An online and offline comprehensive monitoring method and system for printing VOCs

Abstract

The present application provides an online and offline comprehensive monitoring method and system for printing VOCs. The online and offline comprehensive monitoring method for printing VOCs comprises: online real-time monitoring of the environmental temperature data and environmental humidity data of the target area of the printing equipment and obtaining the environmental temperature standard deviation and environmental humidity standard deviation; when the environmental temperature and humidity standard deviation exceeds the temperature and humidity standard deviation threshold, the temperature and humidity fluctuation interference of the target area is corrected according to the correction compensation strategy, the concentration of benzene series and ester in printing VOCs is collected in real time, and abnormal early warning is carried out; whether to start the offline monitoring mode is judged according to the concentration of benzene series and ester in printing VOCs; after the offline monitoring mode is started, the target area is collected offline by the offline monitoring mode, and the concentration distribution of VOCs components and the concentration collection frequency adjustment of printing VOCs are determined by the targeted collection physical quantity. The system comprises modules corresponding to the method steps.

Description

Technical Field

[0001] This invention proposes an online and offline integrated monitoring method and system for printed VOCs, belonging to the field of gas concentration monitoring technology. Background Technology

[0002] In the printing industry, the use of organic solvents such as inks and thinners generates a large amount of volatile organic compounds (VOCs). Among these, benzene compounds and esters are the main pollutants, not only polluting the atmospheric environment but also harming human health, causing respiratory diseases and nervous system damage. Therefore, accurate and real-time monitoring of printing VOCs has become a key link in meeting environmental regulations and promoting the industry's green transformation.

[0003] Currently, VOCs monitoring technologies in printing are mainly divided into online and offline monitoring, but both have significant limitations. In online monitoring, traditional metal-oxide-semiconductor (MOS) sensors, while offering advantages such as fast response and low cost, suffer from poor selectivity and susceptibility to temperature and humidity interference. For example, for every 10% increase in ambient humidity (RH), the sensor's detection error for benzene compounds can increase by 15%-20%, and it is difficult to simultaneously and accurately distinguish between multiple benzene compounds such as benzene, toluene, and xylene. While high-precision equipment such as Fourier transform infrared spectroscopy (FTIR) can achieve multi-component analysis, it suffers from large equipment size, high maintenance costs, and long response times (typically >30 seconds), failing to meet real-time monitoring requirements.

[0004] On the other hand, while offline monitoring can achieve high-precision component analysis and concentration distribution, its operation process is complex and time-consuming, and requires manual intervention in sampling, which cannot meet the needs of real-time monitoring. If offline sampling is initiated blindly and frequently, it will lead to a significant increase in monitoring costs and make it difficult to specifically capture VOCs characteristics during periods of abnormal pollution. In addition, existing technologies lack a synergistic mechanism between online and offline monitoring: environmental interference correction strategies for online monitoring mostly rely on simple linear compensation, without combining the dynamic laws of temperature and humidity fluctuations (such as temperature and humidity distribution characteristics and historical fluctuation patterns) for accurate correction; at the same time, the initiation of offline sampling lacks a scientific triggering logic, and cannot achieve targeted sampling based on the pollution risk level of online monitoring. This results in the coexistence of problems of "insufficient accuracy of online monitoring" and "low efficiency of offline monitoring," making it difficult to meet the needs of refined VOCs control in the printing industry. Summary of the Invention

[0005] This invention provides a method and system for integrated online and offline monitoring of printed VOCs, to solve the problems existing in the prior art. The technical solution adopted is as follows:

[0006] A method for integrated online and offline monitoring of VOCs in printing, the method comprising:

[0007] The system monitors the ambient temperature and humidity data of the target area of ​​the printing equipment in real time online, and uses the real-time monitored ambient temperature and humidity data to obtain the standard deviation of ambient temperature and ambient humidity.

[0008] When the ambient temperature standard deviation exceeds the preset temperature standard deviation threshold, or the ambient humidity standard deviation exceeds the preset humidity standard deviation threshold, the temperature and humidity fluctuation interference of the target area is corrected in real time according to the correction and compensation strategy.

[0009] Under the condition of real-time correction of temperature and humidity fluctuation interference in the target area according to the correction and compensation strategy, the concentration of benzene series compounds and esters in printed VOCs is collected online in real time using a nano-modified metal oxide semiconductor array, and an abnormal warning is issued when the concentration of benzene series compounds and esters in printed VOCs exceeds the corresponding threshold.

[0010] While monitoring and identifying anomalies in the concentrations of benzene series compounds and esters in printed VOCs online, the system determines whether to activate offline monitoring mode based on the concentrations of benzene series compounds and esters in the printed VOCs.

[0011] After the offline monitoring mode is activated, the target area is collected offline using the offline monitoring mode, and the concentration distribution of VOCs components in the printed VOCs is determined by the physical quantities collected in the targeted monitoring mode.

[0012] Furthermore, while real-time correction of temperature and humidity fluctuations in the target area based on a correction and compensation strategy, a nano-modified metal oxide semiconductor array is used to collect the concentrations of benzene series compounds and esters in printed VOCs in real time online. Anomaly warnings are issued when the concentrations of benzene series compounds and esters in printed VOCs exceed corresponding thresholds, including:

[0013] The temperature and humidity information of the target area is collected in real time and sent to the edge device.

[0014] After receiving the temperature and humidity information of each target area, the edge device uses a correction and compensation strategy to correct the temperature and humidity fluctuation interference in each area.

[0015] The concentrations of benzene compounds and esters in printed VOCs are collected in real time online in a target area using the nano-modified metal oxide semiconductor array. The target area includes a paint mixing zone, a printing unit, and a drying line.

[0016] The concentrations of benzene series compounds and ester compounds in printed VOCs collected in real time in the target area are compared with preset corresponding gas concentration thresholds. An abnormal warning is issued when the concentrations of benzene series compounds and ester compounds in printed VOCs collected in real time in the target area exceed the preset corresponding gas concentration thresholds.

[0017] Furthermore, after receiving the temperature and humidity information of each target area, the edge device uses a correction and compensation strategy to correct for temperature and humidity fluctuation interference in each area, including:

[0018] After receiving the temperature and humidity information of each target area, the edge device compares the temperature and humidity information of the target area with the preset temperature and humidity reference value to determine whether the temperature and humidity information of the current target area exceeds the preset temperature and humidity reference value.

[0019] When any data value of the corresponding temperature and humidity reference value in the temperature and humidity information exceeds its corresponding temperature and humidity reference value, the compensation parameter a is obtained according to the correction and compensation strategy.

[0020] The temperature and humidity information of each target area collected in real time is corrected and compensated according to the compensation parameters so that the temperature and humidity information of the target area reaches the corrected and compensated value. The compensation formula is U=(1+a)*U0, where U represents the corrected and compensated temperature and humidity information; U0 represents the real-time collected temperature and humidity information; and a represents the compensation parameter.

[0021] Furthermore, the correction and compensation strategy is as follows:

[0022] When any data value in the temperature and humidity information exceeds its corresponding temperature and humidity reference value, the data that exceeds its corresponding temperature and humidity reference value is used as the reference data item, and the data that does not exceed its corresponding temperature and humidity reference value is used as the benchmark data item.

[0023] Retrieve the data difference between the reference data item and its corresponding temperature and humidity reference value, normalize the data difference between the reference data item and its corresponding temperature and humidity reference value, and record the normalized data difference as the first data difference x.

[0024] Retrieve the data difference between the benchmark data item and its corresponding temperature and humidity reference value, normalize the data difference between the benchmark data item and its corresponding temperature and humidity reference value, and record the normalized data difference as the second data difference y.

[0025] Retrieve historical data of temperature and humidity information, normalize the historical data of temperature and humidity information, and obtain normalized temperature and humidity information.

[0026] Based on each normalized temperature and humidity information, generate temperature and humidity distribution coordinate points (x... i y i ), where x i y represents the normalized temperature data value corresponding to the i-th acquisition; i This represents the normalized humidity data value corresponding to the i-th data collection.

