Water-rich tunnel drainage and pressure reduction regulation and control method and system

Abstract

The invention relates to the technical field of tunnel drainage and pressure reduction control, and discloses a water-rich tunnel drainage and pressure reduction regulation and control method and system which comprises an information sensing unit, an intelligent analysis unit and an execution regulation and control unit. The information sensing unit collects water pressure and drainage flow data behind the tunnel lining in real time; the intelligent analysis unit generates a regulation and control signal based on a preset logic rule and realizes prospective adjustment through a trend prediction module; the execution regulation and control unit accurately controls the drainage flow through an intelligent regulation device, and the water pressure is maintained within a safe range. According to the system, the multi-source data fusion and machine learning technology is adopted, the hysteresis problem of a traditional drainage system is solved, energy waste and environmental influence are avoided, and reliable guarantee is provided for safe operation of the water-rich tunnel.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of tunnel water discharge and pressure reduction control, and specifically relates to a water-rich tunnel water discharge and pressure reduction regulation method and system. BACKGROUND

[0002] In the construction and operation process of a water-rich tunnel, the water pressure of the surrounding rock behind the tunnel lining is a key safety factor. Excessive water pressure can cause deformation, cracking and even instability of the lining structure, thereby affecting the long-term safety and stability of the tunnel. Traditionally, in order to reduce the water pressure behind the lining, a seepage pressure gauge and drainage facilities are usually set up for water discharge and pressure reduction. However, these methods rely on real-time monitoring feedback mechanisms, and their regulation decisions are based on single-dimensional immediate water pressure data, lacking the ability to predict water pressure trends, making it difficult for the system to adapt to dynamic and variable hydrogeological conditions.

[0003] In addition, the existing water discharge system often shows a response lag when dealing with sudden heavy rainfall or changes in upstream water sources. Since the regulation behavior of the system is limited to whether the immediate pressure value exceeds the preset threshold, it may not be able to start the drainage measures in time when the pressure rises rapidly, increasing the risk of the lining structure bearing over-limit pressure. At the same time, frequent start-stop of drainage equipment in unnecessary cases not only causes energy waste, but also may cause regional groundwater level to drop, thereby causing uneven ground consolidation and ground subsidence, etc., and has potential impact on the surrounding environment.

[0004] Therefore, there is an urgent need for an intelligent water discharge regulation system that can integrate multi-source information and achieve forward-looking prediction to improve the safety of tunnel structures, and also take into account energy utilization efficiency and environmental protection needs. SUMMARY

[0005] The purpose of the present application is to provide a water-rich tunnel water discharge and pressure reduction regulation method and system to solve the problems raised in the background.

[0006] To achieve the above object, the present application provides a water-rich tunnel drainage pressure reduction regulation system applied to adjusting the water pressure of surrounding rock behind the tunnel lining, comprising an information sensing unit configured to acquire real-time water pressure data behind the tunnel lining and real-time drainage flow data in the drainage pipeline laid in the tunnel; an intelligent analysis unit connected with the information sensing unit through wired or wireless communication mode, configured to receive the real-time water pressure data and real-time drainage flow data, analyze and judge the received data based on preset logical rules to generate corresponding regulation signals; and an execution regulation unit connected with the intelligent analysis unit through a control signal link, configured to receive and respond to the regulation signals to accurately adjust the drainage flow of the drainage pipeline, so as to maintain the water pressure behind the tunnel lining within a preset safe range.

[0007] The information sensing unit comprises at least one set of pressure detection device, the sensing end of which is placed inside the tunnel lining by embedded installation or surface fixation to directly contact the water environment of surrounding rock behind the lining, thereby continuously monitoring and outputting the real-time water pressure data; and at least one set of flow detection device installed on the drainage pipeline by flange connection or clamp fixation to continuously monitor and output the instantaneous drainage flow through the execution regulation unit as the real-time drainage flow data.

