A waste incinerator tail flue system suitable for high-chlorine corrosion-resistant environments

Abstract

The application relates to the field of flue gas corrosion protection, and discloses a waste incinerator tail flue system suitable for high-chlorine corrosion-resistant environment, which comprises the following steps: continuously collecting the chlorine component concentration, temperature field gradient, humidity change rate and flow velocity fluctuation information of the flue gas at the tail flue inlet, and generating chlorine disturbance basic characterization data; based on the chlorine disturbance basic characterization data, analyzing the coupling relationship between the local temperature drop response of the flue wall surface and the chlorine enrichment fluctuation, and generating wall surface phase change trigger state characterization; according to the phase change trigger state characterization, analyzing the feedback relationship between the chlorine deposition and the change of the wall surface wettability, and establishing the coupling relationship; based on the coupling relationship, analyzing the flow field driving space evolution of the phase change area, and generating a corrosion migration evolution path; based on the corrosion migration evolution path, analyzing the coupling relationship of the chlorine enrichment, condensation and corrosion area, and forming a corrosion feedback regulation mechanism. The application has the advantages of improving the condensation migration identification precision and corrosion inhibition capacity.

Description

Technical Field

[0001] This invention relates to the field of flue gas corrosion protection, specifically to a tail flue system for waste incinerators suitable for high-chlorine corrosion environments. Background Technology

[0002] During waste incineration, the tail flue operates under alternating high-chlorine and low-temperature conditions. The flue gas contains corrosive components such as HCl, Cl2, and metal chlorides, which easily form highly corrosive deposits on the inner wall of the flue and the surface of heat exchange components, thus causing serious low-temperature chlorine corrosion problems. However, current technologies generally reduce the corrosion rate by selecting corrosion-resistant alloy materials, spraying anti-corrosion coatings, or optimizing flue gas temperature control strategies. Under conditions of large fluctuations in waste composition and frequent short-term high-chlorine load shocks, the concentration of chlorine components in the flue gas will rapidly increase within a local time window and form a transient condensation enrichment zone in the low-temperature region of the tail flue.

[0003] Under such transient conditions, existing flue gas systems generally have the following shortcomings: When the flue gas temperature drops below the acid dew point for a short period of time, chlorides are prone to rapid condensation on the local wall of the flue and form a highly adhesive corrosion layer. This causes the condensation area to exhibit dynamic migration characteristics within the flue. At the same time, conventional soot blowing or cleaning devices are mostly fixed and cannot cover such dynamically enriched areas in a timely manner, resulting in intensified local corrosion. During the aforementioned local condensation-re-evaporation cycle, corrosion products accumulate and peel off periodically, easily forming microscale accumulation layers at flue corners or locations where the cross-section changes. This leads to a local corrosion rate that is significantly higher than the overall average level, affecting the service life and operational safety of the flue gas system.

[0004] Therefore, existing technologies are insufficient to effectively suppress the drift of transient condensation enrichment sites in the tail flue under high chlorine fluctuation conditions and the resulting microscale deposition-induced corrosion problems. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a waste incinerator tail flue system suitable for high-chlorine corrosion environments, which has the advantages of improving the accuracy of condensation migration identification and corrosion inhibition capabilities, thus solving the problems mentioned in the background technology.

[0006] To achieve the aforementioned objectives of improving the accuracy of condensation migration identification and corrosion inhibition, this invention provides the following technical solution: a waste incinerator tail flue system suitable for high-chlorine corrosion-resistant environments, comprising: Chlorine disturbance sensing module: continuously collects information on chlorine component concentration, temperature field gradient, humidity change rate and flow velocity pulsation in the flue gas at the tail flue inlet, and generates basic characterization data of chlorine disturbance by combining the heat transfer structure of the flue wall and the boundary layer flow characteristics. Phase change identification module: Based on the basic characterization data of chlorine disturbance, the coupling relationship between the local temperature drop response of the flue wall and the chlorine enrichment fluctuation is analyzed. Combined with the dynamic shift characteristics of the critical condition of acidic condensation on the wall, the phase change triggering interval and spatial distribution of the wall are identified, and the characterization of the phase change triggering state of the wall is generated. Interface coupling module: Based on the characterization of phase change triggering state, the feedback relationship between chlorine deposition and wall wettability changes is analyzed, the positive feedback characteristics of condensation enhancement on chlorine enrichment are extracted, and the coupling relationship between interface state and flow field disturbance response is established by combining the feedback influence of wall phase change and deposition evolution on local boundary layer flow structure. Migration Analysis Module: Based on the coupling relationship analysis, the flow field drives the spatial evolution of the phase change region. Combining the deflection behavior of the local backflow structure and the disturbance propagation path, it extracts the spatial migration characteristics of the corrosion and condensation enrichment regions under the action of fluid disturbance and generates the corrosion migration evolution path. Control and execution module: Based on the corrosion migration and evolution path, the coupling relationship between chlorine enrichment, condensation and corrosion region is analyzed, a corrosion self-organized evolution model is constructed, and the flue temperature field and flow parameters are controlled to form a corrosion feedback control mechanism.

[0007] Preferably, the process for generating basic characterization data of chlorine perturbation is as follows: The concentration of chlorine components in the flue gas is collected by the sensing unit, and the temperature distribution and variation characteristics of the flue section are acquired simultaneously to form initial multiphysics field data. Time-aligned processing was performed on the humidity change rate and flow velocity pulsation signals in the initial multiphysics data to obtain unified time-stamped data; Local heat flux characteristics are calculated based on unified time-scaled data and the heat exchange structure of the flue wall. Segmented analysis of flow velocity fluctuations is performed to extract boundary layer flow structure parameters; By integrating chlorine concentration, temperature distribution, humidity, flow velocity, and flow structure parameters, basic characterization data of chlorine disturbances are generated.

