Organic waste gas desorption control method based on dynamic assessment of adsorption state

Abstract

This invention discloses a method for controlling the desorption of organic waste gas based on dynamic assessment of adsorption state, relating to the fields of waste gas treatment and intelligent control technology. The method includes: injecting multi-frequency AC micro-perturbation electrical signals into an organic waste gas adsorption bed and acquiring a dynamic complex impedance dielectric spectrum; determining the local saturation of the adsorbent and the three-dimensional spatial distribution characteristics of the adsorption state within the adsorption bed; if the local saturation reaches a desorption threshold, generating an instruction containing spatial focusing coordinates and target desorption energy; and using a spatial phased array microwave desorption system to emit a radio frequency beam for targeted desorption of the focusing coordinate region. This invention addresses the problems of passive single-point monitoring with sensing blind spots in traditional waste gas treatment, as well as the uneven desorption and low thermal energy utilization efficiency caused by blind overall heating of the entire bed.

Description

Technical Field

[0001] This invention relates to the field of waste gas treatment and intelligent control technology, and more specifically, to a method for desorption control of organic waste gas based on dynamic assessment of adsorption state. Background Technology

[0002] The adsorption, enrichment, and desorption concentration of volatile organic compounds (VOCs) are core processes in industrial waste gas treatment. During the long-term operation of porous adsorption beds, accurately identifying the local saturation state of the adsorbent and efficiently implementing desorption and regeneration directly determines the purification efficiency and overall energy consumption of the waste gas treatment system. The gas-solid mass transfer process within the porous bed is extremely complex. Achieving real-time visualization of the microscopic adsorption state and precise spatial scheduling of desorption energy is a critical technological bottleneck that urgently needs to be overcome in the field of environmental protection equipment.

[0003] Currently, mainstream desorption control solutions in the industry generally employ thermodynamic sensors or optical concentration probes for passive, single-point status monitoring. When the VOCs concentration or temperature rise at a preset physical monitoring point reaches an empirical threshold, the system triggers whole-bed hot air purging or global blind microwave heating for desorption and regeneration, while relying on traditional mechanical pneumatic valves to physically switch the intake and exhaust flow paths.

[0004] However, the aforementioned existing technologies have limitations: First, traditional passive sensing methods have inherent physical and thermal inertia lag, making it difficult to accurately map the molecular filling state within microscopic pores, and are highly susceptible to interference from unknown fluctuating components in the exhaust gas, leading to frequent distortions in the adsorption front penetration prediction; Second, traditional fluid heat transfer is prone to causing airflow short-circuiting in porous media, and the global overall heating mode not only causes redundant consumption of thermal energy in low-concentration areas, but also leads to the problem of incomplete and non-uniform desorption in high-enrichment areas; Finally, the frequent operation of traditional mechanical valves is prone to mechanical fatigue lag. Summary of the Invention

[0005] To overcome the aforementioned deficiencies of the prior art, embodiments of the present invention provide an organic waste gas desorption control method based on dynamic assessment of adsorption state. This method constructs the three-dimensional spatial distribution characteristics of local saturation of the adsorption bed by analyzing the dynamic complex impedance dielectric spectrum, and uses a spatial phased array microwave radio frequency beam to precisely target and desorb high-saturation aggregation areas. This solves the problems of blind spots in traditional passive single-point monitoring and uneven desorption and low thermal energy utilization efficiency caused by blind overall heating of the entire bed.

[0006] To achieve the above objectives, the present invention provides the following technical solution: The organic waste gas desorption control method based on dynamic assessment of adsorption state includes the following steps: injecting multi-frequency AC micro-perturbation electrical signals into the organic waste gas adsorption bed and collecting the dynamic complex impedance dielectric spectrum of the organic waste gas adsorption bed; determining the local saturation of the adsorbent and the three-dimensional spatial distribution characteristics of the adsorption state in the organic waste gas adsorption bed according to the dynamic complex impedance dielectric spectrum; if the local saturation reaches a preset desorption threshold, generating a target desorption command including spatial focusing coordinates and target desorption energy according to the three-dimensional spatial distribution characteristics; sending the target desorption command to a spatial phased array microwave desorption system to use the phased array microwave radio frequency beam to perform targeted desorption on the region corresponding to the spatial focusing coordinates.

[0007] In a preferred embodiment, the step of injecting a multi-frequency AC perturbation signal into the organic waste gas adsorption bed and acquiring the dynamic complex impedance dielectric spectrum of the organic waste gas adsorption bed includes: applying a multi-frequency AC perturbation signal with a target frequency sweep range to both ends of the organic waste gas adsorption bed; acquiring the response current of the organic waste gas adsorption bed and the phase difference between the applied voltage and the response current; calculating the complex impedance based on the frequency, response current, and phase difference of the multi-frequency AC perturbation signal to obtain the dynamic complex impedance dielectric spectrum, and extracting the dielectric relaxation time constant based on the dynamic complex impedance dielectric spectrum.

[0008] In a preferred embodiment, determining the local saturation and three-dimensional spatial distribution characteristics of the adsorbent in the organic waste gas adsorption bed based on the dynamic complex impedance dielectric spectrum includes: extracting the capacitance change rate and equivalent polarization resistance characteristics from the dynamic complex impedance dielectric spectrum; inputting the capacitance change rate and equivalent polarization resistance characteristics into a pre-trained state assessment model to map the saturation of each zone in the organic waste gas adsorption bed; and performing spatial topological mapping on the saturation of each zone to generate the three-dimensional spatial distribution characteristics.