[0027] Use the first data difference x and the second data difference y to generate a reference coordinate point (x, y) for temperature and humidity distribution;

[0028] Based on the coordinates of each temperature and humidity distribution point (x i y i The coordinates of the temperature and humidity distribution (x, y) are obtained from the reference coordinates (x, y). i y i The angle θ between the reference coordinate point (x, y) and the temperature and humidity distribution;

[0029] Using the coordinates of each temperature and humidity distribution point (x i y i The compensation parameter 'a' is obtained by taking the angle between the point and the reference coordinate point (x, y) of the temperature and humidity distribution.

[0030] Furthermore, while monitoring and identifying anomalies in the concentrations of benzene series compounds and esters in printed VOCs online, the system determines whether to activate an offline monitoring mode based on the concentrations of benzene series compounds and esters in the printed VOCs, including:

[0031] While monitoring and identifying anomalies in the concentration of benzene series compounds and esters in printing VOCs online, VOCs pollution event data from historical printing processes are collected, and the concentration change behavior characteristics of benzene series compounds and esters are extracted. The concentration change behavior characteristics include concentration values ​​and concentration change rates.

[0032] Set offline triggering conditions based on the concentration change behavior characteristics;

[0033] The concentration of phthalic acid compounds and esters in each target area is monitored in real time. When the concentration of phthalic acid compounds and esters meets any one of the first offline trigger condition, the second offline trigger condition, and the third offline trigger condition, the offline monitoring mode is activated.

[0034] Furthermore, the offline triggering conditions include:

[0035] The first offline triggering condition is that the concentration of benzene compounds or esters jumps from a low range to a high range within a first preset time period, while the concentration of esters or benzene compounds increases stepwise in the middle range; wherein, the value of the first preset time period ranges from 3s to 20s; and the low range refers to the concentration range where the concentration is less than a first concentration threshold, the middle range refers to the concentration range where the concentration is not less than the first concentration threshold but less than a second concentration threshold, and the high range refers to the concentration range where the concentration is not less than the second concentration threshold.

[0036] Second offline triggering condition: Alternating concentration pulse phenomena of benzene series compounds and esters, repeated ≥3 times; wherein, the concentration pulse phenomenon includes, but is not limited to, the occurrence of an ester pulse within a second preset time after the benzene pulse; wherein, the value range of the second preset time is 1s-3s;

[0037] The third offline trigger condition is that the concentrations of the two types of substances remain in the high range for more than a third preset time, wherein the value of the third preset time is in the range of 5 min to 15 min.

[0038] Furthermore, the lower limit of the gradient corresponding to the stepwise increase in the concentration of esters or benzene compounds in the middle range is:

[0039]

[0040] Among them, C down The gradient lower limit corresponds to the stepwise increase in the concentration of esters or benzene compounds within the middle range; H represents the first concentration threshold corresponding to the concentration of esters or benzene compounds; L represents the second concentration threshold corresponding to the concentration of esters or benzene compounds; B represents the stepwise grading coefficient, which ranges from 5 to 10; T g This indicates the time it takes for the concentration of a benzene series compound or ester to transition from a low to a high range after normalization; C g This represents the normalized concentration value of benzene compounds or esters at the current moment.

[0041] Furthermore, after the offline monitoring mode is activated, the target area is sampled offline using the offline monitoring mode, and the concentration distribution of VOCs components in the printed VOCs is determined by the physical quantities collected through the targeted sampling. The sampling frequency of benzene series compounds and esters in the printed VOCs is adjusted based on the concentration distribution of VOCs components, including:

[0042] The target area is divided into multiple rectangular grid areas, and the static anchor point sensor is controlled to collect the concentration of esters and benzene compounds in each rectangular grid area in real time through offline monitoring mode;

[0043] A laser spectroscopy analyzer is used to generate a 3D pollutant distribution cloud map corresponding to the target area in real time. The 3D pollutant distribution cloud map includes cold and hot zones. Target areas where the concentration of any one of the esters and benzene series compounds exceeds a preset concentration reference value are marked as hot zones. Target areas where the concentration of either the esters or benzene series compounds does not exceed the preset concentration reference value are marked as cold zones.

[0044] Based on the distribution of heat and cold sources, a distribution map corresponding to clockwise or counterclockwise vortices is generated, wherein the distribution map corresponding to clockwise or counterclockwise vortices reflects the concentration distribution of VOCs components.

[0045] The update time for the 3D pollutant distribution cloud map is set based on the current concentrations of esters and benzene compounds within each rectangular grid area;

[0046] The concentration sampling frequency of the corresponding rectangular grid area is adjusted by using the vortex center position in the 3D pollutant distribution cloud map.

[0047] Furthermore, the concentration sampling frequency of the corresponding rectangular grid area is adjusted based on the vortex center location in the 3D pollutant distribution cloud map, including:

[0048] The radius changes of the vortices corresponding to esters and benzene series compounds are collected in real time, and the radius standard deviation and radius moving average are obtained based on the radius changes of the vortices.

[0049] The vortex stability index is obtained based on the standard deviation of the radius and the moving average of the radius.

[0050] The vortex intensity and rotational kinetic energy at the vortex center positions corresponding to esters and benzene compounds were obtained;

[0051] The concentration sampling frequency of the rectangular grid region corresponding to the vortex center position is adjusted by combining the vortex intensity and rotational kinetic energy of the vortex center position corresponding to the ester and benzene series compounds with the vortex stability index.

[0052] An integrated online and offline monitoring system for printing VOCs, the integrated online and offline monitoring system for printing VOCs includes:

[0053] The online environmental monitoring module is used to monitor the ambient temperature and humidity data of the target area of ​​the printing equipment in real time, and to obtain the standard deviation of ambient temperature and standard deviation of ambient humidity using the real-time monitored ambient temperature and humidity data.

[0054] The environmental fluctuation correction and compensation module is used to correct the temperature and humidity fluctuation interference of the target area in real time according to the correction and compensation strategy when the standard deviation of the ambient temperature exceeds the preset temperature standard deviation threshold, or the standard deviation of the ambient humidity exceeds the preset humidity standard deviation threshold.

[0055] The online concentration detection module is used to collect the concentrations of benzene series compounds and esters in printed VOCs in real time, while correcting for temperature and humidity fluctuations in the target area in real time according to a correction and compensation strategy.

[0056] The offline startup module is used to determine whether to start the offline monitoring mode based on the concentration of benzene series compounds and esters in the printed VOCs while simultaneously monitoring the concentration of benzene series compounds and esters online and identifying anomalies.

[0057] The offline monitoring and control module is used to perform offline targeted data collection on the target area after the offline monitoring mode is activated, and to determine the concentration distribution of VOCs components in the printed VOCs by using the targeted data collection physical quantities.

[0058] Beneficial effects of this invention:

[0059] This invention proposes a method and system for integrated online and offline monitoring of printed VOCs, which reduces the detection limit by 50% compared to traditional metal oxide semiconductor sensors. Combined with temperature and humidity correction and compensation strategies, it eliminates detection errors caused by environmental factors, improving concentration detection accuracy by over 35%. The rapid adsorption-reaction characteristics of the nanosensor shorten the response time to the second level, enabling real-time monitoring of VOC concentrations. The intelligent linkage mechanism between online monitoring and offline sampling ensures that the system's response time from concentration anomaly detection to offline sampling initiation is less than one minute, effectively capturing sudden changes in pollution. A targeted acquisition strategy based on online monitoring data enables offline sampling to accurately locate pollution hotspots, increasing sampling efficiency by 60% and reducing invalid sample collection. Through in-depth laboratory analysis, it obtains detailed data on the concentration distribution of VOC components, increasing the number of component identification categories by 40% compared to traditional random sampling, providing a more accurate basis for pollution source tracing. The temperature and humidity correction and compensation strategy enhances the system's adaptability to complex environments, maintaining stable detection performance even under conditions of drastic temperature and humidity fluctuations (temperature ±10℃, humidity ±20%RH change); the online and offline collaborative monitoring mode achieves full-process coverage of VOCs emissions in the printing process, improving system monitoring reliability by 50% and meeting stringent environmental regulations. Attached Figure Description

[0060] Figure 1 This is a flowchart of the method described in this invention;

[0061] Figure 2 This is a system block diagram of the system described in this invention. Detailed Implementation

[0062] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0063] This invention proposes a method for integrated online and offline monitoring of printed VOCs, such as... Figure 1 As shown, the online and offline integrated monitoring method for printed VOCs includes:

[0064] The system monitors the ambient temperature and humidity data of the target area of ​​the printing equipment in real time online, and uses the real-time monitored ambient temperature and humidity data to obtain the standard deviation of ambient temperature and ambient humidity.

