Gypsum quality monitoring method, system and equipment for carbide slag desulfurization and medium

Abstract

The invention discloses a gypsum quality monitoring method, system and equipment for carbide slag desulfurization and a medium, and aims to solve the problems that the prior art depends on off-line analysis and is poor in real-time performance and low in efficiency. Through online sampling, spectral analysis and turbidity detection technologies, gypsum component characteristics are analyzed in real time, slurry physical characteristics are quantified, and quality parameters are dynamically evaluated in combination with multivariable model fusion and an intelligent prediction algorithm; desulfurization process conditions are automatically adjusted based on a closed-loop control mechanism, gypsum purity, particle size distribution and impurity content are optimized, and continuous and stable quality is ensured; the equipment adopts a modular architecture and an embedded real-time operating system, supports synchronous acquisition and efficient processing of multi-source data, improves the monitoring efficiency and the data reliability, and realizes intelligent collaboration of the whole process; through dynamic feedback control and an intelligent cooperation mechanism, the manual intervention intensity is reduced, the service life of equipment is prolonged, and the economic value and environmental protection benefits of by-products are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of flue gas desulfurization, and in particular to a gypsum quality monitoring method, system, equipment and medium for carbide slag desulfurization. Background Art

[0002] Carbide slag, a byproduct of acetylene production, is rich in Ca(OH)2 and CaCO3, with annual emissions exceeding 10 million tons. Its high calcium content makes it an ideal alternative feedstock for wet flue gas desulfurization (FGD), significantly reducing desulfurization costs and enabling solid waste utilization. The quality of the gypsum (CaSO4·2H2O) produced during the desulfurization process directly impacts its economic value: high-purity gypsum can be used in high-value-added applications such as building materials, while low-purity gypsum, due to its poor performance, can only be landfilled, resulting in a significant value gap.

[0003] Currently, gypsum quality testing relies on offline methods such as X-ray diffraction and chemical titration, which take hours to complete and lack real-time performance. For example, when process parameter fluctuations cause purity to drop, offline testing can't provide timely warnings, resulting in wasted resources. Furthermore, gypsum's particle size distribution and impurity content are crucial to dehydration performance, but traditional technologies cannot simultaneously monitor multiple parameters.

[0004] Research has shown that parameters such as slurry pH and stirring speed significantly affect gypsum quality, but existing systems mostly operate with fixed parameters and lack dynamic control supported by real-time data. Although some studies have attempted to introduce online sensors, single-indicator monitoring is difficult to fully characterize quality, has weak anti-interference capabilities, and is difficult to adapt to complex industrial environments. Therefore, developing an efficient and accurate online monitoring system that can achieve real-time feedback and closed-loop control of gypsum purity, particle size, and impurities is a key requirement for improving the economic and environmental performance of desulfurization. Summary of the Invention

[0005] In view of the above problems in the prior art, the present invention is proposed.

[0006] Therefore, the technical problem to be solved by the present invention is: to propose an online monitoring method for the quality of by-product gypsum in the calcium carbide slag desulfurization system, which realizes real-time monitoring and optimization of gypsum purity, particle size distribution and impurity content through online sampling, spectral analysis, turbidity detection, data processing and prediction, and dynamic feedback control.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0008] In a first aspect, the present invention provides a method for monitoring the quality of gypsum in carbide slag desulfurization, comprising:

[0009] Take samples online, obtain samples and perform technical analysis to obtain analysis results;

[0010] Measuring the bulk slurry physical properties and evaluating the inversion based on a standard model to obtain a first estimate;

[0011] Combining discriminant analysis and intelligent model analysis and prediction, we get the second prediction;

[0012] Through the controller and based on real-time monitoring results, intelligent control is achieved and parameters are adjusted in real time.

[0013] As a preferred embodiment of the method for monitoring gypsum quality in carbide slag desulfurization according to the present invention, online sampling, obtaining samples and performing technical analysis to obtain analysis results include:

[0014] Extract samples from the gypsum slurry of the desulfurization system through online sampling;

[0015] The instrument is used to scan the sample to obtain the purity, crystal structure and impurity characteristics of the gypsum.

