A hydrological data real-time intelligent monitoring and early warning system based on data analysis
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- 黑龙江省水文水资源中心鸡西分中心
- Filing Date
- 2023-11-22
- Publication Date
- 2026-07-21
Smart Images
Figure CN117765704B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of hydrological data monitoring technology, specifically to a real-time intelligent monitoring and early warning system for hydrological data based on data analysis. Background Technology
[0002] Hydrological data typically refers specifically to measured hydrological data, that is, the raw records of various hydrological elements collected through hydrological surveys; such as precipitation, evaporation, water level, flow rate, sediment concentration, etc., and the maximum, minimum, average, total, hydrographic, and isopleths obtained from these data over a certain period. Hydrological data collection refers to the collection of hydrological data from various locations; in computer science, hydrological data collection refers to the automatic collection of hydrological data using computer technology.
[0003] However, in the existing technology, it is impossible to classify hydrological data into different types during the hydrological data acquisition process, and it is also impossible to analyze the degree of impact based on each type of data. As a result, the hydrological data acquisition efficiency is low and the cost cannot be controlled. At the same time, it is impossible to consider the impact of regional hydrological data, which leads to large deviations in hydrological data acquisition. In addition, it is impossible to simulate scenarios and provide early warnings for hydrological data, resulting in low efficiency in hydrological data management.
[0004] To address the aforementioned technical shortcomings, a solution is proposed. Summary of the Invention
[0005] The purpose of this invention is to solve the problems mentioned above by proposing a real-time intelligent monitoring and early warning system for hydrological data based on data analysis.
[0006] The objective of this invention can be achieved through the following technical solutions:
[0007] A real-time intelligent monitoring and early warning system for hydrological data based on data analysis includes a server, which is communicatively connected to a hydrological data analysis unit, a simulation early warning analysis unit, and a dynamic and static monitoring analysis unit.
[0008] The hydrological data analysis unit divides the hydrological monitoring area into sections for hydrological data collection. After the hydrological data division is completed, it performs an impact analysis on different types of hydrological data. After the analysis is completed, it collects data according to the type of hydrological data during the current monitoring period. After the hydrological data collection for the hydrological monitoring area is completed, it performs a hydrological impact analysis on the current hydrological monitoring area.
[0009] After hydrological data analysis and collection, hydrological data early warnings are issued for the hydrological monitoring area under the maximum impact scenario and non-maximum impact scenarios.
[0010] In a preferred embodiment of the present invention, the operation process of the hydrological data analysis unit is as follows:
[0011] Hydrological data is divided into direct and indirect data. The boundaries of the hydrological monitoring area are determined, and the monitoring time period of the hydrological monitoring area is obtained. Hydrological data of the hydrological monitoring area within the monitoring time period is obtained.
[0012] Classified data analysis involves obtaining the types of hydrological data within the current hydrological monitoring area, and then performing classified hydrological data analysis based on the historical monitoring periods of the current hydrological monitoring area. Impact analysis is conducted based on direct and indirect data. Direct and indirect data are divided into direct sub-data and intermediate sub-data. The increase in regional hydrological control time after the fluctuation of direct sub-data values within the hydrological monitoring area during the historical monitoring period, as well as the time required to recover the direct sub-data values within the hydrological monitoring area to their original values after fluctuation, are obtained and compared with the time increase threshold and recovery time threshold, respectively.
[0013] In a preferred embodiment of the present invention, if the increase in the time required for regional hydrological control after the fluctuation of the direct data values within the hydrological monitoring area during the historical monitoring period exceeds the time increase threshold, or if the time required for the direct data values within the hydrological monitoring area to recover to their original value range after fluctuation exceeds the recovery time threshold, then the corresponding direct data is set as high-impact data; if the increase in the time required for regional hydrological control after the fluctuation of the direct data values within the hydrological monitoring area during the historical monitoring period does not exceed the time increase threshold, and the time required for the direct data values within the hydrological monitoring area to recover to their original value range after fluctuation does not exceed the recovery time threshold, then the corresponding direct data is set as low-impact data.
[0014] In a preferred embodiment of the present invention, the reduction in the real-time numerical fluctuation period and the real-time numerical control period of the intermediate data within the hydrological monitoring area during historical monitoring periods, as well as the rate of increase in the deviation between the real-time numerical control amount of the intermediate data within the hydrological monitoring area and the preset numerical control amount of the fluctuation data, are obtained and compared with the period reduction threshold and the deviation increase rate threshold, respectively.
[0015] If the reduction in the real-time value fluctuation period and the real-time value control period of the intermediate data within the hydrological monitoring area exceeds the period reduction threshold during the historical monitoring period, or if the rate of increase in the deviation between the real-time floating value control quantity and the preset floating value control quantity of the intermediate data within the hydrological monitoring area exceeds the deviation increase rate threshold, then the corresponding intermediate data will be set to inefficient control data. If the reduction in the real-time value fluctuation period and the real-time value control period of the intermediate data within the hydrological monitoring area does not exceed the period reduction threshold during the historical monitoring period, and the rate of increase in the deviation between the real-time floating value control quantity and the preset floating value control quantity of the intermediate data within the hydrological monitoring area does not exceed the deviation increase rate threshold, then the corresponding intermediate data will be set to efficient control data.
