CN113534866A - Intelligent humidity control dam and control method thereof - Google Patents
Intelligent humidity control dam and control method thereof Download PDFInfo
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- CN113534866A CN113534866A CN202110807380.XA CN202110807380A CN113534866A CN 113534866 A CN113534866 A CN 113534866A CN 202110807380 A CN202110807380 A CN 202110807380A CN 113534866 A CN113534866 A CN 113534866A
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D22/00—Control of humidity
- G05D22/02—Control of humidity characterised by the use of electric means
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- C—CHEMISTRY; METALLURGY
- C04—CEMENTS; CONCRETE; ARTIFICIAL STONE; CERAMICS; REFRACTORIES
- C04B—LIME, MAGNESIA; SLAG; CEMENTS; COMPOSITIONS THEREOF, e.g. MORTARS, CONCRETE OR LIKE BUILDING MATERIALS; ARTIFICIAL STONE; CERAMICS; REFRACTORIES; TREATMENT OF NATURAL STONE
- C04B40/00—Processes, in general, for influencing or modifying the properties of mortars, concrete or artificial stone compositions, e.g. their setting or hardening ability
- C04B40/02—Selection of the hardening environment
- C04B40/0277—Hardening promoted by using additional water, e.g. by spraying water on the green concrete element
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- E—FIXED CONSTRUCTIONS
- E02—HYDRAULIC ENGINEERING; FOUNDATIONS; SOIL SHIFTING
- E02B—HYDRAULIC ENGINEERING
- E02B7/00—Barrages or weirs; Layout, construction, methods of, or devices for, making same
- E02B7/02—Fixed barrages
Abstract
The invention relates to an intelligent humidity control dam, which comprises a dam body, a concrete strength monitoring device, a humidity sensor group, a medium supply pipeline, a humidity node control unit, a relay medium pressure control unit, a medium compensation source and a control mechanism, wherein the concrete strength monitoring device, the humidity sensor group, the medium supply pipeline, the humidity node control unit, the relay medium pressure control unit, the medium compensation source and the control mechanism are arranged in the dam body; the humidity node regulation and control unit comprises a gasifier, an electric control valve, a humidity diffusion tile, a breathable film and a node controller; the control end of the gasifier and the electric control valve are respectively and electrically connected with the node controller; the medium supply pipeline adopts a tree structure, the input end of the medium supply pipeline is connected with the medium compensation source, and the tail ends of all branches of the medium supply pipeline are connected with the humidity node regulation and control unit. The invention also discloses a control method of the intelligent humidity control dam. According to the invention, the humidity node regulation and control units are arranged at the grid nodes of the dam, so that the humidity diffusion along different directions of the grid volume units is realized, the omnibearing humidity regulation and control is carried out on each area of the dam, the humidity stress increment of the concrete is reduced, and the cracks of the concrete can be effectively prevented.
Description
Technical Field
The invention belongs to the field of intelligent control of dams, and particularly relates to an intelligent humidity control dam.
Background
With the development of hydropower industry in China, concrete dams emerge continuously in high dam construction, and the problem of 'no dam and no crack' of the concrete dams is also highly concerned by academic and engineering circles while the concrete high dam construction is continuously developed. The structural performance of dam concrete is related to the cracking of concrete materials from the decline to the end of service life, and the cracks of the dam concrete in the construction period and the operation period have obvious influence on the structural safety and the service life.
The cracking of the dam concrete structure is mostly caused by non-load factors, that is, the volume expansion or contraction of the concrete caused by the temperature change and the humidity change in the dam concrete structure is restrained, so that the tensile stress is excessive, and the excessive tensile stress is a main cause for the generation of cracks. Therefore, the key to prevent the cracks is to control the temperature, prevent the cracks and protect the dam concrete from being generated at a constant temperature and humidity.
The temperature change of concrete is mainly influenced by the internal hydration heat and the external environment temperature. At present, the temperature control means mainly comprises pre-cooling aggregate, limiting the mixing temperature, controlling the warehousing temperature, paving a cooling water pipe, paving a heat insulation material on the surface and the like. The maximum temperature rise of the concrete is controlled, so that the temperature gradient inside and outside the dam concrete is reduced, the influence of the environmental temperature change on the concrete temperature is resisted, and the temperature stress of the concrete is controlled within a controllable range.
Humidity change is also one of factors causing cracks to be generated on a dam body, the surface of concrete can continuously lose water under the natural evaporation condition, so that the volume shrinkage of the concrete is caused, and when the shrinkage stress under the constrained condition exceeds the ultimate tensile stress of the concrete, the shrinkage cracks are generated. In addition, the moisture distribution of concrete also has an influence on the conduction and diffusion of temperature, and the higher the moisture of concrete, the faster the temperature conduction. Therefore, the moisture retention of the concrete can effectively reduce the generation of the shrinkage cracks and increase the heat conduction between different areas, thereby reducing the temperature gradient and further reducing the generation of the cracks.
The existing concrete dam moisturizing measures are generally to spray water for moisturizing in the pouring period, and little attention is paid to moisturizing in the dam operation period and active regulation and control work on the internal humidity of dam concrete.
Therefore, an effective humidity control method is needed to be found, so that the internal humidity of dam concrete is effectively controlled, the stress caused by a small humidity gradient is reduced, and cracks are prevented.
Disclosure of Invention
The invention aims to solve the problems, and provides an intelligent humidity control dam.A humidity node control unit is arranged at a grid node in the dam, a humidity diffusion tile is arranged outside the humidity node control unit, the humidity diffusion tile faces to the center of a grid, a control medium enters the humidity node control unit, then passes through a gasification device and an electric control valve, and is subjected to humidity diffusion to external breathable film concrete through the surface of the humidity diffusion tile, so that dam humidity active control with the grid as a basic unit is performed, humidity strain increment and humidity stress increment of dam concrete grids are controlled, and cracks of a concrete body are prevented.
