Combined drive control method and system for processing cycle of functional concrete

Abstract

The invention discloses a combined drive control method and system for a functional concrete processing cycle, and relates to the technical field of intelligent control, and the method comprises the steps: carrying out the multi-dimensional feature collection of raw materials of concrete, obtaining the feature information of the raw materials, and carrying out the screening analysis of a combined drive control database through taking the feature information as a constraint, thereby obtaining a control reference database; dividing a control reference database; analyzing functional requirements of the concrete, and determining a functional evaluation plan; performing optimization traversal on the reference library without the additives to obtain a first optimal control strategy, and performing optimization traversal on the reference library with the additives to obtain a second optimal control strategy; and comparing the first optimal control strategy with the second optimal control strategy to obtain a target control strategy, and performing combined drive control on the concrete. The technical problem that the processing control strategy cannot be intelligently matched according to the characteristics of the concrete raw materials in the prior art is solved, and the technical effects of accurate matching and functional control optimization of the concrete processing strategy are achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent control, and particularly relates to a functional concrete processing cycle coupled control method and system. BACKGROUND

[0002] The processing performance and final functional performance of concrete are affected by the types, qualities and mutual proportions of raw materials. In actual production processes, the processing parameters are often formulated according to fixed proportions or experience rules, and there is a lack of a systematic collection and analysis mechanism for multi-dimensional characteristics of raw materials. Due to the differences in strength, particle morphology, clay content and storage conditions of different raw materials, the traditional method is difficult to achieve accurate response to the performance requirements of concrete, resulting in unstable functional control effect in the processing process and difficulty in dynamically optimizing and matching the control strategy for specific raw materials. SUMMARY

[0003] The present application provides a functional concrete processing cycle coupled control method and system, which is used to solve the technical problem that the processing control strategy cannot be intelligently matched according to the characteristics of concrete raw materials in the prior art.

[0004] In view of the above problems, the present application provides a functional concrete processing cycle coupled control method and system.

[0005] In a first aspect of the present application, a functional concrete processing cycle coupled control method is provided, and the method comprises: Multi-dimensional characteristics of raw materials of concrete are collected to obtain raw material characteristic information. The raw material characteristic information is used as a screening constraint to screen and analyze a coupled control database to obtain a control reference database. The control reference database is divided to obtain a division result, wherein the division result includes a no-additive reference library and a with-additive reference library. Functional requirements of the concrete are analyzed, and a functional evaluation plan is determined. The no-additive reference library is optimized and traversed based on the functional evaluation plan to obtain a first optimal control strategy, and the with-additive reference library is optimized and traversed to obtain a second optimal control strategy. The first optimal control strategy and the second optimal control strategy are compared to obtain a target control strategy, and the concrete is coupled controlled according to the target control strategy.

[0006] In a second aspect of the present application, a functional concrete processing cycle coupled control system is provided, and the system comprises: The feature collection module is used for collecting multi-dimensional features of raw materials of the concrete to obtain raw material feature information; the screening and analysis module is used for screening and analyzing the joint drive control database with the raw material feature information as a screening constraint to obtain a control reference database; the division module is used for dividing the control reference database to obtain a division result, wherein the division result includes an external additive-free reference library and an external additive reference library; the analysis module is used for analyzing functional requirements of the concrete and determining a functional evaluation plan; the optimization and traversal module is used for performing optimization and traversal on the external additive-free reference library based on the functional evaluation plan to obtain a first optimal control strategy, and performing optimization and traversal on the external additive reference library to obtain a second optimal control strategy; and the joint drive control module is used for comparing the first optimal control strategy with the second optimal control strategy to obtain a target control strategy, and performing joint drive control on the concrete according to the target control strategy.

[0007] The one or more technical solutions provided in the present application have at least the following technical effects or advantages: The present application collects multi-dimensional features of raw materials of the concrete to obtain raw material feature information; screens and analyzes a joint drive control database with the raw material feature information as a screening constraint to obtain a control reference database; divides the control reference database to obtain a division result, wherein the division result includes an external additive-free reference library and an external additive reference library; analyzes functional requirements of the concrete and determines a functional evaluation plan; performs optimization and traversal on the external additive-free reference library based on the functional evaluation plan to obtain a first optimal control strategy, and performs optimization and traversal on the external additive reference library to obtain a second optimal control strategy; compares the first optimal control strategy with the second optimal control strategy to obtain a target control strategy, and performs joint drive control on the concrete according to the target control strategy. The present application solves the technical problem that the prior art cannot intelligently match a processing control strategy according to the characteristics of concrete raw materials, and achieves the technical effect of realizing accurate matching and functional control optimization of a concrete processing strategy by constructing a joint drive control mechanism based on raw material features and functional requirements. BRIEF DESCRIPTION OF DRAWINGS

[0008] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative effort.

[0009] Figure 1 A functional concrete processing cycle joint drive control method flowchart provided by the embodiments of the present application; Figure 2This is a schematic diagram of a combined drive control system for the processing cycle of functional concrete, provided as an embodiment of this application.

