Circuit board metal smelting regeneration waste gas purification method and system

Abstract

The invention discloses a circuit board metal smelting regeneration waste gas purification method and system, and relates to the technical field of waste gas purification. The method comprises the following steps: carrying out particle size regulation, physical inerting and chemical stabilization treatment on submicron phosphorus oxide dust generated by flame retardant cracking in the circuit board metal smelting waste gas; residual dust particles in the circuit board metal smelting waste gas are subjected to directional charging treatment, and fine particles which are difficult to physically settle or neutralize in the high-temperature tail gas are inhibited from entering a catalytic reactor area; based on the multi-source real-time operation data, the deposition trend of residual dust in the circuit board metal smelting waste gas on the surface of a catalyst is dynamically evaluated, a deposition risk index is constructed, predictive judgment is conducted on the deposition state, and a deposition early warning signal is generated; multi-strategy regulation and control are dynamically executed according to the deposition early warning signal, the dust deposition trend is inhibited, and a catalytic structure is protected; the problems of catalytic poisoning induced by submicron phosphorus oxide dust and uncontrollable deposition are solved.

Description

Technical Field

[0001] This invention relates to the field of waste gas purification technology, and more specifically, to a method and system for purifying waste gas from circuit board metal smelting and regeneration. Background Technology

[0002] With the rapid development of the electronic waste recycling industry, circuit board metal smelting and regeneration processes have been widely applied in the recycling of high-value metals. During these high-temperature smelting processes, the exhaust gas often contains submicron-sized phosphorus oxide dust due to the cracking of flame retardants, fluxes, and composite resins. Because this dust has a small particle size, high surface energy, and readily contains active phosphate groups, it often exhibits high adhesion and catalytic poisoning capabilities, making it difficult to achieve efficient collection through traditional cyclone separation or simple filtration methods. Over long periods of operation, this highly reactive dust easily forms unstable deposits on the surface of the catalytic purification module or pipe walls, leading to problems such as catalyst active site poisoning, decreased heat transfer performance, and increased pressure drop, severely affecting purification efficiency and system stability.

[0003] While some existing technologies attempt to slow down the deposition process using methods such as front-end cooling, mechanical disturbance, or periodic dust removal, most rely on passive removal methods and lack fundamental treatment of the source nature of submicron-level dust. Furthermore, they lack a deposition risk identification mechanism linked to operational status, often responding only after significant deposition has already occurred. This results in delayed device response, low control precision, and even unplanned shutdowns of the purification system. Significant technical bottlenecks remain, particularly in regeneration conditions with high phosphorus content and high exhaust gas loads, where dust collection efficiency, catalytic poisoning control capabilities, and intelligent system adjustment capabilities are crucial.

[0004] Therefore, there is an urgent need to build a comprehensive solution with efficient dust inerting, high-performance charge control, and real-time early warning capabilities for deposition trends. Summary of the Invention

[0005] To overcome the aforementioned deficiencies of the prior art and achieve the above objectives, the present invention provides the following technical solution: a method for purifying waste gas from circuit board metal smelting and regeneration, comprising:

[0006] Particle size control, physical inerting and chemical stabilization treatment are carried out on submicron-sized phosphorus oxide dust generated by the cracking of flame retardants in the exhaust gas of circuit board metal smelting.

[0007] Directional charging treatment is performed on residual dust particles in the exhaust gas from the smelting of circuit board metals to inhibit fine particles in the high-temperature exhaust gas that are difficult to physically settle or neutralize from entering the catalytic reactor area.

[0008] Based on real-time multi-source operational data, the deposition trend of residual dust in the waste gas of circuit board metal smelting on the catalyst surface is dynamically evaluated, a deposition risk index is constructed, and a predictive judgment of the deposition state is made to generate a deposition early warning signal.

[0009] Dynamically implement multi-strategy regulation based on deposition early warning signals to suppress dust deposition trends and protect catalytic structures.

[0010] Furthermore, the sedimentation early warning signals include high sedimentation risk early warning signals, medium sedimentation risk early warning signals, and low sedimentation risk early warning signals; the method for dynamically implementing multi-strategy control based on the sedimentation early warning signals includes:

[0011] When the deposition warning signal is a high deposition risk warning signal, the linkage response adjustment module calls the high-intensity control scheme; specifically, it includes: increasing the discharge voltage of the non-thermal plasma charging unit according to the preset voltage increase ratio, adjusting the electrode spacing and discharge frequency, triggering high-frequency backflush operation to disturb the deposition potential zone, adjusting the alkaline composite powder injection rate in the turbulent mixing-reaction zone, and intermittently cooling the waste gas flow.

[0012] When the deposition warning signal is a medium deposition risk warning signal, maintain the rated discharge voltage, adjust the discharge frequency, adjust the backflushing frequency and directional disturbance, maintain the alkaline composite powder injection flow rate, and monitor the catalyst temperature status.

[0013] When the sedimentation early warning signal is a low sedimentation risk warning signal, the linkage response adjustment module executes the minimum intervention mode; specifically, the linkage response adjustment module maintains each system unit at the default operating parameters, and only maintains continuous monitoring of sedimentation indicators and operating parameters.

[0014] Furthermore, the method for constructing the deposition risk index includes:

[0015] Continuous monitoring of multi-source real-time operating data during high-temperature exhaust gas operation; the multi-source real-time operating data includes exhaust gas instantaneous flow rate, exhaust gas temperature, particle size distribution histogram, dust volume concentration, particle charge potential, infrared reflectance change rate of catalytic surface, and pressure drop change rate before and after the catalytic bed per unit time.

[0016] Based on the particle size distribution histogram, the particle size is divided into N particle size segments, each corresponding to a particle size range; the median particle size is calculated for each particle size segment, and the proportion of particles in that particle size segment in the total particle population is obtained, which is denoted as the particle size segment proportion.

[0017] Based on the median particle size, the proportion of each particle size segment, and the instantaneous flow velocity of the exhaust gas for each of the N particle size segments, the inertial contribution of each of the N particle size segments is calculated; the inertial deposition tendency factor is obtained by summing the N inertial contributions.

[0018] Based on dust volume concentration, particle charge potential, and the median and percentage of particle size corresponding to N particle size segments, the charge migration capacity index is calculated.

[0019] The thermally driven adhesion index was calculated based on the waste gas temperature, the rate of change of infrared reflectance of the catalytic surface, and the rate of change of pressure drop across the catalytic bed per unit time.

[0020] The inertial deposition tendency factor, charge migration ability index, and thermally driven adhesion index were used to construct a deposition risk index.

[0021] Furthermore, the method for obtaining the deposition early warning signal includes:

[0022] Preset deposition risk scoring threshold 1 and deposition risk scoring threshold 2; deposition risk scoring threshold 1 is less than deposition risk scoring threshold 2;

[0023] A sedimentation risk score is calculated based on sedimentation risk indicators;

[0024] If the sedimentation risk score is greater than or equal to the sedimentation risk score threshold 2, a high sedimentation risk warning signal is generated; if the sedimentation risk score is greater than or equal to the sedimentation risk score threshold 1 and less than the sedimentation risk score threshold 2, a medium sedimentation risk warning signal is generated; if the sedimentation risk score is less than the sedimentation risk score threshold 1, a low sedimentation risk warning signal is generated.

[0025] Furthermore, methods for directional charging treatment of residual dust particles in the exhaust gas from circuit board metal smelting include:

[0026] A non-thermal plasma charging unit is installed in the main channel of high-temperature exhaust gas to perform directional charging treatment on the fine particulate matter remaining in the exhaust gas. The non-thermal plasma charging unit has multiple insulated needle-shaped high-voltage discharge electrodes arranged along the flow direction of the main exhaust gas channel. Each electrode is subjected to a DC high voltage through a power control module to form a stable corona discharge region between the electrodes. In the corona discharge region, the high-energy free electrons and ionized plasma clusters released during the discharge process act on the dust particles flowing through the corona discharge region, causing a stable directional charge layer to form on the dust surface.

[0027] Furthermore, the non-thermal plasma charging unit is linked to a dust charging state feedback adjustment unit; the feedback adjustment unit acquires monitoring operating parameters; the monitoring operating parameters include the instantaneous flow rate of the exhaust gas, temperature, dust volume and concentration, and evaluates the particle charging efficiency score of the current particle group based on the monitoring operating parameters; if the particle charging efficiency score is lower than a preset charging efficiency score threshold, the system constructs a charging adjustment model based on the monitoring operating parameters and the particle charging efficiency score, and outputs the corresponding charging adjustment parameters, which include discharge voltage, electrode spacing and frequency adjustment commands;

[0028] Based on the generated charge adjustment parameters, the corona discharge conditions are adjusted in real time to optimize the spatial distribution of free electron density and discharge region. The adjustment process is executed cyclically until the particle charge efficiency score reaches or exceeds the preset charge efficiency score threshold. Once the charge target is determined to be achieved, the charge adjustment operation is stopped, and the directional charge on the particle surface is completed.