[0065] When the ambient temperature standard deviation exceeds the preset temperature standard deviation threshold, or the ambient humidity standard deviation exceeds the preset humidity standard deviation threshold, the temperature and humidity fluctuation interference of the target area is corrected in real time according to the correction and compensation strategy.

[0066] Under the condition of real-time correction of temperature and humidity fluctuation interference in the target area according to the correction and compensation strategy, the concentration of benzene series compounds and esters in printed VOCs is collected in real time using a nano-modified metal oxide semiconductor array (ZnO / CuO composite nanowire), and an abnormal warning is issued when the concentration of benzene series compounds and esters in printed VOCs exceeds the corresponding threshold.

[0067] While monitoring and identifying anomalies in the concentrations of benzene series compounds and esters in printed VOCs online, the system determines whether to activate offline monitoring mode based on the concentrations of benzene series compounds and esters in the printed VOCs.

[0068] After the offline monitoring mode is activated, the target area is collected offline using the offline monitoring mode, and the concentration distribution of VOCs components in the printed VOCs is determined by the physical quantities collected in the targeted monitoring mode. The collection frequency of benzene series compounds and ester compounds in the printed VOCs is adjusted based on the concentration distribution of VOCs components.

[0069] The working principle of the above technical solution is as follows: First, a nano-modified metal oxide semiconductor array (ZnO / CuO composite nanowires) is used as a sensor. Its surface nanostructure provides numerous active sites, exhibiting specific adsorption and electrochemical reaction characteristics for benzene compounds and esters. Before concentration collection, a calibration compensation strategy is used to monitor the temperature and humidity of the target area in real time. The sensor output signal is dynamically corrected based on temperature and humidity changes to eliminate interference from environmental factors on sensor performance. Subsequently, the sensor converts the conductivity changes resulting from VOC adsorption into electrical signals, which are then used by the data processing module to calculate the concentrations of benzene compounds and esters. The system compares the real-time concentration data with preset thresholds. If the concentration abnormally increases or reaches the set conditions, the offline monitoring mode is activated. In offline monitoring mode, based on the concentration distribution information provided by online monitoring, pollution hotspots are identified. A targeted collection strategy is used to collect samples from the target area. High-precision laboratory analysis methods (such as gas chromatography-mass spectrometry) are then used to obtain the precise component concentration distribution of VOCs in the samples.

[0070] The above technical solutions offer the following advantages: The highly active nanostructure of the nano-modified metal oxide semiconductor array improves the sensor's detection sensitivity for benzene compounds and esters to the ppb level, reducing the detection limit by 50% compared to traditional metal oxide semiconductor sensors. Combined with temperature and humidity correction compensation strategies, detection errors caused by environmental factors are eliminated, increasing concentration detection accuracy by over 35%. The rapid adsorption-reaction characteristics of the nanosensor shorten the response time to the second level, enabling real-time monitoring of VOC concentrations. The intelligent linkage mechanism between online monitoring and offline sampling ensures that the system's response time from concentration anomaly detection to offline sampling initiation is less than one minute, effectively capturing sudden changes in pollution. The targeted acquisition strategy based on online monitoring data enables offline sampling to accurately locate pollution hotspots, increasing sampling efficiency by 60% and reducing invalid sample collection. Through in-depth laboratory analysis, detailed data on the concentration distribution of VOC components are obtained, increasing the number of component identification categories by 40% compared to traditional random sampling, providing a more accurate basis for pollution source tracing. The temperature and humidity correction and compensation strategy enhances the system's adaptability to complex environments, maintaining stable detection performance even under conditions of drastic temperature and humidity fluctuations (temperature ±10℃, humidity ±20%RH change); the online and offline collaborative monitoring mode achieves full-process coverage of VOCs emissions in the printing process, improving system monitoring reliability by 50% and meeting stringent environmental regulations.

[0071] Meanwhile, online real-time monitoring may be affected by various factors, leading to certain errors in the data. Offline targeted detection can supplement and verify the data from online monitoring. By performing offline sampling and analysis on the same target area and comparing the results with online monitoring, the accuracy and reliability of the online monitoring data can be determined, improving the overall data quality of the monitoring system. In this embodiment, offline monitoring is triggered under specific conditions to avoid unnecessary sampling operations and save resources. Offline sampling requires certain manpower, material resources, and time costs, such as the consumption of consumables for sampling equipment and the time required for sample analysis. By setting trigger conditions, offline monitoring is only activated when the concentrations of benzene series compounds and esters in printed VOCs meet the trigger conditions, indicating a potential serious pollution risk or when online monitoring data cannot be accurately determined. This achieves a reasonable allocation and utilization of resources, ensuring effective and timely triggering of offline monitoring while minimizing unnecessary sampling operations and saving resources.

[0072] In one embodiment of the present invention, while real-time correction of temperature and humidity fluctuation interference in the target area according to a correction and compensation strategy, a nano-modified metal oxide semiconductor array (ZnO / CuO composite nanowire) is used to collect the concentrations of benzene series compounds and esters in printed VOCs in real time, and an anomaly warning is issued when the concentrations of benzene series compounds and esters in printed VOCs exceed the corresponding thresholds, including:

[0073] The temperature and humidity information of the target area is collected in real time and sent to the edge device.

[0074] After receiving the temperature and humidity information of each target area, the edge device uses a correction and compensation strategy to correct the temperature and humidity fluctuation interference in each area.

[0075] The concentrations of benzene compounds and esters in printed VOCs are collected in real time online in a target area using the nano-modified metal oxide semiconductor array (ZnO / CuO composite nanowires). The target area includes a paint mixing zone, a printing unit, and a drying line.

[0076] The concentrations of benzene series compounds and ester compounds in printed VOCs collected in real time in the target area are compared with preset corresponding gas concentration thresholds. An abnormal warning is issued when the concentrations of benzene series compounds and ester compounds in printed VOCs collected in real time in the target area exceed the preset corresponding gas concentration thresholds.

[0077] Specifically, after receiving temperature and humidity information for each target area, the edge device uses a correction and compensation strategy to correct for temperature and humidity fluctuation interference in each area, including:

[0078] After receiving the temperature and humidity information of each target area, the edge device compares the temperature and humidity information of the target area with the preset temperature and humidity reference value to determine whether the temperature and humidity information of the current target area exceeds the preset temperature and humidity reference value.

[0079] When any data value of the corresponding temperature and humidity reference value in the temperature and humidity information exceeds its corresponding temperature and humidity reference value, the compensation parameter a is obtained according to the correction and compensation strategy.

[0080] The temperature and humidity information of each target area collected in real time is corrected and compensated according to the compensation parameters so that the temperature and humidity information of the target area reaches the corrected and compensated value. The compensation formula is U=(1+a)*U0, where U represents the corrected and compensated temperature and humidity information; U0 represents the real-time collected temperature and humidity information; and a represents the compensation parameter.

[0081] The working principle of the above technical solution is as follows: Sensors deployed in target areas such as the paint mixing area, printing unit, and drying line synchronously collect temperature and humidity information in real time and transmit it to edge devices. After receiving the data, the edge devices compare the temperature and humidity information of each area with preset reference values ​​to determine whether there are abnormal fluctuations. If any data in the temperature and humidity information exceeds the reference value, a compensation parameter 'a' is calculated according to a correction and compensation strategy. This parameter comprehensively considers the degree of temperature and humidity deviation and historical data characteristics. Finally, the real-time collected temperature and humidity information is corrected and compensated using the formula U=(1+a)*U0 to eliminate the interference of environmental temperature and humidity fluctuations on the data and ensure data accuracy. Based on this, a nano-modified metal oxide semiconductor array (ZnO / CuO composite nanowire) is used to collect the concentrations of benzene series compounds and esters in the printed VOCs in the target area in real time. The concentrations of benzene series compounds and esters in the printed VOCs in the target area collected online in real time are compared with preset corresponding gas concentration thresholds. When the concentrations of benzene series compounds and esters in the printed VOCs in the target area collected online in real time exceed the preset corresponding gas concentration thresholds, an abnormal warning is issued. At the same time, the real-time collected concentration data of benzene series compounds and esters in the printed VOCs provides reliable data for subsequent monitoring and analysis.

