Method for controlling regeneration of an SCR catalyst, loading and heat treatment

Abstract

The application discloses an SCR catalyst regeneration loading and heat treatment control method, and belongs to the technical field of industrial process automation and environmental protection equipment, which can at least partially solve the problems of low loading precision, poor batch consistency, high resource consumption and dependence on artificial experience in the existing SCR catalyst regeneration process. The application comprises the following steps: performing multi-parameter detection on the catalyst to be regenerated and generating digital identity data; matching a process formula package based on the digital identity data, generating impregnation liquid preparation instructions and a heat treatment curve; collecting weight-time data in real time during the impregnation process and dynamically determining the impregnation end point; online monitoring and closed-loop adjusting the concentration of the impregnation liquid; performing drying and calcination of the segmented program temperature control according to the heat treatment curve; and online purifying the waste liquid and recycling it to the impregnation process. The application realizes closed-loop control of the whole process of catalyst regeneration loading and heat treatment, and significantly improves the active component reloading precision and product consistency.

Description

Technical Field

[0001] This invention belongs to the field of industrial process automation and environmental protection equipment technology, specifically relating to a method for controlling the regeneration loading and heat treatment of SCR catalysts. Background Technology

[0002] Selective catalytic reduction (SCR) denitrification catalysts are widely used in flue gas denitrification systems of thermal power plants. After a certain period of operation, these catalysts become deactivated due to poisoning, blockage, or loss of active components, requiring regeneration to restore their denitrification activity. In the catalyst regeneration process, the loading of active components and subsequent drying and calcination are the core steps determining the performance of the regenerated catalyst. The accuracy of the loading and the heat treatment process directly affect the activity, selectivity, mechanical strength, and service life of the regenerated product.

[0003] However, existing catalyst regeneration production lines generally have the following shortcomings in the aforementioned core processes: In terms of equipment integration, most regeneration lines adopt a segmented operation mode with independent equipment. The impregnation tank, drying kiln and calcination furnace are transferred between each other by overhead crane or forklift. This causes the catalyst to be exposed to the air for a long time in a humid state after loading, which makes it easy to adsorb dust, deliquinate or migrate active components. At the same time, the production cycle is not continuous and the efficiency is low.

[0004] In terms of process control, the impregnation process often employs an open-loop control method with fixed time and concentration. The concentration of the impregnation solution continuously decreases during use and cannot be monitored and compensated for in real time, leading to significant differences in the loading of different catalyst modules within the same batch. The drying and calcination processes rely on preset, simple temperature control curves, lacking detailed control over the uniformity of the temperature field and the composition of the atmosphere within the furnace, which can easily lead to catalyst cracking or sintering of active components.

[0005] In terms of resource utilization, single-use impregnation solutions are usually treated as hazardous waste after the load is completed. Because they contain precious metals such as vanadium and tungsten, not only is the disposal cost high, but it also wastes chemical resources.

[0006] In terms of quality traceability, due to the lack of full-process data collection and recording, it is difficult to accurately locate the problematic process and cause when product quality fluctuates, and it is even more impossible to achieve continuous optimization of process parameters through data-driven approaches.

[0007] Therefore, there is an urgent need for a control method that can achieve closed-loop control of the entire process of catalyst regeneration loading and heat treatment, high accuracy of active component reloading, good product consistency and high resource utilization. Summary of the Invention

[0008] The present invention aims to solve at least one of the technical problems existing in the prior art, and to provide a method for controlling the regeneration loading and heat treatment of SCR catalyst.

[0009] To achieve the above objectives, the present invention provides a method for controlling the regeneration loading and heat treatment of an SCR catalyst, comprising: Multi-parameter detection data is collected for the catalyst to be regenerated, and digital identity data of the catalyst to be regenerated is generated based on the multi-parameter detection data. Based on the digital identity data, a target process formula package is matched from the process knowledge base, and an impregnation liquid preparation instruction is generated according to the impregnation liquid formula parameters in the target process formula package. Impregnation is performed based on the impregnation solution preparation instructions. During the impregnation process, the weight-time data of the catalyst to be regenerated is collected in real time, and the impregnation endpoint is dynamically determined based on the weight-time data. Furthermore, the concentration of the impregnation solution is monitored online during the impregnation process, and the concentration of the impregnation solution is adjusted in a closed-loop manner based on the deviation between the measured concentration value and the target concentration value. After the impregnation endpoint is determined, the catalyst to be regenerated is subjected to segmented, temperature-controlled drying and calcination treatments sequentially according to the heat treatment curve parameters in the target process formulation package; and The waste liquid generated during the impregnation process is purified online, and the purified liquid is adjusted to the target concentration value and then recycled back to the impregnation process.

[0010] Furthermore, the multi-parameter detection data includes active component content data, water content data, and pore patency data, and the acquisition of the multi-parameter detection data includes: The content distribution data of vanadium, tungsten, sulfur, calcium and potassium elements were obtained by scanning the end face of the catalyst to be regenerated using X-ray fluorescence spectroscopy, and these data were used as the content data of the active components. The overall moisture content data of the catalyst to be regenerated was obtained by near-infrared moisture detection. Images of the pores inside the catalyst to be regenerated are acquired and the proportion of blocked area is identified through image analysis to obtain the pore patency data. The content distribution data, the moisture content data, and the pore patency data are aggregated to generate the digital identity data.

[0011] Furthermore, the matching of the target process recipe package from the process knowledge base based on the digital identity data includes: Based on the loss rate and inactivation type information of the active components in the digital identity data, the process formula package is compared with multiple pre-stored process formula packages in the process knowledge base, and the process formula package that meets the preset matching conditions is selected as the target process formula package. The impregnation solution formulation parameters in the target process formulation package include the target metal ion concentration, impregnation solution temperature, and additive addition ratio of each impregnation solution; the heat treatment curve parameters include the target temperature, holding time, heating rate, and atmosphere composition of each temperature zone.

[0012] Furthermore, the step of dynamically determining the immersion endpoint based on the weight-time data includes: The weight value of the catalyst to be regenerated in the impregnation solution is continuously collected at a preset sampling period to form the weight-time data. Based on the adsorption kinetics model, the instantaneous weight gain rate is calculated according to the weight-time data; When the instantaneous weight gain rate drops below a preset percentage threshold of the initial weight gain rate and remains below that threshold for a preset duration, the immersion is determined to have reached its endpoint. The preset percentage threshold is a set value within the range of 5% to 15% of the initial weight gain rate, and the preset duration is a set value within the range of 2 minutes to 5 minutes.

[0013] Furthermore, the online monitoring of the concentration of the impregnation solution includes: The concentration of target metal ions in the impregnation solution was detected by spectrometry, and the total ionic strength of the impregnation solution was detected by conductivity method. The two detection results were combined to obtain the measured concentration value. When the measured concentration value is lower than the target concentration value, a stock solution of a preset concentration is added to the impregnation solution; when the measured concentration value is higher than the target concentration value, a diluent is added. The closed-loop regulation maintains the concentration of the impregnation solution at the target concentration value. Within.

