A real-time water consumption regulation method and system for concrete production

Abstract

The application discloses a kind of real-time regulation and control methods and systems of water consumption for concrete production, it is related to building material production automation field, including acquisition in the process of concrete production multi-source data, according to temperature, wind speed and environmental humidity calculation evaporation compensation quantity, initial water consumption is corrected;The power signal of mixer is Fourier transformed, and the sequence that rheological spectrum feature vector changes with time is constructed;Real-time calculation first derivative and second derivative of mixing power, determine the rheological critical turning point of concrete in combination with rheological spectrum feature vector sequence, and determine rheological water supply control window according to rheological critical turning point and derivative change trend.The application realizes the real-time fine regulation and control of water consumption for concrete production by fusing evaporation compensation calculation of environmental multi-source data, rheological critical turning identification based on mixing power spectrum feature and pulse water supply control strategy, and improves the stability of concrete flow state.

Description

Technical Field

[0001] This invention relates to the field of automation technology in building material production, and in particular to a method and system for real-time control of water usage in concrete production. Background Technology

[0002] With the continuous development of industrialized construction and centralized production of commercial concrete, the concrete production process is gradually evolving from traditional experience-based control towards digitalization, automation, and precision. In existing technologies, the water consumption for concrete production is typically set based on mix design results, and the initial water consumption is corrected by combining the moisture content test results of raw materials. Some advanced mixing plants have introduced online moisture content sensors, environmental temperature and humidity monitoring devices, and automatic metering and control systems. By collecting parameters such as aggregate moisture content and ambient temperature, they can dynamically adjust the mixing water consumption.

[0003] Existing technologies often focus on monitoring and correcting single or a few parameters. For example, they may only make a one-time correction to the initial water dosage based on aggregate moisture content or ambient temperature, or rely solely on empirical judgments based on changes in the amplitude of mixing power. These technologies lack in-depth analysis of the evolution of the rheological state during the mixing process. Under complex environmental conditions, the evaporation of moisture caused by the combined effects of temperature, wind speed, and ambient humidity is dynamic and uncertain, while the rheological characteristics of concrete during mixing also exhibit distinct stages and critical transitions. If water replenishment is based solely on static parameters or simple threshold controls, it is difficult to accurately identify the optimal timing and amount of water replenishment, easily leading to delayed or excessive adjustments, thus affecting the stability of the final workability of the concrete. Summary of the Invention

[0004] In view of the aforementioned existing problems, the present invention is proposed.

[0005] Therefore, this invention provides a method for real-time control of water consumption in concrete production, which solves the problems of insufficient accuracy in water consumption control and difficulty in real-time determination of rheological state during concrete production.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: In a first aspect, the present invention provides a method for real-time control of water consumption in concrete production, comprising, Collect multi-source data during the concrete production process, calculate the evaporation compensation based on temperature, wind speed and ambient humidity, and correct the initial water consumption. The power signal of the mixer is subjected to Fourier transform to construct a sequence of rheological spectrum feature vectors changing over time. The first and second derivatives of the mixing power are calculated in real time. The rheological critical inflection point of concrete is determined by combining the rheological spectrum feature vector sequence. The rheological water replenishment control window is determined based on the rheological critical inflection point and the trend of derivative change. Within the rheological water replenishment control window, the difference between the rheological spectrum feature vector and the preset target flow regime spectrum feature vector is calculated, and the theoretical water replenishment amount is calculated based on the spectrum deviation value and the evaporation compensation amount. The theoretical water replenishment volume is decomposed into multiple pulse water replenishment volumes in a decreasing proportion. A pulse risk function is constructed in real time after each pulse water replenishment. Water replenishment is stopped when the pulse risk function meets the preset termination condition. Data from the concrete production process is used as empirical data and uploaded to a database for storage.

[0007] As a preferred embodiment of the real-time water consumption control method for concrete production described in this invention, the step of collecting multi-source data during the concrete production process, calculating evaporation compensation based on temperature, wind speed, and ambient humidity, and correcting the initial water consumption includes the following steps: Before concrete is added, ambient temperature, relative humidity, wind speed, and aggregate surface temperature data are collected. The evaporation rate is then calculated using the combined data from temperature, wind speed, and humidity, using the following formula: ; in, Evaporation rate , , These are the ambient temperature coefficient, ambient wind speed coefficient, and ambient humidity coefficient, adjusted according to the season. For ambient temperature, The surface temperature of the aggregate. For ambient wind speed, This refers to the relative humidity of the environment.

[0008] The evaporation compensation is obtained by multiplying the evaporation rate by the stirring time read in the formula and the conversion factor set according to the season, and then using the evaporation compensation to correct the initial water consumption read in the formula.

[0009] As a preferred embodiment of the real-time control method for concrete production water consumption according to the present invention, the step of performing a Fourier transform on the power signal of the mixer to construct a sequence of rheological spectrum feature vectors changing over time includes the following steps: The mixer power signal is collected in real time during the mixing process, and the mixing time is divided into continuous time windows according to a fixed time length. Perform a Fourier transform on the mixer power signal within each time window to convert the power signal from the time domain to the frequency domain and obtain the spectrum information of the corresponding time window.

[0010] Based on the obtained spectrum information, low-frequency energy, high-frequency energy, spectral centroid, and power spectral entropy within the preset frequency range are extracted to construct the rheological spectrum feature vector corresponding to the time window.

