Risk management and control method, system and equipment based on hydraulic engineering project

Abstract

The invention discloses a risk management and control method, system and equipment based on a water conservancy project, and relates to the technical field of risk management and control. A sensor data drift abnormal index is calculated by obtaining multi-source monitoring data of a target water conservancy project after an earthquake, and an engineering structure change abnormal index is calculated based on a preset structure health model and epicenter parameters; and calculating an earthquake propagation influence index by combining the seismic source distance, calculating an earthquake influence coefficient by combining the three factors, and judging whether an original risk early warning evaluation system needs to be updated according to the earthquake influence coefficient. According to the method, after a natural disaster event (such as a slight earthquake) is encountered, whether the risk early warning evaluation system needs to be updated or not can be judged according to the actual disaster degree; it is ensured that early warning is not delayed or invalid, and the possibility of causing larger potential safety hazards is reduced; meanwhile, whether the risk early warning evaluation system is updated or not can be reasonably judged according to the influence of the actual earthquake on the construction of the hydraulic engineering project, and unnecessary waste of computing resources is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of risk management and control, and in particular to a risk management and control method, system and equipment based on water conservancy project. Background Art

[0002] During the construction of water conservancy projects, risk management typically involves establishing a risk early warning and assessment system to acquire real-time data from multiple sources related to project safety (such as water level, seepage pressure, structural stress, and rainfall). This system, combined with historical experience, prediction models, and threshold mechanisms, identifies, assesses, and issues early warnings for potential risks, enabling the implementation of preventative measures in advance. The core of this system lies in real-time dynamic assessments based on a "data-driven + model-based" approach, and is widely used in the safety oversight of projects such as reservoirs, dams, tunnels, and pumping stations.

[0003] However, in actual applications, if a natural disaster event, such as an earthquake, occurs during the construction process, the water conservancy project may be affected by the earthquake, resulting in the original risk warning assessment system being unsuitable for the risk warning assessment of the water conservancy project after the earthquake. If the risk warning assessment system cannot be updated in time, it may cause warning delays or failures, thereby causing greater safety hazards; but changing the overall risk warning assessment system will consume a lot of computing resources. If it is not possible to reasonably judge whether to update the risk warning assessment system based on the actual impact of the earthquake on the construction of the water conservancy project, it may lead to a waste of computing resources. Summary of the Invention

[0004] The purpose of the present invention is to solve the above-mentioned problems and provide a risk management method, system and equipment based on water conservancy project.

[0005] In a first aspect of the present invention, a risk management method for a water conservancy project is first proposed, the method comprising: Obtain multi-source monitoring data of the target water conservancy project after the earthquake, and calculate the sensor's data drift anomaly index based on the multi-source monitoring data to assess whether the sensor has data drift anomalies; Based on the preset structural health model and earthquake epicenter parameters, the potential impact of earthquakes on engineering structures is analyzed and the abnormal index of engineering structure changes is calculated; Obtain the distance between the epicenter and the target water conservancy project, and calculate the earthquake propagation impact index based on the distance; The earthquake impact coefficient is calculated based on the data drift anomaly index, engineering structure change anomaly index and earthquake propagation impact index. Based on the earthquake impact coefficient, it is determined whether the original risk early warning assessment system needs to be updated, and risk management of water conservancy projects is carried out based on the risk early warning assessment system.

[0006] Optionally, the step of calculating the data drift anomaly index of the sensor based on the multi-source monitoring data is: For the data monitored by each sensor, obtain the measured data and the data predicted by the preset prediction model, and calculate the error; Divide the error sequence time window before and after the earthquake, and set the time of earthquake occurrence as , then take The error window before the earthquake is of length , the error window after the earthquake is of length , construct two error windows: the error sequence before the earthquake and the error sequence after the earthquake; The sliding variance of the error sequence in two time windows is calculated, and the sliding window length is , then calculate the sliding variance mean of the error series before the earthquake and the sliding variance mean of the error series after the earthquake ; Define the error fluctuation inflation factor , which is used to measure the degree of change in error fluctuation after an earthquake relative to that before the earthquake. , where is a very small constant to prevent division by zero; Calculate the difference mean absolute value of the error sequence in the post-earthquake window as the trend drift factor , the calculation formula is: ; Calculate the data drift anomaly of each sensor , the calculation formula is: ; The mean of the data drift anomaly values ​​of all sensors is used as the data drift anomaly index.

[0007] Optionally, the step of calculating the engineering structure change abnormality index is: For each settlement monitoring point of the water conservancy project, the average settlement value of each settlement monitoring point before and after the earthquake is obtained, the absolute difference between the average settlement values ​​of each settlement monitoring point before and after the earthquake is calculated, and the absolute difference is divided by the average settlement value of each settlement monitoring point before the earthquake to obtain the settlement offset; Obtain the average values ​​of engineering crack width and length before and after the earthquake in the water conservancy project, subtract the average value of engineering crack width before the earthquake from the average value of engineering crack width after the earthquake, and divide the calculated difference by the average value of engineering crack width before the earthquake to obtain the crack width change rate; The average length of engineering cracks after the earthquake was subtracted from the average length of engineering cracks before the earthquake, and the calculated difference was divided by the average length of engineering cracks before the earthquake to obtain the length crack change rate; the width crack change rate was added to the length crack change rate to obtain the overall crack change rate; For each monitoring point, the attitude angle before and after the earthquake is obtained, and the attitude angle offset ratio before and after the earthquake is calculated. The average of the attitude angle offset ratios of all monitoring points is calculated as the attitude change; The engineering structure change anomaly index is calculated based on the settlement offset, overall crack change rate and posture change. The calculation formula is: , where is the abnormal index of engineering structure change, 、 and They are settlement offset, overall crack change rate and attitude change, respectively.