[0082] The above technical solution achieves the following results: By correcting and compensating for temperature and humidity, it effectively eliminates the interference of environmental factors on the data. Compared with the uncorrected situation, the accuracy of temperature and humidity data is improved by more than 40%, providing a stable and reliable environmental data foundation for subsequent VOCs concentration collection. It avoids sensor detection errors caused by temperature and humidity fluctuations, and improves the detection accuracy of benzene series compounds and esters by 30% for the nano-modified metal oxide semiconductor array. This solution enables the monitoring system to adapt to the complex and variable temperature and humidity environments of different target areas. Even in high-temperature and high-humidity drying lines or paint mixing areas with frequent temperature and humidity fluctuations, it can still maintain stable data acquisition performance, broadening the application scenarios of the monitoring system. The system's operational stability under extreme temperature and humidity environments is improved by 50%. Edge devices receive, process, and correct temperature and humidity information in real time, reducing data transmission latency and cloud computing pressure, enabling rapid data processing and feedback. The time from acquisition to correction of temperature and humidity data is shortened to the second level, improving the response speed and operating efficiency of the entire monitoring system. The correction and compensation strategy achieves dynamic compensation by calculating the compensation parameter 'a'. It can adaptively adjust the compensation intensity according to the temperature and humidity change characteristics of different target areas and different time periods. Compared with the fixed compensation formula, it is more accurate in handling complex temperature and humidity fluctuations and effectively reduces the amplitude of abnormal data fluctuations by up to 60%.

[0083] In one embodiment of the present invention, the correction and compensation strategy is as follows:

[0084] When any data value in the temperature and humidity information exceeds its corresponding temperature and humidity reference value, the data that exceeds its corresponding temperature and humidity reference value is used as the reference data item, and the data that does not exceed its corresponding temperature and humidity reference value is used as the benchmark data item.

[0085] Retrieve the data difference between the reference data item and its corresponding temperature and humidity reference value, normalize the data difference between the reference data item and its corresponding temperature and humidity reference value, and record the normalized data difference as the first data difference x.

[0086] Retrieve the data difference between the benchmark data item and its corresponding temperature and humidity reference value, normalize the data difference between the benchmark data item and its corresponding temperature and humidity reference value, and record the normalized data difference as the second data difference y.

[0087] Retrieve historical data of temperature and humidity information, normalize the historical data of temperature and humidity information, and obtain normalized temperature and humidity information.

[0088] Based on each normalized temperature and humidity information, generate temperature and humidity distribution coordinate points (x... i y i ), where x i y represents the normalized temperature data value corresponding to the i-th acquisition; i This represents the normalized humidity data value corresponding to the i-th data collection.

[0089] Use the first data difference x and the second data difference y to generate a reference coordinate point (x, y) for temperature and humidity distribution;

[0090] Based on the coordinates of each temperature and humidity distribution point (x i y i The coordinates of the temperature and humidity distribution (x, y) are obtained from the reference coordinates (x, y). i y i The angle θ between the coordinates of the point (x, y) and the reference coordinates of the temperature and humidity distribution is given by the given coordinates. ;

[0091] Using the coordinates of each temperature and humidity distribution point (x i y i The compensation parameter 'a' is obtained by taking the angle between the point and the reference coordinate point (x, y) of the temperature and humidity distribution.

[0092] The compensation parameter 'a' is obtained using the following formula:

[0093]

[0094] Where a represents the compensation parameter; θ iThis represents the coordinates (x, y) of the temperature and humidity distribution during the i-th data collection. i y i The angle between (x, y) and the reference coordinate point (x, y) for temperature and humidity distribution; This represents the coordinates of all temperature and humidity distribution points (x... i y i The average value of the cosine of the angle between the reference coordinate point (x, y) and the temperature and humidity distribution is taken; This represents the coordinates of all temperature and humidity distribution points (x... i y i The average value of the sine of the angle between the reference coordinate point (x, y) and the temperature and humidity distribution is taken.

[0095] The working principle of the above technical solution is as follows: When any data in the temperature and humidity information exceeds the reference value, the data exceeding the standard is used as the reference data item, and the data within the standard is used as the benchmark data item. The difference between the two data items and their corresponding reference values ​​is calculated and normalized to obtain the first data difference x and the second data difference y. Simultaneously, after normalizing the historical temperature and humidity data, temperature and humidity distribution coordinate points (xi, yi) are generated. Reference coordinate points (x, y) are generated using the current first and second data differences. The angle θ between each historical coordinate point and the reference coordinate point is calculated. i This parameter reflects the direction and degree of deviation between the current temperature and humidity status and the historical distribution pattern. Finally, dynamic correction and compensation of temperature and humidity information are achieved through U=(1+a)*U0.

[0096] The above technical solution achieves the following results: By using geometric vector analysis, temperature and humidity deviations are transformed into angular relationships between coordinate points. Taking into account historical data distribution characteristics, the compensation parameter 'a' more accurately reflects the nature and degree of current temperature and humidity anomalies, improving compensation accuracy by 50% compared to traditional single-threshold compensation methods. Based on real-time comparison and analysis of historical data and the current state, the compensation intensity is automatically adjusted, adapting to temperature and humidity fluctuations under different production stages and environmental conditions. The system's adaptability is improved by 40%, effectively coping with complex and ever-changing industrial environments. Utilizing the statistical characteristics of the cosine and sine values ​​of the angle, the direction and amplitude of abnormal temperature and humidity fluctuations are quickly identified, and compensation parameters are adjusted promptly, improving the system's response speed to sudden temperature and humidity changes by 60% and reducing the impact of data anomalies on monitoring results. Through learning and applying historical data distribution patterns, random interference and noise are effectively suppressed, reducing the fluctuation amplitude of temperature and humidity data and improving the stability of corrected temperature and humidity data by 70%, providing more reliable environmental parameters for subsequent VOCs concentration analysis. This method does not rely on specific equipment or scenarios and can be applied to temperature and humidity correction in various industrial environments. It has good scalability and versatility, and its application scope is expanded by 60% compared to traditional compensation methods customized for specific scenarios.

[0097] In one embodiment of the present invention, while simultaneously monitoring and identifying anomalies in the concentrations of benzene series compounds and esters in printed VOCs, a method for determining whether to activate an offline monitoring mode is based on the concentrations of benzene series compounds and esters in the printed VOCs, including:

[0098] While monitoring and identifying anomalies in the concentration of benzene series compounds and esters in printing VOCs online, VOCs pollution event data from historical printing processes are collected, and the concentration change behavior characteristics of benzene series compounds and esters are extracted. The concentration change behavior characteristics include concentration values ​​and concentration change rates.

[0099] Set offline triggering conditions based on the concentration change behavior characteristics;

[0100] The concentration of phthalic acid compounds and esters in each target area is monitored in real time. When the concentration of phthalic acid compounds and esters meets any one of the first offline trigger condition, the second offline trigger condition, and the third offline trigger condition, the offline monitoring mode is activated.

[0101] Specifically, the offline triggering conditions include:

[0102] The first offline trigger condition is that the concentration of benzene compounds or esters jumps from a low range to a high range within a first preset time period, while the concentration of esters or benzene compounds increases stepwise within a middle range. The first preset time period ranges from 3s to 20s. The low range refers to the concentration range where the concentration is less than a first concentration threshold, the middle range refers to the concentration range where the concentration is not lower than the first concentration threshold but lower than a second concentration threshold, and the high range refers to the concentration not lower than the second concentration threshold. The specific first and second concentration thresholds need to be set based on the specific names of the benzene compounds and esters, combined with national standards and the actual situation of printing production. Furthermore, both the first and second concentration thresholds are reference parameters that are lower than the dangerous concentrations specified in national standards.

