Steel VOCs regulation and control method based on emission energy consumption coupling

Abstract

The invention relates to the field of steel energy conservation and pollution control, in particular to a steel VOCs regulation and control method based on emission energy consumption coupling, which comprises the following steps: arranging a detection grid and a flow sensor at an outlet of an adsorption area of a zeolite rotating wheel, monitoring waste gas flow in real time, marking a detection period based on variance analysis, and determining the emission energy consumption of the zeolite rotating wheel. And determining an infrared observation time domain section by combining the rotating speed of the rotating wheel. Acquiring an infrared image of an outlet of a desorption area in the time domain section, identifying a specific temperature clustering area through clustering analysis, judging whether the local area of the runner is abnormal or not according to the proportion of the specific temperature clustering area, and marking and adjusting desorption parameters such as the rotating speed of the runner and the temperature of desorption gas for the abnormal area; in the subsequent rotation process, infrared images are collected again to verify the adjustment effect, if the reduction amount of the proportion of the specific temperature clustering area does not reach the threshold value, early warning is given out, and therefore the operation economical efficiency and reliability of the whole treatment system are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of energy saving and pollution control technology in the steel industry, and in particular to a steel VOCs regulation method based on emission and energy consumption coupling. BACKGROUND

[0002] With the continuous development of the steel industry as an important pillar industry of the national economy, the problem of volatile organic compounds (VOCs) emissions generated in the production process is increasingly prominent. VOCs not only directly cause air pollution, but also are closely related to the comprehensive operating cost and carbon emission control of enterprises. Therefore, achieving efficient and energy-saving treatment of VOCs has become an indispensable part of clean production and sustainable development of steel enterprises.

[0003] Chinese patent application publication No. CN120517058A discloses a printing equipment VOCs release real-time monitoring control method and system. Real-time parameters of the printing process are monitored in real time, and VOCs emission amount prediction values corresponding to the current printing task are obtained according to the real-time parameters combined with a VOCs emission prediction model; a print-through error of the current printing process is obtained according to a print-through error detection strategy combined with the reaction temperature and processing air volume of the current oven; the VOCs emission amount prediction values and the print-through error are combined with a VOCs emission and printing quality double-objective optimization function to obtain oven air volume and temperature matching the current printing quality and VOCs release; and the oven air volume and temperature matching the current printing quality and VOCs release are used to regulate and control the oven air speed and temperature of the printing equipment. The system includes modules corresponding to the method.

[0004] However, the prior art still has the following problems, In the VOCs regulation process of the steel industry, due to the diversity of waste gas sources and the complexity of components, VOCs emitted from different sources have great differences in properties and concentrations, which makes the zeolite rotary adsorption zone face great treatment pressure in actual operation, especially in the long-term operation process, part of the high-concentration and difficult-to-degrade organic matter is easy to form local accumulation in the internal area of the zeolite rotary adsorption zone, which leads to the plugging of the micropores of the adsorbent or the local inactivation, thereby reducing the adsorption efficiency and affecting the desorption regeneration effect, and further reducing the long-term operation economy and reliability of the entire VOCs treatment system. SUMMARY

[0005] Therefore, the present application provides a steel VOCs regulation method based on emission and energy consumption coupling to overcome the problems in the prior art in the VOCs regulation process of the steel industry, that is, part of the high-concentration and difficult-to-degrade organic matter is easy to form local accumulation in the internal area of the zeolite rotary adsorption zone, which leads to the local plugging of the adsorbent, thereby reducing the adsorption efficiency and the operation economy and reliability of the entire treatment system.