[0008] Preferably, the process of analyzing the coupling relationship between the local temperature drop response of the flue wall and the chlorine enrichment fluctuation is as follows: Based on the chlorine perturbation-based characterization dataset, local windowing is performed on the temperature distribution characteristics to extract the sensitive sections of the wall temperature drop response. Within the temperature drop response sensitive range, the fluctuation amplitude and rate of change of chlorine component concentration are extracted simultaneously to form the dynamic characteristics of chlorine enrichment. Using the temperature drop response characteristics as a reference, a time-delay matching analysis was performed on the dynamic characteristics of chlorine enrichment to calculate the dynamic correlation parameters between the two. By combining historical data under different operating conditions, the dynamic correlation parameters are analyzed by region, and the coupled characteristic parameters reflecting the synergistic change relationship between temperature drop response and chlorine enrichment are output.

[0009] Preferably, the process of generating the wall phase transition trigger state characterization is as follows: Based on the coupling characteristic parameters, the real-time difference between the flue gas temperature and the acid dew point temperature in each region is calculated to form the temperature difference determination result. Based on the temperature difference determination results, the humidity change rate is introduced to dynamically correct the acidic condensation critical condition, and the condensation threshold curve varies with the operating conditions is obtained. By comparing the temperature difference determination sequence with the condensation threshold curve, the time interval that meets the phase change triggering condition is identified; By mapping the time interval to the spatial location of the flue and combining the phase change duration with the triggering frequency, a characterization of the wall phase change triggering state is generated.

[0010] Preferably, the process of extracting the positive feedback characteristics of condensation enhancement for chlorine enrichment is as follows: Based on the characterization of the triggering state of the wall phase transition, the formation and development process of the liquid film in the phase transition region is extracted to obtain the characteristics of the wall wettability change. Based on the wettability change characteristics, the dissolution, migration and redeposition behavior of chlorine components in the liquid film were analyzed to obtain the chlorine deposition rate change characteristics; Correlation analysis was performed on the wettability variation characteristics and the chlorine deposition rate variation characteristics to determine the feedback enhancement relationship between the two. By combining the changes in phase transition intensity, the amplification effect of chlorine enrichment is evaluated, characteristic parameters of chlorine enrichment under condensation enhancement are extracted, and characteristic results are output to characterize the coupling feedback mechanism of condensation, wetting and deposition.

[0011] Preferably, the process of establishing the coupling relationship between the interface state and the flow field disturbance response is as follows: Based on the feature results, the changes in wall roughness and thermal boundary conditions are parametrically characterized. Based on parametric characterization, the influence of wall state changes on near-wall fluid velocity distribution and turbulence intensity is analyzed to obtain the boundary layer structure evolution characteristics. Based on the boundary layer structure evolution characteristics, the disturbance propagation path in the flow field is identified, and local unstable regions are determined. Establish a mapping model between interface state parameters and flow field disturbance intensity, and output the coupling relationship reflecting the influence of interface changes on the flow structure.

[0012] Preferably, the process of flow field-driven spatial evolution in the phase transition region based on coupling relationship analysis is as follows: Based on the coupling relationship, the hydrodynamic distribution within the phase transition region is reconstructed to obtain the local flow field distribution characteristics; Based on the characteristics of the flow field distribution, regions with significant changes in velocity gradient are extracted; The influence range of the flow field driving effect on chlorine enrichment and condensation region at different time scales was analyzed, and the corresponding driving response characteristics were obtained. Based on the driving response characteristics, the spatial evolution relationship of the phase transition region is determined, and the spatial evolution trend results reflecting the driving characteristics of the flow field are output.

[0013] Preferably, the process of generating corrosion migration evolution paths is as follows: Based on the spatial evolution trend results, identify local backflow structures in the flow field; Based on the recirculation structure, the deflection law of the disturbance propagation path is analyzed to determine the area where the disturbance energy is concentrated; Track the positional changes of chlorine enrichment and condensation regions under disturbance to form spatial migration trajectories; Path clustering and trend fitting are performed on the spatial migration trajectory to output the corrosion migration evolution path.

[0014] Preferably, the process of constructing a corrosion self-organization evolution model is as follows: Based on the corrosion migration evolution path, the evolution path is spatially superimposed with the chlorine concentration distribution and condensation intensity distribution to obtain multi-field coupled distribution results; Based on the results of multi-field coupling distribution, high-risk areas with multiple superposition of factors are identified; The corrosion development process is divided into stages based on the time dimension, and a feedback mechanism is introduced to describe the mutually reinforcing relationship between chlorine enrichment, condensation and corrosion, thus constructing a self-organized evolution model that reflects the corrosion development trend.

[0015] Preferably, the process of forming a corrosion feedback control mechanism is as follows: Based on the corrosion self-organization evolution model, the corrosion development trend in different regions is predicted, and the risk distribution results are obtained; Based on the risk distribution results, the flue temperature field is zoned and adjusted. Based on temperature control, the flow rate and flow structure parameters are optimized and adjusted. By combining real-time monitoring data, the control strategy is dynamically modified, and a corrosion feedback control mechanism is output to control the operation status of the flue.

[0016] Compared with the prior art, the present invention provides a waste incinerator tail flue system suitable for high chlorine corrosion environments, which has the following beneficial effects: This invention constructs a multi-parameter collaborative characterization system based on chlorine component concentration, temperature field gradient, humidity change rate, and flow velocity fluctuation information to achieve a detailed characterization of chlorine disturbance in the tail flue. Furthermore, it introduces dynamic migration analysis of the critical conditions for acidic condensation on the wall surface, enabling accurate identification of the phase change triggering interval and its spatial distribution. By establishing the coupling relationship between the chlorine deposition process and changes in wall wettability, and combining the influence of phase change and deposition evolution on the boundary layer flow structure, it achieves a collaborative characterization of interface state and flow field disturbance. Simultaneously, based on the spatial evolution analysis of the phase change region driven by the flow field, it can extract the dynamic migration paths of corrosion and condensation enrichment regions, and systematically model the coupling relationship between chlorine enrichment regions, condensation regions, and corrosion occurrence regions. Based on this, the flue temperature field and flow parameters are adjusted to transform the corrosion evolution process within the flue from disordered development to controllable evolution, thereby reducing the degree of local corrosion concentration, suppressing the dynamic diffusion trend of condensation enrichment regions, improving the uniformity of corrosion distribution, and enhancing the operational stability and reliability of the flue system under high chlorine fluctuation conditions. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the structure 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 skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Example 1: Please refer to Figure 1 As shown in the embodiment of the present invention, a waste incinerator tail flue system suitable for high-chlorine corrosion-resistant environments includes: Chlorine disturbance sensing module: continuously collects information on chlorine component concentration, temperature field gradient, humidity change rate and flow velocity pulsation in the flue gas at the tail flue inlet, and generates basic characterization data of chlorine disturbance by combining the heat exchange structure of the flue wall and the boundary layer flow characteristics.

