CN117152935A - Tunnel flood early warning system and method based on fluid three-dimensional dynamic simulation - Google Patents
Tunnel flood early warning system and method based on fluid three-dimensional dynamic simulation Download PDFInfo
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Abstract
The invention discloses a tunnel flood early warning system based on fluid three-dimensional dynamic simulation, which comprises: the data processing module is used for storing the water inlet rate model; the model module is used for storing a slice model set of the tunnel water level rising simulation; the prediction module is used for acquiring future rain intensity, calculating water inflow rate and calling a water level rising simulation slice model; the display module is used for displaying the three-dimensional water level simulation video of the tunnel; and the emergency processing module is used for judging the risk level and outputting an emergency plan. The invention has high early warning accuracy, long time effect and timeliness. The utility model discloses a tunnel flood early warning method, which comprises the following steps: establishing and storing a water inlet rate model and a slice model set of a tunnel water level rising simulation; obtaining future rain intensity and predicting V Feeding in The water inflow and the water level depth are used for calling a water level rising simulation slice model; forming and outputting a three-dimensional water level simulation video of the tunnel; discriminating riskGrade and output emergency plans.
Description
Technical Field
The invention relates to the field of tunnel flood disaster early warning. More particularly, the invention relates to a tunnel flood early warning system and method based on three-dimensional dynamic simulation of fluid.
Background
In recent years, highways continue to extend to mountains, cross over the steep mountains, and the bridge-to-tunnel ratio continues to climb. The long tunnel plays an important role in province and province, and city, and plays a very positive role in reducing urban road land, shortening driving mileage and developing urban economy.
The long-distance tunnels between cities are also traffic tunnels, and the passing frequency is high, but because the tunnels are generally low in topography and large in gradient, when urban inland inundation occurs in extreme weather, rainwater on roads is easy to collect and flow into the tunnels, and the tunnels become the earliest and deepest places of accumulated water, so that normal traffic is seriously influenced, and unexpected losses and disasters are extremely easy to cause.
In recent years, extreme weather is frequent, the situation that severe flood disasters encounter heavy rain weather is more serious than before, and extremely heavy rain often causes severe ponding of tunnels, so that the instantaneous water quantity rises rapidly. How to perform flood warning and disposal on an active operation tunnel or a newly built tunnel is very important.
The long-distance tunnel is deep and long, and under the existing technical conditions, the early warning accuracy of the long-distance tunnel for flood control and drainage is low, early warning time is short, related equipment is often required to be executed after disasters occur, emergency hysteresis is caused, and how to improve pertinence, timeliness, channels and means of the early warning information of the long-distance tunnel is researched, so that the long-distance tunnel has important economic value and social value.
Disclosure of Invention
It is an object of the present invention to solve at least the above problems and to provide at least the advantages to be described later.
To achieve these objects and other advantages and in accordance with the purpose of the invention, there is provided a tunnel flood warning system based on a fluid three-dimensional dynamic analog simulation, comprising:
a data processing module for storing a water intake rate model, the water intake rate model being as shown in equations 1 and 2:
when RZ is<RZ 0 V at the time of Feeding in ＝V 0 +α×RZ+V 3 +V 4 -V 5 The method comprises the steps of carrying out a first treatment on the surface of the Equation 1
When RZ is greater than or equal to RZ 0 V at the time of Feeding in ＝V 0 +α×RZ+β×RZ+V 3 +V 4 -V 5 The method comprises the steps of carrying out a first treatment on the surface of the Equation 2
Wherein RZ is rain intensity, alpha is an internal inflow rate parameter, beta is an external inflow rate parameter, V 0 RZ is the average fixed leak rate of the tunnel 0 Is the threshold of rain intensity, V 3 For the water inflow rate of fire-fighting water, V 4 V is the abnormal water inflow rate 5 Is the tunnel drainage rate, wherein alpha, beta, V 0 And RZ 0 Based on historical water inflow data and historical water drainage data of the tunnel, statistical analysis is carried out to obtain;
the model module is used for storing a slice model set of the tunnel water level rising simulation, each slice model takes water as fluid, water level depth as an identifier, the state of accumulated water in the tunnel and corresponding key factor parameter information are displayed, each slice model is provided with a unique configuration number, and the water level depth is calculated by water inflow and tunnel volume;
the prediction module is used for acquiring the rain intensity RZ, the water inflow rate of fire-fighting water, the abnormal water inflow rate and the tunnel water drainage rate in a future period of time, and calling the water inflow rate model to calculate and obtain the water inflow rate V in the future period of time based on the rain intensity RZ Feeding in Calculating the water inflow rate to obtain the water inflow and the tunnel water level depth in a future period, and calling a slice model and key factor parameter information corresponding to configuration numbers corresponding to the water level depth one by one to form a predicted water level rising simulation slice model;
the display module is used for outputting and obtaining tunnel slice models which are arranged in sequence according to the time axis by taking the time as the x axis, and simultaneously displaying the parameter information of the corresponding key factors to form a three-dimensional tunnel water level simulation video;
the emergency processing module is used for statistically analyzing the tunnel flooding time and the predicted flood drainage completion time, presetting a risk level discrimination rule and an emergency plan, and outputting the emergency plan according to the discrimination result of the risk level discrimination rule.
Preferably, the tunnel history water inflow data comprises tunnel water inflow Q of a non-rainfall period Feeding in The water inflow of the tunnel is the inherent leakage Q of the tunnel 0 The tunnel history drainage data includes the tunnel drainage quantity Q of the non-rainfall period Row of rows The data processing module obtains a parameter V based on the statistical analysis fitting of formulas 1, 3-5 0 Is a value of (2);
Q feeding in ＝Q Row of rows Equation 3
Q Feeding in ＝Q 0 Equation 4
V Feeding in ＝Q Feeding in /t Row of rows Equation 5.