[0009] In a preferred embodiment, before inputting the capacitance change rate and equivalent polarization resistance characteristics into the pre-trained state assessment model, the method further includes: determining whether an unknown dielectric relaxation time constant appears in the dynamic complex impedance dielectric spectrum; if an unknown dielectric relaxation time constant appears, it is determined that there is an unknown component in the current organic waste gas, and the unknown dielectric relaxation time constant is used as a new feature node to update the weight of the state assessment model online.

[0010] In a preferred embodiment, the method further includes: after a single desorption cycle, collecting the current reference complex impedance dielectric spectrum of the organic waste gas adsorption bed in a clean state; comparing the current reference complex impedance dielectric spectrum with the preset initial reference complex impedance dielectric spectrum, and calculating the drift of the reference equivalent polarization internal resistance; if the drift is greater than a preset attenuation warning value, then when generating the target desorption command for the next time, adding a deep thermal desorption protocol, which is used to increase the upper limit of the desorption temperature in the region corresponding to the spatial focusing coordinates.

[0011] In a preferred embodiment, generating a target desorption command containing spatial focusing coordinates and target desorption energy based on the three-dimensional spatial distribution features includes: identifying a cluster region in the three-dimensional spatial distribution features where the saturation is greater than a preset desorption threshold; calculating the three-dimensional geometric center of the cluster region and using it as the spatial focusing coordinate; and calculating the microwave radiation duration and emission power based on the saturation, volume, and preset dielectric constant of the cluster region, using them as the target desorption energy.

[0012] In a preferred embodiment, the step of calculating the microwave radiation duration and emission power based on the saturation, volume, and preset dielectric constant of the agglomeration zone further includes: obtaining the target calorific value lower limit required for the catalytic combustion chamber connected to the organic waste gas adsorption bed to maintain a self-sustaining combustion state; converting the expected desorbed organic waste gas concentration into expected latent chemical heat, and determining whether the expected latent chemical heat is greater than or equal to the target calorific value lower limit; if the expected latent chemical heat is less than the target calorific value lower limit, then delaying the triggering time of the target desorption command for the current agglomeration zone until the accumulated expected latent chemical heat meets the target calorific value lower limit.

[0013] In a preferred embodiment, the targeted desorption of the region corresponding to the spatial focusing coordinates using a phased array microwave radio frequency beam includes: calculating the excitation phase difference of multiple microwave transmitting antennas in the spatial phased array microwave desorption system based on the spatial focusing coordinates; and adjusting the transmission phase angle of each microwave transmitting antenna according to the excitation phase difference so that the microwave beams emitted by each microwave transmitting antenna coherently superimpose at the spatial focusing coordinates.

[0014] In a preferred embodiment, the process of targeting and desorbing the region corresponding to the spatial focusing coordinates using a phased array microwave radio frequency beam further includes: real-time monitoring of the real-time equivalent polarization internal resistance of the partition where the spatial focusing coordinates are located; if the real-time equivalent polarization internal resistance falls back to a preset reference resistance range, the current targeted desorption process for the spatial focusing coordinates is terminated.

[0015] In a preferred embodiment, before sending the target desorption command to the space phased array microwave desorption system, the method further includes: laterally injecting control micro-jet into the main airflow flowing into the exhaust gas inlet duct; and using the Coanda effect to change the adhesion state of the main airflow on the wall of the exhaust gas inlet duct, deflecting the main airflow to a backup bypass to cut off the intake of the current organic waste gas adsorption bed.

[0016] The technical effects and advantages of the organic waste gas desorption control method based on dynamic assessment of adsorption state in this invention are as follows: This invention achieves real-time and precise visualization of the three-dimensional spatial distribution characteristics of local saturation and adsorption state within the adsorption bed by actively injecting multi-frequency AC micro-perturbation electrical signals into the organic waste gas adsorption bed and analyzing its dynamic complex impedance dielectric spectrum. This breaks through the perception blind spots of traditional single-point passive monitoring. Based on this, the system can accurately locate the spatial focusing coordinates and required desorption energy of the high-saturation region and drive the spatial phased array microwave desorption system to emit radio frequency beams for targeted desorption of that specific coordinate region. This method deeply couples microscopic electrical situational awareness with spatial phased array directional energy projection, realizing a targeted regeneration mechanism of "precise positioning and on-demand, fixed-point deployment." This effectively avoids the huge waste of thermal energy and uneven desorption caused by traditional whole-bed indiscriminate heating, improving the system's desorption efficiency and overall energy-saving performance. Attached Figure Description

[0017] Figure 1 A schematic diagram of the organic waste gas desorption control method based on dynamic assessment of adsorption state provided in an embodiment of the present invention; Figure 2 Comparison of dielectric relaxation characteristics of toluene and acetone provided in embodiments of the present invention; Figure 3 This is a simulation cloud map of the three-dimensional spatial distribution of local saturation in the adsorption bed provided in an embodiment of the present invention; Figure 4 The simulation diagram of the heat demand of the catalytic combustion chamber and the latent chemical heat of the target aggregation region provided in the embodiments of the present invention; Figure 5 The transient electric field distribution diagram of microwave phased radio frequency beam synthesis in a porous medium provided in an embodiment of the present invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0019] Example 1, Figure 1 The present invention provides a method for controlling the desorption of organic waste gas based on dynamic assessment of adsorption state, comprising the following steps: S1, inject multi-frequency AC micro-perturbation electrical signals into the organic waste gas adsorption bed, and collect the dynamic complex impedance dielectric spectrum of the organic waste gas adsorption bed.

