A BIM-based water conservancy project monitoring method and system

Abstract

A kind of BIM-based hydraulic engineering monitoring method and system, the method includes: based on abnormal monitoring data and historical monitoring time series data, determine the deviation analysis result corresponding to target component, based on deviation analysis result, determine the influence range component and structure deformation type corresponding to target component, determine the deformation parameter set corresponding to influence range component, based on deformation parameter set and preset safe deformation range, determine the risk level and monitoring frequency corresponding to influence range component, based on monitoring frequency, obtain the high-frequency data stream corresponding to influence range component, determine high-risk component from high-frequency data stream, and determine the position information corresponding to high-risk component, based on position information, high-risk component is marked in the preset component model, and obtain water conservancy monitoring detailed report.Through the above method, the accuracy and efficiency of water conservancy engineering monitoring data processing can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a BIM-based water conservancy project monitoring method and system. Background Art

[0002] In the field of water conservancy project monitoring data, accurate monitoring of water conservancy projects plays an important role in flood prevention and disaster relief, and water resources allocation.

[0003] In the traditional method, the monitoring data corresponding to each monitoring point is obtained through sensors. The monitoring data includes a timestamp and a sensor identifier. The monitoring parameters in the monitoring data are extracted. The monitoring parameters can be water level, flow rate, etc. The monitoring parameters are compared with the preset monitoring parameters. When the monitoring parameters are greater than the preset monitoring parameters, it is determined that an abnormality has occurred. The operation and maintenance personnel need to manually query the drawings to locate the position of the sensor. However, water conservancy projects involve a large number of sensors and a large number of monitoring points, which delays the emergency response time.

[0004] In the process described above, the monitoring data is separated from the water conservancy project entity, and the monitoring data cannot accurately reflect the actual status of the water conservancy project entity. When an abnormal situation is determined to have occurred, it is impossible to quickly locate the specific project site, and there is a situation where the monitoring point where the abnormal situation occurs is misjudged as an instrument failure, resulting in low accuracy of water conservancy monitoring. Summary of the Invention

[0005] The present invention provides a water conservancy project monitoring method and system based on BIM, which can improve the accuracy and efficiency of water conservancy project monitoring data processing.

[0006] In a first aspect, the present invention provides a BIM-based water conservancy project monitoring method, the method comprising:

[0007] Obtain abnormal monitoring data and historical monitoring time series data corresponding to the target component;

[0008] Determine a deviation analysis result corresponding to the target component based on the abnormal monitoring data and the historical monitoring time series data, and determine an impact range component and a structural deformation type corresponding to the target component based on the deviation analysis result;

[0009] In response to the structural deformation type being a preset deformation type, determining a deformation parameter set corresponding to the components in the affected range, determining a risk level and a monitoring frequency corresponding to the components in the affected range based on the deformation parameter set and a preset safe deformation range, and acquiring a high-frequency data stream corresponding to the components in the affected range based on the monitoring frequency;

[0010] Determine the parameter change rate corresponding to the high-frequency data stream. If the parameter change rate is greater than the preset parameter change rate, determine the high-risk components from the high-frequency data stream, and determine the position information corresponding to the high-risk components. Based on the position information, mark the high-risk components in the preset component model to obtain a detailed water conservancy monitoring report.

[0011] In one possible design, obtaining abnormal monitoring data corresponding to the target component includes:

[0012] Acquiring real-time monitoring data of each monitoring point, wherein the real-time monitoring data includes: a mapping relationship between each monitoring point and its corresponding component;

[0013] Extracting a monitoring parameter from the real-time monitoring data, and if the monitoring parameter is greater than a preset monitoring threshold, determining the corresponding component as a first component;

[0014] Based on the first component and a preset radius range, determining a first adjacent component corresponding to the first component, and determining the first component and the first adjacent component as the target components;

[0015] The monitoring data corresponding to the target component is determined as the abnormal monitoring data.

[0016] In one possible design, determining the deviation analysis result corresponding to the target component based on the abnormal monitoring data and the historical monitoring time series data includes:

[0017] Determining a current monitoring parameter corresponding to the target component from the abnormal monitoring data, and determining a historical baseline parameter corresponding to the target component from the historical monitoring time series data;

[0018] Determining a difference between the current monitoring parameter and the historical reference parameter as a current deviation, and determining deviation time series data based on the current monitoring parameter and the historical monitoring time series data;

[0019] Determining a deviation trend direction and a deviation change rate based on the deviation time series data;

[0020] The current deviation amount, the deviation trend direction, and the deviation change rate are determined as the deviation analysis result corresponding to the target component.

[0021] In one possible design, determining the affected range components and the structural deformation type corresponding to the target component based on the deviation analysis result includes:

[0022] Extracting the deviation change rate corresponding to the target component from the deviation analysis result;

[0023] If the deviation change rate is greater than a preset deviation change rate, the corresponding component is determined as a deviation trend component, and based on the deviation trend component and a spatial adjacency matrix, a second adjacent component set corresponding to the deviation trend component is obtained;

[0024] determining a structural connection relationship between each second adjacent component in the second adjacent component set, performing path search processing on the deviation trend component and the structural connection relationship to generate an influence propagation path graph, and determining an influence range component corresponding to the target component based on the deviation trend component and the influence propagation path graph;

[0025] Determine the deviation amount corresponding to each component in the affected range component, perform weighted fusion processing on the deviation amount corresponding to each component, and obtain a comprehensive deviation amount. If the comprehensive deviation amount is greater than the overall deformation threshold, determine that the structural deformation type is overall deformation.

[0026] In one possible design, determining the risk level and monitoring frequency corresponding to the components in the affected range based on the deformation parameter set and the preset safe deformation range includes:

[0027] If the deformation parameters in the deformation parameter set exceed the preset safe deformation range, an abnormal state component identifier is generated;

[0028] Classifying the deformation parameters corresponding to the abnormal state component identifier to obtain the risk level corresponding to the abnormal state component identifier;

[0029] Based on the mapping relationship between the preset risk level and the preset monitoring frequency, the monitoring frequency corresponding to the risk level is determined.

