A method and system for safety risk assessment of water conservancy projects

Abstract

This invention discloses a method and system for safety risk assessment of water conservancy projects, specifically relating to the field of water conservancy engineering technology. By analyzing the fluctuation of the rate of change of ground stress over time, it determines whether there is abnormal stress concentration or release. If an anomaly is detected, an array of seismic monitoring sensors is used to analyze the microseismic characteristics and seismic wave velocity anomalies in the dam area to determine whether there are local rock mass structural changes or hidden damage. A geological hazard interference assessment model is constructed, and the interference index is calculated by combining the ground stress fluctuation index and the seismic wave velocity anomaly index. When the interference index reaches a high level of interference, the system immediately activates a dynamic adjustment mechanism to remotely adjust the sensitivity of the monitoring equipment and the data acquisition frequency according to the interference situation, and automatically optimizes the early warning threshold. This invention can effectively reduce the interference of geological hazards on monitoring equipment, improve the accuracy of water conservancy project safety monitoring, realize real-time early warning and intelligent control, and enhance the dam safety management capability.

Description

Technical Field

[0001] This invention relates to the field of water conservancy engineering technology, specifically to a method and system for assessing the safety risks of water conservancy projects. Background Technology

[0002] Safety risk assessment for water conservancy projects refers to the identification, evaluation, and control of potential safety risks during the planning, design, construction, and operation of water conservancy projects through systematic analysis and scientific methods. This assessment typically covers multiple aspects, including structural stability, flood risk, geological hazards, construction safety, and operation and maintenance. It employs a combination of qualitative and quantitative methods, such as risk matrices, the Analytic Hierarchy Process (AHP), and fuzzy comprehensive evaluation, to ensure project safety and reduce the occurrence of accidents.

[0003] Currently, reservoir dam safety monitoring systems are a crucial technical means for assessing the safety risks of water conservancy projects. For example, reservoir dam monitoring technologies based on the Internet of Things and big data analytics can collect real-time data on dam deformation, seepage, stress, and strain, and use artificial intelligence algorithms for risk warnings. For instance, the Three Gorges Dam safety monitoring system employs technologies such as satellite remote sensing and automated monitoring sensors to conduct all-weather monitoring and safety assessments of the dam's operation, effectively improving the level of project safety management.

[0004] The existing technology has the following shortcomings:

[0005] Some dams are built in areas with complex terrain, such as mountains and canyons. Their foundations and surrounding soil and rock structures are significantly affected by geological conditions, potentially leading to risks such as landslides, settlement, ground fissures, and rock collapses. For example, during heavy rainfall or earthquakes, landslides may occur on the mountains upstream or on either side of the dam, causing sensor base displacement, burying or damaging monitoring equipment, resulting in distorted or even interrupted monitoring data. Simultaneously, foundation settlement may cause structural deformation of the dam, affecting the measurement accuracy of the monitoring system. Furthermore, if geological disasters distort data from monitoring equipment, it may affect the reliability of dam safety monitoring and the accuracy of early warning systems. Summary of the Invention

[0006] The purpose of this invention is to provide a method and system for assessing the safety risks of water conservancy projects, in order to address the shortcomings of the prior art.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a method for safety risk assessment of water conservancy projects, comprising the following steps:

[0008] S1: Monitor stress changes in the dam foundation and surrounding rock strata using borehole stress gauges, analyze the fluctuation of the rate of change of ground stress over time, and determine whether there is any abnormal stress concentration or release.

[0009] S2: If there is abnormal stress concentration or release, the array-type seismic monitoring sensors will be used to analyze the abnormal changes in seismic wave velocity based on the micro-seismic activity and the propagation characteristics of seismic waves in the dam area, and to determine whether there are local rock mass structural changes or hidden damage.

[0010] S3: Construct a geological hazard interference assessment model, calculate the interference index based on the fluctuation of the rate of change of ground stress over time and the abnormal changes of seismic wave velocity, and classify the degree of interference into high interference level and low interference level;

[0011] S4: When the interference index reaches the high interference level, the dynamic adjustment mechanism is immediately activated. Based on the interference situation, the sensitivity of the monitoring equipment and the data acquisition frequency are remotely adjusted, and the warning threshold is automatically adjusted to increase or decrease the warning sensitivity.

