Treatment system and treatment method for chemical production waste gas

Abstract

The invention discloses a treatment system and a treatment method for chemical production waste gas, and relates to the technical field of industrial waste gas treatment. The system comprises a waste gas collection unit, a pretreatment unit, a multi-stage purification unit and an intelligent control unit. The intelligent control unit monitors data through a sensor network, the data processing and analysis module evaluates the processing effect and predicts the trend, the intelligent decision and adjustment module optimizes the parameters of each unit in sequence, and the remote monitoring and alarm module monitors and alarms in real time. The system can efficiently treat waste gas, realizes automatic intelligent control, ensures the stable treatment effect, reduces the risk of environmental pollution, and is widely applied to the field of chemical production waste gas treatment.

Description

Technical Field

[0001] The present invention belongs to the technical field of industrial waste gas treatment, and particularly relates to a treatment system and method for waste gas in chemical production. Background Art

[0002] A large amount of waste gas is generated during the chemical production process, which contains various harmful substances, such as organic compounds, acidic gases, alkaline gases, etc. If these waste gases are directly discharged, they will cause serious pollution to the atmospheric environment and endanger human health and ecological balance.

[0003] Currently, common waste gas treatment technologies include adsorption, combustion, biological treatment, etc., but traditional treatment systems have many problems. For example, the lack of collaborative optimization among treatment units makes it impossible to flexibly adjust parameters according to the real-time state of waste gas, resulting in unstable treatment efficiency; some systems have low automation levels and rely on manual experience for operation, making it difficult to accurately control the treatment process; and they have poor adaptability to changes in waste gas composition and concentration, and are prone to situations where the treatment fails to meet the standards or resources are wasted. Summary of the Invention

[0004] In view of the above problems, the present invention provides a treatment system and method for waste gas in chemical production. The system includes a waste gas collection unit, a pretreatment unit, a multi-stage purification unit, and an intelligent control unit, realizing the efficient and intelligent treatment of waste gas.

[0005] To solve the above technical problems, the present invention is realized through the following technical solutions:

[0006] The present invention provides a treatment system for waste gas in chemical production, comprising:

[0007] A waste gas collection unit for collecting waste gas in chemical production;

[0008] A pretreatment unit for performing dust removal and temperature reduction pretreatment on the waste gas;

[0009] A multi-stage purification unit for performing multi-stage purification on the waste gas by using a variety of different purification technologies;

[0010] An intelligent control unit, comprising:

[0011] A sensor network arranged in the waste gas collection, pretreatment, and purification units to real-time monitor waste gas-related parameters;

[0012] A data processing and analysis module for receiving sensor data, performing real-time processing and analysis, evaluating the current waste gas treatment effect, and predicting future change trends;

[0013] The intelligent decision-making and adjustment module automatically adjusts various parameters in the waste gas treatment process according to the output results of the data processing and analysis module, including but not limited to gas flow rate, purifying agent dosage, and equipment operation time;

[0014] The remote monitoring and alarm module provides a remote monitoring interface, allowing operators to monitor the waste gas treatment process in real time and automatically alarm in case of abnormalities or failures;

[0015] The waste gas collection unit, pretreatment unit, and multi-stage purification unit all receive control signals from the intelligent control unit and make corresponding adjustments according to the control signals to ensure the high efficiency of the entire waste gas treatment process.

[0016] As a preferred technical solution of the present invention, the waste gas collection unit uses a large-flow, high-negative-pressure fan to collect waste gas, the rotation speed is adjustable, and its operating parameters are regulated by the intelligent control unit according to the system state. The fan speed regulation range is 500 - 2000 revolutions per minute.

[0017] As a preferred technical solution of the present invention, the pretreatment unit uses a pulse bag filter for dust removal and a water-cooled heat exchanger for temperature reduction. The cooling water circulation flow rate is 5 - 20 cubic meters per hour and is automatically adjusted by the intelligent control unit according to the waste gas inlet temperature. The intelligent control unit dynamically adjusts the operating parameters of the pretreatment unit according to the feedback information of the multi-stage purification unit to ensure that the waste gas outlet temperature is stable at 40 - 60 °C.

[0018] As a preferred technical solution of the present invention, the multi-stage purification unit includes at least two of an activated carbon adsorption unit, a biological trickling filter unit, a catalytic oxidation unit, and a non-thermal plasma unit. The purification parameters of each unit can be automatically adjusted and work in coordination according to the instructions of the intelligent control unit. The intelligent control unit dynamically optimizes parameters such as the purification sequence, duration, and intensity according to the sensor network and the results of the data processing and analysis module.

[0019] As a preferred technical solution of the present invention, the specific working steps of the data processing and analysis module of the intelligent control unit are as follows:

[0020] Data collection step: Collect raw data from the sensor network in the waste gas collection, pretreatment, and purification units;

[0021] Data verification step: Verify the collected data to ensure the accuracy and integrity of the data, check the calibration status of the sensors, the compliance of the sampling process, and the consistency of the data, remove outliers or missing data, or perform corresponding data filling;

[0022] Data preprocessing step: Clean the data, remove noise and redundant information, and convert the raw data into standard units or ratios for subsequent analysis;

[0023] Data fusion step: Data from different sensors is fused to form a new data set to obtain more comprehensive monitoring information and improve the accuracy and reliability of the data;

[0024] Data analysis step: Build a processing large model, input the data set into the processing large model for intelligent analysis and judgment, and output the analysis results.

[0025] As a preferred technical solution of the present invention, in the data fusion step, the following is adopted: an improved algorithm based on the evidence theory, and its basic probability assignment function is:

[0026]

[0027] where m(A) is the basic probability assignment, m i (A) is the basic probability assignment of the i-th sensor, A is a subset in the recognition framework, a is an adjustment factor, and its value range is 0.1 - 0.5. k(A) is a function related to conflict, which is used to handle the conflict situation of sensor data and improve the accuracy of data fusion.

