CN112561246A - Intelligent control method for mass concrete quality - Google Patents
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Abstract
The invention provides an intelligent control method for mass concrete quality, which enables concrete pouring to be free from the influence of high temperature in summer, cold in winter, strong wind and the like through a modular maintenance factory building structure with an expandable size, can detect the temperature and humidity of each area in the maintenance factory building, controls a spraying system to adjust the temperature and humidity of the surface of concrete, realizes real-time detection and intelligent prediction of change trend of the internal temperature of the concrete through embedding a sensor and a condensate pipe in the concrete, and realizes automatic control of circulating water in the condensate pipe by using a control algorithm, thereby effectively improving the mass concrete pouring quality and ensuring the safety and reliability of engineering quality and operation of power transmission and transformation equipment.
Description
Technical Field
The invention relates to the technical field of power transmission and transformation engineering construction, in particular to an intelligent control method for mass concrete quality.
Background
In the construction of power transmission and transformation projects, a GIS foundation, a reactor foundation, an independent lightning rod foundation and the like all adopt large-volume concrete structures. The quality problems of bulging, cracks, even fracture and the like caused by complex phenomena such as initial stress, internal transfer and the like in the large-volume concrete can be caused by temperature, humidity and environmental factors, and the normal operation of power transmission and transformation is further influenced. Therefore, the large-volume concrete pouring plays a very important role in the construction of power transmission and transformation projects, and how to ensure the quality of the concrete in the process of the project construction plays a decisive role in the whole project quality and the safety of power transmission and transformation equipment.
In order to improve the pouring quality of mass concrete, the internal and external temperature and humidity need to be accurately controlled during concrete curing so as to prevent the quality problems of cracks, bulging and the like of the concrete. Meanwhile, when calendaring and slitting operation are carried out, the calendaring and slitting operation is carried out under the external conditions of proper wind speed, temperature and illumination, so that better appearance quality is achieved.
Through the manual temperature measurement of intervallity in traditional concrete maintenance construction, the inside temperature variation condition of concrete has been reflected to a certain extent, nevertheless suffers from the not enough of prior art, and the scene can't realize continuous temperature measurement, can't real-time accurate prediction future temperature variation trend to cause accuse temperature, accuse wet measure lag, reached best maintenance condition and optimal design performance index. The concrete curing process is also easily influenced by the external environment, and the subjective decision of constructors facing various external variables further causes the entity quality to be uneven.
Disclosure of Invention
The invention aims to provide an intelligent control method for mass concrete quality, which aims to solve the problems of poor concrete curing condition and low performance index in the prior art, improve the mass concrete pouring quality and ensure the engineering quality and the safety and reliability of the operation of power transmission and transformation equipment.
In order to achieve the technical purpose, the invention provides an intelligent control method for mass concrete quality, which comprises the following operations:
designing a modular maintenance plant with an expandable size, collecting climate element information on the surface of concrete, and controlling the temperature and humidity of the surface of the concrete through automatic spraying;
embedding a replaceable embedded sensing device in concrete, collecting the internal temperature of the concrete, and carrying out centralized collection and remote transmission on collected temperature data signals;
predicting the internal temperature change trend of the concrete in real time by adopting a support vector regression-based prediction model, and optimizing the parameters of the prediction model based on grid search and K-fold cross validation to obtain optimal parameters and obtain a temperature change prediction result;
and according to a real-time prediction result, designing a self-adaptive controller based on a neural network, performing self-adaptive compensation by adopting fuzzy Smith pre-estimation compensation, eliminating steady state deviation, controlling the rotating speed of a condensate water circulating motor in the concrete, and controlling the internal temperature of the concrete.
Preferably, the modularized maintenance plant adopts a light plastic steel pipe as a framework, and a main framework mechanism with the shape capable of being changed at will is formed through a connecting piece.
Preferably, the concrete surface climate element information includes humidity, relative humidity and heat radiation.
