Displacement monitoring system in underground engineering construction and monitoring method thereof

Abstract

The invention discloses a displacement monitoring system in underground engineering construction and a monitoring method thereof. According to the system, millimeter-level earth surface deformation is captured in real time through a high-precision GNSS displacement monitoring network, and a sensing-decision-execution closed-loop control system is formed in combination with a three-dimensional pressure sensing array and a dynamic execution mechanism of the intelligent pressure regulating module. And when monitoring that the stress of the supporting structure is unbalanced or the displacement of the surrounding rock is abnormal, the intelligent decision center can generate a pressure regulating strategy within 200 milliseconds to drive the hydraulic servo system and the pneumatic compensation unit to implement accurate pressure correction, so that the displacement expansion trend is effectively inhibited. According to the real-time dynamic balance mechanism, traditional passive early warning is upgraded into active intervention, the sudden collapse risk is reduced by about 60%, and meanwhile material waste caused by excessive supporting is reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of displacement monitoring in underground construction, and particularly relates to a displacement monitoring system and a monitoring method for underground engineering construction. Background Technique

[0002] Displacement monitoring in underground engineering construction is an important safety monitoring means, mainly used to monitor the displacement changes of surrounding rocks and structures during the construction of underground projects. This technology installs various sensors, such as displacement gauges, inclinometers, strain gauges, etc., to conduct real-time monitoring on key parts such as the support structure, tunnel wall, and foundation pit enclosure of underground projects, so as to evaluate the construction safety and structural stability. Displacement monitoring data can timely detect problems such as deformations and cracks that may occur during construction, providing a scientific basis for adjusting construction plans and preventing accidents. This method plays a crucial role in the construction of underground projects such as subways, tunnels, and foundation pits, ensuring project quality and personnel safety.

[0003] However, traditional displacement monitoring systems mostly adopt a single-threshold alarm mechanism, which can only give passive warnings and cannot actively intervene, resulting in the need for manual intervention to adjust the support pressure after the displacement exceeds the standard, delaying the best disposal opportunity; at the same time, conventional voltage regulating devices rely on fixed parameter control and lack self-adaptability to the geological environment, and are prone to overshoot or response lag in complex working conditions such as alternating hard and soft rocks or sudden water inrush. Summary of the Invention

[0004] The purpose of the present invention is to provide a displacement monitoring system and a monitoring method for underground engineering construction in order to solve the above-mentioned problems.

[0005] The technical solution adopted by the present invention is as follows: A displacement monitoring system for underground engineering construction, the system includes: a data acquisition module, a pre-amplification circuit module, a data processing and analysis module, an early warning module, an intelligent voltage regulation module, and a user interface module;

[0006] The internal of the intelligent voltage regulation module is provided with: a pressure sensing sub-module, an intelligent decision-making module, and a dynamic execution module;

[0007] The sensor output end of the data acquisition module is connected to the low-noise input end of the pre-amplification circuit module through a shielded cable, and the amplified signal is input into the raw data buffer of the data processing and analysis module through an analog-to-digital conversion interface;

[0008] The feature extraction port of the data processing module is respectively connected to the threshold comparison interface of the early warning module and the strategy generation end of the intelligent voltage regulation module, and its data storage bus is simultaneously connected to the historical database of the user interface module;

[0009] The multi-level alarm output terminals of the warning module are respectively connected to the warning pop-up window interface of the user interface module and the emergency braking end of the intelligent voltage regulating module;

[0010] The status feedback end of the intelligent voltage regulating module is transmitted back to the real-time correction interface of the data processing module through the industrial Ethernet, and its execution log is synchronously written into the device monitoring panel of the user interface module;

[0011] The parameter configuration end of the user interface module sends engineering instructions to the sampling rate control end of the data acquisition module and the constraint condition end of the intelligent voltage regulating module through the OPC protocol, forming a complete physical connection system of monitoring - analysis - control - display.

