Dynamic management method and system for industrial waste gas treatment

Abstract

The invention relates to the technical field of waste gas treatment, and particularly discloses a dynamic management method and system for industrial waste gas treatment, and the system comprises a region division module which is used for dividing an adsorption bed layer in adsorption equipment into a plurality of monitoring regions with similar sizes in a waste gas treatment process, by combining waste gas data at a waste gas outlet for coupling analysis, high-quality real-time waste gas concentration data can be obtained after coupling treatment on the basis of diversified data, and then the concentration of the waste gas is determined based on the data and state data of adsorption equipment in the waste gas treatment process. The real-time adsorption saturation of the adsorption equipment can be accurately analyzed, and the data reflects the adsorption saturation of the current activated carbon adsorption bed layer, so that the waste gas collection air volume can be optimized by dynamically adjusting the waste gas collection air volume through the air speed adjusting module subsequently based on the data, and the desorption of attachments is accelerated; the waste gas treatment effect is improved.

Description

Technical Field

[0001] This invention relates to the field of waste gas treatment technology, specifically to a dynamic management method and system for industrial waste gas treatment. Background Technology

[0002] An industrial waste gas treatment system refers to a comprehensive technical management system that uses physical, chemical, or biological methods to purify waste gas generated during industrial production processes, thereby removing or reducing the concentration of pollutants to meet national or local emission standards or environmental capacity requirements.

[0003] In daily use, industrial waste gas treatment systems first use a gas collection device to efficiently capture pollutant waste gas from the source through negative pressure suction technology. Then, a blower adjusts the waste gas collection air volume according to the waste gas generation rate and delivers the waste gas to the adsorption equipment. The activated carbon adsorption bed in the adsorption equipment can adsorb the pollutants in the waste gas, thereby achieving waste gas treatment. Finally, the pollutant concentration of the treated waste gas is analyzed, and it can be discharged after meeting the standards.

[0004] In existing technologies, during the waste gas treatment process, after the activated carbon adsorption bed has been working for a long time, a large amount of pollutants will accumulate on its surface. Since the waste gas collection air volume is generally adjusted based on the waste gas generation rate, if the collection air volume cannot be adjusted in time, the deposits on the activated carbon adsorption bed will not be able to detach, thus affecting the waste gas treatment effect. Summary of the Invention

[0005] The purpose of this invention is to provide a dynamic management method and system for industrial waste gas treatment, solving the following technical problems:

[0006] How to dynamically adjust the exhaust gas collection air volume to accelerate the desorption of adhering substances.

[0007] The objective of this invention can be achieved through the following technical solutions:

[0008] A dynamic management method and system for industrial waste gas treatment, the system comprising:

[0009] The area division module is used to divide the adsorption bed in the adsorption equipment during the waste gas treatment process into multiple monitoring areas of similar size.

[0010] The data acquisition module is used to collect real-time data on the state of the adsorption bed in various areas during the waste gas treatment process, as well as waste gas data at the waste gas outlet.

[0011] The data calculation module is used to perform coupled analysis with the exhaust gas data at the exhaust gas outlet to calculate the real-time exhaust gas concentration data at the exhaust gas outlet.

[0012] The data analysis module is used to analyze the real-time adsorption saturation of the adsorption equipment by combining the real-time exhaust gas concentration data at the exhaust gas outlet with the status data of the adsorption equipment during the exhaust gas treatment process.

[0013] The wind speed adjustment module is used to dynamically adjust the exhaust gas collection air volume based on the real-time adsorption saturation analysis results of the adsorption equipment.

