Method for preparing high-purity anthracene and carbazole by rectifying crude anthracene

Abstract

The invention discloses a method for preparing high-purity anthracene and carbazole by rectifying crude anthracene, which comprises the following steps: acquiring crude anthracene in a molten state, and inputting the crude anthracene in the molten state into a rectifying tower; evaporating and rectifying the crude anthracene through a rectifying tower to obtain gas containing anthracene and phenanthrene and liquid containing carbazole; condensing the gas containing anthracene and phenanthrene from the top of the rectifying tower to obtain a mixture of anthracene and phenanthrene, and separating the mixture of anthracene and phenanthrene to obtain anthracene; liquid containing carbazole is extracted from the lower side line of the rectifying tower, and carbazole is obtained by separating the liquid containing carbazole; respectively carrying out vacuum drying on anthracene and carbazole to obtain high-purity anthracene and carbazole; according to the method, the purity of anthracene and carbazole is improved, the rectification process is optimized, the production efficiency is improved, and a new technical path is provided for industrial production of high-purity aromatic compounds.

Description

Technical Field

[0001] The present invention belongs to the technical field of the preparation of anthracene and carbazole, and particularly relates to a method for preparing high-purity anthracene and carbazole by rectifying crude anthracene. Background Art

[0002] Anthracene is the starting material for preparing anthraquinone dyes. The non-fading property of anthraquinone is very good. Since the production of dyestuff chemistry, it has become the most important dye except azo dyes; anthracene is also used as pesticides, fungicides, gasoline coagulation inhibitors, etc. Carbazole is an intermediate product for preparing dyes, pigments, pesticides and polymers. At present, the methods for preparing anthracene and carbazole at home and abroad are roughly divided into the following several types: One is the solvent method, which was the process in the 1950s, but currently 70% of domestic manufacturers still use this process. It utilizes the different solubilities of anthracene and carbazole in different solvents. Crude anthracene is put into a solvent in a certain proportion, and then anthracene is fully dissolved in the solvent under stirring and heating. When the temperature reaches 110°C, it is kept at a constant temperature for about 2 hours, and then cooled to about 45°C. After stopping the stirrer and standing for 1 hour, it is filtered. After the first filtration and drying, a semi-finished product of anthracene with a content of about 60% can be obtained. Then, a certain amount of solvent is put into the crystallizer and the above method is continued. After the second filtration and drying, a semi-finished product of anthracene with a content of about 80% can be obtained. After the third filtration and drying, a finished product of anthracene with a content of 90% - 91% can be obtained. And carbazole is dissolved in the filtrate, and the residue containing carbazole can be obtained during the process of recovering the solvent. The residue is put into the crystallizer, and another solvent and the residue are mixed in a certain proportion. Under stirring and heating, the residue is fully dissolved in the solvent. When the temperature reaches 140°C, it is kept at a constant temperature for about 2 hours, and then cooled to about 60°C. After stopping the stirrer and standing for 1 hour, it is filtered. After several filtrations and drying, a finished product of carbazole with a content of 95% - 96% can be obtained. If higher-quality carbazole is desired, the above-obtained carbazole finished product is put into a sublimator for further post-treatment, and a finished product of refined carbazole with a content of about 98% can be obtained.

[0003] Adopting this process, the existing defects are: large consumption of raw materials and auxiliary materials; low product quality, and the content of anthracene only reaches 90% - 91%, which only meets the production requirements of anthraquinone and cannot meet the production needs of other products. If the content must reach 99%, it is difficult to achieve with the solvent method. Even if it is achieved, the yield is only about 50%; similarly, the content of carbazole can only be 95% - 96%, and the higher the content, the narrower the rising range of carbazole content. Only after re-refining can the content reach about 98%, and it simply cannot reach more than 99%. The yield is low. The highest yield of anthracene is about 85%, and the final yield of carbazole in the production process cannot reach 50% either, and the economic benefit is poor.

[0004] Second, there is the chemical method, namely the so-called potassium dissolution method, which is a process adopted by some domestic manufacturers in recent years. This process is divided into two parts. The latter part is the same as the solvent method. The former part is to react the carbazole contained in crude anthracene with KOH to form potassium carbazole salt. Then, some components of anthracene are separated from the potassium carbazole salt, and anthracene is extracted by the solvent method. The quality and yield of its products are comparable to those of the solvent method. The crude carbazole obtained after the hydrolysis of potassium carbazole salt is further purified by the solvent method. When the content of carbazole reaches 97%, the yield will not exceed 80%. Compared with the solvent method, the quality has been improved by 1 to 2 percentage points, but there has been a significant increase in the yield.

[0005] However, the early stage of this process has a relatively large environmental impact, which is not conducive to environmental protection, and the production cost is also relatively high. If the product quality is to be further improved, the production cost will be increased again.

[0006] 3. Anthracene oil crystallization rectification method, which is the most commonly used method for producing anthracene and carbazole abroad and was introduced into China after the 1990s. First, put anthracene oil into the crystallizer, and use the different crystallization points of anthracene, carbazole and phenanthrene and other substances to remove some components lighter than anthracene and carbazole, leaving some heavy components such as anthracene and carbazole. Then, the substances containing anthracene and carbazole are melted and pumped into a tower filled with structured packing for rectification. Anthracene is taken out from the upper side line and carbazole is taken out from the lower side line. The content of anthracene and carbazole produced by this method can reach up to 95%, and the highest yields can reach 90% and 85% respectively.

[0007] The entire production process of this method is complex, and the equipment investment is large. A production device with an annual output of 1,200 tons of anthracene and 1,000 tons of carbazole requires more than 250 million yuan, and the product quality still cannot meet the current international and domestic requirements. The production cost of the product is high and the economic efficiency is low.

[0008] In summary, the three production methods have the characteristics of backward production technology, serious environmental pollution, high production cost, and product quality and yield, and can no longer meet the needs of the rapid economic development. Therefore, it is an urgent problem to be solved today to reform the current production process, reduce environmental pollution, lower production costs, and improve product quality and yield. Summary of the Invention

[0009] The technical problem to be solved by the present invention is to provide a method for preparing high-purity anthracene and carbazole by rectifying crude anthracene in view of the above-mentioned deficiencies in the prior art. It not only improves the purity of anthracene and carbazole, but also optimizes the rectification process and improves the production efficiency, providing a new technical path for the industrial production of high-purity aromatic compounds.

[0010] To solve the above technical problems, the technical solution adopted by the present invention is: a method for preparing high-purity anthracene and carbazole by rectifying crude anthracene, the method comprising the following steps: Obtain crude anthracene in a molten state and input the molten crude anthracene into a rectification column; Evaporate and rectify the crude anthracene through the rectification column to obtain a gas containing anthracene and phenanthrene and a liquid containing carbazole; Condense the gas containing anthracene and phenanthrene from the top of the rectification column to obtain a mixture of anthracene and phenanthrene, and obtain anthracene by separating the mixture of anthracene and phenanthrene; Withdraw the liquid containing carbazole from the lower side line of the rectification column and obtain carbazole by separating the liquid containing carbazole; Vacuum dry anthracene and carbazole respectively to obtain high-purity anthracene and carbazole.