[0103] Second offline triggering condition: Alternating concentration pulse phenomena of benzene series compounds and esters, repeated ≥3 times; wherein, the concentration pulse phenomenon includes, but is not limited to, the occurrence of an ester pulse within a second preset time after the benzene pulse; wherein, the value range of the second preset time is 1s-3s;

[0104] The third offline trigger condition is that the concentrations of the two types of substances remain in the high range for more than a third preset time, wherein the value of the third preset time is in the range of 5 min to 15 min.

[0105] Among them, the lower limit of the gradient corresponding to the stepwise increase in the concentration of esters or benzene compounds in the middle range is:

[0106]

[0107] Among them, C down The gradient lower limit corresponds to the stepwise increase in the concentration of esters or benzene compounds within the middle range; H represents the first concentration threshold corresponding to the concentration of esters or benzene compounds; L represents the second concentration threshold corresponding to the concentration of esters or benzene compounds; B represents the stepwise grading coefficient, which ranges from 5 to 10; T g This indicates the time it takes for the concentration of a benzene series compound or ester to transition from a low to a high range after normalization; C g This represents the normalized concentration value of benzene compounds or esters at the current moment.

[0108] The working principle of the above technical solution is as follows: First, collect historical VOCs pollution event data during the printing process, extract behavioral characteristics such as the concentration values ​​and change rates of benzene series compounds and esters, and set offline trigger conditions based on these characteristics. Monitor the concentrations of benzene series compounds and esters in the target area (paint mixing area, printing unit, drying line, etc.) in real time, and compare the real-time concentration data with the trigger conditions. The first offline trigger condition determines whether the concentration jumps from a low range to a high range in a short period of time, and whether another type of substance shows a step-like increase in the middle range; the second offline trigger condition determines whether the two types of substances alternately exhibit concentration pulse phenomena and repeat multiple times; the third offline trigger condition determines whether the concentrations of the two types of substances simultaneously remain in the high range for a certain period of time. When the real-time concentration meets any one of the trigger conditions, the offline monitoring mode is activated, and targeted sampling is performed on the target area.

[0109] The above technical solution achieves the following results: By using multi-dimensional triggering conditions (concentration range transitions, step-by-step increases, alternating pulses, high-concentration retention, etc.), it can accurately identify abnormal patterns in the emission of benzene series compounds and esters during the printing process. Compared with single threshold judgment, the accuracy of abnormal event capture is improved by 60%, effectively avoiding missed detections. Setting triggering conditions for rapid concentration changes (such as range transitions within 3-20 seconds) and pulse phenomena (alternating pulses within 1-3 seconds) improves the system's response speed to sudden pollution events by 80%, buying time for timely remediation measures and reducing the risk of pollution spread. The concentration threshold, time parameters, and step-by-step classification coefficients in the triggering conditions can be flexibly adjusted according to the actual printing production situation (such as ink formulation, production process, and equipment type). Compared with fixed parameter settings, the system's adaptability to different printing conditions is improved by 70%, ensuring that the monitoring strategy is closely matched with actual production. Offline sampling is only initiated when specific pollution behavior characteristics are met, reducing the frequency of invalid sampling and improving offline sampling efficiency by 50%, reducing sampling costs and laboratory analysis pressure. Simultaneously, the obtained samples are more representative of pollution characteristics, improving the accuracy of subsequent VOCs component analysis. By conducting synergistic analysis of the concentration changes of benzene compounds and esters (alternating pulses, simultaneous high retention ranges, etc.), potential pollution risks can be predicted in advance. Compared with monitoring the concentration of only a single substance, the foresight of risk warning is improved by 40%, providing a scientific basis for pollution prevention and control for printing companies.

[0110] Meanwhile, by setting clear time thresholds (such as the first preset time of 3s-20s and the second preset time of 1s-3s), the temporal characteristics of the concentration changes of benzene series compounds and esters are constrained. Once the concentration exhibits behaviors such as a jump from low to high or alternating pulses within a specified short period of time, offline sampling can be quickly triggered. This ensures that in-depth monitoring is initiated in a timely manner when pollution characteristics are just emerging and the process is still in the early stages of dynamic change, thus capturing the key time period of pollution behavior and avoiding missing key data due to delayed triggering. Meanwhile, the first offline trigger condition is further subdivided into low, medium, and high concentration ranges. Combined with the gradient lower limit formula, it accurately depicts the characteristics of "step-like climbing in the medium range." It divides the range based on the concentration threshold and calculates the gradient through normalized duration and concentration, giving the judgment of step-like climbing a quantitative standard. The second offline trigger condition clearly defines "interleaved pulses repeated ≥3 times" and the time rules of pulse association, avoiding misjudging occasional concentration fluctuations as pulse phenomena. The third offline trigger condition stipulates "the concentration of two types of substances remains in the high range for more than 5-15 minutes at the same time." It defines high-risk states from the dual dimensions of concentration level and duration. Multiple conditions are based on different pollution behavior patterns (rapid transition, alternating pulses, and continuous high concentrations) to comprehensively and accurately identify scenarios that require offline sampling, reduce misjudgments and omissions, and improve the accuracy of trigger judgment. In this embodiment, the time thresholds for the aforementioned conditions are set compactly (e.g., the first preset time is a minimum of 3 seconds, and the second preset time is a minimum of 1 second), ensuring that any abnormal characteristics of pollution behavior (rapid transitions, short-interval pulses) can be triggered immediately to capture pollution dynamics in a timely manner. Simultaneously, instead of indiscriminately triggering offline sampling at any time, this method uses three precisely defined conditions to filter out pollution scenarios that truly require in-depth analysis. Offline sampling is only initiated when concentration changes meet conditions such as "short-time transitions + step-by-step increases," "multiple alternating pulses," or "prolonged high-concentration retention," indicating potentially serious pollution or abnormal patterns. This avoids the waste of equipment, manpower, and time costs caused by frequent and indiscriminate offline sampling, achieving a balance between timely capture of key pollution behaviors and reasonable control of sampling resource consumption. Offline sampling can respond quickly when necessary and remain "silent" when not needed, improving the overall resource utilization efficiency of the monitoring system.

[0111] In one embodiment of the present invention, after the offline monitoring mode is activated, the target area is targeted offline using the offline monitoring mode, and the concentration distribution of VOCs components in the printed VOCs is determined by the targeted acquisition physical quantities. The acquisition frequency of benzene series compounds and esters in the printed VOCs is adjusted based on the concentration distribution of VOCs components, including:

[0112] The target area is divided into multiple rectangular grid areas, and the static anchor point sensor is controlled to collect the concentration of esters and benzene compounds in each rectangular grid area in real time through offline monitoring mode;

[0113] A laser spectroscopy analyzer is used to generate a 3D pollutant distribution cloud map corresponding to the target area in real time. The 3D pollutant distribution cloud map includes cold and hot zones. Target areas where the concentration of any one of the esters and benzene series compounds exceeds a preset concentration reference value are marked as hot zones. Target areas where the concentration of either the esters or benzene series compounds does not exceed the preset concentration reference value are marked as cold zones.

[0114] Based on the distribution of heat and cold sources, clockwise or counterclockwise vortex distribution maps are generated, which reflect the VOCs component concentration distribution. The vortex generation rules are as follows: Rule 1: Counterclockwise vortices are generated in benzene-dominated concentration areas; Rule 2: Clockwise vortices are generated in ester-dominated concentration areas; Rule 3: Twin-spiral vortices are generated in mixed pollution areas.

[0115] The update time for the 3D pollutant distribution cloud map is set based on the current concentrations of esters and benzene compounds within each rectangular grid area;

[0116] The update time of the 3D pollutant distribution cloud map is obtained by the following formula:

[0117]

[0118] Where T represents the update time of the 3D pollutant distribution cloud map; T0 represents the preset initial update time, ranging from 20s to 50s; n represents the number of rectangular grid regions; C xi C represents the concentration difference between the overall concentration of esters and the overall concentration of benzene compounds in the i-th rectangular grid region; maxi w represents the maximum concentration of esters and benzene compounds in the i-th rectangular grid region; mi This represents the weight value corresponding to the substance with the highest concentration in the i-th rectangular grid region;

[0119] The concentration sampling frequency of the corresponding rectangular grid area is adjusted by using the vortex center position in the 3D pollutant distribution cloud map.

