Four-pre function implementation method for water conservancy and hydropower engineering safety monitoring

Abstract

The application discloses a four-prediction function implementation method for water conservancy and hydropower engineering safety monitoring, and comprises the following steps: S1, data sensing and processing, collecting data through a monitoring device, obtaining data through a shared database with an external system, and acquiring engineering basic data; S2, data prediction, data obtained through data sensing is compiled to obtain effective engineering data, a future change trend of a monitoring part is predicted to obtain prediction data, the obtained effective data and prediction data are analyzed to obtain an analysis report; S3, judging whether engineering early warning is performed; S4, after engineering early warning is released, a visual model in the system simulates and imitates a possible abnormal state of a future engineering part, risk evaluation is performed on the simulation and imitation result; and S5, risk treatment is performed, and an engineering safety plan is executed; and the application realizes precision, advancement, digitization and scientization of engineering safety monitoring.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of digital twin water conservancy and hydropower engineering safety monitoring, in particular to a four-pre function implementation method for water conservancy and hydropower engineering safety monitoring. BACKGROUND

[0002] At present, problems such as the full integration of information technology and traditional water conservancy engineering theory still need to be solved; digital twin is to make full use of physical model, sensor update, operation history and other data, integrate multi-disciplinary, multi-physical quantity, multi-scale and multi-probability simulation process, and complete mapping in virtual space, so as to reflect the whole life cycle process of the corresponding entity equipment; as an important means of intelligent water conservancy development, digital twin technology can provide a more feasible solution to solve the above problems.

[0003] In the process of integrating digital twin with water conservancy and hydropower business, the monitoring system takes natural geography, trunk and branch stream system, water conservancy engineering and economic and social information as the main content, and realizes full-factor digital mapping of physical objects of water conservancy engineering, dynamic and real-time information interaction and deep integration between physical objects and digital objects, and keeps the synchronization and twinning of the two.

[0004] Water conservancy and hydropower engineering safety management is an important guarantee for realizing high-quality development of water conservancy at a new stage, promoting water conservancy to a higher level, a more solid foundation, more favorable protection and more optimized function, and an important link in the development process of intelligent water conservancy; however, at present, there are few relevant researches on digital twin water conservancy and hydropower engineering safety monitoring, and the specific application of digital twin water conservancy and hydropower engineering safety monitoring technology is not landed, and there are few specific solutions in the prior art. SUMMARY

[0005] The purpose of the present application is to meet the needs of digital twin water conservancy and hydropower engineering safety monitoring, and to provide a method for realizing four functions of data prediction, engineering early warning, engineering pre-rehearsal and engineering pre-plan for water conservancy and hydropower engineering safety monitoring, which meets the practical application needs of engineering.

[0006] To achieve the above purpose, the technical scheme of the present application is as follows:

[0007] A four-pre function implementation method for water conservancy and hydropower engineering safety monitoring, characterized in that it comprises the following steps:

[0008] S1: data sensing and processing, collecting data through monitoring equipment, obtaining data through a shared database with an external system and obtaining engineering basic data, and storing the obtained data in a system server;

[0009] S2: data prediction, data obtained by data perception is compiled to obtain effective engineering data; on the basis of the obtained effective data, the future trend of the monitoring part is predicted by using the engineering safety analysis model and the online structure calculation model in the system model library combined with the current engineering operation condition, that is, combined with the effective data, the prediction data is obtained, and the analysis report is obtained by analyzing the obtained effective data and prediction data;

[0010] S3: judging whether to perform engineering early warning, comparing the data in the analysis report in step S2 with the early warning index and threshold system, performing engineering safety analysis and evaluation on the current monitoring part to judge whether to issue engineering early warning;

[0011] S4: engineering preplay, after the engineering early warning is issued, the visual model in the system simulates the abnormal state that may occur in the future of the early warning engineering part, and evaluates the risk of the simulation result;

[0012] S5: engineering safety plan processing, after obtaining the risk evaluation result in step S4, performing risk processing, executing the engineering safety plan, and the management decision department evaluates whether to start the emergency plan disposal, if not, performing on-site inspection and disposal on the current early warning engineering part; if the plan disposal measures are started, the specific situation of the engineering risk index is matched with the disposal measures of the engineering plan library, the matched plan is reported to the superior management department, and after the approval of the superior department, the plan is executed.