[0030] In one possible design, obtaining the high-frequency data stream corresponding to the impact range component based on the monitoring frequency includes:

[0031] Determine the mechanically associated components corresponding to the components within the impact range;

[0032] Determining an encryption monitoring component and the monitoring frequency based on the risk level corresponding to the impact range component and the mechanically associated component;

[0033] A high-frequency data stream corresponding to the encrypted monitoring component is obtained based on the monitoring frequency.

[0034] In a possible design, the high-risk components are marked in a preset component model based on the location information to obtain a detailed water conservancy monitoring report, including:

[0035] If the position information exceeds the preset engineering model boundary range, converting the position information from the sensor coordinate system to the preset coordinate system to obtain converted position information;

[0036] determining a displacement corresponding to the high-risk component based on the converted position information, and determining the corresponding high-risk component as a target abnormal component if the displacement is greater than a preset displacement;

[0037] In the preset component model, the target abnormal component is marked with its position and risk level to obtain the detailed water conservancy monitoring report.

[0038] In a possible design, the position and risk level of the target abnormal component are marked to obtain the detailed water conservancy monitoring report, including:

[0039] Marking the location and risk level of the target abnormal components to obtain a project safety status distribution map;

[0040] Clustering the components in the engineering safety status distribution diagram to obtain the abnormal component ratio and clustering coefficient;

[0041] Based on the abnormal component proportion and the clustering coefficient, a processing strategy corresponding to the target abnormal component is obtained;

[0042] The risk level corresponding to the target abnormal component, the processing strategy and the component identification are integrated to obtain the detailed water conservancy monitoring report.

[0043] In a second aspect, the present invention provides a BIM-based water conservancy project monitoring system, the system comprising:

[0044] An acquisition module is used to obtain abnormal monitoring data and historical monitoring time series data corresponding to the target component;

[0045] a determination module, configured to determine a deviation analysis result corresponding to the target component based on the abnormal monitoring data and the historical monitoring time series data, and determine an impact range component and a structural deformation type corresponding to the target component based on the deviation analysis result;

[0046] a displacement module, configured to, in response to the structural deformation type being a preset deformation type, determine a deformation parameter set corresponding to the components within the affected range; determine a risk level and a monitoring frequency corresponding to the components within the affected range based on the deformation parameter set and a preset safe deformation range; and obtain a high-frequency data stream corresponding to the components within the affected range based on the monitoring frequency;

[0047] The marking module is used to determine the parameter change rate corresponding to the high-frequency data stream. If the parameter change rate is greater than the preset parameter change rate, the high-risk components are determined from the high-frequency data stream, and the position information corresponding to the high-risk components is determined. Based on the position information, the high-risk components are marked in the preset component model to obtain a detailed water conservancy monitoring report.

[0048] In one possible design, the acquisition module is specifically used to obtain real-time monitoring data of each monitoring point, wherein the real-time monitoring data includes: a mapping relationship between each monitoring point and its corresponding component, extracting monitoring parameters from the real-time monitoring data, and if the monitoring parameters are greater than a preset monitoring threshold, determining the corresponding component as a first component, and based on the first component and a preset radius range, determining the first adjacent component corresponding to the first component, determining the first component and the first adjacent component as the target components, and determining the monitoring data corresponding to the target component as the abnormal monitoring data.

[0049] In one possible design, the determination module is specifically used to determine the current monitoring parameters corresponding to the target component from the abnormal monitoring data, and determine the historical baseline parameters corresponding to the target component from the historical monitoring time series data, determine the difference between the current monitoring parameters and the historical baseline parameters as the current deviation, and determine the deviation time series data based on the current monitoring parameters and the historical monitoring time series data, determine the deviation trend direction and the deviation change rate based on the deviation time series data, and determine the current deviation, the deviation trend direction and the deviation change rate as the deviation analysis result corresponding to the target component.

[0050] In one possible design, the determination module is further used to extract the deviation change rate corresponding to the target component from the deviation analysis result; if the deviation change rate is greater than a preset deviation change rate, the corresponding component is determined as a deviation trend component; based on the deviation trend component and the spatial adjacency matrix, a second adjacent component set corresponding to the deviation trend component is obtained; the structural connection relationship between each second adjacent component in the second adjacent component set is determined; a path search process is performed on the deviation trend component and the structural connection relationship to generate an influence propagation path graph; based on the deviation trend component and the influence propagation path graph, the influence range component corresponding to the target component is determined; the deviation amount corresponding to each component in the influence range component is determined; the deviation amount corresponding to each component is weightedly fused to obtain a comprehensive deviation amount; if the comprehensive deviation amount is greater than the overall deformation threshold, the structural deformation type is determined to be overall deformation.

[0051] In one possible design, the displacement module is specifically used to generate an abnormal state component identification if the deformation parameter in the deformation parameter set exceeds the preset safe deformation range, classify the deformation parameters corresponding to the abnormal state component identification, obtain the risk level corresponding to the abnormal state component identification, and determine the monitoring frequency corresponding to the risk level based on the mapping relationship between the preset risk level and the preset monitoring frequency.

[0052] In one possible design, the displacement module is also used to determine the mechanical associated component corresponding to the impact range component, determine the encrypted monitoring component and the monitoring frequency based on the risk level corresponding to the impact range component and the mechanical associated component, and obtain the high-frequency data stream corresponding to the encrypted monitoring component based on the monitoring frequency.

[0053] In one possible design, the marking module is specifically used to convert the position information from the sensor coordinate system to the preset coordinate system if the position information exceeds the boundary range of the preset engineering model, to obtain the converted position information, and determine the displacement corresponding to the high-risk component based on the converted position information; if the displacement is greater than the preset displacement, the corresponding high-risk component is determined as a target abnormal component; in the preset component model, the target abnormal component is marked with its position and risk level to obtain the detailed water conservancy monitoring report.

[0054] In a possible design, the labeling module is also used to label the location and risk level of the target abnormal component to obtain a project safety status distribution map, cluster the components in the project safety status distribution map to obtain the abnormal component proportion and clustering coefficient, and based on the abnormal component proportion and the clustering coefficient, obtain the processing strategy corresponding to the target abnormal component, integrate the risk level corresponding to the target abnormal component, the processing strategy and the component identification to obtain the detailed water conservancy monitoring report.