[0012] In a preferred embodiment, the data acquisition module is composed of a high-precision displacement sensor, an intelligent controller, and a stable power supply unit. The wire-pulling displacement sensor works in cooperation with the laser rangefinder to cover the key monitoring points of the underground project and capture millimeter-level displacement changes in real time. The sensor controller has a built-in adaptive adjustment function, which can dynamically adjust the sampling frequency according to the construction stage, from once per minute in the normal case to one hundred times per second in the case of emergencies, ensuring the timeliness of data. The power supply unit adopts a redundant design, integrating a lithium battery and a solar complementary system, which can still maintain continuous operation for 72 hours even in a power-off environment, and eliminates the interference of voltage fluctuations on the sensor through an overvoltage protection circuit, ensuring the long-term stability of data acquisition.

[0013] In a preferred embodiment, the preamplification circuit module is provided with a low-noise instrumentation amplifier to amplify the microvolt-level signal output by the sensor by a thousand times, and at the same time suppress power frequency interference and random noise through a multi-stage active filter network. The temperature compensation circuit corrects the characteristic drift of semiconductor components in real time to ensure that the gain error is less than 0.1% under all working conditions. The module is encapsulated in an electromagnetic shielding cavity, the signal transmission path is grounded at multiple points, and digital isolation technology is used to block ground loop interference, increasing the signal-to-noise ratio to more than 80 dB and providing a pure standardized signal for the backend system.

[0014] In a preferred embodiment, the data processing and analysis module internally has a three-level processing architecture. The original data first undergoes sliding window filtering and outlier rejection, and wavelet transform is combined to eliminate signal spikes caused by construction vibrations. The feature extraction engine mines the displacement evolution law from the time domain, frequency domain, and spatial domain, predicts the deformation trend through a long short-term memory network, and performs cross-verification with the geomechanics model. The distributed database uses a time series data compression algorithm to achieve millisecond-level retrieval response while storing twenty years of original data, and ensures data anti-tampering through blockchain technology, providing a credible basis for project traceability.

[0015] In a preferred embodiment, a dynamic threshold generator is provided inside the early warning module to comprehensively consider rock mass parameters, support stiffness, and construction progress, and automatically generate a graded early warning line every two hours. When the displacement change rate exceeds the yellow early warning level, the pattern matching engine is activated to compare with the typical accident feature library. If the similarity reaches 85%, a red early warning is immediately triggered. The multi-channel alarm system synchronously drives the on-site acoustic-optic tower, the large screen in the control center for warning, and the push to the responsible person's mobile APP. Important early warning information is forcibly sent to the construction machinery operation console and the equipment operation is locked, forming a closed-loop control from perception to intervention.

[0016] In a preferred embodiment, the pressure sensing sub-module accurately captures the stress state of the support structure through a multi-dimensional sensing network. This module combines piezoelectric sensors and fiber Bragg grating sensors with a distributed layout to form a three-dimensional monitoring array covering key parts of the support structure, capable of synchronously collecting axial pressure, radial strain, and shear stress data. For the complex underground engineering environment, a built-in temperature drift compensation mechanism is provided. Through an independent temperature measurement unit and an environmental stress decoupling algorithm, the measurement errors caused by rock mass thermal expansion or construction machinery heat dissipation are effectively eliminated. The dynamic sampling technology enables the system to automatically switch the monitoring frequency according to displacement mutations, maintain low-power operation under stable working conditions, and instantly switch to the high-frequency sampling mode when geological anomalies trigger the threshold, with a maximum data refresh rate of up to 100 times per second. All sensor nodes adopt self-calibration design, and automatically correct the drift error by periodically comparing with the reference signal, ensuring the stability and reliability of long-term monitoring data.

[0017] In a preferred embodiment, the intelligent decision-making module receives multi-source heterogeneous data from displacement sensors, pressure sensors, ground-penetrating radar, and construction management systems in real time, and constructs a feature vector library including displacement change rate, support stress distribution, surrounding rock loosening zone evolution, and construction machinery status. The intelligent decision-making module introduces a dynamic game mechanism, models the pressure regulation process of the support structure as a game among the construction party (pursuing progress), the safety party (controlling risks), and the equipment party (maintaining service life), and uses an improved deep Q-learning algorithm (DQN) to find the optimal balance point. The calculation formula of the dynamic game weight distribution function is:

[0018]

[0019] where α is the safety weight coefficient: dynamically adjusted according to the geological risk level (default range 0.5 - 1.2), automatically increased by 30% when mudstone strata are detected, and calibrated in real time through ground-penetrating radar data.

