A method, apparatus, storage medium, and electronic equipment for construction environment monitoring.

Abstract

This application relates to the field of environmental monitoring technology, specifically providing a method, apparatus, storage medium, and electronic device for monitoring the construction environment. The method may include: during the construction of a tunnel boring machine (TBM) in a target area, collecting the original vibration signal generated by the TBM and the TBM's construction parameters; wherein the construction parameters include thrust and torque; inverting the pre-processed vibration signal from the original vibration signal to obtain a three-dimensional underground velocity model; obtaining the wave velocity change rate based on the underground three-dimensional velocity model, and obtaining index values ​​of rock mass anomalies based on the processed vibration signal; analyzing the construction parameters, the wave velocity change rate, and the index values ​​to obtain monitoring results for the target area; wherein the monitoring results include a risk level and response measures to address the risk level. The embodiments of this application can achieve dynamic monitoring of the construction environment and provide real-time risk warnings.

Description

Technical Field

[0001] This application relates to the field of environmental monitoring technology, and more specifically, to a method, apparatus, storage medium, and electronic equipment for monitoring the construction environment. Background Technology

[0002] In modern underground engineering, especially in tunnel excavation and deep laboratory construction, monitoring the stability and structural integrity of underground rock masses is crucial. Currently, traditional methods for underground engineering geological monitoring typically rely on phased external seismic source deployment and tunnel closures. However, this traditional approach requires the tunnel boring machine (TBM) to be shut down and takes a considerable amount of time to monitor the underground rock mass. Therefore, existing methods for monitoring underground rock masses not only impact construction progress and incur high costs, but also fail to provide timely monitoring, thus hindering timely risk prediction and impacting engineering decisions.

[0003] Therefore, how to provide a technical solution for an efficient method of monitoring the construction environment has become a technical problem that needs to be solved. Summary of the Invention

[0004] The purpose of some embodiments of this application is to provide a method, device, storage medium and electronic device for monitoring the construction environment. The technical solutions of the embodiments of this application can realize timely and accurate monitoring of underground rock conditions during tunnel boring machine construction, providing timely and reliable reference for engineering decision-making.

[0005] In a first aspect, some embodiments of this application provide a method for monitoring the construction environment, comprising: during the construction of a target area by a tunnel boring machine, collecting the original vibration signal generated by the tunnel boring machine and the construction parameters of the tunnel boring machine; wherein the construction parameters include thrust and torque; inverting the preprocessed vibration signal of the original vibration signal to obtain a three-dimensional underground velocity model; obtaining the wave velocity change rate based on the three-dimensional underground velocity model, and obtaining the index value of rock mass anomaly events based on the processed vibration signal; analyzing the construction parameters, the wave velocity change rate, and the index value to obtain the monitoring results of the target area; wherein the monitoring results include a risk level and response measures to address the risk level.

[0006] Some embodiments of this application collect raw vibration signals and construction parameters generated by a tunnel boring machine (TBM) during construction. The raw vibration information is then preprocessed to obtain a processed vibration signal, which is then used to invert and acquire a three-dimensional underground velocity model. Subsequently, the wave velocity change rate, rock mass anomaly index values, and construction parameters obtained from the underground three-dimensional velocity model are comprehensively analyzed to obtain monitoring results. These embodiments enable timely and accurate monitoring of underground rock mass conditions during TBM construction, achieving timely risk warning and response, and providing timely and reliable reference for engineering decisions.

[0007] In some embodiments, the processed vibration signal is obtained by: denoising, bandpass filtering, and correcting the original vibration signal to obtain a corrected vibration signal; and performing wavelet transform and notch filtering on the corrected vibration signal to obtain the processed vibration signal.

[0008] Some embodiments of this application preprocess the original vibration signal to obtain a processed vibration signal, thereby achieving noise and standardization of the signal, so as to extract an accurate processed vibration signal and provide data support for subsequent rock mass monitoring.

[0009] In some embodiments, the step of inverting the preprocessed vibration signal after preprocessing the original vibration signal to obtain a three-dimensional underground velocity model includes: analyzing the wave propagation time in the preprocessed vibration signal to obtain an inversion model; optimizing the inversion model using waveform data in the preprocessed vibration signal to obtain an initial three-dimensional velocity model; confirming that the accuracy of the initial three-dimensional velocity model meets preset conditions, and outputting the three-dimensional underground velocity model.

[0010] Some embodiments of this application obtain a suitable three-dimensional underground velocity model by inverting the processed vibration signal, providing data support for subsequent rock mass monitoring.