The technical scheme of the invention is that the intelligent humidity control dam comprises a dam body, and a concrete strength monitoring device, a humidity sensor group, a medium supply pipeline, a relay medium pressure control unit, a humidity node control unit, a medium compensation source and a control mechanism which are arranged in the dam body.
The concrete strength monitoring device comprises a signal transmitter and a signal receiver which are arranged in the concrete body in pairs, wherein the signal receiver receives signals of the signal transmitter, and the concrete strength change which is increased along with the age of the concrete is monitored according to the strength change of the received signals.
The humidity node regulation and control unit is arranged on the dam concrete grid node and comprises a node controller, a gasifier, an electric control valve and a plurality of humidity diffusion tiles; the humidity diffusion tile is connected with an output port of the gasifier through an electric control valve; the control end of the gasifier and the electric control valve are respectively and electrically connected with the node controller.
The medium supply pipeline adopts a tree structure, the input end of the medium supply pipeline is connected with the medium compensation source, and the tail ends of all branches of the medium supply pipeline are connected with the humidity node regulation and control unit.
And the relay medium pressure control unit is used for carrying out relay reinforcement on the medium pressure of the medium supply pipeline, ensuring that the medium reaching the humidity node regulation and control unit has enough pressure, and driving the medium to be converted into gas through the gasifier, and then the gas is diffused to the concrete in the vertical line direction of the humidity diffusion tile through the gas-permeable film of the humidity diffusion tile.
The control mechanism adopts a decision machine and further comprises a humidity control industrial personal computer connected with the decision machine, and the humidity control industrial personal computer is respectively in communication connection with a controller of the medium compensation source and the relay medium pressure control unit.
The regulating medium adopts liquid with good fluidity, such as antifreeze and water, and also can adopt gas with gasification temperature close to the temperature of concrete.
Preferably, the humidity node control unit comprises 8 humidity diffusion tiles uniformly distributed along a spherical surface, and the perpendicular bisector of the diffusion surface of each humidity diffusion tile faces to the center of the grid where the humidity diffusion tile is located.
Furthermore, the diffusion surface of the humidity diffusion tile of the humidity node control unit is provided with a protection net.
Preferably, a pressure stabilizing valve is arranged at the connecting position of the medium supply pipeline and the gasifier of each humidity node regulating and controlling unit, the pressure stabilizing valve ensures that the pressure of the regulating and controlling medium of each humidity node regulating and controlling unit is kept stable, the phenomenon that the humidity diffusion tile is damaged due to the fact that the pressure of the regulating and controlling medium is too large is avoided, and the phenomenon that the gasification effect of the regulating and controlling medium is influenced due to the fact that the pressure of the regulating and controlling medium is too small is avoided.
Preferably, the concrete strength monitoring device and the humidity sensor group are respectively connected with a data processor, the output end of the data processor is connected with the control mechanism, the data processor performs consistency judgment on input signals, filters noise and abnormal data in the signals, and determines a corresponding value interval according to the signal value.
Preferably, the control mechanism comprises a decision machine, a knowledge base and a database, wherein rules for reasoning and decision making are stored in the knowledge base, and the rules comprise rule antecedents, namely preconditions, and rule postcedents, namely conclusions; and the decision machine is connected with the data processor, performs forward reasoning according to the numerical value interval of the sensor data of each grid acquired in real time and in combination with the rules of the knowledge base, finds a rule front piece which is most matched with the sensor data, and outputs a corresponding rule rear piece as a decision result to the humidity control industrial personal computer.
The control method of the intelligent humidity control dam comprises the following steps:
step 1: collecting concrete strength data of each concrete partition and concrete humidity, temperature and stress data of each concrete grid of each concrete partition; determining a real-time strength value of the concrete according to the concrete strength monitoring device;
step 2: calculating a humidity distribution field, a temperature distribution field and a stress distribution field of the dam by using finite elements;
and step 3: determining a humidity control target of each concrete partition according to the concrete strength of each concrete partition of the dam and the dam anti-cracking requirement;
and 4, step 4: determining a humidity regulation strategy of the concrete grid according to the real-time humidity, temperature, stress and strain data of the concrete grid and the humidity regulation target of the concrete partition;
and 5: sequentially and independently opening humidity diffusion tiles of a plurality of humidity node regulation and control units of the concrete grid, and calculating the humidity change rate of the concrete grid when the humidity diffusion tiles of the humidity node regulation and control units are independently opened according to real-time humidity data acquired by a humidity sensor in the concrete grid;
step 6: according to the humidity regulation and control requirements of the concrete grids, humidity diffusion tiles of a plurality of humidity node regulation and control units of the concrete grids are respectively controlled, and the humidity regulation and control of the concrete grids are implemented;
and 7: simulating the humidity diffusion process of the grid, calculating the humidity change rate in real time by using data acquired by a humidity sensor of the grid, comparing the humidity change rate with a simulation result, and judging whether the humidity node regulation unit fails or the concrete body structure in the grid is abnormal if the real-time humidity change rate is inconsistent with the simulation result;
and 8: the method comprises the steps of calculating a temperature distribution field, a humidity distribution field and a stress distribution field of a concrete grid in real time, inputting acquired data into a decision machine, adjusting the humidity control of the concrete grid in real time according to a decision result of the decision machine, reducing the humidity gradient and the temperature gradient of the concrete body, controlling the humidity strain increment, the temperature strain increment and the stress increment caused by humidity and temperature, and preventing the concrete body from cracking.