[0008] The functional modules of the intelligent analysis unit are divided into a signal processing module and a decision calculation module. The signal processing module is configured to receive raw sensing data from the information sensing unit, perform digital filtering operation and validity verification on the raw sensing data to generate stable and reliable real-time pressure values and real-time flow values; and the decision calculation module is configured to acquire the real-time pressure values and real-time flow values processed by the signal processing module, perform logical analysis on these values according to preset parameter thresholds, and then generate the regulation signals.

[0009] The signal processing module adopts wavelet transform algorithm or adaptive filtering algorithm to perform digital filtering operation on the received raw sensing data to eliminate the influence of field noise interference and signal fluctuation on measurement accuracy.

[0010] The preset parameter thresholds in the decision calculation module include pressure upper threshold, target pressure value, pressure lower threshold and flow abnormal threshold; and the thresholds are preset according to the tunnel geological survey report, surrounding rock stability evaluation and lining structure mechanical property analysis.

[0011] The logic rule executed by the decision calculation module specifically includes the following: when it is judged that the real-time pressure value is greater than or equal to the pressure upper limit threshold value, a signal driving the execution control unit to be fully opened is generated; when it is judged that the real-time pressure value is less than the pressure upper limit threshold value and greater than the target pressure value, a fuzzy control algorithm is started, taking the target pressure value as a reference value, and an accurate adjustment signal for smoothly adjusting the real-time pressure value to the target pressure value is calculated; when it is judged that the real-time pressure value is less than the pressure lower limit threshold value, a signal driving the execution control unit to be reduced in opening degree or completely closed is generated.

[0012] The core component of the execution control unit is an intelligent adjustment device, and the structure of the intelligent adjustment device includes a main body having a threaded interface for connecting the drainage pipeline; an adjustment element arranged in the main body and used for adjusting the flow cross section of water; and a driving assembly connected with the adjustment element and used for driving the adjustment element to be accurately positioned according to the control signal.

[0013] The adjustment element adopts a multi-stage throttling structure, a plurality of radial micro-hole channels are formed on the outer wall of the structure, the micro-hole channels are gradually opened or closed through the axial movement of the adjustment element to realize the step-by-step control of the total pressure drop, and the key throttling surface of the adjustment element in contact with the water flow is formed with a high-hardness wear-resistant coating through a thermal spraying process to resist the erosion and corrosion of the high-pressure water flow.

[0014] The driving assembly is an integrated intelligent electric actuator, and a stepping motor, a gear transmission mechanism and a position sensor are integrated in the driving assembly; the position sensor is used for detecting the actual displacement of the adjustment element in real time and feeding back the displacement information to the intelligent analysis unit to constitute a position closed-loop control of the adjustment opening degree.

[0015] A water-rich tunnel drainage pressure reduction control method includes the following steps: information real-time acquisition, through a pressure detection device arranged behind a tunnel lining and a flow detection device installed on a drainage pipeline, real-time water pressure data and real-time drainage flow data are continuously acquired at a preset sampling period; state analysis and signal generation, the real-time pressure value and the real-time flow value obtained after being collected and processed are continuously compared and analyzed with a preset pressure upper limit threshold value, a target pressure value and a pressure lower limit threshold value, and a control signal is generated accordingly; signal execution, the control signal is sent to an intelligent adjustment device installed on the drainage pipeline to drive the intelligent adjustment device to adjust the opening degree thereof to change the drainage flow; feedback and cycle, the steps of information real-time acquisition, state analysis and signal generation and signal execution are continuously executed to form a closed-loop feedback control, so as to dynamically maintain the water pressure behind the tunnel lining in an ideal safety range defined by the target pressure value and the pressure lower limit threshold value.