[0020] The process of generating basic characterization data of chlorine disturbance in the chlorine disturbance sensing module is as follows: The concentration of chlorine components in the flue gas is collected by the sensing unit, and the temperature distribution and variation characteristics of the flue section are acquired simultaneously to form initial multiphysics field data. Multiple sets of gas composition sensors and temperature measurement units are evenly arranged along the circumference of the cross section at the tail flue inlet and key heat exchange area. The chlorine component concentration is continuously sampled by a corrosion-resistant gas analyzer, and the temperature distribution is acquired by a multi-point thermocouple array or infrared temperature measurement array. Data is collected synchronously at each measuring point according to a preset sampling frequency, such as 1 to 10 Hz. The data is then uniformly collected and preliminarily filtered by the data acquisition module to obtain initial multiphysics field data containing chlorine concentration, spatial temperature distribution and its time variation characteristics. The humidity change rate and flow velocity pulsation signal in the initial multiphysics data are time-aligned to obtain unified time-stamped data. Humidity data is acquired through a flue gas humidity sensor, and flow velocity pulsation signals are measured in real time by a Pitot tube array or ultrasonic flow meter. Considering the differences in sampling frequency and communication delay of different sensors, the data of various types are timestamped, and the interpolation resampling method is used to map the multi-source data to the same time axis. The sliding window alignment strategy is used to eliminate local time offset, and low-pass filtering is combined to suppress high-frequency noise interference. Finally, the humidity change rate and flow velocity pulsation data that change synchronously under the unified time scale are obtained, realizing the consistent expression of multi-source information in the time dimension. Based on unified time-scaled data, local heat flux characteristics are calculated in conjunction with the heat transfer structure of the flue wall. A simplified heat transfer model is established according to the flue structure parameters, including wall thickness, material thermal conductivity, and heat transfer surface arrangement. The wall temperature gradient is calculated using temperature distribution data under the unified time-scale. The local heat flux at each measuring point is solved using the basic heat transfer relationship. The influence of convective heat transfer on the flue gas side is considered, and the empirical convective heat transfer coefficient is introduced for correction. Thus, heat flux characteristic data reflecting the local heat transfer intensity and temperature drop trend of the wall are obtained, which are used to characterize the thermodynamic conditions for condensation triggering. The flow velocity fluctuations are segmented and analyzed to extract boundary layer flow structure parameters. The flow velocity fluctuation signals under a unified time scale are processed by time series segmentation. Based on the amplitude and frequency characteristics of the flow velocity changes, they are divided into stable and disturbed segments. For the disturbed segments, the dominant frequency and energy distribution characteristics are extracted using spectrum analysis or wavelet decomposition. The existence of local recirculation zones, shear layers and vortex structures are inferred by combining the flue geometry. On this basis, the boundary layer thickness variation trend and flow instability index are calculated to form boundary layer flow parameters that can reflect the intensity and structural characteristics of airflow disturbance, providing basic flow information for identifying condensation enrichment regions. Chlorine concentration, temperature distribution, humidity, flow velocity, and flow structure parameters are fused to generate basic characterization data of chlorine disturbance. The chlorine concentration, temperature distribution, humidity change rate, flow velocity fluctuation, and boundary layer flow structure parameters obtained above are uniformly normalized and multi-dimensional features are spliced ​​according to time series to construct a multi-physics field fusion data vector. Furthermore, the key feature expression sensitive to chlorine disturbance is strengthened through weighted fusion or feature mapping, forming basic characterization data of chlorine disturbance that can comprehensively reflect the fluctuation of chlorine components in flue gas and its thermo-flow coupling relationship, providing a unified input basis for phase change identification and corrosion migration analysis.

[0021] Phase change identification module: Based on the basic characterization data of chlorine disturbance, the coupling relationship between the local temperature drop response of the flue wall and the chlorine enrichment fluctuation is analyzed. Combined with the dynamic offset characteristics of the critical condition of acidic condensation on the wall, the phase change triggering interval and spatial distribution of the wall are identified, and the characterization of the phase change triggering state of the wall is generated.

