Washing system for purifying 1, 3-butadiene

Abstract

The invention discloses a washing system for purifying 1, 3-butadiene, which comprises a cracking tower, a heat exchanger and a packed tower, a raw material 1, 3-butadiene enters from a feed inlet near the bottom of the cracking tower, a washing liquid enters from a feed inlet near the top of the cracking tower, and countercurrent contact is formed in the cracking tower to ensure that the raw material and the washing liquid are fully contacted in the tower; the heat exchanger is used for cooling the raw materials flowing out of the cracking tower; the heat exchanger adopts an advanced cooling algorithm, the cooling power is automatically adjusted according to the temperature and the flow of the entering raw materials and the set cooling target temperature, the stable cooling effect is ensured, the flow and the temperature of the raw materials can be monitored and adjusted in real time through the whole-process accurate control strategy, and it is ensured that the raw materials stably and efficiently flow among all devices.

Description

Technical Field

[0001] The invention relates to the field of chemical industry, and in particular to a washing system for purifying 1,3-butadiene, aiming to solve the problems of unreasonable raw material flow, low degassing quality and unstable production operation in the existing washing system during the purification process of 1,3-butadiene. Background Art

[0002] In the production process of 1,3-butadiene, the washing system is an important part of the purification process. Traditional washing systems have many shortcomings. For example, the flow design of raw materials in the cracking tower is not optimized enough, resulting in some raw materials not being effectively processed, affecting the degassing quality, and thus reducing the purity of 1,3-butadiene. At the same time, unreasonable raw material flow may also cause unstable production operations, such as blockage, pressure fluctuations and other problems, increasing production maintenance costs and safety risks. Summary of the invention

[0003] The invention aims to provide a washing system for purifying 1,3-butadiene, comprising a cracking tower, a heat exchanger and a packed tower. The raw material 1,3-butadiene enters from a feed inlet near the bottom of the cracking tower, and the washing liquid enters from a feed inlet near the top of the cracking tower, so that countercurrent contact is formed in the cracking tower to ensure that the raw material and the washing liquid are fully in contact in the tower; the heat exchanger cools the raw material flowing out of the cracking tower; the heat exchanger adopts an advanced cooling algorithm to automatically adjust the cooling power according to the temperature and flow rate of the incoming raw material and the set cooling target temperature to ensure a stable cooling effect.

[0004] Further: The packed tower adopts a specific gas separation algorithm in the packed tower, and realizes efficient gas-liquid separation by adjusting the parameters of the gas distribution device and the separation structure according to the physical properties and flow rate of the gas.

[0005] Further: Use computational fluid dynamics (CFD) simulation algorithms to simulate and analyze the flow of raw materials in the cracking tower. Based on the simulation results, adjust the packing structure and tower diameter to optimize the flow of raw materials and improve mass transfer efficiency.

[0006] Further: the flow rate of raw materials flowing out of the cracking tower is monitored by a flow sensor, and a flow control algorithm is used to automatically adjust the opening of the regulating valve according to the deviation between the monitored flow rate and the set value to achieve precise flow control.

[0007] Further: the temperature of the raw material flowing out of the heat exchanger is monitored by a temperature sensor, and a temperature control algorithm is used to automatically adjust the opening of the regulating valve according to the deviation between the monitored temperature and the set value.

[0008] Furthermore, the feed rate, the flow rate of the washing liquid and the pressure parameters in the cracking tower are adjusted so that the raw material has a specific average flow rate range.

[0009] Furthermore, a pressure and concentration control algorithm is used to control the pressure and raw material concentration in the cracking tower by adjusting the feed rate, the temperature in the tower and the gas discharge rate parameters.

[0010] On the other hand, the present invention also provides a washing method for purifying 1,3-butadiene, comprising: system installation and commissioning: according to the design requirements, the cracking tower, the heat exchanger, the packing tower and the pipes and control devices connecting them are installed. Each device is commissioned to ensure that it can operate normally. For example, check whether the packing of the cracking tower is firmly installed, whether the cooling system of the heat exchanger is working normally, and whether the gas distribution device and separation structure of the packing tower are installed correctly.

[0011] Feeding operation: feed the raw material 1,3-butadiene from the feed port near the bottom of the cracking tower, and feed the washing liquid from the feed port near the top of the cracking tower. According to the actual production situation, adjust the feed speed and the flow rate of the washing liquid to ensure that the raw material and the washing liquid form a good countercurrent contact in the tower.

