A water conservancy flood prevention early warning data real-time analysis processing method

Abstract

The present application relates to the technical field of flood prevention and early warning of water conservancy, and specifically discloses a real-time analysis and processing method for flood prevention and early warning data of water conservancy, which aims to improve the evaluation accuracy of the early warning system for flood threat and dam safety. The present application generates fluid density equivalent by fusing ultrasonic wave and dielectric constant data, calculates real-time physical dynamic pressure impact force in combination with water level and flow rate, which is different from the traditional evaluation mode that only relies on water level and flow rate. At the same time, internal pore water pressure and seepage acoustic energy in the dam body are collected to generate internal piping erosion equivalent, realizing quantitative tracking of internal hidden dangers. Further, an algebraic judgment matrix is constructed to generate multi-level alarm logic by comprehensively considering internal and external risk factors, which not only independently evaluates external impact and internal erosion, but also identifies extreme working conditions of the concurrent of the two, and sets a non-delayed highest level alarm channel. The present application enhances the predictability, pertinence and reliability of the early warning system, and improves the overall efficiency of the flood prevention and early warning system.

Description

Technical Field

[0001] This invention relates to the field of flood control and early warning technology, and more specifically, to a method for real-time analysis and processing of flood control and early warning data. Background Technology

[0002] Hydraulic structures, such as dikes and flood walls, are critical infrastructure for resisting floods and protecting lives and property. To ensure the safe operation of these structures, flood control early warning systems play a vital role. These systems monitor various physical parameters in real time, analyze potential risks, and issue warnings before danger occurs. The sophistication of the data processing and analysis methods used in these early warning systems directly determines the timeliness and accuracy of their warnings.

[0003] Patent CN119516714A discloses a disaster early warning and flood control platform and method for water conservancy scenic areas based on digital twins. The main solution is as follows: multiple types of data are collected from water conservancy scenic areas using sensors, and then water level, water flow velocity, rainfall, geology and facility availability indicators are calculated respectively. Based on these indicators, a digital twin model is constructed using 3D modeling software to simulate and calculate comprehensive environmental data indicators. Data indicators for a future period can be input to simulate future situations. Finally, a disaster early warning threshold is set, and the future comprehensive environmental data indicators are compared with it to determine whether an early warning is triggered. If triggered, an early warning information is generated and issued.

[0004] Patent CN117496667A discloses a method and system for flood control early warning monitoring based on multi-source information interaction, including the following steps: selecting the area to be monitored and establishing a multi-source information database; determining n monitoring points; setting up a monitoring device at each monitoring point; acquiring the water level data monitored by the monitoring device when it is in monitoring mode; acquiring real-time meteorological and hydrological data and predicted meteorological and hydrological data of the area to be monitored in real time; performing calculations based on the real-time meteorological and hydrological data, predicted meteorological and hydrological data, and water level data to obtain calculation results; comparing the calculation results with a preset threshold to obtain comparison results: if the threshold is exceeded, an early warning message is generated and issued in a predetermined manner; otherwise, monitoring of the area to be monitored continues.

[0005] The shortcomings of existing technologies are mainly reflected in the following three aspects: 1) The dimensions of external flood destructive force assessment are limited. Existing technologies mostly rely on conventional macroscopic hydrological parameters such as water level, flow velocity, and rainfall, or surface wireless signal attenuation characteristics, ignoring the problem of the actual physical dynamic water impact force increased due to the increase in fluid density under high sediment content conditions. This can easily lead to serious destructive force assessment bias when facing turbid floods; 2) There are blind spots and slow response in monitoring the safety status of the internal structure of the building. The comparative documents mostly focus on macroscopic geological settlement indicators, apparent water level mapping, or indirect structural surface echo disturbances. The dam lacks the ability to directly and dynamically quantify and track the early and localized micro-level progressive damage processes such as piping erosion and seepage erosion within the dam body, resulting in a serious lag in the discovery of internal hidden dangers; 3) The early warning decision-making and alarm logic is relatively rigid. Its alarm mechanism mostly relies on the simple weighted superposition of individual indicators, comparison of fixed physical thresholds, or statistical quantiles of data. It lacks a mechanism for deeply coupling and judging complex risk factors such as external dynamic water pressure and internal seepage erosion based on the principles of mechanical and physical evolution, making it difficult to make timely, accurate, and differentiated emergency linkage responses to extreme high-risk disaster scenarios where internal and external risks occur simultaneously. Summary of the Invention

[0006] In view of this, in order to solve the problems mentioned in the background technology, a method for real-time analysis and processing of flood control early warning data is proposed.

[0007] The objective of this invention can be achieved through the following technical solution: This invention provides a real-time analysis and processing method for flood control early warning data, including the following steps: S1, obtaining the ultrasonic amplitude attenuation coefficient and dielectric constant drift value of external floods and performing algebraic fitting to generate fluid density equivalent.

[0008] S2. Extract water level and flow velocity values ​​from conventional hydrological parameters, combine them with fluid density equivalent to perform momentum theorem calculations, and generate real-time physical dynamic pressure impact force.

[0009] S3. Collect the pore water pressure value and seepage acoustic frequency energy inside the dam body, extract the first derivative of the pore water pressure value and the low-frequency band energy definite integral value of the seepage acoustic frequency energy, and perform a product operation to generate the internal piping erosion equivalent.

[0010] S4. Couple and compare the real-time physical dynamic pressure impact force with the internal piping erosion equivalent input algebraic judgment matrix to generate the highest hazard level assessment command, and trigger the corresponding flood control alarm equipment according to the highest hazard level assessment command.

[0011] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects: (1) The present invention generates fluid density equivalent by integrating data from two physical dimensions, ultrasonic waves and dielectric constant, and then calculates the real-time physical dynamic pressure impact force that takes into account the turbidity of the flood. This changes the traditional mode of assessing the destructive power of external floods from relying solely on water level and flow velocity. The assessment results are closer to physical reality, thereby improving the accuracy of the early warning system in judging external threats.

[0012] This invention generates an internal piping erosion equivalent by simultaneously collecting pore water pressure and seepage acoustic energy inside the dam body and coupling the dynamic changes of these two micro-modal signals. This enables the quantification and dynamic tracking of structural hazards inside the dam body, allowing the early warning system to capture early signs of progressive internal damage such as piping and erosion, transforming passive response into proactive early warning and improving the system's predictability.

