Self-adaptive supplement method and system for active component of SCR denitration catalyst

Abstract

This invention discloses an adaptive replenishment method and system for the active components of an SCR denitrification catalyst. The method includes the following steps: obtaining key characteristic parameters of the deactivated catalyst module; inputting the key characteristic parameters into an adaptive adjustment strategy prediction model, outputting the predicted catalyst deactivation type, and a replenishment strategy and process parameter adjustment strategy generated based on the catalyst deactivation type; and controlling the system to execute the replenishment strategy and process parameter adjustment strategy to achieve adaptive replenishment of the active components of the SCR denitrification catalyst. This invention achieves excellent and stable regeneration quality, strong process adaptability, high resource utilization, and high automation, while also realizing full-process digital traceability, improving catalyst regeneration effect and production efficiency.

Description

Technical Field

[0001] This invention belongs to the field of industrial flue gas purification and resource recycling technology, specifically relating to an adaptive replenishment method and system for the active components of an SCR denitrification catalyst. Background Technology

[0002] Selective Catalytic Reduction (SCR) technology is currently the mainstream technology for controlling nitrogen oxides (NOx) from stationary sources such as power plant boilers and industrial furnaces. Its core component, the SCR catalyst, gradually deactivates during long-term operation due to physical blockage, chemical poisoning, and loss of active components. Catalyst regeneration, as a crucial step in extending its service life and reducing operating costs, plays a vital role in the environmental protection industry. Currently, SCR catalyst regeneration processes are widely used in various industries such as power, chemical, and steel, aiming to restore catalyst activity through a series of technical means, thereby ensuring effective control of NOx during industrial production.

[0003] In the practical application of SCR catalyst regeneration processes, a series of problems exist. Traditional catalyst regeneration processes typically include offline detection, dust removal, chemical cleaning, active component replenishment (impregnation), drying, and calcination. Among these, active component replenishment is the core step in restoring the chemical activity of the catalyst. However, most regeneration service providers currently use fixed-concentration impregnation solution formulations based on historical experience, which ignores the significant differences in the deactivation mechanisms of different batches of catalysts. Furthermore, the single impregnation method easily leads to excessive accumulation of active components on the outer surface of the support, forming an "eggshell" structure. This not only affects the utilization rate of internal active sites but may also exacerbate SO2 oxidation, negatively impacting catalyst performance. Simultaneously, the lack of real-time feedback and adjustment mechanisms during the regeneration process results in poor regeneration quality from beginning to end, and poor batch uniformity. More seriously, the evaluation of regeneration effectiveness heavily relies on laboratory testing after final calcination or even performance testing after installation, which is time-consuming and costly. Once a problem is discovered, the entire batch of products may be irrecoverable, resulting in economic losses.

[0004] To address the aforementioned issues, existing technologies have attempted some improvements. For example, some regeneration service providers have begun to adjust the impregnation solution concentration based on the degree of catalyst deactivation in order to improve regeneration efficiency. Simultaneously, some studies have proposed using a multiple impregnation method to avoid excessive accumulation of active components on the outer surface of the support. However, these improved methods still have limitations. On the one hand, adjusting the impregnation solution concentration based on the degree of deactivation still relies on manual experience and offline detection data, making real-time and precise adjustments difficult. On the other hand, while the multiple impregnation method can improve the distribution of active components to some extent, it increases process complexity and cost, and still cannot completely prevent the formation of an "eggshell" structure. Furthermore, existing technologies still lack effective real-time feedback and adjustment mechanisms, as well as rapid and accurate methods for evaluating regeneration effectiveness.

[0005] Despite some improvements to SCR catalyst regeneration processes in existing technologies, numerous problems remain. The most prominent is the lack of an adaptive replenishment method and system capable of deeply sensing catalyst deactivation, intelligently deciding on regeneration strategies, and precisely executing the loading process. Current technologies struggle to acquire real-time and accurate information on catalyst deactivation, failing to intelligently adjust regeneration strategies based on actual conditions, resulting in unstable regeneration effects and poor batch uniformity. Furthermore, the lack of rapid and accurate methods for evaluating regeneration performance makes it difficult to promptly identify and resolve problems during the regeneration process, increasing the risk of economic losses. Therefore, developing an adaptive replenishment method and system capable of deeply sensing catalyst deactivation, intelligently deciding on regeneration strategies, and precisely executing the loading process is an urgent need to improve the technological level of the SCR catalyst regeneration industry and achieve high-quality development. Summary of the Invention

[0006] To address the problems existing in the prior art, this invention provides an adaptive replenishment method and system for the active components of an SCR denitrification catalyst, achieving excellent and stable regeneration quality, strong process adaptability, high resource utilization, and high degree of automation. At the same time, it enables full-process digital traceability, improving catalyst regeneration effect and production efficiency.

[0007] To achieve the above objectives, the present invention provides the following technical solution: an adaptive replenishment method for the active components of an SCR denitrification catalyst, the specific steps of which are as follows: Obtain key characteristic parameters of the deactivated catalyst module; The key feature parameters are input into the adaptive adjustment strategy prediction model, which outputs the predicted catalyst deactivation type, as well as the supplementary strategy and process parameter adjustment strategy generated based on the catalyst deactivation type. The control system executes supplementation strategies and process parameter adjustment strategies to achieve adaptive replenishment of the active components of the SCR denitrification catalyst; The adaptive adjustment strategy prediction model includes a deactivation type determination module, a replenishment strategy generation module, a loading concentration calculation module, and a process parameter adjustment module. Specifically: the deactivation type determination module is used to determine the catalyst deactivation type according to key characteristic parameters and preset rules; the replenishment strategy generation module is used to determine the active material replenishment strategy according to the deactivation type; the loading concentration calculation module is used to calculate the target loading concentration of the active material; and the process parameter adjustment module is used to adjust the impregnation process parameters according to key characteristic parameters.