[0016] As a preferred embodiment of the gypsum quality monitoring method for carbide slag desulfurization according to the present invention, the physical properties of the entire slurry are measured and inverted based on a standard model evaluation to obtain a first evaluation, including:

[0017] The turbidity of gypsum slurry is measured using optical scattering technology in the sensor;

[0018] The evaluation inversion is performed based on the fitting results of the optical scattering intensity and the standard curve.

[0019] As a preferred embodiment of the method for monitoring gypsum quality in carbide slag desulfurization according to the present invention, the first evaluation comprises:

[0020] Based on the particle size distribution range and suspended matter content obtained by inversion of the assessment;

[0021] Among them, the particle size distribution range and suspended matter content are set with standard ranges and proportions.

[0022] As a preferred embodiment of the method for monitoring gypsum quality in carbide slag desulfurization according to the present invention, the second prediction is obtained by combining discriminant analysis and intelligent model analysis and prediction, including:

[0023] Spectral and turbidity data were analyzed using a multivariate regression model combining partial least squares discriminant analysis and principal component analysis;

[0024] It runs a real-time operating system and supports multi-threaded processing to process and predict data.

[0025] As a preferred embodiment of the method for monitoring gypsum quality in carbide slag desulfurization according to the present invention, the second prediction includes:

[0026] Purity, particle size and impurity content are predicted based on processing;

[0027] Output to the display interface in image and digital form.

[0028] As a preferred solution of the gypsum quality monitoring method for carbide slag desulfurization described in the present invention, wherein: intelligent control is achieved through a controller based on real-time monitoring results, and parameters are adjusted in real time, including:

[0029] Transmitted to the variable frequency regulator and actuator valve via analog signal;

[0030] Control intelligent electronic control equipment through digital signals;

[0031] Analog and digital signals are automatically switched according to the actuator type, adjusting the command response time, optimizing the gypsum purity, and ensuring uniform particle size distribution and impurity content;

[0032] Among them, real-time adjustment parameters include:

[0033] Dynamically control the slurry solid-liquid ratio through the automatic feeding system;

[0034] Adjust the reaction temperature by heating and cooling devices;

[0035] Dynamic adjustment of stirring speed is achieved through frequency conversion regulator;

[0036] The pH value of the slurry is controlled by an automatic acid and alkali injection system.

[0037] In a second aspect, the present invention provides a gypsum quality monitoring system for carbide slag desulfurization, comprising:

[0038] Sampling and analysis module: online sampling, obtaining samples and performing technical analysis to obtain analysis results;

[0039] a first evaluation module that measures the physical properties of the bulk slurry and performs an inversion based on a standard model evaluation to obtain a first evaluation;

[0040] The second prediction module combines discriminant analysis and intelligent model analysis and prediction to obtain the second prediction;

[0041] The dynamic feedback control module realizes intelligent control and adjusts parameters in real time through the controller based on real-time monitoring results.

[0042] In a third aspect, the present invention provides an electronic device, comprising:

[0043] memory and processor;

[0044] The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of a gypsum quality monitoring method for carbide slag desulfurization are realized.

[0045] In a fourth aspect, the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the gypsum quality monitoring method for carbide slag desulfurization.

[0046] The beneficial effects of the present invention are as follows: the present invention uses high-frequency online sampling and spectral technology to analyze the composition characteristics of gypsum in real time, significantly improving monitoring efficiency and data reliability; combines optical scattering technology to synchronously quantify the physical properties of the slurry, and realizes multi-dimensional dynamic quality evaluation; based on multivariable model fusion and intelligent prediction algorithms, accurately predicts and dynamically optimizes gypsum quality parameters; automatically adjusts key process conditions through a closed-loop control system to ensure continuous and stable gypsum quality; the overall system adopts a modular architecture and intelligent collaborative mechanism, which greatly reduces manual intervention, extends the operating life of equipment, and enhances the economic value of by-products and environmental benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0048] Figure 1 A flow chart of a gypsum quality monitoring method for carbide slag desulfurization provided by one embodiment of the present invention.