[0014] Furthermore, when the target process formulation package includes a multi-component gradient loading scheme, the impregnation process is executed as follows: The catalyst to be regenerated is sequentially placed into multiple impregnation solutions and loaded with different active components. Between two adjacent impregnations, the catalyst to be regenerated is subjected to a controlled atmosphere dredging treatment. For each of the multiple immersions, the acquisition of weight-time data, the determination of the immersion endpoint, and the closed-loop adjustment of the immersion solution concentration are performed independently.

[0015] Furthermore, the segmented temperature-controlled drying and calcination processes include: During the drying stage, the temperature is gradually increased in multiple temperature zones according to the drying temperature range in the heat treatment curve parameters, and the airflow humidity in each temperature zone is gradually reduced. During the transition phase, the temperature is increased from the drying termination temperature to the calcination start temperature at the set heating rate in the heat treatment curve parameters. During the roasting stage, the oven is roasted at a constant temperature according to the roasting temperature range and holding time in the heat treatment curve parameters. The oxygen content during the roasting stage is controlled within a set range according to the atmosphere composition in the heat treatment curve parameters. Throughout the drying and roasting processes, real-time temperature and atmosphere data within the furnace are collected and fed back to adjust the heating power of each temperature zone.

[0016] Furthermore, the parameters of the heat treatment curve are adaptively adjusted according to the digital identity data, and the adjustment method is as follows: When the alkali metal content in the digital identity data is higher than the preset alkali metal threshold, the holding time of the roasting stage is increased and the atmosphere composition is adjusted. When the load recorded in the digital identity data exceeds a preset load threshold, the heating rate of the drying stage is reduced.

[0017] Furthermore, the online purification of the waste liquid includes: The waste liquid is subjected to filtration treatment to remove particulate matter, ion exchange treatment to remove impurity ions, and membrane concentration treatment to separate the clear liquid from the concentrated residue. The concentration of the effective components in the clear liquid is detected online. The clear liquid is mixed with fresh mother liquor according to the calculated ratio to the target concentration value and then transported back to the corresponding impregnation process. The proportion of concentrated residual liquid generated by the membrane concentration treatment to the total waste liquid does not exceed the preset residual liquid proportion.

[0018] Furthermore, the method also includes quality prediction and feedforward control, wherein the quality prediction and feedforward control includes: Before the catalyst to be regenerated enters the impregnation process, the elemental distribution and theoretical performance indicators after loading are predicted using a digital twin model based on the digital identity data; When the theoretical performance index is lower than the preset performance threshold, feedforward correction is performed on the impregnation liquid formulation parameters or heat treatment curve parameters in the target process formulation package. After the catalyst to be regenerated has undergone heat treatment, the sampled data is compared with the theoretical performance indicators, and the parameters in the digital twin model are automatically corrected based on the comparison deviation.

[0019] The beneficial effects of this invention are as follows: This invention collects multi-parameter detection data on the catalyst to be regenerated and generates digital identity data, providing a quantitative basis for subsequent process decisions, realizing personalized regeneration treatment tailored to the material, and avoiding the one-size-fits-all, crude operation in traditional processes.

[0020] This invention replaces the traditional fixed-time open-ring impregnation method by dynamically determining the impregnation endpoint based on the weight-time curve. This allows catalysts with different pore states and adsorption characteristics to achieve optimal loading, and improves the accuracy of active component loading compared to traditional methods. Upgraded to Within.

[0021] This invention ensures that the concentration of the impregnation solution remains stable throughout the entire production process by monitoring the concentration online and implementing closed-loop compensation adjustment, eliminating the concentration drift problem within and between batches, and significantly improving the consistency of product performance.

[0022] This invention achieves an effective component recovery rate of over 95% through online purification and recycling of waste liquid, ultimately producing only a small amount of concentrated residue. This significantly reduces chemical consumption and waste liquid disposal costs, achieving near-zero emission green production.

[0023] This invention uses digital twin models for quality prediction and feedforward control to predict the performance of the catalyst after loading and optimize process parameters in advance before it enters the impregnation process. This achieves the prevention of quality problems rather than the remediation afterward, and further improves the overall yield. Attached Figure Description

[0024] Figure 1 This is a flowchart illustrating the overall process of controlling the SCR catalyst regeneration loading and heat treatment according to an embodiment of the present invention. Figure 2 This is a schematic diagram of the multi-parameter detection and digital identity data generation process according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the weight-time curve and endpoint determination logic during the impregnation process according to an embodiment of the present invention; Figure 4 This is a schematic diagram illustrating the closed-loop control principle of the impregnation solution concentration in an embodiment of the present invention. Figure 5 This is a schematic diagram of the segmented temperature-controlled drying-calcination heat treatment curve according to an embodiment of the present invention; Figure 6 This is a schematic diagram of the online purification and recycling process for waste liquid according to an embodiment of the present invention; Figure 7 This is a schematic diagram of the digital twin model quality prediction and feedforward control architecture according to an embodiment of the present invention. Detailed Implementation

[0025] To make the objectives, technical solutions, and beneficial effects of this application clearer, the following detailed description, in conjunction with the accompanying drawings and specific embodiments, further illustrates this application. It should be understood that the specific embodiments described in this specification are merely for explaining this application and are not intended to limit it.

[0026] The SCR catalyst regeneration loading and heat treatment control method described in this invention is applicable to the regeneration of honeycomb or plate-type selective catalytic reduction denitrification catalyst modules. This method achieves intelligent control of the core catalyst regeneration process through closed-loop management of the entire process, including catalyst module state sensing, adaptive optimization of process parameters, dynamic determination of impregnation endpoint, closed-loop control of impregnation solution concentration, programmed heat treatment, and waste liquid recycling.

[0027] Example 1 This embodiment uses the treatment of deactivated catalyst in a large thermal power plant operating under high-sulfur coal conditions as an example. The catalyst module is a standard honeycomb type, with dimensions of [missing information]. mm. The production line in this embodiment needs to continuously process 30 catalyst modules of the same batch.

[0028] See Figure 1 The control method in this embodiment includes the following steps: Step S1: Multi-parameter detection and digital identity data generation.

[0029] See Figure 2 The catalyst modules to be regenerated enter the testing station from the cleaning and drying line via a roller conveyor. Before entering the testing station, an RFID reader scans the RFID tag on the catalyst module to read the batch number and historical operating information of the module.

[0030] After the catalyst module is automatically positioned at the online testing station, the multi-parameter testing device performs the following testing operations in sequence.

[0031] Data acquisition of active component content: The micro-area X-ray fluorescence spectrometer scanned the windward and leeward sides of the catalyst module separately, with a scanning time of 120 seconds per side, for a total of 240 seconds. The detection range of the X-ray fluorescence spectrometer covers five elements: vanadium, tungsten, sulfur, calcium, and potassium.

