A steel VOCs regulation method based on emission energy consumption coupling

Abstract

The present application relates to the field of steel energy saving and pollution control, and particularly relates to a steel VOCs regulation method based on emission energy consumption coupling. The present application sets a detection grid at the outlet of the zeolite rotary adsorption area and configures a flow sensor to monitor the exhaust gas flow in real time. Based on variance analysis, the detection period is marked, and the infrared observation time domain section is determined in combination with the rotary speed of the rotary wheel. Infrared images of the desorption area outlet are collected in the time domain section. Through cluster analysis, specific temperature cluster areas are identified, and whether there is an abnormality in the local area of the rotary wheel is determined according to the proportion. For the abnormal area, the rotary speed of the rotary wheel and the desorption parameters such as the temperature of the desorption gas are marked and adjusted. Infrared images are collected again in the subsequent rotation process to verify the adjustment effect. If the proportion of the specific temperature cluster area decreases by less than the threshold value, a warning is issued, thereby improving the operation economy and reliability of the entire treatment system.

Description

Technical Field

[0001] This invention relates to the field of energy conservation and pollution control technology in the steel industry, and in particular to a method for regulating VOCs in the steel industry based on emission-energy consumption coupling. Background Technology

[0002] As the steel industry continues to develop as a vital pillar of the national economy, the emission of volatile organic compounds (VOCs) during its production process has become increasingly prominent. VOCs not only directly cause air pollution but are also closely linked to the overall operating costs and carbon emission control of enterprises. Therefore, achieving efficient and energy-saving VOCs control has become an indispensable part of clean production and sustainable development for steel enterprises.

[0003] Chinese Patent Application Publication No. CN120517058A discloses a method and system for real-time monitoring and control of VOCs emissions from printing equipment. The method involves real-time monitoring of printing process parameters, obtaining a predicted VOCs emission value for the current printing task based on these parameters and a VOCs emission prediction model; obtaining the registration error of the current printing process based on a registration error detection strategy combined with the current oven reaction temperature and processing airflow; using the predicted VOCs emission value and registration error, along with a dual-objective optimization function for VOCs emission and printing quality, obtaining an oven airflow and temperature that match the current printing quality and VOCs emissions; and adjusting the oven airflow and temperature of the printing equipment according to the oven airflow and temperature that match the current printing quality and VOCs emissions. The system includes modules corresponding to the method.

[0004] However, the following problems still exist in the existing technology.

[0005] In the process of VOCs control in the steel industry, due to the diverse sources and complex composition of waste gas, there are significant differences in the properties and concentrations of VOCs emitted from different sources. This puts the zeolite rotor adsorption zone under considerable treatment pressure in actual operation. Especially during long-term operation, some high-concentration, recalcitrant organic compounds are prone to local accumulation in specific areas inside the zeolite rotor, leading to micropore blockage or local deactivation of the adsorbent. This reduces adsorption efficiency and affects desorption and regeneration effects, thereby reducing the long-term economic efficiency and reliability of the entire VOCs treatment system. Summary of the Invention

[0006] To address this, the present invention provides a VOCs control method for steel based on emission energy consumption coupling, which overcomes the problems existing in the VOCs control process of the steel industry in the prior art. That is, during long-term operation, some high-concentration, recalcitrant organic matter is prone to local accumulation inside the zeolite rotor, leading to local blockage of the adsorbent, thereby reducing the adsorption efficiency and the economic efficiency and reliability of the entire treatment system.

[0007] To achieve the above objectives, this invention provides a method for controlling VOCs in the steel industry based on emission-energy consumption coupling, comprising the following steps:

[0008] Step S1: A detection grid is set at the outlet of the zeolite rotor adsorption zone so that the exhaust gas passes through the zeolite rotor adsorption zone and then enters the detection grid. Each grid of the detection grid is equipped with a flow sensor to obtain the gas flow rate corresponding to each cross-sectional area of ​​the zeolite rotor adsorption zone within several detection cycles.

[0009] Step S2: Determine whether the corresponding detection cycle needs to be marked based on the variance of the gas flow rate corresponding to each cross-sectional region, and determine the corresponding infrared observation time domain segment based on the rotation speed of the zeolite wheel.