Preferably, the control mechanism utilizes the simulation system to perform simulation analysis of dam humidity, temperature, stress and strain distribution, and extracts rules for reasoning and decision from simulation results. The simulation system is based on a mathematical model of a concrete humidity field, a temperature field and a stress field in a model base and real-time collected humidity, temperature and stress data of a concrete grid output by a data processor, utilizes a Monte Carlo method to carry out simulation calculation on related uncertainty variables of dam concrete to obtain control effect data of the dam concrete humidity and temperature under different control strategies, and utilizes an FP-growth algorithm to extract association rules from the effect data of the dam concrete and corresponding state variables, environment variables and control variable data of the concrete and store the rules in a knowledge base.
Preferably, the humidity, temperature and stress data of the concrete grid, the corresponding state variable, environment variable, control variable and dam humidity regulation and control effect data are clustered and divided by adopting a K-means algorithm.
The FP-growth algorithm is utilized to intensively extract association rules for the effect data of the clustered dam concrete and the corresponding state variable, environment variable and control variable data of the concrete, and the specific process is as follows:
(1) the data set is scanned for the first time, resulting in a set of items with frequent items of 1. Defining minimum support degree, namely the minimum times of occurrence of the items, deleting the items smaller than the minimum support degree, and then arranging the items in the original data set according to the descending order of the item sets.
(2) The dataset is scanned a second time, creating an entry header table and FP-tree. When the FP tree is built, firstly, the data sets are scanned to count each data, the minimum support degree is set to be 2, the data sets are rearranged in a descending order, the data with the count smaller than 2 are deleted, the data list is adjusted again according to the occurrence frequency of the data, the FP tree is built, and the data list is added in sequence.
(3) And after the FP tree foundation is obtained, excavating a frequent item set. Firstly, obtaining a prefix path of a frequent item, and then constructing a conditional FP tree by taking the prefix path as a new data set; and then obtaining frequent items in the new FP tree and constructing a conditional FP tree according to the frequent items, and repeating the steps until only one frequent item is in the conditional FP tree.
(4) And constructing all possible rules by the frequent item set, and then calculating the confidence coefficient of each rule, wherein the rule meeting the condition of more than the minimum confidence coefficient is a reasonable association rule.
Compared with the prior art, the invention has the beneficial effects that:
1) according to the invention, the humidity node regulation and control unit is arranged at the grid node inside the concrete dam, and the diffusion surfaces of a plurality of humidity diffusion tiles outside the humidity node regulation and control unit respectively face the centers of adjacent concrete grids, so that the humidity diffusion from 8 angular points of the concrete grid volume unit to the direction of the grid central point is realized, the omnibearing humidity regulation and control can be carried out on each area of the dam, the strength and the timeliness of the humidity diffusion under the active humidity regulation and control requirements of concrete with different strengths are met, the concrete humidity gradient of the dam is eliminated, the concrete humidity stress increment is reduced, and the concrete can be effectively prevented from cracking;
2) the medium supply pipeline with the downward branch end of the tree structure is adopted, so that the branch pipeline is increased, the medium pressure control of the branch end is facilitated, and the gasification of the medium and the diffusion of the medium into the concrete are promoted by utilizing the gravity;
3) the method adopts the concrete strength monitoring device to monitor the strength of the concrete body of each partition of the dam in real time, determines the real-time strength value according to the signal change of the concrete strength monitoring device, and implements humidity regulation of different strategies aiming at the concrete with different strengths, thereby realizing accurate humidity regulation of the dam;
4) the control mechanism adopts a decision machine, a knowledge base, a model base and a database, adopts a simulation system to simulate and calculate control effect data of a dam humidity field, a temperature field, a stress field and a strain field of different control strategies under various uncertain conditions by utilizing a mathematical model of the model base, excavates association rules from the control effect data and stores the association rules into the knowledge base, utilizes the decision machine to combine grid humidity, temperature, stress and strain data acquired in real time to carry out forward reasoning to obtain a control strategy, and outputs the control strategy to an industrial personal computer and a humidity node regulation and control unit, thereby realizing intelligent regulation and control of the dam;
5) the invention takes account of the stress increment caused by temperature and humidity, calculates the stress field of dam concrete by utilizing finite elements, is convenient for dam operators to master the stress distribution of the dam in real time, and adopts corresponding dam operation management measures to improve the robustness of the dam.
Drawings
The invention is further illustrated by the following figures and examples.
Fig. 1 is a schematic view of an intelligent humidity control dam according to an embodiment of the present invention.
Fig. 2 is a schematic diagram of a concrete strength monitoring device according to an embodiment of the present invention.
Fig. 3 is a schematic structural diagram of a signal receiver of a concrete strength monitoring apparatus according to an embodiment of the present invention.
Fig. 4 is a schematic diagram of a humidity node control unit according to an embodiment of the present invention.
Fig. 5 is a cross-sectional view of a humidity node control unit according to an embodiment of the present invention.
Fig. 6 is a schematic diagram of humidity diffusion performed after the humidity diffusion tile of the humidity node control unit is opened.
Fig. 7 is a schematic view of a control mechanism according to an embodiment of the present invention.
Detailed Description
The invention is described in further detail below with reference to the figures and specific embodiments.
In the embodiment, the intelligent humidity control dam is arranged in western high-altitude areas and belongs to continental climates in the north temperate zone and the cold temperate zone. Dry climate, short spring and autumn, and long summer and winter. The summer is cool, the winter is severe cold, and the temperature is greatly different every year. The geographical latitude of the engineering place is high, and the solar radiation quantity is small. The hydraulic junction engineering barrage is a concrete hyperbolic arch dam, the maximum dam height is 240m, and the average annual temperature of the dam site is 2.8 ℃; the extreme highest temperature is 36.6 ℃; the lowest extreme temperature is-45 ℃; the average precipitation per year is 203.8 mm; actually measuring the maximum daily precipitation of 41.2mm and the average perennial evaporation capacity of 1447.5 mm; the average water surface evaporation capacity for many years is 883 mm; the average wind speed for many years is 2.4 m/s; the maximum wind speed is 35.1 m/s.
