Industrial organic waste gas efficient treatment system adopting catalytic combustion unit

Abstract

The invention relates to the technical field of industrial waste gas treatment, and discloses an industrial organic waste gas efficient treatment system adopting a catalytic combustion unit. A waste gas parameter acquisition module of the system acquires component concentration data and gas inlet flow data of industrial organic waste gas and temperature distribution data of a catalytic combustion unit in real time; the combustion risk analysis module calculates an unburnout risk characteristic value of the current combustion working condition according to the component concentration data and the air inlet flow data; the working condition optimization module generates an optimized operation parameter set of the catalytic combustion unit based on the unburnout risk characteristic value; and the feedback execution module adjusts the operation state of the catalytic combustion unit according to the optimized operation parameter set. The system realizes comprehensive monitoring, accurate risk analysis, dynamic working condition optimization and rapid feedback adjustment of the waste gas treatment process, adapts to different waste gas conditions, improves the stability and effectiveness of industrial organic waste gas treatment, and solves the problems of one-sided parameter acquisition, rigid working condition adjustment and feedback lag of the existing system.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of industrial waste gas treatment, in particular to an industrial organic waste gas efficient treatment system adopting a catalytic combustion unit. BACKGROUND

[0002] In the industrial production process, the petroleum chemical industry, coating, printing, pharmaceutical and other industries will continuously produce a large amount of waste gas containing organic compounds. If these waste gases are directly discharged into the atmosphere, not only will they cause damage to the surrounding ecological environment, but they may also have adverse effects on the human respiratory system, nervous system and other systems. Therefore, the effective treatment of industrial organic waste gas has become an indispensable part of industrial production. At present, the commonly used industrial organic waste gas treatment technologies in the industry include adsorption method, absorption method, condensation method and catalytic combustion method, etc. Among them, the catalytic combustion method is widely used in the treatment of medium and high concentration organic waste gas due to its high treatment efficiency and no secondary pollution.

[0003] The existing industrial organic waste gas treatment system adopting a catalytic combustion unit still has many problems to be solved in actual operation. On the one hand, the waste gas parameter acquisition link of most systems is relatively single, often only one or two of the component concentration of the waste gas or the inlet flow rate data are collected, and real-time acquisition of the internal temperature distribution data of the catalytic combustion unit is lacking. Temperature, as a key influencing factor of catalytic combustion reaction, its uniformity is directly related to the sufficiency of catalytic reaction. If the temperature distribution cannot be grasped in real time, it is difficult to accurately judge the reaction state of the catalytic combustion unit. On the other hand, the existing system lacks scientific quantitative basis in combustion risk analysis, and mostly relies on the experience of the operator to judge whether the combustion condition has the risk of incomplete combustion. This method is highly subjective and may lead to direct discharge of incomplete combustion organic waste gas or energy waste due to excessive adjustment of the working condition.

[0004] In the working condition optimization link, the existing system usually cannot generate a targeted optimization operation parameter set according to the actual combustion risk situation, and most of them can only run according to the preset fixed parameters, which is difficult to adapt to the waste gas treatment demand of different component concentrations and different intake flow rates. For example, when the concentration of waste gas components suddenly increases, if it is still running according to the original parameters, it may lead to insufficient catalytic combustion reaction; and when the intake flow rate suddenly drops, the catalytic combustion unit under fixed parameters may have a local temperature that is too high, affecting the service life of the catalyst. In addition, the feedback execution link of the existing system has obvious response lag, and there is a long time interval between the discovery of the working condition anomaly and the adjustment of the running state, during which not only the waste gas treatment effect will be affected, but also safety hazards may be caused by the continuous abnormal working condition, such as local high temperature causing catalyst sintering, organic waste gas accumulation causing combustion explosion risk, etc. The existence of these problems makes it difficult for the existing catalytic combustion treatment system to stably and efficiently complete the industrial organic waste gas treatment task, and cannot fully meet the strict requirements of industrial production on waste gas treatment. SUMMARY

[0005] The purpose of the present application is to provide an industrial organic waste gas efficient treatment system using a catalytic combustion unit to solve the problems raised in the background art.

[0006] To achieve the above-mentioned purpose, the present application provides an industrial organic waste gas efficient treatment system using a catalytic combustion unit, which comprises: an exhaust gas parameter acquisition module, a combustion risk analysis module, a working condition optimization module, and a feedback execution module; the exhaust gas parameter acquisition module acquires the component concentration data, intake flow rate data and temperature distribution data of the catalytic combustion unit of the industrial organic waste gas in real time; the combustion risk analysis module calculates the unburned risk characteristic value of the current combustion working condition according to the component concentration data and intake flow rate data; the working condition optimization module generates an optimized operation parameter set of the catalytic combustion unit based on the unburned risk characteristic value; and the feedback execution module adjusts the running state of the catalytic combustion unit according to the optimized operation parameter set.

[0007] Preferably, the combustion risk analysis module comprises a dynamic cycle adjustment unit; the dynamic cycle adjustment unit calls a combustion cycle conversion table, determines a first reference control cycle according to the matching result of the remaining processing time and the combustion cycle conversion table; acquires the number of types of waste gas components, determines a second reference control cycle based on the mapping relationship between the number of types and the combustion adjustment coefficient; and obtains the actual control cycle by subtracting the second reference control cycle from the first reference control cycle; wherein the remaining processing time in the combustion cycle conversion table has a negative correlation with the first reference control cycle.