[0010] Step S3: In the infrared observation time domain segment, an infrared image is acquired at the outlet of the desorption zone of the zeolite rotor. The infrared image is analyzed to identify the specific temperature clusters. Based on the proportion of specific temperature clusters, it is verified whether there are any abnormalities in the local area of ​​the zeolite rotor corresponding to the infrared image.

[0011] Step S4: Record the local area of ​​the rotor. When the local area of ​​the rotor rotates to the desorption zone of the zeolite rotor, adjust the desorption parameters and wait for the local area of ​​the rotor to rotate to the desorption zone of the zeolite rotor again to collect infrared images and calculate the reduction in the proportion of the specific temperature clustering area to determine whether to issue an early warning signal.

[0012] The desorption parameters include the rotational speed of the zeolite rotor and the temperature of the gas introduced into the desorption zone.

[0013] Furthermore, the process of determining whether to mark the corresponding detection period includes,

[0014] Calculate the variance of the gas flow rate corresponding to each cross-sectional region;

[0015] If the variance is greater than or equal to a preset variance threshold, then the corresponding detection period is marked.

[0016] Furthermore, the process of determining the corresponding infrared observation time domain segment includes,

[0017] The time required for the zeolite rotor to rotate from the adsorption zone to the desorption zone is used as the extended time period.

[0018] The infrared observation time domain segment is obtained by extending the marked detection period by the corresponding extended time period.

[0019] Furthermore, the process of determining specific temperature clustering regions in the infrared image includes,

[0020] Cluster analysis is performed on infrared images to identify several clusters;

[0021] If the temperature difference between the cluster and the adjacent region is greater than a predetermined temperature difference threshold, it is identified as a specific temperature cluster.

[0022] Furthermore, the process of verifying whether there are anomalies in the local area of ​​the zeolite rotor corresponding to the infrared image based on the proportion of specific temperature clustering regions includes,

[0023] The ratio of the area of ​​the specific temperature cluster region to the area of ​​the infrared image is determined as the proportion of the specific temperature cluster region.

[0024] If the proportion of the specific temperature clustering area is greater than or equal to the proportion threshold, it is determined that there is an anomaly in the local area of ​​the zeolite rotor corresponding to the infrared image.

[0025] Furthermore, the recorded local area of ​​the rotor includes,

[0026] If an anomaly is found in a local area of ​​the zeolite rotor corresponding to the infrared image, then that local area of ​​the rotor is recorded.

[0027] Furthermore, the process of calculating the reduction in the proportion of specific temperature clustering regions includes,

[0028] Determine the proportion of temperature clustering regions after adjusting desorption parameters;

[0029] The absolute value of the difference between the proportion of temperature clusters after adjusting the desorption parameters and the proportion of temperature clusters before adjusting the desorption parameters is determined as the reduction in the proportion of temperature clusters.

[0030] Furthermore, the process of determining whether to issue a warning signal includes,

[0031] If the decrease in percentage is less than a preset percentage decrease threshold, a warning signal will be issued.

[0032] Furthermore, when adjusting the desorption parameters, reduce the rotational speed of the zeolite rotor;

[0033] Among them, the reduction in rotational speed is positively correlated with the variance of gas flow rate in each cross-sectional region.

[0034] Furthermore, when adjusting the desorption parameters, the temperature of the introduced gas is increased;

[0035] Among them, the increase in temperature is positively correlated with the variance of the gas flow rate in each cross-sectional region.

[0036] Compared with existing technologies, this invention improves the efficiency and reliability of the entire treatment system by installing a detection grid and configuring a flow sensor at the outlet of the zeolite rotor adsorption zone to monitor the exhaust gas flow in real time. The detection period is marked based on variance analysis, and the infrared observation time domain is determined by combining the rotor rotation speed. Infrared images of the desorption zone outlet are acquired during this time domain. Cluster analysis identifies specific temperature clusters, and their proportion is used to determine if there are any anomalies in local areas of the rotor. For abnormal areas, the rotor speed and desorption gas temperature, among other desorption parameters, are marked and adjusted. Infrared images are acquired again during subsequent rotations to verify the adjustment effect. If the reduction in the proportion of specific temperature clusters does not reach a threshold, an early warning is issued.