[0028]

[0029] As a preferred technical solution of the present invention, the intelligent decision-making and adjustment module, when working specifically, the steps are as follows:

[0030] Step 1: Receive the output results of the data processing and analysis module, including monitoring results, processing effect evaluation, warning and alarm information, and decision support information;

[0031] Step 2: Evaluate the current processing effect using the processing efficiency index, and predict the future change trend of pollutant concentration using a time series prediction model based on historical data and current data;

[0032] Step 3: According to the evaluation results and prediction trends, automatically adjust the parameters in the waste gas treatment process to achieve the optimal processing effect;

[0033] Step 3.1: When the processing efficiency is lower than the set threshold, automatically adjust the gas flow according to the change of pollutant concentration, and the flow adjustment range is ±20%;

[0034] Step 3.2: For the activated carbon adsorption unit, automatically adjust the dosage of the purifying agent according to the saturation of the adsorption bed, and the basis for the dosage adjustment is the difference between the remaining adsorption capacity of the adsorption bed and the expected adsorption amount;

[0035] Step 3.3: For the catalytic oxidation unit, automatically adjust the equipment operation time according to the reaction temperature and pollutant concentration, and the operation time adjustment range is ±30 minutes;

[0036] Step 3.4. In the adjustment process, a proportional-integral-derivative (PID) control algorithm or a model predictive control (MPC) algorithm is adopted to ensure the accuracy and stability of parameter adjustment;

[0037] Step 4. When warning and alarm messages appear, corresponding emergency treatment measures are automatically triggered to prevent environmental pollution accidents;

[0038] Step 4.1. When the concentration of a certain pollutant in the waste gas exceeds the set warning value, the intelligent control unit issues a warning signal and simultaneously starts the standby purification equipment or increases the treatment capacity of the existing purification equipment;

[0039] Step 4.2. When the pollutant concentration exceeds the alarm value, the relevant production processes are immediately stopped, the emergency emission treatment system is started, the waste gas is introduced into the emergency treatment device for treatment, and at the same time, alarm messages are sent to relevant personnel.

[0040] As a preferred technical solution of the present invention, the sensor network of the intelligent control unit is arranged by comprehensively considering key positions, distribution, priority sorting, and environmental adaptability, and has data correction measures. The data correction measures include, but are not limited to, zero-point calibration, multi-point calibration, data fusion and verification, algorithm optimization, and manual review and intervention. The intelligent control unit can automatically adjust the execution frequency and parameters of the data correction measures according to the data accuracy requirements.

[0041] The present invention also provides a method for treating waste gas from chemical production, based on the above-mentioned waste gas treatment system for chemical production.

[0042] Step 1. The waste gas generated in the chemical production process is collected by the waste gas collection unit;

[0043] Step 2. The waste gas enters the pretreatment unit, first passes through a pulse bag filter for dust removal, and then passes through a water-cooled heat exchanger for temperature reduction. The circulating flow rate of the cooling water is automatically adjusted by the intelligent control unit according to the inlet temperature of the waste gas;

[0044] Step 3. The waste gas enters the multi-stage purification unit and is purified by passing through at least two of the activated carbon adsorption unit, biological trickling filter unit, catalytic oxidation unit, and low-temperature plasma unit in sequence or in parallel according to the composition and concentration of the waste gas. The purification parameters of each unit are automatically adjusted by the intelligent control unit according to the monitoring data of the sensor network and the results of the data processing and analysis module;

[0045] Step 4. During the waste gas treatment process, the intelligent control unit monitors the relevant parameters of the waste gas in real time and automatically adjusts the parameters in the waste gas treatment process according to the monitoring results to achieve the optimal treatment effect;

[0046] Step Five: When an abnormality or failure occurs in the waste gas treatment process, the remote monitoring and alarm module automatically alarms and triggers corresponding emergency treatment measures.

[0047] As a preferred technical solution of the present invention, the following steps are further included:

[0048] Before waste gas treatment, perform component analysis on the waste gas to determine the types and concentrations of the main pollutants in the waste gas;

[0049] According to the waste gas component analysis results, the intelligent control unit automatically selects the most suitable purification technology and purification sequence;

[0050] During the waste gas treatment process, regularly maintain and calibrate the purification equipment and sensors to ensure their normal operation and accuracy;

[0051] Collect and save the relevant data during the waste gas treatment process for subsequent analysis and optimization.

[0052] The present invention has the following beneficial effects:

[0053] Efficient treatment and intelligent optimization: The multi-stage purification unit combines multiple purification technologies, and the intelligent control unit adjusts the parameters of each unit in real time according to the sensor data to ensure that the treatment process is always in an efficient state, significantly improving the waste gas treatment efficiency and purification effect.

[0054] Precise control and stable operation: Through the data processing and analysis module, precise analysis of a large amount of monitoring data provides a reliable basis for intelligent decision-making, making the adjustment of the operating parameters of each unit more precise, ensuring the stable operation of the entire treatment system, and reducing fluctuations and failures.

[0055] Enhanced adaptability and emergency response ability: It can automatically select the appropriate purification technology and sequence according to the changes in the waste gas composition and concentration. At the same time, it has a perfect early warning and emergency treatment mechanism to effectively respond to various abnormal situations, prevent environmental pollution accidents, and reduce the impact on the environment.

[0056] Of course, it is not necessary for any product implementing the present invention to achieve all the above-mentioned advantages simultaneously. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for describing the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0058] Figure 1 It is a schematic structural diagram of the system in the present invention;

[0059] Figure 2 It is a schematic diagram of the step - by - step process when the data processing and analysis module in the system of the present invention works specifically;

[0060] Figure 3 It is a schematic diagram of the step - by - step process when the intelligent decision - making and adjustment module in the system of the present invention works specifically. Specific embodiments

[0061] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts belong to the scope of protection of the present invention.