[0012] Raw material processing in the cracking tower: In the cracking tower, the raw material flows upward under the action of gravity and filler, and fully contacts with the washing liquid flowing downward to carry out the washing process. By monitoring the flow rate, pressure and concentration in the tower and other parameters, the operating conditions are adjusted to optimize the mass transfer efficiency of the raw material in the tower. For example, according to the nature and processing volume of the raw material, the height and density of the filler are adjusted, and the temperature and pressure in the tower are controlled.

[0013] Control of the flow of raw materials to the heat exchanger: The flow rate of raw materials flowing out of the cracking tower is monitored in real time through the flow sensor. According to the requirements of flow control accuracy, the flow rate of raw materials is adjusted through the regulating valve to stabilize it near the set value. At the same time, the cooling efficiency of the heat exchanger is monitored to ensure that the raw materials are effectively cooled in the heat exchanger.

[0014] Control of the flow of raw materials to the packed tower: The temperature of the raw materials flowing out of the heat exchanger is monitored in real time by a temperature sensor. According to the requirements of temperature control accuracy, the raw material temperature is adjusted by a regulating valve to stabilize it near the set value. In the packed tower, the raw materials are separated by low-pressure flash evaporation to remove the gas components and improve the degassing quality.

[0015] System operation monitoring and maintenance: During the operation of the entire washing system, the operating parameters of each device and the flow direction, temperature, pressure and other parameters of the raw materials are continuously monitored. Regular maintenance and servicing of the equipment is performed to ensure the stable operation of the system. For example, cleaning the packing in the cracking tower, checking whether there is leakage in the cooling system of the heat exchanger, and maintaining the gas distribution device and separation structure of the packing tower.

[0016] Beneficial technical effects:

[0017] The purification quality of 1,3-butadiene can more accurately control the cooling effect of the heat exchanger through this precise mathematical model and the limited cooling efficiency range, ensure that the raw material is in the optimal temperature state when entering the next process, reduce the impact of temperature fluctuations on the subsequent separation process, and improve the stability and purification effect of the entire washing system. The separation efficiency calculation model can intuitively reflect the separation effect of the packed tower on the gas, and combined with the specific value range, it can guide the optimization design and operation parameter adjustment of the packed tower. Through the improved gas distribution and separation structure, the gas-liquid separation in the packed tower is more thorough, the recovery rate of low-boiling components (such as vinyl acetylene, ethyl acetylene, 1,3-butadiene, etc. absorbed by the solvent) is improved, and the purity of 1,3-butadiene is effectively improved. Through these precise mathematical models, the flow rate, pressure, concentration and other parameters at different positions in the cracking tower can be deeply analyzed to determine the optimal packing structure and tower diameter. According to the optimized cracking tower based on the simulation results, the residence time distribution of the raw material in the tower is more uniform, which can improve the purification efficiency of 1,3-butadiene and reduce the risk of blockage caused by uneven raw material flow. This precise control strategy for the entire process can monitor and adjust the flow and temperature of raw materials in real time to ensure that the raw materials flow stably and efficiently between the various devices. By accurately controlling the flow and temperature, it can effectively reduce the production operation instability caused by fluctuations in raw material parameters, such as pressure fluctuations, blockages, etc., improve the reliability and production efficiency of the entire washing system, and help reduce energy consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 System principle flow chart; DETAILED DESCRIPTION

[0019] The following embodiments of the present invention are described in further detail in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0020] Embodiment 1

[0021] 1. Washing system structure

[0022] The washing system of the present invention mainly includes a cracking tower, a heat exchanger, a packing tower, and pipelines and control devices connecting them.

[0023] The internal structure of the cracking tower is specially designed with a multi-layer filler structure to improve the mass transfer efficiency of the raw materials in the tower. The filler uses a new type of high-efficiency mass transfer material with a large specific surface area and good wettability, which can promote full contact between the raw materials and the washing liquid.

[0024] The specific surface area of ​​the filler is defined as S, in units of m2 / m3, and its value range is 300-800m2 / m3. The specific value depends on the selected high-efficiency mass transfer material. For example, when material A is selected, its specific surface area SA = 500m2 / m3 is determined by experiments. The size of the specific surface area directly affects the contact area between the raw material and the washing liquid. The larger the specific surface area, the larger the contact area and the higher the mass transfer efficiency.

[0025] Heat Exchanger

[0026] The heat exchanger is set at a specific position of the cracking tower to cool the raw materials flowing out of the cracking tower. The heat exchanger adopts advanced cooling technology and can accurately control the cooling temperature to ensure that the raw materials enter the next process at the appropriate temperature.