[0011] The rheological spectrum feature vectors corresponding to each time window are arranged sequentially according to time order to generate a rheological spectrum feature vector sequence.

[0012] As a preferred embodiment of the real-time control method for concrete production water consumption described in this invention, the method involves: calculating the first and second derivatives of the mixing power in real time, determining the critical rheological inflection point of the concrete by combining the rheological spectrum feature vector sequence, and determining the rheological water replenishment control window based on the critical rheological inflection point and the trend of derivative changes, including the following steps: Based on the power signal of the mixer, the first derivative of the mixing power is calculated using the forward difference method, and the formula is: ; in, For time index, For the power signal of the mixer The first derivative at time t, For the mixer in Power signal at time, This represents the sampling time interval.

[0013] The second derivative of the stirring power is calculated using the central difference method, and the formula is as follows: ; in, For the power signal of the mixer The second derivative at time t.

[0014] The first derivative is used to reflect the rate of change of stirring resistance, while the second derivative is used to reflect the acceleration and trend reversal characteristics of the change of stirring resistance. By jointly analyzing the power change rate characteristics and the rheological spectrum feature vector sequence, when the first derivative of power changes from rising to falling, the second derivative changes sign, and the change in the rheological spectrum feature vector within the corresponding time window exceeds the preset threshold, the moment is determined to be the rheological critical inflection point.

[0015] After identifying the rheological critical inflection point, the power change trend at subsequent moments of the inflection point is tracked and analyzed. When the first derivative of the power is negative within a preset continuous sampling period and the absolute value is less than the set rate of change threshold, the time interval from the rheological critical inflection point to the time interval that meets the above judgment conditions is determined as the rheological water replenishment control window.

[0016] As a preferred embodiment of the real-time control method for concrete production water consumption according to the present invention, the step of calculating the difference between the rheological spectrum feature vector and the preset target flow regime spectrum feature vector within the rheological water replenishment control window, and calculating the theoretical water replenishment amount based on the spectrum deviation value and evaporation compensation amount, includes the following steps: The sensitivity value of each feature component at the rheological critical inflection point is obtained by subtracting the feature component at the time before the inflection point from the feature component at the time after the inflection point. The sensitivity value is then normalized to obtain the sensitivity weight of each feature component, as shown in the formula: ; in, For feature component index, The total number of characteristic components, For the first Sensitivity weights of each feature component Index for rheological critical inflection points. For the first The moment of a rheological critical inflection point The sampling time interval, For the first The values ​​of each feature component This is a very small positive number set to prevent the denominator from being 0.

[0017] Within the rheological water replenishment control window, the components of each feature of the rheological spectrum feature vector at each moment are subtracted from the components of the preset target flow regime spectrum feature vector to obtain the component deviation of each feature. Based on the component deviations of each feature and combined with the sensitivity weights of each feature component, a comprehensive deviation index is constructed using weighted Euclidean distance, as shown in the formula: ; in, for The comprehensive deviation index at any given time, , , , These are the sensitivity weights for low-frequency energy, high-frequency energy, spectral centroid, and power spectral entropy, respectively. This refers to the deviation of the low-frequency energy component. This refers to the component deviation of high-frequency energy. This represents the component deviation of the spectral centroid. This represents the component deviation of the power spectral entropy.

[0018] The evaporation compensation is obtained by multiplying the evaporation rate by the sampling time interval. A nonlinear saturation mapping is then applied to the deviation of the comprehensive index to obtain the required water replenishment for flow correction. The formula is as follows: ; in, for The amount of water required for flow correction at any given moment. The conversion factor for calculating water volume is obtained by fitting historical data to the deviation. The upper limit for water replenishment during a single correction operation is set. This is the sensitivity coefficient.

[0019] The theoretical water replenishment amount is obtained by adding the evaporation compensation amount to the flow correction water replenishment amount.

[0020] As a preferred embodiment of the real-time control method for concrete production water consumption described in this invention, the method of decomposing the theoretical water replenishment amount into multiple pulse water replenishment amounts in a decreasing proportion, constructing a pulse risk function in real time after each pulse water replenishment, and stopping water replenishment when the pulse risk function meets a preset termination condition includes the following steps: After each pulse of water addition, the comprehensive deviation index is calculated, and an adaptive decreasing coefficient is constructed based on the comprehensive deviation index. The formula is as follows: ; in, The pulse number. For the first The decreasing ratio of the next pulse. This is the preset minimum decreasing rate. This is the preset maximum decreasing ratio. This is the risk sensitivity coefficient. This is the pulse risk function value at the time of the previous pulse, set to 0 at the time of the first pulse. For the first The comprehensive deviation index of the secondary pulse. This is a very small positive number set to prevent the denominator from being 0.

[0021] If the overall deviation index is large and the risk is low, water addition will be more aggressive; if the overall index is small and the risk of a sudden surge is high, water addition will be more conservative, forming a gradual water addition process.

[0022] The remaining theoretical water replenishment demand is weighted and limited using an adaptive decreasing coefficient to obtain the water replenishment amount for each pulse, as shown in the formula: ; in, For the first Sub-pulse water addition The initial pulse water injection will be equal to the theoretical water replenishment amount, representing the remaining theoretical water demand. The minimum amount of water added in a single pulse is set. This is the maximum amount of water added in a single pulse.