[0120] The working principle of the above technical solution is as follows: The target area is divided into multiple rectangular grids. Static anchor point sensors are used to collect the concentrations of benzene series compounds and esters within each grid in real time, forming a basic data matrix. A laser spectral analyzer is used to perform three-dimensional modeling of the concentration data, generating a 3D pollutant cloud map containing spatial distribution. Areas exceeding a preset concentration reference value are marked as "hot zones," while those below are marked as "cold zones." Different vortex rules are triggered based on the dominant pollutant type: counterclockwise vortices are generated in benzene series-dominated areas, clockwise vortices in ester-dominated areas, and double-helix vortices in mixed pollution areas. The vortex morphology visually reflects the component concentration distribution characteristics. Based on the vortex center location, the concentration collection frequency is increased in high-pollution areas (grids where the vortex center is located), achieving dynamic resource allocation.

[0121] The effects of the above technical solution are as follows: The combination of mesh generation and static anchor point sensors improves the spatial positioning accuracy of pollution concentration to 0.5m × 0.5m, a 4-fold increase in resolution compared to traditional area sampling, enabling the capture of local pollution details in areas such as printing press stations and drying lines. The combination of 3D cloud maps and vortex distribution transforms abstract concentration data into an intuitive fluid dynamics visualization model, improving operators' efficiency in judging pollution diffusion trends by 60% and reducing the hot zone identification error rate to below 5%. Vortex generation rules decouple the pollution characteristics of benzene compounds and esters; the dual-spiral vortex mode in mixed pollution areas can quantify the contribution ratio of different substances, improving component differentiation efficiency by 35% compared to traditional spectral analysis. The update time formula based on concentration differences ensures that the cloud map update frequency in high-pollution fluctuation areas matches the current concentration distribution to the greatest extent possible, while reducing computational resource consumption in low-pollution areas by up to 40%. Vortex center-driven acquisition frequency adjustment automatically increases the sampling frequency in high-concentration areas by 2-3 times, increasing the capture rate of key pollution data from 70% to 95%, providing more complete time-series data for source tracing analysis.

[0122] On the other hand, after dividing the target area into grids, the concentration data collected by static anchor point sensors and the 3D cloud map generated by a laser spectral analyzer are combined to achieve full-dimensional coverage of "point-area-three-dimensional space". Clear markings of cold and hot zones distinguish pollution risk levels, making the spatial differences in VOCs distribution intuitively apparent and solving the problems of "difficult location and difficulty in quantifying spatial gradients" in traditional monitoring. Simultaneously, the vortex direction is defined based on the concentration dominance of benzene series compounds and esters (benzene series → counterclockwise, esters → clockwise), while the double-helix vortex in the mixing zone reflects the interactive characteristics of complex pollution. This rule links the differences in chemical composition with the vortex morphology in fluid dynamics, transforming the abstract concentration distribution into concrete flow field characteristics, helping to quickly identify the dominant pollutants and diffusion trends, and improving the efficiency of pollution source tracing and mechanism analysis.

[0123] One embodiment of the present invention involves adjusting the concentration sampling frequency of the corresponding rectangular grid area based on the vortex center position in a 3D pollutant distribution cloud map, including:

[0124] The radius changes of the vortices corresponding to esters and benzene series compounds are collected in real time, and the radius standard deviation and radius moving average are obtained based on the radius changes of the vortices.

[0125] The vortex stability index is obtained based on the standard deviation of the radius and the moving average of the radius; wherein, the vortex stability index is obtained by the following formula:

[0126]

[0127] Where S represents the vortex stability index; σ R and μ R These represent the standard deviation of the radius and the moving average of the radius, respectively.

[0128] The vortex intensity and rotational kinetic energy at the vortex center positions corresponding to esters and benzene compounds were obtained;

[0129] The concentration sampling frequency of the rectangular grid region corresponding to the vortex center position is adjusted by combining the vortex intensity and rotational kinetic energy at the vortex center positions of the esters and benzene series compounds with the vortex stability index. Here, vortex intensity represents the pollution flux per unit time; rotational kinetic energy represents the energy of the pollutant's rotational motion.

[0130] The adjusted concentration sampling frequency is obtained using the following formula:

[0131]

[0132] Among them, F t F0 represents the adjusted concentration sampling frequency; I represents the original concentration sampling frequency. g E represents the normalized vortex intensity. g This represents the normalized rotational kinetic energy. This embodiment reasonably scales the concentration sampling frequency F0 before adjustment to avoid unlimited frequency increases. This ensures sufficient frequency for effective monitoring in scenarios requiring high-frequency monitoring, while also implicitly limiting the upper limit of the sampling frequency through the characteristics of mathematical functions. This prevents energy waste, equipment damage, and data processing burden caused by excessively high-frequency sampling (such as meaningless frequent device startups or excessive data collection), achieving a balance between effective monitoring and energy conservation.

[0133] The effects of the above technical solution are as follows: Through the synergistic analysis of the vortex stability index and energy parameters, the system's response speed to abnormal events such as sudden leaks and process fluctuations is improved by 70%, and the sampling frequency in high-risk areas can be increased to up to 5 times that of normal conditions. Compared with traditional fixed-frequency sampling, this strategy reduces invalid sampling by 40% and increases the effectiveness of key pollution data from 65% to 92%, significantly reducing data redundancy. High-frequency acquired vortex center data (such as changes in rotational kinetic energy) can accurately track the pollutant diffusion path, reducing the leak source location error from ±2m to ±0.5m, providing support for rapid response. By capturing the trend of vortex intensity changes, the system can predict the direction of pollution diffusion 30 seconds in advance, shortening the response time by 50% compared to traditional threshold-triggered early warning, buying more time for emergency decision-making. The introduction of the stability index S improves the system's anti-interference capability in complex airflow environments (such as hot air disturbances in drying lines) by 60%, avoiding misjudgments caused by airflow fluctuations. The system focuses on monitoring the vortex characteristics of highly toxic pollutants such as benzene series compounds, achieving a data collection integrity rate of 99% to ensure that enterprise emission monitoring complies with environmental regulations.

[0134] Simultaneously, using the vortex stability index S and vortex intensity I... g Rotational kinetic energy E g An adjustment formula is constructed. Vortex intensity reflects the pollution flux per unit time, and rotational kinetic energy reflects the rotational energy of pollutants. Both are closely related to the actual concentration. Regions with high pollution flux and high rotational kinetic energy are often areas of drastic concentration changes and active pollution behavior. The vortex stability index characterizes the dynamic stability of the vortex, indirectly reflecting the fluctuation trend of the concentration distribution. By calculating the sampling frequency using these parameters related to the actual concentration distribution, the adjusted frequency can accurately adapt to the dynamic changes of the current concentration. This achieves a deep match between the sampling frequency and the actual concentration of esters and benzene series compounds (including concentration levels, trends, and distribution dynamics), ensuring that the monitoring data accurately reflects the actual concentration without data redundancy or missing data due to unreasonable frequencies.

[0135] This invention proposes an online and offline integrated monitoring system for printed VOCs, such as... Figure 2 As shown, the online and offline integrated monitoring system for printed VOCs includes:

[0136] The online environmental monitoring module is used to monitor the ambient temperature and humidity data of the target area of ​​the printing equipment in real time, and to obtain the standard deviation of ambient temperature and standard deviation of ambient humidity using the real-time monitored ambient temperature and humidity data.

[0137] The environmental fluctuation correction and compensation module is used to correct the temperature and humidity fluctuation interference of the target area in real time according to the correction and compensation strategy when the standard deviation of the ambient temperature exceeds the preset temperature standard deviation threshold, or the standard deviation of the ambient humidity exceeds the preset humidity standard deviation threshold.

[0138] The online concentration detection module is used to collect the concentrations of benzene series compounds and esters in printed VOCs in real time, while correcting for temperature and humidity fluctuations in the target area in real time according to a correction and compensation strategy.

[0139] The offline startup module is used to determine whether to start the offline monitoring mode based on the concentration of benzene series compounds and esters in the printed VOCs while simultaneously monitoring the concentration of benzene series compounds and esters online and identifying anomalies.

[0140] The offline monitoring and control module is used to perform offline targeted data collection on the target area after the offline monitoring mode is activated, and to determine the concentration distribution of VOCs components in the printed VOCs by using the targeted data collection physical quantities.

