor 4 and the rear pressure sensor 5 per unit time in real time, and triggers the segmented control mechanism when the change per unit time exceeds a set threshold; the segmented control mechanism divides the control process into three consecutive stages according to the numerical range of the change per unit time: in the first stage, the grouting pump pressure adjustment signal is adjusted to make the grouting pump output pressure decrease according to a linear law; in the second stage, the first electric control valve opening control signal is controlled to make the first electric control valve opening decrease according to a parabolic law; and in the third stage, the second electric control valve opening control signal and the grouting pump pressure adjustment signal are simultaneously adjusted to make the return slurry flow and the grouting flow maintain a predetermined proportional relationship.

[0059] The core control logic of the pressure difference dynamic analysis algorithm includes a rate of change calculation program and a segmented control mechanism to deal with high-risk working conditions such as sudden pressure changes that may occur during grouting. The rate of change calculation program is a real-time monitoring unit in the algorithm, which continuously calculates the change in the pressure difference per unit time measured by the front pressure sensor 4 and the rear pressure sensor 5, i.e., the rate of change of the pressure difference. This calculation is usually based on high-frequency sampled pressure data, for example, the system samples 100 times per second, and the program calculates the difference between the current sampling value and the sampling value one second ago, and then divides by the time interval to obtain the instantaneous rate of change in units of megapascals per second (MPa / s). The system will preset one or more rate of change thresholds to determine whether the working condition has entered an abnormal state, for example, a first-level threshold of 0.5 MPa / s and a second-level threshold of 2.0 MPa / s. These thresholds are reference values obtained from a large amount of historical working condition data and can be adjusted according to the properties of the slurry and the formation conditions of the actual application scenario. When the program calculates the change per unit time that exceeds the set threshold, a more complex segmented control mechanism is immediately triggered, which is the core protection strategy of the system to prevent pressure runaway.

[0060] The segmented control mechanism intelligently divides the subsequent control process into three consecutive and logically rigorous stages according to the numerical range of the change rate when triggered, and each stage adopts a corresponding control strategy for different risk levels. The first stage mainly targets the initial risk when the change rate just exceeds the threshold, and the control goal is to quickly suppress the rapid growth of the pressure difference. At this time, the controller will preferentially adjust the pressure regulating signal output to the grouting pump, which may be a gradually decreasing command that makes the output pressure of the grouting pump decrease according to a preset linear law, for example, reducing the target pressure by 5-10% of the peak value every second in the next two seconds, thereby slowing down the grouting flow from the source and containing the expansion of the pressure difference. If the pressure difference change rate continues to increase or remains high, the system enters the second stage with stronger control. This stage continues to control the pump pressure while focusing on the opening of the first electric control valve. The opening control signal generated by the controller will make the opening of the first electric control valve decrease according to a parabolic law, which ensures that the opening changes quickly in the initial stage to achieve rapid response, and then gradually slows down to avoid water hammer effect caused by the valve closing too quickly. This process may last for three to five seconds. If the control of the previous two stages still cannot return the system to stability, the pressure difference change rate enters the high-risk interval, and the third stage is started. In this stage, the controller will simultaneously adjust the opening control signal of the second electric control valve and the pressure regulating signal of the grouting pump, and the core control goal is to maintain a predetermined proportional relationship between the return slurry pipeline 3 flow and the grouting pipeline 2 flow, for example, controlling the return slurry flow to be 20-40% of the grouting flow, actively and controllably releasing part of the slurry to ensure that the annulus pressure is within a safe range and prevent pump blocking or sealing failure. The entire segmented control process is not rigidly executed, and the controller continuously monitors the decline of the pressure difference change rate at each stage. Once the change rate falls below the safety threshold, the system gradually removes the segmented control and smoothly returns to the normal pressure difference dynamic analysis algorithm control mode. This design ensures that the control response is both quick and decisive when dealing with sudden changes in pressure, and avoids system oscillation caused by excessive adjustment.

[0061] This scheme significantly enhances the rapid response capability and control safety of the system when facing sudden conditions such as rapid pressure changes. Through hierarchical and segmented fine control strategies, this mechanism can effectively suppress the abnormal expansion of the pressure difference, smoothly resolve system risks, and avoid sealing failure, pipeline damage, and even engineering accidents that may be caused by traditional single control methods due to slow response or excessive control, greatly improving the safety and robustness of the entire grouting process.

[0062] It is to be understood that the number of units and the scale of processing described herein are used to simplify the description of the application, and that applications, modifications and variations of the application will be apparent to those skilled in the art. Although embodiments of the application have been disclosed in connection with the illustrative embodiments described above, it should be understood that they can be applied in various fields of endeavor, and that there are many modifications, adaptations and variations which are particularly suited to some alternative embodiments. Therefore, the precise embodiments disclosed above are not to be taken in a limiting sense, and the scope of the present application is defined by the appended claims and their equivalents.