[0008] Preferably, the dynamic cycle adjustment unit further calls a device complexity conversion table; the number of types of exhaust gas components includes: determining a first adjustment amount according to a mapping relationship between the number of types and a combustion adjustment coefficient; counting a number of catalytic reaction layers of the catalytic combustion unit, and determining a second adjustment amount based on a corresponding relationship between the number of catalytic reaction layers and the device complexity conversion table; and taking a sum of the first adjustment amount and the second adjustment amount as the second reference control cycle.

[0009] Preferably, the combustion risk analysis module further includes a risk classification determination unit; the risk classification determination unit compares the unburned risk characteristic value with a combustion risk threshold reference value; if the unburned risk characteristic value exceeds a first risk classification threshold, it is determined as a high-risk working condition; if the unburned risk characteristic value is between the first risk classification threshold and a second risk classification threshold, it is determined as a medium-risk working condition; and if the unburned risk characteristic value is lower than the second risk classification threshold, it is determined as a low-risk working condition.

[0010] Preferably, the working condition optimization module includes a phase matching engine; the phase matching engine receives the working condition risk level output by the risk classification determination unit and the actual control cycle output by the dynamic cycle adjustment unit; according to the working condition risk level matching a phase offset coefficient, the product of the actual control cycle and the phase offset coefficient is taken as the optimized response cycle of the catalytic combustion unit.

[0011] Preferably, the working condition optimization module further includes a multi-parameter collaborative correction unit; the multi-parameter collaborative correction unit acquires real-time temperature distribution data of the catalytic combustion unit, calculates a temperature dispersion index; according to a compensation relationship between the temperature dispersion index and the optimized response cycle, a corrected optimized response cycle is generated; and the corrected optimized response cycle is input into the exhaust gas treatment scheme generation unit.

[0012] Preferably, the exhaust gas treatment scheme generation unit generates at least two exhaust gas treatment candidate schemes based on the corrected optimized response cycle and the component concentration data; each exhaust gas treatment candidate scheme includes a temperature set value of the catalytic combustion unit, an intake flow adjustment amplitude, and a supplementary combustion time length parameter.

[0013] Preferably, the working condition optimization module further includes an entropy weight decision analysis unit; the entropy weight decision analysis unit calls a historical running state data set of the catalytic combustion unit; according to the historical running state data set, a state switching interference entropy value of each exhaust gas treatment candidate scheme is calculated; and a weighted sum of the state switching interference entropy value and the temperature dispersion index is taken as a scheme execution priority parameter.

[0014] Preferably, the feedback execution module comprises an optimal scheme execution unit; the optimal scheme execution unit selects the waste gas treatment candidate scheme with the lowest scheme execution priority parameter, and drives the control valve group and the heater array of the catalytic combustion unit according to the temperature setting value, the intake flow rate adjustment range and the supplementary combustion time length parameter of the waste gas treatment candidate scheme.

[0015] Preferably, the feedback execution module further comprises a running log construction unit; the running log construction unit records the real-time data acquired by the waste gas parameter acquisition module, the unburned risk characteristic value output by the combustion risk analysis module, and the waste gas treatment candidate scheme parameter executed by the optimal scheme execution unit, and generates the running state log data of the catalytic combustion unit.

[0016] Compared with the prior art, the present application has the following beneficial effects: The waste gas parameter acquisition module can acquire the component concentration data of the industrial organic waste gas, the intake flow rate data and the temperature distribution data of the catalytic combustion unit in real time, compared with the prior art system which only acquires part of the parameters, and the key influencing factors of the waste gas treatment are comprehensively covered. The component concentration data can reflect the content of the organic compounds in the waste gas, and provide a basis for judging the required conditions of the combustion reaction; the intake flow rate data can reflect the rate of the waste gas entering the catalytic combustion unit, and is related to the residence time of the waste gas in the reaction space; and the temperature distribution data of the catalytic combustion unit is directly related to the degree of the catalytic reaction, and the three data can form real-time monitoring of the whole waste gas treatment process, avoid the one-sidedness of the working condition judgment caused by incomplete parameter acquisition, and make the subsequent combustion risk analysis and working condition optimization more data-supported.

[0017] The combustion risk analysis module calculates the unburned risk characteristic value of the current combustion working condition according to the component concentration data and the intake flow rate data, and changes the existing system which depends on the experience to judge the risk. The unburned risk characteristic value presents the risk degree of the combustion working condition in a quantitative way, and the operator can intuitively understand whether there is an unburned risk and the risk level according to the value, without relying on subjective experience for speculation. This quantitative analysis method can effectively reduce the human judgment error, and can accurately capture the possible unburned risk in the scene where the waste gas component concentration fluctuates greatly or the intake flow rate is unstable, provide accurate risk warning for timely adjusting the working condition, and avoid the emission of unburned waste gas due to the delay or inaccuracy of risk judgment, or the energy loss caused by excessive prevention and control.

[0018] The working condition optimization module generates an optimized operation parameter set of the catalytic combustion unit based on the unburned risk characteristic value, realizing the pertinence and accuracy of working condition adjustment. Most existing systems use fixed parameters for operation and cannot flexibly adjust according to actual risk conditions. However, the working condition optimization module of the system can generate operation parameters matched with different unburned risk characteristic values, such as adjusting the temperature setting and intake air rate control of the catalytic combustion unit. When the unburned risk characteristic value is high, the optimized operation parameter set can pertinently increase the catalytic combustion temperature or reduce the intake air flow to promote the complete combustion of organic waste gas. When the unburned risk characteristic value is low, the parameter set can adjust the parameters to reduce energy consumption and avoid unnecessary energy waste. This dynamic optimization method based on risk can keep the catalytic combustion unit in the best operating state that adapts to the current waste gas condition, whether it is processing high-concentration and high-flow waste gas or low-concentration and low-flow waste gas, and can maintain stable treatment effect.