[0037] In particular, this invention sets up a detection grid at the outlet of the zeolite rotor adsorption zone, so that the exhaust gas passes through the zeolite rotor adsorption zone and then enters the detection grid. In reality, due to the differences in the properties and concentrations of VOCs emitted from different sources, some high-concentration, recalcitrant organic matter can easily accumulate locally inside the zeolite rotor, which may lead to local blockage of the adsorbent. By setting up a detection grid and installing a flow sensor, the detection grid can decompose the macroscopic total exhaust gas flow into independent flow signals of the microscopic cross-section, thereby more accurately capturing whether there is airflow distribution distortion on the rotor cross-section caused by local blockage or VOC accumulation. Since the zeolite rotor is a continuously rotating device, the abnormal airflow area detected in the adsorption zone can be accurately rotated to the desorption zone in the next operating cycle. Therefore, it is possible to determine whether the corresponding detection cycle needs to be marked based on the variance of the exhaust gas flow rate, and to determine the infrared observation time domain segment based on the rotation speed of the zeolite rotor, providing accurate data support for subsequent infrared detection and desorption parameter adjustment, which helps to detect and handle abnormal situations in a timely manner.

[0038] In particular, this invention analyzes infrared images to identify specific temperature clusters. Based on the proportion of these specific temperature clusters, it verifies whether there are anomalies in the local area of ​​the zeolite rotor corresponding to the infrared image. In practice, since the variance of the waste gas flow rate has already indicated uneven gas flow distribution in the adsorption zone, this suggests that specific local areas of the zeolite rotor may have adsorbent blockage or VOCs enrichment. When this area rotates to the desorption zone, these anomalies may hinder the thermal desorption process, manifesting as abnormal "cold" or "hot" zones with significant temperature differences from the surrounding normal desorption areas on the infrared thermogram. Image clustering algorithms can accurately identify these temperature-anomaly clusters. These specific temperature clusters more intuitively reflect the low local desorption efficiency. The larger the proportion of the specific cluster area, the more severe the incomplete desorption in that local area, and the worse the zeolite regeneration effect. Therefore, the proportion of the specific temperature clustering zone becomes an important basis for judging whether there are abnormalities in the local area of ​​the zeolite rotor. By monitoring the proportion of the specific temperature clustering zone, it is helpful to detect and deal with abnormalities in a timely manner, adjust the desorption parameters, and thus improve the operational economy and reliability of the entire treatment system.

[0039] In particular, this invention adjusts the desorption parameters when a localized area of ​​the zeolite rotor rotates into the desorption zone, and waits for the localized area to rotate back into the desorption zone to acquire infrared images. Based on the reduction in the proportion of specific temperature clusters, it determines whether to issue a warning signal. In practice, since abnormal accumulation in a localized area has already been confirmed through prior diagnosis, the desorption parameters are adjusted by reducing the zeolite rotor speed and increasing the temperature of the introduced gas. Reducing the speed prolongs the residence time of the abnormal area in the desorption zone, providing more sufficient desorption kinetics for deeply adsorbed VOCs. Simultaneously, increasing the temperature of the gas introduced into the desorption zone provides additional thermal energy for the desorption process, helping to decompose and release adsorbed VOCs. This adjustment strategy aims to address locally blocked or ineffective areas. The system focuses on repairing the affected area. Afterward, it waits for the marked area to complete a full rotation cycle before re-entering the desorption zone and acquiring a new round of infrared images for comparative analysis. This evaluates the actual effect of adjusting the desorption parameters. If the reduction in the proportion of the specific temperature cluster area is greater than or equal to the preset threshold, it indicates that the desorption process has improved and local anomalies have been alleviated. Conversely, if the reduction is less than the preset threshold, it indicates that conventional parameter adjustments are insufficient to resolve the deep-seated faults in that area, and the adsorbent has been permanently deactivated or severely clogged. The system will promptly issue a warning signal, indicating that further maintenance measures such as shutdown for cleaning or replacement of the rotor module may be necessary. This proactive approach avoids energy waste and continuous degradation of overall treatment efficiency caused by local treatment failures. Attached Figure Description

[0040] Figure 1 A schematic diagram illustrating the steps of the steel VOCs control method based on emission-energy consumption coupling in an embodiment of the invention;

[0041] Figure 2 A schematic diagram of a detection grid installed at the outlet of the adsorption zone in an embodiment of the invention;

[0042] Figure 3 This is a logic diagram for determining whether the corresponding detection cycle needs to be marked, as shown in the embodiment of the invention.

