Bus system adopting photoelectric technology for fire early warning and escape assistance

Abstract

The invention provides a bus system for fire early warning and escape assistance by adopting a photoelectric technology, and relates to the technical field of bus systems, the bus system comprises a photoelectric imaging module, the photoelectric imaging module enters an image sensor through a lens through an optical signal, and the optical signal enters the image sensor through photoelectric effect, filtering, amplification and analog-to-digital conversion processing; optical signals are decomposed into pixel points to record light intensity and color information during sampling, and the module can convert digital image data into optical signals through a modulator, transmit the optical signals at a speed close to light speed by utilizing the total reflection characteristic of optical fibers and restore the optical signals into electric signals through a photoelectric detector at a receiving end. Through the arrangement of efficient monitoring and data processing, operation states such as bus temperature, current and voltage can be accurately monitored in real time through photoelectric imaging data digitization and high-speed optical fiber transmission technologies, abnormal phenomena can be captured in time, efficient data transmission and processing are achieved, and the operation efficiency and the intelligent level of the system are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of busbar systems, and more specifically, particularly relates to a busbar system for fire warning and escape assistance using optoelectronic technology. Background Art

[0002] Traditional busbar systems have obvious deficiencies in power and information transmission, real-time monitoring, and emergency management. In particular, it is difficult to meet the high requirements of modern industry and smart grids in terms of digital data processing, transmission efficiency, and intelligent functions. Under the current technological development trend, the industrial and grid demands for the intelligence, high efficiency, and safety of busbar systems are increasing day by day, and there is an urgent need for an innovative technology to solve these problems. For example, in the face of complex environmental interference, data transmission in traditional systems is easily affected, and it is unable to timely and accurately warn of and respond to busbar faults, and also lacks effective escape assistance functions, making it difficult to ensure the safety of personnel and equipment in emergency situations. Summary of the Invention

[0003] To solve the above technical problems, the present invention provides a busbar system for fire warning and escape assistance using optoelectronic technology to solve the above problems.

[0004] A busbar system for fire warning and escape assistance using optoelectronic technology includes a busbar system, and the busbar system includes: an optoelectronic imaging module, which enters an image sensor through a light signal via a lens, and through photoelectric effect, filtering, amplification, and analog-to-digital conversion processing, realizes the acquisition and digitization of busbar operation data. Among them, sampling decomposes the light signal into pixel points to record the light intensity and color information, quantization converts the light intensity value into a discrete digital value, and encoding stores the data in a specific format.

[0005] Preferably, the busbar system further includes an optical fiber transmission module, which can convert the digitized image data into an optical signal through a modulator, utilize the total internal reflection characteristic of the optical fiber to transmit at a speed close to the speed of light, and restore it to an electrical signal through a photodetector at the receiving end, and restore the original digital image data through a decoder. It has the characteristics of high bandwidth supporting a transmission rate of 10 Gbps, low loss long-distance transmission, and anti-electromagnetic interference. The busbar system further includes an artificial intelligence analysis module, which uses a deep learning model to analyze optoelectronic imaging data and other sensor information, evaluates the operation state of the busbar in real time, generates a dynamic warning report and triggers an audible and visual alarm when an abnormality is detected, and can announce the fault type, location, and handling suggestions through voice broadcast, and visually display the abnormal area and related parameters on the user interface. The busbar system further includes an artificial intelligence escape assistance module, which automatically generates an optimal escape route based on the environmental data collected by the sensor, marks the escape direction through voice prompts and LED indicators, and can adjust the escape path in real time according to the dynamic changes of the environment.

[0006] Preferably, the busbar system further includes a 360-degree visualization module that collects data through the arrangement of multi-point optoelectronic sensors and generates a 360-degree real-time panoramic image through a stitching algorithm. It uses three-dimensional modeling technology to display the busbar spatial layout and operating parameters, supports free scaling and rotation viewing, and dynamically marks key states and highlights abnormal areas through heat maps. The busbar system also includes a human-computer interaction module for realizing remote management and real-time display of the operating state of the busbar system. The operating data collected by the optoelectronic imaging module includes information such as busbar temperature, current, and voltage to achieve comprehensive monitoring of the busbar operating state and capture abnormal phenomena, such as local overheating and arcing phenomena.

[0007] Preferably, the deep learning model is LSTM, which is used to accurately analyze optoelectronic imaging data and other sensor information, effectively evaluate the operating state of the busbar and give early warnings in a timely manner. The deep learning algorithm is the Dijkstra algorithm, which is used to quickly generate the optimal escape route to ensure the safe evacuation of personnel in case of emergency. The system adopts a modular design, supports long-term stable operation in complex environments such as salt spray, high humidity, and high heat, and is compatible with existing smart grid platforms, with functions of energy recovery and emergency power supply expansion.