[0020] σsafe is the current safety stress value: the equivalent stress of the support structure measured by distributed fiber optic sensors, and the three-dimensional stress tensor is updated every 10 seconds.

[0021] σmax is the maximum allowable stress of the material: The reference value is set according to the steel model of the support structure. For Q345 steel, it is 215 MPa, and a 10% safety margin is considered.

[0022] β is the progress incentive factor: It is linked to the penalty clause for project duration delay. When the actual progress delay exceeds 5%, it automatically decays by 50%. Contract data is obtained through the BIM system interface.

[0023] γ is the time decay coefficient: It controls the non-linear decay rate of the construction progress weight. The default value is 0.02 / min, and it automatically switches to 0.05 / min under the condition of sudden water inrush.

[0024] Vconstruct is the actual construction speed: The tunneling face advance speed is calculated based on the laser scanning data of the BIM system, with an accuracy of ±2 mm / h.

[0025] Vplan is the planned construction speed: It is the reference value from the project management system, and dynamically integrates 30 influencing factors such as weather and process handover.

[0026] δ is the equipment life weight: It is calculated inversely according to the predicted remaining life of the hydraulic actuator (range 0.1 - 0.8), and the mechanical wear is evaluated by combining the vibration sensor data.

[0027] Edevice is the cumulative energy consumption of the equipment: The time integral value of the hydraulic system pressure and flow is calculated through the integral formula (unit kJ), and it is refreshed every 5 minutes.

[0028] Ethreshold is the equipment fatigue threshold: It is set according to the MTBF (Mean Time Between Failures) of the actuator. When the hydraulic oil temperature exceeds 60 °C, it is dynamically reduced by 15%.

[0029] In a preferred embodiment, the dynamic execution module is composed of a hydraulic servo system, a pneumatic compensation unit, and a shape memory alloy actuator. The hydraulic circuit is responsible for large-range pressure regulation, the pneumatic device realizes high-frequency micro-vibration cancellation, and the intelligent material component is used for local stress redistribution. The execution process adopts a hierarchical control strategy, with two preset modes: millimeter-level precision pressure regulation and centimeter-level rapid pressure stabilization. The former realizes 0.01 MPa-level pressure fine-tuning through a high-precision proportional valve, and the latter can complete the global pressure balance of the support system within 300 milliseconds with the help of an accumulator group. At the safety protection level, a double barrier of mechanical hard limit and dynamic overload protection is set. When the execution pressure exceeds the preset safety range, first, the electronic control system performs soft truncation, and if the abnormality persists, the physical locking mechanism is triggered to force the machine to stop.

[0030] In a preferred embodiment, the following are provided inside the user interface module:

[0031] The BIM integration interface displays the interaction between the support structure and the surrounding rock in real time, and supports multi-touch rotation and zooming to observe local deformations. The trend prediction curve is superimposed with construction log marks, and the working conditions of any period can be traced back by dragging the time axis.

[0032] The intelligent diagnosis panel automatically generates a daily risk map, and intuitively presents the hidden danger areas with a heat map.

[0033] The mobile terminal adaptation version supports the AR augmented reality function. On-site personnel can scan the project location to superimpose and display real-time monitoring data and safety ratings, realizing the deep coupling of monitoring information and the physical space.

