Small reservoir group safety attention engine system

Abstract

The invention belongs to the technical field of administrative supervision and management in the water conservancy industry, and particularly relates to a small reservoir group safety attention engine system. According to the engine system, multi-source data such as a health factor (H) and an operation environment factor (E) of a reservoir dam can be fused, a forecasting system for a short-term safety attention index (Sp) in a reservoir group is constructed, then a reservoir dispatching factor (D) and a real-time monitoring factor (B) are adopted for revising calculation, and a dam real-time safety attention index (SDB) evaluation system is further provided. The engine is integrated by a data interaction module, a model driving module and an intelligent interaction module, can support intelligent evaluation, rolling sorting and safety early warning of a million-level reservoir group, and is especially suitable for safety supervision and control of a whole-basin reservoir group dam and joint scheduling of a flood season reservoir.

Description

Technical Field

[0001] The invention belongs to the technical field of administrative supervision and management of water conservancy industry, and specifically relates to a safety attention engine system for a small reservoir group. Background Art

[0002] Small reservoir safety risk forecast and warning are usually carried out in two ways: regular assessment and real-time monitoring. Both methods have the following shortcomings: both methods judge dam safety from the internal factors of the dam, without considering external environmental factors such as reservoir water level, flood peak water level and other dam operating conditions; the regular assessment cycle is generally five years, reviewing the dam engineering characteristics, engineering geology, structural safety, facility safety, etc., and cannot conduct real-time health evaluation; real-time monitoring is to measure the dam safety parameters in real time through deformation, infiltration, seepage and other monitoring facilities buried in the dam, which can only assist in judging the immediate status of the dam, and cannot predict the medium- and short-term risks of the dam; for tens of thousands of reservoirs, both methods cannot provide a comprehensive dynamic ranking of safety indicators, and cannot meet the requirements of advance forecasting, key prevention and emergency dispatch for reservoir groups during flood season. Summary of the invention

[0003] The purpose of the present invention is to provide a small reservoir group safety attention engine system to solve the problems existing in the background technology.

[0004] To achieve the above object, the present invention provides the following technical solutions: a small-scale reservoir group safety attention engine system, which is integrated with a data interaction module, a model driving module and an intelligent interaction module;

[0005] The data interaction module includes a static information library table, a dynamic database table and an evaluation index library table built into the engine. The data interaction module is used to obtain dynamic data and static data of the reservoir group outside the engine, and uses an interface call method to interact with the regional or river basin reservoir group operation and management platform, business system, and perception system. "Regional or river basin reservoir group operation and management platform, business system, and perception system" are common knowledge. For example, the Hunan Provincial Water Resources Department has built the Hunan Small Reservoir Safety Monitoring and Operation Management Platform, the Hunan River and Lake Management System (including the river chief system, sand mining supervision, water area coastline, river-related construction projects and other businesses), and the flood situation perception system.

[0006] The model driving module includes an engine built-in near-expiry index model (applicable to 7 days to 1 day before the target date), a spot index model (applicable within 24 hours of the same day) and a real-time index model (applicable within 1 hour), and uses the dynamic data of the reservoir group to calculate the evaluation index of each target dam;

[0007] The intelligent interaction module includes an intelligent supervision unit, an intelligent early warning unit and an intelligent scheduling unit built into the engine. The intelligent interaction module uses the static data and evaluation indicators of each target dam to provide intelligent supervision, intelligent early warning and intelligent scheduling services to the outside of the engine.