As shown in fig. 1, the intelligent humidity control dam comprises a concrete dam body 1, and a humidity node control unit 2, a medium supply pipeline 4, a relay medium pressure control unit 5 and a concrete strength monitoring device 6 which are arranged in the concrete dam body.
The medium compensation source 7 is arranged at the top of the intelligent humidity control dam, provides a temperature-variable control medium according to the active control requirement of the dam, and the temperature of the provided control medium is close to the temperature of dam concrete, so that the temperature of the dam concrete is prevented from being disturbed, and temperature difference and temperature stress are avoided.
In the embodiment, the dam body is divided into concrete grids according to the time characteristics of the intelligent humidity control dam compartment position pouring and the structural characteristics of the dam body. And concrete strength monitoring devices 6 are arranged in each bin partition of the dam. A humidity node regulation and control unit 2, a temperature sensor and a stress sensor are arranged on grid nodes, humidity sensors 3 are respectively arranged in a concrete grid and on the grid nodes, and the humidity node regulation and control unit 2 is connected with a medium supply pipeline 4. The medium supply pipeline 4 adopts a tree structure, and relay medium pressure regulating units 5 are arranged on a main pipeline of the medium supply pipeline 4 at intervals. The input of the medium supply line 4 is connected to a medium compensation source 7. In an embodiment, the conditioning medium is water.
The control end of the humidity node regulation and control unit 2 is connected with a control mechanism, the output ends of a humidity sensor 3, a temperature sensor and a stress sensor in the dam body are connected with a data processor, the output end of the data processor is connected with the control mechanism, the data processor respectively judges the consistency of input signals, filters noise and abnormal data in the signals, and determines a corresponding numerical value interval according to the signal numerical value.
As shown in fig. 7, the control mechanism includes a decision machine, a knowledge base, and a database, where rules for reasoning and decision are stored in the knowledge base, and the rules include rule antecedents, i.e., preconditions, and rule postcedents, i.e., conclusions; the decision machine is connected with the data processor, forward reasoning is carried out by the decision machine according to the numerical value interval of the sensor data of each grid acquired in real time and in combination with the rules of the knowledge base, a rule front piece which is most matched with the sensor data is found, a corresponding rule rear piece is taken as a decision result and is output to the humidity regulation industrial personal computer, and the relay medium pressure control unit and the controller of the medium compensation source are respectively connected with the humidity regulation industrial personal computer. The wireless communication base station 8 is connected with a humidity control industrial personal computer through a data bus.
As shown in fig. 4 and 5, the humidity node control unit 2 is a spherical structure, and includes a vaporizer 21, an electric control valve 22, and 8 humidity diffusion tiles 23; the humidity diffusion tile 23 is respectively connected with the output port of the gasifier through an electric control valve; a node controller and a wireless communication module are arranged in the humidity node regulation and control unit 2, a control end of the gasifier and the electric control valve are respectively connected with the node controller, the node controller is in communication connection with the wireless communication base station 8 through the wireless communication module, namely the node controller is connected with a humidity regulation and control industrial personal computer through a wireless network. The vaporizer 21 is centrally arranged inside the humidity node control unit 2, is connected to the medium supply line 4, and receives a control medium from the medium compensation source 7. The vaporizer 21 is connected with 8 humidity diffusion tiles 23 through 8 conduits, and each conduit is provided with an electric control valve 22. The 8 humidity diffusion tiles of the humidity node regulation and control unit are uniformly distributed along the spherical surface, and the diffusion surface of each humidity diffusion tile 23 faces to the center of the concrete grid where the humidity diffusion tile 23 is located. The outer side of the humidity diffusion tile 23 adopts a double-layer structure, and the inner layer is a breathable impermeable material film-shaped structure 231, so that the regulation and control medium gas can penetrate and diffuse into the surrounding concrete conveniently; the outer layer is a net-shaped structure 232 formed by firm materials and used for protecting the outer side of the humidity node regulation and control unit and preventing the concrete from being damaged in the pouring process. As shown in fig. 6, when the solenoid valve of the humidity diffusion tile 23 of the humidity node control unit 2 is turned on, the control medium penetrates the diffusion surface of the humidity diffusion tile 23 and diffuses directionally into the concrete.
In the embodiment, a pressure stabilizing valve is installed at the connection position of the medium supply pipeline 4 and the vaporizer 21 of each humidity node regulation and control unit 2, and ensures that the pressure of the regulation and control medium of each humidity node regulation and control unit is kept stable, so that the condition that the breathable film of the humidity diffusion tile is damaged due to the overhigh pressure of the regulation and control medium is avoided, and the condition that the pressure of the regulation and control medium is too low affects the vaporization effect of the regulation and control medium is avoided.
As shown in fig. 2 and 3, the concrete strength monitoring device 6 comprises a signal transmitter 61 and a signal receiver 62 which are arranged in pairs in the concrete body of the dam, wherein the signal receiver receives signals generated by the signal transmitter and monitors the concrete strength change along with the increase of the concrete age according to the strength change of the received signals; the signal receiver 62 comprises a piezoelectric ceramic piece 623, an epoxy resin protective film 622 and a stainless steel shell 624, and the output end of the piezoelectric ceramic piece 623 is connected with the data processor through a cable 621. The signal transmitter 61 and the signal receiver 62 have the same structure.