[0032] In this embodiment, the test results show that the average vanadium pentoxide content on the windward side of the catalyst module is 0.33%, the average vanadium pentoxide content on the leeward side is 0.37%, and the overall average vanadium pentoxide content is 0.35%; the overall average tungsten trioxide content is 2.2%; and the sulfur element, measured in the form of sulfur trioxide, has a content of 6.5%. Based on the initial vanadium pentoxide content of 0.55% and the initial tungsten trioxide content of 3.4% of the fresh catalyst, the vanadium activity loss rate is calculated to be 36%, and the tungsten activity loss rate is 35%.

[0033] Moisture content data acquisition: A near-infrared moisture analyzer scans the outer surface of the catalyst module in a non-contact manner, completing the overall moisture content detection within 30 seconds. In this embodiment, the detection results show that the volumetric moisture content of the catalyst module is 1.2%, meeting the feed standard of less than 2%.

[0034] Data acquisition for pore patency: An industrial endoscope is automatically inserted into the pores along a preset grid path on the catalyst module end face, capturing one image at each detection location. In this embodiment, 16 detection locations are set, with a 3-second capture time at each location, for a total detection time of 48 seconds. The captured images are transmitted to an image analysis algorithm module, which identifies the blocked areas in each pore and calculates the blocked area ratio using edge detection and area statistics methods. The weighted average of the blocked area ratios at the 16 detection locations yields the overall pore patency rate. In this embodiment, the pore patency rate is 98%.

[0035] Digital Identity Data Generation: The above-mentioned active component content distribution data, water content data, and pore patency data, along with the batch number and historical operation information read by the RFID reader, are combined to generate the digital identity data of the catalyst module. The core conclusions of the digital identity data include the determination of the deactivation type and the assessment of the loss rate of each active component. In this embodiment, the digital identity data of the catalyst module shows: "Sulfur poisoning dominates deactivation, tungsten loss rate 35%, vanadium loss rate 36%, good physical structure." This digital identity data is uploaded to the central control system database and bound to the unique identifier of the catalyst module.

[0036] Step S2: Matching the process formulation package and preparing the impregnation solution.

[0037] After receiving the digital identity data generated in step S1, the decision engine of the central control system compares the key parameters with multiple pre-stored process formulation packages in the process knowledge base. The process knowledge base stores standardized process formulation packages for different types of inactivation and different degrees of loss of active components. Each process formulation package contains two parts: impregnation solution formulation parameters and heat treatment curve parameters.

[0038] The comparison process employs a multi-dimensional weighted scoring method. The scoring dimensions include the matching degree of deactivation type, vanadium loss rate, tungsten loss rate, water content, and pore patency. The weights for each dimension are set to 0.30, 0.25, 0.25, 0.10, and 0.10, respectively. For each dimension, the degree of matching between the corresponding parameter value in the digital identity data and the corresponding parameter range in the process formulation package is calculated, yielding a single-item score for that dimension. The single-item scores for each dimension are multiplied by their corresponding weights and then summed to obtain the comprehensive matching score for the process formulation package. The process formulation package with the highest comprehensive matching score is selected as the target process formulation package.

[0039] In this embodiment, the decision engine matched the process formulation package numbered GP-07, named "High-sulfur coal - Tungsten-vanadium gradient loading - Medium-temperature roasting" scheme. The impregnation solution formulation parameters of this target process formulation package are as follows: tungsten solution in the first impregnation tank, with a target tungsten concentration of 120 g / L (calculated as tungsten trioxide), a liquid temperature of 40°C, and containing 0.8% citric acid as a dispersant; vanadium solution in the second impregnation tank, with a target vanadium concentration of 25 g / L (calculated as vanadium pentoxide), a liquid temperature of 30°C, and containing 2.0% oxalic acid, 1.5% tartaric acid, and 0.4% cerium nitrate as additives.

[0040] The central control system generates impregnation solution preparation instructions based on the above impregnation solution formula parameters and issues them to the central batching station. The central batching station is equipped with ammonium tungstate concentrate storage tanks, ammonium metavanadate concentrate storage tanks, citric acid solution storage tanks, oxalic acid solution storage tanks, tartaric acid solution storage tanks, cerium nitrate solution storage tanks, and deionized water storage tanks. All storage tanks are equipped with level sensors, temperature sensors, and precision metering pumps.

[0041] Upon receiving the mixing instruction, the batching station automatically initiates the preparation process of the tungsten solution in the first impregnation tank. The metering pump sequentially draws materials from the ammonium tungstate concentrate storage tank and the citric acid storage tank according to the volume ratio specified in the instruction, while simultaneously adding deionized water to the mixing tank. The mixing tank is equipped with a stirring device and a temperature control jacket. The stirring device operates at 300 rpm to ensure uniform mixing, and the temperature control jacket heats the liquid to 40°C and maintains it. After mixing, the liquid is pumped into the first impregnation tank through pipelines. At this time, the online concentration monitor in the first impregnation tank is activated, using ultraviolet-visible spectroscopy to detect the tungsten ion concentration. When the detected concentration stabilizes at... Once the g / L value is within the range, the system confirms that the first impregnation tank is ready.

[0042] The vanadium solution for the second impregnation tank was prepared using the same method. A metering pump drew materials proportionally from the ammonium metavanadate concentrate tank, oxalic acid tank, tartaric acid tank, and cerium nitrate tank, adding deionized water as needed. The mixture was then heated to 30°C in a mixing tank before being pumped into the second impregnation tank. An online concentration monitor confirmed that the vanadium ion concentration remained stable at [value missing]. Once the g / L range is reached, the second impregnation tank is ready.

[0043] Step S3: Impregnation process execution and dynamic determination of endpoint.

[0044] See Figure 3 In this embodiment, a gradient loading scheme of tungsten first and then vanadium is adopted, and the catalyst module needs to be loaded in two impregnation tanks in sequence.

[0045] First Impregnation – Tungsten Component Loading: A robotic arm grasps the catalyst module and vertically immerses it in the tungsten impregnation solution of the first impregnation tank. The tank body is placed on a precision weighing sensor with a range of 500 kg and a resolution of 10 g. After the catalyst module is fully immersed, the weighing system is zeroed and begins continuously recording weight-time data at a sampling period of 1 second. Simultaneously, a microporous bubbling device at the bottom of the tank is activated, introducing nitrogen gas into the liquid at a rate of 2 L per minute, generating tiny bubbles to gently agitate the liquid and ensure that the concentration and temperature of the impregnation solution remain uniform throughout the tank.

[0046] During the impregnation process, the central control system processes weight-time data in real time. The system first records the average weight gain rate from the first minute to the third minute after the start of impregnation as the initial weight gain rate. .

[0047] In this embodiment, the initial weight gain rate The rate was 85g per minute. The system then continuously calculated the instantaneous weight gain rate at each sampling time. The calculation method is to divide the weight difference between two adjacent sampling times by the time interval: ; in, for Weight value at time, The sampling period is 1 second. To eliminate instantaneous fluctuations in the weighing sensor, the system takes a moving average of 10 consecutive instantaneous weight gain rate values ​​to obtain a smoothed weight gain rate. .

