Carbon black production equipment control method and system based on DCS (Distributed Control System)

Abstract

The invention discloses a carbon black production equipment control method and system based on a DCS (Distributed Control System), relates to the technical field of carbon black production control, and aims to solve the problem that the particle size fluctuation range of particles is increased. In granulation control, particle samples at an outlet of a granulator are selected and fed into a screening machine for multi-stage screening to obtain granulation distribution data; calling a target particle size interval of the quality control database, calculating a particle size quality score in combination with the distribution data, and classifying particle uniformity according to the score; when a classification result is in a coarsening state, collecting hearth gas pressure, analyzing a rising trend, obtaining an equivalence ratio to evaluate front-end dynamic characteristics, detecting quenching water inflow and a forward distance between a nozzle and a thermal peak position, analyzing rear-end inhibition characteristics, and selecting execution process driving regulation or reaction termination regulation by integrating the two types of characteristics; and real-time identification and targeted regulation and control on the carbon black granulation particle size coarsening trend are realized, so that the particle size distribution uniformity is ensured, and the product quality stability is improved.

Description

Technical Field

[0001] This invention relates to the field of carbon black production control technology, and more specifically, to a carbon black production equipment control method and system based on a DCS system. Background Technology

[0002] Carbon black, as an important basic chemical material, is widely used in industries such as rubber, plastics, inks, and coatings. Its production process typically employs a furnace process, where carbon black particles are generated under high-temperature combustion and pyrolysis conditions. These particles are then processed through rapid cooling, collection, and subsequent granulation to form a product with a target particle size distribution. In existing carbon black production processes, the particle size distribution can be influenced by adjusting the rapid cooling water flow or changing the nozzle position.

[0003] The existing technology has the following shortcomings: Currently, existing methods typically obtain particle size distribution through laboratory testing or post-production analysis, which cannot identify the particle size coarsening trend during the production process in real time and lack monitoring of dynamic changes in particle size distribution. When a particle size coarsening trend occurs during the production process, it leads to increased fluctuations in particle size and reduced product quality stability. Therefore, a carbon black production equipment control method and system based on a DCS system is proposed.

[0004] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] To overcome the aforementioned deficiencies of the prior art, embodiments of the present invention provide a carbon black production equipment control method and system based on a DCS system, which solves the problems mentioned in the background art by using granulation distribution data analysis, quality scoring classification, and a comprehensive control mechanism of front-end and back-end characteristics.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a method for controlling carbon black production equipment based on a DCS system, comprising the following steps: Step S1: During the granulation control process, the granulated particles at the outlet of the granulator are sampled to obtain granulated particle samples. The granulated particle samples are then vibrated and sieved by a screening machine to detect the granulation distribution data. Step S2: Retrieve the target particle size range from the quality control database, combine it with the granulation distribution data to generate a particle size quality score, and classify the uniformity of the granulated particles based on the particle size quality score. Step S3: When the uniformity classification result of the granulated particles is coarse, set the sampling time, collect the gas pressure in the carbon black furnace and analyze the pressure rise trend, obtain the equivalence ratio in the current production process, and evaluate the power regulation characteristics in combination with the pressure rise trend. Step S4: Detect the water inlet flow rate of the quenching equipment and the forward movement distance between the quenching nozzle and the furnace heat peak position. Analyze the inhibition and regulation characteristics based on the detection results, and select the adjustment process drive regulation or reaction termination regulation by combining the dynamic regulation characteristics and the inhibition and regulation characteristics.

[0007] In a preferred embodiment, in step S1, during the granulation control process of carbon black production, a sampling period is preset, and granulated particles at the outlet of the granulator are randomly selected as granulated particle samples during the preset sampling period. The granulated particle samples are transported to a sieving machine for particle size classification. The sieve surface of the sieving machine vibrates uniformly, causing the granulated particle samples to disperse on the sieve surface and pass through the sieve in sequence. Granulated particle samples of different sizes fall into the sieve collection bins of different particle size ranges.

[0008] In a preferred embodiment, in step S1, after sieving, the mass of the granulated particle samples in each sieve collection bin is statistically analyzed, and the ratio of the mass of the granulated particle samples in the sieve collection bin to the total mass of the granulated particle samples is taken as the mass ratio of the particle size range. Each screen collection chamber corresponds to a particle size range, which is defined by the sieve aperture size of the two adjacent screen layers. According to the particle size range corresponding to the screen collection bin, the mass percentage of each particle size range is arranged in ascending order to form a particle size distribution percentage set, which is used as the granulation distribution data.