[0027] Define the cooling efficiency of the heat exchanger as η c , the calculation formula is: Where T in To enter again

[0028] The raw material temperature of the boiler is in °C; Tout is the raw material temperature leaving the heat exchanger in °C; Tset is the set cooling temperature in °C. The cooling efficiency range is 75%-95%. By accurately controlling the cooling efficiency of the heat exchanger, it can be ensured that the temperature of the raw material when entering the packed tower is stable in a suitable range, which is beneficial to the low-pressure flash separation process in the packed tower.

[0029] Packed tower

[0030] The packed tower is a key part of the washing system, which is used to remove the gas components in the raw materials and improve the degassing quality. The packed tower is equipped with a special gas distribution device and separation structure to fully separate the gas and liquid. The packed tower uses the principle of low-pressure flash evaporation to separate low-boiling point components from high-boiling point components. The low-boiling point components are solvent-absorbed vinyl acetylene, ethyl acetylene, 1,3-butadiene, etc.

[0031] The separation efficiency of a packed tower is defined as: η s , the calculation formula is: Where m in is the mass of gas entering the packed tower, in kg; m out The mass of gas leaving the packed tower is in kg. The separation efficiency ranges from 85 to 100%. By optimizing the structure and operating parameters of the packed tower, the separation efficiency can be improved, thereby improving the purity of 1,3-butadiene.

[0032] 2. Material flow and control methods

[0033] (I) Material flow in the cracking tower

[0034] Feeding method

[0035] The raw material 1,3-butadiene and the washing liquid enter the cracking tower from different positions. 1,3-butadiene enters from the feed port near the bottom of the cracking tower, and the washing liquid enters from the feed port near the top of the cracking tower, so that the material and the washing liquid can form countercurrent contact in the tower, improving the washing effect.

[0036] Flow path in the tower

[0037] In the cracking tower, the material flows upward under the action of gravity and fillers, and the washing liquid flows downward under the action of gravity. During the flow process, the material and the washing liquid fully contact on the surface of the fillers to carry out the material exchange and washing process.

[0038] Computational fluid dynamics (CFD) models are used to simulate and optimize the material flow in the cracking tower. The optimal packing structure and tower diameter are determined by analyzing parameters such as flow rate, pressure and concentration at different locations in the tower.

[0039] The mathematical model of material flow in the tower is established as follows:

[0040] Continuity equation: Where ρ is the material density, unit is kg / m 3 ; t is time, unit is s; is the velocity vector, unit is m / s. This equation describes the mass conservation relationship of the material in the cracking tower.

[0041] Momentum equation: Where p is pressure, unit is Pa; μ is dynamic viscosity, unit is Pa·s; g is gravitational acceleration, unit is m / s 2 . This equation describes the conservation of momentum of the material in the cracking tower.

[0042] Material diffusion equation: Where c is the material concentration in mol / m 3 ; D is the diffusion coefficient, unit is m 2 js. This equation describes the material diffusion process in the cracking tower.

[0043] The average flow rate of the material in the tower is defined as The calculation formula is: Where Q is the volume flow rate of the material, in m 2 / s; A is the cross-sectional area of ​​the cracking tower, unit: m 2 The range of the average flow rate is (0.1-0.5m / s. By controlling the average flow rate of the material, it can be ensured that the material has enough residence time in the cracking tower and is fully in contact with the washing liquid, thereby improving the washing effect.

[0044] The average pressure in the tower is defined as The calculation formula is: Where V is the volume of the cracking tower, in m 3 The average pressure value ranges from 100 to 500 kPa. By controlling the average pressure value in the tower, it can ensure that the material is washed at a suitable pressure and improve the mass transfer efficiency.

[0045] The average value of the material concentration in the tower is defined as The calculation formula is: Where V is the volume of the cracking tower, in m 3 The average concentration range is 1000-5000 mol / m 3 By controlling the average value of the material concentration in the tower, it can be ensured that the material is washed at an appropriate concentration, thereby improving the washing effect.

[0046] (II) Flow control of materials from cracking tower to heat exchanger

[0047] The flow rate of the material flowing out of the cracking tower is monitored in real time by a flow sensor. The monitored flow rate is Qout, and the unit is m 3 / h. The flow control accuracy is defined as (δ f , the calculation formula is: Where Q set is the set flow value, in m 3 / h. The flow control accuracy range is ±3. According to the flow monitoring results, the material flow is adjusted by controlling the regulating valve on the pipeline connecting the cracking tower and the heat exchanger to stabilize the flow near the set value. The opening of the regulating valve and the flow meet the following relationship: Q out =k f x, where k f is the flow coefficient, and x is the opening of the regulating valve. By adjusting the opening of the regulating valve, the flow of the material can be accurately controlled to ensure that the flow of the material entering the heat exchanger is stable near the set value. Flow direction control of materials from the heat exchanger to the packed tower

[0048] □The temperature of the material flowing out of the heat exchanger is monitored in real time by a temperature sensor. The monitored temperature is T out , unit is C.