[0008] Furthermore, the key characteristic parameters include chemical composition parameters and physical structure parameters, specifically: Chemical composition parameters include the loss rate of active components and the content of key toxic substances. The loss rate of active components includes both absolute loss and relative loss rate, calculated as follows: ΔC V =C V,fresh -C V,now ΔC W =C W,fresh -C W,now A V =ΔC V / C V,fresh ×100% A W =ΔCW / C W,fresh ×100% In the formula, C V,now C W,now The current contents of V2O5 and WO3 are respectively, C V,fresh C W,fresh The standard contents of V2O5 and WO3 of the same type of fresh catalyst, ΔC, are respectively. V ΔC W The absolute losses of V2O5 and WO3 are respectively, A V A W The relative loss rates of V2O5 and WO3 are respectively. Key toxic substances include SO3, K2O, Na2O, CaO, As2O3, and P2O. 5； The physical structural parameters include the specific surface area loss rate and the degree of clogging, which are calculated as follows: Specific surface area loss rate: ΔS=(S fresh -S now ) / S fresh ×100% In the formula, S now S represents the current specific surface area. fresh Standard values ​​for fresh samples; The degree of blockage refers to the extent of blockage in the catalyst channels. The degree of blockage is obtained through endoscopy or pressure drop testing and is classified into three levels: unobstructed, slightly blocked, and severely blocked.

[0009] Furthermore, the specific rules for determining the inactivation type in the module are as follows: Sulfur-dominant type: SO3 content > 3% and A W >A V If the value is +5% and ΔS is between 5% and 15%, it is determined that sulfur poisoning is the dominant factor, accompanied by tungsten loss. Alkali metal poisoning type: (K2O+Na2O) content >1.5% and A V >A W If the value is +10% and ΔS < 8%, it is determined to be selective poisoning of vanadium sites by alkali metals. Calcium-based blockage type: CaO content >2% and ΔS >15%, indicating severe blockage, which is mainly due to physical deactivation caused by calcium-based fly ash blockage; Arsenic / phosphorus chemical poisoning type: If the content of As2O3 or P2O5 exceeds the threshold, it is marked as chemical poisoning. Composite inactivation type: The inactivation type judgment module makes a comprehensive judgment based on the weighted scores of various parameters.

[0010] Furthermore, in the replenishment strategy generation module, the replenishment order of active components is determined based on the catalyst deactivation type: Sulfur-dominant type: Follow the order of supplementing tungsten first, then vanadium; Alkali metal poisoning type: Follow the order of replenishing vanadium first, then tungsten, and add a small amount of phosphate to the vanadium impregnation solution; In the load concentration calculation module, the target load concentrations (C) of vanadium and tungsten are... V,target C W,target The value is dynamically determined by the following function: C i,target = f (A i ,ΔS, poison content, catalyst type) In the formula, i represents vanadium or tungsten; The process parameter adjustment module uses specific surface area loss rate and clogging rating to adjust the impregnation process parameters.

[0011] Furthermore, the specific steps to achieve adaptive replenishment of the active components of the SCR denitrification catalyst are as follows: The control system delivers raw material liquid and additives through a precision metering pump according to the replenishment strategy, monitors the component concentration in real time with an online concentration meter, and adjusts the concentration to the target concentration through closed-loop feedback to complete the impregnation solution preparation. The control system controls the robotic arm to transfer the catalyst module to the impregnation tank. The weighing system monitors the weight gain curve of the catalyst module in real time, and determines the adsorption saturation endpoint based on the gradual weight gain rate, and dynamically adjusts the impregnation time. After impregnation, the control system controls the robotic arm to transfer the catalyst module to complete the draining and converter processes in a closed, dry, low-oxygen, inert atmosphere. Before calcination after drying, the control system uses laser-induced breakdown spectroscopy to conduct online sampling inspections of the active component distribution and loading of the catalyst module. The results are fed back to the control system, and an alarm is triggered when an anomaly occurs, and the process parameters for subsequent batches are automatically corrected. This invention also provides an SCR denitrification catalyst active component regeneration system, including a feeding and intelligent detection unit, a central control and decision-making unit, an impregnation solution supply and preparation unit, a multi-mode impregnation execution unit, a closed draining and transmission unit, a programmed heat treatment unit, and a data management and human-machine interaction unit. The feeding and intelligent detection unit includes an automatic conveyor line, a barcode / RFID identification system, a sampling robotic arm, a rapid XRF detection station, a rapid BET detection station, and an endoscope detection station. The central control and decision-making unit includes an industrial computer equipped with intelligent decision-making software and a central database. The intelligent decision-making software has a built-in process knowledge base and a computer program that runs the above methods. The impregnation solution supply and preparation unit includes multiple raw material storage tanks, a precision metering pump set, an online concentration analyzer, a mixing tank, a constant temperature system, and delivery pipelines. The raw material storage tanks are vanadium salt storage tanks, tungsten salt storage tanks, acid storage tanks, auxiliary agent storage tanks, and deionized water storage tanks. The multi-mode impregnation execution unit includes multiple independently controlled impregnation tanks, each equipped with a lifting mechanism, a temperature control module, a stirring / bubbling assembly, a liquid level sensor, and a weighing sensing system. The closed draining and conveying unit includes a tilting drainer and a closed conveyor belt. The draining zone of the tilting drainer is a closed chamber with a pipeline for introducing hot drying nitrogen. The program heat treatment unit is an integrated chain or roller heat treatment furnace. The front section of the furnace body is equipped with a multi-temperature zone programmable drying belt, and the rear section is equipped with a calcination belt. An atmosphere control component is installed inside the furnace. The data management and human-computer interaction unit includes a large-screen display board and a human-computer interaction terminal, and has built-in process formula management module, report generation module, and remote diagnosis module.

