Water level monitoring and early warning system and method for monitoring the real-time height of the water surface under a bridge

Abstract

The present invention discloses a water level monitoring and early warning system and method for monitoring the real-time height of the water surface under a bridge, which relates to the technical field of shipping channel management. The invention is based on sub-area monitoring points divided at equal intervals, and can collect water level data in real time. In combination with environmental data and ship fluctuation factors, it can achieve accurate correction of the water level height to ensure that the water level is within a safe range. Secondly, the number, distribution and accumulation of floating objects, as well as the density and volume information of floating objects attached to the bridge body, help to accurately assess the stress condition of the bridge body and promptly discover possible structural risks. At the same time, through the linkage analysis of water level data and bridge body stress, the corresponding early warning instructions can be triggered in advance, and control measures can be quickly taken, such as restricting the passage of ships and activating emergency overflow channels to ensure the safety of the bridge. The overall method improves the real-time monitoring capability of water level fluctuations and bridge body safety, and improves the efficiency of early warning and emergency response.

Description

Technical Field

[0001] The present invention relates to the technical field of shipping channel management, and in particular to a water level monitoring and early warning system and method for monitoring the real-time height of a water surface under a bridge. Background Art

[0002] With the increasing congestion of water traffic, bridges, as important transportation hubs, carry a large number of ships. However, water level fluctuations, the passage of ships, and changes in the surrounding environment can have significant impacts on bridge safety. Traditional bridge water level monitoring methods typically rely on a small number of fixed-position sensors, resulting in incomplete data acquisition and an inability to timely reflect the full picture of water level changes. In addition, changes in bridge stress caused by water level fluctuations and environmental factors (such as water flow velocity, sediment concentration, and air pressure) are not effectively monitored and warned.

[0003] Traditional water level monitoring often only focuses on the water level itself, ignoring the impact of factors such as ship fluctuations and environmental changes on the water level and bridge, resulting in the inability to timely detect potential safety risks. Summary of the Invention

[0004] In view of the deficiencies in the prior art, the present invention provides a water level monitoring and early warning system and method for monitoring the real-time height of the water surface under a bridge, so as to solve the problems mentioned in the background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: a water level monitoring and early warning system for monitoring the real-time height of the water surface under a bridge, comprising a water level monitoring module, an environmental data acquisition module, a ship dynamic identification module, a floating object impact analysis module, and a water level correction module;

[0006] The water level monitoring module is used to divide the water surface area under the bridge into several sub-areas, set a monitoring point in each sub-area, monitor and obtain the water level in real time, and generate a first data set;

[0007] The environmental data acquisition module is used to collect water flow velocity v w , sediment concentration C s , air pressure P atm and water temperature T w , generate environmental datasets;

[0008] The ship dynamic identification module is used to monitor the characteristics of ships passing under the bridge, including ship size, speed and the water level fluctuations caused by the ship, and generate the ship fluctuation factor Cbfx through the linkage analysis of ship characteristic data and environmental data sets;

[0009] The floating debris impact analysis module is used to monitor the quantity, distribution, and accumulation of floating debris in the sub-area and construct a floating debris obstruction factor Pfzd. It also collects the density and volume information of floating debris attached to the bridge body, as well as bridge body information, to establish a bridge body force data set to calculate the force conditions of the bridge body foundation points, including the foundation pressure factor Qcya and the structural deformation factor Jzbx. The foundation pressure factor Qcya and the structural deformation factor Jzbx are then correlated to generate a bridge body stress assessment index Qzpg.

[0010] The water level correction module is used to extract the water level height H of the i-th sub-area i , ship fluctuation factor Cbfx, floating object interference correction factor Pfgx, establish the water level correction model and perform correction to obtain the corrected water level height of the i-th sub-area And preset the water level safety threshold Swq, when the corrected water level height of the i-th sub-area When the water level exceeds the safety threshold Swq, the first warning instruction is triggered.

[0011] Preferably, the water level monitoring module includes a region division unit and a water level data aggregation unit;

[0012] The area division unit is used to divide the water surface area under the bridge into several sub-areas at equal intervals according to the number of bridge piers, set a monitoring point in each sub-area, and deploy a water level sensor;

[0013] The water level data aggregation unit is used to obtain the water level heights collected by the water level sensors in several sub-areas, generate a first data group, and after pre-processing the first data group, calculate the average water level height H by the following formula: avg :

[0014]

[0015] Where H i represents the water level measured in the i-th sub-area, and n represents the number of sub-areas.

[0016] Preferably, the environmental data set includes water flow velocity v w , sediment concentration C s , air pressure P atm and water temperature T w ;

[0017] The water flow velocity v w Acquired by Doppler flow meter;

[0018] The sediment concentration C s Obtained through turbidity sensor;

[0019] The air pressure P atmThe data is collected by installing an air pressure sensor on the top of the bridge;

[0020] The water temperature T w Used to install temperature sensor to measure water surface temperature to obtain.

[0021] Preferably, the ship dynamic identification module includes a ship characteristic monitoring unit and a first analysis unit;

[0022] The ship characteristic monitoring unit is used to install a laser ranging sensor in the monitoring point to monitor the ship's draft depth D in real time. ship , ship speed V ship , the height of the wave caused by the ship H wave , generate ship characteristic dataset;

[0023] The first analysis unit is used to analyze and calculate the ship fluctuation factor Cbfx based on the environmental data set and the ship characteristic data set;

[0024] The specific calculation process of the ship fluctuation factor Cbfx is as follows:

[0025] S11. Based on the ship's draft D ship and ship speed V ship , calculate the water level disturbance coefficient W dist :

[0026]

[0027] Where k1 is the disturbance correction coefficient of the bridge structure. Through experimental calibration, the impact of different ship speeds and sizes on water disturbance is simulated, the amplitude of water level changes is recorded, and k1 is obtained through regression analysis. The following includes: under standard river conditions, when the ship length is 50 meters, the speed is 5m / s, the fluctuation amplitude is 10cm, and the fitting k1 is 0.05;

[0028] S12. Based on the wave height H caused by the ship wave and water velocity v w , calculate the corrected wave influence coefficient W wave :

[0029] W wave =k2*H wave *ln(1+v w );

[0030] Where k2 is the correction coefficient for wave amplitude. By counting the wave height and the water level changes caused by hundreds of ships passing under the bridge, k2 is fitted to 1.2.