[0013] Further, the data perception includes monitoring device data collection, data sharing with external systems, and storing engineering data in the system server to obtain data;

[0014] The monitoring device collects data, and the monitoring device can be a sensor or other data collection device. The sensor is remotely connected to the monitoring system of the application, and the collected information is sent to the system server through wired and wireless networks for storage;

[0015] Sharing data with external systems means that the monitoring system of the application can access external water and rainfall systems data, geographic information data, visual models, historical data, knowledge and experience, and rule specifications through other business systems or the Internet;

[0016] Obtaining engineering data means storing engineering design reports, safety monitoring design reports, engineering basic information, historical events and data of similar engineering in the safety monitoring system;

[0017] The data collected by the monitoring device, the external shared data and the engineering basic data jointly constitute the engineering safety monitoring digital board, and the digital board is the data center of the monitoring system of the application.

[0018] Further, the data collation in the S2 step refers to using 3σ criterion or other methods to identify and judge outliers of the obtained data, remove outliers and rough errors in the data, and obtain effective engineering data.

[0019] Further, after obtaining the effective engineering data and prediction data in the S2 step, the obtained effective data and prediction data are analyzed by an engineering analysis model in the system to generate an analysis report, wherein the analysis report includes data of a current running state of the engineering and data of a future development state of the engineering predicted.

[0020] Further, in the S3 step of judging whether to perform engineering early warning, if the data in the analysis report is within a safety range specified by a warning index and a threshold system, it is considered that the engineering running data is normal, the early warning mechanism is not triggered, and the overall process is ended; if the data in the analysis report is within an abnormal range specified by the warning index and the threshold system, the early warning mechanism is triggered, and the system issues an engineering early warning.

[0021] Further, in the S3 step of judging whether to perform engineering early warning, if the data in the analysis report is within an abnormal range specified by a warning index and a threshold system, the data in the analysis report is compared with data in a knowledge base, wherein the data in the knowledge base includes expert experience and engineering specifications, and if the data in the analysis report does not match the data in the knowledge base, an early warning is issued.

[0022] Further, in the S4 step, simulation is performed by using an engineering safety state simulation model to simulate and analyze development trends of engineering safety monitoring indexes under a future prediction scenario by combining the obtained effective engineering data with data of typical historical events, engineering design data and engineering planning data, forwardly pre-visualize risks and influences, and reversely deduce boundary conditions of each engineering index of the engineering safety running.

[0023] Further, the reversely deduced boundary conditions of each engineering index of the engineering safety running are the warning index and the threshold system in the system which are adjusted in time or multiple times according to specific values of each risk index when the engineering has risks during the pre-visualization process.

[0024] Further, the preplan disposal in the S5 step refers to formulating disposal measures corresponding to specific risk conditions of each index influencing the engineering safety running according to the specific risk conditions, and storing the disposal measures in an engineering preplan library of the system, so that when a specific risk condition of an index occurs, the corresponding disposal measures in the engineering preplan library are automatically matched by the preplan disposal.

[0025] The present application has the following beneficial effects:

[0026] 1. The present application can keep the precision, synchronization and timeliness of the interaction between digital twin engineering and physical world of water conservancy and hydropower engineering, realize the application of intelligent water conservancy business of "prediction precision, early warning, digital pre-visualization, scientific pre-visualization".

[0027] 2. The present application describes the implementation method of digital twin water conservancy and hydropower engineering safety monitoring, which provides a clear implementation direction for subsequent digital twin water conservancy and hydropower engineering safety monitoring. BRIEF DESCRIPTION OF DRAWINGS

[0028] Figure 1 The figure is a digital twin water conservancy and hydropower engineering safety monitoring scheme of the present application.

