Method and system for simultaneous removal of multiple pollutants from flue gas of coal-fired power plant

Abstract

This invention relates to the field of flue gas purification and multi-pollutant deep synergistic removal control technology in coal-fired power plants, and particularly to a method and system for synergistic removal control of multiple pollutants in flue gas from coal-fired power plants. The method includes: acquiring polarized scattered light signals from the tail flue; inverting and extracting the spatial distribution characteristics of the cancellation coefficient to generate a transient thermodynamic density scalar field and a local thermal gradient vector matrix; setting transmission parameters based on the aforementioned matrix and outputting a sound wave sequence and a rotating radio frequency electric field to construct a dynamic equivalent acoustic metamaterial potential field to locate the three-dimensional coordinates of topological local valleys; adding latent heat-responsive microcapsules to the flue gas flow field to induce ultrafine aerosol particles to undergo condensation phase transition and expand into secondary large droplets; acquiring local transmittance jump signals to calculate the end-of-pipe dust collection electric field parameters; and collecting droplets by adjusting the electrostatic adsorption parameters of the electrodes to remove colored plume components. This invention solves the problem of abnormal colored plumes caused by ultrafine aerosols.

Description

Technical Field

[0001] This invention relates to the field of flue gas purification and deep synergistic removal control technology for multiple pollutants in coal-fired power plants, and particularly to a method and system for synergistic removal control of multiple pollutants in flue gas from coal-fired power plants. Background Technology

[0002] Coal-fired power generating units produce high-temperature industrial waste gas from fuel combustion. This waste gas contains various pollutants, including sulfur dioxide, nitrogen oxides, and fine dust. Multi-pollutant synergistic removal and control technology aims to integrate the treatment of complex and harmful components within the waste gas. The core of the synergistic purification process lies in utilizing chemical reaction principles to achieve the simultaneous removal of multiple pollutant components. The removal system continuously injects specific chemical agents into the high-temperature flue gas flow field, causing the chemical agents to simultaneously undergo oxidation-reduction and acid-base neutralization reactions with various target pollutant molecules. Different pollutant gases are transformed into physically stable compounds through multiple chemical reactions. The automatic control system adjusts the total amount of chemical agents added in real time based on data transmitted from the equipment. The mixed airflow, after undergoing the synchronous purification process, then directly enters the exhaust system at the end of the unit.

[0003] Existing multi-component deep synergistic purification technologies for flue gas have the following technical challenges, specifically addressing the issue of emissions meeting standards but exhibiting abnormally colored plumes from chimneys due to the aggregation of multi-component byproducts into ultrafine aerosols. Synergistic removal processes require the addition of chemical agents. Incompletely reacted residual chemicals, accompanying the flue gas into the tail-end system, cause complex secondary chemical reactions among various free gaseous components. High-temperature gaseous substances condense as the flue gas temperature decreases, further promoting the adsorption and aggregation of various trace byproducts into ultrafine aerosol particles. Because conventional online monitoring equipment cannot effectively capture submicron-sized suspended particles, the instrument monitoring data may fully comply with environmental standards; however, the large number of suspended fine particles strongly scatters natural light, resulting in a visible colored plume after the exhaust gas is released into the atmosphere. Taking the tail-end exhaust process of a coal-fired power plant as an example, ammonia escaping from the front-end denitrification system undergoes a gaseous chemical reaction with unremoved sulfur trioxide, producing liquid ammonium bisulfate, which is discharged along with saturated water vapor, rapidly forming a high-concentration visually polluting smoke belt under natural light. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a method and system for the synergistic removal and control of multiple pollutants in flue gas from coal-fired power plants. This invention solves the technical problem that, despite meeting emission standards, abnormal colored plumes erupt from chimneys due to the polymerization of multi-component byproducts into ultrafine aerosols.

[0005] To solve the above-mentioned technical problems, the specific contents of the present invention are as follows: In a first aspect, the present invention provides a method for the synergistic removal and control of multiple pollutants in flue gas from coal-fired power plants, comprising: The polarized scattered light signal of the flue gas flow field in the tail flue of a coal-fired power plant is collected, and the light intensity and phase parameters of the polarized scattered light signal are extracted. The spatial distribution characteristics of the extinction coefficient are extracted based on the light intensity and phase parameters. The spatial distribution characteristics of the extinction coefficient are substituted into a preset thermodynamic transfer function to generate the transient thermodynamic density scalar field and the local thermal gradient vector matrix of the flue gas flow field. Based on the transient thermodynamic density scalar field and the local thermal gradient vector matrix, the emission parameters are set, and the acoustic wave sequence and rotating radio frequency electric field are output to the flue gas field according to the emission parameters. The acoustic wave sequence is caused to interfere and superimpose under the Lorentz force constraint of the rotating radio frequency electric field. A dynamic equivalent acoustic metamaterial potential field is constructed inside the flue gas field, and the node coordinates in the dynamic equivalent acoustic metamaterial potential field are extracted to generate the three-dimensional coordinates of the topological local valley. According to the three-dimensional coordinates of the topological local valley, latent heat-responsive chain-type amphiphilic condensation nucleus microcapsules are added to the flue gas flow field, causing the ultrafine aerosol particles existing in the flue gas flow field to undergo condensation phase change with the latent heat-responsive chain-type amphiphilic condensation nucleus microcapsules as condensation nuclei. The ultrafine aerosol particles expand after the condensation phase change to generate secondary large droplets. The local transmittance jump signal caused by the condensation phase change is collected. The DC bias voltage and high-frequency pulse duty cycle data of the end dust collection electric field are calculated using the local transmittance jump signal. The electrostatic adsorption parameters of the plates of the end dust collection electric field are adjusted according to the DC bias voltage and high-frequency pulse duty cycle data to capture the secondary large-particle droplets and remove colored smoke components.

[0006] Furthermore, the method for synergistic removal and control of multiple pollutants in flue gas from coal-fired power plants according to the present invention includes the following steps: acquiring polarized scattered light signals of the flue gas flow field in the tail flue of the coal-fired power plant; extracting the light intensity and phase parameters of the polarized scattered light signals; extracting the spatial distribution characteristics of the extinction coefficient based on the light intensity and phase parameters; and substituting the spatial distribution characteristics of the extinction coefficient into a preset thermodynamic transfer function to generate the transient thermodynamic density scalar field and local thermal gradient vector matrix of the flue gas flow field. An orthogonally modulated polarized laser beam is emitted into the flue gas field, and the backscattered light of the polarized laser beam is received as the polarized scattered light signal. The polarized scattered light signal is converted into an analog voltage signal. The analog voltage signal is discretized and sampled to extract a discrete voltage sequence. The original Stokes parameter matrix is ​​generated by combining the discrete voltage sequences. Perform a Jones matrix inversion operation on the original Stokes parameter matrix to extract the spatial distribution characteristics of the extinction coefficient; The spatial distribution characteristics of the extinction coefficient are substituted into the preset thermodynamic transfer function to solve the equation, and the transient thermodynamic density scalar field and the local thermal gradient vector matrix are output.

[0007] Furthermore, the method for synergistic removal and control of multiple pollutants in flue gas from coal-fired power plants according to the present invention, wherein setting the emission parameters based on the transient thermodynamic density scalar field and the local thermal gradient vector matrix includes: The acoustic impedance spatial distribution matrix of the flue gas field is generated by substituting the local thermal gradient vector matrix into the fluid dynamics equation. The Helmholtz wave equation is numerically solved based on the acoustic impedance spatial distribution matrix to obtain complex eigenvalues, and the emission frequency and initial phase parameters of the acoustic wave sequence are extracted using the complex eigenvalues. A density distribution threshold is set, and data points with values ​​greater than the density distribution threshold are selected from the transient thermodynamic density scalar field to delineate the three-dimensional coordinate set of high-density free gas phase components; The spatial center coordinates of the three-dimensional coordinate set of the high-density free gas phase components are extracted, and the angular frequency of the rotating radio frequency electric field is calculated based on the spatial center coordinates. The transmission frequency, the initial phase parameter and the angular frequency are then combined to form the transmission parameter.

[0008] Furthermore, the method for synergistic removal and control of multiple pollutants in flue gas from coal-fired power plants according to the present invention, wherein the step of constructing a dynamic equivalent acoustic metamaterial potential field within the flue gas flow field and extracting the node coordinates in the dynamic equivalent acoustic metamaterial potential field to generate three-dimensional coordinates of the topological local valleys includes: The sound wave sequence and the rotating radio frequency electric field are input to perform finite element analysis to calculate the interference superposition matrix inside the flue gas field; A spatial mapping three-dimensional model of the dynamic equivalent acoustic metamaterial potential field is established based on the interference superposition matrix. The shear stress distribution data inside the spatially mapped three-dimensional model is quantified, and the three-dimensional coordinates of nodes with shear stress values ​​lower than a preset shear threshold are extracted from the shear stress distribution data. The three-dimensional coordinates of these nodes are then used as the three-dimensional coordinates of the topological local valleys.

[0009] Furthermore, the method for synergistic removal and control of multiple pollutants in flue gas from coal-fired power plants according to the present invention, wherein the step of adding latent heat-responsive chain-type amphiphilic condensation nucleus microcapsules to the flue gas flow field according to the three-dimensional coordinates of the topological local trough includes: The temperature and pressure parameters corresponding to the three-dimensional coordinate positions of the topological local valley are retrieved from the transient thermodynamic density scalar field. Substituting the temperature and pressure parameters into the Clausius-Clapeyron equation, the theoretical threshold of the latent heat flux emitted by condensation is calculated. Based on the theoretical threshold of the microscopic latent heat flux and the three-dimensional coordinates of the topological local valley, the data matrix of the spatial position and ejection rate of the microcapsule injection is derived and calculated. The latent heat-responsive chain-type bihydrophilic condensation nucleus microcapsules are added according to the microcapsule injection spatial position and the injection rate data matrix, initiating an initial condensation phase transition and emitting microscopic latent heat shock waves outward.