[0031] S13. Extract the sediment concentration C measured by the turbidity sensor in the environmental data set s , calculate the water damping coefficient Wsed :

[0032]

[0033] Among them, k3 is the sediment damping adjustment coefficient, including: when the sediment concentration is 0.5kg / m 3 When , the fluctuation damping effect is reduced by 20%, and the fitting k3 is 2;

[0034] S14. Extract the air pressure P in the environmental data set atm and water temperature T w After dimensionless processing, the corrected external environment comprehensive influence coefficient W is calculated by the following formula rnv :

[0035]

[0036] Among them, k4 is the meteorological adjustment coefficient, T ref is the water reference temperature, set to 25°C;

[0037] S15. Extract the water level disturbance coefficient W obtained in S11-S14 dist , Corrected wave influence coefficient W wave , water damping coefficient W sed and the corrected external environment comprehensive influence coefficient W env , after dimensionless processing, the ship fluctuation factor Cbfx is calculated by the following formula:

[0038] Cbfx=W dist *α+W wave *β+W sed *γ+W env *δ;

[0039] Where α, β, γ and δ represent the water level disturbance coefficient W dist , Corrected wave influence coefficient W wave , water damping coefficient W sed and the corrected external environment comprehensive influence coefficient W env The weight value of 0<α<1, 0<β<1, 0<γ<1, 0<δ<1, and α+β+γ+δ=1.

[0040] Preferably, the floating object impact analysis module includes a floating object monitoring unit and a second analysis unit;

[0041] The floating object monitoring unit is used to install an infrared sensor at the monitoring point to monitor the heat reflection of floating objects on the water surface of the sub-area, use a camera to capture the water surface image of the sub-area, use image recognition technology to distinguish and track floating objects, extract the number, distribution and accumulation of floating objects, and obtain the floating object coverage area A. pFloating debris accumulation height H p and the drift velocity V p ;

[0042] The second analysis unit is used to extract the floating object coverage area A p Floating debris accumulation height H p and the drift velocity V p , after dimensionless processing, the floating object occlusion factor Pfzd is calculated using the following formula:

[0043]

[0044] Among them, A total Indicates the total water surface area of ​​the sub-region.

[0045] Preferably, the floating object impact analysis module further includes a bridge monitoring unit, a bridge analysis unit and associated units;

[0046] The bridge monitoring unit is used to divide the bridge into m bridge foundation points through networking, where m represents the total number of bridge foundation points; and collect the density and volume information of floating objects attached to the bridge as well as bridge information to establish a bridge force data set;

[0047] The bridge analysis unit is used to calculate the stress conditions of the bridge foundation points based on the stress data set, and obtain the foundation bearing factor Qcya and the structural deformation factor Jzbx by the following formula:

[0048] F p,f =ρ w *g*H avg ;

[0049] C p,f =ρ p *g*V p,f ;

[0050]

[0051] Among them, F p,f Represents the static pressure at the fth foundation point of the bridge body, in N, ρ w represents the density of water, g represents the acceleration due to gravity, H avg Indicates the average water level height;

[0052] A p,f A represents the effective foundation area of ​​the f-th foundation point of the bridge body. base Indicates the total load-bearing area of ​​the bridge foundation, in m 2 ; C p,f is the total surface pressure of the floating object at point f; ρ p represents the density of floating objects attached to the fth foundation point of the bridge, Vp,f represents the volume of floating objects attached to the fth foundation point of the bridge; m represents the total number of foundation points of the bridge;

[0053] Among them, M j Indicates the bending moment at the f-th foundation point of the bridge, ΔH k Indicates the deviation of water level change at point f, E k It represents the elastic modulus of the f-th foundation point of the bridge body, in Pa;

[0054] The correlation unit is used to correlate the foundation bearing factor Qcya and the structural deformation factor Jzbx to obtain the bridge stress evaluation index Qzpg:

[0055]

[0056] Among them, σ safe Indicates the maximum design safety stress threshold of the bridge.

[0057] Preferably, the water level correction module includes a correction unit and an evaluation module;

[0058] The correction unit is used to establish a water level correction model using a statistical method, and the water level height H of the i-th sub-area i , ship fluctuation factor Cbfx and floating object interference correction factor Pfgx, and the water level height of the ith sub-area is corrected by the following formula to obtain the corrected water level height of the ith sub-area

[0059]

[0060] Preferably, the evaluation module includes a first evaluation unit and a second evaluation unit;

[0061] The first evaluation unit is used to preset the water level safety threshold Swq, and the corrected water level height of the i-th sub-area Compare with the water level safety threshold Swq to obtain the first assessment result, including:

[0062] When the corrected water level height of the i-th sub-area When the water level exceeds the safety threshold Swq, it indicates that the water level in the sub-area is at risk of overflow and there is a risk of collision between ships passing through the bridge, and the first warning instruction is generated;

[0063] When the corrected water level height of the i-th sub-area When the water level is less than or equal to the water level safety threshold Swq, it means that there is no overflow risk in the sub-area and the water level is continuously monitored;

[0064] The second evaluation unit is used to preset a bridge stress risk threshold Qzy, compare the bridge stress evaluation index Qzpg with the bridge stress risk threshold Qzy, and obtain a second evaluation result, including:

[0065] When the bridge stress assessment index Qzpg and the bridge stress risk threshold Qzy are equal, it indicates that the buoyancy of the water and floating objects on the bridge increases, causing the risk of damage to the bridge structure, triggering the second warning instruction;

[0066] When the bridge stress assessment index Qzpg is equal to the bridge stress risk threshold Qzy, it means that the buoyancy of the water and floating objects on the bridge is within a safe range and there is no need to generate an early warning instruction.

[0067] Preferably, the evaluation module further includes a first strategy unit and a second strategy unit;

[0068] The first strategy unit is used to receive the first warning instruction and generate the first control instruction, including: restricting the passage of ships, and reminding ship operators and bridge management departments through broadcasting or mobile phone text messages, requiring temporary suspension of navigation, and activating the emergency overflow channel to divert the water flow in the i-th sub-area until the corrected water level height of the i-th sub-area is reached. ≤water level safety threshold Swq;

[0069] The second strategy unit is used to receive the second early warning instruction and generate the second control instruction, including: setting the proportion of directing water flow to 20%-30% to the storage pool, dispatching the floating debris cleaning vessel on the water surface to clean up the floating debris affecting the bridge, and then directing the water flow stored in the pool back to the current sub-area waters, increasing the frequency of floating debris cleaning to 2-3 times a week, and reinforcing the fth point of bridge deformation with steel plates or steel beams.