[0019] The feedback execution module adjusts the operating state of the catalytic combustion unit according to the optimized operation parameter set, forming a closed-loop processing flow of "data collection-risk analysis-working condition optimization-execution adjustment". The feedback execution of existing systems often has a response lag, while the feedback execution module of the system can quickly adjust the operating state of the catalytic combustion unit after the working condition optimization module generates the optimized parameter set, reducing the time interval between parameter optimization and actual execution. This rapid response capability can timely correct abnormal working conditions and avoid problems such as catalyst damage and substandard waste gas treatment caused by prolonged duration of abnormal working conditions. For example, when the system detects that the local temperature of the catalytic combustion unit is too high, the feedback execution module can quickly adjust the temperature control device to balance the temperature distribution in the unit and protect the catalyst performance. When the intake air flow suddenly increases, the relevant components can be adjusted in time to ensure that the waste gas has enough residence time in the unit for complete combustion. In addition, the formation of the closed-loop flow also enables the system to continuously optimize the parameters according to the real-time operating conditions. As the waste gas treatment process progresses, the waste gas parameter collection module continuously updates the data, the combustion risk analysis module continuously calculates new risk values, the working condition optimization module generates new optimized parameters accordingly, and the feedback execution module adjusts the operating state, so that the system always maintains high processing capacity and adapts to the dynamic changes of waste gas composition and flow in different industrial scenarios, providing reliable protection for the stable treatment of industrial organic waste gas. BRIEF DESCRIPTION OF DRAWINGS

[0020] Figure 1 a timing diagram of the industrial organic waste gas efficient treatment system using a catalytic combustion unit according to the present application; Figure 2 a working flowchart of the dynamic period adjustment unit of the combustion risk analysis module; Figure 3 a working flowchart of the risk grading determination unit of the combustion risk analysis module; Figure 4 The working flow chart of the multi-parameter collaborative correction unit of the working condition optimization module. DETAILED DESCRIPTION

[0021] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative labor fall within the protection scope of the present application.

[0022] Please refer to Figure 1 The present application provides an industrial organic waste gas efficient treatment system using a catalytic combustion unit, which comprises a waste gas parameter acquisition module, a combustion risk analysis module, a working condition optimization module, and a feedback execution module.

[0023] The waste gas parameter acquisition module acquires the component concentration data of the industrial organic waste gas, the inlet gas flow data, and the temperature distribution data of the catalytic combustion unit in real time through a gas component sensor, a flow meter, and a temperature sensor. The combustion risk analysis module receives these data and calculates the unburned risk characteristic value of the current combustion working condition through an embedded algorithm. This characteristic value reflects the possibility of incomplete combustion of the waste gas. The working condition optimization module generates an optimized operation parameter set of the catalytic combustion unit based on the unburned risk characteristic value, including parameters such as temperature setting, flow adjustment, and cycle control. The feedback execution module drives the actuator according to the optimized operation parameter set to adjust the running state of the catalytic combustion unit, such as controlling the valve opening degree, the heater power, and the combustion cycle, to achieve efficient and stable waste gas treatment.

[0024] Embodiment 1: Please refer to Figure 2 In the actual operation of the industrial organic waste gas treatment system, the waste gas parameter acquisition module continuously captures the dynamic characteristics of the waste gas flow through a high-precision sensor network. The laser spectrum analyzer and the electrochemical sensor installed on the inlet gas pipeline monitor the concentration changes of volatile organic compounds such as benzene, toluene, and xylene in the waste gas in real time, while the turbine flow meter records the inlet gas flow data at a frequency of several times per second. Inside the catalytic combustion unit, a distributed thermocouple array is arranged along the axial and radial directions of the catalyst bed, forming a temperature monitoring network. The collected temperature data is transmitted to the central processing unit through an industrial bus. These real-time data constitute the basis for the system to perceive the environment and provide data support for risk analysis and decision-making.

[0025] The dynamic cycle adjustment unit in the combustion risk analysis module is activated, and accesses the combustion cycle conversion table in the system database. The conversion table is stored in matrix form, with row indexes representing the remaining processing time and column indexes corresponding to different processing load levels. For example, when the system detects that the remaining processing time is less than 30% of the standard cycle, the query result points to a shorter first reference control cycle. This design enables the system to use more frequent adjustment strategies at the end of the processing to maintain the processing effect. At the same time, the gas composition analyzer identifies that the current exhaust gas contains five different organic compounds, and according to the pre-set mapping relationship, this multi-component exhaust gas corresponds to a higher combustion adjustment coefficient, thus deriving a longer second reference control cycle.

[0026] The dynamic cycle adjustment unit further calls the device complexity conversion table to complete the calculation. The system automatically scans the structural configuration of the catalytic combustion unit and detects that the unit adopts a three-layer catalytic reaction layer design, with each layer filled with different types of catalysts. According to the device complexity conversion table, this multi-layer structure corresponds to a higher complexity coefficient, resulting in a larger second adjustment amount. At the same time, the complexity of the five components in the exhaust gas also brings about a corresponding first adjustment amount. Adding these two adjustment amounts, the system obtains a comprehensive second reference control cycle. The final actual control cycle is obtained by subtracting this composite value from the first reference control cycle, and this calculation result reflects the system's comprehensive consideration of processing progress, exhaust gas complexity, and device structural characteristics. In another operating scenario, the exhaust gas composition changes significantly, and when the exhaust gas source switches to a different production process, the sensor detects that the number of organic species is reduced to two, and the intake flow tends to be stable. The dynamic cycle adjustment unit responds immediately to this change, and since the number of components is reduced, the combustion adjustment coefficient queried according to the mapping relationship is correspondingly reduced, resulting in a decrease in the value of the second reference control cycle. At the same time, the device complexity remains unchanged, and the catalytic reaction layer still has a three-layer structure. In this case, the calculation result of the actual control cycle shows that more frequent adjustment intervention is needed, because the simpler exhaust gas composition allows the system to optimize the adjustment at a higher frequency without causing operational instability.