[0014] Furthermore, the calculation process of the data calculation module includes:

[0015] Through formula The actual exhaust gas concentration s at the a-th monitoring time point at the exhaust gas outlet was calculated. a ;

[0016] Where 'a' represents the waste gas treatment status monitoring at fixed time intervals, and nd a The concentration of exhaust gas collected at the a-th monitoring time point at the exhaust gas outlet, ls a Let ls be the exhaust gas velocity at the a-th monitoring time point at the exhaust gas outlet. y For the preset exhaust gas flow rate, ls b For ls a The standard value of f c To define a function, if f c If (x)≥1, then let f c (x) = x, otherwise, let f c (x)=1, sf a gt represents the moisture content in the exhaust gas at the a-th monitoring time point at the exhaust gas outlet. a yc represents the particulate matter content in the exhaust gas at the a-th monitoring time point at the exhaust gas outlet. y θ represents the preset abnormal substance content in the exhaust gas. a The factor representing the impact of the data acquisition equipment's lifespan at the a-th monitoring time point is set based on empirical fitting.

[0017] Furthermore, the analysis process of the data analysis module includes:

[0018] Through formula The influence coefficient t of adsorption saturation at the a-th monitoring time point in the i-th monitoring area was calculated. ai ;

[0019] Where i represents any monitoring area divided by the area division module, and yc a Let yc be the internal and external pressure difference within the adsorption device at the a-th monitoring time point. y For the preset internal and external pressure difference, wd ai Let wd be the temperature of the adsorption bed in the i-th monitoring area at the a-th monitoring time point. y The preset adsorption bed temperature, wd b for wdai Standard value, sd ai Let sd represent the humidity of the adsorption bed in the i-th monitoring area at the a-th monitoring time point. y The preset humidity of the adsorption bed.

[0020] Furthermore, the analysis process of the data analysis module also includes:

[0021] By using the adsorption saturation influence coefficient t at the a-th monitoring time point of all monitoring areas ai Compare t with the preset adsorption saturation influence coefficient threshold respectively. 01 ;

[0022] If all t ai All less than t 01 The system determines that the adsorption saturation of the adsorption bed in the adsorption equipment is low at the monitoring time point, and there is no need to adjust the exhaust gas collection air volume.

[0023] If any t ai Greater than or equal to t 01 The system determined that the adsorption saturation of the adsorption bed in the adsorption equipment was high at the monitoring time point, and that the exhaust gas collection air volume needed to be adjusted.

[0024] Furthermore, the adjustment process of the wind speed adjustment module includes:

[0025] Through formula The fluctuation value p of the adsorption saturation influence coefficient for all monitoring areas at the a-th monitoring time point was calculated. a ;

[0026] Where n is the total number of monitoring areas divided by the area division module. For all t ai The average value.

[0027] Furthermore, the adjustment process of the wind speed adjustment module also includes:

[0028] By measuring the fluctuation value p of the adsorption saturation influence coefficient of all monitoring areas at the a-th monitoring time point a Compared with the preset threshold value of the fluctuation value of the adsorption saturation influence coefficient p 01 Perform a comparison;

[0029] If p a ≥p 01 Then let

[0030] If p a <p 01 Then let

[0031] Furthermore, the adjustment process of the wind speed adjustment module also includes:

[0032] Through formula β a =β y *f m (1+t ai )Calculate the corrected exhaust gas collection air volume β at the a-th monitoring time point. a ;

[0033] Where, β y f is the preset exhaust gas collection air volume. m The adjustment coefficient lookup table function has a range of values ​​that is related to 1+t. ai The values ​​of each number correspond one-to-one.

[0034] A dynamic management method for industrial waste gas treatment, the method comprising:

[0035] S1: The adsorption bed in the adsorption equipment during the waste gas treatment process is divided into multiple monitoring areas of similar size by the area division module;

[0036] S2: The data acquisition module collects real-time data on the state of the adsorption bed in each area of ​​the waste gas treatment process, as well as the waste gas data at the waste gas outlet.

[0037] S3: The data calculation module combines the exhaust gas data at the exhaust gas outlet with the exhaust gas data for coupled analysis to calculate the real-time exhaust gas concentration data at the exhaust gas outlet.

[0038] S4: By combining the real-time exhaust gas concentration data at the exhaust gas outlet with the status data of the adsorption equipment during the exhaust gas treatment process through the data analysis module, the real-time adsorption saturation of the adsorption equipment is analyzed.