[0011] In some embodiments, obtaining the wave velocity change rate based on the underground three-dimensional velocity model includes: obtaining the imaging wave velocity structure of the tunnel boring machine through the underground three-dimensional velocity model; and obtaining the wave velocity change rate at different times and locations in the target area based on the imaging wave velocity structure.

[0012] Some embodiments of this application can obtain the imaging wave velocity structure through a three-dimensional underground velocity model, thereby obtaining the wave velocity change rate of the target area at different times and locations, thus achieving accurate acquisition of underground wave velocity data.

[0013] In some embodiments, obtaining the index value of rock mass anomaly events based on the processed vibration signal includes: statistically analyzing rock mass anomaly events in the target area within a preset time period; clustering the rock mass anomaly events into event clusters, and then calculating the index value of the event clusters.

[0014] Some embodiments of this application calculate index values ​​by statistically analyzing and clustering rock mass anomalies, providing data support for subsequent rock mass monitoring.

[0015] In some embodiments, the step of analyzing the construction parameters, the wave velocity change rate, and the index value to obtain monitoring results for the target area includes: analyzing the construction parameters to obtain a first determination result; wherein the first determination result indicates whether the construction parameters are abnormal; comparing the wave velocity change rate with a preset threshold to obtain a second determination result; wherein the second determination result indicates whether the wave velocity change rate is abnormal; analyzing the index value to obtain a third determination result; wherein the third determination result indicates whether the index value is abnormal; wherein the abnormality indicates that the rock mass in the target area is fractured or deformed; combining the first determination result, the second determination result, and the third determination result to determine the risk level; and obtaining the response measures corresponding to the risk level.

[0016] Some embodiments of this application determine the risk level and response measures of the target area by separately judging the anomalies of construction parameters, wave velocity change rate and index values, and comprehensively judging the results. In this way, the risk of the target area environment can be predicted, and the monitoring is timely and accurate.

[0017] In some embodiments, the original vibration signal is acquired by surface geophones and borehole geophones deployed in the target area; the surface geophones are triaxial accelerometers; and the borehole geophones are piezoelectric seismic sensors.

[0018] Some embodiments of this application achieve effective acquisition of the raw vibration signals of the tunnel boring machine by deploying detectors at different locations.

[0019] Secondly, some embodiments of this application provide a construction environment monitoring device, comprising: a data acquisition module for acquiring the original vibration signal generated by the tunnel boring machine and the construction parameters of the tunnel boring machine during the construction of a target area by the tunnel boring machine; wherein the construction parameters include thrust and torque; an inversion module for inverting the preprocessed vibration signal of the original vibration signal to obtain a three-dimensional underground velocity model; a data acquisition module for acquiring the wave velocity change rate based on the three-dimensional underground velocity model and acquiring the index value of rock mass anomaly events based on the processed vibration signal; and a monitoring module for analyzing the construction parameters, the wave velocity change rate, and the index value to obtain the monitoring results of the target area; wherein the monitoring results include a risk level and response measures to address the risk level.

[0020] Thirdly, some embodiments of this application provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, can implement the method described in any embodiment of the first aspect.

[0021] Fourthly, some embodiments of this application provide an electronic device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the program, can implement the method as described in any embodiment of the first aspect.

[0022] Fifthly, some embodiments of this application provide a computer program product, the computer program product including a computer program, wherein the computer program, when executed by a processor, can implement the method described in any embodiment of the first aspect. Attached Figure Description

[0023] To more clearly illustrate the technical solutions of some embodiments of this application, the accompanying drawings used in some embodiments of this application will be briefly described below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 System diagrams for construction environment monitoring provided for some embodiments of this application; Figure 2 Schematic diagrams of a monitoring system provided for some embodiments of this application; Figure 3 One of the flowcharts for a construction environment monitoring method provided in some embodiments of this application; Figure 4 A second flowchart illustrating a method for monitoring the construction environment provided in some embodiments of this application; Figure 5 Block diagrams of a construction environment monitoring device provided for some embodiments of this application; Figure 6 A schematic diagram of an electronic device provided for some embodiments of this application. Detailed Implementation

[0025] The technical solutions of some embodiments of this application will now be described with reference to the accompanying drawings.

[0026] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this application, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0027] In related technologies, underground engineering geological monitoring methods typically rely on phased external seismic source deployment and tunnel closures, resulting in high time and cost consumption; furthermore, they have limitations in terms of data timeliness, accuracy, and continuity. Although existing microseismic monitoring and health monitoring technologies can provide a certain degree of rock mass stability assessment, few methods can obtain comprehensive information on the underground medium and structure in real time and continuously during construction. Existing technologies often cannot efficiently process large amounts of data and are usually not synchronized with the construction process, thus missing many potential risk factors.