Preferably, the historical water inflow data of the tunnel comprises rain intensity RZ, rainfall time and tunnel water inflow Q in the rainfall period Feeding in The tunnel inflow is tunnel fixationWith leakage Q 0 Fixed inflow Q of rainwater 1 External inflow quantity Q of rainwater 2 The tunnel history drainage data comprises the tunnel drainage quantity Q in the rain-down period Row of rows ；
The data processing module is used for carrying out statistical analysis based on a formula 1, and obtaining a parameter RZ when the water inflow rate is increased and the corresponding rain intensity is high 0 Is a value of (2);
selecting rain intensity RZ<RZ 0 The data processing module obtains the value of the parameter alpha by statistical analysis fitting based on a formula 1;
selecting rain intensity RZ>RZ 0 The data processing module obtains the value of the parameter beta based on the statistical analysis fitting of the formula 2.
Preferably, the system further comprises a terminal acquisition device for acquiring historical water inflow data and historical water drainage data of the tunnel, wherein the terminal acquisition device comprises:
the rainfall gauge is used for collecting rainfall and rainfall time in real time, calculating and outputting a real-time rainfall intensity average value RZ, and storing the real-time rainfall intensity average value RZ to obtain historical rainfall intensity data RZ;
the fire control pipeline flowmeter is used for detecting the flow of the fire control water pipeline, and the data processing module calculates the fire control water inflow rate V based on the flow of the fire control water pipeline 3 ；
A liquid level gauge for detecting a liquid level rise value and a rise time, the data processing module calculating a liquid level rise speed V based on the liquid level rise value and the rise time Lifting device And calculating an abnormal water inflow rate V using equation 6 4 ；
V 4 ＝V Lifting device X S formula 6
S is the cross section area of a pump room water gauge;
the drainage pipeline flowmeter and the drainage pump flowmeter are used for collecting drainage amount, counting total flow of each pump, and calculating actual drainage rate V of the water pump by the drainage amount and the total flow of each pump Pump with a pump body The data processing module calculates the tunnel drainage rate V by adopting a formula 7 5 ；
V 5 ＝n×V Pump with a pump body Equation 7
Wherein n is the actual running number of the water pump, V Pump with a pump body Is the actual water discharge rate of the water pump.
Preferably, the device further comprises a device operation situation monitoring device, which comprises:
the active electronic tags are arranged on the water pump and the distribution box and are used for monitoring and storing the voltage and current parameter values of the outlet wire of the distribution box and the temperature of the inlet wire cable in real time, and monitoring the on-off position state and the tripping condition of the switch and the running flow, the lift, the shaft power and the specific rotation number of the water pump equipment in real time;
the system comprises a plurality of pairs of master radio frequency modules and slave radio frequency modules, wherein the master radio frequency modules and the slave radio frequency modules are arranged on the top of a tunnel at intervals, and the master radio frequency modules and the slave radio frequency modules are used for identifying data information of active electronic tags of a pump room and a power distribution room within the radiation range of an antenna and realizing double-channel data communication of an RFID system;
the ZigBee terminal node is connected with the master radio frequency module and the slave radio frequency module through wireless, and is used for receiving data information of the active electronic tag transmitted by the master radio frequency module and the slave radio frequency module and simultaneously transmitting a control command back to the master radio frequency module and the slave radio frequency module;
the ZigBee coordinator node is in wireless connection with the ZigBee terminal node, and is used for receiving data information sent by the ZigBee terminal node and simultaneously returning a control command to the ZigBee terminal node;
the PC upper computer is connected with the ZigBee coordinator node through the local area network, is used for receiving data information sent by the ZigBee coordinator node, judging the running states of the distribution box and the water pump according to a preset rule based on the data information, and is also used for returning a control command to the ZigBee coordinator node.
Preferably, the preset rule includes:
when the voltage and current change rate of the outlet circuit of the distribution box is large or the switching action is abnormal, judging the flow, the lift and the shaft power in the running state of the water pump, specifically:
when (when)And->Or->And->The values of the early warning levels are different by 5-10%, and the early warning levels are primary;
when (when)And->Or->And->The numerical value of the early warning grade is 11-25%, and the early warning grade is a middle grade;
when (when)And->Or->And->The numerical value of the early warning grade is special if the numerical value of the early warning grade is different by 26-40%;
wherein H is 1 And H 2 Representing the lift, Q, between two different periods of time 3 And Q 4 Representing flow between two different time periods, N 1 And N 2 Representing the shaft power between two different time periods.
Preferably, the method further comprises a model early warning level discrimination rule, which comprises the following steps:
when the depth of the tunnel water level is 5-10% higher than the preset standard water level, and V Feeding in When the model early warning level is smaller than 0, the model early warning level is primary;
when the depth of the tunnel water level is 11-25% higher than the preset standard water level, and V Feeding in When the model early warning level is close to 0, the model early warning level is a middle level;
when the depth of the tunnel water level is 26-40% higher than the preset standard water level, and V Feeding in When the model early warning level is greater than 0, the model early warning level is a special level;
the risk level discrimination rule includes:
when the early warning level of the running states of the distribution box and the water pump is primary, and when the early warning level of the model is primary or intermediate, the risk level is primary;
when the early warning level of the running states of the distribution box and the water pump is primary, and when the early warning level of the model is high, the risk level is secondary;
when the early warning level of the running states of the distribution box and the water pump is a medium level, and when the early warning level of the model is a primary level, the risk level is a first level;
when the early warning level of the running states of the distribution box and the water pump is the middle level, and when the early warning level of the model is the middle level, the risk level is the second level;
when the early warning level of the running states of the distribution box and the water pump is a medium level, and when the early warning level of the model is a high level, the risk level is three levels;
when the early warning level of the running state of the distribution box and the water pump is high-grade, and when the early warning level of the model is primary, medium-grade or high-grade, the risk level is three-grade.
Preferably, the emergency plan includes:
when the risk level is one level, displaying the ponding condition in the tunnel in real time on a tunnel portal display board;
when the risk level is the second level, prohibiting the vehicle from entering;
and when the risk level is three-level, vehicles are forbidden to enter, the traffic police signal lamp system is linked, the signal lamps which are positioned at the front intersection of the tunnel and lead to the direction of the tunnel uniformly display red lamps, and all vehicles which lead to the direction of the tunnel are shunted.