[0029] Furthermore, methods for particle size control, physical inerting, and chemical stabilization of submicron-sized phosphorus oxide dust generated from the decomposition of flame retardants in the exhaust gas from circuit board metal smelting include:

[0030] The high-temperature exhaust gas emitted during the smelting of circuit board metal is introduced into a turbulent mixing-reaction zone located at the front end of the purification system; the turbulent mixing-reaction zone is a closed high-temperature reaction chamber;

[0031] Alkaline composite powder is continuously injected into the turbulent mixing-reaction zone through an alkaline composite powder injection device located upstream of the turbulent mixing-reaction zone.

[0032] The alkaline composite powder is introduced through a high-temperature pneumatic injector. Under the action of high-pressure carrier gas, the high-temperature pneumatic injector injects the alkaline composite powder into the turbulent mixing-reaction zone in a high-speed atomized state, so that the alkaline composite powder can fully contact and quickly mix with the submicron-sized phosphorus oxide dust carried in the exhaust gas.

[0033] Within the turbulent mixing-reaction zone, a solid-aerosol reaction occurs between the waste gas and the alkaline composite powder to generate a phosphate complex. Under turbulent thermal diffusion conditions, the phosphate complex precipitates out in the form of particles, forming phosphate particles.

[0034] The phosphate structure is transformed into a stable compound, the surface free energy of the phosphate particles decreases, and the electrostatic adsorption force and liquid bridging between particles are weakened, ultimately completing the particle size control, physical inerting and chemical stabilization treatment of submicron-sized phosphorus oxide dust.

[0035] Furthermore, the method for obtaining the particle charge efficiency score includes:

[0036] The monitored operating parameters are input into the particle charge efficiency evaluation model to obtain the corresponding particle charge efficiency score.

[0037] Furthermore, the training method for the particle charge efficiency evaluation model includes:

[0038] A particle charge efficiency evaluation dataset is pre-constructed, which includes PG group particle charge efficiency evaluation data and corresponding particle charge efficiency scores, where PG is a positive integer; the particle charge efficiency evaluation data includes monitoring operating parameters; the particle charge efficiency evaluation dataset is divided into a training set and a validation set, the training set is used for learning the parameters of the particle charge efficiency evaluation model, and the validation set is used for real-time monitoring of the generalization performance and overfitting of the particle charge efficiency evaluation model;

[0039] A support vector machine model is used as the particle charge efficiency evaluation model. The softmax activation function is used to obtain the probability distribution corresponding to each particle charge efficiency score. Finally, the particle charge efficiency score corresponding to the highest probability is taken as the prediction result of the particle charge efficiency evaluation model. During the training process, the cross-entropy loss function is used as the optimization objective, and the gradient descent optimization algorithm is used to update the network weights. An early stopping strategy is set: when the prediction accuracy on the validation set reaches or exceeds the preset prediction accuracy threshold, it is determined that the particle charge efficiency evaluation model has converged and the training is terminated.

[0040] A circuit board metal smelting and regeneration waste gas purification system is used to implement the circuit board metal smelting and regeneration waste gas purification method, including:

[0041] The pyrolysis interception module is used to control the particle size, physically inertize and chemically stabilize the submicron-sized phosphorus oxide dust generated by the pyrolysis of flame retardants in the exhaust gas of circuit board metal smelting.

[0042] The dust charge control module is used to perform directional charge treatment on the dust particles remaining in the exhaust gas of circuit board metal smelting, and to inhibit the entry of fine particles in the high-temperature exhaust gas that are difficult to physically settle or neutralize into the catalytic reactor area.

[0043] The intelligent deposition early warning module is used to dynamically assess the deposition trend of residual dust in the waste gas of circuit board metal smelting on the catalyst surface based on real-time multi-source operation data, construct deposition risk indicators, make predictive judgments on deposition status, and generate deposition early warning signals.

[0044] The linkage response adjustment module is used to dynamically execute multi-strategy regulation based on the deposition early warning signal to suppress the dust deposition trend and protect the catalytic structure.

[0045] Compared with existing technologies, the technical effects and advantages of the circuit board metal smelting regeneration waste gas purification method and system of the present invention are as follows:

[0046] This application provides a method and system for purifying waste gas during the metal smelting and regeneration process of printed circuit boards. It addresses the problems in the prior art where submicron-level phosphorus oxide dust is difficult to capture, easily induces catalytic poisoning, and causes system failure due to uncontrollable deposition. By setting up a pyrolysis interception module, alkaline composite powder reacts with gaseous phosphorus and oxygen dust in the exhaust gas under turbulent high-temperature conditions in a solid-aerosol reaction. This transforms highly active dust into phosphate particles with increased particle size, reduced surface energy, and no active phosphate structure, significantly reducing dust adhesion and catalytic poisoning potential. Furthermore, through a non-thermal plasma charging unit and a dust charging regulation module, efficient directional charging of residual dust is achieved, improving downstream collection efficiency. Simultaneously, an intelligent deposition early warning module is set up to dynamically construct deposition characteristic indicators based on multi-source real-time operating data, calculate deposition risk scores, and generate risk level signals. The system can identify risks and issue early warnings in real time before deposition occurs. Combined with a linkage response regulation module, non-thermal plasma discharge parameters, alkaline composite powder injection rate, backflushing rhythm, and cooling intensity are precisely controlled according to different deposition risk levels, thereby establishing an integrated closed-loop anti-deposition mechanism of "identification-early warning-response-regulation".

[0047] Compared to existing technologies that rely on static collection and fixed-frequency cleaning, this application not only significantly improves the purification efficiency and treatment stability of submicron dust, but also effectively slows down the degradation process of catalytic structure performance, improves the continuity and reliability of system operation, and has the advantages of high real-time performance, high selectivity and high engineering adaptability. It is particularly suitable for high-load circuit board smelting exhaust gas purification scenarios containing phosphorus additives or flame retardant components. Attached Figure Description

[0048] Figure 1 This is a schematic diagram of the waste gas purification system for circuit board metal smelting and regeneration in Embodiment 1 of the present invention;

[0049] Figure 2 This is a flowchart of the waste gas purification method for circuit board metal smelting and regeneration according to Embodiment 2 of the present invention;

[0050] Figure 3 A flowchart illustrating the methods for particle size control, physical inerting, and chemical stabilization.

[0051] Figure 4 Here is a flowchart of a method for generating sedimentation early warning signals based on sedimentation risk indicators;

[0052] Figure 5 This is a schematic diagram of the linkage response adjustment strategy. Detailed Implementation

[0053] The technical solutions of the embodiments of the present invention will be described in detail, clearly, and completely below with reference to the accompanying drawings. It should be particularly noted that the specific embodiments described below are only for better illustrating and explaining the technical solutions of the present invention, and are intended to enable those skilled in the art to better understand and implement the present invention, and should not be construed as limiting the scope of protection of the present invention. Without departing from the spirit and substance of the present invention, those skilled in the art can modify, adjust, or make equivalent substitutions based on the content disclosed in the present invention, and these should all be considered within the scope of protection of the present invention.

[0054] Example 1

[0055] Please see Figure 1 As shown, this embodiment discloses a circuit board metal smelting and regeneration waste gas purification system, including a pyrolysis interception module, a dust charge control module, an intelligent deposition early warning module, and a linkage response adjustment module. Each module is connected by wires and / or wirelessly to realize data transmission.

[0056] The pyrolysis interception module is used to control the particle size, physically inertize, and chemically stabilize the submicron-sized phosphorus oxide dust generated by the pyrolysis of flame retardants in the exhaust gas from the smelting of circuit board metals. This improves the controllability of particulate matter in subsequent treatment processes and effectively reduces the risk of passivation of the catalyst surface.

[0057] like Figure 3 As shown, the methods for particle size control, physical inerting, and chemical stabilization of submicron-sized phosphorus oxide dust generated by the decomposition of flame retardants in the exhaust gas from circuit board metal smelting include:

[0058] The high-temperature exhaust gas emitted during the smelting of circuit board metal is introduced into a turbulent mixing-reaction zone located at the front end of the purification system. The turbulent mixing-reaction zone is a closed high-temperature reaction chamber with a flow guiding structure designed inside to form a high-shear turbulent flow field, thereby enhancing the mixing rate inside the gas and the collision frequency between particles, and ensuring the uniformity and fullness of the solid-gas mixing process.