[0010] Figure labeling: Feature collection module 11, screening and analysis module 12, partitioning module 13, analysis module 14, optimization traversal module 15, and linkage control module 16. Detailed Implementation

[0011] This application provides a method and system for the combined control of the functional concrete processing cycle, which addresses the technical problem in the prior art that it is impossible to intelligently match processing control strategies based on the characteristics of concrete raw materials. By constructing a combined control mechanism based on raw material characteristics and functional requirements, it achieves the technical effect of accurately matching concrete processing strategies and optimizing functional control.

[0012] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0013] It should be noted that any variation of the terms "comprising" and "having" is intended to cover non-exclusive inclusion, for example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or modules that are not explicitly listed or that are inherent to such processes, methods, products, or devices.

[0014] Example 1, as Figure 1 As shown, this application provides a method for co-driving control of the processing cycle of functional concrete, the method comprising: Step S100: Collect multi-dimensional features of the raw materials of concrete to obtain raw material feature information.

[0015] In the embodiment of the present application, the raw materials of the concrete are collected in multiple dimensions, specifically including sequentially introducing a category feature collection mechanism, a harmful feature collection mechanism and a storage pipe feature collection mechanism, and extracting multiple dimension parameters for each category in the constructed raw material category set. The category feature collection mechanism is used to collect basic performance indicators of the raw materials, forming first arbitrary feature parameters, such as the strength, fineness and setting time of cement, the particle shape, gradation and clay content of aggregate; the harmful feature collection mechanism is used to identify adverse ingredients affecting the performance of the concrete, forming second arbitrary feature parameters, such as impurity content, reactivity mineral proportion, etc.; the storage pipe feature collection mechanism collects storage and management related indicators, forming third arbitrary feature parameters, such as storage time, temperature and humidity environment and packaging integrity of the raw materials. Finally, the above three types of parameters are fused to construct structured raw material feature information.

[0016] Step S200: screening and analyzing the joint drive control database with the raw material feature information as a screening constraint to obtain a control reference database.

[0017] In the embodiment of the present application, when screening and analyzing the joint drive control database with the raw material feature information as a screening constraint, any joint drive control data group in the joint drive control database is extracted, the similarity coefficient of the raw material feature information and the feature information in the data group is calculated, and if the similarity coefficient reaches a predetermined similarity limit value, the data group is included in the control reference database. Through the process, the control reference database is obtained.

[0018] Further, the method provided by the embodiment of the present application, screening and analyzing the joint drive control database with the raw material feature information as a screening constraint to obtain a control reference database, further includes: extracting any joint drive control data group in the joint drive control database; obtaining the similarity coefficient of the raw material feature information and any feature information in the any joint drive control data group; if the similarity coefficient reaches a predetermined similarity limit value, the any joint drive control data group is added to the control reference database; wherein, including: assembling a category set of the raw materials; introducing a category feature collection mechanism to collect category features of any category in the category set to obtain first arbitrary feature parameters; introducing a harmful feature collection mechanism to collect harmful features of the any category to obtain second arbitrary feature parameters; introducing a storage pipe feature collection mechanism to collect storage pipe features of the any category to obtain third arbitrary feature parameters; based on the first arbitrary feature parameters, the second arbitrary feature parameters and the third arbitrary feature parameters, assembling the raw material feature information.

[0019] In the embodiment of the present application, first, any joint drive control data set in the joint drive control database is extracted. The joint drive control database refers to a database for storing different raw material combinations and corresponding processing parameters and control strategies in a historical concrete processing process. By calling the joint drive control database, any joint drive control data set is extracted. By using the Euclidean distance algorithm, the similarity coefficient between the current raw material characteristic information and the characteristic information in the extracted any joint drive control data set is calculated. Each dimension characteristic is uniformly normalized before calculation to ensure dimensional consistency and eliminate extreme value interference. If the similarity coefficient is less than the set predetermined similarity limit value 0.35, the corresponding joint drive control data set is added to the control reference database.

[0020] To establish the raw material characteristic information, first, the category set of the raw material is established, including the cement category, the aggregate category and the additive category. The category characteristic collection mechanism is introduced to collect the category characteristics. The 28d strength is measured by using the compressive strength detector, the fineness is measured by using the specific surface area tester, and the initial setting time and final setting time are obtained by using the automatic setting time detector. The obtained data is normalized to form the first arbitrary characteristic parameter of the cement. For the aggregate category, the particle shape is obtained by using the image particle size analysis system, the particle grading is obtained by using the standard sieve method, and the silt content is obtained by using the washing sedimentation method. The values are recorded and normalized respectively to form the first arbitrary characteristic parameter of the aggregate. For the additive, the viscosity index is measured by using the viscometer, and then the first arbitrary characteristic parameter is formed by uniformly encoding and normalizing.

[0021] Then, the harmful characteristic collection mechanism is introduced to collect the harmful characteristics of any category. The content of heavy metal elements such as Pb and Cd is detected by using the X-ray fluorescence spectrometer, and the concentration of Ra and Th radionuclides is detected by using the gamma spectrometer. The measured data is normalized and counted into the second arbitrary characteristic parameter. The content of organic matter is detected by using the colorimetric tube, and the proportion of mud is determined by using the sedimentation method. The concentrations of chloride ions and alkali ions are detected by using the ion chromatograph. All the detection results are converted into standard units and normalized as the second arbitrary characteristic parameter.