[0043] Figure 4 This is a logic determination diagram for verifying whether there is an anomaly in a local area of ​​the zeolite rotor corresponding to an infrared image, as shown in the embodiment of the invention.

[0044] Figure 5 This is a logic diagram illustrating whether to issue a warning signal according to an embodiment of the invention.

[0045] In the diagram, 1: desorption zone, 2: cooling zone, 3: adsorption zone, and 4: detection grid. Detailed Implementation

[0046] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0047] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0048] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the term "connection" should be interpreted broadly, and can refer to a fixed connection, a detachable connection, or an integral connection; it can refer to a mechanical connection or an electrical connection; it can refer to a direct connection or an indirect connection through an intermediate medium; it can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0049] Please see Figure 1 , Figure 1 This is a schematic diagram illustrating the steps of the steel VOCs control method based on emission-energy consumption coupling according to an embodiment of the present invention. The steel VOCs control method based on emission-energy consumption coupling according to an embodiment of the present invention includes:

[0050] Step S1: A detection grid is set at the outlet of the zeolite rotor adsorption zone so that the exhaust gas passes through the zeolite rotor adsorption zone and then enters the detection grid. Each grid of the detection grid is equipped with a flow sensor to obtain the gas flow rate corresponding to each cross-sectional area of ​​the zeolite rotor adsorption zone within several detection cycles.

[0051] Step S2: Determine whether the corresponding detection cycle needs to be marked based on the variance of the gas flow rate corresponding to each cross-sectional region, and determine the corresponding infrared observation time domain segment based on the rotation speed of the zeolite wheel.

[0052] Step S3: In the infrared observation time domain segment, an infrared image is acquired at the outlet of the desorption zone of the zeolite rotor. The infrared image is analyzed to determine the specific temperature clustering area in the infrared image. Based on the proportion of the specific temperature clustering area, it is verified whether there is an anomaly in the local area of ​​the zeolite rotor corresponding to the infrared image.

[0053] Step S4: Record the local area of ​​the rotor. When the local area of ​​the rotor rotates to the desorption zone of the zeolite rotor, adjust the desorption parameters and wait for the local area of ​​the rotor to rotate to the desorption zone of the zeolite rotor again to collect infrared images and calculate the reduction in the proportion of the specific temperature clustering area to determine whether to issue an early warning signal.

[0054] The desorption parameters include the rotational speed of the zeolite rotor and the temperature of the gas introduced into the desorption zone.

[0055] Specifically, in practice, the exhaust gas is the exhaust gas containing VOCs after preliminary filtration.

[0056] Please see Figure 2 As shown, Figure 2 This is a schematic diagram of a detection grid set at the outlet of the adsorption zone in an embodiment of the invention. The structure of the zeolite rotor is not limited. The zeolite rotor usually includes a desorption zone 1, a cooling zone 2 and an adsorption zone 3.

[0057] The form of the detection grid 4 is not limited; it can be composed of several baffles to form a grid, allowing the airflow to flow relatively independently within the grid. To ensure that the airflow distribution data is sufficiently representative, it is preferable that the ventilation area of ​​the detection grid 4 is basically consistent with the cross-sectional area of ​​the zeolite rotor desorption zone. Furthermore, to achieve zoned diagnosis of the rotor cross-section, the grid is divided into four independent detection areas of equal area, arranged in a grid pattern.

[0058] In practice, there is no limitation on the type of flow sensor. Thermal mass flow meter, electromagnetic flow meter or other sensor types suitable for monitoring exhaust gas flow can be selected, as long as the measurement accuracy and stability meet the requirements. This will not be elaborated further here.

[0059] In implementation, the installation method of the flow sensor is limited. It can be wall-mounted or embedded, as long as the sensor fits tightly against the grid of the detection grille and does not affect the normal passage of airflow. This will not be elaborated further.