[0016] During the current monitoring period, data is collected according to the type of hydrological data. High-impact data and low-efficiency control data are prioritized for collection and transmission, while low-impact data and high-efficiency control data are collected and transmitted periodically. If the data does not fluctuate in value as the cycle lengthens, the current collection and transmission cycle will be extended.
[0017] In a preferred embodiment of the present invention, during the hydrological data collection process in the hydrological monitoring area, the highest reciprocating arbitrary floating span value of the flow rate of each branch of the river in the hydrological monitoring area and the controllable proportion of the instantaneous increase in the discharge of the river into the pipeline in the hydrological monitoring area are obtained, and these values are compared with the floating span value threshold and the controllable proportion threshold, respectively.
[0018] If the highest reciprocating arbitrary floating span value of the flow rate of each branch of the river within the hydrological monitoring area exceeds the floating span value threshold, or if the controllable proportion of the instantaneous increase in the discharge of the river into the pipeline within the hydrological monitoring area does not exceed the controllable proportion threshold, then an impact signal on synchronous monitoring is generated and sent to the server; if the highest reciprocating arbitrary floating span value of the flow rate of each branch of the river within the hydrological monitoring area does not exceed the floating span value threshold, and the controllable proportion of the instantaneous increase in the discharge of the river into the pipeline within the hydrological monitoring area exceeds the controllable proportion threshold, then an impact signal on asynchronous monitoring is generated and sent to the server.
[0019] As a preferred embodiment of the present invention, the operation process of the simulation early warning analysis unit is as follows: based on the historical monitoring period of the hydrological monitoring area, the time when the hydrological data of the hydrological monitoring area exceeds the current environmental qualified range is obtained and marked as the risk time. The hydrological data value corresponding to the historically closest monitoring time of the risk time is set as the red line value. At the same time, the red line values of different types of data in the hydrological data are not uniform.
[0020] Based on the real-time monitoring period of the current hydrological monitoring area, the highest speed or maximum span of the corresponding hydrological data fluctuation is obtained, and the corresponding scenario is marked as a peak impact scenario. Based on the peak impact scenario, the duration of the simulated scenario is obtained, and the rate of decrease of the deviation value between the hydrological data and the corresponding red line value and the ratio of the decrease span value of the interval value between the hydrological data and the corresponding red line value to the total interval value are obtained within the duration of the simulated scenario. These are then compared with the decrease rate threshold and the interval span ratio threshold, respectively.
[0021] As a preferred embodiment of the present invention, if the rate of decrease of the deviation value between the hydrological data and the corresponding red line value exceeds the rate of decrease threshold during the continuous period of the simulated scenario, or if the ratio of the decrease span value of the interval value between the hydrological data and the corresponding red line value to the total interval value exceeds the interval span ratio threshold, then it is determined that the hydrological data in the current hydrological monitoring area is abnormal under the peak value impact scenario, and the hydrological monitoring area is subjected to a non-peak value impact scenario early warning analysis.
[0022] If the rate of decrease of the deviation between the hydrological data and the corresponding red line value does not exceed the rate of decrease threshold during the continuous period of the simulated scenario, and the ratio of the decrease span of the interval between the hydrological data and the corresponding red line value to the total interval value does not exceed the interval span ratio threshold, then the hydrological data in the current hydrological monitoring area is determined to be normal under the peak value impact scenario, a normal hydrological data signal is generated and sent to the server.
[0023] In a preferred embodiment of the present invention, if the hydrological monitoring area does not pass the peak impact scenario, a non-peak impact scenario early warning analysis is performed on the hydrological monitoring area. Based on the real-time monitoring period of the current hydrological monitoring area, the fluctuation span of the corresponding values of the hydrological data at each collection time is obtained and the average value is calculated to obtain the average fluctuation span value. The fluctuation time of the average fluctuation span value is continuously recorded and the current simulation scenario is marked as a non-peak impact scenario. At the same time, low impact data and control efficiency data in the hydrological data within the hydrological monitoring area are uniformly marked as low impact data, and high impact data and control inefficiency data are uniformly marked as high impact data.
[0024] The maximum difference between the percentage fluctuation of high-level shadow data and low-level shadow data in off-peak impact scenarios, as well as the difference in the proportion of data types fluctuating simultaneously in high-level shadow data and low-level shadow data in off-peak impact scenarios, are obtained and compared with the maximum percentage difference threshold and the data type proportion difference threshold, respectively.