[0012] Furthermore, the feeding and intelligent detection unit is used for conveying, identifying, sampling, and detecting the catalyst to be regenerated, and the detection data is uploaded to the central database; the central control and decision-making unit is used to receive detection and equipment operation data, generate process instructions, and schedule various execution units; the impregnation liquid supply and preparation unit is used to complete the preparation, delivery, and maintenance of the tank concentration of the impregnation liquid; the multi-mode impregnation execution unit is used to execute multi-mode impregnation processes and monitor the impregnation process; the closed draining and transmission unit is used for draining the catalyst after impregnation and closed transmission between processes; the programmed heat treatment unit is used for programmed drying and calcination of the catalyst; and the data management and human-machine interaction unit is used for real-time display of production data and system operation and maintenance management.

[0013] The present invention also provides a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described adaptive replenishment method for the active component of an SCR denitrification catalyst.

[0014] The present invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described adaptive replenishment method for the active component of an SCR denitrification catalyst.

[0015] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the above-described adaptive replenishment method for the active component of an SCR denitrification catalyst.

[0016] Compared with the prior art, the present invention has at least the following beneficial effects: This invention provides an adaptive replenishment method for the active components of an SCR denitrification catalyst. Through personalized and precise replenishment, the active components of the regenerated catalyst are restored to their optimal state, resulting in superior performance with high denitrification efficiency, low SO2 conversion rate, and minimal ammonia slip. Furthermore, the performance consistency across batches of regenerated catalyst is excellent. The core of the method lies in acquiring key characteristic parameters of the deactivated catalyst module to provide reliable data support for subsequent precise replenishment. These key characteristic parameters are then input into an adaptive adjustment strategy prediction model. The model's deactivation type judgment module, replenishment strategy generation module, loading concentration calculation module, and process parameter adjustment module work collaboratively to accurately determine the deactivation type, formulate a suitable replenishment strategy, calculate the target loading concentration of active materials, and adjust impregnation process parameters. Finally, the control system strictly executes the relevant strategies to ensure the accuracy and rationality of active component replenishment. This fundamentally avoids the problems of blind replenishment and unreasonable parameters in traditional regeneration processes, leading to poor regeneration quality and large batch variations, thus ensuring the long-term stable denitrification function of the regenerated catalyst.

[0017] Due to differences in coal type and operating conditions in industrial production, the types and degrees of deactivation of deactivated catalysts vary significantly. Traditional regeneration methods often struggle to fully adapt to various deactivation scenarios, resulting in poor versatility. This invention, however, by comprehensively acquiring key characteristic parameters and combining them with the accurate judgment of an adaptive adjustment strategy prediction model, can flexibly formulate specific replenishment strategies and process parameter adjustment strategies for various types of deactivated catalysts caused by different coal types and operating conditions. This achieves efficient regeneration of various deactivated catalysts without requiring additional modifications to the process flow, significantly expanding the method's applicability and reducing the technical difficulty and operating costs of catalyst regeneration in different scenarios, demonstrating strong versatility and practicality.

[0018] This invention achieves dynamic allocation and real-time concentration maintenance of active materials through precise calculation of the target loading concentration of the active material by a loading concentration calculation module and precise control of the replenishment process by a control system. This effectively reduces the waste of chemicals such as vanadium salts and tungsten salts, and improves resource utilization efficiency. Simultaneously, the entire replenishment process forms a closed-loop control logic. This closed-loop system effectively reduces waste liquid generation and pollutant emissions, avoiding problems such as chemical waste and waste liquid pollution in traditional regeneration processes. It not only reduces the material cost of catalyst regeneration but also aligns with the trend of green and low-carbon industrial development, achieving a dual improvement in economic and environmental benefits.

[0019] The method of this invention is entirely controlled by a control system. From acquiring key characteristic parameters and determining the type of deactivation, to generating replenishment strategies and process parameter adjustment strategies, and finally to the implementation of these strategies, all processes are automated, significantly reducing manual intervention. This not only effectively reduces the labor intensity of operators but also eliminates the heavy reliance on operator experience, avoiding the impact of human error on regeneration quality. Simultaneously, it significantly shortens the catalyst regeneration cycle, improves production efficiency, meets the actual needs of large-scale industrial catalyst regeneration, and enhances the industrial application level of catalyst regeneration.