[0013] This invention constructs an algebraic judgment matrix coupled with internal and external risks and a multi-level alarm logic. It can not only provide independent graded alarms for external impacts and internal erosion, but also identify extreme dangerous conditions where the two risks occur simultaneously. It also sets up a zero-delay highest-level alarm channel. This refined and intelligent decision-making mechanism makes the issuance of early warning commands more targeted and reliable, avoids the limitations of single threshold judgment, and enhances the robustness and effectiveness of the entire flood prevention early warning system. Attached Figure Description

[0014] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0015] Figure 1 This is a schematic diagram of the method steps of the present invention. Detailed Implementation

[0016] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] Please see Figure 1 The present invention provides a method for real-time analysis and processing of flood control early warning data, including: S1, obtaining the ultrasonic amplitude attenuation coefficient and dielectric constant drift value of external flood and performing algebraic fitting to generate fluid density equivalent.

[0018] In a specific embodiment of the present invention, the process of obtaining the ultrasonic amplitude attenuation coefficient of the external flood and the dielectric constant drift value and performing algebraic fitting to generate the fluid density equivalent includes: transmitting ultrasonic signals to penetrate the external water body and receiving echo signals, extracting the energy attenuation amplitude of the echo signals, and generating the ultrasonic amplitude attenuation coefficient.

[0019] The capacitance change between the plates in the external water body is measured using a capacitive probe. The degree of dielectric polarization is calculated based on the capacitance change, and the dielectric constant drift value is generated.

[0020] The ultrasonic amplitude attenuation coefficient and dielectric constant drift value are input into a nonlinear algebraic fitting function for fusion calculation, and the mass concentration characterization value of suspended particles in the current water body is output to generate the fluid density equivalent.

[0021] In a specific embodiment of the present invention, the ultrasonic amplitude attenuation coefficient and the dielectric constant drift value are input into a nonlinear algebraic fitting function for fusion calculation, and the mass concentration characterization value of suspended particles in the current water body is output to generate a fluid density equivalent. This includes: obtaining the reference attenuation coefficient and reference dielectric constant under clear water conditions, and performing a differential operation between the ultrasonic amplitude attenuation coefficient and the reference attenuation coefficient to generate an acoustic attenuation increment.

[0022] The electromagnetic drift increment is generated by performing a differential operation between the dielectric constant drift value and the reference dielectric constant.

[0023] After assigning corresponding physical weighting coefficients to the acoustic attenuation increment and electromagnetic drift increment, an exponential function fitting operation is performed to generate the fluid density equivalent.

[0024] Specifically, this step aims to generate a key parameter, namely fluid density equivalent, that can characterize the turbidity and suspended matter content of floodwater by integrating the acoustic and electromagnetic properties of external floodwater.

[0025] The process begins by obtaining the ultrasonic amplitude attenuation coefficient of the flood. An underwater ultrasonic transmitter emits an ultrasonic signal with a preset initial amplitude. After penetrating the external water body, the signal's echo is captured by a synchronous receiver. Suspended particles in the water, such as sediment, scatter and absorb the ultrasonic waves, causing energy attenuation in the echo signal. By extracting the energy attenuation amplitude of the echo signal, the ultrasonic amplitude attenuation coefficient can be generated. The ultrasonic amplitude attenuation coefficient is a physical quantity that quantifies the degree of ultrasonic energy loss in a medium, and its value is closely related to the concentration and particle size distribution of suspended particles in the water. This coefficient can be calculated using the following formula: ; In this formula, This represents the amplitude of the echo signal detected by the receiver, measured in volts (V). This represents the amplitude of the original signal emitted by the transmitter, also measured in volts (V). This is an inherent parameter of the device. This represents the effective distance that ultrasound can travel in water, which is the fixed distance between the transmitter and receiver, and is measured in meters (m). This is the calculated ultrasonic amplitude attenuation coefficient, with dimensions of one part per meter. This reflects the signal amplitude attenuation rate per unit distance.

[0026] Simultaneously, the system utilizes a capacitive probe to measure the dielectric constant drift of the external water body. This probe consists of two parallel plates, submerged in floodwater. The dielectric constant of water changes due to variations in the type and concentration of dissolved salts and suspended particles. By measuring the change in capacitance between the plates, the probe can deduce the degree of polarization of the water body as a dielectric, thus generating the dielectric constant drift value. The dielectric constant drift value is a dimensionless parameter that measures the degree to which the dielectric properties of the current water body deviate from those of pure water. Its calculation formula is as follows: ; Here, It represents the dielectric constant drift value and is a dimensionless pure number. This represents the change in capacitance measured in real time by the capacitive probe, and the unit is farad (F). This represents the fixed distance between the two electrodes of the probe, in meters (m). Represents the effective area of ​​a single electrode plate, in square meters. ; The vacuum permittivity has a value of .

[0027] After obtaining the ultrasonic amplitude attenuation coefficient and dielectric constant drift values, they need to be compared with reference values ​​under clean water conditions to isolate the true changes caused by suspended particles. The system pre-stores reference attenuation coefficients and reference dielectric constants obtained through calibration tests on 200 sets of clean water samples from different sources. By performing a difference operation between the currently measured ultrasonic amplitude attenuation coefficient and the reference attenuation coefficient, an acoustic attenuation increment can be generated, which directly reflects the obstruction effect of suspended particles on sound wave propagation.

[0028] ; In the formula, Acoustic attenuation increment , The ultrasonic amplitude attenuation coefficient is measured in real time. , The preset reference attenuation coefficient .

[0029] Similarly, the measured dielectric constant drift value is differentially calculated with the reference dielectric constant to generate the electromagnetic drift increment, which reflects the influence of suspended matter on the macroscopic electromagnetic properties of the water body.

[0030] ; in, It is the electromagnetic drift increment (dimensionless). Real-time measured dielectric constant drift value (dimensionless). The preset reference dielectric constant (dimensionless).