[0009] In a preferred embodiment, in step S2, the target particle size range is retrieved from the quality control database, and the upper and lower limits of the target particle size range are respectively denoted as the upper limit threshold and the lower limit threshold. In the granulation distribution data, the mass percentage of the particle size range with a particle size greater than the upper limit threshold of the particle size is statistically analyzed, and these percentages are accumulated to obtain the cumulative percentage of coarse particles. The target granulation ratio is obtained by summing the mass percentages of granulated particle samples between the upper and lower particle size thresholds.

[0010] In a preferred embodiment, in step S2, the particle size quality score is calculated based on the cumulative proportion of coarse particles and the target granulation proportion. If the particle size quality score is greater than the preset quality score threshold, the classification result of the granulation particle uniformity is determined to be a non-coarsened state. Conversely, the classification result for the uniformity of granulated particles is a coarsened state.

[0011] In a preferred embodiment, in step S3, when the granulation particle uniformity classification result is determined to be in a coarsened state, a fixed sampling time is set, and the static pressure value of the gas inside the carbon black furnace is obtained as the gas pressure through a pressure sensor arranged in the carbon black furnace. The gas pressure collected during the sampling period is constructed into a pressure time series. The first time derivative of the pressure time series is calculated to obtain the pressure upward trend.

[0012] In a preferred embodiment, in step S3, the ratio of actual oxygen supply to carbonaceous fuel is calculated to the ratio of oxygen supply to carbonaceous fuel under theoretical complete combustion conditions, so as to obtain the equivalence ratio in the current production process. After standardizing the equivalence ratio and the upward trend of pressure, the dynamic regulation characteristics are obtained by comprehensive calculation using a weighted linear combination method.

[0013] In a preferred embodiment, in step S4, the volume of water supplied by the quenching water pump to the nozzle in the inlet water line during the sampling time is obtained by a flow sensor arranged on the quenching device and the volume of water flow supplied by the quenching water pump to the nozzle in the inlet water line during the sampling time, and is taken as the inlet water volume of the quenching device. The axial distance between the spray center of the quench nozzle and the position of the maximum temperature in the furnace is detected by the position sensor, and it is used as the forward displacement distance between the quench nozzle and the position of the heat peak in the furnace. The inflow rate of the quenching equipment is reverse normalized to obtain the inflow rate factor. The forward displacement factor is obtained by positively normalizing the forward displacement distance between the quench nozzle and the furnace hot peak position.

[0014] In a preferred embodiment, in step S4, the influent flow factor and the forward distance factor are combined into a suppression regulation feature using the geometric mean method; When the dynamic regulation characteristic is greater than the dynamic regulation threshold and the inhibition regulation characteristic is less than or equal to the inhibition regulation threshold, the execution process drives the regulation. When the dynamic regulation characteristic is less than or equal to the dynamic regulation threshold and the inhibition regulation characteristic is greater than the inhibition regulation threshold, the response termination regulation is executed. When the dynamic regulation characteristic is greater than the dynamic regulation threshold and the inhibition regulation characteristic is greater than the inhibition regulation threshold, process-driven regulation and response termination regulation are executed simultaneously. When the dynamic regulation characteristic is less than or equal to the dynamic regulation threshold and the inhibition regulation characteristic is less than or equal to the inhibition regulation threshold, no regulation is performed.

[0015] A control system for carbon black production equipment based on a DCS system includes a particle size detection module, a quality classification module, a kinetic assessment module, and an inhibition control module. The functions of each module are as follows: The particle size detection module is used to sample the granulated particles at the outlet of the granulator to obtain granulated particle samples. After the granulated particle samples are vibrated and sieved by a screening machine, the granulation distribution data is detected. The quality classification module is used to call the target particle size range in the quality control database, calculate the particle size quality score by combining it with the granulation distribution data, and classify the uniformity of the particle size distribution based on the score results. The power assessment module is used to analyze cases where the uniformity classification result is coarsened. It collects gas pressure data in the carbon black furnace, analyzes the pressure rise trend, and calculates the power regulation characteristics in combination with the equivalence ratio of the current production process. The suppression and control module is used to detect the water inlet flow of the quenching equipment and the forward movement distance of the quenching nozzle relative to the furnace heat peak position, analyze the suppression and control characteristics, compare them with the dynamic control characteristics, and select to execute process-driven control or reaction termination control.