[0020] The core processes of this invention revolve around key characteristic parameters and adaptive adjustment strategy prediction models, achieving full data management. All key operational and parameter data can be collected, stored, and retrieved in real time, forming a comprehensive end-to-end data system. This system not only enables full traceability of product quality, facilitating rapid identification of problematic stages, investigation of causes, and timely rectification when quality issues arise, but also accumulates rich data support for subsequent process optimization, adaptive adjustment strategy prediction model iteration, and overall technology upgrades. This promotes the continuous improvement of catalyst regeneration technology, further enhancing regeneration efficiency and production effectiveness.

[0021] The SCR denitrification catalyst active component regeneration system provided by this invention offers solid hardware support for the efficient implementation of the aforementioned adaptive replenishment method, significantly improving the scale and standardization of catalyst regeneration. Through multiple detection stations in the feeding and intelligent detection unit, along with automated conveying and sampling mechanisms, the system achieves rapid, accurate, and comprehensive collection of key characteristic parameters of the deactivated catalyst. A barcode / RFID identification system ensures catalyst traceability, providing reliable data for accurate subsequent determination of deactivation types and formulation of replenishment strategies. Simultaneously, it greatly improves detection efficiency, avoiding errors and cumbersome operations associated with manual sampling and testing. The central control and decision-making unit, as the core of the system, is equipped with intelligent decision-making software and a process knowledge base, enabling efficient operation of the adaptive replenishment method. It achieves integrated management and control of detection data reception, process instruction generation, and scheduling of various execution units, ensuring the orderly connection and precise control of the entire regeneration process, effectively improving the stability and reliability of system operation.

[0022] Furthermore, the design of each execution unit in this regeneration system is tailored to actual production needs, further enhancing the practicality and efficiency of the regeneration process. The impregnation solution supply and preparation unit, through components such as precision metering pumps and online concentration analyzers, achieves accurate preparation and dynamic concentration maintenance of the impregnation solution, ensuring the precision of active component replenishment and reducing chemical waste. The multi-mode impregnation execution unit, with its independently controlled impregnation tank and supporting components, can adapt to the impregnation requirements of different types of catalysts with varying degrees of deactivation, improving process flexibility. The sealed draining and transfer unit and the programmed heat treatment unit ensure the standardized treatment of the catalyst after impregnation, avoiding secondary pollution and ensuring regeneration quality. The data management and human-machine interaction unit enables real-time display of production data, process formula management, and remote diagnostics. This facilitates real-time monitoring of system operation and timely troubleshooting by operators, while also providing convenient support for production management and process optimization, comprehensively improving the automation and intelligence level of catalyst regeneration and adapting to the needs of large-scale, continuous industrial production. Attached Figure Description

[0023] Figure 1 This is the overall process flow diagram.

[0024] Figure 2 This is a sub-process for rapid detection of multidimensional features.

[0025] Figure 3 This is a sub-process for predicting inactivation types and generating strategies.

[0026] Figure 4 This is for process verification and closed-loop optimization of sub-processes. Detailed Implementation

[0027] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. The following embodiments are intended to explain the present invention, but not to limit the scope of protection of the present invention.

[0028] This invention provides an adaptive replenishment method for the active component of an SCR denitrification catalyst, the specific steps of which are as follows: Step 1: Rapid Acquisition and Quantization of Multidimensional Feature Parameters like Figure 2 As shown, non-destructive or minimal-destructive rapid detection is performed on the deactivated catalyst module entering the regeneration line to obtain key characteristic parameters, including chemical composition parameters and physical structure parameters, among which: 1) Chemical composition parameters include the loss rate of active components and the content of key toxic substances, specifically: The loss rate of active components was determined by portable X-ray fluorescence spectrometry or by sending samples for ICP-OES analysis to measure the current content (C2O5 and WO3) in the catalyst. V,now C W,now Then compare the current content with the standard content (C) of the same type of fresh catalyst. V,fresh C W,fresh By comparison, the absolute loss ΔC is calculated. V ΔC W and relative loss rate A V A W The calculation formula is as follows: ΔC V =C V,fresh -C V,now ΔC W =C W,fresh -C W,now A V =ΔC V / C V,fresh ×100% A W =ΔCW / C W,fresh ×100% The key toxins detected include SO3, K2O, Na2O, CaO, As2O3, and P2O5, and the degree of poisoning is quantified by the content of these key toxins.

[0029] 2) Physical structural parameters include specific surface area loss rate and degree of clogging, as detailed below: Specific surface area loss rate: The current specific surface area (S) is measured using a rapid BET specific surface area tester (a rapid detection device that can use a small amount of sampling or a full-module non-destructive aspiration method). now ); the current specific surface area (S) now ) and fresh sample standard value (S fresh By comparison, the specific surface area loss rate is calculated using the following formula: ΔS=(S fresh -Snow ) / S fresh ×100%.

[0030] Blockage level: The degree of visual blockage of catalyst channels is graded by using a high-definition industrial endoscope or pressure drop test (e.g., unobstructed, slightly blocked, severely blocked).

[0031] Step 2: Use an adaptive adjustment strategy prediction model to predict catalyst deactivation type and dynamically generate supplementary strategies and process parameter adjustment strategies. 1) Input the key feature parameters obtained in step one into the adaptive adjustment strategy prediction model. The adaptive adjustment strategy prediction model is built based on a large amount of experimental data and mechanistic models, specifically as follows: Figure 3 As shown; The specific rules for determining the inactivation type in the adaptive adjustment strategy prediction model are as follows: Sulfur-dominant type: If SO3 content > 3% and A W >A V If the loss is +5% (i.e., tungsten loss is significantly higher than vanadium loss) and ΔS is between 5% and 15%, then it is determined that sulfur poisoning is the dominant factor, accompanied by tungsten loss.