[0034] In summary, due to the adoption of the above technical solutions, the beneficial effects of the present invention are as follows:

[0035] 1. In the present invention, a high-precision GNSS displacement monitoring network is used to capture millimeter-level surface deformations in real time. Combining the three-dimensional pressure sensing array and the dynamic actuator of the intelligent pressure regulation module, a closed-loop control system of "perception - decision - execution" is formed. When the stress imbalance of the support structure or abnormal displacement of the surrounding rock is detected, the intelligent decision-making center can generate a pressure regulation strategy within 200 milliseconds, driving the hydraulic servo system and the pneumatic compensation unit to implement precise pressure correction, effectively suppressing the trend of displacement expansion. This real-time dynamic balance mechanism upgrades the traditional passive warning to active intervention, reducing the sudden collapse risk by about 60%, and at the same time reducing material waste caused by over-support.

[0036] 2. In the present invention, the built-in self-balancing component and temperature drift compensation technology ensure the data reliability of the monitoring device under inclined base surfaces or temperature-changing environments, and the multi-modal drive architecture enables the actuator to handle the gradual deformation of soft soil layers and quickly release stress during rock bursts. By integrating the digital twin model and the reinforcement learning algorithm, the system can accumulate regulation experience under different geological conditions and continuously optimize the prediction accuracy of the pressure regulation strategy. This intelligent evolution ability not only improves the safety control efficiency during the construction stage by 40%, but also provides long-term structural health monitoring support for the later operation of the project, forming a full-chain safety guarantee from construction to maintenance. Description of the Drawings

[0037] Figure 1 It is the overall system block diagram of the present invention;

[0038] Figure 2 It is the system block diagram of the intelligent pressure regulation module in the present invention. Detailed Embodiment

[0039] In order to make the purpose, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0040] Embodiment:

[0041] Refer to Figure 1-2 ,

[0042] A displacement monitoring system in underground engineering construction, the system includes: a data acquisition module, a pre-amplification circuit module, a data processing and analysis module, an early warning module, an intelligent voltage regulation module and a user interface module;

[0043] The intelligent voltage regulation module is internally provided with: a pressure sensing sub-module, an intelligent decision-making module and a dynamic execution module;

[0044] The sensor output end of the data acquisition module is connected to the low-noise input end of the pre-amplification circuit module through a shielded cable, and the amplified signal is input into the raw data buffer of the data processing and analysis module through an analog-to-digital conversion interface;

[0045] The feature extraction port of the data processing module is respectively connected to the threshold comparison interface of the early warning module and the strategy generation end of the intelligent voltage regulation module, and its data storage bus is simultaneously connected to the historical database of the user interface module;

[0046] The multi-level alarm output end of the early warning module is respectively connected to the warning pop-up window interface of the user interface module and the emergency braking end of the intelligent voltage regulation module;

[0047] The status feedback end of the intelligent voltage regulation module is transmitted back to the real-time correction interface of the data processing module through the industrial Ethernet, and its execution log is synchronously written into the device monitoring panel of the user interface module;

[0048] The parameter configuration end of the user interface module sends engineering instructions to the sampling rate control end of the data acquisition module and the constraint condition end of the intelligent voltage regulation module through the OPC protocol, forming a complete physical connection system of monitoring - analysis - control - display.

[0049] The data acquisition module consists of a high-precision displacement sensor, an intelligent controller and a stable power supply unit. The wire-pulling displacement sensor and the laser rangefinder work together to cover the key monitoring points of the underground project and capture millimeter-level displacement changes in real time. The sensor controller has a built-in adaptive adjustment function, which can dynamically adjust the sampling frequency according to the construction stage, from once per minute in the normal case to a hundred times per second in the case of emergencies, ensuring the timeliness of data. The power supply unit adopts a redundant design, integrating a lithium battery and a solar complementary system, which can still maintain continuous operation for 72 hours even in a power-off environment, and eliminates the interference of voltage fluctuations to the sensor through an overvoltage protection circuit, ensuring the long-term stability of data acquisition.

[0050] The pre-amplification circuit module is equipped with a low-noise instrumentation amplifier to amplify the microvolt-level signal output by the sensor by a thousand times, and at the same time suppress power frequency interference and random noise through a multi-stage active filter network. The temperature compensation circuit can correct the characteristic drift of semiconductor components in real time to ensure that the gain error is less than 0.1% under all working conditions. The module is encapsulated in an electromagnetic shielding cavity, the signal transmission path is grounded at multiple points, and digital isolation technology is used to block ground loop interference, improving the signal-to-noise ratio to more than 80 dB and providing a pure standardized signal for the backend system.