[0023] After each pulse water addition, the cumulative water addition is updated in real time, and the remaining theoretical water replenishment requirement is updated by subtracting the cumulative water addition from the theoretical water replenishment amount. The effective water-cement ratio is obtained by summing the corrected initial water consumption and the cumulative water consumption, and then comparing it with the total amount of concrete materials. Based on the effective water-cement ratio, the risk value of exceeding the water-cement ratio limit is calculated using the following formula: ; in, For the first Risk of exceeding the water-cement ratio limit after secondary pulse water addition For the first The effective water-gel ratio after adding water via the second pulse. , These are the maximum and minimum limits for the effective water-cement ratio, respectively.

[0024] After each pulse water addition, the difference between the comprehensive deviation index and the comprehensive deviation index before pulse water addition is calculated, and the difference is normalized to obtain the pulse response abnormality penalty value.

[0025] A target threshold for the spectral deviation index is preset, and the deviation of the comprehensive deviation index from the target threshold range is calculated. The deviation is then normalized to obtain the risk value of non-compliance of the flow regime.

[0026] The risk values ​​of water-cement ratio exceeding the limit, flow state not meeting the standard, and impulse response abnormality penalty value are weighted and processed to construct an impulse risk function; The weighting coefficients for the weighted processing are determined by regression analysis of historical experimental data and calibration based on engineering experience.

[0027] Multiple termination conditions are set. When any one of the termination conditions is met after pulse water addition, water addition stops. After the mixing time reaches the time specified in the formula, the finished concrete product is obtained. The multi-level termination conditions include: the cumulative water addition has reached the theoretical water replenishment amount, the pulse risk function value has reached the preset risk threshold, the duration of the pulse water addition phase has reached the preset upper limit, and the comprehensive deviation index is lower than the set deviation threshold within the preset continuous sampling period.

[0028] As a preferred embodiment of the real-time control method for concrete production water consumption according to the present invention, the step of uploading and storing data from the concrete production process as empirical data in a database includes the following steps: Real-time monitoring data, impulse risk function values, comprehensive deviation indicators, and termination judgment results during the concrete production process are used as empirical data. After time alignment, they are uploaded to the database for storage in a fixed data format.

[0029] Secondly, the present invention provides a real-time control system for water consumption in concrete production, comprising, The multi-source data acquisition module collects and preprocesses ambient temperature, ambient humidity, ambient wind speed, aggregate surface temperature, and mixer power signal data in real time. The evaporation compensation calculation module calculates the evaporation rate and evaporation compensation based on the collected environmental parameters, and corrects the initial water consumption in the formula. The spectrum feature construction module performs frequency domain transformation on the mixer power signal, extracts low-frequency energy, high-frequency energy, spectral centroid and power spectral entropy, and constructs a rheological spectrum feature vector sequence. The rheological inflection point identification module identifies the critical rheological inflection point based on the first and second derivatives of the stirring power and the rheological spectrum feature vector sequence, and determines the rheological water replenishment control window. The comprehensive deviation calculation module calculates the deviation between the rheological spectrum feature vector and the target flow state feature within the rheological water replenishment control window, and constructs a comprehensive deviation index that quantifies the degree of deviation of the current flow state. The pulse water replenishment module generates multiple pulse water replenishment volumes with decreasing proportions based on the theoretical water replenishment volume, and updates the remaining water replenishment demand after each pulse. The risk assessment module constructs a pulse risk function based on the effective water-cement ratio, comprehensive deviation index, and pulse response changes, and outputs a stop water replenishment command according to preset termination conditions.

[0030] Thirdly, the present invention provides a computer device including a memory and a processor, wherein the memory stores a computer program, wherein when the computer program is executed by the processor, it implements any step of the real-time control method for concrete production water consumption as described in the first aspect of the present invention.

[0031] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, it implements any step of the real-time control method for concrete production water consumption as described in the first aspect of the present invention.

[0032] The beneficial effects of this invention are as follows: By collecting multi-source data such as ambient temperature, humidity, wind speed, and aggregate temperature and constructing an evaporation rate model, the initial water usage of concrete is pre-corrected, improving the environmental adaptability and rationality of water usage settings. By constructing a rheological spectrum feature vector sequence, a frequency domain structured expression of the concrete rheological state is achieved. Through joint analysis of the trends in the first and second derivatives of power with the rheological spectrum feature vector sequence, the critical rheological inflection point is determined, and the rheological water replenishment control window is accordingly identified. This achieves dynamic locking of the water replenishment timing, avoiding blindly adding water too early or too late, and enhancing the timing precision of water usage control. By constructing a comprehensive deviation index based on sensitive weights and combining it with evaporation compensation for nonlinear mapping to calculate the theoretical water replenishment, the water replenishment decision takes into account both environmental impact and flow regime deviation, improving the pertinence and coordination of water replenishment calculation. The theoretical water replenishment is decomposed into multiple pulse water additions with decreasing proportions, and a pulse risk function integrating water-cement ratio risk, flow regime non-compliance risk, and response anomaly penalty is constructed. This achieves closed-loop constraint and risk assessment of the water replenishment process, enabling the water addition behavior to have gradual correction and adaptive termination capabilities. This ensures that the flow performance reaches the target state while suppressing the risk of water-cement ratio runaway, thus improving the safety and stability of concrete quality control. Attached Figure Description

[0033] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0034] Figure 1 A flowchart for a method of real-time control of water consumption in concrete production.