[0049] Define the accuracy of temperature control as δ t , the calculation formula is: Where T set is the set temperature value in °C. The temperature control accuracy range is ±1.5 °C.

[0050] According to the temperature monitoring results, the material temperature is adjusted by controlling the regulating valve on the pipeline connecting the heat exchanger and the packed tower to stabilize the temperature near the set value. The opening of the regulating valve and the temperature satisfy the following relationship: T out =k t x+T min , where k t is the temperature coefficient, T min It is the lowest temperature when the regulating valve is fully closed. By adjusting the opening of the regulating valve, the temperature of the material can be accurately controlled to ensure that the temperature of the material is stable near the set value when entering the packed tower.

[0051] The large specific surface area and good wettability allow the raw material and the washing liquid to have a more sufficient contact area and better contact effect in the tower, significantly improving the mass transfer efficiency. Compared with the traditional packing structure, the contact time between the raw material and the washing liquid can be shortened, thereby improving the washing effect and helping to improve the purification quality of 1,3-butadiene. Through this precise mathematical model and the limited cooling efficiency range, the cooling effect of the heat exchanger can be more accurately controlled to ensure that the raw material is at the optimal temperature when entering the next process, reducing the impact of temperature fluctuations on the subsequent separation process, and improving the stability and purification effect of the entire washing system. For example, the temperature fluctuation range of the raw material when entering the packed tower can be controlled within, which is beneficial to the low-pressure flash separation process in the packed tower. The separation efficiency calculation model can intuitively reflect the separation effect of the packed tower on the gas, and combined with a specific value range, it can guide the optimization design of the packed tower and the adjustment of operating parameters. Through the improved gas distribution and separation structure, the gas-liquid separation in the packed tower is more thorough, the recovery rate of low-boiling point components (such as vinyl acetylene, ethyl acetylene, 1,3-butadiene, etc. absorbed by the solvent) is improved, and the purity of 1,3-butadiene is effectively improved. Through these precise mathematical models, the flow rate, pressure and concentration parameters at different positions in the cracking tower can be deeply analyzed to determine the optimal packing structure and tower diameter. According to the optimized cracking tower based on the simulation results, the residence time distribution of the raw materials in the tower is more uniform, which can improve the purification efficiency of 1,3-butadiene and reduce the risk of blockage caused by uneven flow of raw materials. This precise control strategy for the whole process can monitor and adjust the flow rate and temperature of the raw materials in real time to ensure that the raw materials flow stably and efficiently between the various equipment. By accurately controlling the flow rate and temperature, the production operation instability caused by fluctuations in raw material parameters, such as pressure fluctuations and blockages, can be effectively reduced, the reliability and production efficiency of the entire washing system are improved, and it helps to reduce energy consumption.

[0052] Embodiment 2

[0053] In the purification process of 1,3-butadiene, the flow rate of the washing liquid has a significant impact on the washing effect. The traditional PID control method may not achieve the ideal control effect when facing a complex nonlinear system. This embodiment proposes a washing liquid flow optimization method based on adaptive fuzzy logic control (AFLC), which aims to achieve more stable washing liquid flow control by adaptively adjusting the control parameters. System modeling: input variables, tower pressure, raw material flow, washing liquid flow, washing liquid temperature. Output variable: regulating valve opening. State variable: deviation of washing liquid flow from the set value, deviation change rate. Fuzzy rule base: define fuzzy sets: negative large (NB), negative medium (NM), negative small (NS), zero (ZO), positive small (PS), positive medium (PM), positive large (PB). Set fuzzy rules, for example: if the washing liquid flow deviation is negative large and the deviation change rate is negative large, the regulating valve opening increases a lot. If the washing liquid flow deviation is positive small and the deviation change rate is zero, the regulating valve opening is slightly reduced. Adaptive adjustment factors are introduced to dynamically adjust the weights of fuzzy rules and the shape of membership functions according to the system operation. Gradient descent method or genetic algorithm is used to optimize the parameters in the fuzzy rule base to improve control performance.

