Proportional generation method and device of concrete and computer equipment

Abstract

The invention relates to a proportion generation method and device of concrete and computer equipment. The method comprises the following steps: acquiring material characteristic data of each material for proportioning concrete and current environment data of an environment in which the concrete is located, and identifying first influence information of each material on the concrete; on the basis of the current environment data of the environment, second influence information of the concrete is identified, so that proportioning condition information of the concrete is generated; generating a proportion experiment scheme of the concrete, and collecting experiment result data corresponding to the proportion experiment scheme; and based on the experimental result data, through a concrete performance evaluation network, generating an optimal proportioning scheme of each substance of the concrete in the environment. By adopting the method, the matching accuracy of the matching amount of each substance of the concrete can be comprehensively improved.

Description

Technical Field

[0001] The present application relates to the technical field of engineering analysis and material property identification, and in particular to a method, device and computer equipment for generating a concrete mix ratio. Background Art

[0002] Concrete is one of the important basic materials for engineering construction and road construction, especially for water conservancy projects. The performance of concrete often directly affects the safety and quality of water conservancy projects. Therefore, the optimization and evaluation of concrete quality has always been the research standard for improving the safety and quality of water conservancy projects. The performance of concrete often depends on the composition of each substance in the concrete. From the perspective of concrete working performance, it affects the slump and slump loss of concrete, and will have an impact on the strength of concrete. Therefore, how to improve the optimal ratio of each substance in concrete to improve the quality and performance of concrete is the current research focus.

[0003] The traditional method of determining the proportions of various substances in concrete is through manual mixing, where the proportions of various substances are generated according to theoretical values ​​and workers' construction experience. However, this method has a high error rate, and the sand in concrete often contains some soil, which has a significant impact on the strength of the concrete, resulting in a low accuracy of the proportions of various substances in the concrete. Summary of the Invention

[0004] Based on this, it is necessary to provide a concrete mix ratio generation method, device and computer equipment to address the above technical problems.

[0005] In a first aspect, the present application provides a method for generating a concrete mix ratio, comprising: Acquiring material characteristic data of each substance used for mixing concrete and current environmental data of an environment in which the concrete is located, and identifying first impact information of each substance on the concrete based on the material characteristic data of each substance; identifying second influencing information of the concrete based on current environmental data of the environment, and generating mix condition information of the concrete based on the second influencing information; generating a mix ratio experimental scheme for the concrete based on the first impact information of each substance on the concrete and the mix ratio condition information of the concrete, and collecting experimental result data corresponding to the mix ratio experimental scheme in response to a worker uploading an experimental result based on the concrete mix ratio experimental scheme; Based on the experimental result data, an optimal mix ratio of various substances in the concrete in the environment is generated through a concrete performance evaluation network.

[0006] Optionally, the identifying first impact information of each substance on the concrete based on the substance characteristic data of each substance includes: For each substance, based on the substance characteristic data of the substance, identifying sub-characteristic data of each material component of the substance; In the concrete performance impact database, query the sub-feature data of each material component for the performance impact trend of the concrete; The performance influence trends corresponding to all material components are used as the first influence information of the materials on the concrete.

[0007] Optionally, the identifying the second impact information of the concrete based on the current environmental data of the environment includes: Based on current environmental data, identify environmental factor values ​​for each environmental factor type; Based on the environmental factor values ​​of each environmental factor type, adapting the parameter range of each performance parameter type of the concrete in the environmental impact database; The parameter range of each performance parameter type of the concrete is used as the second influencing information of the concrete.

[0008] Optionally, generating the concrete mix condition information based on the second impact information includes: Based on the parameter range of each performance parameter type, identifying the parameter abnormal deviation value of each abnormal performance parameter type; Based on the parameter abnormality deviation value of each abnormal performance parameter type and the first impact information of each substance on the concrete, identifying the material ratio range corresponding to each substance; The material proportion range corresponding to each of the substances is used as the proportion condition information of the concrete.

[0009] Optionally, generating a mix ratio experimental plan for the concrete based on the first impact information of each substance on the concrete and the mix ratio condition information of the concrete includes: For each substance, based on the first impact information of the substance on the concrete, identifying a concrete performance test type corresponding to the substance; Based on the material proportion range corresponding to the material, a proportion experimental group corresponding to the material is generated, and the proportion experimental group corresponding to each material and the concrete performance test type corresponding to each material are used as the concrete proportion experimental plan.

[0010] Optionally, generating an optimal mix ratio of various substances of the concrete in the environment based on the experimental result data through a concrete performance evaluation network includes: For each substance, based on the concrete performance test type corresponding to the substance and the sub-experiment result data corresponding to the experimental group of the mixture ratio of the substance, using the performance evaluation strategy corresponding to the concrete performance test type, identifying first performance change association information of the concrete performance test type corresponding to the substance; Based on the sub-experimental result data corresponding to the experimental groups of the proportions of the substances, identifying, through a concrete performance evaluation network, correlation information on the effect of the change in the amount of each substance on the second performance change of the concrete; Based on the first performance change correlation information of each concrete performance test type and the second performance change correlation information of the concrete, an optimal mix ratio scheme of each substance of the concrete in the environment is identified.