[0006] To achieve the above object, the application provides a steel VOCs regulation method based on emission energy consumption coupling, comprising the following steps: Step S1, a detection grid is arranged at the outlet of the zeolite rotary adsorption area, so that the exhaust gas passes into the detection grid after passing through the zeolite rotary adsorption area, and a flow sensor is arranged in the grid of the detection grid to obtain the gas flow corresponding to each cross-sectional area of the zeolite rotary adsorption area in several detection periods; Step S2, whether the corresponding detection period needs to be marked is determined based on the variance of the gas flow corresponding to each cross-sectional area, and the corresponding infrared observation time domain segment is determined based on the rotation speed of the zeolite rotary wheel; Step S3, infrared images at the outlet of the desorption area of the zeolite rotary wheel are collected in the infrared observation time domain segment, the infrared images are analyzed, and specific temperature clustering areas are identified, and whether the local area of the zeolite rotary wheel corresponding to the infrared images is abnormal is verified based on the proportion of the specific temperature clustering areas; Step S4, the local area of the rotary wheel is recorded, the desorption parameters are adjusted when the local area of the rotary wheel rotates to the desorption area of the zeolite rotary wheel, and infrared images are collected again when the local area of the rotary wheel rotates to the desorption area of the zeolite rotary wheel, and the specific temperature clustering area proportion reduction amount is calculated to determine whether to issue a warning signal; Wherein, the desorption parameters include the rotation speed of the zeolite rotary wheel and the temperature of the gas passing into the desorption area.

[0007] Further, the process of determining whether the corresponding detection period needs to be marked comprises, calculating the variance of the gas flow corresponding to each cross-sectional area; If the variance is greater than or equal to a preset variance threshold, the corresponding detection period is marked.

[0008] Further, the process of determining the corresponding infrared observation time domain segment comprises, the time required for the zeolite rotary wheel to rotate from the adsorption area to the desorption area is obtained as an extended time period; the marked detection period is delayed by the corresponding extended time period to obtain the infrared observation time domain segment.

[0009] Further, the process of determining the specific temperature clustering area in the infrared image comprises, cluster analysis is performed on the infrared image to identify a plurality of clustering clusters; If the difference between the temperature corresponding to the clustering cluster and the temperature corresponding to the adjacent area is greater than a predetermined temperature difference threshold, the specific temperature clustering area is determined.

[0010] Further, the process of verifying whether the local area of the zeolite rotary wheel corresponding to the infrared image is abnormal based on the proportion of the specific temperature clustering area comprises, determine the ratio of the area of the specific temperature cluster region to the area of the infrared image as the specific temperature cluster region proportion; If the specific temperature cluster region proportion is greater than or equal to a proportion threshold value, it is determined that the local area of the zeolite runner corresponding to the infrared image is abnormal.

[0011] Further, the local area of the runner is recorded, including, If the local area of the zeolite runner corresponding to the infrared image is abnormal, the local area of the runner is recorded.

[0012] Further, the process of calculating the specific temperature cluster region proportion reduction amount includes, determining the temperature cluster region proportion after adjusting the desorption parameters; determining the absolute value of the difference between the temperature cluster region proportion after adjusting the desorption parameters and the temperature cluster region proportion before adjusting the desorption parameters as the temperature cluster region proportion reduction amount.

[0013] Further, the process of determining whether to issue a warning signal includes, If the proportion reduction amount is less than a preset proportion reduction threshold value, a warning signal is issued.

[0014] Further, when adjusting the desorption parameters, the speed of the zeolite runner is reduced; wherein the speed reduction amount is positively correlated with the variance of the gas flow corresponding to each cross-sectional area.

[0015] Further, when adjusting the desorption parameters, the temperature of the inlet gas is increased; wherein the temperature increase amount is positively correlated with the variance of the gas flow corresponding to each cross-sectional area.

[0016] Compared with the prior art, the present application sets a detection grid at the outlet of the adsorption zone of the zeolite runner and configures a flow sensor to monitor the exhaust gas flow in real time, marks the detection period based on variance analysis, and determines the infrared observation time domain segment in combination with the runner rotation speed. Infrared images of the desorption zone outlet are collected in the time domain segment, specific temperature cluster regions are identified through cluster analysis, and whether the local area of the runner is abnormal is determined according to the proportion thereof. For abnormal areas, the runner speed and desorption parameters such as desorption gas temperature are marked and adjusted, and infrared images are collected again in the subsequent rotation process to verify the adjustment effect. If the specific temperature cluster region proportion reduction amount does not reach the threshold value, a warning is issued, thereby improving the operation economy and reliability of the entire treatment system.

