Real-time monitoring system and method for operation of waste gas treatment device

Abstract

The invention relates to the technical field of monitoring control systems, in particular to a real-time monitoring system and method for operation of a waste gas treatment device. The method comprises the following steps: collecting data of a waste gas treatment device by using an intelligent sensor; performing data preprocessing on the waste gas treatment device data to obtain standard waste gas treatment device data; performing multi-modal identification on the standard waste gas treatment device data to generate multi-modal treatment data; performing processing process division on the multi-modal processing data to obtain processing process data; performing waste gas characterization monitoring on the treatment process data to generate waste gas characterization data; and performing equipment state feature recognition on the waste gas treatment device according to the waste gas characterization data to obtain equipment state data. Through the data processing technology, the mode recognition technology and the monitoring control technology, dynamic cooperative control over equipment of the waste gas treatment device is achieved, operation abnormity early warning response is conducted in time, and therefore the operation monitoring efficiency of the waste gas treatment device is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of monitoring control systems, and in particular to a system and method for real-time monitoring the operation of an exhaust gas treatment device. Background Art

[0002] Initially, the operating status of the exhaust gas treatment device mainly relied on manual inspection. Workers need to go to the site regularly to check the various parameters of the equipment, such as temperature, pressure and flow; as programmable logic controllers (PLCs) began to be applied to exhaust gas treatment devices, the specific manifestation is that PLCs collect the operating data of the equipment in real time by connecting various sensors and perform simple logical control. In order to solve the limitations of PLC control, remote monitoring technology has gradually developed. By installing sensors on the exhaust gas treatment device, the collected data is uploaded to the cloud server through a wireless network (such as a SIM card or wireless network card). Workers remotely access the cloud server through a computer client or mobile application, observe the operating status of the equipment in real time, and perform remote control. However, the exhaust gas treatment device is usually composed of multiple devices, such as adsorption towers and catalytic combustion devices. With existing monitoring technology, it is difficult to coordinate control between devices; and the early warning response is not timely, resulting in low efficiency in the operation monitoring of the exhaust gas treatment device. Summary of the invention

[0003] Based on this, it is necessary to provide a real-time monitoring system and method for the operation of an exhaust gas treatment device to solve at least one of the above technical problems.

[0004] To achieve the above object, a method for real-time monitoring of the operation of an exhaust gas treatment device is provided, the method comprising the following steps:

[0005] Step S1: using intelligent sensors to collect exhaust gas treatment device data; performing data preprocessing on the exhaust gas treatment device data to obtain standard exhaust gas treatment device data; performing multimodal recognition on the standard exhaust gas treatment device data to generate multimodal processing data;

[0006] Step S2: dividing the multimodal processing data into processing processes to obtain processing process data; performing exhaust gas characterization monitoring on the processing process data to generate exhaust gas characterization data; and performing equipment state feature identification on the exhaust gas treatment device according to the exhaust gas characterization data to obtain equipment state data;

[0007] Step S3: monitoring the adsorption state of the adsorption tower equipment according to the equipment state data to obtain adsorption state data; evaluating the exhaust gas saturation degree of the adsorption state data to generate an exhaust gas saturation degree value; performing adsorption anomaly detection on the exhaust gas saturation degree value to obtain adsorption anomaly data; dynamically switching the processing operation of the catalytic combustion equipment based on the adsorption anomaly data to generate dynamic processing operation measures;

[0008] Step S4: Continuously monitor the operation of the exhaust gas treatment device and record the real-time operation monitoring data; issue an operation warning for the device based on the real-time operation monitoring data and generate an operation warning report for the device; and execute dynamic treatment operation measures for the exhaust gas treatment device based on the operation warning report to complete the real-time monitoring of the operation of the exhaust gas treatment device.

[0009] The present invention collects the raw data of the exhaust gas treatment device through an intelligent sensor, and performs data preprocessing to ensure the accuracy and consistency of the data, thereby obtaining the data of the standard exhaust gas treatment device. Then, the standard exhaust gas treatment device data is subjected to multimodal recognition, which can fully capture the characteristic information of the exhaust gas treatment device in different states. The multimodal processing data is divided into processing processes, which makes the operation process of the exhaust gas treatment device subdivided into multiple stages, facilitating targeted monitoring and analysis of each stage. Then, the processing process data is subjected to exhaust gas characterization monitoring, which can accurately reflect the key parameters such as the composition and concentration of the exhaust gas, and provides an important basis for the identification of the equipment status. Finally, the equipment status characteristics of the exhaust gas treatment device are identified according to the exhaust gas characterization data, which can fully grasp the operating status of the exhaust gas treatment device, and provide accurate equipment status information for subsequent monitoring and adjustment. According to the equipment status data, the adsorption state of the adsorption tower equipment is monitored, and the adsorption efficiency and adsorption capacity of the adsorption tower can be understood in real time, providing data support for the optimization of the adsorption process. Then, the exhaust gas saturation degree is evaluated on the adsorption state data, which can judge the adsorption saturation state of the adsorption tower, and provide a basis for the replacement and regeneration of the adsorption tower. Then, the adsorption anomaly detection of the exhaust gas saturation value can timely discover the abnormal situation in the adsorption process, and provide early warning information for the fault diagnosis and treatment of the adsorption tower. Finally, the processing operation of the catalytic combustion equipment is dynamically switched based on the adsorption abnormality data, and the working mode of the catalytic combustion equipment can be dynamically adjusted according to the operating status of the adsorption tower to ensure the efficient and stable operation of the exhaust gas treatment device. Continuous operation monitoring of the exhaust gas treatment device and recording of real-time operation monitoring data can fully grasp the operation of the exhaust gas treatment device and provide real-time data support for subsequent analysis and adjustment. Then, the device operation early warning of the real-time operation monitoring data can timely discover the potential problems and risks of the exhaust gas treatment device and provide early warning information for the maintenance and management of the equipment. Finally, based on the device operation early warning report, the dynamic measures for the processing operation of the exhaust gas treatment device are executed to complete the real-time monitoring operation of the exhaust gas treatment device, and the operating parameters and operation mode of the exhaust gas treatment device can be dynamically adjusted according to the early warning information to ensure the stable operation of the exhaust gas treatment device and the optimization of the treatment effect. Therefore, the present invention realizes dynamic coordinated control of the exhaust gas treatment device between devices through data processing technology, pattern recognition technology and monitoring and control technology, and promptly responds to abnormal operation warnings, thereby improving the efficiency of exhaust gas treatment device operation monitoring.

[0010] Preferably, step S1 comprises the following steps:

[0011] Step S11: using intelligent sensors to collect data from the exhaust gas treatment device;

[0012] Step S12: performing data denoising on the exhaust gas treatment device data to obtain device denoised data; performing defect value filling on the device denoised data to generate device defect value filled data;

[0013] Step S13: standardizing the device defect value filling data to obtain standard exhaust gas treatment device data;

[0014] Step S14: extracting the features of the standard exhaust gas treatment device data to generate exhaust gas treatment device features; performing feature structure processing on the exhaust gas treatment device features to obtain device feature structured data;

[0015] Step S15: performing processing mode recognition on the device feature structured data to obtain device processing mode data; performing multimodal feature fusion on the device processing mode data to generate multimodal processing data.

[0016] The present invention collects the original data of the exhaust gas treatment device through intelligent sensors, providing comprehensive basic information for subsequent data processing and analysis. Intelligent sensors can monitor the operating parameters of the exhaust gas treatment device in real time, ensure the real-time and accuracy of the data, and provide a reliable data source for subsequent data processing. Data denoising of the exhaust gas treatment device data can effectively eliminate noise interference in the data, improve the purity and accuracy of the data, and lay a solid foundation for subsequent data processing and analysis. Then, the defect value filling of the device denoising data can repair the missing values ​​and abnormal values ​​in the data, ensure the integrity and consistency of the data, and ensure the accuracy and reliability of subsequent data processing. Data standardization is performed on the device defect value filling data. Specifically, data standardization can unify data of different dimensions and magnitudes into the same scale range, eliminate the dimension differences and magnitude differences between the data, make the data comparable and consistent, and provide a standardized data basis for subsequent feature extraction and pattern recognition, and improve the efficiency and accuracy of data processing. The processing device feature extraction is performed on the standard exhaust gas treatment device data. Feature extraction can extract key feature information reflecting the operating status of the exhaust gas treatment device from a large amount of raw data, reduce the dimension and complexity of the data, and improve the efficiency and effect of data processing. Next, the characteristics of the exhaust gas treatment device are processed by feature structuring, and the extracted feature information can be organized and stored in a structured manner, which is convenient for subsequent data analysis and processing, and improves the operability and interpretability of the data. The device feature structured data is processed by pattern recognition to obtain device processing mode data. Pattern recognition can identify the operating mode and status of the exhaust gas treatment device based on the device feature structured data. Then, multi-modal feature fusion is performed on the device processing mode data, which can integrate and fuse the feature information of different modes to obtain more comprehensive and accurate exhaust gas treatment device operation information, providing rich data support for the monitoring and optimization of the exhaust gas treatment device.

[0017] Preferably, step S2 comprises the following steps:

[0018] Step S21: marking the processing time points of the multimodal processing data to obtain processing time marking points; dividing the processing time of the multimodal processing data according to the processing time marking points to generate processing time segmentation data;

[0019] Step S22: performing processing segment matching on the processing time segmentation data to obtain process segment matching data; performing processing segment division on the multimodal processing data based on the process segment matching data to obtain processing process data;

[0020] Step S23: monitoring the exhaust gas concentration of the processing data to obtain exhaust gas concentration monitoring data; identifying the concentration change characteristics of the exhaust gas concentration monitoring data to generate exhaust gas concentration change characteristics;

[0021] Step S24: monitoring the exhaust gas temperature of the processing data to obtain exhaust gas temperature monitoring data; identifying the temperature change characteristics of the exhaust gas temperature monitoring data to generate exhaust gas temperature change characteristics;

[0022] Step S25: merging the exhaust gas concentration variation characteristics and the exhaust gas temperature variation characteristics to generate exhaust gas characterization data;

[0023] Step S26: Identify the equipment status characteristics of the exhaust gas treatment device according to the exhaust gas characterization data to obtain equipment status data.

[0024] The present invention identifies the processing time points of multimodal processing data, can accurately record the status of the exhaust gas treatment device at different time points, and provides a clear time reference for subsequent time series analysis. Then, the processing time of the multimodal processing data is segmented according to the processing time identification point, and the operation process of the exhaust gas treatment device can be divided into multiple independent time periods, which is convenient for separate analysis and processing of the operation status of each time period, and improves the degree of refinement of data processing. The processing time segmentation data is matched with the processing process segment, and the segmented time period can be matched with the specific processing process of the exhaust gas treatment device to ensure that the data of each time period corresponds to the corresponding processing process, and provide accurate matching information for the subsequent processing process division; the processing process of the multimodal processing data is divided based on the process segment matching data, and the operation process of the exhaust gas treatment device can be subdivided into multiple specific processing stages, which provides a clear process division for subsequent monitoring and analysis. The exhaust gas concentration of the processing process data is monitored, and the exhaust gas concentration information of the exhaust gas treatment device in different processing processes can be obtained in real time. Next, the concentration change characteristics of the exhaust gas concentration monitoring data are identified, which can accurately identify the changing trends and characteristics of the exhaust gas concentration during the treatment process; the exhaust gas temperature is monitored on the treatment process data, which can obtain the exhaust gas temperature information of the exhaust gas treatment device in different treatment processes in real time, providing basic data for subsequent temperature change analysis; the temperature change characteristics of the exhaust gas temperature monitoring data are identified, which can accurately identify the changing trends and characteristics of the exhaust gas temperature during the treatment process, and provide important temperature change information for evaluating the operating status of the exhaust gas treatment device and optimizing temperature control; the exhaust gas concentration change characteristics and the exhaust gas temperature change characteristics are combined for exhaust gas characterization, which can integrate the changing characteristics of the exhaust gas concentration and temperature to form comprehensive exhaust gas characterization information, providing rich data support for the comprehensive evaluation and optimization of the exhaust gas treatment device, and accurately reflecting the operating status and treatment effect of the exhaust gas treatment device; the equipment status characteristics of the exhaust gas treatment device are identified according to the exhaust gas characterization data, which can accurately identify the equipment status of the exhaust gas treatment device according to the exhaust gas characterization data, including normal operation, abnormal status, etc., providing important status information for equipment maintenance, fault diagnosis and operation optimization.