[0011] The above method for preparing high-purity anthracene and carbazole by rectifying crude anthracene, which obtains crude anthracene in a molten state and inputs the molten crude anthracene into a rectification column, includes: Obtain crude anthracene, input the crude anthracene into a molten anthracene kettle through a hoist, and heat the crude anthracene to obtain crude anthracene in a molten state; Maintain the liquid level in the molten anthracene kettle through a tube chain conveyor, and input the molten crude anthracene into the middle of the rectification column through a feed pump; Adjust the feed rate according to the temperature change in the rectification column, determine a constant feed rate, and enter the automatic control state.

[0012] The above method for preparing high-purity anthracene and carbazole by rectifying crude anthracene, which evaporates and rectifies the crude anthracene through the rectification column to obtain a gas containing anthracene and phenanthrene and a liquid containing carbazole, includes: The molten crude anthracene enters the rectification column from above the fourth layer of packing in the rectification column, and the molten crude anthracene is heated by a reboiler to obtain an upward hot gas stream, which exchanges heat and mass with the molten crude anthracene and reflux liquid entering the tower. Different substances are separated during continuous evaporation and condensation to obtain a mixture of anthracene and phenanthrene at the top of the tower, carbazole below the sixth layer of packing, and heavy components at the bottom of the tower.

[0013] The above method for preparing high-purity anthracene and carbazole by rectifying crude anthracene, which condenses the gas containing anthracene and phenanthrene from the top of the rectification column to obtain a mixture of anthracene and phenanthrene, and obtains anthracene by separating the mixture of anthracene and phenanthrene, includes: Obtain the gas containing anthracene and phenanthrene, condense the gas containing anthracene and phenanthrene through a top condenser of the tower to obtain a condensed liquid, discharge and reflux the condensed liquid according to a preset ratio, discharge the discharged part through a discharge self-control valve into a container containing a solvent for diluting and cooling materials to obtain a solid-liquid mixture, send the solid-liquid mixture into an anthracene-phenanthrene separator through vacuum and head difference to separate and obtain anthracene, return the reflux part to the rectification column through a reflux self-control valve, and evenly distribute it by a distributor and move towards the bottom of the tower to conduct heat and mass exchange again.

[0014] The above method for preparing high-purity anthracene and carbazole by crude anthracene rectification, vacuum-drying anthracene and carbazole separately to obtain high-purity anthracene and carbazole, includes: Drying the separated anthracene by a vacuum drying device, controlling the temperature and pressure during the drying process by the vacuum drying device, obtaining the dried anthracene, detecting the purity of the dried anthracene by a detection device, and if the purity of the dried anthracene reaches the preset standard, outputting it as high-purity anthracene; includes: Processing the separated anthracene by a vacuum drying device, collecting temperature and pressure data in real time by a sensor to obtain control parameters; Adjusting the operating state of the vacuum drying device according to the control parameters, optimizing the temperature and pressure combination by an algorithm to obtain preliminarily dried anthracene; Sending the preliminarily dried anthracene into a detection area by a transmission device, scanning the preliminarily dried anthracene by a spectral analyzer to obtain purity data; If the purity data is lower than the preset standard, adjusting the control parameters through a feedback system to obtain optimized dried anthracene; Predicting the purity of the optimized dried anthracene by a machine learning model to judge whether it reaches the preset standard; Classifying the dried anthracene that reaches the preset standard by a screening device to obtain high-purity anthracene; Transmitting the high-purity anthracene to a designated storage area through an automated output system to complete the processing flow; Drying the separated carbazole by a vacuum drying device, controlling the temperature and pressure during the drying process by the vacuum drying device, obtaining the dried carbazole, detecting the purity of the dried carbazole by a detection device, and if the purity of the dried carbazole reaches the preset standard, outputting it as high-purity carbazole; includes: Processing the separated carbazole by a vacuum drying device, collecting temperature and pressure data in real time by a sensor to obtain control parameters; Adjusting the operating state of the vacuum drying device according to the control parameters, optimizing the temperature and pressure combination by an algorithm to obtain preliminarily dried carbazole; Sending the preliminarily dried carbazole into a detection area by a transmission device, scanning the preliminarily dried carbazole by a spectral analyzer to obtain purity data; If the purity data is lower than the preset standard, adjusting the control parameters through a feedback system to obtain optimized dried carbazole; Predicting the purity of the optimized dried carbazole by a machine learning model to judge whether it reaches the preset standard; Classifying the dried carbazole that reaches the preset standard by a screening device to obtain high-purity carbazole; Transmitting the high-purity carbazole to a designated storage area through an automated output system to complete the processing flow.

[0015] The above method for preparing high-purity anthracene and carbazole by crude anthracene rectification uses a rectification column with a pre-optimized configuration. The specific process of pre-optimizing the configuration of the rectification column is as follows: By collecting real-time data on the specific surface area of the packing, the liquid holdup, and the tower internal resistance value, multiple groups of parameter samples are obtained from the operation process of the rectification column. After removing outliers using data cleaning techniques, a multi-dimensional characteristic distribution of the packing performance is obtained; According to the multi-dimensional characteristic distribution of the packing performance, for the mapping relationship between the vapor-liquid contact efficiency and the separation effect index, a support vector regression algorithm is used to train the packing parameter optimization model to determine the optimal value range of the specific surface area and liquid holdup of the packing; A packing design scheme is obtained from the optimal value range output by the packing parameter optimization model. Combining the correlation analysis between the tower internal resistance value and the production efficiency level, if the tower internal resistance value exceeds the preset threshold, the packing structure parameters are iteratively adjusted to obtain low-resistance packing design data; A three-dimensional model of the packing is generated from the low-resistance packing design data. For the coupling relationship between the distributor uniformity and the degree of flow field disorder, computational fluid dynamics simulation technology is used to judge the influence degree of the distributor design on liquid distribution and output the flow field distribution characteristics; The distributor resistance value and uniformity parameters are extracted according to the flow field distribution characteristics. If the distributor resistance value is higher than the preset threshold or the uniformity is lower than the target value, the distributor aperture and layout are optimized by genetic algorithm to obtain the improved distributor design parameters; The distributor geometric structure data is obtained from the improved distributor design parameters. Combining the correlation analysis between the multi-layer packing cooperation and the separation effect index, the Monte Carlo simulation method is used to predict the performance of the multi-layer packing under different working conditions and output the quantitative index of the cooperation effect; The packing layer spacing and the distributor installation position are adjusted according to the quantitative index of the cooperation effect. For the dynamic changes in the probability of flooding and the probability of dry zone formation, the real-time monitoring data is used to update the matching scheme of the packing and the distributor to obtain the overall optimization configuration of the rectification column; A virtual operation scenario is generated according to the overall optimization configuration of the rectification column. Combining the real-time feedback of the vapor-liquid contact efficiency and the production efficiency level, the particle swarm optimization algorithm is used to fine-tune the parameters of the packing and the distributor and output the final process parameter combination; The manufacturing specifications of the packing and the distributor are extracted from the final process parameter combination. For the verification requirements of the degree of flow field disorder and the separation effect index, the digital twin technology is used to simulate the operation state of the rectification column to judge the stability of the optimization scheme under high-load conditions and output the performance verification result.