[0012] Preferably, in S1, the fluctuation of the rate of change of ground stress over time is analyzed to generate a ground stress change rate fluctuation index. The method for obtaining the ground stress change rate fluctuation index is as follows:

[0013] Collect the time-varying rate sequence of ground stress The expression is: ;in: Let Δt be the time interval, representing the change in geostress rate. The signal is decomposed into multiple intrinsic mode functions (IMFs) at different scales. The original signal is then decomposed using the envelope method to extract multiple IMFs. ;in: It is the i-th IMF component. This is the final residual, where N represents the number of intrinsic mode functions obtained from the decomposition, i.e., the number of intrinsic mode functions extracted from the original signal during the decomposition process. A termination condition is set: when the residual... Stop decomposition when the signal becomes a monotonic function or a low-frequency trend signal;

[0014] Calculate the energy percentage of each IMF component. : Calculate the instantaneous amplitude and instantaneous frequency of each IMF component, analyze the fluctuation characteristics of the rate of change of geostress, and perform analysis on each IMF component. Perform a Hilbert transform to obtain its analytic signal, and calculate the instantaneous amplitude. The expression is: ; Given the analytic signal obtained after Hilbert transform; calculate the weighted average instantaneous amplitude. The expression is: ;in: The weighted average instantaneous frequency is calculated using energy weights and M as the total number of instantaneous amplitudes. , the expression is: ; where is the instantaneous frequency, and its calculation expression is: ; calculate the stress change rate fluctuation index SCRFI, and its expression is: .

[0015] Preferably, set the normal range [SCRFImin, SCRFImax] for early warning:

[0016] Low risk: SCRFI ≤ SCRFImin; Medium risk: SCRFImin < SCRFI ≤ SCRFImax; High risk: SCRFI > SCRFImax. At this time, there is stress concentration or release, and an early warning signal is generated.

[0017] Preferably, after analyzing the abnormal change of seismic wave velocity, generate the seismic wave velocity anomaly index. The acquisition method of the seismic wave velocity anomaly index is as follows:

[0018] Let the seismic wave velocity time series be: ; where: V(k) is the seismic wave velocity at the k-th moment. Construct the cumulative generating sequence and perform a first-order cumulative generation: ; where: ; Use the GM(1,1) model to set that the cumulative generating sequence satisfies the differential equation: ; where: a is the development coefficient, indicating the change trend of seismic wave velocity; b is the grey action quantity, indicating the external influence of the system. Use the least squares method to estimate a and b. Based on the solved a and b, obtain the prediction formula of the GM(1,1) model: ; Through the first-order inverse cumulative generation, obtain the predicted value of the original sequence , and the expression is: ; Define the seismic wave velocity anomaly index SWVAI, and its expression is: ; where: represents the actual observed seismic wave velocity at the k-th moment, represents the seismic wave velocity predicted by the GM(1,1) model, is the standard deviation of historical prediction errors, and ϵ is the smoothing factor.

[0019] Preferably, judge the rock mass structure state according to the SWVAI value: SWVAI < 1 indicates that the rock mass state is normal and there is no significant anomaly in seismic wave velocity; 1 ≤ SWVAI < 2 indicates that the rock mass state is slightly abnormal and there is local crack development; 2 ≤ SWVAI < 3 indicates that the rock mass state is moderately abnormal and there is rock mass rupture or increased water infiltration; SWVAI ≥ 3 indicates that the rock mass state is highly abnormal and there is large-scale rock mass rupture, landslide or dam foundation instability; when SWVAI ≥ 3, trigger an automatic early warning, increase the monitoring frequency, and collect seismic wave velocity data with higher density.

[0020] Preferably, in S3, a geological hazard interference assessment model is constructed. Based on the fluctuation of the rate of change of ground stress over time and the abnormal changes in seismic wave velocity, the interference index is calculated, and the interference level is divided into high interference level and low interference level.

[0021] The stress variation rate fluctuation index and the seismic wave velocity anomaly index were normalized so that they were both between [0,1]. The interference index was obtained by weighted averaging the normalized stress variation rate fluctuation index and the seismic wave velocity anomaly index.

[0022] Preferably, the obtained interference index is compared with a pre-set interference index reference threshold based on historical data. If the interference index is greater than or equal to the pre-set interference index reference threshold, it indicates that there is significant geostress anomaly or rock mass structure damage in the dam area, and the monitoring data is severely interfered with, requiring further analysis and early warning. The interference level is classified as high interference level. If the interference index is less than the pre-set interference index reference threshold, it indicates that the rock mass structure in the dam area is stable, the changes in geostress and seismic wave velocity are within the normal range, and the monitoring data is less interfered with. The interference level is classified as low interference level.