[0008] Optionally, the steps of calculating the earthquake propagation impact index based on the distance are: Get the distance between the epicenter and the target water conservancy project , calculate the epicenter distance attenuation factor using the exponential decay model , the calculation formula is: , where is the preset regional geological related attenuation index; Calculating the magnitude energy factor , the calculation formula is: , where is the earthquake magnitude; Obtain the angle between the earthquake propagation direction and the axis of the main dam of the project , calculate the propagation direction angle factor , ; Get the duration of the earthquake , calculate the earthquake duration factor , the calculation formula is: ; Epicenter distance attenuation factor , magnitude energy factor , propagation direction angle factor and earthquake duration factor Multiply them together to get the earthquake propagation impact index.

[0009] Optionally, the steps of calculating the earthquake influence coefficient according to the data drift anomaly index, the engineering structure change anomaly index and the earthquake propagation influence index are: The data drift anomaly index, engineering structure change anomaly index and earthquake propagation impact index are normalized, and the normalized data drift anomaly index, engineering structure change anomaly index and earthquake propagation impact index are assigned the same weight. The data drift anomaly index, engineering structure change anomaly index and earthquake propagation impact index are multiplied by the same weight respectively, and then the multiplication results are added together to obtain the earthquake influence coefficient.

[0010] Optionally, the steps of determining whether the original risk early warning assessment system needs to be updated based on the earthquake impact coefficient, and performing risk control on the water conservancy project based on the risk early warning assessment system are as follows: Compare the earthquake impact coefficient with the preset earthquake impact coefficient threshold. If the earthquake impact coefficient is not less than the preset earthquake impact coefficient threshold, it means that the original risk early warning assessment system can no longer be used for risk management of water conservancy projects after the earthquake. The original risk early warning assessment system needs to be updated, and risk management of water conservancy projects should be carried out according to the risk early warning assessment system. If the earthquake impact coefficient is less than the preset earthquake impact coefficient threshold, it means that the original risk warning assessment system can still be used for risk management of water conservancy projects after the earthquake, and risk management of water conservancy projects can be carried out based on the original risk warning assessment system.

[0011] In a second aspect of the present invention, a risk management and control system for water conservancy projects is proposed, the system comprising: Data drift anomaly module: This module obtains multi-source monitoring data of the target water conservancy project after the earthquake, calculates the sensor's data drift anomaly index based on the multi-source monitoring data, and evaluates whether the sensor has data drift anomalies. Engineering structure change anomaly module: Based on the preset structural health model and earthquake epicenter parameters, it analyzes the potential impact of earthquakes on engineering physical structures and calculates the engineering structure change anomaly index; Earthquake propagation impact module: obtains the distance between the epicenter and the target water conservancy project, and calculates the earthquake propagation impact index based on the distance; Risk management and control module: Calculate the earthquake impact coefficient based on the data drift anomaly index, engineering structure change anomaly index and earthquake propagation impact index, and determine whether the original risk early warning assessment system needs to be updated based on the earthquake impact coefficient, and conduct risk management and control of water conservancy projects based on the risk early warning assessment system.

[0012] In a third aspect of the present invention, an electronic device is provided, comprising a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus; Memory for storing computer programs; The processor is configured to implement any of the above-described method steps when executing a program stored in the memory.

[0013] Beneficial effects of the present invention: The present invention proposes a risk management method, system, and device for water conservancy projects. The method calculates the sensor data drift anomaly index by acquiring multi-source monitoring data of a target water conservancy project after an earthquake; calculates the engineering structure change anomaly index based on a preset structural health model and earthquake epicenter parameters; obtains the distance between the earthquake source center and the target water conservancy project, and calculates the earthquake propagation impact index based on the distance; calculates the earthquake impact coefficient based on the data drift anomaly index, the engineering structure change anomaly index, and the earthquake propagation impact index; and determines whether the existing risk warning assessment system needs to be updated based on the earthquake impact coefficient. Risk management of the water conservancy project is then performed based on the risk warning assessment system. In this way, if a natural disaster event, such as a minor earthquake, occurs during the construction process, the need to update the risk warning assessment system can be determined based on the actual degree of damage, ensuring that the warning will not be delayed or ineffective, thereby reducing the possibility of causing greater safety hazards. At the same time, the method can reasonably determine whether to update the risk warning assessment system based on the actual impact of the earthquake on the construction of the water conservancy project, thereby reducing unnecessary waste of computing resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The present invention will be further described below with reference to the accompanying drawings.

[0015] Figure 1 This is a flow chart of the risk management method based on water conservancy project; Figure 2 This is a framework diagram of the risk management and control system based on water conservancy projects; Figure 3 A schematic structural diagram of a device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0016] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0017] The embodiment of the present invention provides a risk management method based on a water conservancy project. Figure 1 , Figure 1 A flow chart of a risk management method for a water conservancy project provided in an embodiment of the present invention. The method comprises the following steps: Obtain multi-source monitoring data of the target water conservancy project after the earthquake, and calculate the sensor's data drift anomaly index based on the multi-source monitoring data to assess whether the sensor has data drift anomalies; Based on the preset structural health model and earthquake epicenter parameters, the potential impact of earthquakes on engineering structures is analyzed and the abnormal index of engineering structure changes is calculated; Obtain the distance between the epicenter and the target water conservancy project, and calculate the earthquake propagation impact index based on the distance; The earthquake impact coefficient is calculated based on the data drift anomaly index, engineering structure change anomaly index and earthquake propagation impact index. Based on the earthquake impact coefficient, it is determined whether the original risk early warning assessment system needs to be updated, and risk management of water conservancy projects is carried out based on the risk early warning assessment system.