[0055] In a third aspect, the present invention provides an electronic device, comprising:

[0056] Memory for storing computer programs;

[0057] The processor is used to implement the above-mentioned BIM-based water conservancy project monitoring method steps when executing the computer program stored in the memory.

[0058] In a fourth aspect, a computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the computer program implements the above-mentioned steps of a BIM-based water conservancy project monitoring method.

[0059] Compared with the prior art, the present invention has the following beneficial effects:

[0060] Through the above method, an accurate spatial mapping relationship between monitoring points and components is established, which solves the problems of traditional monitoring such as the inability to accurately locate the position of abnormal components, the difficulty in distinguishing local deformation from overall displacement, and the lack of dynamic risk assessment. The monitoring frequency is automatically adjusted according to the risk level of the component, and encrypted monitoring is implemented for high-risk components. The target abnormal components are marked and displayed on the project safety status distribution map, and a detailed water conservancy monitoring report is obtained, which improves the accuracy and efficiency of water conservancy project monitoring data processing. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 A flow chart of the steps of a water conservancy project monitoring method based on BIM provided by the present invention;

[0062] Figure 2 A structural diagram of a water conservancy project monitoring system based on BIM provided by the present invention;

[0063] Figure 3 This is a structural diagram of an electronic device provided by the present invention. DETAILED DESCRIPTION

[0064] In order to make the purpose, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail with reference to the accompanying drawings. The specific operating methods in the method embodiments can also be applied to device embodiments or system embodiments. It should be noted that in the description of the present invention, "multiple" is understood as "at least two". "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A is connected to B, which can represent: A is directly connected to B and A is connected to B through C. In addition, in the description of the present invention, words such as "first" and "second" are only used to distinguish the purpose of description, and cannot be understood as indicating or implying relative importance, nor can they be understood as indicating or implying order.

[0065] In previous technologies, sensors were used to obtain monitoring data corresponding to each monitoring point. The monitoring data included timestamps and sensor identifiers, and monitoring parameters were extracted from the monitoring data. When the monitoring parameters were greater than the preset monitoring parameters, an abnormality was determined to have occurred. Operation and maintenance personnel needed to manually query the drawings to locate the position of the sensors. However, water conservancy projects involve a large number of sensors and a large number of monitoring points, which delayed emergency response time. In addition, the monitoring data was separated from the water conservancy project entity, and the monitoring data could not accurately reflect the actual status of the water conservancy project entity. When an abnormality was determined to have occurred, it was impossible to quickly locate the specific project site. In addition, there was a situation where the monitoring point where the abnormality occurred was misjudged as an instrument failure, resulting in low accuracy in the processing of water conservancy project monitoring data, which was unable to support the safety and control needs of water conservancy projects.

[0066] To address the aforementioned issues, embodiments of the present invention provide a BIM-based water conservancy project monitoring method that improves the accuracy and efficiency of water conservancy project monitoring data processing. The method and device described in these embodiments are based on the same technical concept. Since the principles underlying the problems addressed by these methods and devices are similar, the embodiments of the device and method can be referenced in conjunction with each other, and any repetitions will not be repeated.

[0067] The following describes the first embodiment of the present invention in detail with reference to the accompanying drawings.

[0068] Reference Figure 1 The present invention provides a water conservancy project monitoring method based on BIM. The implementation process of the method is as follows:

[0069] Step S1: Obtain abnormal monitoring data and historical monitoring time series data corresponding to the target component.

[0070] In order to solve the problem of separation between monitoring data and water conservancy project entities, the embodiment of the present invention needs to establish a mapping relationship between monitoring points and components. The specific process of establishing the mapping relationship is as follows:

[0071] Obtain the three-dimensional spatial coordinates corresponding to all monitoring points in the water conservancy project. In order to solve the problem of different coordinate systems used by different measuring equipment, the three-dimensional spatial coordinates of the monitoring points need to be converted from the sensor coordinate system to the preset coordinate system. The preset coordinate system can be the world coordinate system of the water conservancy project or a uniformly set coordinate system to obtain the standard spatial coordinates corresponding to each monitoring point.

[0072] In order to establish a spatial correspondence between monitoring points and components, it is necessary to extract the geometric boundary data corresponding to each component from the engineering component database stored in the system based on the standard spatial coordinates of the monitoring points. The geometric boundary data is determined by the Building Information Model (English full name: Building Information Modeling, abbreviated as: BIM). The geometric boundary data contains complex surfaces and polyhedron structures. In the embodiment of the present invention, the geometric boundary data is converted into minimum outer box parameters based on the boundary resolution algorithm. The minimum outer box parameters are the size parameters of the packaging box that can accommodate the object and has the smallest volume, thereby converting the geometric boundary data into three-dimensional space boundary range parameters.

[0073] For example, the three-dimensional space boundary range parameters include: X-axis range is 2847000.0 to 2847250.0, Y-axis range is 456700.0 to 456900.0, and Z-axis range is 1200.0 to 1300.0.

[0074] Determine the standard space coordinates of each monitoring point, compare the standard space coordinates with the three-dimensional space boundary range parameters, and determine whether the monitoring point is within the boundary range of the component. When the standard space coordinates are within the three-dimensional space boundary range parameters, establish a mapping relationship between the monitoring point and the component, thereby determining the component corresponding to each monitoring point, and then establish a mapping relationship between the monitoring point and the component corresponding to the monitoring point.

[0075] Furthermore, the embodiment of the present invention can determine whether the monitoring point is within the boundary range of the component based on the ray method, thereby achieving accurate judgment of the monitoring point. Since the ray method is a technology well known to those skilled in the art, it will not be explained in detail here.

[0076] It should be noted that the above mapping relationship can be stored in the form of a mapping relationship list, in which the monitoring point number, the unique component identifier, and the location information of the monitoring point and the component are recorded.

[0077] For example: the monitoring point number is MP001, the component identification is DAM_MAIN_001, and the location information is the elevation of 1256.8 meters at the 0+125 section on the left bank of the dam main body.