[0011] In a second aspect, the present application further provides a concrete mix ratio generating device, comprising: an acquisition module, configured to acquire material characteristic data of each substance used for mixing concrete and current environmental data of an environment in which the concrete is located, and identify first impact information of each substance on the concrete based on the material characteristic data of each substance; an identification module, configured to identify second influencing information of the concrete based on current environmental data of the environment, and generate mix condition information of the concrete based on the second influencing information; a generating module configured to generate a mix ratio experimental scheme for the concrete based on the first impact information of each substance on the concrete and the mix ratio condition information of the concrete, and to collect experimental result data corresponding to the mix ratio experimental scheme in response to a worker uploading an experimental result based on the concrete mix ratio experimental scheme; A proportioning module is used to generate an optimal proportioning scheme of various substances in the concrete in the environment based on the experimental result data through a concrete performance evaluation network.

[0012] Optionally, the acquisition module is specifically configured to: For each substance, based on the substance characteristic data of the substance, identifying sub-characteristic data of each material component of the substance; In the concrete performance impact database, query the sub-feature data of each material component for the performance impact trend of the concrete; The performance influence trends corresponding to all material components are used as the first influence information of the materials on the concrete.

[0013] Optionally, the identification module is specifically configured to: Based on current environmental data, identify environmental factor values ​​for each environmental factor type; Based on the environmental factor values ​​of each environmental factor type, adapting the parameter range of each performance parameter type of the concrete in the environmental impact database; The parameter range of each performance parameter type of the concrete is used as the second influencing information of the concrete.

[0014] Optionally, the identification module is specifically configured to: Based on the parameter range of each performance parameter type, identifying the parameter abnormal deviation value of each abnormal performance parameter type; Based on the parameter abnormality deviation value of each abnormal performance parameter type and the first impact information of each substance on the concrete, identifying the material ratio range corresponding to each substance; The material proportion range corresponding to each of the substances is used as the proportion condition information of the concrete.

[0015] Optionally, the generating module is specifically configured to: For each substance, based on the first impact information of the substance on the concrete, identifying a concrete performance test type corresponding to the substance; Based on the material proportion range corresponding to the material, a proportion experimental group corresponding to the material is generated, and the proportion experimental group corresponding to each material and the concrete performance test type corresponding to each material are used as the concrete proportion experimental plan.

[0016] Optionally, the proportioning module is specifically used to: For each substance, based on the concrete performance test type corresponding to the substance and the sub-experiment result data corresponding to the experimental group of the mixture ratio of the substance, using the performance evaluation strategy corresponding to the concrete performance test type, identifying first performance change association information of the concrete performance test type corresponding to the substance; Based on the sub-experimental result data corresponding to the experimental groups of the proportions of the substances, identifying, through a concrete performance evaluation network, correlation information on the effect of the change in the amount of each substance on the second performance change of the concrete; Based on the first performance change correlation information of each concrete performance test type and the second performance change correlation information of the concrete, an optimal mix ratio scheme of each substance of the concrete in the environment is identified.

[0017] In a third aspect, the present application provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of any one of the methods described in the first aspect when executing the computer program.

[0018] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of any one of the methods in the first aspect.

[0019] In a fifth aspect, the present application provides a computer program product, wherein the computer program product comprises a computer program, and when the computer program is executed by a processor, the steps of any one of the methods in the first aspect are implemented.

[0020] The above-mentioned concrete mix ratio generation method, device and computer equipment include: obtaining material characteristic data of each substance used for mix ratioing concrete and current environmental data of the environment in which the concrete is located, and identifying first impact information of each substance on the concrete based on the material characteristic data of each substance; identifying second impact information of the concrete based on the current environmental data of the environment, and generating mix ratio condition information of the concrete based on the second impact information; generating a mix ratio experimental plan for the concrete based on the first impact information of each substance on the concrete and the mix ratio condition information of the concrete, and in response to a staff member uploading an experimental result based on the concrete mix ratio experimental plan, collecting experimental result data corresponding to the mix ratio experimental plan; based on the experimental result data, generating an optimal mix ratio plan for each substance of the concrete in the environment through a concrete performance evaluation network. This solution uses the current environmental data and the material characteristic data of each substance as the starting point, and uses the information on the impact of the current environmental data on concrete to generate concrete mix condition information. When conducting mix ratio experiments on each substance, the experimental scope and number of experiments are reduced, thereby improving the efficiency of concrete mix ratio experiments while ensuring that the mixed concrete is more suitable for the current environment. Then, this solution generates a concrete mix ratio experiment plan by identifying the first impact information of each substance on the concrete and the mix ratio condition information of the concrete, so that the generated mix ratio experiment plan can conduct mix ratio experiments according to the impact information of different concretes, thereby analyzing the actual impact information of the mix ratio of each substance on the concrete in the current environment. Finally, through the concrete performance evaluation network, the optimal mix ratio plan of each substance in the concrete in the environment is generated, so that the obtained optimal mix ratio plan of each substance is not only the optimal mix ratio plan under the current environmental conditions, but also the concrete performance effect that can be achieved by the mix ratio plan is the actual performance effect, avoiding the problem of deviation in concrete performance effect caused by the manual mix ratio method and the generation of the mix ratio of each substance according to theoretical values ​​and workers' construction experience, thereby comprehensively improving the mix ratio accuracy of each substance in the concrete. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments of the present application or related technical descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying any creative work.