[0018] Based on the risk management method for water conservancy projects provided by the embodiment of the present invention, through the above-mentioned method, if a natural disaster event, such as a minor earthquake, occurs during the construction of the project, it can be judged whether the risk warning assessment system needs to be updated based on the actual degree of disaster; ensuring that the warning will not be delayed or invalid, reducing the possibility of causing greater safety hazards; at the same time, it can reasonably judge whether to update the risk warning assessment system based on the actual impact of the earthquake on the construction of the water conservancy project, reducing unnecessary waste of computing resources.

[0019] In one embodiment, multi-source monitoring data of a target water conservancy project after an earthquake is obtained, and a data drift anomaly index of a sensor is calculated based on the multi-source monitoring data to assess whether the sensor has data drift anomaly. Specifically, the steps for calculating the sensor data drift anomaly index based on multi-source monitoring data are as follows: For the data monitored by each sensor, obtain the measured data and the data predicted by the preset prediction model , calculation error ; For the The measured value at the time, No. The model prediction value at time t, For the The error value at the moment; Divide the error sequence time window before and after the earthquake, and set the time of earthquake occurrence as , then take The error window before the earthquake is of length , the error window after the earthquake is of length , construct two error windows: the error sequence before the earthquake: ; Error sequence after the earthquake: ; The sliding variance of the error sequence in two time windows is calculated, and the sliding window length is , then calculate the sliding variance mean of the error series before the earthquake ; Sliding variance mean of the error series after the earthquake Where, represents the variance of the error within the window; Define the error fluctuation inflation factor , which is used to measure the degree of change in error fluctuation after an earthquake relative to that before the earthquake. , where is a very small constant to prevent division by zero; ; Calculate the difference mean absolute value of the error sequence in the post-earthquake window as the trend drift factor , the calculation formula is: ; Calculate the data drift anomaly of each sensor , the calculation formula is: ; The mean of the data drift anomaly values ​​of all sensors is used as the data drift anomaly index.

[0020] It should be noted that multi-source monitoring data refers to a collection of raw data collected from various types of sensors deployed at key locations in water conservancy projects that can reflect the project's operating status and environmental changes. Specifically, these monitoring data may include, but are not limited to, the following categories: ① Water level sensor data, used to reflect water level changes in reservoirs or river channels; ② Piezometer data, used to monitor changes in pore water pressure in dam bodies or underground structures; ③ Stress and strain sensor data, used to capture the stress state and deformation trends of structures such as dam bodies, linings, and cofferdams; ④ Inclinometer and settlement meter data, used to detect abnormal displacement or settlement of the dam body or foundation structure; ⑤ Accelerometer and seismometer data, used to obtain acceleration response characteristics of local areas during or after earthquakes; ⑥ Temperature and humidity sensor data, used to assist in determining changes in material properties, expansion deformation, or abnormal seepage paths; ⑦ GNSS displacement monitoring nodes, used to perform high-precision three-dimensional displacement monitoring of the dam surface and key nodes. The above-mentioned data are collected by wireless or wired communication means to the data processing platform of the engineering center, or uploaded to the remote monitoring system in real time through the cloud platform, forming a complete and continuous time series data stream.

[0021] The so-called "pre-set prediction models" refer to functions or models used to predict the operational status of a project, established through physical modeling, statistical modeling, or machine learning methods based on historical operational data, environmental conditions, and structural conditions. Specifically, these models can be empirical formulas (such as linear regression and ARIMA models) or black-box prediction models (such as LSTM, random forests, and support vector machines). They are used to predict the "normal" or "expected" values ​​of various monitoring indicators at future times based on a given set of environmental inputs (such as rainfall, water levels, and historical stress) and sensor observation sequences over a given period of time. Predictive models must be fully trained and validated before an earthquake using long-term historical data to ensure high predictive accuracy. After an earthquake, the predicted values ​​generated by these models are compared with the actual monitored values ​​to extract error sequences. Methods such as sliding variance analysis and differential feature extraction are then used to assess whether the earthquake has triggered systematic drift and volatility in the sensor data, thereby determining whether the risk warning and assessment system needs to be restructured or adjusted.

