Air purification system for electronic industry factory building

Abstract

The application discloses an air purification system for electronic industrial plants, and relates to the technical field of air purification.The system collects pollution characteristic data in real time through a sensor group, obtains an air particle data group and a purification efficiency data group through data processing, constructs a nanometer pollution disturbance index nan based on the air particle data group to evaluate air cleanliness, and when nanometer pollution is detected, constructs a photocatalytic reaction efficiency index npc based on the purification efficiency data group, fuses the nanometer pollution disturbance index nan to form a purification collapse risk index Rall to evaluate photocatalytic cleaning capacity, dynamically adjusts the operation strategy of an ultraviolet light source and a fan according to the evaluation result, and realizes hierarchical alarm and operation information interaction through a man-machine interface and an audible and visual alarm, and archives to form a closed-loop database.The system can realize real-time monitoring, dynamic purification and risk early warning of air quality of electronic industrial plants, improve air purification efficiency and stability, reduce energy consumption and has traceability.

Description

Technical Field

[0001] This invention relates to the field of air purification technology, specifically to an air purification system for electronic industrial plants. Background Technology

[0002] Electronics industrial plants often have extremely stringent requirements for air cleanliness during production. Due to the presence of high-precision processes such as photolithography, precision welding, and chip packaging, even extremely small particles or organic molecules can severely impact product yield. Traditional air purification methods primarily rely on mechanical filtration and air circulation, which can effectively control larger particles and some dust. However, their effectiveness in capturing and decomposing suspended particles and organic residues with nanometer-sized diameters is extremely limited. These nanoscale organic residues often originate from chemical reaction byproducts in the production process, coating volatilization, or equipment emissions. They exhibit strong diffusion, difficulty in settling, and long-term retention characteristics within the plant. Therefore, how to specifically monitor and purify nanoscale organic residues in the air in real time has become a key technical challenge that needs to be addressed in air purification systems for electronics industrial plants.

[0003] Current technologies for monitoring and treating nanoscale organic residues have several shortcomings. First, traditional air purification systems rely heavily on particulate matter concentration thresholds for judgment, neglecting the effects of enhanced optical scattering and the dilution effect of airflow, which can easily lead to underestimation of pollution levels. Second, photocatalytic purification devices are affected by multiple coupling factors during operation, including ultraviolet light intensity, air humidity, and reactant concentration, resulting in fluctuating purification efficiency. Current technologies lack quantitative evaluation indicators for this dynamic efficiency, making it difficult to detect declining purification efficiency trends in a timely manner. Finally, the lack of a comprehensive judgment method that combines pollution levels and purification efficiency often leads to the purification system only adjusting when pollution accumulates to a critical level, resulting in lag and failing to meet the high standards of "real-time, stable, and accurate" air quality requirements of electronics industrial plants. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides an air purification system for electronic industrial plants, solving the problems mentioned in the background section.

[0005] To achieve the above objectives, the present invention provides the following technical solution: an air purification system for electronic industrial plants, comprising a pollution detection module, a cleanliness analysis module, a purification feedback module, an execution control module, and an operation and maintenance interaction module;

[0006] The pollution detection module is used to collect pollution characteristic data in the electronic industrial plant in real time based on the installed sensor group, and obtain air particle data group and purification efficiency data group after data processing.

[0007] The cleanliness analysis module is used to construct the nanopollution disturbance index nan based on the air particle data set, and to evaluate the air cleanliness with the critical threshold Tm for particle spillage. When the evaluation indicates the presence of nanopollution, photocatalytic degradation analysis is performed.

[0008] The purification feedback module is used to perform photocatalytic degradation analysis. Based on the purification efficiency data set, a photocatalytic reaction efficiency index npc is constructed. Combined with the nano-pollution disturbance index nan, a purification collapse risk index Rall is constructed. Then, the photocatalytic purification capacity is evaluated by combining it with the purification capacity stability threshold Tw and the purification capacity collapse threshold Tj.

[0009] The execution control module is used to receive evaluation information in real time and execute corresponding control instructions;

[0010] The operation and maintenance interaction module is used to display the environmental status in a hierarchical manner on the human-computer interaction interface based on the evaluation information, and to generate operation logs and event archives, which are then stored in the time-series database.

[0011] Preferably, the pollution detection module includes a pollution detection unit and a data processing unit;

[0012] The pollution detection unit is used to activate the air purification system, turn on the fan, photocatalytic device and air circulation pipeline when the electronic industrial plant enters the production mode, and collect pollution characteristic data in the electronic industrial plant in real time based on the installed sensor group.

[0013] The sensor group includes a photoelectric receiver, an optical particulate matter monitor, an air volume sensor, a temperature and humidity sensor, and a VOC sensor;

[0014] The photoelectric receiver is installed at the inlet of the air circulation duct of the air purification system in the electronic factory to directly read the light source scattering intensity Isc.

[0015] The optical particulate matter monitor is installed 2m above the production line in the electronics factory to monitor the mass concentration (mp) of suspended particulate matter in the air of the work area in real time.

[0016] The airflow sensor is installed at the fan outlet and photocatalytic device inlet in the main air duct of the air purification system to collect airflow qa in real time.

[0017] The temperature and humidity sensor is installed at the inlet of the photocatalytic device to monitor the humidity sd of the air entering the air purification system in real time.

[0018] The VOC sensor is fixed to the inlet and outlet of the photocatalytic device on the wall of the outlet duct to collect the concentration of volatile organic compounds (VOCs) at the inlet and outlet of the photocatalytic device in real time. in and VOCsout .

[0019] Preferably, the data processing unit is used to process the pollution characteristic data to obtain air particle data set and purification efficiency data set respectively;

[0020] The data processing includes denoising, timestamp alignment, and dimensionless processing;

[0021] The denoising process removes noise from the contaminated feature data through bandpass filtering; timestamp alignment projects contaminated feature data from different sampling frequencies onto the same time axis, and linear interpolation is used to fill in missing points and uneven contaminated feature data to form a data sequence with a unified time step; dimensionless processing removes the dimensional influence of state data through the Max-Min method.

[0022] The air particle data set includes light source scattering intensity sc, particle mass concentration mp, and air flow rate qa;

[0023] The purification efficiency data set includes ultraviolet light intensity (UV), air humidity (SD), and volatile organic compound (VOC) concentration at the inlet of the photocatalytic device. in and the concentration of volatile organic compounds (VOCs) at the outlet of the photocatalytic device out .