[0029] Figure 2 The figure is an engineering safety monitoring flowchart of the present application. DETAILED DESCRIPTION

[0030] In order to make the purpose, technical scheme and advantages of the application clearer, the present application will be further described below with reference to the drawings.

[0031] The implementation method of the four prediction functions in the present application refers to the method of data prediction, engineering early warning, engineering pre-visualization and engineering pre-visualization.

[0032] The water conservancy and hydropower engineering safety monitoring of the present application includes five modules of monitoring data perception, engineering safety prediction, engineering safety early warning, engineering safety pre-visualization and engineering safety pre-visualization; the data perception and processing module is used to obtain water conservancy and hydropower engineering data, and the obtained data is stored in the system server according to the information type; the engineering safety prediction module is used to compile the water conservancy and hydropower engineering data obtained by data perception, obtain effective engineering data, and predict the future engineering safety monitoring data trend by using engineering safety analysis model and online structure calculation model; the engineering safety early warning module is used to analyze the effective engineering data and data trend, and judge whether to issue a warning; when a warning is issued, the engineering safety pre-visualization module will obtain the change trend of the effective engineering data, and evaluate the risk according to the change trend of the engineering data; the engineering safety pre-visualization module matches the corresponding pre-visualization measures in the system pre-visualization library according to the risk evaluation result.

[0033] Figure 1 The method for realizing the four prediction functions of water conservancy and hydropower engineering safety monitoring by digital twin technology, the digital model of water conservancy and hydropower engineering safety monitoring business scene is constructed by using digital twin technology; the engineering safety monitoring business scene digital model is established according to the engineering three-dimensional model and the water conservancy and hydropower engineering operation data, and the engineering three-dimensional model includes geographic information system GIS and building information model BIM.

[0034] Geographic Information System (GIS) is a computer-based tool that maps and analyzes things and events that exist on the earth. GIS technology integrates the unique visualizations of maps and geographic analysis functions with general database operations. This ability distinguishes GIS from other information systems and makes it useful in explaining events, predicting outcomes, planning strategies, etc. in a wide range of public and business units.

[0035] Building Information Modeling (BIM) is to integrate all relevant information of a construction project through three-dimensional digital technology, and is a detailed expression of the whole cycle information of the project. It is a direct application of digital visualization technology in construction engineering, and can make early warning and analysis on various problems before the project, so that all participants of the project can understand and respond, and provide a solid foundation for collaborative work.

[0036] The operation data of the water conservancy and hydropower engineering is obtained from sensor monitoring data and existing knowledge base data sharing; the operation data of the engineering obtained by the water conservancy and hydropower engineering safety monitoring system is analyzed, the operation state of the engineering is realized in real time, the abnormal condition is alarmed, the future development condition of the engineering is preformed, and the corresponding disposal measures are matched for the abnormal condition in the monitoring system.

[0037] The four-pre function implementation method for water conservancy and hydropower engineering safety monitoring specifically includes five steps of data sensing and processing, data prediction, judging whether to perform engineering early warning, engineering pre-performance, and engineering safety plan processing.

[0038] S1: data sensing and processing

[0039] According to the business division ① in the embodiment, the business process of the water conservancy and hydropower engineering safety monitoring system starts from front-end data sensing, the data sensing includes monitoring equipment data collection, data sharing with external systems, and obtaining engineering basic data. Figure 2 The data sensing and processing module includes two sub-modules of data collection and equipment management.

[0040] Data processing refers to storing the obtained data according to information categories, and the data collection sub-module is used to obtain data and store the obtained data in categories.

[0041] The data collection sub-module collects data, including monitoring equipment data collection, data sharing with external systems, and storing engineering data in the system server.

[0042] The data collection sub-module collects data, including monitoring equipment data collection, data sharing with external systems, and storing engineering data in the system server.

[0043] The monitoring device collects data, which can be a sensor or other data collection device. The sensor is remotely connected to the monitoring system, and the collected information is sent to the monitoring system through wired and wireless networks. The monitoring device collects data including deformation, stress and strain, seepage pressure, and other engineering behavior indicators that need to be monitored.

