Dangerous chemical substance storage environment data analysis system

Abstract

The invention discloses a hazardous chemical substance storage environment data analysis system, and relates to the technical field of hazardous chemical substance safety management, and the system comprises a photocatalytic reaction spectrum acquisition module, an environmental parameter sensing and transmission module, a multi-source data preprocessing module, a self-purification capability dynamic evaluation module and an intelligent early warning linkage control module. A composite photocatalyst coating is deployed by adopting a high-pressure airless spraying process, a photocatalytic reaction characteristic spectrum is monitored in real time in combination with an optical fiber spectrometer, meanwhile, multiple types of sensors are integrated to construct a three-dimensional sensing network, and a multi-source data preprocessing module corrects humidity parameters through a temperature compensation quadratic curve fitting algorithm; the time stamp alignment technology is combined, the data space-time consistency is ensured, the self-cleaning capacity dynamic evaluation module proposes three core indexes of real-time degradation efficiency, risk accumulation indexes and self-cleaning completion time, the influences of coating attenuation and environment variables on the degradation effect are dynamically reflected through a quantification formula, and a scientific early warning basis is provided for storage safety.

Description

Technical Field

[0001] This invention relates to the field of hazardous chemical safety management technology, specifically a hazardous chemical storage environment data analysis system. Background Technology

[0002] In many industrial sectors such as chemical, pharmaceutical, and energy, the storage and management of hazardous chemicals (HCCs) is a crucial link in ensuring production safety and preventing environmental pollution. If environmental conditions are not properly controlled during the storage of HCCs, serious accidents such as leaks, explosions, and poisoning can easily occur, posing a huge threat to personnel safety, the ecological environment, and enterprise property. Therefore, real-time and accurate monitoring and analysis of the HCC storage environment has become an important means of preventing accidents and ensuring safety. With the rapid development of technologies such as the Internet of Things, big data, and artificial intelligence, the construction of intelligent and networked HCC storage environment monitoring systems using advanced sensors, data analysis algorithms, and automated control technologies has become an inevitable trend for improving safety management and reducing accident risks.

[0003] Traditional methods for monitoring the storage environment of hazardous chemicals mainly rely on manual inspections and periodic environmental parameter testing. This approach has many limitations. First, manual inspections are difficult to conduct 24-hour uninterrupted monitoring and are easily affected by human factors, leading to untimely and inaccurate data acquisition. Second, while periodic testing can provide environmental parameters at certain points in time, it cannot reflect environmental changes in real time, especially in emergencies such as sudden leaks, making it difficult to respond quickly. In addition, traditional monitoring methods lack the ability to comprehensively analyze and provide early warnings of environmental parameters, cannot effectively assess the environment's self-cleaning capacity and potential risks, and cannot guide the implementation of targeted prevention and control measures. Therefore, traditional technologies can no longer meet the high requirements of modern industry for the safety monitoring of hazardous chemical storage environments. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of existing technologies and provide a hazardous chemical storage environment data analysis system. This system applies a composite photocatalytic coating to the storage area using a high-pressure airless spraying process and collects photocatalytic reaction spectra using a fiber optic spectrometer. Simultaneously, multiple sensors are deployed to collect environmental parameters in real time. After preprocessing the multi-source data, the system dynamically assesses the self-cleaning capacity, generates an assessment report, and, based on the report, initiates early warnings and coordinates equipment to regulate the environment. By employing multi-parameter collaborative optimization, the system ensures the safe and efficient storage of hazardous chemicals.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a hazardous chemical storage environment data analysis system, the system comprising: Photocatalytic reaction spectral acquisition module: A composite photocatalytic coating is applied to the inner walls, shelf sides and floor seams of the hazardous chemical storage area using a high-pressure airless spraying process, and a fiber optic spectrometer is deployed to collect the characteristic spectra before and after the photocatalytic reaction in real time. Environmental parameter sensing and transmission module: Deploys silicon-based photodiode light sensors, capacitive humidity sensors, temperature sensors, and gas flow rate sensors in the storage area to collect various environmental parameters at a set frequency and complete data transmission; Multi-source data preprocessing module: Receives data from the photocatalytic reaction spectrum acquisition module and the environmental parameter sensing and transmission module, and performs preprocessing operations such as filtering, feature extraction, parameter correction and timestamp alignment on the data. The parameter correction adopts a temperature-compensated quadratic curve fitting algorithm. Self-cleaning capacity dynamic assessment module: Based on the pre-processed dataset, the module uses the real-time degradation efficiency calculation formula, the risk accumulation index calculation formula, and the self-cleaning completion time calculation formula to calculate the real-time degradation efficiency, risk accumulation index, and self-cleaning completion time, and then generates a dynamic assessment report. Intelligent early warning and linkage control module: Receives dynamic evaluation reports, initiates corresponding level of early warning measures based on the report content, and links relevant equipment to perform light adjustment, humidity control, and coating maintenance operations. The light adjustment adopts the light adjustment control target calculation formula, and the multi-parameter collaborative optimization adopts the multi-parameter collaborative optimization objective function.