[0020] In this embodiment, the step of injecting multi-frequency AC micro-perturbation electrical signals into the organic waste gas adsorption bed and collecting the dynamic complex impedance dielectric spectrum of the organic waste gas adsorption bed includes: S101, a multi-frequency AC micro-perturbation electrical signal with a target frequency sweep range is applied to both ends of the organic waste gas adsorption bed; to ensure that the micro-perturbation signal can fully and uniformly cover the complex porous spatial structure inside the adsorption bed, a three-dimensional multi-point matrix distribution of measurement electrodes is adopted. Specifically, the electrode array is made of corrosion-resistant, highly conductive titanium-based platinum-plated (Ti / Pt) alloy material to form needle-shaped microelectrodes, arranged according to a set spatial grid spacing (e.g., ...). The three-dimensional lattice of particles is deeply embedded and interlaced within the porous adsorbent bed. Simultaneously, the target frequency sweep range is set as... to The wide frequency band. The physical meaning of setting this frequency sweep range is: low frequency band ( This can fully stimulate the space charge polarization and interfacial polarization effects between the adsorbent and macromolecular VOCs; while the mid-to-high frequency range ( This allows for the precise capture of the orientation polarization dynamic response of small molecule dipoles, thus providing a complete physical excitation source for the comprehensive reconstruction of the electrical properties of the adsorption bed.

[0021] S102 acquires the response current of the organic waste gas adsorption bed and the phase difference between the applied voltage and the response current. Since the adsorption bed has extremely high impedance after the waste gas is introduced, the response current is typically in the microamp or even nanoamp range. Therefore, a high-precision, low-drift sampling resistor is connected in series in the acquisition circuit to capture the weak current. Simultaneously, a two-phase high-frequency lock-in amplifier is introduced as demodulation hardware. This lock-in amplifier uses the frequency of the perturbation signal as a synchronization reference signal and extracts the weak response signal from background power frequency interference and thermal noise through quadrature phase-sensitive detection, thereby calculating the phase difference between the applied voltage and the response current with high resolution.

[0022] S103, the complex impedance is calculated based on the frequency, response current, and phase difference of the multi-frequency AC perturbation signal to obtain the dynamic complex impedance dielectric spectrum, and the dielectric relaxation time constant is extracted based on the dynamic complex impedance dielectric spectrum. In this process, different volatile organic compounds (VOCs) naturally possess different electric dipole moments (i.e., molecular polarity) due to differences in their molecular spatial configuration and functional groups. When these VOC molecules are trapped in the adsorption bed, the internal dipoles continuously undergo orientation flipping under the action of an applied alternating electric field. The relaxation time required for molecules of different polarities (e.g., nonpolar toluene and strongly polar acetone) to overcome the surrounding lattice constraints and complete the flipping is significantly different. This microscopic dynamic difference manifests as a unique electrical "fingerprint" in the macroscopic dielectric spectrum. By extracting this fingerprint, the compositional characteristics inside the adsorption bed can be accurately inverted. Figure 2 As shown, Figure 2 This is a comparative spectrum of experimental simulations showing the change of dielectric loss tangent of toluene and acetone in an adsorption bed as a function of the frequency of an AC perturbation signal. Figure 2It can be clearly seen that the dielectric relaxation characteristic peak of the nonpolar molecule toluene appears in the lower frequency range (corresponding to a peak frequency of approximately...). ), while acetone, a highly polar molecule, exhibits a significant blue shift of its characteristic loss peak to a higher frequency range due to its large dipole moment (corresponding to a peak frequency of approximately ). The characteristic loss peaks of the two components achieved complete physical separation at extremely high resolution in the frequency domain. This simulation result directly verifies from the perspective of actual data measurement that the specific characteristic loss peak frequency can be extracted based on broadband dynamic dielectric spectrum. It can effectively solve the serious problems of "cross-sensitivity" and signal aliasing in traditional mixed exhaust gas sensing, and realize online component decoupling identification without gas chromatography.

[0023] The formula for calculating the complex impedance is as follows: (1) in, This represents the complex impedance of the organic waste gas adsorption bed at a specific frequency. This represents the voltage amplitude of the applied AC perturbation signal. This indicates the magnitude of the acquired response current. This represents the phase difference between the calculated applied voltage and the response current. It is the imaginary unit.

[0024] The formula for extracting the dielectric relaxation time constant is as follows: (2) in, This represents the extracted dielectric relaxation time constant. This represents the characteristic frequency of the perturbation signal in the generated dynamic complex impedance dielectric spectrum when the absolute value of the imaginary part of the complex impedance caused by dipole polarization reaches a local extremum (i.e., the characteristic loss peak).

[0025] In summary, this embodiment replaces traditional passive measurement methods based on thermodynamics or optical principles with active electrical perturbation sensing by applying multi-frequency AC perturbations to the adsorption bed and calculating its dielectric spectrum characteristics. This mechanism completely solves the physical thermal inertia hysteresis problem of traditional concentration or temperature sensors, as well as the technical pain point of probes being prone to scaling and failure under harsh high-viscosity waste gas conditions. Ultimately, it achieves zero-delay vision and monitoring of the microscopic physicochemical state inside the adsorption bed.

[0026] S2. Based on the dynamic complex impedance dielectric spectrum, the local saturation and three-dimensional spatial distribution characteristics of the adsorbent in the organic waste gas adsorption bed are determined.

[0027] In this embodiment, determining the local saturation and three-dimensional spatial distribution characteristics of the adsorbent's adsorption state within the organic waste gas adsorption bed based on the dynamic complex impedance dielectric spectrum includes: S201, extracting the rate of change of capacitance and equivalent polarization resistance characteristics from the dynamic complex impedance dielectric spectrum; specifically, based on the measured complex impedance The data is plotted on the complex plane as a Nyquist plot with the real part as the abscissa and the imaginary part as the ordinate. Using a nonlinear equivalent circuit model (such as the Randles equivalent circuit) incorporating solution resistance, charge transfer resistance, and double-layer capacitance, the high-frequency semicircular arcs and low-frequency diffusion tails in the Nyquist plot are fitted and separated. Through circuit parameter analysis, pure interface features unaffected by airflow fluctuations are extracted, thereby obtaining the capacitive reactance of the current sampling period and the equivalent polarization resistance caused by dipole polarization.