[0059] Alkaline composite powder is continuously injected into the turbulent mixing-reaction zone via an alkaline composite powder injection device located upstream of the zone. The alkaline composite powder is preferably a CaO / Al₂O₃ composite powder, wherein the molar ratio of calcium oxide to aluminum oxide is controlled between 3.0:1 and 3.5:1 to ensure both good phosphate ion capture capacity and high-temperature structural stability. The average particle size of the alkaline composite powder is controlled within the range of 0.6 to 0.9 micrometers, possessing a large specific surface area and active contact interface, enabling rapid dispersion and reaction in high-temperature gas flow.

[0060] The alkaline composite powder is introduced through a high-temperature pneumatic injector. Under the action of high-pressure carrier gas, the injector injects the alkaline composite powder into the turbulent mixing-reaction zone in a high-speed atomized state, so that the alkaline composite powder can fully contact and quickly mix with the submicron-sized phosphorus oxide dust carried in the exhaust gas.

[0061] In the turbulent mixing-reaction zone, a solid-aerosol reaction occurs between the waste gas and the alkaline composite powder to generate a phosphate composite with a high melting point, such as Ca9Al6(PO4)7. Under turbulent thermal diffusion conditions, the phosphate composite precipitates out in the form of particles with a particle size of 3 to 5 micrometers, forming phosphate particles.

[0062] The phosphate structure is transformed into a stable compound, the surface free energy of phosphate particles decreases, and the electrostatic adsorption force and liquid bridging effect between particles are weakened. Finally, the submicron-sized phosphorus oxide dust is subjected to particle size control, physical inerting and chemical stabilization treatment, and the overall performance shows a reduced tendency to stick and good physical inerting properties.

[0063] It should be noted that, specifically, Ca 2+ And Al 3+ Ions and PO4 3- The groups undergo neutralization and complexation reactions to generate phosphate complexes with high melting points. The melting point of the phosphate complex is greater than 1100℃, which is much higher than the adhesion threshold temperature of submicron phosphorus oxide dust, typically 500℃ to 650℃. Therefore, it can effectively prevent liquid-phase adhesion to the high-temperature pipe walls or catalyst surfaces in subsequent processes.

[0064] Within the solid-aerosol reaction residence time range, if controlled between 0.8 and 1.2 seconds, most of the original submicron-sized phosphorus oxide dust is converted into larger, more stable phosphate particles. Particle size analysis shows that the average particle size of the converted dust increases to between 3 and 5 micrometers, and the particle specific gravity increases to approximately 3.5 g / cm³, significantly improving the gravity settling and inertial separation efficiency. Simultaneously, as the phosphate structure is completely converted into a stable compound, the surface free energy of the particles decreases significantly, and the electrostatic adsorption and liquid bridging effects between particles are greatly weakened, resulting in a reduced adhesion tendency and good physical inertization properties.

[0065] More importantly, due to the aforementioned transformation process, the surface of phosphate particles no longer exposes active phosphate functional groups. These particles cannot react further with the active sites on the catalyst surface, nor do they form a dense deposition layer that inhibits the catalytic reaction. Therefore, they are considered to have high chemical stability, such as oxygen vacancies on the active sites of the catalyst surface, like V₂O₅ and TiO₂ supports. Through the above-mentioned particle size control, physical inerting, and chemical stabilization processes, the physical-chemical pathway of catalyst poisoning induced by submicron-sized phosphorus oxide dust can be cut off at its source, providing a clean and controllable gaseous environment for subsequent charge control, deposition early warning, and regeneration recovery units.

[0066] It should be noted that the submicron-sized phosphorus oxide dust refers to phosphorus-oxygen-based high-temperature aerosol particles with a particle size of less than 1 micrometer. Its main formation mechanism involves the thermal decomposition of phosphorus-containing flame retardants, such as ammonium polyphosphate and red phosphorus-based systems, at melting temperatures of 850℃ to 1100℃, reacting with oxygen in the furnace to generate phosphorus pentoxide (P₂O₅) or in a hydrated state. Submicron-sized phosphorus oxide dust possesses characteristics such as low melting point, high surface energy, and a tendency to undergo liquid-phase bridging and autocatalytic deposition on high-temperature surfaces, making it a key factor affecting catalyst lifetime and downstream purification stability.

[0067] The high surface energy refers to the high surface free energy per unit surface area of ​​particulate matter, manifested as an unsaturated and unstable energy state of its surface atoms / molecules, making them prone to physical adsorption, chemical adsorption, or liquid-phase fusion with other substances, especially metal oxides or catalyst surfaces. The high surface energy of the submicron-sized phosphorus oxide dust described in this application is manifested in the following ways: First, it enhances the tendency for particle aggregation, i.e., high surface energy leads to enhanced van der Waals forces, electrostatic attraction, or liquid bridging between particles, making it easier to form metastable cluster structures at high temperatures. Second, it enhances the affinity with catalyst surfaces, i.e., high surface energy particles are easily adsorbed or undergo interfacial chemical bonding when in contact with catalyst supports with surface hydroxyl groups or metallic active sites, such as titanium dioxide (TiO2) and vanadium pentoxide (V2O5). Third, it induces melt bridging behavior, i.e., when particles have low melting points and high surface energy, liquid-phase bridging or agglomeration deposition occurs near the catalyst surface close to or above its softening point, forming a non-uniform coating. Therefore, the high surface energy emphasizes its high-temperature surface adhesion and deposition dominance in the specification, which is one of the physical reasons for the irreversible contamination of the catalyst by submicron-level phosphorus oxide dust.

[0068] Affecting catalyst lifetime refers to shortening the effective operating cycle of the catalyst in maintaining the target reaction activity. In the embodiments of this application, it mainly affects active site shielding, pore blockage, and irreversible structural damage. Active site shielding refers to the formation of a dense, non-catalytic coating layer after submicron-sized phosphorus oxide dust deposits on the surface of vanadium pentoxide (V₂O₅) or titanium dioxide (TiO₂), inhibiting the reaction contact between the target gas and the catalyst surface. Pore blockage refers to the tendency of small dust particles to deposit at the pore inlets of honeycomb or porous catalyst supports, causing localized pressure drops and uneven gas flow distribution. Irreversible structural damage refers to the chemical reaction between submicron-sized phosphorus oxide dust and catalyst components at high temperatures, such as the formation of calcium phosphate salt deposits, which damage the catalyst's crystal structure and support stability, leading to a continuous decline in catalytic activity. Therefore, affecting catalyst lifetime is not merely about reducing performance, but specifically refers to the actual technical consequences such as accelerated catalytic activity decay rate, shortened regeneration cycle, and even irreversible structural damage.

[0069] The submicron-sized phosphorus oxide dust possesses low melting point and high surface energy, leading to easy agglomeration and adhesion of particles under high-temperature conditions, resulting in liquid-phase bridging on the catalyst support surface and the formation of a continuous deposition layer. This deposition process not only obscures the active sites on the catalyst surface but also triggers irreversible phosphate passivation reactions, causing catalyst poisoning, significantly shortening the effective working life of the catalyst, and compromising the stability of the downstream purification system. Catalytic poisoning refers to the process in which exogenous substances undergo strong adsorption, bonding, or substitution reactions with active sites on the catalyst surface, such as metal oxide crystal faces, oxygen vacancies, and hydroxyl groups on the support, leading to a decrease or stagnation of the catalytic reaction rate. Catalytic poisoning can be classified as reversible or irreversible. Reversible poisoning includes CO adsorption, while irreversible poisoning includes submicron-sized phosphorus oxide dust poisoning. Therefore, the irreversible catalyst poisoning phenomenon caused by submicron-sized phosphorus oxide dust is the technical problem to be solved in this application.

[0070] The dust charge control module is used to directionally charge the dust particles remaining in the exhaust gas from the smelting of circuit board metals, further suppressing fine particles in the high-temperature exhaust gas that are difficult to physically settle or neutralize from entering the catalytic reactor area, thereby protecting the integrity of the catalytic carrier surface and the reaction efficiency.