[0032] Alkali metal poisoning type: If the (K₂O + Na₂O) content is >1.5% and A V >A W If the value is +10% and ΔS is usually small (<8%), it is judged as selective poisoning of vanadium sites by alkali metals.

[0033] Calcium-based blockage type: If the CaO content is >2% and ΔS >15%, and the visible blockage rating of the pores is high, it is judged that the physical deactivation is mainly caused by calcium-based fly ash blockage.

[0034] Arsenic / phosphorus chemical poisoning type: If the content of As2O3 or P2O5 exceeds the threshold, it is marked as chemical poisoning.

[0035] Composite inactivation type: In most cases, multiple types are combined. The adaptive adjustment strategy prediction model will make a comprehensive judgment based on the weighted scores of each parameter.

[0036] 2) Determine the order of replenishment of active components based on the type of catalyst deactivation: Sulfur-dominant type: The order of supplementing tungsten first, followed by vanadium, is to rapidly rebuild the active structural units of WOV.

[0037] Alkali metal poisoning type: Follow the order of replenishing vanadium first, then tungsten, and add a small amount of phosphate to the vanadium impregnation solution to competitively occupy the sites poisoned by alkali metals, thereby improving the regeneration effect.

[0038] 3) Adjustment of process parameters 3.1) Calculation of impregnation solution concentration The target replenishment amount is not simply to make up for the loss. The adaptive adjustment strategy prediction model will comprehensively consider the following factors to determine the target loading concentration (C) of vanadium (V) and tungsten (W). V,target C W,target ): Effective loading rate: related to pore cleanliness and specific surface area.

[0039] Synergistic effect: Consider the optimal ratio range of V and W.

[0040] For a large specific surface area loss (Δ S For catalysts with a loading of >10%, the target loading concentration will be appropriately reduced to avoid overload blockage in the pores. V and W Target load concentration (C) V,target C W,target The value is dynamically determined by the following function: C i,target = f (A i ,ΔS, poison content, catalyst type) Where i represents V or W.

[0041] 3.2) Adjustment of impregnation process parameters Based on the specific surface area loss rate (Δ S Based on the clogging rating, the impregnation process parameters are adjusted. Adjust process parameters such as impregnation time, impregnation solution temperature, and whether to use vacuum-assisted impregnation. For cases of severe pore blockage, extend the impregnation time and use a warm impregnation solution to reduce the viscosity of the impregnation solution, improve its permeability, and ensure that the active components can be effectively loaded onto the catalyst.

[0042] By making the above-mentioned replenishment sequence decisions and adjusting process parameters, it is possible to accurately replenish the active components during the SCR catalyst regeneration process, thereby improving the regeneration effect and catalyst performance.

[0043] Step 3: The control system executes the adaptive adjustment strategy, the supplementary strategy generated by the predictive model, and the process parameter adjustment strategy. The operations performed by the control system to execute the strategy include: 1) Automatic and precise preparation of impregnation solution: Deionized water, ammonium metavanadate / oxalic acid solution, ammonium tungstate solution, and possible auxiliary agent solutions (such as Ce(NO3)3, Mo salt, and phosphoric acid) are mixed in the high-concentration storage tank according to the calculated ratio using a precision metering pump and an online concentration meter (such as UV-Vis spectroscopy to measure vanadium concentration). The mixture is stirred evenly in the preparation tank, and the concentration is monitored and adjusted to the target concentration in real time, with the error controlled within ±2%.

[0044] 2) Programmed Impregnation and Process Monitoring: The catalyst module is transferred to the designated impregnation tank by a robotic arm. During the impregnation process, a gentle stirring or bubbling device is installed in the tank to ensure uniform concentration. The catalyst mass increase curve is monitored in real time by a weight sensor (or tank weighing system) mounted on the catalyst module. When the rate of mass increase tends to level off (indicating that adsorption is close to saturation), the control system determines the impregnation endpoint and dynamically adjusts the impregnation time.

[0045] 3) Inter-process connection and protection: After impregnation, the catalyst module is drained and transferred to the drying oven in a closed channel or in an environment filled with a dry, low-oxygen inert atmosphere (such as nitrogen) to prevent the unfixed active components from migrating or deliquescing due to contact with humid air.

[0046] Step 4: Process Validation and Closed-Loop Optimization 1) After drying and before calcination, an online sampling point is set up to scan the uniformity and approximate content of V and W distribution on the catalyst surface using rapid methods such as laser-induced breakdown spectroscopy. The results are fed back to the control system. If non-uniformity or a deviation from the expected loading is detected, an alarm can be triggered or the process parameters of subsequent modules can be automatically adjusted.

[0047] 2) The initial testing data, process parameters, process monitoring data, and final product testing data of each catalyst module are all linked to its unique ID code and stored in the database. Big data analytics are used to continuously optimize the rules and model parameters in the intelligent decision-making software, enabling the system to self-learn and iteratively upgrade. Specifically, for example… Figure 4 As shown.