Preferably, the method for establishing the tunnel slice model comprises the following steps:
acquiring three-dimensional point cloud data of a tunnel by adopting laser scanning, fitting the three-dimensional point cloud data by adopting point cloud processing software, and guiding out a three-dimensional model of the tunnel to a local place;
the method comprises the steps of importing a three-dimensional model of a tunnel into three-dimensional modeling software, and assembling the three-dimensional model of a facility and the three-dimensional model of equipment on the three-dimensional model of the tunnel to obtain a tunnel refined three-dimensional model, wherein the facility comprises a water blocking ditch, a water guiding ditch, a rain sewage pipeline and a pump house, and the equipment comprises a rain gauge, water supply and drainage equipment, traffic facility equipment and pipeline equipment;
importing the tunnel refined three-dimensional model into fluid simulation software, setting gridding parameters, automatically generating structured grids, setting fluid as water, boundary conditions and environmental condition parameters, and obtaining a structured grid model of the tunnel;
setting key factor parameters, wherein the key factor parameters comprise water level depths, and each water level depth corresponds to a submerged simulated water body surface profile, a submerged simulated water body surface profile position coordinate, a tunnel water accommodating capacity, a water accumulation center point coordinate and a low point coordinate, wherein the water accumulation center point coordinate is a profile geometric center;
simulating the water accumulation condition of the tunnel with uniform flow rate, scanning the structured grid model of the tunnel layer by layer from low to high, and automatically outputting key factor parameter information corresponding to each water level depth;
and establishing a water level rising simulation slice model by using key parameter factor parameter information, setting a configuration number by using the water level depth as a mark, and deriving the slice model to obtain a slice model set.
The utility model provides a tunnel flood early warning system's early warning method based on fluid three-dimensional dynamic analog simulation, including the following steps:
s1, establishing and storing a water inlet rate model, wherein the water inlet rate model is shown in a formula 1 and a formula 2:
when RZ is<RZ 0 V at the time of Feeding in ＝V 0 +α×RZ+V 3 +V 4 -V 5 The method comprises the steps of carrying out a first treatment on the surface of the Equation 1
When RZ is greater than or equal to RZ 0 V at the time of Feeding in ＝V 0 +α×RZ+β×RZ+V 3 +V 4 -V 5 The method comprises the steps of carrying out a first treatment on the surface of the Equation 2
Wherein RZ is rain intensity, alpha is an internal inflow rate parameter, beta is an external inflow rate parameter, V 0 RZ is the average fixed leak rate of the tunnel 0 Is the threshold of rain intensity, V 3 For the water inflow rate of fire-fighting water, V 4 V is the abnormal water inflow rate 5 Is the tunnel drainage rate, wherein alpha, beta, V 0 And RZ 0 Based on historical water inflow data and historical water drainage data of the tunnel, statistical analysis is carried out to obtain;
s2, establishing and storing a slice model set of a tunnel water level rising simulation model, wherein each slice model uses water as fluid, uses water level depth as an identifier, displays and presents a tunnel ponding state and corresponding key factor parameter information, and each slice model has a unique configuration number, wherein the water level depth is calculated by water inflow and tunnel volume;
s3, acquiring the rain intensity RZ, the water inflow rate of fire-fighting water, the abnormal water inflow rate and the tunnel water drainage rate in a future period of time, and calling the water inflow rate model to calculate based on the rain intensity RZ to obtain the water inflow rate V in the future period of time Feeding in Calculating the water inflow rate to obtain the water inflow and the tunnel water level depth in a future period, and calling a slice model and key factor parameter information corresponding to configuration numbers corresponding to the water level depth one by one to form a predicted water level rising simulation slice model;
s4, outputting a tunnel slice model which is arranged in sequence according to a time axis by taking time as an x axis, and simultaneously displaying corresponding key factor parameter information to form a three-dimensional tunnel water level simulation video;
s5, carrying out statistical analysis on the tunnel flooding time and the predicted flood drainage completion time, presetting a risk level judging rule and an emergency plan, and outputting the emergency plan according to the judging result of the risk level judging rule.
The invention at least comprises the following beneficial effects: the invention focuses on four parts of information acquisition such as rainfall of long-distance tunnels, road ponding and the like, equipment operation situation monitoring, algorithm model building, emergency early warning and treatment, forms a grading means for preventing flood disasters, refines emergency plans of flood disasters at all levels, plays an early warning role, and reduces the loss caused by the flood disasters to the greatest extent.
Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention.
Drawings
FIG. 1 is a block diagram of the early warning system of the present invention;
FIG. 2 is a flow chart I of a frame for building a tunnel refinement three-dimensional model according to the present invention;
FIG. 3 is a flow chart II of a frame for creating a tunnel refinement three-dimensional model according to the present invention;
FIG. 4 is a flow chart of a frame for establishing a water level rising simulation slice model according to the invention;
FIG. 5 is a flow chart I of a water inlet rate model building framework of the invention;
FIG. 6 is a flow chart II of a water inlet rate model building framework of the invention;
FIG. 7 is a diagram I of a future rain intensity, water level rising simulation slice model and early warning flow chart of the invention;
FIG. 8 is a diagram II of a future rain intensity, water level rising simulation slice model and an early warning flow chart of the invention.
Detailed Description
The present invention is described in further detail below with reference to the drawings to enable those skilled in the art to practice the invention by referring to the description.
It should be noted that the experimental methods described in the following embodiments, unless otherwise specified, are all conventional methods, and the reagents and materials, unless otherwise specified, are all commercially available; in the description of the present invention, the orientation or positional relationship indicated by the terms are based on the orientation or positional relationship shown in the drawings, are merely for convenience of description and simplification of the description, and do not indicate or imply that the apparatus or element in question must have a specific orientation, be configured and operated in a specific orientation, and therefore should not be construed as limiting the present invention.
As shown in fig. 1 to 8, the present invention provides a tunnel flood warning system based on three-dimensional dynamic simulation of fluid, comprising:
and I, importing the laser scanning data into point cloud processing software according to the tunnel to obtain three-dimensional point cloud data. And carrying out preprocessing operations such as denoising, simplification, registration, hole filling and the like on the three-dimensional point cloud data, setting boundary conditions and precision grades, checking the three-dimensional data, correcting defects, and automatically fitting and deriving a three-dimensional model of the tunnel to the local.