[0010] Furthermore, the multi-pollutant synergistic removal and control method for flue gas from coal-fired power plants described in this invention, after initiating the initial condensation phase change and emitting a microscopic latent heat shock wave, includes: Collect real-time perturbation data of the acoustic refractive index along the propagation path of the acoustic wave sequence; Substitute the real-time perturbation data of the acoustic refractive index into the fluctuation attenuation equation to establish the transmission attenuation model corresponding to the propagation path of the acoustic wave sequence. The preset initial transmission power is input into the transmission attenuation model to perform forward calculation to obtain the power fine-tuning difference. The initial transmission power of the acoustic wave sequence is adjusted according to the power fine-tuning difference to compensate for the nonlinear amplitude loss of the microscopic latent heat shock wave when it propagates along the propagation path. The microscopic latent heat shock wave, after power adjustment, collides with and breaks up the surrounding suspended latent heat-responsive chain-type amphiphilic condensation nucleus microcapsules, triggering an exponential cascade cell-breaking reaction.

[0011] Furthermore, in the multi-pollutant synergistic removal and control method for flue gas from coal-fired power plants described in this invention, the exponential cascade cell disruption reaction disperses hydrophilic groups into the flue gas flow field, and multiple sets of the hydrophilic groups converge to form a hydrophilic active center lattice. The free water vapor and gas phase precursor inside the flue gas flow field converge at the lattice position of the hydrophilic active center and undergo continuous condensation phase change. The free water vapor that undergoes the continuous condensation phase change adsorbs the surrounding ultrafine aerosol particles, and the volume expansion caused by water condensation generates the secondary large droplets.

[0012] Furthermore, the method for synergistic removal and control of multiple pollutants in flue gas from coal-fired power plants according to the present invention, wherein the step of collecting the local transmittance jump signal caused by the condensation phase change and using the local transmittance jump signal to calculate the DC bias voltage and high-frequency pulse duty cycle data of the end-of-line dust collection electric field, includes: The local transmittance jump signal is converted from analog to digital and substituted into the multiphase flow aerosol dynamics equation for numerical calculation. The transient volume expansion rate and charge characteristics of the secondary large droplets are extracted from the numerical calculation results of the multiphase flow aerosol dynamics equations. The transient volume expansion rate and the charge characteristic value are combined and reconstructed into a feedforward input matrix; the feedforward input matrix is ​​then input into the fuzzy proportional-integral-differential algorithm model for feedback error calculation. Extract the output result of the feedback error calculation, map and determine the DC working bias voltage and high-frequency pulse power supply duty cycle of the dust collection plate of the terminal dust collection electric field based on the output result, and record the DC working bias voltage and the high-frequency pulse power supply duty cycle as the DC bias voltage and high-frequency pulse duty cycle data.

[0013] Furthermore, the method for synergistic removal and control of multiple pollutants in flue gas from coal-fired power plants according to the present invention, wherein adjusting the electrostatic adsorption parameters of the terminal dust collection electric field plates based on the DC bias and high-frequency pulse duty cycle data to capture the secondary large-particle droplets to remove colored plume components, includes: Based on the DC bias and high-frequency pulse duty cycle data, a corresponding voltage control command is issued; The electrostatic adsorption parameters of the plates of the terminal dust collection electric field are adjusted according to the voltage control command. The secondary large-particle droplets in the airflow are intercepted and stripped by electrostatic adsorption, thereby removing colored smoke components.

[0014] Secondly, the multi-pollutant synergistic removal control system for flue gas from coal-fired power plants provided by the present invention is applied to the aforementioned multi-pollutant synergistic removal control method for flue gas from coal-fired power plants, including: The signal processing module is used to collect polarized scattered light signals of the flue gas flow field in the tail flue of a coal-fired power plant, extract the light intensity and phase parameters of the polarized scattered light signals, extract the spatial distribution characteristics of the extinction coefficient based on the light intensity and phase parameters, and substitute the spatial distribution characteristics of the extinction coefficient into a preset thermodynamic transfer function to generate the transient thermodynamic density scalar field and local thermal gradient vector matrix of the flue gas flow field. The potential field construction module is used to set the transmission parameters based on the transient thermodynamic density scalar field and the local thermal gradient vector matrix, output the acoustic wave sequence and the rotating radio frequency electric field to the flue gas field according to the transmission parameters, cause the acoustic wave sequence to interfere and superimpose under the Lorentz force constraint of the rotating radio frequency electric field, construct a dynamic equivalent acoustic metamaterial potential field inside the flue gas field, and extract the node coordinates in the dynamic equivalent acoustic metamaterial potential field to generate the three-dimensional coordinates of the topological local valley. The capsule dosing module is used to add latent heat-responsive chain-type amphiphilic condensation nucleus microcapsules to the flue gas flow field according to the three-dimensional coordinates of the topological local valley, so as to cause the ultrafine aerosol particles existing in the flue gas flow field to undergo condensation phase change with the latent heat-responsive chain-type amphiphilic condensation nucleus microcapsules as condensation nuclei, and the ultrafine aerosol particles expand after the condensation phase change to generate secondary large droplets; The electric field adjustment module is used to collect the local transmittance jump signal caused by the condensation phase change, calculate the DC bias voltage and high-frequency pulse duty cycle data of the end dust collection electric field using the local transmittance jump signal, and adjust the electrostatic adsorption parameters of the electrode plates of the end dust collection electric field according to the DC bias voltage and high-frequency pulse duty cycle data to capture the secondary large-particle droplets to remove colored smoke components.

[0015] Beneficial effects of this invention: The present invention provides a method for the coordinated removal and control of multiple pollutants in flue gas from coal-fired power plants. By collecting polarized scattered light signals and inverting to extract the spatial distribution characteristics of the cancellation coefficient, a transient thermodynamic density scalar field and a local thermal gradient vector matrix are generated. This effectively overcomes the physical defect that conventional online monitoring equipment cannot capture submicron-sized suspended particles, achieving high-precision spatial positioning of aerosol precursors in complex water vapor backgrounds. Based on the thermodynamic matrix data, an acoustic wave sequence and a rotating radio frequency electric field are output to the flue gas flow field. Under the constraint of Lorentz force, a dynamic equivalent acoustic metamaterial potential field is constructed, accurately extracting the three-dimensional coordinates of the topological local wave valleys. This successfully establishes an absolutely static polymer microenvironment capable of completely resisting the tearing damage of fluid shear stress in complex high-turbulence environments. According to the positioning coordinates, latent heat-responsive chain-type amphiphilic condensation nucleus microcapsules are directionally added. The microscopic latent heat shock wave released by the initial condensation phase transition triggers an exponential cascade cell-breaking reaction in the microcapsules, completely overturning the traditional design bias of conventional spraying condensation nucleus technology facing severe evaporation failure in high-temperature flue gas. The hydrophilic groups dispersed by the rupture of microcapsules induce continuous condensation phase transitions between free water vapor and ultrafine aerosol particles within the flue gas flow field. This causes the microscopic ultrafine aerosol particles to rapidly expand and grow into macroscopic secondary large-particle droplets. By collecting the local transmittance jump signal caused by the condensation phase transition process and combining it with the multiphase flow aerosol kinetic equations to dynamically calculate the DC bias voltage and high-frequency pulse duty cycle data of the end-of-line dust collection electric field, the electrostatic adsorption parameters of the end-of-line dust collection electric field are adjusted in real time using the calculated power supply data. Relying on high-intensity electrostatic adsorption, the secondary large-particle droplets are completely intercepted and stripped from the main gas flow. This completely blocks the final formation path of abnormal colored plumes from both the underlying data control and physical mechanism dimensions, achieving deep and synergistic purification of the tail gas of coal-fired power generation units. Attached Figure Description

[0016] To more clearly illustrate the technical solution of the present invention, the drawings used in the embodiments will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on the drawings without creative effort.

[0017] Figure 1 This is a schematic flowchart of the multi-pollutant synergistic removal and control method for flue gas from coal-fired power plants according to the present invention. Detailed Implementation

[0018] To make the technical solution of the present invention clearer, the present invention will be clearly and completely described below with reference to specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. The embodiments of the present invention will be described in detail below with reference to the accompanying drawings. To better understand the purpose of the present invention, the present invention will be described in further detail below.

[0019] Please see Figure 1 In a first aspect, the present invention provides a method for the synergistic removal and control of multiple pollutants in flue gas from coal-fired power plants, comprising: Step 1: Collect polarized scattered light signals of flue gas flow field in the tail flue of a coal-fired power plant, extract the light intensity and phase parameters of the polarized scattered light signals, extract the spatial distribution characteristics of the extinction coefficient based on the light intensity and phase parameters, and substitute the spatial distribution characteristics of the extinction coefficient into a preset thermodynamic transfer function to generate the transient thermodynamic density scalar field and local thermal gradient vector matrix of the flue gas flow field. Step 2: Set the transmission parameters based on the transient thermodynamic density scalar field and the local thermal gradient vector matrix. Output the acoustic wave sequence and the rotating radio frequency electric field to the flue gas field according to the transmission parameters. Cause the acoustic wave sequence to interfere and superimpose under the Lorentz force constraint of the rotating radio frequency electric field. Construct a dynamic equivalent acoustic metamaterial potential field inside the flue gas field. Extract the node coordinates in the dynamic equivalent acoustic metamaterial potential field to generate the three-dimensional coordinates of the topological local valley. Step 3: Add latent heat-responsive chain-type amphiphilic condensation nucleus microcapsules to the flue gas flow field according to the three-dimensional coordinates of the topological local wave valley, so as to cause the ultrafine aerosol particles existing in the flue gas flow field to undergo condensation phase change with the latent heat-responsive chain-type amphiphilic condensation nucleus microcapsules as condensation nuclei. The ultrafine aerosol particles expand after the condensation phase change to generate secondary large droplets. Step 4: Collect the local transmittance jump signal caused by the condensation phase change, use the local transmittance jump signal to calculate the DC bias voltage and high-frequency pulse duty cycle data of the end dust collection electric field, adjust the electrostatic adsorption parameters of the electrode plate of the end dust collection electric field according to the DC bias voltage and high-frequency pulse duty cycle data, and capture the secondary large-particle droplets to remove colored smoke components.