[0006] Furthermore, the composite photocatalytic coating in the photocatalytic reaction spectral acquisition module uses nano-titanium dioxide as the substrate, doped with 5% zinc oxide and 2% graphene quantum dots. The particle size of the graphene quantum dots is in the nanometer range (3-5nm), and they are uniformly doped by ultrasonic dispersion.

[0007] Furthermore, the working pressure of the high-pressure airless spraying process in the photocatalytic reaction spectrum acquisition module is 15-20MPa, the spraying speed is 0.5-1m / s, and the coating thickness deviation does not exceed ±5μm.

[0008] Furthermore, the sampling frequency of the silicon-based photodiode light sensor and temperature sensor in the environmental parameter sensing and transmission module is 1Hz; the sampling frequency of the humidity sensor can be automatically adjusted according to the rate of change of ambient humidity. When the rate of change of humidity is ≤5% / min, the sampling frequency is 1Hz, and when the rate of change of humidity is >5% / min, the sampling frequency is automatically increased to 5Hz.

[0009] Furthermore, the temperature-compensated quadratic curve fitting algorithm in the multi-source data preprocessing module is as follows: ,in, This is the compensated humidity value; The humidity value measured by the sensor; , The compensation coefficient; The ambient temperature.

[0010] Furthermore, the formula for calculating the real-time degradation efficiency in the self-cleaning capacity dynamic evaluation module is as follows: ,in for Real-time degradation efficiency at any given moment; This represents the initial degradation efficiency. This is the light influence coefficient; for Light intensity at any given moment; For optimal light intensity; Humidity influence coefficient; for Relative humidity at any given time; For optimal degradation humidity; This represents the maximum humidity measurement value. This is the minimum value for humidity measurement; The coating attenuation coefficient; This refers to the coating's service life.

[0011] Furthermore, the formula for calculating the risk accumulation index in the self-cleaning capacity dynamic assessment module is as follows: ,in, for Risk accumulation index at any given moment; This represents the initial leakage concentration. for Degradation efficiency at any given time; This refers to the volume of the storage area. These are the safety concentration limits for hazardous chemicals; This refers to the temperature sensitivity coefficient. for The ambient temperature at that moment; This is a reference temperature.

[0012] Furthermore, the formula for calculating the self-cleaning completion time in the self-cleaning capacity dynamic assessment module is as follows: ,in, This refers to the self-cleaning completion time. This is the coating attenuation coefficient; This represents the initial leakage concentration. This refers to the volume of the storage area. The rate constant of the photocatalytic reaction; This represents the initial degradation efficiency. To predict the average light intensity within the period; This represents the total area of ​​the photocatalytic coating.