[0070] The water level monitoring and early warning method for monitoring the real-time height of the water surface under the bridge comprises the following steps:

[0071] Step 1: Divide the water surface area under the bridge into several sub-areas at equal intervals based on the number of bridge piers, set a monitoring point in each sub-area, monitor the water level in real time, and generate a first data set;

[0072] Step 2: Collect water flow velocity v w , sediment concentration C s , air pressure P atm and water temperature T w , generate environmental datasets;

[0073] Step 3: Monitor the characteristics of ships passing under the bridge, including ship size, speed, and the water level fluctuations caused by the ships. By linking the ship characteristic data with the environmental data set, the ship fluctuation factor Cbfx is generated.

[0074] Step 4: Monitor the quantity, distribution, and accumulation of floating debris in the sub-area and construct the floating debris obstruction factor Pfzd. Collect the density and volume of floating debris attached to the bridge, as well as bridge information, to establish a bridge stress data set to calculate the stress conditions at the bridge foundation points, including the foundation pressure factor Qcya and the structural deformation factor Jzbx. The foundation pressure factor Qcya and the structural deformation factor Jzbx are then correlated to generate the bridge stress assessment index Qzpg.

[0075] Step 5: Extract the water level H of the i-th sub-area i , ship fluctuation factor Cbfx, floating object interference correction factor Pfgx, establish the water level correction model and perform correction to obtain the corrected water level height of the i-th sub-area And preset the water level safety threshold Swq, when the corrected water level height of the i-th sub-area When the water level is higher than the safety threshold Swq, a first warning instruction is triggered, and a first control instruction is generated according to the first warning instruction;

[0076] Step 6: Preset the bridge stress risk threshold Qzy. If the bridge stress assessment index Qzpg is higher than the bridge stress risk threshold Qzy, trigger the second warning instruction, and generate the second control instruction according to the first warning instruction.

[0077] The present invention provides a water level monitoring and early warning system and method for monitoring the real-time height of the water surface under a bridge. It has the following beneficial effects:

[0078] (1) Traditional water level monitoring methods often ignore environmental factors (such as water velocity, sediment concentration, air pressure, etc.) and the dynamic impact of ships. However, the present invention uses an environmental data acquisition module and a ship dynamic identification module to combine water level monitoring data for comprehensive analysis. This multi-source data fusion method effectively solves the problem that traditional technologies only focus on the water level itself and ignore environmental changes and ship fluctuations, thereby more accurately assessing the impact of water level changes on bridge safety.

[0079] (2) The accumulation and drift of floating objects may cause buoyancy on the bridge, leading to the risk of structural damage. Traditional methods fail to effectively monitor this factor. However, this invention, through a floating object impact analysis module and bridge stress analysis, obtains real-time information on floating objects and assesses their impact on the bridge. By calculating the foundation bearing factor Qcya and the structural deformation factor Jzbx, it generates the bridge stress assessment index Qzpg, providing more comprehensive and accurate data support for bridge safety assessments.

[0080] (3) The present invention introduces a water level correction module that, combined with ship fluctuation factors, floating debris correction factors, and environmental data, can correct water level data based on real-time conditions and generate warning instructions based on a preset water level safety threshold Swq. This dynamic adjustment mechanism can provide early warning of the risk of water levels exceeding safety thresholds, allowing appropriate measures to be taken in advance, such as adjusting ship traffic and berthing or initiating emergency drainage, to avoid potential safety accidents. BRIEF DESCRIPTION OF THE DRAWINGS

[0081] Figure 1 This is a schematic block diagram of a water level monitoring and early warning system for monitoring the real-time height of the water surface under a bridge according to the present invention;

[0082] Figure 2 The figure is a schematic diagram of the steps of the water level monitoring and early warning method for monitoring the real-time height of the water surface under the bridge according to the present invention. DETAILED DESCRIPTION

[0083] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0084] Example 1

[0085] See also Figure 1 , the present invention provides a water level monitoring and early warning system for monitoring the real-time height of the water surface under the bridge, including a water level monitoring module, an environmental data acquisition module, a ship dynamic identification module, a floating object impact analysis module and a water level correction module;

[0086] The water level monitoring module is used to divide the water surface area under the bridge into several sub-areas, set a monitoring point in each sub-area, monitor and obtain the water level in real time, and generate a first data set;

[0087] The environmental data acquisition module is used to collect water flow velocity v w , sediment concentration C s , air pressure P atm and water temperature T w , generate environmental datasets;

[0088] The ship dynamic identification module is used to monitor the characteristics of ships passing under the bridge, including ship size, speed and the water level fluctuations caused by the ship, and generate the ship fluctuation factor Cbfx through the linkage analysis of ship characteristic data and environmental data sets;

[0089] The floating debris impact analysis module is used to monitor the quantity, distribution, and accumulation of floating debris in the sub-area and construct a floating debris obstruction factor Pfzd. It also collects the density and volume information of floating debris attached to the bridge body, as well as bridge body information, to establish a bridge body force data set to calculate the force conditions of the bridge body foundation points, including the foundation pressure factor Qcya and the structural deformation factor Jzbx. The foundation pressure factor Qcya and the structural deformation factor Jzbx are then correlated to generate a bridge body stress assessment index Qzpg.

[0090] The water level correction module is used to extract the water level height H of the i-th sub-area i , ship fluctuation factor Cbfx, floating object interference correction factor Pfgx, establish the water level correction model and perform correction to obtain the corrected water level height of the i-th sub-area And preset the water level safety threshold Swq, when the corrected water level height of the i-th sub-area When the water level exceeds the safety threshold Swq, the first warning instruction is triggered.

[0091] In this embodiment, the present invention achieves comprehensive water level monitoring by dividing the water surface area under the bridge into multiple sub-areas and setting up monitoring points in each sub-area. Compared to traditional methods that rely on a small number of fixed sensors, this system can obtain more comprehensive and accurate water level data, promptly reflecting water level changes in the entire area under the bridge, and avoiding the drawback of traditional methods that cannot fully cover water level fluctuations.