[0027] The system also incorporates an abnormal operating condition handling mechanism. When the exhaust gas composition suddenly increases to more than eight complex components, the dynamic cycle adjustment unit activates a special calculation mode. In this case, not only is the combustion regulation coefficient taken at its maximum value, but an additional safety margin coefficient is also introduced. Simultaneously, the equipment complexity assessment considers not only the number of catalytic reaction layers but also factors such as the current activity state of the catalyst. These combined factors enable the system to adopt a more conservative strategy in actual control cycle calculations, appropriately extending the adjustment cycle to avoid system oscillations caused by overly frequent adjustments. During data processing, the system uses a sliding window algorithm to smooth real-time data. The dynamic cycle adjustment unit considers not only instantaneous data but also analyzes data trends over a recent period. For example, when the types of exhaust gas components fluctuate drastically in a short period, the system uses a weighted average value instead of instantaneous values ​​for calculation. This approach avoids drastic changes in the control cycle caused by sudden data mutations, maintaining the stability of system operation.

[0028] The entire calculation process adopts a modular design, with configurable parameters for the combustion cycle conversion table, mapping relationships, and equipment complexity conversion table. Engineers can calibrate and optimize these parameter tables based on actual operating experience and different application scenarios. This design enables the system to adapt to the exhaust gas characteristics of different industries, from chemical production to printing operations, achieving optimal calculation results through parameter adjustments. All calculations are completed in an industrial-grade controller, with calculation cycles controlled at the millisecond level, meeting real-time control requirements.

[0029] The system also establishes a verification mechanism for the calculation results. Each calculated actual control cycle is compared with historical operating data, and if an abnormal deviation is detected, a recalculation process is automatically triggered. Simultaneously, all intermediate parameters and final results during the calculation process are recorded in the operating log, providing a data foundation for system performance analysis and optimization. This design ensures the reliability and traceability of the calculation results, enabling the system to operate stably for a long period.

[0030] Example 2: See Figure 3During the operation of the industrial organic waste gas treatment system, the risk grading and determination unit of the combustion risk analysis module continuously receives unburned risk characteristic values ​​from the calculation unit. These characteristic values ​​are quantitative indicators derived from comprehensive calculations of waste gas component concentration and inlet flow rate data, reflecting the probability level of incomplete combustion of organic matter under the current operating conditions. The processor built into the risk grading and determination unit compares these characteristic values ​​in real time with combustion risk threshold reference values ​​pre-stored in the system database. These threshold reference values ​​are grading standards established based on extensive experimental data and theoretical models. The first risk grading threshold marks the critical point of high-risk operating conditions, while the second risk grading threshold distinguishes the boundary between medium-risk and low-risk operating conditions. The risk grading and determination unit employs a dynamic threshold adjustment mechanism, and its core grading logic can be expressed by the following formula:

[0031] in: It represents the characteristic value of unburned risk and is a dimensionless comprehensive risk indicator; This represents the real-time concentration value of the i-th organic compound, in milligrams per cubic meter. This is the real-time air intake flow rate, expressed in cubic meters per hour. It is the risk weight coefficient of the i-th organic compound, which is determined based on its combustion characteristics and toxicity; This represents the average operating temperature of the catalytic combustion unit, expressed in degrees Celsius; n represents the total number of detected organic compounds. This formula comprehensively considers multiple factors, including concentration, flow rate, material properties, and operating temperature, and can fully reflect the combustion risk situation.

[0032] When the system detects that the unburned combustion risk characteristic value exceeds the first risk classification threshold, the judgment unit immediately marks the current operating condition as high-risk. In this case, it usually means that there may be a high concentration of non-flammable substances in the exhaust gas or a sudden increase in flow rate, leading to a significant increase in the risk of incomplete combustion. The system automatically triggers an emergency response mechanism, transmitting the risk level signal to the operating condition optimization module, requiring immediate intervention. Simultaneously, the system records the occurrence time, duration, and related parameters of the high-risk event, forming a complete event log. If the unburned combustion risk characteristic value is between the first and second risk classification thresholds, the judgment unit classifies the operating condition as medium-risk. This state indicates a certain degree of uncertainty in the combustion process, possibly caused by fluctuations in exhaust gas composition or changes in equipment status. The system initiates a standard optimization program, reducing the risk level by appropriately adjusting operating parameters. Detailed information such as the duration and trend of the medium-risk state is recorded and analyzed to improve the risk warning model.

[0033] When the unburned combustion risk characteristic value remains below the second risk level threshold, the system determines that it is currently in a low-risk operating condition. This indicates that the exhaust gas composition is relatively stable, the combustion process is relatively complete, and the system is operating in an ideal state. Even so, the system will still maintain monitoring and conduct periodic risk assessments to prevent sudden changes in operating conditions. The operating parameters and risk characteristic value changes under low-risk conditions will be incorporated into the normal operating condition database to provide a reference for system optimization.