[0020] A quadrated polarized laser beam is emitted into the flue gas flow field at the tail end of a coal-fired power plant. Photoelectric sensors deployed on the sidewall of the flue receive the backscattered light penetrating the flue gas flow field as a polarized scattered light signal. The intensity and phase parameters contained within the polarized scattered light signal are extracted and converted into a continuous analog voltage waveform via a photoelectric conversion circuit. The analog voltage waveform is then subjected to high-frequency discretization sampling to generate a discrete voltage sequence. The corresponding original Stokes parameter matrix is ​​constructed by rearranging the discrete voltage sequence. The original Stokes parameter matrix is ​​processed using a Jones matrix inversion model to obtain the spatial distribution characteristics of the extinction coefficient, characterizing the attenuation of the beam in the flow field. A pre-defined thermodynamic transfer function contains a nonlinear mapping conversion formula between optical attenuation and physical mass density. The spatial distribution characteristics of the extinction coefficient are input into the pre-defined thermodynamic transfer function for multidimensional manifold calculation, mapping and outputting the transient thermodynamic density scalar field and the local thermal gradient vector matrix of the flue gas flow field. The transient thermodynamic density scalar field intuitively reflects the three-dimensional distribution of the mass concentration of tiny particles within the flow field. The local thermal gradient vector matrix indicates the direction of change of spatial temperature partial derivatives and the magnitude of temperature gradient in different regions of the flow field through vector arrows.

[0021] By substituting the local thermal gradient vector matrix into the Navier-Stokes equations of fluid dynamics and performing numerical iteration, the spatial distribution matrix of acoustic impedance within the flue gas field is derived. Based on the spatial distribution matrix of acoustic impedance, spatial boundary conditions are set, and eigenvalue calculations are performed on the Helmholtz wave equation to extract complex eigenvalues. These complex eigenvalues ​​are used to define the transmission frequency and initial phase parameters of the acoustic wave sequence. A density distribution threshold is set in the transient thermodynamic density scalar field, and ordinary background data points with values ​​below the threshold are filtered out. Data points with values ​​above the density distribution threshold are retained and defined as a three-dimensional coordinate set of high-density free gas phase components. The spatial geometric center coordinates of the three-dimensional coordinate set of high-density free gas phase components are extracted, and the operating angular frequency of the rotating radio frequency electric field is calculated based on the offset of the geometric center coordinates and the flow field distribution. The transmission frequency, initial phase parameters, and angular frequency are summarized and packaged to generate transmission parameters. A multi-field coupling generator is activated according to the transmission parameters to synchronously output the acoustic wave sequence and the rotating radio frequency electric field to the flue gas field. The acoustic wave sequence undergoes forced deflection of its propagation path under the constraint of the Lorentz force generated by the rotating radio frequency electric field. The deflected acoustic waves intersect each other in space and superimpose with deep phase interference, directly constructing a dynamic equivalent acoustic metamaterial potential field within the flue gas field. Shear stress distribution data within this dynamic equivalent acoustic metamaterial potential field are extracted, and an optimization algorithm is used to search for spatial physical nodes with shear stress values ​​below a predetermined shear threshold. The coordinates of the searched physical nodes are then spatially matched to generate three-dimensional coordinates of topological local valleys.

[0022] Real-time temperature and pressure parameters corresponding to the three-dimensional coordinates of the topological local valleys are retrieved from the transient thermodynamic density scalar field. These parameters are then substituted into the Clausius-Clapeyron equation to calculate the critical point of the thermodynamic phase transition, deriving the theoretical threshold of the latent heat flux required for the condensation and release of gaseous substances. Based on the theoretical threshold of the latent heat flux and the three-dimensional coordinates of the topological local valleys, the spatial position and velocity data matrix of the microcapsule injection is calculated in reverse. The injection system is controlled to quantitatively add latent heat-responsive chain-type hydrophilic condensation nucleus microcapsules into the flue gas field according to the instructions of the microcapsule injection spatial position and velocity data matrix. The microcapsules move with the airflow into the topological local valleys where the physical shear force is extremely low. Upon contact with the high-temperature, high-pressure fluid, the microcapsule walls undergo molecular chain degradation and breakage. The broken microcapsules release a large number of hydrophilic groups into the external environment. Free water vapor and ultrafine aerosol particles present inside the flue gas field are spatially aggregated due to the physical adsorption of these hydrophilic groups. Free water vapor and ultrafine aerosol particles undergo a continuous phase change polymerization process, with latent heat-responsive chain-type amphiphilic condensation nuclei microcapsules serving as the condensation core. The ultrafine aerosol particles absorb a large amount of water during condensation and phase change, resulting in exponential volume expansion. Multiple tiny particles then fuse together to form secondary large droplets.

[0023] Visual monitoring hardware deployed at the tail end of the flue gas duct captures the physical changes in flue gas transmittance during the condensation phase change process in real time, converting these changes into electrical signals to form local transmittance jump signals. Analog-to-digital conversion is performed on these local transmittance jump signals to obtain digitized measurement signals. These digitized measurement signals are then substituted into the multiphase flow aerosol dynamics equations for nonlinear matrix derivation. The transient volume expansion rate and surface charge characteristics of secondary large droplets are extracted from the derivation results. These transient volume expansion rate and charge characteristics are combined to reconstruct a feedforward input matrix. This feedforward input matrix is ​​then imported into a fuzzy proportional-integral-differential algorithm model for feedback error comparison calculation. The output response surface results of the feedback error calculation are extracted, and based on these results, the required DC operating bias voltage and high-frequency pulse power supply duty cycle for the end-of-line dust collection electric field are mapped and matched. The matched DC operating bias voltage and high-frequency pulse power supply duty cycle are recorded and saved as DC bias voltage and high-frequency pulse duty cycle data. The main control equipment sends corresponding voltage regulation control commands to the high-voltage power supply of the terminal dust collection electric field based on the DC bias and high-frequency pulse duty cycle data. The high-voltage power supply responds to the control commands by changing the discharge intensity of the corona wire and the surface electric field gradient of the dust collection plates, thus dynamically adjusting the electrostatic adsorption parameters of the plates. Charged secondary large-particle droplets migrate laterally towards the dust collection plates under the enhanced electrostatic force. These droplets impact the plate surface and are firmly captured, thereby removing colored smoke components from the exhaust gas flow.

[0024] A quadrated polarized laser beam is emitted into the flue gas flow field. A photoelectric receiver deployed on the flue wall receives the backscattered light that passes through the flue gas flow field as a polarized scattered light signal. The polarized scattered light signal carries the absorption and scattering parameters of complex suspended particles in the flow field for light waves of different polarization states. The photoelectric conversion unit extracts the light intensity and phase parameters contained in the polarized scattered light signal, and converts it into a continuously fluctuating analog voltage signal after processing by the photoelectric amplification circuit. A high-frequency analog-to-digital converter performs high-frequency discretization sampling on the continuously fluctuating analog voltage signal to extract and generate a discrete voltage sequence containing timestamps. A matrix construction algorithm constructs the discrete voltage sequence according to the time sequence combination, and arranges it to generate the original Stokes parameter matrix reflecting the polarization characteristics of the flow field. The row and column elements in the matrix correspond to the transient intensity values ​​of different polarization states. The calculation module performs Jones matrix inversion on the original Stokes parameter matrix, and separates the inherent optical properties of the fluid medium through mathematical decoupling of multiple scattering effects, directly extracting the spatial distribution characteristics of the extinction coefficient, which characterizes the attenuation rate of the laser beam at different spatial coordinates of the flow field. The spatial distribution characteristics of the extinction coefficient are input into a preset thermodynamic transfer function for nonlinear equation solving. Using a built-in data mapping formula between optical attenuation rate, mass density, and temperature gradient, the transient thermodynamic density scalar field and local thermal gradient vector matrix of the flue gas field are mapped and output. In the application scenario of deep collaborative purification of the tail flue gas duct of coal-fired power plants, the flue gas is filled with dust and aerosols with extremely uneven concentration distribution. The polarization decoupling and inversion processing step can effectively eliminate optical interference from background saturated water vapor, converting complex optical attenuation data into density data that objectively reflects the three-dimensional aggregation state of multiple pollutant components and vector gradient data that reflects the local temperature change trend.