[0013] Furthermore, the calculation formula for the illumination adjustment control target in the intelligent early warning linkage control module is as follows: ,in, for The target light intensity at any given time; For optimal light intensity; for Real-time degradation efficiency at any given moment.

[0014] Furthermore, the multi-parameter collaborative optimization objective function in the intelligent early warning linkage control module is: The constraints are , , ,in, To comprehensively optimize the objectives; , , These are weighting coefficients (representing time, risk, and energy consumption priority, respectively). This refers to the self-cleaning completion time. To optimize the maximum risk index within the cycle; Energy consumption for auxiliary equipment; for Real-time degradation efficiency at any given moment; for Relative humidity at any given time; for Light intensity at any given time.

[0015] Compared with existing technologies, this hazardous chemical storage environment data analysis system has the following advantages: I. This invention employs a high-pressure airless spraying process to deploy a composite photocatalytic coating, combined with real-time monitoring of the photocatalytic reaction characteristic spectrum using a fiber optic spectrometer. Simultaneously, it integrates multiple types of sensors to construct a three-dimensional sensing network. A multi-source data preprocessing module corrects humidity parameters using a temperature-compensated quadratic curve fitting algorithm, and timestamp alignment technology ensures data spatiotemporal consistency. A self-cleaning capability dynamic assessment module proposes three core indicators: real-time degradation efficiency, risk accumulation index, and self-cleaning completion time. These indicators dynamically reflect the impact of coating decay and environmental variables on degradation effects through quantitative formulas, providing a scientific early warning basis for storage safety and improving the accuracy and timeliness of risk prediction.

[0016] Second, this invention constructs an efficient closed-loop management system for environmental safety through deep collaboration between an intelligent early warning linkage control module and a dynamic evaluation module. The system automatically generates collaborative control strategies for light intensity adjustment, humidity threshold control, and coating regeneration cycle by analyzing the coupling relationship between environmental parameters and photocatalytic reaction efficiency in real time. This ensures that the storage environment is always within a safe and controllable range. Through the linkage control mode of multiple devices and multiple parameters, it not only shortens the response cycle for environmental anomalies but also reduces equipment idling rate and energy consumption through dynamic resource allocation, ultimately achieving the goal of ensuring storage safety and optimizing operating costs.

[0017] Other advantages, objectives and features of the invention will be set forth in part in the description which follows, and in part will be apparent to those skilled in the art from the following examination or study, or may be learned from the practice of the invention. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0019] Figure 1 This is an overall architecture diagram of a hazardous chemical storage environment data analysis system; Figure 2 This is a flowchart of the photocatalytic reaction spectral acquisition module. Figure 3 This is a logic diagram for intelligent early warning and linkage control. Detailed Implementation

[0020] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided below.

[0021] Example 1: Monitoring scenario of a hazardous chemical storage center in a large chemical industrial park In a hazardous chemical storage center of a large chemical industrial park (mainly storing flammable and explosive solvents, toxic chemicals, etc.), the hazardous chemical storage environment data analysis system of this invention was applied. The specific implementation process is as follows: Deployment of the photocatalytic reaction spectral acquisition module: A composite photocatalytic coating (based on nano-titanium dioxide, doped with 5% zinc oxide and 2% graphene quantum dots, with a particle size of 3-5 nm, uniformly doped using ultrasonic dispersion) is applied using a high-pressure airless spraying process to the interior walls, side facades of multi-layer shelving, and floor seams in the storage center. This coating can degrade leaked hazardous chemicals through photocatalysis, reducing the concentration of hazardous chemicals in the air. Simultaneously, fiber optic spectrometers are uniformly deployed in the coating area to collect characteristic spectra before and after the photocatalytic reaction in real time. The spectral changes are used to determine the coating's degradation effect on hazardous chemicals, providing direct data support for evaluating coating performance. Figure 2 As shown, this module achieves real-time monitoring of the photocatalytic reaction through the above process.