[0031] Finally, the acoustic attenuation increment and electromagnetic drift increment are input into a nonlinear algebraic fitting function for fusion calculation, outputting the fluid density equivalent. This step is achieved by assigning corresponding physical weight coefficients to the acoustic attenuation increment and electromagnetic drift increment respectively, followed by exponential function fitting. The physical weight coefficients are determined based on multivariate regression analysis experiments on 150 flood samples with known different sediment contents, used to balance the sensitivity and contribution of the two measurement methods under different turbidity levels. The fluid density equivalent is a parameter characterizing the current suspended particle mass concentration in the water body and equating it to the increase in the overall fluid density. Its generation formula is: ; In this final formula, It is the density equivalent of the generated fluid, expressed in kilograms per cubic meter. ; It is the standard density of pure water, set as , It is the acoustic physics weighting coefficient, used to adjust the influence weight of acoustic attenuation increment. To ensure that the exponential part has one dimension, its unit is set to meter (m). It is an electromagnetic physics weighting coefficient, which is a dimensionless number; These are the acoustic attenuation increment and electromagnetic drift increment obtained from the aforementioned calculations, respectively; This is a natural constant. This exponential function form can effectively capture the nonlinear relationship between suspended solids concentration and two physical parameters, thereby accurately outputting the fluid density equivalent of the current water body.

[0032] It should be noted that, to ensure the engineering feasibility and full disclosure of the above nonlinear algebraic fitting model, the physical meaning, basis for value selection, and typical values ​​of the core preset parameters are clearly defined. The preset baseline attenuation coefficient... This represents the inherent background energy loss rate caused by the viscosity and thermal conduction of the water when ultrasound propagates in a pure, clear water medium free of suspended sediment. Under conditions where the system uses a commonly used 1MHz ultrasonic frequency for hydrological monitoring and is located at a normal temperature (approximately 20°C), its typical value is taken as... Preset reference dielectric constant Representing the inherent relative polarization of the clear water medium, it is used to establish the electromagnetic measurement reference zero point of "zero turbidity," and its typical value at room temperature is taken as [value missing]. In addition, acoustic physics weighting coefficients With electromagnetic physics weighting coefficient The values ​​are based on empirical constants obtained in advance through multivariate nonlinear regression analysis and hydraulic model calibration on a large database of flood samples with known sediment concentrations. These constants are used to balance the sensitivity and attenuation contribution of acoustic and electromagnetic physical parameters under different fluid turbidity conditions. In typical implementation conditions, The typical value is taken as This coefficient not only determines the amplification factor of the acoustic features, but also mathematically cancels out the spatial dimension of the attenuation increment to ensure that the power of the natural exponent is a dimensionless pure number; while The typical value is taken as The explicit assignment of the aforementioned preset parameters ensures that the system can accurately isolate the background interference of clear water and calculate the equivalent of fluid density change induced by suspended matter in floodwater in a realistic and reproducible manner.

[0033] For example, in a specific implementation scenario, the system performs step S1 as follows: A sensor deployed in the river channel begins to operate. The ultrasonic transmitter emits an amplitude of... The signal, after After the flood medium, the amplitude of the echo signal measured by the receiver is At this time, the ultrasonic amplitude attenuation coefficient It was calculated that: Therefore, the generated ultrasonic amplitude attenuation coefficient is Meanwhile, capacitive probes (electrode spacing) plate area The measured inter-plate capacitance value is Based on this, the dielectric constant drift value can be calculated. The generated dielectric constant drift value is The system retrieves a preset reference value, including the reference attenuation coefficient. reference dielectric constant Perform differential operations to generate acoustic attenuation increments. Generate electromagnetic drift increment Finally, the acoustic attenuation increment and electromagnetic drift increment are substituted into the fusion formula. The set physical weighting coefficient is... Density of clear water Calculate the equivalent fluid density. Ultimately, the system output fluid density equivalent is... This value will be used in subsequent calculations of the physical impact force of the flood.

[0034] S2. Extract water level and flow velocity values ​​from conventional hydrological parameters, combine them with fluid density equivalent to perform momentum theorem calculations, and generate real-time physical dynamic pressure impact force.

[0035] In a specific embodiment of the present invention, the water level height value and the water flow velocity value are extracted from conventional hydrological parameters, and the momentum theorem calculation is performed in combination with the fluid density equivalent to generate real-time physical dynamic pressure impact force. This includes: obtaining the liquid surface elevation data of the external water body to generate the water level height value, and obtaining the flow rate data of the external water body to generate the water flow velocity value.

[0036] The flow velocity value is squared to generate the squared value of the flow velocity. The squared value of the flow velocity is then multiplied by the fluid density equivalent to generate the fluid kinetic energy value per unit area.

[0037] The weighted summation of the fluid kinetic energy per unit area and the water level height is used to generate a real-time physical dynamic pressure impact force that characterizes the actual destructive capacity of external floods on structures.

[0038] Specifically, after obtaining the fluid density equivalent characterizing flood turbidity, this step aims to combine conventional hydrological observation data with fluid dynamics calculations to generate a parameter that can directly quantify the physical force exerted by the flood on the exterior of the structure, namely, real-time physical dynamic pressure impact force.

[0039] This process first requires acquiring two key conventional hydrological parameters of the external water body. Using radar level gauges or float-type level gauges installed at the monitoring section, the surface elevation data of the external water body can be continuously acquired; this data is directly used as the water level height value. Simultaneously, the flow velocity data of the water body is measured using equipment such as an acoustic Doppler current profiler; this data generates the water flow velocity value. The water level height value reflects the hydrostatic pressure potential generated by the flood due to its own gravity, while the water flow velocity value reflects the kinetic energy carried by the flood flow.

[0040] Next, to quantify the impact effect of the flood flow, the water velocity value needs to be squared to generate a squared velocity value. This squared velocity value is then multiplied by the fluid density equivalent generated in the previous step. This calculation generates the fluid kinetic energy per unit area, which physically corresponds to the fluid's dynamic pressure, i.e., the pressure generated entirely by the fluid's velocity. Its value directly reflects the intensity of the water flow impact. This relationship is expressed by the following formula:

[0041] In this formula, This represents the obtained water flow velocity value, in meters per second. ; The fluid density equivalent is calculated from step S1, in kilograms per cubic meter. ; This refers to the kinetic energy of the fluid per unit area generated, and its unit is Pascal. That is, Newtons per square meter Its dimensions are the same as those of pressure.