[0023] Preferably, in S4, when the interference index reaches a high interference level, a dynamic adjustment mechanism is immediately activated to remotely adjust the sensitivity and data acquisition frequency of the monitoring equipment, as well as automatically adjust the warning threshold, to increase or decrease the warning sensitivity, based on the interference situation.

[0024] When the interference index reaches a high level of interference, that is, when the interference index is greater than or equal to the preset interference index reference threshold, the dynamic adjustment mechanism is immediately activated to analyze all interference index data within a fixed time period, calculate the mean and standard deviation of the interference index, and determine the interference situation.

[0025] If the mean of the interference index is greater than or equal to the reference threshold of the mean of the interference index, and the standard deviation of the interference index is less than the reference threshold of the standard deviation of the interference index, it indicates that the situation is a stable high interference situation. It is necessary to enhance the sensitivity of the equipment, increase the data acquisition frequency, lower the warning threshold, and improve the warning sensitivity.

[0026] If the mean of the interference index is greater than or equal to the reference threshold of the mean of the interference index, and the standard deviation of the interference index is greater than or equal to the reference threshold of the standard deviation of the interference index, it indicates that the situation is characterized by high volatility interference, and it is necessary to increase the data collection frequency while keeping the warning threshold unchanged.

[0027] If the mean of the interference index is less than the reference threshold for the mean of the interference index, and the standard deviation of the interference index is greater than or equal to the reference threshold for the standard deviation of the interference index, it indicates that this is a short-term abnormal fluctuation. The data collection frequency should be increased, the warning threshold should not be adjusted for the time being, and monitoring should continue.

[0028] If the mean of the interference index is less than the reference threshold for the mean of the interference index, and the standard deviation of the interference index is less than the reference threshold for the standard deviation of the interference index, it indicates that the interference is low and the current monitoring strategy should be maintained without adjustment.

[0029] The present invention also provides a water conservancy project safety risk assessment system, including a ground stress monitoring module, a seismic wave monitoring and analysis module, a geological hazard interference assessment module, and a dynamic adjustment module;

[0030] Ground stress monitoring module: Monitors stress changes in the dam foundation and surrounding rock strata through borehole stress gauges, analyzes the fluctuation of ground stress over time, and determines whether there is abnormal stress concentration or release.

[0031] Seismic wave monitoring and analysis module: If there is abnormal stress concentration or release, the array-type seismic monitoring sensor analyzes the abnormal changes in seismic wave velocity based on the micro-seismic activity and the propagation characteristics of seismic waves in the dam area, and determines whether there are local rock mass structural changes or hidden damage.

[0032] Geological hazard interference assessment module: Constructs a geological hazard interference assessment model, calculates the interference index based on the fluctuation of the rate of change of ground stress over time and the abnormal changes of seismic wave velocity, and classifies the degree of interference into high interference level and low interference level;

[0033] Dynamic adjustment module: When the interference index reaches the high interference level, the dynamic adjustment mechanism is immediately activated. Based on the interference situation, the sensitivity of the monitoring equipment and the data acquisition frequency are remotely adjusted, and the warning threshold is automatically adjusted to increase or decrease the warning sensitivity.

[0034] The technical effects and advantages provided by the present invention in the above technical solution are as follows:

[0035] 1. This invention utilizes the combined monitoring of borehole stress gauges and array-type seismic monitoring sensors to accurately identify abnormal stress changes, seismic wave velocity anomalies, and rock mass structural damage in the dam foundation and surrounding rock strata. By calculating the stress variation rate fluctuation index and the seismic wave velocity anomaly index, a geological hazard interference assessment model is constructed. This model comprehensively analyzes the interference level of the monitoring data and classifies it into high and low interference levels based on the interference index. When the interference index reaches the high interference level, the system immediately activates a dynamic adjustment mechanism to remotely optimize the sensitivity of the monitoring equipment, adjust the data acquisition frequency, and adaptively optimize the early warning threshold, thereby improving the monitoring system's response capability to sudden geological disasters.

[0036] 2. This invention effectively improves the stability, reliability, and accuracy of dam safety monitoring, overcoming the shortcomings of traditional monitoring methods that are susceptible to geological disasters and have low early warning accuracy. In complex terrain environments, this method can achieve real-time monitoring, intelligent identification, and accurate early warning, reducing monitoring errors caused by geological disasters such as landslides, subsidence, and ground fissures, and improving the intelligence level of dam safety assessment. Through remote dynamic adjustment, the system can adaptively adjust monitoring parameters according to real-time monitoring conditions, reducing false alarms and missed alarms, ultimately improving the long-term safety and management efficiency of water conservancy projects. Attached Figure Description

[0037] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0038] Figure 1 Flow chart of the method of the present invention.