[0022] The environmental parameter sensing and transmission module operates as follows: Silicon-based photodiode light sensors, capacitive humidity sensors, temperature sensors, and gas flow rate sensors are deployed in different areas within the storage center. Among them, the silicon-based photodiode light sensors and temperature sensors have a sampling frequency of 1Hz, continuously monitoring light intensity and ambient temperature, which directly affect the efficiency of photocatalytic reaction. The sampling frequency of the humidity sensor is automatically adjusted according to the rate of change of ambient humidity. When the rate of change of humidity is ≤5% / min, the sampling frequency is 1Hz; when the rate of change of humidity is >5% / min, the sampling frequency is automatically increased to 5Hz. This ensures data continuity and allows for rapid capture of changes when humidity changes abruptly. All environmental parameters collected by the sensors are transmitted to the system in real time, providing basic data for subsequent analysis.

[0023] Multi-source data preprocessing module: After receiving data from the photocatalytic reaction spectrum acquisition module and the environmental parameter sensing and transmission module, the system first performs filtering to remove signal noise, then extracts characteristic peaks from the spectrum and key change features from the environmental parameters; subsequently, a temperature-compensated quadratic curve fitting algorithm is used to correct the humidity data, eliminating the interference of temperature on humidity measurement and ensuring the accuracy of the humidity data. The temperature-compensated quadratic curve fitting algorithm is as follows: ,in, This is the compensated humidity value; The humidity value measured by the sensor; , The compensation coefficient; The ambient temperature was used as the reference. Finally, all data were timestamped to match the spectral data with the environmental parameters in time, providing a consistent data foundation for subsequent correlation analysis.

[0024] Analysis of the self-cleaning capacity dynamic assessment module: Based on the preprocessed dataset, the real-time degradation efficiency, risk accumulation index, and self-cleaning completion time are calculated using the real-time degradation efficiency calculation formula, the risk accumulation index calculation formula, and the self-cleaning completion time calculation formula. The real-time degradation efficiency calculation formula is as follows: ,in for Real-time degradation efficiency at any given moment; This represents the initial degradation efficiency. This is the light influence coefficient; for Light intensity at any given moment; For optimal light intensity; Humidity influence coefficient; for Relative humidity at any given time; For optimal degradation humidity; This represents the maximum humidity measurement value. This is the minimum value for humidity measurement; This is the coating attenuation coefficient; The coating usage time; the risk accumulation index calculation formula is: ,in, for Risk accumulation index at any given moment; This represents the initial leakage concentration. for Degradation efficiency at any given time; This refers to the volume of the storage area. These are the safety concentration limits for hazardous chemicals; This refers to the temperature sensitivity coefficient. for The ambient temperature at that moment; The reference temperature is used; the formula for calculating the self-cleaning completion time is: ,in, This refers to the self-cleaning completion time. This is the coating attenuation coefficient; This represents the initial leakage concentration. This refers to the volume of the storage area. The rate constant of the photocatalytic reaction; This represents the initial degradation efficiency. To predict the average light intensity within the period; The total area of ​​the photocatalytic coating; real-time degradation efficiency reflects the coating's current ability to degrade hazardous chemicals; risk accumulation index assesses the risk level after a hazardous chemical leak; and self-cleaning completion time predicts the time it takes for the environment to return to a safe state. These three factors are integrated to form a dynamic assessment report, comprehensively presenting the self-cleaning capacity and potential risks of the storage center, such as... Figure 1 As shown.