[0008] Preferably, the engine has a built-in static information database table for storing static information of the dam name, type, elevation, width, geological conditions, anti-seepage form, and reservoir code, name, administrative division, watershed, water system, and designed water level of the reservoir group;

[0009] The dynamic database table is used to store the reservoir dam operation data required for engine calculation, all in international units, including the following operation parameters:

[0010] Y r - Operation life, the number of years from the target reservoir's current dam completion date;

[0011] Y d - Assessment period, the number of years between the last dam safety assessment of the target reservoir and the completion of the dam;

[0012] P m - Monthly inspection score of the target reservoir dam, which is scored by the reservoir inspection responsible person according to the standardized management regulations of relevant small reservoir projects in the area where the reservoir group is located. When m=0, it is the daily inspection score;

[0013] F p -The maximum water level of the target reservoir during the forecast period;

[0014] F o - Current water level in front of the dam of the target reservoir;

[0015] F m -The highest historical flood level in front of the dam that the target reservoir can safely pass the flood season;

[0016] L r - Target reservoir has a 1-hour dam-front amplitude change;

[0017] L h -The fastest one-hour change of water level in front of the dam during the safe operation of the target reservoir;

[0018] I r - Real-time monitoring data of typical monitoring stations of the target reservoir’s dam, with deformation monitoring data collected first for concrete dams and seepage deformation monitoring data collected first for earth-rock dams;

[0019] I h -The highest historical safety value of the dam of the target reservoir at this typical monitoring station;

[0020] The evaluation index library table is used to store the reservoir group dam safety assessment data output by the model driving module, which are dimensionless values ​​and include the following factors and indicators:

[0021] H f -Basic health factors;

[0022] H y -Current annual dam health factor;

[0023] H m -The health factor of the current month, when m=0, it is the health factor of the day;

[0024] E p - Dam safety environmental factors of the target reservoir;

[0025] E o -Real-time safety environment factors of the dam of the target reservoir;

[0026] D r -Real-time dispatching factor of the dam of the target reservoir;

[0027] B r -Real-time monitoring factors of the dam of the target reservoir;

[0028] S p - Medium- and short-term dam safety concern index of the target reservoir;

[0029] S o - The dam immediate attention index of the target reservoir;

[0030] S DB -Real-time dam safety concern index of target reservoirs.

[0031] Preferably, the engine has a built-in expiration index model to calculate the short- and medium-term safety concern index S of the target dam based on formula (1): p :

[0032] Formula (1)

[0033] The instant index model calculates the instant safety concern index S of the target dam based on formula (2): o :

[0034] Formula (2)

[0035] The real-time index model calculates the real-time safety concern index S of the target dam based on formula (3): DB :

[0036] Formula (3).

[0037] Preferably, the engine has a built-in intelligent supervision unit. The engine automatically detects the health factors, environmental factors, dispatching factors and monitoring factors of each dam in the reservoir group in the evaluation index database table. When a negative number, zero or greater than 1 appears, the corresponding dynamic database table is further checked. If there is an abnormal supervision indicator, statistics and notification of responsibilities are carried out by item according to the river basin or administrative jurisdiction, forming a closed loop of supervision and management;

[0038] The intelligent early warning unit engine automatically detects the impending, immediate and real-time attention indicators of the dams in the evaluation index database table, and sorts them in two ways according to the nine major river basins in the country (the Yangtze River Basin, the Yellow River Basin, the Pearl River Basin, the Haihe River Basin, the Huaihe River Basin, the Songliao River Basin, the southeastern river basins, the southwestern river basins, and the inland river basins) and provincial administrative areas, and issues three-level warnings of "red-orange-yellow" in a graded manner;

[0039] The intelligent scheduling unit uses the inverse operation of the engine model driving module to achieve optimized scheduling: for dams with safety assessment of Class III, the engine uses the lowest single reservoir safety concern index as the automatic optimization scheduling target during the flood season; for cascade reservoirs with water resources and power generation requirements, the maximum reservoir water volume under an acceptable safety concern warning is used as the automatic optimization scheduling target during the flood season. In addition, the engine supports manual optimization scheduling.

[0040] The basic prompt rules for abnormal regulatory indicators include: d - Reservoirs older than five years indicate the need for safety assessment; L r ,I r 、F o -No value, indicating that the monitoring instrument is malfunctioning; P m -No value indicates that the inspection is not in place, and if it is not within the range of 0 to 1, it indicates that the inspection report is abnormal; H f - is equal to 0.6, it is suggested to remove the danger and strengthen it. m - Less than 0.6, prompting to organize special appraisal as soon as possible; F o -When the corresponding design water level in the static database is exceeded, an over-design water level operation prompt will be issued; the prompt rules for abnormalities in the above basic regulatory indicators will be gradually expanded as the engine application data accumulates.