[0025] As a preferred embodiment of the present invention, if the maximum difference between the percentage fluctuation of high shadow intensity data and the percentage fluctuation of low shadow intensity data in a non-peak impact scenario exceeds the maximum percentage difference threshold, or if the difference in the proportion of data types fluctuating simultaneously between high shadow intensity data and low shadow intensity data in a non-peak impact scenario exceeds the data type proportion difference threshold, then a hydrological data warning signal is generated and sent to the server.
[0026] If the maximum difference between the percentage fluctuation of high-level shadow data and low-level shadow data in non-peak impact scenarios does not exceed the maximum percentage difference threshold, and the difference in the proportion of data types fluctuating simultaneously between high-level shadow data and low-level shadow data in non-peak impact scenarios does not exceed the data type proportion difference threshold, then a normal hydrological data signal is generated and sent to the server.
[0027] In a preferred embodiment of the present invention, the operation process of the dynamic and static monitoring and analysis unit is as follows:
[0028] A threshold for the frequency of hydrological data fluctuations is set. Based on the current frequency of hydrological data fluctuations in the monitoring area, the area is divided into dynamic and static time periods. The difference in data acquisition error between the dynamic and static time periods within the current monitoring period, as well as the number of non-overlapping error data types between the dynamic and static time periods, are obtained and compared with the threshold for the difference in acquisition error and the threshold for the number of non-overlapping error data types.
[0029] If the difference in numerical acquisition error between the dynamic and static time periods of the same type of data in the current monitoring period of the hydrological monitoring area exceeds the acquisition error difference threshold, or if the number of non-intersecting data types of error data types between the dynamic and static time periods in the current monitoring period exceeds the non-intersecting data type number threshold, then a monitoring and control signal will be generated and sent to the server.
[0030] If the difference in numerical acquisition error between the dynamic and static time periods for the same type of data within the current monitoring period in the hydrological monitoring area does not exceed the acquisition error difference threshold, and the number of non-intersecting data types of the error data types for the dynamic and static time periods within the current monitoring period does not exceed the non-intersecting data type number threshold, then a normal monitoring signal is generated and sent to the server.
[0031] Compared with the prior art, the beneficial effects of the present invention are:
[0032] 1. In this invention, the hydrological monitoring area is divided into sections for hydrological data collection, which improves the comprehensiveness of hydrological data collection. By synchronously analyzing hydrological data with direct and indirect impacts, the monitoring efficiency of the hydrological monitoring area is improved, ensuring real-time monitoring of hydrological data and facilitating timely control when hydrological data is abnormal. Furthermore, hydrological data early warning is provided when the hydrological monitoring area is under maximum impact. By performing hydrological data impact analysis when the impact of the data is at its maximum, the current hydrological data is judged to be normal under high impact, maximizing early warning and mitigation, and improving the stability of hydrological data.
[0033] 2. Analyze the dynamic and static monitoring of the hydrological monitoring area to determine whether there are monitoring deviations under the current dynamic and static conditions, thereby improving the monitoring feasibility of the hydrological monitoring area and avoiding abnormal monitoring capabilities that could lead to deviations in hydrological data monitoring and early warning. Attached Figure Description
[0034] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.
[0035] Figure 1 This is a schematic diagram of the principle of the present invention;
[0036] Figure 2 This is a flowchart of the hydrological data analysis unit method in this invention;
[0037] Figure 3 This is a flowchart of the method for simulating early warning analysis unit in this invention. Detailed Implementation
[0038] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0039] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.
[0040] Please see Figure 1 As shown, a real-time intelligent monitoring and early warning system for hydrological data based on data analysis includes a server. The server is connected to a hydrological data analysis unit, a simulation early warning analysis unit, and a dynamic and static monitoring analysis unit. The server has bidirectional communication connections with the hydrological data analysis unit, the simulation early warning analysis unit, and the dynamic and static monitoring analysis unit.
[0041] The server generates hydrological data analysis signals and sends them to the hydrological data analysis unit. Please refer to [link / reference]. Figure 2As shown, after receiving the hydrological data analysis signal, the hydrological data analysis unit divides the hydrological monitoring area into sections, improving the comprehensiveness of hydrological data collection. Simultaneous analysis of directly and indirectly affected hydrological data enhances the monitoring efficiency of the area, ensuring real-time monitoring of hydrological data and facilitating timely control measures in case of anomalies. The specific hydrological data analysis steps are as follows:
[0042] S1: Hydrological data division, determining the boundary of the hydrological monitoring area, obtaining the monitoring period of the hydrological monitoring area, obtaining the hydrological data of the hydrological monitoring area within the monitoring period, and dividing the hydrological data into direct data and indirect data. Direct data refers to parameters such as regional water level, water flow velocity, and water flow rate that can directly affect the management efficiency of the hydrological monitoring area. Indirect data refers to parameters such as the number of aquatic plants, silt height, and regional riverbed height that can indirectly affect the management efficiency of the hydrological monitoring area.