[0071] It should be noted that after the pyrolysis interception module completes its treatment, a small amount of unreacted submicron-sized phosphorus oxide dust and particulate matter with increased particle size but still possessing strong adsorption or reactivity remain in the waste gas from circuit board metal smelting. Due to their small particle size (<1.0µm) or the presence of insufficiently passivated phosphate functional groups on their surface, the remaining unreacted submicron-sized phosphorus oxide dust has insufficient migration ability during conventional physical sedimentation or cyclone separation. It easily enters the subsequent catalytic oxidation unit with the high-temperature gas flow, depositing or causing structural interference on the catalyst surface, thus reducing the effective reaction area and lifespan of the catalyst. To enhance the migration control capability of the aforementioned residual submicron-sized dust and surface-active particles in the waste gas, this application includes a dust charge regulation module. This module includes a non-thermal plasma charging unit, a corona discharge electrode plate, a high-temperature electric field guiding structure, and a dust charge state feedback regulation unit.

[0072] Methods for directional charging treatment of residual dust particles in the exhaust gas from circuit board metal smelting include:

[0073] A non-thermal plasma charging unit is installed in the main channel of high-temperature exhaust gas to perform directional charging treatment on the fine particulate matter remaining in the exhaust gas. The non-thermal plasma charging unit has multiple insulated needle-shaped high-voltage discharge electrodes arranged along the flow direction of the main exhaust gas channel. Each electrode is subjected to a DC high voltage through a power control module. The DC voltage is preferably in the range of 22 kV to 28 kV to form a stable corona discharge region between the electrodes. In this corona discharge region, the high-energy free electrons and ionized plasma clusters released during the discharge process act on the dust particles flowing through the region, causing a stable directional charge layer to form on the surface of the dust particles.

[0074] Specifically, the dust particles remaining in the waste gas from the smelting of circuit board metal include, but are not limited to: fine phosphate particles with a particle size of less than 1 micrometer; neutral or partially reactive particles with a particle size between 1 and 3 micrometers and containing strong electrophilic groups on their surface, such as phosphate ions (PO4). 3- ; and composite particles formed by the agglomeration of phosphates and organic pyrolysis products. When the above dust particles enter the corona discharge region, they achieve directional charging of the particle surface through high-frequency collisions with free electrons and ionized clusters, thereby improving their mobility and controllability in subsequent electric or composite fields;

[0075] To ensure the real-time performance and accuracy of the charging process, the non-thermal plasma charging unit is linked to a dust charging state feedback and adjustment unit. This feedback and adjustment unit acquires monitoring operating parameters, including the instantaneous flow rate of the exhaust gas, temperature, dust volume and concentration, and evaluates the particle charging efficiency score of the current particle group based on the monitoring operating parameters. If the particle charging efficiency score is lower than a preset charging efficiency score threshold, the system constructs a charging adjustment model based on the monitoring operating parameters and the particle charging efficiency score, and outputs the corresponding charging adjustment parameters, including discharge voltage, electrode spacing and frequency adjustment commands.

[0076] It should be noted that the particle charge efficiency score is used to comprehensively reflect the charging effect achieved by the current particle population under non-thermal plasma charging treatment. The particle charge efficiency score can be a quantitative result ranging from 0 to 100. The higher the particle charge efficiency score, the more sufficient the surface charge formation of the particle population and the better the migration response capability. When the particle charge efficiency score is lower than the charge efficiency score threshold, an automatic adjustment process for the charge parameters is triggered. The charge efficiency score threshold can be set, for example, to 85 points. The dust charge state feedback adjustment unit includes an electrode probe for measuring aerosol ion concentration and a particle migration rate sensor based on the Coulomb principle.

[0077] The system adjusts the corona discharge conditions in real time based on the generated charge adjustment parameters, optimizing the spatial distribution of free electron density and discharge region to improve the charge efficiency of the particle surface. The adjustment process is executed cyclically until the particle charge efficiency score reaches or exceeds the preset charge efficiency score threshold. At this point, the system determines that the charge target has been achieved, stops the charge adjustment operation, completes the directional charge of the particle surface, and finally achieves a stable control effect of directional charge of dust particle surface, enhances the charge injection effect, and realizes closed-loop control of the entire charge process.

[0078] The method for obtaining the particle charge efficiency score includes:

[0079] The monitored operating parameters are input into the particle charge efficiency evaluation model to obtain the corresponding particle charge efficiency score.

[0080] The training method for the particle charge efficiency evaluation model includes:

[0081] A particle charge efficiency evaluation dataset is pre-constructed, which includes PG group particle charge efficiency evaluation data and corresponding particle charge efficiency scores, where PG is a positive integer; the particle charge efficiency evaluation data includes monitoring operating parameters; the particle charge efficiency evaluation dataset is divided into a training set and a validation set, the training set is used for learning the parameters of the particle charge efficiency evaluation model, and the validation set is used for real-time monitoring of the generalization performance and overfitting of the particle charge efficiency evaluation model;

[0082] A support vector machine (SVM) model is used as the particle charge efficiency evaluation model. A softmax activation function is employed to obtain the probability distribution corresponding to each particle charge efficiency score. Finally, the particle charge efficiency score corresponding to the highest probability is taken as the prediction result of the particle charge efficiency evaluation model. During training, the cross-entropy loss function is used as the optimization objective, and a gradient descent-like optimization algorithm is used to update the network weights. An early stopping strategy is implemented: when the prediction accuracy on the validation set reaches or exceeds a preset prediction accuracy threshold, the particle charge efficiency evaluation model is considered to have converged, and training is terminated. For example, the prediction accuracy threshold is set to 95%, meaning that when the prediction accuracy on the validation set reaches or exceeds 95%, the particle charge efficiency evaluation model is considered to have converged.

[0083] The training method for the charge regulation model includes:

[0084] A pre-constructed equipment charge regulation dataset is constructed, which includes HD group equipment charge regulation data and corresponding charge regulation parameters for HD group equipment charge regulation data, where HD is a positive integer; the equipment charge regulation data includes monitoring operating parameters and particle charge efficiency scores; the equipment charge regulation dataset is divided into a training set and a validation set, the training set is used for learning the parameters of the charge regulation model, and the validation set is used for real-time monitoring of the generalization performance and overfitting degree of the charge regulation model;

[0085] A gradient boosting tree model is used as the charge regulation model. The charge regulation data of the equipment is standardized and vectorized before being input into a deep neural network. The output layer uses the Softmax activation function to obtain the probability distribution corresponding to each charge regulation parameter. Finally, the charge regulation parameter corresponding to the highest probability is taken as the prediction result of the charge regulation model. During the training process, the cross-entropy loss function is used as the optimization objective, and a gradient descent-type optimization algorithm is used to update the network weights. An early stopping strategy is set: when the prediction accuracy on the validation set reaches or exceeds the preset prediction accuracy threshold, the charge regulation model is determined to have converged and training is terminated.

[0086] It should be noted that under the influence of an electric field, submicron particles with a diameter of less than 1 micrometer are prone to circling and distributing themselves in subsequent airflow disturbances due to their low bulk inertia, making them difficult to effectively capture by conventional centrifugal or gravity separators. Through the aforementioned charging treatment, these submicron dust particles acquire a negative charge on their surface, with the charge per unit particle reaching the range of 0.5 to 1.2 fecoulombs, giving the particles a significant directional migration capability. Through the dust charging control module, the originally small-diameter, poorly migratable submicron residual particles acquire a directional charge in the high-temperature flow field, significantly enhancing their migration ability. Ultimately, they can be effectively captured in the subsequent separation module, preventing them from entering the catalytic reactor area and adhering to the catalyst surface. This protects the active centers on the catalyst surface, extends the catalyst's lifespan, and stabilizes the exhaust gas purification performance.

[0087] To further clarify, the dust charging control module introduces non-thermal plasma charging into the circuit board metal smelting exhaust gas purification process, achieving effective directional charging of submicron-sized phosphate particles, surface-active dust, and phosphate-organic aggregate particles remaining after the pyrolysis interception module. Through a high-voltage corona discharge electrode positioned within the high-temperature exhaust gas main channel, a stable charge is imparted to fine particulate matter with small size, poor migration performance, and difficulty in being captured by traditional centrifugal or gravity separation structures, without significantly altering the exhaust gas flow characteristics. This significantly enhances their migration response capability in subsequent electric or composite fields, providing a pretreatment foundation for subsequent particle separation and catalytic protection.

[0088] Compared to existing technologies that rely solely on conventional dust removal methods such as physical cyclone or bag filtration, which cannot achieve precise control of submicron-sized dust, the dust charge control module of this invention has the following significant technical effects: First, it can efficiently charge metastable phosphate particles with an average particle size of less than 1 micrometer, enabling these particles to exhibit excellent migration controllability in subsequent separation stages; Second, it can dynamically sense exhaust gas operating parameters and optimize charge efficiency in real time through a feedback adjustment mechanism, avoiding charge failure or dust escape due to exhaust gas fluctuations; Third, it enhances dust migration response through active charging, achieving pre-deflection of easily deposited dust, significantly reducing particle load at the inlet section of the catalytic reactor, and mitigating the tendency of catalyst active site shielding and passivation.