And importing the three-dimensional model into three-dimensional modeling software, and perfecting facility models such as a water blocking ditch, a water guiding ditch, a rain sewage pipeline, a pump house and the like through three-dimensional modeling according to BIM model modeling as a reference. And importing related models of the rain gauge, the water supply and drainage equipment, the traffic facility equipment and the pipeline equipment into a three-dimensional model, and manually assembling all the components into the three-dimensional model according to BIM design parameters. And (3) observing the assembled three-dimensional model, and checking the assembly interference condition by using an interference checking tool until no abnormality exists in the gridding operation, so as to derive a tunnel refined three-dimensional model.
And importing the tunnel refined three-dimensional model into fluid simulation software, setting gridding parameters, and automatically generating a structured grid. The fluid is set to be water, boundary conditions are set, and environmental conditions are set. Checking the grid, and performing blocking and local encryption processing on the model to obtain a high-quality structured grid model of the tunnel.
Setting key factor parameters, wherein the key factor parameters comprise water level depths, and each water level depth corresponds to a submerged simulated water body surface profile, a submerged simulated water body surface profile position coordinate, a capacity of a tunnel capable of containing water, a ponding central point coordinate and a low point coordinate to form a key parameter monitor, wherein the ponding central point coordinate is a profile geometric center; simulating the water accumulation condition of the uniform flow tunnel, scanning the structured grid model layer by layer from low to high, and automatically outputting water inlet key factor parameter data.
And establishing a water level rising simulation slice model according to the key factor parameters, setting a configuration number by taking the water level depth as a mark, and deriving the slice model. According to the water inlet key factor parameter data and the configuration number, developing a transmission parameter into a volume (the volume of which the tunnel corresponding to each water level depth can contain water), and outputting an API interface P1 which is the configuration number and the key factor parameter data.
According to the slice model, a rendering tool is imported, materials of fluid, building facilities and electromechanical equipment are set, mapping is conducted, automatic rendering generation of the model is conducted, and the model is used for subsequent simulation effect presentation.
The development parameter is a model number (the model number corresponds to the configuration number one by one), and the development parameter is output as a three-dimensional water level simulation video stream pushing interface P2 for effect presentation of a webpage display end.
II, setting siphon rain gauge at tunnel entrance and exit to continuously record precipitation Q t And duration of precipitation (rainfall time) t, calculating continuous rain intensity data rz=q t T, this data varies with the local rainfall moment. The data can be synchronously matched with a local design storm intensity formula to carry out multiple simulation fitting on the rainfall duration t and the design reproduction period P (year) in real time. And the rainfall intensity data is calculated and stored and is used for the prediction analysis calculation of the real-time rainfall and rainfall.
The water inflow source analysis of the tunnel mainly comprises inherent leakage of the tunnel, inflow of flushing water (external inflow), dynamic inflow of rainwater, fire disaster water in the tunnel and abnormal conditions.
In the case of normal operation management (during non-rainfall periods), total tunnel drainage Q Row of rows Equal to the water inflow of the tunnel, the water inflow rate V is designed according to the water inflow rate Feeding in Total drainage/total drainage duration = Q Row of rows ÷t Row of rows . Based on the historical tunnel drainage data, flushing water (external inflow), dynamic inflow of rainwater, fire disaster water and abnormal point data are removed, and leakage quantity Q is calculated at this time Infiltration process And water discharge quantity Q Row of rows Equal. Calculated tunnel management in normal operation (non-rainfallDuring) average fixed leak rate V 0 ＝Q Row of rows ÷t Row of rows . Thereby obtaining the average fixed leakage rate V of the tunnel 0 Is a value of (2). When V is 0 When the numerical value changes obviously, the method can also be used for checking the water leakage condition of the tunnel.
During rainfall, according to the historical tunnel drainage data, unused fire water and abnormal points are removed, and at the moment, the water inlet rate V Feeding in =average fixed leakage rate V 0 +rainwater fixed inflow rate V 1 +rainwater external inflow Rate V 2 . Due to V 1 、V 2 With rain intensity RZ and external drainage V p Capacity dependent, thus modifying the water inlet rate V Feeding in ＝V 0 +α×rz+β×rz, where α is the internal inflow parameter and β is the external inflow parameter. Project data are collected on a daily basis, and data that deviate significantly are called outlier data points.
According to statistical analysis, when the rain intensity RZ is larger than a certain threshold value, the water inflow rate is increased, and the rain intensity RZ is recorded 0 Value, obtain the rain intensity threshold RZ of the tunnel 0 Is a value of (2).
When RZ is<RZ 0 V at the time of Feeding in ＝V 0 +α×RZ equation 1
When RZ is greater than or equal to RZ 0 V at the time of Feeding in ＝V 0 +α×rz+β×rz formula 2
According to the history data of normal production operation of the tunnel, selecting RZ<RZ 0 The historical data is used for controlling variable drawing spss scatter diagram auxiliary judging data to basically meet linear distribution, setting residual errors to obey normal distribution, setting a 'estimated value' in regression coefficients, setting a '95% confidence interval', carrying out significance test and calculation on the regression coefficients, selecting a 'histogram' in a standardized residual error diagram, a 'normal probability diagram', and checking whether residual errors of a regression equation obey normal distribution. And (3) importing a regression algorithm model, and sequentially fitting the optimal parameters of the current alpha through a least-squares method to obtain an alpha value.
RZ is selected to be more than or equal to RZ 0 And (5) repeating the steps according to the historical data, and fitting the optimal parameters of the current beta in sequence by a least binary method to obtain the beta value.
When fire disaster occurs in the tunnel, the fire water is needed to be used, remote transmission data and a flowmeter are arranged at the access outlet of the fire water, and the water inlet rate V of the fire water can be obtained 3 。
A water level gauge is arranged at a low point in the tunnel and in the pump room, and the water gauge cross section area S and the liquid level rising speed V of the pump room are used for measuring the water level Lifting device Calculating abnormal water inlet speed V 4 ，V 4 ＝V Lifting device X S. Under normal conditions, the water pump drainage capacity is higher than the water inflow, and the liquid level is not higher than the set value normally. If the liquid level exceeds the set value, the water level rises due to an unknown factor. Such as pump damage, etc.