[0028] The physical logic for calculating the rate of change of capacitance and the equivalent polarization resistance is characterized by the following formula: (3) (4) in, This represents the extracted equivalent polarization resistance feature. The angular frequency of the multi-frequency AC perturbation signal ( , (where the frequency is the sweep frequency of the multi-frequency AC micro-perturbation signal). This represents the real part of the complex impedance; This represents the rate of change of the extracted capacitance. The capacitance reactance measured at the current moment. This is the reference capacitance of the adsorption bed under completely clean conditions.

[0029] S202, the capacitance resistance change rate and equivalent polarization resistance characteristics are input into a pre-trained state assessment model to map the saturation of each zone within the organic waste gas adsorption bed. The state assessment model adopts a multi-layer feedforward neural network (BPNN) structure, including an input layer, two hidden layers, and an output layer. The feature vectors extracted from each node of the three-dimensional matrix electrode are then used to... The features are input as parameters to the network, which internally performs deep decoding using a nonlinear activation function (such as ReLU), implicitly establishing a nonlinear mapping relationship between the degree of electrical distortion and the physical adsorption amount of organic matter. The final output layer has a range of values. The scalar data corresponds to the local saturation of the adsorbent within the spatial grid.

[0030] S203, the saturation of each partition is spatially topologically mapped to generate the three-dimensional spatial distribution features. This is based on the physical coordinates corresponding to the three-dimensional multi-point matrix distribution of the measurement electrode network in step S1. The discrete local saturation data calculated for each partition are anchored in a virtual three-dimensional coordinate system. Then, a three-dimensional kriging spatial interpolation algorithm is used to smoothly estimate the unknown regions between discrete grid points, thereby transforming the one-dimensional feature data into a continuous three-dimensional saturation cloud map with color gradient mapping, intuitively displaying the distribution of VOCs enrichment hotspots within the adsorption bed. Specific spatial mapping parameters and states are shown in Table 1 and... Figure 3 As shown in Table 1, the dielectric feature extraction values ​​and local saturation mapping comparison data of three typical coordinate nodes in a three-dimensional matrix network during a continuous interception period in a certain industry are recorded: Table 1

[0031] like Figure 3 As shown, Figure 3 This is a 3D spatial simulation cloud map of the local saturation of the adsorption bed, generated through 3D topological mapping based on the massive sensing data of the aforementioned matrix nodes. The red highlighted areas in the map represent polarization-rich regions where the local absolute saturation exceeds 85% (as shown in the coordinates in Table 1). and The blue area represents a relatively clean zone with a saturation level below 20%. This 3D visualization simulation clearly reveals that the penetration profile of industrial waste gas within the porous media bed is not an ideal horizontal progression, but rather exhibits a highly distorted "finding effect" due to the influence of the local flow field. This data confirms the absolute necessity of implementing 3D targeted state assessment rather than global single-point assessment in this invention.

[0032] Furthermore, considering the fluctuating characteristics of industrial waste gas components, before inputting the capacitance resistance change rate and equivalent polarization resistance characteristics into the pre-trained state assessment model, the following steps are also included: S204, determine whether an unknown dielectric relaxation time constant appears in the dynamic complex impedance dielectric spectrum; extract the dielectric relaxation time constant obtained in the current step. The data is then compared with the existing database of known VOC component relaxation time features using Mahalanobis distance clustering. If the calculated Mahalanobis distance exceeds the preset confidence interval threshold (e.g., the boundary corresponding to 95% confidence), it indicates that the currently captured polarization feature peak cannot match historical data, and is therefore determined to be an unknown feature.

[0033] S205: If an unknown dielectric relaxation time constant appears, it is determined that an unknown component exists in the current organic waste gas, and the unknown dielectric relaxation time constant is used as a new feature node to update the weights of the state assessment model online. To prevent singular signals outside the historical training library from causing model mapping distortion or even collapse, an incremental learning mechanism is introduced. This unknown dielectric relaxation time constant is then used as a new feature node to update the weights of the state assessment model online. As new feature anchors, they are extended to the input layer dimension of the neural network, using a small adaptive learning rate (e.g., Online backpropagation training is performed on samples containing data of unknown components. This approach enables rapid compatibility with the electrical characteristics of new components while preserving the original known component mapping weights, thus endowing the evaluation mechanism with online self-evolution capabilities to cope with complex and variable operating conditions.

[0034] As a preferred embodiment, to address the problem of activated carbon lifespan degradation, the method further includes: S206, after a single desorption cycle, the current reference complex impedance dielectric spectrum of the organic waste gas adsorption bed under clean conditions is collected; when the desorption heating in the target area stops and the bed temperature naturally cools down to... After continuously supplying clean purge air for 5 minutes, the "clean state" calibration is triggered. At this time, a multi-frequency AC micro-perturbation electrical signal is reinjected into the bed, and the background electrical response under this physical state is collected and recorded, i.e., the current reference complex impedance dielectric spectrum.

[0035] S207. Compare the current reference complex impedance dielectric spectrum with the preset initial reference complex impedance dielectric spectrum to calculate the drift of the reference equivalent polarization internal resistance; re-extract the equivalent polarization internal resistance based on the newly acquired background dielectric spectrum, and calculate its change relative to the initial use.