[0024] Preferably, the cleanroom analysis module includes an air quality analysis unit and an air quality assessment unit;

[0025] The air quality analysis unit is used to fit the air particle data set, analyze the impact of optical scattering and particle concentration on air quality, quantify the real-time intensity of particulate pollution in the factory air, and construct the nano-pollution disturbance index nan based on the air particle data set. The specific formula is as follows: In the formula, ln represents the logarithmic function, sc(t), mp(t), and qa(t) represent the light source scattering intensity, particle mass concentration, and air flow rate at time t, respectively. base This indicates the intensity of light scattering under standard light source conditions in a clean air environment.

[0026] Preferably, the air quality assessment unit is used to collect the nano-pollution disturbance index nan for all air cleanliness within the normal range in the past month, sort them from smallest to largest, and then set the Q95th quantile value as the critical threshold Tm for particulate spillover according to the percentile method. It is then compared with the real-time acquired nano-pollution disturbance index nan, and the air cleanliness is assessed based on the comparison results. The specific assessment scheme is as follows.

[0027] The particle spillover threshold Tm represents the critical point at which nanoparticles in the air begin to exhibit a spillover effect.

[0028] When the nano-pollution disturbance index nan ≤ the critical threshold for particle spillover Tm, it indicates that the air cleanliness is within the normal range, and the standard air purification procedure should be maintained at this time.

[0029] When the nanopollution disturbance index nan > the critical threshold Tm for particulate spillover, it indicates the presence of nanopollution in the air. At this time, pollution risk information is generated, and photocatalytic degradation analysis is performed simultaneously.

[0030] Preferably, the purification feedback module is used to perform photocatalytic degradation analysis when the air cleanliness assessment indicates the presence of nano-pollutants in the air, specifically including an efficiency analysis unit and a risk assessment unit;

[0031] The efficiency analysis unit is used to fit the purification efficiency data set, analyze the carrying capacity of the photocatalytic reaction to decompose pollutants, dynamically quantify the purification efficiency of photocatalysis, and construct the photocatalytic reaction efficiency index npc based on the purification efficiency data set. The specific formula is as follows: In the formula, ln represents the logarithmic function, uv(t), sd(t), and VOC. in (t) and VOC out (t) represents the ultraviolet light intensity, air humidity, volatile organic compound concentration at the inlet of the photocatalytic device, and volatile organic compound concentration at the outlet of the photocatalytic device at time t, respectively.

[0032] Preferably, the risk assessment unit is used to integrate the real-time air pollution level and purification efficiency to make a comprehensive pollution risk judgment on the air environment in the electronics industrial plant, specifically including a pollution risk analysis unit and a purification assessment unit.

[0033] The pollution risk analysis unit is used to construct a purification collapse risk index Rall based on the nano-pollution disturbance index Nan and the photocatalytic reaction efficiency index NPC. This index combines pollution level and purification efficiency to quantify the antagonistic relationship between pollutant level and purification efficiency. The specific formula is as follows: In the formula, exp represents the exponential decay function.

[0034] Preferably, the purification assessment unit is used to collect all purification collapse risk indices Rall within a historical month, calculate the mean and standard deviation using statistical methods, preset the mean as the purification capacity stability threshold Tw, preset the sum of the mean and standard deviation as the purification capacity collapse threshold Tj, and then compare it with the purification collapse risk index Rall acquired in real time. Based on the comparison results, the photocatalytic purification capacity is assessed. The specific assessment scheme is as follows.

[0035] The cleanliness stability threshold Tw represents the margin of safety for stable operation of clean air in the plant.

[0036] The cleanliness capacity collapse threshold Tj represents the boundary point at which the clean air environment of the factory begins to show stability collapse.

[0037] When the purification collapse risk index Rall < the purification capacity stability threshold Tw, it indicates that the photocatalytic efficiency is excessive, and at this time, purification excess information is generated.

[0038] When the cleanliness stability threshold Tw ≤ the cleanliness collapse risk index Rall ≤ the cleanliness collapse threshold Tj, it means that the photocatalytic efficiency meets the pollution purification requirements, and at this time, the purification maintenance information is generated.

[0039] When the purification collapse risk index Rall is greater than the purification capacity collapse threshold Tj, it indicates that the photocatalytic efficiency is not up to standard, and purification collapse risk information is generated at this time.

[0040] Preferably, the execution control module is used to receive the assessment information generated by the air cleanliness assessment and the photocatalytic cleanliness capability assessment in real time, and execute the corresponding control instructions, as follows;

[0041] Pollution risk information: Immediately increase the power of the ultraviolet light source in the air circulation channel by 15% and increase the fan speed by 15%;

[0042] Purification excess information: The power of the ultraviolet light source and the fan power are gradually reduced to the process baseline at a rate of 5% per minute until the standard air purification procedure is restored, and continuous monitoring is carried out;

[0043] Purification Maintenance Information: Maintain the current air purification program and display a green air quality compliance instruction on the control panel;

[0044] Air purification collapse risk information: Based on the current air purification program, the ultraviolet light source and fan will be gradually increased to the maximum power within the safe range at a rate of 5% per minute, and iterative analysis will be performed through the cleanliness analysis module. If the photocatalytic efficiency still does not meet the standard after ten minutes, the system will be shut down for rectification.

[0045] Preferably, the operation and maintenance interaction module includes an alarm display unit and an event logging unit;

[0046] The alarm display unit is used to automatically switch the human-machine interface and the sound and light device to the corresponding display mode and alarm mode based on different information from air cleanliness assessment and photocatalytic cleanliness assessment, and to issue graded alarms for pollution levels.

[0047] When receiving pollution risk information, the human-machine interface displays a yellow alarm and does not trigger the sound and light devices;

[0048] When receiving information on excess purification and purification maintenance, the human-machine interface displays a green "air environment meets standards" message and does not trigger the sound and light devices.

[0049] When receiving information about the risk of collapse during purification, the human-machine interface displays a red alarm, triggering the sound and light device to issue an audible and visual alarm.

[0050] The event recording unit is used to record the nano-pollution disturbance index (nan), photocatalytic reaction efficiency index (npc), and purification collapse risk index (Rall) in real time during the operation of the air purification system. It also records the corresponding control commands and final execution effects of air cleanliness assessment and photocatalytic purification capability assessment. Combined with the alarm display unit, yellow alarm data and red alarm data are marked as environmental pollution data and purification collapse data, respectively. A complete operation log and event archive are generated, and then paired and archived according to timestamps to form a traceable closed-loop data chain of "data, assessment, command, and result" and stored in the time-series database.