[0092] Traditional water-level monitoring methods often overlook environmental factors (such as water velocity, sediment concentration, and air pressure) as well as the dynamic impact of ships. However, this invention utilizes an environmental data acquisition module and a ship dynamic identification module, combining water-level monitoring data for comprehensive analysis. This multi-source data fusion effectively addresses the problem of traditional technologies focusing solely on water levels while ignoring environmental changes and ship movements, enabling a more accurate assessment of the impact of water-level fluctuations on bridge safety.

[0093] The accumulation and drift of floating debris can cause buoyancy on bridges, leading to the risk of structural damage. Traditional methods fail to effectively monitor this factor. However, this invention, through a floating debris impact analysis module and bridge stress analysis, acquires real-time information on floating debris and assesses its impact on the bridge. By calculating the foundation bearing factor Qcya and the structural deformation factor Jzbx, it generates the bridge stress assessment index Qzpg, providing more comprehensive and accurate data support for bridge safety assessments.

[0094] This invention introduces a water level correction module that, combined with ship fluctuation factors, floating debris correction factors, and environmental data, can adjust water level data based on real-time conditions and generate warning instructions based on a preset water level safety threshold Swq. This dynamic adjustment mechanism provides early warning of the risk of water levels exceeding safety thresholds, allowing appropriate measures to be taken in advance, such as adjusting the order of ship passage or initiating emergency drainage, to avoid potential safety accidents.

[0095] Example 2

[0096] This example is explained in Example 1. Figure 1 ,Specifically, the water level monitoring module includes a region division unit and a water level data ,aggregation unit;

[0097] The area division unit is used to divide the water surface area under the bridge into several sub-areas at equal intervals based on the number of bridge piers. Each sub-area is equipped with a monitoring point and a water level sensor. By dividing the water surface area under the bridge into several sub-areas at equal intervals based on the number of bridge piers, and setting independent monitoring points and water level sensors in each sub-area, the entire water surface area can be effectively covered. This precise division method is more comprehensive than traditional single monitoring point methods, avoiding data blind spots caused by too few monitoring points and ensuring the comprehensiveness and accuracy of water level data.

[0098] The water level data aggregation unit is used to obtain the water level heights collected by the water level sensors in several sub-areas, generate a first data group, and after pre-processing the first data group, calculate the average water level height H by the following formula: avg :

[0099]

[0100] Where H i represents the water level measured in the i-th sub-area, and n represents the number of sub-areas.

[0101] In this embodiment, the water level data aggregation unit collects and aggregates water level sensor data from multiple sub-areas. Through data preprocessing and formula calculation, it obtains the average water level for each sub-area. This method allows for timely monitoring of water level changes across the entire area under the bridge. By calculating the average water level height, it reduces uncertainty caused by individual sensor measurement errors, providing more stable and reliable water level data.

[0102] Example 3

[0103] This example is explained in Example 1. Figure 1 Specifically, the environmental data set includes water flow velocity v w , sediment concentration C s, air pressure P atm and water temperature T w ;

[0104] The water flow velocity v w Acquired by Doppler flow meter;

[0105] The sediment concentration C s Obtained through turbidity sensor;

[0106] The air pressure P atm The data is collected by installing an air pressure sensor on the top of the bridge;

[0107] The water temperature T w Used to install temperature sensor to measure water surface temperature to obtain.

[0108] By integrating multiple environmental data sets, such as water velocity, sediment concentration, air pressure, and water temperature, into a single environmental dataset, the system can perform comprehensive analysis under varying environmental conditions. This multi-dimensional data monitoring provides powerful data support for the system, enabling more accurate predictions of environmental changes and water level fluctuations, thereby enhancing bridge safety monitoring capabilities.

[0109] Example 4

[0110] This example is explained in Example 1. Figure 1 ,Specifically, the ship dynamic identification module includes a ship characteristic monitoring unit and a first analysis unit;

[0111] The ship characteristic monitoring unit is used to install a laser ranging sensor in the monitoring point to monitor the ship's draft depth D in real time. ship , ship speed V ship , the height of the wave caused by the ship H wave , generate ship characteristic dataset;

[0112] The first analysis unit is used to analyze and calculate the ship fluctuation factor Cbfx based on the environmental data set and the ship characteristic data set;

[0113] The specific calculation process of the ship fluctuation factor Cbfx is as follows:

[0114] S11. Based on the ship's draft D ship and ship speed V ship , calculate the water level disturbance coefficient W dist :

[0115]

[0116] Among them, k1 is the disturbance correction coefficient of the bridge structure. Through experimental calibration, the influence of different ship speeds and sizes on water flow disturbance is simulated, the water level change amplitude is recorded, and k1 is obtained by regression analysis. This includes: under standard river conditions, when the ship length is 50 meters and the speed is 5m / s, the fluctuation amplitude is 10cm, and the fitting k1 is 0.05; the water level disturbance coefficient is calculated based on the ship draft and ship speed. The water level disturbance coefficient W dist It reflects the direct disturbance of water level caused by ship passage.

[0117] S12. Based on the wave height H caused by the ship wave and water velocity v w , calculate the corrected wave influence coefficient W wave :

[0118] W wave =k2*H wave *ln(1+v w );

[0119] Among them, k2 is the correction coefficient of wave amplitude; by counting the wave height and the water level changes caused by hundreds of ships passing under the bridge, k2 is fitted to 1.2; according to the wave height and water flow speed caused by the ship, the corrected wave influence coefficient W is calculated wave . Corrected wave influence coefficient W wave Measures the effect of waves on water level changes. Waves caused by a passing ship will cause noticeable ripples on the water surface. Corrected wave influence coefficient W wave The impact on water level fluctuations is more significant, especially when the water flow is slow or the water body is shallow, the effect of waves is more prominent.

[0120] S13. Extract the sediment concentration C measured by the turbidity sensor in the environmental data set s , calculate the water damping coefficient W sed :

[0121]

[0122] Among them, k3 is the sediment damping adjustment coefficient, including: when the sediment concentration is 0.5kg / m 3 When the water level is 1000 m / s, the wave damping effect decreases by 20%, and the fitted k3 is 2. The damping coefficient of the water body is calculated by measuring the sediment concentration. Higher sediment concentrations increase the resistance to water flow, slowing the amplitude and speed of water wave propagation. High sediment concentrations have a greater wave damping effect, meaning the amplitude of water level fluctuations is "weakened" or slowed. The effect of sediment concentration on fluctuations is achieved by correcting for the resistance to water flow.