[0022] Subsequently, the storage pipe characteristic collection mechanism is introduced to collect the storage pipe characteristics of any category. The relative humidity threshold of the material storage area is set to 60%, and the temperature and humidity sensor is used to automatically record for 24 hours. The RFID system is used to set the storage identifier for different raw materials to record the time of entry and batch. Manual inspection is arranged once every 7 days to remove damaged or overdue materials to form storage data such as qualified rate, storage period and environmental stability, and to form the third arbitrary characteristic parameter by standardizing the code.

[0023] Finally, the first arbitrary characteristic parameter, the second arbitrary characteristic parameter and the third arbitrary characteristic parameter after normalization are summarized to output the raw material characteristic information of the current batch.

[0024] Further, the method provided by the application embodiment further comprises: If the arbitrary category is a cement category, the arbitrary category is collected according to predetermined cement characteristics in the category feature collection mechanism, to obtain cement feature parameters, and the cement feature parameters are taken as the first arbitrary feature parameters, wherein the predetermined cement characteristics at least include strength, fineness and setting time.

[0025] In the application embodiment, if the arbitrary category is a cement category, the cement category is collected according to predetermined cement characteristics in the category feature collection mechanism, wherein the predetermined cement characteristics at least include strength, fineness and setting time.

[0026] Specifically, first, the cement category sample is subjected to sample preparation processing, and a cement mortar test piece is prepared by using a standard mold of 40mm*40mm*160mm, and is cured for 28 days under constant temperature and humidity conditions. The cured test piece is subjected to physical testing by using an electric compression and bending testing machine, to obtain the bending strength and compressive strength values (unit: MPa), so as to characterize the load-carrying capacity of the cement, and the result constitutes the strength parameter of the cement category. The above operation is executed by the category feature collection mechanism to dispatch the strength detection module.

[0027] Subsequently, for the fineness characteristics, two ways are combined to collect. On the one hand, the particle size distribution of the cement sample is measured by using a laser particle size analyzer, to obtain particle size parameters such as D10, D50 and D90. On the other hand, the unit mass specific surface area of the cement sample is measured by using a gas permeation method specific surface area tester (such as Blaine specific surface area tester), and the unit is m² / kg. After the particle size distribution parameters and the specific surface area results are processed, they are taken as the cement fineness parameters.

[0028] Then, for the setting time characteristics, a standard consistency cement paste is prepared, is injected into a Vicat test mold with a center hole, and is placed in a 20℃ environment for time recording. An automatic setting time tester is used for whole-process monitoring, to record the time when the measuring needle first sinks to a position of 6mm above the bottom surface of the test mold as the initial setting time, and to record the time when the measuring needle completely stops sinking as the final setting time, and the units are both minutes, and both are taken as the cement setting time parameters.

[0029] Finally, the obtained cement strength parameters, cement fineness parameters and cement setting time parameters are respectively subjected to normalization processing, to eliminate the dimensional differences, and are collected to form structured cement feature parameters, and the cement feature parameters are taken as the first arbitrary feature parameters.

[0030] Further, the method provided by the application embodiment further comprises: If the arbitrary category is an aggregate category, the arbitrary category is characterized according to predetermined aggregate characteristics in the category characteristic collection mechanism, to obtain aggregate characteristic parameters, and the aggregate characteristic parameters are taken as the first arbitrary characteristic parameters, wherein the predetermined aggregate characteristics at least include particle shape, gradation, and clay content.

[0031] In the embodiments of the present application, if the arbitrary category is an aggregate category, the arbitrary category is characterized according to predetermined aggregate characteristics in the category characteristic collection mechanism. The predetermined aggregate characteristics at least include particle shape, gradation, and clay content.

[0032] Specifically, first, for the particle shape, an image particle shape analysis method is used. The aggregate sample is uniformly laid on a black background plate, and a high-resolution image is taken under a stable light source. The edge recognition technology is used to extract the contour of each particle, measure the length of the long axis and the short axis of the particle, and calculate the axis ratio. The number of particles with a long axis to short axis ratio greater than 3:1 is counted, and the percentage of the total particle number is calculated as the content of needle-shaped particles, which is used to represent the aggregate particle shape parameter.

[0033] Then, for the gradation, a standard sieving method is used. 1000g of the dried aggregate sample is weighed and placed in four levels of sieve nets of 5.0mm, 10mm, 20mm, and 31.5mm, respectively, and is continuously sieved for 5 minutes using a vibrating sieve machine. Each sieve net is taken out and weighed using an electronic balance to measure the mass of the oversize, and the percentage of each particle size range is calculated. The maximum particle size, the minimum particle size, and the particle size concentration interval are counted as the aggregate gradation parameters.

[0034] Then, for the clay content, a washing and sedimentation method is used. 500g of the aggregate sample is weighed and placed in a stirring container, and 1L of water is added and stirred thoroughly. After standing for 15 minutes, the upper muddy water is poured out, and the remaining aggregate is dried using a forced air drying oven until a constant weight is reached. The residual mass after drying is recorded. The clay content is calculated using the formula: clay content=(original sample mass-dried mass) / original sample mass*100%, to obtain the aggregate clay content parameter.