[0016] The above-mentioned method for preparing high-purity anthracene and carbazole by distilling crude anthracene, by collecting real-time data of filler specific surface area, liquid holdup and tower resistance value, obtains multiple sets of parameter samples from the operation process of the distillation tower, and uses data cleaning technology to eliminate abnormal values to obtain a multi-dimensional characteristic distribution of filler performance, including: The sensors are used to collect real-time data on the specific surface area of the packing, liquid holdup and the resistance inside the tower to obtain the original parameter set; The statistical filtering method is used to clean the original parameter set, remove outliers, and obtain the cleaned parameter set; The multi-dimensional characteristics of packing specific surface area, liquid holdup and tower resistance were extracted from the cleaned parameter set to obtain the characteristic matrix. Calculate the distribution characteristics of each feature for the feature matrix and obtain a distribution parameter set; If the filler performance in the distribution parameter set exceeds the preset threshold, the dimension reduction process is performed by principal component analysis to obtain a reduced dimension feature set; According to the dimension reduction feature set, the changing trend of filler performance is judged to obtain the performance evaluation result; The correlation pattern between filler performance and multidimensional features is determined through performance evaluation results, and feature association rules are obtained.

[0017] The above-mentioned method for preparing high-purity anthracene and carbazole by distilling crude anthracene obtains a packing design scheme from the optimal value range output by the packing parameter optimization model, and combines the correlation analysis between the tower resistance value and the production efficiency level. If the tower resistance value exceeds a preset threshold, the packing structure parameters are iteratively adjusted to obtain low-resistance packing design data, including: Obtain the best value range from the packing parameter optimization model and determine the initial packing design scheme; By analyzing the correlation between the tower resistance value and the production efficiency level, it is determined whether the tower resistance value exceeds the preset threshold value; If the resistance value in the tower exceeds a preset threshold, the packing structure parameters are adjusted iteratively to obtain adjusted structure parameter data; According to the adjusted structural parameter data, the low-resistance filler design data is obtained; The initial packing design scheme is updated using the low-resistance packing design data to obtain an optimized packing design scheme; Verify the optimized packing design through correlation analysis to determine the matching degree between the tower resistance value and the production efficiency level; The optimization model is iteratively updated according to the verification results to obtain the final packing design data.

[0018] The above method for preparing high-purity anthracene and carbazole by crude anthracene rectification obtains the geometric structure data of the distributor from the improved distributor design parameters, combines the correlation analysis of the cooperation and separation effect index of multi-layer packing, and uses the Monte Carlo simulation method to predict the performance of multi-layer packing under different working conditions, and outputs the quantitative index of the synergistic effect, including: Obtain the geometric structure data from the distributor design parameters, extract the key features using a data analysis tool, and obtain the geometric description of the distributor; Match the geometric structure data with the multi-layer packing configuration, and use the correlation analysis method to determine the synergistic effect parameters to obtain the packing synergistic characteristics; Construct a Monte Carlo simulation framework for the packing synergistic characteristics and the separation effect index, and output the performance distribution under different working conditions; Obtain the performance distribution data, combine the working condition change conditions, judge the fluctuation range of the performance, and obtain the performance prediction result; Extract the key statistical values from the performance prediction results, use the quantification method to calculate the synergistic effect index, and determine the synergistic quantitative description; Through the comparative analysis of the synergistic quantitative description and the separation effect data, judge the applicability of the multi-layer packing under the target working conditions, and obtain the optimized suggestion data; Adjust the distributor design parameters according to the optimized suggestion data, and use the iterative calculation method to update the geometric structure description to obtain the improved distributor configuration.

[0019] The above method for preparing high-purity anthracene and carbazole by crude anthracene rectification extracts the manufacturing specifications of the packing and the distributor from the final process parameter combination. For the verification requirements of the flow field disorder degree and the separation effect index, the digital twin technology is used to simulate the operation state of the rectification column, judge the stability of the optimization scheme under high load conditions, and output the performance verification result, including: Extract the packing specifications and distributor specifications from the process parameter combination to generate the initial manufacturing data; Obtain the flow field disorder degree characteristics from the initial manufacturing data, and use the computational fluid dynamics method to simulate the flow field distribution to obtain the disorder degree index; For the disorder degree index and the separation effect index, construct a virtual model of the rectification column through digital twin technology, and output the operation state data; Judge the feasibility of the optimization scheme according to the operation state data. If the disorder degree shown in the virtual model exceeds the preset threshold, adjust the packing specifications and distributor specifications to obtain the adjusted manufacturing data; Simulate the operation state under high load conditions through the adjusted manufacturing data, and use the support vector machine algorithm to analyze the stability trend, and output the stability evaluation value; Obtain the stability evaluation value and the separation effect index, determine whether the performance results meet the verification requirements, and obtain the performance verification data of the final optimization plan; Extract key indicators from the performance verification data, generate a performance change trend chart through a visualization tool, and determine the applicability of the optimization plan.

[0020] Compared with the prior art, the present invention has the following advantages: The present invention optimizes the gas-liquid exchange process in the distillation column to ensure that the separation effect reaches the preset standard. At the same time, the bottom heavy component liquid is used as a raw material for carbon black production, realizing the comprehensive utilization of resources. This method not only improves the purity of anthracene and carbazole, but also optimizes the distillation process, improves the production efficiency, and provides a new technical route for the industrial production of high-purity aromatic compounds.

[0021] The technical solution of the present invention will be further described in detail below with reference to the drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 It is a process flow block diagram of the method for preparing high-purity anthracene and carbazole by crude anthracene distillation according to the present invention; Figure 2 It is a process flow block diagram of the method for pre-optimizing and configuring the distillation column according to the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0023] As Figure 1 shown, the method for preparing high-purity anthracene and carbazole by crude anthracene distillation according to the present invention includes the following steps: Obtain molten crude anthracene and input the molten crude anthracene into the distillation column; In this embodiment, obtaining molten crude anthracene and inputting the molten crude anthracene into the distillation column includes: Obtain crude anthracene, put the crude anthracene into the anthracene melting kettle by a hoist, and heat the crude anthracene to obtain molten crude anthracene; Maintain the liquid level in the anthracene melting kettle by a tube chain conveyor, and input the molten crude anthracene into the distillation column from the middle of the distillation column by a feed pump; Adjust the feed rate according to the temperature change in the distillation column, determine a constant feed rate, and enter the automatic control state.

[0024] Specifically, when implementing, transfer the molten crude anthracene to 5m by a hoist 3In the molten anthracene kettle, heat it to a temperature of 190°C to 200°C, and use a temperature sensor to monitor the temperature in the kettle in real time to ensure that the temperature is stable within the set range. Judge the liquid level height according to the data of the liquid level sensor in the molten anthracene kettle. When the liquid level is lower than 200 cm, start the tube chain conveyor to supplement crude anthracene, and keep the liquid level data within the range of 200 cm to 250 cm after supplementation. Continuously monitor the temperature in the molten anthracene kettle through the temperature sensor to ensure that the temperature of the molten crude anthracene is maintained at 190°C to 200°C. According to the stable state of the molten crude anthracene, use a metering device to input materials to the upper part of the fourth layer of packing in the rectifying column at a flow rate of 500 kg per hour. Obtain temperature data through the temperature sensor in the rectifying column. When it is judged that there is no obvious change in temperature after half an hour, adjust the feed rate to 1200 kg per hour; monitor the feed rate through the automatic control system. After determining that the feed rate is constant, maintain the bottom temperature of the rectifying column at 255°C to 265°C. According to the bottom temperature data, use a reboiler to heat the bottom materials of the column to make part of the materials evaporate to form an upward hot gas stream. Analyze the separation state of anthracene, phenanthrene and carbazole through the heat and mass exchange data of the gas flow in the column, the molten crude anthracene and the reflux liquid to ensure that the separation effect meets the expectations.

