Concrete mixing quality evaluation and early warning method for concrete faced rockfill dam
Through the concrete performance prediction model constructed using a neural network on panel rock dams in high-altitude areas, combined with the concrete mixing process parameters and meteorological conditions, intelligent quality analysis and early warning are achieved, solving the problem that the existing technology cannot effectively control the concrete quality and improving the level of construction quality control.
Patent Information
- Application Number
- CN202411706788.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-26
- Publication Date
- 2025-03-14
AI Technical Summary
The existing technology cannot effectively analyze and control the mixing quality of panel rock dam concrete in high-altitude areas, and it is difficult to meet the complex requirements of concrete performance in this area.
A neural network is used to build a concrete performance prediction model, combining the parameters of the concrete mixing process and high-altitude meteorological conditions, intelligent monitoring and early warning are carried out, including multi-level analysis of the mix ratio design stage and the panel construction process stage.
Intelligent quality analysis and early warning of concrete in panel rock dams in high-altitude areas has been achieved, the construction quality control level has been improved, and the concrete performance has been ensured to meet the design requirements.
Smart Images
Figure CN119624234A_ABST
Abstract
Description
Technical Field
[0001] The present invention belongs to the technical field of water conservancy and hydropower engineering construction quality analysis, and in particular relates to a concrete mixing quality evaluation and early warning method and system for a panel rockfill dam in cold and high altitude areas. Background Art
[0002] Due to the advantages of relatively small engineering volume, high construction efficiency, and strong foundation adaptability, panel rockfill dams have been widely used in my country's water conservancy and hydropower projects, such as the large-scale water conservancy and hydropower projects such as Maerdang, Lawa and Dashixia. At the same time, many of the above projects are currently located in high-cold and high-altitude areas. The construction environment in high-cold and high-altitude areas is harsh and the climatic conditions are complex. Compared with concrete panel rockfill dams in other regions, the concrete of the panel part needs to meet different requirements such as tensile strength, compressive strength, impermeability and frost resistance. How to conduct intelligent analysis and feedback on the concrete mixing quality of panel rockfill dams in high-cold and high-altitude areas, realize ex ante control of concrete performance, and improve the level of construction quality control is an important test faced by many current projects.
[0003] In order to realize intelligent analysis of concrete mixing quality, there are many studies on intelligent monitoring of mixing quality in the civil engineering industry. The main method is to analyze the concrete mix ratio deviation and concrete compressive strength index. However, the above methods can only analyze conventional concrete mix ratio and compressive strength index, which is difficult to adapt to the requirements of concrete performance indicators in high-cold and high-altitude conditions. Summary of the invention
[0004] In order to solve the defect that the concrete mixing quality analysis method in the prior art cannot be applied to the complex and harsh environment and multiple performance index requirements faced by the concrete of panel rockfill dams in high-cold and high-altitude areas, the purpose of the present invention is to provide a concrete mixing quality early warning method and system for panel rockfill dams, which can be used for construction progress analysis of panel rockfill dams in high-cold and high-altitude areas.
[0005] The present invention proposes a concrete mixing quality evaluation and early warning method for a face rockfill dam, which is suitable for high-cold and high-altitude areas, including a mix ratio design stage and a face plate construction process stage; wherein:
[0006] During the mix design stage:
[0007] Obtain the parameters of the concrete mixing process, conduct concrete block tests, and cure the concrete blocks to the design age under the corresponding high-cold and high-altitude simulated meteorological conditions to obtain the performance indicators of the panel concrete;
[0008] Constructing a concrete performance prediction model based on a neural network, the model takes concrete mixing process parameters and meteorological conditions as input and takes corresponding panel concrete performance indicators as output, and training the concrete performance prediction model;
[0009] Stages in the panel construction process:
[0010] The actual concrete mixing process parameters and the actual meteorological conditions of high cold and high altitude are collected simultaneously, and the actual concrete mixing process parameters and the actual meteorological conditions are input into the trained concrete performance prediction model to obtain the actual concrete performance prediction index of the panel construction stage under the current meteorological conditions;
[0011] Comprehensively consider the comparison between the actual concrete mixing process parameters and the designed concrete mixing process parameters, and establish a graded warning model for the deviation degree of concrete mixing process parameters, including the first warning level, the second warning level and the third warning level;
[0012] Based on the prediction index and design index of concrete performance, the deviation of concrete performance index is analyzed, and a graded early warning model of the deviation degree of prediction index is established according to the degree of deviation, including the first warning level, the second warning level and the third warning level.