[0016] The technical effects and advantages of this invention are as follows: This invention, during the granulation process, selects granulated particles from the granulator outlet as samples and feeds them into a sieving machine for multi-stage sieving. Based on the sieving results, granulation distribution data is obtained. The target particle size range is retrieved from a quality control database, and a particle size quality score is calculated using the granulation distribution data. The particle size distribution uniformity is then classified according to the score. When the classification result indicates a coarsening state, gas pressure data within the carbon black furnace is collected and the pressure rise trend is analyzed. The equivalent ratio is obtained to evaluate the front-end power regulation characteristics. Simultaneously, the water inlet flow of the quenching equipment and the forward movement distance between the quenching nozzle and the furnace heat peak position are detected to analyze the back-end suppression regulation characteristics. By combining these two types of characteristics, either process-driven regulation or reaction termination regulation is selected. This allows for the identification of particle size coarsening trends during the carbon black granulation process, enabling real-time identification and targeted regulation of these trends. This ensures the uniformity of particle size distribution and improves product quality stability. Attached Figure Description

[0017] Figure 1 This is a flowchart of a method for controlling carbon black production equipment based on a DCS system according to the present invention.

[0018] Figure 2 This is a schematic diagram of a control system for carbon black production equipment based on a DCS system according to the present invention. Detailed Implementation

[0019] 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.

[0020] This invention, during the granulation process, selects granulated particles from the granulator outlet as samples and feeds them into a sieving machine for multi-stage sieving. Based on the sieving results, granulation distribution data is obtained. The target particle size range is retrieved from a quality control database, and a particle size quality score is calculated using the granulation distribution data. The particle size distribution uniformity is then classified according to the score. When the classification result indicates a coarsening state, gas pressure data within the carbon black furnace is collected and the pressure rise trend is analyzed. The equivalent ratio is obtained to evaluate the front-end dynamic regulation characteristics. Simultaneously, the water inlet flow rate of the quenching equipment and the forward movement distance between the quenching nozzle and the furnace heat peak position are detected to analyze the back-end suppression regulation characteristics. By combining these two types of characteristics, either process-driven regulation or reaction termination regulation is selected. This allows for the identification of particle size coarsening trends in the carbon black granulation process, enabling real-time identification and targeted regulation of these trends.

[0021] Example 1 Please see Figure 1 A method for controlling carbon black production equipment based on a DCS system includes the following steps: Step S1: During the granulation control process, the granulated particles at the outlet of the granulator are sampled to obtain granulated particle samples. The granulated particle samples are then vibrated and sieved by a screening machine to detect the granulation distribution data. Step S2: Retrieve the target particle size range from the quality control database, combine it with the granulation distribution data to generate a particle size quality score, and classify the uniformity of the granulated particles based on the particle size quality score. Step S3: When the uniformity classification result of the granulated particles is coarse, set the sampling time, collect the gas pressure in the carbon black furnace and analyze the pressure rise trend, obtain the equivalence ratio in the current production process, and evaluate the power regulation characteristics in combination with the pressure rise trend. Step S4: Detect the water inlet flow rate of the quenching equipment and the forward movement distance between the quenching nozzle and the furnace heat peak position. Analyze the inhibition and regulation characteristics based on the detection results, and select process-driven regulation or reaction termination regulation by combining the dynamic regulation characteristics and inhibition and regulation characteristics.

[0022] The specific implementation is as follows: In step S1, during the granulation control process of carbon black production, a sampling period is preset. During the preset sampling period, granulated particles at the outlet of the granulator are randomly selected as granulated particle samples. To ensure the representativeness of the samples, an automatic sampling device can be used to collect granulated particles at the outlet of the granulator to obtain granulated particle samples. The granulated particle samples are then transported to a screening machine for particle size classification. For example, the preset sampling period refers to the time cycle for sampling granulated particles. It can be dynamically set according to the carbon black production batch and equipment operating status. When the granulator is in a stable operating phase, sampling is performed every 10 minutes.

[0023] It should be explained that the automatic sampling device includes a sampling valve, a sampling pipeline, a quantitative sampling chamber, and a drive execution unit. It introduces the granulated particles from the granulator outlet into the quantitative sampling chamber and completes one sampling to obtain a granulated sample according to a preset volume or mass. The sieving machine is a device used to classify granulated particle samples into multiple stages of particle size. It includes multi-stage screens, a vibration drive device, and a screen collection bin. The sieving machine performs step-by-step sieving of the granulated particle samples, so that granulated particle samples of different sizes pass through the corresponding screens in sequence and fall into the corresponding screen collection bins.

[0024] The sieve surface of the screening machine vibrates uniformly, causing the granulated particle samples to disperse on the sieve surface and pass through the sieve in sequence. Granulated particle samples of different sizes fall into the sieve collection bins of different particle size ranges.