[0008] Compared with the prior art, the present invention has the following beneficial effects:

[0009] In the present invention, through the provision of efficient monitoring and data processing: through optoelectronic imaging data digitization and high-speed optical fiber transmission technology, it is possible to accurately monitor the operating states such as busbar temperature, current, and voltage in real time, capture abnormal phenomena in a timely manner, realize efficient data transmission and processing, and improve the operating efficiency and intelligent level of the system.

[0010] In the present invention, through the provision of precise early warning and safety guarantee: using the artificial intelligence analysis module, based on the deep learning model to analyze the data, when abnormal conditions such as overload and temperature exceeding the standard occur, a dynamic early warning report is quickly generated and an audible and visual alarm is triggered. At the same time, voice broadcast and visual display are provided, so that users can know the fault situation in a timely manner and take measures.

[0011] In the present invention, through the provision of intelligent escape assistance: the artificial intelligence escape assistance module generates the optimal escape route based on environmental data and deep learning algorithms, and guides personnel to evacuate through voice and LED indicators, and can adjust the route in real time according to dynamic changes such as the spread of fire, greatly improving the escape probability of personnel in case of emergency.

[0012] In the present invention, through the provision of all-round visualization: the 360-degree visualization technology presents a panoramic image and detailed operating parameters of the busbar for users with the help of multi-point optoelectronic sensors and three-dimensional modeling technology, supports free viewing and heat map annotation, facilitating users to comprehensively understand the operating state of the busbar and discover abnormalities in a timely manner.

[0013] In the present invention, intelligent control and environmental adaptation are provided: the in-depth analysis module and the automatic control module can predict faults and optimize operating parameters based on historical and real-time data, improving energy efficiency and reducing risks. At the same time, the environmental adaptability and modular design of the system enable it to operate stably in complex environments, be compatible with existing platforms, have expansion functions, and adapt to various application scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 is the system topology diagram of the system composition modules of the present invention;

[0015] Figure 2 is the system topology diagram of the optoelectronic imaging module of the present invention;

[0016] Figure 3 is the system topology diagram of the optical fiber transmission module of the present invention;

[0017] Figure 4 is the system topology diagram of the artificial intelligence analysis module of the present invention;

[0018] Figure 5 is the system topology diagram of the artificial intelligence escape assistance module of the present invention;

[0019] Figure 6 is the system topology diagram of the 360-degree visualization module of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0020] The following further describes in detail the embodiments of the present invention in conjunction with the drawings and embodiments. The following embodiments are used to illustrate the present invention, but cannot be used to limit the scope of the present invention.

[0021] Please refer to Figures 1 - 6 , the present invention provides a bus system for fire warning and escape assistance using optoelectronic technology, including a bus system, and the bus system includes: an optoelectronic imaging module, which enters the image sensor through an optical signal through a lens, and through photoelectric effect, filtering, amplification, and analog-to-digital conversion processing, realizes the acquisition and digitization of bus operation data, where sampling decomposes the optical signal into pixel points to record the light intensity and color information, quantization converts the light intensity value into a discrete digital value, and encoding stores the data in a specific format.

[0022] The busbar system also includes an optical fiber transmission module, which can convert digital image data into optical signals through a modulator, transmit them at near the speed of light by utilizing the total internal reflection characteristic of optical fibers, and restore them to electrical signals at the receiving end through a photoelectric detector. After passing through a decoder, the original digital image data is restored. It has the characteristics of high bandwidth supporting a transmission rate of 10 Gbps, low-loss long-distance transmission, and anti-electromagnetic interference. The busbar system also includes an artificial intelligence analysis module, which uses a deep learning model to analyze electro-optical imaging data and other sensor information, evaluate the operating status of the busbar in real time, generate a dynamic warning report and trigger an audible and visual alarm when an abnormality is detected, and can announce the fault type, location, and handling suggestions through voice, and visually display the abnormal area and related parameters on the user interface. The busbar system also includes an artificial intelligence escape assistance module, which automatically generates the optimal escape route based on the environmental data collected by sensors, marks the escape direction through voice prompts and LED indicators, and can adjust the escape route in real time according to dynamic changes in the environment.

[0023] The busbar system also includes a 360-degree visualization module, which collects data through the arrangement of multi-point optoelectronic sensors and generates a 360-degree real-time panoramic image through a stitching algorithm. It uses three-dimensional modeling technology to display the spatial layout and operating parameters of the busbar, supports free scaling and rotation viewing, and dynamically marks key states and highlights abnormal areas through heat maps. The busbar system also includes a human-computer interaction module for realizing remote management and real-time display of the operating status of the busbar system. The operating data collected by the electro-optical imaging module includes information such as the temperature, current, and voltage of the busbar to achieve comprehensive monitoring of the operating status of the busbar and capture abnormal phenomena such as local overheating and arc phenomena.