[0060] This invention introduces a detection grid at the outlet of the zeolite rotor adsorption zone. This allows waste gas to pass through the adsorption zone and then into the detection grid. In practice, due to differences in the properties and concentrations of VOCs emitted from different sources, some high-concentration, recalcitrant organic compounds can easily accumulate locally inside the zeolite rotor, potentially causing localized blockage of the adsorbent. By installing a detection grid and a flow sensor, the grid can decompose the macroscopic total waste gas flow into independent flow signals at the microscopic cross-section. This allows for more accurate detection of airflow distribution distortions caused by localized blockages or VOC accumulation on the rotor's cross-section. Since the zeolite rotor is a continuously rotating device, any abnormal airflow areas detected in the adsorption zone can be precisely rotated to the desorption zone in the next operating cycle. Therefore, the variance of the waste gas flow rate can be used to determine whether a corresponding detection cycle needs to be marked, and the infrared observation time domain can be determined based on the rotation speed of the zeolite rotor.

[0061] Please see Figure 3 As shown, it is a logic decision diagram for determining whether to mark the corresponding detection period according to an embodiment of the invention. Specifically, the process of determining whether to mark the corresponding detection period includes,

[0062] Calculate the variance of the gas flow rate corresponding to each cross-sectional region;

[0063] If the variance is greater than or equal to a preset variance threshold, then the corresponding detection period is marked.

[0064] In implementation, the purpose of the variance threshold is to characterize the degree of anomaly in airflow distribution, and the variance threshold is predetermined. Those skilled in the art can collect sample data of gas flow rates in each cross-sectional area under normal operating conditions and calculate the mean variance to represent the normal airflow distribution. To represent anomalies in airflow distribution, the variance threshold is set as the product of the mean variance and the variance precision coefficient. Typically, the variance precision coefficient is selected within the range of [0.85, 1.35], and is preferably 1.25 in implementation.

[0065] Specifically, the process of determining the corresponding infrared observation time domain segment includes,

[0066] The time required for the zeolite rotor to rotate from the adsorption zone to the desorption zone is used as the extended time period.

[0067] The infrared observation time domain segment is obtained by extending the marked detection period by the corresponding extended time period.

[0068] In practice, there is no limitation on the method for determining the time required for the zeolite rotor to rotate from the adsorption zone to the desorption zone. It can be calculated by installing a rotary encoder on the rotor spindle and measuring the angular displacement data in real time, or by theoretical calculation based on a preset fixed rotation speed and a fixed angle between the adsorption / desorption zone. As long as the method can accurately obtain or calculate the extended time period and ensure that the acquisition time domain of the infrared image is precisely synchronized with the spatiotemporal position of the abnormal area reaching the desorption zone, it will not be elaborated further.

[0069] Specifically, the process of identifying specific temperature clusters in infrared images includes,

[0070] Cluster analysis was performed on the infrared images to identify several clusters;

[0071] If the temperature difference between the cluster and the adjacent region is greater than a predetermined temperature difference threshold, it is identified as a specific temperature cluster.

[0072] In practice, there is no limitation on the method of clustering analysis of the infrared image. The temperature values ​​of the image pixels can be automatically grouped by the K-means clustering algorithm, or the density-based DBSCAN clustering method can be used to identify continuous regions with similar temperature characteristics. As long as the clusters with significant temperature differences can be accurately identified, this will not be elaborated further.

[0073] In implementation, the purpose of setting a predetermined temperature difference threshold is to characterize the degree of difference between abnormal temperature areas and normal areas. This predetermined temperature difference threshold is determined in advance. Those skilled in the art can collect temperature data from various regions in an infrared image under normal operating conditions and calculate the average temperature difference between each region to represent the normal temperature distribution. To represent temperature-specific situations, the predetermined temperature difference threshold is set as the product of the average temperature difference and a temperature error coefficient. Typically, the temperature error coefficient is selected within the range of [1.05, 1.45], and is preferably 1.25 in implementation.

[0074] Please see Figure 4 As shown, this is a logic determination diagram for verifying whether there are anomalies in a local area of ​​the zeolite rotor corresponding to an infrared image, according to an embodiment of the invention. Specifically, the process of verifying whether there are anomalies in the local area of ​​the zeolite rotor corresponding to the infrared image based on the proportion of specific temperature clustering regions includes,

[0075] The ratio of the area of ​​the specific temperature cluster region to the area of ​​the infrared image is determined as the proportion of the specific temperature cluster region.

[0076] If the proportion of the specific temperature clustering area is greater than or equal to the proportion threshold, it is determined that there is an anomaly in the local area of ​​the zeolite rotor corresponding to the infrared image.