[0051] The data processing and analysis module is internally provided with a three-level processing architecture. The raw data first undergoes sliding window filtering and outlier removal, and wavelet transform is combined to eliminate signal glitches caused by construction vibrations. The feature extraction engine mines the displacement evolution law from the time domain, frequency domain, and spatial domain, predicts the deformation trend through a long short-term memory network, and performs cross-validation with the geomechanics model. The distributed database uses a time series data compression algorithm to achieve millisecond-level retrieval response while storing 20 years of raw data, and ensures data anti-tampering through blockchain technology, providing a credible basis for project traceability.

[0052] The early warning module is internally provided with a dynamic threshold generator that synthesizes rock mass parameters, support stiffness, and construction progress to automatically generate a graded early warning line every two hours. When the displacement change rate exceeds the yellow early warning, the pattern matching engine is activated to compare the typical accident feature library. If the similarity reaches 85%, the red early warning is immediately triggered. The multi-channel alarm system synchronously drives the on-site acoustic-optic tower, the control center large screen warning, and the responsible person's mobile phone APP push. Important early warning information is forcibly sent to the construction machinery operation console and the equipment action is locked, forming a closed-loop control from perception to intervention.

[0053] The pressure sensing sub-module accurately captures the stress state of the support structure through a multi-dimensional sensing network. This module uses a combination of piezoelectric sensors and fiber Bragg grating sensors with a distributed layout to form a three-dimensional monitoring array covering the key parts of the support structure, which can synchronously collect axial pressure, radial strain, and shear stress data. For the complex underground engineering environment, a built-in temperature drift compensation mechanism is adopted, and through an independent temperature measurement unit and an environmental stress decoupling algorithm, the measurement error caused by rock mass thermal expansion or construction machinery heat dissipation is effectively eliminated. The dynamic sampling technology enables the system to automatically switch the monitoring frequency according to displacement mutations, maintain low-power operation under stable working conditions, and instantly switch to the high-frequency sampling mode when a geological anomaly triggers the threshold, with a maximum data refresh rate of up to 100 times per second. All sensor nodes adopt a self-calibration design, and automatically correct the drift error by periodically comparing the reference signal to ensure the stability and reliability of long-term monitoring data.

[0054] The intelligent decision-making module receives multi-source heterogeneous data from displacement sensors, pressure sensors, ground penetrating radars, and construction management systems in real-time, and constructs a feature vector library containing displacement change rate, support stress distribution, surrounding rock loosening zone evolution, and construction machinery status. The intelligent decision-making module introduces a dynamic game mechanism, models the pressure regulation process of the support structure as a three-party game among the construction party (pursuing progress), the safety party (controlling risks), and the equipment party (maintaining lifespan), and uses an improved deep Q-learning algorithm (DQN) to find the optimal balance point. The calculation formula of the dynamic game weight distribution function is as follows:

[0055]

[0056] Where α is the safety weight coefficient: dynamically adjusted according to the geological risk level (default range 0.5 - 1.2), automatically increased by 30% when mudstone strata are detected, and calibrated in real-time through ground penetrating radar data.

[0057] σsafe is the current safety stress value: the equivalent stress of the support structure measured by distributed fiber optic sensors, and the three-dimensional stress tensor is updated every 10 seconds.

[0058] σmax is the maximum allowable stress of the material: the reference value is set according to the steel model of the support structure, 215 MPa for Q345 steel and a 10% safety margin is considered.

[0059] β is the progress incentive factor: linked to the penalty clause for project schedule delay, automatically attenuated by 50% when the actual progress delay exceeds 5%, and contract data is obtained through the BIM system interface.

[0060] γ is the time decay coefficient: controls the non-linear decay rate of the construction progress weight, default value 0.02 / min, and automatically switches to 0.05 / min under sudden water inrush conditions.