[0048] like Figure 1 As shown, the present invention also provides an SCR denitrification catalyst active component regeneration system, which mainly includes the following units: Feeding and Intelligent Inspection Unit: Includes an automated conveyor line, barcode / RFID identification system, sampling robotic arm, rapid XRF inspection station, rapid BET inspection station, and endoscopic inspection station. All inspection data is automatically uploaded to a central database.

[0049] Central Control and Decision-Making Unit: The industrial computer is equipped with intelligent decision-making software, a built-in knowledge base, and computer programs capable of executing the above methods and steps. It is responsible for receiving detection data, running decision-making algorithms, generating process instructions, and scheduling various execution units.

[0050] The impregnation solution supply and preparation unit consists of multiple raw material storage tanks (vanadium salt, tungsten salt, acid, additives, deionized water), a precision metering pump set, an online concentration analyzer, a mixing tank, a temperature control system, and delivery pipelines. Upon receiving instructions, it automatically completes the preparation, delivery, and maintenance of the impregnation solution concentration.

[0051] Multi-mode impregnation execution unit: Composed of multiple independently controlled impregnation tanks, each equipped with a lifting mechanism, temperature control, stirring / bubbling, liquid level and weighing sensors. It can perform different processes such as atmospheric pressure impregnation, vacuum-assisted impregnation, and warm impregnation.

[0052] Sealed draining and conveying unit: A tilting drainer is used, with the draining area being a sealed chamber vented with hot, dry nitrogen gas. This accelerates surface liquid evaporation and prevents contamination. The conveyor belt is enclosed.

[0053] Programmable heat treatment unit: Integrated chain or roller conveyor heat treatment furnace, with a multi-temperature programmable drying zone at the front and a calcination zone at the rear. The furnace atmosphere is controllable (air or oxygen-deficient), with temperature uniformity within ±3℃.

[0054] Data Management and Human-Machine Interaction Unit: A large-screen display dashboard shows real-time production status, process parameters, and quality data. It provides functions such as process formula management, report generation, and remote diagnostics.

[0055] Example 1: Treatment of deactivated catalysts from high-sulfur coal-fired power plants A power plant burns bituminous coal with a sulfur content of 2.8%. After the catalyst runs for 24,000 hours, it becomes deactivated, and the denitrification efficiency drops from 95% to 78%.

[0056] Test data: XRF:C V,now =0.38%, C W,now =2.05% (Freshness Standard: C) V,fresh =0.55%, C W,fresh =3.40%).

[0057] Calculation yields: A V =(0.55-0.38) / 0.55≈30.9%; A W =(3.40-2.05) / 3.40≈39.7%. A W >A V .

[0058] SO3 content: 7.2%.

[0059] Quick BET:S now =38m 2 / g(S fresh =45m 2 / g), ΔS≈15.6%.

[0060] Endoscopic examination: Some orifices have a dense, grayish-white covering, with a blockage rating of "moderate".

[0061] The above data is transmitted to the adaptive adjustment strategy prediction model, and the output deactivation type is sulfur-dominant composite deactivation (high SO3, A).W >A V (ΔS is relatively large). The active component replenishment sequence is W first, then V; considering partial pore blockage, the effective loading rate coefficient is set to 0.9. The target replenishment level for W is 3.2% (slightly lower than the fresh value, leaving room for subsequent V loading), and the target replenishment level for V is 0.52% (close to the fresh value). Impregnation process parameters: impregnation solution temperature 40℃, impregnation time set to 45 minutes (default value), with dynamic adjustment enabled via weight monitoring.

[0062] The regeneration system controls the supply and preparation of impregnation solutions, and the tungsten and vanadium impregnation solutions are prepared by the impregnation unit. The specific impregnation steps are as follows: For the first impregnation (W), the catalyst module was immersed in the tungsten impregnation solution. Weight monitoring showed that the weight gain stabilized after 40 minutes, at which point the system determined the impregnation was complete. The module was then drained and dried at 100℃ until the moisture content was approximately 12%. The target concentration of the tungsten impregnation solution corresponds to 2 wt% ammonium tungstate. The system automatically prepared and verified this concentration. In the second impregnation (V), the catalyst module was immersed in the vanadium impregnation solution for 35 minutes until the weight gain endpoint was reached, and then drained. The target concentration of the vanadium impregnation solution corresponds to 1 wt% ammonium metavanadate, with 0.1% Ce(NO3)3 added as an additive.

[0063] Then dry at 120℃ for 2 hours, and then calcine at 400℃ for 4 hours by increasing the temperature at 2℃ / min.

[0064] Result verification: Laboratory tests showed that after regeneration, V₂O₅ = 0.51%, WO₃ = 3.18%, and the specific surface area recovered to 43 m². 2 / g.

[0065] Activity evaluation (simulated flue gas, 350℃): denitrification efficiency = 94.5%, SO2 conversion rate = 0.85%, ammonia slip < 2.5 ppm.

[0066] The same batch processed 20 modules, with the following performance standard deviations: denitrification efficiency ±1.2% and SO2 conversion rate ±0.15%.

[0067] Example 2: Treatment of deactivated catalysts from high-alkali coal coupled with high-calcium fly ash A steel plant's self-owned power plant uses high-alkali coal and co-fires limestone slurry, resulting in severe catalyst deactivation.

[0068] Test data: XRF:C V,now =0.18%, C W,now =2.80%, (K2O+Na2O)=2.1%, CaO=3.5%.

[0069] A V =(0.55-0.18) / 0.55≈67.3%; AW =(3.40-2.80) / 3.40≈17.6%. A V >>A W .