[0123] S14. Extract the air pressure P in the environmental data set atm and water temperature T wAfter dimensionless processing, the corrected external environment comprehensive influence coefficient W is calculated by the following formula env :

[0124]

[0125] Among them, k4 is the meteorological adjustment coefficient, T ref The reference temperature of the water body is set to 25℃. The changes in air pressure and water temperature will affect the physical properties of the water body, and thus affect the propagation speed and amplitude of water waves. By correcting the comprehensive influence coefficient of the external environment W env , the system is able to adjust the fluctuation factor under different meteorological conditions.

[0126] S15. Extract the water level disturbance coefficient W obtained in S11-S14 dist , Corrected wave influence coefficient W wave , water damping coefficient W sed and the corrected external environment comprehensive influence coefficient W env , after dimensionless processing, the ship fluctuation factor Cbfx is calculated by the following formula:

[0127] Cbfx=W dist *α+W wave *β+W sed *γ+W env *δ;

[0128] Where α, β, γ and δ represent the water level disturbance coefficient W dist , Corrected wave influence coefficient W wave , water damping coefficient W sed and the corrected external environment comprehensive influence coefficient W env The weight value of 0<α<1, 0<β<1, 0<γ<1, 0<δ<1, and α+β+γ+δ=1.

[0129] In this embodiment, by analyzing multiple factors such as the ship's draft, speed, wave height, sediment concentration, air pressure, and water temperature, the system can accurately calculate and correct water level fluctuations, ensuring more comprehensive and accurate water level monitoring. dist , Corrected wave influence coefficient W wave , water damping coefficient W sed and the corrected external environment comprehensive influence coefficient W env The calculation method of the ship fluctuation factor Cbfx obtained by the correlation calculation works together to provide the ability to dynamically adjust the water level fluctuation prediction, which helps to timely detect potential water level anomalies and enhance the response speed and accuracy of the early warning system.

[0130] Example 5

[0131] This example is explained in Example 1. Figure 1 ,Specifically, the floating object impact analysis module includes a floating object monitoring unit and a second analysis unit;

[0132] The floating object monitoring unit is used to install an infrared sensor at the monitoring point to monitor the heat reflection of floating objects on the water surface of the sub-area, use a camera to capture the water surface image of the sub-area, use image recognition technology to distinguish and track floating objects, extract the number, distribution and accumulation of floating objects, and obtain the floating object coverage area A. p Floating debris accumulation height H p and the drift velocity V p ;

[0133] The second analysis unit is used to extract the floating object coverage area A p Floating debris accumulation height H p and the drift velocity V p , after dimensionless processing, the floating object occlusion factor Pfzd is calculated using the following formula:

[0134]

[0135] Among them, A total Indicates the total water surface area of ​​the sub-region.

[0136] In this embodiment, the coverage area and accumulation height of floating objects directly affect the effective volume of the water surface and thus the stability of the water level. Floating objects with higher accumulations will reduce the effective area of ​​the water surface, which may lead to irregular changes in the water level, such as rising or sinking. The floating object impact analysis module provides key inputs for water level prediction by accurately monitoring the number, distribution, accumulation and drift speed of floating objects, combined with the dimensionless calculated floating object obstruction factor Pfzd. The coverage area and accumulation height of floating objects affect the water surface area, which may affect the fluctuation of the water level. As the floating object impact factor changes, the water flow speed, surface evaporation rate and heat exchange of the water body will also change, which will indirectly affect the change of water level, especially when the water flow is slow or the floating objects are accumulated heavily.

[0137] Example 6

[0138] This example is explained in Example 1. Figure 1 ,Specifically, the floating object impact analysis module also includes a bridge monitoring unit, a bridge analysis unit and associated units;

[0139] The bridge monitoring unit is used to divide the bridge into m bridge foundation points through networking, where m represents the total number of bridge foundation points; and collect the density and volume information of floating objects attached to the bridge as well as bridge information to establish a bridge force data set;

[0140] The bridge analysis unit is used to calculate the stress conditions of the bridge foundation points based on the stress data set, and obtain the foundation bearing factor Qcya and the structural deformation factor Jzbx by the following formula:

[0141] F p,f =ρ w *g*H avg ;

[0142] C p,f =ρ p *g*V p,f ;

[0143]

[0144] Among them, F p,f Represents the static pressure at the fth foundation point of the bridge body, in N, ρ w represents the density of water, g represents the acceleration due to gravity, H avg Indicates the average water level height;

[0145] A p,f A represents the effective foundation area of ​​the f-th foundation point of the bridge body. base Indicates the total load-bearing area of ​​the bridge foundation, in m 2 ; C p,f is the total surface pressure of the floating object at point f; ρ p represents the density of floating objects attached to the fth foundation point of the bridge, V p,f represents the volume of floating objects attached to the fth foundation point of the bridge; m represents the total number of foundation points of the bridge;

[0146] Among them, M j Indicates the bending moment at the f-th foundation point of the bridge, ΔH k Indicates the deviation of water level change at point f, E k It represents the elastic modulus of the f-th foundation point of the bridge body, in Pa;

[0147] The correlation unit is used to correlate the foundation bearing factor Qcya and the structural deformation factor Jzbx to obtain the bridge stress evaluation index Qzpg:

[0148]

[0149] Among them, σ safe Indicates the maximum design safety stress threshold of the bridge.

[0150] In this embodiment, the bridge body is divided into m basic points through networking, and each basic point is used to monitor the stress status of the bridge body. Through network monitoring technology, the density, volume information and other relevant bridge data of floating objects at each basic point can be obtained in real time. The stress conditions of these basic points are closely related to the changes in water level. The attachment of floating objects directly affects the buoyancy of the water body, which in turn affects the stress distribution of the bridge body and the water level changes. The floating object impact analysis module provides comprehensive data support for evaluating the safety of the bridge body under water level changes and the influence of floating objects by calculating the foundation bearing factor Qcya and the structural deformation factor Jzbx, as well as the bridge body stress assessment index Qzpg. The fluctuation of water level and the attachment of floating objects will jointly affect the stress condition of the bridge body, ultimately affecting the stability and safety of the bridge body. Through an effective stress assessment index, possible risks of the bridge body can be warned in advance to ensure the safety of the bridge structure.