[0022] The process of analyzing the coupling relationship between the local temperature drop response of the flue wall and the chlorine enrichment fluctuation in the phase change identification module is as follows: Based on the chlorine disturbance basic characterization dataset, the temperature distribution characteristics are divided into local windows to extract the sensitive sections of wall temperature drop response. The temperature distribution data in the aforementioned chlorine disturbance basic characterization dataset is used to construct a two-dimensional temperature field matrix according to the flue axial length and cross-sectional spatial location. A sliding window method is used, such as dividing the temperature data into local windows with a step size of 0.5 to 2m along the flue length direction, to process the temperature data into partitions. The temperature change gradient and temperature drop rate over time are calculated in each local window, and a temperature drop threshold is set. For example, the critical cooling rate range obtained from historical operation data is used to screen out the area of ​​rapid temperature drop. The area that meets the threshold condition is marked as the sensitive section of wall temperature drop response, which is used to characterize high-risk locations where condensation or phase change may occur. Within the temperature drop response sensitive range, the fluctuation amplitude and rate of change of chlorine component concentration are extracted simultaneously to form dynamic characteristics of chlorine enrichment. For the identified temperature drop response sensitive range, the chlorine component concentration data sequence is extracted from the corresponding time window, and its instantaneous fluctuation amplitude and rate of change are calculated. At the same time, the maximum fluctuation range and mean offset within the local time period are obtained through the sliding window statistical method to characterize the dynamic enrichment degree of chlorine concentration in this region. Furthermore, the dissolution and condensation trend of chlorine component can be further corrected by combining the humidity change rate. Finally, dynamic characteristic data of chlorine enrichment containing fluctuation amplitude, rate of change and enrichment trend are formed to describe the response behavior of chlorine component in the temperature drop region. Using the temperature drop response characteristics as a reference, a time-delay matching analysis was performed on the dynamic characteristics of chlorine enrichment to calculate the dynamic correlation parameters between the two. The temperature drop response characteristic sequence was used as the reference signal, and the chlorine enrichment dynamic characteristic sequence was used as the comparison signal. The time-delay correlation analysis method was used to perform time-shift scanning on the two. Within a preset time delay range, such as ±10 to 30 s, the chlorine concentration sequence was gradually shifted, and the correlation coefficient under the corresponding time delay was calculated. The time delay corresponding to the maximum correlation coefficient was selected as the optimal matching time delay, and the maximum correlation coefficient was recorded as the dynamic correlation index between the two. At the same time, normalization was introduced to eliminate dimensional differences and improve the comparability of data under different operating conditions, thereby obtaining dynamic correlation parameters that can reflect the coupling strength and response lag between temperature drop and chlorine enrichment. By combining historical data under different operating conditions, dynamic correlation parameters are analyzed by region, and coupling characteristic parameters reflecting the synergistic change relationship between temperature drop response and chlorine enrichment are output. Historical operating data under different load levels, waste composition fluctuations, and operating temperature conditions are collected, and the corresponding dynamic correlation parameters are classified and stored according to operating condition categories. Based on statistical analysis methods, the distribution characteristics of correlation parameters under different operating conditions are extracted to identify high coupling intervals and low coupling intervals. Furthermore, by setting coupling judgment thresholds, the synergistic change relationship between temperature drop response and chlorine enrichment is divided into strong coupling, medium coupling, and weak coupling levels, and the corresponding parameters are output as coupling characteristic parameters, which are used as the judgment basis in phase change identification and corrosion migration analysis.

[0023] The process of generating a representation of the wall phase transition trigger state in the phase transition identification module is as follows: Based on the coupling characteristic parameters, the real-time difference between the flue gas temperature and the acid dew point temperature in each region is calculated to form a temperature difference judgment result. According to the coupling characteristic parameters and the temperature data of the corresponding region, the discrete spatial units of the flue are divided. The spatial unit includes the region divided by the segment along the flue axis and the cross-sectional grid. The actual flue gas temperature in each spatial unit is calculated. The acid dew point temperature is calculated based on the hydrogen chloride concentration, the moisture content of the flue gas and the empirical dew point model. The corresponding dew point temperature value can be obtained by using empirical formulas or by looking up tables. Under a unified time series, the difference between the flue gas temperature and the acid dew point temperature of each spatial unit is calculated, and the obtained difference is output as the temperature difference judgment result in time order. The region where the temperature difference is close to or less than zero is judged as a potential condensation risk zone, providing an initial criterion for phase change identification. Based on the temperature difference determination results, the humidity change rate is introduced to dynamically correct the acid condensation critical condition, resulting in a condensation threshold curve that varies with operating conditions. Considering the influence of flue gas humidity changes on the acid dew point, the initial acid dew point temperature is dynamically corrected by introducing a humidity change rate parameter. Specifically, the humidity change rate is correlated with the temperature difference determination results, a correction function is constructed, and the acid dew point temperature is offset and adjusted to obtain the corrected critical condensation temperature. Furthermore, the corrected critical temperature is continuously calculated in the time dimension to form a condensation threshold curve that varies with operating conditions. This allows the threshold to dynamically reflect the influence of flue gas humidity fluctuations and transient operating conditions on the condensation triggering conditions, thereby improving the accuracy of the determination. By comparing the temperature difference determination sequence with the condensation threshold curve, the time interval that meets the phase change triggering condition is identified. The temperature difference determination sequence corresponding to each spatial unit is compared with its corresponding condensation threshold curve time by time. When the temperature difference value is lower than or close to the corrected condensation threshold, it is determined that the condensation phase change triggering condition is met at that time. Through continuous time determination, the time interval that meets the condition is extracted, and short-term noise triggering is filtered out. For example, a minimum duration threshold is set, such as 5 to 20 seconds, to avoid false judgment. Finally, a stable phase change triggering time interval is output to describe the time range and duration characteristics of condensation. By mapping time intervals to spatial locations within the flue and combining phase change duration with triggering frequency, a wall phase change triggering state characterization is generated. The identified phase change triggering time intervals are associated with corresponding spatial unit locations to construct a time-space correspondence matrix. Based on this, the phase change duration (i.e., the triggering time interval length) and triggering frequency (i.e., the number of triggers per unit time) at each spatial location are statistically analyzed and normalized to eliminate sampling differences between different regions. Furthermore, the duration and triggering frequency are weighted and fused to form a state index reflecting the activity level of phase change. This index is then classified and labeled according to preset grading standards, such as high risk, medium risk, and low risk. Finally, a wall phase change triggering state characterization is generated to intuitively reflect the intensity and spatial distribution characteristics of condensation in each region within the flue.

[0024] Interface Coupling Module: Based on the characterization of phase change triggering state, the feedback relationship between chlorine deposition and wall wettability changes is analyzed, the positive feedback characteristics of condensation enhancement on chlorine enrichment are extracted, and the coupling relationship between interface state and flow field disturbance response is established by combining the feedback influence of wall phase change and deposition evolution on local boundary layer flow structure.