[0051] This invention provides an air purification system for electronic industrial plants. It has the following beneficial effects:

[0052] (1) The pollution detection module of this system, through the coordinated deployment of photoelectric receiver, optical particulate matter monitor, air volume sensor, temperature and humidity sensor and VOC sensor, can directly collect light source scattering intensity Isc, particulate mass concentration mp, air flow rate qa, ultraviolet light intensity uv, air humidity sd, and volatile organic compound concentration VOC at the inlet of the photocatalytic device. in and the concentration of volatile organic compounds (VOCs) at the outlet of the photocatalytic device out Key parameters, such as air quality data, are processed through bandpass filtering for noise reduction, timestamp alignment, and dimensionless conversion to form air particle data sets and purification efficiency data sets. This avoids biases caused by data collection at different frequencies and eliminates the influence of dimensions, ensuring that subsequent analysis is based on a unified and comparable standard. In this way, the air quality inside the factory can be quantified in real time with high sensitivity and accuracy.

[0053] (2) The system's cleanliness analysis module constructs a nano-pollution disturbance index nan using air particle data sets, capturing the abnormal amplification effect of particulate pollution on optical signals. It then uses the percentile method to set a critical threshold Tm for particle spillover, comparing it with the real-time acquired nano-pollution disturbance index nan. Based on the comparison results, air cleanliness is assessed, ensuring that even trace amounts of nanoparticle diffusion are not overlooked. When the assessment results indicate potential pollution, the purification feedback module immediately intervenes, quantifying purification efficiency by constructing a photocatalytic reaction efficiency index npc using purification efficiency data sets. This is then combined with the nano-pollution disturbance index nan to construct a purification collapse risk index Rall. Subsequently, the system performs a graded judgment based on the historically obtained cleanliness stability threshold Tw and cleanliness collapse threshold Tj. This allows it to identify situations of excess efficiency and normal operation, as well as potential collapse risks, thus achieving accurate multi-level air cleanliness assessment.

[0054] (3) The system's execution control module and operation and maintenance interaction module jointly ensure a closed-loop chain of "assessment, action, and retrospection". The execution control module can intelligently adjust the power of the ultraviolet light source and the speed of the fan according to different assessment results, so as to achieve rapid enhancement under pollution risk, gradual reduction when there is surplus, and full compensation or shutdown for rectification when there is collapse risk, thus ensuring a balance between energy utilization and purification effect. The operation and maintenance interaction module presents the assessment information intuitively through the human-computer interaction interface and sound and light alarms, making different levels of air conditions clear at a glance. At the same time, it also archives the nano-pollution disturbance index, photocatalytic efficiency index, and purification risk index along with the execution results, forming a complete time-series data chain. This operation log and event archive not only provide traceable basis for daily operation and maintenance, but also provide data support for system optimization and risk modeling in the long term. Overall, while realizing real-time monitoring and purification of factory air, the system also enhances the resilience against pollution and the energy efficiency of operation, ensuring the stability, safety and efficiency of the electronic industry production environment. Attached Figure Description

[0055] Figure 1 This is a schematic diagram of an air purification system for electronic industrial plants according to the present invention;

[0056] Figure 2 This is a schematic diagram illustrating the operating principle of an air purification system for electronic industrial plants according to the present invention.

[0057] Figure 3 This is a broken-line diagram illustrating the photocatalytic cleanliness assessment of the present invention. Detailed Implementation

[0058] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0059] Example 1

[0060] Please see Figure 1 This invention provides an air purification system for electronic industrial plants. To achieve the above objectives, this invention is implemented through the following technical solutions: including a pollution detection module, a cleanliness analysis module, a purification feedback module, an execution control module, and an operation and maintenance interaction module.

[0061] The pollution detection module is used to collect pollution characteristic data in the electronic industrial plant in real time based on the installed sensor group, and obtain air particle data group and purification efficiency data group after data processing.

[0062] The cleanliness analysis module is used to construct the nanopollution disturbance index nan based on the air particle data set, and to evaluate the air cleanliness with the critical threshold Tm for particle spillage. When the evaluation indicates the presence of nanopollution, photocatalytic degradation analysis is performed.

[0063] The purification feedback module is used to perform photocatalytic degradation analysis. Based on the purification efficiency data set, a photocatalytic reaction efficiency index npc is constructed. Combined with the nano-pollution disturbance index nan, a purification collapse risk index Rall is constructed. Then, the photocatalytic purification capacity is evaluated by combining it with the purification capacity stability threshold Tw and the purification capacity collapse threshold Tj.

[0064] The execution control module is used to receive evaluation information in real time and execute corresponding control instructions;

[0065] The operation and maintenance interaction module is used to display the environmental status in a hierarchical manner on the human-computer interaction interface based on the evaluation information, and to generate operation logs and event archives, which are then stored in the time-series database.

[0066] In this embodiment, the pollution detection module collects pollution characteristic data in the electronics industrial plant in real time using a photoelectric receiver, optical particulate matter monitor, air volume sensor, temperature and humidity sensor, and VOC sensor. After noise reduction, timestamp alignment, and dimensionless processing, a unified air particle data set and purification efficiency data set are formed, achieving comprehensive capture and standardized input of plant pollution characteristics. This overcomes the shortcomings of existing technologies, such as single monitoring parameters, inconsistent data, and difficulty in reflecting complex pollution states. The cleanliness analysis module constructs a nano-pollution disturbance index nan using the air particle data set and assesses air cleanliness using the particulate spillover threshold Tm, enabling early identification and warning of air cleanliness. When nano-pollution is detected, photocatalytic degradation analysis is performed. The purification feedback module constructs a photocatalytic reaction efficiency index npc based on the purification efficiency data set, and combines it with the nano-pollution disturbance index nan to construct a purification collapse risk index Rall. This is then compared with the historically obtained cleanliness stability threshold Tw and cleanliness collapse threshold Tj to assess photocatalytic purification capacity, achieving a comprehensive assessment of pollution level and purification capacity, completing the entire chain from pollution detection to risk assessment. Compared to existing purification systems that rely on single-concentration monitoring or fixed-power operation, this invention can dynamically identify the antagonistic relationship between pollution diffusion trends and purification capacity, significantly improving the precision and scientific rigor of factory air environment assessment. The execution control module and operation and maintenance interaction module closely link assessment results with control measures, achieving intelligent adjustment of light source power and fan speed to achieve the dual goals of energy saving and stable purification. Simultaneously, it provides tiered alerts through a human-machine interface and audible and visual alarms, and fully archives monitoring data, assessment conclusions, and control commands. Compared to traditional technologies, this invention not only enhances the adaptability of the purification system in complex environments but also establishes a traceable closed-loop operation data chain, thereby achieving significant improvements in operational efficiency, pollution control effectiveness, and safety reliability.