[0151] Example 7

[0152] This example is explained in Example 6. Figure 1 ,Specifically, the water level correction module includes a correction unit and an ,evaluation module;

[0153] The correction unit is used to establish a water level correction model using a statistical method, and the water level height H of the i-th sub-area i , ship fluctuation factor Cbfx and floating object interference correction factor Pfgx, and the water level height of the ith sub-area is corrected by the following formula to obtain the corrected water level height of the ith sub-area

[0154]

[0155] Refer to the following chart:

[0156]

[0157] In this embodiment, the passage of ships causes water level fluctuations, particularly due to changes in ship draft, speed, and wave effects. The water level correction model corrects for the effects of these fluctuations on the water level by calculating the ship fluctuation factor. The presence of floating objects can alter the water's surface reflection and buoyancy, affecting the accuracy of water level data. The floating object interference correction factor compensates for these disturbances, ensuring accurate water level measurements.

[0158] Example 8

[0159] This example is explained in Example 7. Figure 1 ,Specifically, the evaluation module includes a first evaluation unit and a second evaluation unit;

[0160] The first evaluation unit is used to preset the water level safety threshold Swq, and the corrected water level height of the i-th sub-area Compare with the water level safety threshold Swq to obtain the first assessment result, including:

[0161] When the corrected water level height of the i-th sub-area When the water level exceeds the safety threshold Swq, it indicates that the water level in the sub-area is at risk of overflow and there is a risk of collision between ships passing through the bridge, and the first warning instruction is generated;

[0162] When the corrected water level height of the i-th sub-area When the water level is less than or equal to the water level safety threshold Swq, it means that there is no overflow risk in the sub-area and the water level is continuously monitored;

[0163] The second evaluation unit is used to preset a bridge stress risk threshold Qzy, compare the bridge stress evaluation index Qzpg with the bridge stress risk threshold Qzy, and obtain a second evaluation result, including:

[0164] When the bridge stress assessment index Qzpg and the bridge stress risk threshold Qzy are equal, it indicates that the buoyancy of the water and floating objects on the bridge increases, causing the risk of damage to the bridge structure, triggering the second warning instruction;

[0165] When the bridge stress assessment index Qzpg is equal to the bridge stress risk threshold Qzy, it means that the buoyancy of the water and floating objects on the bridge is within a safe range and there is no need to generate an early warning instruction.

[0166] In this embodiment, the assessment module dynamically monitors water levels and bridge structures through both water level safety assessments and bridge stress risk assessments, effectively providing early warnings of potential risks. The first assessment unit monitors water level changes and compares them with safety thresholds, issuing timely warnings of overflow risks and ship collisions. The second assessment unit, by assessing the stresses on the bridge structure, ensures structural stability and prevents damage from water and floating debris. Overall, this dual early warning mechanism provides reliable protection for water and bridge safety.

[0167] Example 9

[0168] This example is explained in Example 8. Figure 1 ,Specifically, the evaluation module also includes a first strategy unit and a second strategy unit;

[0169] The first strategy unit is used to receive the first warning instruction and generate the first control instruction, including: restricting the passage of ships, and reminding ship operators and bridge management departments through broadcasting or mobile phone text messages, requiring temporary suspension of navigation, and activating the emergency overflow channel to divert the water flow in the i-th sub-area until the corrected water level height of the i-th sub-area is reached. until;

[0170] The second strategy unit is used to receive the second early warning instruction and generate the second control instruction, including: setting the proportion of directing water flow to 20%-30% to the storage pool, dispatching the floating debris cleaning vessel on the water surface to clean up the floating debris affecting the bridge, and then directing the water flow stored in the pool back to the current sub-area waters, increasing the frequency of floating debris cleaning to 2-3 times a week, and reinforcing the fth point of bridge deformation with steel plates or steel beams.

[0171] In this embodiment, the policy unit effectively addresses issues such as overflow risks, ship collisions, floating debris impacts, and damage to bridge structures through two independent policy modules. The first policy unit effectively controls the risk of water level violations by promptly restricting ship traffic, activating overflow channels, and implementing water diversion measures. The second policy unit reduces the buoyancy of floating debris on the bridge and ensures its structural stability through measures such as debris removal and bridge reinforcement. Overall, these control measures enable dynamic management of water levels, ships, floating debris, and bridges, ensuring the safe operation of waterways and bridges.

[0172] Example 10, please refer to Figure 2 The water level monitoring and early warning method for monitoring the real-time height of the water surface under the bridge comprises the following steps:

[0173] Step 1: Divide the water surface area under the bridge into several sub-areas at equal intervals based on the number of bridge piers, set a monitoring point in each sub-area, monitor the water level in real time, and generate a first data set;

[0174] Step 2: Collect water flow velocity v w , sediment concentration C s , air pressure P atm and water temperature T w , generate environmental datasets;

[0175] Step 3: Monitor the characteristics of ships passing under the bridge, including ship size, speed, and the water level fluctuations caused by the ships. By linking the ship characteristic data with the environmental data set, the ship fluctuation factor Cbfx is generated.

[0176] Step 4: Monitor the quantity, distribution, and accumulation of floating debris in the sub-area and construct the floating debris obstruction factor Pfzd. Collect the density and volume of floating debris attached to the bridge, as well as bridge information, to establish a bridge stress data set to calculate the stress conditions at the bridge foundation points, including the foundation pressure factor Qcya and the structural deformation factor Jzbx. The foundation pressure factor Qcya and the structural deformation factor Jzbx are then correlated to generate the bridge stress assessment index Qzpg.

[0177] Step 5: Extract the water level H of the i-th sub-area i , ship fluctuation factor Cbfx, floating object interference correction factor Pfgx, establish the water level correction model and perform correction to obtain the corrected water level height of the i-th sub-area And preset the water level safety threshold Swq, when the corrected water level height of the i-th sub-area When the water level is higher than the safety threshold Swq, a first warning instruction is triggered, and a first control instruction is generated according to the first warning instruction;

[0178] Step 6: Preset the bridge stress risk threshold Qzy. If the bridge stress assessment index Qzpg is higher than the bridge stress risk threshold Qzy, trigger the second warning instruction, and generate the second control instruction according to the first warning instruction.