[0041] Preferably, for a newly built reservoir dam, the highest historical flood level in front of the dam for the target reservoir to safely pass the flood season is F m The initial value is replaced by the dam's designed high water level multiplied by a safety factor of 0.8, until the highest water level in the new dam's history of safe flood season exceeds the designed high water level.

[0042] Preferably, for a newly built reservoir dam, the historical highest safety value I of the typical monitoring station of the target reservoir dam is h The initial value is replaced by the design threshold multiplied by a safety factor of 0.8 until the highest historical safety value of the monitoring site exceeds the design threshold.

[0043] Preferably, the target reservoir dams that are assessed as Class I, Class II, or Class III dams according to the reservoir dam safety assessment guidelines have their corresponding basic health factors H f The values ​​are 0.9, 0.8 and 0.6 respectively.

[0044] Preferably, the medium- and short-term safety concern index S of the target reservoir dam p The initial warning value is 1.2, and the real-time safety concern index of the target reservoir is S DB The initial warning value is 1.5.

[0045] The beneficial effects of the present invention are as follows: the engine system comprehensively considers internal and external influencing factors, integrates weather forecasts with real-time rainfall monitoring and construction monitoring, and provides operators with medium-term, immediate and real-time early warning indicators to increase dam safety awareness. It can be used for the safe dispatch of a single reservoir, joint dispatch of a group of reservoirs in a river basin, and rolling ranking of reservoir safety warnings. It is especially beneficial for a management platform of a group of reservoirs at the 10,000-level or a group of reservoirs in the entire river basin to achieve the safe flood standards of advance forecasting, key prevention and emergency dispatch. In addition, operators can rely on the engine system to manage the overall situation and gain insight into management problems such as lack of safety evaluation, inadequate inspections, and failure of monitoring instruments at the first time. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 Schematic diagram of the engine system architecture and operation flow. DETAILED DESCRIPTION

[0047] The specific implementation of the present invention is described in detail below in conjunction with preferred embodiments.

[0048] like Figure 1 As shown in the figure, a small-scale reservoir group safety attention engine system is integrated with three modules: data interaction module, model driving module and intelligent interaction module:

[0049] Data interaction module

[0050] The engine has built-in static information library tables, dynamic database tables and evaluation index library tables, and uses interface calls to interact with regional or river basin reservoir group operation and management platforms, business systems and perception systems for data exchange.

[0051] Static database table, used to store static information such as the name, type, elevation, width, geological conditions, anti-seepage form of the reservoir group dams and the reservoir code, name, administrative division, river basin, water system, and design water level.

[0052] Dynamic database table, used to store reservoir dam operation data required by engine calculation, all in international units, including the following operation parameters:

[0053] Y r- Operation life, the number of years from the target reservoir's current dam completion date;

[0054] Y d - Assessment period, the number of years between the last dam safety assessment of the target reservoir and the completion of the dam;

[0055] P m - Monthly inspection score of the target reservoir dam, which is scored by the reservoir inspection responsible person according to the standardized management regulations of relevant small reservoir projects in the area where the reservoir group is located. When m=0, it is the daily inspection score;

[0056] F p -The maximum water level of the target reservoir during the forecast period;

[0057] F o - Current water level in front of the dam of the target reservoir;

[0058] F m -The highest historical flood level in front of the dam for safe flood control of the target reservoir. For newly built reservoir dams, the initial value is replaced by the dam design high water level multiplied by the safety factor of 0.8, until the highest historical water level for safe flood control of the newly built dam exceeds the design high water level;

[0059] L r - Target reservoir has a 1-hour dam-front amplitude change;

[0060] L h -The fastest one-hour change of water level in front of the dam during the safe operation of the target reservoir;

[0061] I r - Real-time monitoring data of typical monitoring stations of the target reservoir’s dam, with deformation monitoring data collected first for concrete dams and seepage deformation monitoring data collected first for earth-rock dams;

[0062] I h -The historical highest safety value of the typical monitoring station for the target reservoir dam. For newly built reservoir dams, the initial value is replaced by the design threshold multiplied by a safety factor of 0.8 until the historical highest safety value of the monitoring station exceeds the design threshold.