[0035] Finally, the obtained aggregate particle shape parameters, aggregate gradation parameters, and aggregate clay content parameters are normalized respectively to form structured aggregate characteristic parameters, which are taken as the first arbitrary characteristic parameters.

[0036] Step S300: dividing the control reference database to obtain a division result, wherein the division result includes a non-external additive reference library and an external additive reference library.

[0037] In the embodiment of the present application, when the control reference database is divided, first, the process record in each set of joint control data is extracted, and classified and identified according to whether it contains additional agent adding information. Specifically, the raw material ratio field in the data set is read, and it is judged whether there is valid record of the type and amount of additional agent. If the record contains the names of additional agents such as water reducing agent, retarder, air entraining agent and the corresponding adding proportion, the data set is classified into the additional agent reference library. If there is no record of the use of additional agent or the amount of all additional agents is zero, it is classified into the additional agent-free reference library. In this way, the control reference database is structured and split, and the division result is obtained.

[0038] Step S400: analyze the functional requirements of the concrete, and determine a functional evaluation plan.

[0039] In the embodiment of the present application, first, a functional index set containing a plurality of functional indexes with demand degree identifiers is extracted based on the functional requirements of the concrete, then a first index is randomly selected from the set, and the index is adjusted according to the corresponding first demand degree to form a functional evaluation plan.

[0040] Further, in the method provided by the application, analyzing the functional requirements of the concrete and determining a functional evaluation plan further includes: analyzing the functional requirements to obtain a functional index set, wherein the functional index set includes a plurality of functional indexes with demand degree identifiers; extracting a first index from the plurality of functional indexes with demand degree identifiers, and the first index corresponds to a first demand degree; and adjusting the first index according to the first demand degree as a weight to form the functional evaluation plan.

[0041] In the embodiment of the present application, first, the performance indicators that the current concrete should meet are listed according to the engineering structure design specification, the use environment and the performance requirements of the concrete by using the artificial list method, and a functional index set is constructed, for example, including compressive strength, workability, impermeability, frost resistance, durability, etc. A value set by a technical expert according to the site requirements is attached to each index, which is called demand degree identifier. The identifier uses a decimal between 0 and 1 to represent the importance of the index. For example, the compressive strength identifier is 0.4, the workability is 0.3, the impermeability is 0.2, and the frost resistance is 0.1.

[0042] Then, a randomly selected index from the functional index set is selected as a first index, for example, the compressive strength, and the target value is recorded as 40MPa. The corresponding first demand degree is read, which is 0.4. Then, the weighted calculation method is used to multiply the target value of the first index by the first demand degree, and the weighted index value, i.e. the weighted value = 40 x 0.4 = 16, is calculated.

[0043] Finally, the weighted value is taken as the first item evaluation value, and the above weighting calculation process is repeated for other functional indicators in turn. After all the weighted values are combined, a comprehensive evaluation structure of the current concrete performance requirement is formed, that is, a functional evaluation plan.

[0044] Step S500: based on the functional evaluation plan, performing optimization traversal on the no-additive reference library to obtain a first optimal control strategy, and performing optimization traversal on the additive reference library to obtain a second optimal control strategy.

[0045] In the embodiments of the present application, based on the functional evaluation plan, each reference set in the no-additive reference library and the additive reference library is respectively functionally evaluated and analyzed, and the functional index is calculated and sorted in descending order. Among them, the co-driven control strategy corresponding to the data group with the highest functional index in the no-additive reference library is taken as the first optimal control strategy; if there is a reference set with a higher functional index in the additive reference library, it is included in the target reference center and sorted, and finally the co-driven control strategy with the highest functional index is selected as the second optimal control strategy.

[0046] Further, the method provided in the embodiments of the present application, based on the functional evaluation plan, performs optimization traversal on the no-additive reference library to obtain a first optimal control strategy, and further includes: based on the functional evaluation plan, performing functional evaluation analysis on the first reference set in the no-additive reference library to obtain a first functional index; arranging the no-additive reference library in descending order according to the first functional index to obtain a no-additive reference list; obtaining the first reference set in the no-additive reference list, and taking the co-driven control strategy in the first reference set as the first optimal control strategy.

[0047] In the embodiments of the present application, when the first reference set in the no-additive reference library is functionally evaluated and analyzed based on the functional evaluation plan, first, the performance index extraction method is used to traverse and extract each reference set, i.e. the first reference set, from the no-additive reference library, to read the recorded concrete performance indexes therein, including compressive strength, workability, impermeability, frost resistance, etc. The above performance indexes correspond one-to-one to the functional index set listed in the functional evaluation plan.

[0048] Subsequently, based on the target index value and the demand degree identifier defined in the functional evaluation plan, the first reference set is functionally evaluated and analyzed. Specifically, each performance index is first normalized to eliminate the dimension effect. After normalization, a linear weighting method is used, that is, each normalized value is multiplied by its corresponding demand degree identifier and summed to obtain the first functional index corresponding to the first reference set.

[0049] Then, the no-additive reference library is rearranged by using a descending order sorting method to form a no-additive reference list based on the functional indexes of all the reference sets.