[0062] Embodiment 1

[0063] As Figure 1 shown: The present invention discloses a treatment system for waste gas in chemical production, including:

[0064] An exhaust gas collection unit, which is used to centrally collect the waste gas generated in the chemical production process through a high - efficiency suction device to ensure that the waste gas does not leak and reduce environmental pollution; the high - efficiency suction device uses a large - flow, high - negative - pressure fan, the blade material of the fan is a corrosion - resistant high - strength alloy material, and its rotation speed can be adjusted within the range of 500 - 2000 revolutions per minute to meet the waste gas collection requirements under different working conditions; the suction pipeline is made of acid - and alkali - resistant rubber and stainless steel composite material with good sealing performance, and the pipeline joints are fastened by sealing rubber rings and flanges to ensure no waste gas leakage in a high - negative - pressure environment; and the operating parameters of the exhaust gas collection unit are adjusted in real time by the intelligent control unit according to the overall system state;

[0065] A pretreatment unit, which uses advanced dust removal and temperature reduction technologies to pretreat the waste gas, remove large - particle substances in the waste gas and reduce the temperature, providing favorable conditions for subsequent purification steps; the dust removal technology uses a pulse bag filter, the bag material is a high - temperature - resistant and antistatic polytetrafluoroethylene - coated needle felt, and the filtration accuracy can reach 5 microns; the bags are regularly back - blown and cleaned by pulse solenoid valves, the back - blow pressure is 0.3 - 0.6 MPa, and the cleaning cycle can be automatically adjusted according to the dust concentration in the waste gas and is controlled by the intelligent control unit; the temperature reduction technology uses a water - cooled heat exchanger, the heat exchange tube material is copper alloy, the internal cooling water circulation flow rate is 5 - 20 cubic meters per hour, and the intelligent control unit automatically adjusts the cooling water flow rate according to the waste gas inlet temperature to ensure that the waste gas outlet temperature is stable at 40 - 60 °C; the intelligent control unit dynamically adjusts the operating parameters of the pretreatment unit according to the feedback information of the multi - stage purification unit;

[0066] Multi-stage purification unit: Design a multi-stage purification unit according to the composition and concentration of the waste gas. Each stage of the purification unit adopts different treatment technologies, such as activated carbon adsorption, biotrickling filtration, catalytic oxidation, non-thermal plasma, etc., to ensure comprehensive and efficient purification of the waste gas. The activated carbon adsorption unit uses columnar activated carbon with an iodine value of not less than 800 mg / g. The filling amount is determined according to the waste gas flow rate and pollutant concentration, ranging from 1 to 5 cubic meters, and a regeneration program is provided. The regeneration uses hot air desorption method, with a desorption temperature of 120 - 150 °C and a desorption time of 2 - 6 hours. The biotrickling filtration unit uses a special biological packing material, which consists of polyurethane foam and microbial inoculum. The microbial inoculum is screened and cultured for specific pollutants in chemical industrial waste gas. The spraying liquid flow rate of the biotrickling filtration unit is 0.5 - 2 cubic meters per hour, and the spraying liquid uses an aqueous solution added with nutrients. The nutrient concentration is automatically adjusted according to the growth requirements of microorganisms. The catalytic oxidation unit uses a noble metal catalyst supported on a honeycomb ceramic carrier, with the active component content of the catalyst being 0.5% - 2%. The reaction temperature is controlled at 200 - 400 °C, and the heating power is automatically adjusted by the intelligent control unit according to the concentration and type of pollutants in the waste gas. The non-thermal plasma unit uses a dielectric barrier discharge plasma generator, with the discharge electrode spacing of 5 - 15 mm, the discharge voltage of 10 - 30 kV, and the frequency of 5 - 20 kHz. The treatment time is automatically adjusted within 1 - 10 seconds according to the waste gas flow rate and pollutant concentration. Each purification unit works in coordination according to the instructions of the intelligent control unit. The intelligent control unit dynamically optimizes parameters such as the purification sequence, purification duration, and purification intensity of the multi-stage purification unit based on the monitoring data of the sensor network and the results of the data processing and analysis module.

[0067] The intelligent control unit is the "brain" of the entire waste gas treatment system. It is responsible for real-time monitoring, analysis, and regulation of the operating status of the entire system. The intelligent control unit includes the following key parts:

[0068] Sensor network: The sensors in the sensor network use high-precision and high-sensitivity sensor elements. For example, the gas composition sensor uses an electrochemical sensor or an infrared sensor, with a concentration measurement accuracy of up to ±1 ppm. The temperature sensor uses a platinum resistance thermometer with an accuracy of ±0.1 °C. The humidity sensor uses a capacitive humidity sensor with an accuracy of ±2% RH. The sampling frequency of the sensors is 1 - 10 seconds per time, which can be adjusted by the intelligent control unit according to actual needs.

[0069] Data processing and analysis module: Receives the data transmitted by the sensor network and performs real-time processing and analysis. This module checks, cleans, fuses, and intelligently analyzes and judges the data to evaluate the current waste gas treatment effect and predict future change trends.

[0070] Intelligent Decision-making and Adjustment Module: According to the output results of the data processing and analysis module, automatically adjust various parameters in the waste gas treatment process, such as gas flow rate, dosage of purification agent, equipment operation time, etc. Advanced control algorithms are used in the adjustment process, such as proportional-integral-derivative (PID) control algorithm or model predictive control (MPC) algorithm, to ensure the accuracy and stability of parameter adjustment.

[0071] Remote Monitoring and Alarm Module: Provide a remote monitoring interface to allow operators to monitor the waste gas treatment process in real time. When an abnormality or failure occurs, this module will automatically alarm and trigger corresponding emergency treatment measures to prevent environmental pollution accidents.

[0072] In summary, the waste gas treatment system provided by the present invention for chemical production has the characteristics of high efficiency, intelligence, and stability. Through the precise regulation of the intelligent control unit and the synergistic effect of various purification technologies, this system can effectively treat the waste gas from chemical production and meet the requirements of relevant national emission standards.