[0035] Figure 2 A schematic diagram of a real-time water consumption control system for concrete production.

[0036] Figure 3 The flowchart is used to calculate evaporation compensation and revise the initial water consumption.

[0037] Figure 4 Flowchart for determining the critical inflection point of rheology. Detailed Implementation

[0038] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0039] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0040] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0041] Reference Figures 1-4 As one embodiment of the present invention, this embodiment provides a method for real-time control of water consumption in concrete production, comprising the following steps: Collect multi-source data during the concrete production process, calculate the evaporation compensation based on temperature, wind speed, and ambient humidity, and correct the initial water consumption.

[0042] Specifically, before concrete is added, data on ambient temperature, relative humidity, wind speed, and aggregate surface temperature are collected. The evaporation rate is then calculated using the temperature, wind speed, and ambient humidity data, using the following formula: ; in, Evaporation rate , , These are the ambient temperature coefficient, ambient wind speed coefficient, and ambient humidity coefficient, adjusted according to the season. For ambient temperature, The surface temperature of the aggregate. For ambient wind speed, This refers to the relative humidity of the environment.

[0043] The evaporation compensation is obtained by multiplying the evaporation rate by the stirring time read in the formula and the conversion factor set according to the season, and then using the evaporation compensation to correct the initial water consumption read in the formula.

[0044] By collecting multi-source data and constructing an evaporation rate calculation model based on the coupling relationship between temperature, wind speed, and humidity, the potential water loss trend during the mixing stage can be predicted in advance, improving the foresight and scientific nature of water use control. By correlating the evaporation rate with the mixing time and seasonal conversion coefficient read from the formula, the evaporation compensation amount is obtained, and the initial water consumption is corrected accordingly. While maintaining the stability of the original mix design logic, its environmental adaptability is enhanced, reducing the risk of workability deviations caused by climate fluctuations.

[0045] The power signal of the mixer is subjected to Fourier transform to construct a sequence of rheological spectrum feature vectors changing over time.

[0046] Specifically, the power signal of the mixer is collected in real time during the mixing process, and the mixing time is divided into continuous time windows according to a fixed time length; Perform a Fourier transform on the mixer power signal within each time window to convert the power signal from the time domain to the frequency domain and obtain the spectrum information of the corresponding time window.

[0047] Based on the obtained spectrum information, low-frequency energy, high-frequency energy, spectral centroid, and power spectral entropy within the preset frequency range are extracted to construct the rheological spectrum feature vector corresponding to the time window.

[0048] The rheological spectrum feature vectors corresponding to each time window are arranged sequentially according to time order to generate a rheological spectrum feature vector sequence.

[0049] By dividing the mixing time into continuous time windows, segmented dynamic observation of the concrete mixing process is achieved, transforming the originally continuous and complex power fluctuations into analyzable staged data units, thus enhancing the process's reproducibility. By performing Fourier transforms on the power signals within each time window and extracting features such as low-frequency energy, high-frequency energy, spectral centroid, and power spectral entropy within a preset frequency range to construct rheological spectrum feature vectors, a multi-dimensional quantitative description of concrete rheological behavior is achieved. This expands the single power amplitude index into a comprehensive characterization system encompassing energy distribution, frequency shift, and complexity characteristics. Arranging the rheological spectrum feature vectors of each time window in chronological order generates a rheological spectrum feature vector sequence, enabling a sequential expression of the rheological state evolution process and providing continuous dynamic basis for subsequent critical transition identification and water replenishment control decisions.

[0050] The first and second derivatives of the mixing power are calculated in real time. The rheological critical inflection point of concrete is determined by combining the rheological spectrum feature vector sequence. The rheological water replenishment control window is determined based on the rheological critical inflection point and the trend of derivative change.

[0051] Specifically, based on the power signal of the mixer, the first derivative of the mixing power is calculated using the forward difference method, with the following formula: ; in, For time index, For the power signal of the mixer The first derivative at time t, For the mixer in Power signal at time, This represents the sampling time interval.

[0052] The second derivative of the stirring power is calculated using the central difference method, and the formula is as follows: ; in, For the power signal of the mixer The second derivative at time t.

[0053] The first derivative is used to reflect the rate of change of stirring resistance, while the second derivative is used to reflect the acceleration and trend reversal characteristics of the change of stirring resistance. By jointly analyzing the power change rate characteristics and the rheological spectrum feature vector sequence, when the first derivative of power changes from rising to falling, the second derivative changes sign, and the change in the rheological spectrum feature vector within the corresponding time window exceeds the preset threshold, the moment is determined to be the rheological critical inflection point.

[0054] After identifying the rheological critical inflection point, the power change trend at subsequent moments of the inflection point is tracked and analyzed. When the first derivative of the power is negative within a preset continuous sampling period and the absolute value is less than the set rate of change threshold, the time interval from the rheological critical inflection point to the time interval that meets the above judgment conditions is determined as the rheological water replenishment control window.