Preferably, the replaceable embedded sensing device comprises a data transmission line, an inner steel pipe, an outer steel pipe, an asphalt layer and a sensor, wherein the data transmission line is arranged inside the inner steel pipe, the data transmission end is connected with the sensor, the outer steel pipe is sleeved outside the inner steel pipe, and the outer side of the outer steel pipe is provided with the asphalt layer.
Preferably, the predicting model parameter optimization based on grid search and K-fold cross validation specifically comprises:
establishing grid coordinates, dividing a grid by using an exponential function, and enabling a to be (-m, m) and b to be (-n, n), wherein the grid point coordinates of model parameters are (c, g) to be (2a, 2 b);
dividing samples, equally dividing the original samples into K groups by using a K-fold cross verification method, taking each group as a verification set in turn, and testing models obtained by training other K-1 groups;
determining a prediction error, and taking the average value of the mean square errors of the K times of test results as a performance index of the model;
and determining an optimal parameter combination, and after the parameter combinations at all the cross points on the grid are subjected to K-fold cross validation, determining the parameter combination corresponding to the minimum mean square error value as the optimal parameter of the model.
Preferably, the controlling of the internal temperature of the concrete is specifically:
the temperature value set externally and the acquired temperature measurement value are transmitted to the control part of the microprocessor simultaneously, the deviation between the set value and the actual value is calculated, the output control quantity is obtained according to a pre-designed control algorithm, and the rotating speed of the motor of the condensed water circulation system is controlled in a certain period.
The effect provided in the summary of the invention is only the effect of the embodiment, not all the effects of the invention, and one of the above technical solutions has the following advantages or beneficial effects:
compared with the prior art, the invention has the advantages that through the modular maintenance factory building structure with the expandable size, the concrete pouring is not influenced by high temperature in summer, cold in winter, strong wind and the like, the temperature and the humidity of each area in the maintenance factory building can be detected, the temperature and the humidity of the surface of the concrete can be adjusted by controlling the spraying system, the real-time detection and the intelligent prediction of the variation trend of the internal temperature of the concrete are realized through embedding the sensor and the condensate pipe in the concrete, and the automatic control of the circulating water in the condensate pipe is realized by utilizing a control algorithm, so the pouring quality of the large-volume concrete is effectively improved, and the safety and the reliability of the operation of engineering quality and.
Drawings
FIG. 1 is a flow chart of a mass concrete quality intelligent control method provided in the embodiment of the present invention;
FIG. 2 is a schematic diagram of an embodiment of intelligent mass concrete quality control provided in the examples of the present invention;
FIG. 3 is a schematic diagram of a main structure of an alternative embedded sensing device provided in an embodiment of the present invention;
FIG. 4 is an alternative schematic view of a sensor provided in an embodiment of the present invention;
FIG. 5 is a schematic diagram of a temperature control structure for condensed water in concrete according to an embodiment of the present invention;
FIG. 6 is a schematic diagram of temperature control provided in an embodiment of the present invention;
in the figure, 1-data transmission line, 2-inner steel tube, 3-outer steel tube, 4-asphalt layer, 5-sensor, 6-latex cement, 7-concrete, 8-new sensor, and 9-old sensor.
Detailed Description
In order to clearly explain the technical features of the present invention, the following detailed description of the present invention is provided with reference to the accompanying drawings. The following disclosure provides many different embodiments, or examples, for implementing different features of the invention. To simplify the disclosure of the present invention, the components and arrangements of specific examples are described below. Furthermore, the present invention may repeat reference numerals and/or letters in the various examples. This repetition is for the purpose of simplicity and clarity and does not in itself dictate a relationship between the various embodiments and/or configurations discussed. It should be noted that the components illustrated in the figures are not necessarily drawn to scale. Descriptions of well-known components and processing techniques and procedures are omitted so as to not unnecessarily limit the invention.
The following describes an intelligent control method for mass concrete quality according to an embodiment of the present invention in detail with reference to the accompanying drawings.