[0025] Preferably, step S26 includes the following steps:

[0026] Step S261: determining the continuous rising stage of the exhaust gas concentration variation characteristics to obtain the concentration rising stage; determining the continuous falling stage of the exhaust gas concentration variation characteristics to obtain the concentration falling stage;

[0027] Step S262: Identify the equipment concentration state of the exhaust gas treatment device according to the concentration rising stage and the concentration falling stage to obtain equipment concentration state data;

[0028] Step S263: performing temperature fluctuation detection on the exhaust gas temperature variation characteristics to obtain temperature fluctuation data; determining the fluctuation frequency of the temperature fluctuation data to generate fluctuation frequency data;

[0029] Step S264: Identify the temperature state of the exhaust gas treatment device according to the fluctuation frequency data to obtain the temperature state data of the device;

[0030] Step S265: Integrate the device concentration status data and the device temperature status data to obtain device status data.

[0031] The present invention determines the continuous rising stage of the exhaust gas concentration change characteristics, obtains the concentration rising stage, can accurately identify the time period when the exhaust gas concentration continues to rise during the treatment process, and provides important rising stage information for analyzing the treatment efficiency and stability of the exhaust gas treatment device. At the same time, the exhaust gas concentration change characteristics are continuously determined to be in a downward rising stage, which can accurately identify the time period when the exhaust gas concentration continues to decline during the treatment process, and provide important downward rising stage information for evaluating the treatment effect of the exhaust gas treatment device and optimizing the treatment process. According to the concentration rising stage and the concentration downward rising stage, the exhaust gas treatment device is identified for the equipment concentration state, which can comprehensively consider the rising and falling stages of the exhaust gas concentration, comprehensively evaluate the concentration state of the exhaust gas treatment device at different treatment stages, provide accurate concentration state information for the operation monitoring and fault diagnosis of the equipment, and timely discover and deal with abnormal concentration problems. The temperature fluctuation detection of the exhaust gas temperature change characteristics can monitor the temperature fluctuation of the exhaust gas treatment device in real time during the treatment process, and provide basic data for analyzing the temperature stability and thermal efficiency of the equipment. Then, the temperature fluctuation data is determined to have a fluctuation frequency, which can accurately identify the frequency characteristics of the exhaust gas temperature fluctuation, and provide important frequency information for evaluating the temperature control performance of the exhaust gas treatment device and optimizing the temperature adjustment strategy. The temperature status of the exhaust gas treatment device can be identified based on the fluctuation frequency data. It can accurately identify the temperature status of the exhaust gas treatment device according to the frequency characteristics of temperature fluctuations, including stable status, frequent fluctuation status, etc., which provides important temperature status information for equipment temperature monitoring and fault prevention, and improves the equipment's operating reliability and thermal efficiency. Integrating equipment concentration status data and equipment temperature status data can combine the concentration status and temperature status of the exhaust gas treatment device to form comprehensive equipment status information, providing rich data support for comprehensive equipment evaluation, operation optimization and fault diagnosis, fully grasping the equipment's operating status, and improving the equipment's operating efficiency and reliability.

[0032] Preferably, step S3 comprises the following steps:

[0033] Step S31: determining the adsorption layer structure of the adsorption tower equipment to generate adsorption layer structure data; performing adsorption channel detection on the adsorption layer structure data to obtain the exhaust gas adsorption channel;

[0034] Step S32: monitoring the adsorption area of ​​the exhaust gas adsorption channel according to the equipment status data to generate adsorption channel area data; identifying the adsorption state of the adsorption tower equipment according to the adsorption channel area data to obtain adsorption state data;

[0035] Step S33: determining the exhaust gas capacity of the adsorption state data to obtain the exhaust gas capacity state data; evaluating the exhaust gas saturation degree of the adsorption tower equipment based on the exhaust gas capacity state data to generate an exhaust gas saturation degree value;

[0036] Step S34: monitoring the exhaust gas saturation value for abnormal activity of the adsorption material to obtain abnormal activity data of the adsorption material; performing adsorption abnormality detection on the adsorption tower equipment according to the abnormal activity data of the adsorption material to obtain abnormal adsorption data;

[0037] Step S35: Dynamically switch the processing operation of the catalytic combustion equipment based on the adsorption abnormality data and generate dynamic processing operation measures.

[0038] The present invention determines the adsorption layer structure of the adsorption tower equipment, can accurately describe the adsorption layer structure inside the adsorption tower, and provides a structural basis for subsequent adsorption channel detection. Next, the adsorption channel detection is performed on the adsorption layer structure data, which can identify the flow path of the waste gas in the adsorption tower, provide important channel information for analyzing the adsorption efficiency and distribution of the waste gas, and optimize the design and operation of the adsorption tower. The adsorption area monitoring of the waste gas adsorption channel according to the equipment status data can monitor the distribution of the waste gas in the adsorption channel in real time, and provide regional distribution information for evaluating the adsorption performance of the adsorption tower. Then, the adsorption state of the adsorption tower equipment is identified according to the adsorption channel area data, which can accurately identify the adsorption state of the adsorption tower in different areas, including adsorption efficiency, adsorption capacity, etc., which provides important state information for the operation monitoring and optimization of the adsorption tower, and improves the processing efficiency and stability of the adsorption tower. The waste gas capacity is determined by the adsorption state data, which can accurately calculate the waste gas capacity of the adsorption tower under different states, and provide capacity information for evaluating the adsorption capacity and processing capacity of the adsorption tower. Next, the exhaust gas saturation degree of the adsorption tower equipment is evaluated based on the exhaust gas capacity status data, which can determine the adsorption saturation state of the adsorption tower, provide a basis for the replacement and regeneration of the adsorption tower, extend the service life of the adsorption tower and improve the adsorption efficiency. Abnormal monitoring of the adsorption material activity of the exhaust gas saturation value can timely discover problems such as the decrease in activity of the adsorption material during the adsorption process, and provide abnormal monitoring information for the maintenance and replacement of the adsorption material. Then, adsorption abnormality detection of the adsorption tower equipment based on the abnormal data of the adsorption material activity can accurately identify the abnormal conditions that occur during the operation of the adsorption tower, provide important abnormal data for the fault diagnosis and treatment of the adsorption tower, and improve the operational reliability and stability of the adsorption tower. Based on the abnormal adsorption data, the processing operation of the catalytic combustion equipment is dynamically switched, and the working mode and parameters of the catalytic combustion equipment can be dynamically adjusted according to the operating state and abnormal conditions of the adsorption tower, ensuring the overall operating efficiency and treatment effect of the exhaust gas treatment device, and realizing the intelligent control and optimized operation of the exhaust gas treatment device.

[0039] Preferably, step S33 includes the following steps:

[0040] Step S331: determining the reduction in thickness of the adsorption layer of the adsorption tower equipment to obtain the reduction in thickness of the adsorption layer; correlating the adsorption state data with the waste gas adsorption amount according to the reduction in thickness of the adsorption layer to obtain the waste gas adsorption amount;

[0041] Step S332: dividing the adsorption layer pressure gradient of the adsorption tower equipment based on the exhaust gas adsorption amount to obtain the adsorption layer pressure gradient; mapping the channel pressure level of the exhaust gas adsorption channel according to the adsorption layer pressure gradient to generate channel pressure level data;

[0042] Step S333: determining the exhaust gas capacity state according to the exhaust gas adsorption amount and the channel pressure level data to obtain the exhaust gas capacity state data;

[0043] Step S334: setting an exhaust gas capacity threshold for the exhaust gas capacity state data to generate an exhaust gas capacity threshold; performing exhaust gas capacity saturation judgment on the exhaust gas capacity state data and the exhaust gas capacity threshold to obtain an exhaust gas capacity saturation situation;

[0044] Step S335: Calculate the saturation of the waste gas capacity to generate waste gas saturation data; determine the waste gas capacity saturation degree of the adsorption tower equipment based on the waste gas saturation data to generate a waste gas saturation degree value.

[0045] The present invention determines the reduction in the thickness of the adsorption layer of the adsorption tower equipment, can accurately measure the thickness change of the adsorption layer during use, and provides basic data for evaluating the loss of the adsorption material. Then, the adsorption state data is associated with the waste gas adsorption amount according to the reduction in the thickness of the adsorption layer, and the thickness change of the adsorption layer can be directly associated with the adsorption amount of the waste gas, providing accurate adsorption information for analyzing the adsorption efficiency and adsorption capacity of the adsorption tower, and optimizing the operating parameters and replacement cycle of the adsorption tower. Based on the waste gas adsorption amount, the adsorption tower equipment is divided into adsorption layer pressure gradients, and the pressure distribution in the adsorption layer can be divided into different gradient areas according to the adsorption amount of the waste gas, providing pressure gradient information for analyzing the pressure change and adsorption efficiency of the adsorption layer. Then, according to the pressure gradient of the adsorption layer, the channel pressure level mapping of the waste gas adsorption channel is performed, and the pressure gradient of the adsorption layer can correspond to the pressure distribution of the waste gas adsorption channel, providing detailed channel pressure level information for evaluating the flow characteristics and adsorption efficiency of the waste gas in the adsorption channel, and optimizing the design and operation of the adsorption channel. The waste gas capacity state is determined according to the waste gas adsorption amount and channel pressure level data, which can comprehensively consider the waste gas adsorption amount and the pressure distribution of the adsorption channel, accurately evaluate the waste gas capacity state of the adsorption tower, including the size and distribution of the adsorption capacity, and provide comprehensive capacity state information for the operation monitoring and optimization of the adsorption tower, and improve the processing capacity and efficiency of the adsorption tower. The waste gas capacity threshold is set for the waste gas capacity state data, and a reasonable waste gas capacity threshold can be set according to the design and operation requirements of the adsorption tower, providing a standard basis for judging the adsorption saturation state of the adsorption tower. Then, the waste gas capacity state data and the waste gas capacity threshold are used to judge the waste gas capacity saturation, which can accurately judge whether the waste gas capacity of the adsorption tower under the current operating state has reached saturation, providing important saturation judgment information for the maintenance and replacement of the adsorption tower, and timely adjusting the operation strategy of the adsorption tower and extending its service life. The saturation quantity of the waste gas capacity saturation is measured and the waste gas saturation quantity data is generated, which can accurately calculate the waste gas saturation quantity of the adsorption tower according to the waste gas capacity saturation, and provide specific saturation quantity information for evaluating the adsorption saturation degree of the adsorption tower. Then, based on the waste gas saturation data, the waste gas capacity saturation degree of the adsorption tower equipment is determined, and the waste gas saturation can be compared with the total adsorption capacity of the adsorption tower, providing important saturation information for operation monitoring, maintenance and optimization of the adsorption tower, thereby improving the operation efficiency and processing capacity of the adsorption tower.

[0046] Preferably, step S34 includes the following steps:

[0047] Step S341: Determine the difference between the exhaust gas saturation value and the exhaust gas capacity threshold to generate an exhaust gas supersaturation difference;

[0048] Step S342: recording the adsorption amount per unit time of the adsorption tower equipment according to the waste gas supersaturation difference to obtain the adsorption amount per unit time; calculating the adsorption rate of the adsorption amount per unit time to generate the adsorption rate of the adsorption tower;

[0049] Step S343: extracting the abnormal rate of the adsorption tower adsorption rate to obtain the abnormal adsorption rate; detecting the abnormal level of adsorption material activity of the adsorption tower equipment based on the abnormal adsorption rate to generate abnormal adsorption material activity data;

[0050] Step S344: judging the degree of influence of the adsorption efficiency of the adsorption tower equipment according to the abnormal activity data of the adsorption material to obtain the degree of influence of the adsorption efficiency; determining the adsorption abnormality of the degree of influence of the adsorption efficiency to obtain the adsorption abnormality data.