[0025] The process of extracting the positive feedback feature of condensation enhancement on chlorine enrichment in the interface coupling module is as follows: Based on the characterization of the wall phase change triggering state, the formation and development process of the liquid film is extracted within the phase change region to obtain the wall wettability change characteristics. According to the characterization of the wall phase change triggering state, the spatial region and corresponding time interval of condensation in the flue are determined, and wall temperature sensors and conductivity or capacitance thin film detection units are arranged in this region to indirectly characterize the formation and thickness change of the liquid film. By monitoring the wall temperature recovery hysteresis characteristics and changes in conductivity or capacitance signals, the formation, expansion and regression processes of the liquid film are judged. Combined with time series analysis, the changes in liquid film coverage and thickness are extracted. Furthermore, the liquid film coverage, formation rate and duration are used as characterization parameters to construct the wall wettability change characteristics to reflect the degree of influence of condensation on the wall state. Based on the wettability variation characteristics, the dissolution, migration, and redeposition behavior of chlorine components in the liquid film were analyzed to obtain the chlorine deposition rate variation characteristics. Based on the liquid film existence conditions, the dissolution process of chlorine components such as hydrogen chloride in the liquid film was regarded as a gas-liquid mass transfer process. By combining the chlorine concentration data in the flue gas and the liquid film thickness estimation, a simplified mass transfer model was used to calculate the flux of chlorine components entering the liquid film. At the same time, considering the migration behavior of the liquid film under gravity and airflow shear, the migration path and residence time of chlorine components on the wall were estimated. Under the conditions of liquid film evaporation or local temperature rise, the redeposition rate of chloride on the wall was calculated. By performing time series statistics on the above dissolution flux, migration amount, and redeposition amount, the chlorine deposition rate variation characteristics were extracted to describe the dynamic evolution of the chlorine enrichment process. Correlation analysis was performed on the wettability change characteristics and chlorine deposition rate change characteristics to determine the feedback enhancement relationship between the two. The wettability change characteristic sequence and the chlorine deposition rate change characteristic sequence were uniformly time-aligned, and correlation analysis methods, such as sliding window correlation coefficient calculation or regression analysis, were used to assess the degree of influence of liquid film change on chlorine deposition rate. By analyzing the synchronous change trend of the two types of characteristics in different time periods, it was identified whether the increase in liquid film thickness or coverage corresponds to the increase in chlorine deposition rate, thereby determining the positive correlation between the two. Furthermore, by setting a correlation threshold to screen significant correlation intervals, the feedback enhancement relationship of condensation wetting on the chlorine enrichment process was determined, providing a basis for modeling the coupling mechanism. By combining the changes in phase transition intensity, the amplification effect of chlorine enrichment is evaluated, and characteristic parameters of chlorine enrichment under condensation enhancement are extracted. Characteristic results for characterizing the coupling feedback mechanism of condensation, wetting, and deposition are output. Based on the phase transition intensity indices obtained from the characterization of phase transition triggering state, such as phase transition duration and triggering frequency, the chlorine deposition rate variation characteristics are weighted and corrected to reflect the differences in chlorine enrichment under different phase transition intensities. By constructing an amplification coefficient, the chlorine deposition rate corresponding to the strong phase transition region is enhanced and compared with the weak phase transition region to evaluate the amplification effect of the condensation process on chlorine enrichment. Furthermore, the wettability variation characteristics, chlorine deposition rate variation characteristics, and phase transition intensity parameters are integrated to form comprehensive characteristic parameters, and characteristic results for characterizing the coupling feedback mechanism of condensation, wetting, and deposition are output, providing input basis for corrosion migration analysis and control.

[0026] The process of establishing the coupling relationship between the interface state and the flow field disturbance response in the interface coupling module is as follows: Based on the feature results, the changes in wall roughness and thermal boundary conditions are parametrically characterized. Based on the coupled feature results of condensation, wetting and chlorine deposition, the state of the flue wall is parametrically described. The wall roughness can be characterized by the equivalent roughness height, which can be estimated by combining the changes in sediment thickness and operational experience data, or by setting up wall deposition monitoring points to obtain the trend of change. The thermal boundary conditions are characterized by wall temperature, heat flux and temperature gradient, and the equivalent convective heat transfer coefficient is calculated by combining the heat transfer model. The above parameters are further normalized, and corresponding parameter sets are established according to spatial units, thus forming a parametric characterization result that can reflect the changes in the physical state of the wall. Based on parametric characterization, the influence of wall state changes on near-wall fluid velocity distribution and turbulence intensity is analyzed to obtain boundary layer structure evolution characteristics. Based on wall roughness and thermal boundary parameters, combined with the airflow conditions in the flue, the flow in the near-wall region is analyzed. Empirical formulas or simplified models can be used to calculate the near-wall velocity distribution change trend. For example, the velocity profile shape can be corrected according to the roughness change, and the turbulence intensity change can be estimated by combining turbulence empirical relationships. When conditions permit, it can also be corrected by numerical simulation or online velocity measurement data. By comparing the velocity distribution and turbulence intensity changes at different times or in different regions, the boundary layer thickness change trend, shear strength change and flow stability index are extracted to form boundary layer structure evolution characteristics, which are used to describe the influence of wall state changes on the flow structure. Based on the boundary layer structure evolution characteristics, the disturbance propagation path in the flow field is identified to determine local unstable regions. According to the flow instability indicators reflected in the boundary layer structure evolution characteristics, the disturbance propagation behavior in the flue flow field is analyzed. Specifically, by tracking the velocity fluctuation signal in time series and combining it with the spatial unit position, the propagation direction and path of the disturbance in the flue are identified, and its amplification or attenuation in local regions is analyzed. When certain regions show a significant increase in turbulence intensity or a sudden change in velocity gradient, they are identified as flow unstable regions. Further analysis of multi-time data superposition determines the main path of disturbance propagation and the spatial location where instability is likely to occur, providing a flow characteristic basis for establishing coupling relationships. A mapping model between interface state parameters and flow field disturbance intensity is established, outputting the coupling relationship reflecting the influence of interface changes on the flow structure. Correlation analysis is performed between wall state parameters and the flow field disturbance intensity of the corresponding spatial unit to construct a mapping relationship between them. Regression analysis or multivariate fitting methods are used to establish a relationship model with wall roughness and thermal boundary parameters as inputs and disturbance intensity or flow instability index as outputs. During model building, multi-condition data are introduced for parameter training or calibration to improve the model's adaptability and accuracy. The final output reflects the degree of influence of interface state changes on flow field disturbance, which can be used for corrosion migration analysis and control strategy formulation.

[0027] Migration Analysis Module: Based on the coupling relationship analysis, the flow field drives the spatial evolution of the phase change region. Combined with the deflection behavior of the local backflow structure and the disturbance propagation path, the module extracts the spatial migration characteristics of the corrosion and condensation enrichment regions under the action of fluid disturbance and generates the corrosion migration evolution path.