[0036] The formula for calculating the drift amount is as follows: (5) in, This represents the drift of the reference equivalent polarization internal resistance. This represents the polarization resistance extracted from the dielectric spectrum of the current reference complex impedance. This indicates the polarization resistance corresponding to the preset initial reference complex impedance dielectric spectrum extracted when the equipment is first loaded with fresh activated carbon.

[0037] S208, if the drift amount exceeds a preset attenuation warning value, a deep thermal desorption protocol is added when generating the next target desorption command. The deep thermal desorption protocol is used to increase the upper limit of the desorption temperature in the region corresponding to the spatial focusing coordinates. Physically, this involves the irreversible positive drift of the reference equivalent polarization internal resistance (e.g., ...). The preset attenuation warning value represents the stubborn accumulation of high-boiling-point residues (Heel) inside the adsorbent micropores, which cannot be vaporized at conventional desorption temperatures. At this point, a deep thermal desorption protocol is triggered, raising the upper limit of the desorption temperature in the focusing region during the microwave desorption stage from the conventional value. Instantly boosted to Within [a certain range]. Through instantaneous high-temperature microwave radiation, stubborn macromolecular residues are weakly oxidized and pyrolyzed, thereby forcibly opening up blocked physical pores and restoring the long-term operational vitality of the adsorption bed.

[0038] This step, through a combination of multidimensional electrical feature mapping and online adaptive updating, not only accurately reconstructs the microscopic three-dimensional map inside the bed, but also overcomes the industry-wide problems of perception drift caused by fluctuations in unknown components and the blind accumulation of irreversible high-boiling-point residues.

[0039] S3, if the local saturation reaches the preset desorption threshold, then a target desorption command containing spatial focusing coordinates and target desorption energy is generated based on the three-dimensional spatial distribution characteristics.

[0040] In this embodiment, generating a target desorption command containing spatial focusing coordinates and target desorption energy based on the three-dimensional spatial distribution characteristics includes: S301, identify clusters in the three-dimensional spatial distribution features where the saturation is greater than a preset desorption threshold; for the three-dimensional spatial distribution features generated in step S2 (which are represented by a three-dimensional spatial saturation matrix at the data level), a 26-neighborhood connected component labeling algorithm based on three-dimensional voxels is used for spatial matrix analysis. The saturation of each grid partition is compared point-by-point with the preset desorption threshold (e.g., set to 85%), and all high-saturation voxel points are filtered out through binarization. Then, spatially adjacent high-saturation voxel points are clustered and merged to accurately define the three-dimensional connected space to be desorbed with continuous physical boundaries, i.e., the clusters.

[0041] S302, calculate the three-dimensional geometric center of the cluster area and use it as the spatial focusing coordinate; in order to achieve accurate targeting and positioning of the subsequent phased array microwave radio frequency beam, a centroid calculation algorithm based on local saturation weighting is used to extract the three-dimensional spatial coordinates of the identified cluster area.

[0042] The formula for calculating the spatial focusing coordinates is as follows: (6) in, This represents the calculated spatial focus coordinates. Indicates the number of clusters within the cluster. Local saturation of the individual pixel mesh, This represents the three-dimensional physical coordinates of the voxel grid within the organic waste gas adsorption bed. By introducing a saturation weight, it is ensured that the geometric center is more biased towards the high-concentration adsorption core points.

[0043] S303, based on the saturation, volume, and preset dielectric constant of the aggregation region, the microwave radiation duration and transmission power required for desorption are calculated as the target desorption energy. Traditional whole-bed hot air purging is prone to generating a "channeling effect" that causes airflow short-circuiting within the pores, resulting in a large amount of heat energy being lost in low-concentration areas. This embodiment eliminates the global heating blind zone and strictly limits energy projection only to the high-concentration core aggregation region located at the aforementioned spatial focusing coordinates. Specifically, based on the three-dimensional spatial integral domain of the aggregation region and its internal local saturation, the absorbed heat energy required for VOCs in this local region to overcome physical van der Waals forces and achieve a vaporization phase change is first calculated. Subsequently, combined with the microwave frequency, spatial electric field strength, and preset dielectric constant (i.e., dielectric loss factor), the actual attenuation absorption power of the microwave in the aggregation region is calculated, and then the transient transmission power (e.g., 5kW) and precise radiation duration (e.g., 120s) that the microwave RF antenna should be set to are calculated. These two factors constitute the target desorption energy.

[0044] The formula for calculating the absorbed heat energy is as follows: (7) in, This represents the heat energy absorbed during desorption. The three-dimensional spatial integral domain (i.e., the volume of the cluster) represents the identified cluster region. Indicates the location in spatial coordinates Local saturation at that location This indicates the maximum absolute adsorption capacity of the adsorbent per unit volume. This represents the Mohr van der Waals binding energy between the target organic molecule and the surface of the adsorbent material. This represents the molar latent heat of vaporization of the target organic molecule.

[0045] The calculation formulas for microwave radiation duration and transmission power are as follows: (8) (9) in, This represents the inversely calculated transient transmit power. This indicates the operating frequency of the microwave radio frequency beam (e.g., 2.45 GHz). The vacuum permittivity, The dielectric constant is a preset value (specifically, the equivalent dielectric loss factor of the adsorption bed at this frequency). This represents the target spatial electric field intensity within the focusing area. For the volume of the cluster, This indicates the energy transfer efficiency from the microwave antenna to the adsorption bed; This indicates the duration of microwave radiation required for desorption.