The control method of the intelligent humidity control dam specifically comprises the following steps:
step 1: the method comprises the steps that a concrete strength monitoring device is used for collecting concrete strength data of each bin partition of a dam in real time, and a humidity sensor, a temperature sensor and a stress sensor are used for collecting concrete humidity, temperature and stress data of each concrete grid of each bin partition in real time; respectively carrying out consistency judgment on input signals by using a data processor, filtering noise and abnormal data in the signals, determining a corresponding numerical value interval according to the numerical value of the signals, and acquiring the concrete strength value of each bin partition in real time according to the concrete strength monitoring device of each bin partition;
the concrete of position in a storehouse subregion has different intensity when being in different ages, and the signal energy value that concrete intensity detection device detected is all inequality, and the signal that concrete intensity detection device's signal transmitter produced pierces through the concrete body and is received by signal receiver, and the concrete intensity is different, and the loss degree of the signal of receiving is inequality, calculates signal receiver's detected signal's energy ratio
R1Representing the ratio of the energy of the signal received by the signal receiver at the current moment to the energy of the transmitted signal, EaRepresenting the energy value of the real-time detection signal of the signal receiver of the concrete strength detection device, E representing the energy value of the transmission signal of the signal transmitter, R1Is inverse number of
The strength of the concrete is reflected.
In the embodiment, a test concrete body is manufactured according to the same concrete mixing proportion of dam concrete, a concrete strength monitoring device is arranged in the test concrete body, the ratio of the energy of a signal receiver receiving signal to the energy of a transmitting signal of the concrete strength monitoring device when the test concrete body is in different ages is collected and calculated, and a curve equation of the energy ratio and the concrete strength is fitted. The data processor collects data in real time according to the intensity monitoring device of the concrete of each bin position subarea collected and calculated in real time, and calculates to obtain the concrete implementation intensity value of each bin position subarea by combining the energy ratio.
Step 2: combining humidity, temperature and stress data acquired by a sensor in real time, and calculating a humidity distribution field, a temperature distribution field and a stress distribution field of the dam by using a finite element;
and step 3: determining a humidity control target of each concrete partition according to the concrete strength of each concrete partition of the dam and the dam anti-cracking requirement;
and 4, step 4: determining a humidity regulation strategy of the concrete grid according to the real-time humidity, temperature, stress and strain data of the concrete grid and the humidity regulation target of the concrete partition;
and 5: sequentially and independently opening humidity diffusion tiles of a plurality of humidity node regulation and control units of the concrete grid, and calculating the humidity change rate of the concrete grid when the humidity diffusion tiles of the humidity node regulation and control units are independently opened according to real-time humidity data acquired by a humidity sensor in the concrete grid;
step 6: according to the humidity regulation and control requirements of the concrete grids, humidity diffusion tiles of a plurality of humidity node regulation and control units of the concrete grids are respectively controlled, and the humidity regulation and control of the concrete grids are implemented;
and 7: simulating the humidity diffusion process of the grid, calculating the humidity change rate in real time by using data acquired by a humidity sensor of the grid, comparing the humidity change rate with a simulation result, and judging whether the humidity node regulation unit fails or the concrete body structure in the grid is abnormal if the real-time humidity change rate is inconsistent with the simulation result;
and 8: the method comprises the steps of calculating a temperature distribution field, a humidity distribution field and a stress distribution field of a concrete grid in real time, inputting acquired data into a decision machine, adjusting the humidity control of the concrete grid in real time according to a decision result of the decision machine, reducing the humidity gradient and the temperature gradient of the concrete body, controlling the humidity strain increment, the temperature strain increment and the stress increment caused by humidity and temperature, and preventing the concrete body from cracking.
The diffusion of humidity in concrete satisfies the following equation:
m＝-D×grad(P) (1)
wherein m is the humidity flow; d is humidity diffusion coefficient: p is the driving force, i.e. relative humidity; grad () represents a gradient operator;
the humidity diffusion equation obtained from equation (1) and conservation of humidity is as follows:
wherein h ═ h (x, y, z, t) is the relative humidity distribution of the concrete; d is the humidity diffusion coefficient;
the rate of loss from dry relative humidity is caused by the consumption of water by the concrete gel hydration reaction, and its value depends mainly on the properties of the compound itself;
the initial conditions were:
h(x，y,z,0)＝h0(x,y,z) (3)
in the formula h0(x, y, z) is the initial relative humidity profile of the concrete;
the humidity field boundary conditions fall into three categories:
1) concrete surface humidity is a known function of time:
h(x,y,z,t)＝f(x,y,z,t) (4)
2) the moisture insulation boundary:
3) for concrete in air boundary conditions were:
wherein f (x, y, z, t) is a known function that varies with time;
is the moisture gradient on the dry surface along the boundary unit normal; f is the surface water exchange coefficient hsIs a surface is opposite toHumidity; h iseAmbient relative humidity;
according to the variation principle, the solution requiring the solution to satisfy the expressions (1) to (5) is equivalent to solving the extremum min I (h) of the following functional:
wherein alpha represents the diffusion coefficient of humidity, H0iThe maximum hydration consumption of the ith area is,
is the self-drying relative humidity loss rate, λ is the surface humidity exchange coefficient, h is the surface humidity value, h isaIs the air humidity value;
r is to betThe zones are discretized by finite elements and the humidity pattern of each unit is taken as:
where m is the number of unit nodes, NiAs a function of cell shape, HiIs the cell node temperature.
Solving for R using finite elementstHumidity field of the area.
The humidity diffusion equation for the humidity diffusion tile is as follows:
wherein h ═ h (x, y, z, t) is the initial relative humidity distribution of the concrete; d is the humidity diffusion coefficient;
the rate of loss from dry relative humidity is caused by the consumption of water by the concrete gel hydration reaction, and its value depends mainly on the properties of the compound itself,
the humidity diffusion tile is replenished with the rate of humidity increase when opened.