[0016] Further technical features of the present application are that the intelligent analysis unit further comprises a trend prediction module configured to fuse multi-source heterogeneous data inside and outside the tunnel, including but not limited to real-time water pressure data inside the tunnel, real-time drainage flow data, surrounding rock seepage pressure data, and meteorological forecast data (such as future 72-hour rainfall) outside the tunnel, and peripheral hydrogeological data. The trend prediction module models and analyzes the above-mentioned data through a machine learning algorithm to predict the water pressure change trend in the future and generate a corresponding forward control signal.

[0017] The trend prediction module uses a long short-term memory network (LSTM) or a support vector machine (SVM) algorithm to model multi-source data to capture the nonlinear relationship between the time series characteristics of water pressure changes and external influencing factors.

[0018] The specific generation rules of the forward control signal include the following contents: when the prediction result shows that the future water pressure value may exceed the pressure upper limit threshold, a signal is generated in advance to drive the execution control unit to gradually increase; when the prediction result shows that the future water pressure value may be lower than the pressure lower limit threshold, a signal is generated in advance to drive the execution control unit to gradually decrease or shut down.

[0019] The information perception unit further comprises an auxiliary detection device configured to monitor the temperature, humidity and groundwater chemical composition of the surrounding environment of the tunnel to supplement the completeness of the multi-source data; the auxiliary detection device establishes a data connection with the intelligent analysis unit through wireless communication.

[0020] The main body of the intelligent adjustment device is made of corrosion-resistant material and coated with an epoxy resin coating on its outer surface to enhance its corrosion resistance; the key throttling surface of the adjustment element is formed with a high-hardness alloy coating through a laser cladding process to improve its erosion resistance.

[0021] The gear transmission mechanism of the intelligent electric actuator adopts a precision helical gear design to reduce friction loss and noise during transmission; the stepper motor is provided with a temperature control protection circuit to prevent damage caused by overload or overheating.

[0022] Compared with the prior art, the present application has the following advantages: The present application introduces multi-source data fusion and machine learning technology to construct an intelligent control system that can predict the future water pressure change trend. This system not only solves the problem of passive response lag of traditional drainage systems, but also avoids energy waste and environmental impact caused by excessive drainage, providing a reliable guarantee for the safe operation of water-rich tunnels. BRIEF DESCRIPTION OF DRAWINGS

[0023] Figure 1 The overall structure of the system of the present application is shown in the figure.

[0024] Figure 2 The composition of the information sensing unit is shown in the figure.

[0025] Figure 3 The functional module diagram of the intelligent analysis unit is shown in the figure.

[0026] Figure 4 The core component structure of the execution control unit is shown in the figure.

[0027] Figure 5 The flow chart of the method of the present application is shown in the figure. DETAILED DESCRIPTION

[0028] The present application relates to a water-rich tunnel water discharge pressure reduction control method and system, which realizes dynamic control of water pressure of surrounding rock behind tunnel lining through the cooperative work of an information sensing unit, an intelligent analysis unit and an execution control unit. The following will be described in detail in combination with the accompanying Figure 1 to the accompanying Figure 5 The specific embodiments of the present application will be described in detail.

[0029] In actual application, the information sensing unit includes at least one set of pressure detection devices and at least one set of flow detection devices. The sensing end of the pressure detection device is arranged in the embedded or surface fixed manner inside the tunnel lining, directly contacts with the water environment of surrounding rock behind the lining, and is used for continuously monitoring and outputting real-time water pressure data. The flow detection device is installed on the drainage pipeline in the flange connection or clamp fixed manner, and is used for continuously monitoring and outputting instantaneous drainage flow data as real-time drainage flow data. Each device in the information sensing unit transmits the collected data to the intelligent analysis unit through wired or wireless communication, so as to realize centralized processing and analysis of the data.

[0030] The functional modules of the intelligent analysis unit are divided into a signal processing module, a decision calculation module and a trend prediction module. The signal processing module receives the original sensing data from the information sensing unit, and adopts a wavelet transform algorithm or an adaptive filtering algorithm to perform digital filtering operation on the received original data, so as to eliminate the influence of field noise interference and signal fluctuation, and generate stable and reliable real-time pressure value and real-time flow value.