[0039] S5: By combining the wind speed adjustment module with the real-time adsorption saturation analysis results of the adsorption equipment, the exhaust gas collection air volume is dynamically adjusted.

[0040] The beneficial effects of this invention are:

[0041] (1) By combining the exhaust gas data at the exhaust gas outlet for coupled analysis, the present invention can obtain high-quality real-time exhaust gas concentration data based on diversified data and after coupling processing. Then, based on this data and the status data of the adsorption equipment in the exhaust gas treatment process, the real-time adsorption saturation of the adsorption equipment can be accurately analyzed. This data reflects the current adsorption saturation of the activated carbon adsorption bed. Based on this data, the exhaust gas collection air volume can be dynamically adjusted by the wind speed adjustment module to optimize the exhaust gas collection air volume, thereby accelerating the desorption of attached substances and improving the exhaust gas treatment effect.

[0042] (2) This invention uses the influence coefficient t of the adsorption saturation at the a-th monitoring time point of all monitoring areas.ai Compare t with the preset adsorption saturation influence coefficient threshold respectively. 01 Through this comparison method, the influence coefficient t of adsorption saturation at the a-th monitoring time point in all monitoring areas can be obtained based on the fusion of diversified data. ai The size of the value is used to analyze the adsorption saturation of the adsorption bed in the adsorption equipment at the monitoring time point, and further make decisions to achieve dynamic adjustment of the waste gas collection air volume and improve the waste gas treatment effect.

[0043] (3) This invention measures the fluctuation value p of the adsorption saturation influence coefficient of all monitoring areas at the a-th monitoring time point. a Compared with the preset threshold value of the fluctuation value of the adsorption saturation influence coefficient p 01 By comparing the adsorption saturation differences between different regions of the activated carbon adsorption bed, the influence coefficient t of the adsorption saturation at the a-th monitoring time point in the i-th monitoring region can be determined. ai This process assigns values ​​to provide additional data support for subsequent optimization and adjustment of the exhaust gas collection air volume, thereby improving the accuracy of the adjustment results.

[0044] (4) This invention first combines the exhaust gas data at the exhaust gas outlet for coupling analysis. After coupling processing, the real-time exhaust gas concentration data can be obtained to avoid the situation of falsely high values, thereby reflecting the true concentration change of the exhaust gas after adsorption treatment. Then, based on this data and the status data of the adsorption equipment during the exhaust gas treatment process, the real-time adsorption saturation of the adsorption equipment can be accurately analyzed. Based on this data, the exhaust gas collection air volume can be dynamically adjusted through the wind speed adjustment module to optimize the exhaust gas collection air volume, thereby accelerating the desorption of attached substances and improving the exhaust gas treatment effect. Attached Figure Description

[0045] The invention will now be further described with reference to the accompanying drawings.

[0046] Figure 1 This is a schematic block diagram of a dynamic management system for industrial waste gas treatment according to the present invention;

[0047] Figure 2 This is a flowchart of a dynamic management method for industrial waste gas treatment according to the present invention. Detailed Implementation

[0048] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0049] Please see Figure 1 As shown, in one embodiment, this application provides a dynamic management method and system for industrial waste gas treatment, the system comprising:

[0050] The area division module is used to divide the adsorption bed in the adsorption equipment during the waste gas treatment process into multiple monitoring areas of similar size.

[0051] The data acquisition module is used to collect real-time data on the state of the adsorption bed in various areas during the waste gas treatment process, as well as waste gas data at the waste gas outlet.

[0052] The data calculation module is used to perform coupled analysis with the exhaust gas data at the exhaust gas outlet to calculate the real-time exhaust gas concentration data at the exhaust gas outlet.

[0053] The data analysis module is used to analyze the real-time adsorption saturation of the adsorption equipment by combining the real-time exhaust gas concentration data at the exhaust gas outlet with the status data of the adsorption equipment during the exhaust gas treatment process.