[0179] In this embodiment, the water level monitoring and early warning method establishes a precise water level correction and bridge stress assessment model by comprehensively monitoring multiple factors, such as water level, environmental data, ship fluctuations, and floating object interference. This model enables dynamic monitoring of the real-time height of the water surface beneath the bridge. First, based on equally spaced sub-area monitoring points, water level data can be collected in real time. Combined with environmental data and ship fluctuation factors, this method accurately corrects the water level to ensure it remains within a safe range. Second, the number, distribution, and accumulation of floating objects, as well as the density and volume of floating objects attached to the bridge, help accurately assess the stress conditions of the bridge and promptly identify potential structural risks. Furthermore, by linking water level data with bridge stress analysis, early warning instructions can be triggered, allowing for swift control measures, such as restricting ship traffic and activating emergency overflow channels, to ensure bridge safety. This integrated approach enhances the real-time monitoring capabilities of water level fluctuations and bridge safety, improves the efficiency of early warning and emergency response, and reduces the potential risk of overflow and the probability of structural damage.

[0180] The threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by technicians in this field for each set of sample data; as long as it does not affect the proportional relationship between the parameter and the quantized value.

[0181] The above formulas are obtained by collecting a large amount of data and performing software simulation, and a formula close to the actual value is selected. The coefficients in the formula are set by those skilled in the art according to actual conditions. The above is only a preferred specific implementation method of the present invention, but the protection scope of the present invention is not limited to this. Any technician familiar with this technical field, within the technical scope disclosed by the present invention, can make equivalent replacements or changes based on the technical solution and inventive concept of the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A water level monitoring and early warning system for monitoring the real-time height of the water surface under the bridge, characterized by: It includes water level monitoring module, environmental data acquisition module, ship dynamic identification module, floating object impact analysis module and water level correction module; The water level monitoring module is used to divide the water surface area under the bridge into several sub-areas, set a monitoring point in each sub-area, monitor and obtain the water level in real time, and generate a first data set; The environmental data acquisition module is used to collect water flow velocity , sediment concentration , air pressure and water temperature , generate environmental datasets; The ship dynamic identification module is used to monitor the characteristics of ships passing under the bridge, including ship size, speed and the water level fluctuations caused by the ship, and generate the ship fluctuation factor Cbfx through the linkage analysis of ship characteristic data and environmental data sets; The ship dynamic identification module includes a ship characteristic monitoring unit and a first analysis unit; The ship characteristic monitoring unit is used to install a laser ranging sensor in the monitoring point to monitor the ship's draft in real time. , ship speed , ship-induced wave height , generate ship characteristic dataset; The first analysis unit is used to analyze and calculate the ship fluctuation factor Cbfx based on the environmental data set and the ship characteristic data set; The specific calculation process of the ship fluctuation factor Cbfx is as follows: S11. Based on the ship's draft and ship speed , calculate the water level disturbance coefficient : in, The disturbance correction coefficient of the bridge structure is obtained by calibrating the experiment, simulating the influence of different speeds and sizes of ships on water disturbance, recording the amplitude of water level change, and using regression analysis to obtain ; Including: Under standard river conditions, when the ship length is 50 meters, the speed is 5m / s, the fluctuation amplitude is 10cm, and the fitting is 0.05; S12. Based on the height of waves caused by ships and water flow rate , calculate the corrected wave influence coefficient : in, is the correction coefficient of wave amplitude; by counting the wave height and water level changes caused by hundreds of ships passing under the bridge, is 1.2; S13. Extract sediment concentration measured by turbidity sensor from environmental dataset , calculate the water damping coefficient : in, is the sediment damping adjustment coefficient, including: when the sediment concentration is 0.5kg / m³, the wave damping effect is reduced by 20%, fitting is 2; S14. Extract air pressure from environmental dataset and water temperature , after dimensionless processing, the corrected external environment comprehensive influence coefficient is calculated by the following formula : in, is the meteorological adjustment factor, is the water reference temperature, set to 25°C; S15. Extract the water level disturbance coefficient obtained in S11-S14 , Corrected wave influence coefficient , water damping coefficient and corrected external environment comprehensive impact coefficient , after dimensionless processing, the ship fluctuation factor Cbfx is calculated by the following formula: Where, 、 、 and Represent the water level disturbance coefficients , Corrected wave influence coefficient , water damping coefficient and corrected external environment comprehensive impact coefficient The weight value of , , , ,and ; The floating debris impact analysis module is used to monitor the quantity, distribution, and accumulation of floating debris in the sub-area and construct a floating debris obstruction factor Pfzd. It also collects the density and volume information of floating debris attached to the bridge body, as well as bridge body information, to establish a bridge body force data set to calculate the force conditions of the bridge body foundation points, including the foundation pressure factor Qcya and the structural deformation factor Jzbx. The foundation pressure factor Qcya and the structural deformation factor Jzbx are then correlated to generate a bridge body stress assessment index Qzpg. The floating object impact analysis module includes a floating object monitoring unit and a second analysis unit; The floating object monitoring unit is used to install an infrared sensor at the monitoring point to monitor the heat reflection of floating objects on the water surface of the sub-area, use a camera to capture the water surface image of the sub-area, use image recognition technology to distinguish and track floating objects, extract the number, distribution and accumulation of floating objects, and obtain the floating object coverage area. Floating debris accumulation height and drift speed of floating objects ; The second analysis unit is used to extract the floating object coverage area Floating debris accumulation height and drift speed of floating objects , after dimensionless processing, the floating object occlusion factor Pfzd is calculated using the following formula: in, represents the total water surface area of ​​the sub-region; The floating object impact analysis module also includes a bridge monitoring unit, a bridge analysis unit and associated units; The bridge monitoring unit is used to divide the bridge into m bridge foundation points through networking, where m represents the total number of bridge foundation points; and collect the density and volume information of floating objects attached to the bridge as well as bridge information to establish a bridge force data set; The bridge analysis unit is used to calculate the stress conditions of the bridge foundation points based on the stress data set, and obtain the foundation bearing factor Qcya and the structural deformation factor Jzbx by the following formula: in, Indicates the static pressure at the f-th foundation point of the bridge body, in N. represents the density of water, g represents the acceleration due to gravity, Indicates the average water level height; represents the effective foundation area of ​​the f-th foundation point of the bridge body, Indicates the total load-bearing area of ​​the bridge foundation, in m 2 ; is the total surface pressure of the floating object at point f; represents the density of floating objects attached to the f-th foundation point of the bridge body, represents the volume of floating objects attached to the fth foundation point of the bridge; m represents the total number of foundation points of the bridge; in, represents the bending moment of the f-th foundation point of the bridge body, Indicates the deviation of the water level change at point f, It represents the elastic modulus of the f-th foundation point of the bridge body, in Pa; The correlation unit is used to correlate the foundation bearing factor Qcya and the structural deformation factor Jzbx to obtain the bridge stress evaluation index Qzpg: in, Indicates the maximum design safety stress threshold of the bridge; The water level correction module is used to extract the water level height of the i-th sub-area , ship fluctuation factor Cbfx, floating object interference correction factor Pfgx, establish the water level correction model and perform correction to obtain the corrected water level height of the i-th sub-area , and preset the water level safety threshold Swq, when the corrected water level height of the i-th sub-area When the water level exceeds the safety threshold Swq, the first warning instruction is triggered; The water level correction module includes a correction unit and an evaluation module; The correction unit is used to establish a water level correction model using a statistical method, and the water level height H of the i-th sub-area i , ship fluctuation factor Cbfx and floating object interference correction factor Pfgx, and the water level height of the ith sub-area is corrected by the following formula to obtain the corrected water level height of the ith sub-area : 。 2. The water level monitoring and early warning system for monitoring the real-time height of the water surface under the bridge according to claim 1 is characterized in that: The water level monitoring module includes a region division unit and a water level data aggregation unit; The area division unit is used to divide the water surface area under the bridge into several sub-areas at equal intervals according to the number of bridge piers, set a monitoring point in each sub-area, and deploy a water level sensor; The water level data aggregation unit is used to obtain the water level heights collected by the water level sensors in several sub-areas, generate a first data group, and after pre-processing the first data group, calculate the average water level height using the following formula : Where, represents the water level measured in the i-th sub-area, and n represents the number of sub-areas.