[0013] In some embodiments, according to the design of concrete components for panels in high-cold and high-altitude areas, the concrete mixing process parameters include at least the dosage of each component and the mixing time, wherein the dosage information of each component includes at least the coarse aggregate content, fine aggregate content, cement content, sand content, fly ash content, water content, and admixture content, and the mixing time refers to the time from the entry of each component into the concrete mixing tank to the discharge of the material.
[0014] In some embodiments, according to the pouring time period of panel concrete in high-cold and high-altitude areas, historical data is used to analyze at least a time series of meteorological conditions including the temperature, humidity, and air pressure during the pouring time period. When performing concrete curing, the above time series of meteorological conditions including the temperature, humidity, and air pressure during the pouring time period is used to adjust the external environment until the designed concrete curing age is reached.
[0015] In some embodiments, according to the service environment faced by panel concrete in high-cold and high-altitude areas, the performance indicators of the panel concrete include not only the compressive strength of the concrete, but also the tensile strength, impermeability grade and frost resistance grade of the concrete.
[0016] In some embodiments, the concrete performance prediction model is used to further obtain multi-input / multi-output panel concrete performance prediction results.
[0017] In some embodiments, the hierarchical warning model further includes: establishing a hierarchical warning model for the degree of deviation of concrete mixing process parameters and a first warning level model for the degree of deviation of prediction indicators by analyzing the degree of deviation between the actual concrete mixing process parameters and the designed concrete mixing process parameters, and the expression is as follows:
[0018]
[0019] Among them, R i is the actual mixing parameter, D i is the design mixing parameter, i is the mixing parameter number, div i is the warning intensity, i.e., the deviation intensity, It is the first warning level.
[0020] In some embodiments, if the deviation between the actual concrete mixing process parameters and the designed concrete mixing process parameters exceeds 20%, it is set to the first warning level state, indicating that the current parameters are seriously deviated; if the deviation of the concrete mixing process parameters exceeds 10%, but does not exceed 20%, it is set to the second warning level state, indicating that there is a certain degree of deviation at present, and the progress can be adjusted according to the actual construction situation; if the deviation of the concrete mixing process parameters exceeds 5%, but does not exceed 10%, it is set to the third warning level state;
[0021] In some embodiments, if the deviation degree of the predicted indicator is less than the design indicator for more than 10 years, it is a first-level warning state; if the deviation degree of the predicted indicator is less than the design indicator for more than 5 years, but not more than 10 years, it is a second-level warning state; if the deviation degree of the predicted indicator is less than the design indicator for more than 2 years, but not more than 5 years, it is a third-level warning state.
[0022] In some embodiments, the hierarchical warning model further includes: establishing a hierarchical warning model for the degree of deviation of concrete mixing process parameters and a second warning level model for the degree of deviation of continuous variables in the prediction index, the expression is as follows:
[0023]
[0024]
[0025] Among them, S j To predict the tensile or compressive strength of concrete, D j is the tensile or compressive strength of the designed concrete, j is the performance parameter number, is the warning intensity of the continuity indicator, that is, the deviation intensity, It is the second warning level.
[0026] In some embodiments, the hierarchical warning model further includes: establishing a hierarchical warning model for the degree of deviation of concrete mixing process parameters and a third warning level model for the degree of deviation of discrete variables in the prediction index, the expression is as follows:
[0027]
[0028] Among them, S i To predict the tensile or compressive strength of concrete, D i is the tensile or compressive strength of the designed concrete, j is the performance parameter number, is the warning intensity of discrete indicators, that is, the deviation intensity, It is the third warning level.