[0025] During specific implementation, when the bottom temperature of the rectifying column reaches above 200°C and the absolute pressure at the top of the column is 10 Pa to 20 Pa, start feeding materials into a rectifying column with a diameter of 1.8 m and a height of 46 m.

[0026] Evaporate and rectify the crude anthracene through the rectifying column to obtain a gas containing anthracene and phenanthrene and a liquid containing carbazole; In this embodiment, evaporating and rectifying the crude anthracene through the rectifying column to obtain a gas containing anthracene and phenanthrene and a liquid containing carbazole includes: The molten crude anthracene enters the rectifying column from the upper part of the fourth layer of packing in the rectifying column. Heat the molten crude anthracene through a reboiler to obtain an upward hot gas stream, which exchanges heat and mass with the molten crude anthracene and the reflux liquid entering the column. Different substances are separated during the continuous evaporation and condensation processes to obtain a mixture of anthracene and phenanthrene at the top of the column, carbazole at the lower part of the sixth layer of packing, and heavy components at the bottom of the column.

[0027] Condense the gas containing anthracene and phenanthrene from the top of the rectifying column to obtain a mixture of anthracene and phenanthrene, and obtain anthracene by separating the mixture of anthracene and phenanthrene; In this embodiment, condensing the gas containing anthracene and phenanthrene from the top of the rectifying column to obtain a mixture of anthracene and phenanthrene, and obtaining anthracene by separating the mixture of anthracene and phenanthrene includes: Obtain the gas containing anthracene and phenanthrene, condense the gas containing anthracene and phenanthrene through the top condenser of the tower to obtain a condensed liquid, discharge and reflux the condensed liquid according to a preset ratio, discharge the discharged part through the discharge automatic control valve into a container containing a solvent for diluting and cooling the material to obtain a solid-liquid mixture, send the solid-liquid mixture into the anthracene-phenanthrene separator through vacuum and head difference to separate anthracene, return the reflux part to the rectification tower through the reflux automatic control valve, and after being evenly distributed by the distributor, move towards the bottom of the tower to conduct heat and mass exchange again.

[0028] In specific implementation, when the gas in the tower rises to the top of the tower, the liquid at 170 °C - 180 °C after being condensed by the top condenser of the tower is discharged and refluxed at a ratio of 1:4 - 6, that is, 16.7% of the liquid is discharged out of the tower through the discharge automatic control valve for solvent method extraction of anthracene - enter a container containing a solvent prepared in advance for diluting and cooling the material. When the ratio of solid to liquid in the container reaches 2:1, use vacuum and head difference to send it into the separator of anthracene and phenanthrene to separate anthracene and phenanthrene. The anthracene is vacuum-dried to obtain anthracene with a purity of over 99%; 83.3% of the liquid returns to the top of the tower through the reflux automatic control valve, and after being evenly distributed by the distributor, moves towards the bottom of the tower to conduct heat and mass exchange again.

[0029] Collect the liquid containing carbazole from the lower side line of the rectification tower, and obtain carbazole by separating the liquid containing carbazole; In specific implementation, the temperature at the lower part of the sixth packing section is between 240 °C - 245 °C. At such a high vacuum state, this temperature is exactly the condensation critical point of carbazole; taking advantage of this feature, open a side line on the side of the rectification tower, and pump out carbazole through this lower side line at a rate of 300 kg - 400 kg per hour for solvent method extraction of carbazole - enter a container containing a solvent prepared in advance for diluting and cooling the material. When the ratio of solid to liquid in the container reaches 2:1, use vacuum and head difference to send it into the separator of carbazole and heavy components to separate carbazole and heavy components. The separated carbazole is vacuum-dried to obtain carbazole with a purity of over 99%.

[0030] Vacuum-dry anthracene and carbazole respectively to obtain high-purity anthracene and carbazole.

[0031] In this embodiment, vacuum-drying anthracene and carbazole respectively to obtain high-purity anthracene and carbazole includes: Dry the separated anthracene through a vacuum drying device, control the temperature and pressure during the drying process through the vacuum drying device to obtain the dried anthracene, detect the purity of the dried anthracene through a detection device, and if the purity of the dried anthracene reaches the preset standard, output it as high-purity anthracene; includes: Process the separated anthracene through a vacuum drying device, and use sensors to collect temperature and pressure data in real time to obtain control parameters; Adjust the operating state of the vacuum drying equipment according to the control parameters, optimize the temperature and pressure combination through an algorithm, and obtain preliminarily dried anthracene; Send the preliminarily dried anthracene into the detection area through a transmission device, scan the preliminarily dried anthracene with a spectral analyzer, and obtain purity data; If the purity data is lower than the preset standard, adjust the control parameters through a feedback system to obtain optimized dried anthracene; Predict the purity of the optimized dried anthracene through a machine learning model to determine whether it meets the preset standard; Classify the dried anthracene that meets the preset standard through a screening device to obtain high-purity anthracene; Transmit the high-purity anthracene to the designated storage area through an automated output system to complete the processing flow; Dry the separated carbazole through a vacuum drying equipment, control the temperature and pressure during the drying process through the vacuum drying equipment, obtain the dried carbazole, detect the purity of the dried carbazole through a detection device, and if the purity of the dried carbazole reaches the preset standard, output it as high-purity carbazole; including: Process the separated carbazole through a vacuum drying equipment, use sensors to collect temperature and pressure data in real time to obtain control parameters; Adjust the operating state of the vacuum drying equipment according to the control parameters, optimize the temperature and pressure combination through an algorithm, and obtain preliminarily dried carbazole; Send the preliminarily dried carbazole into the detection area through a transmission device, scan the preliminarily dried carbazole with a spectral analyzer, and obtain purity data; If the purity data is lower than the preset standard, adjust the control parameters through a feedback system to obtain optimized dried carbazole; Predict the purity of the optimized dried carbazole through a machine learning model to determine whether it meets the preset standard; Classify the dried carbazole that meets the preset standard through a screening device to obtain high-purity carbazole; Transmit the high-purity carbazole to the designated storage area through an automated output system to complete the processing flow.