[0034] The risk grading and determination unit also possesses adaptive learning capabilities. Through long-term operation and the accumulation of extensive risk grading data, the system can automatically update and optimize threshold settings. When a new type of organic compound is detected or operating conditions change significantly, the system initiates a threshold recalibration procedure. By analyzing historical data and the current operating status, it dynamically adjusts the grading thresholds, making risk assessment more accurate and reliable. This adaptive mechanism ensures the system can cope with various complex operating environments.

[0035] During data processing, the risk grading unit employs a multi-verification mechanism. Each risk characteristic value undergoes three steps before being used for grading judgment: data validity verification, trend rationality analysis, and historical data comparison. This rigorous process avoids misjudgments caused by sensor malfunctions or data anomalies, ensuring the accuracy and reliability of the risk grading results. All verification processes and results are meticulously recorded, forming a complete quality assurance document. The risk grading results are output in a standardized data format, including risk level codes, characteristic value values, judgment timestamps, and confidence indices. This standardized output facilitates module parsing and processing, and also enables data exchange and integration with other systems. A unique identifier is generated for each risk judgment event, ensuring the integrity of data traceability.

[0036] The system also establishes a collaborative mechanism between risk grading and other modules. When the risk level changes, the judgment unit immediately sends a status change notification to the relevant modules, enabling the entire system to respond quickly to changes in operating conditions. Simultaneously, the judgment unit also receives feedback from other modules to verify and correct risk assessment results. This collaborative mechanism ensures the coordination and consistency of system operation. The operational status of the risk grading judgment unit is continuously monitored. The system periodically performs self-diagnostic checks to verify the accuracy of sensor data, the correctness of calculation logic, and the reliability of output results. When any anomalies are detected, the system automatically switches to backup calculation mode or requests manual intervention to ensure the risk grading function always operates normally. All self-diagnostic results and intervention records are fully saved for system maintenance and performance optimization.

[0037] Example 3: See Figure 4During the operation of the industrial organic waste gas treatment system, the phase matching engine of the operating condition optimization module continuously receives operating condition risk level signals from the risk classification judgment unit and actual control cycle data from the dynamic cycle adjustment unit. The phase matching engine internally stores a table corresponding to risk levels and phase offset coefficients, where high-risk operating conditions correspond to larger offset coefficients, medium-risk operating conditions to medium coefficients, and low-risk operating conditions to smaller coefficients. When a high-risk operating condition signal is received, the engine automatically selects a larger phase offset coefficient, multiplies the actual control cycle by this coefficient, and obtains a shortened optimized response cycle. This design allows the system to respond faster and adjust operating conditions more promptly under high-risk conditions. For medium-risk operating conditions, the system uses a moderate phase offset coefficient, resulting in an optimized response cycle that ensures a certain level of timeliness while avoiding system oscillations that may be caused by overly frequent adjustments. Under low-risk operating conditions, a smaller phase offset coefficient results in a relatively longer optimized response cycle, reducing unnecessary adjustment operations and contributing to stable system operation.

[0038] The multi-parameter collaborative correction unit starts working simultaneously, acquiring real-time temperature data from various regions of the catalytic combustion unit through a distributed temperature sensor network. This temperature data comes from temperature measurement points installed at different locations on the catalyst bed, including key locations such as the inlet, reaction, and outlet zones. The unit's internal processor calculates the dispersion of this temperature data and derives a uniformity index for the temperature distribution through statistical analysis. When uneven temperature distribution is detected—that is, some areas are too hot while others are too cold—the system dynamically adjusts the response period based on the compensation relationship between the dispersion and the optimized response period. The more uneven the temperature distribution, the shorter the optimized response period, allowing for more timely adjustments to the temperature control parameters; when the temperature distribution is relatively uniform, the system appropriately extends the response period to reduce unnecessary adjustments.

[0039] The entropy weight decision analysis unit is activated, accessing the system's historical database and retrieving operational status data of the catalytic combustion unit over a past period. This data includes historical temperature records, flow rate variation curves, combustion efficiency indicators, and previous operational adjustment records. The analysis unit uses an information entropy algorithm to analyze and process this historical data, calculating the degree of system state change that each candidate exhaust gas treatment scheme may cause during execution. By analyzing the differences between the scheme parameters and historical operating modes, the impact of scheme execution on system stability is assessed. A higher state transition disturbance entropy value indicates that the scheme may cause significant system fluctuations after execution; a lower entropy value indicates that the scheme is more compatible with the current system operating state, resulting in a smoother system transition after implementation.

[0040] While calculating the entropy value of state switching disturbance, the entropy weight decision analysis unit also comprehensively considers the temperature dispersion index provided by the multi-parameter collaborative correction unit. Based on pre-set weight allocation principles, the system weights and integrates the state switching disturbance entropy value and the temperature dispersion index to generate execution priority parameters for each candidate scheme. The weight coefficients are set based on long-term operating experience and a deep understanding of system characteristics, ensuring a reasonable balance between temperature distribution uniformity and system stability factors. The lower the calculated priority parameter value, the better the overall evaluation result of the scheme, and the more likely it should be prioritized for implementation. Throughout the decision-making process, the system uses an iterative optimization algorithm to dynamically adjust the weight allocation. By analyzing historical decision effects and actual operating results, the system continuously optimizes the weight coefficient settings, making priority evaluation more accurate and reliable. All calculation processes and decision-making basis are recorded in detail in the system log, including the calculation parameters, weight allocation basis, and final priority score for each candidate scheme.