[0048] In this embodiment, the preset percentage threshold is set to 10% of the initial weight gain rate, that is, when The endpoint timing begins when the weight gain rate reaches 8.5 g / min. The preset duration is set to 3 minutes. At the 35th minute of immersion, the smooth weight gain rate first drops below 8.5 g / min. The system then starts the endpoint timing, continuously monitoring whether the weight gain rate remains below the threshold. From the 35th to the 38th minute, the smooth weight gain rate remains between 6.2 g / min and 8.3 g / min, below the threshold of 8.5 g / min. At the 38th minute, the 3-minute duration condition is met, and the system triggers the "first immersion complete" signal.

[0049] The robotic arm removes the catalyst module from the first impregnation tank and transfers it to a sealed drying tunnel. The drying tunnel is filled with a nitrogen stream at 75°C and a dew point of -25°C. The catalyst module remains in the drying tunnel for 5 minutes to remove excess droplets adhering to the module surface and pore openings.

[0050] Second impregnation – vanadium component loading: After draining, a robotic arm transfers the catalyst module to the second impregnation tank and immerses it in the vanadium impregnation solution. The second impregnation tank is also equipped with a precision weighing sensor and a microporous bubbling device, performing the same weight-time data acquisition and endpoint determination logic as the first impregnation.

[0051] In this embodiment, the initial weight gain rate of the second immersion is 62g per minute, and the preset percentage threshold is also set to 10% of the initial weight gain rate, i.e., the threshold is 6.2g / min. The preset duration is also set to 3 minutes. The endpoint determination timing starts at the 22nd minute of immersion, and the duration condition is met at the 25th minute, triggering the "second immersion complete" signal.

[0052] After the catalyst module is removed from the second impregnation tank, it re-enters the sealed asphalt tunnel for final asphalt treatment, with a dwell time of 8 minutes.

[0053] Step S4: Closed-loop control of impregnation solution concentration.

[0054] See Figure 4 Throughout the entire impregnation process in step S3, the closed-loop control of the impregnation solution concentration operates synchronously.

[0055] The execution process of closed-loop control is illustrated using the tungsten solution in the first impregnation tank as an example. An online UV-Vis concentration monitor and an online conductivity monitor are installed on the circulation pipeline of the first impregnation tank. The online UV-Vis concentration monitor determines the tungsten ion concentration by detecting the intensity of the characteristic absorption peak of tungstate ions near 250 nm, with a detection cycle of 30 seconds. The online conductivity monitor reflects the total ionic strength by measuring the conductivity value of the impregnation solution, also with a detection cycle of 30 seconds.

[0056] The central control system fuses the tungsten ion concentration detection value from ultraviolet-visible spectroscopy and the total ion strength detection value from conductivity. The fusion method uses the ultraviolet-visible spectroscopy value as the primary detection value and the conductivity value as an auxiliary calibration value. When the deviation between the two values ​​is within a preset range, the ultraviolet-visible spectroscopy value is taken as the final measured concentration value. When the deviation exceeds the preset range, the system issues a sensor malfunction alarm, suspends the immersion operation, and awaits manual confirmation.

[0057] In this embodiment, the target concentration of the tungsten solution in the first impregnation tank is 120 g / L, and the preset concentration deviation range is [missing information]. That is, the measured concentration should be maintained at g / L to Between g / L. After the first catalyst module completed impregnation, the online concentration monitor detected that the tungsten concentration in the bath had dropped from 120 g / L to 115 g / L, exceeding the allowable deviation range. The central control system immediately calculated the volume of ammonium tungstate concentrate that needed to be added. Assuming the concentrate concentration is 300 g / L, the current bath volume is 500 L, the current concentration is 115 g / L, and the target concentration is 120 g / L, the required replenishment volume is... satisfy: ; Solving L. The system instructs the metering pump to add 13.9L of ammonium tungstate concentrate to the circulation pipeline. During the addition process, the concentrate is evenly mixed into the tank solution by the circulation pump. Approximately 2 minutes after the addition is completed, the online concentration monitor detects that the concentration has recovered to 119.8g / L, within the target concentration deviation range. The system confirms that the concentration adjustment is complete. The first impregnation tank returns to the ready state, ready to receive the next catalyst module.

[0058] The closed-loop control of the vanadium solution concentration in the second impregnation tank adopts the same logic and process. The target concentration is 25 g / L, and the preset concentration deviation range is [missing information]. That is, the measured concentration should be maintained at g / L to Between g / L. If the concentration is too low, add concentrated ammonium metavanadate solution; if it is too high, add deionized water.

[0059] Step S5: Segmented program temperature-controlled heat treatment.

[0060] See Figure 5 After being drained, the catalyst module is smoothly pushed into the feed end of the integrated tunnel furnace by the pusher mechanism at the furnace front. The integrated tunnel furnace adopts a single-tunnel through-type design, with the front section being the drying zone and the rear section being the roasting zone. The furnace body uses multi-zone independent PID temperature control, with each temperature zone equipped with an independent heating element and a strong convection circulating fan. Thermocouple temperature sensors, oxygen content sensors, and humidity sensors are installed at multiple cross-sectional locations inside the furnace, and the data is fed back to the central control system in real time at a frequency of once every 5 seconds.

[0061] In this embodiment, the heat treatment curve corresponding to the GP-07 formulation package is loaded, and the specific parameters are as follows.

[0062] The drying stage consists of three temperature zones. The first zone has a target temperature of 80℃, a holding time of 30 minutes, and an airflow humidity setting of 60% relative humidity. The second zone has a target temperature of 100℃, a holding time of 60 minutes, and an airflow humidity setting of 40% relative humidity. The third zone has a target temperature of 120℃, a holding time of 120 minutes, and an airflow humidity setting of 20% relative humidity. During the drying stage, the heating rate between each zone is set to 1℃ per minute.

[0063] The heating rate during the transition phase was set at 1.5°C per minute, increasing from the drying termination temperature of 120°C to the calcination initiation temperature of 250°C. This transition phase lasted approximately 87 minutes.

[0064] The roasting stage consists of two parts: a pre-oxidation zone and a constant-temperature roasting zone. The target temperature in the pre-oxidation zone is 250℃, with a holding time of 30 minutes, and the oxygen content is controlled between 18% and 20%. The target temperature in the constant-temperature roasting zone is 380℃, with a heating rate of 2℃ per minute from 250℃ to 380℃, and a constant-temperature roasting time of 240 minutes, with the oxygen content controlled between 18% and 20%.

[0065] Throughout the heat treatment process, the central control system collects readings from all temperature sensors in each temperature zone every 5 seconds, calculating the average temperature and temperature uniformity of each cross-section. The control objective for temperature uniformity is to ensure that the temperature difference within the same cross-section does not exceed [a certain value]. ℃. When the temperature difference at a certain cross-section exceeds At a temperature of ℃, the system automatically adjusts the power output of each heating element and the speed of the circulating fan within that temperature zone until the temperature difference returns to the allowable range.

[0066] Meanwhile, the system continuously monitors the oxygen content in the roasting zone. When the oxygen content is below 18%, the opening of the intake valve is increased to replenish fresh air; when the oxygen content is above 20%, the opening of the intake valve is decreased and the amount of inert gas supplied is appropriately increased.