Acquiring the actual drainage capacity V of the water pump according to the historic drainage capacity of each water pump Pump with a pump body Acquiring actual drainage capacity according to the running number n of the equipment, V 5 ＝n×V Pump with a pump body ；
Thus, the water inlet rate model is set, and the water inlet rate V Feeding in Total amount of drainage Q Row of rows Total duration t of drainage Row of rows Intrinsic leakage rate V 0 +rainwater fixed inflow rate V 1 +rainwater external inflow Rate V 2 Rate of fire water V 3 +abnormal Rate V 4 Drainage rate V 5 ＝V 0 +α×RZ+β×RZ+V 3 +V Lifting device ×S-n×V Pump with a pump body . According to the real-time state and data of equipment of the hardware system collected by the Internet of things platform, developing an API interface P3 with the transmission parameter of RZ and the output of RZ as the water inlet rate.
III, acquiring the rain intensity RZ in a future period of time according to the future rainfall data accessed from the weather bureau Pre-preparation ；
The system will rain intensity RZ Pre-preparation And (3) obtaining the expected water inlet rate as a P3 interface for parameter transmission, so as to draw a time and water inlet curve.
The system takes the water inflow as a parameter, calls a P1 interface, and can obtain configuration numbers and key factor parameter data of each time period.
And the system takes the configuration number as a parameter, calls the P2 interface and acquires the three-dimensional water level simulation video stream. And taking the video stream as a large-screen background of the webpage, placing statistical data such as key factor parameter data and the like on two sides, placing a time axis at the bottom, and enabling a user to freely drag the time axis to acquire water level model simulation videos and data at different times so as to form a tunnel flooding dynamic three-dimensional simulation page, so that visual experience is provided for the user.
IV, defining a water level model early warning grade (model early warning grade discrimination rule):
when the depth of the tunnel water level is 5-10% higher than the preset standard water level, and V Feeding in When the model early warning level is smaller than 0, the model early warning level is primary;
when the depth of the tunnel water level is 11-25% higher than the preset standard water level, and V Feeding in When the model early warning level is close to 0, the model early warning level is a middle level; when approaching 0, it is understood that the tunnel is equal to 0 or is set to about 0 according to the actual tunnel condition.
When the depth of the tunnel water level is 26-40% higher than the preset standard water level, and V Feeding in When the model early warning level is greater than 0, the model early warning level is special.
V, monitoring equipment operation situation, aiming at the problems of inconvenient monitoring of operation information of traditional tunnel electromechanical equipment, low maintainability of traditional monitoring technology and poor system expandability, by utilizing the electronic tag identification technology of ZigBee and RFID technology, the system has the advantages of strong penetrability, high safety, large data storage space, low cost, high flexibility, long transmission distance, low power consumption and the like, and can monitor and display the operation state of a water pump in a tunnel, the working condition of facilities such as a distribution box and the like in real time. The system hardware structure mainly comprises 5 parts: the system comprises an active electronic tag, a master-slave radio frequency module, a ZigBee terminal node, a ZigBee coordinator node and a PC upper computer.
Setting voltage and current detection instruments at the tail end water pump and distribution box equipment, setting an upper limit value and a lower limit value, defining a plurality of active electronic tags such as current, voltage, temperature and the like, monitoring and storing the values of voltage and current parameters of outgoing lines of the distribution box and the temperature of incoming lines cables in real time, and simultaneously monitoring the switch opening and closing position state and the tripping condition of the switch;
carrying out electronic tags on the operation flow, the lift, the shaft power, the specific rotation number and the like of the drainage pump equipment, monitoring the data information relationship between the drainage pump equipment and the shaft power in real time during operation, and knowing whether the operation state of the water pump is in a normal state or an abnormal state in real time;
and master-slave radio frequency modules (RFID readers and writers), a master SPI and a slave SPI are arranged at intervals on the top plate of the tunnel section, so that the dual-channel data communication of the RFID system is realized, and the active electronic tag data information of the water pump room and the power distribution room within the radiation range of the antenna is identified.
The received electronic tag information is wirelessly transmitted to the ZigBee terminal node positioned in the tunnel management center, and meanwhile, the control command transmitted by the ZigBee terminal node can be received;
the ZigBee terminal node transmits the active electronic tag data information identified by the master-slave radio frequency module to the water pump room and the power distribution room to the ZigBee coordinator node in a wireless mode, and meanwhile, the ZigBee terminal node controls the master-slave radio frequency module according to a control instruction transmitted by the coordinator, so that the corresponding processing of the terminal state information is realized.
The ZigBee coordinator node is responsible for realizing data communication between the active electronic tag data sent by the ZigBee terminal node and the PC upper computer through the local area network, and simultaneously sending the control instruction received from the upper computer to the ZigBee terminal node.
The PC upper computer application software supports the development of languages such as Python, java, C ++, develops a digital twinning software display interface, and the like, and realizes the processing, analysis and storage of the ID information of the active electronic tags in the power distribution room and the pump room, thereby facilitating the later calling and inquiring.