[0054] The wind speed adjustment module is used to dynamically adjust the exhaust gas collection air volume based on the real-time adsorption saturation analysis results of the adsorption equipment.

[0055] Through the above technical solution, this example provides a region division module, which is used to divide the adsorption bed in the adsorption equipment during the waste gas treatment process into multiple monitoring areas of similar size. During waste gas treatment, the data acquisition module first collects the state data of the adsorption bed in each area and the waste gas data at the waste gas outlet in real time. Then, the data calculation module performs coupled analysis with the waste gas data at the waste gas outlet to calculate the real-time waste gas concentration data at the waste gas outlet. The data analysis module combines the real-time waste gas concentration data at the waste gas outlet with the state data of the adsorption equipment during the waste gas treatment process to analyze the real-time adsorption saturation of the adsorption equipment. Finally, the wind speed adjustment module dynamically adjusts the waste gas collection air volume based on the real-time adsorption saturation analysis results of the adsorption equipment.

[0056] Through the above technical solution, when treating waste gas, by combining and analyzing the waste gas data at the waste gas outlet, high-quality real-time waste gas concentration data can be obtained based on diversified data and after coupling processing. Then, based on this data and the status data of the adsorption equipment during the waste gas treatment process, the real-time adsorption saturation of the adsorption equipment can be accurately analyzed. This data reflects the current adsorption saturation of the activated carbon adsorption bed. Based on this data, the waste gas collection air volume can be dynamically adjusted by the wind speed adjustment module to optimize the waste gas collection air volume, thereby accelerating the desorption of attached substances and improving the waste gas treatment effect.

[0057] The calculation process of the data calculation module includes:

[0058] Through formula The actual exhaust gas concentration s at the a-th monitoring time point at the exhaust gas outlet was calculated. a ;

[0059] Where 'a' represents the waste gas treatment status monitoring at fixed time intervals, and nd a The concentration of exhaust gas collected at the a-th monitoring time point at the exhaust gas outlet, ls a Let ls be the exhaust gas velocity at the a-th monitoring time point at the exhaust gas outlet. y For the preset exhaust gas flow rate, ls b For ls a The standard value, which can be selected and set based on the allowable error in empirical data, f c To define a function, if f c If (x)≥1, then let f c (x) = x, otherwise, let f c (x)=1, sf a gt represents the moisture content in the exhaust gas at the a-th monitoring time point at the exhaust gas outlet. a yc represents the particulate matter content in the exhaust gas at the a-th monitoring time point at the exhaust gas outlet. y θ represents the preset abnormal substance content in the exhaust gas. a The influence coefficient of the data acquisition equipment lifespan at the a-th monitoring time point is set based on empirical fitting. Specifically, it can be obtained by using a deep learning model trained on a large amount of data.

[0060] Using the above technical solution, this example provides the actual exhaust gas concentration s at the a-th monitoring time point at the exhaust gas outlet. a It can be done through the formula Calculations show that, obviously, the faster the exhaust gas flow rate at the a-th monitoring time point at the exhaust gas outlet, and the higher the moisture and particulate matter content in the exhaust gas at the a-th monitoring time point at the exhaust gas outlet, the higher the actual exhaust gas concentration s at the a-th monitoring time point at the exhaust gas outlet. a The larger the concentration of the exhaust gas, the lower the concentration of the exhaust gas. Conversely, the slower the exhaust gas flow rate at the a-th monitoring time point at the exhaust gas outlet, and the lower the moisture content and particulate matter content in the exhaust gas at the a-th monitoring time point at the exhaust gas outlet, the higher the actual exhaust gas concentration s at the a-th monitoring time point at the exhaust gas outlet. a The smaller it is;

[0061] Specifically, a faster exhaust gas flow rate at the a-th monitoring time point at the exhaust gas outlet may result in a shorter residence time of the gas in the sampling tube, leading to insufficient capture of some pollutants and indirectly causing an overestimation of the reading. Furthermore, the exhaust gas contains various interfering substances, such as moisture and particulate matter, which can interfere with the monitoring of the target pollutants, resulting in falsely high exhaust gas concentrations. Therefore, by combining diverse data, the exhaust gas concentration collected at the a-th monitoring time point at the exhaust gas outlet can be corrected. This avoids using falsely high exhaust gas concentration data when analyzing the adsorption saturation of the activated carbon adsorption bed, preventing significant errors in the analysis results and improving the accuracy of the activated carbon adsorption bed adsorption saturation analysis.