[0073] Embodiment 2

[0074] As Figure 2 shown: This embodiment is further refined and optimized based on Embodiment 1, especially in the workflow of the data processing and analysis module of the intelligent control unit. The following is a detailed description of this embodiment:

[0075] Workflow of the data processing and analysis module of the intelligent control unit:

[0076] Data collection step: Widely collect raw data from the sensor network in the waste gas collection, pretreatment, and purification unit. This data covers multiple key parameters such as waste gas flow rate, temperature, pressure, concentration, etc.

[0077] Data verification step: Strictly verify the collected raw data to ensure its accuracy and integrity. This includes checking whether the calibration status of the sensor is good, whether the sampling process complies with the regulations, and whether the data is consistent.

[0078] During the verification process, outliers or missing data will be identified and removed. For missing data, appropriate methods will be used to fill it to ensure the integrity of the data set.

[0079] Data preprocessing step: Clean the verified data to remove noise and redundant information. This helps to improve the quality and analysis efficiency of the data. Convert the raw data to standard units or ratios for subsequent unified analysis and comparison.

[0080] An improved algorithm based on the evidence theory is adopted in the data fusion step, and its basic probability assignment function is:

[0081] Among them, m(A) is the basic probability assignment, and m i (A) is the basic probability assignment of the i-th sensor, A is a subset in the recognition framework, a is an adjustment factor, and its value range is 0.1 - 0.5. k(A) is a function related to conflict, which is used to handle the conflict situation of sensor data and improve the accuracy of data fusion.

[0082]

[0083] An improved algorithm based on the evidence theory is used to fuse data from different sensors. This algorithm can comprehensively consider the information of multiple sensors and form a more comprehensive monitoring data set.

[0084] In the data fusion process, the basic probability assignment function is used to calculate the credibility of each sensor data. This function is the core part of the data fusion step and is used to calculate the basic probability assignment of each sensor data. By comprehensively considering factors such as the reliability of the sensor and the data conflict situation, the credibility of each sensor data can be obtained, and the data fusion result can be optimized through the adjustment factor and the conflict-related function. The value range of the adjustment factor is 0.1 - 0.5, which is used to adjust the weight between different sensor data. In practical applications, the reliability of different sensors may vary, so the adjustment factor is needed to reflect this difference. The conflict function is used to handle the conflict situation between sensor data. In the data fusion process, if there are large differences or conflicts between the data of different sensors, the conflict-related function can be used to comprehensively consider the information of multiple sensors, thereby improving the accuracy and reliability of data fusion.

[0085] Data analysis step: Build a large processing model that can process large-scale data sets and perform intelligent analysis and judgment. Input the fused data set into the large processing model for in-depth analysis and output the analysis results. These analysis results can provide strong support for the optimization of the waste gas treatment process.

[0086] In summary, in this embodiment, in-depth optimization has been carried out on the data processing and analysis module of the intelligent control unit. By adopting an improved algorithm based on the evidence theory to fuse data from different sensors, the accuracy and reliability of data fusion have been improved. This helps to provide more accurate and comprehensive information support for the optimization of the waste gas treatment process.

[0087] Embodiment Three

[0088] As Figure 3 shown: Based on Embodiment One, the difference in this embodiment is:

[0089] The intelligent decision-making and adjustment module, the specific working steps are as follows:

[0090] Step 1: Receive the output results of the data processing and analysis module, including monitoring results, treatment effect evaluation, early warning and alarm information, and decision-making support information. The intelligent decision-making and adjustment module and the data processing and analysis module perform data transmission through a high-speed data bus, and the data transmission rate is not less than 100 Mbps to ensure the real-time and accuracy of data, enabling decision-making adjustments to respond promptly to the dynamic changes of the waste gas treatment system.

[0091] Step 2: Evaluate the current treatment effect using the treatment efficiency index. The treatment efficiency index is the pollutant removal rate, and its calculation formula is: Removal rate = (Inlet pollutant concentration - Outlet pollutant concentration) / Inlet pollutant concentration × 100%. Use a time series prediction model to predict the future pollutant concentration change trend based on historical data and current data. The prediction time span is 1 - 24 hours, and the prediction accuracy requirement is ±10%. When constructing the time series prediction model, use the autoregressive integrated moving average model (ARIMA), and determine parameters such as the autoregressive order, moving average order, and differencing order of the model through the analysis of historical data to improve the accuracy and reliability of the prediction. For example, for the prediction of sulfur dioxide concentration in the waste gas of a certain chemical enterprise, first perform a stationarity test and differencing processing on the sulfur dioxide concentration data per hour in the past week to determine the appropriate ARIMA model parameters, so as to effectively predict the sulfur dioxide concentration change trend within the next 24 hours.

[0092] Step 3: Automatically adjust various parameters in the waste gas treatment process according to the evaluation results and prediction trends to achieve the optimal treatment effect.

[0093] Step 3.1: When the treatment efficiency is lower than the set threshold (such as 90%), automatically adjust the gas flow according to the change of pollutant concentration. The flow adjustment range is ±20%. When adjusting the gas flow, use the proportional-integral-derivative (PID) control algorithm. By continuously comparing the deviation between the set flow value and the actual flow value, calculate the outputs of the proportional term, integral term, and derivative term, so as to accurately adjust the speed of the fan and achieve precise control of the gas flow. For example, when it is detected that the treatment efficiency of the waste gas treatment system drops to 85% at a certain moment and the concentration of a certain main pollutant increases, the PID controller calculates that a 15% increase in gas flow is required according to the deviation, and increases the fan speed through the control signal to increase the gas flow accordingly, thereby improving the treatment effect.