[0055] By calculating the first derivative of the mixer power signal using the forward difference method and the second derivative using the central difference method, the rate and acceleration of change in the mixing load are characterized. This allows for a more sensitive capture of the reorganization of the internal particle structure and the changes in the agglomeration state of the paste, improving the precision of process perception and trend judgment. By jointly analyzing the power change rate characteristics and the rheological spectrum feature vector sequence, the rheological critical inflection point is determined when the trend of the first derivative of power reverses, the sign of the second derivative changes, and the spectral characteristics shift significantly. This enables accurate identification of the transition moment from the structural construction stage to the stable flow stage of concrete, and avoids interference with the control results due to misjudgment of a single signal, enhancing the reliability and stability of the critical state determination. After identifying the rheological critical inflection point, the subsequent power change trend is continuously tracked, and the rheological water replenishment control window is defined when the rate of change tends to level off, achieving dynamic limitation of the optimal water replenishment period and improving the rationality of the water replenishment sequence.

[0056] Within the rheological water replenishment control window, the difference between the rheological spectrum feature vector and the preset target flow regime spectrum feature vector is calculated, and the theoretical water replenishment amount is calculated based on the spectrum deviation value and the evaporation compensation amount.

[0057] Specifically, the difference between the feature components at the time before and after the inflection point is calculated to obtain the sensitivity value of each feature component at the rheological critical inflection point. The sensitivity values ​​are then normalized to obtain the sensitivity weight of each feature component, as shown in the formula: ; in, For feature component index, The total number of characteristic components, For the first Sensitivity weights of each feature component Index for rheological critical inflection points. For the first The moment of a rheological critical inflection point The sampling time interval, For the first The values ​​of each feature component This is a very small positive number set to prevent the denominator from being 0.

[0058] Within the rheological water replenishment control window, the components of each feature of the rheological spectrum feature vector at each moment are subtracted from the components of the preset target flow regime spectrum feature vector to obtain the component deviation of each feature. Based on the component deviations of each feature and combined with the sensitivity weights of each feature component, a comprehensive deviation index is constructed using weighted Euclidean distance, as shown in the formula: ; in, for The comprehensive deviation index at any given time, , , , These are the sensitivity weights for low-frequency energy, high-frequency energy, spectral centroid, and power spectral entropy, respectively. This refers to the deviation of the low-frequency energy component. This refers to the component deviation of high-frequency energy. This represents the component deviation of the spectral centroid. This represents the component deviation of the power spectral entropy.

[0059] The evaporation compensation is obtained by multiplying the evaporation rate by the sampling time interval. A nonlinear saturation mapping is then applied to the deviation of the comprehensive index to obtain the required water replenishment for flow correction. The formula is as follows: ; in, for The amount of water required for flow correction at any given moment. The conversion factor for calculating water volume is obtained by fitting historical data to the deviation. The upper limit for water replenishment during a single correction operation is set. This is the sensitivity coefficient.

[0060] The theoretical water replenishment amount is obtained by adding the evaporation compensation amount to the flow correction water replenishment amount.

[0061] By performing difference calculations on the feature components before and after the rheological critical inflection point, the response amplitude of each feature at the moment of structural abrupt change is extracted. The obtained sensitivity values ​​are then normalized to construct sensitivity weights, thus quantifying the contribution of different spectral features in the rheological evolution process and improving the targeting and discrimination accuracy of water replenishment decisions. Within the rheological water replenishment control window, the component difference calculation between the real-time rheological spectral feature vector and the preset target flow state spectral feature vector explicitly expresses the degree of deviation between the current flow state and the ideal flow state, enhancing the control directionality. Combined with the sensitivity weights, an additive... The weighted Euclidean distance is used to construct a comprehensive deviation index, which realizes the fusion and compression of multi-dimensional rheological deviation information. This integrates complex frequency domain differences into a single evaluation quantity that can be used for control decision-making, improving the efficiency and feasibility of the water replenishment process. By correlating the evaporation rate with the sampling time to obtain the evaporation compensation amount, and performing nonlinear saturation mapping on the comprehensive deviation index, the flow regime correction water replenishment demand is generated. This achieves the coordinated adjustment of environmental loss factors and flow regime structure deviation, so that the water replenishment amount reflects both the internal structural adjustment needs of the material and the influence of the external environment, improving the stability and adaptability of the water replenishment calculation.

[0062] The theoretical water replenishment volume is decomposed into multiple pulse water replenishment volumes in a decreasing proportion. After each pulse water replenishment, a pulse risk function is constructed in real time. Water replenishment is stopped when the pulse risk function meets the preset termination condition.

[0063] Specifically, after each pulse of water addition, a comprehensive deviation index is calculated, and an adaptive decreasing coefficient is constructed based on the comprehensive deviation index. The formula is as follows: ; in, The pulse number. For the first The decreasing ratio of the next pulse. This is the preset minimum decreasing rate. This is the preset maximum decreasing ratio. This is the risk sensitivity coefficient. This is the pulse risk function value at the time of the previous pulse, set to 0 at the time of the first pulse. For the first The comprehensive deviation index of the secondary pulse. This is a very small positive number set to prevent the denominator from being 0.

[0064] The remaining theoretical water replenishment demand is weighted and limited using an adaptive decreasing coefficient to obtain the water replenishment amount for each pulse, as shown in the formula: ; in, For the first Sub-pulse water addition The initial pulse water injection will be equal to the theoretical water replenishment amount, representing the remaining theoretical water demand. The minimum amount of water added in a single pulse is set. This is the maximum amount of water added in a single pulse.