[0039] Figure 2 This is a system module diagram of the present invention. Detailed Implementation

[0040] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0041] Example 1, please refer to Figure 1 As shown in this embodiment, a method for assessing the safety risks of water conservancy projects includes the following steps:

[0042] S1: Monitor stress changes in the dam foundation and surrounding rock strata using borehole stress gauges, analyze the fluctuation of the rate of change of ground stress over time, and determine whether there is any abnormal stress concentration or release.

[0043] S2: If there is abnormal stress concentration or release, the array-type seismic monitoring sensors will be used to analyze the abnormal changes in seismic wave velocity based on the micro-seismic activity and the propagation characteristics of seismic waves in the dam area, and to determine whether there are local rock mass structural changes or hidden damage.

[0044] S3: Construct a geological hazard interference assessment model, calculate the interference index based on the fluctuation of the rate of change of ground stress over time and the abnormal changes of seismic wave velocity, and classify the degree of interference into high interference level and low interference level;

[0045] S4: When the interference index reaches the high interference level, the dynamic adjustment mechanism is immediately activated. Based on the interference situation, the sensitivity of the monitoring equipment and the data acquisition frequency are remotely adjusted, and the warning threshold is automatically adjusted to increase or decrease the warning sensitivity.

[0046] In S1, borehole stress gauges are deployed at key locations in the dam foundation and surrounding rock strata (such as the dam abutment, deep within the dam foundation, and near fault zones) to monitor the three-dimensional stress state. A multi-point deployment strategy is adopted to ensure data representativeness and avoid local anomalies affecting the overall assessment.

[0047] High-precision borehole stress sensors are used to periodically measure the magnitude, direction, and rate of change of principal stress in rock strata. The data is transmitted to a remote monitoring center via wireless transmission, fiber optic, or LoRa communication.

[0048] The fluctuation of the rate of change of ground stress over time is analyzed to generate a ground stress change rate fluctuation index, which is used to determine whether there is abnormal stress concentration or release. The method for obtaining the ground stress change rate fluctuation index is as follows:

[0049] Collect the time-varying rate sequence of ground stress The expression is: ;in: Let Δt be the change in geostress, and Δt be the time interval (e.g., seconds, hours, days). The geostress change rate sequence... The system is decomposed into multiple IMF components of different scales, and the main oscillation modes are extracted.

[0050] The original signal is decomposed using the envelope method to extract multiple intrinsic mode functions: ;in: It is the i-th IMF component. This is the final residual, representing the overall trend term. N represents the number of intrinsic mode functions (IMFs) obtained from the decomposition, i.e., the number of IMFs extracted from the original signal during the decomposition process. A termination condition is set: when the residual... Stop decomposition when the signal becomes a monotonic function or a low-frequency trend signal.

[0051] Calculate the energy percentage of each IMF component. : ; Select the IMF component with higher energy for subsequent analysis (usually remove high-frequency components with high noise).

[0052] Calculate the instantaneous amplitude and instantaneous frequency of each IMF component, analyze the fluctuation characteristics of the in-situ stress change rate, and for each IMF component perform the Hilbert transform to obtain its analytic signal and calculate the instantaneous amplitude , with the expression: ; is the analytic signal obtained after the Hilbert transform; calculate the weighted average instantaneous amplitude , with the expression: ; where: is the energy weight, M is the total number of instantaneous amplitudes, calculate the weighted average instantaneous frequency , with the expression: ; in the formula, is the instantaneous frequency, and the calculation expression is: ; calculate the in-situ stress change rate fluctuation index SCRFI, with the expression: .

[0053] Set the normal range [SCRFImin, SCRFImax] (which can be statistically based on historical data) and issue early warnings:

[0054] Normal (low risk): SCRFI ≤ SCRFImin; Attention (medium risk): SCRFImin < SCRFI ≤ SCRFImax; Abnormal (high risk): SCRFI > SCRFImax. At this time, there is stress concentration or release, and an early warning signal is generated.

[0055] S2: If there is abnormal stress concentration or release, then through an array of seismic monitoring sensors, according to the propagation characteristics of microseisms and seismic waves in the dam area, analyze the abnormal changes in seismic wave velocity to determine whether there are local rock mass structure changes or hidden damages.

[0056] Deploy an array of seismic monitoring sensors in the key areas of the dam foundation, dam shoulders, and surrounding rock masses, and adopt a three-dimensional seismic monitoring network to ensure that data covers the entire dam area. Select high-sensitivity three-component seismometers (3C Geophones) that can monitor P-waves (primary waves) and S-waves (secondary waves).