[0025] After screening, the mass of the granulated particle samples in each screen collection bin is statistically analyzed, and the mass ratio of the corresponding particle size range in each screen collection bin is calculated. The ratio of the mass of the granulated particle samples in the screen collection bin to the total mass of the granulated particle samples is taken as the mass ratio of the particle size range. Each sieve collection chamber corresponds to a particle size range, which is defined by the sieve aperture size of the two adjacent sieve layers. The sieve aperture size of each sieve layer serves as the particle size dividing point. For example, if the sieve aperture size is 45μm, then this sieve layer is used to separate particles with a particle size greater than 45μm. A particle size range is formed between the two adjacent sieve layers. Granulated particles that fall below the upper sieve aperture size and cannot pass through the finer sieve aperture of the lower layer will be collected in the sieve collection chamber. For example, when the upper sieve aperture size is 150μm and the lower sieve aperture size is 106μm, the particle size range corresponding to the sieve collection chamber is [106μm, 150μm].

[0026] According to the particle size range corresponding to the sieve collection chamber, the mass percentage of each particle size range is arranged in ascending order to form a particle size distribution percentage set. The particle size distribution percentage set is used as granulation distribution data to reflect the distribution of granulated particle samples in each particle size range.

[0027] This step involves collecting granulated particle samples and performing multi-stage particle size classification using a vibrating sieving process. This reflects the particle size distribution of granulated particles during the current carbon black production process. By calculating the mass percentage of each particle size range and combining them to form granulation distribution data, a reliable data foundation is provided for subsequent quality scoring and uniformity classification.

[0028] In step S2, the target particle size range is retrieved from the quality control database. The upper and lower limits of the target particle size range are denoted as the upper limit threshold and the lower limit threshold, respectively.

[0029] It should be explained that the quality control database refers to a database used to store process benchmarks and historical statistical data related to particle size control during carbon black production. In this embodiment, it is used to provide the target particle size range corresponding to the current carbon black production process. The target particle size range refers to the particle size range used to limit the range of particle size distribution of granulated particles to meet the standard.

[0030] In the granulation distribution data, the mass percentage of the particle size range with a particle size greater than the upper limit threshold of the particle size is statistically analyzed, and these percentages are accumulated to obtain the cumulative percentage of coarse particles. The target granulation ratio is obtained by summing the mass percentages of granulated particle samples between the upper and lower particle size thresholds. Particle size quality score is calculated based on the cumulative proportion of coarse particles and the target granulation proportion: ,in, To achieve the target granulation ratio, This represents the cumulative percentage of coarse particles. For particle size quality scoring; The higher the cumulative percentage of coarse particles, the higher the proportion of granulated particles falling above the upper threshold of the target particle size range. The particle size distribution of the current granulated particle sample is significantly shifted towards the coarse end. The more serious the deviation from the target particle size range, the smaller the particle size quality score. The uniformity of granulated particles is evaluated by comparing a preset quality score threshold with the particle size quality score. If the particle size quality score is greater than the preset quality score threshold, the classification result of the granulation particle uniformity is determined to be a non-coarsened state. If the particle size quality score is less than or equal to the preset quality score threshold, the classification result of the granulation particle uniformity is determined to be coarsened.

[0031] It should be explained that the preset quality score threshold is a benchmark value used to determine whether the particle size distribution of granulated particles is coarsened. It is preset by the quality control database or historical statistical data. For example, the median of the particle size quality score in qualified batches minus one median absolute deviation is taken as the preset quality score threshold.

[0032] After acquiring granulation distribution data, the target particle size range is retrieved from the quality control database, the particle size quality score is calculated, and the score result is compared with the preset quality score threshold to determine the coarsening state of the granulated particles. This quantifies the degree of deviation between the particle size distribution and the target particle size range, thereby improving the monitoring accuracy and response speed of the carbon black granulation process.

[0033] In step S3, when the granulation particle uniformity classification result is determined to be in a coarsened state, a fixed sampling time is set, and the static pressure value of the gas inside the carbon black furnace is obtained by a pressure sensor arranged in the carbon black furnace as the gas pressure, reflecting the gas generation rate and flow intensity during the reaction process in the furnace. It should be noted that the fixed sampling time refers to the time interval set when collecting the output signal of the pressure sensor during the carbon black production process. It is divided into multiple periodic sampling moments, and its setting satisfies the Nyquist sampling law, that is, the sampling frequency should be greater than twice the highest change frequency of the pressure signal, so as to ensure that the sampling data can be used for subsequent time derivative calculation and pressure rise trend analysis. The pressure sensor is a detection element installed in the carbon black production furnace or its connecting pipes to output the static pressure value of the gas inside the furnace.

[0034] The gas pressures collected during the sampling period are constructed into a pressure time series. The first-order time derivative of the pressure time series is then calculated to obtain the pressure upward trend. ; in, The pressure is on the rise. Sampling time Under the gas pressure, This is the first derivative of gas pressure with respect to time.