The PC upper computer application software takes the change rate of the processed monitoring parameters in unit time as a judging basis of the running condition of the tunnel electromechanical equipment, when the voltage and current change rate monitored by a power distribution room is large or the switching action is abnormal, and the flow, the lift and the shaft power in the running state of the water pump are judged, the system monitors and displays the working condition of the equipment in real time, when the equipment is abnormal, the system records and stores fault alarm information, the state is transmitted to a configuration page related to the upper computer, and corresponding equipment icons on an application software interface are highlighted and displayed to display corresponding early warning grade information;
the relation among pump lift, flow and shaft power in the pump house can be used for dividing equipment state early-warning grade information by taking the ratio change rate as an example, and the change rate calculation formula of the water pump is as follows:and->The preset rules are as follows:
when (when)And->Or->And->The values of the early warning levels are different by 5-10%, and the early warning levels are primary;
when (when)And->Or->And->The numerical value of the early warning grade is 11-25%, and the early warning grade is a middle grade;
when (when)And->Or->And->The numerical value of the early warning grade is special if the numerical value of the early warning grade is different by 26-40%;
wherein H is 1 And H 2 Representing the lift, Q, between two different periods of time 3 And Q 4 Representing flow between two different time periods, N 1 And N 2 Representing the shaft power between two different time periods; the comprehensive risk level and the emergency plan of the long-distance tunnel flood warning are matched by combining the water level model warning level and the equipment abnormal condition level information as shown in the table 1:
TABLE 1 Risk level discriminant rules
| Comprehensive risk level | Early warning primary water level model | Early warning middle level of water level model | Early warning high-grade water level model |
| Device abnormality primary | First level | First level | Second-level |
| Abnormal condition middle level of equipment | First level | Second-level | Three stages |
| Device abnormality advanced | Three stages | Three stages | Three stages |
The method comprises the following steps: when the early warning level of the abnormal voltage or current of an outlet loop of the distribution box and the running state of the water pump is primary, and when the early warning level of the model is primary or intermediate, the risk level is primary;
when the early warning level of the abnormal voltage or current of an outlet loop of the distribution box and the running state of the water pump is primary, and when the early warning level of the model is high, the risk level is secondary;
when the early warning level of the abnormal voltage or current of two outlet loops of the distribution box and the running state of the water pump is a middle level, and when the early warning level of the model is a primary level, the risk level is a primary level;
when the early warning level of the abnormal voltage or current of the two outlet loops of the distribution box and the running state of the water pump is the middle level, and when the early warning level of the model is the middle level, the risk level is the second level;
when the voltage or current of two outlet loops of the distribution box is abnormal and the early warning level of the running state of the water pump is a medium level, and when the early warning level of the model is a high level, the risk level is three levels;
when the voltage or current of three or more outlet loops of the distribution box is abnormal and the early warning level of the running state of the water pump is high, and when the early warning level of the model is primary, medium or high, the risk level is three-level.
Emergency pre-warning and treatment, according to statistical data analysis, different plans are made according to different risk levels: the water drainage capacity of the pump station is higher than the water inlet rate, the water accumulation condition in the tunnel is displayed on a portal display board of the tunnel portal in real time, the entrance of vehicles is not limited, and only the vehicles are prompted to carefully pass; second, the entrance of the vehicle is forbidden in time, and the vehicle can be intercepted by linking the tunnel portal electronic barrier or gate; and thirdly, when the short-time tunnel is submerged through a model or calculated, vehicles are forbidden to enter in time, and the traffic police signal lamp system is connected in parallel, so that the signal lamps in the direction of the tunnel at the previous intersection uniformly display red lamps, and all vehicles in the direction of the tunnel are shunted.
Although embodiments of the present invention have been disclosed above, it is not limited to the details and embodiments shown and described, it is well suited to various fields of use for which the invention would be readily apparent to those skilled in the art, and accordingly, the invention is not limited to the specific details and illustrations shown and described herein, without departing from the general concepts defined in the claims and their equivalents.
Claims (10)
1. The tunnel flood early warning system based on the three-dimensional dynamic simulation of fluid is characterized by comprising:
a data processing module for storing a water intake rate model, the water intake rate model being as shown in equations 1 and 2:
when RZ is<RZ 0 V at the time of Feeding in ＝V 0 +α×RZ+V 3 +V 4 -V 5 The method comprises the steps of carrying out a first treatment on the surface of the Equation 1
When RZ is greater than or equal to RZ 0 V at the time of Feeding in ＝V 0 +α×RZ+β×RZ+V 3 +V 4 -V 5 The method comprises the steps of carrying out a first treatment on the surface of the Equation 2
Wherein RZ is rain intensity, alpha is an internal inflow rate parameter, beta is an external inflow rate parameter, V 0 RZ is the average fixed leak rate of the tunnel 0 Is the threshold of rain intensity, V 3 For the water inflow rate of fire-fighting water, V 4 V is the abnormal water inflow rate 5 Is the tunnel drainage rate, wherein alpha, beta, V 0 And RZ 0 Based on historical water inflow data and historical water drainage data of the tunnel, statistical analysis is carried out to obtain;
the model module is used for storing a slice model set of the tunnel water level rising simulation, each slice model takes water as fluid, water level depth as an identifier, the state of accumulated water in the tunnel and corresponding key factor parameter information are displayed, each slice model is provided with a unique configuration number, and the water level depth is calculated by water inflow and tunnel volume;
the prediction module is used for acquiring the rain intensity RZ, the water inflow rate of fire-fighting water, the abnormal water inflow rate and the tunnel water drainage rate in a future period of time, and calling the water inflow rate model to calculate and obtain the water inflow rate V in the future period of time based on the rain intensity RZ Feeding in Calculating the water inflow rate to obtain the water inflow and the tunnel water level depth in a future period, and calling a slice model and key factor parameter information corresponding to configuration numbers corresponding to the water level depth one by one to form a predicted water level rising simulation slice model;
the display module is used for outputting and obtaining tunnel slice models which are arranged in sequence according to the time axis by taking the time as the x axis, and simultaneously displaying the parameter information of the corresponding key factors to form a three-dimensional tunnel water level simulation video;
the emergency processing module is used for statistically analyzing the tunnel flooding time and the predicted flood drainage completion time, presetting a risk level discrimination rule and an emergency plan, and outputting the emergency plan according to the discrimination result of the risk level discrimination rule.
2. The tunnel flood warning system based on fluid three-dimensional dynamic simulation according to claim 1, wherein the tunnel history water inflow data comprises a tunnel water inflow Q of a non-rainfall period Feeding in The water inflow of the tunnel is the inherent leakage Q of the tunnel 0 The tunnel history drainage data includes the tunnel drainage quantity Q of the non-rainfall period Row of rows The data processing module obtains a parameter V based on the statistical analysis fitting of formulas 1, 3-5 0 Is a value of (2);
Q feeding in ＝Q Row of rows Equation 3
Q Feeding in ＝Q 0 Equation 4
V Feeding in ＝Q Feeding in /t Row of rows Equation 5.