[0029] Compared with the prior art, the fusion method designed in the present invention fully considers the negative impact of lossy communication on features, and achieves better detection accuracy and perception effect in the collaborative perception 3D target detection task in the lossy communication scenario. BRIEF DESCRIPTION OF THE DRAWINGS
[0030] Figure 1 The present invention is an overall flow chart of the concrete mixing quality early warning method for a face rockfill dam. DETAILED DESCRIPTION
[0031] In order to make the purpose, technical solutions and advantages of the embodiments of this specification more clear, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are part of the embodiments of this specification, not all of the embodiments. Based on the embodiments in this specification, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
[0032] like Figure 1 As shown, the present invention provides an intelligent monitoring system for concrete mixing quality of a face rockfill dam in a cold and high altitude area, including but not limited to steps S101 to S103:
[0033] Step S101: in the concrete mix design stage, concrete mixing process parameters are obtained, and concrete test blocks are tested, that is, concrete test blocks are cured to the design age under corresponding high-cold and high-altitude simulated meteorological conditions, and panel concrete performance indicators are screened;
[0034] In an optional implementation of step S101, concrete mixing process parameters and concrete test block test parameters are obtained, and test block maintenance is performed based on meteorological condition information of high-cold and high-altitude areas obtained from previous historical statistics, further comprising:
[0035] Step S1011, where it should be noted that, according to the concrete mix design information of the face rockfill dam in the high-cold and high-altitude areas, the concrete mixing process parameters include but are not limited to coarse aggregate content, fine aggregate content, cement content, sand content, fly ash content, water content, admixture content and mixing time, etc. At the same time, since the face concrete in the high-cold and high-altitude areas needs to consider the impact of freeze-thaw cycles and the dam body's impermeability, crack resistance and compression resistance, the face concrete performance indicators include but are not limited to concrete compressive strength, and if necessary, further include concrete tensile strength, impermeability grade and frost resistance grade, etc.
[0036] Step S1012, where it should be noted that due to the complex meteorological conditions in high-altitude and cold regions, the concrete strength growth process under different meteorological conditions is complex. Therefore, when performing concrete block maintenance, the concrete block test parameters include but are not limited to the specific meteorological conditions of the project site. Therefore, it is necessary to fully simulate the specific meteorological conditions of the project site, that is, in the time period from the start of concrete pouring to the design age, fully simulate and analyze the changes in the on-site meteorological conditions during this period.
[0037] Step S102: constructing a concrete performance prediction model based on a neural network, the model taking concrete mixing process parameters and meteorological conditions as input and corresponding panel concrete performance indicators as output, and training the concrete performance prediction model;
[0038] In an optional implementation of step S102, the concrete new energy prediction model is obtained based on neural network model training. There are many types of neural network models currently, and BP neural network, convolutional neural network, etc. can be used as the basis for model training, including:
[0039] Step S1021, selecting a specific neural network basis, that is, selecting a neural network model according to concrete mixing process parameters, concrete test block test parameters and panel concrete performance indicators;
[0040] Step S1022: according to the selected neural network model, the original input / output data is imported into the neural network model to obtain a trained concrete performance prediction model;
[0041] Step S103, during the panel construction process, the actual concrete mixing process parameters and the actual meteorological conditions are collected simultaneously, and the actual concrete mixing process parameters and meteorological conditions are input into the trained concrete performance prediction model to obtain the output of the model, i.e., the panel concrete performance prediction index under the current meteorological conditions; further comprising:
[0042] In an optional implementation of step S103, during the concrete pouring stage, actual concrete mixing process parameters and on-site meteorological conditions are obtained in real time, and the above actual mixing process parameters and meteorological conditions are input into a concrete performance prediction model, thereby obtaining the output of the model, i.e., panel concrete performance prediction data under current meteorological conditions and current construction parameter conditions.
[0043] Step S104: During the panel construction process, a comparison between the actual concrete mixing process parameters and the mixing process parameters in the design phase is comprehensively considered to establish a concrete mixing process parameter classification early warning model;
[0044] In an optional implementation of step S104, during the concrete pouring stage, based on the actual mixing process parameters obtained and the designed mixing process parameters, the performance indicators of each panel concrete are compared and analyzed one by one to obtain the difference and relative deviation of each indicator; graded warning is performed according to the relative deviation. Therefore, step S104 further includes:
[0045] Step S1041, calculate the relative deviation of the mixing process parameter index, as shown in formula (1):
[0046]
[0047] Among them, R i is the actual mixing parameter, D i is the design mixing parameter, i is the mixing process parameter number, div i is the relative deviation, which serves as the warning intensity;
[0048] Step S1042: Implement intelligent early warning according to the relative deviation degree and establish an intelligent early warning model, as shown in formula (2):
[0049]
[0050] in, The first warning level;
[0051] Among them, it should be noted that if the deviation of the mixing process parameters exceeds 20%, it is set to the first-level warning state, indicating that the current parameters are seriously deviated; if the deviation of the mixing process parameters exceeds 10%, but does not exceed 20%, it is set to the second-level warning state, indicating that there is a certain degree of deviation at present, and the progress can be adjusted according to the actual construction situation; if the deviation of the mixing process parameters exceeds 5%, but does not exceed 10%, it is set to the third-level warning state, indicating that the current construction progress is slightly behind, and whether the progress adjustment is needed can be judged according to the actual construction situation.