[0035] The pressure rise trend is used to characterize the rate of change of furnace gas pressure, reflecting the strength of the reaction driving force inside the furnace. The greater the pressure rise trend, the faster the furnace gas pressure increases over time, and the more material supply and energy conditions the downstream granulated particles obtain during their growth process, thus increasing the particle size and exacerbating the coarsening trend. Conversely, the smaller the pressure rise trend, or even when it approaches zero, the more gradual the change in furnace gas pressure, the weaker the reaction driving force, and the lower the impact on particle size coarsening.

[0036] The ratio of actual oxygen supply to carbonaceous fuel in the carbon black furnace during the current production process is measured in real time using a gas flow meter and a component analyzer. The ratio of the actual oxygen supply to carbonaceous fuel ratio to the ratio of oxygen supply to carbonaceous fuel under the theoretical complete combustion condition is calculated to obtain the equivalence ratio in the current production process. Among them, the ratio of oxygen to carbonaceous fuel under theoretical complete combustion conditions is the theoretical ratio calculated based on the stoichiometric ratio of complete combustion. The equivalence ratio reflects the degree of deviation between the oxygen-fuel ratio under the current reaction conditions and the theoretical combustion conditions. If the equivalence ratio is greater than 1, it indicates that the reaction system is in a state of excess oxygen supply, the oxidation reaction is driven more strongly, the combustion rate is accelerated, the particle growth power of the carbon black product is stronger, and thus the average particle size of the granules increases and the coarsening trend is more significant. If the equivalence ratio is less than 1, it indicates that the reaction system is in a state of excess fuel, the oxygen supply is insufficient, and the coarsening trend of the granules is weakened.

[0037] It should be noted that a gas flow meter is a detection device installed in the air inlet pipe or fuel gas supply pipeline of a carbon black production system. Its function is to measure the volumetric flow rate or mass flow rate of gas passing through the pipeline in real time. A component analyzer is a detection device arranged on the gas sampling pipeline in the carbon black production process. Its function is to quantitatively analyze the composition of the gas entering the furnace, to provide actual ratio data of oxygen and carbonaceous fuel, and to calculate the equivalent ratio by combining the measurement results of the gas flow meter.

[0038] After standardizing the equivalence ratio and the upward trend of pressure, a comprehensive calculation is performed using a weighted linear combination method to obtain the dynamic regulation characteristics. The calculation formula is shown below: ; in, As a dynamic regulation characteristic, This is the standardized value of the equivalence ratio. This is the value standardized by the upward trend of pressure. and These are the preset weighting coefficients.

[0039] The larger the dynamic regulation characteristic, the stronger the reaction driving force under the combined effect of oxygen supply status and pressure change rate, and the more significant the coarsening trend of granulated particles; the smaller the dynamic regulation characteristic, the less the reaction driving force, and the weaker the effect on the coarsening of granulated particles.

[0040] It should be noted that standardization refers to the process of mapping raw data of different physical quantities or different dimensions to a uniform dimension, uniform numerical range or uniform statistical distribution through specific mathematical transformations. Standardization methods include, but are not limited to, standard linear transformation based on interval scaling, Z-Score standardization based on statistics, or normalization method based on nonlinear mapping functions. The application methods of standardization will not be elaborated here. The weighting coefficient is used to characterize the relative contribution of the equivalence ratio and the pressure rise trend to the reaction driving characteristics in the comprehensive calculation of dynamic regulation characteristics. The equivalence ratio and pressure rise trend are collected under different working conditions, and the changes in the coarsening trend of granulated particles are recorded. The sensitivity to the coarsening trend is determined by analysis of variance, and the sensitivity is used as the corresponding weighting coefficient.

[0041] In step S4, the water inlet flow rate of the quenching equipment and the forward displacement distance between the quenching nozzle and the furnace heat peak position are detected. It should be noted that a quenching device is a process unit located at the rear end of a carbon black production furnace. Its function is to rapidly cool down and terminate the reaction inside the furnace by spraying water or other cooling media onto the high-temperature reaction gas.

[0042] The flow rate of the quenching equipment is determined by the flow sensor installed on the quenching equipment and the volume of water supplied by the quenching pump to the nozzle in the inlet pipe during the sampling time. The axial distance between the spray center of the quench nozzle and the position of the maximum temperature in the furnace is detected by the position sensor, and it is used as the forward displacement distance between the quench nozzle and the position of the heat peak in the furnace. It should be noted that a flow sensor is a detection element installed in the inlet water pipe of a quenching device to detect the volume of water flowing through the pipe in real time; a position sensor is a detection element installed on the moving mechanism of the quenching nozzle to measure the axial distance of the nozzle spray center relative to the position of the furnace heat peak.