[0028] However, tunnel boring machines (TBMs), as commonly used construction equipment in underground engineering, generate broadband vibration signals during the tunneling process. These vibration signals are stable and repeatable; the applicant has found that they can serve as "quasi-active sources" for long-term geological monitoring. Utilizing these vibration signals, through a suitable sensor array, continuous observation of underground rock masses can be achieved, thereby deriving the three-dimensional velocity structure and health status.

[0029] In view of the above findings, some embodiments of this application provide a method for monitoring the construction environment. This method combines vibration signals generated by the TBM during construction with existing microseismic monitoring systems to achieve long-term stable monitoring of quasi-active sources. In particular, without affecting the normal operation of the TBM, rolling imaging of the underground three-dimensional velocity structure effectively improves the safety and stability of underground engineering projects. The embodiments of this application can not only dynamically monitor changes in the construction environment but also provide real-time risk warnings, supporting engineering decision-making and possessing high practical and promotional value.

[0030] It should be understood that the vibration signals generated by a TBM during construction cover multiple frequency bands (from low to high frequency), and their amplitude, frequency, and propagation mode are affected by factors such as rock hardness, tunneling method, and cutterhead wear. These vibration signals are not only related to the mechanical operation of the TBM itself, but also closely related to the elasticity and strain characteristics of the surrounding rock mass. Specifically, the low-frequency components of the TBM reflect the large-scale mechanical properties of the rock mass and are suitable for monitoring large-scale structures. The high-frequency components of the TBM are related to minute fracture activity or microseismic events and can be used to accurately detect changes in local rock masses. By monitoring and analyzing the vibration signals generated by the TBM in real time, the velocity characteristics of the underground rock mass can be deduced, and structural changes can be further identified.

[0031] The following is in conjunction with the appendix Figure 1 The overall composition and structure of a construction environment monitoring system provided by some embodiments of this application are illustrated by way of example.

[0032] like Figure 1 As shown, some embodiments of this application provide a system diagram for construction environment monitoring. This system diagram includes multiple detectors 100 and a terminal 200. The multiple detectors 100 can wirelessly transmit the raw vibration signals of the TBM to the central data analysis system of the terminal 200. The central data analysis system can process and analyze the raw vibration signals in real time to obtain monitoring results, and store the data involved in the processing in a cloud data center.

[0033] In some embodiments of this application, the terminal 200 can be a mobile terminal or a non-portable computer terminal, and the embodiments of this application are not specifically limited here.

[0034] In some embodiments of this application, the plurality of geophones 100 may include surface geophones and borehole geophones. The original vibration signal is acquired by the surface geophones and borehole geophones deployed in the target area; the surface geophones are triaxial accelerometers; and the borehole geophones are piezoelectric seismic sensors.

[0035] Specifically, each surface geophone is a triaxial accelerometer capable of capturing vibration data in both horizontal and vertical directions. Each geophone transmits data to a central data processing system via a wireless transmission module. The borehole geophones utilize piezoelectric seismic sensors, which exhibit high stability in underground environments. The geophones are connected to the ground data acquisition system via a wired transmission system, which then wirelessly transmits the acquired vibration signals to the central data processing system. The sampling frequency of all geophones can be set to 1000 Hz to ensure the capture of high-frequency microseismic signals. During acquisition, GNSS (Global Positioning System) and PPS (Precision Clock Synchronization) signals are used to achieve high-precision time synchronization of all geophones, ensuring data timeliness and consistency.

[0036] The following example illustrates the deployment of detectors using a 5000-meter-long ramp and a 720-degree spiral tunneling method with a TBM.

[0037] As an example, a geophone array (as surface geophones) is deployed at the entrance (ground) of the ramp, specifically a 10×10 square array with a spacing of 200 meters, totaling 100 geophones. These geophones are evenly distributed along the ramp's direction, effectively monitoring the vibration propagation during ramp excavation and advancement, and its impact on the surrounding rock mass. To improve the resolution and accuracy of deep data, four boreholes were selected, located in the four directions of the ramp (one borehole in each direction), covering the entire construction area (i.e., the target area). The depth range of these boreholes is 1000 to 2000 meters. Each borehole contains eight geophones (i.e., in-well geophones), with a spacing of 100 meters between geophones. This effectively monitors the vibration signals of the TBM at different depths.