[0067] Example 2

[0068] Please refer to Figure 1 and Figure 2 Specifically: the pollution detection module includes a pollution detection unit and a data processing unit;

[0069] The pollution detection unit is used to activate the air purification system, turn on the fan, photocatalytic device and air circulation pipeline when the electronic industrial plant enters the production mode, and collect pollution characteristic data in the electronic industrial plant in real time based on the installed sensor group.

[0070] The sensor group includes a photoelectric receiver, an optical particulate matter monitor, an air volume sensor, a temperature and humidity sensor, and a VOC sensor;

[0071] The photoelectric receiver is installed at the inlet of the air circulation duct of the air purification system in the electronic factory to directly read the light source scattering intensity Isc, which represents the intensity of the light scattered by particulate matter in the air to the light source.

[0072] The optical particulate matter monitor is installed 2m above the production line in the electronics factory to monitor the mass concentration (mp) of suspended particulate matter in the air in the work area in real time, which represents the mass concentration of suspended particulate matter in the air and reflects the degree of air cleanliness.

[0073] The airflow sensor is installed at the fan outlet and photocatalytic device inlet in the main air duct of the air purification system to collect the airflow qa in real time, which represents the airflow through the air purification device and the air duct.

[0074] The temperature and humidity sensor is installed at the inlet of the photocatalytic device to monitor the air humidity sd entering the air purification system in real time, which represents the relative humidity in the air and affects the photocatalytic reaction rate.

[0075] The VOC sensor is fixed to the inlet and outlet of the photocatalytic device on the wall of the outlet duct to collect the concentration of volatile organic compounds (VOCs) at the inlet and outlet of the photocatalytic device in real time. in and VOCs out , representing the concentration of volatile organic compounds in the air before entering the photocatalytic reaction zone and the concentration of volatile organic compounds remaining in the air after passing through the photocatalytic reaction zone, respectively.

[0076] The data processing unit is used to process pollution characteristic data to obtain air particle data set and purification efficiency data set respectively.

[0077] The data processing includes denoising, timestamp alignment, and dimensionless processing;

[0078] The denoising process removes noise from the contaminated feature data through bandpass filtering; timestamp alignment projects contaminated feature data from different sampling frequencies onto the same time axis, and linear interpolation is used to fill in missing points and uneven contaminated feature data to form a data sequence with a unified time step; dimensionless processing removes the dimensional influence of state data through the Max-Min method.

[0079] The air particle data set includes light source scattering intensity sc, particle mass concentration mp, and air flow rate qa;

[0080] The purification efficiency data set includes ultraviolet light intensity (UV), air humidity (SD), and volatile organic compound (VOC) concentration at the inlet of the photocatalytic device. in and the concentration of volatile organic compounds (VOCs) at the outlet of the photocatalytic device out .

[0081] In this embodiment, the pollution detection module is activated by the central controller when the electronics industrial plant enters production mode. Through the coordinated operation of the fan, photocatalytic device, and air circulation pipeline, combined with a multi-source sensor group including a photoelectric receiver, optical particulate matter monitor, airflow sensor, temperature and humidity sensor, and VOC sensor, it can collect data in real time at different locations and stages, including light scattering intensity (Isc), particulate mass concentration (mp), airflow rate (qa), ultraviolet light intensity (UV), air humidity (SD), and volatile organic compound (VOC) concentration at the inlet of the photocatalytic device. in and the concentration of volatile organic compounds (VOCs) at the outlet of the photocatalytic device out Pollution characteristic data are processed through bandpass filtering for noise reduction, timestamp alignment and linear interpolation, and Max-Min dimensionless transformation to generate unified air particle data sets and purification efficiency data sets. This implementation method not only achieves full-process monitoring of the state of air particles and the photocatalytic purification effect within the factory, but also effectively avoids problems such as uneven data collection, large dimensional differences, and severe noise interference in existing technologies. Its beneficial effects include reflecting the true state of air pollution in the factory with higher accuracy and stability, forming a highly comparable and continuous data input foundation, thus providing reliable support for subsequent cleanliness analysis and purification feedback. Compared to traditional methods relying on single-point detection or manual sampling, this invention significantly improves the sensitivity and timeliness of pollution detection, achieving dynamic and refined control of air cleanliness in electronics industrial plants, thereby enhancing the safety and stability of the production environment and providing conditions for improving overall air purification efficiency and energy utilization.

[0082] Example 3

[0083] Please refer to Figure 1 and Figure 2 Specifically: the cleanroom analysis module includes an air quality analysis unit and an air quality assessment unit;

[0084] The air quality analysis unit is used to fit the air particle data set, analyze the impact of optical scattering and particle concentration on air quality, quantify the real-time intensity of particulate pollution in the factory air, and construct the nano-pollution disturbance index nan based on the air particle data set. The specific formula is as follows: In the formula, ln represents the logarithmic function, sc(t), mp(t), and qa(t) represent the light source scattering intensity, particle mass concentration, and air flow rate at time t, respectively. base This represents the scattering intensity of a standard light source in a clean air environment. It represents the intensity of optical scattering anomalies and is used to capture the amplification effect of nanoparticles in optical signals. It reflects the dynamic balance between pollution concentration and air flow rate, preventing the dilution effect from being ignored when judging solely by concentration.

[0085] The air quality assessment unit is used to collect the nano-pollution disturbance index nan for all air cleanliness within the normal range in the past month. After sorting them from smallest to largest, the Q95th quantile value is preset as the critical threshold Tm for particulate spillover according to the percentile method. Then, it is compared with the real-time acquired nano-pollution disturbance index nan. The air cleanliness is assessed based on the comparison results. The specific assessment scheme is as follows.

[0086] The particle spillover threshold Tm represents the critical point at which nanoparticles in the air begin to exhibit a spillover effect.