[0065] After each pulse water addition, the cumulative water addition is updated in real time, and the remaining theoretical water replenishment requirement is updated by subtracting the cumulative water addition from the theoretical water replenishment amount. The effective water-cement ratio is obtained by summing the corrected initial water consumption and the cumulative water consumption, and then comparing it with the total amount of concrete materials. Based on the effective water-cement ratio, the risk value of exceeding the water-cement ratio limit is calculated using the following formula: ; in, For the first Risk of exceeding the water-cement ratio limit after secondary pulse water addition For the first The effective water-gel ratio after adding water via the second pulse. , These are the maximum and minimum limits for the effective water-cement ratio, respectively.

[0066] After each pulse water addition, the difference between the comprehensive deviation index and the comprehensive deviation index before pulse water addition is calculated, and the difference is normalized to obtain the pulse response abnormality penalty value.

[0067] A target threshold for the spectral deviation index is preset, and the deviation of the comprehensive deviation index from the target threshold range is calculated. The deviation is then normalized to obtain the risk value of non-compliance of the flow regime.

[0068] The risk values ​​of water-cement ratio exceeding the limit, flow state not meeting the standard, and impulse response abnormality penalty value are weighted and processed to construct an impulse risk function; The weighting coefficients for the weighted processing are determined by regression analysis of historical experimental data and calibration based on engineering experience.

[0069] Multiple termination conditions are set. When any one of the termination conditions is met after pulse water addition, water addition stops. After the mixing time reaches the time specified in the formula, the finished concrete product is obtained. The multi-level termination conditions include: the cumulative water addition has reached the theoretical water replenishment amount, the pulse risk function value has reached the preset risk threshold, the duration of the pulse water addition phase has reached the preset upper limit, and the comprehensive deviation index is lower than the set deviation threshold within the preset continuous sampling period.

[0070] By recalculating the comprehensive deviation index after each pulse of water addition and constructing an adaptive decreasing coefficient based on this index, the water replenishment intensity dynamically converges as the flow regime approaches the target state, forming a progressively corrected water addition behavior. The adaptive decreasing coefficient is used to weight and limit the remaining theoretical water replenishment demand, and combined with real-time updates of the cumulative water addition, achieving full-process constraint and dynamic balance of the total water replenishment, enhancing the closed-loop nature and controllability of the control strategy. By integrating the corrected initial water consumption and cumulative water addition and converting them into an effective water-cement ratio, a risk value for exceeding the water-cement ratio limit is constructed, ensuring that flow regime adjustment is no longer solely focused on workability but also considers strength and durability requirements, improving the comprehensiveness and safety of quality control. The difference in the comprehensive deviation index before and after the pulse is further analyzed. Normalization is performed to obtain anomaly penalty values ​​for impulse response, enabling real-time assessment of the sensitivity of water addition effect. Furthermore, a flow regime failure risk value is constructed by combining the target threshold of spectral deviation, and weighted and fused with the water-cement ratio exceeding limit risk value and the anomaly penalty value to form an impulse risk function. This achieves a unified quantitative expression of material performance risk, flow regime deviation risk, and control response risk, providing a multi-dimensional constraint basis for water addition decisions and improving the comprehensiveness and scientific nature of the decision-making process. Multiple termination conditions are set, and water addition is stopped when any condition is met, achieving adaptive termination and safe exit of the water addition process. This ensures that the concrete locks in its state promptly when it reaches the target flow regime and meets performance boundary conditions, avoiding over-adjustment or hysteresis, and improving the stability of the finished concrete and the reliability of the production process.

[0071] Data from the concrete production process is used as empirical data and uploaded to a database for storage.

[0072] Specifically, real-time monitoring data, impulse risk function values, comprehensive deviation indicators, and termination judgment results during the concrete production process are used as empirical data. After time alignment, they are uploaded to the database for storage in a fixed data format.

[0073] By uniformly collecting and integrating real-time monitoring data, impulse risk function values, comprehensive deviation indicators, and termination judgment results during the concrete production process, a structured summary of key control variables and decision results throughout the entire production process is achieved. This enables data scattered across different control links to form a complete data chain, providing a basis for subsequent quality traceability and process review, and enhancing production transparency and traceability.

[0074] This embodiment also provides a real-time control system for water consumption in concrete production, including: The multi-source data acquisition module collects and preprocesses ambient temperature, ambient humidity, ambient wind speed, aggregate surface temperature, and mixer power signal data in real time. The evaporation compensation calculation module calculates the evaporation rate and evaporation compensation based on the collected environmental parameters, and corrects the initial water consumption in the formula. The spectrum feature construction module performs frequency domain transformation on the mixer power signal, extracts low-frequency energy, high-frequency energy, spectral centroid and power spectral entropy, and constructs a rheological spectrum feature vector sequence. The rheological inflection point identification module identifies the critical rheological inflection point based on the first and second derivatives of the stirring power and the rheological spectrum feature vector sequence, and determines the rheological water replenishment control window. The comprehensive deviation calculation module calculates the deviation between the rheological spectrum feature vector and the target flow state feature within the rheological water replenishment control window, and constructs a comprehensive deviation index that quantifies the degree of deviation of the current flow state. The pulse water replenishment module generates multiple pulse water replenishment volumes with decreasing proportions based on the theoretical water replenishment volume, and updates the remaining water replenishment demand after each pulse. The risk assessment module constructs a pulse risk function based on the effective water-cement ratio, comprehensive deviation index, and pulse response changes, and outputs a stop water replenishment command according to preset termination conditions.

