Bleed concrete proportioning error prevention early warning system based on multi-source data fusion verification

Abstract

The application discloses a clean concrete proportioning mistake-proofing early warning system based on multi-source data fusion verification. A multi-source data fusion verification controller starts a discharging program, constructs a real-time material phase characteristic vector by using a powder diffuse reflection spectrum during a discharging period, and calculates the similarity of the real-time material phase characteristic vector and a material phase benchmark vector to perform mistake-proofing interception of material feeding; after release, a material phase microscopic fluctuation deviation is used to dynamically generate a downstream judgment matrix, generate a dynamic target dielectric upper limit value and a target rheological vector; during a dry and wet mixing stage, the mixed material complex dielectric constant and the initial hydration temperature rise value are collected for coupling compensation and moisture verification; during a mixing final state stage, the mechanical torque root mean square and the ultrasonic attenuation coefficient are collected to construct a real-time rheological vector, and the norm distance of the real-time rheological vector and the target rheological vector is calculated; when the norm distance is over the limit, the volume of the additional agent is calculated based on a conversion matrix, and a directional injection assembly is driven to perform online dynamic compensation.

Description

Technical Field

[0001] This invention relates to the field of building material processing and automation control technology, specifically to a fair-faced concrete mix design error prevention and early warning system based on multi-source data fusion verification. Background Technology

[0002] Fair-faced concrete has strict standards for the consistency of its appearance quality after molding and is widely used in modern construction projects. The quality of finished fair-faced concrete depends not only on the preset formula, but also on the control logic of the automated batching system of the mixing plant and the stability of the raw materials.

[0003] In existing automated concrete mixing production, conventional mix proportion control mainly adopts static gravity weighing. During production, the control system uses weighing sensors installed at the bottom of the storage silos to dynamically accumulate weights according to the target mass set in the formula, and controls the opening and closing of the corresponding silo doors to allow material to fall. After gravity weighing, all kinds of basic materials are directly collected and fall into the mixing host below for mixing with water.

[0004] However, existing control schemes have technical limitations in actual production. Current gravity metering control logic can only monitor the absolute mass parameters of materials, lacking a means to identify the optical characteristics of powder phases in real time. When the microstructure of different batches of powder fluctuates, existing batching control systems in mixing plants mainly rely on static gravity metering, lacking a closed-loop error-proofing mechanism that links online identification of powder phase spectral characteristics with the feeding actuator. This makes it difficult to intercept powder materials whose properties deviate from the baseline in real time during the feeding stage. This lack of a pre-feeding material property identification mechanism leads to a loss of accurate baseline for subsequent water addition verification and rheological state control. This may result in a decrease in the accuracy of fair-faced concrete mix proportions, thus affecting the stability of the finished product quality. It is crucial to avoid attributing complex, multi-factor problems excessively to a single technical defect. Summary of the Invention

[0005] The technical problem to be solved by this invention is that the existing technology lacks a full-process multi-parameter online monitoring and dynamic compensation mechanism for the production process of fair-faced concrete, especially the lack of online identification capability of the phase optical characteristics of powder materials, which leads to material abnormalities and fluctuations in the workability of concrete. The invention provides a fair-faced concrete mix proportion error prevention and early warning system based on multi-source data fusion verification.

[0006] To address the aforementioned issues, this invention provides a fair-faced concrete mix design error prevention and early warning system based on multi-source data fusion verification, comprising: a multi-source data fusion verification controller, a static metering module, a phase spectroscopy module, a dielectric and temperature rise monitoring module, a rheological monitoring module, a discharge gate actuator, an admixture-assisted precision metering pump group, and an acoustic-dielectric combined directional injection component;

[0007] The multi-source data fusion verification controller establishes physical and electrical connections and communication synchronization with the static metering module, phase spectroscopy module, dielectric and temperature rise monitoring module, rheological monitoring module, as well as the unloading gate actuator, admixture auxiliary precision metering pump group, and acoustic-dielectric combined directional injection assembly.

[0008] The static metering module is used to collect the cumulative mass data of the base material; the phase spectroscopy module is used to continuously acquire the reflectance spectrum data of the material flow during the falling process of the powder material; the discharge gate actuator is used to respond to control commands and perform mechanical actions to lock or open the discharge valve.

[0009] The dielectric and temperature rise monitoring module is used to acquire the complex dielectric constant and temperature characteristic data of the mixture during the dry mixing and initial wet mixing stages; the rheology monitoring module is used to simultaneously measure the torque electrical waveform of the motor and the high-frequency acoustic wave penetration attenuation rate in the suspension.

[0010] The admixture-assisted precision metering pump unit receives compensation commands and injects liquid admixtures into the mixing host; the acoustic-dielectric combined directional injection component applies an ultrasonic energy field and feeds back local transient dielectric signals.

[0011] The multi-source data fusion verification controller is used to perform feeding error prevention interception based on reflectance spectral data, and after feeding error prevention release, it performs moisture characteristic verification and rheological state dynamic correction based on complex dielectric constant, temperature characteristic data, torque electrical waveform and high-frequency acoustic wave penetration attenuation rate.

[0012] Furthermore, the static metering module includes a strain gauge weighing sensor array, a transmitter amplifier, and an analog-to-digital converter unit; the multi-source data fusion verification controller sends a global clock synchronization pulse through the industrial control bus to control the static metering module to perform hardware-level timestamp marking on the multi-channel digital weighing baseband signal output by the analog-to-digital converter unit; the multi-source data fusion verification controller converts the multi-channel digital weighing baseband signal into physical mass data of the basic material and constructs a static proportion mass matrix, and the physical mass data in the static proportion mass matrix is ​​aligned with the spectral data sequence synchronously acquired by the phase spectral module on the time axis.

[0013] Furthermore, the phase spectroscopy module initiates a scanning program when the powder material flows through the feeding buffer section of the feeding chute. It converts the diffuse reflection light signal into an analog electrical signal through an internal photodetector and uses a built-in analog-to-digital converter to discretize and sample the analog electrical signal, generating an original spectral reflectance sequence that is transmitted to the multi-source data fusion verification controller. The multi-source data fusion verification controller converts the original spectral reflectance sequence into an original absorbance distribution sequence, uses a standard normal variable transformation algorithm to perform scattering correction on the original absorbance distribution sequence to generate a corrected absorbance sequence, and extracts the corrected absorbance values ​​corresponding to the pre-stored characteristic wavelength table in the system database from the corrected absorbance sequence. These values ​​are then combined in ascending order of wavelength to construct a real-time phase feature vector.