[0028] The process of analyzing the flow field-driven spatial evolution of the phase transition region based on coupling relationships in the migration analysis module is as follows: Based on the coupling relationship, the hydrodynamic distribution within the phase change region is reconstructed to obtain the local flow field distribution characteristics. Based on the coupling relationship between the interface state and the flow field disturbance, and combined with the phase change region determined by the phase change trigger state characterization, the hydrodynamic state of the corresponding spatial unit in the flue is reconstructed. The magnitude and direction of the flow velocity in each spatial unit are estimated using flow velocity measurement data and flow velocity fluctuation information, and the near-wall flow is corrected by combining boundary layer structure parameters. In the absence of direct measurement data, interpolation methods or simplified flow models are used to complete the data, thereby obtaining the local flow field distribution characteristics covering the phase change region. Based on the flow field distribution characteristics, regions with significant velocity gradient changes are extracted. By calculating the velocity differences between spatial units, the velocity gradient distribution results are obtained, and the velocity change amplitude between adjacent spatial units is compared. When the velocity gradient exceeds a preset threshold, the corresponding region is marked as a region with significant gradient changes. This type of region usually corresponds to shear layer, recirculation zone or flow separation zone, and is used to characterize the unstable position of the flow structure. The influence range of the flow field driving effect on chlorine enrichment and condensation regions at different time scales was analyzed to obtain the corresponding driving response characteristics. The flow field evolution process was divided into short-term and long-term time scales for analysis. The short-term time scale was used to capture the influence range of transient disturbances on chlorine enrichment and condensation regions. The disturbance propagation range was determined by synchronously analyzing flow velocity fluctuations and chlorine concentration changes. The long-term time scale was used to analyze the continuous influence of the average flow structure on the spatial distribution of chlorine enrichment and condensation regions. The migration trend was determined by statistically analyzing the changes in regional positions over different time periods, thereby obtaining the influence range and intensity characteristics of the flow field driving effect. Based on the driving response characteristics, the spatial evolution relationship of the phase change region is determined, and the spatial evolution trend results reflecting the driving characteristics of the flow field are output. By tracking the changes in the center position and boundary range of the phase change region at different times, the spatial evolution trajectory is constructed, and the migration direction and expansion trend are analyzed in combination with the positional relationship of the region with significant velocity gradient. The evolution trajectory is smoothed and the trend is fitted, and finally the continuous spatial evolution relationship and trend results are obtained, which are used to characterize the dynamic evolution characteristics of the phase change region under the driving action of the flow field.

[0029] The process of generating corrosion migration evolution paths in the migration analysis module is as follows: Based on the spatial evolution trend results, local recirculation structures in the flow field are identified. Based on the spatial evolution trend results of the phase change region, the velocity vector field in the flue is analyzed. By detecting the velocity reversal region and the velocity closed loop, the local recirculation structure region is identified. At the same time, combined with the region of significant velocity gradient, the boundary range of the recirculation structure is corrected to improve the identification accuracy. By comparing and analyzing the recirculation structure at different time sections, its stability and duration are determined, thus obtaining the distribution results of representative local recirculation structures in the flow field. Based on the backflow structure, the deflection law of the disturbance propagation path is analyzed to determine the area of ​​concentrated disturbance energy. Based on the identified backflow structure, the velocity pulsation signal is spatiotemporally tracked and analyzed to construct the disturbance propagation path. By analyzing the changes in the deflection angle and propagation direction of the disturbance under the action of the backflow structure, the convergence and dispersion characteristics of the disturbance path are identified. When the disturbance shows a continuous enhancement or path convergence phenomenon in a local area, the area is determined to be the area of ​​concentrated disturbance energy. The area is then weighted and corrected in combination with the turbulence intensity distribution to improve the stability and reliability of the identification. The spatial migration trajectory of chlorine enrichment and condensation regions under disturbance is formed by tracking the positional changes of these regions. Based on the phase change triggering state characterization and chlorine enrichment characteristic parameters, the chlorine enrichment and condensation regions are spatially calibrated and their spatial positions are tracked in a continuous time series. By comparing the changes in the center position and boundary range of the regions at different time points, the migration path under the influence of disturbance is constructed. At the same time, the migration trajectory is corrected by combining the flow field driven response characteristics to eliminate the influence of local measurement errors and short-term fluctuations, thereby forming a stable spatial migration trajectory. The spatial migration trajectory is clustered and trend-fitted to output the corrosion migration evolution path. Multi-path clustering analysis is performed on the obtained spatial migration trajectory. Clustering methods based on spatial distance or similarity are used to divide the migration trajectory into several typical evolution paths. On this basis, trend fitting processing is performed on each type of path. For example, piecewise linear fitting or curve regression methods are used to extract the migration direction and evolution trend. Finally, the weight distribution of each type of typical path is combined to output the corrosion migration evolution path, which is used to characterize the spatial evolution law and development trend of the corrosion region under the action of flow field disturbance.

[0030] Control and execution module: Based on the corrosion migration and evolution path, the coupling relationship between chlorine enrichment, condensation and corrosion region is analyzed, a corrosion self-organized evolution model is constructed, and the flue temperature field and flow parameters are controlled to form a corrosion feedback control mechanism.