[0078] Through the above mapping relationship list, the specific component position can be immediately located, providing accurate spatial positioning information for the safety assessment of water conservancy projects, realizing the precise association between monitoring points and components, and improving the spatial positioning accuracy of components.

[0079] After the mapping relationship list is established, the system obtains the real-time monitoring data of each monitoring point. The real-time monitoring data includes at least: a timestamp and a component identifier. The monitoring parameters corresponding to each monitoring point are determined from the real-time monitoring data. When the monitoring parameters are greater than the preset monitoring parameters, the monitoring data corresponding to the monitoring point is determined to be an abnormal monitoring record; when the monitoring parameters are not greater than the preset monitoring parameters, it is determined that the monitoring data corresponding to the monitoring point is in a normal state. The component identifier of the first component in the abnormal monitoring record can be used to query in the mapping relationship list to obtain the location information of the first component in the abnormal monitoring record.

[0080] In order to improve query efficiency, the embodiment of the present invention can establish a mapping relationship list based on a B+ tree index method, with the component identifier as the primary key, and the component identifier can correspond to multiple monitoring numbers.

[0081] In order to achieve accurate analysis of the monitoring data of water conservancy projects, with each first component as the center, other components are searched within a preset radius range, the other components within the preset radius range are determined as first adjacent components, the first component and the first adjacent component are determined as target components, the monitoring data corresponding to the target component is determined as abnormal monitoring data, and the historical monitoring time series data of the target component within a preset time period is obtained. The preset time period can be the past 30 days.

[0082] Through the above method, the spatial mapping between monitoring points and components is realized. The specific components can be quickly located through the mapping relationship list, ensuring that the efficiency and accuracy of water conservancy project monitoring data processing can be improved.

[0083] Step S2: Based on the abnormal monitoring data and the historical monitoring time series data, the deviation analysis result corresponding to the target component is determined, and based on the deviation analysis result, the affected range component and the structural deformation type corresponding to the target component are determined.

[0084] After determining the abnormal monitoring data and historical monitoring time series data of the target component, in order to realize the dynamic analysis of the water conservancy project monitoring data, it is necessary to determine the current monitoring parameters corresponding to the target component from the abnormal monitoring data, and determine the historical benchmark parameters corresponding to the target component from the historical monitoring time series data. The difference between the current monitoring parameters and the historical benchmark parameters is determined as the current deviation. The historical benchmark parameters can be the average value of the monitoring parameters within a set time period. The set time period can be 7 days. Based on the current monitoring parameters and the historical monitoring time series data, the deviation time series data is determined, and based on the deviation time series data, the deviation trend direction and the deviation change rate are determined.

[0085] The deviation time series data can be determined based on the deviation amount of at least three consecutive time points. The deviation amount is the difference between the current monitoring parameter and the corresponding historical benchmark parameter at each time point. If the deviation time series data is data that continuously increases over time, the deviation trend direction is determined to be a positive deviation. Otherwise, the deviation trend direction is determined to be a directional deviation.

[0086] Furthermore, the ratio between the deviation amount at each time point and the time interval between adjacent time points is determined, and the ratio is determined as the deviation change rate. Based on the above current deviation amount, deviation trend direction and deviation change rate, the deviation analysis result corresponding to the target component is generated.

[0087] In addition, based on the current deviation amount and deviation trend direction, the abnormal type of the target component can be determined. The specific determination process is as follows:

[0088] Since the target component includes a first component and a first adjacent component, the first monitoring parameter corresponding to the first component is determined from the abnormal detection data, and the second monitoring parameter corresponding to the first adjacent component is determined. The first historical baseline parameter corresponding to the first component and the second historical baseline parameter corresponding to the first adjacent component are determined from the historical monitoring time series data. The first current deviation between the first monitoring parameter and the first historical baseline parameter is calculated, and the second current deviation between the second monitoring parameter and the second historical baseline parameter is calculated.

[0089] Furthermore, based on the first monitoring parameter and the historical monitoring time series data, the first deviation time series data is determined, and based on the first deviation time series data, the first deviation trend direction is determined; and based on the second monitoring parameter and the historical monitoring time series data, the second deviation time series data is determined, and based on the second deviation time series data, the second deviation trend direction is determined. Since the determination process of the first deviation trend direction and the second deviation trend direction is consistent with the above-mentioned determination process of the deviation trend direction, no further explanation will be given here.

[0090] When the first current deviation is greater than the first preset deviation threshold and the second current deviation is less than the second preset deviation threshold, it means that the deviation of the first adjacent component is within the normal range, the first preset deviation threshold and the second preset deviation threshold can be the same, and the abnormality type is determined to be local deformation. When the first current deviation is greater than the first preset deviation threshold, the second current deviation is greater than the second preset deviation threshold, and the trend direction of the first deviation is the same as the trend direction of the second deviation, the abnormality type is determined to be overall displacement.

[0091] In a possible design, in order to ensure the accuracy of the abnormality type, the geometric topological relationship and connection relationship of the components in the water conservancy project entity are obtained. Based on the geometric topological relationship and connection relationship, the spatial adjacency matrix is ​​determined. The spatial adjacency matrix is ​​an n×n square matrix, where n is the total number of components. When the components have an adjacent relationship in space, it is represented as 1 in the spatial adjacency matrix. When the components do not have an adjacent relationship in space, it is represented as 0 in the spatial adjacency matrix. The spatial adjacency matrix characterizes the spatial position relationship between the components. The spatial adjacency matrix is ​​used to determine adjacent components and determine the displacement correlation coefficient between the first component and the first adjacent component. When the displacement correlation coefficient is greater than the preset correlation coefficient, it is determined to be an overall displacement. When the displacement correlation coefficient is less than the preset correlation coefficient, the preset correlation coefficient can be 0.7, which is determined to be a local deformation, thereby avoiding misjudgment caused by fluctuations in the monitoring data of a single component and ensuring the accuracy and reliability of the abnormality type classification.

[0092] The displacement correlation coefficient may be determined based on the Pearson correlation coefficient. Since the Pearson correlation coefficient is a well-known technique to those skilled in the art, it will not be elaborated here.