In step 2, the grid volume RiThe definite solution equation of the concrete temperature field in (i ═ 1,2, … …, n) is:
in the formula, tau represents time, and T represents time,
to coefficient of thermal conductivity, θ0iIs the maximum adiabatic temperature rise, T, of the ith concrete gridi0Is the initial temperature, T, of the first concrete gridiwTemperature of the medium, phi, of the medium supply line for the ith concrete gridiTemperature reduction function for the medium supply line psiiIs an equivalent negative heat source function;
Riboundary S ofiThree types of boundaries are included:
Si＝Si1∪Si2∪Si3 (11)
boundary of the first kind Si1The upper temperature is known, and the boundary conditions are:
T＝Tb(t) (12)
wherein T isbGiven temperature, such as known ground temperature, water temperature;
second type boundary Si2For an adiabatic boundary, the boundary condition can be expressed as:
boundary of the third kind Si3The temperature gradient is proportional to the difference between the internal and external temperatures and can be expressed as:
wherein λ is the thermal conductivity, TaIs the air temperature, beta is the surface heat release coefficient;
according to the variational principle, a solution requiring a solution satisfying the equations (10) to (14) is equivalent to solving an extremum min I (T) of the following functional:
r is to beiThe grid area is discretized by finite elements, and the temperature mode of each unit is taken as:
where m is the number of unit nodes, NiAs a function of cell shape, TiIs the cell node temperature;
solving for R using finite elementsiTemperature field of the grid area.
Considering the influence of humidity load, temperature load and concrete creep, solving a creep stress field according to a finite element implicit solution, wherein the basic equation is as follows:
in the formula [ K]Representing a stiffness matrix; { DeltanRepresents a node displacement increment vector; { Delta PnRepresents the external load increment;
indicating the load increment caused by humidity;
represents the temperature induced load increase;
represents the dry shrinkage strain increment;
indicating the increment of load caused by self volume deformation.
The stress increment Δ σ is calculated by the following equation:
in the formula [ Dn]Representing an elasticity matrix; [ B ]]Representing a geometric matrix;
represents the humidity strain increase;
representing a creep strain increment;
indicating an increase in temperature strain;
representing the self volume deformation;
for each time step, solving the stress increment according to the formula (18), and superposing the stress increment with the stress of the previous time step to obtain:
{σn}＝{σn-1)+{Δσn} (19)
aiming at the ith moment of simulation analysis, in a dam concrete subarea region gamma, the temperature increment and the humidity increment in a subarea j are taken as targets, and an objective function is established:
fTH-i＝wTΔTij+wHΔHij (20)
in the formula fTH-iRepresenting the weighted sum, Δ T, of the temperature increase and the humidity increase of the sub-zone j at time iijIs time iTemperature increase of sub-region j; Δ HijIs the humidity increase of sub-zone j at time i. WT、wHWeight factors, w, representing temperature and humidity increments, respectivelyT+wH＝1。
If the combined action of the temperature increment and the humidity increment on the region j is strain, the influence of the dimension between the temperature increment and the humidity increment can be eliminated by adopting the formula (21), and if the temperature strain and the humidity strain are linear relations, the following steps are provided:
and obtaining a weighting factor of the temperature increment and the humidity increment.
Considering that the compressive strength of concrete is far greater than the tensile strength, the negative strain caused by the temperature and humidity increment is unfavorable. Therefore, an objective function under the condition of maximum negative strain caused by temperature and humidity increment in the concrete subarea region gamma at the moment i needs to be searched as a utility function:
Fi＝Min{fTH-1，fTH-2,fTH-3…fTH-n} (22)
wherein n is the number of sub-regions within concrete subregion Γ.
According to the simulation result, the utility function values at all moments in the temperature adjusting process are obtained, the minimum value of the utility function in the whole process is taken as the most unfavorable condition, and the regulation and control effect is evaluated by the value:
Fe＝Min{F0,F1,F2…Fm} (23)
i.e. the control effect variable F of the control strategyeThe larger the strain, the smaller the negative strain caused by the regulation and control process, and the better the control effect.
The control mechanism utilizes the simulation system to perform simulation analysis on the distribution of the dam humidity, temperature, stress and strain, and extracts rules for reasoning and decision from simulation results. The simulation system is based on a mathematical model of a concrete humidity field, a temperature field and a stress field in a model base and real-time collected humidity, temperature and stress data of a concrete grid output by a data processor, utilizes a Monte Carlo method to carry out simulation calculation on related uncertainty variables of dam concrete to obtain control effect data of the dam concrete humidity, temperature, stress and strain under different control strategies, utilizes an FP-grow algorithm to extract association rules from the effect data of the dam concrete and corresponding state variables, environment variables and control variable data of the concrete, and stores the association rules into a knowledge base.
And respectively clustering and dividing humidity, temperature and stress data of the concrete grid, corresponding state variables, environment variables, control variables and dam humidity regulation and control effect data by adopting a K-means algorithm. The K-means algorithm of the embodiment refers to a K-means algorithm disclosed in 'case prediction application based on K-means algorithm' paper of Wangjianhao et al published in journal computer and digital engineering 2019, 8 th edition.
The FP-growth algorithm is utilized to intensively extract association rules for the effect data of the clustered dam concrete and the corresponding state variable, environment variable and control variable data of the concrete, and the specific process is as follows:
(1) the data set is scanned for the first time, resulting in a set of items with frequent items of 1. Defining minimum support degree, namely the minimum times of occurrence of the items, deleting the items smaller than the minimum support degree, and then arranging the items in the original data set according to the descending order of the item sets.
(2) The dataset is scanned a second time, creating an entry header table and FP-tree. When the FP tree is built, firstly, the data sets are scanned to count each data, the minimum support degree is set to be 2, the data sets are rearranged in a descending order, the data with the count smaller than 2 are deleted, the data list is adjusted again according to the occurrence frequency of the data, the FP tree is built, and the data list is added in sequence.