[0044] Sharing data with external systems means that the monitoring system can access external water and rainfall systems data, geographic information data, visual models, historical data, knowledge and experience, and rule specifications through an internal network business system or the Internet.

[0045] Obtaining engineering data means storing engineering design reports, safety monitoring design reports, engineering foundation information, historical events and data of similar projects in the safety monitoring system.

[0046] The data collected by the monitoring device, external shared data, and engineering foundation data collectively form the engineering safety monitoring digital board, which is the data center of the monitoring system. The data collected through data sensing is stored in the computer platform used by the water conservancy and hydropower engineering safety monitoring system. The data collected through data sensing is stored in the monitoring system server according to information categories such as deformation information, stress and strain information.

[0047] Device management means adding device information of the monitoring device used to collect data to the system server, or deleting, modifying, or querying new information of the monitoring device in the system server.

[0048] Data sensing business is used to build a digital twin engineering safety monitoring digital board containing engineering foundation information, monitoring data, business data, spatial data, and other information. Through monitoring data sensing, external data sharing, and engineering foundation data archiving, various water conservancy and hydropower engineering safety monitoring business data is gathered. Through data sensing and processing, data collection process management and corresponding monitoring device information management are realized.

[0049] S2: Data prediction

[0050] The engineering safety prediction module compiles the data obtained through data sensing. Specifically, the 3σ rule is used to identify and judge outliers, and then remove the outliers and rough errors in the data to obtain effective engineering data.

[0051] On the basis of the effective data obtained, the engineering safety analysis model and the online structure calculation model in the system model library are combined with the current engineering operation condition, i.e. combined with the effective data, to realize the prediction of the future change trend of the specific monitoring effect quantity and obtain prediction data; the engineering safety analysis model uses mathematical statistics and data mining technology in use; the online structure calculation model is a mechanism model; the engineering safety analysis model and the online structure calculation model are combined with the effective data and combined with the current engineering operation condition to predict the future change trend of the specific monitoring object.

[0052] The engineering safety data prediction mainly uses the built-in model in the system model library to predict the future change trend of the data and obtain prediction data, including data management and data analysis sub-function modules; the data management is to compile the data obtained by data sensing to obtain effective data; the data analysis refers to realizing data query, display and analysis through the existing model in the system, analyzing the obtained effective data and prediction data by using the existing engineering analysis model in the system model library, and generating an analysis report; the analysis report includes the data of the current engineering operation state and the data of the predicted future development state of the engineering, and the analysis report can be specific report data or a model of the predicted engineering operation state; the analysis report serves the water conservancy engineering safety monitoring business management to improve the engineering safety management level and efficiency.

[0053] The data prediction business takes the output of the data sensing business module as business input, analyzes the sensing data through data compilation, constructs an effective data set, and on the basis of summarizing and analyzing typical historical events and mastering the current situation, uses the engineering safety analysis model and the mechanism model to make quantitative or qualitative analysis of the development trend of the engineering safety monitoring elements for different prediction periods, and realizes the prediction of the engineering safety monitoring elements.

[0054] S3: Determine whether to perform engineering early warning

[0055] After obtaining the analysis report in S2, the current engineering prepared early warning index and threshold system stored in the system are used to compare the engineering current operation state data and the predicted future development state data of the engineering in the analysis report with the early warning index and threshold system, and perform engineering safety analysis and evaluation on the engineering monitoring parts; if the data in the analysis report is within the safety range specified by the early warning index and threshold system, it is considered that the engineering operation data is normal, the early warning mechanism is not triggered, and the overall process is directly ended; if the data in the analysis report is within the abnormal range specified by the early warning index and threshold system, the early warning mechanism is triggered, and the system issues an engineering early warning.