[0024] The deep learning model is LSTM, which is used to accurately analyze electro-optical imaging data and other sensor information, effectively evaluate the operating status of the busbar and give early warnings in a timely manner. The deep learning algorithm is the Dijkstra algorithm, which is used to quickly generate the optimal escape route to ensure the safe evacuation of personnel in case of emergency. The system adopts a modular design, supports long-term stable operation in complex environments such as salt spray, high humidity, and high heat, and is compatible with existing smart grid platforms, with functions of energy recovery and emergency power supply expansion.

[0025] Example 1, Application in industrial workshops:

[0026] Install this intelligent optoelectronic technology bus system in a large machinery manufacturing plant. The optoelectronic imaging module is closely installed at key parts of the bus to accurately collect bus operation data, such as real-time monitoring of the large current load condition of the bus during the production peak period. The fiber optic transmission module stably and rapidly transmits the data to the central processor. The artificial intelligence analysis module, through learning and analyzing a large amount of historical data and real-time collected data, when the temperature of the primary bus abnormally rises close to the critical value, quickly issues an audible and visual alarm, and broadcasts through voice "The bus temperature is about to exceed the standard, please immediately check the cooling system", and at the same time, the abnormal temperature area, the corresponding bus position and temperature value are highlighted in red on the monitoring interface. The 360-degree visualization module provides the plant management personnel with a clear panoramic image of the bus and the display of operation parameters, facilitating them to view the overall state of the bus at any time. During a simulated fire drill, the artificial intelligence escape assistance module, based on the data of the smoke sensors and temperature sensors in the plant, quickly plans an escape route to avoid the fire hazard area, and through voice prompts "Please follow the voice instructions and the green LED indicators to evacuate to the safety exit", and at the same time, the green LED indicators light up in sequence on the escape route to guide the workers to evacuate safely.

[0027] Embodiment 2, Application in an intelligent power grid substation:

[0028] Deploy this bus system inside a substation of an urban intelligent power grid. The optoelectronic imaging module has high resolution and can clearly capture the subtle changes in the operation state of the bus, such as tiny arc phenomena. The fiber optic transmission module, relying on its anti-interference ability, ensures accurate data transmission in the complex electromagnetic environment of the substation, and the transmission rate meets the requirements of the substation for real-time monitoring of a large amount of data. The artificial intelligence analysis module combines the real-time data of the power grid operation and the surrounding environment information. When detecting the risk of bus overload caused by external weather changes, it generates a warning report in advance and shows the possibly affected areas and the estimated fault time to the operation and maintenance personnel through the visualization interface. When a sudden fault causes smoke to fill the station, the artificial intelligence escape assistance module is quickly activated, dynamically adjusts the escape route according to the environmental data, guides the operation and maintenance personnel to evacuate safely, and at the same time, the man-machine interaction module sends the fault information to the remote monitoring center in a timely manner so that the power grid dispatching personnel can take countermeasures in a timely manner.

[0029] Embodiment 3, Application in the power distribution room of high-rise buildings:

[0030] This system is applied in the power distribution room of high-rise buildings. The photoelectric imaging module has high sampling and quantization accuracy and can accurately monitor the voltage fluctuation of the busbar. The fiber optic transmission module realizes efficient data transmission within limited wiring space to ensure data integrity. The artificial intelligence analysis module is optimized for the electricity consumption characteristics of high-rise buildings. When abnormal changes in the busbar current are detected during the low electricity consumption period at night, it issues an early warning in a timely manner and prompts the operation and maintenance personnel to check relevant equipment through voice and visual interfaces. The 360-degree visualization module provides an intuitive display of the busbar layout and operating status for the operation and maintenance personnel through three-dimensional modeling technology, facilitating them to quickly locate problems during daily inspections and troubleshooting. When a fire occurs, the artificial intelligence escape assistance module plans a safe escape route for the people in the building according to the structure of the power distribution room and the development of the fire, and guides the evacuation of people through voice and LED indicator lights to ensure the safe evacuation of people to the safe area of the building.

[0031] Comparison of embodiments:

[0032] Environmental characteristics and key points of data collection:

[0033] Industrial factory buildings: The environment is complex, with a lot of electromagnetic interference and dust generated by a large number of mechanical equipment. The photoelectric imaging module pays more attention to the collection of parameters such as temperature and current of the busbar under complex working conditions, because the load changes frequently during the mechanical production process, which is likely to cause fluctuations in the busbar temperature and current.