[0051] The present invention determines the difference between the waste gas saturation value and the waste gas capacity threshold, and can accurately calculate the extent to which the waste gas adsorption amount of the adsorption tower in the current state exceeds its design capacity, providing important difference information for evaluating the operating state and adsorption efficiency of the adsorption tower. Through the waste gas supersaturation difference, it is identified whether the adsorption tower is in a supersaturated state. According to the waste gas supersaturation difference, the adsorption amount per unit time of the adsorption tower equipment is recorded, and the waste gas adsorption amount per unit time of the adsorption tower can be monitored in real time, providing data support in the time dimension for analyzing the adsorption performance of the adsorption tower. Then, the adsorption rate calculation of the adsorption amount per unit time can accurately calculate the adsorption rate of the adsorption tower, that is, the amount of waste gas that the adsorption tower can adsorb per unit time, providing important rate information for evaluating the adsorption efficiency and processing capacity of the adsorption tower, optimizing the operating parameters of the adsorption tower and improving its processing efficiency. Abnormal rate extraction of the adsorption rate of the adsorption tower can identify abnormal adsorption rates that occur during the operation of the adsorption tower, such as too low or too high adsorption rates, and provide abnormal rate information for monitoring the operating state of the adsorption tower. Based on the abnormal adsorption rate, the abnormal level of adsorption material activity of the adsorption tower equipment is detected. It can be judged whether the activity level of the adsorption material is abnormal according to the abnormal adsorption rate, such as aging or failure of the adsorption material, etc., which provides abnormal detection data for the maintenance and replacement of the adsorption material, and improves the operation reliability and adsorption efficiency of the adsorption tower. According to the abnormal data of adsorption material activity, the degree of influence of the adsorption efficiency of the adsorption tower equipment is judged, and the specific degree of influence of the abnormal activity of the adsorption material on the adsorption efficiency of the adsorption tower can be accurately evaluated, and the degree of influence information is provided for the optimization and maintenance of the adsorption tower. Then, the degree of influence of the adsorption efficiency is determined by the adsorption abnormality. According to the degree of influence of the adsorption efficiency, it can be judged whether there is an adsorption abnormality in the adsorption tower, such as a significant decrease in adsorption efficiency, etc., which provides important abnormal data for the fault diagnosis and treatment of the adsorption tower, and timely discovers and solves the operation problems of the adsorption tower to ensure its normal operation and efficient treatment of waste gas.

[0052] Preferably, step S35 includes the following steps:

[0053] Step S351: when the adsorption tower equipment shows abnormal adsorption data, the catalytic combustion equipment is started;

[0054] Step S352: extracting the abnormal exhaust gas adsorption amount from the abnormal adsorption data to generate the abnormal exhaust gas adsorption amount;

[0055] Step S353: determining the catalyst type of the catalytic combustion equipment based on the abnormal adsorption amount of exhaust gas to generate the catalyst type; matching the catalyst usage of the catalyst type to obtain catalyst usage data;

[0056] Step S354: determining the exhaust gas intake amount of the catalytic combustion equipment based on the exhaust gas abnormal adsorption amount to generate the combustion exhaust gas intake amount; matching the combustion exhaust gas intake amount with the oxygen supply amount to obtain the oxygen supply matching amount;

[0057] Step S355: determining the catalytic combustion conditions of the catalytic combustion equipment based on the catalyst usage data, the combustion exhaust gas intake volume and the oxygen supply matching volume, and obtaining the exhaust gas catalytic combustion conditions;

[0058] Step S356: Dynamically switch the processing operation of the catalytic combustion equipment according to the exhaust gas catalytic combustion conditions, and generate dynamic processing operation measures.

[0059] When the adsorption tower equipment has abnormal adsorption data, the present invention can start the catalytic combustion equipment in time to ensure the continuity and effectiveness of the exhaust gas treatment process. It can quickly respond to the abnormal situation of the adsorption tower to avoid the interruption of exhaust gas treatment or the decline of treatment effect, thereby ensuring the stable operation of the entire exhaust gas treatment system. The exhaust gas abnormal adsorption amount is extracted from the adsorption abnormal data, and the exhaust gas adsorption amount of the adsorption tower under the abnormal state can be accurately identified, which provides important abnormal adsorption amount data for the subsequent catalytic combustion equipment parameter adjustment, optimizes the catalytic combustion process in a targeted manner, and improves the exhaust gas treatment efficiency. The catalyst type of the catalytic combustion equipment is determined based on the abnormal adsorption amount of the exhaust gas, and the appropriate catalyst type can be selected according to the abnormal adsorption characteristics of the exhaust gas to improve the efficiency and effect of the catalytic combustion. Then, the catalyst type is matched with the catalyst dosage, and the optimal catalyst dosage can be determined according to the catalyst type and the exhaust gas characteristics, ensuring the efficient progress of the catalytic combustion process and avoiding the waste of the catalyst. The exhaust gas intake amount of the catalytic combustion equipment is determined based on the abnormal adsorption amount of the exhaust gas, and the exhaust gas intake amount of the catalytic combustion equipment can be reasonably determined according to the abnormal adsorption amount of the exhaust gas, providing a suitable exhaust gas flow rate for the catalytic combustion process. Then, the oxygen supply is matched to the combustion exhaust gas intake, and the oxygen supply can be accurately matched according to the exhaust gas intake and the needs of the catalytic combustion reaction, ensuring the full progress of the catalytic combustion reaction and improving the efficiency and effect of the exhaust gas treatment. The catalytic combustion conditions of the catalytic combustion equipment are determined based on the catalyst dosage data, the combustion exhaust gas intake and the oxygen supply matching amount, and the exhaust gas catalytic combustion conditions are obtained. The optimal operating conditions of the catalytic combustion equipment can be accurately determined by comprehensively considering factors such as the catalyst dosage, the exhaust gas intake and the oxygen supply, providing comprehensive condition data for the optimization of the catalytic combustion process, and achieving efficient and stable exhaust gas treatment. The catalytic combustion equipment is dynamically switched according to the exhaust gas catalytic combustion conditions, and the operating parameters and operation modes of the catalytic combustion equipment can be dynamically adjusted according to the changes in the catalytic combustion conditions, ensuring that the catalytic combustion process is always in the best state, improving the efficiency and effect of exhaust gas treatment, and realizing intelligent control and optimized operation of the exhaust gas treatment system.

[0060] Preferably, step S4 comprises the following steps:

[0061] Step S41: continuously monitor the operation of the exhaust gas treatment device to obtain real-time operation monitoring data;

[0062] Step S42: identifying the abnormal operation state of the device based on the real-time operation monitoring data to obtain the abnormal operation state of the device; determining the abnormal operation mode of the abnormal operation state of the device to generate the abnormal operation mode of the device;

[0063] Step S43: Perform an abnormal operation warning on the abnormal operation mode of the device and generate an abnormal operation warning report of the device;

[0064] Step S44: Based on the abnormal operation warning report of the device, the abnormal operation equipment area of ​​the exhaust gas treatment device is located to obtain abnormal equipment area information; the abnormal equipment area information is processed and dynamic measures are executed to complete the real-time monitoring operation of the exhaust gas treatment device.

[0065] The present invention continuously monitors the operation of the waste gas treatment device and can obtain the operation parameters and status information of the waste gas treatment device in real time. Through continuous monitoring, any changes and abnormalities of the waste gas treatment device during operation can be discovered in time, ensuring a comprehensive grasp of the operation of the device. The abnormal operation state of the device can be identified based on the real-time operation monitoring data, and the abnormal state of the waste gas treatment device during operation can be accurately identified, such as parameter deviation from the normal range or equipment failure, etc., providing important abnormal state information for subsequent abnormal processing. Then, the abnormal operation mode of the device operation is determined, and the abnormal operation mode of the device is generated. The identified abnormal state can be classified into specific abnormal modes, such as overload, overheating, etc., which provides clear abnormal mode data for analyzing the cause of the abnormality and formulating countermeasures, and improves the pertinence and effectiveness of abnormal processing. The abnormal operation mode of the device is given an abnormal operation warning, and a warning signal can be issued in time according to the abnormal operation mode of the device, and a detailed warning report can be generated, providing warning information for the maintenance and management of the equipment. Through the warning report, relevant personnel can quickly understand the abnormal conditions and risks of the device, take measures to deal with it in advance, avoid further deterioration of the abnormal conditions, and ensure the stable operation of the waste gas treatment device. Based on the abnormal operation warning report of the device, the abnormal operation equipment area of ​​the exhaust gas treatment device is located to obtain the abnormal equipment area information. The equipment area with abnormalities in the exhaust gas treatment device can be accurately located according to the warning report, providing clear area information for subsequent processing operations. Then, dynamic measures are executed to process the abnormal equipment area information to complete the real-time monitoring of the exhaust gas treatment device operation. According to the specific situation of the abnormal equipment area, the corresponding processing measures can be dynamically adjusted and executed, such as adjusting the operating parameters, starting the backup equipment, etc., to ensure the normal operation of the exhaust gas treatment device and the optimization of the treatment effect, and realize real-time monitoring and effective control of the device operation.

[0066] In this specification, a real-time monitoring system for the operation of an exhaust gas treatment device is provided, which is used to execute the above-mentioned real-time monitoring method for the operation of an exhaust gas treatment device. The real-time monitoring system for the operation of an exhaust gas treatment device includes:

[0067] The device data acquisition module uses intelligent sensors to collect exhaust gas treatment device data; performs data preprocessing on the exhaust gas treatment device data to obtain standard exhaust gas treatment device data; performs multi-modal recognition on the standard exhaust gas treatment device data to generate multi-modal processing data;

[0068] The equipment status identification module divides the multi-modal processing data into processing processes to obtain processing process data; performs exhaust gas characterization monitoring on the processing process data to generate exhaust gas characterization data; and identifies equipment status characteristics of the exhaust gas treatment device based on the exhaust gas characterization data to obtain equipment status data;

[0069] The exhaust gas abnormal state operation module monitors the adsorption state of the adsorption tower equipment according to the equipment state data to obtain the adsorption state data; evaluates the exhaust gas saturation degree based on the adsorption state data to generate the exhaust gas saturation degree value; performs adsorption abnormality detection on the exhaust gas saturation degree value to obtain the adsorption abnormality data; dynamically switches the processing operation of the catalytic combustion equipment based on the adsorption abnormality data to generate dynamic processing operation measures;

[0070] The device operation monitoring module continuously monitors the operation of the waste gas treatment device and records the real-time operation monitoring data; issues device operation warnings based on the real-time operation monitoring data and generates device operation warning reports; and executes dynamic treatment operation measures for the waste gas treatment device based on the device operation warning reports to complete the real-time monitoring of the operation of the waste gas treatment device.