[0049] Figure 2 A schematic diagram of the module structure of a gypsum quality monitoring method for carbide slag desulfurization provided by an embodiment of the present invention.

[0050] Figure 3 A real-time monitoring curve diagram of a gypsum quality monitoring method for carbide slag desulfurization provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0051] To make the above-mentioned objects, features, and advantages of the present invention more clearly understood, the following detailed description of the specific embodiments of the present invention is given in conjunction with the accompanying drawings. It is obvious that the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in this field without creative work should fall within the scope of protection of the present invention.

[0052] Example 1, with reference to Figure 1-Figure 2 , as one embodiment of the present invention, provides a method for monitoring gypsum quality in carbide slag desulfurization, comprising:

[0053] S1: Take samples online, obtain samples and perform technical analysis to obtain analysis results;

[0054] S2: Measure the physical properties of the bulk slurry and evaluate the inversion based on the standard model to obtain a first estimate;

[0055] S3: Combine discriminant analysis and intelligent model analysis and prediction to obtain the second prediction;

[0056] S4: Intelligent control is achieved through the controller based on real-time monitoring results, and parameters are adjusted in real time.

[0057] It should be noted that in the existing carbide slag desulfurization process, gypsum quality monitoring relies on offline laboratory analysis, which has defects such as long detection cycle, poor real-time performance, and frequent manual intervention. Specifically, it is unable to capture the impact of process parameter fluctuations on gypsum purity in real time, resulting in the production of low-quality gypsum within a few hours; traditional methods make it difficult to simultaneously evaluate particle size distribution and impurity content, exacerbating the uncertainty of dehydration performance and downstream applications; process parameter adjustments rely on experience judgment, lack of data-driven dynamic control mechanism, and system stability and economy are limited.

[0058] Therefore, to address the above-mentioned problems of detection lag, lack of multi-parameter evaluation and passive control, a full-process closed-loop solution is constructed through steps S1-S4; Figure 1 As shown in Figure 2, online sampling and spectral analysis enable minute-level dynamic monitoring of gypsum composition, and turbidity detection is combined with inversion models to quantify physical properties, such as Figure 2 As shown, the multivariable algorithm integrates spectral and turbidity data to accurately predict quality trends, and the controller provides real-time feedback to adjust the solid-liquid ratio, temperature, stirring speed, and pH value, ultimately ensuring the continuous stability of gypsum quality and improving resource utilization efficiency and system intelligence.

[0059] Example 2, reference Figure 1-Figure 3 , which is an embodiment of the present invention, provides a gypsum quality monitoring method for carbide slag desulfurization based on the above embodiment.

[0060] In the embodiment of the present application, the sample is obtained and technical analysis is performed in step S1 by extracting a sample from the gypsum slurry of the desulfurization system through an online sampling system, such as Figure 1As shown; the sampling frequency is 1 minute / time, the sample volume is controlled at 10-20mL, and the filtration accuracy is 5 microns, which is used to remove large particle impurities (such as >50μm) in the slurry; the sample is scanned by a near-infrared spectrometer (NIR), with an operating wavelength range of 900-2500nm, a resolution of less than 4nm, and a scanning time of less than 5 seconds to obtain the purity, crystal structure and impurity characteristics of gypsum; Among them, as Figure 2 As shown in Figure 1, the online sampling system includes an automatic valve, a microporous filter device, and a constant pressure pump. The sampling pressure is maintained at 0.1-0.3 MPa to prevent slurry blockage or volatilization. The near-infrared spectrometer is equipped with a high-sensitivity detector and a fiber optic probe, which is directly inserted into the sampling pipe to collect the molecular oscillation characteristics of gypsum. The data resolution reaches 0.1 nm, which is used to identify the purity of CaSO4·2H2O (determined by characteristic peaks such as 1400 nm and 1900 nm), crystal structure (such as the difference between dihydrate gypsum and anhydrous gypsum), and the content of common impurities (such as SiO2, MgO, and Al2O3).