[0067] The catalyst module moves at a constant speed inside the tunnel furnace, passing through each temperature zone sequentially according to a set time. The total residence time from entering the furnace to exiting is approximately 480 minutes. After exiting the furnace, the catalyst module enters a natural cooling zone, where it is cooled to ambient temperature before being conveyed out.

[0068] Step S6: Online purification and recycling of waste liquid.

[0069] See Figure 6 During the production processes in steps S3 and S4, a portion of the waste liquid in the impregnation tank is periodically discharged into the waste liquid collection tank, while an equal amount of fresh liquid is added to maintain a stable total liquid volume in the tank. The discharge cycle is once after processing every 5 catalyst modules, with each discharge amount being 10% of the total liquid volume in the tank. In addition, the dripping liquid collected in the draining tunnel is also discharged into the waste liquid collection tank.

[0070] The waste liquid in the waste liquid collection tank is treated by an online purification system. The online purification system adopts a three-stage series process.

[0071] The first stage is filtration. The waste liquid first passes through a precision filter with a pore size of 1 micrometer to remove solid suspended matter such as catalyst powder and dust particles. The filtered liquid then enters the second stage of treatment.

[0072] The second stage is ion exchange treatment. The filtered liquid is passed through an ion exchange column. The ion exchange resin used is a strong acid cation exchange resin with selective adsorption capacity for alkali metal ions and alkaline earth metal ions. This resin can effectively remove impurity ions such as potassium, sodium, and calcium from the waste liquid, while retaining effective components such as vanadate and tungstate ions. The ion exchange column has a processing capacity of 100L per hour, and the resin regeneration cycle is 500L of waste liquid treated before regeneration with hydrochloric acid.

[0073] The third stage is membrane concentration. The liquid after ion exchange treatment enters the nanofiltration membrane concentration system. The nanofiltration membrane has a molecular weight cutoff of 200 to 300 Daltons, effectively retaining large molecular weight ions such as vanadate and tungstate, while allowing water molecules and small molecular weight impurities to pass through. The membrane concentration system separates the waste liquid into purified liquid and concentrated residue. The purified liquid accounts for more than 95% of the total waste liquid, while the concentrated residue accounts for no more than 5%.

[0074] Concentration adjustment and reuse of purified solution: The purified solution is collected in a concentration adjustment tank. An online analyzer detects the concentrations of vanadium and tungsten, the effective components, in the solution. In this embodiment, the detection results show that the tungsten concentration in the purified solution is 15 g / L and the vanadium concentration is 3 g / L.

[0075] For tungsten liquid reuse, the system calculates the volume of fresh ammonium tungstate concentrate that needs to be added to ensure the tungsten concentration in the reused liquid reaches the target value of 120 g / L. Let the volume of the purified liquid be... The concentration is The concentration of the fresh concentrate is The target concentration is The volume of concentrate to be added is... satisfy: ; In this embodiment, L, g / L, g / L, g / L, calculated L. The system automatically controls the metering pump to replenish and mix the concentrate. After the concentrate is mixed evenly, it is transported to the spare liquid storage tank in the first impregnation tank.

[0076] The same calculation logic is used for vanadium solution reuse. The vanadium concentration in the purified solution is 3 g / L, the concentration of ammonium metavanadate concentrate is 100 g / L, and the target concentration is 25 g / L. The calculation shows that 14.7 L of concentrate needs to be added for every 50 L of purified solution. The prepared reuse solution is then transferred to the spare solution storage tank in the second impregnation tank.

[0077] After collection, the concentrated residual liquid is entrusted to a qualified hazardous waste disposal unit for treatment. Since the volume of the concentrated residual liquid accounts for less than 5% of the total waste liquid, the amount of hazardous waste to be disposed of is reduced by more than 95% compared to the traditional method of treating all waste liquid.

[0078] Step S7: Quality prediction and feedforward control.

[0079] See Figure 7 A digital twin model was deployed in the central control system. This digital twin model integrates the mass transfer equation in the porous catalyst medium, the adsorption kinetics equation of the impregnation liquid, and the heat transfer and chemical reaction kinetics equations in the heat treatment process, and uses historical production data to train and correct the model parameters.

[0080] Before each catalyst module enters the impregnation process, the central control system inputs the module's digital identity data into a digital twin model. Based on the input data and the parameters of the currently matched target process formulation package, the digital twin model predicts the theoretical performance indicators of the catalyst module after loading and heat treatment, such as vanadium content, tungsten content, specific surface area, and denitrification efficiency.

[0081] In this embodiment, the digital twin model predicts that the theoretical vanadium pentoxide content of the first catalyst module after treatment with the GP-07 formulation is 0.50%, the theoretical tungsten trioxide content is 3.20%, and the theoretical denitrification efficiency is 96.1%. All of these theoretical performance indicators are higher than the preset performance thresholds; therefore, the system maintains the current process parameters unchanged and directly performs the impregnation operation.

[0082] When the digital twin model predicts that the theoretical performance of a catalyst module is lower than a preset performance threshold, the system automatically performs feedforward correction on the parameters in the target process formulation package. The correction methods include: adjusting the impregnation solution temperature to change the adsorption rate and adsorption equilibrium concentration of the active component; adjusting the proportion threshold for determining the impregnation endpoint to change the final loading; and adjusting the calcination temperature or holding time to optimize the dispersion state of the active component.

[0083] In this embodiment, after all 30 catalyst modules were cooled and discharged from the furnace, a quality inspection was conducted on one out of every five modules. The inspection items included vanadium pentoxide content, tungsten trioxide content, specific surface area, and denitrification efficiency at 300°C. After the inspection data was uploaded to the central control system, the big data analysis module automatically compared the actual inspection results with the predicted values ​​from the digital twin model item by item.

[0084] In this embodiment, the comparison results show that the actual vanadium pentoxide content of the six sampling modules is 0.47%, which is 0.03% lower than the model-predicted average of 0.50%. The system automatically initiates the model self-learning process and fine-tunes the surface diffusion coefficient parameter in the adsorption kinetic equation, thereby reducing the prediction deviation of the corrected model for subsequent batches.

[0085] Step S8: Full-process data recording and statistical analysis.

[0086] During the execution of all the above steps, the central control system binds all the detection data, process parameters, equipment operating status and energy consumption data of each catalyst module in each process with the unique identifier of the module and stores them in the database to realize full-process quality traceability.

[0087] The statistical results of this embodiment after continuously processing 30 catalyst modules are as follows. Regarding quality consistency, the average vanadium pentoxide content of the 30 modules was 0.48%, with a standard deviation of 0.04%, which is within the target range. Within the control range. The average tungsten trioxide content was 3.18%, with a standard deviation of 0.15%, which is within the target range. Within the controllable range. The average denitrification efficiency at 300℃ is 95.8%, with a standard deviation of 0.7%. In terms of resource utilization, ammonium tungstate raw material is reduced by 31% compared to the traditional process, ammonium metavanadate raw material is reduced by 28%, and wastewater discharge is reduced by 95%. In terms of production efficiency, the average processing cycle of a single module from feeding to exiting the furnace is 12 hours, and only one operator is needed to monitor the entire line.