[0071] The present invention uses an intelligent sensor to collect the original data of the exhaust gas treatment device through the device data acquisition module, and performs data preprocessing to ensure the accuracy and consistency of the data, thereby obtaining the standard exhaust gas treatment device data. Then, the standard exhaust gas treatment device data is multimodally identified, which can fully capture the characteristic information of the exhaust gas treatment device in different states, and provide a detailed data basis for subsequent analysis and processing. Through the equipment state recognition module, the multimodal processing data is divided into processing processes, which makes the operation process of the exhaust gas treatment device subdivided into multiple stages, which is convenient for targeted monitoring and analysis of each stage. Then, the processing process data is monitored for exhaust gas characterization, which can accurately reflect the key parameters such as the composition and concentration of the exhaust gas, and provides an important basis for the identification of the equipment state. Finally, the exhaust gas treatment device is identified according to the exhaust gas characterization data. The operating state of the exhaust gas treatment device can be fully grasped, and accurate equipment state information is provided for subsequent monitoring and adjustment. Through the exhaust gas abnormal state operation module, the adsorption state of the adsorption tower equipment is monitored according to the equipment state data, and the adsorption efficiency and adsorption capacity of the adsorption tower can be understood in real time, providing data support for the optimization of the adsorption process. Next, the exhaust gas saturation degree is evaluated on the adsorption state data, which can determine the adsorption saturation state of the adsorption tower and provide a basis for the replacement and regeneration of the adsorption tower. Then, the exhaust gas saturation value is detected for adsorption anomaly, which can timely discover abnormal conditions in the adsorption process and provide early warning information for fault diagnosis and treatment of the adsorption tower. Finally, the processing operation of the catalytic combustion equipment is dynamically switched based on the adsorption abnormality data, and the working mode of the catalytic combustion equipment can be dynamically adjusted according to the operating state of the adsorption tower to ensure the efficient and stable operation of the exhaust gas treatment device. Through the device operation monitoring module, the exhaust gas treatment device is continuously monitored and the real-time operation monitoring data is recorded, which can fully grasp the operation of the exhaust gas treatment device and provide real-time data support for subsequent analysis and adjustment. Then, the real-time operation monitoring data is used for device operation early warning, which can timely discover potential problems and risks of the exhaust gas treatment device and provide early warning information for equipment maintenance and management. Finally, based on the device operation early warning report, the exhaust gas treatment device is processed and operated dynamically to complete the real-time monitoring operation of the exhaust gas treatment device, and the operating parameters and operation mode of the exhaust gas treatment device can be dynamically adjusted according to the early warning information to ensure the stable operation of the exhaust gas treatment device and the optimization of the treatment effect. Therefore, the present invention realizes dynamic coordinated control of the exhaust gas treatment device between devices through data processing technology, pattern recognition technology and monitoring and control technology, and promptly responds to abnormal operation warnings, thereby improving the efficiency of exhaust gas treatment device operation monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] Figure 1 A schematic flow chart of the steps of a method for real-time monitoring of the operation of an exhaust gas treatment device;

[0073] Figure 2 for Figure 1 Detailed implementation steps of step S3 in FIG.

[0074] Figure 3 for Figure 2 Detailed implementation steps of step S35;

[0075] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0076] The technical method of the present invention is described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by technicians in this field without creative work are within the scope of protection of the present invention.

[0077] In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities are implemented in software form, or in one or more hardware modules or integrated circuits, or in different network and / or processor methods and / or microcontroller methods.

[0078] It should be understood that, although the terms "first", "second", etc. are used herein to describe various units, these units should not be limited by these terms. These terms are used only to distinguish one unit from another unit. For example, without departing from the scope of the exemplary embodiments, the first unit is referred to as the second unit, and similarly the second unit is referred to as the first unit. The term "and / or" used herein includes any and all combinations of one or more of the listed associated items.

[0079] To achieve this, please refer to Figures 1 to 3 , a method for real-time monitoring of the operation of an exhaust gas treatment device, the method comprising the following steps:

[0080] Step S1: using intelligent sensors to collect exhaust gas treatment device data; performing data preprocessing on the exhaust gas treatment device data to obtain standard exhaust gas treatment device data; performing multimodal recognition on the standard exhaust gas treatment device data to generate multimodal processing data;

[0081] Step S2: dividing the multimodal processing data into processing processes to obtain processing process data; performing exhaust gas characterization monitoring on the processing process data to generate exhaust gas characterization data; and performing equipment state feature identification on the exhaust gas treatment device according to the exhaust gas characterization data to obtain equipment state data;

[0082] Step S3: monitoring the adsorption state of the adsorption tower equipment according to the equipment state data to obtain adsorption state data; evaluating the exhaust gas saturation degree of the adsorption state data to generate an exhaust gas saturation degree value; performing adsorption anomaly detection on the exhaust gas saturation degree value to obtain adsorption anomaly data; dynamically switching the processing operation of the catalytic combustion equipment based on the adsorption anomaly data to generate dynamic processing operation measures;

[0083] Step S4: Continuously monitor the operation of the exhaust gas treatment device and record the real-time operation monitoring data; issue an operation warning for the device based on the real-time operation monitoring data and generate an operation warning report for the device; and execute dynamic treatment operation measures for the exhaust gas treatment device based on the operation warning report to complete the real-time monitoring of the operation of the exhaust gas treatment device.

[0084] The present invention collects the raw data of the exhaust gas treatment device through an intelligent sensor, and performs data preprocessing to ensure the accuracy and consistency of the data, thereby obtaining the data of the standard exhaust gas treatment device. Then, the standard exhaust gas treatment device data is subjected to multimodal recognition, which can fully capture the characteristic information of the exhaust gas treatment device in different states. The multimodal processing data is divided into processing processes, which makes the operation process of the exhaust gas treatment device subdivided into multiple stages, facilitating targeted monitoring and analysis of each stage. Then, the processing process data is subjected to exhaust gas characterization monitoring, which can accurately reflect the key parameters such as the composition and concentration of the exhaust gas, and provides an important basis for the identification of the equipment status. Finally, the equipment status characteristics of the exhaust gas treatment device are identified according to the exhaust gas characterization data, which can fully grasp the operating status of the exhaust gas treatment device, and provide accurate equipment status information for subsequent monitoring and adjustment. According to the equipment status data, the adsorption state of the adsorption tower equipment is monitored, and the adsorption efficiency and adsorption capacity of the adsorption tower can be understood in real time, providing data support for the optimization of the adsorption process. Then, the exhaust gas saturation degree is evaluated on the adsorption state data, which can judge the adsorption saturation state of the adsorption tower, and provide a basis for the replacement and regeneration of the adsorption tower. Then, the adsorption anomaly detection of the exhaust gas saturation value can timely discover the abnormal situation in the adsorption process, and provide early warning information for the fault diagnosis and treatment of the adsorption tower. Finally, the processing operation of the catalytic combustion equipment is dynamically switched based on the adsorption abnormality data, and the working mode of the catalytic combustion equipment can be dynamically adjusted according to the operating status of the adsorption tower to ensure the efficient and stable operation of the exhaust gas treatment device. Continuous operation monitoring of the exhaust gas treatment device and recording of real-time operation monitoring data can fully grasp the operation of the exhaust gas treatment device and provide real-time data support for subsequent analysis and adjustment. Then, the device operation early warning of the real-time operation monitoring data can timely discover the potential problems and risks of the exhaust gas treatment device and provide early warning information for the maintenance and management of the equipment. Finally, based on the device operation early warning report, the dynamic measures for the processing operation of the exhaust gas treatment device are executed to complete the real-time monitoring operation of the exhaust gas treatment device, and the operating parameters and operation mode of the exhaust gas treatment device can be dynamically adjusted according to the early warning information to ensure the stable operation of the exhaust gas treatment device and the optimization of the treatment effect. Therefore, the present invention realizes dynamic coordinated control of the exhaust gas treatment device between devices through data processing technology, pattern recognition technology and monitoring and control technology, and promptly responds to abnormal operation warnings, thereby improving the efficiency of exhaust gas treatment device operation monitoring.

[0085] In the embodiment of the present invention, reference Figure 1 As shown, in this example, the real-time monitoring method for the operation of the exhaust gas treatment device includes the following steps:

[0086] Step S1: using intelligent sensors to collect exhaust gas treatment device data; performing data preprocessing on the exhaust gas treatment device data to obtain standard exhaust gas treatment device data; performing multimodal recognition on the standard exhaust gas treatment device data to generate multimodal processing data;

[0087] In the embodiment of the present invention, a variety of intelligent sensors, such as gas composition sensors, temperature sensors, humidity sensors, pressure sensors, and flow sensors, are installed at key positions of the exhaust gas treatment device; exhaust ports and inside the treatment tower to monitor the composition, temperature, humidity, pressure, flow and other parameters of the exhaust gas in real time; the sensors are specifically used to communicate with the data acquisition platform through wireless connection, and the collected raw exhaust gas data is transmitted to the data acquisition platform, such as using the HJ212 protocol to transmit the data to the environmental protection bureau platform or the enterprise local monitoring platform, so as to facilitate the centralized management and analysis of the data. Data preprocessing technologies such as data cleaning, data conversion and data standardization are used to process the collected raw exhaust gas data to improve the quality and availability of the data. The raw data is cleaned to remove invalid data such as outliers, duplicate values ​​and missing values, such as identifying and eliminating abnormal data beyond the normal range by setting thresholds. Then, the data is converted to convert data in different formats and units into standard formats and units, such as converting temperature data from Celsius to Kelvin; finally, the data is standardized to meet the requirements of standard exhaust gas treatment device data, such as normalizing the exhaust gas concentration data so that its value range is between 0 and 1. Use pattern recognition technology to perform multimodal recognition on standard exhaust gas treatment device data, extract feature information from the data, and generate multimodal processing data; select appropriate machine learning algorithms, such as support vector machines (SVM), to train and learn standard exhaust gas treatment device data, and establish a mapping relationship between data features and exhaust gas treatment effects. Then, input the new standard exhaust gas treatment device data into the trained model for feature extraction and recognition to generate processing data containing multimodal features such as exhaust gas composition, temperature, humidity, pressure and flow; identify the correlation between different exhaust gas components and their influence on the exhaust gas treatment effect through a neural network model, thereby providing a basis for subsequent exhaust gas treatment optimization.

[0088] Step S2: dividing the multimodal processing data into processing processes to obtain processing process data; performing exhaust gas characterization monitoring on the processing process data to generate exhaust gas characterization data; and performing equipment state feature identification on the exhaust gas treatment device according to the exhaust gas characterization data to obtain equipment state data;

[0089] In the embodiment of the present invention, the time series analysis technology is used to divide the multimodal processing data in chronological order to obtain the processing process data. The specific operation is to first determine the operation cycle of the exhaust gas treatment device, the entire process from startup to shutdown, and then divide the multimodal processing data into different subsequences according to the working stages of the exhaust gas treatment device, such as the pretreatment stage, the adsorption stage and the desorption stage, each subsequence corresponds to a specific processing stage. The processing data in the pretreatment stage includes the change sequence of parameters such as temperature, humidity, pressure and flow rate before the exhaust gas enters the treatment device; the processing data is analyzed and monitored by machine learning algorithms and pattern recognition technology. Specifically, cluster analysis is performed on the processing data to identify different patterns and characteristics in the exhaust gas treatment process. The exhaust gas concentration data is clustered into three categories of high concentration, medium concentration and low concentration through the K-means algorithm, thereby obtaining exhaust gas characterization data, such as the clustering results of exhaust gas concentration and the characteristic parameters of each category; the equipment status characteristics of the exhaust gas treatment device are identified according to the exhaust gas characterization data using deep learning models and feature extraction technology to obtain equipment status data; specifically, a convolutional neural network is constructed, the exhaust gas characterization data is used as input, and the data is feature extracted through the convolution layer and pooling layer of the model to identify the equipment status characteristics of the exhaust gas treatment device, such as the operating status, fault status and maintenance status of the equipment. For example, the equipment status characteristics of the exhaust gas treatment device when treating high-concentration exhaust gas, such as abnormal temperature increase and pressure fluctuation, are identified through the CNN model, thereby obtaining equipment status data.

[0090] Step S3: monitoring the adsorption state of the adsorption tower equipment according to the equipment state data to obtain adsorption state data; evaluating the exhaust gas saturation degree of the adsorption state data to generate an exhaust gas saturation degree value; performing adsorption anomaly detection on the exhaust gas saturation degree value to obtain adsorption anomaly data; dynamically switching the processing operation of the catalytic combustion equipment based on the adsorption anomaly data to generate dynamic processing operation measures;

[0091] In the embodiment of the present invention, the adsorption state of the adsorption tower equipment is monitored in real time by using a sensor network and a data acquisition system. The specific operation is to install temperature sensors, pressure sensors and flow sensors at key positions of the adsorption tower to collect parameters such as the inlet flue gas temperature, filler temperature, outlet flue gas temperature, pressure and flow of the adsorption tower; by comparing the inlet flue gas temperature with the first temperature range, the filler temperature with the second temperature range and the outlet flue gas temperature with the third temperature range, the adsorption state of the adsorption tower is monitored, and corresponding alarm information is issued according to the comparison result; data analysis and modeling technology are used to evaluate the saturation degree of the exhaust gas on the adsorption state data, and specifically the collected adsorption state data is input into a pre-established exhaust gas saturation evaluation model, and the exhaust gas saturation value is calculated according to the changes in parameters such as the temperature, pressure and flow of the adsorption tower; by analyzing the changing trends of the outlet flue gas temperature and pressure of the adsorption tower, the saturation degree of the exhaust gas is evaluated, and the exhaust gas saturation value is generated. Anomaly detection algorithms are used to analyze the exhaust gas saturation values ​​to identify anomalies in the adsorption process. Specifically, statistical methods or machine learning algorithms are used to detect anomalies in the exhaust gas saturation values, identify abnormal data beyond the normal range, and generate adsorption abnormality data. For example, when the exhaust gas saturation value suddenly increases or decreases and exceeds the set threshold range, it is identified as adsorption abnormality data. Based on the adsorption abnormality data, an automated control system is used to dynamically switch the processing operations of the catalytic combustion equipment. Specifically, the adsorption abnormality data is transmitted to the PLC control system of the catalytic combustion equipment, and the operating parameters of the catalytic combustion equipment are automatically adjusted according to the type and degree of the adsorption abnormality data, and dynamic processing operation measures are generated. When an adsorption saturation abnormality occurs in the adsorption tower, the PLC control system automatically switches to the catalytic combustion mode to transfer the exhaust gas from the adsorption tower to the catalytic combustion equipment for processing.