[0025] Intelligent early warning and linkage control module response: After receiving the dynamic assessment report, if the system detects abnormal risk indicators, it immediately activates the corresponding level of early warning (such as audible and visual alarms, sending early warning text messages to management personnel); simultaneously, it links relevant equipment: adjusting the supplementary lighting system of the storage center according to the light adjustment control target calculation formula to optimize light intensity. The light adjustment control target calculation formula is: ,in, for The target light intensity at any given time; For optimal light intensity; for Real-time degradation efficiency; humidity is regulated within a suitable range using ventilation and humidification equipment; if coating performance declines, a coating maintenance prompt is triggered. The entire process balances various indicators through a multi-parameter collaborative optimization objective function to ensure a safe storage environment. The multi-parameter collaborative optimization objective function is: The constraints are , , ,in, To comprehensively optimize the objectives; , , These are weighting coefficients (representing time, risk, and energy consumption priority, respectively). This refers to the self-cleaning completion time. To optimize the maximum risk index within the cycle; Energy consumption for auxiliary equipment; for Real-time degradation efficiency at any given moment; for Relative humidity at any given time; for The light intensity at any given time, and its early warning and linkage control logic, are as follows: Figure 3 As shown.

[0026] In summary, in the application scenario of a hazardous chemical storage center in a large chemical industrial park, this hazardous chemical storage environment data analysis system, by deploying a composite photocatalytic coating and a fiber optic spectrometer, achieves real-time monitoring of the photocatalytic degradation process. Combined with multiple types of sensors collecting environmental parameters at dynamic frequencies, it provides comprehensive raw data for the system. After filtering, correction, and timestamp alignment by the multi-source data preprocessing module, the dynamic evaluation report generated by the self-cleaning capacity dynamic evaluation module through three core calculation formulas accurately reflects the degradation efficiency, risk level, and self-cleaning time of the storage center. Finally, the intelligent early warning and linkage control module initiates tiered early warnings based on the report and links equipment for light and humidity control and coating maintenance. Through multi-parameter collaborative optimization, it ensures the safety of hazardous chemical storage while achieving a balance between energy consumption and efficiency, fully demonstrating the system's precise control capabilities in complex environments within large-scale storage scenarios.

[0027] Example 2: Monitoring scenario of a hazardous chemical storage room in a pharmaceutical and chemical enterprise In a hazardous chemical storage room (containing pharmaceutical intermediates, corrosive reagents, etc.) of a pharmaceutical and chemical company, the hazardous chemical storage environment data analysis system of this invention was applied. The specific implementation process is as follows: Deployment of the photocatalytic reaction spectral acquisition module: A composite photocatalytic coating (using nano-titanium dioxide as the substrate, doped with 5% zinc oxide and 2% graphene quantum dots, with a particle size of 3-5 nm, uniformly doped by ultrasonic dispersion) is applied to the inner walls of the storage room, the inner side of the reagent storage cabinet, and the gaps in the floor using a high-pressure airless spraying process. This coating can decompose leaked hazardous chemicals under light irradiation, reducing the concentration of toxic substances in the room. Simultaneously, fiber optic spectrometers are deployed at key locations on the coating to collect characteristic spectra before and after the photocatalytic reaction in real time. The degree of degradation reaction is determined by the spectral differences, providing a basis for evaluating the coating's effectiveness. Figure 2 As shown.

[0028] The environmental parameter sensing and transmission module operates as follows: Inside the storage room, silicon-based photodiode light sensors, capacitive humidity sensors, temperature sensors, and gas flow rate sensors are deployed. Among them, the light and temperature sensors collect data at a frequency of 1Hz to continuously monitor the key environmental conditions of the photocatalytic reaction; the humidity sensor adjusts the collection frequency according to the humidity change rate, collecting at 1Hz when the humidity change is slow and increasing to 5Hz when the change is rapid, ensuring timely capture of the impact of humidity on coating activity. All parameters are transmitted to the system in real time to ensure the timeliness of the data.

[0029] Multi-source data preprocessing module: After receiving spectral data and environmental parameters, the system first filters the data to remove interference signals, then extracts key features; a temperature-compensated quadratic curve fitting algorithm is used to correct humidity data and eliminate temperature interference. The temperature-compensated quadratic curve fitting algorithm is as follows: Finally, timestamp alignment is performed to synchronize data from different sources in time, providing reliable data for subsequent analysis of the relationship between photocatalytic reactions and environmental parameters.