[0061] In an optional embodiment, the sample obtained in step S1 and the technical analysis can also be quickly separated from the large particle impurities in the slurry by a centrifugal separation device, the sampling volume is controlled at 15-25 mL, and a UV-visible spectrometer is used to perform a rapid scan in the wavelength range of 300-800 nm to obtain the light absorption characteristics of the gypsum to analyze the purity and impurity composition.

[0062] In another optional embodiment, the sample obtained in step S1 and the technical analysis can also be performed by periodically collecting slurry samples through a dynamic pressure regulation system, combining nano-scale membrane filtration technology to remove ultrafine particles, and using a Fourier transform infrared spectrometer at 2500-4000 cm -1 The band is scanned at high resolution to analyze the chemical bond vibration characteristics of gypsum in real time to determine the crystal structure and impurity distribution.

[0063] In the embodiment of the present application, in step S1, online sampling is performed to obtain samples and perform technical analysis to obtain analysis results, and the following steps are also included:

[0064] The following online detection modules are installed at the gypsum output section of the desulfurization system (such as the outlet of the desulfurization tower or the outlet of the gypsum slurry pump):

[0065] Near-infrared spectroscopy probe (working band 900–2500 nm): used to collect reflectance spectrum information of gypsum slurry;

[0066] Turbidity sensor: used to monitor changes in suspended matter concentration in slurry;

[0067] Laser particle size analyzer: used to detect the particle size distribution range of gypsum crystals in the slurry (usually concentrated in 80–150 μm);

[0068] All sensor signals are sampled with a refresh cycle of 5–10 seconds and sent to the data processing unit through the analog / digital signal conversion module.

[0069] In the embodiment of the present application, in step S2, the physical properties of the entire slurry are measured and the turbidity of the gypsum slurry is measured using a turbidity sensor based on the fitting result of the optical scattering intensity and the standard curve based on the standard model evaluation inversion, such as Figure 1 As shown, the measurement range is 0-1000NTU, the accuracy is ±0.5NTU, the response time is less than 2 seconds, and the particle size distribution and suspended matter content are evaluated; Figure 2 As shown, the turbidity sensor uses optical scattering technology. The sensor is installed downstream of the sampling pipeline and works in parallel with the spectrometer to collect data synchronously. The standard curve is used to evaluate the gypsum particle size (80-150μm range) and suspended solids content (<5%). Specifically, the optical scattering sensor is used to collect the scattering intensity response signal of particles of different particle sizes to the incident light at multiple angles. Combined with the scattering intensity-particle size distribution fitting curve established in advance through standard samples, the real-time collected signal is reversely fitted and solved to obtain the main particle size range (generally 80-150μm) and distribution characteristics of the current gypsum by-product. At the same time, the suspended solids content is inverted by comparing the turbidity output value with the turbidity-solid content standard regression model, and the control accuracy is better than ±0.5%.

[0070] In an optional embodiment, the physical properties of the entire slurry are measured in step S2 and the inversion is evaluated based on the standard model. Multi-angle scattering signal acquisition technology can also be used to dynamically capture the light intensity distribution characteristics at different scattering angles. Combined with a pre-calibrated multidimensional scattering model, the particle size distribution range of the gypsum particles and the suspended matter concentration gradient can be synchronously inverted to enhance the robustness of the evaluation under complex working conditions.

[0071] In another optional embodiment, the physical properties of the entire slurry are measured in step S2 and the inversion is evaluated based on the standard model. An adaptive dynamic calibration algorithm is introduced to automatically correct the standard curve parameters according to the real-time changes in the slurry composition, and the fitting accuracy is optimized by combining historical data with online feedback to achieve a stable evaluation of the particle size and suspended matter content under variable operating conditions.