[0050] Finally, the first-ranked reference set is extracted from the no-additive reference list, which is the first top reference set and contains a complete set of control parameters, including water-binder ratio, sand ratio, mixing time, temperature control range, etc. The set of parameters is the co-driven control strategy in the reference set, which is determined as the first optimal control strategy as the performance-optimal strategy of the current concrete under the no-additive condition.

[0051] Further, the method provided in the application embodiment further includes: extracting the second reference set in the additive reference library; performing functional evaluation analysis on the second reference set based on the functional evaluation plan to obtain a second functional index; determining whether the second functional index is greater than the first top functional index of the first top reference set; if yes, adding the second reference set to the target reference platform; arranging the target reference platform in descending order based on the second functional index to obtain an additive reference list; obtaining a second top reference set in the additive reference list, and taking the co-driven control strategy in the second top reference set as the second optimal control strategy.

[0052] In the application embodiment, the additive reference library is first traversed, and the reference sets therein are extracted in sequence as the current second reference sets. Each second reference set contains concrete performance data under the participation of an additive, including compressive strength, workability, impermeability, and frost resistance, etc., and records the type and dosage of the additive, such as the dosage of polycarboxylate superplasticizer and air-entraining agent.

[0053] Subsequently, the performance target values and requirement degree identifiers in the functional evaluation plan are used to perform functional evaluation analysis on the second reference set. Specifically, the normalization method is used to normalize each performance index to the interval of 0-1, and then the linear weighting method is used to calculate the functional score, i.e., the normalized performance value is multiplied by the corresponding requirement degree weight and summed to obtain the second functional index of the reference set.

[0054] Then, the second functional index is compared with the first top functional index of the first top reference set to determine whether it is better. If the second functional index is greater than the first top functional index, the second reference set is added to the target reference platform, i.e., a candidate strategy pool is constructed. For all the second reference sets added to the target reference platform, a descending order sorting method is used to sort them from high to low according to their corresponding functional indexes to generate an additive reference list.

[0055] Finally, the first ranked reference set from the admixture reference list is obtained, i.e., a second first-ranked reference set, which contains complete joint driving control parameters, including water-binder ratio, admixture content, feeding sequence, mixing time, etc., and is extracted as a second optimal control strategy.

[0056] Step S600: Comparing the first optimal control strategy with the second optimal control strategy to obtain a target control strategy, and performing joint driving control on the concrete according to the target control strategy.

[0057] In the embodiments of the present application, when comparing the first optimal control strategy with the second optimal control strategy, first, predetermined comparison features are read, including admixture cost, joint driving processing time and functional index. The first control record in the first first-ranked reference set is analyzed based on the comparison features respectively, and the comprehensive performance matching degree is calculated using a normalized scoring method to obtain a first control fitness. The second control record in the second first-ranked reference set is scored in the same way to obtain a second control fitness. Then, the first control fitness and the second control fitness are compared, and the final target control strategy is determined according to the one with higher score.

[0058] Subsequently, according to the joint parameters (such as water-binder ratio, admixture content, mixing time, feeding sequence, etc.) contained in the target control strategy, the control execution system is issued to automatically control the processes of raw material metering, admixture adding, equipment speed regulation, temperature control and maintenance, etc., to complete the joint driving control of the concrete processing cycle.

[0059] Further, the method provided in the embodiments of the present application, comparing the first optimal control strategy with the second optimal control strategy to obtain a target control strategy, further comprises: reading predetermined comparison features; performing traversal analysis of the first control record in the first first-ranked reference set based on the predetermined comparison features to obtain a first control fitness; performing traversal analysis of the second control record in the second first-ranked reference set based on the predetermined comparison features to obtain a second control fitness; determining the target control strategy by comparing the first control fitness with the second control fitness; wherein the predetermined comparison features at least include admixture cost, joint driving processing time and functional index.

[0060] In the embodiment of the present application, first, predetermined comparative features are read, including at least admixture cost, joint drive processing time and functional index. Among them, the admixture cost is calculated by extracting the type and corresponding dosage percentage of the admixture in the control record, combining the unit price data, and using the calculation formula admixture cost = dosage x unit price. Finally, the total admixture cost per cubic meter of concrete is obtained. The joint drive processing time is calculated by reading the time stamps of the mixing start time and end time, and calculating the time difference between the two, in seconds. The functional index is directly called from the weighted score obtained based on the aforementioned functional evaluation plan.

[0061] After obtaining the three comparative features, the first control record in the first first-place reference set is analyzed. Specifically, the corresponding admixture cost, joint drive processing time and functional index in the control record are extracted. To eliminate dimensional differences and make each index comparable within the same numerical interval, the admixture cost and joint drive processing time are standardized using the min-max normalization method, which is compressed to the [0, 1] interval. The functional index remains the original value as the performance weight item. Then, the three indexes are multiplied by the preset weight coefficients (such as the functional index weight is 0.5, the joint drive processing time weight is 0.3, and the admixture cost weight is 0.2), and the product values are summed to obtain the first control fitness, which is used to represent the comprehensive degree of the control strategy.