[0043] After obtaining the water inlet flow rate of the quenching equipment and the forward displacement distance between the quenching nozzle and the furnace heat peak position, the water inlet flow rate of the quenching equipment is reverse normalized to obtain the water inlet flow rate factor, and the forward displacement distance between the quenching nozzle and the furnace heat peak position is forward normalized to obtain the forward displacement distance factor. The calculation formulas are as follows: ; in, For the inflow factor, For the forward distance factor, This refers to the inlet water volume of the quenching equipment. This refers to the forward displacement of the quench nozzle relative to the furnace heat peak position. and These represent the maximum and minimum water inflow rates of the quenching equipment within the allowable range of the process. and These represent the maximum and minimum forward movement distances within the adjustable range of the quench nozzle position.

[0044] It should be noted that the maximum and minimum water inflow rates and the maximum and minimum forward movement distances are all derived from the factory-set process allowable operating range of the quenching equipment. During the normalization process, the water inflow rate of the quenching equipment is normalized in reverse to ensure that the numerical value is consistent with the physical meaning. That is, the larger the water inflow rate, the smaller the water inflow factor, and the stronger the inhibition effect; the smaller the water inflow rate, the larger the water inflow factor, and the weaker the inhibition effect.

[0045] The geometric mean method is used to combine the influent flow factor and the forward displacement factor into a suppression and regulation characteristic. The specific calculation formula is as follows: ; in, To suppress regulatory characteristics, For the inflow factor, This is the forward shift distance factor.

[0046] It should be noted that the geometric mean method is a mathematical processing method used to combine two or more parameters with different dimensions or numerical ranges to obtain a single characteristic value.

[0047] The smaller the water inlet of the quenching equipment, the further back the quenching nozzle is, and the lower the spray pressure, the greater the inhibition and regulation characteristics, indicating that the quenching equipment has a weaker inhibitory effect on the furnace reaction, that is, the reaction termination is delayed and the granulated particles are coarser. The larger the water inlet of the quenching equipment, the further forward the quenching nozzle is, and the higher the spray pressure, the smaller the inhibition and regulation characteristics, indicating that the inhibitory effect is sufficient and the constraint on the coarsening trend of particles is more significant.

[0048] The dynamic regulation characteristics and inhibition regulation characteristics are compared with the dynamic regulation threshold and inhibition regulation threshold, respectively, to determine the selection of the control strategy: When the dynamic regulation characteristic is greater than the dynamic regulation threshold and the inhibition regulation characteristic is less than or equal to the inhibition regulation threshold, it is determined that the front-end reaction driving force is too strong while the back-end inhibition effect is normal. The process driving control is executed, and the reaction driving force in the furnace is reduced by adjusting the fuel supply, oxygen flow rate or other front-end process parameters, thereby slowing down the coarsening trend of granulated particles. When the dynamic regulation characteristic is less than or equal to the dynamic regulation threshold and the inhibition regulation characteristic is greater than the inhibition regulation threshold, it is determined that the downstream reaction inhibition is insufficient while the front-end driving force is normal. The reaction termination control is executed by increasing the quench water volume, moving the nozzle position forward, or increasing the spray pressure to enhance the quenching effect, so that the reaction is terminated in time and the particles are inhibited from coarsening further. When the dynamic regulation characteristic is greater than the dynamic regulation threshold and the inhibition regulation characteristic is greater than the inhibition regulation threshold, it indicates that the front-end driving force is too strong and the back-end inhibition effect is insufficient. In this case, process driving regulation and reaction termination regulation are executed simultaneously to coordinate and adjust the front-end reaction intensity and the back-end rapid cooling inhibition effect in order to achieve dynamic optimization of carbon black granulation particle size. When the dynamic regulation characteristic is less than or equal to the dynamic regulation threshold and the inhibition regulation characteristic is less than or equal to the inhibition regulation threshold, it indicates that the front-end reaction driving force is within the normal range, while the back-end inhibition effect is sufficient and effective. The reaction process is operating within the stable range, and the particle coarsening trend is not significant. No active control is required. Only the current process parameters should be kept unchanged to avoid unnecessary fluctuations caused by excessive intervention.

[0049] It should be noted that the power adjustment threshold and the inhibition adjustment threshold are used to determine whether the front-end driving force and the back-end inhibition effect are within the normal range. The power adjustment threshold is based on the historical stable data of the furnace gas equivalence ratio and pressure rise rate under typical operating conditions of the carbon black production unit. The mean and standard deviation are obtained through statistical analysis, and an appropriate upper limit value is set in combination with the process requirements of product particle size distribution. The inhibition adjustment threshold is based on the factory setting parameters of the quenching equipment, including the maximum allowable water inflow and the maximum nozzle forward movement distance. Combined with the boundary conditions where coarsening of granulated particles begins in actual production, the critical range is determined by the normalized geometric mean result.