[0025] The fluid dynamics calculation module receives the local thermal gradient vector matrix and substitutes the temperature partial derivative terms contained within it into the fluid dynamics equations for numerical calculation. The fluid dynamics equations, through the fluid state equation, describe the coupling state between the temperature gradient and the fluid's sound velocity and density, thereby generating an acoustic impedance spatial distribution matrix that reflects the distribution of sound wave propagation resistance within the flue gas field. The acoustic analysis module defines the spatial boundary conditions for solving the wave equation based on the acoustic impedance spatial distribution matrix, and iteratively solves the Helmholtz wave equation to obtain a set of complex eigenvalues. The real part of these complex eigenvalues ​​corresponds to the spatial resonant frequency parameters of the system, while the imaginary part reflects the sound frequency energy dissipation characteristics of the system. The system extracts analytically the transmission frequency and initial phase parameters of the multi-frequency nonlinearly coupled sound wave sequence from the complex eigenvalues. A density distribution threshold is set in the transient thermodynamic density scalar field to distinguish between background components and high-concentration pollutant components. A filtering algorithm directly removes ordinary environmental background data points with values ​​below the density distribution threshold from the transient thermodynamic density scalar field, retaining only data points with values ​​above the density distribution threshold to delineate a three-dimensional coordinate set of high-density free gas phase components. This three-dimensional coordinate set clearly indicates the heavily enriched regions of escaped ammonia and unremoved sulfur trioxide and other pollutant molecules. The spatial center coordinates of the three-dimensional coordinate set of high-density free gas phase components are extracted. Based on the swirling flow characteristics at the spatial center coordinates, the operating angular frequency of the rotating radio frequency electric field is calculated. The central processing unit combines and packages the calculated transmission frequency, initial phase parameters, and operating angular frequency into transmission parameters that control the operation of the back-end generator.

[0026] After outputting the acoustic wave sequence and rotating radio frequency electric field to the flue gas flow field, the acoustic and electromagnetic field interference data processing step is initiated. The frequency and phase parameters of the acoustic wave sequence and the angular frequency parameters of the rotating radio frequency electric field are input into the finite element analysis software for three-dimensional mesh calculation. Within the three-dimensional mesh space, the energy interaction and evolution process of the acoustic mechanical wave and the radio frequency electromagnetic field are simulated. The interference superposition matrix at each mesh node within the flue gas flow field is calculated, recording the combined potential energy value after the Lorentz force constraint superposition of the acoustic and electromagnetic energy. A three-dimensional visualization rendering algorithm is applied to establish a spatially mapped three-dimensional model of the dynamic equivalent acoustic metamaterial potential field based on the interference superposition matrix. This spatially mapped three-dimensional model visually presents the energy fluctuation distribution state constructed by the wave field interference superposition within the flow field. The computational unit quantifies the shear stress distribution data at different nodes within the spatially mapped three-dimensional model caused by the superposition of fluid dynamics and physical fields. This shear stress distribution data characterizes the mechanical gradient within the flue gas flow field that physically damages the initially agglomerated fine particles. The comparison module searches and extracts the three-dimensional coordinates of spatial nodes whose shear stress values ​​are lower than a preset shear threshold from the shear stress distribution data. A shear stress value lower than the preset shear threshold indicates that there is an absolutely static physical environment in which the fluid shear force and acoustic radiation force cancel each other out in a local area. The control system uses the extracted node three-dimensional coordinates as the three-dimensional coordinates of the topological local valley.

[0027] After locating the three-dimensional coordinates of the topological local valleys, the system proceeds to the physical phase change environment parameter derivation stage. The data extraction program retrieves the real-time temperature and pressure parameters corresponding to the three-dimensional coordinates of the topological local valleys from the transient thermodynamic density scalar field. These retrieved temperature and pressure parameters are then substituted into the Clausius-Clapeyron equation as key thermodynamic boundary variables. The Clausius-Clapeyron equation describes the physical law governing the change of vapor pressure with temperature within a single-component two-phase equilibrium system of a pure substance. Numerical solution to the Clausius-Clapeyron equation calculates the theoretical threshold of the latent heat flux required for the gaseous substance to undergo a condensation phase change. This theoretical threshold defines the minimum energy barrier required to initiate a large-area condensation phase change. Based on the theoretical threshold of the latent heat flux and the spatial distribution density of the three-dimensional coordinates of the topological local valleys, a flow field trajectory inverse solution algorithm is used to derive and calculate the data matrix of microcapsule injection spatial positions and injection rates. The injection rate data matrix contains the optimal dosage and flow rate control commands for each microcapsule injection spatial position. The drug delivery system precisely delivers latent heat-responsive chain-type hydrophilic condensation nucleus microcapsules into the flue gas field according to parameters set by the microcapsule injection spatial position and injection rate data matrix. As the microcapsules move with the airflow, they enter a topological trough region with extremely low physical shear force. Upon contact with the high-temperature fluid, the polymer material of the microcapsule wall undergoes molecular chain degradation and breakage. The free gaseous components undergo an initial condensation phase transition around the hydrophilic groups generated by the degradation, while the liquid ammonium hydrogen sulfate phase transition releases a large amount of latent heat, dissipating outwards to form a microscopic latent heat shock wave.

[0028] Microscopic latent heat shock waves propagate in high-temperature, highly turbulent flue gas and are prone to energy attenuation and dissipation. Acoustic sensors are used to collect real-time perturbation data of the acoustic refractive index along the propagation path of the sound wave sequence. This real-time perturbation data objectively reflects the difference in photoacoustic propagation speed caused by minute fluctuations in the density and temperature of the medium within the flue gas field. The collected real-time perturbation data is substituted into the wave attenuation equation for path integration, establishing a transmission attenuation model specifically for the sound wave sequence propagation path. This model quantitatively predicts the amplitude loss curve of the microscopic latent heat shock wave along its propagation path. A preset initial transmission power is used as an input variable to the transmission attenuation model for forward calculation, yielding the corresponding power fine-tuning difference. The main control system uses this calculated power fine-tuning difference to perform feedforward control on the sound-generating equipment, adjusting the initial transmission power of the sound wave sequence in real-time. The superimposed energy of the sound wave sequence after power adjustment compensates for the nonlinear amplitude loss caused by fluid viscosity and thermal conduction during the propagation of the microscopic latent heat shock wave along its path. The high-amplitude microscopic latent heat shock wave is propelled by the airflow and collides with the surrounding suspended latent heat-responsive chain-type bihydrophilic condensation nucleus microcapsules. The mechanical shock wave pressure breaks the capsule walls, and a large number of latent heat-responsive chain-type bihydrophilic condensation nucleus microcapsules undergo mechanical rupture, releasing hydrophilic nuclei and latent heat of phase transition, triggering a cascaded and amplified exponential wall-breaking reaction in the flue gas field.

[0029] The exponential cascade cell disruption reaction releases a large number of hydrophilic groups encapsulated within the latent heat-responsive chain-like bihydrophilic condensation nucleus microcapsules into the flue gas flow field. These released hydrophilic groups are dispersed into the external space by turbulent diffusion within the flow field. Multiple groups of dispersed hydrophilic groups intertwine and converge in specific regions, forming a lattice of hydrophilic active centers with high surface energy according to hydrodynamic distribution principles. Free water vapor and incompletely combined gaseous precursors, widely distributed within the flue gas flow field, are attracted by surface energy and spontaneously converge to the hydrophilic active center lattice. The free water vapor and gaseous precursors overcome the energy barrier of homogeneous nucleation, undergoing continuous condensation phase transitions around the hydrophilic active center lattice. During interphase mass transfer, the free water vapor undergoing these phase transitions generates strong capillary adsorption forces, adsorbing and encapsulating surrounding suspended ultrafine aerosol particles into the liquid phase system. As moisture continues to condense, the liquid system containing ultrafine aerosol particles expands in volume, and the micro-scale particles aggregate and grow to form macro-scale secondary large droplets.

[0030] Visual monitoring sensors deployed at the back end of the removal system emit detection beams into the flue gas flow field and receive transmitted light. Based on the transmittance attenuation data caused by secondary large droplets blocking the light, they collect in real time the local transmittance jump signal induced by condensation phase change. The local transmittance jump signal objectively reflects the dynamic physical process of transmittance decreasing stepwise over time within a specific detection field of view. The data acquisition board receives the local transmittance jump signal and uses the built-in analog-to-digital converter circuit to perform high-frequency sampling and quantization operations on the continuously fluctuating analog electrical signal, converting the analog local transmittance jump signal into a discrete digital time series signal. The computing unit inputs the digital time series signal into a preset multiphase flow aerosol dynamics equation to perform nonlinear numerical calculations. The multiphase flow aerosol dynamics equation contains calculus operators describing particle collision, aggregation, condensation, and growth. The numerical calculation process deconstructs the particle concentration change gradient data contained in the digital time series signal. The data processing module extracts the transient volume expansion rate, reflecting the slope of the secondary large droplet size change over time, and the charge characteristic value, reflecting the charge density attached to the droplet surface, from the numerical calculation results of the multiphase flow aerosol kinetic equations. The extracted transient volume expansion rate and charge characteristic values ​​are concatenated according to a multidimensional vector data structure and reconstructed into a feedforward input matrix with temporal characteristics.