[0041] The system also establishes a decision verification mechanism, where each calculated priority parameter is cross-validated with real-time operational data. By monitoring the actual operational effects after the implementation of the plan and comparing them with the predicted priorities, deviations in the calculation model can be identified and corrected in a timely manner. This closed-loop verification mechanism ensures the accuracy and reliability of the decision results, enabling the system to continuously improve and optimize its performance. Under special operating conditions, such as sudden changes in exhaust gas composition or abnormal equipment status, the system will activate an emergency decision-making mode. In this mode, the entropy weight decision analysis unit will use a specially trained algorithm model, increasing the weight given to the characteristics of the new operating condition and appropriately reducing the requirement for matching historical data, so that the generated priority parameters are more in line with the needs of the current emergency. All calculation processes and parameter adjustments in the emergency decision-making mode are specially marked and recorded, providing a reference for subsequent abnormal operating condition handling.

[0042] The decision-making results are output in a standardized data format, including information such as the scheme number, priority parameters, decision timestamp, and confidence index. This data is transmitted to the feedback execution module via industrial communication protocols, providing direct evidence for the selection and execution of the optimal solution. Simultaneously, the decision results are displayed in real-time on the user interface, providing operators with intuitive decision-making references and allowing for manual intervention and adjustments when necessary.

[0043] Example 4: During the operation of the industrial organic waste gas treatment system, the waste gas treatment scheme generation unit receives the corrected optimized response cycle from the multi-parameter collaborative correction unit and real-time component concentration data from the waste gas parameter acquisition module. This unit initiates a multi-objective optimization algorithm to generate at least two candidate waste gas treatment schemes with different focuses based on these input parameters. Each candidate scheme is a complete set of parameters, including the temperature setpoint for the catalytic combustion unit, the inlet flow rate adjustment range, and the afterburning time parameters. The temperature setpoint is determined by comprehensively considering the ignition temperature of each organic compound in the waste gas and the current activity state of the catalyst, ensuring that the set temperature guarantees combustion efficiency without causing energy waste. The inlet flow rate adjustment range is calculated based on the difference between the current flow rate and the ideal flow rate, ensuring treatment efficiency while avoiding excessively high airflow velocity that would lead to insufficient residence time. The afterburning time parameter is determined based on the proportion and concentration of recalcitrant components in the waste gas, ensuring these components have sufficient reaction time. The core calculation model used in the scheme generation process is as follows:

[0044] in: This represents the comprehensive score of the j-th scheme, used for internal scheme optimization; , , These are the weighting coefficients for temperature, flow rate, and time, which are dynamically adjusted according to the operating strategy. It is the weighting factor of the i-th organic compound, which is determined by its combustion characteristics; This represents the temperature adjustment amount for the i-th organic compound in the j-th scheme; Let be the expected response time for the j-th option; It represents the flow rate adjustment range of the j-th scheme; This is the set value for the afterburning time of the j-th scheme. This model ensures the coordination and consistency among various parameters.

[0045] When generating candidate solutions, the system establishes a mechanism to ensure solution diversity. The first solution typically prioritizes energy efficiency optimization, employing a relatively conservative temperature setting and moderate flow rate adjustment to reduce energy consumption while maintaining treatment effectiveness. The second solution prioritizes treatment efficiency, using a higher temperature setting and precise flow control to ensure stable treatment results even under fluctuating exhaust gas composition. The third solution may focus on system stability, employing a gradual parameter adjustment strategy to avoid drastic operational changes. Each solution includes a complete set of operating parameters and an assessment of expected performance. The solution generation unit also considers the impact of the equipment's current operating status. When determining the temperature setpoint, the thermal inertia of the catalytic combustion unit and the heater response characteristics are taken into account to avoid discrepancies between the setpoint and actual capacity. The calculation of the flow rate adjustment range incorporates pipeline pressure characteristics and valve adjustment accuracy to ensure the feasibility and accuracy of flow rate adjustment. The setting of the afterburning time considers the combustion chamber volume and gas velocity to ensure the integrity of the afterburning process. All these factors are incorporated into the solution generation algorithm in the form of weighted coefficients.

[0046] The scheme generation process employs an iterative optimization method. The system first generates an initial scheme set and then evaluates the expected performance of each scheme under different operating conditions through simulation calculations. Based on the evaluation results, the scheme parameters are fine-tuned, and after multiple iterations, a final candidate scheme set is formed. Each iteration cycle records the adjustment process and evaluation results; this data is used to optimize algorithm parameters and improve the generation strategy. The convergence criteria used during the iteration process ensure the stability of the scheme quality.

[0047] The generated candidate schemes all include detailed operating instruction sequences. Temperature setpoints not only specify the target value but also include detailed parameters such as heating rate control requirements and temperature maintenance accuracy. The intake flow rate adjustment range clearly indicates the starting value, target value, and transition time requirements. The afterburning duration parameter specifies the afterburning start conditions, duration, and termination criteria. These details ensure the executability and operational accuracy of the schemes. The scheme generation unit also has real-time adjustment capabilities; when a significant change in exhaust gas component concentration is detected, the unit immediately recalculates and updates the candidate scheme set. This dynamic adjustment mechanism ensures that the schemes always match the current operating conditions. All scheme adjustment records, including the reason for adjustment, the content of the adjustment, and the adjustment time, are fully recorded in the system log. To ensure the scientific validity and reliability of the schemes, the system has a built-in scheme verification mechanism. Each generated candidate scheme must pass a series of feasibility checks, including parameter range verification, equipment capability matching verification, and safety assessment. Only schemes that pass all checks are output to subsequent modules. All prompts and warnings generated during the verification process are transmitted along with the scheme, providing a reference for subsequent decision-making. The output solutions employ a standardized data structure, with each solution containing a unique identifier, a generation timestamp, expected performance metrics, and a detailed parameter list. This standardized format facilitates parsing and processing by subsequent modules and also enables data exchange with other systems. All output solutions are cached locally for a period of time for later querying and reference. The system also establishes a solution generation quality monitoring system. By comparing the expected results with the actual execution outcomes, the generation algorithm and parameter settings are continuously optimized. Significant deviations and improvement measures discovered during monitoring are meticulously recorded and used to refine the solution generation model. This continuous improvement mechanism ensures the continuous enhancement of solution generation quality.