[0022] It should be noted that the data drift anomaly index (DAI) is a metric used to comprehensively assess whether various sensors experienced systematic drift, abnormal fluctuations, or sudden trend changes during monitoring by comparing the error changes between sensor measurements and the predicted values ​​from a pre-set prediction model after an earthquake. This index not only reflects the monitoring stability and data reliability of the sensors themselves, but also indirectly reveals the extent of the earthquake's disruption to the entire water conservancy project monitoring system. A higher DAI indicates that the error between the sensor data and the prediction model output exhibits greater volatility (e.g., increased sliding variance), trend changes (e.g., significantly increased error spread), or abnormal patterns (e.g., frequent error changes). This is typically not due to sporadic noise, but rather to systematic changes triggered by a severe external disturbance (e.g., an earthquake). Specifically, a higher DAI indicates that the risk warning and assessment system originally established under steady-state conditions may no longer be applicable to the current project operation after the earthquake. On the one hand, significant physical changes to the structure (such as cracking, displacement, or foundation settlement) may have caused the environmental parameters at the sensor observation points to no longer conform to the model's pre-set assumptions. On the other hand, the sensors themselves may have been subjected to mechanical shock or electrical interference, causing their output signals to become less stable, thereby reducing the data's credibility. Continuing to use pre-earthquake trained or calibrated models for engineering safety early warnings at this point could lead to missed alerts, false alarms, or delayed alerts, potentially causing managers to misjudge the actual risk and delay response. For example, suppose a large reservoir dam had a multi-point stress monitoring network in place before the earthquake. The prediction model was able to reliably predict the dam's stress response under typical water levels and meteorological conditions. However, after the earthquake, despite no significant change in water level, the measured values ​​from multiple stress sensors deviated significantly from the predicted values, manifested by a significant increase in the sliding variance of the error and a continuous upward trend in the error difference. At this point, the calculated data drift anomaly index exceeded the preset warning threshold, indicating that the stress monitoring data had significantly deviated from the model's assumed behavior. This likely indicates damage to the dam's internal structure and altered stress transmission pathways. If the early warning model is not reassessed and updated in a timely manner at this time, it may not be possible to accurately identify subsequent developing dangerous situations, such as the expansion of secondary cracks and the increase in leakage points. In serious cases, the optimal disposal window may even be missed.

[0023] Therefore, a significant increase in the data drift anomaly index not only indicates a single sensor anomaly but also serves as a key signal for the dynamic updating of the overall project risk assessment system. By introducing this index, it is possible to quickly identify distorted or invalid monitoring data after an earthquake, allowing for targeted corrections or reconstruction of existing models, thereby improving the emergency response capabilities and safety management of the entire water conservancy project following natural disasters.

[0024] In one implementation, analyzing the data drift anomaly index to determine whether to update it for risk management in water conservancy projects offers the following benefits: It enables dynamic control of monitoring data quality and project structural conditions. Its greatest benefit is improved accuracy and timeliness in risk response. Specifically, the data drift anomaly index quantifies the degree of deviation between post-earthquake sensor data and model predictions. A significant increase in the index indicates that the current monitoring model may have failed and requires timely adjustment to adapt to the new project conditions. This prevents erroneous decisions based on distorted data and effectively prevents risk underestimation or misjudgment. It also enables on-demand iterative model updates, ensuring the early warning system remains highly sensitive and adaptable to project risks, providing project managers with a more reliable and scientific basis for risk control. For example, if abnormal drift in dam stress data after an earthquake occurs, timely model updates can identify potential dam failure trends early, allowing for rapid reinforcement or flood release measures to avert catastrophic consequences.

[0025] In one embodiment, based on a preset structural health model and earthquake epicenter parameters, the steps of analyzing the potential impact of an earthquake on an engineering physical structure and calculating an engineering structure change anomaly index are as follows: For each settlement monitoring point of the water conservancy project, the average settlement value of each settlement monitoring point before and after the earthquake is obtained, the absolute difference between the average settlement values ​​of each settlement monitoring point before and after the earthquake is calculated, and the absolute difference is divided by the average settlement value of each settlement monitoring point before the earthquake to obtain the settlement offset; Obtain the average values ​​of engineering crack width and length before and after the earthquake in the water conservancy project, subtract the average value of engineering crack width before the earthquake from the average value of engineering crack width after the earthquake, and divide the calculated difference by the average value of engineering crack width before the earthquake to obtain the crack width change rate; The average length of engineering cracks after the earthquake was subtracted from the average length of engineering cracks before the earthquake, and the calculated difference was divided by the average length of engineering cracks before the earthquake to obtain the length crack change rate; the width crack change rate was added to the length crack change rate to obtain the overall crack change rate; For each monitoring point, the attitude angle before and after the earthquake is obtained, and the attitude angle offset ratio before and after the earthquake is calculated. The average of the attitude angle offset ratios of all monitoring points is calculated as the attitude change; The engineering structure change anomaly index is calculated based on the settlement offset, overall crack change rate and posture change. The calculation formula is: , where is the abnormal index of engineering structure change, 、 and They are settlement offset, overall crack change rate and attitude change, respectively.

[0026] It should be noted that the data involved in calculating the aforementioned engineering structure change anomaly index is primarily acquired in real time by high-precision monitoring equipment deployed at key locations within the water conservancy project: settlement data is provided by levels or GNSS settlement monitoring systems; crack width and length data are acquired by crack meters, laser rangefinders, or image recognition systems; and attitude angle data is recorded by inclinometers, triaxial accelerometers, or GNSS attitude sensing devices. These devices established a baseline model of structural health before the earthquake and, through continuous pre- and post-earthquake data collection, provide full-cycle monitoring of structural response, ensuring the timely and accurate assessment of the engineering structure change anomaly index.