[0042] Ultimately, to obtain a comprehensive index reflecting the combined effect of hydrostatic pressure and dynamic impact force, a weighted summation of the fluid kinetic energy per unit area and the water level is required. This calculation is not a simple numerical addition, as it incorporates pressure from two different physical sources. The hydrostatic pressure represented by the water level needs to be converted to the same dimension as the fluid kinetic energy per unit area using a formula. Therefore, the final real-time physical dynamic impact force is a weighted combination of dynamic and static pressure, calculated using the following formula: ; In this formula, It is the final generated real-time physical dynamic pressure impact force, measured in Pascals. It comprehensively represents the total force exerted by external floods on a unit area of ​​a structure; This is the fluid kinetic energy per unit area calculated above. ; The obtained water level height value is in meters. ; fluid density equivalent ; This is the acceleration due to gravity, and its value is set to a standard value. . and These are dimensionless physical weighting coefficients, representing the contribution weights of dynamic pressure and static pressure to the total impact force, respectively. These two coefficients are derived from regression analysis of physical impact test data from 300 hydraulic models under different working conditions. Their setting is based on the fact that the dominant roles of dynamic and static pressure on structural damage differ under different flow regimes, and generally satisfy the following... The normalization relation is used to ensure the completeness of the physical meaning.

[0043] It should be noted that, to ensure the engineering feasibility of the above-mentioned weighted summation model of physical dynamic pressure impact force, the dimensionless physical weight coefficients are now adjusted. and The typical values ​​and their mechanical basis are clearly defined. In typical high-risk conditions of flood control (such as the passage of flood peaks during the flood season), water bodies often exhibit turbulent flow with high velocity and carrying large amounts of sediment. In this case, the instantaneous destructive force of the enormous kinetic energy carried by the flood flow on the water-facing structure usually exceeds the hydrostatic pressure generated solely by water level accumulation. Multivariate nonlinear regression analysis based on data from 300 hydraulic model physical impact experiments shows that under such dangerous flow conditions, the destructive contribution of dynamic pressure is dominant. Therefore, in a typical embodiment, the system will assign a weight representing the contribution of dynamic pressure to the dynamic pressure. A typical value is set to 0.6, which represents the weight of static pressure contribution. The typical value is set to 0.4. This set of values ​​not only strictly satisfies... The normalized mathematical relationship is accurately reproduced in a physical sense, and the comprehensive disaster-causing mechanical characteristics of "dynamic water dominance and static water superposition" during the flood peak impact period are accurately reproduced, so that the real-time physical dynamic pressure impact force parameters generated by the system have high engineering reference value.

[0044] For example, based on the calculation results of step S1, the current fluid density equivalent of the water body for Based on this, the implementation process of step S2 is as follows: The hydrological monitoring equipment collects the liquid level elevation data of the external water body and generates water level height values. Simultaneously, flow rate data is acquired, generating water flow velocity values. The system squares the water flow velocity value to generate the squared value of the flow velocity: Then, the square of the flow velocity is multiplied by the equivalent fluid density to generate the fluid kinetic energy per unit area. Finally, a weighted summation is performed. Based on the experimental calibration results, the physical weight coefficient set under the current operating conditions is: Substituting the fluid kinetic energy per unit area and the water level height into the formula, the real-time physical dynamic pressure impact force is calculated. Ultimately, the generated real-time physical dynamic pressure impact force, characterizing the actual destructive capacity of external floods on structures, is: This value will be used in subsequent external threat level assessments.

[0045] S3. Collect the pore water pressure value and seepage acoustic frequency energy inside the dam body, extract the first derivative of the pore water pressure value and the low-frequency band energy definite integral value of the seepage acoustic frequency energy, and perform a product operation to generate the internal piping erosion equivalent.

[0046] In a specific embodiment of the present invention, the pore water pressure value and seepage acoustic dominant frequency energy inside the dam body are collected, and the first derivative of the pore water pressure value and the low-frequency band energy definite integral value of the seepage acoustic dominant frequency energy are extracted and multiplied to generate the internal piping erosion equivalent. This includes: continuously collecting the acoustic modal signals generated by water flow friction inside the dam body through a pre-embedded high-frequency hydrophone, and performing spectrum analysis on the acoustic modal signals to generate the seepage acoustic dominant frequency energy.

[0047] The fluid dynamics mode signals in the soil pores inside the dam body are collected synchronously by a pore water pressure gauge to generate pore water pressure values.

[0048] The pressure drop rate is generated by taking the first derivative of the pore water pressure in the time dimension and taking its absolute value. The low-frequency band of the acoustic energy of seepage is integrated in the time dimension to generate the low-frequency energy integral value. The pressure drop rate value and the low-frequency energy integral value are multiplied by an algebraic equation to generate the internal piping erosion equivalent.

[0049] Specifically, this step aims to generate an indicator that can quantify the risk of internal seepage and erosion, namely the internal piping erosion equivalent, by monitoring microscopic fluid dynamics and acoustic changes within the dam body. This process does not rely on external observations but delves deep into the structure to capture early signals of progressive structural failure.

[0050] This process is achieved through two synchronously acquired internal modal signals. First, high-frequency hydrophones pre-embedded at key locations within the dam body continuously acquire acoustic modal signals generated by the friction and collision of internal water flow with soil particles. These weak acoustic signals carry crucial information about the formation and expansion of seepage channels. The acquired raw acoustic modal signals are time-domain waveforms, which need to be converted to the frequency domain using spectral analysis techniques, such as Fast Fourier Transform, to generate the dominant acoustic frequency energy of the seepage. The dominant acoustic frequency energy of the seepage is a function describing how acoustic energy is distributed across different frequencies, and its energy variation in specific frequency bands is directly related to the severity of internal erosion.

[0051] Secondly, by using pre-embedded pore water pressure gauges, hydrodynamic mode signals in the soil pores inside the dam body are simultaneously collected; these signals represent the pore water pressure value. The pore water pressure value reflects the seepage head at a specific location, and its stability is crucial for determining whether the seepage field inside the dam body is balanced. When piping or concentrated seepage occurs inside, the local hydraulic gradient changes drastically, causing abnormal fluctuations in the pore water pressure value.