[0094] Step 3.2: For the activated carbon adsorption unit, automatically adjust the dosage of the purification agent according to the saturation degree of the adsorption bed. The basis for dosage adjustment is the difference between the remaining adsorption capacity and the expected adsorption amount of the adsorption bed. A pressure sensor and a concentration sensor are installed in the activated carbon adsorption bed. By monitoring the pressure difference before and after the adsorption bed and the change in the concentration of pollutants in the waste gas, the saturation degree of the adsorption bed is calculated. When the saturation degree reaches a certain threshold (such as 80%), the intelligent decision-making and adjustment module calculates the amount of activated carbon that needs to be supplemented according to a pre-set algorithm, combined with the current waste gas flow rate and pollutant concentration, and automatically starts the activated carbon addition device for addition. For example, for the activated carbon adsorption unit treating benzene-containing waste gas, when the saturation degree of the adsorption bed reaches 80%, and the waste gas flow rate is 100m 3 / h, and the benzene concentration is 50mg / m 3 ³, it is calculated that 20 kg of activated carbon needs to be added according to the difference between the remaining adsorption capacity and the expected adsorption amount of the adsorption bed. The addition device evenly adds the activated carbon into the adsorption bed according to the set procedure.

[0095] Step 3.3: For the catalytic oxidation unit, automatically adjust the equipment operation time according to the reaction temperature and pollutant concentration. The adjustment range of the operation time is ±30 minutes. The catalytic oxidation unit is equipped with a temperature sensor and a gas composition sensor to monitor the reaction temperature and the concentration of pollutants in the waste gas in real time. When the reaction temperature deviates from the set range (such as 200 - 400 °C) or the pollutant concentration changes significantly, the intelligent decision-making and adjustment module adopts the model predictive control (MPC) algorithm. According to the dynamic model of the system, it predicts the treatment effect under different operation times and selects the optimal operation time adjustment plan. For example, when the concentration of nitrogen oxides in the waste gas suddenly increases and the reaction temperature drops slightly, the MPC algorithm comprehensively considers the influence of temperature change on the catalytic reaction and the change of nitrogen oxide concentration on the treatment requirements, predicts that extending the operation time by 20 minutes can make the treatment effect of nitrogen oxides reach the best, and then automatically adjusts the operation time of the catalytic oxidation unit.

[0096] Step 3.4: The proportional-integral-derivative (PID) control algorithm or the model predictive control (MPC) algorithm is used in the adjustment process to ensure the accuracy and stability of parameter adjustment; when using the PID control algorithm, according to different control objects (such as gas flow rate, dosage of purification agent, etc.), carefully adjust parameters such as the proportional coefficient, integral time constant, and derivative time constant. Through a large number of experiments and simulations for optimization, the best parameter combination is determined to achieve a fast and stable control response. For the model predictive control (MPC) algorithm, an accurate dynamic model of the waste gas treatment system is established, including the reaction kinetics model and heat and mass transfer model of each purification unit, etc. Advanced optimization algorithms are used to solve the control sequence, and under the premise of meeting the system constraints (such as equipment operation range, treatment effect requirements, etc.), the optimal adjustment of parameters is realized.

[0097] Step 4: When warning and alarm messages occur, automatically trigger corresponding emergency treatment measures to prevent environmental pollution accidents from occurring;

[0098] Step 4.1: When the concentration of a certain pollutant in the waste gas exceeds the set warning value (such as 80% of the national standard), the intelligent control unit issues a warning signal and simultaneously starts the standby purification equipment or increases the treatment capacity of the existing purification equipment. The warning system is linked with the enterprise's production management system. When a warning signal is issued, not only is the warning information displayed in the control room, but relevant production departments are also automatically notified to take corresponding emission reduction measures, such as adjusting production process parameters and reducing the amount of waste gas generated. At the same time, the standby purification equipment (such as a standby activated carbon adsorption tower or a low-temperature plasma generator) is quickly started to work in coordination with the existing purification equipment to improve the waste gas treatment capacity. For example, when the concentration of VOCs in the waste gas exceeds the warning value, the intelligent control unit, on the one hand, issues a warning signal, and on the other hand, starts the standby low-temperature plasma generator to jointly treat the waste gas with the original activated carbon adsorption unit and catalytic oxidation unit to reduce the VOCs emission concentration.

[0099] Step 4.2: When the pollutant concentration exceeds the alarm value (such as the national standard), immediately stop the relevant production process, start the emergency emission treatment system, introduce the waste gas into the emergency treatment device (such as an emergency activated carbon adsorption tank) for treatment, and at the same time send an alarm message to relevant personnel. The emergency emission treatment system has an independent power source and control system to ensure that it can be quickly started in case of main system failure or serious pollutant concentration exceeding the standard. The alarm message is sent through multiple methods, including sending text messages to enterprise management personnel and environmental protection department supervisors, and at the same time setting up audible and visual alarms in the factory area to remind on-site staff to take protective measures in time. For example, when the concentration of sulfur dioxide in the waste gas exceeds the national standard, the intelligent control unit immediately stops the production process that generates sulfur dioxide, starts the emergency emission treatment system, introduces the waste gas into the emergency activated carbon adsorption tank for temporary adsorption treatment, and at the same time sends text message alarms to the general manager of the enterprise and the person in charge of the environmental protection department, and an ear-piercing audible and visual alarm signal sounds in the factory area.

[0100] In this embodiment, through the precise control of the waste gas treatment process parameters by the intelligent decision-making and adjustment module and the effective implementation of emergency treatment measures, the intelligent level of the chemical production waste gas treatment system and the ability to respond to emergencies are significantly improved, ensuring that the waste gas treatment effect is stably up to standard and minimizing environmental pollution to the greatest extent.

[0101] Embodiment 4

[0102] Based on Embodiment 3, the difference in this embodiment is that:

[0103] The sensor network layout of the intelligent control unit comprehensively considers key positions, distribution, priority ranking, and environmental adaptability, and has data correction measures. The data correction measures include, but are not limited to, zero-point calibration, multi-point calibration, data fusion and verification, algorithm optimization, and manual review and intervention. The intelligent control unit can automatically adjust the execution frequency and parameters of the data correction measures according to the data accuracy requirements.