[0092] Step S4: Continuously monitor the operation of the exhaust gas treatment device and record the real-time operation monitoring data; issue an operation warning for the device based on the real-time operation monitoring data and generate an operation warning report for the device; and execute dynamic treatment operation measures for the exhaust gas treatment device based on the operation warning report to complete the real-time monitoring of the operation of the exhaust gas treatment device.

[0093] In an embodiment of the present invention, the Internet of Things technology is used to construct a real-time monitoring system for the exhaust gas treatment device, and various sensors such as temperature sensors, pressure sensors, flow sensors, etc. are installed to collect the operating parameters of the exhaust gas treatment device in real time. The collected data is transmitted to the central monitoring system through a wireless communication module to store and manage the data; for example, temperature sensors are installed at the inlet and outlet of the catalytic combustion equipment to monitor the temperature change of the exhaust gas in real time. At the same time, a data acquisition and processing unit is used to store the collected temperature, pressure, flow and other data to form real-time operation monitoring data; data analysis and early warning algorithms are used to analyze the real-time operation monitoring data to generate an early warning report for the operation of the device; specifically, an early warning model is established to set the normal operating range and early warning threshold of parameters such as temperature and pressure. When the monitored data exceeds the normal range, the system will automatically trigger the early warning mechanism and generate an early warning report for the device operation; when the inlet temperature of the catalytic combustion equipment exceeds the preset threshold, the system will judge it as a first-level warning according to the early warning model and generate an early warning report, which contains the specific values ​​and occurrence time of the abnormal parameters; based on the device operation early warning report, dynamic measures for the processing operation of the exhaust gas treatment device are executed through the automatic control system; specifically, the abnormal information in the early warning report is transmitted to the PLC control system, and the control system automatically adjusts the operating parameters of the exhaust gas treatment device according to the preset control logic and strategy; specifically, when the temperature of the catalytic combustion equipment rises abnormally, the PLC control system will automatically reduce the power of the burner or start the cooling system to reduce the equipment temperature and ensure the safe operation of the equipment; at the same time, the system will record the adjusted operating parameters and equipment status.

[0094] Preferably, step S1 comprises the following steps:

[0095] Step S11: using intelligent sensors to collect data from the exhaust gas treatment device;

[0096] Step S12: performing data denoising on the exhaust gas treatment device data to obtain device denoised data; performing defect value filling on the device denoised data to generate device defect value filled data;

[0097] Step S13: standardizing the device defect value filling data to obtain standard exhaust gas treatment device data;

[0098] Step S14: extracting the features of the standard exhaust gas treatment device data to generate exhaust gas treatment device features; performing feature structure processing on the exhaust gas treatment device features to obtain device feature structured data;

[0099] Step S15: performing processing mode recognition on the device feature structured data to obtain device processing mode data; performing multimodal feature fusion on the device processing mode data to generate multimodal processing data.

[0100] In the embodiment of the present invention, a variety of intelligent sensors are installed at key parts of the exhaust gas treatment device, such as gas composition sensors, temperature sensors, humidity sensors, pressure sensors, flow sensors, etc., to monitor the operating parameters of the exhaust gas treatment device in real time. For example, a gas composition sensor is installed at the inlet of the exhaust gas treatment device to monitor the CO, SO x 、NO xThe concentration of polluted gases; temperature sensors and humidity sensors are installed inside the treatment device to monitor the temperature and humidity changes of the exhaust gas; pressure sensors and flow sensors are installed at the exhaust gas outlet to monitor the exhaust gas discharge pressure and flow. Digital filtering technology is used to denoise the collected data of the exhaust gas treatment device. Commonly used digital filters include low-pass filters, high-pass filters, band-pass filters, and band-stop filters. For example, when denoising the temperature data of the exhaust gas treatment device, a low-pass filter is used to set a cutoff frequency to filter out noise signals above the frequency and retain the effective signals of the low frequency to obtain the denoised data of the device. Interpolation methods are used to fill the defective values ​​in the denoised data of the device. Commonly used interpolation methods include linear interpolation, polynomial interpolation, spline interpolation, etc. For example, when there are missing values ​​in the flow data of the exhaust gas treatment device, linear interpolation is used to calculate the estimated value of the missing value based on the flow values ​​of the two valid data points before and after the missing value, fill it into the data sequence, and generate the device defect value filling data. The data standardization method is used to process the device defect value filling data. Common standardization methods include Z-score standardization, minimum-maximum standardization and normalization. For example, when standardizing the temperature data of the exhaust gas treatment device, the Z-score standardization method is used to calculate the difference between each temperature value and the average value, and then divided by the standard deviation to convert the temperature data into a standard normal distribution to obtain the standard exhaust gas treatment device data. Signal processing technology is used to extract features from the standard exhaust gas treatment device data. Common signal processing methods include Fourier transform, wavelet transform, time-frequency analysis, etc. When extracting features from the vibration signal data of the exhaust gas treatment device, Fourier transform is used to convert the time domain signal into a frequency domain signal, extract the frequency characteristics and amplitude characteristics of the signal, and generate the exhaust gas treatment device characteristics. The extracted exhaust gas treatment device features are organized and stored using data structuring technology; for example, the extracted exhaust gas treatment device features are stored in a relational database, a data table structure is established, and different features are organized according to attribute fields, such as temperature features, pressure features, flow features, etc., to generate device feature structured data. Machine learning algorithms are used to perform pattern recognition on the characteristic structured data of the device. For example, support vector machines are used to identify the operating mode of the exhaust gas treatment device. The characteristic structured data of the device is used as input, and a classification model is established through training to identify the normal operating mode and abnormal operating mode of the device, so as to obtain the device processing mode data. The device processing mode data of different modes are integrated using feature fusion technology. Common fusion methods include weighted fusion, series fusion and parallel fusion. The temperature mode data, pressure mode data and flow mode data of the exhaust gas treatment device are weighted and fused. Different weight coefficients are set according to the importance and relevance of each modal data, and each modal data is weighted and summed to generate comprehensive multi-modal processing data.

[0101] Preferably, step S2 comprises the following steps:

[0102] Step S21: marking the processing time points of the multimodal processing data to obtain processing time marking points; dividing the processing time of the multimodal processing data according to the processing time marking points to generate processing time segmentation data;

[0103] Step S22: performing processing segment matching on the processing time segmentation data to obtain process segment matching data; performing processing segment division on the multimodal processing data based on the process segment matching data to obtain processing process data;

[0104] Step S23: monitoring the exhaust gas concentration of the processing data to obtain exhaust gas concentration monitoring data; identifying the concentration change characteristics of the exhaust gas concentration monitoring data to generate exhaust gas concentration change characteristics;

[0105] Step S24: monitoring the exhaust gas temperature of the processing data to obtain exhaust gas temperature monitoring data; identifying the temperature change characteristics of the exhaust gas temperature monitoring data to generate exhaust gas temperature change characteristics;

[0106] Step S25: merging the exhaust gas concentration variation characteristics and the exhaust gas temperature variation characteristics to generate exhaust gas characterization data;

[0107] Step S26: Identify the equipment status characteristics of the exhaust gas treatment device according to the exhaust gas characterization data to obtain equipment status data.

[0108] In the embodiment of the present invention, the time series analysis technology is used to mark the time points of the multimodal processing data; during the operation of the exhaust gas treatment device, the multimodal processing data is analyzed by the sliding window algorithm, a fixed time window length (such as 1 minute) is set, and a time point is extracted every 1 minute in the data sequence as the processing time identification point. Based on the processing time identification point, the multimodal processing data is time-segmented by using the data segmentation technology; according to the processing time identification point, the multimodal processing data is segmented according to the time interval of every 1 minute, and each segmented data block contains multimodal data such as exhaust gas concentration and temperature within 1 minute. The processing time segmentation data is matched with the process segment using the pattern matching algorithm, and the commonly used algorithms are dynamic time warping (DTW); a normal operation process template of the exhaust gas treatment device is established, which includes the characteristic data of the pretreatment, adsorption, desorption and other stages, and then the processing time segmentation data is matched with the template using the DTW algorithm, and the process segment corresponding to each segmented data block is identified to obtain the process segment matching data. Based on the process segment matching data, data integration technology is used to divide the processing process of the multimodal processing data; the pretreatment stage data, adsorption stage data and desorption stage data in the process segment matching data are respectively integrated together to form complete processing process data. The data of each stage contains the corresponding multimodal information such as exhaust gas concentration and temperature. The exhaust gas concentration is monitored in real time by using gas sensors and data acquisition systems. Electrochemical sensors are installed at the exhaust outlet of the exhaust gas treatment device to monitor the concentration in the exhaust gas in real time, and the data is transmitted to the data acquisition system to obtain the exhaust gas concentration monitoring data. Data analysis and feature extraction techniques are used to identify the concentration change characteristics of the exhaust gas concentration monitoring data, and time series analysis is performed on the exhaust gas concentration monitoring data. The mean, variance, maximum, minimum and other statistical characteristics of the concentration data are calculated to identify the rising trend, falling trend, fluctuation and other change characteristics of the concentration. The exhaust gas temperature is monitored in real time by using temperature sensors and data acquisition systems. Thermocouple sensors are installed inside the exhaust gas treatment device to monitor the temperature change of the exhaust gas in real time. Data analysis and feature extraction techniques are used to identify the temperature change characteristics of the exhaust gas temperature monitoring data, and time series analysis is performed on the exhaust gas temperature monitoring data. The mean, variance, maximum, minimum and other statistical characteristics of the temperature data are calculated to identify the rising trend, falling trend, fluctuation and other change characteristics of the temperature. The exhaust gas concentration change characteristics and the exhaust gas temperature change characteristics are weightedly fused. According to the importance of concentration characteristics and temperature characteristics in exhaust gas characterization, different weight coefficients are set, and the two characteristics are weighted and summed to generate exhaust gas characterization data; the exhaust gas characterization data is classified using a support vector machine, and the data is divided into categories such as normal operating status and fault status. An equipment status feature recognition model is established, and the exhaust gas characterization data is input and the equipment status data is output.

[0109] Preferably, step S26 includes the following steps:

[0110] Step S261: determining the continuous rising stage of the exhaust gas concentration variation characteristics to obtain the concentration rising stage; determining the continuous falling stage of the exhaust gas concentration variation characteristics to obtain the concentration falling stage;

[0111] Step S262: Identify the equipment concentration state of the exhaust gas treatment device according to the concentration rising stage and the concentration falling stage to obtain equipment concentration state data;

[0112] Step S263: performing temperature fluctuation detection on the exhaust gas temperature variation characteristics to obtain temperature fluctuation data; determining the fluctuation frequency of the temperature fluctuation data to generate fluctuation frequency data;

[0113] Step S264: Identify the temperature state of the exhaust gas treatment device according to the fluctuation frequency data to obtain the temperature state data of the device;

[0114] Step S265: Integrate the device concentration status data and the device temperature status data to obtain device status data.