[0050] Example 2: A control system for carbon black production equipment based on a DCS system, such as... Figure 2 As shown, a control method for carbon black production equipment based on a DCS system is implemented, including a particle size detection module, a quality classification module, a kinetic assessment module, and an inhibition control module. The functions of each module are as follows: The particle size detection module is used to sample the granulated particles at the outlet of the granulator to obtain granulated particle samples. After the granulated particle samples are vibrated and sieved by a screening machine, the granulation distribution data is detected. The quality classification module is used to call the target particle size range in the quality control database, calculate the particle size quality score by combining it with the granulation distribution data, and classify the uniformity of the particle size distribution based on the score results. The power assessment module is used to analyze cases where the uniformity classification result is coarsened. It collects gas pressure data in the carbon black furnace, analyzes the pressure rise trend, and calculates the power regulation characteristics in combination with the equivalence ratio of the current production process. The suppression and control module is used to detect the water inlet flow of the quenching equipment and the forward movement distance of the quenching nozzle relative to the furnace heat peak position, analyze the suppression and control characteristics, compare them with the dynamic control characteristics, and select to execute process-driven control or reaction termination control.

[0051] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0052] Finally, it should be noted that in this paper, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0053] Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0054] In this document, the singular forms “a,” “an,” and “the” may also include the plural forms unless the context clearly indicates otherwise. It should also be understood that terms such as “comprising / including” or “having” specify the presence of the stated features, integrals, steps, operations, components, parts, or combinations thereof, but do not preclude the possibility of the presence or addition of one or more other features, integrals, steps, operations, components, parts, or combinations thereof. Meanwhile, the term “and / or” as used in this specification includes any and all combinations of the associated listed items.

[0055] The various embodiments in this specification are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. The various embodiments can be combined as needed, and the same or similar parts can be referred to each other.

[0056] The above description of the disclosed embodiments will enable those skilled in the art to make or use various modifications to these embodiments. It will be readily apparent to those skilled in the art that the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for controlling a carbon black production plant based on a DCS system, characterized in that: The method comprises the following steps: Step S1: In the granulation control process, granulation particles at the outlet of the granulator are sampled to obtain a granulation particle sample, and the granulation distribution data is detected after the granulation particle sample is vibrated and sieved by a screening machine; Step S2: The target particle size interval is called from the quality control database, and the particle size quality score is generated by combining the granulation distribution data; the uniformity of the granulation particles is classified according to the particle size quality score; Step S3: When the uniformity classification result of the granulation particles is coarse, the sampling time is set, the gas pressure in the carbon black furnace is collected, and the pressure rising trend is analyzed to obtain the equivalence ratio in the current production process, and the dynamic adjustment feature is evaluated in combination with the pressure rising trend; Step S4: The water inflow of the quenching equipment and the forward distance of the quenching nozzle and the hot peak position of the furnace are detected, the inhibition adjustment feature is analyzed according to the detection results, and the dynamic adjustment feature and the inhibition adjustment feature are comprehensively selected to select the adjustment process driving regulation or the reaction termination regulation.

2. The carbon black production equipment control method based on the DCS system according to claim 1, characterized in that: In step S1, in the granulation control process of carbon black production, a preset sampling period is set, and granulation particles at the outlet of the granulator are randomly selected as the granulation particle sample in the preset sampling period; The granulation particle sample is transported to the screening machine for particle size classification, the screen surface of the screening machine is uniformly vibrated, the granulation particle sample is dispersed on the screen surface and passes through the screen in turn, and granulation particle samples of different particle sizes fall into screen collection bins of different particle size intervals.

3. The carbon black production equipment control method based on the DCS system according to claim 2, characterized in that: In step S1, after the screening is completed, the quality of the granulation particle sample in each screen collection bin is counted, and the ratio of the quality of the granulation particle sample in the screen collection bin to the total quality of the granulation particle sample is taken as the particle size interval quality proportion; Each screen collection bin corresponds to a particle size interval, and the particle size interval is defined by the screen hole sizes of two adjacent layers of screens; According to the order from small to large of the particle size intervals corresponding to the screen collection bins, the particle size interval quality proportions are arranged in turn to form a particle size distribution proportion set, and the particle size distribution proportion set is taken as the granulation distribution data.