[0052] It should be noted that, after obtaining the warning level, the construction progress graded warning model can push information to the construction supervisors to remind them to take timely response measures.
[0053] Step S105: During the panel construction process, a concrete performance early warning model is established by analyzing the degree of deviation between the concrete performance prediction index and the design prediction index;
[0054] In an optional implementation of step S105, during the concrete pouring stage, concrete performance prediction results are performed based on the actual mixing process parameters and meteorological conditions obtained, and intelligent early warning is performed for different types of concrete performance indicators. Specifically, considering that the compressive strength and tensile strength of the panel concrete performance indicators are both continuous variables, and the impermeability and frost resistance grades are discrete variables, and the larger the indicators of the above two types of variables are, the better the concrete performance is, so step S105 further includes:
[0055] Step S1051: Establish an early warning model for continuous variables such as concrete compressive strength, tensile strength and other design indicators. The expression is as follows:
[0056]
[0057] Among them, S j To predict the tensile or compressive strength of concrete, D j is the tensile or compressive strength of the designed concrete, j is the performance parameter number, is the warning intensity of the continuity indicator, that is, the degree of deviation, It is the second warning level.
[0058] It should be noted that if the predicted performance index value of the panel concrete is less than the designed performance index value of the panel concrete, the first-level warning state is reached; if the deviation degree exceeds 5% but does not exceed 10%, the second-level warning state is reached; if the deviation degree exceeds 2% but does not exceed 3%, the third-level warning state is reached;
[0059] Step S1052: Establish an early warning model for discrete variables such as concrete impermeability grade, frost resistance grade and other design indicators. The expression is as follows:
[0060]
[0061] Among them, S i To predict the tensile or compressive strength of concrete, D i is the tensile or compressive strength of the designed concrete, j is the performance parameter number, is the warning intensity of discrete indicators, that is, the deviation intensity, It is the third warning level.
[0062] Among them, it should be noted that if the deviation degree of the predicted indicator is less than the design indicator for more than 10 years, it is the first level warning state; if the deviation degree of the predicted indicator is less than the design indicator for more than 5 years, but not more than 10 years, it is the second level warning state; if the deviation degree of the predicted indicator is less than the design indicator for more than 2 years, but not more than 5 years, it is the third level warning state.
[0063] It should be noted that, after obtaining the warning level, the construction progress graded warning model can push information to the construction supervisors to remind them to take timely response measures.
[0064] In an optional implementation of this embodiment, the method further includes:
[0065] The meteorological parameters, the mixing process parameters, meteorological condition parameters, test block test data, etc. are stored in a basic database.
[0066] It should be noted that the construction of the basic database is mainly used to provide a data basis for the construction progress simulation model and the construction progress classification warning model, so as to avoid tedious data collection or acquisition process.
[0067] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the protection scope of the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.
[0068] For those skilled in the art, improvements and changes can be made according to the above invention content. Any modification, improvement and change made on the basis of the present invention should fall within the protection scope of the present invention.
Claims
1. A concrete mixing quality evaluation and early warning method for a face rockfill dam, characterized in that: Applicable to high-cold and high-altitude areas, including the mix design stage and the panel construction process stage; among which: During the mix design stage: Obtain the parameters of the concrete mixing process, conduct concrete block tests, and cure the concrete blocks to the design age under the corresponding high-cold and high-altitude simulated meteorological conditions to obtain the performance indicators of the panel concrete; Constructing a concrete performance prediction model based on a neural network, the model takes concrete mixing process parameters and meteorological conditions as input and takes corresponding panel concrete performance indicators as output, and training the concrete performance prediction model; Stages in the panel construction process: The actual concrete mixing process parameters and the actual meteorological conditions of high cold and high altitude are collected simultaneously, and the actual concrete mixing process parameters and the actual meteorological conditions are input into the trained concrete performance prediction model to obtain the actual concrete performance prediction index of the panel construction stage under the current meteorological conditions; Comprehensively consider the comparison between the actual concrete mixing process parameters and the designed concrete mixing process parameters, and establish a graded warning model for the deviation degree of concrete mixing process parameters, including the first warning level, the second warning level and the third warning level; Based on the prediction index and design index of concrete performance, the deviation of concrete performance index is analyzed, and a graded early warning model of the deviation degree of prediction index is established according to the degree of deviation, including the first warning level, the second warning level and the third warning level.