[0077] In practice, there is no limit to the area of ​​the specific temperature cluster. It can be calculated by counting the total number of all pixels that make up the cluster and multiplying it by the actual physical area corresponding to each pixel, or by using a contour extraction algorithm after image morphology processing to obtain its boundary and calculate the area of ​​the region it encloses. As long as the accuracy and reliability of the area measurement are ensured, this will not be elaborated further.

[0078] In practice, the purpose of the percentage threshold is to characterize the degree of abnormality of the proportion of the specific temperature clustering area in the infrared image, thereby verifying whether there is an anomaly in the local area of ​​the zeolite wheel corresponding to the infrared image. The percentage threshold is predetermined, and in practice, it is preferably 8.5%.

[0079] This invention analyzes infrared images to identify specific temperature clusters. Based on the proportion of these specific temperature clusters, it verifies whether there are anomalies in local areas of the zeolite rotor corresponding to the infrared image. In practice, since the variance of the waste gas flow rate has already indicated uneven gas flow distribution in the adsorption zone, this suggests that specific local areas of the zeolite rotor may have adsorbent blockage or VOCs enrichment. When this area rotates to the desorption zone, these anomalies may hinder the thermal desorption process, appearing as abnormal "cold" or "hot" zones with significant temperature differences from the surrounding normal desorption areas on the infrared thermogram. Image clustering algorithms can accurately identify these temperature-anomaly clusters. These specific temperature clusters more intuitively reflect the low local desorption efficiency. The larger the proportion of the specific cluster area, the more severe the incomplete desorption in that local area, and the worse the zeolite regeneration effect. Therefore, the proportion of the specific temperature clustering zone becomes an important basis for judging whether there are abnormalities in the local area of ​​the zeolite rotor. By monitoring the proportion of the specific temperature clustering zone, it is helpful to detect and deal with abnormalities in a timely manner, adjust the desorption parameters, and thus improve the operational economy and reliability of the entire treatment system.

[0080] Specifically, recording the local area of ​​the rotor includes,

[0081] If an anomaly is found in a local area of ​​the zeolite rotor corresponding to the infrared image, then that local area of ​​the rotor is recorded.

[0082] In practice, there is no limitation on the method of recording the local area of ​​the zeolite rotor. It can be determined by setting physical scale marks on the circumference of the zeolite rotor and establishing a position mapping with the abnormal image, or by calculating the correlation between the real-time position signal of the rotor rotary encoder and the image acquisition timestamp. As long as the recording method can establish and maintain the precise correspondence between the rotor rotation motion and the spatial position, and ensure that the marked local area can be uniquely identified and accurately located in any subsequent rotation cycle, it is sufficient. This will not be elaborated further.

[0083] Specifically, the process of calculating the reduction in the proportion of specific temperature cluster regions includes,

[0084] Determine the proportion of temperature clustering regions after adjusting desorption parameters;

[0085] The absolute value of the difference between the proportion of temperature clusters after adjusting the desorption parameters and the proportion of temperature clusters before adjusting the desorption parameters is determined as the reduction in the proportion of temperature clusters.

[0086] Please see Figure 5 As shown, this is a logic diagram for determining whether to issue a warning signal according to an embodiment of the invention. Specifically, the process of determining whether to issue a warning signal includes:

[0087] If the decrease in percentage is less than a preset percentage decrease threshold, a warning signal will be issued.

[0088] In implementation, the purpose of the reduction threshold is to serve as a benchmark for characterizing the degree of improvement in the treatment effect after the desorption parameter adjustment, and it is a key indicator for judging whether the initial control measures have resolved the local anomalies. The reduction threshold is determined in advance based on historical system operating data. Those skilled in the art can select historical data on the reduction in the proportion of the specific temperature cluster area after a successful control process, calculate its average reduction, and represent the expected improvement effect that parameter adjustment can achieve under normal conditions. To indicate a situation where the control effect does not meet expectations, the reduction threshold is set as the product of the average reduction and the proportion accuracy coefficient. Typically, the proportion accuracy coefficient is selected within the range of [0.55, 0.85], and is preferably 0.65 in implementation.

[0089] Specifically, when adjusting the desorption parameters, reduce the rotational speed of the zeolite rotor;

[0090] Among them, the reduction in rotational speed is positively correlated with the variance of gas flow rate in each cross-sectional region.

[0091] In implementation, optionally, a first variance threshold and a second variance threshold can be set.