[0062] The analysis process of the data analysis module includes:

[0063] Through formula The influence coefficient t of adsorption saturation at the a-th monitoring time point in the i-th monitoring area was calculated. ai ;

[0064] Where i represents any monitoring area divided by the area division module, and yc a Let yc be the internal and external pressure difference within the adsorption device at the a-th monitoring time point. y For the preset internal and external pressure difference, wd ai Let wd be the temperature of the adsorption bed in the i-th monitoring area at the a-th monitoring time point. y The preset adsorption bed temperature, wd b for wd ai The standard value mentioned above can be selected and set based on the allowable error in empirical data. ai Let sd represent the humidity of the adsorption bed in the i-th monitoring area at the a-th monitoring time point. y The preset humidity of the adsorption bed;

[0065] Through the above technical solution, this example provides the adsorption saturation influence coefficient t for the i-th monitoring area at the a-th monitoring time point. ai It can be done through the formula Calculations show that the higher the internal and external pressure difference within the adsorption device at monitoring time point a, and the higher the temperature and humidity of the adsorption bed in monitoring region i at monitoring time point a, the higher the influence coefficient t of adsorption saturation at monitoring region i at monitoring time point a. ai The larger the pressure difference between the inside and outside of the adsorption device at the a-th monitoring time point, and the lower the temperature and humidity of the adsorption bed in the i-th monitoring area at the a-th monitoring time point, the greater the influence coefficient t of the adsorption saturation at the i-th monitoring area at the a-th monitoring time point. ai The smaller it is;

[0066] Specifically, a higher internal and external pressure difference within the adsorption equipment indicates ash accumulation or adsorption saturation in the adsorption bed. Higher bed temperature and humidity indicate an exothermic reaction leading to increased bed temperature and competitive adsorption of water vapor leading to increased humidity. Therefore, the saturation state can be determined by the linkage between temperature and humidity. Based on this, by integrating and analyzing diverse data, and combining it with the actual waste gas concentration s at the a-th monitoring time point at the waste gas outlet... a This can improve the accuracy of the calculation results, thereby providing accurate data for subsequent judgment of the adsorption saturation of the adsorption bed.

[0067] The analysis process of the data analysis module also includes:

[0068] By using the adsorption saturation influence coefficient t at the a-th monitoring time point of all monitoring areas ai Compare t with the preset adsorption saturation influence coefficient threshold respectively. 01 ;

[0069] If all t ai All less than t 01 The system determines that the adsorption saturation of the adsorption bed in the adsorption equipment is low at the monitoring time point, and there is no need to adjust the exhaust gas collection air volume.

[0070] If any t ai Greater than or equal to t 01 The system determines that the adsorption saturation of the adsorption bed in the adsorption equipment is high at the monitoring time point, and the exhaust gas collection air volume needs to be adjusted.

[0071] Using the above technical solution, this example uses the influence coefficient t of the adsorption saturation at the a-th monitoring time point in all monitoring areas. ai Compare t with the preset adsorption saturation influence coefficient threshold respectively. 01 Through this comparison method, the influence coefficient t of adsorption saturation at the a-th monitoring time point in all monitoring areas can be obtained based on the fusion of diversified data. ai The size of the value is used to analyze the adsorption saturation of the adsorption bed in the adsorption equipment at the monitoring time point, and further make decisions to achieve dynamic adjustment of the waste gas collection air volume and improve the waste gas treatment effect.