[0027] It should be noted that the Project Structural Change Anomaly Index is a key comprehensive indicator used to assess the impact of earthquakes on the structural integrity and stability of hydraulic projects. The core logic behind this indicator is that, after an earthquake, existing structures may experience abnormal settlement, crack expansion, and angular displacement. If these issues are not promptly identified and quantified, the risk assessment system may continue to use pre-earthquake models, ignoring the fact that the structure has undergone significant changes. This can lead to delays or deviations in risk identification, assessment, and response. A larger anomaly index indicates more significant structural changes, lower structural stability and safety margins, and a reassessment of the overall project risk level is necessary. Specifically, first, settlement displacement reflects whether the foundation or structure's center of gravity has shifted abnormally. For example, softening of the foundation downstream of a reservoir dam can lead to increased settlement in a localized area after an earthquake. This settlement can lead to uneven stress distribution across the structure, resulting in shear stress concentrations and further damage. If the settlement change is small, it may be the result of natural structural settlement; however, a significant change indicates that the earthquake has substantially affected the foundation or structural stiffness. Second, the crack change rate indicates whether the tensile and compressive limits of the structural material have been exceeded. For example, cracks on the gate control tower increased from 0.3 mm to 1.2 mm after the earthquake, and their length grew from 20 cm to 80 cm. This indicates that the material structure may have transitioned from elastic deformation to plasticity or even failure. This crack expansion not only increases the risk of leakage but can also be the starting point for structural failure. Third, changes in posture reflect the stability of the structure's overall spatial posture. For example, the top tilt angle of a pump station increased from 0.5 degrees to 3 degrees before and after the earthquake. This angle change can affect the operating accuracy of mechanical equipment, redistribute stress, and even induce secondary structural instability. When the three types of anomalies mentioned above occur simultaneously within the same time period, the anomaly index value will increase significantly, indicating that the structural operating state has substantially deviated. The original risk model it relied on no longer accurately reflects the new risk state after the earthquake. Continuing to rely on the pre-earthquake assessment model can lead to serious consequences such as underestimation of risk levels, delayed early warning responses, and inadequate emergency measures. Even secondary disasters may result from underestimating potential risks.

[0028] For example, in a certain mountain reservoir project, after an earthquake, the dam body tilted downward as a whole, and the top control equipment was also subjected to tension, causing structural deformation. At this time, the anomaly index rose rapidly. If the risk model based on the pre-earthquake assumption that the structure was intact was still used, the overall risk of slip or collapse would be underestimated, resulting in the failure to issue evacuation orders in a timely manner, which could cause disasters to residents behind the dam. Therefore, if the anomaly index is too high, the model update process should be immediately triggered to recalculate the structural stress, stability, and safety margin to ensure that the early warning system can reflect the latest structural status, improving the overall project's safety management capabilities and emergency response efficiency.

[0029] In one implementation, analyzing the engineering structure change anomaly index (ITI) to determine whether to update the data drift anomaly index for risk management in water conservancy projects offers the following advantages: it can serve as a bridge indicator, effectively linking the structural response of the engineering entity with the credibility assessment of sensor data. This avoids the risk distortion caused by using outdated data drift models even after significant structural changes. By analyzing the changing trends of the ITI, it is possible to promptly identify whether structural excursions caused by sudden events such as earthquakes have exceeded the original sensor installation reference conditions, thereby determining whether the sensor data has exhibited systematic drift. When the ITI significantly increases, a recalculation of the data drift anomaly index is triggered. This not only avoids misjudgments or missed risk events, but also ensures that the risk assessment model obtains more accurate data support at the initial stages of structural instability. For example, if a dam's anomaly index increases after an earthquake but the drift index is not updated promptly, this could mask deviations in the settlement monitoring values ​​and delay early warnings. Dynamically updating the drift index based on the anomaly index improves the adaptability and robustness of the overall risk monitoring system.

[0030] In one embodiment, the steps of obtaining the distance between the earthquake source center and the target water conservancy project and calculating the earthquake propagation impact index based on the distance are as follows: Get the distance between the epicenter and the target water conservancy project , calculate the epicenter distance attenuation factor using the exponential decay model , the calculation formula is: , where is the preset regional geological related attenuation index; Calculating the magnitude energy factor , the calculation formula is: , where is the earthquake magnitude; Obtain the angle between the earthquake propagation direction and the axis of the main dam of the project , calculate the propagation direction angle factor , ; Get the duration of the earthquake , calculate the earthquake duration factor , the calculation formula is: ; Epicenter distance attenuation factor , magnitude energy factor , propagation direction angle factor and earthquake duration factor Multiply them together to get the earthquake propagation impact index.

[0031] It should be noted that the data acquisition methods involved in calculating the earthquake propagation impact index mainly include the following aspects: the distance from the epicenter to the target water conservancy project is usually obtained from the earthquake rapid report data released by the earthquake monitoring center or the earthquake bureau, and can be accurately calculated through the GIS geographic information system in combination with the project's geographic coordinates; the earthquake level (magnitude intensity) is monitored in real time by the seismic network and publicly released, which is highly authoritative and reliable; the angle between the earthquake propagation direction and the axis of the project's main dam can be extracted through remote sensing mapping or engineering design drawings to obtain the dam body azimuth, and then calculated in combination with the direction of seismic wave propagation; the earthquake duration is obtained from the vibration time period recorded by seismic instruments and is usually included in post-earthquake reports or monitoring data records. Through these authoritative data sources and technical means, the accuracy and operability of the data used to calculate the earthquake propagation impact index are ensured, providing a scientific basis for the subsequent evaluation of the project risk early warning system.