[0014] Furthermore, the multi-source data fusion verification controller calculates the cosine similarity of the angle between the real-time phase feature vector and the reference vector of the phase of the special powder for fair-faced concrete. If the cosine similarity is less than the system safety judgment threshold, the multi-source data fusion verification controller determines that the current powder material properties do not meet the reference requirements, generates a hardware interrupt level signal to the unloading gate actuator, disconnects the power supply to the control circuit of the unloading gate actuator, and causes the mechanical valve of the unloading gate actuator to perform a reset and lock action to block the falling path of the powder material. At the same time, the current production status is marked as abnormal and the production control process is terminated. If the cosine similarity is greater than or equal to the system safety judgment threshold, the multi-source data fusion verification controller outputs an opening signal to the unloading gate actuator to maintain the open state of the mechanical valve, allowing the material to enter the mixing host, and starts the downstream judgment parameter dynamic generation program.

[0015] Furthermore, the multi-source data fusion verification controller performs a difference operation on the absorbance at corresponding wavelengths between the real-time phase feature vector and the phase reference vector of the special powder for fair-faced concrete, constructing a phase absorbance deviation vector. The controller then retrieves the upper limit of the reference dielectric constant and the phase-dielectric coupling conversion coefficient matrix stored internally. It adds the upper limit of the reference dielectric constant to the sum of the products of the conversion coefficients corresponding to the wavelengths of each characteristic absorption peak in the phase-dielectric coupling conversion coefficient matrix and the absorbance deviation values ​​at the corresponding wavelengths in the phase absorbance deviation vector, dynamically generating a dynamic target dielectric upper limit value and writing it into the internal register. This serves as a dynamic benchmark boundary for verifying the free water content during the dry mixing and initial wet mixing stages. Simultaneously, the multi-source data fusion verification controller retrieves a rheological benchmark vector containing the root mean square value of the benchmark torque and the benchmark ultrasonic attenuation coefficient under standard conditions, as well as a phase-rheological coupling conversion coefficient matrix. The rheological benchmark vector is then multiplied by the product matrix of the transpose of the phase-rheological coupling conversion coefficient matrix and the phase absorbance deviation vector. This matrix is ​​used to dynamically generate a target rheological vector containing the target root mean square value of the torque and the target ultrasonic attenuation coefficient, which is stored in the control memory. This serves as the numerical boundary basis for judging the rheological state of the material and triggering online dynamic compensation of the admixture during the final mixing stage.

[0016] Furthermore, the dielectric constant and temperature rise monitoring module collects the complex dielectric constant and temperature characteristic data of the mixture and packages them into a real-time dielectric constant and temperature rise vector, which is then transmitted to the multi-source data fusion verification controller. The multi-source data fusion verification controller parses the real-time dielectric constant and temperature rise vector and extracts the real part, imaginary part, and initial hydration temperature rise value of the complex dielectric constant. The multi-source data fusion verification controller uses the imaginary part and initial hydration temperature rise value to perform a multivariate regression coupling compensation calculation on the real part of the complex dielectric constant to compensate for the physical drift interference caused by temperature rise and ion concentration changes, generating a temperature-compensated real dielectric constant. The specific multivariate regression coupling compensation calculation process is as follows: multiply the real part of the complex dielectric constant by the empirical compensation coefficient a, add the initial hydration temperature rise value multiplied by the empirical compensation coefficient b, and add the imaginary part of the complex dielectric constant multiplied by... The real part of the temperature-compensated dielectric is obtained by adding the empirical compensation coefficient c to the empirical compensation coefficient d. The multi-source data fusion verification controller calculates the absolute deviation between the real part of the temperature-compensated dielectric and the upper limit of the dynamic target dielectric as the absolute value of the dielectric deviation, and compares the absolute value of the dielectric deviation with the system's preset allowable dielectric error limit. If the absolute value of the dielectric deviation is greater than the allowable dielectric error limit, the multi-source data fusion verification controller determines that the moisture carried in the aggregate exceeds the set ratio or that the water scale measurement is deviated, and outputs an abnormal free water content warning signal. If the absolute value of the dielectric deviation is less than or equal to the allowable dielectric error limit, the multi-source data fusion verification controller determines that the amount of free water in the current mixture meets the requirements of fair-faced concrete mix proportion, maintains the mixing action of the mixing host, and controls the production process to enter the final mixing stage.

[0017] Furthermore, the rheological monitoring module collects the root mean square value of the torque of the main drive motor circuit of the mixer, and collects the high-frequency acoustic wave penetration attenuation coefficient in the suspension at low-speed mixing or pause of the mixer's main shaft. This data is used to construct a real-time rheological vector, which is then transmitted to the multi-source data fusion verification controller. The multi-source data fusion verification controller calculates the Euclidean distance between the real-time rheological vector and the target rheological vector to obtain the vector norm distance, and compares this vector norm distance with the system's preset rheological tolerance limit. If the vector norm distance is less than or equal to the rheological tolerance limit, the multi-source data fusion verification controller... The device determines that the rheological state of the mixture is qualified and sends an opening command to the discharge gate actuator to execute the discharge. If the vector norm distance is greater than the rheological tolerance limit, the multi-source data fusion verification controller will subtract the target rheological vector from the real-time rheological vector to calculate the rheological compensation deviation vector, and retrieve the rheological-volume compensation transformation matrix obtained in advance based on the specific fair-faced concrete mix proportion data. The rheological-volume compensation transformation matrix and the transpose matrix of the rheological compensation deviation vector are used to perform matrix operation to obtain the admixture volume supplementation amount, and the injection command is output to the admixture auxiliary precision metering pump set.