[0115] In an embodiment of the present invention, a trend detection algorithm in time series analysis, such as the Cusum algorithm, is used to determine the continuous rising stage of the exhaust gas concentration change characteristics; first, a concentration rising threshold is set, and then the exhaust gas concentration change characteristics are subjected to Cusum detection. When the concentration exceeds the threshold for a certain period of time (such as 5 minutes), it is determined to be a concentration rising stage, and the concentration rising stage data is obtained; a concentration falling threshold is set, and a Cusum detection is performed on the exhaust gas concentration change characteristics. When the concentration is continuously lower than the threshold for a certain period of time (such as 5 minutes), it is determined to be a concentration falling stage; a machine learning algorithm is used to identify the concentration state of the equipment for the concentration rising stage and the concentration falling stage data, and specifically a decision tree algorithm is used to take the concentration rising stage and the concentration falling stage data as input features, train the decision tree model, and identify the concentration state of the equipment, such as normal concentration state, high concentration state, and low concentration state; a signal The Fourier transform or wavelet transform in the processing is used to detect the temperature fluctuation of the exhaust gas temperature change characteristics. Specifically, the Fourier transform is performed on the exhaust gas temperature change characteristics, the time domain signal is converted into a frequency domain signal, and the frequency component of the temperature fluctuation is identified; the fluctuation frequency of the temperature fluctuation data is determined through spectrum analysis technology, and the temperature fluctuation data is subjected to spectrum analysis to calculate the main frequency and secondary frequency of the temperature fluctuation; the machine learning algorithm is used to identify the temperature state of the equipment based on the fluctuation frequency data, and specifically a neural network algorithm is used to train the neural network model using the fluctuation frequency data as input features to identify the temperature state of the equipment, such as the normal temperature state, abnormal temperature fluctuation state, etc.; the equipment concentration state data and the equipment temperature state data are weightedly fused, and different weight coefficients are set according to the importance of the concentration state and the temperature state in the equipment state identification, and the two state data are weightedly summed to generate comprehensive equipment state data.

[0116] As an example of the present invention, refer to Figure 2 As shown, in this example, step S3 includes:

[0117] Step S31: determining the adsorption layer structure of the adsorption tower equipment to generate adsorption layer structure data; performing adsorption channel detection on the adsorption layer structure data to obtain the exhaust gas adsorption channel;

[0118] Step S32: monitoring the adsorption area of ​​the exhaust gas adsorption channel according to the equipment status data to generate adsorption channel area data; identifying the adsorption state of the adsorption tower equipment according to the adsorption channel area data to obtain adsorption state data;

[0119] Step S33: determining the exhaust gas capacity of the adsorption state data to obtain the exhaust gas capacity state data; evaluating the exhaust gas saturation degree of the adsorption tower equipment based on the exhaust gas capacity state data to generate an exhaust gas saturation degree value;

[0120] Step S34: monitoring the exhaust gas saturation value for abnormal activity of the adsorption material to obtain abnormal activity data of the adsorption material; performing adsorption abnormality detection on the adsorption tower equipment according to the abnormal activity data of the adsorption material to obtain abnormal adsorption data;

[0121] Step S35: Dynamically switch the processing operation of the catalytic combustion equipment based on the adsorption abnormality data and generate dynamic processing operation measures.

[0122] In an embodiment of the present invention, the internal structure of the adsorption tower equipment is modeled using computer-aided design (CAD) software. According to the design drawings and process requirements of the adsorption tower, a three-dimensional model of the adsorption tower is established in the CAD software, and each component of the adsorption tower, such as the tower body structure, the packing layer, the resin bed layer, the feed and discharge ports, is described in detail to generate adsorption layer structure data; the adsorption layer structure data is simulated and analyzed using gas flow simulation software, the exhaust gas adsorption channel is detected, the adsorption layer structure data is imported into the gas flow simulation software, the exhaust gas flow rate, pressure and other parameters are set, the flow path of the exhaust gas in the adsorption tower is simulated, the exhaust gas adsorption channel is identified, and the exhaust gas adsorption channel data is obtained; according to the equipment status data, the exhaust gas adsorption channel is monitored for adsorption area using a sensor network, and a gas concentration sensor and a pressure sensor are installed at a key position of the adsorption channel to monitor the concentration distribution and pressure change of the exhaust gas in the adsorption channel in real time; the adsorption channel area data is analyzed using a machine learning algorithm, and the support vector machine (SVM) algorithm is used to take the adsorption channel area data as input features to train an adsorption state recognition model to identify the normal adsorption state and adsorption saturation state of the adsorption tower; according to the adsorption state data , the exhaust gas capacity is calculated using the adsorption kinetic model, and the exhaust gas capacity of the adsorption tower in the current state is calculated according to the adsorption amount and adsorption rate in the adsorption state data, combined with the pseudo-first-order or pseudo-second-order adsorption kinetic model; based on the exhaust gas capacity state data, the exhaust gas saturation degree is evaluated using the adsorption saturation calculation formula, and the adsorption saturation of the adsorption material in the adsorption tower is calculated, that is, the ratio of the exhaust gas amount adsorbed by the adsorption material to the maximum adsorption capacity; the exhaust gas saturation value is monitored in real time, and the abnormal activity of the adsorption material is identified using the anomaly detection algorithm; the normal range threshold of the adsorption saturation degree is set, and when the exhaust gas saturation degree value exceeds the threshold, it is judged that the adsorption material activity is abnormal; combined with the abnormal activity data of the adsorption material and the operating parameters of the adsorption tower, the fault diagnosis algorithm is used to identify abnormal conditions such as the decrease in the adsorption efficiency of the adsorption tower and the failure of the adsorption material; based on the abnormal adsorption data, the catalytic combustion equipment is dynamically switched through the automatic control system for processing operations; the abnormal adsorption data is transmitted to the PLC control system of the catalytic combustion equipment, and the control system automatically adjusts the operating parameters of the catalytic combustion equipment according to the type and degree of the abnormal adsorption data, such as increasing the combustion temperature, extending the combustion time, etc., to generate dynamic processing operation measures.

[0123] Preferably, step S33 includes the following steps:

[0124] Step S331: determining the reduction in thickness of the adsorption layer of the adsorption tower equipment to obtain the reduction in thickness of the adsorption layer; correlating the adsorption state data with the waste gas adsorption amount according to the reduction in thickness of the adsorption layer to obtain the waste gas adsorption amount;

[0125] Step S332: dividing the adsorption layer pressure gradient of the adsorption tower equipment based on the exhaust gas adsorption amount to obtain the adsorption layer pressure gradient; mapping the channel pressure level of the exhaust gas adsorption channel according to the adsorption layer pressure gradient to generate channel pressure level data;

[0126] Step S333: determining the exhaust gas capacity state according to the exhaust gas adsorption amount and the channel pressure level data to obtain the exhaust gas capacity state data;

[0127] Step S334: setting an exhaust gas capacity threshold for the exhaust gas capacity state data to generate an exhaust gas capacity threshold; performing exhaust gas capacity saturation judgment on the exhaust gas capacity state data and the exhaust gas capacity threshold to obtain an exhaust gas capacity saturation situation;

[0128] Step S335: Calculate the saturation of the waste gas capacity to generate waste gas saturation data; determine the waste gas capacity saturation degree of the adsorption tower equipment based on the waste gas saturation data to generate a waste gas saturation degree value.

[0129] In an embodiment of the present invention, the reduction in thickness of the adsorption layer is calculated by measuring the initial thickness and current thickness of the adsorption layer of the adsorption tower equipment; during the adsorption process of the adsorption tower, the thickness of the adsorption layer is regularly measured using an ultrasonic thickness gauge, the initial thickness and the current thickness are recorded, and then the difference between the two is calculated to obtain the reduction in thickness of the adsorption layer; the adsorption amount of the waste gas is calculated based on the reduction in thickness of the adsorption layer and the operating parameters of the adsorption tower; given the reduction in thickness of the adsorption layer and the operating time of the adsorption tower, the waste gas flow rate and other parameters, the change in adsorption amount of the waste gas when the thickness of the adsorption layer is reduced is calculated to obtain the adsorption amount of the waste gas; pressure sensors are installed at different adsorption layer positions of the adsorption tower to measure the pressure value of each layer and divide the pressure gradient of the adsorption layer; pressure sensors are respectively installed at the upper, middle and lower adsorption layer positions of the adsorption tower to monitor and record the pressure value of each layer in real time, and the pressure gradient of the adsorption layer is divided according to the changing trend of the pressure value. The pressure gradient of the adsorption layer is mapped to the waste gas adsorption channel, and the pressure value of each adsorption layer is allocated to the corresponding waste gas adsorption channel according to the pressure gradient of the adsorption layer and the distribution of the waste gas adsorption channel to form channel pressure level data, which is used to reflect the pressure distribution of the waste gas in the adsorption channel; the waste gas capacity state of the adsorption tower is calculated based on the waste gas adsorption amount and the channel pressure level data, and the waste gas capacity of the adsorption tower in the current adsorption state is calculated according to the waste gas adsorption amount and the channel pressure level data to obtain the waste gas capacity state data, which is used to evaluate the adsorption efficiency and operation of the adsorption tower; the maximum adsorption capacity of the adsorption tower is determined, and a waste gas capacity threshold value lower than the maximum adsorption capacity is set as a standard for judging the saturation of the waste gas capacity. The exhaust gas capacity status data is compared with the exhaust gas capacity threshold to determine whether the exhaust gas capacity has reached saturation; when the exhaust gas capacity status data exceeds the set exhaust gas capacity threshold, it is determined that the exhaust gas capacity is saturated, and the exhaust gas capacity saturation situation is obtained, indicating that the adsorption capacity of the adsorption tower has reached its limit; given the maximum adsorption capacity of the adsorption material in the adsorption tower and the current amount of waste gas adsorbed, the adsorption saturation is calculated, that is, the ratio of the amount of waste gas adsorbed by the adsorption material to the maximum adsorption capacity, to obtain the exhaust gas saturation data; the exhaust gas saturation data is compared with the maximum adsorption capacity of the adsorption tower to generate an exhaust gas saturation value, which is used to reflect the adsorption efficiency and operating status of the adsorption tower equipment.

[0130] Preferably, step S34 includes the following steps:

[0131] Step S341: Determine the difference between the exhaust gas saturation value and the exhaust gas capacity threshold to generate an exhaust gas supersaturation difference;

[0132] Step S342: recording the adsorption amount per unit time of the adsorption tower equipment according to the waste gas supersaturation difference to obtain the adsorption amount per unit time; calculating the adsorption rate of the adsorption amount per unit time to generate the adsorption rate of the adsorption tower;

[0133] Step S343: extracting the abnormal rate of the adsorption tower adsorption rate to obtain the abnormal adsorption rate; detecting the abnormal level of adsorption material activity of the adsorption tower equipment based on the abnormal adsorption rate to generate abnormal adsorption material activity data;

[0134] Step S344: judging the degree of influence of the adsorption efficiency of the adsorption tower equipment according to the abnormal activity data of the adsorption material to obtain the degree of influence of the adsorption efficiency; determining the adsorption abnormality of the degree of influence of the adsorption efficiency to obtain the adsorption abnormality data.

[0135] In the embodiment of the present invention, the difference between the exhaust gas saturation value and the exhaust gas capacity threshold is calculated to generate the exhaust gas supersaturation difference; the exhaust gas saturation value is known to be 85%, and the exhaust gas capacity threshold is 90%; the exhaust gas adsorption amount of the adsorption tower equipment per unit time is recorded by a data acquisition system, and during the operation of the adsorption tower, the exhaust gas adsorption amount of the adsorption tower is recorded every hour to obtain the adsorption amount per unit time data; the adsorption rate of the adsorption tower is calculated according to the adsorption amount per unit time and the time interval; it is known that the adsorption tower adsorbs 100 cubic meters of exhaust gas within 1 hour, and the adsorption rate is 100 cubic meters / hour; a statistical analysis method is used to extract the abnormal rate from the adsorption rate data of the adsorption tower, Calculate the mean and standard deviation of the adsorption rate of the adsorption tower, and identify the adsorption rate that exceeds the mean ± 2 times the standard deviation as an abnormal adsorption rate; detect the abnormal level of adsorption material activity of the adsorption tower equipment based on the abnormal adsorption rate; when the adsorption rate of the adsorption tower decreases abnormally, it indicates that the activity of the adsorption material is reduced; judge the degree of influence of the adsorption efficiency of the adsorption tower equipment based on the abnormal data of the adsorption material activity; evaluate the degree of decrease in adsorption efficiency by analyzing the relationship between the abnormal data of the adsorption material activity and the adsorption efficiency; determine the abnormal adsorption data of the adsorption tower equipment based on the degree of influence of the adsorption efficiency; when the degree of influence of the adsorption efficiency exceeds the preset threshold, judge that the adsorption tower equipment has adsorption abnormality and generate abnormal adsorption data.