[0092] If the variance of the gas flow rate corresponding to each cross-sectional region is less than the first variance threshold, the rotation speed is reduced to 0.25 times the current rotation speed of the zeolite rotor;

[0093] If the variance of the gas flow rate corresponding to each cross-sectional region is greater than or equal to the first variance threshold and less than or equal to the second variance threshold, when the rotational speed of the zeolite rotor is reduced, the rotational speed is reduced to 0.35 times the current rotational speed of the zeolite rotor.

[0094] If the variance of the gas flow rate corresponding to each cross-sectional region is greater than the second variance threshold, when the rotational speed of the zeolite rotor is reduced, the amount of reduction in rotational speed is positively correlated with the variance of the gas flow rate corresponding to each cross-sectional region. Preferably, the rotational speed is reduced to 0.55 times the current rotational speed of the zeolite rotor.

[0095] The first variance threshold is set to 1.25 times the variance threshold, and the second variance threshold is set to 1.45 times the variance threshold.

[0096] Specifically, when adjusting the desorption parameters, the temperature of the introduced gas is increased;

[0097] Among them, the increase in temperature is positively correlated with the variance of the gas flow rate in each cross-sectional region.

[0098] In implementation, optional,

[0099] Set a first variance threshold and a second variance threshold.

[0100] If the variance of the gas flow rate corresponding to each cross-sectional region is less than the first variance threshold, when the temperature of the introduced gas is increased, the temperature increases to 1.15 times the current temperature.

[0101] If the variance of the gas flow rate corresponding to each cross-sectional region is greater than or equal to the first variance threshold and less than or equal to the second variance threshold, when the temperature of the introduced gas is increased, the temperature increase is positively correlated with the variance of the gas flow rate corresponding to each cross-sectional region. Preferably, the temperature increase is 1.25 times the current temperature.

[0102] If the variance of the gas flow rate corresponding to each cross-sectional region is greater than the second variance threshold, the temperature increases to 1.35 times the current temperature;

[0103] The first variance threshold is set to 1.25 times the variance threshold, and the second variance threshold is set to 1.45 times the variance threshold.

[0104] This invention adjusts the desorption parameters when a localized area of ​​the zeolite rotor rotates into the desorption zone. After the localized area rotates back into the desorption zone, infrared images are acquired. Based on the reduction in the proportion of specific temperature clusters, a warning signal is issued. In practice, since the abnormal accumulation in the localized area has been confirmed through prior diagnosis, this invention adjusts the desorption parameters by reducing the rotational speed of the zeolite rotor and increasing the temperature of the introduced gas. Reducing the rotational speed prolongs the residence time of the abnormal area in the desorption zone, providing more sufficient desorption kinetic conditions for deeply adsorbed VOCs. At the same time, increasing the temperature of the gas introduced into the desorption zone provides additional heat energy for the desorption process, helping to decompose and release adsorbed VOCs, thus achieving targeted repair of locally blocked or failed areas. Subsequently, after the marked area completes a full rotation cycle, it re-enters the desorption zone and acquires a new round of infrared images for comparative analysis. This evaluates the actual effect of adjusting the desorption parameters. If the reduction in the proportion of the specific temperature clustering area is greater than or equal to the preset threshold, it indicates that the desorption process has improved and local anomalies have been alleviated. Conversely, if the reduction is less than the preset threshold, it indicates that conventional parameter adjustments are insufficient to resolve deeper faults in the area, such as permanent deactivation or severe blockage of the adsorbent. The system will promptly issue a warning signal, indicating that further maintenance measures may be necessary, such as shutdown for cleaning or replacement of the rotor module. This proactively avoids energy waste and continuous degradation of overall treatment efficiency caused by local treatment failures, thereby more accurately ensuring the long-term economic efficiency and reliability of the system.

[0105] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the resulting technical solutions will all fall within the scope of protection of the present invention.