[0054] Initialization: Set the initial fuzzy rule base and membership function. Real-time monitoring: Collect the pressure, raw material flow, washing liquid flow and temperature in the tower in real time through sensors. Fuzzy reasoning: According to the current input variables, reason through the fuzzy rule base to obtain the fuzzy output of the control valve opening. Defuzzification: Convert the fuzzy output into a specific control valve opening value. Adaptive adjustment: According to the actual effect, dynamically adjust the parameters in the fuzzy rule base to optimize the control performance.

[0055] Efficiency comparison test, control group: traditional PID control method. Experimental group: adaptive fuzzy logic control method. Test conditions: same raw material flow, washing liquid flow setting value, tower pressure and temperature. Flow stability: measure the fluctuation range of washing liquid flow. Response time: record the time for the system to reach a stable state from the initial state. Energy consumption: calculate the total energy consumption during the system operation.

[0056] Flow stability: The fluctuation range of the washing liquid flow in the experimental group is significantly smaller than that in the control group, indicating that the AFLC method can better maintain flow stability. Response time: The response time of the experimental group is shorter, and the set value can be reached faster, which improves the dynamic performance of the system. Energy consumption: The total energy consumption of the experimental group is lower, indicating that the AFLC method can reduce energy consumption while ensuring the control effect.

[0057] The adaptive fuzzy logic control method showed excellent performance in the purification process of 1,3-butadiene, which could control the flow of washing liquid more stably and improve the response speed and energy efficiency of the system. Compared with the traditional PID control method, the AFLC method has significant advantages in flow stability, response time and energy consumption.

[0058] Embodiment 3

[0059] In the process of 1,3-butadiene purification, the gas distribution device in the packed tower has an important influence on the gas-liquid separation effect. Traditional design methods often rely on experience and it is difficult to take into account multiple optimization objectives. This embodiment proposes a gas distribution device design method based on multi-objective optimization (MOO), which aims to maximize the gas-liquid separation efficiency and minimize the pressure drop through mathematical modeling and optimization algorithms.

[0060] Objective function: maximum gas-liquid separation efficiency f1 and minimum pressure drop f2. Design variables: aperture, hole spacing, plate spacing, etc. of the gas distribution plate. Constraints: gas flow rate, liquid flow rate, tower diameter, etc.

[0061] NSGA-II (Non-dominated Sorting Genetic Algorithm II) was used for multi-objective optimization. Multiple non-dominated solutions were generated through crossover, mutation, and selection operations of the genetic algorithm to form the Pareto frontier. Computational fluid dynamics (CFD) software was used to simulate different design schemes to evaluate the gas-liquid separation efficiency and pressure drop. The simulation results were verified through experiments to select the optimal design scheme.

[0062] Control group: traditional design method. Experimental group: multi-objective optimization design method. Test conditions: same gas flow rate, liquid flow rate, tower diameter and operating conditions. Gas-liquid separation efficiency: measure the gas-liquid separation effect at the outlet of the packed tower. Pressure drop: record the pressure difference between the inlet and outlet of the packed tower. Energy consumption: calculate the total energy consumption during the operation of the system. Gas-liquid separation efficiency: the gas-liquid separation efficiency of the experimental group is significantly higher than that of the control group, indicating that the MOO method can better optimize the design of the gas distribution device. Pressure drop: the pressure drop of the experimental group is smaller, indicating that the optimized design reduces the resistance loss of the system while ensuring the separation effect. Energy consumption: the total energy consumption of the experimental group is lower, indicating that the optimized design not only improves the separation efficiency, but also reduces the operating cost.

[0063] Embodiment 4

[0064] The present embodiment provides a washing system for purifying 1,3-butadiene, which mainly includes a membrane separation module, a preheater, an intelligent control unit, and related connecting pipes and control devices. Membrane separation module: It is composed of a multi-layer selective permeable membrane. The raw material 1,3-butadiene enters from the feed port on one side of the membrane separation module, and the washing liquid enters from the feed port on the other side. In the membrane separation module, the difference in permeability of different substances to the membrane is utilized to achieve the separation of the raw material and impurities and the efficient contact washing with the washing liquid. Preheater: Preheat the raw material before entering the membrane separation module to make it reach a suitable temperature range to improve the membrane separation efficiency. Intelligent control unit: It integrates a variety of unreported algorithm models for real-time monitoring and control of the operating parameters of the system.

[0065] Membrane permeation rate prediction algorithm: Based on Fick's law and the diffusion coefficient of substances in the membrane, the following mathematical model was established to predict the permeation rate of different substances through the membrane:

[0066]

[0067] Among them, J i represents the permeation flux of substance i (unit: mol / (m 2 .s)), D ij is the diffusion coefficient of substance i in membrane material j (unit: m 2 / s), is the concentration gradient of substance i in the membrane along the permeation direction (unit: mol / m 4 ).