[0087] When the nano-pollution disturbance index nan ≤ the critical threshold for particle spillover Tm, it indicates that the air cleanliness is within the normal range, and the standard air purification procedure should be maintained at this time.

[0088] When the nanopollution disturbance index nan > the critical threshold Tm for particulate spillover, it indicates the presence of nanopollution in the air. At this time, pollution risk information is generated, and photocatalytic degradation analysis is performed simultaneously.

[0089] In this embodiment, the air quality analysis unit performs fitting processing on the air particle data set, jointly modeling the light source scattering intensity (sc), particle mass concentration (mp), and airflow rate (qa) to obtain the nanoparticle pollution disturbance index (nan). This index not only reflects the real-time intensity of particulate pollution in the air, but also captures optical scattering anomalies by comparing it with the baseline scattering intensity (scbase) in a clean environment, thereby revealing the potential amplification effect of nanoparticles in the air and avoiding misjudgments caused by traditional techniques relying solely on a single concentration index.

[0090] The formula's logic, derivation basis, and significance are explained, and a logarithmic function is used to represent the light source scattering intensity sc. Derived from the principles of signal amplification and logarithmic compression, this method is used to sensitively capture minute anomalies even with large numerical ranges. It represents the anomalous amplitude of light scattering intensity relative to a reference. Due to the extremely small size of nanoparticles but significant scattering cross-sections, even trace concentrations can cause scattering anomalies. Logarithmic processing ensures sensitivity to low-concentration disturbances while avoiding nonlinear distortion under strong scattering conditions. Airflow rate qa affects the dilution and diffusion of particulate matter in space. Insufficient flow rate easily leads to the formation of high-concentration regions, while excessive flow rate reduces the concentration of particulate matter per unit volume. A ratio is established between the particle mass concentration mp(t) and the airflow rate qa(t). Essentially, it is based on the principle of mass conservation in continuum mechanics, reflecting the dynamic balance between pollutant concentration and ventilation volume; and By employing a product structure to couple optical scattering anomalies with the balance between particle concentration and airflow, the amplification effect of nanoparticles in optical signals is captured through scattering intensity anomalies. Simultaneously considering dilution conditions, a nano-pollution disturbance index nan is obtained that reflects both "detection visibility" and "pollution load".

[0091] The air quality assessment unit statistically analyzes the nanoparticle disturbance index (nan) that has been within the normal range for the past month. Using the percentile method, it calculates the critical threshold (Tm) for particulate spillover and compares it with the real-time nanoparticle disturbance index (nan) to assess air cleanliness. When nanoparticle pollution is detected in the air, risk information is generated and photocatalytic degradation analysis is triggered. Through this implementation, the present invention achieves early identification and risk classification control of airborne nanoparticle diffusion, improving detection sensitivity and reducing missed and false positives. Compared to existing methods that rely on average concentrations or fixed thresholds, this invention can issue early warnings in the initial stages of pollution, improving the system's response speed and processing accuracy to sudden pollution events, thereby significantly enhancing the stability of the air environment and the safety of production processes in electronics industrial plants.

[0092] Example 4

[0093] Please refer to Figure 1 , Figure 2 and Figure 3 Specifically: the purification feedback module is used to perform photocatalytic degradation analysis when the air cleanliness assessment indicates the presence of nano-pollutants in the air, and specifically includes an efficiency analysis unit and a risk assessment unit;

[0094] The efficiency analysis unit is used to fit the purification efficiency data set, analyze the carrying capacity of the photocatalytic reaction to decompose pollutants, dynamically quantify the purification efficiency of photocatalysis, and construct the photocatalytic reaction efficiency index npc based on the purification efficiency data set. The specific formula is as follows: In the formula, ln represents the logarithmic function, uv(t), sd(t), and VOC. in (t) and VOC out uv(t) represents the ultraviolet light intensity, air humidity, volatile organic compound concentration at the inlet of the photocatalytic device, and volatile organic compound concentration at the outlet of the photocatalytic device at time t, respectively. uv(t) represents the ultraviolet light intensity, which determines the energy input of the photocatalytic reaction. The purification effect of volatile organic compounds is expressed by dividing by the sum of the inlet concentration and humidity, reflecting the inhibitory effect of reaction conditions on efficiency.

[0095] The risk assessment unit is used to integrate real-time air pollution levels and purification efficiency to make a comprehensive pollution risk assessment of the air environment in the electronics industrial plant. Specifically, it includes a pollution risk analysis unit and a purification assessment unit.

[0096] The pollution risk analysis unit is used to construct a purification collapse risk index Rall based on the nano-pollution disturbance index Nan and the photocatalytic reaction efficiency index NPC. This index combines pollution level and purification efficiency to quantify the antagonistic relationship between pollutant level and purification efficiency. The specific formula is as follows: In the formula, exp represents the exponential decay function. By taking the square root, the impact of extreme pollution intensity on the system is reduced. exp(-npc) represents the inhibitory effect of photocatalytic efficiency on risk.

[0097] The purification assessment unit is used to collect all purification collapse risk indices Rall within the past month, and calculate the mean and standard deviation using statistical methods. The mean is preset as the purification capacity stability threshold Tw, and the sum of the mean and standard deviation is preset as the purification capacity collapse threshold Tj. It is then compared with the purification collapse risk index Rall acquired in real time, and the photocatalytic purification capacity is assessed based on the comparison results. The specific assessment scheme is as follows.

[0098] The cleanliness stability threshold Tw represents the margin of safety for stable operation of clean air in the plant.

[0099] The cleanliness capacity collapse threshold Tj represents the boundary point at which the clean air environment of the factory begins to show stability collapse.

[0100] When the purification collapse risk index Rall < the purification capacity stability threshold Tw, it indicates that the photocatalytic efficiency is excessive, and at this time, purification excess information is generated.

[0101] When the cleanliness stability threshold Tw ≤ the cleanliness collapse risk index Rall ≤ the cleanliness collapse threshold Tj, it means that the photocatalytic efficiency meets the pollution purification requirements, and at this time, the purification maintenance information is generated.

[0102] When the purification collapse risk index Rall is greater than the purification capacity collapse threshold Tj, it indicates that the photocatalytic efficiency is not up to standard, and purification collapse risk information is generated at this time.