[0062] Similarly, the same process is performed on the second control record in the second first-place reference set. The corresponding admixture cost, joint drive processing time and functional index are extracted, and the first two values are normalized. Then, they are multiplied by their respective weights and summed to obtain the second control fitness.

[0063] Finally, by comparing the first control fitness and the second control fitness, the control strategy corresponding to the higher score is selected as the final target control strategy.

[0064] Further, in the method provided by the embodiment of the present application, after the joint drive control of the concrete according to the target control strategy, the method further comprises: obtaining a strength grade parameter of the concrete; collecting an application environment parameter of the concrete; collecting an application climate parameter of the concrete; establishing a curing constraint based on the strength grade parameter, the application environment parameter and the application climate parameter; matching a target curing scheme in a curing database based on the curing constraint, and curing the concrete according to the target curing scheme.

[0065] In the embodiment of the present application, after the concrete pouring construction is completed, first, the strength grade parameter of the concrete is obtained, which is derived from the technical requirements in the construction drawings, such as C30, C40, etc. grade identification.

[0066] Then, the application environment parameters of the concrete are collected. The application environment parameters are used to describe the service environment of the concrete structure, and specifically include the structure position (such as ground, underground, elevated), the use place (such as indoor, outdoor), and whether exposed to corrosive medium (such as chloride, sulfate, etc.). These parameters are collected by consulting the structure design drawings, construction site environment records or safety technology disclosure documents.

[0067] Then, the application climate parameters of the concrete are collected. The application climate parameters include external meteorological data, such as daily average temperature (℃), air relative humidity (%), wind speed (m / s), and whether there is strong sunlight or rainfall. These data are obtained through the meteorological collection equipment arranged on site or the third-party meteorological platform.

[0068] Subsequently, the curing constraints are established based on the strength grade parameters, the application environment parameters and the application climate parameters. The curing constraints are a set of curing conditions formed for the current engineering actual situation, and are used to limit the curing mode, the duration, the moisture retention means, etc. For example, when the strength grade is C40, the application environment is outdoor exposure, and the climate condition is high temperature and low humidity, the curing constraints will clearly require the use of sunshade, water spraying, covering and other comprehensive measures to avoid early dry cracking and water loss.

[0069] Subsequently, the target curing scheme is matched in the curing database based on the curing constraints. The curing database predefines multiple typical curing schemes, each of which contains the applicable strength grade interval, the environment classification and the climate range, for example, “C30-C50, exposed environment, temperature > 30℃ and humidity < 50% recommend using spray + plastic film curing”. Through the condition matching algorithm, the curing mode corresponding to the current curing constraints is found, and the target curing scheme is determined.

[0070] Finally, the concrete is cured according to the target curing scheme.

[0071] In the embodiments of the present application, as described above, the embodiments of the present application at least have the following technical effects: This application collects multi-dimensional features of concrete raw materials to obtain raw material feature information; uses the raw material feature information as a screening constraint to screen and analyze the joint-drive control database to obtain a control reference database; divides the control reference database to obtain a division result, wherein the division result includes a reference library without admixtures and a reference library with admixtures; analyzes the functional requirements of the concrete and determines a functional evaluation plan; based on the functional evaluation plan, performs an optimization traversal on the reference library without admixtures to obtain a first optimal control strategy, and performs an optimization traversal on the reference library with admixtures to obtain a second optimal control strategy; compares the first optimal control strategy and the second optimal control strategy to obtain a target control strategy, and performs joint-drive control on the concrete according to the target control strategy. This invention solves the technical problem in the prior art that it is impossible to intelligently match processing control strategies based on the characteristics of concrete raw materials. By constructing a joint-drive control mechanism based on raw material characteristics and functional requirements, it achieves the technical effect of accurate matching of concrete processing strategies and optimization of functional control.

[0072] Example 2, based on the same inventive concept as the co-drive control method for the processing cycle of functional concrete in the foregoing examples, such as... Figure 2 As shown, this application provides a co-drive control system for the functional concrete processing cycle. The system and method embodiments in this application are based on the same inventive concept. The system includes: The system comprises the following modules: Feature Collection Module 11, for collecting multi-dimensional features of concrete raw materials to obtain raw material feature information; Screening and Analysis Module 12, for using the raw material feature information as a screening constraint to screen and analyze the joint drive control database to obtain a control reference database; Division Module 13, for dividing the control reference database to obtain a division result, wherein the division result includes a reference library without admixtures and a reference library with admixtures; Analysis Module 14, for analyzing the functional requirements of the concrete and determining a functional evaluation plan; Optimization Traversal Module 15, for performing optimization traversal on the reference library without admixtures based on the functional evaluation plan to obtain a first optimal control strategy, and performing optimization traversal on the reference library with admixtures to obtain a second optimal control strategy; and Joint Drive Control Module 16, for comparing the first optimal control strategy and the second optimal control strategy to obtain a target control strategy, and performing joint drive control on the concrete according to the target control strategy.