[0089] Especially in the scenario of treating high-temperature smelting waste gas containing phosphorus cracking components, traditional mechanical dust collectors such as bag filters or cyclones are difficult to effectively separate sticky fine particles without introducing a cooling process. This module achieves efficient pre-control under high-temperature conditions through non-thermal plasma charging, which not only maintains process continuity but also significantly improves system integration efficiency, and has strong engineering adaptability and industrial application potential.

[0090] In summary, the dust charge control module establishes a refined dust control mechanism based on particle charge-migration-deflection path control without relying on significant cooling or high-energy-consuming equipment. It breaks through the technical bottlenecks of "indiscriminate treatment of submicron dust" or "uncontrollable charge intensity" in existing technologies. It has significant innovation and creativity in terms of active adjustment capability of particle behavior and protection efficiency of catalytic system, and can provide key support for the deep purification of high-temperature complex waste gas.

[0091] The intelligent deposition early warning module is used to dynamically assess the deposition trend of residual dust in the waste gas of circuit board metal smelting on the catalyst surface based on real-time multi-source operating data, construct deposition risk indicators, make predictive judgments on deposition status, and generate deposition early warning signals.

[0092] The method for constructing the deposition risk index includes:

[0093] Continuous monitoring of multi-source real-time operating data during high-temperature exhaust gas operation; the multi-source real-time operating data includes exhaust gas instantaneous flow rate, exhaust gas temperature, particle size distribution histogram, dust volume concentration, particle charge potential, infrared reflectance change rate of catalytic surface, and pressure drop change rate before and after the catalytic bed per unit time.

[0094] The dust particle size distribution histogram is divided into N particle size segments, each corresponding to a particle size range; the median particle size is calculated for each particle size segment, and the proportion of particles in that particle size segment in the total particle population is obtained, which is denoted as the particle size segment proportion.

[0095] Based on the median particle size, the proportion of each particle size segment, and the instantaneous flow velocity of the exhaust gas for each of the N particle size segments, the inertial contribution of each of the N particle size segments is calculated; the inertial deposition tendency factor is obtained by summing the N inertial contributions.

[0096] Based on dust volume concentration, particle charge potential, and the median and percentage of particle size corresponding to N particle size segments, the charge migration capacity index is calculated.

[0097] The thermally driven adhesion index was calculated based on the waste gas temperature, the rate of change of infrared reflectance of the catalytic surface, and the rate of change of pressure drop across the catalytic bed per unit time.

[0098] The inertial deposition tendency factor, charge migration ability index, and thermally driven adhesion index were used to construct a deposition risk index.

[0099] It should be noted that the instantaneous flow velocity of the exhaust gas is obtained through a hot-film flow meter, the exhaust gas temperature is obtained through a thermocouple, and the particle size distribution histogram is obtained through a laser particle size analyzer. The particle size distribution histogram is used to reflect the number or volume ratio of particles of different sizes in the particle population. The dust volume concentration is obtained through an optical concentration meter, and the particle charge potential is obtained through a charge sensor. Both dust volume concentration and particle charge potential refer to the overall average value on the cross-section of the exhaust gas flow at the current sampling time point, that is, the macroscopic statistical parameters of the entire particle population. The rate of change of infrared reflectivity of the catalytic surface is obtained through an infrared reflection probe, and the rate of change of pressure drop across the catalytic bed per unit time is obtained through a differential pressure sensor. Multi-source real-time operating data is transmitted to the data processing unit through a data bus.

[0100] In this embodiment, to achieve dynamic perception and risk prediction of particle deposition trends, the intelligent deposition early warning module needs to collect multi-source real-time operating data during the operation of the high-temperature exhaust gas system. Synchronous acquisition of multi-source real-time operating data is fundamental to assessing particle deposition trends. Specifically, particle deposition behavior is jointly determined by flow field characteristics and particle dynamics. The instantaneous flow velocity of the exhaust gas directly affects the inertial displacement ability and residence time of particles in the airflow, serving as a core input for assessing inertial deposition risk. Meanwhile, the exhaust gas temperature relates to the melting behavior and surface adhesion tendency of particles on the catalyst surface. At high temperatures, particles are prone to phase transition adhesion, leading to the formation of a difficult-to-remove deposition layer. Therefore, real-time monitoring of flow velocity and temperature is crucial for constructing a particle dynamics model.

[0101] Dust particle size distribution and volume concentration together characterize the collective properties of particulate matter in exhaust gas. Particle size is the main factor determining particle migration path, inertial response, and surface adhesion probability, while volume concentration reflects the density level of particles per unit volume of exhaust gas and is an important basis for judging changes in particle load on the catalytic bed. Particle charge potential reflects the actual response of upstream charge regulation in the system. The degree of charge determines whether particles have sufficient deflection ability to avoid the deposition path on the catalytic surface, and its changes can significantly affect migration efficiency.

[0102] The rate of change of infrared reflectance on the catalytic surface, as an important surface physical parameter characterizing early signs of deposition, can provide real-time feedback on whether particles have begun to form a capping layer on the catalytic surface. When particles accumulate on the catalytic surface, their reflectance usually shows a continuous downward trend, exhibiting strong predictive power. Meanwhile, the rate of change of pressure drop across the catalytic bed per unit time reflects the evolution trend of system channel resistance. When the pressure difference increases rapidly, it often indicates that particle blockage or surface deposition has entered an accelerated phase, making it a key indicator for determining whether the deposition trend has become explicit.

[0103] In summary, by synchronously acquiring the aforementioned multi-source real-time operational data, the system can construct a multi-dimensional assessment perspective encompassing particle behavior characteristics, catalytic surface response, and system pressure drop evolution. This perspective covers both the physical conditions of deposition and the characterization signals of deposition formation, thus providing accurate and continuous data support for the subsequent establishment of deposition risk indicators. This data acquisition process is a prerequisite for the intelligent deposition early warning module to achieve accurate judgment and early warning response, significantly improving the feasibility and engineering reliability of the overall solution of this invention under actual complex working conditions.

[0104] The method for obtaining the inertial deposition tendency factor includes:

[0105] ;

[0106] in, As an inertial deposition tendency factor, This represents the inertial contribution corresponding to the nth particle size segment, where N is the total number of particle size segments. This represents the median particle size corresponding to the nth particle size segment. This represents the squared enhancement effect of particle size on inertial response; The instantaneous velocity of the exhaust gas corresponds to the nth particle size segment, where n is the index variable in the summation formula; the instantaneous velocity of the exhaust gas represents the kinetic energy of the airflow that drives the particles to undergo inertial displacement. This represents the percentage of the particle size range corresponding to the nth particle size range.

[0107] It should be noted that the inertial deposition tendency factor reflects the strength of the tendency of dust particles to deviate from the main airflow path due to inertia and tend to deposit on the catalyst surface or channel wall under the current exhaust gas flow field conditions. It can be used to dynamically determine whether particles have entered a high-deposition-risk state, providing strong trend support for deposition early warning. A larger inertial deposition tendency factor indicates a stronger inertial derailment capability of the particle group under the current operating conditions, and a higher deposition risk. This index is calculated through the coupling relationship between dust particle size distribution and instantaneous exhaust gas velocity, and all calculation data comes from multi-source operating parameters collected in real time by the system, possessing clear data traceability.

[0108] The method for obtaining the charge mobility index includes:

[0109] ;

[0110] in, As an indicator of charge migration capability, Dust volume concentration, This represents the particle's charge potential.

[0111] It should be noted that, in order to quantitatively assess the migration trend of dust particles in the exhaust gas under a charged state and thus predict their potential deposition on downstream surfaces, this application proposes a charged migration capability index to characterize the overall migration response capability of a dust particle population under current charge-driven and flow field conditions. A larger charged migration capability index indicates a stronger migratory capability of the dust population in the current exhaust gas under charge-driven conditions. The charged migration capability index provides a comprehensive assessment quantity reflecting the coupling effect between charge intensity, concentration scale, and particle size characteristics, providing prior feature support for the deposition risk early warning module.