[0046] Furthermore, in order to achieve system-level closed-loop thermal energy balance, the calculation of the microwave radiation duration and emission power required for desorption based on the saturation, volume, and preset dielectric constant of the aggregation region also includes: S304, Obtain the lower limit of the target calorific value required for the catalytic combustion chamber connected to the organic waste gas adsorption bed to maintain a self-sustaining combustion state; the catalytic combustion chamber needs to be maintained at the catalyst's ignition temperature (e.g., the temperature corresponding to a precious metal composite catalyst). Only when the above conditions are met can efficient oxidation of VOCs be achieved. This target lower limit of calorific value is dynamically calculated in real time using a built-in thermodynamic balance equation. The calculation comprehensively considers the current real-time ignition temperature requirement of the catalyst, the real-time ambient heat loss rate of the reactor shell, and the specific heat capacity of the mixed-in room-temperature fresh desorbed air, and calculates the minimum injected heat threshold required for the reactor to maintain internal heat self-sufficiency without turning on the external auxiliary electric heater.

[0047] S305 converts the expected concentration of desorbed organic waste gas into expected latent chemical heat and determines whether the expected latent chemical heat is greater than or equal to the target calorific value lower limit. It performs three-dimensional volumetric space integration on the identified accumulation zone, and, combined with the absolute saturation within the grid, calculates the total molar amount of VOCs expected to be completely purged from the adsorption bed under the current target desorption command. Subsequently, based on the standard molar enthalpy of combustion of the main components of the current waste gas, it converts the expected total molar amount of desorbed VOCs into the total heat release that can be achieved through complete oxidation and decomposition in the catalytic combustion chamber, i.e., the expected latent chemical heat, and then logically compares it with the aforementioned target calorific value lower limit.

[0048] S306, if the expected latent heat of chemical reaction is less than the target calorific value lower limit, the triggering time of the target desorption command for the current accumulation zone is delayed until the accumulated expected latent heat of chemical reaction meets the target calorific value lower limit. The core purpose of this control logic is to treat the high concentration of organic waste gas itself as "fuel" to maintain the operation of the environmental protection system. If the latent heat released by the current local accumulation zone is insufficient to compensate for the physical heat dissipation of the catalytic combustion chamber, immediate desorption will force the control loop to activate the high-energy-consuming electric heating tube to supplement the heat energy. Therefore, the desorption action is strategically delayed, allowing the adsorption bed to continue operating to intercept the waste gas and continuously accumulate the "fuel" concentration until the expected latent heat of chemical reaction can completely cover and exceed the target calorific value lower limit. Figure 4 As shown, Figure 4 This is a simulation graph showing the time-series relationship between the dynamic target calorific value lower limit of the catalytic combustion chamber and the expected accumulated latent chemical heat in the aggregation zone within a certain continuous operating band in this embodiment. The solid fluctuating curve at the bottom of the graph represents the dynamically changing target calorific value lower limit power demand (unit: kW) affected by industrial ambient temperature loss and fluctuations in fresh air volume; while the dashed, stepped upward curve at the top represents the pre-calculated total expected latent chemical heat released by the complete oxidation of VOCs in the target aggregation zone as the adsorption bed continues to retain air. At the time-series nodes... Previously, the dotted line was below the solid line (latent heat supply < combustion chamber heat demand). If desorption were started blindly at this time, it would inevitably trigger forced reheating of the hundreds of kilowatts of electric heating tubes at the downstream end; however, when the sequence progressed to... At that moment, the dashed line and the solid line intersect and form a positive crossover (latent heat supply). (Combustion chamber heat demand). The control loop of this invention precisely captures the optimal timing for triggering the target desorption command at the intersection point. The timing control simulation curve intuitively demonstrates the feasibility of achieving smooth hot start-up and thermal self-sustaining operation of the RCO system with zero external electric heating energy consumption.

[0049] The formula for calculating the expected latent chemical heat is as follows: (10) in, This represents the calculated expected latent chemical heat. The standard molar enthalpy of combustion of the target organic waste gas component is represented.

[0050] This step, through the deep integration of targeted focusing coordinate solution and chemical latent heat self-sustaining matching strategy, completely breaks the local heat waste and "channeling effect" caused by traditional whole-bed blind desorption at the physical level, and eliminates the risk of thermal runaway of the back-end catalytic oxidation equipment and dependence on high external power consumption from the perspective of the global system.

[0051] S4 sends the target de-detachment command to the space phased array microwave de-detachment system to use the phased array microwave radio frequency beam to perform targeted de-detachment on the area corresponding to the space focusing coordinates.

[0052] In this embodiment, before sending the target desorption command to the space phased array microwave desorption system, the following steps are also included: S401 involves laterally injecting control micro-jets into the main airflow flowing within the exhaust gas inlet duct. Specifically, a high-frequency electromagnetic control valve with microsecond-level response is connected to an extremely high-pressure control gas source. At a micron-level slit pre-set on the sidewall of the main flow channel throat (i.e., the section with the highest flow velocity and lowest static pressure) of the exhaust gas inlet duct, upon receiving the desorption pre-signal, a high-energy pulsed micro-jets are injected into the flowing main fluid with an extremely high momentum ratio, thereby creating a lateral momentum disturbance to the main airflow.

[0053] S402 utilizes the Coanda effect to alter the adhesion state of the main airflow on the wall of the exhaust gas inlet pipe, deflecting the main airflow to a backup bypass to cut off the intake of the current organic waste gas adsorption bed. This process relies on pure fluid dynamics to construct a fluid valve without moving parts. When the lateral microjets intervene, based on the Coanda effect, the high-speed main airflow, which originally flows along the central axis of the main channel, will generate a low-pressure vortex region locally on one side of the throat due to the asymmetric entrainment effect of the microjets. This low-pressure boundary will force the main airflow to deflect along the streamlined pipe wall, smoothly switch and stably adhere to the inner wall of the backup bypass for venting or circulation. Since this fluid topology switching process involves no mechanical moving parts, it completely eliminates the hysteresis phenomenon caused by mechanical inertia in traditional pneumatic flap valves or butterfly valves, while avoiding the flow field shock waves and aerodynamic flutter noise generated when the valve plate rigidly cuts off the high-pressure airflow, achieving millisecond-level non-destructive cutoff of the current adsorption bed intake.