Claims

1. A method for controlling VOCs in the steel industry based on emission-energy consumption coupling, characterized in that, Includes the following steps, Step S1: A detection grid is set at the outlet of the zeolite rotor adsorption zone so that the exhaust gas passes through the zeolite rotor adsorption zone and then enters the detection grid. Each grid of the detection grid is equipped with a flow sensor to obtain the gas flow rate corresponding to each cross-sectional area of ​​the zeolite rotor adsorption zone within several detection cycles. Step S2: Determine whether the corresponding detection cycle needs to be marked based on the variance of the gas flow rate corresponding to each cross-sectional region, and determine the corresponding infrared observation time domain segment based on the rotation speed of the zeolite wheel. Step S3: In the infrared observation time domain segment, an infrared image is acquired at the outlet of the desorption zone of the zeolite rotor. The infrared image is analyzed to determine the specific temperature clustering area in the infrared image. Based on the proportion of the specific temperature clustering area, it is verified whether there is an anomaly in the local area of ​​the zeolite rotor corresponding to the infrared image. Step S4: Record the local area of ​​the rotor. When the local area of ​​the rotor rotates to the desorption zone of the zeolite rotor, adjust the desorption parameters and wait for the local area of ​​the rotor to rotate to the desorption zone of the zeolite rotor again to collect infrared images and calculate the reduction in the proportion of the specific temperature clustering area to determine whether to issue an early warning signal. The desorption parameters include the rotational speed of the zeolite rotor and the temperature of the gas introduced into the desorption zone.

2. The method for controlling VOCs in the steel industry based on emission-energy consumption coupling according to claim 1, characterized in that, The process of determining whether to mark the corresponding detection period includes: Calculate the variance of the gas flow rate corresponding to each cross-sectional region; If the variance is greater than or equal to a preset variance threshold, then the corresponding detection period is marked.

3. The method for controlling VOCs in the steel industry based on emission-energy consumption coupling according to claim 1, characterized in that, The process of determining the corresponding infrared observation time domain segment includes: The time required for the zeolite rotor to rotate from the adsorption zone to the desorption zone is used as the extended time period. The infrared observation time domain segment is obtained by extending the marked detection period by the corresponding extended time period.

4. The method for controlling VOCs in the steel industry based on emission-energy consumption coupling according to claim 1, characterized in that, The process of identifying specific temperature clusters in infrared images includes, Cluster analysis was performed on the infrared images to identify several clusters; If the temperature difference between the cluster and the adjacent region is greater than a predetermined temperature difference threshold, it is identified as a specific temperature cluster.

5. The method for controlling VOCs in the steel industry based on emission-energy consumption coupling according to claim 1, characterized in that, The process of verifying whether there are anomalies in the local area of ​​the zeolite rotor corresponding to the infrared image based on the proportion of specific temperature clustering regions includes: The ratio of the area of ​​the specific temperature cluster region to the area of ​​the infrared image is determined as the proportion of the specific temperature cluster region. If the proportion of the specific temperature clustering area is greater than or equal to the proportion threshold, it is determined that there is an anomaly in the local area of ​​the zeolite rotor corresponding to the infrared image.

6. The method for controlling VOCs in the steel industry based on emission-energy consumption coupling according to claim 5, characterized in that, The recorded local area of ​​the rotor includes, If an anomaly is found in a local area of ​​the zeolite rotor corresponding to the infrared image, then that local area of ​​the rotor is recorded.

7. The method for controlling VOCs in the steel industry based on emission-energy consumption coupling according to claim 1, characterized in that, The process of calculating the reduction in the proportion of specific temperature cluster regions includes: Determine the proportion of temperature clustering regions after adjusting desorption parameters; The absolute value of the difference between the proportion of temperature clusters after adjusting the desorption parameters and the proportion of temperature clusters before adjusting the desorption parameters is determined as the reduction in the proportion of temperature clusters.

8. The method for controlling VOCs in the steel industry based on emission-energy consumption coupling according to claim 7, characterized in that, The process of determining whether to issue a warning signal includes... If the decrease in percentage is less than a preset percentage decrease threshold, a warning signal will be issued.

9. The method for controlling VOCs in the steel industry based on emission-energy consumption coupling according to claim 1, characterized in that, When adjusting the desorption parameters, reduce the rotational speed of the zeolite rotor; Among them, the reduction in rotational speed is positively correlated with the variance of gas flow rate in each cross-sectional region.

10. The method for controlling VOCs in the steel industry based on emission-energy consumption coupling according to claim 1, characterized in that, When adjusting the desorption parameters, increase the temperature of the introduced gas; Among them, the increase in temperature is positively correlated with the variance of the gas flow rate in each cross-sectional region.

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