[0112] The charged migration capability index is constructed based on directly collected multi-source real-time operational data, namely dust volume concentration, particle charge potential, median particle size, and particle size segment percentage. First, particle charge potential reflects the overall charge level of the current particle population in the exhaust gas and is the main controlling variable affecting the particle's response capability in an electrostatic field. Second, dust volume concentration characterizes the total quantity of dust per unit volume, directly influencing the macroscopic amplification effect on migration trends. The product of the median particle size and the particle size segment percentage represents the contribution weight of the nth particle size segment to migration capability, reflecting the physical influence factor of "size × percentage" for that particle size segment in the particle population. Summing the contributions of all particle size segments yields the particle size structure intensity of the migration trend. Combining the overall dust volume concentration and particle charge potential achieves a holistic coupling of the microscopic charge properties of particles with macroscopic concentration intensity, thereby constructing a unified dimensional charged migration capability index with explanatory and predictive power.

[0113] The method for obtaining the thermally driven adhesion index includes:

[0114] ;

[0115] in, The thermally driven adhesion index, The exhaust gas temperature, The rate of change of infrared reflectance of the catalytic surface. The rate of change of pressure drop across the catalyst bed per unit time; , and These are the corresponding normalized weighting coefficients. For example, in this application, the following can be used: Set to 0.4, Set it to 0.3, Set it to 0.3.

[0116] It should be noted that, to avoid calculation deviations or confusion of physical meanings caused by inconsistent units of physical quantities in the thermally driven adhesion index formula, the parameters involved in the calculation of the thermally driven adhesion index in this application have been dimensionless and normalized. For example, the numerical range of all parameters in the thermally driven adhesion index formula is limited to... This is to ensure the scientific validity of the formula structure and the comparability of the results.

[0117] Furthermore, in this embodiment, to further enhance the ability to predict particle deposition risks, the system introduces a thermally driven adhesion index to quantitatively assess the risk trends of thermally induced adhesion, melting and bonding, or surface energy-induced deposition of exhaust gas particles in a high-temperature thermal field. This index is specifically designed to capture the thermally induced deposition mechanism triggered by the superposition of three factors: temperature gradient, surface energy change, and pressure drop fluctuation. In addition to particle charge migration and inertial migration indices, it provides an independent risk assessment basis for adhesive deposition.

[0118] Specifically, exhaust gas temperature reflects the thermal energy level of the high-temperature flue gas at the catalytic bed inlet. Higher temperatures increase the probability of particle phase change, softening, or melting, leading to a stronger trend of surface energy reduction. Consequently, particles are more easily passively attached to downstream structural surfaces. The rate of change in infrared reflectance of the catalytic surface represents its ability to absorb infrared radiation, indirectly reflecting localized temperature increases, reduced exposure of active sites, or obscuring by particles. Therefore, a larger rate of change in infrared reflectance indicates a higher risk of interference from high-temperature contaminating particles adhering to the catalytic surface. The rate of change in pressure drop across the catalytic bed per unit time is used to capture the real-time impact of particle deposition on airflow. During normal operation, the pressure difference should be stable. Significant fluctuations may be caused by localized particle melting and adhesion, pore blockage, or the formation of a buildup layer, leading to narrowing of the flow path—a direct consequence of high-temperature thermal adhesion behavior.

[0119] In summary, the thermally driven adhesion index effectively integrates the three factors of high-temperature thermal field behavior, surface energy change feedback, and fluid impedance fluctuation, serving as a key characteristic parameter for mechanistic completion and lateral redundancy discrimination of dust deposition risk. This index compensates for the insufficient coverage of thermal adhesion factors by the inertial deposition tendency factor and charge migration ability index, thereby improving the system's adaptability in real-world complex flue gas environments.

[0120] The method for obtaining the deposition early warning signal includes:

[0121] Preset deposition risk scoring threshold 1 and deposition risk scoring threshold 2; deposition risk scoring threshold 1 is less than deposition risk scoring threshold 2;

[0122] A sedimentation risk score is calculated based on sedimentation risk indicators;

[0123] For example, a deposition risk score threshold of 0.45 is set. When the deposition risk score is below threshold 1, it indicates that the overall deposition driving force of the exhaust gas system is within an acceptable range, the deposition rate is slow or fluctuates only slightly, and the system can maintain a minimal intervention operating mode. A deposition risk score threshold of 0.75 is set. When the deposition risk score is greater than or equal to threshold 2, it indicates that multiple deposition driving factors are synergistically enhanced, the system is in a potential rapid deposition trend, and a high-intensity regulatory response needs to be triggered to avoid uncontrolled deposition.

[0124] If the sedimentation risk score is greater than or equal to the sedimentation risk score threshold 2, a high sedimentation risk warning signal is generated; if the sedimentation risk score is greater than or equal to the sedimentation risk score threshold 1 and less than the sedimentation risk score threshold 2, a medium sedimentation risk warning signal is generated; if the sedimentation risk score is less than the sedimentation risk score threshold 1, a low sedimentation risk warning signal is generated.

[0125] It should be noted that the flowchart of the method for generating sedimentation early warning signals based on sedimentation risk indicators is as follows: Figure 4 As shown.

[0126] The method for calculating the deposition risk score includes:

[0127] ;

[0128] in, Assess the depositional risk score; , and These are the corresponding normalized weighting coefficients. For example, in this application, the following can be used: Set it to 0.3, Set it to 0.3, Set it to 0.4.

[0129] It should be noted that, to avoid calculation deviations or confusion of physical meanings caused by inconsistent units of various physical quantities in the sedimentation risk scoring formula, the parameters involved in the calculation of the sedimentation risk score in this application have been dimensionless and normalized. For example, the numerical range of all parameters in the sedimentation risk scoring formula is limited to [specific range missing]. This is to ensure the scientific validity of the formula structure and the comparability of the results.

[0130] Furthermore, in this embodiment, intelligent identification of deposition risk is not only an auxiliary function of the dust purification process, but also a key technical link to ensure the long-term efficient operation of the system and prevent structural performance degradation and shortened catalytic life. By integrating three types of deposition characteristics derived from multi-source real-time operating data—inertial deposition tendency factor, charge migration capacity index, and thermally driven adhesion index—the system can predict the potential adhesion trend and risk level of exhaust gas particles before large-scale deposition occurs, thereby achieving proactive process control and preventive intervention.

[0131] Without such a deposition risk identification mechanism, submicron particles in exhaust gas are highly susceptible to adhesion and deposition on the surface of catalytic structures under high temperature, high flow rate, or strong charging environments, leading to the formation of deposits in localized areas. On the one hand, this deposition behavior can cause localized loss of catalytic surface activity and a significant decrease in catalytic reaction efficiency; on the other hand, particle adhesion will alter the internal fluid dynamics of the system, causing abnormally high pressure drops, which may ultimately lead to thermal cracking of the catalyst structure, gas path blockage, and in severe cases, even affect the functional stability and safety of the entire exhaust gas purification system.

[0132] Compared to existing technologies that rely on passive strategies such as statically set thresholds, backend pressure alarms, or periodic manual maintenance, this solution combines particle-level behavior patterns with real-time operating conditions to issue early warning signals in the early stages of deposition. It is forward-looking, intelligent, and controllable. This warning signal can be dynamically responded to through a linkage response adjustment module, thereby proactively mitigating the risk of particle deposition, extending the lifespan of the catalyst support, and significantly reducing maintenance frequency and downtime risk without affecting the main system flow.

[0133] In summary, by intelligently identifying and dynamically responding to the risk of particle deposition, the solution not only overcomes the lack of a mechanism to respond in the dust pre-deposition stage of existing technologies, but also improves the safety, continuity, and economy of the exhaust gas purification system. It has significant application value and engineering feasibility in high-load industrial flue gas environments.

[0134] The linkage response adjustment module is used to dynamically execute multi-strategy regulation based on deposition warning signals, thereby effectively suppressing dust deposition trends, protecting the stability of the catalytic structure, and maintaining the long-term efficient operation of the purification system. The linkage response adjustment module automatically matches a preset adjustment scheme based on high, medium, and low-level deposition risk warning signals and outputs the scheme to each adjustment submodule to execute corresponding response actions.

[0135] The methods for dynamically implementing multi-strategy control based on sedimentation early warning signals include:

[0136] When the deposition warning signal is a high deposition risk warning signal, the linkage response adjustment module calls a high-intensity control scheme; specifically, this includes: increasing the discharge voltage of the non-thermal plasma charging unit and adjusting the electrode spacing and discharge frequency to enhance particle charge density and electric field guiding ability; triggering a high-frequency backflush system to momentarily disturb the deposition potential zone through periodic gas pulses to disrupt the initial particle adhesion conditions; temporarily increasing the injection rate of alkaline composite powder in the turbulent mixing-reaction zone to enhance the physical inertization effect of front-end dust and reduce deposition tendency from the source; and intermittently cooling the waste gas flow to weaken the thermally driven adhesion path and reduce the probability of particle melting and adhesion.

