High-risk chemical real-time simulation monitoring method based on virtual reality technology

Abstract

The invention provides a high-risk chemical real-time simulation monitoring method based on a virtual reality technology. According to the method, data interaction is carried out among a warehouse environment database, a virtual warehouse monitoring module, a simulation early warning unit and a simulation chemical management module; the warehouse environment database carries out data interaction with the virtual warehouse monitoring module, the simulation early warning unit and the simulation chemical management module through wireless transmission, the warehouse environment database obtains data through interaction with the above modules, and after the collected data is sorted, the collected data is concentrated to the simulation early warning unit; the virtual warehouse monitoring module is used for constructing a warehouse storage model, setting environment data acquisition points in the model, performing fixed-time and fixed-point data acquisition on the acquisition points preset in a warehouse through a real-time environment data acquisition unit, sending the acquired data to a management unit, recording the acquired data through the management unit, and storing the recorded data in the warehouse; and carrying out parameter correction on the model in the warehouse storage model according to the recorded data.

Description

Technical Field

[0001] This invention belongs to the field of simulation monitoring, and specifically relates to a real-time simulation monitoring method for high-risk chemical products based on virtual reality technology. Background Technology

[0002] Virtual reality (VR) technology is a computer simulation system that creates and allows users to experience virtual worlds. It uses computers to generate a simulated environment that surrounds the user's senses, making them feel as if they are actually in that environment. In recent years, with the rapid development of computer technology, sensor technology, and image processing technology, virtual reality technology has been widely applied in various fields, including education, healthcare, entertainment, and the military.

[0003] In the chemical industry, the production, storage, and transportation of hazardous chemicals are extremely dangerous due to their flammable, explosive, and toxic properties; accidents involving these chemicals can have very serious consequences. Therefore, real-time monitoring of hazardous chemicals is crucial. However, traditional monitoring methods often fail to meet the demands for real-time, comprehensive, and accurate monitoring, and manual monitoring poses significant safety risks in high-risk environments.

[0004] A real-time simulation monitoring method for high-risk chemicals based on virtual reality technology can effectively solve these problems. First, virtual reality technology can construct a virtual environment highly similar to the actual production environment. By simulating the actual production process in this virtual environment, real-time monitoring of the production process can be achieved. Second, by combining various sensor data with the virtual environment, real-time monitoring of various parameters in the production process, including temperature, pressure, and flow rate, can be achieved, thus realizing comprehensive monitoring of the production process. Furthermore, virtual reality technology enables remote monitoring of the production process, significantly reducing the safety risks to personnel in high-risk environments.

[0005] However, real-time simulation monitoring methods for high-risk chemicals based on virtual reality technology also face some challenges. First, constructing the virtual environment requires substantial data support, necessitating in-depth research and analysis of the actual production environment. Second, synchronizing the virtual and real-world environments is a technical challenge, requiring efficient data processing and transmission technologies. Furthermore, the realism and interactivity of the virtual environment are issues that require further investigation.

[0006] In summary, the real-time simulation monitoring method for high-risk chemicals based on virtual reality technology is a novel monitoring approach with great application potential. However, further research and development are needed to address various challenges in its practical application. Summary of the Invention

[0007] This invention proposes a real-time simulation monitoring method for high-risk chemicals based on virtual reality technology, solving the problem of real-time monitoring and management of high-risk chemical warehouses. Through virtual reality technology, it enables real-time data acquisition of the warehouse environment, ring-shaped image data acquisition of early warning points, allocation and management of hazardous chemicals within the warehouse area, and the establishment of emergency management procedures. This achieves real-time, comprehensive, and accurate monitoring of high-risk chemical warehouses, improving the efficiency and safety of warehouse management.

[0008] The technical solution of this invention is implemented as follows: a real-time simulation monitoring method for high-risk chemicals based on virtual reality technology, including data interaction between a warehouse environment database, a virtual warehouse monitoring module, a simulation early warning unit, and a simulation chemical management module;

[0009] The warehouse environment database interacts with the virtual warehouse monitoring module, the simulation early warning unit, and the simulation chemical management module via wireless transmission. The warehouse environment database acquires data by interacting with the above modules, organizes the collected data, and then centralizes the collected data to the simulation early warning unit.

[0010] The virtual warehouse monitoring module: constructs a warehouse storage model and sets environmental data collection points within the model. The real-time environmental data collection unit collects data from the pre-set collection points in the warehouse at fixed times and locations, and sends the collected data to the management unit. The management unit records the collected data and uses the recorded data to correct the parameters of the warehouse storage model.