[0022] Figure 1 1 is a flow chart of a method for generating a concrete mix ratio in one embodiment; Figure 2 A schematic diagram of a flow chart of an example of generating a concrete mix ratio in one embodiment; Figure 3 is a structural block diagram of a concrete mix ratio generating device in one embodiment; Figure 4 FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0023] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0024] The concrete mix ratio generation method provided in the embodiment of the present application can be applied to the application environment of the concrete mix ratio generation system. The system can be applied to a terminal, a server, or a system including a terminal and a server, and is implemented through the interaction between the terminal and the server. The terminal can be, but is not limited to, various personal computers, laptops, etc. The terminal generates concrete mix ratio condition information by taking the current environmental data and the material characteristic data of each substance as the entry point and the information on the impact of the current environmental data on the concrete, so that when performing mix ratio experiments on each substance, the experimental scope and the number of experiments are reduced, thereby improving the efficiency of the concrete mix ratio experiment while ensuring that the mixed concrete is more suitable for the current environment. Then, this solution generates a concrete mix ratio experiment plan by identifying the first impact information of each substance on the concrete and the mix ratio condition information of the concrete, so that the generated mix ratio experiment plan can conduct mix ratio experiments according to the impact information of different concretes, thereby analyzing the actual impact information of the mix ratio of each substance on the concrete in the current environment. Finally, through the concrete performance evaluation network, the optimal mix ratio plan of each substance in the concrete in the environment is generated, so that the obtained optimal mix ratio plan of each substance is not only the optimal mix ratio plan under the current environmental conditions, but also the concrete performance effect that can be achieved by the mix ratio plan is the actual performance effect, avoiding the problem of deviation in concrete performance effect caused by the manual mix ratio method and the generation of the mix ratio of each substance according to theoretical values ​​and workers' construction experience, thereby comprehensively improving the mix ratio accuracy of each substance in the concrete.

[0025] In an exemplary embodiment, Figure 1 As shown, a method for generating a concrete mix ratio is provided, which is described by taking the method applied to a terminal as an example, and includes the following steps S101 to S104. Among them: Step S101 : obtaining material characteristic data of each substance used for mixing concrete and current environmental data of the environment in which the concrete is located, and identifying first impact information of each substance on the concrete based on the material characteristic data of each substance.

[0026] In this embodiment, in response to a worker's information upload operation, the terminal obtains material characteristic data for each substance in the mixed concrete. These substances include, but are not limited to, cement, water, coarse aggregate (stone), fine aggregate (sand), mineral admixtures (such as fly ash), and chemical admixtures (such as water reducers). The material characteristic data for each substance characterizes the substance's use in the composition of concrete. In practice, each substance may contain certain impurities and additives. For example, stone and sand may contain soil, fly ash may contain impurities, and the material and proportion of the actual active substance in the water reducer may vary. Therefore, the material characteristic data also includes information on the impact of each substance's impurities / additions on the composition of the concrete. For example, the impact of sand's mud content on concrete strength. Then, based on the material characteristic data for each substance, the terminal identifies first impact information for each substance on the concrete. This first impact information includes the performance trend of the concrete's sub-feature data for each component. For example, this performance trend may indicate that an increase in mud content leads to a decrease in concrete strength. The properties of the concrete include, but are not limited to, mortar fluidity, mortar strength, concrete slump, concrete compressive strength, etc. The specific identification process will be described in detail later.

[0027] Step S102 : identifying second impact information of concrete based on current environmental data of the environment, and generating mix condition information of concrete based on the second impact information.

[0028] In this embodiment, the terminal identifies second impact information on concrete based on current environmental data and generates concrete mix condition information based on this second impact information. The second impact information includes parameter ranges for various concrete performance parameter types. These performance parameter types include mortar fluidity parameter types, mortar strength parameter types, concrete slump parameter types, and concrete compressive strength parameter types. The concrete mix condition information includes the ranges of the corresponding material ratios for each substance. The specific identification and generation process will be described in detail later.

[0029] Step S103: Based on the first impact information of each substance on the concrete and the mix condition information of the concrete, a mix experimental plan for the concrete is generated, and in response to the staff uploading the experimental results based on the mix experimental plan for the concrete, experimental result data corresponding to the mix experimental plan is collected.