[0093] The deviation change rate corresponding to the target component is extracted from the deviation analysis results. When the deviation change rate is greater than the preset deviation change rate, the corresponding component is determined as a deviation trend component. Based on the above spatial adjacency matrix, the second adjacent component set corresponding to the deviation trend component can be determined.

[0094] An embodiment of the present invention can determine the current deviation of the second adjacent component in the second adjacent component set. The process of determining the current deviation refers to the process of determining the current deviation of the target component mentioned above, and will not be repeated here. If the current deviation of the second adjacent component is greater than the preset reference parameter, it means that the deviation impact has spread to the second adjacent component, then the structural connection relationship between each second adjacent component in the second adjacent component set is determined, and path search processing is performed on the deviation trend component and the structural connection relationship to generate an impact propagation path diagram. The structural connection relationship includes: a physical connection relationship and a mechanical transfer characteristic relationship. Taking the deviation trend component as the starting point, the deviation propagation range is tracked along the connection path in the impact propagation path diagram to obtain the impact range component, so as to accurately define the problem impact range and avoid missing key affected components.

[0095] Furthermore, the deviation corresponding to each component in the affected range is determined, and the deviation corresponding to each component is weighted and fused to obtain a comprehensive deviation. If the comprehensive deviation is greater than the overall deformation threshold, the structural deformation type of the water conservancy project is determined to be holistic deformation; otherwise, the structural deformation type is non-holistic deformation.

[0096] For example: the weight of the main load-bearing component M01 is 0.4, the weights of the secondary components M02 and M05 are 0.3 and 0.3 respectively, the deviations of M01, M02 and M05 are 3.2, 2.1 and 1.8 respectively, and the weighted average of 3.2, 2.1 and 1.8 is 2.41, the overall deformation threshold is 2.0, 2.41>2.0, and the system determines that the structural deformation type is overall deformation.

[0097] Through the above method, after determining that the abnormality type is overall displacement, the structural deformation type is determined to be overall deformation. Overall deformation is the systematic cause of the overall displacement abnormality, avoiding the misjudgment problem in the water conservancy project monitoring data processing process and ensuring the accuracy of water conservancy project monitoring data processing.

[0098] Step S3: In response to the structural deformation type being a preset deformation type, determine the deformation parameter set corresponding to the components in the affected range; based on the deformation parameter set and the preset safe deformation range, determine the risk level and monitoring frequency corresponding to the components in the affected range; and obtain the high-frequency data stream corresponding to the components in the affected range based on the monitoring frequency.

[0099] In response to the structural deformation type being a preset deformation type, which may be an overall deformation, a deformation parameter set corresponding to the components in the affected range is determined, and the deformation parameters in the deformation parameter set are compared with the preset safe deformation range. When the deformation parameters exceed the preset safe deformation range, an abnormal state component identification is generated, and the deformation parameters corresponding to the abnormal state component identification are classified based on a decision tree algorithm to obtain a risk level corresponding to the abnormal state component identification.

[0100] Specifically, the embodiment of the present invention can set different risk levels corresponding to different deformation parameter ranges. The deformation parameter range can be divided into three parameter range intervals, thereby dividing the risk level into high risk level, medium risk level and low risk level. The determination of different risk levels can be adjusted according to actual conditions.

[0101] An embodiment of the present invention stores a mapping relationship between a preset risk level and a preset monitoring frequency, matches the risk level corresponding to the abnormal state component identifier with the preset risk level, obtains a preset monitoring frequency corresponding to the preset risk level consistent with the risk level, and determines the matched preset monitoring frequency as the monitoring frequency corresponding to the risk level.

[0102] For example: the monitoring frequency for low-risk level is once every 4 hours, the monitoring frequency for medium-risk level is once every 2 hours, and the monitoring frequency for high-risk level is once every 30 minutes.

[0103] In one possible design, the risk level corresponding to the impact range component and the mechanically related component are determined, the encrypted monitoring component and the monitoring frequency are determined, and the high-frequency data stream corresponding to the encrypted monitoring component is obtained based on the monitoring frequency.

[0104] In one possible design, when the risk level corresponding to the abnormal state component identifier is a high risk level, the abnormal state component corresponding to the abnormal state component identifier is determined, and the adjacent components and mechanically associated components corresponding to the abnormal state component are determined, and the abnormal state component, the adjacent components corresponding to the structural deformation type, and the mechanically associated components are determined as encrypted monitoring components.

[0105] In the embodiment of the present invention, the risk level corresponding to the abnormal state component identification and the monitoring frequency can be integrated and processed to obtain a component risk level assessment report.

[0106] For example: when the main beam component M05 is determined to be at a high risk level, the system will simultaneously identify its adjacent support component S02 and the connected secondary beam component B03 as encrypted monitoring components, thereby ensuring full coverage of the risk area.

[0107] Through the above method, the monitoring frequency can be dynamically adjusted based on the risk level of the component, ensuring the optimal allocation of resources, avoiding the waste of monitoring resources, and improving the operating efficiency and early warning accuracy of the overall monitoring system.

[0108] Step S4: Determine the parameter change rate corresponding to the high-frequency data stream. If the parameter change rate is greater than the preset parameter change rate, determine the high-risk components from the high-frequency data stream, and determine the location information corresponding to the high-risk components. Based on the location information, the high-risk components are marked in the preset component model to obtain a detailed water conservancy monitoring report.

[0109] After determining the high-frequency data stream, in order to achieve accurate analysis of the water conservancy project monitoring data, it is necessary to group and store the high-frequency data stream according to the component identification, classify the high-frequency data stream according to the risk level, and calculate the parameter change rate of adjacent time points. The parameter change rate can be the displacement change rate. When the parameter change rate is greater than the preset parameter change rate, the corresponding component is determined as a high-risk component and an early warning is triggered. The high-risk component is matched with the early warning rule library to obtain the corresponding early warning level of the high-risk component, and the early warning mechanism is activated based on the early warning level. When the parameter change rate is not greater than the preset parameter change rate, the corresponding component is recorded and no early warning is triggered.