[0032] It should be noted that the Earthquake Propagation Impact Index (EPI) is a comprehensive indicator that measures the intensity of disturbances caused by a propagating earthquake event to the input stability and structural response prediction accuracy of a specific water conservancy project's risk warning and assessment system. It comprehensively reflects the degree of disturbance that earthquake waves may cause to the project system along their propagation path by integrating the attenuation factor of epicenter distance, the magnitude energy factor, the propagation direction angle factor, and the earthquake duration factor. A higher EPI indicates a stronger earthquake energy, a longer duration, a closer epicenter to the target project, and an incident angle that is more likely to induce resonance or shear deformation in the dam or key structures. This can have a greater impact on the stress distribution of the project structure, the stability of sensor data, and even the accuracy of the existing risk assessment model. For example, if a magnitude 7.0 earthquake is located only 5 kilometers from a reservoir's main dam, lasts for 40 seconds, and propagates nearly perpendicular to the dam's main axis (with an angle close to 90°), all factors will be maximized, resulting in a significantly increased EPI. In this context, the parameter settings and warning thresholds of the risk warning model, originally established based on a lower-intensity, teleseismic context, no longer accurately reflect the current structural risk situation, potentially leading to underestimation of key risks or delayed response. Therefore, a higher index indicates a greater likelihood of misjudgment or delayed response in the current risk warning system. There is an urgent need to reassess post-earthquake engineering response patterns, revise model parameters, and update risk thresholds to ensure that the risk warning assessment system can continue to play an effective role in disaster prevention and mitigation in this new post-earthquake context.

[0033] In one implementation, analyzing the earthquake propagation impact index (EPI) to determine whether to update the data drift anomaly index for risk management of water conservancy projects offers the following benefits: it accurately captures potential disruptions to the stability of structural monitoring data caused by earthquake propagation. A high EPI indicates strong earthquake energy and significant impacts on the project's propagation path, potentially leading to dramatic changes in structural response. This can cause sensor data drift, distortion, or sudden changes, making existing data drift anomaly detection models trained on stationary data ineffective. Failure to promptly update the EPI can lead to misjudgments or omissions of structural safety status. Therefore, the introduction of the EPI helps determine whether recalibration of sensor data background distribution and adjustment of anomaly identification strategies are necessary immediately after an earthquake, ensuring that risk assessment systems for water conservancy projects maintain accuracy and responsiveness in the post-earthquake environment. For example, if a high-intensity earthquake causes a significant shift in the dam's posture and sudden changes in sensor readings, if the index assessment fails to trigger an update mechanism, the anomaly could be misidentified as a normal trend, delaying risk intervention.

[0034] In one embodiment, an earthquake impact coefficient is calculated based on the data drift anomaly index, the engineering structure change anomaly index, and the earthquake propagation impact index. Based on the earthquake impact coefficient, it is determined whether the existing risk early warning and assessment system needs to be updated. Risk management and control of water conservancy projects is then performed based on the risk early warning and assessment system. The steps for calculating the earthquake influence coefficient based on the data drift anomaly index, the engineering structure change anomaly index and the earthquake propagation influence index are as follows: The data drift anomaly index, engineering structure change anomaly index and earthquake propagation impact index are normalized and given the same weight. The data drift anomaly index, engineering structure change anomaly index and earthquake propagation impact index are multiplied by the same weight respectively, and then the multiplication results are added together to obtain the earthquake influence coefficient. The specific calculation formula is: , where is the earthquake influence coefficient, They are respectively the normalized data drift anomaly index, engineering structure change anomaly index and earthquake propagation impact index. In general, the sum of the weight values ​​of the normalized data drift anomaly index, engineering structure change anomaly index and earthquake propagation impact index is 1.

[0035] In one embodiment, the steps of determining whether the original risk early warning assessment system needs to be updated based on the earthquake impact coefficient and performing risk control on the water conservancy project based on the risk early warning assessment system are as follows: Compare the earthquake impact coefficient with the preset earthquake impact coefficient threshold. If the earthquake impact coefficient is not less than the preset earthquake impact coefficient threshold, it means that the original risk early warning assessment system can no longer be used for risk management of water conservancy projects after the earthquake. The original risk early warning assessment system needs to be updated, and risk management of water conservancy projects should be carried out according to the risk early warning assessment system. If the earthquake impact coefficient is less than the preset earthquake impact coefficient threshold, it means that the original risk warning assessment system can still be used for risk management of water conservancy projects after the earthquake, and risk management of water conservancy projects can be carried out based on the original risk warning assessment system.

[0036] It's important to note that determining whether to update the existing risk early warning and assessment system based on the earthquake impact coefficient is a key step in ensuring the safe management of water conservancy projects. Specifically, when the calculated earthquake impact coefficient is compared with a preset threshold, if the coefficient is at or above the threshold, it means that the impact of the earthquake on the project has reached or exceeded the risk range effectively covered by the system's design. The existing risk early warning and assessment system may not accurately reflect the actual status and potential risks of the water conservancy project after the earthquake. For example, a dam may experience a strong earthquake, resulting in a significant increase in structural settlement and a significant increase in the number and width of cracks. Furthermore, the direction and duration of seismic wave propagation also significantly affect the system. These factors may collectively push the earthquake impact coefficient above the threshold. In this case, the model parameters and risk assessment logic of the existing early warning system need to be readjusted or fully upgraded to accurately capture the new risk characteristics triggered by the earthquake, ensure the timeliness and accuracy of early warnings, and provide a scientific basis for project maintenance decisions to prevent the escalation of safety hazards. Conversely, if the earthquake impact coefficient is less than the threshold, it indicates that the earthquake event has limited impact on the project's risk status, and the existing risk warning and assessment system remains effective, allowing risk monitoring and control to continue using its existing data models and algorithms. For example, a weak or distant earthquake may have a minor impact, with settlement and crack changes within a controllable range. The warning system can function normally without adjustment, ensuring the continuity and stability of project operations. This dynamic judgment mechanism based on the earthquake impact coefficient enables scientific maintenance and dynamic updates of the risk warning system, effectively improving the preparedness and emergency response capabilities of water conservancy projects facing natural disasters such as earthquakes. At the same time, it can also rationally determine whether to update the risk warning and assessment system based on the actual impact of earthquakes on water conservancy project construction, reducing unnecessary waste of computing resources.