[0048] Example 5: During the operation of the industrial organic waste gas treatment system, the optimal solution execution unit of the feedback execution module continuously receives the solution execution priority parameters output by the entropy weight decision analysis unit. This unit automatically selects the solution with the lowest priority parameter value as the execution target by comparing the priority parameter values ​​of all candidate solutions. This indicates that the solution is optimal in terms of system stability, temperature uniformity, and operational feasibility. After selecting a solution, the execution unit immediately parses the complete parameter set contained in the solution, including specific temperature setpoints, inlet flow rate adjustment ranges, and afterburning time parameters. These parameters are converted into specific control commands and transmitted to the actuator of the catalytic combustion unit via the industrial bus.

[0049] The execution of control commands first targets the temperature regulation system. The optimal solution execution unit drives the heater array to adjust its power according to the temperature setpoint in the solution. The heater array adopts a zoned control strategy, with heaters in different zones adjusting independently according to temperature distribution requirements to ensure the uniformity of the catalytic bed temperature. The temperature regulation process employs a progressive control algorithm to avoid damage to the catalyst caused by sudden temperature changes. Simultaneously, the system monitors the temperature change trend in real time, compares it with the setpoint, and ensures the accuracy of temperature control through closed-loop control. Throughout the entire temperature regulation process, the heater's operating status, power output, and actual temperature changes are recorded in real time.

[0050] Intake flow regulation is achieved through a control valve assembly. The execution unit calculates the opening command for each valve based on the flow regulation range specified in the plan. The valve assembly employs a series control method, first regulating the main pipeline valves and then fine-tuning through the branch valves to ensure the accuracy of flow control. During flow regulation, the system monitors pipeline pressure changes and uses a pressure compensation algorithm to eliminate the impact of pressure fluctuations on flow control. The valve opening adjustment adopts a slow-opening and slow-closing strategy to avoid sudden airflow changes affecting combustion stability. The deviation between the actual flow value and the set value is continuously monitored and corrected through feedback adjustment.

[0051] Controlling the afterburning duration involves the coordinated operation of multiple actuators. The actuators precisely calculate the start time, duration, and termination conditions of afterburning based on the pre-set afterburning duration. During afterburning, the system adjusts the power output of the auxiliary burner and controls the supply of afterburning air to ensure effective afterburning. Simultaneously, it monitors changes in exhaust gas composition, analyzes data in real time to assess the afterburning effect, and dynamically adjusts afterburning parameters as needed. After afterburning, the system executes standard shutdown procedures, including gradually reducing the temperature and adjusting the flow rate to standby mode.

[0052] The operation log construction unit works synchronously throughout the entire execution process, continuously recording system operation data. This unit collects real-time data from the exhaust gas parameter acquisition module, including raw readings from each sensor, calculated component concentration values, and flow statistics. It also records the unburned risk characteristic values ​​output by the combustion risk analysis module and the intermediate parameters used in its calculation. The execution details of the optimal solution execution unit are also fully recorded, including the final selected solution identifier, execution start time, operating instructions for each actuator, and actual response data. Log data is stored in a structured format, organized according to time sequence, with each data point containing a precise timestamp and data source information. The data storage format is optimized to ensure both query efficiency and space efficiency. Log files are managed using rolling storage, automatically deleting expired data while archiving important data to a long-term storage system. All log records include data integrity verification information to prevent data tampering or corruption.

[0053] The operation log construction unit also implements data preprocessing functions. Raw data is filtered before being stored in the log to eliminate noise interference; data standardization is also performed to unify data units and formats; important data is also summarized into statistical summaries, including indicators such as average, maximum, minimum values, and trends. These preprocessing operations improve the quality and usability of log data. The system establishes a comprehensive log query and analysis mechanism. Operators can query log records by time range, data type, or specific event through a human-machine interface. The system provides data visualization functions, capable of generating trend curves and statistical charts for operating parameters. Advanced analysis functions support multi-data correlation analysis, helping to discover the inherent relationships between operating parameters. All query operations are recorded in the audit log, ensuring the traceability of data access.

[0054] Log data is also used for system performance evaluation and optimization. By analyzing historical operating data, the system can identify operating patterns and optimize control parameters. Analysis of abnormal operating data helps improve fault diagnosis algorithms and enhance system reliability. Statistical results from long-term operating data provide a basis for equipment maintenance and upgrades, extending equipment lifespan. The operating log construction unit implements strict data security management. All log data is stored encrypted, access permissions are managed hierarchically, and critical operations require multi-factor authentication. Data backup employs an incremental backup strategy, with regular backup integrity verification. The system also establishes a data recovery mechanism to ensure rapid recovery of operating data in case of unforeseen circumstances, guaranteeing continuous and stable system operation.

[0055] The long-term storage and management of log data adheres to industry standards. The system automatically generates operational reports, meeting environmental regulatory requirements. All recorded data is available for third-party auditing, ensuring the transparency and compliance of system operation. This comprehensive log management system provides reliable data support for the optimized operation of the entire waste gas treatment system.