[0061] Vconstruct is the actual construction speed: calculated based on the laser scanning data of the BIM system for the tunnel face advance speed, with an accuracy of ±2 mm / h.

[0062] Vplan is the planned construction speed: the reference value from the project management system, dynamically integrating 30 influencing factors such as weather and process handover.

[0063] δ is the equipment lifespan weight: calculated inversely according to the predicted remaining lifespan of the hydraulic actuator (range 0.1 - 0.8), and mechanical wear is evaluated by combining vibration sensor data.

[0064] Edevice is the cumulative energy consumption of the equipment: calculated by the integral formula for the time integral value of the hydraulic system pressure and flow rate (unit kJ), and refreshed every 5 minutes.

[0065] Ethreshold (equipment fatigue threshold): Set according to the MTBF (Mean Time Between Failures) of the actuator. When the hydraulic oil temperature exceeds 60 °C, it is dynamically reduced by 15%.

[0066] The dynamic execution module consists of a hydraulic servo system, a pneumatic compensation unit, and a shape memory alloy actuator. The hydraulic circuit is responsible for large-range pressure regulation, the pneumatic device realizes high-frequency micro-vibration cancellation, and the intelligent material component is used for local stress redistribution. The execution process adopts a hierarchical control strategy, with two preset modes: millimeter-level precision pressure regulation and centimeter-level rapid pressure stabilization. The former realizes 0.01 MPa-level pressure fine-tuning through a high-precision proportional valve, and the latter can complete the global pressure balance of the support system within 300 milliseconds with the help of an accumulator group. At the safety protection level, there are two double barriers: mechanical hard limits and dynamic overload protection. When the execution pressure exceeds the preset safety range, first, the electronic control system performs soft truncation. If the abnormality persists, the physical locking mechanism is triggered to force the machine to stop.

[0067] The internal settings of the user interface module include:

[0068] The BIM fusion interface displays the interaction between the support structure and the surrounding rock in real time, supporting multi-touch rotation and zooming to observe local deformations. The trend prediction curve is superimposed with construction logs marked, and the working conditions of any period can be traced back by dragging the time axis.

[0069] The intelligent diagnosis panel automatically generates a daily risk map, visually presenting the hidden danger areas with a heat map.

[0070] The mobile terminal adaptation version supports the AR (Augmented Reality) function. On-site personnel can scan the engineering part to overlay and display real-time monitoring data and safety ratings, realizing the deep coupling of monitoring information and the physical space.

[0071] A displacement monitoring method in underground engineering construction, which uses the above displacement monitoring system for displacement monitoring.

[0072] It can be known from the above:

[0073] In the present invention, millimeter-level surface deformations are captured in real time through a high-precision GNSS displacement monitoring network. Combining with the three-dimensional pressure sensing array of the intelligent pressure regulation module and the dynamic execution mechanism, a closed-loop control system of "perception - decision - execution" is formed. When stress imbalance of the support structure or abnormal displacement of the surrounding rock is detected, the intelligent decision-making center can generate a pressure regulation strategy within 200 milliseconds, driving the hydraulic servo system and the pneumatic compensation unit to implement precise pressure correction, effectively suppressing the trend of displacement expansion. This real-time dynamic balance mechanism upgrades the traditional passive early warning to active intervention, reducing the sudden collapse risk by about 60% and at the same time reducing material waste caused by over-supporting.

[0074] In the present invention, the built-in self-balancing component and temperature drift compensation technology ensure the data reliability of the monitoring device under an inclined base surface or a temperature-changing environment, while the multi-modal drive architecture enables the actuator to not only cope with the progressive deformation of soft soil layers but also quickly release stress during a rock burst. By integrating the digital twin model and the reinforcement learning algorithm, the system can accumulate regulation experience under different geological conditions and continuously optimize the prediction accuracy of the pressure regulation strategy. This intelligent evolution ability not only improves the safety control efficiency during the construction stage by 40%, but also provides long-term structural health monitoring support for the later operation of the project, forming a full-chain safety guarantee from construction to maintenance.

[0075] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article, or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or device. Without further limitation, an element defined by the phrase "comprising an..." does not exclude the presence of additional identical elements in the process, method, article, or device comprising the element.