[0088] Example 2 This embodiment uses the treatment of a slightly deactivated catalyst under medium-sulfur coal conditions as an application scenario. The catalyst module is a standard honeycomb type, with dimensions of [missing information]. mm.

[0089] Step S1: Multi-parameter detection and digital identity data generation.

[0090] After the catalyst module entered the testing station, X-ray fluorescence spectroscopy revealed an average vanadium pentoxide content of 0.42%, an average tungsten trioxide content of 2.8%, and a sulfur trioxide content of 3.2%. Near-infrared moisture analyzer showed a volumetric water content of 0.8%. Industrial endoscope image analysis showed a pore patency rate of 99%. Based on the initial content, the vanadium activity loss rate was calculated to be 24%, and the tungsten activity loss rate was 18%. The core conclusion of the digital identity data is: "Mild sulfur poisoning, minimal loss of active components, and intact physical structure."

[0091] Step S2: Matching the process formulation package and preparing the impregnation solution.

[0092] After comparing the digital identity data with the process knowledge base, the decision engine matched the process formulation package numbered GP-03, named "Medium-sulfur Coal - Single-Step Vanadium-Tungsten Co-leaching - Low-Temperature Roasting" scheme. This formulation package adopts a single-step co-leaching scheme, using only one impregnation tank to simultaneously load both vanadium and tungsten, the two active components. The impregnation solution formulation parameters are: tungsten concentration (calculated as tungsten trioxide) 60 g / L, vanadium concentration (calculated as vanadium pentoxide) 10 g / L, solution temperature 35℃, containing 1.0% oxalic acid and 0.5% citric acid as additives. The heat treatment curve parameters are: the drying stage has three temperature zones of 70℃ for 30 minutes, 90℃ for 45 minutes, and 110℃ for 90 minutes; the transition stage increases the temperature from 110℃ to 220℃ at a rate of 1℃ per minute; the roasting stage is roasted at a constant temperature of 350℃ for 180 minutes, with the oxygen content controlled between 18% and 20%.

[0093] After receiving the mixing instruction, the central batching station mixes ammonium tungstate concentrate, ammonium metavanadate concentrate, oxalic acid solution, citric acid solution, and deionized water in a mixing tank according to the above formula parameters. The mixture is heated to 35°C and then pumped into the impregnation tank. Online concentration monitors detect the concentrations of tungsten ions and vanadium ions, confirming that both are within the target concentration range. Once within the specified range, the impregnation tank is ready.

[0094] Step S3: Impregnation process execution and dynamic determination of endpoint.

[0095] Because this embodiment employs a single-step co-impregnation scheme, the catalyst module only needs to complete the loading of all active components in one impregnation tank. A robotic arm immerses the catalyst module in the impregnation solution, the weighing system is zeroed, and weight-time data is recorded. A microporous bubbling device introduces nitrogen gas at a rate of 1.5 L per minute.

[0096] Initial weight gain rate after impregnation begins The initial weight gain rate is 55g / min. The preset percentage threshold is set to 10% of the initial weight gain rate, i.e., a threshold of 5.5g / min. The preset duration is set to 3 minutes. At the 28th minute of immersion, the smooth weight gain rate drops below 5.5g / min. The system starts the endpoint determination timing. At the 31st minute, the 3-minute duration condition is met, and the system triggers the "immersion complete" signal.

[0097] After being removed from the impregnation tank, the catalyst module enters a sealed drying tunnel and is dried for 6 minutes in a dry airflow at a temperature of 70°C and a dew point of -20°C.

[0098] Step S4: Closed-loop control of impregnation solution concentration.

[0099] During the impregnation process, the online concentration monitor continuously monitors the concentrations of tungsten and vanadium ions in the bath. When the tungsten concentration drops to 58.5 g / L, the system instructs the metering pump to add ammonium tungstate concentrate to the circulation pipeline. When the vanadium concentration drops to 9.7 g / L, the system instructs the metering pump to add ammonium metavanadate concentrate. Both addition operations can be performed simultaneously. Once the concentration returns to the target range, the system confirms that the adjustment is complete.

[0100] Step S5: Segmented program temperature-controlled heat treatment.

[0101] After the catalyst module is pushed into the integrated tunnel furnace, the system loads the heat treatment curve corresponding to the GP-03 formulation package. During the drying stage, the target temperature in the first zone is 70℃ for 30 minutes, the target temperature in the second zone is 90℃ for 45 minutes, and the target temperature in the third zone is 110℃ for 90 minutes. The heating rate between each zone is 1℃ per minute, and the airflow humidity gradually decreases from 55% relative humidity in the first zone to 15% relative humidity in the third zone. During the transition stage, the temperature is increased from 110℃ to 220℃ at a rate of 1℃ per minute. The calcination stage involves constant calcination at 350℃ for 180 minutes. The temperature uniformity within the furnace is controlled within a specified range. Within a certain temperature range, the oxygen content is controlled between 18% and 20%. Temperature and atmosphere sensor data are fed back in real-time to the central control system for closed-loop regulation throughout the entire process.

[0102] Step S6: Online purification and recycling of waste liquid.

[0103] The online purification process for the waste liquid is the same as in Example 1, involving three stages of treatment: filtration, ion exchange, and membrane concentration. Because this example uses a single-tank co-immersion scheme, the purified liquid contains both tungsten and vanadium as effective components. The concentration of the purified liquid in the concentration adjustment tank was measured at 8 g / L for tungsten and 1.5 g / L for vanadium. The system calculates the required volumes of ammonium tungstate concentrate and ammonium metavanadate concentrate, adjusts them to the target concentration, and then reuses them.

[0104] Step S7: Quality prediction and feedforward control.

[0105] Based on the digital identity data of the catalyst module and the GP-03 formulation parameters, the digital twin model predicted a theoretical vanadium pentoxide content of 0.52% and a theoretical tungsten trioxide content of 3.35% after loading. These indicators are all higher than the preset performance thresholds, and the system maintains the current parameters unchanged. The deviation between the post-furnace sampling results and the predicted values ​​is within the allowable range, and the model requires no adjustment.

[0106] Example 3 This embodiment uses a deactivated catalyst primarily designed to treat alkali metal poisoning as its application scenario. The catalyst module is a standard honeycomb type, with dimensions of [missing information]. mm.

[0107] Step S1: Multi-parameter detection and digital identity data generation.

[0108] X-ray fluorescence spectroscopy results showed an average vanadium pentoxide content of 0.30%, an average tungsten trioxide content of 2.0%, a sulfur trioxide content of 2.8%, a potassium oxide content of 1.5%, and a calcium oxide content of 2.0%. Near-infrared moisture analyzer showed a volumetric water content of 1.5%. Industrial endoscope image analysis showed a channel patency rate of 92%. Based on the initial content, the vanadium activity loss rate was calculated to be 45%, and the tungsten activity loss rate was 41%. The core conclusion of the digital identity data analysis is: "Severe alkali metal poisoning, significant loss of active components, and slight channel blockage."