[0056] As a preferred embodiment, the data in the analysis report can be further compared with the data in the knowledge base, which includes expert experience and engineering specifications, if the data in the analysis report is inconsistent with the data in the knowledge base, the pre-warning is issued, if the data in the analysis report is consistent with the data in the knowledge base, the pre-warning is not triggered. For example, the strain value in the analysis report is a value obtained under a certain natural condition, the knowledge base stores strain values of the hydropower project under various natural conditions, if the strain value in the analysis report is within the abnormal range specified by the pre-warning index and threshold system, the system can further compare the strain value in the analysis report with the strain value under the corresponding natural condition in the knowledge base, if the strain value in the analysis report is inconsistent with the strain value in the knowledge base, the pre-warning is triggered.

[0057] The engineering safety pre-warning module includes a model analysis and monitoring pre-warning sub-function module, realizes pre-warning model management and calculation, and provides pre-warning business management, the model analysis module is to use the engineering data analysis model in the system to analyze and compare the data in the report obtained by the data prediction business with the pre-warning index and threshold system; the monitoring pre-warning sub-module is used for issuing engineering pre-warning.

[0058] The engineering pre-warning business takes the output of the data prediction business as input, takes the pre-warning index and threshold system as guidance, realizes the diagnosis of the engineering safety operation state through engineering safety analysis and evaluation means, if the pre-warning mechanism is triggered, the pre-warning is issued, which provides guidance for the engineering safety management personnel to take disposal measures; if the mechanism is not triggered, the business process will be directly ended.

[0059] S4: engineering pre-play

[0060] After the engineering pre-warning is triggered, the engineering pre-play business is activated, and the visual model in the system is used to simulate the abnormal state that may occur in the future in the pre-warning engineering part.

[0061] The simulation is used to obtain the development state of the risk indexes in the risk index system in the monitoring system, and the risk index system includes indexes affecting the safe operation of the water conservancy project, such as the deformation state of the water conservancy project part, the stress and strain state, the seepage and seepage pressure state and the like. The further development trend of the water conservancy project part state can be simulated, such as the deformation development trend of the water conservancy project part, the stress and strain development trend, the seepage and seepage pressure development trend and the like. The development state of the water conservancy project simulated, such as the deformation state of the water conservancy project part, the stress and strain state, the seepage and seepage pressure state is further evaluated by using the engineering safety risk evaluation model in the monitoring system, the future engineering safety state information is obtained through the engineering risk evaluation model, the engineering safety state information is fed back to the engineering operation management decision-making department, and decision support is provided for subsequent correction of the engineering operation scheme or supplement of the operation scheme for coping with the engineering state.

[0062] The engineering pre-performance is used to simulate and evaluate the future operation scheme of the water conservancy project under the typical working condition and the early warning scene, so as to support the correction of the operation scheme. The engineering safety pre-performance module includes the simulation and the risk evaluation sub-function module. The simulation module is used to simulate the future change development trend of the engineering safety monitoring risk index after triggering the engineering early warning, and provide important engineering safety risk evaluation basis for the safety monitoring professional personnel. The risk evaluation module is used to evaluate the development state of the water conservancy project simulated by using the risk evaluation model in the system.

[0063] The engineering pre-performance business mainly includes two contents. One is that the engineering safety state simulation model in the system model library simulates the development trend of the engineering safety monitoring index under the future prediction scene by combining the effective engineering data obtained, the data of the typical historical event, the engineering design data and the engineering planning data, positively pre-plays the risk and the influence, and obtains the data of the engineering safety state change development trend. The boundary conditions of each engineering index of the engineering safety operation are deduced reversely. The boundary conditions of each engineering index of the engineering safety operation are that the change trend of the engineering operation state in the engineering pre-performance step is observed, the pre-warning index and the threshold system in the system are adjusted in time or multiple times according to the specific values of each risk index when the engineering appears the risk in the pre-performance process, and the pre-warning index and the threshold system are the boundary conditions. The other is that after the data of the engineering safety state change development trend is obtained, the corresponding safety monitoring index development trend is evaluated by using the knowledge base and the model base in the system as the tools, the risk evaluation report is obtained, and the specific conditions of the risk index and the risk that may occur according to the current state development of the engineering are included in the risk evaluation report.