As shown in fig. 1-6, the invention discloses a mass concrete quality intelligent control method, which comprises the following operations:
designing a modular maintenance plant with an expandable size, collecting climate element information on the surface of concrete, and controlling the temperature and humidity of the surface of the concrete through automatic spraying;
embedding a replaceable embedded sensing device in concrete, collecting the internal temperature of the concrete, and carrying out centralized collection and remote transmission on collected temperature data signals;
predicting the internal temperature change trend of the concrete in real time by adopting a support vector regression-based prediction model, and optimizing the parameters of the prediction model based on grid search and K-fold cross validation to obtain optimal parameters and obtain a temperature change prediction result;
and according to a real-time prediction result, designing a self-adaptive controller based on a neural network, performing self-adaptive compensation by adopting fuzzy Smith pre-estimation compensation, eliminating steady state deviation, controlling the rotating speed of a condensate water circulating motor in the concrete, and controlling the internal temperature of the concrete.
The maintenance factory building structure of the expanded size of design, factory building adopt light-duty plastic steel pipe spare to be the skeleton, form the main skeleton mechanism that can change the shape wantonly through the connecting piece, satisfy the modular demand, realize easy equipment, quick dismantlement's requirement, the skeleton outside adopts insulation material and glass material, realizes the interaction with the environment outside the factory building. The inside spraying system who can dismantle, assemble in a flexible way that sets up of factory building can effectively reduce the interior concrete surface temperature of maintenance factory building in hot summer, improves surface humidity, and when the temperature was lower winter, accessible steam generator sprayed high-temperature steam, improves and pours operation ambient temperature, reaches the purpose that the operation of pouring does not receive the influence in season.
Through collection equipment, to concrete surface climate key element information, including humidity, relative humidity and heat radiation etc. gather in real time, utilize wireless mode to upload to the server in real time. Through carrying out real-time analysis to a large amount of data of gathering to contrast with the control by temperature change standard of formulating in advance, and then control on-the-spot spraying equipment automatically, with the effective regulation and control that realizes the subregion, finally make concrete surface humiture adjust to ideal state.
And for the real-time monitoring of the internal temperature of the concrete, the real-time monitoring is carried out through the concrete embedded sensor technology. By improving the packaging effect of the sensor, the reliability of the sensor can be improved. The replaceable embedded sensing device comprises a data transmission line, an inner steel pipe, an outer steel pipe, an asphalt layer and a sensor, wherein the data transmission line is arranged inside the inner steel pipe, a data transmission end is connected with the sensor, the outer steel pipe is sleeved outside the inner steel pipe, and the outer side of the outer steel pipe is provided with the asphalt layer. The whole sensing device is fixed on a steel bar framework or a template, so that the asphalt layer end of the device just reaches the surface of a concrete member after pouring, and in order to achieve the purpose, an arc-shaped pore channel is adopted for pouring. When the concrete is poured, the sensor is in close contact with the concrete and works in cooperation with the concrete. When the sensing device is to be replaced, the sensing device is heated and melted through the outer steel pipe from the outer surface of the concrete structure to remove the asphalt layer, the outer steel pipe is rotated to break the connection between the asphalt layer and the concrete, so that the asphalt can be smoothly cleaned out, and even if the asphalt cannot be directly pulled out, the heat can be conducted through the outer steel pipe to accelerate the melting of the asphalt layer. And the sensor is ensured to be firmly connected with the concrete through latex cement so as to ensure cooperative work. After the latex cement is solidified, the sensor can work normally.
The temperature acquisition sensor carries out data communication through a technical protocol, transmits temperature data to the sink node through a GPRS wireless network, and completes centralized collection and remote transmission of internal area temperature data signals through an RS485 network. After receiving the real-time temperature data signals collected by the temperature sensors, the data concentrator at the sink node transmits data to the local area network through the internal RS485 serial port, so that the data can be conveniently read and analyzed by station control layer equipment such as a station control layer operator workstation and an engineer workstation. And the data processing unit receives the temperature data signal, forms corresponding temperature data through data analysis and processing, displays the temperature data on the monitoring LCD screen, analyzes whether the temperature data signal exceeds a set value through data judgment, and sends out an alarm signal when the temperature data signal of the concrete exceeds the set value.