[0043] S2: Classified data analysis. After obtaining the type of hydrological data in the current hydrological monitoring area, classified hydrological data analysis is performed based on the historical monitoring period of the current hydrological monitoring area. Impact analysis is conducted based on direct and indirect data, thereby improving the accuracy of hydrological data collection, avoiding excessive hydrological data collection volume that causes high data transmission and storage pressure, and failing to achieve the effect of intelligent early warning of hydrological data, resulting in uncontrollable costs when monitoring and issuing early warnings of hydrological data.
[0044] Direct and indirect data are divided into direct sub-data and intermediate sub-data. The increase in regional hydrological control time after fluctuations in direct sub-data values within the hydrological monitoring area during historical monitoring periods, and the time required to recover the direct sub-data values to their original range are obtained. These increases in regional hydrological control time and the time required to recover the direct sub-data values to their original range are then compared with thresholds for the increase in time and the recovery time, respectively.
[0045] If the increase in the time required for regional hydrological control after the fluctuation of the direct data values within the hydrological monitoring area during the historical monitoring period exceeds the time increase threshold, or if the time required for the direct data values within the hydrological monitoring area to recover to their original value range after fluctuation exceeds the recovery time threshold, then the corresponding direct data will be set as high-impact data. If the increase in the time required for regional hydrological control after the fluctuation of the direct data values within the hydrological monitoring area during the historical monitoring period does not exceed the time increase threshold, and the time required for the direct data values within the hydrological monitoring area to recover to their original value range after fluctuation does not exceed the recovery time threshold, then the corresponding direct data will be set as low-impact data.
[0046] The reduction in the real-time numerical fluctuation period and real-time numerical control period of intermediate data within the hydrological monitoring area during historical monitoring periods, as well as the rate of increase in the deviation between the real-time numerical control quantity and the preset numerical control quantity of intermediate data within the hydrological monitoring area, are obtained. The reduction in the real-time numerical fluctuation period and real-time numerical control period of intermediate data within the hydrological monitoring area during historical monitoring periods, as well as the rate of increase in the deviation between the real-time numerical control quantity and the preset numerical control quantity of intermediate data within the hydrological monitoring area, are compared with the period reduction threshold and the deviation increase rate threshold, respectively. It can be understood that the reduction in the real-time numerical fluctuation period and real-time numerical control period of intermediate data represents the reduction in the silt height growth period and silt removal period when the intermediate data is silt height. A larger reduction in these two periods indicates lower control efficiency of the intermediate data, which can easily lead to deviations in the hydrological data within the area.
[0047] If the reduction in the real-time value fluctuation period and the real-time value control period of the intermediate data in the hydrological monitoring area exceeds the threshold of the period reduction, or if the deviation between the real-time value control of the intermediate data in the hydrological monitoring area and the preset value control exceeds the threshold of the deviation increase rate, then the control efficiency of the intermediate data in the hydrological monitoring area is determined to be low, and the corresponding intermediate data is set to control inefficient data.
[0048] If the reduction in the real-time value fluctuation period and the real-time value control period of the intermediate data in the hydrological monitoring area during the historical monitoring period does not exceed the period reduction threshold, and the deviation increase rate between the real-time floating value control quantity and the preset floating value control quantity of the intermediate data in the hydrological monitoring area does not exceed the deviation increase rate threshold, then it is determined that the control efficiency of the intermediate data in the hydrological monitoring area is high, and the corresponding intermediate data is set to control high efficiency data.
[0049] During the current monitoring period, data is collected according to the type of hydrological data. High-impact data and low-efficiency control data are collected and transmitted first, while low-impact data and high-efficiency control data are collected and transmitted periodically. If the data does not fluctuate in value as the period extends, the current collection and transmission period will be extended.
[0050] S3: Regional hydrological impact analysis. After completing the hydrological data collection in the hydrological monitoring area, a hydrological impact analysis is conducted on the current hydrological monitoring area. Based on the hydrological impact analysis in the current hydrological monitoring area, the fluctuation of the current hydrological data is evaluated to avoid the decrease in the reliability of hydrological data collection due to large hydrological impacts in the hydrological monitoring area. At the same time, synchronous monitoring of hydrological impacts is carried out when there are large hydrological impacts to ensure the accuracy of hydrological data collection.
[0051] During the hydrological data collection process in the hydrological monitoring area, the maximum reciprocating arbitrary floating span value of the flow of each branch of the river in the hydrological monitoring area and the controllable proportion of the instantaneous increase in the discharge of the river into the pipeline in the hydrological monitoring area are obtained. The maximum reciprocating arbitrary floating span value of the flow of each branch of the river in the hydrological monitoring area and the controllable proportion of the instantaneous increase in the discharge of the river into the pipeline in the hydrological monitoring area are compared with the floating span value threshold and the controllable proportion threshold, respectively. Among them, the reciprocating arbitrary floating span value represents the increase or decrease span of the flow of the branch flow.