[0032] Specifically, in a vacuum drying equipment, the separated anthracene is placed in the drying chamber. The initial temperature is set at 50°C and gradually increased to 80°C at a heating rate of 2°C / min to avoid thermal decomposition of anthracene. Meanwhile, the system pressure is reduced to below 10 kPa by a vacuum pump to ensure rapid evaporation of moisture. During the drying process, the PID control algorithm is used to adjust the heating power and vacuum degree in real time. The proportional coefficient Kp is set to 0.8, the integral time Ti is 120 s, and the derivative time Td is 30 s to maintain the temperature fluctuation within the range of ±1°C. The drying time is set to 4 hours. During this period, the moisture content of anthracene is monitored by an on-line moisture sensor, and the drying is terminated when the moisture content is below 0.5%. After drying, the purity of anthracene is detected by a high performance liquid chromatograph (HPLC). The chromatographic conditions are as follows: a C18 chromatographic column, the mobile phase is methanol-water (volume ratio 85:15), the flow rate is 1.0 mL / min, and the detection wavelength is 254 nm. The purity is calculated by the area normalization method. When the detection result is ≥99.5%, the system automatically transports anthracene to the finished product warehouse; if the purity is lower than the standard, the feedback control loop is triggered to adjust the drying parameters (such as raising the temperature to 85°C or extending the drying time by 30 minutes) for secondary treatment until the standard is reached. The whole process is realized by PLC programming for automatic control, and the data is uploaded to the MES system in real time for recording and analysis.

[0033] Specifically, in a vacuum drying equipment, the separated carbazole is placed in the drying chamber. The initial temperature is set at 50°C and gradually increased to 80°C at a heating rate of 2°C / min to avoid thermal decomposition of carbazole. Meanwhile, the system pressure is reduced to below 10 kPa by a vacuum pump to ensure rapid evaporation of moisture. During the drying process, the PID control algorithm is used to adjust the heating power and vacuum degree in real time. The proportional coefficient Kp is set to 0.8, the integral time Ti is 120 s, and the derivative time Td is 30 s to maintain the temperature fluctuation within the range of ±1°C. The drying time is set to 4 hours. During this period, the moisture content of carbazole is monitored by an on-line moisture sensor, and the drying is terminated when the moisture content is below 0.5%. After drying, the purity of carbazole is detected by a high performance liquid chromatograph (HPLC). The chromatographic conditions are as follows: a C18 chromatographic column, the mobile phase is methanol-water (volume ratio 85:15), the flow rate is 1.0 mL / min, and the detection wavelength is 254 nm. The purity is calculated by the area normalization method. When the detection result is ≥99.5%, the system automatically transports carbazole to the finished product warehouse; if the purity is lower than the standard, the feedback control loop is triggered to adjust the drying parameters (such as raising the temperature to 85°C or extending the drying time by 30 minutes) for secondary treatment until the standard is reached. The whole process is realized by PLC programming for automatic control, and the data is uploaded to the MES system in real time for recording and analysis.

[0034] In the specific implementation, crude anthracene is evaporated into gas in the distillation tower, and through continuous condensation and evaporation, heat and mass exchange are carried out to improve the purity of anthracene and carbazole in the tower; anthracene and carbazole with a purity of more than 99% are obtained.

[0035] In this embodiment, the distillation tower adopts a distillation tower with pre-optimized configuration, such as Figure 2 As shown, the specific process of pre-optimizing the configuration of the distillation tower is: By collecting real-time data on the specific surface area, liquid holdup and tower resistance of the packing, multiple sets of parameter samples are obtained during the operation of the distillation tower. After using data cleaning technology to remove abnormal values, the multi-dimensional characteristic distribution of the packing performance is obtained. In this embodiment, by collecting real-time data of filler specific surface area, liquid holdup and tower resistance value, multiple groups of parameter samples are obtained from the operation process of the distillation tower, and after using data cleaning technology to remove abnormal values, a multi-dimensional characteristic distribution of filler performance is obtained, including: The sensors are used to collect real-time data on the specific surface area of the packing, liquid holdup and resistance in the tower to obtain the original parameter set; The statistical filtering method is used to clean the original parameter set, remove outliers, and obtain the cleaned parameter set; The multi-dimensional characteristics of packing specific surface area, liquid holdup and tower resistance were extracted from the cleaned parameter set to obtain the characteristic matrix. Calculate the distribution characteristics of each feature for the feature matrix and obtain a distribution parameter set; If the filler performance in the distribution parameter set exceeds the preset threshold, the dimension reduction process is performed by principal component analysis to obtain a reduced dimension feature set; According to the dimension reduction feature set, the changing trend of filler performance is judged to obtain the performance evaluation result; The correlation pattern between filler performance and multidimensional features is determined through performance evaluation results, and feature association rules are obtained.

[0036] According to the multi-dimensional characteristic distribution of packing performance, the support vector regression algorithm is used to train the packing parameter optimization model for the mapping relationship between vapor-liquid contact efficiency and separation effect index to determine the optimal value range of packing specific surface area and liquid holdup. In the specific implementation, according to the multi-dimensional characteristic distribution of the packing performance, the support vector regression algorithm is used to train the packing parameter optimization model for the mapping relationship between the vapor-liquid contact efficiency and the separation effect index to determine the optimal value range of the packing specific surface area and liquid holdup, including: The packing performance data was collected through multi-dimensional features, and the support vector regression algorithm was used to build a mapping model between vapor-liquid contact efficiency and separation effect index to obtain the initial training results. Based on the initial training results, the multi-dimensional characteristic distribution of the filler performance is obtained, and the preliminary value range of the specific surface area and liquid holdup is determined; For the initial value range, the regression algorithm is used to iteratively optimize the mapping relationship to judge the deviation degree between the efficiency index and the separation effect; Through the deviation degree analysis, the parameter weight of the specific surface area is adjusted to obtain the optimized gas-liquid contact efficiency distribution; According to the optimized efficiency distribution, calculate the dynamic change trend of the liquid holdup and determine the stable interval of the separation effect index; If the stable interval exceeds the preset threshold, the model is retrained by support vector regression to obtain the correction parameters of the packing performance; The multi-dimensional feature distribution is updated with the correction parameters to determine the optimal value range of the specific surface area and the liquid holdup.

[0037] Obtain the packing design scheme from the optimal value range output by the packing parameter optimization model. Combining the correlation analysis between the tower internal resistance value and the production efficiency level, if the tower internal resistance value exceeds the preset threshold, the packing structure parameters are iteratively adjusted to obtain the low-resistance packing design data; In this embodiment, obtain the packing design scheme from the optimal value range output by the packing parameter optimization model. Combining the correlation analysis between the tower internal resistance value and the production efficiency level, if the tower internal resistance value exceeds the preset threshold, the packing structure parameters are iteratively adjusted to obtain the low-resistance packing design data, including: Obtain the optimal value range from the packing parameter optimization model and determine the initial packing design scheme; Through the correlation analysis between the tower internal resistance value and the production efficiency level, judge whether the tower internal resistance value exceeds the preset threshold; If the tower internal resistance value exceeds the preset threshold, the packing structure parameters are iteratively adjusted to obtain the adjusted structure parameter data; According to the adjusted structure parameter data, obtain the low-resistance packing design data; Update the initial packing design scheme with the low-resistance packing design data to obtain the optimized packing design scheme; Verify the optimized packing design scheme through correlation analysis and judge the matching degree between the tower internal resistance value and the production efficiency level; Iteratively update the optimization model according to the verification result to obtain the final packing design data.