[0073] Furthermore, the system is also used to implement the following functions: extracting any joint drive control data set in the joint drive control database; obtaining a similarity coefficient of the raw material characteristic information and any characteristic information in the any joint drive control data set; if the similarity coefficient reaches a predetermined similarity limit value, adding the any joint drive control data set to the control reference database; wherein: assembling a category set of the raw materials; introducing a category characteristic collection mechanism to collect category characteristics of any category in the category set to obtain a first any characteristic parameter; introducing a harmful characteristic collection mechanism to collect harmful characteristics of the any category to obtain a second any characteristic parameter; introducing a storage pipe characteristic collection mechanism to collect storage pipe characteristics of the any category to obtain a third any characteristic parameter; and assembling the raw material characteristic information based on the first any characteristic parameter, the second any characteristic parameter, and the third any characteristic parameter.

[0074] Further, the system is also used to implement the following functions: If the any category is a cement category, collecting characteristics of the any category according to a predetermined cement characteristic in the category characteristic collection mechanism to obtain a cement characteristic parameter, and taking the cement characteristic parameter as the first any characteristic parameter, wherein the predetermined cement characteristic at least includes strength, fineness, and setting time.

[0075] Further, the system is also used to implement the following functions: If the any category is an aggregate category, collecting characteristics of the any category according to a predetermined aggregate characteristic in the category characteristic collection mechanism to obtain an aggregate characteristic parameter, and taking the aggregate characteristic parameter as the first any characteristic parameter, wherein the predetermined aggregate characteristic at least includes particle shape, gradation, and clay content.

[0076] Further, the system is also used to implement the following functions: analyzing the functional requirements to obtain a functional index set, wherein the functional index set includes a plurality of functional indexes with demand degree identifiers; extracting a first index in the plurality of functional indexes with demand degree identifiers, and the first index corresponds to a first demand degree; adjusting the first index with the first demand degree as a weight to form the functional evaluation plan.

[0077] Further, the system is also used to implement the following functions: based on the functional evaluation plan, performing functional evaluation analysis on a first reference set in the no-additive reference library to obtain a first functional index; arranging the no-additive reference library in descending order according to the first functional index to obtain a no-additive reference list; obtaining a first top reference set in the no-additive reference list, and taking a joint drive control strategy in the first top reference set as the first optimal control strategy.

[0078] Further, the system is further configured to implement the following functions: extracting a second reference set in the admixture reference library; performing functional evaluation analysis on the second reference set based on the functional evaluation plan to obtain a second functional index; determining whether the second functional index is greater than a first primary functional index of the first primary reference set; if yes, adding the second reference set to a target reference platform; arranging the target reference platform in descending order according to the second functional index to obtain an admixture reference list; obtaining a second primary reference set in the admixture reference list, and taking a coupled drive control strategy in the second primary reference set as the second optimal control strategy.

[0079] Further, the system is further configured to implement the following functions: reading a predetermined comparison feature; performing traversal analysis on a first control record in the first primary reference set based on the predetermined comparison feature to obtain a first control fitness; performing traversal analysis on a second control record in the second primary reference set based on the predetermined comparison feature to obtain a second control fitness; and determining the target control strategy by comparing the first control fitness and the second control fitness; wherein the predetermined comparison feature at least includes an admixture cost, a coupled drive processing time length, and a functional index.

[0080] Further, the system is further configured to implement the following functions: obtaining a strength grade parameter of the concrete; collecting an application environment parameter of the concrete; collecting an application climate parameter of the concrete; establishing a curing constraint based on the strength grade parameter, the application environment parameter, and the application climate parameter; matching a target curing scheme in a curing database based on the curing constraint, and curing the concrete according to the target curing scheme.

[0081] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description, and does not represent the advantages and disadvantages of the embodiments. The above describes a specific embodiment of the present application. The processes depicted in the drawings do not necessarily require the specific order and continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are also possible or can be advantageous.

[0082] The above only describes the preferred embodiments of the present application, and does not limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

[0083] The specification and drawings are, of course, to be regarded in an illustrative rather than a restrictive sense. It is to be understood that any such modifications, variations, combinations or equivalents that fall within the scope of the application are intended to be embraced herein.

Claims

1. A method for controlling the processing cycle of functional concrete, characterized in that, include: Multi-dimensional feature collection of concrete raw materials yields feature information. Using the raw material characteristic information as a screening constraint, the joint drive control database is screened and analyzed to obtain a control reference database; The control reference database is divided to obtain a division result, wherein the division result includes a reference library without admixtures and a reference library with admixtures; Analyze the functional requirements of the concrete and determine a functional evaluation plan; Based on the aforementioned functional evaluation plan, the first optimal control strategy is obtained by performing an optimization traversal on the reference library without admixtures, and the second optimal control strategy is obtained by performing an optimization traversal on the reference library with admixtures. By comparing the first optimal control strategy with the second optimal control strategy, a target control strategy is obtained, and the concrete is subjected to co-drive control based on the target control strategy.

2. The method for controlling the processing cycle of functional concrete as described in claim 1, characterized in that, Using the raw material characteristic information as a screening constraint, the co-drive control database is screened and analyzed to obtain a control reference database, including: Extract any group of joint drive control data from the joint drive control database; Obtain the similarity coefficient between the raw material characteristic information and any characteristic information in any joint drive control data group; If the similarity coefficient reaches a predetermined similarity limit, then the arbitrary joint drive control data group is added to the control reference database; This includes: Construct a category set for the aforementioned raw materials; A category feature collection mechanism is introduced to collect category features for any category in the category set, thereby obtaining the first arbitrary feature parameter; A harmful feature collection mechanism is introduced to collect harmful features of the arbitrary product category to obtain a second arbitrary feature parameter; A storage feature collection mechanism is introduced to collect storage features for any category of product to obtain a third arbitrary feature parameter. The raw material feature information is constructed based on the first arbitrary feature parameter, the second arbitrary feature parameter, and the third arbitrary feature parameter.