[0030] In this embodiment, the terminal generates a concrete mix experimental plan based on the first impact information of each substance on the concrete and the concrete mix condition information. In response to the staff's upload of the experimental results based on the concrete mix experimental plan, the terminal collects the experimental result data corresponding to the mix experimental plan. The mix experimental plan includes experimental groups of mix quantities corresponding to each substance and concrete performance test types corresponding to each substance. The concrete performance test types are test types for each concrete property, and therefore, each concrete performance test type corresponds to a concrete property. The terminal sends the concrete mix experimental plan to the staff client and, in response to the staff's information upload operation, obtains the sub-experimental result data obtained after testing the experimental groups of mix quantities corresponding to each substance, and uses all of the sub-experimental result data as the experimental result data corresponding to the mix experimental plan.

[0031] Step S104: Based on the experimental result data, the optimal ratio of various materials in the concrete environment is generated through the concrete performance evaluation network.

[0032] In this embodiment, the terminal generates the optimal mix ratios of various concrete materials in the environment using a concrete performance evaluation network based on experimental results. This network is a deep learning-based convolutional neural network that uses the test results of various concrete performance test types corresponding to the mix ratios of each material as input data to identify correlations between the effects of variations in the amounts of different materials on concrete performance. This allows the terminal to select a mix ratio that achieves the optimal performance parameters for each concrete performance test type under the current environment.

[0033] Based on the above scheme, by taking the current environmental data and the material characteristic data of each substance as the entry point, the impact information of the current environmental data on concrete is used to generate the concrete mix condition information, so that when conducting mix ratio experiments on each substance, the experimental scope and number of experiments are reduced, thereby improving the efficiency of the concrete mix ratio experiment while ensuring that the mixed concrete is more suitable for the current environment. Then, this solution generates a concrete mix ratio experiment plan by identifying the first impact information of each substance on the concrete and the mix ratio condition information of the concrete, so that the generated mix ratio experiment plan can conduct mix ratio experiments according to the impact information of different concretes, thereby analyzing the actual impact information of the mix ratio of each substance on the concrete in the current environment. Finally, through the concrete performance evaluation network, the optimal mix ratio plan of each substance in the concrete in the environment is generated, so that the obtained optimal mix ratio plan of each substance is not only the optimal mix ratio plan under the current environmental conditions, but also the concrete performance effect that can be achieved by the mix ratio plan is the actual performance effect, avoiding the problem of deviation in concrete performance effect caused by the manual mix ratio method and the generation of the mix ratio of each substance according to theoretical values ​​and workers' construction experience, thereby comprehensively improving the mix ratio accuracy of each substance in the concrete.

[0034] Optionally, based on the material characteristic data of each substance, the first impact information of each substance on the concrete is identified, including: for each substance, based on the material characteristic data of the substance, identifying the sub-characteristic data of each material component of the substance; querying the concrete performance impact database for the performance impact trend of the sub-characteristic data of each material component on the concrete; and using the performance impact trends corresponding to all material components as the first impact information of the substance on the concrete.

[0035] In this embodiment, for each substance, the terminal identifies sub-feature data for each component of the substance based on the substance's material feature data. This sub-feature data represents the percentage of each component (substance or impurities) of the substance. Specifically, due to different environments, the range of percentages of each component that can be obtained for different substances also varies. Therefore, the sub-feature data for each component obtained here represents the actual percentage information of each component that can be obtained under the current environmental conditions.

[0036] The concrete performance impact database is queried for the performance impact trends of each material component's sub-feature data on concrete. The database includes information on the corresponding relationship between the percentage ranges of each material component and their impact trends on concrete. Based on this correspondence information, the terminal identifies the performance impact trends corresponding to each material component through range adaptation.

[0037] Finally, the terminal takes the performance influence trends corresponding to all material components as the first impact information of the material on concrete.

[0038] Based on the above scheme, by analyzing the different material components of each substance separately, the performance impact trend corresponding to each material component is identified, and the first impact information of each substance on concrete is obtained, which improves the comprehensiveness and accuracy of the identification of the first impact information.

[0039] Optionally, based on the current environmental data of the environment, the second impact information of the concrete is identified, including: based on the current environmental data, identifying the environmental factor value of each environmental factor type; based on the environmental factor value of each environmental factor type, adapting the parameter range of each performance parameter type of concrete in the environmental impact database; and using the parameter range of each performance parameter type of concrete as the second impact information of the concrete.