[0038] To facilitate understanding of the detector deployment method, embodiments of this application provide, as follows: Figure 2 The diagram shows a monitoring system. Figure 2 The plan view shows the entire layout area of ​​the ramp, including the 10×10 geophone array on the surface, and marks the location of each well. The cross-sectional view shows the depth of each well and the distribution of geophones within it, indicating the spacing between the eight levels of geophones and the monitoring depth (1000–2000 meters). The 3D view shows the cross-sectional structure of the tunnel, as well as the deployment of surface and well sensors at different depths.

[0039] Once it is confirmed that all detectors are securely installed and the sensor sampling system is functioning properly, the detectors are activated to continuously monitor the vibration signals of the TBM, automatically collect data, and upload it to the central data analysis system in real time.

[0040] The following is in conjunction with the appendix Figure 3 The present application provides an exemplary embodiment of the construction environment monitoring process performed by terminal 200.

[0041] Please see the appendix Figure 3 , Figure 3 A flowchart of a construction environment monitoring method is provided for some embodiments of this application. The construction environment monitoring method may include: S310, during the tunnel boring machine's construction of the target area, the original vibration signal generated by the tunnel boring machine and the construction parameters of the tunnel boring machine are collected; wherein, the construction parameters include thrust and torque.

[0042] For example, in a specific embodiment of this application, during the tunneling process of the TBM in the construction area (i.e., the target area), detectors on the surface and in the well continuously collect raw vibration signals. Simultaneously, the thrust and torque of the TBM are collected in real time.

[0043] To ensure the quality of the acquired raw vibration signal and to obtain meaningful vibration waveform data from it, preprocessing is required to obtain a processed vibration signal. In some embodiments of this application, the processed vibration signal is obtained by: denoising, bandpass filtering, and correcting the raw vibration signal to obtain a corrected vibration signal; and performing wavelet transform and notch filtering on the corrected vibration signal to obtain the processed vibration signal.

[0044] For example, in a specific embodiment of this application, the raw vibration signals acquired by each detector undergo the following preprocessing operations: detrending and mean-removing processing is used to remove long-period noise from the raw vibration signals, highlighting the true vibration signals; a bandpass filter is used to remove low-frequency noise while preserving high-frequency details, typically in the 10-50Hz range; then, the gain differences between different detectors are corrected to obtain the corrected vibration signals. These methods ensure data quality and provide clear and reliable input signals for subsequent imaging inversion. Furthermore, to obtain meaningful vibration waveform data, wavelet transform is performed on the corrected vibration signals to convert them from the time domain to the frequency domain, removing high-frequency noise. For fixed-frequency noise generated by mechanical equipment or other external interference, a notch filter is used for removal. These operations yield the processed vibration signals from which meaningful vibration waveform data can be extracted subsequently.

[0045] S320, the preprocessed vibration signal of the original vibration signal is inverted to obtain the underground three-dimensional velocity model.

[0046] For example, in a specific embodiment of this application, imaging inversion uses the collected and processed vibration signal data to infer information such as the velocity structure and stress state of the underground rock mass. By combining techniques such as arrival-time picking, travel-time tomography, and waveform inversion of the processed vibration signals, a three-dimensional underground velocity model is obtained, accurately revealing the characteristics of the underground medium.

[0047] In some embodiments of this application, S320 may include: S321, Analyze the wave propagation time in the processed vibration signal to obtain the inversion model.

[0048] For example, in a specific embodiment of this application, travel-time tomography (TTTo) constructs a three-dimensional model of the subsurface medium by analyzing the wave propagation time (the time difference from the source (i.e., TBM) to the receiver). Specifically, forward modeling is first performed using the finite difference method (FDM) or ray tracing method to obtain the wave propagation in different media. By combining the least squares method and Tikhonov regularization, the observed processed vibration signal is fitted with theoretical values ​​to obtain a velocity model of the subsurface medium (as a specific example of an inversion model). During the inversion process, prior knowledge (such as velocity data measured downhole) is introduced to improve the accuracy of the inversion results. The inversion model can output physical properties of the subsurface rock mass such as P-wave velocity (Vp), S-wave velocity (Vs), Vp / Vs ratio, and Poisson's ratio.

[0049] S322, The inversion model is optimized using the waveform data in the processed vibration signal to obtain an initial three-dimensional velocity model.

[0050] For example, in a specific embodiment of this application, waveform inversion is performed again based on travel-time tomography to further improve the imaging resolution. By fitting the waveform data of the microseismic signal (i.e., the processed vibration signal), an initial three-dimensional velocity model with higher accuracy than travel-time inversion can be obtained.