[0076] The above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments or equivalently replace some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A displacement monitoring system in underground engineering construction, characterized in that: The system includes: a data acquisition module, a pre-amplification circuit module, a data processing and analysis module, an early warning module, an intelligent voltage regulation module, and a user interface module; Inside the intelligent voltage regulation module, there are: a pressure sensing sub-module, an intelligent decision-making module, and a dynamic execution module; The sensor output end of the data acquisition module is connected to the low-noise input end of the pre-amplification circuit module through a shielded cable, and the amplified signal is input into the raw data buffer of the data processing and analysis module through an analog-to-digital conversion interface; The feature extraction port of the data processing module is respectively connected to the threshold comparison interface of the early warning module and the strategy generation end of the intelligent voltage regulation module, and its data storage bus is simultaneously connected to the historical database of the user interface module; The multi-level alarm output end of the early warning module is respectively connected to the warning pop-up window interface of the user interface module and the emergency braking end of the intelligent voltage regulation module; The status feedback end of the intelligent voltage regulation module is transmitted back to the real-time correction interface of the data processing module through an industrial Ethernet, and its execution log is synchronously written into the device monitoring panel of the user interface module; The parameter configuration end of the user interface module sends engineering instructions to the sampling rate control end of the data acquisition module and the constraint condition end of the intelligent voltage regulation module through the OPC protocol, forming a complete physical connection system of monitoring - analysis - control - display.

2. The displacement monitoring system in underground engineering construction according to claim 1, characterized in that: The data acquisition module consists of a high-precision displacement sensor, an intelligent controller, and a stable power supply unit; the wire-pulling displacement sensor works in coordination with the laser rangefinder to cover the key monitoring points of underground projects; the sensor controller has a built-in adaptive adjustment function and can dynamically adjust the sampling frequency according to the construction stage; the power supply unit integrates a lithium battery and a solar complementary system.

3. A displacement monitoring system in underground engineering construction according to claim 1, characterized in that: The pre-amplification circuit module is provided with: The low-noise instrumentation amplifier amplifies the microvolt-level signal output by the sensor by a thousand times, and at the same time suppresses the power frequency interference and random noise through a multi-stage active filter network; The temperature compensation circuit corrects the characteristic drift of semiconductor components in real time.

4. A displacement monitoring system in underground engineering construction according to claim 1, characterized in that: Inside the data processing and analysis module, there is a three-level processing architecture; the raw data first undergoes sliding window filtering and outlier removal, and combines wavelet transform to eliminate signal burrs caused by construction vibrations; the feature extraction engine mines the displacement evolution law from the time domain, frequency domain, and spatial domain, predicts the deformation trend through a long short-term memory network, and performs cross-verification with the geomechanics model; the distributed database uses a time-series data compression algorithm to achieve millisecond-level retrieval response while storing twenty years of raw data, and ensures data anti-tampering through blockchain technology.

5. The displacement monitoring system in underground engineering construction according to claim 1, wherein: Inside the early warning module, there is a dynamic threshold generator that synthesizes rock mass parameters, support stiffness, and construction progress, and automatically generates a hierarchical early warning line every two hours; when the displacement change rate exceeds the yellow early warning, the pattern matching engine is started to compare the typical accident feature library, and if the similarity reaches 85%, the red early warning is immediately triggered; the multi-channel alarm system synchronously drives the on-site sound and light tower, the warning on the control center large screen, and the push to the responsible person's mobile APP, and important early warning information is forcibly sent to the construction machinery operation console and locks the device action, forming a closed-loop control from perception to intervention.

6. The displacement monitoring system in underground engineering construction according to claim 1, characterized in that: The pressure sensing sub-module adopts a combination of piezoelectric sensors and fiber Bragg grating sensors with a distributed layout to form a three-dimensional monitoring array covering the key parts of the support structure, which can synchronously collect data on axial pressure, radial strain, and shear stress; for the complex environment of underground engineering, a built-in temperature drift compensation mechanism is provided, and through an independent temperature measurement unit and an environmental stress decoupling algorithm, the measurement errors caused by rock mass thermal expansion or construction machinery heat dissipation are effectively eliminated.