Claims

1. A slurry stopping plugging device, characterized by, It includes a grout sealing module, a grouting control module, and a monitoring control module; The grout sealing module includes a grout plug body and an expansion sealing mechanism. The grout plug body has a front pressure transmission interface at the front end and a rear pressure transmission interface at the rear end. The grouting control module includes a grouting pipeline, a return grouting pipeline, a grouting pump, a first electrically controlled valve, and a second electrically controlled valve. The grouting pump and the first electrically controlled valve are connected in series on the grouting pipeline, and the second electrically controlled valve is located on the return grouting pipeline. The monitoring and control module includes a front pressure sensor, a rear pressure sensor, a flow sensor, and a controller. The front pressure sensor is coupled and fixed to the front pressure transmission interface, the rear pressure sensor is coupled and fixed to the rear pressure transmission interface, and the flow sensor is installed on the grouting pipeline. The front pressure sensor, the rear pressure sensor, and the flow sensor are all connected to the signal input terminal of the controller, and the grouting pump, the first solenoid valve, and the second solenoid valve are all connected to the signal output terminal of the controller. The controller has a built-in dynamic pressure difference analysis algorithm, which calculates the pressure difference between the front and rear pressure sensors in real time. Based on the real-time change characteristics of the pressure difference and the flow data from the flow sensor, it generates a grouting pump pressure regulation signal, a first solenoid valve opening control signal, and a second solenoid valve opening control signal. The controller outputs the grouting pump pressure regulation signal to control the working pressure of the grouting pump, outputs the first solenoid valve opening control signal to regulate the grouting flow, and outputs the second solenoid valve opening control signal to regulate the return grout flow.

2. The grout-stopping and sealing device according to claim 1, characterized in that, The pressure difference dynamic analysis algorithm includes a data validity verification step, which judges the reliability of the pressure data by comparing the correlation between the reading change trends of the front and rear pressure sensors and the flow change trend of the flow sensor. When the instantaneous change in the pressure difference between the current pressure sensor and the subsequent pressure sensor does not meet the preset correlation with the flow rate change, the data correction mode is activated. The most recent reliable pressure data and real-time flow data are used for weighted calculation to generate an alternative pressure difference. In the data correction mode, the controller maintains the output of the grouting pump pressure regulation signal, the first solenoid valve opening control signal, and the second solenoid valve opening control signal, and at the same time sends a command to the grouting pump to maintain the current working pressure until the pressure sensor data returns to normal correlation.

3. The grout-stopping and sealing device according to claim 2, characterized in that, The data correction mode includes a dynamic weight adjustment unit, which calculates weighting coefficients based on the duration of pressure sensor data anomalies and the reliability of flow sensor data. The dynamic weight adjustment unit monitors the recovery of readings from the upstream and downstream pressure sensors in real time. When the data from either sensor returns to normal, it adjusts the weighting ratio of the most recent reliable pressure data and the real-time flow data. In data correction mode, the controller continuously compares the correlation between the instantaneous change in pressure difference and the change in flow rate. When the correlation is detected to have recovered to a preset threshold, the controller exits the data correction mode. After exiting the data correction mode, the controller generates a mode switching command and transmits it to the grouting pump and the electric control valve, restoring the grouting pump pressure regulation signal and the electric control valve opening control signal to the normal control mode.

4. The grout-stopping and sealing device according to claim 3, characterized in that, The dynamic weight adjustment unit includes a transition interval controller, which establishes a gradual transition interval between the data correction mode and the normal control mode. The transition interval controller monitors the rate of change of the weighting coefficients. When the rate of change of the weighting coefficients exceeds the set value, the gradual adjustment mechanism is activated. The gradual adjustment mechanism uses a piecewise linear interpolation algorithm to gradually adjust the output values ​​of the grouting pump pressure regulation signal and the electric valve opening control signal to the target value within a preset time window. The transition interval controller compares the correlation between the instantaneous change in pressure difference and the change in flow rate in real time. When the correlation enters the stable range, the mode switching preparation program is started. The mode switching preparation program sends a ready signal to the controller. After receiving the ready signal, the controller releases the control parameters of the data correction mode in stages and gradually restores the calculation weights of the normal control algorithm until it is fully switched to the normal control mode.

5. The grout-stopping and sealing device according to claim 1, characterized in that, The expansion sealing mechanism includes a ring-shaped group of pressure chambers, each with an independent pressure transmission channel. The pressure transmission channel forms a continuous loop with the front and rear pressure transmission interfaces. A flexible partition layer made of elastic material is provided between the pressure chambers. The front and rear pressure sensors are coupled to the pressure transmission channels. The controller receives multi-point pressure data from the front and rear pressure sensors and calculates the pressure difference between each pressure chamber using a dynamic pressure difference analysis algorithm. The controller generates a grouting pump pressure adjustment signal based on the calculated pressure difference, which includes independent pressure adjustment parameters for each pressure chamber.