[0064] S5: Engineering safety preplan processing

[0065] The engineering safety plan processing, risk processing, and execution of the engineering plan are performed. In step S4, the risk report is obtained, the specific situation of the risk index is acquired, and the risk situation that may occur in the project is obtained. The management decision department assesses whether to start the emergency plan disposal. If not, the current early warning engineering part must be on-site patrolled and disposed. If the plan disposal measures are started, the engineering plan library disposal measures are matched automatically according to the specific situation of the engineering risk index. The matched plan is reported to the superior management department for approval. After the approval of the superior department, the plan is executed, and the execution process and result are fed back to the superior management department. At the same time, the current overall process is archived and arranged to form knowledge and experience, which is archived in the knowledge base of the system.

[0066] The engineering safety plan construction has a plan disposal and a plan management sub-function module. The plan disposal refers to the development of disposal measures corresponding to the specific risk situation of each index affecting the safe operation of the project by the system. The disposal measures are stored in the engineering plan library of the system. When a specific risk situation occurs in an index, the engineering plan disposal module automatically matches the corresponding disposal measures in the engineering plan library. The engineering plan management refers to the issuance of emergency plan instructions, such as the need to increase the observation frequency of a part of the project, and the work flow management from the emergency plan adaptation to the disposal measure execution and the data flow archiving process.

[0067] The engineering safety plan business includes two processing flows. One is to match the corresponding disposal scheme according to the output of the rehearsal, combine the latest working conditions of the project, report to the superior management unit for approval, and execute the corresponding disposal measures after the approval and feedback the disposal result. The other is on-site processing. After the engineering safety monitoring rehearsal, the plan mechanism is not started, and the on-site processing can be directly solved.

[0068] Taking a digital twin safety monitoring system of a hydropower station as an example:

[0069] Figure 1 For the implementation method of the monitoring system, the Figure 2 is used to guide the construction of the “four pre” function, and the two aspects of business application and comprehensive decision are respectively performed.

[0070] The business application level is mainly used by the safety monitoring management personnel of the hydropower station. According to the Figure 2 flow design, it mainly includes five function modules of monitoring data perception, engineering safety prediction, engineering safety early warning, engineering safety rehearsal, and engineering safety plan.

[0071] The comprehensive decision level mainly applies the digital twin technology to construct a digital model of the hydropower station engineering safety monitoring business scene from the perspective of visualization, thereby mapping the physical world, and realizing the twinning and synchronization of the physical world and the digital world. The comprehensive decision application includes five function modules of data perception, data prediction, monitoring and early warning, scenario deduction, and pre-disposal, and mainly realizes the fusion of the data of the business level application in the digital model of the hydropower station engineering safety monitoring business scene, so as to achieve the management of the safety monitoring "four pre" function business through the three-dimensional visualization means.

[0072] Finally, it should be noted that: the content not described in detail in the specification belongs to the prior art known to those skilled in the art, and the above description is only the preferred embodiment of the present application and is not used to limit the present application. Although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions recorded in the foregoing embodiments or make equivalent replacements to some technical features. Any modification, equivalent replacement, improvement, etc. within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A four-pre function implementation method for water conservancy and hydropower engineering safety monitoring, characterized by: The method comprises the following steps, S1: data sensing and processing, collecting data through monitoring equipment, obtaining data by sharing database with external systems, and obtaining engineering basic information, and storing the obtained data in a system server; S2: data prediction, compiling the data obtained by data sensing to obtain effective engineering data; on the basis of the obtained effective data, using engineering safety analysis models and online structure calculation models in a system model library in combination with the obtained effective data, predicting future change trends of the monitoring positions to obtain prediction data, analyzing the obtained effective data and prediction data to obtain an analysis report; S3: determining whether to perform engineering early warning, comparing the data in the analysis report in step S2 with a warning index and a threshold system, performing engineering safety analysis and evaluation on the current monitoring position to determine whether to issue an engineering early warning; S4: engineering pre-performance, after the engineering early warning is issued, a visual model in the system simulates possible abnormal states of the early warning engineering position in the future, and performs risk evaluation on the simulation results; The simulation simulation is to simulate and simulate the development trend of the engineering safety monitoring index under the future prediction scene by using an engineering safety state simulation simulation model, combining the obtained effective engineering data with the data of typical historical events, engineering design data, and engineering planning data, positively preforming the risk and influence, and inversely deducing the boundary conditions of each engineering index of the engineering safety operation; The inverse deduction of the boundary conditions of each engineering index of the engineering safety operation is to timely or multiple times adjust the warning index and threshold system in the system through the specific values of each risk index when the engineering appears risk in the pre-performance process, and the warning index and threshold system are the boundary conditions; S5: engineering safety plan processing, after obtaining the risk evaluation result in step S4, performing risk processing, executing an engineering safety plan, and evaluating whether to start an emergency plan disposal by a management decision department, if not, performing on-site inspection and disposal on the current early warning engineering position; if the plan disposal measures are started, the specific conditions of the engineering risk index are matched with the disposal measures of the engineering plan library, the matched plan is reported to the superior management department, and after the plan is approved by the superior department, the plan is executed.