[0052] After acquiring these two signals, the system performs a fusion calculation. First, the time-series data of the pore water pressure is differentiated in the time dimension, and its absolute value is taken. This operation generates the pressure drop rate value. The pressure drop rate value characterizes the drastic change in pore water pressure. A high pressure drop rate value usually indicates the sudden opening or blockage of internal seepage channels, and is a direct mechanical precursor to piping. Its calculation formula is: ; In this formula, Represents the passage of time The varying pore water pressure, expressed in Pascals. ; Time is measured in seconds (s). This is the generated pressure drop rate, measured in Pascals per second. .

[0053] Simultaneously, the system performs a time-dimensional definite integral calculation on the low-frequency band of the dominant acoustic energy of seepage. Based on the acoustic data analysis of 100 soil sample seepage failure experiments, it was found that low-frequency acoustic energy below 500 Hz has the strongest correlation with the overall movement of soil particles and the formation of cavities. Therefore, time integration of the energy in this low-frequency band can cumulatively reflect the total amount of structural erosion occurring over a period of time, generating a low-frequency energy integral value. The calculation formula is as follows: ; in, Represents time The total energy power of the percolation acoustic dominant frequency energy within the preset low-frequency band, expressed in watts (W). The time interval for integration is defined; This is the generated low-frequency energy integral value, in joules (J).

[0054] Finally, the pressure drop rate value and the low-frequency energy integral value are multiplied by an algebraic equation to generate the internal piping erosion equivalent. This multiplication operation couples the "instantaneous triggering" (drastic pressure change) and "cumulative effect" (acoustic energy accumulation) of the erosion event, thereby providing a more comprehensive risk assessment.

[0055] ; In this final formula, It is the equivalent of internal piping erosion generated, which is a calibrated dimensionless risk index; It is the pressure drop rate value ; It is the low-frequency energy integral value (J). This is a calibration coefficient whose function is to eliminate dimensions and convert the calculation results into a standardized risk index. This coefficient was determined through seepage failure experiments on a dam model and regression analysis with actual soil loss; its unit is per second (Pascal-joules). .

[0056] It should be noted that, to ensure the full disclosure and engineering feasibility of the internal piping erosion equivalent calculation model, the calibration coefficients are now... The physical meaning, basis for setting, and typical values ​​of the pressure drop rate are clearly explained. Since the pressure drop rate value characterizes the abrupt change in hydraulic gradient when a seepage channel partially becomes open (its dimension is...), the pressure drop rate is... The low-frequency energy integral value characterizes the energy accumulation of work done by water scouring and soil particle friction (its dimensions are...). The dimension of their product is . Essentially, it is a conversion constant reflecting the "vulnerability to seepage and erosion" of the materials used in a specific dam structure, and it is assigned a physical unit that is the reciprocal of the aforementioned product. This allows for the strict elimination of dimensions of relevant variables in mathematical calculations, seamlessly converting the product of physical quantities into a standardized dimensionless risk index. This coefficient is precisely determined in advance through multiple rigorous seepage failure (piping) experiments on a scaled-down model of a typical dam, and by performing multivariate nonlinear regression analysis on the product of the 'pressure-acoustic' signal characteristics acquired in real-time by sensors and the actual measured physical soil loss after the experiments. In a typical embodiment, for common earth-rock dam materials, the system will... The typical value is set to This value and dimension setting not only accurately closes the formula derivation mathematically, but also precisely builds a quantitative bridge between microscopic modal signal mutations and macroscopic soil loss and damage in terms of physical mechanisms, so that the final output erosion equivalent can truly and intuitively reflect the severity of the hidden danger of hollowing inside the dam body.

[0057] For example, in a scenario of safety monitoring inside a dam, the system executes step S3. At time point... At that time, the pore water pressure measured by a pore water pressure gauge is [value missing]. In the subsequent The pore water pressure measured by the pressure gauge suddenly dropped. The system calculates the pressure drop rate based on this. During the same time period, a high-frequency hydrophone acquired acoustic modal signals. Spectral analysis revealed a significant energy enhancement in the low-frequency band (set to 20Hz to 500Hz). Further analysis was conducted on the energy power of this frequency band... arrive The system calculates the low-frequency energy integral value through time-dimension definite integral operations. .

[0058] The system uses preset calibration coefficients. Substituting the pressure drop rate and low-frequency energy integral into the product algebraic equation, the equivalent of internal piping erosion is calculated. Ultimately, the generated internal piping erosion equivalent is 1. This dimensionless value will serve as a key basis for assessing the internal structural stability of the dam and for subsequent identification of internal hidden dangers.

[0059] S4. Couple and compare the real-time physical dynamic pressure impact force with the internal piping erosion equivalent input algebraic judgment matrix to generate the highest hazard level assessment command, and trigger the corresponding flood control alarm equipment according to the highest hazard level assessment command.

[0060] In a specific embodiment of the present invention, the real-time physical dynamic pressure impact force is coupled and compared with the internal piping erosion equivalent input algebraic judgment matrix to generate the highest hazard level assessment command, and the corresponding flood control alarm device is triggered according to the highest hazard level assessment command, including: obtaining the physical yield limit parameter of the structure design stage to generate a first threshold, comparing the real-time physical dynamic pressure impact force with the first threshold, and generating an external threat judgment mark.

[0061] In a specific embodiment of the present invention, the physical yield limit parameter obtained during the design phase of the structure is used to generate a first threshold. The real-time physical dynamic pressure impact force is compared with the first threshold to generate an external threat determination identifier, including: calculating the percentage value of the real-time physical dynamic pressure impact force to the first threshold and generating an external load rate.

[0062] It determines whether the external load rate is greater than the critical load ratio that indicates the structure is about to be damaged. If the external load rate is greater than the critical load ratio that indicates the structure is about to be damaged, an external limit trigger signal is generated and the external threat determination flag is set to "true".

[0063] If the external load rate is not greater than the critical load ratio that indicates the structure is about to be damaged, no external limit trigger signal will be generated, and the external threat judgment flag will be set to "false".

[0064] Based on the external over-limit trigger signal, a first-level alarm drive command is generated. The corresponding relay is closed by the first-level alarm drive command, triggering the first-level flood control alarm equipment to perform external physical blockage and audible and visual warning.

[0065] The maximum allowable erosion parameter under stable internal conditions of the dam body is obtained to generate a second threshold. The internal piping erosion equivalent is compared with the second threshold to generate an internal hidden danger judgment mark.