[0072] In the embodiment of the present application, in step S3, the partial least squares discriminant analysis and principal component analysis multivariate regression model analysis are combined to analyze the spectrum and turbidity data by combining the partial least squares discriminant analysis (PLS-DA) and the principal component analysis (PCA) multivariate regression model to predict the purity, particle size and impurity content of gypsum, such as Figure 1As shown in the figure, the prediction accuracy is ±1%, and the update cycle is 30 seconds. Specifically, a multivariate regression model is used to process and predict the spectral and turbidity data. The model is based on partial least squares discriminant analysis (PLS-DA) combined with principal component analysis (PCA). The PLS-DA model extracts characteristic variables from the training data set (containing gypsum samples of different purity, particle size and impurity content). PCA is used to reduce the dimension and remove noise. The prediction accuracy is ±1%, the update cycle is 30 seconds, and the regression prediction value is finally output. Among them, as shown in the figure, Figure 2 As shown, the data processing module integrates an embedded computer, runs a real-time operating system (RTOS), supports multi-threaded processing, and outputs the prediction results to the display interface in digital form.

[0073] In an optional embodiment, the multivariate regression model analysis combining partial least squares discriminant analysis and principal component analysis in step S3 can also perform nonlinear feature extraction and classification modeling on spectral and turbidity data by integrating support vector machine and kernel function mapping technology, thereby enhancing the prediction robustness under complex working conditions.

[0074] In another optional embodiment, the multivariate regression model analysis combining partial least squares discriminant analysis and principal component analysis in step S3 can also dynamically learn the correlation between multi-source data through an adaptive neural network model, and iteratively update the model weights in combination with the gradient optimization algorithm to improve the generalization prediction ability of gypsum quality parameters.

[0075] In the embodiment of the present application, in step S3, the regression prediction value is output to the display interface in the form of images and numbers, with the collected spectral data (900-2500nm) and turbidity data as input, and the output is three continuous values ​​of purity (%), particle size (μm), and impurities (%). The update cycle is 30 seconds, and the prediction error is controlled within ±1%; the model is deployed in an embedded real-time system to achieve rapid response.

[0076] In the embodiment of the present application, step S3 combines the discriminant analysis and the intelligent model analysis and prediction to obtain the second prediction, and further includes the following steps:

[0077] All raw signals are filtered, normalized, and denoised to eliminate noise factors such as slurry disturbances and water film interference. The data is then packaged in a standardized format and transmitted to an edge controller or embedded analysis terminal via Modbus protocol or industrial Ethernet, ensuring the timeliness and integrity of data input.

[0078] The signal-processed data is fed into an embedded real-time quality modeling module, built using a combination of principal component analysis (PCA) and partial least squares regression (PLS) algorithms. The model, trained on pre-collected gypsum samples (>30 groups), enables online prediction and output of the following indicators:

[0079] Gypsum purity (CaSO4·2H2O mass fraction), accuracy better than ±1%;

[0080] Average particle size and distribution range (μm);

[0081] Impurity content (insoluble solids, unreacted particles) is typically controlled below 4–5%.

[0082] The model automatically updates the forecast results every 30 seconds and displays them in graphical and digital form, facilitating on-site monitoring and remote early warning.

[0083] All results are displayed simultaneously on the local touchscreen and the remote monitoring platform, with the interface switchable to trend charts, alarm charts, and recipe review charts. The system also supports parameter anomaly alarms (such as purity <90% and impurities >6%), automatically linking the S4 process parameter adjustment system to achieve closed-loop control.

[0084] For example, the output results are shown in Table 1:

[0085] Table 1 Output result example table

[0086]

[0087]

[0088] In the embodiment of the present application, in step S4, dynamic feedback control is implemented by the controller according to the real-time monitoring results, such as Figure 2 As shown, the desulfurization process parameters including slurry solid-liquid ratio (1:3-1:6), reaction temperature (40-60°C), stirring speed (100-300rpm) and slurry pH value (6.5-7.5) are adjusted in real time by the PLC controller according to the monitoring results.

[0089] For example, real-time monitoring results are as follows: Figure 3 Real-time monitoring curve shows:

[0090] Among them, Dynamic Monitoring of Gypsum By-product Quality means dynamic monitoring of gypsum by-product quality; Gypsum Purity means gypsum purity; Particle Size means particle size; Impurity Content means impurity content; Measured Values ​​means measured values.