[0052] If the highest reciprocating arbitrary floating span value of the flow of each branch of the river in the hydrological monitoring area exceeds the floating span value threshold, or if the controllable proportion of the instantaneous increase in the discharge of the river into the pipeline in the hydrological monitoring area does not exceed the controllable proportion threshold, it is determined that there is an impact on the hydrological data collection in the hydrological monitoring area. An impact synchronous monitoring signal is generated and sent to the server. After receiving the impact synchronous monitoring signal, the server performs synchronous monitoring on the river branch flow and the pipeline in the hydrological monitoring area.
[0053] If the highest reciprocating arbitrary floating span value of the flow of each branch of the river within the hydrological monitoring area does not exceed the floating span value threshold, and the controllable proportion of the instantaneous increase in the discharge of the pipeline flowing into the river within the hydrological monitoring area exceeds the controllable proportion threshold, then it is determined that there is no impact on the hydrological data collection within the hydrological monitoring area. An impact signal for asynchronous monitoring is generated and sent to the server. After receiving the impact signal for asynchronous monitoring, the server performs synchronous monitoring after continuous deviations occur in the hydrological data collection within the hydrological monitoring area.
[0054] After hydrological data is collected and analyzed, the server generates a simulated early warning analysis signal and sends it to the simulated early warning analysis unit. Upon receiving the signal, the unit issues a hydrological data warning for the area under the maximum impact scenario. By performing hydrological data impact analysis when the impact on the data is at its peak, the unit determines whether the current hydrological data is normal under high impact conditions, maximizing the possibility of warning rejection and improving the stability of the hydrological data. Please refer to [link / reference]. Figure 3 As shown, the specific simulation and early warning analysis process is as follows:
[0055] F1: Warning under the scenario of maximum impact. Based on the historical monitoring period of the hydrological monitoring area, the moment when the hydrological data of the hydrological monitoring area exceeds the current environmental acceptable range is obtained and marked as the risk moment. The hydrological data value corresponding to the closest historical monitoring time of the risk moment is set as the red line value. At the same time, the red line values of different types of data in the hydrological data are not uniform.
[0056] Based on the real-time monitoring period of the current hydrological monitoring area, the highest rate of fluctuation or the maximum span of the corresponding hydrological data values is obtained, and the corresponding scenario is marked as a peak impact scenario. Based on the peak impact scenario, the duration of the simulated scenario is obtained, and the rate of decrease in the deviation value between the hydrological data and the corresponding red line value, as well as the ratio of the decrease span of the interval value between the hydrological data and the corresponding red line value to the total interval value, are obtained within the duration of the simulated scenario. These rates of decrease and the ratio of the decrease span of the interval value between the hydrological data and the corresponding red line value to the total interval value are then compared with the decrease rate threshold and the interval span ratio threshold, respectively.
[0057] If the rate of decrease of the deviation between the hydrological data and the corresponding red line value exceeds the decrease rate threshold during the continuous period of the simulated scenario, or if the ratio of the decrease span of the interval between the hydrological data and the corresponding red line value to the total interval value exceeds the interval span ratio threshold, then the hydrological data in the current hydrological monitoring area is determined to be abnormal under the peak value impact scenario, and the hydrological monitoring area will be subjected to a non-peak value impact scenario early warning analysis.
[0058] If the rate of decrease of the deviation between the hydrological data and the corresponding red line value does not exceed the rate of decrease threshold during the continuous period of the simulated scenario, and the ratio of the decrease span of the interval between the hydrological data and the corresponding red line value to the total interval value does not exceed the interval span ratio threshold, then the hydrological data in the current hydrological monitoring area is determined to be normal under the peak impact scenario. A normal hydrological data signal is generated and sent to the server. After receiving the normal hydrological data signal, the server adjusts the monitoring cycle according to the fluctuation of the hydrological data in the current hydrological monitoring area to control the monitoring input cost.
[0059] F2: Assessment under non-maximum impact scenario. If the hydrological monitoring area does not pass the peak impact scenario, a non-peak impact scenario early warning analysis is performed on the hydrological monitoring area. Based on the real-time monitoring period of the current hydrological monitoring area, the fluctuation span of the corresponding values of hydrological data at each collection time is obtained and the average value is calculated to obtain the average fluctuation span value. The fluctuation time of the average fluctuation span value is continuously recorded and the current simulation scenario is marked as a non-peak impact scenario. At the same time, low impact data and control efficiency data in the hydrological data within the hydrological monitoring area are uniformly marked as low impact data, and high impact data and control inefficiency data are uniformly marked as high impact data.