(3) And after the FP tree foundation is obtained, excavating a frequent item set. Firstly, obtaining a prefix path of a frequent item, and then constructing a conditional FP tree by taking the prefix path as a new data set; and then obtaining frequent items in the new FP tree and constructing a conditional FP tree according to the frequent items, and repeating the steps until only one frequent item is in the conditional FP tree.
(4) And constructing all possible rules by the frequent item set, and then calculating the confidence coefficient of each rule, wherein the rule meeting the condition of more than the minimum confidence coefficient is a reasonable association rule.
In the embodiment, after one bin of the intelligent humidity control dam is successfully poured for one day, the humidity distribution condition inside concrete is changed, when the relative humidity inside the concrete is lower than 80%, the hydration heat reaction of the concrete tends to stop, the durability of the concrete is influenced by early drying of the concrete in the pouring process, and the strength and the impermeability of the concrete are greatly influenced. If the environment of the early concrete is not kept with sufficient humidity, a large amount of water in the concrete can be evaporated, on one hand, hydration heat reaction is influenced due to drying dehydration, and on the other hand, tensile stress caused by shrinkage of the concrete under low strength is borne due to drying shrinkage reaction, so that cracks are generated on the surface of the concrete, and the strength of the concrete is influenced. After the dam is poured for 1 day, the decision machine finds out the most matched rule from the knowledge base according to the real-time humidity, temperature and stress data of the bin partitions output by the data processor and the corresponding intervals of the bin partitions, a decision result is obtained, a control instruction is output to the humidity control industrial personal computer, the humidity control industrial personal computer outputs control signals to all humidity node control units of the bin partitions respectively, the humidity diffusion tiles are opened, and active humidity control is carried out on all concrete grids of the bin partitions, so that the humidity of concrete in all the concrete grids of the bin partitions is not lower than 90%. Through controlling the inside humidity of concrete, make the concrete can fully carry out the hydration heat reaction, avoid leading to because the hydration heat reaction is incomplete to cause the concrete intensity can't reach the expected value, and then lead to the crack influence concrete dam whole operation safety that partial region concrete leads to because the shrinkage deformation.
Claims (10)
1. The intelligent humidity control dam is characterized by comprising a dam body, and a concrete strength monitoring device, a humidity sensor group, a medium supply pipeline, a humidity node control unit, a medium compensation source and a control mechanism which are arranged in the dam body;
the concrete strength monitoring device comprises a signal transmitter and a signal receiver which are arranged in a concrete body in pairs, wherein the signal receiver receives signals of the signal transmitter and monitors the concrete strength change increased along with the age of the concrete according to the strength change of the received signals; the humidity node regulation and control unit is arranged on the dam concrete grid node and comprises a node controller, a gasifier, an electric control valve and a plurality of humidity diffusion tiles; the humidity diffusion tile is connected with an output port of the gasifier through an electric control valve; the control end of the gasifier and the electric control valve are respectively and electrically connected with the node controller;
the medium supply pipeline adopts a multi-branch structure, the input end of the medium supply pipeline is connected with the medium compensation source, and the tail ends of all branches of the medium supply pipeline are connected with the humidity node regulation and control unit; a relay medium pressure regulating unit is arranged on the medium supply pipeline;
a relay medium pressure control unit for performing relay reinforcement on the medium pressure of the medium supply pipeline;
the control mechanism adopts a decision machine and further comprises a humidity control industrial personal computer connected with the decision machine, and the humidity control industrial personal computer is respectively in communication connection with a controller of the medium compensation source and the relay medium pressure control unit.
2. The intelligent humidity control dam of claim 1, wherein the diffusion surface of the humidity diffusion tile of the humidity node control unit is provided with a protective mesh.
3. The intelligent humidity control dam of claim 1, wherein the humidity node control unit comprises 8 humidity diffusion tiles uniformly distributed along a spherical surface, and a perpendicular bisector of a diffusion surface of each humidity diffusion tile faces to the center of all grids of the humidity diffusion tiles.
4. The intelligent humidity control dam of claim 1, wherein the concrete strength monitoring device and the humidity sensor group are respectively connected with a data processor, an output end of the data processor is connected with the control mechanism, the data processor performs consistency judgment on input signals, filters noise and abnormal data in the signals, and determines corresponding numerical value intervals according to the signal numerical values.
5. The intelligent humidity control dam of claim 1, wherein the control mechanism comprises a decision machine, a knowledge base and a database, wherein rules for reasoning and decision making are stored in the knowledge base, and the rules comprise rule antecedent parts, namely preconditions, and rule postconclusion parts, namely conclusions; and the decision machine is connected with the data processor, performs forward reasoning according to the numerical value interval of the sensor data of each grid acquired in real time and in combination with the rules of the knowledge base, finds a rule front piece which is most matched with the sensor data, and outputs a corresponding rule rear piece as a decision result to the humidity control industrial personal computer.