[0104] In terms of the sensor network layout, for the layout of key positions, high-precision sensors are set before and after the key treatment links of the waste gas treatment system, such as the inlet and outlet of the pretreatment unit, the connection points of different purification technology units in the multi-stage purification unit, etc., in order to accurately monitor the key parameter changes of the waste gas during the generation and treatment process. The distributed layout ensures that sensors are evenly distributed throughout the chemical production workshop and the waste gas treatment plant area at a certain interval and layout, avoiding monitoring blind spots and comprehensively covering possible waste gas leakage points and diffusion areas. The priority ranking divides the priority levels of sensors at different positions according to factors such as the toxicity of pollutants, treatment difficulty, and potential harm to the environment and human health. For example, the highest priority is given to sensors that monitor highly toxic pollutants or are prone to cause serious environmental problems (such as precursors of photochemical smog), and higher-frequency data collection and stricter data processing standards are adopted. In terms of environmental adaptability, considering that the chemical production environment often has harsh conditions such as high temperature, high humidity, and strongly corrosive gases, special protective enclosures and adaptable components are equipped for the sensors. For example, sensors in high-temperature areas are encapsulated with high-temperature-resistant ceramics, a dehumidification device is added or a waterproof and moisture-proof sensor model is selected in high-humidity environments, and for areas with strongly corrosive gases, the sensor housing and contact parts are made of corrosion-resistant alloy materials, and the anti-corrosion coating is maintained regularly.

[0105] In terms of zero-point calibration, the zero-point calibration program is automatically started at a fixed time every day (such as 2 am, when production activities are relatively stable and interference factors are less). For gas composition sensors, pure nitrogen or other standard gases with known zero concentration are introduced, and the sensor records the signal value at this time as the zero-point reference. If the detected signal value deviates from the preset zero-point range (for example, ±0.5 mV), the calibration circuit inside the sensor is automatically adjusted to make the output signal zero. The multi-point calibration is carried out once a week, using standard gas mixtures with different concentration gradients. These standard gas mixtures cover the concentration ranges of common pollutants in the waste gas, and the number of concentration points is not less than 5 (such as low concentration, medium concentration, high concentration, and two intermediate transition concentrations). The sensor is successively exposed to these standard gases, records the corresponding measured values, calculates the calibration coefficient by comparing with the standard values, and updates the calibration parameters of the sensor to ensure accuracy within the entire measurement range.

[0106] In the data fusion and verification stage, a fusion algorithm based on Dempster-Shafer (D-S) evidence theory is adopted. For example, for multiple sensor data measuring the same exhaust gas parameter (such as SO 2 concentration) at the same location or in adjacent areas, different basic probability assignments are first given according to the accuracy, stability, and historical reliability of the sensors. Then, based on the combination rules of D-S evidence theory, the data from multiple sensors are fused to obtain a more comprehensive and reliable concentration value. At the same time, a verification mechanism is set up to verify the rationality of the fused data by comparing with the historical data trend and judging the logical relationship with other relevant parameters (such as exhaust gas flow rate, temperature, etc.). If data anomalies are found (such as a sudden significant increase in the fused SO 2 concentration while there are no obvious changes in the exhaust gas flow rate and production process), a further data review process is initiated, including checking the sensor status and re-collecting data.

[0107] The algorithm optimization is based on the analysis of a large amount of historical data and machine learning techniques. For example, deep learning algorithms are used to learn the change patterns of sensor data and identify the characteristics and rules of data under different working conditions. According to the learning results, the parameters in the data processing algorithm are automatically adjusted, such as the window size of data filtering and the threshold for outlier judgment. When it is found that the data fluctuates greatly and there are many suspected outliers in a certain period, the algorithm automatically increases the data filtering window and adopts a more stringent outlier judgment standard to improve the stability and reliability of the data.

[0108] As the final safeguard measure, when the data processing system detects data anomalies and cannot be resolved through automatic procedures, or when the system receives a manual review instruction from the operator (such as when there is doubt about the data accuracy after equipment maintenance or process adjustment), the relevant data and detailed information on the data processing process are submitted to professional technicians. The technicians conduct a manual review of the data by checking the original data records, sensor calibration records, data processing logs, etc., and combining their professional knowledge and experience. If it is determined that there are errors in the data, the data can be manually corrected or the parameters of the data processing system can be adjusted, and at the same time, the review process and results are recorded for subsequent analysis and optimization of the data processing process.

[0109] The intelligent control unit automatically adjusts the execution frequency and parameters of data correction measures according to the data accuracy requirements. For example, when the system is in a stable operation state and the data accuracy is relatively high (evaluated by comparing with standard samples or analyzing the consistency with historical data), the frequencies of zero-point correction and multi-point correction are appropriately reduced. For instance, the zero-point correction can be adjusted to once every two days, and the multi-point correction to once every two weeks. At the same time, the computing resource input in data fusion and verification is reduced. When the system is in a process adjustment period, equipment maintenance period, or when there are significant changes in environmental conditions (such as large changes in temperature and humidity due to seasonal alternation), the execution frequency of data correction measures is automatically increased, and the intensity of data monitoring and processing is strengthened to ensure that the accuracy and reliability of the data can meet the requirements of waste gas treatment control.

[0110] In this embodiment, through the carefully designed sensor network layout, comprehensive data correction measures, and the flexible regulation of the intelligent control unit on data correction measures, the accuracy and reliability of sensor data are effectively improved, providing a solid data foundation for the precise control and efficient operation of the entire chemical production waste gas treatment system, and further enhancing the adaptability of the system to complex chemical waste gas treatment environments and the stability of treatment effects.