[0110] The above-mentioned early warning rule library includes: a mapping relationship between abnormal change patterns and early warning levels, the abnormal change patterns are determined based on the parameter change rate, different parameter change rates correspond to different abnormal change patterns, and the above-mentioned early warning mechanism includes: sending alarm information to the monitoring center, notifying on-site engineers and starting emergency monitoring procedures, the early warning mechanism includes sending alarm information to the monitoring center, notifying on-site engineers and starting emergency monitoring procedures.

[0111] For example: the parameter change rate of high-risk component M05 is 0.7 mm / hour, which is considered rapid deformation in the early warning rule library. When the high-risk component M05 successfully matches the "high-risk component rapid deformation" rule in the early warning rule library, the early warning level is determined to be level two, and the level two early warning mechanism is activated, and an alarm message is sent to the monitoring center.

[0112] Determine the location information corresponding to the high-risk component, where the location information includes: the standard space coordinates corresponding to the high-risk component.

[0113] In one possible design, an embodiment of the present invention can call a map rendering interface to mark the location information and component identification in a component location map to obtain a component location marking map, and integrate the risk level, parameter change rate, and timestamp corresponding to the high-risk components in the component location marking map to obtain a component location report.

[0114] In one possible design, in order to prevent measurement errors and false alarms caused by sensor failures, it is necessary to determine whether the position information corresponding to the high-risk component exceeds the boundary range of the preset engineering model. When the position information does not exceed the boundary range of the preset engineering model, the position information of the high-risk component is determined to be in a normal state. When the position information exceeds the boundary range of the preset engineering model, the corresponding high-risk component is determined as a position-abnormal component, and the position information is converted from the sensor coordinate system to the preset coordinate system to obtain the converted position information. The displacement corresponding to the high-risk component is determined based on the converted position information. If the displacement is greater than the preset displacement, the corresponding high-risk component is determined as a target abnormal component.

[0115] In the preset component model, the preset component model is a model corresponding to the water conservancy project entity. The target abnormal component is marked with its position and risk level to obtain a project safety status distribution map. The components in the project safety status distribution map are clustered to obtain the abnormal component proportion and clustering coefficient. The clustering coefficient represents the concentrated distribution trend of the target abnormal component in the local area. When the abnormal component proportion is greater than the preset abnormal component proportion, or the clustering coefficient is greater than the preset clustering coefficient, the emergency response program is triggered and the emergency knowledge base is called. The emergency knowledge base stores the processing strategies corresponding to different abnormal levels of the target abnormal component. The abnormal level is determined based on the risk level and the warning level. The longer the warning duration corresponding to the warning level, the higher the abnormal level can be, thereby improving the response efficiency.

[0116] For example: if the abnormality level is level one, work needs to be stopped immediately for inspection and reinforcement. If the abnormality level is level two, the monitoring frequency needs to be increased and an observation plan needs to be formulated. If the abnormality level is level three, regular maintenance measures need to be adopted.

[0117] The risk level, processing strategy and component identification corresponding to the target abnormal component are integrated and processed to obtain a detailed water conservancy monitoring report.

[0118] Through the above method, an accurate spatial mapping relationship between monitoring points and components is established, which solves the problems of traditional monitoring such as the inability to accurately locate the position of abnormal components, the difficulty in distinguishing local deformation from overall displacement, and the lack of dynamic risk assessment. The monitoring frequency is automatically adjusted according to the risk level of the component, and encrypted monitoring is implemented for high-risk components. The target abnormal components are marked and displayed on the project safety status distribution map, and a detailed water conservancy monitoring report is obtained, which improves the accuracy and efficiency of water conservancy project monitoring data processing.

[0119] Based on the same inventive concept, the embodiment of the present invention further provides a BIM-based water conservancy project monitoring system for realizing the function of a BIM-based water conservancy project monitoring method, referring to Figure 2 , the device comprises:

[0120] Acquisition module 201, used to acquire abnormal monitoring data and historical monitoring time series data corresponding to the target component;

[0121] A determination module 202 is configured to determine a deviation analysis result corresponding to the target component based on the abnormal monitoring data and the historical monitoring time series data, and determine an impact range component and a structural deformation type corresponding to the target component based on the deviation analysis result;

[0122] The displacement module 203 is configured to, in response to the structural deformation type being a preset deformation type, determine a deformation parameter set corresponding to the components within the affected range; based on the deformation parameter set and a preset safe deformation range, determine a risk level and a monitoring frequency corresponding to the components within the affected range; and obtain a high-frequency data stream corresponding to the components within the affected range based on the monitoring frequency;

[0123] The marking module 204 is used to determine the parameter change rate corresponding to the high-frequency data stream. If the parameter change rate is greater than the preset parameter change rate, the high-risk components are determined from the high-frequency data stream, and the position information corresponding to the high-risk components is determined. Based on the position information, the high-risk components are marked in the preset component model to obtain a detailed water conservancy monitoring report.

[0124] In one possible design, the acquisition module 201 is specifically used to obtain real-time monitoring data of each monitoring point, wherein the real-time monitoring data includes: a mapping relationship between each monitoring point and its corresponding component, extracting monitoring parameters from the real-time monitoring data, and if the monitoring parameters are greater than a preset monitoring threshold, determining the corresponding component as a first component, and based on the first component and a preset radius range, determining the first adjacent component corresponding to the first component, determining the first component and the first adjacent component as the target components, and determining the monitoring data corresponding to the target component as the abnormal monitoring data.

[0125] In one possible design, the determination module 202 is specifically used to determine the current monitoring parameters corresponding to the target component from the abnormal monitoring data, and determine the historical baseline parameters corresponding to the target component from the historical monitoring time series data, determine the difference between the current monitoring parameters and the historical baseline parameters as the current deviation, and determine the deviation time series data based on the current monitoring parameters and the historical monitoring time series data, determine the deviation trend direction and the deviation change rate based on the deviation time series data, and determine the current deviation, the deviation trend direction and the deviation change rate as the deviation analysis result corresponding to the target component.