[0060] The maximum difference between the percentage fluctuation of high-level shadow data and low-level shadow data in off-peak impact scenarios, as well as the difference in the proportion of data types fluctuating simultaneously in off-peak impact scenarios, are obtained. The maximum difference between the percentage fluctuation of high-level shadow data and low-level shadow data in off-peak impact scenarios, and the difference in the proportion of data types fluctuating simultaneously in off-peak impact scenarios, are compared with the maximum percentage difference threshold and the data type proportion difference threshold, respectively. Here, the data type proportion difference represents the difference between the number of high-level shadow data types and the number of low-level shadow data types fluctuating at the same time.
[0061] If the maximum difference between the percentage fluctuation of high-level shadow data and low-level shadow data exceeds the maximum percentage difference threshold under non-peak impact scenarios, or if the difference in the proportion of data types fluctuating simultaneously between high-level shadow data and low-level shadow data exceeds the data type proportion difference threshold under non-peak impact scenarios, then the hydrological data analysis of the current hydrological monitoring area is determined to be abnormal under non-peak impact scenarios. A hydrological data early warning signal is generated and sent to the server. After receiving the hydrological data early warning signal, the server performs direct and indirect control according to the type of current hydrological data, that is, it controls the direct data and the indirect data.
[0062] If the maximum difference between the percentage fluctuation of high-level shadow data and low-level shadow data in non-peak impact scenarios does not exceed the maximum percentage difference threshold, and the difference in the proportion of data types fluctuating simultaneously between high-level shadow data and low-level shadow data in non-peak impact scenarios does not exceed the data type proportion difference threshold, then the hydrological data analysis of the current hydrological monitoring area is determined to be normal in non-peak impact scenarios, a normal hydrological data signal is generated and sent to the server;
[0063] After completing the hydrological data early warning, the server generates dynamic and static monitoring analysis signals and sends them to the dynamic and static monitoring analysis unit. After receiving the dynamic and static monitoring analysis signals, the dynamic and static monitoring analysis unit analyzes the dynamic and static monitoring of the hydrological monitoring area to determine whether there is a monitoring deviation in the current dynamic and static states of the hydrological monitoring area. This improves the monitoring feasibility of the hydrological monitoring area and avoids deviations in hydrological data monitoring and early warning caused by abnormal monitoring capabilities of the hydrological monitoring area.
[0064] A threshold for the frequency of hydrological data fluctuations is set. Based on the frequency of fluctuations in hydrological data values in the current monitoring area, the hydrological monitoring area is divided into dynamic and static time periods. The difference in numerical acquisition errors for the same type of data in the dynamic and static time periods within the current monitoring period, as well as the number of non-overlapping data types of the error data types in the dynamic and static time periods within the current monitoring period, are obtained. These differences are then compared with the threshold for the difference in numerical acquisition errors for the same type of data in the dynamic and static time periods within the current monitoring period, and the number of non-overlapping data types of the error data types in the dynamic and static time periods, respectively.
[0065] If the difference in numerical acquisition error between the dynamic and static data of the same type during the current monitoring period in the hydrological monitoring area exceeds the acquisition error difference threshold, or if the number of non-intersecting error data types between the dynamic and static data types during the current monitoring period exceeds the non-intersecting data type number threshold, then the dynamic and static monitoring analysis of the hydrological monitoring area during the current monitoring period is determined to be abnormal. A monitoring and control signal is generated and sent to the server. Upon receiving the monitoring and control signal, the server adjusts the working time of the measurable and required measurable quantities at the current moment and controls the monitoring error.
[0066] If the difference in numerical acquisition error between the dynamic and static time periods within the current monitoring period of the hydrological monitoring area does not exceed the acquisition error difference threshold, and the number of non-intersecting data types of the error data types between the dynamic and static time periods within the current monitoring period does not exceed the non-intersecting data type number threshold, then the dynamic and static monitoring analysis of the hydrological monitoring area during the current monitoring period is determined to be normal, a normal monitoring signal is generated, and the normal monitoring signal is sent to the server.
[0067] In use, the hydrological data analysis unit divides the hydrological monitoring area into sections for hydrological data collection. After dividing the hydrological data, it performs impact analysis on different types of hydrological data. After the analysis, it collects data according to the type of hydrological data during the current monitoring period. After completing the hydrological data collection for the hydrological monitoring area, it performs hydrological impact analysis on the current hydrological monitoring area. After the hydrological data analysis and collection, it issues a hydrological data warning for the hydrological monitoring area under the maximum impact scenario and non-maximum impact scenarios.