[0091] In the embodiment of the present application, in step S4, the analog signal and the digital signal are automatically switched according to the type of actuator, the instruction response time is adjusted, the gypsum purity is optimized, and the uniform particle size distribution and impurity content are ensured by transmitting the 4-20mA analog signal or digital signal to the actuator, and the instruction response time is adjusted to be less than 5 seconds, and the gypsum purity is optimized to be stable at more than 90%, the particle size distribution is uniform (80-150μm), and the impurity content is less than 5%; wherein, the analog signal is a standard 4-20mA signal, which is transmitted to the frequency converter and the actuator valve; the digital signal is a ModbusRTU / 485 protocol instruction, which is used to control the intelligent electronic control equipment; the two signals are automatically switched according to the type of actuator, and the response time is <5 seconds.

[0092] In the embodiment of the present application, each control action in the real-time adjustment parameters in step S4 is triggered based on a specific prediction indicator;

[0093] The slurry solid-liquid ratio is dynamically adjusted to a range of 1:3 to 1:6 based on the gypsum purity and particle size prediction results, and is precisely controlled by an automatic feeding device.

[0094] Reaction temperature: Maintained within the range of 40-60°C, precisely adjusted by heating or cooling systems;

[0095] Stirring speed: adjusted to 100-300 rpm according to turbidity data to ensure slurry uniformity;

[0096] Slurry pH: maintained at 6.5-7.5 by adding acid-base regulator.

[0097] In summary, the present invention uses high-frequency online sampling and multi-spectral fusion technology to analyze the characteristics of gypsum composition in real time, combines dynamic turbidity detection and standard curve inversion to accurately evaluate the physical properties of the slurry, and realizes multi-dimensional synchronous monitoring of gypsum purity, particle size distribution and impurity content; based on multivariable model fusion and intelligent prediction algorithm, a quality prediction system with a minute-level update cycle is constructed to drive the closed-loop control system to dynamically adjust the desulfurization process parameters to ensure the continuous and stable quality of gypsum; the system adopts a modular architecture and adaptive signal transmission mechanism to realize intelligent coordination of data acquisition, analysis and regulation, significantly reduce the intensity of manual intervention, and improve the operating life of equipment and the economic value of by-products, providing a full-process solution for the industrial-level optimization of calcium carbide slag desulfurization process.

[0098] Example 3, the above is a schematic scheme of a method for monitoring the quality of gypsum of carbide slag desulfurization in this embodiment. It should be noted that the technical scheme of the system of the method for monitoring the quality of gypsum of carbide slag desulfurization and the technical scheme of the above-mentioned method for monitoring the quality of gypsum of carbide slag desulfurization belong to the same concept. For details not described in detail in the technical scheme of the system for monitoring the quality of gypsum of carbide slag desulfurization in this embodiment, please refer to the description of the technical scheme of the above-mentioned method for monitoring the quality of gypsum of carbide slag desulfurization.

[0099] This embodiment also provides a gypsum quality monitoring system for carbide slag desulfurization, comprising:

[0100] Sampling and analysis module: online sampling, obtaining samples and performing technical analysis to obtain analysis results;

[0101] a first evaluation module that measures the physical properties of the bulk slurry and performs an inversion based on a standard model evaluation to obtain a first evaluation;

[0102] The second prediction module combines discriminant analysis and intelligent model analysis and prediction to obtain the second prediction;

[0103] The dynamic feedback control module realizes intelligent control and adjusts parameters in real time through the controller based on real-time monitoring results.

[0104] This embodiment further provides a computing device applicable to a method for monitoring gypsum quality in carbide slag desulfurization, comprising:

[0105] Memory and processor; the memory is used to store computer-executable instructions, and the processor is used to execute computer-executable instructions to implement a gypsum quality monitoring method for carbide slag desulfurization as proposed in the above embodiment.

[0106] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, a gypsum quality monitoring method for carbide slag desulfurization as proposed in the above embodiment is implemented.