[0011] The simulated early warning unit establishes early warning points in the warehouse storage model, performs ring-shaped image data acquisition on the early warning points, customizes the image acquisition focus position, obtains the current focal length and focus position information, and adjusts the focus and focal length in real time through the standard focus and focal length parameters recorded in the warehouse environment database.

[0012] The simulated chemical management module manages warehouse area allocation within the warehouse storage model. It distinguishes hazardous chemicals by their properties according to the type of hazardous chemicals stored and classifies warehouse areas based on their chemical properties. Chemicals with matching chemical characteristics are allocated to adjacent warehouse areas. The module also sends environmental management parameter data corresponding to the hazardous chemical to the simulated early warning unit and virtual warehouse monitoring module of that warehouse area. Furthermore, it establishes an emergency management process sheet based on the warehouse area allocation. When the monitoring data of the virtual warehouse monitoring module or the simulated early warning unit exceeds the threshold, it sends a warning signal to the simulated warehouse monitoring module.

[0013] This application document presents a real-time simulation monitoring method for high-risk chemicals based on virtual reality technology. Compared with existing technologies, the main difference of this method lies in its deep integration of virtual reality technology with traditional monitoring methods. It creates a virtual simulation space that reflects the real warehouse environment in real time and achieves efficient data interaction between various modules through wireless transmission technology. Its main advantages are as follows: Real-time data monitoring and visualization: The warehouse storage model constructed through the virtual warehouse monitoring module enables real-time acquisition and visualization of environmental data, allowing managers to intuitively monitor the real-time status of the storage environment. Remote monitoring capability: Due to the use of wireless transmission technology, remote monitoring is possible, reducing the risk of personnel directly contacting the high-risk environment and improving safety. Intelligent early warning system: The simulated early warning unit can monitor the set early warning points in real time and make real-time adjustments and issue early warnings when anomalies are detected, effectively preventing accidents. Refined management: The simulated chemical management module realizes warehouse area allocation management based on chemical properties, ensuring that chemicals of different properties receive appropriate storage conditions and reducing potential chemical reaction risks. Emergency Response Procedures: When data exceeds a threshold, the system immediately initiates emergency management procedures, allowing for proactive emergency preparedness and shortening response time. Data Integration and Analysis: The integration of the warehouse environment database enables unified management and analysis of all collected data, providing data support for decision-making and laying the data foundation for future risk prediction and accident prevention.

[0014] In summary, this technology is more intelligent and automated than traditional monitoring methods, and can provide a more efficient and secure monitoring and management solution, especially suitable for the storage and monitoring of high-risk chemicals.

[0015] In a preferred embodiment, the management unit establishes an environmental parameter analysis template based on the environmental data collected by the real-time environmental data acquisition unit. By using historical environmental parameter data pre-set in the management unit, an environmental parameter curve is formed based on the collected environmental parameters. The time change rate data is stored based on the parameter curve or the time change rate data and compared with the actual change data to obtain the comparison error value.

[0016] As a preferred implementation, after setting the comparison error value, when the error value between the collected real-time data and the time change rate data in the template exceeds the set threshold, an alarm signal is sent to the simulation early warning unit and the warehouse environment database, and the data collection frequency is increased.

[0017] As a preferred implementation, users can access the simulated warehouse monitoring module by logging into the client, where the data is visualized and displayed on the user login interface.

[0018] In a preferred embodiment, the simulated early warning unit acquires images using a simulated circumferential fisheye camera. After image acquisition, the acquired images are denoised using Gaussian filtering to smooth the images, reduce noise interference, and enhance image contrast through histogram equalization.

[0019] The beneficial effects of this invention, achieved by adopting the above technical solution, are as follows: Through real-time monitoring and intelligent early warning systems, potential hazards can be detected and responded to promptly, reducing the probability of accidents and protecting the safety of personnel and facilities. The system boasts a high degree of automation, reducing reliance on manual operation and mitigating the risk of human error. Intelligent warehouse allocation management ensures that chemicals are stored correctly according to their properties, improving space utilization and storage efficiency. In the event of abnormal situations, the system can quickly activate emergency procedures, shortening accident response time and reducing potential damage. Managers can remotely monitor the warehouse without being physically present, thereby reducing the time workers are exposed to high-risk environments. This monitoring method can significantly improve the safety management level of high-risk chemical warehouses, reduce risks for enterprises, improve production and storage efficiency, and aligns with the trend of modern chemical industries towards intelligent and digital transformation. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a flowchart of the system of the present invention. Detailed Implementation

[0022] 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.

[0023] Example:

[0024] like Figure 1 As shown, a real-time simulation monitoring method for high-risk chemicals based on virtual reality technology includes data interaction between a warehouse environment database, a virtual warehouse monitoring module, a simulation early warning unit, and a simulation chemical management module.