[0017] Especially, the application sets a detection grid at the outlet of the zeolite rotary adsorption zone, so that the exhaust gas passes into the detection grid after passing through the zeolite rotary adsorption zone. In actual situations, due to the differences in the nature and concentration of VOCs emitted from different sources, part of the high-concentration and difficult-to-degrade organic matter is easy to form local accumulation inside the zeolite rotary adsorption zone, which may cause local blockage of the adsorbent. By setting the detection grid and installing the flow sensor, the detection grid can decompose the macroscopic total flow of the exhaust gas into independent flow signals of micro cross sections, so as to more accurately capture whether there is airflow distribution distortion caused by local blockage or VOCs accumulation on the cross section of the rotary wheel. Since the zeolite rotary adsorption zone is a continuous rotary device, the abnormal airflow area detected in the adsorption zone can be accurately rotated to the desorption zone in the next operation cycle. Therefore, whether the corresponding detection cycle needs to be marked can be determined based on the variance of the exhaust gas flow, the infrared observation time domain segment is determined based on the rotation speed of the zeolite rotary adsorption zone, accurate data support is provided for subsequent infrared detection and desorption parameter adjustment, and it is helpful to timely discover and handle abnormal situations.

[0018] Especially, the application analyzes the infrared image to determine a specific temperature clustering area in the infrared image, and verifies whether a local area of the zeolite rotary adsorption zone corresponding to the infrared image is abnormal based on a specific temperature clustering area proportion of the specific temperature clustering area. In actual situations, since the airflow distribution is uneven in the adsorption zone based on the variance of the exhaust gas flow in the early stage, it indicates that adsorbent blockage or VOCs enrichment may occur in a specific local area of the zeolite rotary adsorption zone. When the area is rotated to the desorption zone, these abnormalities may cause the heat desorption process to be blocked, which is manifested as an abnormal "cold area" or "hot area" with a significant temperature difference from the surrounding normal desorption area on the infrared thermal image. Through the image clustering algorithm, the clustering cluster of the temperature anomaly can be accurately identified. The specific temperature clustering area can more directly reflect the low desorption efficiency of the local area. The larger the specific clustering cluster area proportion is, the more serious the phenomenon of incomplete desorption of the local area is, and the worse the zeolite regeneration effect is. Therefore, the specific temperature clustering area proportion becomes an important basis for judging whether a local area of the zeolite rotary adsorption zone is abnormal. Through monitoring the specific temperature clustering area proportion, it is helpful to timely discover and handle abnormal situations and adjust the desorption parameters, so as to improve the operation economy and reliability of the entire treatment system.

[0019] Especially, the application adjusts the desorption parameters when the local area of the rotating wheel rotates to the zeolite wheel desorption zone, waits for the local area of the rotating wheel to rotate to the zeolite wheel desorption zone again to collect infrared images, and determines whether to issue a warning signal based on the reduction amount of the proportion of the specific temperature clustering area. In actual situations, since the abnormal accumulation of the local area has been confirmed through early diagnosis, the desorption parameters are adjusted by reducing the rotating speed of the zeolite wheel and increasing the temperature of the gas introduced, wherein reducing the rotating speed can prolong the residence time of the abnormal area in the desorption zone, providing more sufficient desorption kinetic conditions for the deeply adsorbed VOCs, and at the same time, increasing the temperature of the gas introduced into the desorption zone can provide additional heat energy for the desorption process, helping to decompose and release the adsorbed VOCs. The adjustment strategy aims to achieve focused repair of the local blocked or failed area. Subsequently, the marked area is allowed to enter the desorption zone again after completing a complete rotation period, and a new round of infrared images is collected for comparative analysis to evaluate the actual effect of adjusting the desorption parameters. If the reduction amount of the proportion of the specific temperature clustering area is greater than or equal to the preset proportion threshold, it indicates that the desorption process has improved and the local abnormality has been alleviated. Conversely, if the reduction amount of the proportion is less than the preset proportion reduction threshold, it indicates that regular parameter adjustment is not enough to solve the deep-seated failure of the area, and the adsorbent is permanently inactivated or severely blocked. The system will promptly issue a warning signal, indicating that further maintenance measures such as shutdown cleaning or replacement of the rotating wheel module may be needed, which can more actively avoid energy waste and continuous decline in overall treatment efficiency due to local governance failure. BRIEF DESCRIPTION OF DRAWINGS