[0126] In one possible design, the determination module 202 is further used to extract the deviation change rate corresponding to the target component from the deviation analysis result; if the deviation change rate is greater than a preset deviation change rate, the corresponding component is determined as a deviation trend component; based on the deviation trend component and the spatial adjacency matrix, a second adjacent component set corresponding to the deviation trend component is obtained; the structural connection relationship between each second adjacent component in the second adjacent component set is determined; a path search process is performed on the deviation trend component and the structural connection relationship to generate an influence propagation path graph; based on the deviation trend component and the influence propagation path graph, an influence range component corresponding to the target component is determined; the deviation amount corresponding to each component in the influence range component is determined; the deviation amount corresponding to each component is weightedly fused to obtain a comprehensive deviation amount; if the comprehensive deviation amount is greater than an overall deformation threshold, the structural deformation type is determined to be overall deformation.

[0127] In one possible design, the displacement module 203 is specifically used to generate an abnormal state component identification if the deformation parameter in the deformation parameter set exceeds the preset safe deformation range, classify the deformation parameters corresponding to the abnormal state component identification, obtain the risk level corresponding to the abnormal state component identification, and determine the monitoring frequency corresponding to the risk level based on the mapping relationship between the preset risk level and the preset monitoring frequency.

[0128] In one possible design, the displacement module 203 is also used to determine the mechanical associated component corresponding to the impact range component, determine the encrypted monitoring component and the monitoring frequency based on the risk level corresponding to the impact range component and the mechanical associated component, and obtain the high-frequency data stream corresponding to the encrypted monitoring component based on the monitoring frequency.

[0129] In one possible design, the marking module 204 is specifically used to convert the position information from the sensor coordinate system to the preset coordinate system if the position information exceeds the boundary range of the preset engineering model, to obtain the converted position information, and determine the displacement corresponding to the high-risk component based on the converted position information; if the displacement is greater than the preset displacement, the corresponding high-risk component is determined as a target abnormal component; in the preset component model, the target abnormal component is marked with its position and risk level to obtain the detailed water conservancy monitoring report.

[0130] In one possible design, the labeling module 204 is also used to label the position and risk level of the target abnormal component to obtain a project safety status distribution map, cluster the components in the project safety status distribution map to obtain the abnormal component proportion value and the clustering coefficient, and based on the abnormal component proportion value and the clustering coefficient, obtain the processing strategy corresponding to the target abnormal component, integrate the risk level corresponding to the target abnormal component, the processing strategy and the component identification to obtain the water conservancy monitoring detailed report.

[0131] Based on the same inventive concept, an electronic device is also provided in an embodiment of the present invention, which can realize the functions of the aforementioned BIM-based water conservancy project monitoring system. Figure 3 , the electronic device includes:

[0132] At least one processor 301, and a memory 303 connected to the at least one processor 301. The embodiment of the present invention does not limit the specific connection medium between the processor 301 and the memory 303. Figure 3 In the example, the processor 301 and the memory 303 are connected via the bus 300. Figure 3 The bus 300 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 3 The diagram is represented by only one thick line, but this does not mean that there is only one bus or one type of bus. Alternatively, the processor 301 may also be referred to as a controller, without limitation to the name.

[0133] In the embodiment of the present invention, the memory 303 stores instructions that can be executed by at least one processor 301. The at least one processor 301 can execute the BIM-based water conservancy project monitoring method discussed above by executing the instructions stored in the memory 303. The processor 301 can implement Figure 2 The functions of each module in the system are shown.

[0134] Among them, the processor 301 is the control center of the system, which can use various interfaces and lines to connect various parts of the entire control device, and monitor the system as a whole by running or executing instructions stored in the memory 303 and calling data stored in the memory 303, various functions of the system and processing data.

[0135] In one possible design, processor 301 may include one or more processing units. Processor 301 may integrate an application processor and a modem processor. The application processor primarily processes the operating system, user interface, and application programs, while the modem processor primarily handles wireless communications. It is understood that the modem processor may not be integrated into processor 301. In some embodiments, processor 301 and memory 303 may be implemented on the same chip. In some embodiments, they may also be implemented on separate chips.

[0136] The processor 301 can be a general-purpose processor, such as a central processing unit (CPU), a digital signal processor, an application-specific integrated circuit, a field programmable gate array or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component, and can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present invention. A general-purpose processor can be a microprocessor or any conventional processor. The steps of the BIM-based water conservancy project monitoring method disclosed in the embodiments of the present invention can be directly embodied as being executed by a hardware processor, or can be executed by a combination of hardware and software modules in the processor.

[0137] The memory 303 is a non-volatile computer-readable storage medium that can be used to store non-volatile software programs, non-volatile computer executable programs and modules. The memory 303 may include at least one type of storage medium, such as a flash memory, a hard disk, a multimedia card, a card-type memory, a random access memory (RAM), a static random access memory (SRAM), a programmable read-only memory (PROM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a magnetic memory, a magnetic disk, an optical disk, etc. The memory 303 is any other medium that can be used to carry or store desired program codes in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory 303 in the embodiment of the present invention can also be a circuit or any other device that can realize a storage function, for storing program instructions and / or data.

[0138] By designing and programming the processor 301, the code corresponding to the BIM-based water conservancy project monitoring method described in the above embodiment can be fixed into the chip, so that the chip can execute the code when running. Figure 1The embodiment shown is a BIM-based water conservancy project monitoring step. How to design and program the processor 301 is a technology well known to those skilled in the art and will not be described in detail here.

[0139] Based on the same inventive concept, an embodiment of the present invention further provides a storage medium storing computer instructions. When the computer instructions are executed on a computer, the computer executes a BIM-based water conservancy project monitoring method discussed above.

[0140] In some possible embodiments, various aspects of the BIM-based water conservancy project monitoring method provided by the present invention can also be implemented in the form of a program product, which includes program code. When the program product is run on the device, the program code is used to enable the control device to execute the steps of the BIM-based water conservancy project monitoring method according to various exemplary embodiments of the present invention described above in this specification.