[0136] As an example of the present invention, refer to Figure 3 As shown, in this example, step S35 includes:

[0137] Step S351: when the adsorption tower equipment shows abnormal adsorption data, the catalytic combustion equipment is started;

[0138] Step S352: extracting the abnormal exhaust gas adsorption amount from the abnormal adsorption data to generate the abnormal exhaust gas adsorption amount;

[0139] Step S353: determining the catalyst type of the catalytic combustion equipment based on the abnormal adsorption amount of exhaust gas to generate the catalyst type; matching the catalyst usage of the catalyst type to obtain catalyst usage data;

[0140] Step S354: determining the exhaust gas intake amount of the catalytic combustion equipment based on the exhaust gas abnormal adsorption amount to generate the combustion exhaust gas intake amount; matching the combustion exhaust gas intake amount with the oxygen supply amount to obtain the oxygen supply matching amount;

[0141] Step S355: determining the catalytic combustion conditions of the catalytic combustion equipment based on the catalyst usage data, the combustion exhaust gas intake volume and the oxygen supply matching volume, and obtaining the exhaust gas catalytic combustion conditions;

[0142] Step S356: Dynamically switch the processing operation of the catalytic combustion equipment according to the exhaust gas catalytic combustion conditions, and generate dynamic processing operation measures.

[0143] In the embodiment of the present invention, when the adsorption tower equipment has abnormal adsorption data, the catalytic combustion equipment is started through the automatic control system; the adsorption efficiency of the adsorption tower equipment decreases, and the abnormal data of the activity of the adsorption material indicates that the adsorption has reached a saturated state. After receiving the abnormal adsorption data, the control system automatically closes the adsorption pneumatic air valve of the adsorption tower, opens the desorption pneumatic air valve of the catalytic combustion equipment, and starts the catalytic combustion equipment; the change in the exhaust gas adsorption amount before and after the adsorption efficiency of the adsorption tower equipment decreases is analyzed, and the difference between the exhaust gas adsorption amount during the period of decreased adsorption efficiency and the normal adsorption amount is calculated to obtain the abnormal exhaust gas adsorption amount; the type of catalyst required for the catalytic combustion equipment is determined according to the abnormal exhaust gas adsorption amount and the exhaust gas composition; when the abnormal exhaust gas adsorption amount is large and the main component is toluene, a precious metal catalyst such as a platinum / carbon catalyst is selected because it has good catalytic oxidation performance for toluene; the catalyst dosage is matched according to the catalyst type and the abnormal exhaust gas adsorption amount; the required catalyst dosage is calculated according to the activity of the platinum / carbon catalyst and the abnormal exhaust gas adsorption amount to ensure that the catalyst can effectively treat the exhaust gas; the exhaust gas intake volume is determined according to the abnormal exhaust gas adsorption amount and the design parameters of the catalytic combustion equipment; the abnormal exhaust gas adsorption amount is 100 cubic meters / hour, the maximum air intake allowed by the design parameters of the catalytic combustion equipment is 200 cubic meters / hour, so the exhaust gas intake is set to 100 cubic meters / hour; the oxygen supply is matched according to the exhaust gas intake and the oxidation requirements of the exhaust gas components; the exhaust gas intake is 100 cubic meters / hour, and the main component is toluene. The required oxygen amount is calculated according to the oxidation reaction equation of toluene, and the oxygen supply is matched to meet the needs of the oxidation reaction; the catalytic combustion conditions of the catalytic combustion equipment are determined by combining the catalyst dosage data, the combustion exhaust gas intake and the oxygen supply matching amount; the catalyst dosage is set to 100 grams / cubic meter, the exhaust gas intake volume is set to 100 cubic meters / hour, and the oxygen supply volume is set to 200 cubic meters / hour. The catalytic combustion conditions of the catalytic combustion equipment are determined, including the amount of catalyst, the intake volume and the oxygen supply volume. According to the exhaust gas catalytic combustion conditions, the catalytic combustion equipment is dynamically switched to perform treatment operations through the automatic control system. The specific control system automatically adjusts the operating parameters of the catalytic combustion equipment, such as the catalyst bed temperature, the intake flow rate and the oxygen supply volume, according to the determined catalytic combustion conditions, and generates dynamic treatment operation measures to ensure that the catalytic combustion equipment can efficiently treat the exhaust gas.

[0144] Preferably, step S4 comprises the following steps:

[0145] Step S41: continuously monitor the operation of the exhaust gas treatment device to obtain real-time operation monitoring data;

[0146] Step S42: identifying the abnormal operation state of the device based on the real-time operation monitoring data to obtain the abnormal operation state of the device; determining the abnormal operation mode of the abnormal operation state of the device to generate the abnormal operation mode of the device;

[0147] Step S43: Perform an abnormal operation warning on the abnormal operation mode of the device and generate an abnormal operation warning report of the device;

[0148] Step S44: Based on the abnormal operation warning report of the device, the abnormal operation equipment area of ​​the exhaust gas treatment device is located to obtain abnormal equipment area information; the abnormal equipment area information is processed and dynamic measures are executed to complete the real-time monitoring operation of the exhaust gas treatment device.

[0149] In an embodiment of the present invention, a sensor network and a data acquisition system are used to continuously monitor the operation of the exhaust gas treatment device; a variety of sensors, such as temperature sensors, pressure sensors, flow sensors, and gas concentration sensors, are installed at key locations of the exhaust gas treatment device to collect operating parameters of the device, such as temperature, pressure, flow, and exhaust gas concentration, in real time, and transmit these data to the data acquisition system to obtain real-time operation monitoring data; data analysis and anomaly detection algorithms are used to analyze the real-time operation monitoring data, identify abnormal operation states of the device, set normal operating ranges and warning thresholds for parameters such as temperature and pressure, and when the monitored data exceeds the normal range, the system will automatically identify the device as being in an abnormal operation state; based on the identified abnormal state, combined with historical operation data and a fault mode library, the device operation abnormal mode is determined, and when the temperature abnormally rises and lasts for a long time, the system will compare it with historical data and determine it as an overheating abnormal mode. The abnormal operation mode of the device is warned and an abnormal operation warning report of the device is generated. When it is determined to be an abnormal overheating mode, the system will generate a warning report containing the abnormal mode type, occurrence time, and information, and notify relevant personnel through SMS, email, etc.; according to the abnormal operation warning report of the device, the equipment layout diagram and sensor location information are used to locate the abnormal operation equipment area of ​​the exhaust gas treatment device; the warning report shows that the abnormal temperature rise occurs in the catalytic combustion equipment area, and the system will accurately locate the abnormal area of ​​the catalytic combustion equipment according to the equipment layout diagram and sensor location information. Based on the abnormal equipment area information, dynamic measures for processing operations of the exhaust gas treatment device are implemented through the automatic control system; when an overheating abnormality occurs in the catalytic combustion equipment area, the system will automatically adjust the operating parameters of the catalytic combustion equipment, such as lowering the combustion temperature, increasing the cooling water flow, etc., to eliminate the abnormal state and ensure the safe and stable operation of the device.

[0150] In this specification, a real-time monitoring system for the operation of an exhaust gas treatment device is provided, which is used to execute the above-mentioned real-time monitoring method for the operation of an exhaust gas treatment device. The real-time monitoring system for the operation of an exhaust gas treatment device includes:

[0151] The device data acquisition module uses intelligent sensors to collect exhaust gas treatment device data; performs data preprocessing on the exhaust gas treatment device data to obtain standard exhaust gas treatment device data; performs multi-modal recognition on the standard exhaust gas treatment device data to generate multi-modal processing data;

[0152] The equipment status identification module divides the multi-modal processing data into processing processes to obtain processing process data; performs exhaust gas characterization monitoring on the processing process data to generate exhaust gas characterization data; and identifies equipment status characteristics of the exhaust gas treatment device based on the exhaust gas characterization data to obtain equipment status data;

[0153] The exhaust gas abnormal state operation module monitors the adsorption state of the adsorption tower equipment according to the equipment state data to obtain the adsorption state data; evaluates the exhaust gas saturation degree based on the adsorption state data to generate the exhaust gas saturation degree value; performs adsorption abnormality detection on the exhaust gas saturation degree value to obtain the adsorption abnormality data; dynamically switches the processing operation of the catalytic combustion equipment based on the adsorption abnormality data to generate dynamic processing operation measures;

[0154] The device operation monitoring module continuously monitors the operation of the waste gas treatment device and records the real-time operation monitoring data; issues device operation warnings based on the real-time operation monitoring data and generates device operation warning reports; and executes dynamic treatment operation measures for the waste gas treatment device based on the device operation warning reports to complete the real-time monitoring of the operation of the waste gas treatment device.

[0155] The present invention uses an intelligent sensor to collect the original data of the exhaust gas treatment device through the device data acquisition module, and performs data preprocessing to ensure the accuracy and consistency of the data, thereby obtaining the standard exhaust gas treatment device data. Then, the standard exhaust gas treatment device data is multimodally identified, which can fully capture the characteristic information of the exhaust gas treatment device in different states, and provide a detailed data basis for subsequent analysis and processing. Through the equipment state recognition module, the multimodal processing data is divided into processing processes, which makes the operation process of the exhaust gas treatment device subdivided into multiple stages, which is convenient for targeted monitoring and analysis of each stage. Then, the processing process data is monitored for exhaust gas characterization, which can accurately reflect the key parameters such as the composition and concentration of the exhaust gas, and provides an important basis for the identification of the equipment state. Finally, the exhaust gas treatment device is identified according to the exhaust gas characterization data. The operating state of the exhaust gas treatment device can be fully grasped, and accurate equipment state information is provided for subsequent monitoring and adjustment. Through the exhaust gas abnormal state operation module, the adsorption state of the adsorption tower equipment is monitored according to the equipment state data, and the adsorption efficiency and adsorption capacity of the adsorption tower can be understood in real time, providing data support for the optimization of the adsorption process. Next, the exhaust gas saturation degree is evaluated on the adsorption state data, which can determine the adsorption saturation state of the adsorption tower and provide a basis for the replacement and regeneration of the adsorption tower. Then, the exhaust gas saturation value is detected for adsorption anomaly, which can timely discover abnormal conditions in the adsorption process and provide early warning information for fault diagnosis and treatment of the adsorption tower. Finally, the processing operation of the catalytic combustion equipment is dynamically switched based on the adsorption abnormality data, and the working mode of the catalytic combustion equipment can be dynamically adjusted according to the operating state of the adsorption tower to ensure the efficient and stable operation of the exhaust gas treatment device. Through the device operation monitoring module, the exhaust gas treatment device is continuously monitored and the real-time operation monitoring data is recorded, which can fully grasp the operation of the exhaust gas treatment device and provide real-time data support for subsequent analysis and adjustment. Then, the real-time operation monitoring data is used for device operation early warning, which can timely discover potential problems and risks of the exhaust gas treatment device and provide early warning information for equipment maintenance and management. Finally, based on the device operation early warning report, the exhaust gas treatment device is processed and operated dynamically to complete the real-time monitoring operation of the exhaust gas treatment device, and the operating parameters and operation mode of the exhaust gas treatment device can be dynamically adjusted according to the early warning information to ensure the stable operation of the exhaust gas treatment device and the optimization of the treatment effect. Therefore, the present invention realizes dynamic coordinated control of the exhaust gas treatment device between devices through data processing technology, pattern recognition technology and monitoring and control technology, and promptly responds to abnormal operation warnings, thereby improving the efficiency of exhaust gas treatment device operation monitoring.