[0038] Generate a three-dimensional model of the packing with the low-resistance packing design data. For the coupling relationship between the distributor uniformity and the flow field disorder degree, use the computational fluid dynamics simulation technology to judge the influence degree of the distributor design on the liquid distribution and output the flow field distribution characteristics; In specific implementation, a three-dimensional model of the packing is generated based on the low-resistance packing design data. Regarding the coupling relationship between the distributor uniformity and the flow field disorder degree, computational fluid dynamics simulation technology is adopted to judge the influence degree of the distributor design on liquid distribution and output the flow field distribution characteristics, including: A three-dimensional model is constructed based on the packing design data to obtain the spatial geometric structure of the packing. The three-dimensional model is meshed using computational fluid dynamics method to obtain the basic data for flow field calculation. Regarding the meshing result, simulation technology is run to judge the preliminary characteristics of the flow field disorder degree and distribution uniformity. The flow field velocity and pressure distributions are output through simulation technology to determine the regional characteristics of liquid distribution. If the flow field disorder degree exceeds the preset threshold, the packing design parameters are adjusted to obtain an optimized three-dimensional model. According to the optimized three-dimensional model, the simulation technology is run again to obtain the quantitative data of the coupling relationship. Through the quantitative data analysis of the influence degree of liquid distribution and distribution uniformity, the final flow field characteristics are output.

[0039] According to the flow field distribution characteristics, the resistance value and uniformity parameter of the distributor are extracted. If the resistance value of the distributor is higher than the preset threshold or the uniformity is lower than the target value, the aperture and layout of the distributor are optimized by genetic algorithm to obtain the improved distributor design parameters. In specific implementation, according to the flow field distribution characteristics, the resistance value and uniformity parameter of the distributor are extracted. If the resistance value of the distributor is higher than the preset threshold or the uniformity is lower than the target value, the aperture and layout of the distributor are optimized by genetic algorithm to obtain the improved distributor design parameters, including: The resistance value and uniformity parameter are obtained from the flow field distribution data to obtain the initial performance index of the distributor. Judge from the initial performance index whether the resistance value is higher than the preset threshold or the uniformity is lower than the target value to determine the optimization trigger condition. If the trigger condition is established, genetic algorithm is used to process the aperture optimization and layout optimization to obtain the preliminary optimization result. According to the preliminary optimization result, the distributor design parameters are adjusted to obtain the improved aperture and layout data. The flow field distribution is recalculated through the improved aperture and layout data to obtain the updated resistance value and uniformity parameter. Compare the updated resistance value and uniformity parameter with the preset threshold and target value to judge whether the requirements are met. If the requirements are not met, the genetic algorithm optimization process is repeated to obtain the final design parameters.

[0040] Obtain the distributor geometric structure data from the improved distributor design parameters. Combining the correlation analysis of the cooperation and separation effect indexes of the multi-layer packing, use the Monte Carlo simulation method to predict the performance of the multi-layer packing under different working conditions, and output the quantitative index of the synergistic effect; In this embodiment, obtain the distributor geometric structure data from the improved distributor design parameters. Combining the correlation analysis of the cooperation and separation effect indexes of the multi-layer packing, use the Monte Carlo simulation method to predict the performance of the multi-layer packing under different working conditions, and output the quantitative index of the synergistic effect, including: Obtain the geometric structure data from the distributor design parameters, extract the key features using a data analysis tool, and obtain the geometric description of the distributor; Match the geometric structure data with the multi-layer packing configuration, and use the correlation analysis method to determine the synergistic effect parameters to obtain the packing synergistic characteristics; Construct a Monte Carlo simulation framework for the packing synergistic characteristics and the separation effect index, and output the performance distribution under different working conditions; Obtain the performance distribution data, combine the working condition change conditions, judge the fluctuation range of the performance, and obtain the performance prediction result; Extract the key statistical values from the performance prediction results, use the quantification method to calculate the synergistic effect index, and determine the synergistic quantitative description; Through the comparative analysis of the synergistic quantitative description and the separation effect data, judge the applicability of the multi-layer packing under the target working conditions, and obtain the optimized suggestion data; Adjust the distributor design parameters according to the optimized suggestion data, and use the iterative calculation method to update the geometric structure description to obtain the improved distributor configuration.

[0041] Adjust the packing layer spacing and the distributor installation position through the quantitative index of the synergistic effect. For the dynamic changes in the flooding probability and the dry zone formation probability, use the real-time monitoring data to update the matching scheme of the packing and the distributor to obtain the overall optimized configuration of the distillation column; During specific implementation, adjust the packing layer spacing and the distributor installation position through the quantitative index of the synergistic effect. For the dynamic changes in the flooding probability and the dry zone formation probability, use the real-time monitoring data to update the matching scheme of the packing and the distributor to obtain the overall optimized configuration of the distillation column, including: Obtain the real-time monitoring data through sensors, quantify the current state of the packing layer spacing and the distributor position, and obtain the initial parameter set; Use the data quantification results to calculate the synergistic effect value of the packing layer spacing and the distributor position, and determine the distribution characteristics of the flooding probability and the dry zone probability; If the flooding probability exceeds the preset threshold, adjust the packing layer spacing through the algorithm, and combine the distributor position offset to obtain the updated matching scheme; Analyze the fluctuation characteristics of the flooding probability and dry zone probability according to the dynamic change trend, use the support vector machine to predict the probability distribution in the next time period, and obtain the prediction result; Update the adjustment range of the packing layer spacing and the distributor position through the prediction result, judge whether the synergy effect reaches the optimal state, and obtain the optimal parameter set; After obtaining the optimal parameter set, combine the real-time monitoring data to verify the reduction degree of the flooding probability and dry zone probability, and determine the overall optimal configuration of the distillation column; Run the system with the adjusted configuration parameters, update the matching scheme through the subsequent monitoring data, and obtain a continuously optimized operating state.

[0042] Generate a virtual operation scenario according to the overall optimal configuration of the distillation column, combine the real-time feedback of the vapor-liquid contact efficiency and production efficiency level, and use the particle swarm optimization algorithm to fine-tune the parameters of the packing and distributor, and output the final process parameter combination; During specific implementation, generate a virtual operation scenario according to the overall optimal configuration of the distillation column, combine the real-time feedback of the vapor-liquid contact efficiency and production efficiency level, and use the particle swarm optimization algorithm to fine-tune the parameters of the packing and distributor, and output the final process parameter combination, including: Generate a virtual operation scenario through the distillation column configuration data and obtain the initial simulation result; Extract the real-time feedback data of the vapor-liquid contact efficiency and production efficiency from the virtual operation scenario, and determine the efficiency change trend; According to the efficiency change trend, use the particle swarm optimization algorithm to perform iterative calculations on the packing parameters and distributor parameters to obtain the adjusted parameter set; Update the virtual operation scenario through the adjusted parameter set and obtain new efficiency feedback data; If the new efficiency feedback data does not reach the preset threshold, repeat the iterative calculation of the particle swarm optimization algorithm to judge the optimized parameter combination; Generate the final process parameters according to the optimized parameter combination to obtain the operating configuration of the distillation column; Verify the virtual operation scenario through the final process parameters and obtain the efficiency feedback data under the stable operating state.

[0043] Extract the manufacturing specifications of the packing and distributor from the final process parameter combination, and for the verification requirements of the flow field disorder degree and separation effect index, simulate the operating state of the distillation column through digital twin technology, judge the stability of the optimization scheme under high load conditions, and output the performance verification result.