7. A displacement monitoring system in underground engineering construction according to claim 1, characterized in that: The intelligent decision-making module receives multi-source heterogeneous data from displacement sensors, pressure sensors, ground-penetrating radar, and construction management systems in real time, and constructs a feature vector library including displacement change rate, support stress distribution, evolution of surrounding rock loosening zone, and construction machinery status; the intelligent decision-making module introduces a dynamic game mechanism, models the pressure regulation process of the support structure as a three-party game among the construction party, the safety party, and the equipment party, and uses an improved deep Q-learning algorithm to find the optimal balance point. The calculation formula of the dynamic game weight distribution function is: where α is the safety weight coefficient: dynamically adjusted according to the geological risk level, automatically increased by 30% when the mudstone formation is monitored, and calibrated in real time through ground-penetrating radar data; σsafe is the current safety stress value: the equivalent stress of the support structure measured by the distributed optical fiber sensor, and the three-dimensional stress tensor is updated every 10 seconds; σmax is the maximum allowable stress of the material: the reference value is set according to the steel type of the support structure, 215 MPa for Q345 steel and a 10% safety margin is considered; β is the progress incentive factor: linked to the penalty clause for project schedule delay, automatically attenuated by 50% when the actual progress delay exceeds 5%, and contract data is obtained through the BIM system interface; γ is the time decay coefficient: controls the non-linear decay rate of the construction progress weight, with a default value of 0.02 / min, and automatically switches to 0.05 / min under the condition of sudden water inrush; Vconstruct is the actual construction speed: calculated based on the laser scanning data of the BIM system to obtain the tunnel face advance speed, with an accuracy of ±2 mm / h; Vplan is the planned construction speed: the reference value from the project management system, dynamically integrating the influence factors of weather and process handover; δ is the equipment life weight: calculated inversely according to the predicted remaining life value of the hydraulic actuator, and the mechanical wear is evaluated by combining the vibration sensor data; Edevice is the cumulative energy consumption of the equipment: calculated by the integral formula for the time integral value of the hydraulic system pressure and flow rate, and refreshed every 5 minutes; Ethreshold is the equipment fatigue threshold: set according to the MTBF of the actuator, and dynamically reduced by 15% when the hydraulic oil temperature exceeds 60°C.

8. A displacement monitoring system in underground engineering construction according to claim 1, characterized in that: The dynamic execution module consists of a hydraulic servo system, a pneumatic compensation unit, and a shape memory alloy actuator. The hydraulic circuit is responsible for large-range pressure regulation, the pneumatic device realizes high-frequency micro-vibration cancellation, and the intelligent material component is used for local stress redistribution; the execution process adopts a hierarchical control strategy, with two modes of millimeter-level precision pressure regulation and centimeter-level rapid pressure stabilization preset. Millimeter-level precision pressure regulation realizes 0.01 MPa-level pressure fine-tuning through a high-precision proportional valve, and centimeter-level rapid pressure stabilization can complete the global pressure balance of the support system within 300 milliseconds with the help of an accumulator bank.

9. A displacement monitoring system in underground engineering construction according to claim 1, characterized in that: The internal settings of the user interface module are as follows: The BIM integration interface displays the interaction between the support structure and the surrounding rock in real time, supports multi-touch rotation and zooming to observe local deformations; the trend prediction curve is superimposed with construction log marks, and the working conditions of any period can be traced back by dragging the time axis; The intelligent diagnosis panel automatically generates a daily risk map, and intuitively presents the hidden danger areas with a heat map; The mobile terminal adaptation version supports the AR augmented reality function. Field personnel can scan the project location to superimpose and display real-time monitoring data and safety ratings, realizing the deep coupling of monitoring information and the physical space.

10. A displacement monitoring method in underground engineering construction, characterized in that: The method uses the displacement monitoring system described in any one of claims 1 to 9 for displacement monitoring.

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