[0066] In a specific embodiment of the present invention, the maximum allowable erosion parameter under the stable state inside the dam body is obtained to generate a second threshold, and the internal piping erosion equivalent is compared with the second threshold to generate an internal hidden danger judgment mark, including: calculating the difference between the internal piping erosion equivalent and the second threshold to generate an internal erosion exceeding the limit deviation value.

[0067] If the internal erosion deviation value exceeds the safety margin value indicating a rapid deterioration of internal cavities, an internal erosion trigger signal is generated, and the internal hidden danger judgment flag is set to "true".

[0068] If the internal erosion deviation value does not exceed the safety margin value that characterizes the rapid deterioration of internal cavities, no internal cavitation trigger signal will be generated, and the internal hidden danger judgment mark will be set to "false".

[0069] Based on the internal hollowing trigger signal, a second-level alarm drive command is generated. The second-level alarm drive command is used to activate the directional broadcasting equipment, which in turn triggers the second-level flood control alarm equipment to broadcast personnel evacuation information.

[0070] The external threat assessment identifier and the internal hidden danger assessment identifier are input into the algebraic judgment matrix and logically ANDed to generate the highest hazard level assessment instruction. Based on the highest hazard level assessment instruction, a hard-wired drive level is sent to the edge alarm controller to trigger the corresponding flood control alarm device.

[0071] In a specific embodiment of the present invention, the external threat determination identifier and the internal hidden danger determination identifier are input into an algebraic determination matrix and subjected to a logical AND operation to generate a highest risk level assessment instruction. Specifically, when the external threat determination identifier is set to "true" and the internal hidden danger determination identifier is set to "true", a highest risk level assessment instruction is generated.

[0072] In a specific embodiment of the present invention, a hard-wired drive level is sent to the edge alarm controller according to the highest hazard level assessment instruction to trigger the corresponding flood control alarm device, including: extracting the duration parameter of the real-time physical dynamic pressure impact force to generate a high-level holding time value, and performing time-dimensional derivative calculation on the internal piping erosion equivalent to generate an erosion deterioration rate value.

[0073] Determine whether the high-level holding time value is greater than the external continuous pressure time threshold, and whether the erosion and deterioration rate value shows a positive sudden increase trend, to generate a high-risk signal of external pressure and internal erosion superposition.

[0074] Based on the superposition of external pressure and internal scouring high-risk signals, the highest-level alarm drive command is generated. The highest-level alarm drive command ignores the graded confirmation delay and directly triggers the whole basin dam failure flood control alarm equipment.

[0075] Specifically, this step is the core of the entire decision-making and response system. It inputs the external and internal analysis parameters generated in the previous steps, namely the real-time physical dynamic pressure impact force and the internal piping erosion equivalent, into an algebraic judgment matrix for coupling and comparison, and finally generates a hazard level assessment instruction for driving flood control equipment.

[0076] The process begins with an independent assessment of external threats. The system acquires the physical yield limit parameters of the structure, determined during the design phase based on materials mechanics and structural engineering calculations, and uses this as the first threshold. The real-time physical dynamic pressure impact force generated in step S2 is compared with this first threshold to generate a Boolean-type external threat assessment indicator, used to preliminarily determine whether the external load constitutes a threat. To achieve tiered early warning, the system calculates the percentage of the real-time physical dynamic pressure impact force relative to the first threshold, generating the external load factor.

[0077] ; In this formula, It is the real-time physical dynamic pressure impact force, and the unit is Pascal. ; It is the physical yield limit parameter that serves as the first threshold, and its unit is also Pascal. ; This refers to the generated external load factor, which is a dimensionless percentage value.

[0078] Subsequently, the system determines whether the external load rate exceeds the critical load ratio that indicates the structure is about to be damaged. This critical load ratio is set according to structural safety codes, typically ranging from 70% to 90%, with a typical value of 85%. If the external load rate exceeds the critical load ratio that indicates the structure is about to be damaged, an external limit trigger signal is generated. Based on the external limit trigger signal, the system generates a first-level alarm drive command. This command closes the corresponding relay through a hardwired level signal, thereby triggering the first-level flood control alarm equipment, such as initiating the closing procedure of the floodgate or illuminating a high-intensity audible and visual warning light.

[0079] In parallel, the system assesses internal hazards. The system obtains the maximum permissible erosion parameter determined through geotechnical tests and historical data analysis under long-term stable operation of the dam body, and uses this as a second threshold. The internal piping erosion equivalent generated in step S3 is compared with the second threshold to generate an internal hazard assessment indicator. To assess the severity of the hazard, the system calculates the difference between the internal piping erosion equivalent and the second threshold, generating an internal erosion exceedance deviation value.

[0080] ; Here, It is the internal piping erosion equivalent (dimensionless). It is the maximum permissible erosion parameter (dimensionless) used as the second threshold. This is the internal erosion deviation value (dimensionless) generated.

[0081] Next, the system determines whether the internal erosion exceedance value exceeds the safety margin value representing a rapid deterioration of internal cavities. This safety margin value is set based on a conservative estimate of the erosion resistance of the dam material. If the internal erosion exceedance value exceeds the safety margin value representing a rapid deterioration of internal cavities, an internal erosion trigger signal is generated. Based on this internal erosion trigger signal, the system generates a second-level alarm drive command. This command activates the directional broadcasting equipment via the bus communication protocol, triggering the second-level flood control alarm equipment to broadcast personnel evacuation instructions to the specific area.

[0082] The final decision is made within an algebraic decision matrix. The core logic of this matrix is ​​to perform a logical AND operation between external threat assessment indicators and internal hazard assessment indicators. Only when both are true will a highest-risk level assessment instruction be generated.

[0083] In addition, to cope with the extreme danger of simultaneous external high pressure and internal erosion, the system also includes an emergency response mechanism. The system extracts the duration parameter of the real-time physical dynamic pressure impact force maintained at a high level, generates a high-level maintenance time value, and performs derivative calculation on the time series of internal piping erosion equivalent to generate an erosion deterioration rate value.

[0084]

[0085] in, It is the time-varying internal piping erosion equivalent. This is the rate of erosion and deterioration, expressed in fractions of a second. .

[0086] The system determines whether the high-pressure holding time exceeds the external continuous pressure time threshold set based on the fatigue resistance characteristics of the structure, and simultaneously determines whether the erosion deterioration rate shows a positive sudden increase. If both conditions are met, a high-risk signal of external pressure and internal erosion superposition is generated. Based on this high-risk signal, the system generates the highest-level alarm drive command. This command ignores any graded confirmation delay and directly triggers the basin-wide dam-break flood control alarm equipment through a dedicated hard-wired drive level.