In order to improve the control effect of the system, the internal temperature of the concrete needs to be accurately predicted. The embodiment of the invention adopts an intelligent temperature change trend prediction model based on a Support Vector Regression (SVR) algorithm to predict the internal temperature of the concrete in real time. The penalty parameter c and the kernel function parameter g have great influence on the calculation performance of the SVR prediction model, so that the SVR parameter optimization is carried out based on grid search and K-fold cross validation, and the specific operation steps are as follows:
establishing grid coordinates, wherein the range of the grid coordinates determines the parameter optimization range, and in order to ensure that the optimization range is wide enough, dividing grids by adopting an exponential function, and enabling a to be (-m, m) and b to be (-n, n), so that the grid point coordinates of the model parameters are (c, g) to be (2a, 2 b);
dividing samples, dividing the original samples into K groups equally when a K-fold cross verification method is utilized, taking each group as a verification set in turn, and testing the models obtained by training other K-1 groups;
determining a prediction error, and taking the average value of the mean square errors of the K times of test results as a performance index of the model;
and determining an optimal parameter combination, and after the parameter combinations at all the cross points on the grid are subjected to K-fold cross validation, determining the parameter combination corresponding to the minimum mean square error value as the optimal parameter of the model.
Based on grid search and K-fold cross validation, not only can a global optimal solution be found out, but also the influence of improper fitting can be effectively avoided, and therefore the prediction precision of the whole model is improved.
For the internal temperature control of concrete, two interconnected water storage tanks are arranged and are used for water inlet and outlet respectively, and the purpose of cooling is achieved by controlling the water circulation of condensed water through a controller according to the current temperature of concrete.
According to the predicted temperature change trend, the temperature of the concrete is controlled in combination with the real-time temperature of the concrete, in order to improve the precision and stability of temperature control, a traditional control method and neural network control are integrated, a self-adaptive controller based on a neural network is designed, and the fuzzy Smith intelligent control method is adopted to carry out prediction compensation on the pure lag of the system so as to eliminate the overshoot of the system and enhance the stability of control.
The concrete temperature control adopts a closed-loop control mode, an externally set temperature value and a temperature measurement value acquired by a temperature sensor are simultaneously transmitted to a control part of a microprocessor, the deviation between a set value and an actual value is calculated, an output control quantity is obtained according to a pre-designed control algorithm, and the rotating speed of a motor of a condensation water circulation system is controlled within a certain period, so that the temperature is controlled within a certain range near a target value and is kept stable.
Because the Smith estimation compensation is sensitive to the model deviation, in order to eliminate the influence of unmatched model parameters, a divider, a multiplier and a leading differential are added on the basis of a fuzzy Smith compensation model to perform self-adaptive compensation on the gain of the model, and the deviation between the compensation model and a signal is used for correcting the estimated gain through the combined action, so that the self-adaptive adjustment effect is realized, and the steady-state deviation can be eliminated.