[0018] Furthermore, the admixture-assisted precision metering pump unit activates the pumping component to inject admixture into the mixing host at a volume equal to the admixture volume replenishment. Simultaneously, the multi-source data fusion verification controller controls the high-frequency ultrasonic transmitter inside the acoustic-dielectric combined directional injection assembly to perform ultrasonic-assisted dispersion in the area in front of the injection port to promote the mixing reaction between the admixture and powder particles. The multi-source data fusion verification controller collects the transient local dielectric constant of the area in front of the injection port through the near-field dielectric probe inside the acoustic-dielectric combined directional injection assembly and calculates the derivative of the transient local dielectric constant with respect to time. To obtain the local dielectric abrupt change gradient, the multi-source data fusion verification controller compares the local dielectric abrupt change gradient with the system's preset gradient threshold. When the local dielectric abrupt change gradient reaches or exceeds the gradient threshold, or when the amount of admixture injected reaches the admixture volume replenishment amount, the multi-source data fusion verification controller sends a stop command to the admixture-assisted precision metering pump group and the acoustic-dielectric combined directional injection component to terminate the liquid injection and high-frequency ultrasonic emission actions. After the online compensation action is completed, it sends an opening command to the unloading gate actuator to execute the discharge, thus completing the proportioning error prevention and dynamic performance correction.

[0019] The present invention, by adopting the above technical solution, can bring the following beneficial effects:

[0020] 1. This invention acquires material flow reflection spectrum data by installing a phase spectroscopy module in the powder feeding chute to construct a real-time phase feature vector. The real-time phase feature vector is then compared with the pre-stored phase reference vector for fair-faced concrete powder to obtain the cosine similarity of the included angle. When the cosine similarity of the included angle is less than the system's safety judgment threshold, a hardware interrupt signal is output to control the locking of the unloading gate actuator. This achieves the effect of preventing feeding errors by physically intercepting and blocking abnormal powder materials in the early stage of production.

[0021] 2. This invention utilizes a dielectric and temperature rise monitoring module to acquire the complex dielectric constant and temperature characteristic data of the mixture. It uses the imaginary part of the complex dielectric constant and the initial hydration temperature rise value to perform coupling compensation calculation on the real part of the complex dielectric constant corresponding to the free water content to generate a temperature-compensated dielectric real part. It then compares and judges the deviation with the dynamically generated dynamic target dielectric upper limit value of the absorbance deviation vector of the bound phase. This achieves the effect of compensating for the interference of physical drift of ion concentration and hydration temperature rise of the mixture, and providing abnormal moisture warning for abnormal water content or weighing deviation of aggregates entering the mixing host.

[0022] 3. This invention uses a rheological monitoring module to collect the root mean square value of the torque of the main drive motor circuit and the high-frequency acoustic wave penetration attenuation coefficient of the suspension to construct a real-time rheological vector. It calculates the rheological compensation deviation vector between the vector and the target rheological vector dynamically generated by the system, and combines the rheological compensation deviation vector with the compensation transformation matrix to convert it into the admixture volume replenishment amount to drive the matching pump set and spraying assembly. This achieves the control effect of online dynamic admixture compensation and dynamic correction of rheological state for concrete workability deviation at the final mixing state. Attached Figure Description

[0023] Figure 1 This is a hardware architecture topology diagram of the fair-faced concrete mix proportion error prevention and early warning system based on multi-source data fusion verification according to the present invention.

[0024] Figure 2 This is a flowchart illustrating the overall workflow of the error prevention, early warning, and dynamic compensation mechanisms of this invention.

[0025] Figure 3 This is a flowchart of the dynamic phase spectrum acquisition and feeding error prevention and interception control process of the present invention;

[0026] Figure 4 This is a flowchart of the dielectric-temperature rise coupled moisture verification and additive quantitative compensation process of the present invention. Detailed Implementation

[0027] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0028] Please refer to the appendix. Figure 1-4 This invention provides a fair-faced concrete mix design error prevention and early warning system based on multi-source data fusion verification, comprising: a multi-source data fusion verification controller 100, a static metering module 200, a phase spectroscopy module 300, a dielectric and temperature rise monitoring module 400, a rheological monitoring module 500, a discharge gate actuator 600, an admixture-assisted precision metering pump group 700, and an acoustic-dielectric combined directional injection assembly 800;

[0029] The multi-source data fusion verification controller 100 establishes physical and electrical connections and communication synchronization with the static metering module 200, the phase spectroscopy module 300, the dielectric and temperature rise monitoring module 400, the rheology monitoring module 500, and the actuator, respectively.

[0030] The static metering module 200 is installed at the bottom of the cement silo, mineral admixture silo, aggregate silo, and liquid storage tank. The static metering module 200 uses strain gauge weighing sensors to collect cumulative mass data of the basic materials during the production process. The multi-source data fusion verification controller 100 receives the mass data signals sent by the static metering module 200 and generates a static proportioning mass record matrix. ;

[0031] A phase spectroscopy module 300 is embedded in the inner wall of the powder feeding chute. The phase spectroscopy module 300 includes a near-infrared spectral sensor and a UV-Vis diffuse reflectance spectral sensor. The phase spectroscopy module 300 is used to continuously acquire the reflectance spectral data of the powder flow during its descent. A multi-source data fusion and verification controller 100 receives the spectral data sequence from the phase spectroscopy module 300 in real time, extracts the absorbance at characteristic wavelengths, and constructs a phase feature vector. :

[0032]

[0033] In the formula, Indicates the first Characteristic wavelengths Instantaneous absorbance at the point, The total number of characteristic absorption peaks;

[0034] The dielectric constant and temperature rise monitoring module 400 is arrayed in the non-wear area of ​​the inner cavity sidewall of the mixing host. The module integrates a high-frequency microwave dielectric constant probe and a thermocouple element. It is used to acquire the complex dielectric constant and temperature characteristic data of the mixture during the dry mixing and initial wet mixing stages, and packages this data into a dielectric constant and temperature rise vector. Feedback to the multi-source data fusion verification controller 100:

[0035]

[0036] In the formula, Let be the real part of the complex permittivity of the mixture. Let imaginary part be the complex permittivity of the mixture. This represents the initial hydration temperature rise.

[0037] The rheological monitoring module 500 consists of a main drive current acquisition circuit and an ultrasonic monitoring component. The main drive current acquisition circuit is connected to the inverter terminal of the main motor of the mixing host, and the ultrasonic monitoring component is fixed to the outer side wall of the mixing host. The rheological monitoring module 500 synchronously measures the electrical waveform of the motor's torque and the high-frequency acoustic wave penetration attenuation rate in the suspension to construct a rheological vector. And send it to the multi-source data fusion verification controller 100:

[0038]

[0039] In the formula, This represents the root mean square value of the torque fluctuation of the stirring motor. The penetration attenuation coefficient of high-frequency ultrasound in the mixture;

[0040] The unloading gate actuator 600 is located at the material discharge end of the storage bin. The multi-source data fusion verification controller 100 transmits the control commands output by internal calculation to the unloading gate actuator 600. The unloading gate actuator 600 responds to the control commands and performs mechanical actions to lock or open the discharge valve.