[0109] Step S2: Matching the process formulation package and preparing the impregnation solution.

[0110] The decision engine matched process formulation package GP-12, named "Alkali Metal Poisoning - Tungsten-Vanadium Gradient Loading - Adjusted Atmosphere Calcination". This formulation package employs a two-step gradient impregnation scheme. The parameters for the first impregnation tank tungsten solution are: tungsten concentration (calculated as tungsten trioxide) of 150 g / L, liquid temperature of 45℃, and containing 1.2% citric acid. The parameters for the second impregnation tank vanadium solution are: vanadium concentration (calculated as vanadium pentoxide) of 35 g / L, liquid temperature of 35℃, and containing 2.5% oxalic acid, 2.0% tartaric acid, and 0.6% cerium nitrate.

[0111] In the heat treatment curve parameters, since the potassium oxide content of 1.5% in the digital identity data is higher than the preset alkali metal threshold of 0.5%, the system adaptively adjusted the calcination parameters: the constant temperature during the calcination stage was adjusted from the standard 380℃ to 400℃, the holding time was extended from the standard 240 minutes to 300 minutes, and the calcination atmosphere was adjusted from the standard air atmosphere to a humid air atmosphere containing 5% water vapor to promote the volatilization and removal of alkali metal compounds. Meanwhile, since the load in this embodiment is expected to be relatively large, the heating rate between each temperature zone during the drying stage was reduced from the standard 1℃ per minute to 0.5℃ per minute to avoid cracking caused by excessively rapid evaporation of moisture in the catalyst module due to excessively rapid heating.

[0112] The central batching station prepares the impregnation solution for the two impregnation tanks according to the above formula parameters. After the online concentration monitoring instrument confirms that the concentration meets the standard, the impregnation tanks are ready.

[0113] Step S3: Impregnation process execution and dynamic determination of endpoint.

[0114] The catalyst module underwent gradient loading sequentially in two impregnation tanks. The initial weight gain rate for the first tungsten impregnation was 95 g / min, with a preset threshold of 8% of the initial weight gain rate, i.e., a threshold of 7.6 g / min. Due to the lower pore patency of the catalyst in this embodiment, the diffusion rate of the active component into the pores was slower, resulting in a longer impregnation time than in Example 1. The endpoint timing was initiated at 45 minutes of impregnation, and the "first impregnation complete" signal was triggered at 48 minutes when the 3-minute duration condition was met. After draining for 5 minutes, the module entered the second impregnation tank. The initial weight gain rate for the second vanadium impregnation was 70 g / min, with a threshold of 5.6 g / min. The endpoint timing was initiated at 30 minutes of impregnation, and the "second impregnation complete" signal was triggered at 33 minutes. Finally, the module was drained for 8 minutes.

[0115] Step S4: Closed-loop control of impregnation solution concentration.

[0116] The closed-loop concentration control of the two impregnation tanks follows the same process as in Example 1. Because the impregnation solution concentration is higher in this example, the concentration drop after a single impregnation is relatively large. In the first impregnation tank, the tungsten solution concentration drops from 150 g / L to 140 g / L after impregnating one module; the system replenishes the concentrate to restore the concentration to 149.5 g / L. In the second impregnation tank, the vanadium solution concentration drops from 35 g / L to 32 g / L after impregnating one module; the system replenishes the concentrate to restore the concentration to 34.8 g / L.

[0117] Step S5: Segmented program temperature-controlled heat treatment.

[0118] After the catalyst module is pushed into the tunnel furnace, the system is loaded with the adaptively adjusted heat treatment curve of the GP-12 formulation package. The drying stage consists of three temperature zones: 80℃ for 45 minutes, 100℃ for 75 minutes, and 120℃ for 150 minutes, with a heating rate of 0.5℃ per minute between each zone. The transition stage involves heating from 120℃ to 250℃ at a rate of 1℃ per minute. The calcination stage involves pre-oxidation at 250℃ for 40 minutes, followed by heating to 400℃ at a rate of 1.5℃ per minute, and then calcining at this constant temperature for 300 minutes. Moist air containing 5% water vapor is introduced into the calcination zone; the water vapor is supplied by a steam generator and metered by a mass flow controller. Temperature uniformity within the furnace is controlled at... Within ℃.

[0119] Step S6: Online purification and recycling of waste liquid.

[0120] The wastewater purification process is the same as in Example 1. In this example, due to the high alkali metal content, the ion exchange column is loaded at a faster rate. The system determines whether the resin needs regeneration by monitoring the concentration of alkali metal ions in the effluent from the ion exchange column online. When the concentration of alkali metal ions in the effluent exceeds a preset threshold, the system automatically switches to a standby ion exchange column and performs regeneration on the saturated column.

[0121] Step S7: Quality prediction and feedforward control.

[0122] The digital twin model predicted that the theoretical vanadium pentoxide content of the alkali metal poisoned catalyst module after treatment with the GP-12 formulation would be 0.52%, the theoretical tungsten trioxide content would be 3.30%, and the theoretical denitrification efficiency would be 93.5%. Due to the continued impact of alkali metal residue on catalyst activity, the theoretical denitrification efficiency was slightly lower than the predicted value in Example 1, but still higher than the preset performance threshold of 90%. The system parameters remained unchanged. Random sampling results after the catalyst was unloaded showed an actual denitrification efficiency of 93.1%, a deviation of 0.4% from the predicted value, which is within the acceptable range.

[0123] In summary, the embodiments disclosed herein have at least the following technical effects: This invention collects multi-parameter detection data on the catalyst to be regenerated and generates digital identity data, providing a quantitative basis for subsequent process decisions and realizing personalized regeneration treatment tailored to the specific catalyst.

[0124] This invention dynamically determines the impregnation endpoint based on the weight-time curve, enabling catalysts with different pore states to achieve optimal loading, and significantly improving the accuracy of active component loading.

[0125] This invention ensures that the concentration of the impregnation solution remains stable throughout the entire production process by monitoring the concentration of the impregnation solution online and implementing closed-loop compensation adjustment, thus eliminating the problem of concentration drift.

[0126] This invention adaptively adjusts the heat treatment curve parameters based on digital identity data, enabling catalysts with different deactivation types to obtain the optimal heat treatment process, thus avoiding cracking or insufficient activity caused by process mismatch.

[0127] This invention significantly reduces chemical consumption and waste disposal costs through online purification and recycling of waste liquid.

[0128] This invention achieves proactive prevention of quality problems through quality prediction and feedforward control using a digital twin model, thereby further improving the overall yield rate.

[0129] It is understood that the above embodiments are merely exemplary implementations used to illustrate the principles of the present invention, and the present invention is not limited thereto. For those skilled in the art, various modifications and improvements can be made without departing from the spirit and essence of the present invention, and these modifications and improvements are also considered to be within the scope of protection of the present invention.