[0063] The evaluation index database table is used to store the reservoir group dam safety assessment data output by the model driving module. All of them are dimensionless values, including the following factors and indicators:

[0064] H f -Basic health factors;

[0065] H y -Current annual dam health factor;

[0066] H m -The health factor of the current month, when m=0, it is the health factor of the day;

[0067] E p - Dam safety environmental factors of the target reservoir;

[0068] E o -Real-time safety environment factors of the dam of the target reservoir;

[0069] D r -Real-time dispatching factor of the dam of the target reservoir;

[0070] B r -Real-time monitoring factors of the dam of the target reservoir;

[0071] S p - Medium- and short-term dam safety concern index of the target reservoir;

[0072] S o - The dam immediate attention index of the target reservoir;

[0073] S DB -Real-time dam safety concern index of the target reservoir;

[0074] Model Driven Module

[0075] The engine has built-in impending index models (1 to 7 days) (applicable to 7 days to 1 day before the target date), spot index models (within 24 hours) (applicable to within 24 hours of the day) and real-time index models (within 1 hour) (applicable to within 1 hour). It uses regular inspections, automatic encrypted calculations and manual adjustments to drive the model to calculate the evaluation indicators of each target dam.

[0076] The near-term index model calculates the short- and medium-term safety concern index S of the target dam based on formula (1): p :

[0077] Formula (1)

[0078] The specific calculation process is as follows: Determine the basic health factor H according to the most recent safety assessment level of the target dam f ; Based on the dam safety assessment period Y d 、Operation life Y r and basic health factor H f , use the interpolation method to calculate the dam health factor H for the current year y , multiplied by the monthly inspection score P m Calculate the dam's current monthly health factor H m ; Calculate the maximum water level F of the target reservoir during the forecast period using the hydrological model based on the medium- and short-term weather forecast p , and the highest historical flood level F in front of the dam that the target dam can safely pass through the flood season m Compared with the target dam safety environment factor E in the forecast period, p; Use the safety environment factor E of the target dam p Divide by the current month's dam health factor H m , calculate the short- and medium-term safety concern index S of the target dam p .

[0079] Further: The target reservoir dams with the most recent safety assessment levels of Class I, Class II, and Class III have the corresponding basic health factors H f The values ​​are 0.9, 0.8 and 0.6 respectively; the above short-term and medium-term weather forecast can be used for 7-day, 3-day and 1-day weather forecasts, and the corresponding 7-day, 3-day and 1-day safety concern index S of the target dam is calculated. 7 , S 3 and S 1 The above hydrological model is preferably a distributed VIC model or a semi-distributed TOPMODEL model suitable for large-scale calculations;

[0080] The immediate index model calculates the immediate safety concern index S of the target dam based on formula (2): o :

[0081] Formula (2)

[0082] The real-time index model calculates the real-time safety concern index S of the target dam based on formula (3): DB :

[0083] Formula (3)

[0084] The specific calculation process of the immediate index model and the real-time index model is as follows: use the current water level in front of the target dam F o Replace the highest water level of the reservoir F p Substitute the above model and calculate the real-time safety environment factor E of the target dam in turn. o and real-time attention index S o ; Use the water level change L in front of the target dam within 1 hour r Divide by the fastest one-hour fluctuation of the water level in front of the target dam during safe operation history L h , calculate the real-time dispatch factor D of the target dam r ; Using real-time monitoring data from typical monitoring stations of the target dam r , divided by the highest historical safety value I of the monitoring site h , calculate the real-time monitoring factor B of the target dam r ; Use real-time attention index S o , real-time scheduling factor D r , Real-time monitoring of factor B r The product of the three is used to calculate the real-time safety concern index S of the target dam. DB .