[0037] Based on the same inventive concept, the present invention also provides a risk management system based on water conservancy projects. Figure 2 , Figure 2 A framework diagram of a risk management system for water conservancy projects provided by an embodiment of the present invention, the system includes: Data drift anomaly module: This module obtains multi-source monitoring data of the target water conservancy project after the earthquake, calculates the sensor's data drift anomaly index based on the multi-source monitoring data, and evaluates whether the sensor has data drift anomalies. Engineering structure change anomaly module: Based on the preset structural health model and earthquake epicenter parameters, it analyzes the potential impact of earthquakes on engineering physical structures and calculates the engineering structure change anomaly index; Earthquake propagation impact module: obtains the distance between the epicenter and the target water conservancy project, and calculates the earthquake propagation impact index based on the distance; Risk management and control module: Calculate the earthquake impact coefficient based on the data drift anomaly index, engineering structure change anomaly index and earthquake propagation impact index, and determine whether the original risk early warning assessment system needs to be updated based on the earthquake impact coefficient, and conduct risk management and control of water conservancy projects based on the risk early warning assessment system.

[0038] Based on the risk management and control system for water conservancy projects provided by the embodiment of the present invention, through the above-mentioned method, if a natural disaster event, such as a minor earthquake, occurs during the construction of the project, it can be determined whether the risk warning assessment system needs to be updated based on the actual degree of disaster; ensuring that the warning will not be delayed or fail, reducing the possibility of causing greater safety hazards; at the same time, it can reasonably determine whether to update the risk warning assessment system based on the actual impact of the earthquake on the construction of the water conservancy project, reducing unnecessary waste of computing resources.

[0039] The embodiment of the present invention also provides a device, such as Figure 3 As shown, it includes a processor 301, a communication interface 302, a memory 303 and a communication bus 304, wherein the processor 301, the communication interface 302, and the memory 303 communicate with each other through the communication bus 304. Memory 303, for storing computer programs; The processor 301 is configured to execute the program stored in the memory 303, and implement the following steps: Obtain multi-source monitoring data of the target water conservancy project after the earthquake, and calculate the sensor's data drift anomaly index based on the multi-source monitoring data to assess whether the sensor has data drift anomalies; Based on the preset structural health model and earthquake epicenter parameters, the potential impact of earthquakes on engineering structures is analyzed and the abnormal index of engineering structure changes is calculated; Obtain the distance between the epicenter and the target water conservancy project, and calculate the earthquake propagation impact index based on the distance; The earthquake impact coefficient is calculated based on the data drift anomaly index, engineering structure change anomaly index and earthquake propagation impact index. Based on the earthquake impact coefficient, it is determined whether the original risk early warning assessment system needs to be updated, and risk management of water conservancy projects is carried out based on the risk early warning assessment system.

[0040] The communication bus mentioned in the above devices can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. This communication bus can be divided into address buses, data buses, control buses, etc. For ease of illustration, the figure shows only one thick line, but this does not mean that there is only one bus or only one type of bus.

[0041] The communication interface is used for communication between the above devices and other devices.

[0042] The memory may include random access memory (RAM) or non-volatile memory (NVM), such as at least one disk storage. Alternatively, the memory may be at least one storage device located away from the processor.

[0043] The above-mentioned processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, and discrete hardware components.

[0044] The above is a detailed description of an embodiment of the present invention. However, the content described is only a preferred embodiment of the present invention and should not be considered to limit the scope of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. The risk management and control method based on water conservancy project is characterized by: The following steps are involved: Obtain multi-source monitoring data of the target water conservancy project after the earthquake, and calculate the sensor's data drift anomaly index based on the multi-source monitoring data to assess whether the sensor has data drift anomalies; Based on the preset structural health model and earthquake epicenter parameters, the potential impact of earthquakes on engineering structures is analyzed and the abnormal index of engineering structure changes is calculated; Obtain the distance between the epicenter and the target water conservancy project, and calculate the earthquake propagation impact index based on the distance; The earthquake impact coefficient is calculated based on the data drift anomaly index, engineering structure change anomaly index and earthquake propagation impact index. Based on the earthquake impact coefficient, it is determined whether the original risk early warning assessment system needs to be updated, and risk management of water conservancy projects is carried out based on the risk early warning assessment system.

2. The risk management method based on water conservancy project according to claim 1 is characterized in that: The steps for calculating the sensor's data drift anomaly index based on multi-source monitoring data are as follows: For the data monitored by each sensor, obtain the measured data and the data predicted by the preset prediction model, and calculate the error; Divide the error sequence time window before and after the earthquake, and set the time of earthquake occurrence as , then take The error window before the earthquake is of length , the error window after the earthquake is of length , construct two error windows: the error sequence before the earthquake and the error sequence after the earthquake; The sliding variance of the error sequence in two time windows is calculated, and the sliding window length is , then calculate the sliding variance mean of the error series before the earthquake and the sliding variance mean of the error series after the earthquake ; Define the error fluctuation inflation factor , which is used to measure the degree of change in error fluctuation after an earthquake relative to that before the earthquake. , where is a very small constant to prevent division by zero; Calculate the difference mean absolute value of the error sequence in the post-earthquake window as the trend drift factor , the calculation formula is: ; Calculate the data drift anomaly value of each sensor , the calculation formula is: ; The mean of the data drift anomaly values ​​of all sensors is used as the data drift anomaly index.