[0087] It should be noted that, to ensure the reliability and full disclosure of the multidimensional safety assessment model, the physical meaning and basis for the various judgment thresholds and safety margins set by the system are now clearly defined. First, the physical yield limit parameter, which serves as the first threshold... Typical value set to This value represents the upper limit of the combined physical impact force of external dynamic and static water pressure that the water-facing surface of the structure can withstand before the initiation of micro-cracks. Secondly, the typical value of the external continuous pressure time threshold, set according to the fatigue resistance characteristics of the structure, is 15 minutes. This value is based on the low-cycle fatigue characteristics of hydraulic structures under long-term flood peak loads and the softening creep model of saturated soil, representing the time limit boundary of the dam structure under high-intensity continuous pressure without irreversible plastic deformation. Thirdly, the maximum allowable erosion parameter serves as the second threshold. The typical value is set at 1.5. This value is determined based on the critical hydraulic gradient theory and experimental analysis of piping evolution, representing the critical equivalent index limit at which fine particles inside the dam are continuously eroded and lost until a penetrating seepage channel (i.e., piping failure) is triggered. Finally, the typical safety margin of the system is set at 0.2. This margin value is based on a conservative estimate of the erosion resistance of the dam material, and it is in accordance with the reliability specifications for geotechnical engineering disaster prevention design. It fully compensates for unmodeled hidden uncertainties such as aging reduction caused by long-term service of the dam and material heterogeneity. By introducing this safety margin to defensively shrink the absolute physical limit, it ensures that the system can trigger alarms in advance and reserve sufficient emergency response time for flood control and disaster relief before the structure truly reaches the physical failure threshold.

[0088] For example, based on the calculation results of the aforementioned steps, the real-time physical dynamic pressure impact force Internal piping erosion equivalent The system begins executing step S4. First, an external threat assessment is performed. The physical yield limit parameters from the structure design phase are acquired, generating a first threshold. The system calculates the external load factor. The set critical load ratio is 85%. Since 33.5% is not greater than 85%, no external over-limit trigger signal is generated, and the external threat judgment flag is set to "false".

[0089] Simultaneously, an internal hazard assessment was conducted. The maximum permissible erosion parameter obtained under the stable state of the dam body was used as the second threshold. The system calculates the internal erosion exceeding the limit deviation value. The set safety margin value is 0.2. Because... Since the value is less than 0.2, no internal cavitation trigger signal is generated, and the internal hidden danger judgment mark is set to "false".

[0090] Subsequently, the two judgment indicators are input into the algebraic judgment matrix for logical AND operation: Since the external threat judgment indicator is set to "false" and the internal hidden danger judgment indicator is set to "false", no highest risk level assessment instruction is generated.

[0091] Now, considering a worsening scenario to illustrate the emergency response mechanism, let's generate a highest-risk assessment instruction. Assume that in subsequent monitoring, the real-time physical dynamic pressure impact force rises to... And it has been going on Minutes. Meanwhile, the internal piping erosion equivalent value in the previous minute was... The current value is The system's set threshold for continuous external pressure is 15 minutes. The system determines the high-level holding time value: This condition is met. The system calculates the erosion degradation rate. The value is positive, indicating that erosion is accelerating and showing a positive surge trend, and this condition is also met. Since the two emergency conditions are met simultaneously, the system generates a high-risk signal of external pressure and internal erosion superposition, and generates the highest-level alarm drive command based on this signal, ignoring the graded confirmation delay, and directly triggering the basin-wide dam-break flood control alarm equipment.

[0092] The above content is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, and all such modifications and additions should fall within the protection scope of the present invention.

Claims

1. A method for real-time analysis and processing of flood control early warning data, characterized in that, Includes the following steps: S1. Obtain the ultrasonic amplitude attenuation coefficient and dielectric constant drift value of the external flood and perform algebraic fitting to generate the fluid density equivalent; S2. Extract water level and flow velocity values ​​from conventional hydrological parameters, combine them with fluid density equivalent to perform momentum theorem calculations, and generate real-time physical dynamic pressure impact force. S3. Collect the pore water pressure value and seepage acoustic frequency energy inside the dam body, extract the first derivative of the pore water pressure value and the low-frequency band energy definite integral value of the seepage acoustic frequency energy, and perform a product operation to generate the internal piping erosion equivalent. S4. Couple and compare the real-time physical dynamic pressure impact force with the internal piping erosion equivalent input algebraic judgment matrix to generate the highest hazard level assessment command, and trigger the corresponding flood control alarm equipment according to the highest hazard level assessment command.

2. The method for real-time analysis and processing of flood control early warning data according to claim 1, characterized in that, The process of algebraically fitting the ultrasonic amplitude attenuation coefficient and dielectric constant drift value of the acquired external flood to generate the fluid density equivalent includes: The ultrasonic signal is emitted to penetrate the external water body and the echo signal is received. The energy attenuation amplitude of the echo signal is extracted to generate the ultrasonic amplitude attenuation coefficient. The capacitance change between the plates in the external water body is measured using a capacitive probe. The degree of dielectric polarization is calculated based on the capacitance change, and the dielectric constant drift value is generated. The ultrasonic amplitude attenuation coefficient and dielectric constant drift value are input into a nonlinear algebraic fitting function for fusion calculation, and the mass concentration characterization value of suspended particles in the current water body is output to generate the fluid density equivalent.

3. The method for real-time analysis and processing of flood control early warning data according to claim 2, characterized in that, The process of inputting the ultrasonic amplitude attenuation coefficient and the dielectric constant drift value into a nonlinear algebraic fitting function for fusion calculation, outputting the mass concentration characterization value of suspended particles in the current water body, and generating the fluid density equivalent includes: Obtain the reference attenuation coefficient and reference dielectric constant under clear water conditions, and perform differential calculation between the ultrasonic amplitude attenuation coefficient and the reference attenuation coefficient to generate the acoustic attenuation increment. The electromagnetic drift increment is generated by performing a differential operation between the dielectric constant drift value and the reference dielectric constant. After assigning corresponding physical weighting coefficients to the acoustic attenuation increment and electromagnetic drift increment, an exponential function fitting operation is performed to generate the fluid density equivalent.