[0075] This embodiment also provides a computer device applicable to the real-time control method for water consumption in concrete production, comprising: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to realize the real-time control method for water consumption in concrete production as proposed in the above embodiment.

[0076] The computer device can be a terminal, comprising a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0077] This embodiment also provides a storage medium storing a computer program, which, when executed by a processor, implements the method for real-time control of water usage in concrete production as proposed in the above embodiments. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0078] In summary, this invention achieves pre-correction of initial water usage in concrete by collecting multi-source data such as ambient temperature, humidity, wind speed, and aggregate temperature and constructing an evaporation rate model, thereby improving the environmental adaptability and rationality of water usage settings. Furthermore, by constructing a rheological spectrum feature vector sequence, it achieves a frequency-domain structured expression of the concrete rheological state. By jointly analyzing the trends of the first and second derivatives of power with the rheological spectrum feature vector sequence, it determines the critical rheological inflection point and accordingly establishes the rheological water replenishment control window, achieving dynamic locking of the water replenishment timing. This avoids blindly adding water too early or too late, enhancing the timing accuracy of water usage control. By constructing a comprehensive deviation index based on sensitive weights and combining it with evaporation compensation for nonlinear mapping to calculate the theoretical water replenishment, the water replenishment decision takes into account both environmental impact and flow pattern deviation, improving the pertinence and coordination of water replenishment calculation. The theoretical water replenishment is decomposed into multiple pulse water additions with decreasing proportions, and a pulse risk function integrating water-cement ratio risk, flow pattern non-compliance risk, and response anomaly penalty is constructed. This achieves closed-loop constraint and risk assessment of the water replenishment process, enabling the water addition behavior to have gradual correction and adaptive termination capabilities. This ensures that the flow performance reaches the target state and suppresses the risk of water-cement ratio runaway, improving the safety and stability of concrete quality control.

[0079] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for real-time control of water consumption in concrete production, characterized in that: include, Collect multi-source data during the concrete production process, calculate the evaporation compensation based on temperature, wind speed and ambient humidity, and correct the initial water consumption. The power signal of the mixer is subjected to Fourier transform to construct a sequence of rheological spectrum feature vectors changing over time. The first and second derivatives of the mixing power are calculated in real time. The rheological critical inflection point of concrete is determined by combining the rheological spectrum feature vector sequence. The rheological water replenishment control window is determined based on the rheological critical inflection point and the trend of derivative change. Within the rheological water replenishment control window, the difference between the rheological spectrum feature vector and the preset target flow regime spectrum feature vector is calculated, and the theoretical water replenishment amount is calculated based on the spectrum deviation value and the evaporation compensation amount. The theoretical water replenishment volume is decomposed into multiple pulse water replenishment volumes in a decreasing proportion. A pulse risk function is constructed in real time after each pulse water replenishment. Water replenishment is stopped when the pulse risk function meets the preset termination condition. Data from the concrete production process is used as empirical data and uploaded to a database for storage.

2. The method for real-time control of water consumption in concrete production as described in claim 1, characterized in that: The process of collecting multi-source data during concrete production, calculating evaporation compensation based on temperature, wind speed, and ambient humidity, and correcting the initial water consumption includes the following steps: Before concrete is added, data on ambient temperature, relative humidity, wind speed, and aggregate surface temperature are collected, and the evaporation rate is calculated using temperature, wind speed, and ambient humidity. The evaporation compensation is obtained by multiplying the evaporation rate by the stirring time read in the formula and the conversion factor set according to the season, and then using the evaporation compensation to correct the initial water consumption read in the formula.

3. The method for real-time control of water consumption in concrete production as described in claim 2, characterized in that: The step of performing a Fourier transform on the power signal of the mixer to construct a sequence of rheological spectrum feature vectors changing over time includes the following steps: The mixer power signal is collected in real time during the mixing process, and the mixing time is divided into continuous time windows according to a fixed time length. Perform a Fourier transform on the mixer power signal within each time window to convert the power signal from the time domain to the frequency domain and obtain the spectrum information of the corresponding time window; Based on the obtained spectrum information, low-frequency energy, high-frequency energy, spectral centroid and power spectral entropy within the preset frequency range are extracted to construct the rheological spectrum feature vector corresponding to the time window. The rheological spectrum feature vectors corresponding to each time window are arranged sequentially according to time order to generate a rheological spectrum feature vector sequence.

4. The method for real-time control of water consumption in concrete production as described in claim 3, characterized in that: The process of calculating the first and second derivatives of the real-time mixing power, determining the critical rheological inflection point of the concrete by combining the rheological spectrum feature vector sequence, and determining the rheological water replenishment control window based on the critical rheological inflection point and the trend of derivative changes includes the following steps: Based on the power signal of the mixer, the first derivative of the mixing power is calculated using the forward difference method, and the second derivative of the mixing power is calculated using the central difference method. By jointly analyzing the power change rate characteristics and the rheological spectrum feature vector sequence, when the first derivative of power changes from rising to falling, the second derivative changes sign, and the change in the rheological spectrum feature vector within the corresponding time window exceeds the preset threshold, the moment is determined to be the rheological critical inflection point. After identifying the rheological critical inflection point, the power change trend at subsequent moments of the inflection point is tracked and analyzed. When the first derivative of the power is negative within a preset continuous sampling period and the absolute value is less than the set rate of change threshold, the time interval from the rheological critical inflection point to the time interval that meets the above judgment conditions is determined as the rheological water replenishment control window.