[0031] The central controller's computational core receives the feedforward input matrix and inputs this time-series-characteristic matrix into the fuzzy proportional-integral-differential (PID) algorithm model for feedback error calculation. The fuzzy PID algorithm model incorporates a nonlinear membership function tailored to the highly turbulent characteristics of flue gas. The feedback error calculation step dynamically compares the feedforward input matrix with preset ideal dust removal rate benchmark data to calculate the dynamic deviation between the system's current physical operating state and the ideal dust removal state. The computational core extracts the dynamic deviation output from the feedback error calculation and performs optimization mapping within a pre-calibrated control rule base based on this dynamic deviation to determine the required DC operating bias voltage and high-frequency pulse power supply duty cycle for the dust collection plates of the end-of-line dust collection electric field under the current flow field condition. A detailed explanation of the inherent correlations of the fuzzy PID algorithm model in the scenario of coordinated removal of multiple pollutants from flue gas is provided. The fuzzy PID algorithm model includes a fuzzification processing subroutine, multi-dimensional fuzzy inference association rules, and defuzzification analytical calculation steps. The fuzzification subroutine receives the transient volume expansion rate and charge characteristic values ​​extracted from the feedforward input matrix, and combines them with the dynamic deviation output from the feedback error calculation, which together serve as the basic universe of discourse input variables for the algorithm. The fuzzification subroutine utilizes a nonlinear membership function tailored to the highly turbulent characteristics of flue gas to transform the basic universe of discourse input variables into discrete fuzzy linguistic variables. These fuzzy linguistic variables are divided into five physical state levels: negative large, negative small, zero, positive small, and positive large. A pre-calibrated control rule base contains multidimensional fuzzy inference association rules that establish nonlinear coupling relationships between fuzzy linguistic variables and proportional, integral, and derivative coefficient adjustment values. The inherent physical logic of the multidimensional fuzzy inference association rule is set as follows: When the dynamic deviation is evaluated as positive and the transient volume expansion rate is evaluated as positive, it indicates that the generation rate of secondary large droplets increases sharply and the system deviates significantly from the ideal dust removal state. The multidimensional fuzzy inference association rule outputs a positive proportional coefficient adjustment and a negative integral coefficient adjustment to suppress the oversaturation integral effect and prevent the instantaneous aggregation of high-concentration droplets from causing the breakdown of the electric field of the dust collection plate. When the dynamic deviation is evaluated as zero and the charge characteristic value is evaluated as positive, it indicates that the system is in the stable adsorption critical range. The multidimensional fuzzy inference association rule outputs a zero proportional coefficient adjustment and a positive small integral coefficient adjustment to maintain the stable corona discharge of the end dust collection electric field. The defuzzification analytical calculation step receives the adjustment values ​​of each state level output by the multidimensional fuzzy inference association rule and uses the centroid analytical algorithm to solve the state level into a continuous real number of proportional coefficient increment, integral coefficient increment, and differential coefficient increment.The core operation iteratively accumulates the determined incremental values ​​of the proportional coefficient, integral coefficient, and differential coefficient, and substitutes the updated system constants into the output equation of the fuzzy proportional-integral-differential algorithm model to perform calculus operations. Finally, it determines the DC operating bias voltage and high-frequency pulse power supply duty cycle required by the end-of-line dust collection electric field execution unit, and completes the low-level closed-loop association between the input parameters of the control algorithm model and the execution parameters of the physical hardware.

[0032] The storage module inputs the calculated DC operating bias voltage and high-frequency pulse power supply duty cycle into the database, saving the data as DC bias voltage and high-frequency pulse duty cycle data. The main control unit reads the DC bias voltage and high-frequency pulse duty cycle data from the database in real time and sends corresponding voltage control commands to the high-voltage power supply driver of the terminal dust collection electric field. The high-voltage power supply driver responds to the voltage control commands and dynamically adjusts the electrostatic adsorption parameters of the terminal dust collection electric field plates, changing the electric field gradient distribution of the corona discharge intensity and the distance between the dust collection plates. The secondary large-particle droplets carrying charges are driven by the electrostatic force within the established high-intensity electrostatic field, and undergo directional migration towards the surface of the dust collection plates. The dust collection plates use electrostatic adsorption to intercept the secondary large-particle droplets close to the plate surface and physically separate them from the main airflow. The separated secondary large-particle droplets collect along the plate surface and flow into the bottom ash hopper system to perform the operation of removing colored smoke components.

[0033] This paper supplements the underlying data flow and mathematical logic deduction processes involved in the multi-pollutant synergistic removal control method for flue gas from coal-fired power plants, providing corresponding data processing paths and detailed physical equation calculations. After the photoelectric detection sensor converts the collected polarized scattered light signal into an original Stokes parameter matrix, the computation module performs a Jones matrix inversion operation on the original Stokes parameter matrix to extract the spatial distribution characteristics of the extinction coefficient within the flue gas flow field. The specific formula for the Jones matrix inversion operation is as follows:

[0034] In the formula, This represents the spatial distribution characteristics of the extinction coefficient. This represents the limit constant for the propagation distance of a polarized laser beam within the flue gas field. Represents the natural logarithm operator. Represents the matrix determinant calculation operator. This represents the Jones inverse matrix corresponding to the polarized scattered light signal. This represents the original Stokes parameter matrix generated by arranging discrete voltage sequences.

[0035] After obtaining the spatial distribution characteristics of the extinction coefficient, the computation unit substitutes these characteristics into a preset thermodynamic transfer function. The preset thermodynamic transfer function includes density mapping component formulas and gradient calculation component formulas, which respectively generate the transient thermodynamic density scalar field and the local thermal gradient vector matrix. The density mapping component formula is as follows:

[0036] In the formula, Represents the transient thermodynamic density scalar field. This represents the mass extinction conversion factor, calibrated experimentally. This represents the spatial distribution characteristics of the extinction coefficient. This represents the baseline flue gas density constant under clean and dust-free conditions. The gradient calculation component formula is:

[0037] In the formula, Represents the local thermal gradient vector matrix. Represents the inherent thermodynamic coupling constants of the flue gas components. Represents the partial derivative operator in three-dimensional space. This represents the transient thermodynamic density scalar field. After the fluid dynamics calculation module generates the acoustic impedance spatial distribution matrix, the acoustic analysis module iteratively solves the Helmholtz wave equation based on the acoustic impedance spatial distribution matrix to extract complex eigenvalues. The specific form of the Helmholtz wave equation is as follows:

[0038] In the formula, Represents the Laplace operator, Represents the sound pressure wave function within the physical field of audio frequencies. The frequency of the multi-frequency nonlinear coupled acoustic wave sequence to be solved represents the transmission frequency. This represents the local sound velocity of the fluid within the spatial distribution matrix of acoustic impedance. Represents the imaginary unit. This represents the dissipation coefficient of sound energy penetrating the smoke flow field. The complex eigenvalues ​​obtained from the equation contain real and imaginary parts. The real part directly corresponds to the transmission frequency parameters of the multi-frequency nonlinearly coupled sound wave sequence, while the imaginary part is derived and converted into the initial phase parameters of the sound wave sequence.

[0039] The data extraction program retrieves real-time temperature and pressure parameters corresponding to the three-dimensional coordinates of the topological local valleys from the transient thermodynamic density scalar field. These parameters are then substituted into the Clausius-Clapeyron equation to calculate the theoretical threshold of the microscopic latent heat flux required to induce a large-area condensation phase transition. The transformation formula for the Clausius-Clapeyron equation is as follows:

[0040] In the formula, Represents the theoretical threshold of microscopic latent heat flux. This represents the real-time temperature parameter corresponding to the three-dimensional coordinates of the topological local valley extracted from the transient thermodynamic density scalar field. This represents the difference in specific volume during the gas-liquid phase transition of ultrafine aerosol particles. This represents the rate of change of saturated vapor pressure with temperature, calculated based on real-time temperature and pressure parameters. The control system of the end-of-pipe dust collection electric field inputs a feedforward input matrix containing transient volume expansion rate and charge characteristic values ​​into the fuzzy proportional-integral-differential algorithm model. Dynamic comparison is performed to calculate the dynamic deviation, and the required DC operating bias voltage and high-frequency pulse power supply duty cycle for the output end-of-pipe dust collection electric field are calculated. The output equation of the fuzzy proportional-integral-differential algorithm model is:

[0041] In the formula, The DC operating bias voltage and high-frequency pulse power supply duty cycle represent the output of the fuzzy proportional-integral-differential algorithm model. Operators representing time variables in system operation. This represents the dynamic deviation generated by comparing the current physical operating state with the ideal dust removal state. Represents the fuzzy proportional coefficients within the control algorithm model. Represents the fuzzy integral coefficients within the control algorithm model. Represents the integral operator. These represent the fuzzy differential coefficients within the control algorithm model. It represents the first derivative term of the dynamic deviation as it changes over time.

[0042] To verify the objective feasibility of the aforementioned mathematical model and physical equations under the synergistic purification environment of coal-fired power generating units, a set of data processing examples with specific numerical values ​​is provided. During the deep synergistic purification monitoring of the tail flue, photoelectric detection sensors receive signals and input them into the Jones matrix inversion operation model. The known limit constant for the transmission distance of the polarized laser beam is given. The setting is 5.0 meters, and the calculation program extracts the original Stokes parameter matrix. Inverse matrix of Jones The determinant of the product is 0.6065. Substituting the known value into the aforementioned formula for inverting the Jones matrix, the spatial distribution characteristics of the extinction coefficient are calculated. The value is 0.1. The computation unit inputs the spatial distribution characteristic value of the extinction coefficient (0.1) into the density mapping component formula. The mass extinction conversion coefficient is known. The reference flue gas density constant is 2.5. The transient thermodynamic density scalar field was calculated using a setting of 1.2 kg / m³. The value is 1.45 kg per cubic meter. After locating the three-dimensional coordinates of the local trough in the topology, the system retrieves the real-time temperature parameters. The value is 380 Kelvin. The difference in specific volume during the gas-liquid phase transition of ultrafine aerosol particles is known. The calculated rate of change of saturated vapor pressure with temperature is 0.8 cubic meters per kilogram. The value is 150 Pascals per Kelvin. Substituting the known value into the transformation formula of the Clausius-Clapeyron equation, the theoretical threshold for the microscopic latent heat flux is calculated. The precise value is 45,600 joules per kilogram. After performing the microcapsule dosing operation based on the theoretical threshold of latent heat flux, the control system extracts the dynamic deviation output from the feedback error calculation. Within a specific control period, assuming the effects of the integral and derivative terms are in the steady-state balancing phase, the dynamic deviation... The value is set to 12 to control the fuzzy scaling factor within the algorithm model. The adaptive adjustment is set to 5.5, and the DC operating bias voltage and high-frequency pulse power supply duty cycle of the output are calculated. The value is 66 kV. The main control equipment issues instructions based on the 66 kV voltage control parameter to adjust the electrostatic adsorption parameters of the electrode plates, relying on the high-intensity electrostatic adsorption to completely intercept and peel off the secondary large droplets.