3. The tunnel flood warning system based on fluid three-dimensional dynamic analog simulation of claim 2, wherein the tunnelThe historical water inflow data comprises rain intensity RZ in the period of falling rain, rainfall time and tunnel water inflow Q Feeding in The water inflow of the tunnel is the inherent leakage Q of the tunnel 0 Fixed inflow Q of rainwater 1 External inflow quantity Q of rainwater 2 The tunnel history drainage data comprises the tunnel drainage quantity Q in the rain-down period Row of rows ；
The data processing module is used for carrying out statistical analysis based on a formula 1, and obtaining a parameter RZ when the water inflow rate is increased and the corresponding rain intensity is high 0 Is a value of (2);
selecting rain intensity RZ<RZ 0 The data processing module obtains the value of the parameter alpha by statistical analysis fitting based on a formula 1;
selecting rain intensity RZ>RZ 0 The data processing module obtains the value of the parameter beta based on the statistical analysis fitting of the formula 2.
4. The tunnel flood warning system based on three-dimensional dynamic simulation of fluid according to claim 3, further comprising an end acquisition device for acquiring the historical inflow data and the historical drainage data of the tunnel, wherein the end adoption device comprises:
the rainfall gauge is used for collecting rainfall and rainfall time in real time, calculating and outputting a real-time rainfall intensity average value RZ, and storing the real-time rainfall intensity average value RZ to obtain historical rainfall intensity data RZ;
the fire control pipeline flowmeter is used for detecting the flow of the fire control water pipeline, and the data processing module calculates the fire control water inflow rate V based on the flow of the fire control water pipeline 3 ；
A liquid level gauge for detecting a liquid level rise value and a rise time, the data processing module calculating a liquid level rise speed V based on the liquid level rise value and the rise time Lifting device And calculating an abnormal water inflow rate V using equation 6 4 ；
V 4 ＝V Lifting device X S formula 6
S is the cross section area of a pump room water gauge;
drainage pipeline flowmeter and drainage pump flowmeter for collecting drainage amount and counting each pumpThe total flow, the water discharge and the total flow of each pump are used for calculating and obtaining the actual water discharge rate V of the water pump Pump with a pump body The data processing module calculates the tunnel drainage rate V by adopting a formula 7 5 ；
V 5 ＝n×V Pump with a pump body Equation 7
Wherein n is the actual running number of the water pump, V Pump with a pump body Is the actual water discharge rate of the water pump.
5. The tunnel flood warning system based on three-dimensional dynamic simulation of fluid according to claim 1, further comprising a device operation situation monitoring means comprising:
the active electronic tags are arranged on the water pump and the distribution box and are used for monitoring and storing the voltage and current parameter values of the outlet wire of the distribution box and the temperature of the inlet wire cable in real time, and monitoring the on-off position state and the tripping condition of the switch and the running flow, the lift, the shaft power and the specific rotation number of the water pump equipment in real time;
the system comprises a plurality of pairs of master radio frequency modules and slave radio frequency modules, wherein the master radio frequency modules and the slave radio frequency modules are arranged on the top of a tunnel at intervals, and the master radio frequency modules and the slave radio frequency modules are used for identifying data information of active electronic tags of a pump room and a power distribution room within the radiation range of an antenna and realizing double-channel data communication of an RFID system;
the ZigBee terminal node is connected with the master radio frequency module and the slave radio frequency module through wireless, and is used for receiving data information of the active electronic tag transmitted by the master radio frequency module and the slave radio frequency module and simultaneously transmitting a control command back to the master radio frequency module and the slave radio frequency module;
the ZigBee coordinator node is in wireless connection with the ZigBee terminal node, and is used for receiving data information sent by the ZigBee terminal node and simultaneously returning a control command to the ZigBee terminal node;
the PC upper computer is connected with the ZigBee coordinator node through the local area network, is used for receiving data information sent by the ZigBee coordinator node, judging the running states of the distribution box and the water pump according to a preset rule based on the data information, and is also used for returning a control command to the ZigBee coordinator node.
6. The tunnel flood warning system based on three-dimensional dynamic simulation of fluid according to claim 5, wherein the preset rule comprises:
when the voltage and current change rate of the outlet circuit of the distribution box is large or the switching action is abnormal, judging the flow, the lift and the shaft power in the running state of the water pump, specifically:
when (when)And->Or->And->The values of the early warning levels are different by 5-10%, and the early warning levels are primary;
when (when)And->Or->And->The numerical value of the early warning grade is 11-25%, and the early warning grade is a middle grade;
when (when)And->Or->And->The numerical value of the early warning grade is special if the numerical value of the early warning grade is different by 26-40%;
wherein H is 1 And H 2 Representing the lift, Q, between two different periods of time 3 And Q 4 Representing flow between two different time periods, N 1 And N 2 Representing the shaft power between two different time periods.
7. The tunnel flood warning system based on fluid three-dimensional dynamic simulation of claim 5, further comprising model warning level discrimination rules comprising:
when the depth of the tunnel water level is 5-10% higher than the preset standard water level, and V Feeding in When the model early warning level is smaller than 0, the model early warning level is primary;
when the depth of the tunnel water level is 11-25% higher than the preset standard water level, and V Feeding in When the model early warning level is close to 0, the model early warning level is a middle level;
when the depth of the tunnel water level is 26-40% higher than the preset standard water level, and V Feeding in When the model early warning level is greater than 0, the model early warning level is a special level;
the risk level discrimination rule includes:
when the early warning level of the running states of the distribution box and the water pump is primary, and when the early warning level of the model is primary or intermediate, the risk level is primary;
when the early warning level of the running states of the distribution box and the water pump is primary, and when the early warning level of the model is high, the risk level is secondary;
when the early warning level of the running states of the distribution box and the water pump is a medium level, and when the early warning level of the model is a primary level, the risk level is a first level;
when the early warning level of the running states of the distribution box and the water pump is the middle level, and when the early warning level of the model is the middle level, the risk level is the second level;
when the early warning level of the running states of the distribution box and the water pump is a medium level, and when the early warning level of the model is a high level, the risk level is three levels;
when the early warning level of the running state of the distribution box and the water pump is high-grade, and when the early warning level of the model is primary, medium-grade or high-grade, the risk level is three-grade.