[0111] The present invention also provides a method for treating waste gas in chemical production, specifically including:

[0112] Step 1: Collect the waste gas generated during chemical production through the waste gas collection unit;

[0113] Step 2: The waste gas enters the pretreatment unit, first passes through a pulse bag filter for dust removal, and then through a water-cooled heat exchanger for cooling. The circulating flow rate of the cooling water is automatically adjusted by the intelligent control unit according to the waste gas inlet temperature;

[0114] Step 3: The waste gas enters the multi-stage purification unit and is purified by passing through at least two of the activated carbon adsorption unit, biological trickling filter unit, catalytic oxidation unit, and low-temperature plasma unit in sequence or in parallel according to the waste gas composition and concentration. The purification parameters of each unit are automatically adjusted by the intelligent control unit according to the sensor network monitoring data and the results of the data processing and analysis module;

[0115] Step 4: During the waste gas treatment process, the intelligent control unit monitors the waste gas-related parameters in real time and automatically adjusts the parameters in the waste gas treatment process according to the monitoring results to achieve the optimal treatment effect;

[0116] Step 5: When an abnormality or failure occurs in the waste gas treatment process, the remote monitoring and alarm module automatically alarms and triggers corresponding emergency treatment measures.

[0117] It further includes the following steps:

[0118] Before waste gas treatment, conduct a composition analysis of the waste gas to determine the types and concentrations of the main pollutants in the waste gas;

[0119] Adopt advanced on-line gas analysis instruments, such as Fourier transform infrared spectrometer (FTIR) or gas chromatography-mass spectrometry (GC-MS), to conduct real-time composition analysis of the waste gas. The analysis results are directly transmitted to the intelligent control unit, which selects the most suitable purification technology and purification sequence from the pre-stored treatment plan database according to the types and concentrations of the main pollutants. For example, when it is detected that the main pollutants in the waste gas are high-concentration sulfur dioxide and a small amount of nitrogen oxides, the intelligent control unit preferentially selects a purification plan that combines a catalytic oxidation unit with an alkali solution absorption unit, and determines to carry out catalytic oxidation treatment first and then alkali solution absorption to improve the treatment efficiency and reduce the treatment cost.

[0120] According to the waste gas composition analysis results, the intelligent control unit automatically selects the most suitable purification technology and purification sequence;

[0121] During the waste gas treatment process, regularly maintain and calibrate the purification equipment and sensors to ensure their normal operation and accuracy;

[0122] The maintenance cycle of the purification equipment is determined according to the operating time, treatment load and historical failure data of the equipment. For example, the activated carbon adsorption unit conducts a comprehensive inspection and activated carbon replacement (if necessary) every 1000 hours of operation; the catalytic oxidation unit checks the catalyst activity every 500 hours of operation and conducts catalyst regeneration or replacement every 1000 hours of operation. The calibration cycle of the sensor is determined according to its type and accuracy requirements. Generally, the general gas composition sensor is calibrated once a week, the temperature sensor is calibrated once a month, and the pressure sensor is calibrated once a quarter. The calibration process uses standard gases, standard temperature sources and standard pressure sources, and is operated by professional technicians according to the operating procedures. The calibration data is recorded and uploaded to the intelligent control unit for storage and analysis.

[0123] Collect and save the relevant data during the waste gas treatment process for subsequent analysis and optimization.

[0124] Establish a dedicated data storage server to store all data in the exhaust gas treatment process, including exhaust gas composition, concentration, temperature, humidity, purification equipment operating parameters, sensor data, maintenance records, etc. Use data mining and machine learning technology to regularly analyze these data and explore potential patterns and optimization points in the data. For example, by analyzing the exhaust gas treatment data in different seasons and under different production processes, it is found that due to the high temperature in summer, the cooling efficiency of the water-cooled heat exchanger decreases, resulting in a slight decrease in the exhaust gas treatment effect. Therefore, based on this analysis result, the intelligent control unit automatically increases the circulation flow of cooling water in summer and adjusts the operating parameters of other purification units to compensate for the decrease in cooling efficiency, thereby achieving stable and efficient exhaust gas treatment throughout the year.

[0125] In this embodiment, through the above-mentioned detailed and intelligent waste gas treatment method, it is possible to achieve comprehensive, efficient and precise treatment of chemical production waste gas, effectively cope with various complex waste gas components and operating conditions, and continuously optimize the treatment process, improve the stability and reliability of the system, reduce pollution to the environment, and meet increasingly stringent environmental protection requirements.

[0126] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0127] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A system for treating waste gas from chemical production, characterized in that: include: Waste gas collection unit, used to collect waste gas from chemical production; Pretreatment unit, which performs dust removal and temperature reduction pretreatment on the exhaust gas; Multi-stage purification unit, using a variety of different purification technologies to purify the exhaust gas in multiple stages; Intelligent control unit, including: A sensor network is arranged in the exhaust gas collection, pretreatment and purification units to monitor exhaust gas related parameters in real time; The data processing and analysis module receives sensor data, performs real-time processing and analysis, evaluates the current exhaust gas treatment effect, and predicts future change trends; Intelligent decision-making and adjustment module, which automatically adjusts various parameters in the waste gas treatment process according to the output results of the data processing and analysis module, including but not limited to gas flow, purifier dosage, and equipment operation time; Remote monitoring and alarm module, which provides a remote monitoring interface, allowing operators to monitor the exhaust gas treatment process in real time and automatically alarm when abnormalities or failures occur; The exhaust gas collection unit, pre-treatment unit and multi-stage purification unit all receive control signals from the intelligent control unit, and make corresponding adjustments according to the control signals to ensure the efficiency of the entire exhaust gas treatment process.

2. A system for treating waste gas from chemical production according to claim 1, characterized in that: The exhaust gas collection unit adopts a large-flow, high-negative-pressure fan to collect exhaust gas, the speed of which is adjustable, and its operating parameters are regulated by an intelligent control unit according to the system status, and the fan speed adjustment range is 500-2000 rpm.

3. A system for treating waste gas from chemical production according to claim 1, characterized in that: The pretreatment unit adopts a pulse bag dust collector for dust removal and a water-cooled heat exchanger for cooling. The cooling water circulation flow rate is 5-20 cubic meters per hour, which is automatically adjusted by the intelligent control unit according to the exhaust gas inlet temperature. The intelligent control unit dynamically adjusts the operating parameters of the pretreatment unit according to the feedback information of the multi-stage purification unit to ensure that the exhaust gas outlet temperature is stable at 40-60°C.