6. A control method of an intelligent humidity conditioning dam as claimed in any one of claims 1 to 5, comprising the steps of:
step 1: collecting concrete strength data of each concrete partition of the dam and concrete humidity, temperature and stress data of each concrete grid of each concrete partition; calculating the real-time strength value of the concrete according to the signal change of the concrete strength monitoring device;
step 2: calculating a humidity distribution field, a temperature distribution field and a stress distribution field of the dam by using finite elements;
and step 3: determining a humidity control target of each concrete partition according to the concrete strength of each concrete partition of the dam and the dam anti-cracking requirement;
and 4, step 4: determining a humidity regulation strategy of the concrete grid according to the real-time humidity, temperature, stress and strain data of the concrete grid and the humidity regulation target of the concrete partition;
and 5: sequentially and independently opening humidity diffusion tiles of a plurality of humidity node regulation and control units of the concrete grid, and calculating the humidity change rate of the concrete grid when the humidity diffusion tiles of the humidity node regulation and control units are independently opened according to real-time humidity data acquired by a humidity sensor in the concrete grid;
step 6: according to the humidity regulation and control requirements of the concrete grids, humidity diffusion tiles of a plurality of humidity node regulation and control units of the concrete grids are respectively controlled, and the humidity regulation and control of the concrete grids are implemented;
and 7: simulating the humidity diffusion process of the grid, calculating the humidity change rate in real time by using data acquired by a humidity sensor of the grid, comparing the humidity change rate with a simulation result, and judging whether the humidity node regulation unit fails or the concrete body structure in the grid is abnormal if the real-time humidity change rate is inconsistent with the simulation result;
and 8: the method comprises the steps of calculating a temperature distribution field, a humidity distribution field and a stress distribution field of a concrete grid in real time, inputting acquired data into a decision machine, adjusting the humidity control of the concrete grid in real time according to a decision result of the decision machine, reducing the humidity gradient and the temperature gradient of the concrete body, controlling the humidity strain increment, the temperature strain increment and the stress increment caused by humidity and temperature, and preventing the concrete body from cracking.
7. The control method according to claim 6, wherein the diffusion of humidity in the concrete satisfies the following equation: m ═ -D × grad (p) (1)
Wherein m is the humidity flow; d is humidity diffusion coefficient: p is the driving force, i.e. relative humidity; grad () represents a gradient operator;
the humidity diffusion equation obtained from equation (1) and conservation of humidity is as follows:
wherein h ═ h (x, y, z, t) is the relative humidity distribution of the concrete; d is the humidity diffusion coefficient;
the rate of loss from dry relative humidity is caused by the consumption of water by the concrete gel hydration reaction, and its value depends mainly on the properties of the compound itself;
the initial conditions were:
h(x,y,z,0)＝h0(x,y,z) (3)
in the formula h0(x, y, z) is the initial relative humidity profile of the concrete;
the humidity field boundary conditions fall into three categories:
1) concrete surface humidity is a known function of time:
h(x,y,z,t)＝f(x,y,z,t) (4)
2) the moisture insulation boundary:
3) for concrete in air boundary conditions were:
wherein f (x, y, z, t) is a known function that varies with time;
is the moisture gradient on the dry surface along the boundary unit normal; f is the surface water exchange coefficient hsSurface relative humidity; h iseAmbient relative humidity;
according to the variation principle, the solution requiring the solution to satisfy the expressions (1) to (5) is equivalent to solving the extremum min I (h) of the following functional:
wherein alpha represents the diffusion coefficient of humidity, H0iThe maximum hydration consumption of the ith area is,
is the self-drying relative humidity loss rate, lambda is the surface humidity exchange coefficient, h is the tableSurface humidity value, haIs the air humidity value;
r is to betThe zones are discretized by finite elements and the humidity pattern of each unit is taken as:
where m is the number of unit nodes, NiIs a unit shape function, hiIs the cell node temperature;
solving for R using finite elementstHumidity field of the area.
8. The control method of claim 7, wherein the humidity diffusion equation of the humidity diffusion tile is as follows:
wherein h ═ h (x, y, z, t) is the initial relative humidity distribution of the concrete; d is the humidity diffusion coefficient;
the rate of loss from dry relative humidity is caused by the consumption of water by the concrete gel hydration reaction, and its value depends mainly on the properties of the compound itself,
the humidity diffusion tile is replenished with the rate of humidity increase when opened.
9. Control method according to claim 8, characterized in that in step 2, the grid volume RiThe definite solution equation of the concrete temperature field in (i ═ 1,2, … …, n) is:
wherein τ represents time, α is temperature coefficient, and θ0iIs the maximum adiabatic temperature rise, T, of the ith concrete gridi0Is the initial temperature, T, of the ith concrete gridiwTemperature of the medium, phi, of the medium supply line for the ith concrete gridiTemperature reduction function for the medium supply line psiiIs an equivalent negative heat source function;
Riboundary S ofiThree types of boundaries are included:
Si＝Si1∪Si2∪Si3 (11)
boundary of the first kind Si1The upper temperature is known, and the boundary conditions are:
T＝Tb(t) (12)
wherein T isbIs a given temperature;
second type boundary Si2For an adiabatic boundary, the boundary condition can be expressed as:
boundary of the third kind Si3The temperature gradient is proportional to the difference between the internal and external temperatures and can be expressed as:
wherein λ is the thermal conductivity, TaIs the air temperature, beta is the surface heat release coefficient;
according to the variational principle, a solution requiring a solution satisfying the equations (10) to (14) is equivalent to solving an extremum min I (T) of the following functional:
r is to beiThe grid area is discretized by finite elements, and the temperature of each unit is takenThe degree mode is:
where m is the number of unit nodes, NiAs a function of cell shape, TiIs the cell node temperature;
solving for R using finite elementsiTemperature field of the grid area.
10. The control method of claim 9, wherein the creep stress field is obtained by a finite element implicit solution taking into account the humidity load, the temperature load and the concrete creep effect, and the basic equation is as follows:
in the formula [ K]Representing a stiffness matrix; { DeltanRepresents a node displacement increment vector; { Delta PnRepresents the external load increment;
indicating the load increment caused by humidity;
represents the temperature induced load increase;
represents the dry shrinkage strain increment;
representing the load increment caused by self volume deformation;
the stress increment Δ σ is calculated by the following equation:
in the formula [ Dn]Representing an elasticity matrix; [ B ]]Representing a geometric matrix;
represents the humidity strain increase;
representing a creep strain increment;
indicating an increase in temperature strain;
representing the self volume deformation;
for each time step, solving the stress increment according to the formula (18), and superposing the stress increment with the stress of the previous time step to obtain:
{σn}＝{σn-1)+{Δσn} (19)。
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