[0103] In this embodiment, the purification feedback module starts working when the air cleanliness assessment indicates the presence of nano-pollutants in the air. The efficiency analysis unit first fits the purification efficiency data set to construct a photocatalytic reaction efficiency index (NPC) to quantify ultraviolet light intensity (UV), air humidity (SD), and the concentration of volatile organic compounds (VOCs) at the inlet of the photocatalytic device. in The actual contribution of the volatile organic compound concentration (VOCout) at the outlet of the photocatalytic device to the purification process is ensured to dynamically reflect the combined effect of energy input and inhibition conditions of the photocatalytic reaction.

[0104] The formula logic, derivation basis, and significance: The basic mechanism of photocatalytic reaction originates from surface chemistry and photochemistry principles; ultraviolet light intensity (UV) represents incident energy, which determines the number of electron-hole pairs excited by the semiconductor photocatalyst, thus determining the reaction initiation rate. Physically, the driving force of the photocatalytic reaction originates from the photon flux density. Higher energy is more conducive to exciting electrons on the catalyst surface; the concentration change of volatile organic compounds (VOCs) is described based on the law of mass conservation and the conversion rate formula in chemical kinetics. in (t)-VOC out (t) represents the amount of pollutants removed per unit time, reflecting the purification effect of the photocatalytic reaction. It is the core indicator of conversion rate and directly reflects the actual purification capacity of the catalyst. VOCs in In the traditional formula, (t)+sd(t) should be a single normalization of VOCin. Corresponding to the classic definition of conversion rate, this application introduces air humidity sd as a correction term because air humidity sd has a significant impact on free radical generation and VOC adsorption concentration. By adding air humidity sd to the denominator, the dilution and inhibition effect of excessive humidity on reaction efficiency is reflected. The logarithmic function ln(1+x) is often used for nonlinear response modeling. Its function is to compress extreme values ​​and avoid the dominance of results by a single parameter that is too large. This is consistent with the phenomenon that photocatalytic efficiency gradually tends to saturate at high concentrations. The logarithmic function reflects the decreasing effect of pollutant conversion efficiency as conditions improve. The combination form is a product and logarithmic function structure, which is consistent with the classic modeling method of multi-factor coupling, namely "external energy input (light intensity) multiplied by internal conversion efficiency (logarithmically expressed concentration difference and humidity effect)".

[0105] The risk assessment unit combines the photocatalytic reaction efficiency index npc with the nano-pollution disturbance index nan to construct the purification collapse risk index Rall. This allows for a quantitative assessment of the antagonistic relationship between pollutant levels and purification capacity, and the introduction of square roots and an exponential decay function suppresses the impact of extreme pollution values ​​on system judgment. Furthermore, the system uses statistical methods to extract the mean and standard deviation of historical purification collapse risk indices Rall, sets a cleanliness capacity stability threshold Tw and a cleanliness capacity collapse threshold Tj, and classifies the real-time purification collapse risk index Rall to distinguish between three states: purification surplus, purification maintenance, and purification collapse. Through this implementation, the present invention achieves closed-loop management of the entire process from pollution detection and purification efficiency quantification to comprehensive risk assessment, enabling early identification of air cleanliness risks and dynamic adjustment of purification intensity. Compared to existing technologies that rely on single pollution concentration judgment or fixed purification modes, this invention significantly improves the adaptability, risk perception accuracy, and energy utilization efficiency of air purification systems in electronic industrial plants, thereby ensuring the stability and safety of the production environment.

[0106] The formula logic, derivation basis, and significance show that the air purification process is an "antagonistic" relationship between pollution intensity and purification efficiency. The higher the pollutant level, the greater the system risk; the higher the photocatalytic efficiency, the lower the risk. The quantification of risk needs to consider both the pollution source intensity, i.e., the nano-pollution disturbance index nan, and the system's inhibition ability, i.e., the photocatalytic reaction efficiency index npc. In physical modeling, a common approach is to use a product model, i.e., "risk = pollution driving term × inhibition term", which is consistent with ecological and environmental engineering risk models. The concept of amplitude normalization is derived from statistics and signal processing; taking the square root of the pollution intensity is equivalent to compressing the weight of extremely high values, so that the index will not dominate the system in extreme cases, thus avoiding oversensitivity; exp(-npc) is derived from the classic exponential decay formula, which is often used to describe the process of a certain effect decreasing rapidly as efficiency / energy increases. In this system, the larger the photocatalytic reaction efficiency index npc is, the higher the photocatalytic efficiency and the more obvious the suppression effect on risk. The product form reflects the dynamic balance between pollution-driven forces and efficiency-inhibiting capabilities. The formula essentially describes the game relationship between pollution-driving forces and purification and inhibition capabilities.

[0107] Example 5

[0108] Please refer to Figure 1 and Figure 2 Specifically: the execution control module is used to receive the assessment information generated by the air cleanliness assessment and the photocatalytic cleanliness assessment in real time, and execute the corresponding control instructions, as follows;

[0109] Pollution risk information: Immediately increase the power of the ultraviolet light source in the air circulation channel by 15% and increase the fan speed by 15%;

[0110] Purification excess information: The power of the ultraviolet light source and the fan power are gradually reduced to the process baseline at a rate of 5% per minute until the standard air purification procedure is restored, and continuous monitoring is carried out;

[0111] Purification Maintenance Information: Maintain the current air purification program and display a green air quality compliance instruction on the control panel;

[0112] Air purification collapse risk information: Based on the current air purification program, the ultraviolet light source and fan will be gradually increased to the maximum power within the safe range at a rate of 5% per minute, and iterative analysis will be performed through the cleanliness analysis module. If the photocatalytic efficiency still does not meet the standard after ten minutes, the system will be shut down for rectification.

[0113] In this embodiment, the control module achieves dynamic control matching the pollution state by receiving and analyzing air cleanliness assessments and photocatalytic purification capacity assessments in real time. When the system determines a pollution risk, it immediately increases the power of the ultraviolet light source and the fan speed to rapidly enhance purification capacity; when it determines that purification is excessive, it gradually reduces power to avoid energy waste; when in a purification maintenance state, it maintains the current operating conditions to ensure stable purification; and when there is a risk of purification collapse, it adopts a method of gradually increasing power and superimposed iterative analysis for extreme compensation. If the standard is still not met, a shutdown for rectification is triggered. Through the above implementation method, a precise linkage between pollution state and control measures is achieved, avoiding the energy consumption redundancy and purification lag problems caused by the "fixed power operation" or "delayed response" of traditional systems, and improving the real-time performance and targeting of the purification system. Its beneficial effects are that it achieves the dual goals of energy saving and consumption reduction and safety protection, enabling the air purification system in the electronics industrial plant to have higher operating efficiency, risk response capabilities, and long-term stability.