3. The risk management and control method based on water conservancy project according to claim 1 is characterized in that: The steps for calculating the engineering structure change anomaly index are: For each settlement monitoring point of the water conservancy project, the average settlement value of each settlement monitoring point before and after the earthquake is obtained, the absolute difference between the average settlement values ​​of each settlement monitoring point before and after the earthquake is calculated, and the absolute difference is divided by the average settlement value of each settlement monitoring point before the earthquake to obtain the settlement offset; Obtain the average values ​​of engineering crack width and length before and after the earthquake in the water conservancy project, subtract the average value of engineering crack width before the earthquake from the average value of engineering crack width after the earthquake, and divide the calculated difference by the average value of engineering crack width before the earthquake to obtain the crack width change rate; The average length of engineering cracks after the earthquake was subtracted from the average length of engineering cracks before the earthquake, and the calculated difference was divided by the average length of engineering cracks before the earthquake to obtain the length crack change rate; the width crack change rate was added to the length crack change rate to obtain the overall crack change rate; For each monitoring point, the attitude angle before and after the earthquake is obtained, and the attitude angle offset ratio before and after the earthquake is calculated. The average of the attitude angle offset ratios of all monitoring points is calculated as the attitude change; The engineering structure change anomaly index is calculated based on the settlement offset, overall crack change rate and posture change. The calculation formula is: , where is the abnormal index of engineering structure change, 、 and They are settlement offset, overall crack change rate and attitude change, respectively.

4. The risk management and control method based on water conservancy project according to claim 1 is characterized in that: The steps for calculating the earthquake propagation impact index based on distance are: Get the distance between the epicenter and the target water conservancy project , calculate the epicenter distance attenuation factor using the exponential decay model , the calculation formula is: , where is the preset regional geological related attenuation index; Calculating the magnitude energy factor , the calculation formula is: , where is the earthquake magnitude; Obtain the angle between the earthquake propagation direction and the axis of the main dam of the project , calculate the propagation direction angle factor , ; Get the duration of the earthquake , calculate the earthquake duration factor , the calculation formula is: ; Epicenter distance attenuation factor , magnitude energy factor , propagation direction angle factor and earthquake duration factor Multiply them to get the earthquake propagation impact index.

5. The risk management and control method based on water conservancy project according to claim 1 is characterized in that: The steps for calculating the earthquake influence coefficient based on the data drift anomaly index, engineering structure change anomaly index and earthquake propagation influence index are as follows: The data drift anomaly index, engineering structure change anomaly index and earthquake propagation impact index are normalized, and the normalized data drift anomaly index, engineering structure change anomaly index and earthquake propagation impact index are assigned the same weight. The data drift anomaly index, engineering structure change anomaly index and earthquake propagation impact index are multiplied by the same weight respectively, and then the multiplication results are added together to obtain the earthquake influence coefficient.

6. The risk management method based on water conservancy project according to claim 1 is characterized in that: The steps to determine whether the original risk early warning assessment system needs to be updated based on the earthquake impact coefficient and to conduct risk control of water conservancy projects based on the risk early warning assessment system are as follows: Compare the earthquake impact coefficient with the preset earthquake impact coefficient threshold. If the earthquake impact coefficient is not less than the preset earthquake impact coefficient threshold, it means that the original risk early warning assessment system can no longer be used for risk management of water conservancy projects after the earthquake. The original risk early warning assessment system needs to be updated, and risk management of water conservancy projects should be carried out according to the risk early warning assessment system. If the earthquake impact coefficient is less than the preset earthquake impact coefficient threshold, it means that the original risk warning assessment system can still be used for risk management of water conservancy projects after the earthquake, and risk management of water conservancy projects can be carried out based on the original risk warning assessment system.

7. The risk management and control system based on water conservancy projects is characterized by: A method for risk control based on a water conservancy project according to any one of claims 1 to 6, characterized in that the system comprises: Data drift anomaly module: This module obtains multi-source monitoring data of the target water conservancy project after the earthquake, calculates the sensor's data drift anomaly index based on the multi-source monitoring data, and evaluates whether the sensor has data drift anomalies. Engineering structure change anomaly module: Based on the preset structural health model and earthquake epicenter parameters, it analyzes the potential impact of earthquakes on engineering physical structures and calculates the engineering structure change anomaly index; Earthquake propagation impact module: obtains the distance between the epicenter and the target water conservancy project, and calculates the earthquake propagation impact index based on the distance; Risk management and control module: Calculate the earthquake impact coefficient based on the data drift anomaly index, engineering structure change anomaly index and earthquake propagation impact index, and determine whether the original risk early warning assessment system needs to be updated based on the earthquake impact coefficient, and conduct risk management and control of water conservancy projects based on the risk early warning assessment system.

8. Risk management and control equipment based on water conservancy projects, characterized by: It includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus; Memory for storing computer programs; The processor is configured to implement the steps of the risk control method based on a water conservancy project as described in any one of claims 1 to 6 when executing the program stored in the memory.

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