[0020] Figure 1 A step schematic diagram of the steel VOCs regulation method based on emission energy consumption coupling of the embodiment of the application; Figure 2 A structure schematic diagram of the detection grid arranged at the outlet of the adsorption zone of the embodiment of the application; Figure 3 A logic determination diagram for determining whether to mark the corresponding detection period of the embodiment of the application; Figure 4 A logic determination diagram for verifying whether the local area of the zeolite wheel corresponding to the infrared image has an abnormality of the embodiment of the application; Figure 5 A logic determination diagram for determining whether to issue a warning signal of the embodiment of the application; In the figure, 1: desorption zone, 2: cooling zone, 3: adsorption zone, 4: detection grid. DETAILED DESCRIPTION

[0021] In order to make the purpose and advantages of the application more clear and explicit, the application will be further described below in combination with embodiments; it should be understood that the specific embodiments described herein are only used to explain the application and do not limit the application.

[0022] The preferred embodiments of the present application will be described below with reference to the accompanying drawings. Those skilled in the art will appreciate that the embodiments are only used to explain the technical principles of the present application, and are not intended to limit the scope of protection of the present application.

[0023] In addition, it should be noted that, in the description of the present application, unless otherwise explicitly specified and limited, the term "connection" should be understood broadly, which can be fixed connection, detachable connection, or integral connection; can be mechanical connection, or electrical connection; can be direct connection, or indirect connection through an intermediate medium; and can be internal connection of two elements. Those skilled in the art can understand the specific meaning of the above-mentioned term in the present application according to the specific circumstances.

[0024] Please refer to Figure 1 , Figure 1 The figure shows the steps of the steel VOCs regulation method based on emission energy consumption coupling according to an embodiment of the present application. The steel VOCs regulation method based on emission energy consumption coupling according to an embodiment of the present application comprises the following steps: Step S1, a detection grid is arranged at the outlet of the zeolite rotary adsorption zone, so that the exhaust gas passes into the detection grid after passing through the zeolite rotary adsorption zone. A flow sensor is arranged in each grid of the detection grid, so as to obtain the gas flow corresponding to each cross-sectional area of the zeolite rotary adsorption zone in a plurality of detection periods; Step S2, whether the corresponding detection period needs to be marked is determined based on the variance of the gas flow corresponding to each cross-sectional area, and the corresponding infrared observation time domain segment is determined based on the rotation speed of the zeolite rotary wheel; Step S3, infrared images at the outlet of the desorption zone of the zeolite rotary wheel are collected in the infrared observation time domain segment. The infrared images are analyzed to determine the specific temperature clustering area in the infrared images. Whether there is an abnormality in the local area of the zeolite rotary wheel corresponding to the infrared images is verified based on the specific temperature clustering area proportion of the specific temperature clustering area; Step S4, the local area of the rotary wheel is recorded. The desorption parameters are adjusted when the local area of the rotary wheel rotates to the desorption zone of the zeolite rotary wheel. The infrared images are collected again when the local area of the rotary wheel rotates to the desorption zone of the zeolite rotary wheel. The specific temperature clustering area proportion reduction amount is calculated to determine whether to issue a warning signal; The desorption parameters include the rotation speed of the zeolite rotary wheel and the temperature of the gas passing into the desorption zone.

[0025] Specifically, in the implementation, the exhaust gas is the exhaust gas containing VOCs after preliminary filtration.

[0026] Please refer to Figure 2 as shown, Figure 2The structural schematic view of the detection grid arranged at the outlet of the adsorption zone of the application embodiment does not limit the structure of the zeolite wheel, and the zeolite wheel generally comprises a desorption zone 1, a cooling zone 2 and an adsorption zone 3; The form of the detection grid 4 is not limited, which can be composed of several partitions to form a grid so that the gas flow is relatively independent in the grid. In order to ensure that the gas flow distribution data is sufficiently representative, preferably, the ventilation area of the detection grid 4 is substantially consistent with the cross-sectional area of the desorption zone of the zeolite wheel. In addition, in order to realize the partition diagnosis of the cross section of the wheel, the grid is divided into four independent detection areas with equal area, which are distributed in a cross shape.