[0072] The adjustment process of the wind speed adjustment module includes:

[0073] Through formula The fluctuation value p of the adsorption saturation influence coefficient for all monitoring areas at the a-th monitoring time point was calculated. a ;

[0074] Where n is the total number of monitoring areas divided by the area division module. For all t ai The average value;

[0075] Using the above technical solution, this example provides the fluctuation value p of the adsorption saturation influence coefficient for all monitoring areas at the a-th monitoring time point. a It can be done through the formula The calculated data reflects the difference in adsorption saturation between different regions of the activated carbon adsorption bed at monitoring time point a. If the fluctuation value p of the adsorption saturation influence coefficient of all monitoring regions at monitoring time point a... a A large value indicates that the adsorption saturation in a certain area at the monitoring time point is much higher than that in other areas. Therefore, when optimizing the exhaust gas collection airflow, this area should be given priority. The fluctuation value p of the adsorption saturation influence coefficient of all monitoring areas at the a-th monitoring time point... a When the value is relatively low, it means that the adsorption saturation of each area at that monitoring time point is almost the same. Therefore, when optimizing and adjusting the exhaust gas collection air volume, it can be adjusted according to the average adsorption saturation.

[0076] By setting it up in this way, and combining the fluctuation value p of the adsorption saturation influence coefficient of all monitoring areas at the a-th monitoring time point, a This can provide additional data support for subsequent optimization and adjustment of the exhaust gas collection air volume, thereby improving the accuracy of the adjustment results.

[0077] The adjustment process of the wind speed adjustment module also includes:

[0078] By measuring the fluctuation value p of the adsorption saturation influence coefficient of all monitoring areas at the a-th monitoring time point a Compared with the preset threshold value of the fluctuation value of the adsorption saturation influence coefficient p 01 Perform a comparison;

[0079] If p a ≥p 01 Then let

[0080] If p a <p 01 Then let

[0081] Through the above technical solution, this example uses the fluctuation value p of the adsorption saturation influence coefficient of all monitoring areas at the a-th monitoring time point. a Compared with the preset threshold value of the fluctuation value of the adsorption saturation influence coefficient p 01 By comparing the adsorption saturation differences between different regions of the activated carbon adsorption bed, the influence coefficient t of the adsorption saturation at the a-th monitoring time point in the i-th monitoring region can be determined. aiThis process assigns values ​​to provide additional data support for subsequent optimization and adjustment of the exhaust gas collection air volume, thereby improving the accuracy of the adjustment results.

[0082] The adjustment process of the wind speed adjustment module also includes:

[0083] Through formula β a =β y *f m (1+t ai )Calculate the corrected exhaust gas collection air volume β at the a-th monitoring time point. a ;

[0084] Where, β y f is the preset exhaust gas collection air volume. m The adjustment coefficient lookup table function has a range of values ​​that is related to 1+t. ai The values ​​of these values ​​correspond one-to-one. It should be noted that the values ​​of the adjustment coefficient lookup table function can be based on empirical data such as 1+t. ai The impact of the numerical value range on the exhaust gas collection air volume was obtained through testing based on a deep learning model.

[0085] Using the above technical solution, this example provides the corrected exhaust gas collection air volume at the a-th monitoring time point, which can be expressed by formula β. a =β y *f m (1+t ai The calculations show that by setting it up in this way, the adjustment strategy and results of the exhaust gas collection air volume can be optimized based on diversified data support, so that the adjusted exhaust gas collection air volume can accelerate the desorption of attached substances and improve the exhaust gas treatment effect.

[0086] Please see Figure 2 As shown, a dynamic management method for industrial waste gas treatment includes:

[0087] S1: The adsorption bed in the adsorption equipment during the waste gas treatment process is divided into multiple monitoring areas of similar size by the area division module;

[0088] S2: The data acquisition module collects real-time data on the state of the adsorption bed in each area of ​​the waste gas treatment process, as well as the waste gas data at the waste gas outlet.

[0089] S3: The data calculation module combines the exhaust gas data at the exhaust gas outlet with the exhaust gas data for coupled analysis to calculate the real-time exhaust gas concentration data at the exhaust gas outlet.