6. The grout-stopping and sealing device according to claim 1, characterized in that, The controller includes a pressure-flow coupling analysis unit, which receives the pressure difference signal from the upstream pressure sensor and the downstream pressure sensor, as well as the real-time flow signal from the flow sensor. The pressure-flow coupling analysis unit performs time-series alignment processing on the pressure difference signal and the flow signal to generate a synchronous monitoring dataset. The controller calculates the reference working pressure value of the grouting pump based on the pressure-flow correlation characteristics in the synchronous monitoring dataset, converts the reference working pressure value into a pulse width modulation signal, and transmits it to the motor driver of the grouting pump. The motor driver adjusts the armature voltage of the grouting pump according to the pulse width modulation signal to control the output pressure of the grouting pump; at the same time, the pressure-flow coupling analysis unit generates the opening correction coefficient of the first solenoid valve according to the deviation between the real-time flow signal and the preset reference flow and controls the opening of the first solenoid valve.

7. The grout-stopping and sealing device according to claim 1, characterized in that, The monitoring and control module includes a data verification unit that receives raw monitoring data from the upstream pressure sensor, downstream pressure sensor, and flow sensor. The data verification unit comprises three independent data processing channels, each corresponding to a sensor signal. Each data processing channel includes a signal filtering circuit and an analog-to-digital converter (ADC). The signal filtering circuit uses a second-order Butterworth filter, and the ADC uses a 16-bit precision converter. The outputs of the three data processing channels are connected to a data comparator, which simultaneously receives the expected data range value from the controller. The data comparator compares the sensor data processed by the data processing channels with the expected data range value in real time. When any sensor data exceeds the expected data range, the data comparator sends a data anomaly flag signal to the controller. Upon receiving the data anomaly flag signal, the controller automatically switches to standby control mode, using the average historical data within the most recent reliable time window as the control reference value, and maintaining the output of the grouting pump pressure regulation signal and the electric valve opening control signal based on the control reference value.

8. The grout-stopping and sealing device according to claim 7, characterized in that, The data verification unit includes a historical data tracing program. When it receives a data anomaly flag signal, the program retrieves the historical data storage area within the most recent reliable time window. The historical data storage area adopts a circular buffer structure, storing monitoring data from the upstream pressure sensor, downstream pressure sensor, and flow sensor in chronological order. The historical data tracing program filters the historical data in the buffer using a data quality assessment algorithm, which calculates the smoothness index between the monitoring data at each time point and the data at adjacent time points. The algorithm selects the continuous time segment with the optimal smoothness index and calculates the weighted average of the sensor data within that segment. In standby control mode, the controller uses the weighted average as the control basis to generate grouting pump pressure regulation signals and electronic valve opening control signals, while continuously monitoring whether the sensor data has returned to normal.

9. The grout sealing device according to claim 7, characterized in that, The expected data range is generated by the data learning module, which continuously collects monitoring data from the upstream pressure sensor, downstream pressure sensor, and flow sensor under normal operating conditions to establish a sensor data feature library. The data learning module uses a sliding time window approach to perform statistical analysis on the data in the feature library, calculating the mean and standard deviation of each sensor data point. The expected data range is dynamically determined based on the mean and standard deviation, with the upper limit being the mean plus three times the standard deviation and the lower limit being the mean minus three times the standard deviation. The data learning module updates the expected data range every five minutes and transmits the updated values ​​to the data comparator. The data comparator compares the real-time sensor data with the dynamically updated expected data range, and sends a data anomaly flag signal to the controller when the data exceeds the range.

10. The grout-stopping and sealing device according to claim 1, characterized in that, The pressure difference dynamic analysis algorithm includes a change rate calculation program and a segmented control mechanism. The change rate calculation program calculates the unit time change of the pressure difference between the front pressure sensor and the rear pressure sensor in real time. When the unit time change exceeds the set threshold, the segmented control mechanism is triggered. The segmented control mechanism divides the control process into three continuous stages according to the numerical range of the unit time change: the first stage adjusts the grouting pump pressure regulation signal so that the grouting pump output pressure decreases linearly. The second stage controls the opening control signal of the first solenoid valve, causing the opening of the first solenoid valve to decrease according to a parabolic law; the third stage synchronously adjusts the opening control signal of the second solenoid valve and the pressure adjustment signal of the grouting pump, so that the return grout flow rate and the grouting flow rate maintain a predetermined proportional relationship.

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