[0031] The process of constructing the corrosion self-organization evolution model in the regulation and execution module is as follows: Based on the corrosion migration and evolution path, the evolution path is spatially superimposed with the chlorine concentration distribution and condensation intensity distribution to obtain multi-field coupled distribution results. The corrosion migration and evolution path is mapped to a unified flue gas spatial coordinate system and spatially registered with the chlorine concentration distribution data and condensation intensity distribution data at the same scale. The chlorine concentration distribution is obtained through online gas detection or sensor array, and the condensation intensity distribution is characterized by changes in liquid film thickness or wall temperature hysteresis characteristics. By superimposing the three types of data at the spatial unit level, multi-field coupled distribution results that simultaneously reflect the corrosion path, chlorine enrichment degree, and condensation intensity are obtained to describe the comprehensive driving environment of corrosion evolution. Based on the results of multi-field coupling distribution, high-risk areas with multiple superimposed factors are identified. The results of multi-field coupling distribution are normalized, and thresholds for chlorine concentration, condensation intensity, and corrosion path density are set respectively. When a spatial unit meets multiple threshold conditions at the same time, the area is determined to be a high-risk area with multiple superimposed factors. In addition, combined with spatial neighborhood expansion analysis, connectivity judgment and region merging are performed on high-risk areas to identify high-risk corrosion areas with continuous spatial distribution characteristics, which are used to characterize potential core areas for rapid corrosion development. The corrosion development process is divided into stages based on the time dimension, and a feedback mechanism is introduced to describe the mutually reinforcing relationship between chlorine enrichment, condensation, and corrosion, thus constructing a self-organized evolution model that reflects the corrosion development trend. The corrosion evolution process is divided into an initial germination stage, an accelerated development stage, and a stable expansion stage according to the time sequence. The changes in chlorine enrichment intensity, condensation intensity, and corrosion migration rate in each stage are statistically analyzed. A feedback enhancement mechanism is introduced to describe the progressive relationship between condensation enhancing liquid film formation, liquid film promoting chlorine enrichment, and chlorine enrichment accelerating corrosion development. By constructing a state transition relationship or a dynamic weight update model, the self-organized evolution description of the corrosion system in the time dimension is realized, thus forming a self-organized evolution model that reflects the corrosion development trend.

[0032] The process of forming a corrosion feedback control mechanism in the control execution module is as follows: Based on the corrosion self-organization evolution model, the corrosion development trend of different regions is predicted to obtain the risk distribution results. The corrosion self-organization evolution model is input into the current state parameters of each spatial unit, including chlorine concentration level, condensation intensity, flow field disturbance intensity and corrosion migration rate. The corrosion development trend of each spatial unit is predicted and calculated based on the time progression method. By evaluating the corrosion growth trend in the future, the corresponding spatial risk distribution results are generated. Different regions of the flue are divided according to the risk level, thereby identifying high-risk areas and potential expansion areas, providing a basis for regulation. Based on the risk distribution results, the flue temperature field is regulated by zone. The flue is spatially divided into zones based on the risk distribution results, and differentiated temperature regulation strategies are set for different risk level zones. For high-risk zones, the flue gas temperature is moved away from the acid dew point temperature by increasing the wall temperature or adjusting the local heat exchange conditions to suppress condensation. For medium and low-risk zones, a micro-temperature optimization method is adopted to maintain system stability. Specifically, this can be achieved by adjusting the parameters of the flue heating device or the waste heat recovery system, thereby forming a spatially targeted temperature field regulation result. Based on temperature regulation, the flow velocity and flow structure parameters are optimized and adjusted. After completing the temperature field zoning regulation, the flow velocity distribution and flow structure in the flue are further optimized and controlled. By adjusting the operating parameters of the induced draft fan or the local guiding structure, the flow field structure near the high-risk area is stabilized, the backflow and eddy intensity are reduced, and the flow velocity gradient is homogenized to reduce the local accumulation effect of chlorine enrichment and condensation, thereby weakening the dynamic conditions for corrosion development and achieving synergistic optimization control of temperature and flow field. By combining real-time monitoring data to dynamically correct the control strategy, a corrosion feedback control mechanism is output to control the operation of the flue. By collecting real-time data on temperature, chlorine concentration, humidity, and flow rate in the flue, the current control effect is evaluated online and compared with the corrosion risk prediction results. When the monitoring results deviate from the predicted trend, the temperature adjustment parameters and flow field control parameters are adaptively corrected to keep the system in a low corrosion risk operating range. Finally, a corrosion feedback control mechanism with closed-loop control capability is formed to continuously optimize the flue operation and inhibit corrosion development.

[0033] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0034] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A tail flue system for a waste incinerator suitable for high-chlorine corrosion-resistant environments, characterized in that, include: Chlorine disturbance sensing module: continuously collects information on chlorine component concentration, temperature field gradient, humidity change rate and flow velocity pulsation in the flue gas at the tail flue inlet, and generates basic characterization data of chlorine disturbance by combining the heat transfer structure of the flue wall and the boundary layer flow characteristics. Phase change identification module: Based on the basic characterization data of chlorine disturbance, the coupling relationship between the local temperature drop response of the flue wall and the chlorine enrichment fluctuation is analyzed. Combined with the dynamic shift characteristics of the critical condition of acidic condensation on the wall, the phase change triggering interval and spatial distribution of the wall are identified, and the characterization of the phase change triggering state of the wall is generated. Interface coupling module: Based on the characterization of phase change triggering state, the feedback relationship between chlorine deposition and wall wettability changes is analyzed, the positive feedback characteristics of condensation enhancement on chlorine enrichment are extracted, and the coupling relationship between interface state and flow field disturbance response is established by combining the feedback influence of wall phase change and deposition evolution on local boundary layer flow structure. Migration Analysis Module: Based on the coupling relationship analysis, the flow field drives the spatial evolution of the phase change region. Combining the deflection behavior of the local backflow structure and the disturbance propagation path, it extracts the spatial migration characteristics of the corrosion and condensation enrichment regions under the action of fluid disturbance and generates the corrosion migration evolution path. Control and execution module: Based on the corrosion migration and evolution path, the coupling relationship between chlorine enrichment, condensation and corrosion region is analyzed, a corrosion self-organized evolution model is constructed, and the flue temperature field and flow parameters are controlled to form a corrosion feedback control mechanism.

2. The waste incinerator tail flue system suitable for high-chlorine corrosion-resistant environments according to claim 1, characterized in that, The process of generating basic characterization data for chlorine perturbation is as follows: The concentration of chlorine components in the flue gas is collected by the sensing unit, and the temperature distribution and variation characteristics of the flue section are acquired simultaneously to form initial multiphysics field data. Time-aligned processing was performed on the humidity change rate and flow velocity pulsation signals in the initial multiphysics data to obtain unified time-stamped data; Local heat flux characteristics are calculated based on unified time-scaled data and the heat exchange structure of the flue wall. Segmented analysis of flow velocity fluctuations is performed to extract boundary layer flow structure parameters; By integrating chlorine concentration, temperature distribution, humidity, flow velocity, and flow structure parameters, basic characterization data of chlorine disturbances are generated.