[0027] In the implementation, the type of the flow sensor is not limited, and a thermal mass flow meter, an electromagnetic flow meter or other sensor types suitable for exhaust gas flow monitoring can be selected, as long as the measurement accuracy and stability meet the requirements. Here, no further description is given.

[0028] In the implementation, the installation mode of the flow sensor is limited, which can be wall-mounted or embedded, as long as the sensor is closely attached to the grid of the detection grid and does not affect the normal passage of the gas flow. Here, no further description is given.

[0029] The application arranges a detection grid at the outlet of the adsorption zone of the zeolite wheel, so that the exhaust gas passes through the adsorption zone of the zeolite wheel and enters the detection grid. In actual situations, due to the differences in properties and concentrations of VOCs emitted from different sources, some high-concentration and difficult-to-degrade organic matters are easy to form local accumulation in the zeolite wheel, which may cause local blockage of the adsorbent. By arranging the detection grid and installing the flow sensor, the detection grid can decompose the macroscopic total flow of the exhaust gas into independent flow signals of the micro cross section, so as to more accurately capture whether there is flow distribution distortion caused by local blockage or VOCs accumulation on the cross section of the wheel. Since the zeolite wheel is a continuous rotating device, the abnormal flow area detected in the adsorption zone can be accurately rotated to the desorption zone in the next operating cycle. Therefore, whether the corresponding detection period needs to be marked can be determined based on the variance of the exhaust gas flow, and the infrared observation time domain segment can be determined based on the rotation speed of the zeolite wheel.

[0030] Please refer to Figure 3 The logic determination diagram for determining whether the corresponding detection period needs to be marked, specifically, the process of determining whether the corresponding detection period needs to be marked comprises, calculating the variance of the gas flow of each cross-sectional area; If the variance is greater than or equal to a preset variance threshold, the corresponding detection period is marked.

[0031] In implementation, the variance threshold is predetermined to represent the abnormality degree of the air flow distribution. In which, the skilled in the art can collect sample data of the air flow of each cross-sectional area in normal operation state, and calculate the mean value of the variance to represent the air flow distribution in normal state. To represent the abnormal air flow distribution, the variance threshold is set as the product of the mean value of the variance and the variance precision coefficient. Generally, the variance precision coefficient is selected within [0.85, 1.35], and preferably 1.25 in implementation.

[0032] Specifically, the process of determining the corresponding infrared observation time domain segment comprises, obtaining the time required for the zeolite runner to rotate from the adsorption zone to the desorption zone as the extended time period; delaying the marked detection period by the corresponding extended time period to obtain the infrared observation time domain segment.

[0033] In implementation, the way of determining the time required for the zeolite runner to rotate from the adsorption zone to the desorption zone is not limited, which can be calculated by real-time measurement of angular displacement data through the installation of a rotary encoder on the runner main shaft, or theoretically calculated based on the preset fixed rotating speed and the fixed included angle between the adsorption / desorption zone, as long as the extended time period can be accurately obtained or calculated to ensure the accurate synchronization of the time domain of infrared image acquisition and the spatial position of the abnormal area reaching the desorption zone, which will not be repeated here.

[0034] Specifically, the process of determining the specific temperature clustering area in the infrared image comprises, performing clustering analysis on the infrared image to identify a plurality of clustering clusters; if the difference between the temperature corresponding to the clustering cluster and the temperature corresponding to the adjacent area is greater than the predetermined temperature difference threshold, the clustering cluster is determined as a specific temperature clustering area.

[0035] In implementation, the way of performing clustering analysis on the infrared image is not limited, which can be automatically grouped by K-means clustering algorithm on the temperature value of the image pixel, or identified as a continuous area with similar temperature characteristics by DBSCAN clustering method based on density, as long as the clustering cluster with significant temperature difference can be accurately identified, which will not be repeated here.

[0036] In the implementation, the predetermined temperature difference threshold is set to represent the difference degree between the abnormal area and the normal area, wherein the temperature data of each area in the infrared image under the normal operation state is collected to calculate the mean temperature difference between the areas to represent the temperature distribution under the normal state, and the predetermined temperature difference threshold is set as the product of the mean temperature difference and a temperature error coefficient to represent the specific temperature condition. Generally, the temperature error coefficient is selected within [1.05, 1.45], and preferably 1.25 in the implementation.