[0056] 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.

[0057] 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 high-efficiency treatment system for industrial organic waste gas using a catalytic combustion unit, characterized in that, It includes an exhaust gas parameter acquisition module, a combustion risk analysis module, an operating condition optimization module, and a feedback execution module; the exhaust gas parameter acquisition module acquires real-time data on the composition concentration of industrial organic waste gas, inlet flow rate, and temperature distribution data of the catalytic combustion unit; the combustion risk analysis module calculates the unburned risk characteristic value of the current combustion condition based on the composition concentration data and inlet flow rate data; The operating condition optimization module generates an optimized operating parameter set for the catalytic combustion unit based on the unburned combustion risk characteristic value; the feedback execution module adjusts the operating state of the catalytic combustion unit according to the optimized operating parameter set.

2. The industrial organic waste gas high-efficiency treatment system using a catalytic combustion unit according to claim 1, characterized in that, The combustion risk analysis module includes a dynamic cycle adjustment unit; the dynamic cycle adjustment unit retrieves a combustion cycle conversion table, determines a first benchmark control cycle based on the matching result between the remaining processing time and the combustion cycle conversion table; obtains the types and quantities of exhaust gas components, and determines a second benchmark control cycle based on the mapping relationship between the types and quantities and the combustion adjustment coefficient; subtracts the second benchmark control cycle from the first benchmark control cycle to obtain the actual control cycle; wherein, the remaining processing time in the combustion cycle conversion table is negatively correlated with the first benchmark control cycle.

3. The industrial organic waste gas high-efficiency treatment system using a catalytic combustion unit according to claim 2, characterized in that, The dynamic cycle adjustment unit also calls the equipment complexity conversion table; the acquisition of the types and quantities of exhaust gas components includes: determining a first adjustment amount based on the mapping relationship between the types and quantities and the combustion adjustment coefficient; counting the number of catalytic reaction layers in the catalytic combustion unit, and determining a second adjustment amount based on the correspondence between the number of catalytic reaction layers and the equipment complexity conversion table; and using the sum of the first adjustment amount and the second adjustment amount as the second benchmark control cycle.

4. The industrial organic waste gas high-efficiency treatment system using a catalytic combustion unit according to claim 1, characterized in that, The combustion risk analysis module also includes a risk classification and determination unit; the risk classification and determination unit compares the unburned risk characteristic value with the combustion risk threshold reference value; if the unburned risk characteristic value exceeds the first risk classification threshold, it is determined to be a high-risk condition. If the unburned risk characteristic value is between the first risk classification threshold and the second risk classification threshold, it is determined to be a medium-risk operating condition. If the unburned risk characteristic value is lower than the second risk classification threshold, it is determined to be a low-risk operating condition.

5. The industrial organic waste gas high-efficiency treatment system using a catalytic combustion unit according to claim 4, characterized in that, The operating condition optimization module includes a phase matching engine; the phase matching engine receives the operating condition risk level output by the risk classification determination unit and the actual control cycle output by the dynamic cycle adjustment unit; The phase offset coefficient is matched according to the risk level of the operating condition, and the product of the actual control cycle and the phase offset coefficient is used as the optimized response cycle of the catalytic combustion unit.

6. The industrial organic waste gas high-efficiency treatment system employing a catalytic combustion unit according to claim 5, characterized in that, The operating condition optimization module also includes a multi-parameter collaborative correction unit; the multi-parameter collaborative correction unit acquires real-time temperature distribution data of the catalytic combustion unit and calculates the temperature dispersion index; based on the compensation relationship between the temperature dispersion index and the optimized response cycle, it generates a corrected optimized response cycle; and inputs the corrected optimized response cycle into the exhaust gas treatment scheme generation unit.

7. The industrial organic waste gas high-efficiency treatment system employing a catalytic combustion unit according to claim 6, characterized in that, The waste gas treatment scheme generation unit generates at least two waste gas treatment candidate schemes based on the corrected optimized response cycle and component concentration data; each waste gas treatment candidate scheme includes the temperature setpoint of the catalytic combustion unit, the air intake flow rate adjustment range, and the afterburning time parameters.

8. The industrial organic waste gas high-efficiency treatment system using a catalytic combustion unit according to claim 7, characterized in that, The operating condition optimization module also includes an entropy weight decision analysis unit; the entropy weight decision analysis unit retrieves the historical operating status dataset of the catalytic combustion unit; calculates the state switching interference entropy value of each waste gas treatment candidate scheme based on the historical operating status dataset; and uses the weighted sum of the state switching interference entropy value and the temperature dispersion index as the scheme execution priority parameter.

9. The industrial organic waste gas high-efficiency treatment system using a catalytic combustion unit according to claim 8, characterized in that, The feedback execution module includes an optimal solution execution unit; the optimal solution execution unit selects the exhaust gas treatment candidate solution with the lowest execution priority parameter, and drives the control valve group and heater array of the catalytic combustion unit according to the temperature setpoint, air flow rate adjustment range and combustion time parameters of the exhaust gas treatment candidate solution.

10. The industrial organic waste gas high-efficiency treatment system employing a catalytic combustion unit according to claim 1, characterized in that, The feedback execution module also includes an operation log construction unit; the operation log construction unit records the real-time data acquired by the exhaust gas parameter acquisition module, the unburned risk characteristic value output by the combustion risk analysis module, and the exhaust gas treatment candidate scheme parameters executed by the optimal scheme execution unit, and generates the operation status log data of the catalytic combustion unit.

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