2. The concrete mixing quality evaluation and early warning method for a face rockfill dam according to claim 1 is characterized in that: According to the design of concrete components for panels in high-cold and high-altitude areas, the concrete mixing process parameters include at least the dosage of each component and the mixing time, where the dosage information of each component includes at least the coarse aggregate content, fine aggregate content, cement content, sand content, fly ash content, water content, and admixture content. The mixing time refers to the time from the entry of each component into the concrete mixing tank to the discharge.
3. The concrete mixing quality evaluation and early warning method for a face rockfill dam according to claim 1 is characterized in that: According to the pouring time period of panel concrete in high-cold and high-altitude areas, historical data is used to at least analyze the time series of meteorological conditions including the temperature, humidity, and air pressure during the pouring time period. When curing concrete, the above time series of meteorological conditions including the temperature, humidity, and air pressure during the pouring time period is used to adjust the external environment until the designed concrete curing age is reached.
4. The method for evaluating and warning the quality of concrete mixing for a face rockfill dam according to claim 1 is further characterized in that: According to the service environment faced by panel concrete in high-cold and high-altitude areas, the performance indicators of panel concrete include not only the compressive strength of concrete, but also the tensile strength, impermeability grade and frost resistance grade of concrete.
5. The concrete mixing quality evaluation and early warning method for a face rockfill dam according to claim 1 is characterized in that: The concrete performance prediction model is used to further obtain multi-input / multi-output panel concrete performance prediction results.
6. The concrete mixing quality evaluation and early warning method for a face rockfill dam according to claim 1 is characterized in that: The hierarchical warning model further includes: establishing a hierarchical warning model for the deviation degree of concrete mixing process parameters and a first warning level model for the deviation degree of prediction indexes by analyzing the deviation degree of the actual concrete mixing process parameters and the designed concrete mixing process parameters, and the expression is as follows: Among them, R i is the actual mixing parameter, D i is the design mixing parameter, i is the mixing parameter number, div i is the warning intensity, i.e., the deviation intensity, It is the first warning level.
7. The concrete mixing quality evaluation and early warning method for a face rockfill dam according to claim 1 is characterized in that: If the deviation between the actual concrete mixing process parameters and the designed concrete mixing process parameters exceeds 20%, it is set to the first warning level state, indicating that the current parameters are seriously deviated; if the deviation of the concrete mixing process parameters exceeds 10% but does not exceed 20%, it is set to the second warning level state, indicating that there is a certain degree of deviation at present, and the progress can be adjusted according to the actual construction situation; if the deviation of the concrete mixing process parameters exceeds 5% but does not exceed 10%, it is set to the third warning level state.
8. The concrete mixing quality evaluation and early warning method for a face rockfill dam according to claim 1 is characterized in that: If the deviation of the predicted indicator is less than the design indicator for more than 10 years, it is the first level warning state; if the deviation of the predicted indicator is less than the design indicator for more than 5 years, but not more than 10 years, it is the second level warning state; if the deviation of the predicted indicator is less than the design indicator for more than 2 years, but not more than 5 years, it is the third level warning state.
9. The method for evaluating and warning the concrete mixing quality of a face rockfill dam according to claim 1, characterized in that: The hierarchical warning model further includes: establishing a hierarchical warning model for the degree of deviation of concrete mixing process parameters and a second warning level model for the degree of deviation of continuous variables in the prediction index, the expression is as follows: Among them, S j To predict the tensile or compressive strength of concrete, D j is the tensile or compressive strength of the designed concrete, j is the performance parameter number, is the warning intensity of the continuity indicator, that is, the deviation intensity, It is the second warning level.
10. The concrete mixing quality evaluation and early warning method for a face rockfill dam according to claim 1, characterized in that: The hierarchical warning model further includes: establishing a hierarchical warning model for the degree of deviation of concrete mixing process parameters and a third warning level model for the degree of deviation of discrete variables in the prediction index, the expression is as follows: Among them, S i To predict the tensile or compressive strength of concrete, D i is the tensile or compressive strength of the designed concrete, j is the performance parameter number, is the warning intensity of discrete indicators, that is, the deviation intensity, It is the third warning level.