[0031] The decision calculation module obtains the real-time pressure value and real-time flow value processed by the signal processing module, and performs logical analysis on these values according to the preset pressure upper threshold value, target pressure value, pressure lower threshold value and flow abnormal threshold value.

[0032] When the real-time pressure value is greater than or equal to the upper pressure threshold value, the decision calculation module generates a signal to drive the execution control unit to be fully opened; when the real-time pressure value is less than the upper pressure threshold value and greater than the target pressure value, the fuzzy control algorithm is started, the target pressure value is taken as a reference value, and an accurate adjustment signal for smoothly adjusting the real-time pressure value to the target pressure value is calculated; when the real-time pressure value is less than the lower pressure threshold value, a signal to drive the execution control unit to be reduced in opening degree or completely closed is generated.

[0033] In addition, the trend prediction module fuses multi-source heterogeneous data inside and outside the tunnel, including but not limited to real-time water pressure data, real-time drainage flow data, surrounding rock seepage pressure data, meteorological forecast data outside the tunnel and surrounding hydrogeological data, models and analyzes the above data through a long short-term memory network (LSTM) or a support vector machine (SVM) algorithm to predict the water pressure change trend in a future period of time and generate a corresponding forward control signal.

[0034] The core component of the execution control unit is an intelligent adjustment device, the main body of which is made of a corrosion-resistant material, and a layer of epoxy resin coating is coated on the outer surface to enhance the corrosion resistance, and threaded interfaces are arranged at both ends of the main body for connecting the drainage pipeline. The adjustment element is arranged inside the main body, and a plurality of radial micro-pore channels are processed on the outer wall of the adjustment element, and the micro-pore channels are gradually opened or closed through axial movement to realize step-by-step control of the total pressure drop.

[0035] The key throttling surface of the adjustment element is formed with a high-hardness alloy coating layer through a laser cladding process to improve the erosion resistance. The drive assembly is an integrated intelligent electric actuator, which internally integrates a stepping motor, a gear transmission mechanism and a position sensor. The gear transmission mechanism adopts a precision helical gear design to reduce friction loss and noise during transmission, and the stepping motor is provided with a temperature control protection circuit to prevent damage caused by overload or overheating.

[0036] The position sensor is used to detect the actual displacement of the adjustment element in real time and feed back the displacement information to the intelligent analysis unit to constitute a position closed-loop control of the adjustment opening degree.

[0037] The working process of the present application is as follows: Firstly, the information perception unit continuously acquires real-time water pressure data and real-time drainage flow data according to a preset sampling period through the pressure detection device and the flow detection device, and transmits the data to the intelligent analysis unit. The signal processing module in the intelligent analysis unit performs digital filtering operation and validity verification on the received original data to generate real-time pressure value and real-time flow value.

[0038] Subsequently, the decision calculation module performs logical analysis on the real-time pressure value and the real-time flow value according to the preset parameter threshold, to generate a control signal. If prospective control is required, the trend prediction module will predict the future water pressure change trend in combination with multi-source data, and generate a corresponding prospective control signal. The generated control signal is sent to the execution control unit through the control signal link, to drive the intelligent adjustment device to adjust its opening degree to change the drainage flow.

[0039] During the entire process, the adjustment element of the intelligent adjustment device opens or closes the micro-pore channel step by step through axial movement, thereby realizing accurate control of the drainage flow. At the same time, the position sensor in the driving assembly detects the actual displacement of the adjustment element in real time and feeds back the displacement information to the intelligent analysis unit, to ensure the accuracy of the adjustment opening degree. The above steps are continuously executed in a loop, forming a closed-loop feedback control, to dynamically maintain the water pressure behind the tunnel lining within the ideal safety range defined by the target pressure value and the lower pressure threshold.