[0030] Analysis of the self-cleaning capacity dynamic assessment module: Based on preprocessed data, the real-time degradation efficiency, risk accumulation index, and self-cleaning completion time are obtained using the formulas for calculating real-time degradation efficiency, risk accumulation index, and self-cleaning completion time. The formula for calculating real-time degradation efficiency is as follows: The formula for calculating the risk accumulation index is: The formula for calculating the self-cleaning completion time is: These indicators together constitute a dynamic assessment report, reflecting the storage room's self-cleaning capacity and risk status in real time, providing data support for safety management, such as... Figure 1 As shown.

[0031] Intelligent early warning and linkage control module response: Based on the dynamic assessment report, if the system detects that the risk exceeds the standard, it immediately activates early warning measures (such as illuminating the warning light at the storage room entrance and linking the access control system to restrict entry); simultaneously, it links the equipment to adjust the indoor light source intensity according to the light adjustment control target calculation formula to optimize the photocatalytic reaction conditions. The light adjustment control target calculation formula is as follows: Maintain suitable humidity using humidity control equipment; prompt maintenance if coating performance deteriorates; balance safety and energy consumption through multi-parameter collaborative optimization of the objective function to ensure a stable and safe storage environment. The multi-parameter collaborative optimization objective function is as follows: Its early warning and linkage control logic is as follows: Figure 3 As shown.

[0032] In summary, in the application scenario of hazardous chemical storage rooms in pharmaceutical and chemical enterprises, this system effectively captures the degradation state of hazardous chemicals by photocatalytic reactions through the application of a composite photocatalytic coating and the deployment of spectral acquisition equipment in a closed space. The environmental parameter sensing and transmission module dynamically adjusts the acquisition frequency according to humidity changes, ensuring timely acquisition of key parameters. The pre-processed multi-source data is transformed into an intuitive dynamic assessment report through the three calculation formulas of the self-cleaning capacity dynamic assessment module, presenting the self-cleaning capacity and risk level of the storage room in real time. The intelligent early warning and linkage control module initiates targeted early warnings and equipment adjustments based on the report. By optimizing lighting, humidity, and coating maintenance, the system ensures the safety of the storage room environment while also taking into account energy consumption control. This process fully demonstrates the system's adaptability and efficient management capabilities in small, closed storage spaces with high safety requirements.

[0033] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A hazardous chemical storage environment data analysis system, characterized by, The system includes: Photocatalytic reaction spectral acquisition module: A composite photocatalytic coating is applied to the inner walls, shelf sides and floor seams of the hazardous chemical storage area using a high-pressure airless spraying process, and a fiber optic spectrometer is deployed to collect the characteristic spectra before and after the photocatalytic reaction in real time. Environmental parameter sensing and transmission module: Deploys silicon-based photodiode light sensors, capacitive humidity sensors, temperature sensors, and gas flow rate sensors in the storage area to collect various environmental parameters at a set frequency and complete data transmission; Multi-source data preprocessing module: Receives data from the photocatalytic reaction spectrum acquisition module and the environmental parameter sensing and transmission module, and performs preprocessing operations such as filtering, feature extraction, parameter correction and timestamp alignment on the data. The parameter correction adopts a temperature-compensated quadratic curve fitting algorithm. Self-cleaning capacity dynamic assessment module: Based on the pre-processed dataset, the module uses the real-time degradation efficiency calculation formula, the risk accumulation index calculation formula, and the self-cleaning completion time calculation formula to calculate the real-time degradation efficiency, risk accumulation index, and self-cleaning completion time, and then generates a dynamic assessment report. Intelligent early warning and linkage control module: Receives dynamic evaluation reports, initiates corresponding level of early warning measures based on the report content, and links relevant equipment to perform light adjustment, humidity control, and coating maintenance operations. The light adjustment adopts the light adjustment control target calculation formula, and the multi-parameter collaborative optimization adopts the multi-parameter collaborative optimization objective function.