[0107] The storage medium proposed in this embodiment and the gypsum quality monitoring method for carbide slag desulfurization proposed in the above embodiment belong to the same inventive concept. The technical details not described in detail in this embodiment can be referred to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0108] Through the above description of the implementation methods, those skilled in the art can clearly understand that the present invention can be implemented with the help of software and necessary general hardware, and of course can also be implemented by hardware. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory (FLASH), hard disk or optical disk, etc., including a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute the methods of various embodiments of the present invention.

[0109] 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 the present invention. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for monitoring the quality of gypsum from carbide slag desulfurization, characterized in that: include: Take samples online, obtain samples and perform technical analysis to obtain analysis results; Measuring the bulk slurry physical properties and evaluating the inversion based on a standard model to obtain a first estimate; Combining discriminant analysis and intelligent model analysis and prediction, we get the second prediction; Through the controller and based on real-time monitoring results, intelligent control is achieved and parameters are adjusted in real time.

2. The method for monitoring gypsum quality in carbide slag desulfurization according to claim 1, wherein: Take samples online, perform technical analysis on them, and obtain analytical results, including: Extract samples from the gypsum slurry of the desulfurization system through online sampling; The instrument is used to scan the sample to obtain the purity, crystal structure and impurity characteristics of the gypsum.

3. The method for monitoring gypsum quality in carbide slag desulfurization according to claim 2, wherein: The bulk slurry physical properties were measured and evaluated against the inversion of the standard model, resulting in a first estimate including: The turbidity of gypsum slurry is measured using optical scattering technology in the sensor; The evaluation inversion is performed based on the fitting results of the optical scattering intensity and the standard curve.

4. The method for monitoring gypsum quality in carbide slag desulfurization according to claim 3, wherein: The first assessment includes: Based on the particle size distribution range and suspended matter content obtained by inversion of the assessment; Among them, the particle size distribution range and suspended matter content are set with standard ranges and proportions.

5. The method for monitoring gypsum quality in carbide slag desulfurization according to claim 4, wherein: Combining discriminant analysis and intelligent model analysis and prediction, the second prediction is obtained, including: Spectral and turbidity data were analyzed using a multivariate regression model combining partial least squares discriminant analysis and principal component analysis; It runs a real-time operating system and supports multi-threaded processing to process and predict data.

6. The method for monitoring gypsum quality in carbide slag desulfurization according to claim 5, wherein: The second prediction includes: Purity, particle size and impurity content are predicted based on processing; Output to the display interface in image and digital form.

7. The method for monitoring gypsum quality in carbide slag desulfurization according to claim 6, wherein: Through the controller and based on real-time monitoring results, intelligent control is achieved and parameters are adjusted in real time, including: Transmitted to the variable frequency regulator and actuator valve via analog signal; Control intelligent electronic control equipment through digital signals; Analog and digital signals are automatically switched according to the actuator type, adjusting the command response time, optimizing the gypsum purity, and ensuring uniform particle size distribution and impurity content; Among them, real-time adjustment parameters include: Dynamically control the slurry solid-liquid ratio through the automatic feeding system; Adjust the reaction temperature by heating and cooling devices; Dynamic adjustment of stirring speed is achieved through frequency conversion regulator; The pH value of the slurry is controlled by an automatic acid and alkali injection system.

8. A gypsum quality monitoring system for carbide slag desulfurization, using the method according to any one of claims 1 to 7, characterized in that: include: Sampling and analysis module: online sampling, obtaining samples and performing technical analysis to obtain analysis results; a first evaluation module that measures the physical properties of the bulk slurry and performs an inversion based on a standard model evaluation to obtain a first evaluation; The second prediction module combines discriminant analysis and intelligent model analysis and prediction to obtain the second prediction; The dynamic feedback control module realizes intelligent control and adjusts parameters in real time through the controller based on real-time monitoring results.

9. An electronic device comprising: memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, the steps of the gypsum quality monitoring method for calcium carbide slag desulfurization as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the steps of the gypsum quality monitoring method for carbide slag desulfurization as described in any one of claims 1 to 7.

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