[0040] In this embodiment, the terminal identifies environmental factor values ​​for each environmental factor type based on current environmental data. These environmental factor types include, but are not limited to, temperature, humidity, and wind speed. The terminal then adapts parameter ranges for each performance parameter type of concrete based on the environmental factor values ​​for each environmental factor type in the environmental impact database. The higher the ambient temperature, the faster the concrete hydration rate and the faster its strength development. When the ambient temperature is too high, the evaporation rate of moisture within the concrete accelerates, potentially causing premature drying and affecting its strength and durability. When the ambient temperature is too low, the hydration rate slows, potentially leading to insufficient strength development. At low temperatures, moisture within the concrete may even freeze, damaging the concrete structure. Excessive humidity increases the saturation within the concrete, affecting strength development. Low humidity (dryness) increases moisture evaporation, causing the concrete to harden and impact its workability. The impact of wind speed on concrete is primarily reflected in the evaporation rate of surface moisture. Excessive wind speed accelerates surface moisture evaporation, reducing workability and potentially causing surface cracking and other issues. Based on these principles, researchers conducted theoretical analysis and simulation experiments to construct an environmental impact database. This database identifies the corresponding environmental factor value ranges for different environmental factor types and their corresponding parameter ranges for various concrete performance parameter types. The terminal then adapts the parameter ranges for each concrete performance parameter type through range adaptation.

[0041] Finally, the terminal uses the parameter range of each performance parameter type of the concrete as the second influencing information of the concrete.

[0042] Based on the above scheme, by combining environmental influencing factors, the parameter range of each performance parameter type can be identified, so that when actually proportioning the proportions of each substance, the proportioning can be carried out according to the abnormalities of each performance parameter type, thereby ensuring that the proportioned concrete is more suitable for the current environment.

[0043] Optionally, based on the second impact information, concrete mix condition information is generated, including: identifying the parameter abnormality deviation value of each abnormal performance parameter type based on the parameter range of each performance parameter type; identifying the material mix ratio range corresponding to each substance based on the parameter abnormality deviation value of each abnormal performance parameter type and the first impact information of each substance on the concrete; and using the material mix ratio range corresponding to each substance as the concrete mix condition information.

[0044] In this embodiment, the terminal identifies the parameter abnormality deviation value of each abnormal performance parameter type based on the parameter range of each performance parameter type. The terminal presets a standard parameter range corresponding to each performance parameter type, then screens performance parameter types that are not within the standard parameter range as abnormal performance parameter types, and uses the parameter range of the abnormal performance parameter type and the deviation value between the standard parameter range as the parameter abnormality deviation value.

[0045] Then, the terminal calculates an adjustment value for the sub-substance ratio range of each material component of each substance based on the parameter abnormality deviation value for each abnormal performance parameter type and the performance impact trend corresponding to each material component of each substance. The terminal presets the standard sub-substance ratio range for each material component of each substance under standard conditions. Then, based on the standard sub-substance ratio range for each material component of each substance and the performance impact trend corresponding to each material component of each substance, the terminal calculates the performance impact value corresponding to each material component of each substance (wherein this performance impact value corresponds to a performance parameter impact value of one or more performance parameter types). Based on the parameter abnormality deviation value and the performance impact value corresponding to each material component of each substance, the terminal calculates an adjustment value for each substance's performance impact value. Based on the adjustment value for each material component, the terminal inverses the aforementioned steps to obtain an adjustment value for the sub-substance ratio range of each material component of each substance.

[0046] Finally, the terminal uses the material ratio range corresponding to each substance as the concrete ratio condition information.

[0047] Based on the above scheme, by combining the current environmental factors, the material proportion range of each material component of each substance in the concrete is determined, thereby improving the applicability of the concrete obtained by proportioning to the current environment.

[0048] Optionally, based on the first impact information of each substance on the concrete and the mix condition information of the concrete, a mix experimental plan for concrete is generated, including: for each substance, based on the first impact information of the substance on the concrete, identifying the concrete performance test type corresponding to the substance; based on the material mix quantity range corresponding to the substance, generating a mix quantity experimental group corresponding to the substance, and using the mix quantity experimental group corresponding to each substance and the concrete performance test type corresponding to each substance as the concrete mix experimental plan.

[0049] In this embodiment, for each substance, the terminal identifies the concrete performance test type corresponding to the substance based on the first impact information of the substance on concrete. The terminal then generates a corresponding experimental group of proportions based on the sub-substance proportion ranges of each substance component corresponding to the substance. This experimental group of proportions is based on the substance proportion range corresponding to the substance, and according to a preset proportion interval selection strategy, the proportions of each substance within the preset proportion interval are screened to obtain the experimental group of sub-substance proportions of each substance component corresponding to the substance. The experimental group of sub-substance proportions of each substance component corresponding to the substance is then used as the experimental group of proportions corresponding to the substance.

[0050] Finally, the terminal uses the experimental group of the proportions of each substance and the concrete performance test type corresponding to each substance as the concrete proportioning experimental plan.

[0051] Based on the above scheme, by identifying the concrete performance test types corresponding to different substances, the corresponding mix ratio experimental groups of each substance are generated, which improves the guidance effect of the experimental objectives and experimental result data requirements when conducting mix ratio experiments on each substance in the generation of mix ratio experimental plans.