[0090] S4: By combining the real-time exhaust gas concentration data at the exhaust gas outlet with the status data of the adsorption equipment during the exhaust gas treatment process through the data analysis module, the real-time adsorption saturation of the adsorption equipment is analyzed.

[0091] S5: Dynamically adjust the exhaust gas collection air volume by combining the wind speed adjustment module with the real-time adsorption saturation analysis results of the adsorption equipment;

[0092] Through the above technical solution, this example provides a dynamic management method for industrial waste gas treatment. First, the adsorption bed in the adsorption equipment during the waste gas treatment process is divided into multiple monitoring areas of similar size by a region division module. During the waste gas treatment operation, the data acquisition module collects the state data of the adsorption bed in each area and the waste gas data at the waste gas outlet in real time. Then, the data calculation module performs coupled analysis with the waste gas data at the waste gas outlet to calculate the real-time waste gas concentration data at the waste gas outlet. After that, the data analysis module combines the real-time waste gas concentration data at the waste gas outlet with the state data of the adsorption equipment during the waste gas treatment process to analyze the real-time adsorption saturation of the adsorption equipment. Finally, the airflow adjustment module dynamically adjusts the waste gas collection airflow based on the real-time adsorption saturation analysis results of the adsorption equipment.

[0093] The above technical solution first combines the exhaust gas data from the exhaust outlet for coupled analysis. After coupling processing, the real-time exhaust gas concentration data can be obtained, avoiding the possibility of artificially inflated values. This reflects the true concentration change of the exhaust gas after adsorption treatment. Then, based on this data and the status data of the adsorption equipment during the exhaust gas treatment process, the real-time adsorption saturation of the adsorption equipment can be accurately analyzed. Based on this data, the exhaust gas collection air volume can be dynamically adjusted through the wind speed adjustment module to optimize the exhaust gas collection air volume, thereby accelerating the desorption of attached substances and improving the exhaust gas treatment effect.

[0094] The foregoing has provided a detailed description of one embodiment of the present invention, but this description is merely a preferred embodiment and should not be construed as limiting the scope of the invention. All equivalent variations and modifications made within the scope of the claims of this invention should still fall within the patent coverage of this invention.

Claims

1. A dynamic management system for industrial waste gas treatment, characterized in that, The system includes: The area division module is used to divide the adsorption bed in the adsorption equipment during the waste gas treatment process into multiple monitoring areas of similar size. The data acquisition module is used to collect real-time data on the state of the adsorption bed in various areas during the waste gas treatment process, as well as waste gas data at the waste gas outlet. The data calculation module is used to perform coupled analysis with the exhaust gas data at the exhaust gas outlet to calculate the real-time exhaust gas concentration data at the exhaust gas outlet. The data analysis module is used to analyze the real-time adsorption saturation of the adsorption equipment by combining the real-time exhaust gas concentration data at the exhaust gas outlet with the status data of the adsorption equipment during the exhaust gas treatment process. The wind speed adjustment module is used to dynamically adjust the exhaust gas collection air volume based on the real-time adsorption saturation analysis results of the adsorption equipment.

2. The dynamic management system for industrial waste gas treatment according to claim 1, characterized in that, The calculation process of the data calculation module includes: Through formula The actual exhaust gas concentration s at the a-th monitoring time point at the exhaust gas outlet was calculated. a ; Where 'a' represents the waste gas treatment status monitoring at fixed time intervals, and nd a The concentration of exhaust gas collected at the a-th monitoring time point at the exhaust gas outlet, ls a Let ls be the exhaust gas velocity at the a-th monitoring time point at the exhaust gas outlet. y For the preset exhaust gas flow rate, ls b For ls a The standard value of f c To define a function, if f c If (x)≥1, then let f c (x) = x, otherwise, let f c (x)=1, sf a gt represents the moisture content in the exhaust gas at the a-th monitoring time point at the exhaust gas outlet. a yc represents the particulate matter content in the exhaust gas at the a-th monitoring time point at the exhaust gas outlet. y θ represents the preset abnormal substance content in the exhaust gas. a The factor representing the impact of the data acquisition equipment's lifespan at the a-th monitoring time point is set based on empirical fitting.