[0114] Example 6

[0115] Please refer to Figure 1 and Figure 2 Specifically: the operation and maintenance interaction module includes an alarm display unit and an event recording unit;

[0116] The alarm display unit is used to automatically switch the human-machine interface and the sound and light device to the corresponding display mode and alarm mode based on different information from air cleanliness assessment and photocatalytic cleanliness assessment, and to issue graded alarms for pollution levels.

[0117] When receiving pollution risk information, the human-machine interface displays a yellow alarm and does not trigger the sound and light devices;

[0118] When receiving information on excess purification and purification maintenance, the human-machine interface displays a green "air environment meets standards" message and does not trigger the sound and light devices.

[0119] When receiving information about the risk of collapse during purification, the human-machine interface displays a red alarm, triggering the sound and light device to issue an audible and visual alarm.

[0120] The event recording unit is used to record the nano-pollution disturbance index (nan), photocatalytic reaction efficiency index (npc), and purification collapse risk index (Rall) in real time during the operation of the air purification system. It also records the corresponding control commands and final execution effects of air cleanliness assessment and photocatalytic purification capability assessment. Combined with the alarm display unit, yellow alarm data and red alarm data are marked as environmental pollution data and purification collapse data, respectively. A complete operation log and event archive are generated, and then paired and archived according to timestamps to form a traceable closed-loop data chain of "data, assessment, command, and result" and stored in the time-series database.

[0121] In this embodiment, the operation and maintenance interaction module, through the collaborative operation of the alarm display unit and the event recording unit, realizes graded prompts and full-process traceability during the operation of the air purification system. When the system receives different assessment information, it can issue graded alarms through the human-machine interface and audio-visual devices. Pollution risk information corresponds to a yellow prompt, purification surplus and maintenance information corresponds to a green prompt, and purification collapse risk information corresponds to a red prompt accompanied by an audio-visual alarm, enabling operation and maintenance personnel to intuitively perceive the air environment status at the first moment. At the same time, the event recording unit synchronously records the nano-pollution disturbance index (nan), the photocatalytic reaction efficiency index (npc), and the purification collapse risk index (Rall) with the corresponding control commands and execution results. Combined with the graded labeling of the alarm display, it generates an operation log and event archive, which are archived with timestamps to form a traceable data chain and stored in a time-series database. Through the above implementation method, not only is real-time monitoring and visual prompts of the air purification process realized, but also closed-loop management between data, assessment, commands, and execution results is achieved. Compared with existing methods that can only generate a single alarm or lack complete archiving, this invention significantly improves the traceability and reliability of the system in fault diagnosis, operation optimization and long-term operation and maintenance, ensures the stability and safety of air purification in electronic industrial plants, and brings substantial improvements in reducing operation and maintenance costs and improving management efficiency.

[0122] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. An air purification system for an electronic industry plant, characterized by: The system comprises a pollution detection module, a clean analysis module, a purification feedback module, an execution control module and an operation and maintenance interaction module. The pollution detection module is configured to collect pollution characteristic data in the electronic industrial plant in real time according to the installed sensor group, and obtain an air particle data group and a purification efficiency data group after data processing. The air particle data group comprises light source scattering intensity sc, particle mass concentration mp and air flow qa. The purification performance data set comprises an ultraviolet light intensity uv, an air humidity sd, a volatile organic compound concentration at the inlet of the photocatalytic device VOC in and a volatile organic compound concentration at the outlet of the photocatalytic device VOC out ; The clean analysis module comprises an air quality analysis unit and an air quality evaluation unit. The air quality analysis unit is used for data fitting on the air particle data set, analyzing the influence of optical scattering and particle concentration on air quality, quantifying the real-time intensity of particle pollution in the plant air, and constructing a nanometer pollution disturbance index nan according to the air particle data set, and then performing air cleanliness evaluation with the air quality evaluation unit and the particle overflow critical threshold Tm, and performing photocatalytic degradation analysis when nanometer pollution is evaluated to exist, and the specific formula is: , wherein, ln represents a logarithmic function, sc(t), mp(t) and qa(t) respectively represent the light source scattering intensity, particle mass concentration and air flow at time t, sc base represents the standard light source scattering intensity in a clean air environment; The purification feedback module is configured to perform photocatalytic degradation analysis when the air cleanliness evaluation indicates that there is nano-pollution in the air, and specifically comprises an efficiency analysis unit and a risk evaluation unit. The efficiency analysis unit is used for data fitting on the purification efficiency data set, analyzing the carrying efficiency of the photocatalytic reaction in decomposing pollutants, dynamically quantifying the purification efficiency of photocatalysis, and constructing a photocatalytic reaction efficiency index npc according to the purification efficiency data set, and the specific formula is: , wherein, ln represents a logarithmic function, uv(t), sd(t), VOC in (t) and VOC out (t) represent the ultraviolet light intensity, air humidity, volatile organic compound concentration at the inlet of the photocatalytic device and volatile organic compound concentration at the outlet of the photocatalytic device at t moment, respectively. The risk evaluation unit is configured to comprehensively judge the air environment in the electronic industrial plant by comprehensively comparing the real-time air pollution degree and the purification efficiency, and specifically comprises a pollution risk analysis unit and a purification evaluation unit. The pollution risk analysis unit is used for constructing a purification collapse risk index Rall according to the nanometer pollution disturbance index nan and the photocatalytic reaction efficiency index npc, combining the pollution level with the purification efficiency, quantifying the confrontation relationship between the pollution level and the purification efficiency, and performing photocatalytic cleaning capacity evaluation through the purification evaluation unit and the clean capacity stability threshold Tw and the clean capacity collapse threshold Tj, and the specific formula is: , wherein exp represents an exponential decay function. The execution control module is configured to receive evaluation information in real time and execute corresponding control instructions. The operation and maintenance interaction module is configured to display the environmental state in a hierarchical manner on a man-machine interaction interface according to the evaluation information, and store the operation log and event archive to a time sequence database.