[0137] When the deposition warning signal is a medium deposition risk warning signal, the linkage response adjustment module invokes the medium-intensity control scheme. Specifically, this includes: maintaining the non-thermal plasma charging voltage at its rated value and adjusting the discharge frequency; reducing the activation frequency of the backflushing system and performing directional perturbation only on high-risk areas; adjusting the alkaline composite powder injection flow rate in the reaction zone to maintain its default value and monitoring the catalyst temperature. The medium-intensity control scheme, while maintaining stable system operation, moderately curbs the deposition evolution trend and extends the equipment's operating window.

[0138] When the deposition warning signal is a low deposition risk warning signal, the linkage response adjustment module executes the minimum intervention mode; specifically, the linkage response adjustment module maintains each system unit under the default operating parameters, does not activate additional adjustment operations, only maintains continuous monitoring of deposition indicators and operating parameters, ensures that the system is in a low-load and low-risk state, and avoids energy waste and system disturbance.

[0139] It should be noted that, in order to improve the flexibility and adaptability of sedimentation risk control strategies, this application proposes to divide the configuration of control parameters corresponding to sedimentation early warning levels into two paths. Specifically, one is the matching acquisition method based on a pre-built parameter setting table, and the other is the dynamic reasoning setting method based on a trained machine learning model.

[0140] Specifically, during implementation, this application can pre-construct multiple parameter setting tables that match the deposition risk level. These parameter setting tables are formulated based on historical operating data and actual control effects, covering control requirements under different operating conditions. For example, when a high deposition risk warning signal is detected, the system will automatically retrieve the parameter set corresponding to high deposition risk from the parameter setting table, including the voltage boost ratio of the non-thermal plasma charging unit, the electrode spacing adjustment range, the discharge frequency, the backflush disturbance frequency, the alkaline composite powder injection rate in the turbulent mixing-reaction zone, and the cooling range of the exhaust gas, etc., to achieve one-click parameter recall.

[0141] Building upon this foundation, to enhance the system's generalization ability and adaptive adjustment capability under complex operating conditions, this application may also introduce a pre-trained parameter setting machine learning model, such as one based on random forest, support vector regression, or deep neural networks. This model utilizes multi-source real-time operating data, including deposition risk scores and current operating parameters, as input features to dynamically predict the optimal parameter setting combination. The parameter setting machine learning model can be trained in the initial stage using supervised learning on historical control samples and continuously optimized during operation to achieve intelligent setting and self-evolution of deposition control parameters.

[0142] Furthermore, for example, in this embodiment, to improve the practical engineering feasibility of the deposition trend control mechanism, the linkage response adjustment module further specifies corresponding physical adjustment quantification parameters for different levels of deposition early warning signals. This ensures that each adjustment unit has a specific adjustment path and operating threshold in the closed-loop response, facilitating direct implementation and optimization by those skilled in the art in an industrial environment; such as Figure 5 The diagram shown is a schematic of the linkage response adjustment strategy corresponding to this application.

[0143] When a high deposition risk warning signal is detected, the linkage response adjustment module increases the discharge voltage of the non-thermal plasma charging unit by 20%–30% from the default value. For example, if the default voltage is ±12kV, the adjusted voltage is ±15.6kV. The increase is determined by the rate at which the charging efficiency score decreases. The electrode spacing is reduced from the original 10mm to 6–7mm to enhance the electric field strength and increase the charge density per unit volume. The discharge frequency is increased from the initial 50Hz to 80–100Hz to increase the charging frequency and interaction time density of high-speed passing particles. This adjustment range is adjusted in real time based on the residual dust particle size concentration and surface activity index, and is automatically limited within the safe range of equipment insulation strength through a feedback model.

[0144] For the backflushing system, under the high deposition risk warning signal state, the backflushing cycle of each gas path is adjusted from once every 10 minutes to once every 3 minutes, the backflushing pressure is maintained at 0.25–0.3 MPa, and the duration is 3–5 seconds. The specific values ​​are determined by the rate of change of flow rate and the rate of change of pressure drop in the catalyst bed. The backflushing sequence can be scheduled based on the temperature gradient of the catalyst structure and the priority of deposition risk hotspots to avoid unnecessary disturbances.

[0145] The injection rate of alkaline composite powder in the turbulent mixing-reaction zone was increased from the default 0.8 g / m³ to 1.2–1.4 g / m³, and the maintenance time was defined as “short time,” that is, continuously for 3–5 minutes or until the deposition score fell below the set threshold, followed by a 60-second confirmation period before stopping. This strategy inhibits the formation of adhesion conditions for particles in the downstream system by enhancing the physical inerting degree and phosphate neutralization efficiency of the initial particles.

[0146] Regarding catalytic bed temperature control, an auxiliary cooling module is activated under high deposition warning conditions. By adjusting the gaseous cooling gas, such as increasing the flow rate of inert nitrogen or air by 15%, the average gas temperature in the catalytic bed region is controlled to decrease by 40–60°C, with a target temperature drop not exceeding 200°C, to avoid disrupting the system's thermal balance. The cooling operation duration is limited to 2–3 minutes, and the process is controlled by a closed-loop temperature feedback loop to prevent insufficient or excessive cooling.

[0147] When a mid-deposition risk warning signal is detected, the non-thermal plasma charging voltage is maintained at the rated value, the backflushing cycle is 5-6 minutes, the alkaline composite powder injection rate is increased from the default 0.8 g / m³ to about 1.0 g / m³, and the cooling gas flow rate is increased by no more than 10%. The system continuously monitors the response values ​​of the indicators after adjustment. If the deposition score continues to rise, the system will automatically transition to a high-risk adjustment level.

[0148] When the "low deposition risk warning signal" is in effect, the system enters maintenance mode. Each submodule maintains its basic operating parameters and does not actively perform any disruptive operations. It only maintains continuous monitoring and dynamic assessment capabilities to ensure that it can quickly respond to and switch adjustment schemes when the risk increases.

[0149] With the addition of the above specific implementation details, the linkage response adjustment module has a clear and operable engineering path from risk identification to parameter execution, avoiding the problems of ambiguous adjustment instructions and missing implementation parameters in existing technologies, and effectively improving the actual deployment value and control accuracy of this solution.

[0150] Example 2

[0151] Please see Figure 2 As shown, this embodiment provides a method for purifying waste gas from circuit board metal smelting and regeneration, including:

[0152] Particle size control, physical inerting and chemical stabilization treatment are carried out on submicron-sized phosphorus oxide dust generated by the cracking of flame retardants in the exhaust gas of circuit board metal smelting.

[0153] Directional charging treatment is performed on residual dust particles in the exhaust gas from the smelting of circuit board metals to inhibit fine particles in the high-temperature exhaust gas that are difficult to physically settle or neutralize from entering the catalytic reactor area.

[0154] Based on real-time multi-source operational data, the deposition trend of residual dust in the waste gas of circuit board metal smelting on the catalyst surface is dynamically evaluated, deposition risk indicators are constructed, and the deposition status is predicted and a deposition early warning signal is generated.

[0155] Dynamically implement multi-strategy regulation based on deposition early warning signals to suppress dust deposition trends and protect catalytic structures.