[0041] The admixture-assisted precision metering pump assembly 700 works in conjunction with the acoustic-dielectric combined directional injection assembly 800. The acoustic-dielectric combined directional injection assembly 800 is located at the injection port on the side wall of the mixing host. The acoustic-dielectric combined directional injection assembly 800 integrates a high-frequency ultrasonic transmitter and a near-field dielectric probe. The admixture-assisted precision metering pump assembly 700 receives compensation commands from the multi-source data fusion verification controller 100 and injects a set volume of liquid admixture into the mixing host. At the same time, the acoustic-dielectric combined directional injection assembly 800 applies an ultrasonic energy field and feeds back a local transient dielectric signal to the multi-source data fusion verification controller 100.

[0042] Furthermore, based on the above system, the present invention also provides an overall workflow for a method for error prevention and early warning of fair-faced concrete mix proportions based on multi-source data fusion verification, including the following steps:

[0043] In step S100, the multi-source data fusion verification controller 100 receives the production instruction and sends a control signal to the unloading gate actuator 600 to start the unloading program. The static metering module 200 and the phase spectroscopy module 300 operate synchronously and collect data. The multi-source data fusion verification controller 100 extracts the spectral data fed back by the phase spectroscopy module 300 and constructs a real-time phase feature vector. ;

[0044] Step S200: The multi-source data fusion verification controller 100 calculates the real-time phase feature vector. With the system's built-in phase reference vector for fair-faced concrete powder Cosine similarity of the included angle The multi-source data fusion verification controller 100 determines the cosine similarity of the included angle. Is it greater than or equal to the system security judgment threshold? ;

[0045] If the cosine similarity of the included angle Less than the system security threshold The multi-source data fusion verification controller 100 outputs a hardware interrupt signal to the unloading gate actuator 600. The unloading gate actuator 600 responds to the hardware interrupt signal, performs the action of locking the unloading gate, and terminates the production process.

[0046] Step S300: If the cosine similarity of the included angle... Greater than or equal to the system security judgment threshold The multi-source data fusion verification controller 100 controls the discharge gate actuator 600 to remain open, allowing materials to enter the mixing host. The multi-source data fusion verification controller 100 initiates the downstream judgment matrix dynamic generation program to extract real-time phase feature vectors. Reference vector of phase of special powder for fair-faced concrete Phase absorbance deviation vector The calculation formula is:

[0047] The multi-source data fusion verification controller 100 uses the phase absorbance deviation vector... Combined with the system's preset phase-dielectric coupling conversion coefficient matrix and the upper limit of the reference dielectric constant Generate dynamic target dielectric upper limit value The calculation formula is:

[0048] Meanwhile, the multi-source data fusion verification controller 100 combines the phase absorbance deviation vector The system pre-establishes a 2×n-dimensional empirical coupling conversion coefficient matrix of phase-rheology based on historical mix proportion data. and rheological reference vector Generate target rheotropic vector The calculation formula is:

[0049] In step S400, the material enters the dry mixing and initial wet mixing stage. The dielectric and temperature rise monitoring module 400 sends real-time dielectric and temperature rise vectors to the multi-source data fusion verification controller 100. The multi-source data fusion verification controller 100 extracts real-time dielectric and temperature rise vectors. The dielectric real part And calculate the real part of the dielectric. With dynamic target dielectric upper limit value The absolute deviation;

[0050] If the absolute deviation is greater than the permissible dielectric error limit The multi-source data fusion verification controller 100 outputs an abnormal free water content warning signal. If the absolute deviation is less than or equal to the allowable dielectric error limit... The process enters the final stage of stirring;

[0051] In step S500, the rheological monitoring module 500 sends a real-time rheological vector to the multi-source data fusion verification controller 100. The multi-source data fusion verification controller 100 calculates real-time rheological vectors. With the target rheodynamic vector vector norm distance The calculation formula is:

[0052] Multi-source data fusion verification controller 100 determines vector norm distance Is it less than or equal to the rheological tolerance limit? ;

[0053] If the vector norm distance Less than or equal to the rheological tolerance limit The multi-source data fusion verification controller 100 sends an opening command to the unloading gate actuator 600. If the vector norm distance... Greater than the rheological tolerance limit The multi-source data fusion verification controller 100 calculates the rheological compensation deviation vector. The calculation formula is:

[0054] The multi-source data fusion verification controller 100 combines the system's preset rheological-volume compensation conversion matrix. The rheological compensation deviation vector Converted to admixture volume supplement The calculation formula is:

[0055] The multi-source data fusion verification controller 100 outputs compensation commands to the admixture-assisted precision metering pump set 700;

[0056] The admixture-assisted precision metering pump unit 700 works in conjunction with the acoustic-dielectric combined directional injection assembly 800 to inject the admixture into the mixing unit at a volume equal to the admixture volume replenishment amount. After the injection action is completed, the multi-source data fusion verification controller 100 sends an opening command to the unloading gate actuator 600 to execute the discharge.

[0057] To further explain in detail the various control nodes in the above macro workflow and ensure the full disclosure of the control logic, the specific implementation details of each module are elaborated below.

[0058] The multi-source data fusion verification controller 100 and the static metering module 200 establish a bidirectional data communication connection through the industrial control bus. The static metering module 200 includes a strain gauge weighing sensor array, a transmitter amplifier, and an analog-to-digital conversion unit. The strain gauge weighing sensor array is connected to the steel structure support frame at the bottom of the cement silo, mineral admixture silo, aggregate silo, and liquid storage tank.

[0059] In the material weighing and unloading stage of step S100, the hardware configuration and data synchronization of the static gravity metering unit are implemented through the following steps:

[0060] Step S110: The multi-source data fusion verification controller 100 outputs control commands and starts the feeding program. The gravity of the basic material is applied to the strain gauge weighing sensor array. The strain gauge weighing sensor array outputs an analog voltage signal. The analog voltage signal is input to the transmitter amplifier for low-pass filtering and amplification. The analog voltage signal is converted into a digital weighing baseband signal by the analog-to-digital converter unit.