[0040] The information perception unit also includes an auxiliary detection device for monitoring the temperature, humidity and groundwater chemical composition of the tunnel surroundings, to supplement the completeness of the multi-source data. The auxiliary detection device establishes a data connection with the intelligent analysis unit through wireless communication, to provide more comprehensive data support for it. The trend prediction module in the intelligent analysis unit models and analyzes these multi-source data through a machine learning algorithm, to capture the time series characteristics of the water pressure change and the nonlinear relationship between external influencing factors, thereby generating more accurate prospective control signals.

[0041] The present application introduces multi-source data fusion and machine learning technology to construct an intelligent control system capable of predicting the future water pressure change trend. The system not only solves the problem of passive response lag of traditional drainage systems, but also avoids energy waste and environmental impact caused by excessive drainage, providing reliable protection for the safe operation of water-rich tunnels.

[0042] The present application is further described below in conjunction with two embodiments.

[0043] Example 1: A newly built mountain tunnel passes through a water-rich sandstone layer. When the construction reaches the K18+200 section, it encounters concentrated water gushing, and the water pressure behind the lining rises sharply, with the maximum measured water pressure reaching 1.2 MPa. If not controlled in time, it may cause the initial support to deform and crack. The meteorological characteristics of this area are heavy rain during the rainy season, and there is a sustained rainfall in the next 72 hours. It is necessary to dynamically control the water pressure to be stable below 0.5 MPa to ensure construction safety.

[0044] Six groups of pressure detection devices were embedded in the tunnel vault, haunch and side wall, with a sampling period of 10 seconds to monitor the water pressure behind the lining in real time. Two groups of electromagnetic flow detection devices were connected to the 300 mm diameter drainage pipeline through flanges to synchronously collect the drainage flow.

[0045] Auxiliary detection devices were added to monitor the temperature of surrounding rock, pH value of groundwater and surrounding rainfall, and the data were transmitted to the intelligent analysis unit through wireless transmission.

[0046] The signal processing module used wavelet transform algorithm to filter the original water pressure data, eliminate construction vibration interference, and generate stable real-time pressure and flow values.

[0047] The decision calculation module preset the parameter threshold: the upper limit threshold of pressure 0.8 MPa, the target pressure value 0.5 MPa, and the lower limit threshold of pressure 0.3 MPa. When the real-time pressure value rises to 0.85 MPa, the full opening signal of the execution control unit is generated; when it drops to 0.6 MPa, the fuzzy control algorithm is started to calculate the opening adjustment amount.

[0048] The trend prediction module integrates real-time water pressure, flow data and 72-hour rainfall forecast, and models through LSTM algorithm to predict that the water pressure may rise to 0.9 MPa after 12 hours, and generate a forward-looking control signal to gradually increase the opening degree in advance.

[0049] After receiving the control signal, the intelligent adjustment device drives the stepper motor of the assembly through precise helical gear transmission, which drives the adjustment element to move axially. The adjustment element adopts a three-stage throttling structure, which controls the flow by opening radial micro-hole channels: the flow reaches 180 m³ / h when fully open, and the fuzzy control stage adjusts by 0.05 MPa / second, and finally stabilizes at 120 m³ / h. The position sensor feedbacks the displacement of the adjustment element in real time, forming an opening degree closed loop control to ensure that the flow regulation error is less than 5%.

[0050] Continuous monitoring shows that the water pressure drops to 0.55 MPa 3 hours after control, and rises to 0.6 MPa 12 hours later due to rainfall. The system increases the opening degree to 80% in advance through forward-looking control, and finally stabilizes the water pressure at 0.48 MPa, without triggering the overrun warning.

[0051] Compared with traditional manual valve regulation, the response delay of this system is shortened from 30 minutes to 1 minute, and the water pressure fluctuation amplitude is controlled within ±0.05 MPa, avoiding the over-limit stress of the lining structure and reducing the invalid start-stop of the drainage equipment.