[0068] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims
1. A real-time intelligent monitoring and early warning system for hydrological data based on data analysis, characterized in that, It includes a server, and the server communication connection includes a hydrological data analysis unit, a simulation early warning analysis unit, and a dynamic and static monitoring analysis unit; The hydrological data analysis unit divides the hydrological monitoring area into sections for hydrological data collection. After dividing the hydrological data, it performs impact analysis on different types of hydrological data. Following the analysis, it collects data according to the type of hydrological data during the current monitoring period. After completing the hydrological data collection for the current monitoring area, it performs hydrological impact analysis on the current hydrological monitoring area. The operation process of the hydrological data analysis unit is as follows: Hydrological data is divided into direct and indirect data. The boundaries of the hydrological monitoring area are determined, and the monitoring time period of the hydrological monitoring area is obtained. Hydrological data of the hydrological monitoring area within the monitoring time period is obtained. Classified data analysis involves obtaining the types of hydrological data within the current hydrological monitoring area, then conducting classified hydrological data analysis based on the historical monitoring periods of the current hydrological monitoring area, and performing impact analysis based on direct and indirect data. Direct and indirect data are divided into direct sub-data and indirect sub-data. The increase in regional hydrological control time after the fluctuation of direct sub-data values in the hydrological monitoring area during the historical monitoring period and the time required to restore the direct sub-data values in the hydrological monitoring area to the original value area after the fluctuation of direct sub-data values are obtained, and these are compared with the time increase threshold and the recovery time threshold, respectively. After hydrological data analysis and collection, hydrological data early warning is issued for the hydrological monitoring area under the maximum impact scenario and non-maximum impact scenario. The operation process of the simulated early warning analysis unit is as follows: Based on the historical monitoring period of the hydrological monitoring area, the time when the hydrological data of the hydrological monitoring area exceeds the current environmental acceptable range is obtained and marked as the risk time. The hydrological data value corresponding to the historically closest monitoring time of the risk time is set as the red line value. At the same time, the red line values of different types of data in the hydrological data are not uniform. Based on the real-time monitoring period of the current hydrological monitoring area, obtain the highest speed or maximum span of the corresponding hydrological data fluctuation, and mark the corresponding scene as the peak value impact scene; Based on the peak impact scenario, the duration of the simulated scenario is obtained. The rate of decrease of the deviation between the hydrological data and the corresponding red line value during the duration of the simulated scenario, as well as the ratio of the decrease span of the interval between the hydrological data and the corresponding red line value to the total interval value, are obtained and compared with the decrease rate threshold and the interval span ratio threshold, respectively. The operation process of the static and dynamic monitoring and analysis unit is as follows: Set a threshold for the frequency of fluctuation of hydrological data values, and divide the hydrological monitoring area into dynamic and static time periods based on the current frequency of fluctuation of hydrological data values in the current hydrological monitoring area. The numerical acquisition error difference between dynamic and static time periods within the current monitoring period of the hydrological monitoring area, as well as the number of non-overlapping data types of the error data types for dynamic and static time periods within the current monitoring period, are obtained and compared with the acquisition error difference threshold and the non-overlapping data type number threshold, respectively. If the difference in numerical acquisition error between the dynamic and static time periods of the same type of data in the current monitoring period of the hydrological monitoring area exceeds the acquisition error difference threshold, or if the number of non-intersecting data types of error data types between the dynamic and static time periods in the current monitoring period exceeds the non-intersecting data type number threshold, then a monitoring and control signal will be generated and sent to the server. If the difference in numerical acquisition error between the dynamic and static time periods for the same type of data within the current monitoring period in the hydrological monitoring area does not exceed the acquisition error difference threshold, and the number of non-intersecting data types of the error data types for the dynamic and static time periods within the current monitoring period does not exceed the non-intersecting data type number threshold, then a normal monitoring signal is generated and sent to the server.
2. The real-time intelligent monitoring and early warning system for hydrological data based on data analysis according to claim 1, characterized in that, If the increase in the time required for regional hydrological control after fluctuations in the values of direct data within the hydrological monitoring area during the historical monitoring period exceeds the threshold for the increase in time, or if the time required for the values of direct data within the hydrological monitoring area to recover to their original range after fluctuations exceeds the threshold for recovery time, then the corresponding direct data will be set as high-impact data. If the increase in the time required for regional hydrological control after fluctuations in the values of direct data within the hydrological monitoring area during the historical monitoring period does not exceed the threshold for the increase in time, and the time required for the values of direct data within the hydrological monitoring area to recover to their original range after fluctuations does not exceed the threshold for recovery time, then the corresponding direct data will be set as low-impact data.
3. The real-time intelligent monitoring and early warning system for hydrological data based on data analysis according to claim 2, characterized in that, The reduction in the real-time numerical fluctuation period and real-time numerical control period of the intermediate data within the hydrological monitoring area during historical monitoring periods, as well as the rate of increase in the deviation between the real-time numerical fluctuation control quantity and the preset numerical fluctuation control quantity of the intermediate data within the hydrological monitoring area, are obtained and compared with the period reduction threshold and the deviation increase rate threshold, respectively. If the reduction in the real-time value fluctuation period and the real-time value control period of the intermediate data in the hydrological monitoring area exceeds the period reduction threshold during the historical monitoring period, or if the rate of increase of the deviation between the real-time value control quantity and the preset value control quantity of the intermediate data in the hydrological monitoring area exceeds the deviation increase rate threshold, then the corresponding intermediate data will be set to inefficient control data; if the reduction in the real-time value fluctuation period and the real-time value control period of the intermediate data in the hydrological monitoring area does not exceed the period reduction threshold during the historical monitoring period, and the rate of increase of the deviation between the real-time value control quantity and the preset value control quantity of the intermediate data in the hydrological monitoring area does not exceed the deviation increase rate threshold, then the corresponding intermediate data will be set to efficient control data. During the current monitoring period, data is collected according to the type of hydrological data. High-impact data and low-efficiency control data are prioritized for collection and transmission, while low-impact data and high-efficiency control data are collected and transmitted periodically. If the data does not fluctuate in value as the cycle lengthens, the current collection and transmission cycle will be extended.