[0025] The warehouse environment database interacts with the virtual warehouse monitoring module, the simulation early warning unit, and the simulation chemical management module via wireless transmission. The warehouse environment database acquires data by interacting with the above modules, organizes the collected data, and then centralizes the collected data to the simulation early warning unit.

[0026] The virtual warehouse monitoring module: constructs a warehouse storage model and sets environmental data collection points within the model. The real-time environmental data collection unit collects data from the pre-set collection points in the warehouse at fixed times and locations, and sends the collected data to the management unit. The management unit records the collected data and uses the recorded data to correct the parameters of the warehouse storage model.

[0027] The simulated early warning unit establishes early warning points in the warehouse storage model, performs ring-shaped image data acquisition on the early warning points, customizes the image acquisition focus position, obtains the current focal length and focus position information, and adjusts the focus and focal length in real time through the standard focus and focal length parameters recorded in the warehouse environment database.

[0028] The simulated chemical management module manages warehouse area allocation within the warehouse storage model. It distinguishes hazardous chemicals by their properties according to the type of hazardous chemicals stored and classifies warehouse areas based on their chemical properties. Chemicals with matching chemical characteristics are allocated to adjacent warehouse areas. The module also sends environmental management parameter data corresponding to the hazardous chemical to the simulated early warning unit and virtual warehouse monitoring module of that warehouse area. Furthermore, it establishes an emergency management process sheet based on the warehouse area allocation. When the monitoring data of the virtual warehouse monitoring module or the simulated early warning unit exceeds the threshold, it sends a warning signal to the simulated warehouse monitoring module.

[0029] A real-time simulation monitoring method for high-risk chemicals based on virtual reality technology is an integrated monitoring system. It creates a highly realistic simulation environment of a chemical warehouse using virtual reality, reflecting and managing the real warehouse's status in real time within this environment. The system consists of four main parts: a warehouse environment database, a virtual warehouse monitoring module, a simulation early warning unit, and a simulated chemical management module. These modules exchange data wirelessly, forming a closed-loop monitoring and management network.

[0030] Warehouse Environment Database: This is the system's data center, responsible for collecting, organizing, and storing data from other modules. It interacts with other modules wirelessly, receiving environmental data collected from various monitoring points and sending the organized data to the simulation early warning unit.

[0031] Virtual Warehouse Monitoring Module: This module constructs a virtual warehouse storage model with multiple environmental data collection points. These points are monitored by a real-time environmental data acquisition unit, which periodically collects data such as warehouse temperature, humidity, and harmful gas concentrations. The collected data is sent to the management unit for recording and is used to update and correct the parameters of the virtual warehouse model, ensuring that the model always reflects the state of the real environment.

[0032] Simulated Early Warning Unit: In the virtual warehouse model, the simulated early warning unit sets up warning points and collects image data from these points. By customizing the position of the image acquisition focus, the system can obtain the current focal length and focus position information. Simultaneously, it utilizes standard focus and focal length parameters from the warehouse environment database to adjust the focus and focal length in real time to ensure the accuracy of the monitored images.

[0033] Simulated Chemical Management Module: This module is responsible for the allocation and management of storage areas within the virtual warehouse model. It classifies hazardous chemicals based on their storage type and chemical properties, assigning chemicals with similar chemical characteristics to adjacent storage areas. Simultaneously, it sends environmental management parameter data to the simulated early warning unit and virtual warehouse monitoring module of the corresponding storage area to ensure that the storage environment in these areas is suitable for the stored chemicals. Furthermore, the module establishes an emergency management process flow sheet to guide emergency response when monitoring data exceeds safety thresholds.

[0034] When the data detected by the virtual warehouse monitoring module or the simulation early warning unit exceeds the set safety threshold, the system will immediately send an alarm signal to the simulation warehouse monitoring module and activate the pre-set emergency response procedure to mitigate or avoid dangers and losses.

[0035] In summary, this monitoring method not only provides real-time monitoring of the environment in high-risk chemical warehouses, but also enables intelligent early warning and emergency management, greatly improving the safety performance and management efficiency of chemical warehouses.

[0036] In a preferred embodiment, the management unit establishes an environmental parameter analysis template based on environmental data collected by the real-time environmental data acquisition unit. Using historical environmental parameter data pre-set in the management unit, it generates an environmental parameter curve based on the collected environmental parameters. Based on the parameter curve or time-varying rate data, the time-varying rate data is stored and compared with the actual change data to obtain a comparison error value. First, the management unit establishes an environmental parameter analysis template based on the collected environmental data. Then, it generates an environmental parameter curve using historical environmental parameter data pre-set in the management unit. This curve reflects the trend of environmental parameters changing over time. Next, the management unit calculates the time-varying rate of environmental parameters and stores this data. Finally, the management unit compares the calculated time-varying rate data with the actual change data to obtain a comparison error value. This error value can be used to evaluate the accuracy of environmental parameter prediction and the system performance.