4. The method for real-time analysis and processing of flood control early warning data according to claim 1, characterized in that, The process of extracting water level and flow velocity values ​​from conventional hydrological parameters, combining them with fluid density equivalents to perform momentum theorem calculations, and generating real-time physical dynamic pressure impact force includes: The system acquires the surface elevation data of the external water body to generate the water level height value, and acquires the flow rate data of the external water body to generate the water flow velocity value. The flow velocity value is squared to generate the flow velocity square value. The flow velocity square value is then multiplied by the fluid density equivalent to generate the fluid kinetic energy value per unit area. The weighted summation of the fluid kinetic energy per unit area and the water level height is used to generate a real-time physical dynamic pressure impact force that characterizes the actual destructive capacity of external floods on structures.

5. The method for real-time analysis and processing of flood control early warning data according to claim 1, characterized in that, The method involves collecting the pore water pressure and seepage acoustic frequency energy inside the dam body, extracting the first derivative of the pore water pressure and the definite integral of the low-frequency band energy of the seepage acoustic frequency energy, and multiplying them to generate the internal piping erosion equivalent, including: The acoustic modal signals generated by the friction of water flow inside the dam are continuously collected by the pre-embedded high-frequency hydrophones, and the spectrum analysis of the acoustic modal signals is performed to generate the seepage acoustic main frequency energy. The fluid dynamic mode signals in the soil pores inside the dam body are collected synchronously by a pore water pressure gauge to generate pore water pressure values. The pressure drop rate is generated by taking the first derivative of the pore water pressure in the time dimension and taking its absolute value. The low-frequency band of the acoustic energy of seepage is integrated in the time dimension to generate the low-frequency energy integral value. The pressure drop rate value and the low-frequency energy integral value are multiplied by an algebraic equation to generate the internal piping erosion equivalent.

6. The method for real-time analysis and processing of flood control early warning data according to claim 1, characterized in that, The process of coupling and comparing real-time physical dynamic pressure impact force with the internal piping erosion equivalent input algebraic judgment matrix to generate a highest hazard level assessment command, and triggering the corresponding flood control alarm equipment based on the highest hazard level assessment command, includes: The physical yield limit parameters of the structure during the design phase are obtained to generate a first threshold. The real-time physical dynamic pressure impact force is compared with the first threshold to generate an external threat judgment mark. The maximum allowable erosion parameter under stable internal conditions of the dam body is obtained to generate a second threshold. The internal piping erosion equivalent is compared with the second threshold to generate an internal hidden danger judgment mark. The external threat assessment identifier and the internal hidden danger assessment identifier are input into the algebraic judgment matrix and logically ANDed to generate the highest hazard level assessment instruction. Based on the highest hazard level assessment instruction, a hard-wired drive level is sent to the edge alarm controller to trigger the corresponding flood control alarm device.

7. The method for real-time analysis and processing of flood control early warning data according to claim 6, characterized in that, The process involves obtaining the physical yield limit parameters from the structure design phase to generate a first threshold, comparing the real-time physical dynamic pressure impact force with the first threshold, and generating an external threat determination indicator, including: Calculate the percentage of real-time physical dynamic pressure impact force relative to the first threshold to generate the external load rate; Determine whether the external load rate is greater than the critical load ratio that indicates the structure is about to be damaged. If the external load rate is greater than the critical load ratio that indicates the structure is about to be damaged, generate an external limit trigger signal and set the external threat judgment flag to "true". If the external load rate is not greater than the critical load ratio that indicates the structure is about to be damaged, no external limit trigger signal will be generated, and the external threat judgment flag will be set to "false". Based on the external over-limit trigger signal, a first-level alarm drive command is generated. The corresponding relay is closed by the first-level alarm drive command, triggering the first-level flood control alarm equipment to perform external physical blockage and audible and visual warning.

8. The method for real-time analysis and processing of flood control early warning data according to claim 7, characterized in that, The process involves obtaining the maximum permissible erosion parameter under stable internal conditions of the dam body to generate a second threshold, comparing the internal piping erosion equivalent with the second threshold, and generating an internal hidden danger assessment indicator, including: Calculate the difference between the internal piping erosion equivalent and the second threshold to generate the internal erosion exceedance deviation value; Determine whether the internal erosion exceedance deviation value is greater than the safety margin value that indicates the rapid deterioration of internal cavities. If the internal erosion exceedance deviation value is greater than the safety margin value that indicates the rapid deterioration of internal cavities, generate an internal cavitation trigger signal and set the internal hidden danger judgment flag to "true". If the internal erosion deviation value is not greater than the safety margin value that characterizes the rapid deterioration of internal cavities, no internal cavitation trigger signal will be generated, and the internal hidden danger judgment mark will be set to "false". Based on the internal hollowing trigger signal, a second-level alarm drive command is generated. The second-level alarm drive command is used to activate the directional broadcasting equipment, which in turn triggers the second-level flood control alarm equipment to broadcast personnel evacuation information.

9. A method for real-time analysis and processing of flood control early warning data according to claim 8, characterized in that, The step of inputting the external threat determination identifier and the internal hidden danger determination identifier into the algebraic determination matrix for logical AND operation to generate the highest risk level assessment instruction is as follows: when the external threat determination identifier is set to "true" and the internal hidden danger determination identifier is set to "true", the highest risk level assessment instruction is generated.

10. A method for real-time analysis and processing of flood control early warning data according to claim 9, characterized in that, The step of sending a hard-wired drive level to the edge alarm controller based on the highest hazard level assessment command to trigger the corresponding flood control alarm device includes: The duration parameter of real-time physical dynamic pressure impact force is extracted to generate a high-level holding time value, and the time dimension derivative of the internal piping erosion equivalent is calculated to generate an erosion deterioration rate value. Determine whether the high-level holding time value is greater than the external continuous pressure time threshold, and whether the erosion deterioration rate value shows a positive sudden increase trend, to generate a high-risk signal of external pressure and internal erosion superposition; Based on the superposition of external pressure and internal scouring high-risk signals, the highest-level alarm drive command is generated. The highest-level alarm drive command ignores the graded confirmation delay and directly triggers the whole basin dam failure flood control alarm equipment.

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