[0156] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

[0157] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for purifying exhaust gas from a metal smelting process for a circuit board, characterized by, The application relates to a method for dynamically controlling deposition of dust in waste gas from metal smelting of circuit boards. The method comprises the following steps: carrying out particle size regulation, physical inertization and chemical stabilization treatment on submicron phosphorus oxide dust generated by cracking of a flame retardant in waste gas from metal smelting of circuit boards; carrying out directional charging treatment on residual dust particles in the waste gas; based on real-time acquisition of multi-source real-time operation data, dynamically evaluating deposition tendency of the residual dust in the waste gas from metal smelting of circuit boards on a catalyst surface, constructing a deposition risk index, and predictively judging a deposition state to generate a deposition early warning signal; 2. The method according to claim 1, wherein dynamically executing multi-strategy regulation according to the deposition early warning signal. The deposition early warning signal comprises a high-deposition-risk early warning signal, a medium-deposition-risk early warning signal and a low-deposition-risk early warning signal. The method for dynamically executing multi-strategy regulation according to the deposition early warning signal comprises the following steps: when the deposition early warning signal is the high-deposition-risk early warning signal, the discharge voltage of a non-thermal plasma charging unit is increased according to a preset voltage increase ratio, the electrode spacing and the discharge frequency are adjusted, a high-frequency back-blowing operation is triggered to disturb a deposition potential area, the injection rate of alkaline composite powder of a turbulent mixing-reaction area is adjusted, and the waste gas flow is cooled; when the deposition early warning signal is the medium-deposition-risk early warning signal, the discharge voltage is maintained at a rated value, the discharge frequency is adjusted, the back-blowing frequency is adjusted and is directionally disturbed, the injection flow of the alkaline composite powder is maintained, and the temperature state of the catalyst is monitored; 3. The method of claim 1, wherein the exhaust gas is generated from a process of melting a metal for a circuit board. when the deposition early warning signal is the low-deposition-risk early warning signal, a linkage response adjustment module maintains the operation of each system unit under default operation parameters, and only continuous monitoring of the deposition index and the operation parameters is maintained. The method for constructing the deposition risk index comprises the following steps: continuous monitoring of multi-source real-time operation data in the high-temperature waste gas operation process; the multi-source real-time operation data comprises waste gas instantaneous flow rate, waste gas temperature, particle size distribution histogram, dust volume concentration, particle charging potential, infrared reflectivity change rate of a catalyst surface and change rate of pressure drop before and after a catalytic bed per unit time; N particle size sections are divided based on the particle size distribution histogram, the particle size median and the particle size section proportion of each particle size section are calculated, and the inertial contribution of each particle size section is calculated based on the particle size median, the particle size section proportion and the waste gas instantaneous flow rate; the inertial deposition tendency factor is obtained by summing the inertial contribution; the charged migration ability index is calculated based on the dust volume concentration, the particle charging potential, the particle size median and the particle size section proportion of each particle size section; and the heat-driven adhesion index is calculated based on the waste gas temperature, the infrared reflectivity change rate and the change rate of pressure drop before and after the catalytic bed; 4. The method of claim 1, wherein the exhaust gas is generated from a process of melting a metal for a circuit board. the inertial deposition tendency factor, the charged migration ability index and the heat-driven adhesion index are combined to construct the deposition risk index. The method for obtaining the deposition early warning signal comprises the following steps: presetting a deposition risk score threshold one and a deposition risk score threshold two; the deposition risk score threshold one is smaller than the deposition risk score threshold two; calculating the deposition risk score based on the deposition risk index; If the deposition risk score is greater than or equal to the deposition risk score threshold two, a high deposition risk warning signal is generated; if the deposition risk score is greater than or equal to the deposition risk score threshold one and less than the deposition risk score threshold two, a medium deposition risk warning signal is generated; if the deposition risk score is less than the deposition risk score threshold one, a low deposition risk warning signal is generated.

5. The method of claim 1, wherein the exhaust gas is a waste gas from a copper smelting process. The method for directional charging treatment of dust particles remaining in the circuit board metal smelting waste gas comprises the following steps: The non-thermal plasma charging unit is arranged in the high-temperature waste gas main channel and is used for implementing directional charging treatment on fine particulate matters remaining in the waste gas; the non-thermal plasma charging unit is arranged with a plurality of insulation type needle-shaped high-voltage discharge electrodes along the flow direction of the waste gas main channel, each electrode applies a direct current high voltage through a power supply control module to form a stable corona discharge region between the electrodes; in the corona discharge region, high-energy free electrons and ionized plasma clusters released during the discharge process act on dust particles flowing through the corona discharge region, so as to promote the formation of a stable directional charge layer on the surface of the dust.

6. The method according to claim 5, wherein the exhaust gas is a waste gas from a copper smelting process. The non-thermal plasma charging unit is linked with a dust charging state feedback adjustment unit; the feedback adjustment unit acquires monitoring operation parameters; the monitoring operation parameters include instantaneous flow rate, temperature, dust volume and concentration of the waste gas, and the particle charging efficiency score of the current particle group is evaluated based on the monitoring operation parameters; if the particle charging efficiency score is lower than a preset charging efficiency score threshold, the system constructs a charging adjustment model based on the monitoring operation parameters and the particle charging efficiency score, and outputs corresponding charging adjustment parameters, the charging adjustment parameters including discharge voltage, electrode spacing and frequency adjustment instructions; According to the generated charging adjustment parameters, the corona discharge conditions are adjusted in real time, and the spatial distribution of free electron density and the discharge region is optimized; The adjustment process is cyclically executed until the particle charging efficiency score reaches or exceeds the preset charging efficiency score threshold, it is judged that the charging target has been completed, the charging adjustment operation is stopped, and the directional charging on the surface of the particles is completed.

7. The method of claim 1, wherein the method is characterized by: The method for particle size regulation, physical inertization and chemical stabilization treatment of submicron phosphorus oxide dust generated due to the cracking of flame retardants in the circuit board metal smelting waste gas comprises the following steps: The high-temperature waste gas discharged during the circuit board metal smelting process is introduced into a turbulent mixing-reaction zone arranged at the front end of the purification system; the turbulent mixing-reaction zone is a closed high-temperature reaction cavity; An alkaline composite powder injection device arranged upstream of the turbulent mixing-reaction zone is used to continuously inject alkaline composite powder into the turbulent mixing-reaction zone; The alkaline composite powder is introduced by a high-temperature pneumatic injector, which injects the alkaline composite powder into the turbulent mixing-reaction zone in a high-speed atomized state under the action of high-pressure carrier gas, so that the alkaline composite powder fully contacts and rapidly mixes with the submicron phosphorus oxide dust carried in the waste gas; In the turbulent mixing-reaction zone, a solid-gasoloid reaction occurs between the waste gas and the alkaline composite powder, generating a phosphate complex, which is precipitated in the form of particles under the condition of turbulent heat diffusion, forming a phosphate particle; The phosphate structure is converted into a stable compound, the surface free energy of the phosphate particles decreases, the electrostatic adsorption force and liquid bridge effect between the particles are weakened, and finally the sub-micron phosphorus oxide dust is subjected to particle size regulation, physical inertization and chemical stabilization treatment.

8. The method according to claim 6, wherein the exhaust gas is a waste gas from a copper smelting process. The method for obtaining the particle charging efficiency score comprises: The monitoring operation parameters are input into the particle charging efficiency evaluation model to obtain the corresponding particle charging efficiency score.

9. The method according to claim 8, wherein the exhaust gas is a waste gas from a copper smelting process. The training method of the particle charging efficiency evaluation model comprises: A particle charging efficiency evaluation dataset is constructed in advance, the particle charging efficiency evaluation dataset comprises PG group particle charging efficiency evaluation data and particle charging efficiency scores corresponding to the PG group particle charging efficiency evaluation data, PG is a positive integer, and the particle charging efficiency evaluation data comprises monitoring operation parameters; the particle charging efficiency evaluation dataset is divided into a training set and a verification set, the training set is used for learning parameters of the particle charging efficiency evaluation model, and the verification set is used for monitoring generalization performance and overfitting degree of the particle charging efficiency evaluation model in real time; The support vector machine model is used as the particle charging efficiency evaluation model, the Softmax activation function is used to obtain a probability distribution corresponding to each particle charging efficiency score, and finally the particle charging efficiency score corresponding to the maximum probability is taken as the prediction result of the particle charging efficiency evaluation model; in the training process, the cross-entropy loss function is used as the optimization target, the gradient descent type optimization algorithm is used to update the network weight, and the early stopping strategy is set: when the prediction accuracy on the verification set reaches or exceeds a preset prediction accuracy threshold, it is determined that the particle charging efficiency evaluation model has converged and the training is terminated.

10. A system for purifying off-gas from a circuit board metal smelting and recycling process, according to any one of claims 1 to 9, characterized in that, The method comprises: The cracking interception module is used for particle size regulation, physical inertization and chemical stabilization treatment of sub-micron phosphorus oxide dust generated by cracking of flame retardants in the circuit board metal smelting waste gas; The dust charging regulation module is used for directional charging treatment of residual dust particles in the circuit board metal smelting waste gas, and inhibits fine particles in the high-temperature tail gas that are difficult to be physically settled or neutralized from entering the catalytic reactor region; The intelligent deposition early warning module is used for dynamically evaluating the deposition trend of residual dust in the circuit board metal smelting waste gas on the catalyst surface based on real-time acquisition of multi-source real-time operation data, constructing a deposition risk index, and predictively judging the deposition state to generate a deposition early warning signal; The linkage response adjustment module is used for dynamically executing multi-strategy regulation according to the deposition early warning signal to inhibit the dust deposition trend and protect the catalytic structure.

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