[0061] Step S120: The multi-source data fusion verification controller 100 sends a global clock synchronization pulse to the static metering module 200 through the industrial control bus. The static metering module 200 receives the global clock synchronization pulse and performs hardware-level timestamp marking on the multi-channel digital weighing baseband signal output by the analog-to-digital conversion unit. The multi-channel digital weighing baseband signal with unified timestamp marking is transmitted to the multi-source data fusion verification controller 100.

[0062] Step S130: The multi-source data fusion verification controller 100 parses the multi-channel digital weighing baseband signal with a unified timestamp, extracts the digital weighing baseband signal of each channel under the same clock cycle, and converts the digital weighing baseband signal of each channel into the physical mass data of each basic material. The calculation formula is as follows:

[0063]

[0064] In the formula, This refers to the physical quality data of a single type of basic material. The corresponding channel digital weighing baseband signal value. For the pre-calibrated load cell calibration coefficients, The empty tare weight of the storage silo;

[0065] Step S140: The multi-source data fusion verification controller 100 constructs a static proportioning quality matrix based on the physical quality data of each basic material. Static proportion mass matrix The calculation expression is:

[0066]

[0067] In the formula, The cumulative mass of cement at the same time point. For the cumulative mass of mineral admixtures, For aggregate accumulation quality, For the cumulative quality of production water, The cumulative mass of the admixture;

[0068] Step S150: The multi-source data fusion verification controller 100 will convert the static proportioning quality matrix... Write to internal registers, static proportion mass matrix The physical quality data and the spectral data sequence synchronously acquired by the phase spectral module 300 are aligned on the time axis, providing the physical quality input of the basic material for the free water verification and rheological compensation process;

[0069] Simultaneously with the start of the feeding procedure in step S100, the phase spectroscopy module 300 performs real-time scanning of the feeding stream, regarding dynamic phase spectral acquisition and feature vector analysis. The specific construction plan includes the following steps:

[0070] In step S160, when the powder material flows through the feeding buffer section of the feeding chute, the phase spectral module 300 starts the scanning program. The phase spectral module 300 emits a continuous spectrum to the powder material according to the set sampling frequency and receives the diffuse reflection light signal of the powder material. The photodetector inside the phase spectral module 300 converts the diffuse reflection light signal into an analog electrical signal. The analog-to-digital converter built into the phase spectral module 300 discretizes the analog electrical signal to generate the original spectral reflectance sequence and transmits the original spectral reflectance sequence to the multi-source data fusion verification controller 100.

[0071] Step S170: The multi-source data fusion verification controller 100 receives the original spectral reflectance sequence and converts it into an original absorbance distribution sequence. The calculation formula is as follows:

[0072]

[0073] In the formula, For the first A discrete wavelength point, For discrete wavelength points The original absorbance at that location, For discrete wavelength points The corresponding original spectral reflectance;

[0074] Step S180: To eliminate light scattering interference caused by particle size differences and bulk density fluctuations during the falling of powder materials, the multi-source data fusion verification controller 100 uses a standard normal variable transformation algorithm to perform scattering correction on the original absorbance distribution sequence. The multi-source data fusion verification controller 100 calculates the mean and standard deviation of the original absorbance across the entire wavelength range. The formula for calculating the mean is:

[0075]

[0076] The formula for calculating standard deviation is:

[0077]

[0078] In the formula, This represents the average original absorbance across the entire wavelength range. The standard deviation of the original absorbance across the entire wavelength range. This represents the total number of effective discrete wavelength points in the spectral scan.

[0079] Step S190: The multi-source data fusion verification controller 100 verifies the average absorbance across the entire wavelength band. Standard deviation of original absorbance across the entire wavelength range The original absorbance distribution sequence is standardized to generate a corrected absorbance sequence, calculated using the following formula:

[0080]

[0081] In the formula, For discrete wavelength points Corrected absorbance at the location;

[0082] Step S1100: The multi-source data fusion verification controller 100 retrieves the pre-stored characteristic wavelength table of fair-faced concrete from the system database. The multi-source data fusion verification controller 100 extracts the corrected absorbance values ​​corresponding to the characteristic wavelength table from the corrected absorbance sequence. The multi-source data fusion verification controller 100 combines the extracted corrected absorbance values ​​in ascending order of wavelength to construct a real-time phase feature vector. Real-time phase feature vector The expanded expression is:

[0083]

[0084] In the formula, The total number of characteristic absorption peak wavelengths preset for the system. For the first The wavelength of each characteristic absorption peak The characteristic absorption peak wavelength The corresponding corrected absorbance, the multi-source data fusion verification controller 100 will generate the real-time phase feature vector Write to the internal storage area.

[0085] After obtaining the above real-time phase feature vector Subsequently, corresponding to step S200 of the overall process, the system executes specific feeding error prevention and interception boundary condition verification and control instructions:

[0086] Step S210: The multi-source data fusion verification controller 100 retrieves the real-time phase feature vector from its internal storage area. And the system's pre-stored phase reference vector for fair-faced concrete special powder materials. Reference vector of phase composition for special powder for fair-faced concrete The expanded expression is:

[0087]

[0088] In the formula, The characteristic absorption peak wavelength of fair-faced concrete The corresponding standard absorbance is used to calculate the real-time phase feature vector by the multi-source data fusion verification controller 100. Reference vector of phase of special powder for fair-faced concrete Cosine similarity of the included angle The calculation formula is:

[0089]

[0090] In the formula, Real-time phase feature vector Reference vector of phase of special powder for fair-faced concrete The inner product, Real-time phase feature vector The 2-norm, Reference vector of phase composition for powder materials used in fair-faced concrete The second norm;

[0091] Step S220: The multi-source data fusion verification controller 100 reads the preset system security judgment threshold. The multi-source data fusion verification controller 100 will use the cosine similarity of the included angle. With system security judgment threshold Perform numerical comparison;

[0092] Step S230: If the cosine similarity of the included angle Less than the system security threshold The multi-source data fusion verification controller 100 determines that the current powder material properties do not meet the benchmark requirements. The multi-source data fusion verification controller 100 generates a hardware interrupt level signal and sends the hardware interrupt level signal to the unloading gate actuator 600.

[0093] Step S240: The unloading gate actuator 600 receives a hardware interrupt level signal, disconnects the power supply to the control circuit, and the mechanical valve of the unloading gate actuator 600 performs a reset and locking action to block the falling path of the powder material. Simultaneously, the multi-source data fusion verification controller 100 marks the current production status as abnormal and terminates the production control process.