[0057] The sensors record microseismic and seismic waveform data in real time at a high sampling rate (≥100 Hz), including information such as amplitude, frequency, and phase. Record signals from different seismic sources such as natural earthquakes, engineering blasts, and internal microseisms in the dam body.

[0058] The calculation formula for seismic wave velocity V: ; where: d is the propagation distance between two sensors; t is the time difference for the seismic wave to reach the two sensors.

[0059] A double-difference seismic location method is employed to eliminate source error and improve location accuracy. The relative arrival time difference (Time Delay) of multiple sensors is calculated using a cross-correlation method to determine the source location.

[0060] The first arrival times of the P-wave and S-wave were extracted through waveform analysis: ;in: The first arrival time of the P wave. The first arrival time of the S-wave is given. Poisson's ratio is calculated to infer rock mass fracture characteristics. If the Poisson's ratio changes abnormally, it may indicate that there is crack propagation or fracturing inside the rock mass.

[0061] After analyzing the abnormal changes in seismic wave velocity, a seismic wave velocity anomaly index is generated to determine whether there are local changes in rock mass structure or hidden damage. The method for obtaining the seismic wave velocity anomaly index is as follows:

[0062] Let the seismic wave velocity time series be: Where: V(k) is the seismic wave velocity at time k (e.g., P-wave velocity). or S-wave velocity To construct an accumulation generation sequence, and to reduce randomness, perform an accumulation generation (AGO): ;in: The purpose of this step is to enhance the smoothness of the data and reduce the impact of short-term fluctuations. Using the GM(1,1) model, the accumulated generation sequence is set to satisfy the differential equation: Where: a is the development coefficient, representing the trend of seismic wave velocity variation; b is the grey action quantity, representing the external influence of the system. a and b are estimated using the least squares method. Based on the solved a and b, the prediction formula of the GM(1,1) model is obtained: The predicted value of the original sequence is obtained through a single cumulative subtraction. The expression is: The seismic wave velocity anomaly index SWVAI is defined as follows: ;in: This represents the actual observed seismic wave velocity at time k. This represents the seismic wave velocity predicted by the GM(1,1) model. ϵ is the standard deviation of historical prediction errors, and ϵ is a smoothing factor to prevent the denominator from approaching zero.

[0063] The rock mass structural condition is determined based on the SWVAI value: SWVAI<1 indicates that the rock mass condition is normal and there is no significant abnormality in seismic wave velocity; 1≤SWVAI<2 indicates that the rock mass condition is slightly abnormal and there may be local crack development; 2≤SWVAI<3 indicates that the rock mass condition is moderately abnormal and there may be rock mass rupture or increased water seepage; SWVAI≥3 indicates that the rock mass condition is highly abnormal and there may be large-scale rock mass rupture, landslide or dam foundation instability.

[0064] When SWVAI≥3, an automatic warning is triggered. Recommendations include: increasing the monitoring frequency and collecting higher density seismic wave velocity data; combining GNSS monitoring to assess whether the dam body has shifted; and conducting engineering inspections to check for new cracks or seepage in the dam foundation rock layer.

[0065] S3: Construct a geological hazard interference assessment model, calculate the interference index based on the fluctuation of the rate of change of ground stress over time and the abnormal changes of seismic wave velocity, and classify the degree of interference into high interference level and low interference level.

[0066] The stress variation rate fluctuation index and the seismic wave velocity anomaly index were normalized so that they were both between [0,1]. The interference index was obtained by weighted averaging the normalized stress variation rate fluctuation index and the seismic wave velocity anomaly index.

[0067] For example, the present invention can use the following formula to calculate the interference index, the calculation expression being: In the formula, The SCRFI is the rate of change of ground stress fluctuation index, and the SWVAI is the seismic wave velocity anomaly index. The weighting coefficients for the stress variation rate fluctuation index and the seismic wave velocity anomaly index (which can be obtained through experimental experience or machine learning optimization to determine the relative contributions of stress and seismic wave velocity anomalies to the overall disturbance) are: .

[0068] The obtained interference index is compared with a pre-set interference index reference threshold based on historical data. If the interference index is greater than or equal to the pre-set interference index reference threshold, it indicates that there may be significant geostress anomalies or rock mass structure damage in the dam area, and the monitoring data is severely interfered with, requiring further analysis and early warning. The interference level is classified as high interference level. If the interference index is less than the pre-set interference index reference threshold, it indicates that the rock mass structure in the dam area is stable, the changes in geostress and seismic wave velocity are within the normal range, and the monitoring data is less interfered with. The interference level is classified as low interference level.