5. The method for real-time control of water consumption in concrete production as described in claim 4, characterized in that: Within the rheological water replenishment control window, the difference between the rheological spectrum feature vector and the preset target flow regime spectrum feature vector is calculated, and the theoretical water replenishment amount is calculated based on the spectrum deviation value and the evaporation compensation amount. This includes the following steps: The difference between the feature components at the moment before the inflection point and the feature components at the moment after the inflection point is used to obtain the sensitivity value of each feature component at the rheological critical inflection point. The sensitivity value is then normalized to obtain the sensitivity weight of each feature component. Within the rheological water replenishment control window, the component deviations of each feature of the rheological spectrum feature vector at each moment are obtained by subtracting the components of each feature from the preset target flow regime spectrum feature vector. Based on the component deviations of each feature, and combined with the sensitivity weights of each feature component, a comprehensive deviation index is constructed using weighted Euclidean distance. The evaporation compensation amount is obtained by multiplying the evaporation rate by the sampling time interval. The deviation of the comprehensive index is then subjected to nonlinear saturation mapping to obtain the flow correction and water replenishment demand. The theoretical water replenishment amount is obtained by adding the evaporation compensation amount to the flow correction water replenishment amount.

6. The method for real-time control of water consumption in concrete production as described in claim 5, characterized in that: The process of decomposing the theoretical water replenishment volume into multiple pulse water replenishment volumes in a decreasing proportion, constructing a pulse risk function in real time after each pulse water replenishment, and stopping water replenishment when the pulse risk function meets a preset termination condition includes the following steps: After each pulse of water addition, the comprehensive deviation index is calculated, and an adaptive decreasing coefficient is constructed based on the comprehensive deviation index; The remaining theoretical water replenishment demand is weighted and limited using an adaptive decreasing coefficient to obtain the water replenishment amount for each pulse. After each pulse water addition, the cumulative water addition is updated in real time, and the remaining theoretical water addition requirement is obtained by subtracting the cumulative water addition from the theoretical water replenishment amount. The effective water-cement ratio is obtained by summing the corrected initial water consumption and the cumulative water consumption, and then comparing it with the total amount of concrete materials. Based on the effective water-cement ratio, the risk value of exceeding the water-cement ratio limit is calculated. After each pulse water injection, the difference between the comprehensive deviation index and the comprehensive deviation index before pulse water injection is calculated, and the difference is normalized to obtain the pulse response abnormality penalty value. The target threshold of the spectrum deviation index is preset, and the deviation of the comprehensive deviation index from the target threshold range is calculated. The deviation is then normalized to obtain the risk value of non-compliance of the flow regime. The risk values ​​of water-cement ratio exceeding the limit, flow state not meeting the standard, and impulse response abnormality penalty value are weighted and processed to construct an impulse risk function; Multiple termination conditions are set. When any one of the termination conditions is met after pulse water addition, water addition stops. After the mixing time reaches the time specified in the formula, the finished concrete product is obtained.

7. The method for real-time control of water consumption in concrete production as described in claim 6, characterized in that: The process of uploading and storing data from the concrete production process as empirical data in a database includes the following steps: Real-time monitoring data, impulse risk function values, comprehensive deviation indicators, and termination judgment results during the concrete production process are used as empirical data. After time alignment, they are uploaded to the database for storage in a fixed data format.

8. A real-time water consumption control system for concrete production, based on the real-time water consumption control method for concrete production according to any one of claims 1 to 7, characterized in that: include, The multi-source data acquisition module collects and preprocesses ambient temperature, ambient humidity, ambient wind speed, aggregate surface temperature, and mixer power signal data in real time. The evaporation compensation calculation module calculates the evaporation rate and evaporation compensation based on the collected environmental parameters, and corrects the initial water consumption in the formula. The spectrum feature construction module performs frequency domain transformation on the mixer power signal, extracts low-frequency energy, high-frequency energy, spectral centroid and power spectral entropy, and constructs a rheological spectrum feature vector sequence. The rheological inflection point identification module identifies the critical rheological inflection point based on the first and second derivatives of the stirring power and the rheological spectrum feature vector sequence, and determines the rheological water replenishment control window. The comprehensive deviation calculation module calculates the deviation between the rheological spectrum feature vector and the target flow state feature within the rheological water replenishment control window, and constructs a comprehensive deviation index that quantifies the degree of deviation of the current flow state. The pulse water replenishment module generates multiple pulse water replenishment volumes with decreasing proportions based on the theoretical water replenishment volume, and updates the remaining water replenishment demand after each pulse. The risk assessment module constructs a pulse risk function based on the effective water-cement ratio, comprehensive deviation index, and pulse response changes, and outputs a stop water replenishment command according to preset termination conditions.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, it implements the steps of the real-time control method for concrete production water consumption as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the real-time control method for concrete production water volume as described in any one of claims 1 to 7.

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