[0085] (3) Intelligent interaction module

[0086] The engine includes a built-in intelligent supervision unit, an intelligent early warning unit and an intelligent dispatching unit, and interacts with reservoir inspection personnel, technical personnel, administrative personnel, and supervisors at all levels of provinces, cities, counties and river basins through digital billboards, GIS platforms and mobile apps.

[0087] The intelligent supervision unit engine automatically detects the health factors, environmental factors, dispatching factors and monitoring factors of each dam in the evaluation index database table. When a negative number, zero or greater than 1 appears, the corresponding dynamic database table is further checked. If there is an abnormal supervision index, statistics and notification of responsibilities are made by basin or administrative jurisdiction, forming a closed loop of supervision and management. The basic prompt rules for abnormal supervision indicators include: d - Reservoirs older than five years indicate the need for safety assessment; L r ,I r 、F o -No value, indicating that the monitoring instrument is malfunctioning; P m -No value indicates that the inspection is not in place, and if it is not within the range of 0 to 1, it indicates that the inspection report is abnormal; H f - is equal to 0.6, it is suggested to remove the danger and strengthen it. m - Less than 0.6, prompting to organize special appraisal as soon as possible; F o -When the corresponding design water level in the static database is exceeded, an over-design water level operation prompt will be issued. The prompt rules for abnormalities in the above basic regulatory indicators will be gradually expanded as the engine application data accumulates.

[0088] The intelligent early warning unit engine automatically detects the impending, immediate and real-time attention indicators of the dams in the evaluation index database table, and sorts them in two ways: according to the nine major river basins in the country (Yangtze River Basin, Yellow River Basin, Pearl River Basin, Haihe River Basin, Huaihe River Basin, Songliao River Basin, Southeast River Basin, Southwest River Basin, Inland River Basin) and provincial administrative areas, and issues three-level warnings of "red-orange-yellow" in a graded manner. The short-term and medium-term safety attention index S p The initial warning value is 1.2, and the real-time safety concern index of the target reservoir is S DB The initial warning value is 1.5.

[0089] Furthermore, the 92,000 small reservoirs in China can be divided into nine forecast areas according to the nine major river basins in China. Each 10,000-level forecast area has 10 1,000-level forecast areas, and each 1,000-level forecast area has 10 100-level forecast areas. The medium- and short-term safety concern index S of the reservoirs in the whole area can be calculated on a rolling basis during the flood season. p and real-time safety concern index S DB, ranked from large to small, and the top 111 reservoirs, namely 1 "one in ten thousand", 10 "one in a thousand", and 100 "one in a hundred" risk reservoirs were selected for attention. At present, the world's low dam breach standard is one in ten thousand. The historical dam breaches in different seasons and regions are unevenly distributed in time and space. The highest can be controlled at 3 / 10,000, 3 / 1,000, and 3% respectively, that is, the top 333 reservoirs are selected for key attention. On the GIS basin map, the "large-medium-small" blue rings are used to show the ten thousand, thousand, and percent attention levels. If the "red-orange-yellow" three-level warning level has been reached, the blue ring will be filled with the corresponding warning color.

[0090] Intelligent scheduling unit, the inverse operation of the engine model driving module realizes optimized scheduling: for dams with safety assessment of Class III, the engine automatically optimizes scheduling during the flood season with the lowest single reservoir safety concern index; for cascade reservoirs with water resources and power generation requirements, the maximum reservoir water volume under the acceptable safety concern warning is used as the automatic optimization scheduling target during the flood season. In addition, the engine supports manual optimization scheduling.

[0091] Furthermore, for the same reservoir, restricted operation and pre-discharge flood-preparation dispatching methods can be adopted to reduce risks; for cascade reservoirs in the same basin, the reservoir group joint dispatching method can be used to adjust the short-term and medium-term safety concern index S of upstream and downstream reservoirs. p The distribution of target values ​​is to raise the water level by intercepting and storing flood water in upstream safe reservoirs, lower the maximum water level in downstream dangerous reservoirs, balance the temporal and spatial risks of the entire river basin, and meet the overall flood safety standards.