[0070] ΔS=22% (pore volume decreased significantly).

[0071] The above data was transmitted to an adaptive adjustment strategy prediction model, which output the inactivation type as a complex of alkali metal poisoning and calcium-based blockage. After routine cleaning, a dilute acid activation step was added (immersion in 1% oxalic acid solution to remove some alkali metals and calcium from the surface). A V-W sequence was adopted, with 0.5% ammonium dihydrogen phosphate added to the V impregnation solution to compete with residual alkali metals for sites. Due to the large ΔS, the target loading concentration was moderately reduced: V target 0.45%, W target 3.0%. Vacuum-assisted impregnation was used to improve solution permeability.

[0072] The regeneration system controls the supply and preparation of the impregnation solution, and the specific impregnation steps are as described in Example 1: Result verification: Catalyst strength test after regeneration: Axial strength retention rate is 88% of that of fresh catalyst.

[0073] Activity evaluation: The denitrification efficiency recovered to 92%, which is slightly lower than that of Example 1, but considering the extremely poor initial condition, the recovery effect is significant. The SO2 conversion rate was 0.95%.

[0074] In summary, the adaptive replenishment method and intelligent system provided by this invention represent a significant breakthrough in the development of SCR catalyst regeneration technology towards refinement, intelligence, and digitalization. Driven by data and ensuring quality through precise execution, it not only significantly improves the overall performance and lifespan of the regenerated catalyst but also brings greater economic and environmental benefits to operators, demonstrating broad prospects for industrial application.

[0075] The following are embodiments of the apparatus of the present invention, which can be used to execute embodiments of the method of the present invention. For details not disclosed in the apparatus embodiments, please refer to the embodiments of the method of the present invention.

[0076] In another embodiment of the present invention, a terminal device is also provided, comprising a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the memory. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions to achieve a corresponding method flow or corresponding function. The processor described in this embodiment of the present invention can implement an adaptive replenishment method for the active components of an SCR denitrification catalyst.

[0077] In another embodiment of the present invention, a storage medium is provided, specifically a computer-readable storage medium (Memory), which is a memory device in a terminal device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the terminal device and extended storage media supported by the terminal device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, the storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory or non-volatile memory, such as at least one disk storage device. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the corresponding steps of the adaptive replenishment method for the active component of an SCR denitrification catalyst in the above embodiments.

[0078] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0079] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0080] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0081] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0082] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the present invention.

Claims

1. An adaptive replenishment method for the active component of an SCR denitrification catalyst, characterized in that, The specific steps are as follows: Obtain key characteristic parameters of the deactivated catalyst module; The key feature parameters are input into the adaptive adjustment strategy prediction model, which outputs the predicted catalyst deactivation type, as well as the supplementary strategy and process parameter adjustment strategy generated based on the catalyst deactivation type. The control system executes supplementation strategies and process parameter adjustment strategies to achieve adaptive replenishment of the active components of the SCR denitrification catalyst; The adaptive adjustment strategy prediction model includes a deactivation type determination module, a replenishment strategy generation module, a loading concentration calculation module, and a process parameter adjustment module, wherein: the deactivation type determination module is used to determine the catalyst deactivation type according to key characteristic parameters and preset rules; the replenishment strategy generation module is used to determine the active substance replenishment strategy according to the deactivation type. The loading concentration calculation module is used to calculate the target loading concentration of the active material; the process parameter adjustment module is used to adjust the impregnation process parameters according to the key characteristic parameters.

2. The adaptive replenishment method for the active component of an SCR denitrification catalyst according to claim 1, characterized in that, The key characteristic parameters include chemical composition parameters and physical structure parameters, specifically: Chemical composition parameters include the loss rate of active components and the content of key toxic substances. The loss rate of active components includes both absolute loss and relative loss rate, calculated as follows: ΔC V = C V,fresh - C V,now ΔC W =C W,fresh -C W,now A V = ΔC V / C V,fresh x 100% A W = ΔCW / C W,fresh × 100% wherein C V,now , C W,now are the current contents of V2O5 and WO3, respectively, C V,fresh , C W,fresh are the standard contents of V2O5 and WO3, respectively, of a fresh catalyst of the same type, ΔC V , ΔC W are the absolute losses of V2O5 and WO3, respectively, A V , A W are the relative loss rates of V2O5 and WO3, respectively. Key poisons include SO3, K2O, Na2O, CaO, As2O3, P2O 5； The physical structural parameters include the specific surface area loss rate and the degree of clogging, which are calculated as follows: Specific surface area loss rate: ΔS = (S fresh -S now ) / S fresh × 100% In the formula, S now is the current specific surface area (S now ) S fresh is the standard value for the fresh sample; The degree of blockage refers to the extent of blockage in the catalyst channels. The degree of blockage is obtained through endoscopy or pressure drop testing and is classified into three levels: unobstructed, slightly blocked, and severely blocked.