[0051] Specifically, the inversion model is optimized by matching the time-domain waveforms of the processed vibration signals from the seismic source and receiver. Using least-squares waveform fitting techniques, the difference between the inversion model and the actual acquired signals is calculated, and the inversion model is iteratively updated until the error is minimized, at which point an initial three-dimensional velocity model is output. Waveform inversion can reveal more subtle geological structures and medium variations, and is particularly suitable for localized or small-scale structural imaging.

[0052] S323, confirm that the accuracy of the initial three-dimensional velocity model meets the preset conditions, and output the underground three-dimensional velocity model.

[0053] For example, in a specific embodiment of this application, the accuracy of the inversion results directly affects the subsequent imaging quality. Residual analysis of the initial 3D velocity model allows for the evaluation of the reliability of the inversion results. The difference between the predicted and actual travel times of the initial 3D velocity model is calculated, and it is checked whether it meets the accuracy requirements (e.g., whether the difference value is greater than a preset accuracy value, as a specific example of a preset condition). If not, the model parameters are changed until a model that meets the preset accuracy value is obtained. Additionally, the sensitivity of the initial 3D velocity model to different input data needs to be evaluated (e.g., global sensitivity analysis or adjoint methods can be used) to ensure that its sensitivity meets preset conditions, thereby ensuring the stability of the imaging results. Once the accuracy and sensitivity requirements are met, the subsurface 3D velocity model is output.

[0054] In addition, the coverage of data (i.e., processed vibration signals) can be assessed based on the deployment of detectors; for areas with missing or insufficient coverage, supplementary measures can be taken by adding temporary stations or optimizing detector layout.

[0055] S330, based on the underground three-dimensional velocity model, the wave velocity change rate is obtained, and based on the processed vibration signal, the index value of the rock mass abnormal event is obtained.

[0056] For example, in a specific embodiment of this application, in order to achieve health monitoring of underground rock masses, it is necessary to obtain the velocity structure of the underground rock masses, namely the wave velocity change rate dv / v and the index value b.

[0057] Specifically, S330 may include: obtaining the imaging wave velocity structure of the tunnel boring machine through the underground three-dimensional velocity model; and obtaining the wave velocity change rate at different times and locations in the target area based on the imaging wave velocity structure.

[0058] For example, in a specific embodiment of this application, dv / v is a core indicator in health monitoring, used to monitor the stress and fracture state of rock mass. Changes in dv / v reflect physical changes in the underground medium, such as stress changes, fracture propagation, and fluid permeability. A three-dimensional underground velocity model can be used to acquire and dynamically compare the imaging wave velocity structure of the TBM active source in real time. Combined with vibration data from the active source (i.e., the TBM), the time-varying trend of dv / v at different locations and times can be analyzed. By comparing the relative rate of change of wave velocity (i.e., dv / v) at different times and in different regions, it can be seen whether the surrounding rock hardens or softens during excavation, and whether stress concentration or loosening occurs. Subsequently, the Coda wave interferometry can be used to capture even more subtle dv / v changes in the underground rock mass. Coda waves are highly sensitive to minute changes in the wave velocity of seismic waves. By comparing Coda wave signals from different time windows, the interference principle is used to amplify minute differences in wave velocity, thereby accurately capturing dv / v changes of 0.01% or even smaller.

[0059] Using the aforementioned underground three-dimensional velocity model and Coda wave interferometry, comprehensive and accurate dv / v changes can be obtained.

[0060] Specifically, S330 may include: statistically analyzing rock mass anomalies in the target area within a preset time period; clustering the rock mass anomalies into event clusters, and then calculating the index value of the event clusters.

[0061] For example, in a specific embodiment of this application, the fracturing and sliding processes of underground rock masses are assessed by analyzing the clustering of microseismic events. A microseismic event characterizes the detection of fracturing or deformation in the rock mass; the location of a detected fracturing or deformation represents a microseismic event. The spatial clustering of events is analyzed by statistically analyzing the number of microseismic events within a certain time period (as a specific example of a preset time period). Dense clusters of events often indicate stress accumulation, suggesting potential fracturing or sliding risks. Based on the Gutenberg-Richter rule, the vulnerability of the rock mass is assessed by calculating the b-value of the event clusters of microseismic events.

[0062] S340, Analyze the construction parameters, the wave velocity change rate, and the index values ​​to obtain the monitoring results of the target area; wherein, the monitoring results include the risk level and the response measures to address the risk level.

[0063] For example, in a specific embodiment of this application, by dynamically monitoring and evaluating the rock mass, and conducting risk assessments on the obtained dv / v changes, b-values ​​of microseismic events, and construction parameters, potential risk areas can be identified in a timely manner, and corresponding control measures can be taken.