[0141] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0142] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0143] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0144] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0145] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A BIM-based water conservancy project monitoring method, characterized in that: include: Obtain abnormal monitoring data and historical monitoring time series data corresponding to the target component; Determine a deviation analysis result corresponding to the target component based on the abnormal monitoring data and the historical monitoring time series data, and determine an impact range component and a structural deformation type corresponding to the target component based on the deviation analysis result; In response to the structural deformation type being a preset deformation type, determining a deformation parameter set corresponding to the components in the affected range, determining a risk level and a monitoring frequency corresponding to the components in the affected range based on the deformation parameter set and a preset safe deformation range, and acquiring a high-frequency data stream corresponding to the components in the affected range based on the monitoring frequency; Determine the parameter change rate corresponding to the high-frequency data stream. If the parameter change rate is greater than the preset parameter change rate, determine the high-risk components from the high-frequency data stream, and determine the position information corresponding to the high-risk components. Based on the position information, mark the high-risk components in the preset component model to obtain a detailed water conservancy monitoring report.

2. The method according to claim 1, wherein The obtaining of abnormal monitoring data corresponding to the target component includes: Acquiring real-time monitoring data of each monitoring point, wherein the real-time monitoring data includes: a mapping relationship between each monitoring point and its corresponding component; Extracting a monitoring parameter from the real-time monitoring data, and if the monitoring parameter is greater than a preset monitoring threshold, determining the corresponding component as a first component; Based on the first component and a preset radius range, determining a first adjacent component corresponding to the first component, and determining the first component and the first adjacent component as the target components; The monitoring data corresponding to the target component is determined as the abnormal monitoring data.

3. The method according to claim 1, wherein Determining the deviation analysis result corresponding to the target component based on the abnormal monitoring data and the historical monitoring time series data includes: Determining a current monitoring parameter corresponding to the target component from the abnormal monitoring data, and determining a historical baseline parameter corresponding to the target component from the historical monitoring time series data; Determining a difference between the current monitoring parameter and the historical reference parameter as a current deviation, and determining deviation time series data based on the current monitoring parameter and the historical monitoring time series data; Determining a deviation trend direction and a deviation change rate based on the deviation time series data; The current deviation amount, the deviation trend direction, and the deviation change rate are determined as the deviation analysis result corresponding to the target component.

4. The method according to claim 1, wherein Determining the affected range component and the structural deformation type corresponding to the target component based on the deviation analysis result includes: Extracting the deviation change rate corresponding to the target component from the deviation analysis result; If the deviation change rate is greater than a preset deviation change rate, the corresponding component is determined as a deviation trend component, and based on the deviation trend component and a spatial adjacency matrix, a second adjacent component set corresponding to the deviation trend component is obtained; determining a structural connection relationship between each second adjacent component in the second adjacent component set, performing path search processing on the deviation trend component and the structural connection relationship to generate an influence propagation path graph, and determining an influence range component corresponding to the target component based on the deviation trend component and the influence propagation path graph; Determine the deviation amount corresponding to each component in the affected range component, perform weighted fusion processing on the deviation amount corresponding to each component, and obtain a comprehensive deviation amount. If the comprehensive deviation amount is greater than the overall deformation threshold, determine that the structural deformation type is overall deformation.

5. The method according to claim 1, wherein The step of determining the risk level and monitoring frequency corresponding to the components in the affected range based on the deformation parameter set and the preset safe deformation range includes: If the deformation parameters in the deformation parameter set exceed the preset safe deformation range, an abnormal state component identifier is generated; Classifying the deformation parameters corresponding to the abnormal state component identifier to obtain the risk level corresponding to the abnormal state component identifier; Based on the mapping relationship between the preset risk level and the preset monitoring frequency, the monitoring frequency corresponding to the risk level is determined.

6. The method according to claim 1, wherein The obtaining of the high-frequency data stream corresponding to the impact range component based on the monitoring frequency includes: Determine the mechanically associated components corresponding to the components within the impact range; Determining an encryption monitoring component and the monitoring frequency based on the risk level corresponding to the impact range component and the mechanically associated component; A high-frequency data stream corresponding to the encrypted monitoring component is obtained based on the monitoring frequency.

7. The method according to claim 1, wherein The high-risk components are marked in a preset component model based on the location information to obtain a detailed water conservancy monitoring report, including: If the position information exceeds the preset engineering model boundary range, converting the position information from the sensor coordinate system to the preset coordinate system to obtain converted position information; determining a displacement corresponding to the high-risk component based on the converted position information, and determining the corresponding high-risk component as a target abnormal component if the displacement is greater than a preset displacement; In the preset component model, the target abnormal component is marked with its position and risk level to obtain the detailed water conservancy monitoring report.

8. The method according to claim 7, wherein The position and risk level of the target abnormal component are marked to obtain the detailed water conservancy monitoring report, including: Marking the location and risk level of the target abnormal components to obtain a project safety status distribution map; Clustering the components in the engineering safety status distribution diagram to obtain the abnormal component ratio and clustering coefficient; Based on the abnormal component proportion and the clustering coefficient, a processing strategy corresponding to the target abnormal component is obtained; The risk level corresponding to the target abnormal component, the processing strategy and the component identification are integrated to obtain the detailed water conservancy monitoring report.

9. A BIM-based water conservancy project monitoring system, characterized in that: Used to implement the method according to any one of claims 1 to 8, comprising: An acquisition module is used to obtain abnormal monitoring data and historical monitoring time series data corresponding to the target component; a determination module, configured to determine a deviation analysis result corresponding to the target component based on the abnormal monitoring data and the historical monitoring time series data, and determine an impact range component and a structural deformation type corresponding to the target component based on the deviation analysis result; a displacement module, configured to, in response to the structural deformation type being a preset deformation type, determine a deformation parameter set corresponding to the components within the affected range; determine a risk level and a monitoring frequency corresponding to the components within the affected range based on the deformation parameter set and a preset safe deformation range; and obtain a high-frequency data stream corresponding to the components within the affected range based on the monitoring frequency; The marking module is used to determine the parameter change rate corresponding to the high-frequency data stream. If the parameter change rate is greater than the preset parameter change rate, the high-risk components are determined from the high-frequency data stream, and the position information corresponding to the high-risk components is determined. Based on the position information, the high-risk components are marked in the preset component model to obtain a detailed water conservancy monitoring report.

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