2. The four-pre function implementation method for water conservancy and hydropower engineering safety monitoring according to claim 1, characterized in that: The data sensing comprises collecting data by monitoring equipment, sharing data with external systems, and storing engineering information in a system server to obtain data; The monitoring equipment collects data, the monitoring equipment is a sensor data collection device, the sensor is remotely connected with the monitoring system, and the collected information is sent and stored to the system server through wired and wireless networks; The data sharing with external systems refers to that the monitoring system can access external water and rainfall condition system data, geographic information data, visual models, historical data, knowledge experience and rule specification database through other business systems in an intranet or the Internet; The obtained engineering information refers to storing engineering design reports, safety monitoring design reports, engineering basic information, historical events and data of similar engineering in the safety monitoring system; The data collected by the monitoring device, the externally shared data and the engineering basic information jointly constitute an engineering safety monitoring digital bottom plate, and the digital bottom plate is a data center of the monitoring system.

3. The four-pre function implementation method for water conservancy and hydropower engineering safety monitoring according to claim 1, characterized in that: The data compilation in the S2 step refers to rough error identification and abnormal value judgment on the obtained data by using a 3σ criterion, removal of the rough error and abnormal value in the data, and obtaining of effective engineering data.

4. The four-pre function implementation method for water conservancy and hydropower engineering safety monitoring according to claim 1, characterized in that: After the effective engineering data and the prediction data are obtained in the S2 step, the effective data and the prediction data are analyzed by using an engineering analysis model in the system, an analysis report is generated, and the analysis report includes current engineering operation state data and predicted future engineering development state data.

5. The four-pre function implementation method for water conservancy and hydropower engineering safety monitoring according to claim 1, characterized in that: In the S3 step of judging whether to perform engineering early warning, if the data in the analysis report is within a safety range defined by a warning index and a threshold value system, it is considered that the engineering operation data is normal, the early warning mechanism is not triggered, and the overall process is ended; if the data in the analysis report is within an abnormal range defined by the warning index and the threshold value system, engineering early warning is performed.

6. The four-pre function implementation method for water conservancy and hydropower engineering safety monitoring according to claim 1, characterized in that: In the S3 step of judging whether to perform engineering early warning, if the data in the analysis report is within an abnormal range defined by a warning index and a threshold value system, the data in the analysis report is compared with data in a knowledge base, the data in the knowledge base includes expert experience and engineering specifications, and if the data in the analysis report does not match the data in the knowledge base, engineering early warning is performed.

7. The four-pre function implementation method for water conservancy and hydropower engineering safety monitoring according to claim 1, characterized in that: In the S5 step, the preplan treatment refers to formulating treatment measures corresponding to specific risk conditions of various indexes affecting the safety operation of the engineering according to the specific risk conditions, and the treatment measures are stored in an engineering preplan library in the system, and when a specific risk condition of an index occurs, the corresponding treatment measures in the engineering preplan library are automatically matched by the preplan treatment.

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