[0068] By real-time monitoring of the concentration of each component in the raw material and washing liquid, as well as the pressure difference on both sides of the membrane and other parameters, combined with the algorithm model, the permeation rate of different substances can be accurately predicted, thereby optimizing the operating conditions of the membrane separation module. Intelligent temperature control algorithm: Based on the heat transfer principle and the thermal balance equation of the system, the following mathematical model is established to automatically adjust the heating power of the preheater:

[0069] Q=mc P ΔT

[0070]

[0071] Where Q represents the required heat (unit: J), m is the mass flow rate of the raw material (unit: kg / s), c P is the specific heat capacity of the raw material (unit: J / (kg·K)), ΔT is the temperature difference that needs to be raised (unit: K), P is the heating power of the preheater (unit: W), η is the thermal efficiency of the preheater, and t is the heating time (unit: s)

[0072] The intelligent control unit calculates the required heating power based on the real-time monitored raw material temperature, flow rate and set target temperature using the above mathematical model, and automatically adjusts the operating parameters of the preheater to ensure that the temperature of the raw material entering the membrane separation module is stable within the optimal range.

[0073] Membrane permeability coefficient: For the permeability of each substance in a specific membrane material, its membrane permeability coefficient K is defined ij is the diffusion coefficient D ij The ratio of the film thickness L is (Unit: m / s). This parameter is used to measure the difficulty of a substance passing through the membrane and plays a key role in the control and optimization of the membrane separation process. Preheating temperature range: According to the physical and chemical properties of 1,3-butadiene and related impurities, the appropriate temperature range for the preheater to preheat the raw material is determined as T. min to T max , where T min =30℃, T max = 50°C. Within this temperature range, the membrane separation efficiency can reach a high level while avoiding adverse effects on raw materials and membrane materials due to excessively high or low temperatures.

[0074] A new type of complexing agent, calcium disodium ethylenediaminetetraacetate (CaNa 2EDTA), is added to the washing liquid, and its mechanism of action is as follows:

[0075] Forming stable complexes with impure metal ions: 1,3-Butadiene raw materials may contain trace amounts of metal impurity ions, such as iron and copper, which can affect product quality and subsequent processing. CaNa2EDTA can form stable complexes with these metal ions through coordination bonds, separating them from the raw materials and improving the purity of 1,3-Butadiene. Enhanced washing effect: The presence of CaNa2EDTA can change the surface tension and wettability of the washing liquid, making it easier to fully contact the raw materials, thereby improving the removal efficiency of impurities during the washing process.

[0076] In order to verify the synergistic effect of the system of this embodiment relative to the prior art (PID system), the following comparative tests were conducted: Purity improvement comparison: The system of this embodiment and the prior art system were used to purify the same batch of 1,3-butadiene raw materials with the same initial purity. After treatment, the purity of the product was analyzed by gas chromatography. The results showed that the purity of 1,3-butadiene after treatment by the system of this embodiment can reach more than 99.8%, while the purity after treatment by the prior art system is about 99.0%. The system of this embodiment has significantly improved the purity improvement compared with the prior art system, with an increase of about 0.8%. Energy consumption comparison: Under the same processing volume and processing time conditions, the energy consumption of the two systems is monitored. The system of this embodiment adopts a more accurate intelligent control algorithm and efficient membrane separation technology, and its energy consumption is significantly lower than that of the prior art system. Specifically, the energy consumption of the system of this embodiment is about 70% of the prior art system, showing obvious advantages in energy saving. Processing efficiency comparison: The processing efficiency is compared by recording the time required for the two systems to complete the purification of the same processing volume of 1,3-butadiene. The system of this embodiment has the advantages of rapid membrane separation process and intelligent regulation, and the processing time is shortened by about 30% compared with the prior art system, thereby greatly improving the production efficiency.

[0077] Embodiment 5

[0078] The washing system of this embodiment is mainly composed of an ion exchange resin column, a cooler, a dynamic optimization control unit, and supporting pipelines and control devices. Ion exchange resin column: filled with special ion exchange resin, the raw material 1,3-butadiene enters from the upper feed port of the ion exchange resin column, and the washing liquid enters from the lower feed port. In the column, the ion exchange resin removes impurity ions in the raw material through ion exchange, and cooperates with the washing liquid to achieve washing and purification of the raw material. Cooler: Cool the raw material flowing out of the ion exchange resin column to reduce its temperature to a suitable storage or subsequent processing temperature range. Dynamic optimization control unit: An unreported dynamic optimization algorithm model is used to monitor and adjust the various operating parameters of the system in real time to ensure that the system is in the best operating state. Ion exchange kinetic model: Based on the rate equation of the ion exchange reaction and the law of conservation of mass, the following mathematical model is established to describe the ion exchange process in the ion exchange resin column:

[0079]

[0080] Where q represents the adsorption amount of a certain ion on the resin (unit: mol / kg), t is the time (unit: s), and k is the ion exchange rate constant (unit: s -1 ), qeq is the equilibrium adsorption capacity of the resin for the ion (unit: mol / kg)

[0081] By real-time monitoring of the concentration and flow rate of each ion in the resin column, as well as the adsorption capacity of the resin, the model can be combined to accurately predict the progress of the ion exchange process, thereby optimizing the operating conditions of the ion exchange resin column, such as adjusting the feed rate, washing liquid flow rate, etc. Cooling power dynamic adjustment algorithm: Based on the heat conduction equation and the heat transfer characteristics of the cooler, the following mathematical model is established to dynamically adjust the cooling power of the cooler:

[0082] Q o =UAΔT m

[0083]

[0084] Among them, Q represents the heat that the cooler needs to take away (unit: J), and U is the total heat transfer coefficient of the cooler (unit: W / (m 2 ·K)), A is the heat transfer area of ​​the cooler (unit: m 2 ), ΔT m is the logarithmic mean temperature difference (unit: K),

[0085] P o is the cooling power of the cooler (unit: W), \(η o is the cooling efficiency of the cooler, \(t o is the cooling time (unit: s).

[0086]

[0087] Among them, q i and are the adsorption capacity of the resin for ion i and ion j (unit: mol / kg), c1 and c j $ are the concentrations of ion \(i and ion j in the solution (unit: (mol / L), respectively. This parameter is used to measure the ability of ion exchange resin to preferentially adsorb certain ions in the presence of different ions, and is crucial for optimizing the ion exchange process.

[0088] Cooling target temperature range: According to the physical and chemical properties of 1,3-butadiene and the subsequent processing requirements, the appropriate temperature range for the cooler to cool the raw material is determined to be T omin to T omax ,in Within this temperature range, the stability and processability of the raw materials are good.

[0089] A special surfactant, sodium dodecylbenzene sulfonate (SDBS), is added to the washing liquid, which has the following functions: Improve the wettability of the washing liquid: SDBS can reduce the surface tension between the washing liquid and 1,3-butadiene, making it easier for the washing liquid to spread on the surface of the raw material, thereby increasing the contact area between the washing liquid and the raw material and enhancing the washing effect. Promote the ion exchange process: The presence of SDBS can change the charge distribution and microenvironment on the surface of the ion exchange resin, which is beneficial to the interaction between the ion exchange resin and the impurity ions in the raw material, accelerate the ion exchange rate, and improve the impurity removal efficiency.

[0090] Purity improvement comparison: The same 1,3-butadiene raw material was purified by the system of this embodiment and the prior art system (PID control), and the product purity was analyzed by gas chromatography after treatment. The results show that the purity of 1,3-butadiene after treatment by the system of this embodiment can reach more than 99.9%, which is about 0.9% higher than the 99.0% purity after treatment by the prior art system, indicating that the system of this embodiment has obvious advantages in improving product purity. Energy consumption comparison: Under the same processing volume and processing time conditions, the energy consumption of the two systems is monitored. Due to the use of efficient ion exchange resin and precise dynamic optimization control algorithm, the energy consumption of the system of this embodiment is only about 60% of that of the prior art system, showing outstanding advantages in energy saving. Processing efficiency comparison: The processing efficiency is compared by recording the time required to purify the same processing volume of 1,3-butadiene. With its fast ion exchange process and intelligent control mechanism, the processing time of the system of this embodiment is shortened by about 40% compared with the prior art system, significantly improving production efficiency.

Claims

1. A washing system for purifying 1,3-butadiene, comprising a cracking tower, a heat exchanger and a packed tower, characterized in that: The raw material 1,3-butadiene enters from the feed port near the bottom of the cracking tower, and the washing liquid enters from the feed port near the top of the cracking tower, forming countercurrent contact in the cracking tower to ensure that the raw material and the washing liquid are fully in contact in the tower; the heat exchanger cools the raw material flowing out of the cracking tower; the heat exchanger adopts an advanced cooling algorithm to automatically adjust the cooling power according to the temperature and flow rate of the incoming raw material and the set cooling target temperature; the gas separation algorithm is adopted in the packed tower to achieve efficient 1,3-butadiene gas-liquid separation by adjusting the parameters of the 1,3-butadiene gas distribution device and the separation structure according to the physical properties and flow rate of the 1,3-butadiene gas.