[0092] Example 1: There are 4 small reservoirs in a river basin, and it is predicted that there will be heavy rain in the river basin 7 days later. The calculation results of this engine system are shown in the following table:

[0093]

[0094] (1) Reservoir 2 is a newly built dam. The design water level of 24.7 meters multiplied by 0.8 is used as the historical highest flood level for evaluation, that is, 19.76 meters. The flood level is expected to be 22.2 meters in 7 days, and the safety concern index is 1.38, which exceeds the initial warning value of 1.2. The new reservoir adopts restrictive measures to reduce the water level to 19 meters in time. After draining water to the downstream reservoir 3, the 7-day safety concern index of reservoir 2 is reduced to 1.15, which meets the flood control requirements.

[0095] (2) Reservoir 4 is located downstream of Reservoir 3 and has been under construction for a long time. It is rated as a Class III dam with a 7-day safety threshold of 1.92 and a real-time concern of 1.6, which are relatively dangerous. Reservoir 3 is a concrete dam rated as a Class I dam. It uses the horizontal deformation monitoring value as the monitoring factor. The 7-day concern is 1.08 and the real-time concern is 0.88, which are extremely safe. To balance the load, Reservoir 3 is impounded and the real-time water level is raised by 5 meters. The 7-day safety concern is increased from 1.08 to 1.15, and the safety risk does not increase significantly. Reservoir 4 is pre-discharged and the real-time water level drops by 7 meters. The safety concern after 7 days is reduced from 1.92 to 1.41, and the safety risk is greatly reduced. However, it still requires high attention during the flood season and on-duty personnel should be strengthened. It is recommended to remove hazards and reinforce the dam or downgrade it for scrapping.

[0096] It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention, and these improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A small reservoir group safety attention engine system, characterized in that: It is integrated by data interaction module, model-driven module and intelligent interaction module; The data interaction module includes a static information library table, a dynamic database table and an evaluation index library table built into the engine. The data interaction module is used to obtain dynamic and static data of the reservoir group outside the engine, and uses an interface call method to interact with the regional or river basin reservoir group operation management platform, business system, and perception system for data; The model driving module includes an engine built-in impending index model, an immediate index model and a real-time index model, and uses the reservoir group dynamic data to calculate the evaluation index of each target dam; The intelligent interaction module includes an intelligent supervision unit, an intelligent early warning unit and an intelligent scheduling unit built into the engine. The intelligent interaction module uses the static data and evaluation indicators of each target dam to provide intelligent supervision, intelligent early warning and intelligent scheduling services to the outside of the engine.

2. A small reservoir group safety attention engine system according to claim 1, characterized in that: The engine has a built-in static information database table for storing static information on the dam group's name, type, elevation, width, geological conditions, anti-seepage form, and reservoir code, name, administrative division, river basin, water system, and design water level; The dynamic database table is used to store the reservoir dam operation data required for engine calculation, all in international units, including the following operation parameters: Y r - Operation life, the number of years from the target reservoir's current dam completion date; Y d - Assessment period, the number of years between the last dam safety assessment of the target reservoir and the completion of the dam; P m - Monthly inspection score of the target reservoir dam, which is scored by the reservoir inspection responsible person according to the standardized management regulations of relevant small reservoir projects in the area where the reservoir group is located. When m=0, it is the daily inspection score; F p -The maximum water level of the target reservoir during the forecast period; F o - Current water level in front of the dam of the target reservoir; F m -The highest historical flood level in front of the dam that the target reservoir can safely pass the flood season; L r - Target reservoir has a 1-hour dam-front amplitude change; L h -The fastest one-hour change of water level in front of the dam during the safe operation of the target reservoir; I r - Real-time monitoring data of typical monitoring stations of the target reservoir’s dam, with deformation monitoring data collected first for concrete dams and seepage deformation monitoring data collected first for earth-rock dams; I h -The highest historical safety value of the dam of the target reservoir at this typical monitoring station; The evaluation index library table is used to store the reservoir group dam safety assessment data output by the model driving module, which are dimensionless values ​​and include the following factors and indicators: H f -Basic health factors; H y -Current annual dam health factor; H m -The health factor of the current month, when m=0, it is the health factor of the day; E p - Dam safety environmental factors of the target reservoir; E o -Real-time safety environment factors of the dam of the target reservoir; D r -Real-time dispatching factor of the dam of the target reservoir; B r -Real-time monitoring factors of the dam of the target reservoir; S p - Medium- and short-term dam safety concern index of the target reservoir; S o - The dam immediate attention index of the target reservoir; S DB -Real-time dam safety concern index of target reservoirs.