4. A system for treating waste gas from chemical production according to claim 3, characterized in that: The multi-stage purification unit includes at least two of an activated carbon adsorption unit, a biological trickling filter unit, a catalytic oxidation unit and a low-temperature plasma unit. The purification parameters of each unit can be automatically adjusted and work together according to the instructions of the intelligent control unit. The intelligent control unit dynamically optimizes its purification sequence, duration, intensity and other parameters according to the results of the sensor network and the data processing and analysis module.

5. A system for treating waste gas from chemical production according to claim 1, characterized in that: The data processing and analysis module of the intelligent control unit specifically works in the following steps: Data collection step: Collect raw data from the sensor network in the exhaust gas collection, pretreatment and purification units; Data verification step: Verify the collected data to ensure the accuracy and completeness of the data, check the calibration status of the sensor, the compliance of the sampling process and the consistency of the data, remove outliers or missing data, or perform corresponding data filling; Data preprocessing steps: clean the data, remove noise and redundant information, and convert the raw data into standard units or ratios for subsequent analysis; Data fusion step: fuse data from different sensors to form a new data set to obtain more comprehensive monitoring information and improve data accuracy and reliability; The data analysis step is to build a large processing model, input the data set into the large processing model for intelligent analysis and judgment, and output the analysis results.

6. A system for treating waste gas from chemical production according to claim 5, characterized in that: The data fusion step adopts: an improved algorithm based on evidence theory is adopted, and its basic probability assignment function is: Among them, m(A) is the basic probability assignment, m i (A) is the basic probability assignment of the i-th sensor, A is the subset in the recognition framework, a is the adjustment factor, and its value range is 0.1-0.

5. k(A) is a conflict-related function used to handle sensor data conflicts and improve data fusion accuracy.

7. A system for treating waste gas from chemical production according to claim 4, characterized in that: The intelligent decision-making and adjustment module specifically works in the following steps: Step 1: Receive the output results of the data processing and analysis module, including monitoring results, treatment effect evaluation, early warning and alarm information, and decision support information; Step 2: Use treatment efficiency indicators to evaluate the current treatment effect, and use time series prediction models based on historical data and current data to predict future pollutant concentration trends; Step 3: Automatically adjust various parameters in the waste gas treatment process according to the evaluation results and predicted trends to achieve the optimal treatment effect; Step 3.1, when the treatment efficiency is lower than the set threshold, the gas flow rate is automatically adjusted according to the change of pollutant concentration, and the flow rate adjustment range is ±20%; Step 3.2, for the activated carbon adsorption unit, the dosage of the purifier is automatically adjusted according to the saturation of the adsorption bed, and the basis for adjusting the dosage is the difference between the remaining adsorption capacity of the adsorption bed and the expected adsorption amount; Step 3.3, for the catalytic oxidation unit, automatically adjust the equipment operation time according to the reaction temperature and pollutant concentration, and the operation time adjustment range is ±30 minutes; Step 3.4: The adjustment process uses a proportional-integral-derivative (PID) control algorithm or a model predictive control (MPC) algorithm to ensure the accuracy and stability of parameter adjustment; Step 4: When early warning and alarm information appears, the corresponding emergency treatment measures are automatically triggered to prevent environmental pollution accidents; Step 4.1: When the concentration of a certain pollutant in the exhaust gas exceeds the set warning value, the intelligent control unit sends out a warning signal and simultaneously starts the backup purification equipment or increases the processing capacity of the existing purification equipment; Step 4.2: When the pollutant concentration exceeds the alarm value, immediately stop the relevant production process, start the emergency emission treatment system, introduce the exhaust gas into the emergency treatment device for treatment, and send an alarm message to relevant personnel.

8. A system for treating waste gas from chemical production according to claim 1, characterized in that: The sensor network layout of the intelligent control unit comprehensively considers key locations, distribution, priority sorting and environmental adaptability, and is equipped with data correction measures. The data correction measures include but are not limited to zero-point correction, multi-point correction, data fusion and verification, algorithm optimization and manual review and intervention. The intelligent control unit can automatically adjust the execution frequency and parameters of the data correction measures according to the data accuracy requirements.

9. A method for treating waste gas from chemical production, based on a system for treating waste gas from chemical production according to claims 1 to 8, characterized in that: Step 1: Collect waste gas generated during chemical production by a waste gas collection unit; Step 2: The exhaust gas enters the pretreatment unit, where it is first dedusted by a pulse bag filter and then cooled by a water-cooled heat exchanger. The cooling water circulation flow is automatically adjusted by the intelligent control unit according to the exhaust gas inlet temperature. Step 3: The waste gas enters a multi-stage purification unit and is purified by passing through at least two of the activated carbon adsorption unit, the bio-trickling unit, the catalytic oxidation unit and the low-temperature plasma unit in sequence or in parallel according to the waste gas composition and concentration. The purification parameters of each unit are automatically adjusted by the intelligent control unit according to the sensor network monitoring data and the results of the data processing and analysis module; Step 4: During the waste gas treatment process, the intelligent control unit monitors the waste gas related parameters in real time, and automatically adjusts the various parameters in the waste gas treatment process according to the monitoring results to achieve the optimal treatment effect; Step 5. When an abnormality or failure occurs in the exhaust gas treatment process, the remote monitoring and alarm module automatically alarms and triggers corresponding emergency treatment measures.

10. A method for treating waste gas from chemical production according to claim 9, characterized in that: The following steps are also included: Before waste gas treatment, the waste gas is analyzed to determine the types and concentrations of the main pollutants in the waste gas; According to the exhaust gas composition analysis results, the intelligent control unit automatically selects the most appropriate purification technology and purification sequence; During the exhaust gas treatment process, the purification equipment and sensors are regularly maintained and calibrated to ensure their normal operation and accuracy; Collect and save relevant data in the exhaust gas treatment process for subsequent analysis and optimization.

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