[0043] The method for synergistic removal and control of multiple pollutants in flue gas from coal-fired power plants includes the systematic construction process of a multiphase flow aerosol dynamics model. The computation module reads digital time-series signals and uses them as input data for the multiphase flow aerosol dynamics model. The multiphase flow aerosol dynamics model is based on the discrete phase population equilibrium equations to construct its fundamental mathematical framework. Within this framework, a collision kernel function describing the random Brownian motion of small particles and a condensation growth rate function describing the mass transfer between the gas and liquid phases are embedded. The central processing unit, combined with the transient thermodynamic density scalar field of the flue gas flow field, performs three-dimensional spatial integration on the collision kernel function to quantify and solve for the transient volume expansion rate of secondary large droplets. The multiphase flow aerosol dynamics model further introduces a unipolar charge evolution equation considering ion diffusion. Based on the concentration gradient change data in the digital time-series signal, the computation module performs numerical difference decomposition on the unipolar charge evolution equation to calculate the charge characteristic values ​​reflecting the charge density attached to the droplet surface. The multiphase flow aerosol dynamics model realizes a closed-loop data mapping logic from optical transmittance signals to physical phase transition parameters by coupling the discrete phase population equilibrium equation and the unipolar charge evolution equation at the bottom layer.

[0044] The multi-pollutant synergistic removal control method for flue gas from coal-fired power plants relies on several key physical thresholds. The density distribution threshold is set by scalar amplification of the baseline flue gas density under clean, dust-free conditions by 1.5 to 2.0 times. The calibrated density distribution threshold is embedded within the filtering algorithm, with a value set between 1.8 kg / m³ and 2.4 kg / m³. The filtering algorithm uses this density distribution threshold to accurately separate ordinary environmental background data from high-concentration free gas phase components in a three-dimensional coordinate system. The preset shear threshold is calculated based on the van der Waals force limit pull-out parameter of micron-sized aggregates in fluid mechanics. The calculation module limits the preset shear threshold to a physical range of 0.2 Pascal to 0.6 Pascal. Spatial nodes with shear stress values ​​below the preset shear threshold represent the absolutely safe aggregation zone where fluid shear force cannot tear the liquid phase system. The theoretical threshold for microscopic latent heat flux is generated through dynamic derivation using the Clausius-Clapeyron equation combined with the on-site temperature and pressure environment. The effective range of the theoretical threshold for latent heat flux spans from 35,000 joules per kilogram to 55,000 joules per kilogram. The theoretical threshold for latent heat flux directly determines the precise mass of the latent heat-responsive chain-type amphiphilic condensation nucleus microcapsules that need to be added, constituting the energy threshold for initiating a continuous condensation phase transition.

[0045] Example 1: For a 600 MW coal-fired power generation unit operating at full load, the flue gas temperature at the tail end is kept constant at 110 degrees Celsius. A photoelectric detection sensor deployed on the sidewall of the flue emits an orthogonally modulated polarized laser beam with a wavelength of 650 nm, receives the polarized scattered light signal generated by the penetrating flue gas flow field, and uses a photoelectric conversion circuit to convert the light intensity and phase parameters carrying the absorption and scattering parameters of suspended particles into an analog voltage waveform. A high-frequency analog-to-digital converter discretizes the analog voltage waveform at a frequency of 1000 Hz, generating a discrete voltage sequence containing timestamps. A matrix construction algorithm combines the discrete voltage sequence to generate the original Stokes parameter matrix. The computation module performs a Jones matrix inversion operation on the original Stokes parameter matrix, extracts the spatial distribution characteristics of the extinction coefficient, inputs the spatial distribution characteristics of the extinction coefficient into a preset thermodynamic transfer function for nonlinear mapping calculation, and outputs a transient thermodynamic density scalar field reflecting the three-dimensional distribution of particle mass concentration and a local thermal gradient vector matrix indicating the direction of temperature partial derivative changes.

[0046] The fluid dynamics calculation module substitutes the local thermal gradient vector matrix into the fluid dynamics equations to generate the acoustic impedance spatial distribution matrix. The acoustic analysis module iteratively solves the Helmholtz wave equation based on the acoustic impedance spatial distribution matrix, extracting complex eigenvalues ​​and analyzing the 2500 Hz transmission frequency and corresponding initial phase parameters. A filtering algorithm sets a density distribution threshold in the transient thermodynamic density scalar field, extracts the spatial center coordinates of the three-dimensional coordinate set of high-density free gas phase components, and calculates the 2.4 GHz rotating radio frequency electric field operating angular frequency. A multi-field coupling generator synchronously outputs an acoustic wave sequence and a rotating radio frequency electric field according to the set transmission parameters. The acoustic wave sequence interferes and superimposes under Lorentz force constraints, establishing a spatially mapped three-dimensional model of the dynamic equivalent acoustic metamaterial potential field. The comparison module quantifies the shear stress distribution data within the spatially mapped three-dimensional model, searches for the three-dimensional coordinates of spatial nodes with shear stress values ​​below 0.5 Pascals, and locates the three-dimensional coordinates of topological local valleys.

[0047] The data extraction program retrieves real-time temperature and pressure parameters corresponding to the three-dimensional coordinates of the topological local wave valley. These parameters are then substituted into the Clausius-Clapeyron equation for numerical solution, deriving the theoretical threshold of the latent heat flux required for the condensation phase transition of the gaseous substance. The flow field trajectory inverse solution algorithm calculates the microcapsule injection spatial position and injection rate data matrix based on the theoretical threshold of the latent heat flux. The dosing actuator injects latent heat-responsive chain-type hydrophilic condensation nucleus microcapsules into the flue gas field at a dosage of 500 grams per second. The microcapsules enter the topological wave valley region with extremely low physical shear force, where molecular chain degradation and breakage occur. The free gaseous components undergo condensation phase transition around the hydrophilic groups, emitting microscopic latent heat shock waves. Acoustic sensors collect real-time data on the acoustic refractive index disturbance along the propagation path of the sound wave sequence, substituting this data into the wave attenuation equation to calculate the power fine-tuning difference, and then feedforward to adjust the initial transmission power of the sound-generating device. High-amplitude microscopic latent heat shock waves trigger an exponential cascade cell disruption reaction in microcapsules. Free water vapor and gaseous precursors converge at the lattice position of the hydrophilic active center, breaking through the homogeneous nucleation barrier and undergoing continuous condensation phase transition. This process adsorbs ultrafine aerosol particles and induces volume expansion, generating secondary large droplets.

[0048] The visual monitoring hardware captures the local transmittance jump signal caused by the condensation phase transition, processes the analog electrical signal into a digital time-series signal through an analog-to-digital converter, and inputs it into the multiphase flow aerosol dynamics equation to perform nonlinear numerical calculations. The data processing module extracts the transient volume expansion rate and charge characteristics of the secondary large droplets, and splices and reconstructs them into a feedforward input matrix with time-series characteristics. The central controller's computing core inputs the feedforward input matrix into a fuzzy proportional-integral-differential algorithm model to calculate the dynamic deviation between the system's current operating state and the ideal dust removal state, and maps and matches the 60 kV DC operating bias voltage and 30% high-frequency pulse power supply duty cycle data in the control rule base. The main control equipment sends corresponding voltage control commands to the downstream high-voltage power supply driver to dynamically adjust the electrostatic adsorption parameters of the electrode plates. The charged secondary large droplets migrate laterally towards the dust collection electrode plates within the enhanced electrostatic field, are firmly intercepted by the dust collection electrode plates, and are physically separated from the exhaust gas flow.

[0049] Example 2: In a scenario involving severe ammonia escape in the front-end denitrification system of a 1000 MW ultra-supercritical generator unit, the concentrations of free ammonia and sulfur trioxide molecules in the tail flue are significantly increased. A photoelectric receiver receives polarized scattered light signals generated by the high-concentration pollutant cloud. A photoelectric amplifier circuit converts the weak light intensity and phase parameters into analog voltage signals with amplified fluctuations. A high-frequency analog-to-digital converter extracts the discrete voltage sequence and arranges it to generate the original Stokes parameter matrix. The Jones matrix inversion step decouples the multiple scattering effect and extracts the spatial distribution characteristics of the high-value extinction coefficient. The transient thermodynamic density scalar field output by the thermodynamic transfer function mapping exhibits a distribution pattern of sharply increasing local concentration gradients.

[0050] The fluid dynamics calculation module substitutes the temperature partial derivatives with steeply increasing gradients into the fluid dynamics equations, and the resulting acoustic impedance spatial distribution matrix shows a significant jump in fluid acoustic impedance. The acoustic analysis module extracts complex eigenvalues ​​reflecting high-frequency energy dissipation from the Helmholtz wave equation, defining a transmission frequency of 3500 Hz. A filtering algorithm eliminates ordinary environmental background data points, defining a larger set of three-dimensional coordinates for high-density free gas phase components. Finite element analysis simulates wave field energy interaction within a three-dimensional mesh space, and the interference superposition matrix records the increased comprehensive potential energy value under Lorentz force constraints. The three-dimensional visualization rendering algorithm establishes a spatially mapped three-dimensional model that presents a dense energy distribution. The comparison module rigorously searches for the three-dimensional coordinates of spatial nodes with shear stress values ​​below 0.3 Pascals as the three-dimensional coordinates of topological local wave valleys.