2. The washing system according to claim 1, characterized in that: The packed tower uses a computational fluid dynamics simulation algorithm to simulate and analyze the flow of raw materials in the cracking tower, and adjusts the packing structure and tower diameter size according to the simulation results.

3. The washing system according to claim 1, characterized in that: The flow rate of the raw materials flowing out of the cracking tower is monitored by a flow sensor, and a flow control algorithm is used to automatically adjust the opening of the regulating valve according to the deviation between the monitored flow rate and the set value.

4. The washing system according to claim 1, characterized in that: The temperature of the raw materials flowing out of the heat exchanger is monitored by a temperature sensor, and a temperature control algorithm is used to automatically adjust the opening of the regulating valve according to the deviation between the monitored temperature and the set value.

5. The washing system according to claim 1, characterized in that: The feed rate, the flow rate of the washing liquid and the pressure parameters in the cracking tower are adjusted so that the raw materials have an average flow rate range.

6. The washing system according to claim 1, characterized in that: The pressure and concentration control algorithm is adopted to control the pressure and raw material concentration in the cracking tower by adjusting the feed rate, the temperature in the tower and the gas discharge rate parameters.

7. A washing method for purifying 1,3-butadiene, characterized in that: s1 System installation and commissioning: Install the cracking tower, heat exchanger, packing tower and the pipes and control devices connecting them according to the design requirements, and commission each device to ensure its normal operation; S2 Feeding operation: feed the raw material 1,3-butadiene from the feed port near the bottom of the cracking tower, and feed the washing liquid from the feed port near the top of the cracking tower; S3 Raw material processing in the cracking tower: In the cracking tower, the raw material flows upward under the action of gravity and fillers, and fully contacts with the washing liquid flowing downward to carry out the washing process. The operating conditions are adjusted by monitoring the flow rate, pressure and concentration parameters of 1,3-butadiene gas in the tower; s4 Control of the flow of raw materials to the heat exchanger: The flow rate of raw materials flowing out of the cracking tower is monitored in real time through the flow sensor. According to the requirements of flow control accuracy, the flow rate of raw materials is adjusted through the regulating valve to stabilize it at the set value; s5 Control of the flow of raw materials to the packed tower: The temperature of the raw materials flowing out of the heat exchanger is monitored in real time by a temperature sensor. According to the requirements of temperature control accuracy, the raw material temperature is adjusted by a regulating valve to stabilize it at the set value; s6 system operation monitoring and maintenance: During the operation of the entire washing system, the operating parameters of each device and the flow direction, temperature and pressure parameters of the raw materials are continuously monitored; the equipment is regularly maintained and serviced to ensure the stable operation of the system.

8. The washing method according to claim 7, characterized in that: Membrane permeation rate prediction algorithm is used: Based on Fick's law and the diffusion coefficient of substances in the membrane, the following mathematical model is established to predict the permeation rate of different substances through the membrane: Among them, J i represents the permeation flux of substance i (unit: mol / (m 2 .s)), D ij is the diffusion coefficient of substance i in membrane material j (unit: is the concentration gradient of substance i in the membrane along the permeation direction (unit: mol / m 4 ).

9. The washing method according to claim 7, characterized in that: Adopt intelligent temperature control algorithm: According to the heat transfer principle and the thermal balance equation of the system, the following mathematical model is established to automatically adjust the heating power of the preheater: Q=nv p ΔT Where Q represents the required heat (unit: J), m is the mass flow rate of the raw material (unit: kg / s), c p is the specific heat capacity of the raw material (unit: J / (kg·K)), ΔT is the temperature difference that needs to be raised (unit: K), P is the heating power of the preheater (unit: W), η is the thermal efficiency of the preheater, and t is the heating time (unit: s).

10. The washing method according to claim 7, characterized in that: Adopt cooling power dynamic adjustment algorithm: According to the heat conduction equation and the heat transfer characteristics of the cooler, the following mathematical model is established to dynamically adjust the cooling power of the cooler: Q c =UAΔT m Among them, Q represents the heat that the cooler needs to take away (unit: J), and U is the total heat transfer coefficient of the cooler (unit: W / (m 2 ·K)), A is the heat transfer area of ​​the cooler (unit: m 2 ), ΔT m is the logarithmic mean temperature difference (unit: K), P c is the cooling power of the cooler (unit: W), \(η o Q is the cooling efficiency of the cooler, \(t o S is the cooling time (unit: s).

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