[0044] In this embodiment, the manufacturing specifications of the packing and the distributor are extracted from the final process parameter combination. In response to the verification requirements for the flow field disorder degree and the separation effect index, the operating state of the distillation column is simulated by digital twin technology to judge the stability of the optimization scheme under high load conditions, and the performance verification results are output, including: Extract the packing specifications and distributor specifications through the process parameter combination to generate initial manufacturing data; Obtain the characteristics of the flow field disorder degree from the initial manufacturing data, simulate the flow field distribution by computational fluid dynamics method, and obtain the disorder degree index; Construct a virtual model of the distillation column through digital twin technology for the disorder degree index and the separation effect index, and output the operating state data; Judge the feasibility of the optimization scheme according to the operating state data. If the disorder degree shown by the optimization scheme in the virtual model exceeds the preset threshold, adjust the packing specifications and distributor specifications to obtain the adjusted manufacturing data; Simulate the operating state under high load conditions through the adjusted manufacturing data, analyze the stability trend by the support vector machine algorithm, and output the stability evaluation value; Obtain the stability evaluation value and the separation effect index, judge whether the performance result meets the verification requirements, and obtain the performance verification data of the final optimization scheme; Extract the key indicators from the performance verification data, generate a performance change trend chart through a visualization tool, and determine the applicability of the optimization scheme.

[0045] The above are only the preferred embodiments of the present invention, and do not impose any limitations on the present invention. Any simple modifications, changes, and equivalent structural changes made to the above embodiments according to the technical essence of the present invention still fall within the protection scope of the technical solution of the present invention.

Claims

1. A method for preparing high-purity anthracene and carbazole by rectifying crude anthracene, characterized in that, The method comprises the following steps: Obtain crude anthracene in a molten state and input the molten crude anthracene into a rectification column; Evaporate and rectify the crude anthracene through the rectification column to obtain a gas containing anthracene and phenanthrene and a liquid containing carbazole; Condense the gas containing anthracene and phenanthrene at the top of the rectification column to obtain a mixture of anthracene and phenanthrene, and separate anthracene from the mixture of anthracene and phenanthrene; Withdraw the liquid containing carbazole from the lower side line of the rectification column and separate carbazole from the liquid containing carbazole; Perform vacuum drying on the anthracene and the carbazole respectively to obtain high-purity anthracene and carbazole.

2. The method for preparing high-purity anthracene and carbazole by crude anthracene rectification according to claim 1, characterized in that: The obtaining of the molten crude anthracene and the input of the molten crude anthracene into the rectification column includes: Obtain crude anthracene, input the crude anthracene into a molten anthracene kettle through a hoist, and heat the crude anthracene to obtain molten crude anthracene; Maintain the liquid level in the molten anthracene kettle through a tube chain conveyor, and input the molten crude anthracene into the rectification column from the middle of the rectification column through a feed pump; Adjust the feed rate according to the temperature change in the rectification column, determine a constant feed rate, and enter the automatic control state.

3. The method for preparing high-purity anthracene and carbazole by crude anthracene rectification according to claim 1, characterized in that: The evaporation and rectification of the crude anthracene through the rectification column to obtain a gas containing anthracene and phenanthrene and a liquid containing carbazole includes: The molten crude anthracene enters the rectification column from above the fourth layer of packing in the rectification column, and the molten crude anthracene is heated through a reboiler to obtain an upward hot gas stream, which exchanges heat and mass with the molten crude anthracene and the reflux liquid entering the column. Different substances are separated during the continuous evaporation and condensation processes to obtain a mixture of anthracene and phenanthrene at the top of the column, carbazole below the sixth layer of packing, and heavy components at the bottom of the column.

4. A method for preparing high-purity anthracene and carbazole by crude anthracene rectification according to claim 1, characterized in that: The condensation of the gas containing anthracene and phenanthrene at the top of the rectification column to obtain a mixture of anthracene and phenanthrene and the separation of anthracene from the mixture of anthracene and phenanthrene includes: Obtain the gas containing anthracene and phenanthrene, condense the gas containing anthracene and phenanthrene through a top condenser of the column to obtain a condensed liquid, discharge and reflux the condensed liquid according to a preset ratio, discharge the discharged part through a discharge self-control valve into a container containing a solvent for diluting and cooling materials to obtain a solid-liquid mixture, send the solid-liquid mixture into an anthracene-phenanthrene separator through vacuum and high-level difference to separate anthracene, and return the reflux part to the rectification column through a reflux self-control valve, and after being evenly distributed by a distributor, move towards the bottom of the column to conduct heat and mass exchange again.

5. A method for preparing high-purity anthracene and carbazole by crude anthracene rectification according to claim 1, characterized in that: The vacuum drying of the anthracene and the carbazole respectively to obtain high-purity anthracene and carbazole includes: Perform drying treatment on the separated anthracene through a vacuum drying device, control the temperature and pressure during the drying process through the vacuum drying device to obtain dried anthracene, detect the purity of the dried anthracene through a detection device, and if the purity of the dried anthracene reaches a preset standard, output it as high-purity anthracene; includes: Perform treatment on the separated anthracene through a vacuum drying device, and use sensors to collect temperature and pressure data in real time to obtain control parameters; Adjust the operating state of the vacuum drying device according to the control parameters, optimize the temperature and pressure combination through an algorithm to obtain preliminarily dried anthracene; The preliminary dried anthracene is sent to the detection area through a transmission device, and the preliminary dried anthracene is scanned by a spectrum analyzer to obtain purity data; If the purity data is lower than the preset standard, the control parameters are adjusted through the feedback system to obtain the optimized dried anthracene; The machine learning model is used to predict the purity of the optimized dried anthracene to determine whether it meets the preset standard; The dried anthracene that meets the preset standard is classified by a screening device to obtain high-purity anthracene; The processing flow is completed by transferring high-purity anthracene to a designated storage area through an automated output system; The separated carbazole is dried by a vacuum drying device, the temperature and pressure in the drying process are controlled by the vacuum drying device to obtain the dried carbazole, the purity of the dried carbazole is detected by a detection device, and if the purity of the dried carbazole reaches a preset standard, it is output as high-purity carbazole; including: The separated carbazole is processed by a vacuum drying device, and the temperature and pressure data are collected in real time by a sensor to obtain the control parameters; Adjust the operating state of the vacuum drying equipment according to the control parameters, optimize the temperature and pressure combination through the algorithm, and obtain the preliminary drying of carbazole; The preliminary dried carbazole is sent to the detection area through a transmission device, and the preliminary dried carbazole is scanned by a spectrum analyzer to obtain purity data; If the purity data is lower than the preset standard, the control parameters are adjusted through the feedback system to obtain the optimized dry carbazole; The purity of the optimized dried carbazole is predicted through a machine learning model to determine whether it meets the preset standard; The dried carbazole that meets the preset standard is classified by a screening device to obtain high-purity carbazole; The high-purity carbazole is transferred to the designated storage area through an automated output system to complete the processing process.