[0051] Substituting the retrieved real-time temperature and pressure parameters into the Clausius-Clapeyron equation, the theoretical threshold for the microscopic latent heat flux in the high-energy state is derived. A reverse flow trajectory algorithm calculates and generates a data matrix for the injection rate that increases the dosage. The injection actuator delivers latent heat-responsive chain-type amphiphilic condensation nucleus microcapsules to the contaminated area at a rate of 800 grams per second. The microcapsule walls rapidly degrade and fracture upon contact with the high-temperature, high-pressure fluid, causing free ammonia and saturated water vapor to undergo an initial condensation phase transition and release a high-intensity microscopic latent heat shock wave. A transmission attenuation model quantifies and predicts the amplitude loss curve along the shock wave propagation path, and the calculated power fine-tuning difference drives the sound-generating equipment to significantly increase the initial transmission power of the sound wave sequence. The high-intensity mechanical wave pressure deeply ruptures the microcapsule walls, and numerous hydrophilic groups are scattered and interwoven to form a lattice of hydrophilic active centers with extremely high surface energy. The high-concentration gaseous precursor undergoes an avalanche-like continuous condensation phase transition, generating a massive number of secondary large-particle droplets.

[0052] A visual monitoring sensor acquires a local transmittance jump signal, indicating a step-like decrease in transmittance over time. After the digital time-series signal is input into the multiphase flow aerosol dynamics equation, the computational unit deconstructs the transient volume expansion rate with an extremely steep slope and the high-density charge characteristic values. A feedforward input matrix with time-series characteristics is input into the fuzzy proportional-integral-differential algorithm model to calculate the feedback error and determine the excessively large dynamic deviation. The computational core optimizes the mapping in the control rule base to establish a 72 kV DC operating bias and a 45% high-frequency pulse power supply duty cycle. The high-voltage power supply driver responds to the voltage control command by significantly increasing the corona discharge intensity. Secondary large droplets, driven by an extremely high gradient electrostatic field, undergo high-speed directional migration towards the dust collecting plates, converging along the plate surface and flowing into the bottom ash hopper system for interception.

[0053] Example 3: Under the condition of 300 MW low-load deep peak-shaving operation of a coal-fired power generation unit, the fluid velocity inside the flue is reduced and the thermal field distribution exhibits highly discrete characteristics. A photoelectric detection sensor emits an orthogonally modulated polarized laser beam that penetrates the low-velocity flue gas field, and the received backscattered light carries weakly varying absorption and scattering parameters. The analog-to-digital conversion module performs sampling and quantization operations on the continuously fluctuating analog voltage signal to extract a discrete voltage sequence. The original Stokes parameter matrix generated by the matrix construction algorithm exhibits low-frequency variation properties. The computation module performs Jones matrix inversion on the original Stokes parameter matrix to obtain the spatial distribution characteristics of the extinction coefficient. Substituting this into a preset thermodynamic transfer function, a multidimensional manifold solution is performed. The output transient thermodynamic density scalar field shows that the tiny particles are sparsely and unevenly distributed.

[0054] Substituting the temperature partial derivative terms into the fluid dynamics equations generates a numerically smooth, fluctuating acoustic impedance spatial distribution matrix. Based on the spatial boundary conditions, the Helmholtz wave equation is solved to extract complex eigenvalues, analytically yielding the acoustic wave sequence emission frequency reduced to 1500 Hz. A filtering algorithm sets an adaptive density distribution threshold in a sparse density scalar field, extracting a smaller set of three-dimensional coordinates for high-density free gas phase components. The swirling characteristics of the flow field at the spatial center coordinates are measured to obtain a lower operating angular frequency of the rotating radio frequency electric field. The acoustic wave sequence and the rotating radio frequency electric field, under finite element analysis, generate a smoothly evolving interference superposition matrix, establishing a spatially mapped three-dimensional model of the dynamic equivalent acoustic metamaterial potential field, exhibiting a gently undulating energy distribution. The shear stress distribution data within the spatially mapped three-dimensional model is quantified, and large-area mechanical equilibrium physical nodes are searched as the three-dimensional coordinates of topological local valleys.

[0055] The Clausius-Clapeyron equation, using low-temperature and low-pressure parameters, calculates a theoretical threshold for a low-level microscopic latent heat flux. A reverse-engineering algorithm derives a data matrix of the spatial location and ejection rate of microcapsules corresponding to a dosage of 200 grams per second, based on spatial distribution density. The latent heat-responsive chain-like bihydrophilic condensation nucleus microcapsules slowly enter the topological trough region with a low-speed airflow. After undergoing an extended thermal response, the polymer material in the microcapsules experiences molecular chain degradation and breakage. The microscopic latent heat shock wave released during the initial condensation phase transition is relatively weak. An acoustic sensing device collects real-time perturbation data of the acoustic refractive index along the path to establish a transmission attenuation model. The initial transmission power of the sound-generating device is slowly adjusted based on a small power fine-tuning difference calculated in the forward calculation. The adjusted power microscopic latent heat shock wave collides and breaks the microcapsule wall, releasing the hydrophilic nucleus and triggering a low-intensity exponential cascade wall-breaking reaction. Free water vapor and free gaseous precursors converge to produce a continuous condensation phase transition, generating secondary large droplets.

[0056] The multiphase flow aerosol kinetic equations receive gradually varying local transmittance jump signals, extracting numerically low transient volume expansion rates and charge characteristics. The reconstructed feedforward input matrix is ​​imported into a fuzzy proportional-integral-differential algorithm model to perform feedback error comparison calculations, outputting a minimal dynamic deviation. The computational core maps and establishes a 45 kV DC operating bias and a 20% high-frequency pulse power supply duty cycle. The main control equipment issues voltage control commands to reduce the corona discharge intensity and decrease the electric field gradient distribution between the dust collecting plates. Secondary large droplets carrying weak charges are driven by Coulomb forces within a gentle electrostatic field, slowly migrating laterally towards the dust collecting plates, and smoothly adhering to the plate surface through electrostatic adsorption, thus being detached from the main airflow.

[0057] To verify the practical technical effectiveness of the synergistic removal and control method for multiple pollutants in flue gas from coal-fired power plants, this invention conducted a comparative verification experiment using a 600 MW coal-fired power generating unit. The comparative verification experiment was divided into two groups: the first group used conventional chemical spraying removal technology, and the second group used the synergistic removal and control method for multiple pollutants in flue gas from coal-fired power plants. After the first group of units operated continuously at full load for 168 hours, the average exhaust light transmittance at the chimney outlet recorded by the visual monitoring sensor was 82%, and the average concentration of submicron aerosols detected by the particulate matter sampling equipment reached 15 mg / m³. After the second group of units operated continuously at full load for 168 hours using the synergistic removal and control method for multiple pollutants in flue gas from coal-fired power plants, the average exhaust light transmittance recorded by the visual monitoring sensor at the chimney outlet increased to 98%, and the average concentration of submicron aerosols detected by the particulate matter sampling equipment decreased to 1.2 mg / m³. The comparative test data objectively demonstrates that the synergistic removal and control method for multiple pollutants in flue gas from coal-fired power plants significantly reduces the escape rate of fine suspended particles and eliminates the physical conditions that cause strong scattering of natural light by exhaust gas.

Claims

1. A method for synergistic removal and control of multiple pollutants in flue gas from coal-fired power plants, characterized in that, include: The polarized scattered light signal of the flue gas flow field in the tail flue of a coal-fired power plant is collected, and the light intensity and phase parameters of the polarized scattered light signal are extracted. The spatial distribution characteristics of the extinction coefficient are extracted based on the light intensity and phase parameters. The spatial distribution characteristics of the extinction coefficient are substituted into a preset thermodynamic transfer function to generate the transient thermodynamic density scalar field and the local thermal gradient vector matrix of the flue gas flow field. Based on the transient thermodynamic density scalar field and the local thermal gradient vector matrix, the emission parameters are set, and the acoustic wave sequence and rotating radio frequency electric field are output to the flue gas field according to the emission parameters. The acoustic wave sequence is caused to interfere and superimpose under the Lorentz force constraint of the rotating radio frequency electric field. A dynamic equivalent acoustic metamaterial potential field is constructed inside the flue gas field, and the node coordinates in the dynamic equivalent acoustic metamaterial potential field are extracted to generate the three-dimensional coordinates of the topological local valley. According to the three-dimensional coordinates of the topological local valley, latent heat-responsive chain-type amphiphilic condensation nucleus microcapsules are added to the flue gas flow field, causing the ultrafine aerosol particles existing in the flue gas flow field to undergo condensation phase change with the latent heat-responsive chain-type amphiphilic condensation nucleus microcapsules as condensation nuclei. The ultrafine aerosol particles expand after the condensation phase change to generate secondary large droplets. The local transmittance jump signal caused by the condensation phase change is collected. The DC bias voltage and high-frequency pulse duty cycle data of the end dust collection electric field are calculated using the local transmittance jump signal. The electrostatic adsorption parameters of the plates of the end dust collection electric field are adjusted according to the DC bias voltage and high-frequency pulse duty cycle data to capture the secondary large-particle droplets and remove colored smoke components.