4. The carbon black production equipment control method based on the DCS system according to claim 3, characterized in that: In step S2, the target particle size interval is called from the quality control database, and the upper limit and the lower limit of the target particle size interval are denoted as the particle size upper limit threshold and the particle size lower limit threshold respectively; In the granulation distribution data, the particle size interval quality proportion of the granulation particle sample with a particle size greater than the particle size upper limit threshold is counted, and the coarse particle cumulative proportion is obtained by accumulation; The particle size interval quality proportion of the granulation particle sample with a particle size between the particle size upper limit threshold and the particle size lower limit threshold is accumulated to obtain the target granulation proportion.

5. The carbon black production equipment control method based on the DCS system according to claim 4, characterized in that: In step S2, the particle size quality score is calculated according to the coarse particle cumulative proportion and the target granulation proportion. If the particle size quality score is greater than the preset quality score threshold, it is determined that the classification result of the granulation particle uniformity is a non-coarsening state. On the contrary, it is determined that the classification result of the granulation particle uniformity is a coarsening state.

6. The carbon black production equipment control method based on the DCS system according to claim 1, characterized in that: In step S3, when the granulation particle uniformity classification result is determined to be a coarsening state, a fixed sampling time is set, and the static pressure value of the gas in the carbon black furnace is obtained as the gas pressure by the pressure sensor arranged in the carbon black furnace; The gas pressure collected in the sampling time is constructed as a pressure time sequence, and a first-order time derivative operation is performed on the pressure time sequence to obtain the pressure rising trend.

7. The carbon black production equipment control method based on the DCS system according to claim 6, characterized in that: In step S3, the ratio of the actual oxygen supply to the carbonaceous fuel and the ratio of the oxygen supply to the carbonaceous fuel under the theoretical complete combustion condition are calculated to obtain the equivalence ratio in the current production process; After the equivalence ratio and the pressure rising trend are standardized, the dynamic adjustment feature is obtained by comprehensive calculation in a weighted linear combination manner.

8. The carbon black production equipment control method based on the DCS system according to claim 1, characterized in that: In step S4, the water flow volume supplied to the nozzle by the quenching water pump in the water inlet pipeline in the sampling time is obtained as the water inlet amount of the quenching equipment by the flow sensor arranged on the quenching equipment; The axial distance of the quenching nozzle jet center relative to the maximum temperature position in the furnace is detected as the forward distance of the quenching nozzle and the hot peak position in the furnace by the position sensor; The water inlet amount of the quenching equipment is inversely normalized to obtain the water inlet amount factor; The forward distance of the quenching nozzle and the hot peak position in the furnace is positively normalized to obtain the forward distance factor.

9. The carbon black production equipment control method based on the DCS system according to claim 8, characterized in that: In step S4, the water inlet amount factor and the forward distance factor are integrated into the inhibition adjustment feature by using the geometric mean method; When the dynamic adjustment feature is greater than the dynamic adjustment threshold and the inhibition adjustment feature is less than or equal to the inhibition adjustment threshold, the process driving regulation is executed; When the dynamic adjustment feature is less than or equal to the dynamic adjustment threshold and the inhibition adjustment feature is greater than the inhibition adjustment threshold, the reaction termination regulation is executed; When the dynamic adjustment feature is greater than the dynamic adjustment threshold and the inhibition adjustment feature is greater than the inhibition adjustment threshold, the process driving regulation and the reaction termination regulation are simultaneously executed; When the dynamic adjustment feature is less than or equal to the dynamic adjustment threshold and the inhibition adjustment feature is less than or equal to the inhibition adjustment threshold, no regulation is executed.

10. A carbon black production plant control system based on a DCS system for implementing a carbon black production plant control method based on a DCS system according to any one of claims 1 to 9, characterized in that: The system comprises a particle size detection module, a quality classification module, a dynamic evaluation module, and an inhibition regulation module, and the functions of each module are as follows: The particle size detection module is used to sample the granulation particles at the outlet of the granulator to obtain a granulation particle sample, and the granulation distribution data is detected after the granulation particle sample is vibrated and sieved by the sieve machine; The quality classification module is used to call the target particle size interval in the quality control database, calculate the particle size quality score in combination with the granulation distribution data, and classify the uniformity of the granulation particle size distribution according to the score result; The power evaluation module is used to analyze the case that the uniformity classification result is the coarsening state, collect the gas pressure data in the carbon black hearth, analyze the pressure rising trend, and calculate the power adjustment feature in combination with the equivalence ratio of the current production process; The inhibition regulation module is used to detect the water inlet quantity of the quenching equipment and the forward distance of the quenching nozzle relative to the hot peak position of the hearth, analyze the inhibition adjustment feature, comprehensively compare with the power adjustment feature, and select the process driving regulation or reaction termination regulation for execution.

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