[0156] Therefore, the embodiments should be regarded as illustrative and non-restrictive from all points, and the scope of the present invention is limited by the appended claims rather than the above description, and it is therefore intended that all changes falling within the meaning and range of equivalent elements of the application documents are included in the present invention.

[0157] The foregoing is merely a specific embodiment of the present invention, which enables those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features invented herein.

Claims

1. A method for real-time monitoring of the operation of an exhaust gas treatment device, characterized in that: The exhaust gas treatment device is provided with an intelligent sensor, an adsorption tower device and a catalytic combustion device. The real-time monitoring method for the operation of the exhaust gas treatment device comprises the following steps: Step S1: using intelligent sensors to collect exhaust gas treatment device data; performing data preprocessing on the exhaust gas treatment device data to obtain standard exhaust gas treatment device data; performing multimodal recognition on the standard exhaust gas treatment device data to generate multimodal processing data; Step S2: dividing the multimodal processing data into processing processes to obtain processing process data; performing exhaust gas characterization monitoring on the processing process data to generate exhaust gas characterization data; and performing equipment state feature identification on the exhaust gas treatment device according to the exhaust gas characterization data to obtain equipment state data; Step S3: monitoring the adsorption state of the adsorption tower equipment according to the equipment state data to obtain adsorption state data; evaluating the exhaust gas saturation degree of the adsorption state data to generate an exhaust gas saturation degree value; performing adsorption anomaly detection on the exhaust gas saturation degree value to obtain adsorption anomaly data; dynamically switching the processing operation of the catalytic combustion equipment based on the adsorption anomaly data to generate dynamic processing operation measures; Step S4: Continuously monitor the operation of the exhaust gas treatment device and record the real-time operation monitoring data; issue an operation warning for the device based on the real-time operation monitoring data and generate an operation warning report for the device; and execute dynamic treatment operation measures for the exhaust gas treatment device based on the operation warning report to complete the real-time monitoring of the operation of the exhaust gas treatment device.

2. The method for real-time monitoring of the operation of an exhaust gas treatment device according to claim 1, characterized in that: Step S1 includes the following steps: Step S11: using intelligent sensors to collect data from the exhaust gas treatment device; Step S12: performing data denoising on the exhaust gas treatment device data to obtain device denoised data; performing defect value filling on the device denoised data to generate device defect value filled data; Step S13: standardizing the device defect value filling data to obtain standard exhaust gas treatment device data; Step S14: extracting the features of the standard exhaust gas treatment device data to generate exhaust gas treatment device features; performing feature structure processing on the exhaust gas treatment device features to obtain device feature structured data; Step S15: performing processing mode recognition on the device feature structured data to obtain device processing mode data; performing multimodal feature fusion on the device processing mode data to generate multimodal processing data.

3. The method for real-time monitoring of the operation of an exhaust gas treatment device according to claim 1, characterized in that: Step S2 includes the following steps: Step S21: marking the processing time points of the multimodal processing data to obtain processing time marking points; dividing the processing time of the multimodal processing data according to the processing time marking points to generate processing time segmentation data; Step S22: performing processing segment matching on the processing time segmentation data to obtain process segment matching data; performing processing segment division on the multimodal processing data based on the process segment matching data to obtain processing process data; Step S23: monitoring the exhaust gas concentration of the processing data to obtain exhaust gas concentration monitoring data; identifying the concentration change characteristics of the exhaust gas concentration monitoring data to generate exhaust gas concentration change characteristics; Step S24: monitoring the exhaust gas temperature of the processing data to obtain exhaust gas temperature monitoring data; identifying the temperature change characteristics of the exhaust gas temperature monitoring data to generate exhaust gas temperature change characteristics; Step S25: merging the exhaust gas concentration variation characteristics and the exhaust gas temperature variation characteristics to generate exhaust gas characterization data; Step S26: Identify the equipment status characteristics of the exhaust gas treatment device according to the exhaust gas characterization data to obtain equipment status data.

4. The method for real-time monitoring of the operation of an exhaust gas treatment device according to claim 3, characterized in that: Step S26 includes the following steps: Step S261: determining the continuous rising stage of the exhaust gas concentration variation characteristics to obtain the concentration rising stage; determining the continuous falling stage of the exhaust gas concentration variation characteristics to obtain the concentration falling stage; Step S262: Identify the equipment concentration state of the exhaust gas treatment device according to the concentration rising stage and the concentration falling stage to obtain equipment concentration state data; Step S263: performing temperature fluctuation detection on the exhaust gas temperature variation characteristics to obtain temperature fluctuation data; determining the fluctuation frequency of the temperature fluctuation data to generate fluctuation frequency data; Step S264: Identify the temperature state of the exhaust gas treatment device according to the fluctuation frequency data to obtain the temperature state data of the device; Step S265: Integrate the device concentration status data and the device temperature status data to obtain device status data.

5. The method for real-time monitoring of the operation of an exhaust gas treatment device according to claim 1, characterized in that: Step S3 includes the following steps: Step S31: determining the adsorption layer structure of the adsorption tower equipment to generate adsorption layer structure data; performing adsorption channel detection on the adsorption layer structure data to obtain the exhaust gas adsorption channel; Step S32: monitoring the adsorption area of ​​the exhaust gas adsorption channel according to the equipment status data to generate adsorption channel area data; identifying the adsorption state of the adsorption tower equipment according to the adsorption channel area data to obtain adsorption state data; Step S33: determining the exhaust gas capacity of the adsorption state data to obtain the exhaust gas capacity state data; evaluating the exhaust gas saturation degree of the adsorption tower equipment based on the exhaust gas capacity state data to generate an exhaust gas saturation degree value; Step S34: monitoring the exhaust gas saturation value for abnormal activity of the adsorption material to obtain abnormal activity data of the adsorption material; performing adsorption abnormality detection on the adsorption tower equipment according to the abnormal activity data of the adsorption material to obtain abnormal adsorption data; Step S35: Dynamically switch the processing operation of the catalytic combustion equipment based on the adsorption abnormality data and generate dynamic processing operation measures.

6. The method for real-time monitoring of the operation of an exhaust gas treatment device according to claim 5, characterized in that: Step S33 includes the following steps: Step S331: determining the reduction in thickness of the adsorption layer of the adsorption tower equipment to obtain the reduction in thickness of the adsorption layer; correlating the adsorption state data with the waste gas adsorption amount according to the reduction in thickness of the adsorption layer to obtain the waste gas adsorption amount; Step S332: dividing the adsorption layer pressure gradient of the adsorption tower equipment based on the exhaust gas adsorption amount to obtain the adsorption layer pressure gradient; mapping the channel pressure level of the exhaust gas adsorption channel according to the adsorption layer pressure gradient to generate channel pressure level data; Step S333: determining the exhaust gas capacity state according to the exhaust gas adsorption amount and the channel pressure level data to obtain the exhaust gas capacity state data; Step S334: setting an exhaust gas capacity threshold for the exhaust gas capacity state data to generate an exhaust gas capacity threshold; performing exhaust gas capacity saturation judgment on the exhaust gas capacity state data and the exhaust gas capacity threshold to obtain an exhaust gas capacity saturation situation; Step S335: Calculate the saturation of the waste gas capacity to generate waste gas saturation data; determine the waste gas capacity saturation degree of the adsorption tower equipment based on the waste gas saturation data to generate a waste gas saturation degree value.

7. The method for real-time monitoring of the operation of an exhaust gas treatment device according to claim 5, characterized in that: Step S34 includes the following steps: Step S341: Determine the difference between the exhaust gas saturation value and the exhaust gas capacity threshold to generate an exhaust gas supersaturation difference; Step S342: recording the adsorption amount per unit time of the adsorption tower equipment according to the waste gas supersaturation difference to obtain the adsorption amount per unit time; calculating the adsorption rate of the adsorption amount per unit time to generate the adsorption rate of the adsorption tower; Step S343: extracting the abnormal rate of the adsorption tower adsorption rate to obtain the abnormal adsorption rate; detecting the abnormal level of adsorption material activity of the adsorption tower equipment based on the abnormal adsorption rate to generate abnormal adsorption material activity data; Step S344: judging the degree of influence of the adsorption efficiency of the adsorption tower equipment according to the abnormal activity data of the adsorption material to obtain the degree of influence of the adsorption efficiency; determining the adsorption abnormality of the degree of influence of the adsorption efficiency to obtain the adsorption abnormality data.

8. The method for real-time monitoring of the operation of an exhaust gas treatment device according to claim 7, characterized in that: Step S35 includes the following steps: Step S351: when the adsorption tower equipment shows abnormal adsorption data, the catalytic combustion equipment is started; Step S352: extracting the abnormal exhaust gas adsorption amount from the abnormal adsorption data to generate the abnormal exhaust gas adsorption amount; Step S353: determining the catalyst type of the catalytic combustion equipment based on the abnormal adsorption amount of exhaust gas to generate the catalyst type; matching the catalyst usage of the catalyst type to obtain catalyst usage data; Step S354: determining the exhaust gas intake amount of the catalytic combustion equipment based on the exhaust gas abnormal adsorption amount to generate the combustion exhaust gas intake amount; matching the combustion exhaust gas intake amount with the oxygen supply amount to obtain the oxygen supply matching amount; Step S355: determining the catalytic combustion conditions of the catalytic combustion equipment based on the catalyst usage data, the combustion exhaust gas intake volume and the oxygen supply matching volume, and obtaining the exhaust gas catalytic combustion conditions; Step S356: Dynamically switch the processing operation of the catalytic combustion equipment according to the exhaust gas catalytic combustion conditions, and generate dynamic processing operation measures.

9. The method for real-time monitoring of the operation of an exhaust gas treatment device according to claim 1, characterized in that: Step S4 includes the following steps: Step S41: continuously monitor the operation of the exhaust gas treatment device to obtain real-time operation monitoring data; Step S42: identifying the abnormal operation state of the device based on the real-time operation monitoring data to obtain the abnormal operation state of the device; determining the abnormal operation mode of the abnormal operation state of the device to generate the abnormal operation mode of the device; Step S43: Perform an abnormal operation warning on the abnormal operation mode of the device and generate an abnormal operation warning report of the device; Step S44: Based on the abnormal operation warning report of the device, the abnormal operation equipment area of ​​the exhaust gas treatment device is located to obtain abnormal equipment area information; the abnormal equipment area information is processed and dynamic measures are executed to complete the real-time monitoring operation of the exhaust gas treatment device.

10. A real-time monitoring system for the operation of an exhaust gas treatment device, characterized in that: Used to execute the real-time monitoring method for the operation of the exhaust gas treatment device according to claim 1, the real-time monitoring system for the operation of the exhaust gas treatment device comprises: The device data acquisition module uses intelligent sensors to collect exhaust gas treatment device data; performs data preprocessing on the exhaust gas treatment device data to obtain standard exhaust gas treatment device data; performs multi-modal recognition on the standard exhaust gas treatment device data to generate multi-modal processing data; The equipment status identification module divides the multi-modal processing data into processing processes to obtain processing process data; performs exhaust gas characterization monitoring on the processing process data to generate exhaust gas characterization data; and identifies equipment status characteristics of the exhaust gas treatment device based on the exhaust gas characterization data to obtain equipment status data; The exhaust gas abnormal state operation module monitors the adsorption state of the adsorption tower equipment according to the equipment state data to obtain the adsorption state data; evaluates the exhaust gas saturation degree based on the adsorption state data to generate the exhaust gas saturation degree value; performs adsorption abnormality detection on the exhaust gas saturation degree value to obtain the adsorption abnormality data; dynamically switches the processing operation of the catalytic combustion equipment based on the adsorption abnormality data to generate dynamic processing operation measures; The device operation monitoring module continuously monitors the operation of the waste gas treatment device and records the real-time operation monitoring data; issues device operation warnings based on the real-time operation monitoring data and generates device operation warning reports; and executes dynamic treatment operation measures for the waste gas treatment device based on the device operation warning reports to complete the real-time monitoring of the operation of the waste gas treatment device.

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