2. The method for synergistic removal and control of multiple pollutants in flue gas from coal-fired power plants according to claim 1, characterized in that, The process involves collecting polarized scattered light signals from the flue gas flow field in the tail flue of a coal-fired power plant, extracting the intensity and phase parameters of the polarized scattered light signals, retrieving the spatial distribution characteristics of the extinction coefficient based on the intensity and phase parameters, and substituting these extinction coefficient spatial distribution characteristics into a preset thermodynamic transfer function to generate the transient thermodynamic density scalar field and local thermal gradient vector matrix of the flue gas flow field. This includes: An orthogonally modulated polarized laser beam is emitted into the flue gas field, and the backscattered light of the polarized laser beam is received as the polarized scattered light signal. The polarized scattered light signal is converted into an analog voltage signal. The analog voltage signal is discretized and sampled to extract a discrete voltage sequence. The original Stokes parameter matrix is ​​generated by combining the discrete voltage sequences. Perform a Jones matrix inversion operation on the original Stokes parameter matrix to extract the spatial distribution characteristics of the extinction coefficient; The spatial distribution characteristics of the extinction coefficient are substituted into the preset thermodynamic transfer function to solve the equation, and the transient thermodynamic density scalar field and the local thermal gradient vector matrix are output.

3. The method for synergistic removal and control of multiple pollutants in flue gas from coal-fired power plants according to claim 2, characterized in that, The step of setting the emission parameters based on the transient thermodynamic density scalar field and the local thermal gradient vector matrix includes: The acoustic impedance spatial distribution matrix of the flue gas field is generated by substituting the local thermal gradient vector matrix into the fluid dynamics equation. The Helmholtz wave equation is numerically solved based on the acoustic impedance spatial distribution matrix to obtain complex eigenvalues, and the emission frequency and initial phase parameters of the acoustic wave sequence are extracted using the complex eigenvalues. A density distribution threshold is set, and data points with values ​​greater than the density distribution threshold are selected from the transient thermodynamic density scalar field to delineate the three-dimensional coordinate set of high-density free gas phase components; The spatial center coordinates of the three-dimensional coordinate set of the high-density free gas phase components are extracted, and the angular frequency of the rotating radio frequency electric field is calculated based on the spatial center coordinates. The transmission frequency, the initial phase parameter and the angular frequency are then combined to form the transmission parameter.

4. The method for synergistic removal and control of multiple pollutants in flue gas from coal-fired power plants according to claim 3, characterized in that, The process of constructing a dynamic equivalent acoustic metamaterial potential field within the flue gas flow field and extracting the node coordinates in the dynamic equivalent acoustic metamaterial potential field to generate three-dimensional coordinates of the topological local valley includes: The sound wave sequence and the rotating radio frequency electric field are input to perform finite element analysis to calculate the interference superposition matrix inside the flue gas field; A spatial mapping three-dimensional model of the dynamic equivalent acoustic metamaterial potential field is established based on the interference superposition matrix. The shear stress distribution data inside the spatially mapped three-dimensional model is quantified, and the three-dimensional coordinates of nodes with shear stress values ​​lower than a preset shear threshold are extracted from the shear stress distribution data. The three-dimensional coordinates of these nodes are then used as the three-dimensional coordinates of the topological local valleys.

5. The method for synergistic removal and control of multiple pollutants in flue gas from coal-fired power plants according to claim 4, characterized in that, The step of adding latent heat-responsive chain-type bihydrophilic condensation nucleus microcapsules to the flue gas field according to the three-dimensional coordinates of the topological local trough includes: The temperature and pressure parameters corresponding to the three-dimensional coordinate positions of the topological local valley are retrieved from the transient thermodynamic density scalar field. Substituting the temperature and pressure parameters into the Clausius-Clapeyron equation, the theoretical threshold of the latent heat flux emitted by condensation is calculated. Based on the theoretical threshold of the microscopic latent heat flux and the three-dimensional coordinates of the topological local valley, the data matrix of the spatial position and ejection rate of the microcapsule injection is derived and calculated. The latent heat-responsive chain-type bihydrophilic condensation nucleus microcapsules are added according to the microcapsule injection spatial position and the injection rate data matrix, initiating an initial condensation phase transition and emitting microscopic latent heat shock waves outward.

6. The method for synergistic removal and control of multiple pollutants in flue gas from coal-fired power plants according to claim 5, characterized in that, After initiating the initial condensation phase transition and emitting a microscopic latent heat shock wave outward, the process includes: Collect real-time perturbation data of the acoustic refractive index along the propagation path of the acoustic wave sequence; Substitute the real-time perturbation data of the acoustic refractive index into the fluctuation attenuation equation to establish the transmission attenuation model corresponding to the propagation path of the acoustic wave sequence. The preset initial transmission power is input into the transmission attenuation model to perform forward calculation to obtain the power fine-tuning difference. The initial transmission power of the acoustic wave sequence is adjusted according to the power fine-tuning difference to compensate for the nonlinear amplitude loss of the microscopic latent heat shock wave when it propagates along the propagation path. The microscopic latent heat shock wave, after power adjustment, collides with and breaks up the surrounding suspended latent heat-responsive chain-type amphiphilic condensation nucleus microcapsules, triggering an exponential cascade cell-breaking reaction.

7. The method for synergistic removal and control of multiple pollutants in flue gas from coal-fired power plants according to claim 6, characterized in that, The exponential cascade cell-breaking reaction disperses hydrophilic groups into the flue gas field, and multiple sets of the hydrophilic groups converge to form a hydrophilic active center lattice. The free water vapor and gas phase precursor inside the flue gas flow field converge at the lattice position of the hydrophilic active center and undergo continuous condensation phase change. The free water vapor that undergoes the continuous condensation phase change adsorbs the surrounding ultrafine aerosol particles, and the volume expansion caused by water condensation generates the secondary large droplets.

8. The method for synergistic removal and control of multiple pollutants in flue gas from coal-fired power plants according to claim 7, characterized in that, The process of acquiring the local transmittance jump signal induced by the condensation phase transition and using the local transmittance jump signal to calculate the DC bias voltage and high-frequency pulse duty cycle data of the end-of-line dust collection electric field includes: The local transmittance jump signal is converted from analog to digital and substituted into the multiphase flow aerosol dynamics equation for numerical calculation. The transient volume expansion rate and charge characteristics of the secondary large droplets are extracted from the numerical calculation results of the multiphase flow aerosol dynamics equations. The transient volume expansion rate and the charge characteristic value are combined and reconstructed into a feedforward input matrix; the feedforward input matrix is ​​then input into the fuzzy proportional-integral-differential algorithm model for feedback error calculation. Extract the output result of the feedback error calculation, map and determine the DC working bias voltage and high-frequency pulse power supply duty cycle of the dust collection plate of the terminal dust collection electric field based on the output result, and record the DC working bias voltage and the high-frequency pulse power supply duty cycle as the DC bias voltage and high-frequency pulse duty cycle data.

9. The method for synergistic removal and control of multiple pollutants in flue gas from coal-fired power plants according to claim 8, characterized in that, The step of adjusting the electrostatic adsorption parameters of the terminal dust collection electric field based on the DC bias and high-frequency pulse duty cycle data to capture the secondary large-particle droplets and remove colored plume components includes: Based on the DC bias and high-frequency pulse duty cycle data, a corresponding voltage control command is issued; The electrostatic adsorption parameters of the plates of the terminal dust collection electric field are adjusted according to the voltage control command. The secondary large-particle droplets in the airflow are intercepted and stripped by electrostatic adsorption, thereby removing colored smoke components.

10. A multi-pollutant synergistic removal control system for flue gas from coal-fired power plants, applied to the multi-pollutant synergistic removal control method for flue gas from coal-fired power plants as described in any one of claims 1 to 9, characterized in that, include: The signal processing module is used to collect polarized scattered light signals of the flue gas flow field in the tail flue of a coal-fired power plant, extract the light intensity and phase parameters of the polarized scattered light signals, extract the spatial distribution characteristics of the extinction coefficient based on the light intensity and phase parameters, and substitute the spatial distribution characteristics of the extinction coefficient into a preset thermodynamic transfer function to generate the transient thermodynamic density scalar field and local thermal gradient vector matrix of the flue gas flow field. The potential field construction module is used to set the transmission parameters based on the transient thermodynamic density scalar field and the local thermal gradient vector matrix, output the acoustic wave sequence and the rotating radio frequency electric field to the flue gas field according to the transmission parameters, cause the acoustic wave sequence to interfere and superimpose under the Lorentz force constraint of the rotating radio frequency electric field, construct a dynamic equivalent acoustic metamaterial potential field inside the flue gas field, and extract the node coordinates in the dynamic equivalent acoustic metamaterial potential field to generate the three-dimensional coordinates of the topological local valley. The capsule dosing module is used to add latent heat-responsive chain-type amphiphilic condensation nucleus microcapsules to the flue gas flow field according to the three-dimensional coordinates of the topological local valley, so as to cause the ultrafine aerosol particles existing in the flue gas flow field to undergo condensation phase change with the latent heat-responsive chain-type amphiphilic condensation nucleus microcapsules as condensation nuclei, and the ultrafine aerosol particles expand after the condensation phase change to generate secondary large droplets; The electric field adjustment module is used to collect the local transmittance jump signal caused by the condensation phase change, calculate the DC bias voltage and high-frequency pulse duty cycle data of the end dust collection electric field using the local transmittance jump signal, and adjust the electrostatic adsorption parameters of the electrode plates of the end dust collection electric field according to the DC bias voltage and high-frequency pulse duty cycle data to capture the secondary large-particle droplets to remove colored smoke components.

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