3. The water level monitoring and early warning system for monitoring the real-time height of the water surface under the bridge according to claim 1 is characterized in that: The environmental data set includes water velocity , sediment concentration , air pressure and water temperature ; The water flow rate Acquired by Doppler flow meter; The sediment concentration Obtained through turbidity sensor; The air pressure The data is collected by installing an air pressure sensor on the top of the bridge; The water temperature Used to install temperature sensor to measure water surface temperature to obtain.

4. The water level monitoring and early warning system for monitoring the real-time height of the water surface under the bridge according to claim 3 is characterized in that: The evaluation module includes a first evaluation unit and a second evaluation unit; The first evaluation unit is used to preset the water level safety threshold Swq, and the corrected water level height of the i-th sub-area Compare with the water level safety threshold Swq to obtain the first assessment result, including: When the corrected water level height of the i-th sub-area When the water level exceeds the safety threshold Swq, it indicates that the water level in the sub-area is at risk of overflow and there is a risk of collision between ships passing through the bridge, and the first warning instruction is generated; When the corrected water level height of the i-th sub-area When the water level is less than or equal to the water level safety threshold Swq, it means that there is no overflow risk in the sub-area and the water level is continuously monitored; The second evaluation unit is used to preset a bridge stress risk threshold Qzy, compare the bridge stress evaluation index Qzpg with the bridge stress risk threshold Qzy, and obtain a second evaluation result, including: When the bridge stress assessment index Qzpg and the bridge stress risk threshold Qzy are equal, it indicates that the buoyancy of the water and floating objects on the bridge increases, causing the risk of damage to the bridge structure, triggering the second warning instruction; When the bridge stress assessment index Qzpg is equal to the bridge stress risk threshold Qzy, it means that the buoyancy of the water and floating objects on the bridge is within a safe range and there is no need to generate an early warning instruction.

5. The water level monitoring and early warning system for monitoring the real-time height of the water surface under the bridge according to claim 4 is characterized in that: The evaluation module further includes a first strategy unit and a second strategy unit; The first strategy unit is used to receive the first warning instruction and generate the first control instruction, including: restricting the passage of ships, and reminding ship operators and bridge management departments through broadcasting or mobile phone text messages, requiring temporary suspension of navigation, and activating the emergency overflow channel to divert the water flow in the i-th sub-area until the corrected water level height of the i-th sub-area is reached. ≤water level safety threshold Swq; The second strategy unit is used to receive the second early warning instruction and generate the second control instruction, including: setting the proportion of directing water flow to 20%-30% to the storage pool, dispatching surface floating debris cleaning vessels to clean up floating debris affecting the bridge, and then directing the water flow stored in the pool back to the current sub-area waters, increasing the frequency of floating debris cleaning to 2-3 times a week, and reinforcing the fth point of bridge deformation with steel plates or steel beams.

6. A water level monitoring and early warning method for monitoring the real-time height of the water surface under a bridge, comprising the water level monitoring and early warning system for monitoring the real-time height of the water surface under a bridge as claimed in any one of claims 1 to 5, characterized in that: The following steps are involved: Step 1: Divide the water surface area under the bridge into several sub-areas at equal intervals based on the number of bridge piers, set a monitoring point in each sub-area, monitor the water level in real time, and generate a first data set; Step 2: Collect water flow velocity , sediment concentration , air pressure and water temperature , generate environmental datasets; Step 3: Monitor the characteristics of ships passing under the bridge, including ship size, speed, and the water level fluctuations caused by the ships. By linking the ship characteristic data with the environmental data set, the ship fluctuation factor Cbfx is generated. Step 4: Monitor the quantity, distribution and accumulation of floating objects in the sub-area and construct the floating object blocking factor Pfzd; The density and volume information of floating objects attached to the bridge body and bridge body information are collected to establish a bridge body force data set to calculate the force conditions of the bridge body foundation points, including the foundation pressure factor Qcya and the structural deformation factor Jzbx. The foundation pressure factor Qcya and the structural deformation factor Jzbx are then correlated to generate the bridge body stress assessment index Qzpg. Step 5: Extract the water level of the i-th sub-area , ship fluctuation factor Cbfx, floating object interference correction factor Pfgx, establish the water level correction model and perform correction to obtain the corrected water level height of the i-th sub-area , and preset the water level safety threshold Swq, when the corrected water level height of the i-th sub-area When the water level is higher than the safety threshold Swq, a first warning instruction is triggered, and a first control instruction is generated according to the first warning instruction; Step 6: Preset the bridge stress risk threshold Qzy. If the bridge stress assessment index Qzpg is higher than the bridge stress risk threshold Qzy, trigger the second warning instruction, and generate the second control instruction according to the first warning instruction.

Images