[0052] Example two: A certain city subway line 3 tunnel through water-rich fine sand layer, after 5 years of operation, there is local leakage, the lining behind the long-term water pressure is maintained at 0.6-0.9MPa, far beyond the design allowable value. The tunnel has a large daily passenger flow, and needs to achieve precise regulation of water pressure without affecting operation, while avoiding excessive drainage leading to ground subsidence.

[0053] On the surface of the existing lining structure, 10 groups of pressure detection devices are fixed, and on the interval drainage branch pipe, 4 groups of ultrasonic flow detection devices are installed through the clamp. The sampling period is set to 30 seconds.

[0054] Access to the subway operation monitoring system data, fusion of tunnel temperature and humidity, train vibration frequency and other auxiliary information, build a multi-source database.

[0055] The signal processing module uses an adaptive filtering algorithm to filter out high-frequency interference caused by train traffic, and the signal-to-noise ratio of water pressure data is improved to more than 30dB.

[0056] The decision calculation module dynamically adjusts the threshold value: the early peak is temporarily relaxed to 0.6MPa to reduce equipment noise, and the flat peak period restores the 0.5MPa standard. When the real-time pressure value is in the 0.5-0.6MPa interval, the flow is smoothly adjusted through the fuzzy control algorithm.

[0057] The trend prediction module is based on the operation data of the past 3 months to train the SVM model to predict the water pressure change under different rainfall: when the forecasted daily rainfall is >20mm, the pre-drainage is started 2 hours in advance to reduce the peak water pressure.

[0058] The key surface of the regulating element of the intelligent regulating device is coated with a Ni60 alloy coating by laser cladding to resist sand erosion. The drive assembly is equipped with a temperature control protection circuit that automatically slows down when the motor temperature exceeds 60℃ to avoid overload damage. Combined with flow feedback, when the drainage flow is less than 20m³ / h, a reduced opening signal is generated, with a minimum of 10% opening to maintain a small amount of drainage to prevent pipe clogging.

[0059] Continuous operation for 3 months shows that the water pressure is stable at 0.45-0.55MPa, the daily average drainage time is shortened from 12 hours of the traditional system to 8 hours, and the monthly power saving is about 200kWh; the ground subsidence monitoring value is <1mm / month, meeting the safety requirements.

[0060] The system realizes unattended operation during operation + precise regulation, and the water pressure compliance rate is increased from 65% to 98%. At the same time, through forward-looking regulation and energy-saving logic, the structure safety and energy consumption are balanced, and the problem of lagging behind in traditional manual inspection is solved.

[0061] It is to be understood that the terminology used herein such as first and second, and the like, is only used to distinguish one entity or action from another entity or action, and does not necessarily require or imply any such actual relationship or order between such entities or actions. Moreover, the terms includes and comprising, and any other variant thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements is not necessarily limited to those elements, but can include other elements not expressly listed or inherent to such process, method, article, or apparatus.

[0062] While embodiments of the application have been shown and described, it is to be understood that the application is not limited to the details of the embodiments described, since numerous modifications and changes can be made to the embodiments without departing from the spirit and scope of the application as defined by the appended claims and their equivalents.

Claims

1. A water-rich tunnel drainage pressure reduction regulation system applied to regulating the water pressure of surrounding rock behind the tunnel lining, characterized in that, The system comprises: An information sensing unit configured to acquire real-time water pressure data behind the tunnel lining and real-time drainage flow data in the drainage pipeline laid in the tunnel in real time; An intelligent analysis unit connected with the information sensing unit through wired or wireless communication, configured to receive the real-time water pressure data and real-time drainage flow data, and analyze and judge the received data based on preset logical rules to generate corresponding control signals; An execution control unit connected with the intelligent analysis unit through a control signal link, configured to receive and respond to the control signals to accurately adjust the drainage flow of the drainage pipeline, so as to maintain the water pressure behind the tunnel lining within a preset safe range.