[0069] S4: When the interference index reaches the high interference level, the dynamic adjustment mechanism is immediately activated. Based on the interference situation, the sensitivity of the monitoring equipment and the data acquisition frequency are remotely adjusted, and the warning threshold is automatically adjusted to increase or decrease the warning sensitivity.

[0070] When the interference index reaches a high level of interference, that is, when the interference index is greater than or equal to the preset interference index reference threshold, the dynamic adjustment mechanism is immediately activated to analyze all interference index data within a fixed time period, calculate the mean and standard deviation of the interference index, and determine the interference situation.

[0071] If the mean of the interference index is greater than or equal to the reference threshold of the mean of the interference index, and the standard deviation of the interference index is less than the reference threshold of the standard deviation of the interference index, it indicates that there is stable high interference at this time, and it is necessary to enhance the sensitivity of the equipment, increase the data acquisition frequency, lower the warning threshold, and improve the warning sensitivity.

[0072] If the mean of the interference index is greater than or equal to the reference threshold of the mean of the interference index, and the standard deviation of the interference index is greater than or equal to the reference threshold of the standard deviation of the interference index, it indicates that there is high volatility interference at this time. It is necessary to increase the data collection frequency, keep the warning threshold unchanged, and combine it with manual analysis.

[0073] If the mean of the interference index is less than the reference threshold for the mean of the interference index, and the standard deviation of the interference index is greater than or equal to the reference threshold for the standard deviation of the interference index, it indicates that this is a short-term abnormal fluctuation. The data collection frequency should be appropriately increased, the warning threshold should not be adjusted for the time being, and monitoring should continue.

[0074] If the mean of the interference index is less than the reference threshold for the mean of the interference index, and the standard deviation of the interference index is less than the reference threshold for the standard deviation of the interference index, it indicates that the interference is low and the current monitoring strategy should be maintained without adjustment.

[0075] Adjust the monitoring system remotely according to the interference situation:

[0076] Adjusting sensor sensitivity: Increase or decrease the sensor's measurement accuracy and reduce noise interference.

[0077] Optimize data acquisition frequency: Increase the data acquisition frequency under high interference conditions to improve real-time monitoring capabilities.

[0078] Dynamically adjust the warning threshold: If the interference index is consistently high (stable high interference), lower the warning threshold to enhance warning sensitivity.

[0079] If the interference index fluctuates significantly (high volatility interference), maintain the warning threshold to prevent false alarms.

[0080] In this embodiment, firstly, borehole stress gauges are used to monitor changes in in-situ stress in the dam foundation and surrounding rock strata, analyzing the fluctuations in the rate of change of in-situ stress over time to determine whether there is abnormal stress concentration or release. If an anomaly is detected, array-type seismic monitoring sensors are further used to analyze the microseismic characteristics and abnormal changes in seismic wave velocity in the dam area to determine whether there are local rock mass structural changes or hidden damage. Subsequently, a geological hazard interference assessment model is constructed, integrating the in-situ stress fluctuation index and the seismic wave velocity anomaly index to calculate the interference index, and based on this, the interference level is divided into high interference and low interference levels. When the interference index reaches the high interference level, the system immediately activates a dynamic adjustment mechanism, remotely adjusting the sensitivity of the monitoring equipment and the data acquisition frequency according to the interference situation, and automatically adjusting the early warning threshold to optimize the early warning sensitivity and improve the adaptability and accuracy of the monitoring system.

[0081] Example 2, please refer to Figure 2 As shown in the figure, the water conservancy project safety risk assessment system described in this embodiment includes a ground stress monitoring module, a seismic wave monitoring and analysis module, a geological hazard interference assessment module, and a dynamic adjustment module;

[0082] Ground stress monitoring module: Monitors stress changes in the dam foundation and surrounding rock strata through borehole stress gauges, analyzes the fluctuation of ground stress over time, and determines whether there is abnormal stress concentration or release.

[0083] Seismic wave monitoring and analysis module: If there is abnormal stress concentration or release, the array-type seismic monitoring sensor analyzes the abnormal changes in seismic wave velocity based on the micro-seismic activity and the propagation characteristics of seismic waves in the dam area, and determines whether there are local rock mass structural changes or hidden damage.