[0052] Optionally, based on the experimental result data, an optimal mix ratio scheme of each substance in the concrete in the environment is generated through a concrete performance evaluation network, including: for each substance, based on the concrete performance test type corresponding to the substance and the sub-experimental result data corresponding to the experimental group of the substance's mix ratio, identifying the first performance change association information of the concrete performance test type corresponding to the substance through a performance evaluation strategy corresponding to the concrete performance test type; based on the sub-experimental result data corresponding to the experimental group of the mix ratio of each substance, identifying the second performance change association information of the change between each substance on the concrete through the concrete performance evaluation network; based on the first performance change association information of each concrete performance test type and the second performance change association information of the concrete, identifying the optimal mix ratio scheme of each substance in the environment.

[0053] In this embodiment, for each substance, the terminal identifies first performance change association information for the concrete performance test type corresponding to the substance, based on the concrete performance test type corresponding to the substance and the sub-experiment result data corresponding to the experimental group of the substance's mix ratio, using a performance evaluation strategy corresponding to the concrete performance test type. This performance evaluation strategy includes performance evaluation values ​​corresponding to different experimental result data ranges. The terminal then identifies performance evaluation values ​​corresponding to different sub-test result data through range adaptation. Finally, based on the correspondence between the change amount of each substance and each performance evaluation value, the terminal constructs performance change distribution information for each concrete performance test type, thereby obtaining first performance change association information for the concrete performance test type.

[0054] Based on the sub-experimental result data corresponding to the experimental groups of the mix ratios of each substance, the terminal uses the concrete performance evaluation network to identify association information about the effect of the variation between the substances on the second performance change of the concrete. Specifically, the association information about the effect of the variation between the substances, such as the change in the mud content of sand, on the water reduction rate of the water reducer is used. That is, based on the sub-experimental result data corresponding to the experimental groups of the mix ratios of the sand and the sub-experimental result data corresponding to the experimental groups of the mix ratios of the water reducer, the terminal uses the concrete performance evaluation network to identify the variation distribution information of the performance evaluation values ​​of each concrete performance test type, and then uses this variation distribution information as the association information about the variation between the substances on the second performance change of the concrete.

[0055] Then, based on the first performance change association information of each concrete performance test type and the second performance change association information of the concrete, the terminal generates the proportion information of each material part of each substance through a classifier neural network based on reinforcement learning, as the optimal proportion scheme of each material in the concrete in the environment.

[0056] Based on the above scheme, after identifying the performance change distribution information of each concrete performance test type from the change amount of each substance, the mutual influence information between the change amounts of each substance and the information on the performance of concrete are identified, thereby improving the comprehensiveness and accuracy of the correlation analysis between the change amounts between each substance and the performance change of concrete. Then, through the classifier neural network, the proportion information of each material part of each substance is generated, so that the optimal proportion scheme of each substance obtained is not only the optimal proportion scheme under the current environmental conditions, but also the concrete performance effect that can be achieved by the proportion scheme is the actual performance effect, avoiding the problem of deviation in concrete performance effect caused by the manual proportioning method and the generation of the proportion of each substance according to theoretical values ​​and workers' construction experience, thereby comprehensively improving the proportion accuracy of the proportion of each material in concrete.

[0057] This application also provides an example of generating a concrete mix ratio, such as Figure 2 As shown, the specific processing process includes the following steps: Step S201: Acquire the material characteristic data of each material used for mixing concrete and the current environmental data of the environment in which the concrete is located.

[0058] Step S202 : for each substance, based on the substance characteristic data of the substance, identifying the sub-characteristic data of each component of the substance.

[0059] Step S203: In the concrete performance impact database, query the sub-feature data of each material component for the performance impact trend of the concrete.

[0060] Step S204: taking the performance influence trends corresponding to all material components as the first influence information of the material on the concrete.

[0061] Step S205 : identifying the environmental factor value of each environmental factor type based on the current environmental data.

[0062] Step S206 : Based on the environmental factor values ​​of each environmental factor type, the parameter ranges of each performance parameter type of concrete are adapted in the environmental impact database.

[0063] Step S207: taking the parameter range of each performance parameter type of concrete as the second influencing information of the concrete.

[0064] Step S208 : identifying the abnormal parameter deviation value of each abnormal performance parameter type based on the parameter range of each performance parameter type.

[0065] Step S209 : identifying the material proportion range corresponding to each material based on the parameter abnormality deviation value of each abnormal performance parameter type and the first impact information of each material on concrete.

[0066] In step S210, the material proportion range corresponding to each material is used as the proportion condition information of the concrete.

[0067] Step S211 : for each substance, based on the first impact information of the substance on concrete, identifying the concrete performance test type corresponding to the substance.

[0068] Step S212: generating a mix ratio experimental group corresponding to the substance based on the substance mix ratio range corresponding to the substance, and using the mix ratio experimental group corresponding to each substance and the concrete performance test type corresponding to each substance as a concrete mix ratio experimental plan.