[0064] In some embodiments of this application, S340 may include: analyzing the construction parameters to obtain a first determination result; wherein the first determination result indicates whether the construction parameters are abnormal; comparing the wave velocity change rate with a preset threshold to obtain a second determination result; wherein the second determination result indicates whether the wave velocity change rate is abnormal; analyzing the index value to obtain a third determination result; wherein the third determination result indicates whether the index value is abnormal; wherein the abnormality indicates that the rock mass in the target area is fractured or deformed; combining the first determination result, the second determination result, and the third determination result to determine the risk level; and obtaining the response measures corresponding to the risk level.

[0065] For example, in a specific embodiment of this application, by real-time monitoring of the TBM's thrust, torque, and vibration signals, combined with construction load analysis, the response of the underground rock mass can be determined. Specifically, when the TBM's thrust or torque fluctuates abnormally during construction, it indicates that the rock mass may have fractured or deformed. At this time, by combining the intensity and spectral characteristics of the processed vibration signal corresponding to the original vibration signal, the deformation and stress state of the underground rock mass can be analyzed. The method for determining abnormal fluctuations in the TBM's thrust or torque is as follows: Unexpected sudden increases, decreases, or periodic oscillations in the axial thrust output by the TBM propulsion system (used to overcome surrounding rock resistance and drive the cutterhead to break rock) are considered abnormal fluctuations. Unexpected sudden changes, jitters, or irregular fluctuations in the torsional torque output by the TBM cutterhead rotation system (used to drive the cutterhead to cut rock) are also considered abnormal fluctuations.

[0066] A preset threshold is set for dv / v changes; when the dv / v change in a certain area exceeds the preset threshold, an anomaly is confirmed. For example, |dv / v| ≥ 0.05% (as a specific example of the preset threshold).

[0067] A lower limit can be set for the b value. When the b value is lower than the lower limit, it indicates an anomaly, which means that the rock mass is relatively fragile and may fracture.

[0068] By combining multiple parameters such as dv / v, b-value of event cluster density, and construction parameters, a comprehensive evaluation is conducted, and a tiered early warning mechanism is used to provide real-time risk assessment.

[0069] Specifically, if the dv / v, b-value, and construction parameters are all normal, the rock mass is stable and requires no special attention; this is at the green warning level of the risk classification. If either the dv / v or b-value is abnormal, this is at the yellow warning level of the risk classification, and enhanced monitoring is recommended (as a specific example of response measures). If any two of the dv / v, b-value, and construction parameters are abnormal, the rock mass may fracture or undergo large-scale deformation; this is at the orange warning level of the risk classification, requiring immediate adjustment of the construction plan and reinforcement of support (as a specific example of response measures). If all of the dv / v, b-value, and construction parameters are abnormal, this is at the red warning level of the risk classification, requiring immediate cessation of construction and a comprehensive assessment; structural reinforcement or a redesign of the construction plan may be necessary (as a specific example of response measures).

[0070] It is understood that the above risk levels and response measures can be flexibly adjusted according to actual needs, and the embodiments of this application are not limited thereto.

[0071] The following is in conjunction with the appendix Figure 4 The present application provides an exemplary description of the specific process of construction environment monitoring provided by some embodiments.

[0072] Please see the appendix Figure 4 , Figure 4 A flowchart of a construction environment monitoring method provided for some embodiments of this application.

[0073] The above process is illustrated below by example.

[0074] S410 acquires the raw vibration signals of the TBM in the construction area, continuously acquired by geophones on the ground and in the well.

[0075] For example, surface stations employ high-precision geophones and wireless transmission systems to send the acquired raw vibration signals to a central data processing system (or data processing and analysis platform). In-well stations utilize long-life sensors and high-strength packaging to ensure long-term stable operation. The data integration platform within the data processing and analysis platform integrates data from different sources (e.g., microseismic, TBM, etc.) for unified management and analysis. Data analysis tools include specialized algorithms and tools for subsequent data preprocessing, imaging inversion, health monitoring, and risk assessment. Simultaneously, this application ensures throughout the entire process that data acquisition and monitoring during construction will not interfere with TBM operations, avoiding any impact on construction safety; and employs low-noise, low-pollution equipment and technologies to minimize environmental impact.

[0076] S420 preprocesses the original vibration signal to obtain the processed vibration signal.

[0077] For example, preprocessing types include denoising, filtering, and normalization, as well as removing environmental noise and instrument interference.

[0078] S430 inverts the processed vibration signal to obtain a three-dimensional underground velocity model.

[0079] S440, wave velocity change rate obtained based on underground three-dimensional velocity model.