2. The air purification system for electronic industry factory building according to claim 1, characterized in that: The pollution detection module comprises a pollution detection unit and a data processing unit. The pollution detection unit is configured to activate the air purification system of the electronic industrial plant when the electronic industrial plant enters the production mode, start the fan, the photocatalytic device and the air circulation pipeline, and collect pollution characteristic data in the electronic industrial plant in real time according to the installed sensor group. The sensor group comprises a photoelectric receiver, an optical particulate matter monitor, an air volume sensor, a temperature and humidity sensor and a VOC sensor. The photoelectric receiver is configured to be installed at the inlet of the air circulation pipeline of the air purification system in the electronic plant to directly read the light source scattering intensity Isc. The optical particulate matter monitor is configured to be installed 2m above the production line in the electronic plant to monitor the suspended particle mass concentration mp in the air of the working area in real time. The air volume sensor is configured to be arranged at the outlet of the fan and the inlet of the photocatalytic device in the main air duct of the air purification system to collect the air flow qa in real time. The temperature and humidity sensor is configured to be arranged at the inlet of the photocatalytic device to monitor the air humidity sd entering the air purification system in real time. The VOC sensor is used for fixing at the inlet and outlet of the photocatalytic device fixed on the wall surface of the outlet air duct, and real-time collection of the volatile organic compound concentration VOC at the inlet and outlet of the photocatalytic device in and VOC out .

3. The air purification system for electronic industry factory building according to claim 2, characterized in that: The data processing unit is configured to process the pollution characteristic data to obtain the air particle data group and the purification efficiency data group. The data processing comprises denoising, timestamp alignment and dimensionless processing. The denoising removes the noise influence in the pollution characteristic data through band-pass filtering; the timestamp alignment is used to project the pollution characteristic data with different sampling frequencies to the same time axis, and linear interpolation is used to fill in the missing points and uneven pollution characteristic data to form a data sequence with uniform time step; the dimensionless processing removes the dimension influence of the state data by the Max-Min maximum and minimum method.

4. The air purification system for electronic industry factory building according to claim 1, characterized in that: The air quality assessment unit is used to collect all nanometer pollution disturbance indexes nan in the historical one month when the air cleanliness is in the normal range, sort them from small to large, and then preset the Q95 percentile value as the particle overflow critical threshold Tm according to the percentile method, and then compare the real-time obtained nanometer pollution disturbance index nan, and perform air cleanliness assessment according to the comparison result, and the specific assessment scheme is as follows: The particle overflow critical threshold Tm represents the critical point at which the overflow effect of the nanometer particles in the air begins to appear. When the nanometer pollution disturbance index nan is less than or equal to the particle overflow critical threshold Tm, it indicates that the air cleanliness is in the normal range, and at this time the standard air purification program is maintained. When the nanometer pollution disturbance index nan is greater than the particle overflow critical threshold Tm, it indicates that there is nanometer pollution in the air, at which time pollution risk information is generated, and photocatalytic degradation analysis is performed at the same time.

5. The air purification system for electronic industry factory building according to claim 1, characterized in that: The purification assessment unit is used to collect all purification collapse risk indexes Rall in the historical one month, and calculate the mean and standard deviation by statistical method, and preset the mean as the clean ability stability threshold Tw, and preset the sum of the mean and the standard deviation as the clean ability collapse threshold Tj, and then compare the real-time obtained purification collapse risk index Rall, and perform photocatalytic clean ability assessment according to the comparison result, and the specific assessment scheme is as follows: The clean ability stability threshold Tw represents the surplus boundary of the stable operation of the plant air cleaning. The clean ability collapse threshold Tj represents the demarcation point at which the stability of the plant air cleaning environment begins to collapse. When the purification collapse risk index Rall is less than the clean ability stability threshold Tw, it indicates that the photocatalytic efficiency is surplus, at which time purification surplus information is generated. When the clean ability stability threshold Tw is less than or equal to the purification collapse risk index Rall and is less than or equal to the clean ability collapse threshold Tj, it indicates that the photocatalytic efficiency meets the pollution purification, at which time purification maintenance information is generated. When the purification collapse risk index Rall is greater than the clean ability collapse threshold Tj, it indicates that the photocatalytic efficiency is not up to standard, at which time purification collapse risk information is generated.

6. The air purification system for electronic industry factory building according to claim 1, characterized in that: The execution control module is used to receive the assessment information generated by the air cleanliness assessment and the photocatalytic clean ability assessment in real time, and execute the corresponding control instructions, and the specific control instructions are as follows: Pollution risk information: immediately increase the power of the ultraviolet light source in the air circulation channel by 15%, and increase the fan speed by 15%; Purification surplus information: the power of the ultraviolet light source and the fan power is reduced to the process baseline at a rate of 5% per minute, until the standard air purification program is restored, and continuous monitoring is performed; Purification maintenance information: maintain the current air purification program, and display the green air standard instruction on the control panel; Purification collapse risk information: on the basis of the current air purification program, the ultraviolet light source and the fan are slowly increased to the maximum power in the safe range at a rate of 5% per minute, and iterative analysis is performed through the clean analysis module, if the photocatalytic efficiency is still not up to standard after ten minutes, then stop and rectify.

7. The air purification system for electronic industry factory building according to claim 1, characterized in that: The operation and maintenance interaction module includes an alarm display unit and an event recording unit. The alarm display unit is used for switching the man-machine interactive interface and the sound and light device to the corresponding display mode and alarm mode according to different information of the air cleanliness evaluation and the photocatalytic cleaning ability evaluation, and performing hierarchical alarm of the pollution level; When receiving the pollution risk information, the man-machine interactive interface displays yellow alarm, and the sound and light device is not triggered; When receiving the purification surplus information and the purification maintenance information, the man-machine interactive interface displays green air environment up to standard, and the sound and light device is not triggered; When receiving the purification collapse risk information, the man-machine interactive interface displays red alarm, and the sound and light device is triggered to perform sound and light alarm; The event recording unit is used for recording the nanometer pollution disturbance index nan, the photocatalytic reaction efficiency index npc and the purification collapse risk index Rall in real time during the operation of the air purification system, and recording the corresponding regulation instructions and the final execution effect of the air cleanliness evaluation and the photocatalytic cleaning ability evaluation synchronously, marking the yellow alarm data and the red alarm data as environmental pollution data and purification collapse data respectively by combining the alarm display unit, generating complete operation logs and event archives, pairing and archiving according to the time stamp, forming a closed-loop data chain of "data, evaluation, instruction and result" which is traceable, and storing to a time sequence database.

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