8. The tunnel flood warning system based on three-dimensional dynamic simulation of fluid according to claim 7, wherein the emergency plan comprises:
when the risk level is one level, displaying the ponding condition in the tunnel in real time on a tunnel portal display board;
when the risk level is the second level, prohibiting the vehicle from entering;
and when the risk level is three-level, vehicles are forbidden to enter, the traffic police signal lamp system is linked, the signal lamps which are positioned at the front intersection of the tunnel and lead to the direction of the tunnel uniformly display red lamps, and all vehicles which lead to the direction of the tunnel are shunted.
9. The tunnel flood warning system based on the fluid three-dimensional dynamic simulation as set forth in claim 1, wherein the tunnel slice model building method comprises the following steps:
acquiring three-dimensional point cloud data of a tunnel by adopting laser scanning, fitting the three-dimensional point cloud data by adopting point cloud processing software, and guiding out a three-dimensional model of the tunnel to a local place;
the method comprises the steps of importing a three-dimensional model of a tunnel into three-dimensional modeling software, and assembling the three-dimensional model of a facility and the three-dimensional model of equipment on the three-dimensional model of the tunnel to obtain a tunnel refined three-dimensional model, wherein the facility comprises a water blocking ditch, a water guiding ditch, a rain sewage pipeline and a pump house, and the equipment comprises a rain gauge, water supply and drainage equipment, traffic facility equipment and pipeline equipment;
importing the tunnel refined three-dimensional model into fluid simulation software, setting gridding parameters, automatically generating structured grids, setting fluid as water, boundary conditions and environmental condition parameters, and obtaining a structured grid model of the tunnel;
setting key factor parameters, wherein the key factor parameters comprise water level depths, and each water level depth corresponds to a submerged simulated water body surface profile, a submerged simulated water body surface profile position coordinate, a tunnel water accommodating capacity, a water accumulation center point coordinate and a low point coordinate, wherein the water accumulation center point coordinate is a profile geometric center;
simulating the water accumulation condition of the tunnel with uniform flow rate, scanning the structured grid model of the tunnel layer by layer from low to high, and automatically outputting key factor parameter information corresponding to each water level depth;
and establishing a water level rising simulation slice model by using key parameter factor parameter information, setting a configuration number by using the water level depth as a mark, and deriving the slice model to obtain a slice model set.
10. The method for early warning of a tunnel flood early warning system based on three-dimensional dynamic simulation of fluid according to any one of claims 1 to 9, comprising the following steps:
s1, establishing and storing a water inlet rate model, wherein the water inlet rate model is shown in a formula 1 and a formula 2:
when RZ is<RZ 0 V at the time of Feeding in ＝V 0 +α×RZ+V 3 +V 4 -V 5 The method comprises the steps of carrying out a first treatment on the surface of the Equation 1
When RZ is greater than or equal to RZ 0 V at the time of Feeding in ＝V 0 +α×RZ+β×RZ+V 3 +V 4 -V 5 The method comprises the steps of carrying out a first treatment on the surface of the Equation 2
Wherein RZ is rain intensity, alpha is an internal inflow rate parameter, beta is an external inflow rate parameter, V 0 RZ is the average fixed leak rate of the tunnel 0 Is the threshold of rain intensity, V 3 For the water inflow rate of fire-fighting water, V 4 V is the abnormal water inflow rate 5 Is the tunnel drainage rate, wherein alpha, beta, V 0 And RZ 0 Based on historical water inflow data and historical water drainage data of the tunnel, statistical analysis is carried out to obtain;
s2, establishing and storing a slice model set of a tunnel water level rising simulation model, wherein each slice model uses water as fluid, uses water level depth as an identifier, displays and presents a tunnel ponding state and corresponding key factor parameter information, and each slice model has a unique configuration number, wherein the water level depth is calculated by water inflow and tunnel volume;
s3, acquiring the rain intensity RZ, the water inflow rate of fire-fighting water, the abnormal water inflow rate and the tunnel water drainage rate in a future period of time, and calling the water inflow rate model to calculate based on the rain intensity RZ to obtain the water inflow rate V in the future period of time Feeding in Calculating the water inflow rate to obtain the water inflow and the tunnel water level depth in a future period, and calling a slice model and key factor parameter information corresponding to configuration numbers corresponding to the water level depth one by one to form a predicted water level rising simulation slice model;
s4, outputting a tunnel slice model which is arranged in sequence according to a time axis by taking time as an x axis, and simultaneously displaying corresponding key factor parameter information to form a three-dimensional tunnel water level simulation video;
s5, carrying out statistical analysis on the tunnel flooding time and the predicted flood drainage completion time, presetting a risk level judging rule and an emergency plan, and outputting the emergency plan according to the judging result of the risk level judging rule.
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| CN118094737A (en) * | 2024-04-29 | 2024-05-28 | 八维通科技有限公司 | Digital twinning-based subway tunnel interval water inflow analysis method, system and medium |
| CN118297442A (en) * | 2024-06-05 | 2024-07-05 | 四川国蓝中天环境科技集团有限公司 | Urban underpass tunnel flood early warning method based on multilayer perception model |
| CN118333355A (en) * | 2024-06-14 | 2024-07-12 | 江西省交通科学研究院有限公司 | Expressway tide-based sewage emergency treatment method and control system |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN118094737A (en) * | 2024-04-29 | 2024-05-28 | 八维通科技有限公司 | Digital twinning-based subway tunnel interval water inflow analysis method, system and medium |
| CN118094737B (en) * | 2024-04-29 | 2024-08-30 | 八维通科技有限公司 | Digital twinning-based subway tunnel interval water inflow analysis method, system and medium |
| CN118297442A (en) * | 2024-06-05 | 2024-07-05 | 四川国蓝中天环境科技集团有限公司 | Urban underpass tunnel flood early warning method based on multilayer perception model |
| CN118333355A (en) * | 2024-06-14 | 2024-07-12 | 江西省交通科学研究院有限公司 | Expressway tide-based sewage emergency treatment method and control system |
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