[0080] For example, dv / v change analysis can monitor and assess wave velocity changes in underground rock masses in real time.

[0081] S450, calculate and analyze the density and b-value of microseismic event clusters in the processed vibration signal.

[0082] For example, the density and b-value of microseismic event clusters can be calculated and analyzed to assess the stability of rock masses.

[0083] S460, obtain the construction parameters of the TBM.

[0084] For example, the response of the rock mass during construction can be analyzed by combining the thrust and torque of the TBM.

[0085] S470 analyzes construction parameters, wave velocity change rate, and b-value to obtain the risk level and response measures for the construction area.

[0086] For example, a green risk level requires maintaining routine monitoring without special intervention. A yellow risk level requires increasing monitoring frequency and adjusting the construction plan if necessary. An orange risk level requires initiating emergency response measures, such as reinforcement and adjusting the progress rate. A red risk level requires halting construction, conducting a comprehensive risk assessment, and reinforcing the site. After a risk level warning is triggered, the construction team takes appropriate measures based on system feedback. Warning information is transmitted to relevant personnel via SMS, email, etc., and a detailed report is generated.

[0087] It is understood that the specific implementation process of S410~S470 can refer to the method implementation examples provided above. To avoid repetition, detailed descriptions are omitted here.

[0088] As can be seen from the above embodiments of this application, this application can continuously monitor the physical state of underground rock mass through TBM vibration signals without affecting tunnel construction. This method has high timeliness, can dynamically identify the change process of rock mass, and promptly detect potential safety hazards. Compared with traditional external seismic sources, TBM quasi-active sources have the advantages of long-term operation, low cost, and high efficiency. During engineering construction, using existing TBM vibration signals eliminates the need for additional seismic source deployment, greatly saving construction and maintenance costs. Through real-time feedback from the health monitoring system, potential risk areas can be identified in a timely manner, providing decision-making basis for construction personnel and management, and improving construction safety.

[0089] Moreover, the embodiments of this application are not only applicable to tunnels and underground laboratories, but can also be extended to various underground projects such as subways and underground factories. The technical process and equipment layout in this method can be flexibly adjusted according to the needs of different projects. This application has strong standardization and automation characteristics, and can reduce manual intervention and improve monitoring efficiency and accuracy through automated monitoring systems and data processing processes. Furthermore, this application is replicable and universal; the implementation and operation steps of this method are highly replicable, can be promoted on a large scale, and can be customized according to the geological conditions of different regions.

[0090] Please refer to Figure 5 , Figure 5 The diagram shows a block diagram of a construction environment monitoring device provided in some embodiments of this application. It should be understood that this construction environment monitoring device corresponds to the method embodiments described above and is capable of performing the various steps involved in the method embodiments. The specific functions of this construction environment monitoring device can be found in the description above; detailed descriptions are omitted here to avoid repetition.

[0091] Figure 5 The construction environment monitoring device includes at least one software functional module that can be stored in a memory or embedded in the construction environment monitoring device in the form of software or firmware. The device includes: a data acquisition module 510, used to acquire the original vibration signal generated by the tunnel boring machine and the construction parameters of the tunnel boring machine during construction in the target area; wherein the construction parameters include thrust and torque; an inversion module 520, used to invert the pre-processed vibration signal of the original vibration signal to obtain a three-dimensional underground velocity model; a data acquisition module 530, used to obtain the wave velocity change rate based on the three-dimensional underground velocity model and to obtain the index value of rock mass anomaly events based on the processed vibration signal; and a monitoring module 540, used to analyze the construction parameters, the wave velocity change rate, and the index value to obtain the monitoring results of the target area; wherein the monitoring results include the risk level and response measures to address the risk level.

[0092] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working process of the device described above can be referred to the corresponding process in the aforementioned method, and will not be elaborated further here.

[0093] Some embodiments of this application also provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, can perform the operation of any of the methods corresponding to the methods provided in the above embodiments.

[0094] Some embodiments of this application also provide a computer program product, which includes a computer program, wherein when the computer program is executed by a processor, it can implement the operation of any of the methods corresponding to the above embodiments provided in the above embodiments.

[0095] like Figure 6 As shown, some embodiments of this application provide an electronic device 600, which includes a memory 610, a processor 620, and a computer program stored in the memory 610 and executable on the processor 620. When the processor 620 reads the program from the memory 610 via a bus 630 and executes the program, it can implement the methods of any of the above embodiments.

[0096] Processor 620 can process digital signals and can include various computing architectures. For example, it can be a complex instruction set computer architecture, a reduced instruction set computer architecture, or an architecture that implements multiple instruction set combinations. In some examples, processor 620 can be a microprocessor.