According to the embodiment of the invention, through the modular maintenance factory building structure with the expandable size, concrete pouring is not affected by high temperature in summer, cold in winter, strong wind and the like, the temperature and the humidity of each area in the maintenance factory building can be detected, the temperature and the humidity of the surface of concrete can be adjusted by controlling the spraying system, the real-time detection and the intelligent prediction of the change trend of the internal temperature of the concrete are realized through embedding the sensor and the condensate pipe in the concrete, and the automatic control of circulating water in the condensate pipe is realized by utilizing a control algorithm, so that the pouring quality of large-volume concrete is effectively improved, and the safety and the reliability of the operation of engineering quality and power transmission and transformation.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (6)
1. An intelligent control method for mass concrete quality is characterized by comprising the following operations:
designing a modular maintenance plant with an expandable size, collecting climate element information on the surface of concrete, and controlling the temperature and humidity of the surface of the concrete through automatic spraying;
embedding a replaceable embedded sensing device in concrete, collecting the internal temperature of the concrete, and carrying out centralized collection and remote transmission on collected temperature data signals;
predicting the internal temperature change trend of the concrete in real time by adopting a support vector regression-based prediction model, and optimizing the parameters of the prediction model based on grid search and K-fold cross validation to obtain optimal parameters and obtain a temperature change prediction result;
and according to a real-time prediction result, designing a self-adaptive controller based on a neural network, performing self-adaptive compensation by adopting fuzzy Smith pre-estimation compensation, eliminating steady state deviation, controlling the rotating speed of a condensate water circulating motor in the concrete, and controlling the internal temperature of the concrete.
2. The intelligent mass concrete quality control method according to claim 1, wherein the modular maintenance factory building adopts light plastic steel pipe fittings as frameworks, and a main framework mechanism capable of changing shapes at will is formed through connecting pieces.
3. The intelligent control method for the quality of the mass concrete according to claim 1, wherein the concrete surface climate factor information comprises humidity, relative humidity and heat radiation.
4. The intelligent mass concrete quality control method according to claim 1, wherein the replaceable embedded sensor device comprises a data transmission line, an inner steel tube, an outer steel tube, an asphalt layer and a sensor, the data transmission line is arranged inside the inner steel tube, the data transmission end is connected with the sensor, the outer steel tube is sleeved outside the inner steel tube, and the outer side of the outer steel tube is provided with the asphalt layer.
5. The intelligent control method for the mass concrete quality according to claim 1, wherein the prediction model parameter optimization based on grid search and K-fold cross validation specifically comprises:
establishing grid coordinates, dividing a grid by using an exponential function, and enabling a to be (-m, m) and b to be (-n, n), wherein the grid point coordinates of model parameters are (c, g) to be (2a, 2 b);
dividing samples, equally dividing the original samples into K groups by using a K-fold cross verification method, taking each group as a verification set in turn, and testing models obtained by training other K-1 groups;
determining a prediction error, and taking the average value of the mean square errors of the K times of test results as a performance index of the model;
and determining an optimal parameter combination, and after the parameter combinations at all the cross points on the grid are subjected to K-fold cross validation, determining the parameter combination corresponding to the minimum mean square error value as the optimal parameter of the model.
6. The intelligent control method for the mass concrete quality according to claim 1, wherein the controlling of the internal temperature of the concrete specifically comprises:
the temperature value set externally and the acquired temperature measurement value are transmitted to the control part of the microprocessor simultaneously, the deviation between the set value and the actual value is calculated, the output control quantity is obtained according to a pre-designed control algorithm, and the rotating speed of the motor of the condensed water circulation system is controlled in a certain period.
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| CN116149402A (en) * | 2023-04-23 | 2023-05-23 | 中建西南咨询顾问有限公司 | Temperature control system and control method based on convolutional neural network |
| CN117580010A (en) * | 2024-01-15 | 2024-02-20 | 中交三公局桥梁隧道工程(北京)有限公司 | Spraying monitoring data transmission system based on wireless sensor |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116149402A (en) * | 2023-04-23 | 2023-05-23 | 中建西南咨询顾问有限公司 | Temperature control system and control method based on convolutional neural network |
| CN116149402B (en) * | 2023-04-23 | 2023-07-28 | 中建西南咨询顾问有限公司 | Temperature control system and control method based on convolutional neural network |
| CN117580010A (en) * | 2024-01-15 | 2024-02-20 | 中交三公局桥梁隧道工程(北京)有限公司 | Spraying monitoring data transmission system based on wireless sensor |
| CN117580010B (en) * | 2024-01-15 | 2024-04-05 | 中交三公局桥梁隧道工程(北京)有限公司 | Spraying monitoring data transmission system based on wireless sensor |
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