3. The method for controlling the processing cycle of functional concrete as described in claim 2, characterized in that, If the arbitrary category is a cement category, then the arbitrary category is subjected to feature collection according to the predetermined cement characteristics in the category feature collection mechanism to obtain cement feature parameters, and the cement feature parameters are used as the first arbitrary feature parameter, wherein the predetermined cement characteristics include at least strength, fineness and setting time.

4. The method for controlling the processing cycle of functional concrete as described in claim 2, characterized in that, If any category is an aggregate category, then the arbitrary category is subjected to feature collection according to the predetermined aggregate characteristics in the category feature collection mechanism to obtain aggregate feature parameters, and the aggregate feature parameters are used as the first arbitrary feature parameter, wherein the predetermined aggregate characteristics include at least particle shape, gradation and mud content.

5. The method for controlling the processing cycle of functional concrete as described in claim 1, characterized in that, Analyze the functional requirements of the concrete and determine a functional evaluation plan, including: The functional requirements are analyzed to obtain a set of functional indicators, wherein the set of functional indicators includes multiple functional indicators with a degree of demand identification. Extract the first indicator from the plurality of functional indicators with demand indicators, and the first indicator corresponds to the first demand. The first indicator is adjusted with the first demand level as the weight to form the functional evaluation plan.

6. The method for controlling the processing cycle of functional concrete as described in claim 1, characterized in that, Based on the aforementioned functional evaluation plan, an optimization traversal is performed on the admixture-free reference library to obtain a first optimal control strategy, including: Based on the aforementioned functional evaluation plan, a functional evaluation analysis is performed on the first reference set in the additive-free reference library to obtain a first functional index; The additive-free reference library is sorted in descending order based on the first functional index to obtain an additive-free reference list; Obtain the first first reference set in the additive-free reference list, and use the co-drive control strategy in the first first reference set as the first optimal control strategy.

7. The method for controlling the processing cycle of functional concrete as described in claim 6, characterized in that, An optimization traversal is performed on the aforementioned reference library of admixtures to obtain a second optimal control strategy, including: Extract the second reference set from the admixture reference library; Based on the aforementioned functional evaluation plan, a functional evaluation analysis is performed on the second reference set to obtain a second functional index; Determine whether the second functional index is greater than the first first functional index of the first first reference set; If it is greater than, add the second reference set to the target reference platform; The target reference platform is sorted in descending order based on the second functional index to obtain a reference list with admixtures; Obtain the second first reference set from the admixture reference list, and use the co-drive control strategy in the second first reference set as the second optimal control strategy.

8. The method for controlling the processing cycle of functional concrete as described in claim 7, characterized in that, By comparing the first optimal control strategy with the second optimal control strategy, a target control strategy is obtained, including: Read the predefined comparison features; Based on the predetermined comparison features, a traversal analysis of the first control record in the first first reference set is performed to obtain the first control fitness. Based on the predetermined comparison features, a traversal analysis of the second control record in the second first reference set is performed to obtain the second control fitness. The target control strategy is determined by comparing the first control fitness with the second control fitness. The predetermined comparative features include at least the cost of admixtures, the duration of combined drive processing, and the functionality index.

9. The method for controlling the processing cycle of functional concrete as described in claim 1, characterized in that, After performing co-drive control on the concrete according to the target control strategy, the method further includes: Obtain the strength grade parameters of the concrete; Collect the application environment parameters of the concrete; Collect the application climate parameters of the concrete; Maintenance constraints are established based on the intensity level parameters, the application environment parameters, and the application climate parameters. Based on the maintenance constraints, a target maintenance scheme is matched in the maintenance database, and the concrete is maintained according to the target maintenance scheme.

10. A co-drive control system for the functional concrete processing cycle, characterized in that, The system is used to execute a co-drive control method for the processing cycle of functional concrete as described in any one of claims 1-9, the system comprising: The feature collection module is used to collect multi-dimensional features of concrete raw materials to obtain raw material feature information; The screening and analysis module is used to perform screening and analysis on the joint drive control database using the raw material characteristic information as screening constraints, so as to obtain a control reference database. A partitioning module is used to partition the control reference database to obtain partitioning results, wherein the partitioning results include a reference library without admixtures and a reference library with admixtures; The analysis module is used to analyze the functional requirements of the concrete and determine the functional evaluation plan. The optimization traversal module is used to perform optimization traversal on the reference library without admixtures based on the functional evaluation plan to obtain the first optimal control strategy, and to perform optimization traversal on the reference library with admixtures to obtain the second optimal control strategy. The co-drive control module is used to compare the first optimal control strategy with the second optimal control strategy to obtain a target control strategy, and to perform co-drive control on the concrete according to the target control strategy.

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