[0037] Compared to existing technologies, the main differences and advantages of this method are: Real-time performance: Through the real-time environmental data acquisition unit, the management unit can acquire real-time environmental parameter data, thereby achieving real-time monitoring of the environmental status. Predictive capability: By establishing environmental parameter analysis templates and environmental parameter curves, the management unit can predict future trends in environmental parameters, thus enabling proactive countermeasures. Self-correction: By comparing the time change rate data with actual change data, the management unit can obtain the comparison error value, thereby self-correcting the system and improving the accuracy of predictions. Data backup: The management unit will back up the time change rate data, which can be used not only for error analysis but also to provide valuable historical data for future data analysis.

[0038] In summary, this method achieves real-time, accurate, and automated monitoring of the environment in high-risk chemical warehouses through real-time data acquisition, data analysis and prediction, self-correction, and data backup, greatly improving the efficiency and safety of warehouse management.

[0039] As a preferred implementation, after setting the comparison error value, when the error value between the collected real-time data and the time change rate data in the template exceeds the set threshold, an alarm signal is sent to the simulation early warning unit and the warehouse environment database, and the data collection frequency is increased. The main advantage of this mechanism is its real-time performance and sensitivity. Once abnormal changes occur in environmental parameters, the system can immediately issue an alarm and strengthen monitoring, thereby detecting and handling problems as early as possible and preventing accidents from occurring.

[0040] Compared to existing technologies, the main differences and advantages of this method are: Real-time early warning: Traditional monitoring systems typically only issue warnings when abnormal signals are received, while this method, by comparing real-time data with preset templates, can issue warnings before problems occur, improving the timeliness of warnings. Dynamic adjustment: After a warning signal is issued, the system automatically increases the data acquisition frequency, allowing managers to monitor environmental changes more closely, something many traditional systems cannot do. Data-driven: This method is data-based, using data analysis and comparison to drive warnings and responses, making warnings more accurate and responses more timely. Self-learning: The system can continuously adjust and optimize preset templates based on real-time and historical data, enabling the warning mechanism to continuously improve and optimize over time. Through real-time data acquisition, data analysis and early warning, dynamic adjustment, and self-learning, this method achieves real-time, accurate, and automated monitoring of the high-risk chemical warehouse environment, significantly improving the efficiency and safety of warehouse management.

[0041] Users access the simulated warehouse monitoring module by logging into the client. This module visualizes the data and displays it on the user login screen. After logging in, users can access the simulated warehouse monitoring module, which presents real-time monitored data in graphical and chart formats, allowing users to intuitively understand the warehouse's real-time environmental conditions and development trends. Simultaneously, the data display is also integrated into the user login screen, enabling users to quickly view the most critical information.

[0042] Compared to existing technologies, the main differences and advantages of this method include: User-friendly interface: Through the interactive interface provided by the client software, users can intuitively view data. Compared to the more complex and difficult-to-understand raw data or log files, the visual presentation is easier for users to understand and analyze. Instant access and response: Users can access monitoring data in real time, meaning that they can respond quickly and take necessary measures when any signs indicate a potential problem. Remote monitoring: Users do not need to be physically present to view warehouse monitoring data by logging into the client, which greatly improves the convenience and efficiency of monitoring. Integrated information display: Integrating monitoring data into the user login interface means that the system has a dashboard function that can centrally display the most important monitoring data and alarm information, improving the speed and accuracy of information acquisition. Personalization: The client allows users to customize the data display according to their needs, such as selecting different charts or alarm settings, thus providing a more personalized service.

[0043] Data sharing and collaboration: Data viewed by users through the client can be shared with other users or team members, which facilitates team collaboration and decision-making. Compared to traditional monitoring technologies, this client-based data visualization approach places greater emphasis on user experience and interaction design, enabling even non-professionals to easily monitor and understand the warehouse environment, thereby improving the overall usability and practicality of the monitoring system.

[0044] The simulated early warning unit acquires images using a simulated circumferential fisheye camera. After acquisition, the images are denoised using Gaussian filtering to smooth the images and reduce noise interference. Histogram equalization is then used to enhance image contrast. The simulated circumferential fisheye camera is a special type of camera with an extremely wide field of view, capable of capturing a wider field of view than traditional cameras, and is often used to achieve 360-degree panoramic shooting. After acquiring the images, the simulated early warning unit performs post-processing to improve their quality and usability.