[0084] Geological hazard interference assessment module: Constructs a geological hazard interference assessment model, calculates the interference index based on the fluctuation of the rate of change of ground stress over time and the abnormal changes of seismic wave velocity, and classifies the degree of interference into high interference level and low interference level;

[0085] Dynamic adjustment module: When the interference index reaches the high interference level, the dynamic adjustment mechanism is immediately activated. Based on the interference situation, the sensitivity of the monitoring equipment and the data acquisition frequency are remotely adjusted, and the warning threshold is automatically adjusted to increase or decrease the warning sensitivity.

[0086] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A method for safety risk assessment of water conservancy projects, characterized in that: It includes the following steps: S1: Monitor the stress changes of the dam foundation and surrounding rock strata through borehole stress gauges, analyze the fluctuation of the change rate of in-situ stress over time, and judge whether there is abnormal stress concentration or release; The fluctuation of the rate of change of geostress over time is analyzed to generate a geostress rate of change fluctuation index. The method for obtaining the geostress rate of change fluctuation index is as follows: collect the geostress rate of change sequence over time. The expression is: ;in: This represents the change in geostress. The time interval is used to sequence the rate of change of geostress. The signal is decomposed into multiple intrinsic mode functions (IMFs) at different scales. The original signal is then decomposed using the envelope method to extract multiple IMFs. ;in: It is the i-th IMF component. This is the final residual, where N represents the number of intrinsic mode functions obtained from the decomposition, i.e., the number of intrinsic mode functions extracted from the original signal during the decomposition process. A termination condition is set: when the residual... Stop decomposition when the signal becomes a monotonic function or a low-frequency trend signal; Calculate the energy percentage of each IMF component. Calculate the instantaneous amplitude and instantaneous frequency of each IMF component, analyze the fluctuation characteristics of the rate of change of geostress, and perform analysis on each IMF component. Perform a Hilbert transform to obtain its analytic signal, and calculate the instantaneous amplitude. The expression is: ; Given the analytic signal obtained after Hilbert transform; calculate the weighted average instantaneous amplitude. The expression is: ;in: The weighted average instantaneous frequency is calculated using energy weights and M as the total number of instantaneous amplitudes. The expression is: In the formula, For the instantaneous frequency, the calculation expression is: The stress variation rate fluctuation index (SCRFI) is calculated using the following expression: ; S2: If there is abnormal stress concentration or release, use array seismic monitoring sensors to analyze the abnormal changes in seismic wave velocity according to the propagation characteristics of microseisms and seismic waves in the dam area, and judge whether there are local rock mass structure changes or hidden damages; After analyzing the abnormal changes in seismic wave velocity, generate a seismic wave velocity anomaly index. The acquisition method of the seismic wave velocity anomaly index is as follows: Let the seismic wave velocity time series be: Where: V(k) is the seismic wave velocity at time k. An accumulation generation sequence is constructed, and one accumulation generation is performed: ;in: Using the GM(1,1) model, the cumulative generation sequence is set to satisfy the differential equation: Where: a is the development coefficient, representing the trend of seismic wave velocity variation; b is the grey action quantity, representing the external influence of the system. a and b are estimated using the least squares method. Based on the solved a and b, the prediction formula of the GM(1,1) model is obtained: The predicted value of the original sequence is obtained through a single cumulative subtraction. The expression is: The seismic wave velocity anomaly index SWVAI is defined as follows: ;in: This represents the actual observed seismic wave velocity at time k. This represents the seismic wave velocity predicted by the GM(1,1) model. The standard deviation of historical prediction errors. It is a smoothing factor; S3: Construct a geological disaster interference assessment model, calculate the interference index based on the fluctuation of the change rate of in-situ stress over time and the abnormal changes in seismic wave velocity, and divide the interference degree into high interference degree level and low interference degree level; Normalize the in-situ stress change rate fluctuation index and the seismic wave velocity anomaly index so that they are both within [0, 1]. After weighted averaging the normalized in-situ stress change rate fluctuation index and the seismic wave velocity anomaly index, obtain the interference index; S4: When the interference index reaches the high interference degree level, immediately activate the dynamic adjustment mechanism, remotely adjust the sensitivity and data acquisition frequency of the monitoring equipment according to the interference situation, and automatically adjust the warning threshold to increase or decrease the warning sensitivity.

2. The method for safety risk assessment of water conservancy projects according to claim 1, characterized in that: Set the normal range [SCRFImin, SCRFImax] for early warning: Low risk: SCRFI ≤ SCRFImin; Medium risk: SCRFImin < SCRFI ≤ SCRFImax; High risk: SCRFI > SCRFImax. At this time, there is stress concentration or release, and a warning signal is generated.