4. The real-time intelligent monitoring and early warning system for hydrological data based on data analysis according to claim 3, characterized in that, During the hydrological data collection process in the hydrological monitoring area, the highest reciprocating arbitrary floating span value of the flow rate of each branch of the river within the hydrological monitoring area and the controllable proportion of the instantaneous increase in the discharge of the river into the pipeline within the hydrological monitoring area are obtained, and these values are compared with the floating span value threshold and the controllable proportion threshold, respectively. If the highest reciprocating arbitrary floating span value of the flow rate of each branch of the river within the hydrological monitoring area exceeds the floating span value threshold, or if the controllable proportion of the instantaneous increase in the discharge of the river into the pipeline within the hydrological monitoring area does not exceed the controllable proportion threshold, then an impact signal on synchronous monitoring is generated and sent to the server; if the highest reciprocating arbitrary floating span value of the flow rate of each branch of the river within the hydrological monitoring area does not exceed the floating span value threshold, and the controllable proportion of the instantaneous increase in the discharge of the river into the pipeline within the hydrological monitoring area exceeds the controllable proportion threshold, then an impact signal on asynchronous monitoring is generated and sent to the server.
5. The real-time intelligent monitoring and early warning system for hydrological data based on data analysis according to claim 1, characterized in that, If the rate of decrease of the deviation between the hydrological data and the corresponding red line value exceeds the decrease rate threshold during the continuous period of the simulated scenario, or if the ratio of the decrease span of the interval between the hydrological data and the corresponding red line value to the total interval value exceeds the interval span ratio threshold, then the hydrological data in the current hydrological monitoring area is determined to be abnormal under the peak value impact scenario, and the hydrological monitoring area will be subjected to a non-peak value impact scenario early warning analysis. If the rate of decrease of the deviation between the hydrological data and the corresponding red line value does not exceed the rate of decrease threshold during the continuous period of the simulated scenario, and the ratio of the decrease span of the interval between the hydrological data and the corresponding red line value to the total interval value does not exceed the interval span ratio threshold, then the hydrological data in the current hydrological monitoring area is determined to be normal under the peak value impact scenario, a normal hydrological data signal is generated and sent to the server.
6. The real-time intelligent monitoring and early warning system for hydrological data based on data analysis according to claim 5, characterized in that, If the hydrological monitoring area does not pass the peak impact scenario, then a non-peak impact scenario early warning analysis is performed on the hydrological monitoring area. Based on the real-time monitoring period of the current hydrological monitoring area, the fluctuation span of the corresponding values of hydrological data at each collection time is obtained and the average value is calculated to obtain the average fluctuation span value. The fluctuation time of the average fluctuation span value is continuously recorded and the current simulation scenario is marked as a non-peak impact scenario. At the same time, low impact data and control efficiency data in the hydrological data within the hydrological monitoring area are uniformly marked as low impact data, and high impact data and control inefficiency data are uniformly marked as high impact data. The maximum difference between the percentage fluctuation of high-level shadow data and low-level shadow data in off-peak impact scenarios, as well as the difference in the proportion of data types fluctuating simultaneously in high-level shadow data and low-level shadow data in off-peak impact scenarios, are obtained and compared with the maximum percentage difference threshold and the data type proportion difference threshold, respectively.
7. The real-time intelligent monitoring and early warning system for hydrological data based on data analysis according to claim 6, characterized in that, If the maximum difference between the percentage fluctuation of high shadow intensity data and low shadow intensity data exceeds the maximum percentage difference threshold in non-peak impact scenarios, or if the difference in the proportion of data types fluctuating simultaneously between high shadow intensity data and low shadow intensity data exceeds the data type proportion difference threshold in non-peak impact scenarios, then a hydrological data warning signal will be generated and sent to the server. If the maximum difference between the percentage fluctuation of high-level shadow data and low-level shadow data in non-peak impact scenarios does not exceed the maximum percentage difference threshold, and the difference in the proportion of data types fluctuating simultaneously between high-level shadow data and low-level shadow data in non-peak impact scenarios does not exceed the data type proportion difference threshold, then a normal hydrological data signal is generated and sent to the server.