[0045] Image processing steps include: Denoising: Using a Gaussian filter to denoise the image. Gaussian filtering is a commonly used image smoothing technique that can effectively reduce random noise in an image without excessively blurring image edges. Image Smoothing: In addition to denoising, filtering operations can also smooth the image and reduce noise interference. This is very important for extracting image features and improving visual effects. Histogram Equalization: Histogram equalization enhances image contrast, making details in the image clearer, especially in areas where image brightness changes little.

[0046] Compared with existing technologies, the main differences and advantages of this image processing method for simulated early warning units include: Panoramic monitoring: The panoramic view provided by the circumferential fisheye camera enables the early warning unit to monitor a wider area, reducing blind spots and improving the comprehensiveness of monitoring. Image quality enhancement: Gaussian filtering and histogram equalization improve image quality, making important information in the image more obvious and easier to identify. Automated processing: Automated image processing steps ensure that monitoring images can be processed and analyzed quickly and continuously, improving the system's response speed and accuracy. Strong adaptability: The above image processing method can adapt to image acquisition under various environmental conditions, such as low-light environments or environments with high image noise, while still maintaining image quality.

[0047] In summary, this analog early warning unit's image acquisition and processing method provides a wider field of view and higher quality images compared to traditional monitoring technologies, which helps improve the efficiency and reliability of the monitoring system.

[0048] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A real-time simulation monitoring method for high-risk chemical products based on virtual reality technology, characterized in that, This includes data interaction between the warehouse environment database, virtual warehouse monitoring module, simulation early warning unit, and simulation chemical management module; The warehouse environment database interacts with the virtual warehouse monitoring module, the simulation early warning unit, and the simulation chemical management module via wireless transmission. The warehouse environment database acquires data by interacting with the above modules, organizes the collected data, and then centralizes the collected data to the simulation early warning unit. The virtual warehouse monitoring module: constructs a warehouse storage model and sets environmental data collection points within the model. The real-time environmental data collection unit collects data from the pre-set collection points in the warehouse at fixed times and locations, and sends the collected data to the management unit. The management unit records the collected data and uses the recorded data to correct the parameters of the warehouse storage model. The simulated early warning unit establishes early warning points in the warehouse storage model, performs ring-shaped image data acquisition on the early warning points, customizes the image acquisition focus position, obtains the current focal length and focus position information, and adjusts the focus and focal length in real time through the standard focus and focal length parameters recorded in the warehouse environment database. The simulated chemical management module manages warehouse area allocation within the warehouse storage model. It distinguishes hazardous chemicals by their properties according to the type of hazardous chemicals stored and classifies warehouse areas based on their chemical properties. Chemicals with matching chemical characteristics are allocated to adjacent warehouse areas. The module also sends environmental management parameter data corresponding to the hazardous chemical to the simulated early warning unit and virtual warehouse monitoring module of that warehouse area. Furthermore, it establishes an emergency management process sheet based on the warehouse area allocation. When the monitoring data of the virtual warehouse monitoring module or the simulated early warning unit exceeds the threshold, it sends a warning signal to the simulated warehouse monitoring module.

2. The real-time simulation monitoring method for high-risk chemical products based on virtual reality technology as described in claim 1, characterized in that: The management unit establishes an environmental parameter analysis template based on the environmental data collected by the real-time environmental data acquisition unit. By using historical environmental parameter data pre-set in the management unit, it generates an environmental parameter curve based on the collected environmental parameters. Based on the parameter curve or the time change rate data, the time change rate data is stored and compared with the actual change data to obtain the comparison error value.

3. The real-time simulation monitoring method for high-risk chemical products based on virtual reality technology as described in claim 2, characterized in that: After setting the comparison error value, when the error value between the collected real-time data and the time change rate data in the template exceeds the set threshold, an alarm signal is sent to the simulation early warning unit and the warehouse environment database, and the data collection frequency is increased.

4. The real-time simulation monitoring method for high-risk chemical products based on virtual reality technology as described in claim 1, characterized in that: Users access the simulated warehouse monitoring module by logging into the client. The data is then visualized within the simulated warehouse monitoring module and displayed on the user login interface.

5. The real-time simulation monitoring method for high-risk chemical products based on virtual reality technology as described in claim 1, characterized in that: The simulated early warning unit acquires images using a simulated circumferential fisheye camera. After image acquisition, the acquired images are denoised using Gaussian filtering to smooth the images, reduce noise interference, and enhance image contrast through histogram equalization.

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