[0094] Step S250: If the cosine similarity of the included angle... Greater than or equal to the system security judgment threshold The multi-source data fusion verification controller 100 determines that the current powder material properties meet the benchmark requirements. The multi-source data fusion verification controller 100 outputs an opening signal to the unloading gate actuator 600. The unloading gate actuator 600 maintains the mechanical valve in the open state. The multi-source data fusion verification controller 100 starts the downstream judgment matrix dynamic generation program.

[0095] After the material feeding and error-proofing release in step S250, corresponding to step S300 in the overall process, the dynamic generation mathematical model of the downstream decision matrix is ​​implemented according to the following steps:

[0096] In step S310, after performing the feeding error prevention interception and release operation, the multi-source data fusion verification controller 100 starts the downstream judgment matrix dynamic generation program, and the multi-source data fusion verification controller 100 generates the real-time phase feature vector. Reference vector of phase of special powder for fair-faced concrete Perform absorbance difference calculations at corresponding wavelengths to construct a phase absorbance deviation vector. Phase absorbance deviation vector The element expansion expression is:

[0097]

[0098] In the formula, The total number of characteristic absorption peak wavelengths. For the first Wavelength of each characteristic absorption peak The absorbance deviation value at that location. The calculation formula is:

[0099]

[0100] In the formula, Real-time phase feature vector Real-time absorbance correction in the process. Reference vector of phase composition for powder materials used in fair-faced concrete Standard absorbance in;

[0101] Step S320: The multi-source data fusion verification controller 100 retrieves the upper limit value of the reference dielectric constant stored internally in the system. and the phase-dielectric coupling conversion coefficient matrix Phase-dielectric coupling conversion coefficient matrix The multi-source data fusion verification controller 100, using a one-dimensional row matrix structure, calculates the dynamic target dielectric upper limit value based on the absorbance deviation. The matrix calculation formula is:

[0102]

[0103] In the formula, for The phase-dielectric empirical coupling conversion coefficient matrix of the dimensionality. The transpose of the phase absorbance deviation vector is used by the multi-source data fusion verification controller 100 to dynamically determine the upper limit of the target dielectric. Write it into the internal register as a dynamic reference boundary for verifying the free water content during the dry mixing and initial wet mixing stages;

[0104] Step S330: The multi-source data fusion verification controller 100 retrieves the rheological reference vector stored internally in the system. and the phase-rheology coupling conversion coefficient matrix Rheological reference vector Includes the root mean square value of the reference torque under standard conditions. Compared with the reference ultrasonic attenuation coefficient Phase-rheology empirical coupling conversion coefficient matrix Two rows pre-built based on historical production data The two-dimensional matrix of columns, the multi-source data fusion verification controller 100 calculates the target rheological vector. The formula for matrix expansion is:

[0105]

[0106] In the formula, The target torque root mean square value, The target ultrasonic attenuation coefficient, For the first The wavelengths of the characteristic absorption peaks correspond to the torque mapping conversion coefficients. For the first The wavelength of each characteristic absorption peak corresponds to the mapping conversion coefficient of the ultrasonic attenuation coefficient;

[0107] Step S340: The multi-source data fusion verification controller 100 calculates the generated target rheological vector. Store the target rheotropic vector in control memory. The numerical boundary criteria for determining the rheological state of materials and triggering online dynamic compensation of admixtures at the final stage of mixing are established. The multi-source data fusion verification controller 100, through the aforementioned matrix operation logic, converts the input real-time phase feature vector... The numerical fluctuations are converted into the control boundary parameters of the mixing host.

[0108] When the material has completely fallen into the mixing host and water is added for mixing, the control process enters the dry mixing and initial wet mixing stage corresponding to step S400. At this time, the moisture characteristic verification mechanism under the dielectric-temperature rise coupling state is implemented through the following steps:

[0109] In step S410, the multi-source data fusion verification controller 100 sends an opening command to the unloading gate actuator 600, allowing the base material to enter the mixing host. The mixture enters the dry mixing and initial wet mixing stage. The dielectric and temperature rise monitoring module 400 starts the data acquisition program, collecting the complex dielectric constant and temperature characteristic data of the mixture, and packaging the complex dielectric constant and temperature characteristic data into a real-time dielectric and temperature rise vector. Transmitted to the multi-source data fusion verification controller 100;

[0110] Step S420: The multi-source data fusion verification controller 100 receives and parses the real-time dielectric and temperature rise vectors. Extract real-time dielectric and temperature rise vectors The real part of the complex permittivity Imaginary part of complex permittivity and initial hydration temperature rise Real part of complex permittivity The imaginary part of the complex permittivity corresponds to the free water content in the mixture. The corresponding ionic conductivity loss of the mixture and the initial hydration temperature rise. The initial heat release corresponding to the cement hydration reaction;

[0111] Step S430: Due to the physical drift of the dielectric constant of the mixture caused by temperature rise and ion concentration changes, the multi-source data fusion verification controller 100 utilizes the imaginary part of the complex dielectric constant. Compared with the initial hydration temperature rise For the real part of the complex permittivity Perform multivariate regression coupling compensation calculations to generate the temperature-compensated dielectric real part. The calculation formula is:

[0112]

[0113] In the formula, For temperature-compensated dielectric real part, , , , These are empirical compensation coefficients obtained in advance based on historical production data of specific fair-faced concrete mix proportions through regression calibration. They are used to quantify the linear mapping relationship between each parameter. This is a calibration model based on multiple regression, where the dependent variable is the real part of the standard state dielectric calibrated in the laboratory, and the independent variable is the field measurement value.

[0114] Step S440: The multi-source data fusion verification controller 100 retrieves the dynamic target dielectric upper limit value stored in its internal register. And calculate the temperature-compensated real part of the dielectric. With dynamic target dielectric upper limit value absolute value of dielectric deviation The calculation formula is:

[0115]

[0116] In the formula, The absolute value of the dielectric deviation is read by the multi-source data fusion verification controller 100, which reads the system's preset allowable dielectric error limit. and the absolute value of dielectric deviation With permissible dielectric tolerance Perform numerical comparison;

[0117] Step S450: If the absolute value of the dielectric deviation Greater than the permissible dielectric error limit The multi-source data fusion verification controller 100 determines that the moisture content of the aggregate exceeds the set ratio or that the water scale measurement is deviated, and outputs an abnormal free water content warning signal.