3. A small reservoir group safety attention engine system according to claim 2, characterized in that: The engine has a built-in expiration index model, which calculates the short- and medium-term safety concern index S of the target dam based on formula (1): p : Formula (1) The instant index model calculates the instant safety concern index S of the target dam based on formula (2): o : Formula (2) The real-time index model calculates the real-time safety concern index S of the target dam based on formula (3): DB : Formula (3).

4. A small reservoir group safety attention engine system according to claim 2, characterized in that: The engine has a built-in intelligent supervision unit. The engine automatically detects the health factors, environmental factors, dispatching factors and monitoring factors of each dam in the reservoir group in the evaluation index database table. When a negative number, zero or greater than 1 appears, the corresponding dynamic database table is further checked. If there is an abnormal supervision index, statistics and notification of responsibilities are carried out by river basin or administrative jurisdiction to form a closed loop of supervision and management. The intelligent early warning unit engine automatically detects the impending, immediate and real-time attention indicators of each dam in the evaluation index database table, sorts them in two ways according to the nine major river basins and provincial administrative regions, and issues three-level warnings of "red-orange-yellow" in different levels; The intelligent scheduling unit uses the inverse operation of the engine model driving module to achieve optimized scheduling: for dams with safety assessment of Class III, the engine uses the lowest single reservoir safety concern index as the automatic optimization scheduling target during the flood season; for cascade reservoirs with water resources and power generation requirements, the maximum reservoir water volume under an acceptable safety concern warning is used as the automatic optimization scheduling target during the flood season. In addition, the engine supports manual optimization scheduling.

5. A small reservoir group safety attention engine system according to claim 4, characterized in that: The basic prompt rules for abnormal regulatory indicators include: d - Reservoirs older than five years indicate the need for safety assessment; L r ,I r 、F o -No value, indicating that the monitoring instrument is malfunctioning; P m -No value indicates that the inspection is not in place, and if it is not within the range of 0 to 1, it indicates that the inspection report is abnormal; H f - is equal to 0.6, it is suggested to remove the danger and strengthen it. m - Less than 0.6, prompting to organize special appraisal as soon as possible; F o -When the corresponding design water level in the static database is exceeded, an over-design water level operation prompt is given; the basic prompt rules for abnormal supervision indicators are gradually expanded as the engine application data accumulates.

6. A small reservoir group safety attention engine system according to claim 2, characterized in that: For a newly built reservoir dam, the highest historical flood level F in front of the dam for the target reservoir to safely pass the flood season is m The initial value is replaced by the dam's designed high water level multiplied by a safety factor of 0.8, until the highest water level in the new dam's history of safe flood season exceeds the designed high water level.

7. A small reservoir group safety attention engine system according to claim 2, characterized in that: For newly built reservoir dams, the historical highest safety value I of the typical monitoring station of the target reservoir dam h The initial value is replaced by the design threshold multiplied by a safety factor of 0.8 until the highest historical safety value of the monitoring site exceeds the design threshold.

8. A small reservoir group safety attention engine system according to claim 2, characterized in that: According to the guidelines for reservoir dam safety assessment, the target reservoir dam is assessed as a Class I dam, a Class II dam, or a Class III dam, and its corresponding basic health factor H f The values ​​are 0.9, 0.8 and 0.6 respectively.

9. A small reservoir group safety attention engine system according to claim 2, characterized in that: The medium- and short-term safety concern index S of the target reservoir dam p The initial warning value is 1.2, and the real-time safety concern index of the target reservoir is S DB The initial warning value is 1.5.

Images