[0054] After the gas path switching, the targeted desorption of the region corresponding to the spatial focusing coordinates using a phased array microwave radio frequency beam includes: S403, based on the spatial focusing coordinates, calculate the excitation phase difference of multiple microwave transmitting antennas in the space phased array microwave de-adsorption system; extract the spatial focusing coordinates calculated in the previous step S3. And obtain the first [unclear] in the space phased array microwave desorption system. The fixed physical three-dimensional spatial coordinates of each microwave transmitting antenna element are determined. Using three-dimensional analytical geometry, the Euclidean distance difference from the geometric center of each antenna element to the target spatial focusing coordinates is calculated. Subsequently, combining this with the equivalent operating wavelength of the microwave in the current porous adsorption medium (such as activated carbon or molecular sieve), the initial excitation phase angle difference (i.e., excitation phase difference) required for each antenna to ensure that the wave peaks are aligned at the same spatiotemporal point is calculated in reverse.

[0055] S404: Adjust the transmission phase angle of each microwave transmitting antenna according to the excitation phase difference, so that the microwave beams emitted by each microwave transmitting antenna coherently superimpose at the spatial focusing coordinates. Control the underlying high-frequency solid-state phase shifter network to strictly change the initial transmission phase of the output radio frequency electromagnetic waves of each microwave transmitting antenna according to the calculated excitation phase difference. At the same time, call the target desorption energy parameters calculated in step S3 to accurately set the output power of the microwave source to the calculated transmission power. Because the radio frequency beams emitted by each antenna carry a precisely calibrated phase difference as they propagate through the porous medium, they will undergo constructive interference (constructive interference) when they reach the spatial focusing coordinates, thus obtaining a signal in three-dimensional physical space that is consistent with... A high-density thermal focus with energy matching. Radio frequency energy is locked within the targeted aggregation region and instantaneously converted into desorption heat, while other low-concentration blank regions within the adsorption bed are in a destructive interference field, avoiding energy waste caused by global heating. For example... Figure 5 As shown, Figure 5 This is a profile cloud map of the steady-state electric field intensity distribution of the 16-element microwave phased antenna in this embodiment, obtained using finite element electromagnetic field simulation software (FEM) in a porous activated carbon medium with an equivalent relative permittivity of 3.5. The cross-marked areas in the figure represent the system based on the rigorous phase calculation equations. The synthesized spatial focusing hotspot. Extracting the electromagnetic physical quantities from the profile mesh reveals that, under the condition of a total system transmit power of 5kW, the peak transient spatial electric field intensity in the central region of this infrared hotspot reaches... This causes the organic molecules in the region to undergo intense polarization and high-frequency frictional heating; while in the surrounding destructive interference region (dark blue background region) 15cm away from the focal point, the electric field intensity rapidly decays to less than The energy attenuation ratio exceeds 40 times. This simulation data strongly confirms that the spatial microwave interferometry additive technology used in this case can achieve precise targeted thermal desorption isolation within the complex industrial adsorption bed, a spatial energy resolution that is physically unattainable by traditional macroscopic hot air purging methods.

[0056] The formula for calculating the excitation phase difference is as follows: (11) (12) in, Indicates the first The three-dimensional physical Euclidean distance from a microwave transmitting antenna to the spatial focusing coordinates. Indicates the first The fixed three-dimensional physical coordinates of a microwave transmitting antenna Focus coordinates in the target space; Represents the calculated first... The required excitation phase difference for each microwave transmitting antenna This represents the equivalent propagation wavelength of microwaves in a porous medium currently filled with adsorbent and organic waste gas. This represents the reference distance from the selected reference antenna to the spatial focusing coordinates.

[0057] As a preferred implementation, in order to form a strict dual closed-loop control of "feedforward constraint + feedback truncation", the process of targeted desorption of the region corresponding to the spatial focusing coordinates using a phased array microwave radio frequency beam also includes: S405 monitors the real-time equivalent polarization resistance of the region where the space focusing coordinates are located. During the continuous microwave targeted radiation, a high-frequency AC perturbation signal is synchronously injected into the physical region where the space focusing coordinates are located through a probe network. The dynamic changes of dipole polarization intensity in this local area are extracted and tracked to obtain the real-time equivalent polarization resistance. .

[0058] S406, if the real-time equivalent polarization resistance falls back to the preset reference resistance range, the current targeted desorption process for the spatial focusing coordinates ends. As VOCs molecules within the target coordinates continuously absorb microwave energy and vaporize, the number of polar dipoles in this local region decreases sharply, and the macroscopic electrical response is characterized by a sharp rise in polarization resistance followed by a rapid fall. When the real-time equivalent polarization resistance steadily decreases and falls back to the preset reference resistance range where the adsorbent has just completed thermal regeneration, it means that the organic matter at the target location has been completely cleared. At this point, the system immediately terminates the current microwave emission. Furthermore, the microwave radiation duration calculated in step S3 is... This serves as the maximum timeout safety threshold for the targeted desorption process. Even if the equivalent polarization internal resistance fails to decrease due to a very low probability of sensor misalignment, as long as the duration of microwave emission reaches the specified time... The system will also be forced to shut down. Through the dual insurance mechanism of in-situ physical internal resistance closed loop and feedforward theoretical duration, the fatal risk of thermal carbonization and cracking of the activated carbon skeleton due to excessive application of radio frequency energy is completely prevented.