3. The method for safety risk assessment of water conservancy projects according to claim 1, characterized in that: Judge the rock mass structure state according to the SWVAI value: SWVAI < 1 indicates that the rock mass state is normal and there is no significant abnormality in seismic wave velocity; 1 ≤ SWVAI < 2 indicates that the rock mass state is slightly abnormal and there is local fissure development; 2 ≤ SWVAI < 3 indicates that the rock mass state is moderately abnormal and there are rock mass fractures or increased water infiltration; SWVAI ≥ 3 indicates that the rock mass state is highly abnormal and there are large-scale rock mass fractures, landslides or dam foundation instability. When SWVAI ≥ 3, trigger an automatic warning and increase the monitoring frequency to collect seismic wave velocity data with higher density.

4. The method for safety risk assessment of water conservancy projects according to claim 1, characterized in that: Compare the obtained interference index with the interference index reference threshold preset according to historical data. If the interference index is greater than or equal to the preset interference index reference threshold, it indicates that there is significant in-situ stress anomaly or rock mass structure damage in the dam area, the monitoring data is seriously interfered, and further analysis and warning are required, and the interference degree is divided into the high interference degree level; if the interference index is less than the preset interference index reference threshold, it indicates that the rock mass structure in the dam area is stable, the changes in in-situ stress and seismic wave velocity are within the normal range, the monitoring data is less interfered, and the interference degree is divided into the low interference degree level.

5. The method for safety risk assessment of water conservancy projects according to claim 4, characterized in that: In S4, when the interference index reaches the high interference level, the dynamic adjustment mechanism is immediately activated. Based on the interference situation, the sensitivity of the monitoring equipment and the data acquisition frequency are remotely adjusted, and the warning threshold is automatically adjusted to increase or decrease the warning sensitivity. When the interference index reaches a high level of interference, that is, when the interference index is greater than or equal to the preset interference index reference threshold, the dynamic adjustment mechanism is immediately activated to analyze all interference index data within a fixed time period, calculate the mean and standard deviation of the interference index, and determine the interference situation. If the mean of the interference index is greater than or equal to the reference threshold of the mean of the interference index, and the standard deviation of the interference index is less than the reference threshold of the standard deviation of the interference index, it indicates that the situation is a stable high interference situation. It is necessary to enhance the sensitivity of the equipment, increase the data acquisition frequency, lower the warning threshold, and improve the warning sensitivity. If the mean of the interference index is greater than or equal to the reference threshold of the mean of the interference index, and the standard deviation of the interference index is greater than or equal to the reference threshold of the standard deviation of the interference index, it indicates that the situation is characterized by high volatility interference, and it is necessary to increase the data collection frequency while keeping the warning threshold unchanged. If the mean of the interference index is less than the reference threshold for the mean of the interference index, and the standard deviation of the interference index is greater than or equal to the reference threshold for the standard deviation of the interference index, it indicates that this is a short-term abnormal fluctuation. The data collection frequency should be increased, the warning threshold should not be adjusted for the time being, and monitoring should continue. If the mean of the interference index is less than the reference threshold for the mean of the interference index, and the standard deviation of the interference index is less than the reference threshold for the standard deviation of the interference index, it indicates that the interference is low and the current monitoring strategy should be maintained without adjustment.

6. A water conservancy project safety risk assessment system, used to implement the water conservancy project safety risk assessment method according to any one of claims 1-5, characterized in that: It includes a ground stress monitoring module, a seismic wave monitoring and analysis module, a geological hazard interference assessment module, and a dynamic adjustment module; Ground stress monitoring module: Monitors stress changes in the dam foundation and surrounding rock strata through borehole stress gauges, analyzes the fluctuation of ground stress over time, and determines whether there is abnormal stress concentration or release. Seismic wave monitoring and analysis module: If there is abnormal stress concentration or release, the array-type seismic monitoring sensor analyzes the abnormal changes in seismic wave velocity based on the micro-seismic activity and the propagation characteristics of seismic waves in the dam area, and determines whether there are local rock mass structural changes or hidden damage. Geological hazard interference assessment module: Constructs a geological hazard interference assessment model, calculates the interference index based on the fluctuation of the rate of change of ground stress over time and the abnormal changes of seismic wave velocity, and classifies the degree of interference into high interference level and low interference level; Dynamic adjustment module: When the interference index reaches the high interference level, the dynamic adjustment mechanism is immediately activated. Based on the interference situation, the sensitivity of the monitoring equipment and the data acquisition frequency are remotely adjusted, and the warning threshold is automatically adjusted to increase or decrease the warning sensitivity.

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