[0037] Referring to FIG. 8, Figure 4 FIG. 8 is a logic determination diagram for verifying whether the local area of the zeolite runner corresponding to the infrared image exists abnormally according to the embodiment of the application, and specifically, the process of verifying whether the local area of the zeolite runner corresponding to the infrared image exists abnormally based on the specific temperature clustering area proportion includes, determining the area proportion of the specific temperature clustering area as the specific temperature clustering area proportion; if the specific temperature clustering area proportion is greater than or equal to the proportion threshold, it is determined that the local area of the zeolite runner corresponding to the infrared image exists abnormally.

[0038] In the implementation, the area of the specific temperature clustering area is not limited, and the total number of all pixel points constituting the clustering cluster can be counted and multiplied by the actual physical area corresponding to a unit pixel to calculate, or the contour extraction algorithm after image morphological processing is used to obtain the boundary and calculate the area surrounded thereby to determine, as long as the accuracy and reliability of the area measurement are ensured, which will not be repeated here.

[0039] In the implementation, the proportion threshold is set to represent the abnormal degree of the proportion of the specific temperature clustering area in the infrared image to verify whether the local area of the zeolite runner corresponding to the infrared image exists abnormally, and the proportion threshold is predetermined, and preferably 8.5% in the implementation.

[0040] The present application determines specific temperature clustering areas in the infrared image, verifies whether the local area of the zeolite wheel corresponding to the infrared image is abnormal based on the specific temperature clustering area proportion of the specific temperature clustering area, and determines the specific temperature clustering area proportion of the specific temperature clustering area. In actual situations, since the variance based on the exhaust flow rate has determined that the adsorption area has uneven airflow distribution, it indicates that the adsorbent in a specific local area of the zeolite wheel may be blocked or VOCs are enriched. When the area rotates to the desorption area, these abnormalities may hinder the thermal desorption process, which is manifested as an abnormal "cold area" or "hot area" with a significant temperature difference from the surrounding normal desorption area on the infrared thermal image. Through the image clustering algorithm, the clustering cluster of the temperature anomaly can be accurately identified. The specific temperature clustering area can more directly reflect the low desorption efficiency of the local area. The larger the specific clustering area proportion, the more serious the incomplete desorption phenomenon in the local area, and the poorer the zeolite regeneration effect. Therefore, the specific temperature clustering area proportion is an important basis for determining whether the local area of the zeolite wheel is abnormal. Through monitoring the specific temperature clustering area proportion, the abnormal situation can be found and handled in time, and the desorption parameters can be adjusted, so as to improve the operation economy and reliability of the entire treatment system.

[0041] Specifically, the local area of the wheel is recorded, including, If the local area of the zeolite wheel corresponding to the infrared image is abnormal, the local area of the wheel is recorded.

[0042] In implementation, the way of recording the local area of the wheel is not limited, which can be determined by setting a physical scale mark on the circumferential surface of the zeolite wheel and establishing a position mapping with the abnormal image, or by correlating the real-time position signal of the wheel rotation encoder with the image acquisition timestamp for calculation, as long as the recording method can establish and maintain the accurate correspondence between the wheel rotation and the spatial position, and ensure that the marked local area can be uniquely identified and accurately positioned in any subsequent rotation period. This will not be repeated here.

[0043] Specifically, the process of calculating the specific temperature clustering area proportion reduction amount includes, Determine the temperature clustering area proportion after adjusting the desorption parameters; The absolute value of the difference between the temperature clustering area proportion after adjusting the desorption parameters and the temperature clustering area proportion before adjusting the desorption parameters is determined as the temperature clustering area proportion reduction amount.

[0044] Please refer to Figure 5 The logic determination diagram for determining whether to issue a warning signal is shown in the figure, and the process of determining whether to issue a warning signal includes, If the proportion reduction amount is less than the preset proportion reduction threshold, a warning signal is issued.