2. The system of claim 1, wherein, The information sensing unit comprises: At least one set of pressure detection devices, the sensing end of which is placed inside the tunnel lining by embedded installation or surface fixation, to directly contact the surrounding rock water environment behind the lining, so as to continuously monitor and output the real-time water pressure data; At least one set of flow detection devices, which are installed on the drainage pipeline by flange connection or clamp fixation, to continuously monitor and output the instantaneous drainage flow through the execution control unit as the real-time drainage flow data.

3. The system of claim 1, wherein, The functional modules of the intelligent analysis unit are divided into a signal processing module and a decision calculation module, the signal processing module is configured to receive raw sensing data from the information sensing unit, and perform digital filtering operation and validity verification on the raw sensing data to generate stable and reliable real-time pressure values and real-time flow values; the decision calculation module is configured to acquire the real-time pressure values and real-time flow values processed by the signal processing module, and perform logical analysis on these values according to preset parameter thresholds to generate the control signals.

4. The system of claim 3, wherein, The signal processing module uses wavelet transform algorithm or adaptive filtering algorithm to perform digital filtering operation on the received raw sensing data.

5. The system of claim 3, wherein, The preset parameter thresholds in the decision calculation module include pressure upper threshold, target pressure value, pressure lower threshold and flow abnormal threshold.

6. The system of claim 5, wherein, The logical rules executed by the decision calculation module specifically include the following contents: When it is judged that the real-time pressure value is greater than or equal to the pressure upper threshold, a signal driving the execution control unit to be fully opened is generated; When it is judged that the real-time pressure value is less than the pressure upper threshold and greater than the target pressure value, a fuzzy control algorithm is started, taking the target pressure value as a reference value to calculate an accurate adjustment signal for smoothly adjusting the real-time pressure value to the target pressure value; When it is judged that the real-time pressure value is less than the pressure lower threshold, a signal driving the execution control unit to be reduced in opening degree or completely closed is generated.

7. The system of claim 1, wherein, The core component of the execution control unit is an intelligent adjustment device, the structure of the intelligent adjustment device comprises a main body with a threaded interface for connecting the drainage pipeline; An adjustment element arranged inside the main body for adjusting the flow cross section of water flow; A driving assembly connected with the regulating element in linkage and used for driving the regulating element to be precisely positioned according to the control signal.

8. The system of claim 7, wherein, The regulating element adopts a multi-stage throttling structure, and a plurality of groups of radial micro-hole channels are formed on the outer wall of the structure; the micro-hole channels are gradually opened or closed by axial movement of the regulating element to realize the step-by-step control of the total pressure drop. The key throttling surface of the regulating element in contact with the water flow is formed with a high-hardness wear-resistant coating by a thermal spraying process.

9. The system of claim 7, wherein, The driving assembly is an integrated intelligent electric actuator, which internally integrates a stepping motor, a gear transmission mechanism and a position sensor; the position sensor is used for detecting the actual displacement of the regulating element in real time and feeding back the displacement information to the intelligent analysis unit to constitute a position closed-loop control of the regulating opening.

10. A water-rich tunnel drainage pressure reduction regulation method, characterized in that, The method comprises the following steps: Real-time information acquisition is achieved by deploying a pressure detection device behind the tunnel lining and a flow detection device on the drainage pipeline to continuously obtain real-time water pressure data and real-time drainage flow data at a preset sampling period; State analysis and signal generation are performed by continuously comparing and analyzing the real-time pressure value and the real-time flow value obtained after processing with a preset upper pressure threshold value, a target pressure value and a lower pressure threshold value, and generating a control signal accordingly; Signal execution sends the control signal to an intelligent regulating device installed on the drainage pipeline to drive the intelligent regulating device to adjust its opening to change the drainage flow; Feedback and circulation continuously execute the steps of real-time information acquisition, state analysis and signal generation and signal execution to form a closed-loop feedback control, so as to dynamically maintain the water pressure behind the tunnel lining within an ideal safety range defined by the target pressure value and the lower pressure threshold value.

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