3. The adaptive replenishment method for the active component of an SCR denitrification catalyst according to claim 2, characterized in that, The specific rules for determining the inactivation type are as follows: Sulfur dominant: SO3 content > 3% and A W A V +5%, and ΔS is between 5%-15%, then it is judged as sulfur poisoning dominant, accompanied by tungsten loss; Alkali poisoning type: (K2O + Na2O) content > 1.5% and A V > A W + 10%, and ΔS < 8%, it is judged as selective poisoning of alkali metal to vanadium sites; Calcium-based blockage type: CaO content >2% and ΔS >15%, indicating severe blockage, which is mainly due to physical deactivation caused by calcium-based fly ash blockage; Arsenic / phosphorus chemical poisoning type: If the content of As2O3 or P2O5 exceeds the threshold, it is marked as chemical poisoning. Composite inactivation type: The inactivation type judgment module makes a comprehensive judgment based on the weighted scores of various parameters.

4. The adaptive replenishment method for the active component of an SCR denitrification catalyst according to claim 3, characterized in that, In the replenishment strategy generation module, the replenishment order of active components is determined based on the catalyst deactivation type: Sulfur-dominant type: Follow the order of supplementing tungsten first, then vanadium; Alkali metal poisoning type: Follow the order of replenishing vanadium first, then tungsten, and add a small amount of phosphate to the vanadium impregnation solution; In the load concentration calculation module, the target load concentrations (C) of vanadium and tungsten are... V,target C W,target The value is dynamically determined by the following function: C i,target = f (A i ,ΔS, poison content, catalyst type) In the formula, i represents vanadium or tungsten; The process parameter adjustment module uses specific surface area loss rate and clogging rating to adjust the impregnation process parameters.

5. The adaptive replenishment method for the active component of an SCR denitrification catalyst according to claim 1, characterized in that, The specific steps to achieve adaptive replenishment of the active components in the SCR denitrification catalyst are as follows: The control system delivers raw material liquid and additives through a precision metering pump according to the replenishment strategy, monitors the component concentration in real time with an online concentration meter, and adjusts the concentration to the target concentration through closed-loop feedback to complete the impregnation solution preparation. The control system controls the robotic arm to transfer the catalyst module to the impregnation tank. The weighing system monitors the weight gain curve of the catalyst module in real time, and determines the adsorption saturation endpoint based on the gradual weight gain rate, and dynamically adjusts the impregnation time. After impregnation, the control system controls the robotic arm to transfer the catalyst module to complete the draining and converter processes in a closed, dry, low-oxygen, inert atmosphere. Before calcination after drying, the control system uses laser-induced breakdown spectroscopy to conduct online sampling inspections of the active component distribution and loading of the catalyst module. The results are fed back to the control system, and an alarm is triggered when an anomaly occurs, and the process parameters for subsequent batches are automatically corrected.

6. A regeneration system for the active component of an SCR denitrification catalyst, characterized in that, It includes a feeding and intelligent detection unit, a central control and decision-making unit, an impregnation solution supply and preparation unit, a multi-mode impregnation execution unit, a closed draining and transmission unit, a program heat treatment unit, and a data management and human-machine interaction unit. The feeding and intelligent detection unit includes an automatic conveyor line, a barcode / RFID identification system, a sampling robotic arm, a rapid XRF detection station, a rapid BET detection station, and an endoscope detection station. The central control and decision-making unit includes an industrial computer equipped with intelligent decision-making software and a central database. The intelligent decision-making software has a built-in process knowledge base and a computer program that runs the methods described in claims 1 to 5. The impregnation solution supply and preparation unit includes multiple raw material storage tanks, a precision metering pump set, an online concentration analyzer, a mixing tank, a constant temperature system, and delivery pipelines. The raw material storage tanks are vanadium salt storage tanks, tungsten salt storage tanks, acid storage tanks, auxiliary agent storage tanks, and deionized water storage tanks. The multi-mode impregnation execution unit includes multiple independently controlled impregnation tanks, each equipped with a lifting mechanism, a temperature control module, a stirring / bubbling assembly, a liquid level sensor, and a weighing sensing system. The closed draining and conveying unit includes a tilting drainer and a closed conveyor belt. The draining zone of the tilting drainer is a closed chamber with a pipeline for introducing hot drying nitrogen. The program heat treatment unit is an integrated chain or roller heat treatment furnace. The front section of the furnace body is equipped with a multi-temperature zone programmable drying belt, and the rear section is equipped with a calcination belt. An atmosphere control component is installed inside the furnace. The data management and human-computer interaction unit includes a large-screen display board and a human-computer interaction terminal, and has built-in process formula management module, report generation module, and remote diagnosis module.

7. The SCR denitrification catalyst active component regeneration system according to claim 6, characterized in that, The feeding and intelligent detection unit is used for conveying, identifying, sampling, and detecting the catalyst to be regenerated, and the detection data is uploaded to the central database; the central control and decision-making unit is used for receiving detection and equipment operation data, generating process instructions, and scheduling various execution units; the impregnation solution supply and preparation unit is used for preparing, conveying, and maintaining the concentration of the impregnation solution; the multi-mode impregnation execution unit is used for executing multi-mode impregnation processes and monitoring the impregnation process; the closed draining and transmission unit is used for draining the catalyst after impregnation and for closed transmission between processes; the programmed heat treatment unit is used for programmed drying and calcination of the catalyst; and the data management and human-machine interaction unit is used for real-time display of production data and system operation and maintenance management.

8. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of an adaptive replenishment method for the active component of an SCR denitrification catalyst as described in any one of claims 1 to 5.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of an adaptive replenishment method for the active component of an SCR denitrification catalyst as described in any one of claims 1 to 5.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of an adaptive replenishment method for the active component of an SCR denitrification catalyst as described in any one of claims 1 to 5.

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