3. The dynamic management system for industrial waste gas treatment according to claim 2, characterized in that, The analysis process of the data analysis module includes: Through formula The influence coefficient t of adsorption saturation at the a-th monitoring time point in the i-th monitoring area was calculated. ai ; Where i represents any monitoring area divided by the area division module, and yc a Let yc be the internal and external pressure difference within the adsorption device at the a-th monitoring time point. y For the preset internal and external pressure difference, wd ai Let wd be the temperature of the adsorption bed in the i-th monitoring area at the a-th monitoring time point. y The preset adsorption bed temperature, wd b for wd ai Standard value, sd ai Let sd represent the humidity of the adsorption bed in the i-th monitoring area at the a-th monitoring time point. y The preset humidity of the adsorption bed.

4. The dynamic management system for industrial waste gas treatment according to claim 3, characterized in that, The analysis process of the data analysis module also includes: By using the adsorption saturation influence coefficient t at the a-th monitoring time point of all monitoring areas ai Compare t with the preset adsorption saturation influence coefficient threshold respectively. 01 ; If all t ai All less than t 01 The system determines that the adsorption saturation of the adsorption bed in the adsorption equipment is low at the monitoring time point, and there is no need to adjust the exhaust gas collection air volume. If any t ai Greater than or equal to t 01 The system determined that the adsorption saturation of the adsorption bed in the adsorption equipment was high at the monitoring time point, and that the exhaust gas collection air volume needed to be adjusted.

5. A dynamic management system for industrial waste gas treatment according to claim 4, characterized in that, The adjustment process of the wind speed adjustment module includes: Through formula The fluctuation value p of the adsorption saturation influence coefficient for all monitoring areas at the a-th monitoring time point was calculated. a ; Where n is the total number of monitoring areas divided by the area division module. For all t ai The average value.

6. A dynamic management system for industrial waste gas treatment according to claim 5, characterized in that, The adjustment process of the wind speed adjustment module also includes: By measuring the fluctuation value p of the adsorption saturation influence coefficient of all monitoring areas at the a-th monitoring time point a Compared with the preset threshold value of the fluctuation value of the adsorption saturation influence coefficient p 01 Perform a comparison; If p a ≥p 01 Then let t ai =t aimax ; If p a <p 01 Then let 7. A dynamic management system for industrial waste gas treatment according to claim 6, characterized in that, The adjustment process of the wind speed adjustment module also includes: Through formula β a =β y *f m (1+t ai )Calculate the corrected exhaust gas collection air volume β at the a-th monitoring time point. a ; Where, β y f is the preset exhaust gas collection air volume. m The adjustment coefficient lookup table function has a range of values ​​that is related to 1+t. ai The values ​​of each number correspond one-to-one.

8. A dynamic management method for industrial waste gas treatment, wherein the method employs a dynamic management system for industrial waste gas treatment as described in claims 1-7, characterized in that, The method includes: S1: The adsorption bed in the adsorption equipment during the waste gas treatment process is divided into multiple monitoring areas of similar size by the area division module; S2: The data acquisition module collects real-time data on the state of the adsorption bed in each area of ​​the waste gas treatment process, as well as the waste gas data at the waste gas outlet. S3: The data calculation module combines the exhaust gas data at the exhaust gas outlet with the exhaust gas data for coupled analysis to calculate the real-time exhaust gas concentration data at the exhaust gas outlet. S4: By combining the real-time exhaust gas concentration data at the exhaust gas outlet with the status data of the adsorption equipment during the exhaust gas treatment process through the data analysis module, the real-time adsorption saturation of the adsorption equipment is analyzed. S5: By combining the wind speed adjustment module with the real-time adsorption saturation analysis results of the adsorption equipment, the exhaust gas collection air volume is dynamically adjusted.

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