[0069] Step S213: For each substance, based on the concrete performance test type corresponding to the substance and the sub-experiment result data corresponding to the experimental group of the substance's mix ratio, the first performance change association information of the concrete performance test type corresponding to the substance is identified using the performance evaluation strategy corresponding to the concrete performance test type.

[0070] Step S214 , based on the sub-experimental result data corresponding to the experimental group of the proportion of each substance, the concrete performance evaluation network is used to identify the second performance change correlation information of the change amount between each substance on the concrete.

[0071] Step S215 : identifying the optimal mix ratio of various substances in the concrete environment based on the first performance change correlation information of each concrete performance test type and the second performance change correlation information of the concrete.

[0072] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above can include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0073] Based on the same inventive concept, embodiments of the present application also provide a concrete mix ratio generating device for implementing the aforementioned concrete mix ratio generating method. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations of one or more embodiments of the concrete mix ratio generating device provided below can be found in the above-described limitations of the concrete mix ratio generating method and will not be further elaborated here.

[0074] In an exemplary embodiment, Figure 3 As shown, a concrete mix ratio generating device is provided, comprising: an acquisition module 310, an identification module 320, a generation module 330 and a mix ratio module 340, wherein: An acquisition module 310 is configured to acquire material characteristic data of each substance used for mixing concrete and current environmental data of the environment in which the concrete is located, and identify first impact information of each substance on the concrete based on the material characteristic data of each substance; an identification module 320 for identifying second influencing information of the concrete based on current environmental data of the environment, and generating mix condition information of the concrete based on the second influencing information; a generating module 330 for generating a mix ratio experimental scheme for the concrete based on the first impact information of each substance on the concrete and the mix ratio condition information of the concrete, and collecting experimental result data corresponding to the mix ratio experimental scheme in response to a worker uploading an experimental result based on the concrete mix ratio experimental scheme; The proportioning module 340 is used to generate an optimal proportioning scheme of various substances of the concrete in the environment based on the experimental result data through a concrete performance evaluation network.

[0075] Optionally, the acquisition module 310 is specifically configured to: For each substance, based on the substance characteristic data of the substance, identifying sub-characteristic data of each material component of the substance; In the concrete performance impact database, query the sub-feature data of each material component for the performance impact trend of the concrete; The performance influence trends corresponding to all material components are used as the first influence information of the materials on the concrete.

[0076] Optionally, the identification module 320 is specifically configured to: Based on current environmental data, identify environmental factor values ​​for each environmental factor type; Based on the environmental factor values ​​of each environmental factor type, adapting the parameter range of each performance parameter type of the concrete in the environmental impact database; The parameter range of each performance parameter type of the concrete is used as the second influencing information of the concrete.

[0077] Optionally, the identification module 320 is specifically configured to: Based on the parameter range of each performance parameter type, identifying the parameter abnormal deviation value of each abnormal performance parameter type; Based on the parameter abnormality deviation value of each abnormal performance parameter type and the first impact information of each substance on the concrete, identifying the material ratio range corresponding to each substance; The material proportion range corresponding to each of the substances is used as the proportion condition information of the concrete.

[0078] Optionally, the generating module 330 is specifically configured to: For each substance, based on the first impact information of the substance on the concrete, identifying a concrete performance test type corresponding to the substance; Based on the material proportion range corresponding to the material, a proportion experimental group corresponding to the material is generated, and the proportion experimental group corresponding to each material and the concrete performance test type corresponding to each material are used as the concrete proportion experimental plan.

[0079] Optionally, the matching module 340 is specifically configured to: For each substance, based on the concrete performance test type corresponding to the substance and the sub-experiment result data corresponding to the experimental group of the mixture ratio of the substance, using the performance evaluation strategy corresponding to the concrete performance test type, identifying first performance change association information of the concrete performance test type corresponding to the substance; Based on the sub-experimental result data corresponding to the experimental groups of the proportions of the substances, identifying, through a concrete performance evaluation network, correlation information on the effect of the change in the amount of each substance on the second performance change of the concrete; Based on the first performance change correlation information of each concrete performance test type and the second performance change correlation information of the concrete, an optimal mix ratio scheme of each substance of the concrete in the environment is identified.

[0080] Each module in the above-mentioned concrete mix ratio generating device can be implemented in whole or in part through software, hardware, or a combination thereof. Each module can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in the form of software in a memory in the computer device, so that the processor can call and execute the corresponding operations of each module.

[0081] In an exemplary embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as shown in FIG. Figure 4As shown. The computer device includes a processor, memory, an input / output interface, a communication interface, a display unit, and an input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and external devices. The communication interface of the computer device is used to communicate with external terminals via wired or wireless means, and the wireless means can be implemented via Wi-Fi, a mobile cellular network, near-field communication (NFC), or other technologies. When executed by the processor, the computer program implements a method for generating a concrete mix ratio. The display unit of the computer device is used to produce a visually visible image and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device casing, or an external keyboard, touchpad or mouse.