2. The dangerous chemical storage environment data analysis system according to claim 1, wherein, The composite photocatalytic coating in the photocatalytic reaction spectral acquisition module uses nano-titanium dioxide as the substrate, doped with zinc oxide and graphene quantum dots. The graphene quantum dots have a particle size of nanometers and are uniformly doped by ultrasonic dispersion.

3. The hazardous chemical storage environment data analysis system according to claim 1, characterized in that, The working pressure of the high-pressure airless spraying process in the photocatalytic reaction spectrum acquisition module is 15-20MPa, the spraying speed is 0.5-1m / s, and the coating thickness deviation does not exceed ±5μm.

4. The hazardous chemical storage environment data analysis system according to claim 1, characterized in that, The sampling frequency of the silicon-based photodiode light sensor and temperature sensor in the environmental parameter sensing and transmission module is 1Hz; the sampling frequency of the humidity sensor can be automatically adjusted according to the rate of change of ambient humidity. When the rate of change of humidity is ≤5% / min, the sampling frequency is 1Hz, and when the rate of change of humidity is >5% / min, the sampling frequency is automatically increased to 5Hz.

5. The hazardous chemical storage environment data analysis system according to claim 1, characterized in that, The temperature-compensated quadratic curve fitting algorithm in the multi-source data preprocessing module is as follows: ,in, This is the compensated humidity value; The humidity value measured by the sensor; , This is the compensation coefficient; The ambient temperature.

6. The hazardous chemical storage environment data analysis system according to claim 1, characterized in that, The formula for calculating the real-time degradation efficiency in the self-cleaning capacity dynamic assessment module is as follows: ,in for Real-time degradation efficiency at any given moment; This represents the initial degradation efficiency. This is the light influence coefficient; for Light intensity at any given moment; For optimal light intensity; Humidity influence coefficient; for Relative humidity at any given time; For optimal degradation humidity; This represents the maximum humidity measurement value. This is the minimum value for humidity measurement; This is the coating attenuation coefficient; This refers to the coating's service life.

7. The hazardous chemical storage environment data analysis system according to claim 1, characterized in that, The formula for calculating the risk accumulation index in the self-cleaning capacity dynamic assessment module is as follows: ,in, for Risk accumulation index at any given moment; This represents the initial leakage concentration. for Degradation efficiency at any given time; This refers to the volume of the storage area. These are the safety concentration limits for hazardous chemicals; This refers to the temperature sensitivity coefficient. for The ambient temperature at that moment; This is a reference temperature.

8. The hazardous chemical storage environment data analysis system according to claim 1, characterized in that, The formula for calculating the self-cleaning completion time in the self-cleaning capacity dynamic assessment module is as follows: ,in, This refers to the self-cleaning completion time. This is the coating attenuation coefficient; This represents the initial leakage concentration. This refers to the volume of the storage area. The rate constant of the photocatalytic reaction; This represents the initial degradation efficiency. To predict the average light intensity within the period; This represents the total area of ​​the photocatalytic coating.

9. A hazardous chemical storage environment data analysis system according to claim 1, characterized in that, The calculation formula for the illumination adjustment control target in the intelligent early warning and linkage control module is as follows: ,in, for The target light intensity at any given time; For optimal light intensity; for Real-time degradation efficiency at any given moment.

10. A hazardous chemical storage environment data analysis system according to claim 1, characterized in that, The multi-parameter collaborative optimization objective function in the intelligent early warning and linkage control module is: The constraints are , , ,in, To comprehensively optimize the objectives; , , These are the weighting coefficients; This refers to the self-cleaning completion time. To optimize the maximum risk index within the cycle; Energy consumption for auxiliary equipment; for Real-time degradation efficiency at any given moment; for Relative humidity at any given time; for Light intensity at any given time.

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