[0141] The working principle of the above technical solution is as follows: First, a nano-modified metal oxide semiconductor array (ZnO / CuO composite nanowires) is used as a sensor. Its surface nanostructure provides numerous active sites, exhibiting specific adsorption and electrochemical reaction characteristics for benzene compounds and esters. Before concentration collection, a calibration compensation strategy is used to monitor the temperature and humidity of the target area in real time. The sensor output signal is dynamically corrected based on temperature and humidity changes to eliminate interference from environmental factors on sensor performance. Subsequently, the sensor converts the conductivity changes resulting from VOC adsorption into electrical signals, which are then used by the data processing module to calculate the concentrations of benzene compounds and esters. The system compares the real-time concentration data with preset thresholds. If the concentration abnormally increases or reaches the set conditions, the offline monitoring mode is activated. In offline monitoring mode, based on the concentration distribution information provided by online monitoring, pollution hotspots are identified. A targeted collection strategy is used to collect samples from the target area. High-precision laboratory analysis methods (such as gas chromatography-mass spectrometry) are then used to obtain the precise component concentration distribution of VOCs in the samples.

[0142] The above technical solutions offer the following advantages: The highly active nanostructure of the nano-modified metal oxide semiconductor array improves the sensor's detection sensitivity for benzene compounds and esters to the ppb level, reducing the detection limit by 50% compared to traditional metal oxide semiconductor sensors. Combined with temperature and humidity correction compensation strategies, detection errors caused by environmental factors are eliminated, increasing concentration detection accuracy by over 35%. The rapid adsorption-reaction characteristics of the nanosensor shorten the response time to the second level, enabling real-time monitoring of VOC concentrations. The intelligent linkage mechanism between online monitoring and offline sampling ensures that the system's response time from concentration anomaly detection to offline sampling initiation is less than one minute, effectively capturing sudden changes in pollution. The targeted acquisition strategy based on online monitoring data enables offline sampling to accurately locate pollution hotspots, increasing sampling efficiency by 60% and reducing invalid sample collection. Through in-depth laboratory analysis, detailed data on the concentration distribution of VOC components are obtained, increasing the number of component identification categories by 40% compared to traditional random sampling, providing a more accurate basis for pollution source tracing. The temperature and humidity correction and compensation strategy enhances the system's adaptability to complex environments, maintaining stable detection performance even under conditions of drastic temperature and humidity fluctuations (temperature ±10℃, humidity ±20%RH change); the online and offline collaborative monitoring mode achieves full-process coverage of VOCs emissions in the printing process, improving system monitoring reliability by 50% and meeting stringent environmental regulations.

[0143] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for integrated online and offline monitoring of VOCs in printing, characterized in that, include: The system monitors the ambient temperature and humidity data of the target area of ​​the printing equipment in real time online, and uses the real-time monitored ambient temperature and humidity data to obtain the standard deviation of ambient temperature and ambient humidity. When the ambient temperature standard deviation exceeds the preset temperature standard deviation threshold, or the ambient humidity standard deviation exceeds the preset humidity standard deviation threshold, the temperature and humidity fluctuation interference of the target area is corrected in real time according to the correction and compensation strategy. Under the condition of real-time correction of temperature and humidity fluctuation interference in the target area according to the correction and compensation strategy, the concentration of benzene series compounds and esters in printed VOCs is collected online in real time using a nano-modified metal oxide semiconductor array, and an abnormal warning is issued when the concentration of benzene series compounds and esters in printed VOCs exceeds the corresponding threshold. While monitoring and identifying anomalies in the concentrations of benzene series compounds and esters in printed VOCs online, the system determines whether to activate offline monitoring mode based on the concentrations of benzene series compounds and esters in the printed VOCs. After the offline monitoring mode is activated, the target area is collected offline using the offline monitoring mode, and the concentration distribution of VOCs components in the printed VOCs is determined by the physical quantities collected by the targeted monitoring mode. The collection frequency of benzene series compounds and ester compounds in the printed VOCs is adjusted by the concentration distribution of VOCs components. The correction and compensation strategy is as follows: When any data value in the temperature and humidity information exceeds its corresponding temperature and humidity reference value, the data that exceeds its corresponding temperature and humidity reference value is used as the reference data item, and the data that does not exceed its corresponding temperature and humidity reference value is used as the benchmark data item. Retrieve the data difference between the reference data item and its corresponding temperature and humidity reference value, normalize the data difference between the reference data item and its corresponding temperature and humidity reference value, and record the normalized data difference as the first data difference x. Retrieve the data difference between the benchmark data item and its corresponding temperature and humidity reference value, normalize the data difference between the benchmark data item and its corresponding temperature and humidity reference value, and record the normalized data difference as the second data difference y. Retrieve historical data of temperature and humidity information, normalize the historical data of temperature and humidity information, and obtain normalized temperature and humidity information. Based on each normalized temperature and humidity information, generate temperature and humidity distribution coordinate points (x... i y i ), where x i y represents the normalized temperature data value corresponding to the i-th acquisition; i This represents the normalized humidity data value corresponding to the i-th data collection. Use the first data difference x and the second data difference y to generate a reference coordinate point (x, y) for temperature and humidity distribution; Based on the coordinates of each temperature and humidity distribution point (x i y i The coordinates of the temperature and humidity distribution (x, y) are obtained from the reference coordinates (x, y). i y i The angle θ between the reference coordinate point (x, y) and the temperature and humidity distribution; Using the coordinates of each temperature and humidity distribution point (x i y i The compensation parameter 'a' is obtained by taking the angle between the point and the reference coordinate point (x, y) of the temperature and humidity distribution.

2. The online and offline integrated monitoring method for printed VOCs according to claim 1, characterized in that, Under the condition of real-time correction of temperature and humidity fluctuation interference in the target area according to the correction and compensation strategy, a nano-modified metal oxide semiconductor array is used to collect the concentration of benzene series compounds and esters in printed VOCs in real time online, and anomaly warnings are issued when the concentration of benzene series compounds and esters in printed VOCs exceeds the corresponding threshold, including: The temperature and humidity information of the target area is collected in real time and sent to the edge device. After receiving the temperature and humidity information of each target area, the edge device uses a correction and compensation strategy to correct the temperature and humidity fluctuation interference in each area. The concentrations of benzene compounds and esters in printed VOCs are collected in real time online in a target area using the nano-modified metal oxide semiconductor array. The target area includes a paint mixing zone, a printing unit, and a drying line. The concentrations of benzene series compounds and ester compounds in printed VOCs collected in real time in the target area are compared with preset corresponding gas concentration thresholds. An abnormal warning is issued when the concentrations of benzene series compounds and ester compounds in printed VOCs collected in real time in the target area exceed the preset corresponding gas concentration thresholds.

3. The online and offline integrated monitoring method for printed VOCs according to claim 2, characterized in that, After receiving temperature and humidity information for each target area, the edge device uses a correction and compensation strategy to correct for temperature and humidity fluctuation interference in each area, including: After receiving the temperature and humidity information of each target area, the edge device compares the temperature and humidity information of the target area with the preset temperature and humidity reference value to determine whether the temperature and humidity information of the current target area exceeds the preset temperature and humidity reference value. When any data value of the corresponding temperature and humidity reference value in the temperature and humidity information exceeds its corresponding temperature and humidity reference value, the compensation parameter a is obtained according to the correction and compensation strategy. The temperature and humidity information of each target area collected in real time is corrected and compensated according to the compensation parameters so that the temperature and humidity information of the target area reaches the corrected and compensated value. The compensation formula is U=(1+a)*U0, where U represents the corrected and compensated temperature and humidity information; U0 represents the real-time collected temperature and humidity information; and a represents the compensation parameter.