[0118] Step S460: If the absolute value of the dielectric deviation Less than or equal to the permissible dielectric tolerance limit The multi-source data fusion verification controller 100 determines that the amount of free water in the current mixture meets the requirements of fair-faced concrete mix proportion, maintains the mixing action of the mixing host, and controls the production process to enter the final mixing stage.

[0119] After the water addition test is normal and the process enters the final stirring state, corresponding to step S500 in the macroscopic process, the specific execution process of the dynamic rheological state determination and admixture targeted compensation implementation scheme is as follows:

[0120] Step S510: When the production process enters the final stage of stirring, the rheological monitoring module 500 collects the root mean square value of the torque of the main drive motor circuit, and collects the high-frequency sound wave penetration attenuation coefficient in the suspension at the moment when the main shaft of the stirring host is stirring at low speed or paused. The rheological monitoring module 500 constructs a real-time rheological vector. and real-time rheovector Transmitted to the multi-source data fusion verification controller 100, real-time rheovector The expression is:

[0121]

[0122] In the formula, The root mean square value of the torque in the main drive motor circuit. is the high-frequency acoustic wave penetration attenuation coefficient in the suspension;

[0123] Step S520: The multi-source data fusion verification controller 100 retrieves the target rheological vector from its internal register. Calculate real-time rheological vectors With the target rheodynamic vector vector norm distance ,

[0124]

[0125] Multi-source data fusion verification controller 100 reads rheological tolerance limit and vector norm distance With rheological tolerance limit Perform numerical comparison;

[0126] Step S530, if the vector norm distance Less than or equal to the rheological tolerance limit The multi-source data fusion verification controller 100 determines that the rheological state of the mixture is qualified, and sends an opening command to the unloading gate actuator 600.

[0127] Step S540: If the vector norm distance Greater than the rheological tolerance limit The multi-source data fusion verification controller 100 calculates real-time rheological vectors. With the target rheodynamic vector Rheological compensation deviation vector The calculation formula is:

[0128]

[0129] The multi-source data fusion verification controller 100 combines the system's preset rheological-volume compensation conversion matrix. Calculate the volumetric amount of admixture to be added. The calculation formula is:

[0130]

[0131] In the formula, This is a 1×2 dimensional rheological-volume compensation transformation matrix, which was calibrated based on specific fair-faced concrete mix proportion data. This refers to the volumetric amount of the admixture added.

[0132] The multi-source data fusion and verification controller 100 outputs a liquid injection command to the admixture-assisted precision metering pump set 700;

[0133] Step S550: The admixture-assisted precision metering pump unit 700 receives the injection command and starts the pumping component to inject the volume of the admixture into the mixing host, which is the volume of the admixture to be added. Simultaneously, the multi-source data fusion verification controller 100 outputs a start command to the acoustic-dielectric combined directional injection assembly 800. The high-frequency ultrasonic transmitter inside the acoustic-dielectric combined directional injection assembly 800 performs ultrasonic-assisted dispersion in the area in front of the injection port to promote the mixing reaction of the additive and the powder particles.

[0134] Step S560: The near-field dielectric probe inside the acoustic-dielectric combined directional injection assembly 800 collects the transient local dielectric constant of the region in front of the injection port. The acoustic-dielectric combined directional injection assembly 800 will change the transient local dielectric constant. The data is transmitted to the multi-source data fusion verification controller 100, which calculates the transient local dielectric constant. For time-dependent micro-commerce, obtain the local dielectric gradient of abrupt change. The calculation formula is:

[0135]

[0136] In the formula, For injection time, It is the transient local dielectric constant;

[0137] Step S570: The multi-source data fusion verification controller 100 will convert the local dielectric abrupt gradient... Compared with the system's preset gradient threshold Numerical comparison was performed to determine the local dielectric gradient. Reaching and exceeding the gradient threshold Or the amount of admixture injected reaches the admixture volume replenishment amount. At the same time, the multi-source data fusion verification controller 100 sends a stop command to the admixture-assisted precision metering pump group 700 and the acoustic-dielectric combined directional injection assembly 800;

[0138] In step S580, the admixture-assisted precision metering pump group 700 stops pumping and injecting liquid, the acoustic-dielectric combined directional injection component 800 stops high-frequency ultrasonic emission, and after the online compensation action is completed, the multi-source data fusion verification controller 100 sends an opening command to the unloading gate actuator 600. The unloading gate actuator 600 executes the action of opening the mechanical valve to complete the material discharge control.

Claims

1. A mix design error prevention and early warning system for fair-faced concrete based on multi-source data fusion verification, characterized in that, include: Multi-source data fusion verification controller (100), static metering module (200), phase spectroscopy module (300), dielectric and temperature rise monitoring module (400), rheological monitoring module (500), unloading gate actuator (600), admixture-assisted precision metering pump group (700), and acoustic-dielectric combined directional injection assembly (800). The multi-source data fusion verification controller (100) establishes physical and electrical connections and communication synchronization with the static metering module (200), phase spectroscopy module (300), dielectric and temperature rise monitoring module (400), rheological monitoring module (500), unloading gate actuator (600), admixture-assisted precision metering pump group (700), and acoustic-dielectric combined directional injection assembly (800), respectively. The static metering module (200) is used to collect the cumulative mass data of the base material; the phase spectroscopy module (300) is used to continuously acquire the reflectance spectrum data of the material flow during the falling process of the powder material; the unloading gate actuator (600) is used to respond to control commands and perform mechanical actions to lock or open the unloading valve. The dielectric and temperature rise monitoring module (400) is used to acquire the complex dielectric constant and temperature characteristic data of the mixture during the dry mixing and initial wet mixing stages; the rheology monitoring module (500) is used to simultaneously measure the torque electrical waveform of the motor and the high-frequency acoustic wave penetration attenuation rate in the suspension. The admixture-assisted precision metering pump group (700) receives compensation instructions to inject liquid admixture into the mixing host, and the acoustic-dielectric combined directional injection assembly (800) applies an ultrasonic energy field and feeds back a local transient dielectric signal; The multi-source data fusion verification controller (100) is used to perform feeding error prevention interception based on the reflection spectrum data, and after feeding error prevention release, to perform moisture characteristic verification and rheological state dynamic correction based on the complex dielectric constant, temperature characteristic data, torque electrical waveform and high-frequency acoustic wave penetration attenuation rate.