[0045] In implementation, the purpose of the proportion reduction threshold is to represent the qualified benchmark of the improvement degree of the treatment effect after the desorption parameter adjustment, which is the key indicator to determine whether the preliminary control measures solve the local anomaly. The proportion reduction threshold is determined in advance based on the historical operation data of the system, wherein the person skilled in the art can select the historical data of the proportion reduction amount of the specific temperature clustering area of the system after experiencing a successful control process, calculate the mean of the proportion reduction amount to represent the expected improvement effect that can be achieved by parameter adjustment under normal circumstances. To represent the case where the control effect does not meet the expected requirements, the proportion reduction threshold is set as the product of the mean of the proportion reduction amount and the proportion accuracy coefficient. Generally, the proportion accuracy coefficient is selected within [0.55, 0.85], and in implementation, it is preferably 0.65.

[0046] Specifically, when adjusting the desorption parameter, the rotational speed of the zeolite runner is reduced; wherein the rotational speed reduction amount is positively correlated with the variance of the gas flow corresponding to each cross-sectional area.

[0047] In implementation, optionally, a first variance threshold and a second variance threshold are set, if the variance of the gas flow corresponding to each cross-sectional area is less than the first variance threshold, the rotational speed is reduced to 0.25 times the current rotational speed of the zeolite runner; if the variance of the gas flow corresponding to each cross-sectional area is greater than or equal to the first variance threshold and less than or equal to the second variance threshold, when reducing the rotational speed of the zeolite runner, the rotational speed is reduced to 0.35 times the current rotational speed of the zeolite runner; if the variance of the gas flow corresponding to each cross-sectional area is greater than the second variance threshold, when reducing the rotational speed of the zeolite runner, the rotational speed reduction amount is positively correlated with the variance of the gas flow corresponding to each cross-sectional area, and preferably, the rotational speed is reduced to 0.55 times the current rotational speed of the zeolite runner; wherein 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.

[0048] Specifically, when adjusting the desorption parameter, the temperature of the inlet gas is increased; wherein the temperature increase amount is positively correlated with the variance of the gas flow corresponding to each cross-sectional area.

[0049] In implementation, optionally, a first variance threshold and a second variance threshold are set, if the variance of the gas flow corresponding to each cross-sectional area is less than the first variance threshold, when increasing the temperature of the inlet gas, the temperature is increased to 1.15 times the current temperature; If the variance of the gas flow corresponding to each cross-sectional area 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 input gas is increased, the temperature increase is positively correlated with the variance of the gas flow corresponding to each cross-sectional area, preferably, the temperature increase is 1.25 times the current temperature; If the variance of the gas flow corresponding to each cross-sectional area is greater than the second variance threshold, the temperature increase is 1.35 times the current temperature; 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.

[0050] The present application adjusts the desorption parameters when the local area of the rotating wheel rotates to the zeolite wheel desorption zone, waits for the local area of the rotating wheel to rotate to the zeolite wheel desorption zone again, collects infrared images, and determines whether to issue a warning signal based on the reduction amount of the specific temperature clustering area ratio. In actual situations, the abnormal accumulation of the local area has been confirmed through early diagnosis. The present application adjusts the desorption parameters by reducing the speed of the zeolite wheel and increasing the temperature of the input gas. Reducing the speed can prolong 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 input gas in the desorption zone can provide additional heat energy for the desorption process, helping to decompose and release the adsorbed VOCs, and achieving key repair of the local blocked or failed area. Subsequently, the marked area enters the desorption zone again after completing a complete rotation period, and a new round of infrared images is collected for comparative analysis to evaluate the actual effect of adjusting the desorption parameters. If the reduction amount of the specific temperature clustering area ratio is greater than or equal to the preset ratio threshold, it indicates that the desorption process has improved and the local abnormality has been alleviated. Conversely, if the reduction amount is less than the preset ratio reduction threshold, it indicates that regular parameter adjustment is not enough to solve the deep-seated failure of 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 needed, such as shutdown cleaning or replacement of the wheel module, which can more actively avoid energy waste and continuous decline in overall treatment efficiency due to local governance failure, thereby more accurately ensuring the economy and reliability of long-term operation of the system.

[0051] The technical solutions of the present application have been described in conjunction with the preferred embodiments shown in the accompanying drawings, but those skilled in the art will readily understand that the protection scope of the present application is obviously not limited to these specific embodiments. Those skilled in the art can make equivalent changes or replacements to related technical features without departing from the principles of the present application, and the technical solutions formed thereby will fall within the protection scope of the present application.

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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