Claims

1. A method for controlling the regeneration loading and heat treatment of an SCR catalyst, characterized in that, include: Multi-parameter detection data is collected for the catalyst to be regenerated, and digital identity data of the catalyst to be regenerated is generated based on the multi-parameter detection data. Based on the digital identity data, a target process formula package is matched from the process knowledge base, and an impregnation liquid preparation instruction is generated according to the impregnation liquid formula parameters in the target process formula package. Impregnation is performed based on the impregnation solution preparation instructions. During the impregnation process, the weight-time data of the catalyst to be regenerated is collected in real time, and the impregnation endpoint is dynamically determined based on the weight-time data. Furthermore, the concentration of the impregnation solution is monitored online during the impregnation process, and the concentration of the impregnation solution is adjusted in a closed-loop manner based on the deviation between the measured concentration value and the target concentration value. After the impregnation endpoint is determined, the catalyst to be regenerated is subjected to segmented temperature-controlled drying and calcination treatments in sequence according to the heat treatment curve parameters in the target process formulation package. as well as The waste liquid generated during the impregnation process is purified online, and the purified liquid is adjusted to the target concentration value and then recycled back to the impregnation process.

2. The method for controlling the SCR catalyst regeneration loading and heat treatment according to claim 1, characterized in that, The multi-parameter detection data includes active component content data, water content data, and pore patency data. The acquisition of the multi-parameter detection data includes: The content distribution data of vanadium, tungsten, sulfur, calcium and potassium elements were obtained by scanning the end face of the catalyst to be regenerated using X-ray fluorescence spectroscopy, and these data were used as the content data of the active components. The overall moisture content data of the catalyst to be regenerated was obtained by near-infrared moisture detection. Images of the pores inside the catalyst to be regenerated are acquired and the proportion of blocked area is identified through image analysis to obtain the pore patency data. The content distribution data, the moisture content data, and the pore patency data are aggregated to generate the digital identity data.

3. The method for controlling the SCR catalyst regeneration loading and heat treatment according to claim 1, characterized in that, The matching of the target process formula package from the process knowledge base based on the digital identity data includes: Based on the loss rate and inactivation type information of the active components in the digital identity data, the process formula package is compared with multiple pre-stored process formula packages in the process knowledge base, and the process formula package that meets the preset matching conditions is selected as the target process formula package. The impregnation solution formulation parameters in the target process formulation package include the target metal ion concentration, impregnation solution temperature, and additive addition ratio of each impregnation solution; the heat treatment curve parameters include the target temperature, holding time, heating rate, and atmosphere composition of each temperature zone.

4. The method for controlling the SCR catalyst regeneration loading and heat treatment according to claim 1, characterized in that, The step of dynamically determining the immersion endpoint based on the weight-time data includes: The weight value of the catalyst to be regenerated in the impregnation solution is continuously collected at a preset sampling period to form the weight-time data. Based on the adsorption kinetics model, the instantaneous weight gain rate is calculated according to the weight-time data; When the instantaneous weight gain rate drops below a preset percentage threshold of the initial weight gain rate and remains below that threshold for a preset duration, the immersion is determined to have reached its endpoint. The preset percentage threshold is a set value within the range of 5% to 15% of the initial weight gain rate, and the preset duration is a set value within the range of 2 minutes to 5 minutes.

5. The method for controlling the SCR catalyst regeneration loading and heat treatment according to claim 1, characterized in that, The online monitoring of the concentration of the impregnation solution includes: The concentration of target metal ions in the impregnation solution was detected by spectrometry, and the total ionic strength of the impregnation solution was detected by conductivity method. The two detection results were combined to obtain the measured concentration value. When the measured concentration value is lower than the target concentration value, a stock solution of a preset concentration is added to the impregnation solution; when the measured concentration value is higher than the target concentration value, a diluent is added. The closed-loop regulation maintains the concentration of the impregnation solution at the target concentration value. Within.

6. The method for controlling the SCR catalyst regeneration loading and heat treatment according to claim 1, characterized in that, When the target process formulation package includes a multi-component gradient loading scheme, the impregnation process is executed as follows: The catalyst to be regenerated is sequentially placed into multiple impregnation solutions and loaded with different active components. Between two adjacent impregnations, the catalyst to be regenerated is subjected to a controlled atmosphere dredging treatment. For each of the multiple immersions, the acquisition of weight-time data, the determination of the immersion endpoint, and the closed-loop adjustment of the immersion solution concentration are performed independently.

7. The method for controlling the SCR catalyst regeneration loading and heat treatment according to claim 1, characterized in that, The segmented temperature-controlled drying and calcination processes include: During the drying stage, the temperature is gradually increased in multiple temperature zones according to the drying temperature range in the heat treatment curve parameters, and the airflow humidity in each temperature zone is gradually reduced. During the transition phase, the temperature is increased from the drying termination temperature to the calcination start temperature at the set heating rate in the heat treatment curve parameters. During the roasting stage, the oven is roasted at a constant temperature according to the roasting temperature range and holding time in the heat treatment curve parameters. The oxygen content during the roasting stage is controlled within a set range according to the atmosphere composition in the heat treatment curve parameters. Throughout the drying and roasting processes, real-time temperature and atmosphere data within the furnace are collected and fed back to adjust the heating power of each temperature zone.

8. The method for controlling the SCR catalyst regeneration loading and heat treatment according to claim 7, characterized in that, The heat treatment curve parameters are adaptively adjusted based on the digital identity data, and the adjustment method is as follows: When the alkali metal content in the digital identity data is higher than the preset alkali metal threshold, the holding time of the roasting stage is increased and the atmosphere composition is adjusted. When the load recorded in the digital identity data exceeds a preset load threshold, the heating rate of the drying stage is reduced.

9. The method for controlling the SCR catalyst regeneration loading and heat treatment according to any one of claims 1 to 8, characterized in that, The online purification of the waste liquid includes: The waste liquid is subjected to filtration treatment to remove particulate matter, ion exchange treatment to remove impurity ions, and membrane concentration treatment to separate the clear liquid from the concentrated residue. The concentration of the effective components in the clear liquid is detected online. The clear liquid is mixed with fresh mother liquor according to the calculated ratio to the target concentration value and then transported back to the corresponding impregnation process. The proportion of concentrated residual liquid generated by the membrane concentration treatment to the total waste liquid does not exceed the preset residual liquid proportion.

10. The method for controlling the SCR catalyst regeneration loading and heat treatment according to any one of claims 1 to 8, characterized in that, It also includes quality prediction and feedforward control, wherein the quality prediction and feedforward control includes: Before the catalyst to be regenerated enters the impregnation process, the elemental distribution and theoretical performance indicators after loading are predicted using a digital twin model based on the digital identity data; When the theoretical performance index is lower than the preset performance threshold, feedforward correction is performed on the impregnation liquid formulation parameters or heat treatment curve parameters in the target process formulation package. After the catalyst to be regenerated has undergone heat treatment, the sampled data is compared with the theoretical performance indicators, and the parameters in the digital twin model are automatically corrected based on the comparison deviation.

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