2. The fair-faced concrete mix design error prevention and early warning system based on multi-source data fusion verification according to claim 1, characterized in that, The static metering module (200) includes a strain gauge weighing sensor array, a transmitter amplifier, and an analog-to-digital converter unit; the multi-source data fusion verification controller (100) sends a global clock synchronization pulse through the industrial control bus to control the static metering module (200) to perform hardware-level timestamp marking on the multi-channel digital weighing baseband signal output by the analog-to-digital converter unit; the multi-source data fusion verification controller (100) converts the digital weighing baseband signal of each channel into physical mass data of each basic material and constructs a static proportion mass matrix, wherein the physical mass data in the static proportion mass matrix is ​​aligned with the spectral data sequence synchronously acquired by the phase spectral module (300) on the time axis.

3. The fair-faced concrete mix design error prevention and early warning system based on multi-source data fusion verification according to claim 1, characterized in that, The phase spectral module (300) initiates a scanning program when the powder material flows through the discharge buffer section of the discharge chute, generating an original spectral reflectance sequence and transmitting it to the multi-source data fusion verification controller (100). The multi-source data fusion verification controller (100) converts the original spectral reflectance sequence into an original absorbance distribution sequence, performs scattering correction on the original absorbance distribution sequence using a standard normal variable transformation algorithm to generate a corrected absorbance sequence, and extracts the corrected absorbance values ​​corresponding to the pre-stored characteristic wavelength table to construct a real-time phase feature vector. .

4. The fair-faced concrete mix design error prevention and early warning system based on multi-source data fusion verification according to claim 3, characterized in that, The multi-source data fusion verification controller (100) calculates the real-time phase feature vector. Reference vector of phase of special powder for fair-faced concrete Cosine similarity of the included angle ; If the cosine similarity of the included angle Less than the system security threshold A hardware interrupt level signal is sent to the unloading gate actuator (600) to perform a reset and locking action; if it is greater than or equal to the system safety judgment threshold... Initiate the downstream judgment matrix dynamic generation program to construct the phase absorbance deviation vector. And calculate the dynamic target dielectric upper limit value. The calculation formula is: In the formula, The upper limit of the reference dielectric constant, The system is pre-built based on historical production data 3D phase-dielectric empirical coupling conversion coefficient matrix, is the transpose of the phase absorbance deviation vector.

5. The fair-faced concrete mix design error prevention and early warning system based on multi-source data fusion verification according to claim 4, characterized in that, The multi-source data fusion verification controller (100) combines the phase absorbance deviation vector The system pre-establishes a 2×n-dimensional empirical coupling conversion coefficient matrix of phase-rheology based on historical mix proportion data. and rheological reference vector Dynamically generate target rheotropic vectors The target rheological vector This forms the numerical boundary basis for judging the rheological state of materials and triggering online dynamic compensation of admixtures during the final stage of mixing.

6. The fair-faced concrete mix design error prevention and early warning system based on multi-source data fusion verification according to claim 5, characterized in that, The dielectric and temperature rise monitoring module (400) packages the collected complex dielectric constant and temperature characteristic data into a real-time dielectric and temperature rise vector. The data is transmitted to the multi-source data fusion verification controller (100); the multi-source data fusion verification controller (100) extracts the real-time dielectric and temperature rise vector. The real part of the complex permittivity Imaginary part of complex permittivity and initial hydration temperature rise And utilizing the imaginary part of the complex permittivity Compared with the initial hydration temperature rise For the real part of the complex permittivity Perform multivariate regression coupling compensation calculations to generate the temperature-compensated dielectric real part. .

7. The fair-faced concrete mix design error prevention and early warning system based on multi-source data fusion verification according to claim 6, characterized in that, The real part of the temperature-compensated dielectric The calculation formula is: In the formula, , , , These are empirical compensation coefficients obtained in advance based on regression calibration of historical production data of specific fair-faced concrete mix proportions, used to quantify the linear mapping relationship between each parameter; The multi-source data fusion verification controller (100) calculates the real part of the temperature-compensated dielectric. With the aforementioned dynamic target dielectric upper limit value absolute value of dielectric deviation When the absolute value of the dielectric deviation Greater than the system's preset allowable dielectric error limit At that time, an early warning signal for abnormal free water content will be output.

8. The fair-faced concrete mix design error prevention and early warning system based on multi-source data fusion verification according to claim 7, characterized in that, The rheological monitoring module (500) collects the root mean square value of the torque of the main drive motor circuit when the production process enters the final stage of stirring, and collects the high-frequency sound wave penetration attenuation coefficient in the suspension at the moment when the main shaft of the stirring host is stirring at low speed or paused, thus constructing a real-time rheological vector. The multi-source data fusion verification controller (100) calculates the real-time rheological vector. With the target rheological vector vector norm distance and the vector norm distance With rheological tolerance limit Perform numerical comparison.

9. The fair-faced concrete mix design error prevention and early warning system based on multi-source data fusion verification according to claim 8, characterized in that, If the vector norm distance Greater than the rheological tolerance limit The multi-source data fusion verification controller (100) calculates the real-time rheological vector. With the target rheological vector Rheological compensation deviation vector Combined with calibration based on specific fair-faced concrete mix proportion data Dimensional rheological-volume compensation transformation matrix The rheological compensation deviation vector Converted to admixture volume supplement The additive-assisted precision metering pump unit (700) outputs an injection command.

10. The fair-faced concrete mix design error prevention and early warning system based on multi-source data fusion verification according to claim 9, characterized in that, The admixture-assisted precision metering pump unit (700) injects a volume equal to the admixture volume replenishment amount into the mixing host upon startup. The additive, the high-frequency ultrasonic transmitter inside the acoustic-dielectric combined directional injection assembly (800) performs ultrasonic-assisted dispersion in the area in front of the injection port; the multi-source data fusion verification controller (100) collects transient local dielectric constant through a near-field dielectric probe. And calculate the derivative with respect to time to obtain the local dielectric gradient. When the local dielectric abrupt gradient Reaching and exceeding the gradient threshold Or the amount of admixture injected reaches the admixture volume replenishment amount. When the stop command is sent, the unloading gate actuator (600) is controlled to perform the opening and unloading action.

Images