6. A method for preparing high-purity anthracene and carbazole by crude anthracene rectification according to claim 1, characterized in that: The distillation tower adopts a pre-optimized distillation tower, and the specific process of pre-optimized configuration of the distillation tower is: By collecting real-time data on the specific surface area, liquid holdup and tower resistance of the packing, multiple sets of parameter samples are obtained during the operation of the distillation tower. After using data cleaning technology to remove abnormal values, the multi-dimensional characteristic distribution of the packing performance is obtained. According to the multi-dimensional characteristic distribution of packing performance, the support vector regression algorithm is used to train the packing parameter optimization model for the mapping relationship between vapor-liquid contact efficiency and separation effect index to determine the optimal value range of packing specific surface area and liquid holdup. The packing design scheme is obtained from the optimal value range output by the packing parameter optimization model, and the correlation analysis between the tower resistance value and the production efficiency level is combined. If the tower resistance value exceeds the preset threshold, the packing structure parameters are iteratively adjusted to obtain the low-resistance packing design data; Generate a three-dimensional packing model through the design data of low-resistance packing, use computational fluid dynamics simulation technology to determine the influence of the distributor design on liquid distribution and output the flow field distribution characteristics based on the coupling relationship between the distributor uniformity and the flow field turbulence; The distributor resistance value and uniformity parameters are extracted according to the flow field distribution characteristics. If the distributor resistance value is higher than the preset threshold or the uniformity is lower than the target value, the distributor aperture and layout are optimized by genetic algorithm to obtain the improved distributor design parameters. The geometric structure data of the distributor is obtained from the improved distributor design parameters. Combined with the correlation analysis between the synergy of the multi-layer packing and the separation effect index, the Monte Carlo simulation method is used to predict the performance of the multi-layer packing under different working conditions, and the quantitative index of the synergy is output; The packing layer spacing and distributor installation position are adjusted through the quantitative indicators of synergy. According to the dynamic changes in the probability of flooding and the probability of dry zone formation, the matching scheme of packing and distributor is updated using real-time monitoring data to obtain the overall optimal configuration of the distillation tower. Generate a virtual operation scenario based on the overall optimized configuration of the distillation tower, combine the real-time feedback of vapor-liquid contact efficiency and production efficiency level, use particle swarm optimization algorithm to fine-tune the parameters of the filler and distributor, and output the final process parameter combination; The manufacturing specifications of the packing and distributor are extracted from the final process parameter combination. Based on the verification requirements of the flow field turbulence degree and the separation effect index, the operating status of the distillation tower is simulated through digital twin technology, the stability of the optimization scheme under high load conditions is determined, and the performance verification results are output.

7. A method for preparing high-purity anthracene and carbazole by rectifying crude anthracene according to claim 1, characterized in that: By collecting real-time data on the specific surface area, liquid holdup and tower resistance of the filler, multiple sets of parameter samples are obtained from the operation of the distillation tower, and after removing abnormal values using data cleaning technology, a multi-dimensional characteristic distribution of the filler performance is obtained, including: The sensors are used to collect real-time data on the specific surface area of the packing, liquid holdup and the resistance inside the tower to obtain the original parameter set; The statistical filtering method is used to clean the original parameter set, remove outliers, and obtain the cleaned parameter set; The multi-dimensional characteristics of packing specific surface area, liquid holdup and tower resistance were extracted from the cleaned parameter set to obtain the characteristic matrix. Calculate the distribution characteristics of each feature for the feature matrix and obtain a distribution parameter set; If the filler performance in the distribution parameter set exceeds the preset threshold, the dimension reduction process is performed by principal component analysis to obtain a reduced dimension feature set; According to the dimension reduction feature set, the changing trend of filler performance is judged to obtain the performance evaluation result; The correlation pattern between filler performance and multidimensional features is determined through performance evaluation results, and feature association rules are obtained.

8. A method for preparing high-purity anthracene and carbazole by crude anthracene rectification according to claim 1, characterized in that: The packing design scheme is obtained from the optimal value range output by the packing parameter optimization model, and the correlation analysis between the tower resistance value and the production efficiency level is combined. If the tower resistance value exceeds the preset threshold, the packing structure parameters are iteratively adjusted to obtain low-resistance packing design data, including: Obtain the best value range from the packing parameter optimization model and determine the initial packing design scheme; By analyzing the correlation between the tower resistance value and the production efficiency level, it is determined whether the tower resistance value exceeds the preset threshold value; If the resistance value in the tower exceeds a preset threshold, the packing structure parameters are adjusted iteratively to obtain adjusted structure parameter data; According to the adjusted structural parameter data, the low-resistance filler design data is obtained; The initial packing design scheme is updated using the low-resistance packing design data to obtain an optimized packing design scheme; Verify the optimized packing design through correlation analysis to determine the matching degree between the tower resistance value and the production efficiency level; The optimization model is iteratively updated according to the verification results to obtain the final packing design data.

9. A method for preparing high-purity anthracene and carbazole by rectifying crude anthracene, as claimed in claim 1, characterized in that: Obtain the distributor geometric structure data from the improved distributor design parameters, combine the correlation analysis of the multi-layer packing synergy and separation effect index, and use the Monte Carlo simulation method to predict the performance of the multi-layer packing under different working conditions, and output the quantitative indicators of the synergy effect, including: Obtain the geometric structure data from the distributor design parameters, extract the key features using a data analysis tool, and obtain the geometric description of the distributor; Match the geometric structure data with the multi-layer packing configuration, and use the correlation analysis method to determine the synergy parameters to obtain the packing synergy characteristics; Construct a Monte Carlo simulation framework for the packing synergy characteristics and separation effect index, and output the performance distribution under different working conditions; Obtain the performance distribution data, combine the working condition change conditions, judge the fluctuation range of the performance, and obtain the performance prediction result; Extract the key statistical values from the performance prediction result, use the quantification method to calculate the synergy effect index, and determine the quantitative description of the synergy; Conduct a comparative analysis of the quantitative description of the synergy and the separation effect data to judge the applicability of the multi-layer packing under the target working conditions, and obtain the optimization suggestion data; Adjust the distributor design parameters according to the optimization suggestion data, and use the iterative calculation method to update the geometric structure description to obtain the improved distributor configuration.

10. A method for preparing high-purity anthracene and carbazole by crude anthracene rectification according to claim 1, characterized in that: Extract the manufacturing specifications of the packing and the distributor from the final process parameter combination. For the verification requirements of the flow field disorder degree and the separation effect index, simulate the operation state of the distillation column through digital twin technology, judge the stability of the optimization scheme under high load conditions, and output the performance verification result, including: Extract the packing specifications and distributor specifications through the process parameter combination to generate the initial manufacturing data; Obtain the flow field disorder degree characteristics from the initial manufacturing data, and use the computational fluid dynamics method to simulate the flow field distribution to obtain the disorder degree index; Construct a virtual model of the distillation column through digital twin technology for the disorder degree index and the separation effect index, and output the operation state data; Judge the feasibility of the optimization scheme according to the operation state data. If the disorder degree shown in the virtual model exceeds the preset threshold, adjust the packing specifications and distributor specifications to obtain the adjusted manufacturing data; Simulate the operation state under high load conditions through the adjusted manufacturing data, and use the support vector machine algorithm to analyze the stability trend to output the stability evaluation value; Obtain the stability evaluation value and the separation effect index, judge whether the performance result meets the verification requirements, and obtain the performance verification data of the final optimization scheme; Extract the key indicators from the performance verification data, generate a performance change trend chart through a visualization tool, and determine the applicability of the optimization scheme.

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