[0097] The memory 610 can be used to store instructions executed by the processor 620 or data related to the execution of instructions. These instructions and / or data may include code for implementing some or all of the functions of one or more modules described in the embodiments of this application. The processor 620 of this disclosure embodiment can be used to execute the instructions in the memory 610 to implement the methods shown above. The memory 610 includes dynamic random access memory, static random access memory, flash memory, optical memory, or other memories well known to those skilled in the art.

[0098] The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application. It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0099] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0100] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

Claims

1. A method for monitoring the construction environment, characterized in that, include: During the tunnel boring machine's construction in the target area, the original vibration signals generated by the tunnel boring machine and the construction parameters of the tunnel boring machine are collected; wherein, the construction parameters include thrust and torque; The preprocessed vibration signal of the original vibration signal is inverted to obtain a three-dimensional underground velocity model; The wave velocity change rate is obtained based on the underground three-dimensional velocity model, and the index value of rock mass anomaly event is obtained based on the processed vibration signal. The construction parameters, wave velocity change rate, and index values ​​are analyzed to obtain monitoring results for the target area; wherein, the monitoring results include the risk level and response measures to address the risk level.

2. The method as described in claim 1, characterized in that, The processed vibration signal was obtained through the following method: The original vibration signal is denoised, bandpass filtered, and corrected to obtain the corrected vibration signal; The corrected vibration signal is subjected to wavelet transform and notch filtering to obtain the processed vibration signal.

3. The method as described in claim 1 or 2, characterized in that, The process of inverting the preprocessed vibration signal after the original vibration signal to obtain a three-dimensional underground velocity model includes: The wave propagation time in the processed vibration signal is analyzed to obtain an inversion model; The inversion model is optimized using waveform data from the processed vibration signal to obtain an initial three-dimensional velocity model. Once the accuracy of the initial three-dimensional velocity model is confirmed to meet the preset conditions, the underground three-dimensional velocity model is output.

4. The method as described in claim 1 or 2, characterized in that, The process of obtaining the wave velocity change rate based on the underground three-dimensional velocity model includes: The imaging wave velocity structure of the tunnel boring machine is obtained through the underground three-dimensional velocity model; The rate of change of wave velocity at different locations at different times in the target region is obtained based on the imaging wave velocity structure.

5. The method as described in claim 1 or 2, characterized in that, The index values ​​for rock mass anomaly events obtained based on the processed vibration signals include: Statistical analysis of rock mass anomalies in the target area within a preset time period; After clustering the rock mass anomalies into event clusters, the index values ​​of the event clusters are calculated.

6. The method as described in claim 1 or 2, characterized in that, The analysis of the construction parameters, the wave velocity change rate, and the index values ​​to obtain the monitoring results of the target area includes: The construction parameters are analyzed to obtain a first determination result; wherein, the first determination result indicates whether the construction parameters are abnormal. The wave velocity change rate is compared with a preset threshold to obtain a second determination result; wherein, the second determination result indicates whether the wave velocity change rate is abnormal; The index values ​​are analyzed to obtain a third judgment result; wherein, the third judgment result indicates whether the index values ​​are abnormal; wherein, the abnormality indicates that the rock mass in the target area is fractured or deformed; The risk level is determined by combining the first determination result, the second determination result, and the third determination result; and the response measures corresponding to the risk level are obtained.

7. The method as described in claim 1 or 2, characterized in that, The original vibration signal was acquired by surface geophones and borehole geophones deployed in the target area; the surface geophones are triaxial accelerometers; and the borehole geophones are piezoelectric seismic sensors.

8. A device for monitoring the construction environment, characterized in that, include: The data acquisition module is used to collect the original vibration signals generated by the tunnel boring machine and the construction parameters of the tunnel boring machine during the construction of the target area; wherein, the construction parameters include thrust and torque; The inversion module is used to invert the preprocessed vibration signal of the original vibration signal to obtain a three-dimensional underground velocity model. The data acquisition module is used to obtain the wave velocity change rate based on the underground three-dimensional velocity model, and to obtain the index value of rock mass abnormal events based on the processed vibration signal. The monitoring module is used to analyze the construction parameters, the wave velocity change rate, and the index values ​​to obtain the monitoring results of the target area; wherein, the monitoring results include the risk level and the response measures to address the risk level.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein the computer program is executed by a processor to perform the method as described in any one of claims 1-7.

10. An electronic device, characterized in that, It includes a memory, a processor, and a computer program stored on the memory and running on the processor, wherein the computer program is executed by the processor to perform the method as described in any one of claims 1-7.

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