[0059] This step achieves zero-wear, rapid reversal of the intake pipeline and atomic-level fixed-point thermal desorption closed loop within the adsorption bed through a combination of pure fluid topology switching and spatial phased array microwave interferometry. Combined with feedforward energy calculation and feedback impedance monitoring, it overturns the traditional desorption system's inefficient, sluggish, and easily thermal runaway physical execution framework.

[0060] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0061] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, in the form of a computer program product.

[0062] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0063] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0064] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0065] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for controlling the desorption of organic waste gas based on dynamic assessment of adsorption state, characterized in that, include: Multi-frequency AC micro-perturbation electrical signals were injected into the organic waste gas adsorption bed, and the dynamic complex impedance dielectric spectrum of the organic waste gas adsorption bed was collected. Extract the capacitance change rate and equivalent polarization resistance features from the dynamic complex impedance dielectric spectrum; input the capacitance change rate and equivalent polarization resistance features into a pre-trained state assessment model to map the saturation of each zone in the organic waste gas adsorption bed; perform spatial topological mapping on the saturation of each zone to generate three-dimensional spatial distribution features. If the local saturation reaches the preset desorption threshold, a target desorption command containing spatial focusing coordinates and target desorption energy is generated based on the three-dimensional spatial distribution characteristics. The target desorption command is sent to the space phased array microwave desorption system to use the phased array microwave radio frequency beam to perform targeted desorption on the area corresponding to the space focusing coordinates.

2. The method according to claim 1, characterized in that, The process of injecting multi-frequency AC micro-perturbation electrical signals into the organic waste gas adsorption bed and collecting the dynamic complex impedance dielectric spectrum of the organic waste gas adsorption bed includes: Multi-frequency AC micro-perturbation electrical signals with a target frequency sweep range are applied to both ends of the organic waste gas adsorption bed; The response current of the organic waste gas adsorption bed and the phase difference between the applied voltage and the response current are obtained. The complex impedance is calculated based on the frequency, response current, and phase difference of the multi-frequency AC micro-perturbation signal to obtain the dynamic complex impedance dielectric spectrum, and the dielectric relaxation time constant is extracted based on the dynamic complex impedance dielectric spectrum.

3. The method according to claim 1, characterized in that, Before inputting the capacitance resistance change rate and equivalent polarization resistance characteristics into the pre-trained state evaluation model, the following steps are also included: Determine whether an unknown dielectric relaxation time constant appears in the dynamic complex impedance dielectric spectrum; If an unknown dielectric relaxation time constant is found, it is determined that there is an unknown component in the current organic waste gas, and the unknown dielectric relaxation time constant is used as a new feature node to update the weight of the state assessment model online.

4. The method according to claim 1, characterized in that, Also includes: After a single desorption cycle, the current reference complex impedance dielectric spectrum of the organic waste gas adsorption bed under clean conditions is collected. Compare the current reference complex impedance dielectric spectrum with the preset initial reference complex impedance dielectric spectrum to calculate the drift of the reference equivalent polarization internal resistance. If the drift amount is greater than the preset attenuation warning value, a deep thermal desorption protocol will be added when the target desorption command is generated next time. The deep thermal desorption protocol is used to increase the upper limit of the desorption temperature in the region corresponding to the spatial focusing coordinates.

5. The method according to claim 1, characterized in that, The step of generating a target desorption command containing spatial focusing coordinates and target desorption energy based on the three-dimensional spatial distribution characteristics includes: Identify clusters in the three-dimensional spatial distribution features where the saturation is greater than a preset desorption threshold; Calculate the three-dimensional geometric center of the cluster area and use it as the spatial focal coordinate. Based on the saturation, volume, and preset dielectric constant of the aggregation region, the microwave radiation duration and emission power are calculated as the target desorption energy.

6. The method according to claim 5, characterized in that, The step of calculating the microwave radiation duration and transmission power based on the saturation, volume, and preset dielectric constant of the aggregation region further includes: To obtain the lower limit of the target calorific value required for the catalytic combustion chamber connected to the organic waste gas adsorption bed to maintain a self-sustaining combustion state; The concentration of the organic waste gas to be desorbed is converted into the expected latent heat of chemical energy, and it is determined whether the expected latent heat of chemical energy is greater than or equal to the lower limit of the target calorific value. If the expected latent chemical heat is less than the target calorific value lower limit, the triggering time of the target desorption command for the current accumulation area is postponed until the accumulated expected latent chemical heat meets the target calorific value lower limit.

7. The method according to claim 5, characterized in that, The method of using a phased array microwave radio frequency beam to target and de-attach the region corresponding to the spatial focusing coordinates includes: Based on spatial focusing coordinates, the excitation phase difference of multiple microwave transmitting antennas in a spatial phased array microwave desorption system is calculated. The transmission phase angle of each microwave transmitting antenna is adjusted according to the excitation phase difference, so that the microwave beams emitted by each microwave transmitting antenna coherently superimpose at the spatial focusing coordinates.

8. The method according to claim 1, characterized in that, The process of using a phased array microwave radio frequency beam to target and desorb the region corresponding to the spatial focusing coordinates also includes: Real-time monitoring of the real-time equivalent polarization internal resistance of the partition where the spatial focusing coordinates are located; If the real-time equivalent polarization internal resistance falls back to the preset reference resistance range, the current targeted desorption process for the spatial focusing coordinates will end.

9. The method according to claim 1, characterized in that, Before sending the target de-detachment command to the space phased array microwave de-detachment system, the following steps are also included: Laterally inject control micro-jet into the main airflow flowing into the exhaust gas inlet pipe; By utilizing the Coanda effect to change the adhesion state of the main airflow on the wall of the exhaust gas inlet pipe, the main airflow is deflected to the backup bypass, thereby cutting off the intake of the current organic waste gas adsorption bed.

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