[0082] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0083] In an exemplary embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor implements steps corresponding to a method for generating a concrete mix ratio when executing the computer program.

[0084] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the computer program implements the steps corresponding to the method for generating a concrete mix ratio.

[0085] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements steps corresponding to a method for generating a mix ratio of concrete.

[0086] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0087] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. In particular, any reference to memory, database, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the various embodiments provided herein may be, but are not limited to, general-purpose processors, central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), programmable logic devices (PLDs), quantum computing-based data processing logic devices, artificial intelligence (AI) processors, and the like.

[0088] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0089] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A method for producing a concrete mix ratio, characterized in that: The method comprises: Acquiring material characteristic data of each substance used for mixing concrete and current environmental data of an environment in which the concrete is located, and identifying first impact information of each substance on the concrete based on the material characteristic data of each substance; identifying second influencing information of the concrete based on current environmental data of the environment, and generating mix condition information of the concrete based on the second influencing information; generating a mix ratio experimental scheme for the concrete based on the first impact information of each substance on the concrete and the mix ratio condition information of the concrete, and collecting experimental result data corresponding to the mix ratio experimental scheme in response to a worker uploading an experimental result based on the concrete mix ratio experimental scheme; Based on the experimental result data, an optimal mix ratio of various substances in the concrete in the environment is generated through a concrete performance evaluation network.

2. The method according to claim 1, characterized in that The identifying first impact information of each substance on the concrete based on the substance characteristic data of each substance includes: For each substance, based on the substance characteristic data of the substance, identifying sub-characteristic data of each material component of the substance; In the concrete performance impact database, query the sub-feature data of each material component for the performance impact trend of the concrete; The performance influence trends corresponding to all material components are used as the first influence information of the materials on the concrete.

3. The method according to claim 1, characterized in that The identifying, based on the current environmental data of the environment, second impact information of the concrete includes: Based on current environmental data, identify environmental factor values ​​for each environmental factor type; Based on the environmental factor values ​​of each environmental factor type, adapting the parameter range of each performance parameter type of the concrete in the environmental impact database; The parameter range of each performance parameter type of the concrete is used as the second influencing information of the concrete.

4. The method according to claim 3, characterized in that The generating of the concrete mix condition information based on the second impact information includes: Based on the parameter range of each performance parameter type, identifying the parameter abnormal deviation value of each abnormal performance parameter type; Based on the parameter abnormality deviation value of each abnormal performance parameter type and the first impact information of each substance on the concrete, identifying the material ratio range corresponding to each substance; The material proportion range corresponding to each of the substances is used as the proportion condition information of the concrete.

5. The method according to claim 4, characterized in that Generating a mix ratio experimental plan for the concrete based on the first impact information of each substance on the concrete and the mix ratio condition information of the concrete includes: For each substance, based on the first impact information of the substance on the concrete, identifying a concrete performance test type corresponding to the substance; Based on the material proportion range corresponding to the material, a proportion experimental group corresponding to the material is generated, and the proportion experimental group corresponding to each material and the concrete performance test type corresponding to each material are used as the concrete proportion experimental plan.

6. The method according to claim 5, characterized in that The method of generating an optimal mix ratio of various materials of the concrete in the environment based on the experimental result data through a concrete performance evaluation network includes: For each substance, based on the concrete performance test type corresponding to the substance and the sub-experiment result data corresponding to the experimental group of the mixture ratio of the substance, using the performance evaluation strategy corresponding to the concrete performance test type, identifying first performance change association information of the concrete performance test type corresponding to the substance; Based on the sub-experimental result data corresponding to the experimental groups of the proportions of the substances, identifying, through a concrete performance evaluation network, correlation information on the effect of the change in the amount of each substance on the second performance change of the concrete; Based on the first performance change correlation information of each concrete performance test type and the second performance change correlation information of the concrete, an optimal mix ratio scheme of each substance of the concrete in the environment is identified.

7. A concrete mix ratio generating device, characterized in that: The device comprises: an acquisition module, configured to acquire material characteristic data of each substance used for mixing concrete and current environmental data of an environment in which the concrete is located, and identify first impact information of each substance on the concrete based on the material characteristic data of each substance; an identification module, configured to identify second influencing information of the concrete based on current environmental data of the environment, and generate mix condition information of the concrete based on the second influencing information; a generating module configured to generate a mix ratio experimental scheme for the concrete based on the first impact information of each substance on the concrete and the mix ratio condition information of the concrete, and to collect experimental result data corresponding to the mix ratio experimental scheme in response to a worker uploading an experimental result based on the concrete mix ratio experimental scheme; A proportioning module is used to generate an optimal proportioning scheme of various substances of the concrete in the environment based on the experimental result data through a concrete performance evaluation network.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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