4. The online and offline integrated monitoring method for printed VOCs according to claim 1, characterized in that, While monitoring and identifying anomalies in the concentrations of benzene series compounds and esters in printed VOCs online, the system determines whether to activate offline monitoring mode based on the concentrations of benzene series compounds and esters in the printed VOCs, including: While monitoring and identifying anomalies in the concentration of benzene series compounds and esters in printing VOCs online, VOCs pollution event data from historical printing processes are collected, and the concentration change behavior characteristics of benzene series compounds and esters are extracted. The concentration change behavior characteristics include concentration values ​​and concentration change rates. Offline triggering conditions are set according to the concentration change behavior characteristics, wherein the offline triggering conditions include a first offline triggering condition, a second offline triggering condition, and a third offline triggering condition; The concentration of phthalic acid compounds and esters in each target area is monitored in real time. When the concentration of phthalic acid compounds and esters meets any one of the first offline trigger condition, the second offline trigger condition, and the third offline trigger condition, the offline monitoring mode is activated.

5. The online and offline integrated monitoring method for printed VOCs according to claim 4, characterized in that, The first offline trigger condition, the second offline trigger condition, and the third offline trigger condition include: The first offline triggering condition is that the concentration of the corresponding benzene series compound or ester jumps from a low range to a high range within a first preset time period, while the concentration of the ester or benzene series compound increases stepwise in the middle range; wherein, the value of the first preset time period ranges from 3s to 20s; and the low range refers to the concentration range where the concentration is less than a first concentration threshold, the middle range refers to the concentration range where the concentration is not less than the first concentration threshold but less than a second concentration threshold, and the high range refers to the concentration range where the concentration is not less than the second concentration threshold. The second offline triggering condition is that the concentration pulse phenomenon of benzene series compounds and esters alternates, and is repeated continuously for ≥3 times; wherein, the concentration pulse phenomenon includes, but is not limited to, the occurrence of an ester pulse within a second preset time after the benzene pulse; wherein, the value range of the second preset time is 1s-3s; The third offline triggering condition is that the concentrations of the two types of substances remain in the high range for more than a third preset time, wherein the value of the third preset time is in the range of 5 min to 15 min.

6. The online and offline integrated monitoring method for printed VOCs according to claim 5, characterized in that, The lower limit of the gradient corresponding to the stepwise increase in concentration of esters or benzene compounds in the middle range is: Among them, C down The gradient lower limit corresponds to the stepwise increase in the concentration of esters or benzene compounds within the middle range; H represents the first concentration threshold corresponding to the concentration of esters or benzene compounds; L represents the second concentration threshold corresponding to the concentration of esters or benzene compounds; B represents the stepwise grading coefficient, which ranges from 5 to 10; T g This indicates the time it takes for the concentration of a benzene series compound or ester to transition from a low to a high range after normalization; C g This represents the normalized concentration value of benzene compounds or esters at the current moment.

7. The online and offline integrated monitoring method for printed VOCs according to claim 1, characterized in that, After the offline monitoring mode is activated, the target area is sampled offline using this mode. The concentration distribution of VOC components in the printed VOCs is determined by the physical quantities collected through this targeted sampling. The sampling frequency of benzene series compounds and esters in the printed VOCs is then adjusted based on the concentration distribution of VOC components, including: The target area is divided into grids to form multiple rectangular grid areas, and the static anchor point sensors are controlled in offline monitoring mode to collect the concentrations of esters and benzene compounds in each rectangular grid area in real time. A laser spectroscopy analyzer is used to generate a 3D pollutant distribution cloud map corresponding to the target area in real time. The 3D pollutant distribution cloud map includes cold and hot zones. Target areas where the concentration of any one of the esters and benzene series compounds exceeds a preset concentration reference value are marked as hot zones. Target areas where the concentration of either the esters or benzene series compounds does not exceed the preset concentration reference value are marked as cold zones. Based on the distribution of heat and cold sources, a distribution map corresponding to clockwise or counterclockwise vortices is generated, wherein the distribution map corresponding to clockwise or counterclockwise vortices reflects the concentration distribution of VOCs components. The update time for the 3D pollutant distribution cloud map is set based on the current concentrations of esters and benzene compounds within each rectangular grid area; The concentration sampling frequency is adjusted by using the rectangular grid area corresponding to the vortex center position in the 3D pollutant distribution cloud map.

8. The online and offline integrated monitoring method for printed VOCs according to claim 7, characterized in that, The concentration sampling frequency of the rectangular grid area corresponding to the vortex center position in the 3D pollutant distribution cloud map is adjusted, including: The radius changes of the vortices corresponding to esters and benzene series compounds are collected in real time, and the radius standard deviation and radius moving average are obtained based on the radius changes of the vortices. The vortex stability index is obtained based on the standard deviation of the radius and the moving average of the radius. The vortex intensity and rotational kinetic energy at the vortex center positions corresponding to esters and benzene compounds were obtained; The concentration sampling frequency of the rectangular grid region corresponding to the vortex center position is adjusted by combining the vortex intensity and rotational kinetic energy of the vortex center position corresponding to the ester and benzene series compounds with the vortex stability index.

9. A comprehensive online and offline monitoring system for printed VOCs, characterized in that, The online and offline integrated monitoring system for printed VOCs includes: The online environmental monitoring module is used to monitor the ambient temperature and humidity data of the target area of ​​the printing equipment in real time, and to obtain the standard deviation of ambient temperature and standard deviation of ambient humidity using the real-time monitored ambient temperature and humidity data. The environmental fluctuation correction and compensation module is used to correct the temperature and humidity fluctuation interference of the target area in real time according to the correction and compensation strategy when the standard deviation of the ambient temperature exceeds the preset temperature standard deviation threshold, or the standard deviation of the ambient humidity exceeds the preset humidity standard deviation threshold. An online concentration detection module is used to collect the concentrations of benzene series compounds and esters in printed VOCs in real time using a nano-modified metal oxide semiconductor array, while correcting for temperature and humidity fluctuations in the target area in real time according to a correction and compensation strategy. It also issues an anomaly warning when the concentrations of benzene series compounds and esters in printed VOCs exceed corresponding thresholds. The correction and compensation strategy is as follows: when either temperature or humidity data exceeds a reference value, the module distinguishes between reference data items and benchmark data items; it normalizes the differences between the two types of data items and their corresponding temperature and humidity reference values ​​to obtain a first data difference x for temperature data and a second data difference y for humidity data; it generates temperature and humidity distribution coordinate points using historical temperature and humidity data, and generates reference coordinate points (x, y) using the first data difference x and the second data difference y; it calculates the angle θ between each coordinate point and the reference coordinate point (x, y); and it obtains the compensation parameter a based on the angle. The offline startup module is used to determine whether to start the offline monitoring mode based on the concentration of benzene series compounds and esters in the printed VOCs while simultaneously monitoring the concentration of benzene series compounds and esters online and identifying anomalies. The offline monitoring and control module is used to perform offline targeted acquisition of the target area after the offline monitoring mode is activated, and to determine the concentration distribution of VOCs components in the printed VOCs by the targeted acquisition physical quantities. The correction and compensation strategy is as follows: When any data value in the temperature and humidity information exceeds its corresponding temperature and humidity reference value, the data that exceeds its corresponding temperature and humidity reference value is used as the reference data item, and the data that does not exceed its corresponding temperature and humidity reference value is used as the benchmark data item. Retrieve the data difference between the reference data item and its corresponding temperature and humidity reference value, normalize the data difference between the reference data item and its corresponding temperature and humidity reference value, and record the normalized data difference as the first data difference x. Retrieve the data difference between the benchmark data item and its corresponding temperature and humidity reference value, normalize the data difference between the benchmark data item and its corresponding temperature and humidity reference value, and record the normalized data difference as the second data difference y. Retrieve historical data of temperature and humidity information, normalize the historical data of temperature and humidity information, and obtain normalized temperature and humidity information. Based on each normalized temperature and humidity information, generate temperature and humidity distribution coordinate points (x... i y i ), where x i y represents the normalized temperature data value corresponding to the i-th acquisition; i This represents the normalized humidity data value corresponding to the i-th data collection. Use the first data difference x and the second data difference y to generate a reference coordinate point (x, y) for temperature and humidity distribution; Based on the coordinates of each temperature and humidity distribution point (x i y i The coordinates of the temperature and humidity distribution (x, y) are obtained from the reference coordinates (x, y). i y i The angle θ between the reference coordinate point (x, y) and the temperature and humidity distribution; Using the coordinates of each temperature and humidity distribution point (x i y i The compensation parameter 'a' is obtained by taking the angle between the point and the reference coordinate point (x, y) of the temperature and humidity distribution.

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