3. The waste incinerator tail flue system suitable for high-chlorine corrosion-resistant environments according to claim 2, characterized in that, The process of analyzing the coupling relationship between the local temperature drop response of the flue wall and the chlorine enrichment fluctuation is as follows: Based on the chlorine perturbation-based characterization dataset, local windowing is performed on the temperature distribution characteristics to extract the sensitive sections of the wall temperature drop response. Within the temperature drop response sensitive range, the fluctuation amplitude and rate of change of chlorine component concentration are extracted simultaneously to form the dynamic characteristics of chlorine enrichment. Using the temperature drop response characteristics as a reference, a time-delay matching analysis was performed on the dynamic characteristics of chlorine enrichment to calculate the dynamic correlation parameters between the two. By combining historical data under different operating conditions, the dynamic correlation parameters are analyzed by region, and the coupled characteristic parameters reflecting the synergistic change relationship between temperature drop response and chlorine enrichment are output.

4. A waste incinerator tail flue system suitable for high-chlorine corrosion-resistant environments according to claim 3, characterized in that, The process of generating a characterization of the wall phase transition trigger state is as follows: Based on the coupling characteristic parameters, the real-time difference between the flue gas temperature and the acid dew point temperature in each region is calculated to form the temperature difference judgment result. Based on the temperature difference determination results, the humidity change rate is introduced to dynamically correct the acidic condensation critical condition, and the condensation threshold curve varies with the operating conditions is obtained. By comparing the temperature difference determination sequence with the condensation threshold curve, the time interval that meets the phase change triggering condition is identified; By mapping the time interval to the spatial location of the flue and combining the phase change duration with the triggering frequency, a characterization of the wall phase change triggering state is generated.

5. A waste incinerator tail flue system suitable for high-chlorine corrosion-resistant environments according to claim 4, characterized in that, The process of extracting the positive feedback characteristics of condensation enhancement for chlorine enrichment is as follows: Based on the characterization of the triggering state of the wall phase transition, the formation and development process of the liquid film in the phase transition region is extracted to obtain the characteristics of the wall wettability change. Based on the wettability change characteristics, the dissolution, migration and redeposition behavior of chlorine components in the liquid film were analyzed to obtain the chlorine deposition rate change characteristics; Correlation analysis was performed on the wettability variation characteristics and the chlorine deposition rate variation characteristics to determine the feedback enhancement relationship between the two. By combining the changes in phase transition intensity, the amplification effect of chlorine enrichment is evaluated, characteristic parameters of chlorine enrichment under condensation enhancement are extracted, and characteristic results are output to characterize the coupling feedback mechanism of condensation, wetting and deposition.

6. A waste incinerator tail flue system suitable for high-chlorine corrosion-resistant environments according to claim 5, characterized in that, The process of establishing the coupling relationship between the interface state and the flow field disturbance response is as follows: Based on the feature results, the changes in wall roughness and thermal boundary conditions are parametrically characterized. Based on parametric characterization, the influence of wall state changes on near-wall fluid velocity distribution and turbulence intensity is analyzed to obtain the boundary layer structure evolution characteristics. Based on the boundary layer structure evolution characteristics, the disturbance propagation path in the flow field is identified, and local unstable regions are determined. Establish a mapping model between interface state parameters and flow field disturbance intensity, and output the coupling relationship reflecting the influence of interface changes on the flow structure.

7. A waste incinerator tail flue system suitable for high-chlorine corrosion-resistant environments according to claim 6, characterized in that, The process of flow field-driven spatial evolution in the phase transition region, based on the coupling relationship analysis, is as follows: Based on the coupling relationship, the hydrodynamic distribution within the phase transition region is reconstructed to obtain the local flow field distribution characteristics; Based on the characteristics of the flow field distribution, regions with significant changes in velocity gradient are extracted; The influence range of the flow field driving effect on chlorine enrichment and condensation region at different time scales was analyzed, and the corresponding driving response characteristics were obtained. Based on the driving response characteristics, the spatial evolution relationship of the phase transition region is determined, and the spatial evolution trend results reflecting the driving characteristics of the flow field are output.

8. A waste incinerator tail flue system suitable for high-chlorine corrosion-resistant environments according to claim 7, characterized in that, The process of generating corrosion migration evolution paths is as follows: Based on the spatial evolution trend results, identify local backflow structures in the flow field; Based on the recirculation structure, the deflection law of the disturbance propagation path is analyzed to determine the area where the disturbance energy is concentrated; Track the positional changes of chlorine enrichment and condensation regions under disturbance to form spatial migration trajectories; Path clustering and trend fitting are performed on the spatial migration trajectory to output the corrosion migration evolution path.

9. A waste incinerator tail flue system suitable for high-chlorine corrosion-resistant environments according to claim 8, characterized in that, The process of constructing a corrosion self-organization evolution model is as follows: Based on the corrosion migration evolution path, the evolution path is spatially superimposed with the chlorine concentration distribution and condensation intensity distribution to obtain multi-field coupled distribution results; Based on the results of multi-field coupling distribution, high-risk areas with multiple superposition of factors are identified; The corrosion development process is divided into stages based on the time dimension, and a feedback mechanism is introduced to describe the mutually reinforcing relationship between chlorine enrichment, condensation and corrosion, thus constructing a self-organized evolution model that reflects the corrosion development trend.

10. A waste incinerator tail flue system suitable for high-chlorine corrosion-resistant environments according to claim 9, characterized in that, The process of forming a corrosion feedback control mechanism is as follows: Based on the corrosion self-organization evolution model, the corrosion development trend in different regions is predicted, and the risk distribution results are obtained; Based on the risk distribution results, the flue temperature field is zoned and adjusted. Based on temperature control, the flow rate and flow structure parameters are optimized and adjusted. By combining real-time monitoring data, the control strategy is dynamically modified, and a corrosion feedback control mechanism is output to control the operation status of the flue.

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