[0034] Smart grid substations: The electromagnetic environment is extremely complex, but the requirements for data accuracy and stability are extremely high. The photoelectric imaging module needs to have high resolution to capture subtle abnormal phenomena, such as electric arcs, and data collection needs to be combined with the overall situation of the power grid operation, because busbar faults in substations may affect the power supply stability of the entire power grid.

[0035] Power distribution rooms in high-rise buildings: They are relatively enclosed and have limited space, with relatively high requirements for voltage stability. The photoelectric imaging module focuses on monitoring voltage fluctuations within limited space, and at the same time, it is necessary to consider the impact of the peak-valley characteristics of electricity consumption in high-rise buildings on the operation of the busbar.

[0036] Differences in early warning and escape requirements:

[0037] Industrial factory buildings: The personnel are dense and the production activities are diverse. The early warning needs to clarify the fault type and treatment suggestions. The escape assistance needs to consider the equipment layout and passage conditions in the factory building to ensure that clear escape guidance is provided for a large number of people in case of emergencies such as fires, and to prevent people from straying into dangerous areas due to panic.

[0038] Smart grid substation: The operation and maintenance personnel are relatively professional, but the scope of fault impact is wide. The early warning should provide detailed fault analysis and possible impact scope. The escape assistance needs to cooperate closely with the power grid dispatching. While ensuring the safe evacuation of the operation and maintenance personnel, it should minimize the impact on the power grid operation and ensure the continuity of power supply.

[0039] High-rise building power distribution room: It mainly ensures the power consumption safety of the building occupants. The early warning should promptly notify the operation and maintenance personnel and the building residents. The escape assistance should be combined with the building structure and evacuation route design to ensure accurate escape routes for people on different floors in case of fire and avoid crowding and trampling accidents caused by panic.

[0040] System function focus:

[0041] Industrial factory building: It focuses on stable operation in a complex production environment and reliable guarantee for the power consumption of a large number of devices. The modular design of the system facilitates flexible expansion during factory building expansion or equipment update to adapt to the changing production requirements.

[0042] Smart grid substation: The key lies in ensuring the safe and stable operation of the power grid. It has extremely high requirements for the anti-interference ability of the system, the accuracy of data transmission, and the timeliness of early warning. At the same time, it should be seamlessly connected with the overall intelligent management system of the power grid to achieve remote precise monitoring and efficient management of the busbars.

[0043] High-rise building power distribution room: It emphasizes the continuous and stable power supply to the building and the quick response in case of emergency. The 360-degree visualization module plays an important auxiliary role in the daily inspection and fault troubleshooting of the operation and maintenance personnel, helping them quickly locate and solve problems and ensuring the power consumption safety of the building.

[0044] From the comparison of the above embodiments, it can be seen that the intelligent optoelectronic technology busbar system can give full play to its various functional advantages according to the environmental and demand characteristics in different application scenarios, providing effective solutions for the busbar operation management and safety guarantee in different places.

[0045] The embodiments of the present invention are given for purposes of illustration and description, and are not exhaustive or limit the present invention to the disclosed form. Many modifications and variations are obvious to those of ordinary skill in the art. The embodiments are selected and described to better illustrate the principles and practical applications of the present invention, and enable those of ordinary skill in the art to understand the present invention and design various embodiments with various modifications suitable for specific purposes.

Claims

1. A busbar system for fire warning and escape assistance using optoelectronic technology, including a busbar system, characterized in that: The busbar system includes: an optoelectronic imaging module, which enters the image sensor through an optical signal via a lens, and through photoelectric effect, filtering, amplification, and analog-to-digital conversion processing, realizes the acquisition and digitization of busbar operation data. Among them, sampling decomposes the optical signal into pixel points to record the light intensity and color information, quantization converts the light intensity value into discrete digital values, and encoding stores the data in a specific format.

2. The busbar system for fire warning and escape assistance using optoelectronic technology as described in claim 1, wherein The busbar system further includes an optical fiber transmission module, which can convert the digitized image data into an optical signal through a modulator, utilize the total internal reflection characteristic of the optical fiber to transmit at a speed close to the speed of light, and restore it to an electrical signal through a photodetector at the receiving end, and restore the original digital image data through a decoder. It has the characteristics of high bandwidth supporting a transmission rate of 10 Gbps, low loss long-distance transmission, and anti-electromagnetic interference.

3. The busbar system for fire warning and escape assistance using optoelectronic technology according to claim 1, characterized in that, The busbar system further includes an artificial intelligence analysis module, which uses a deep learning model to analyze the optoelectronic imaging data and other sensor information, evaluates the busbar operation state in real time, generates a dynamic warning report and triggers an audible and visual alarm when an abnormality is detected, and can announce the fault type, location, and handling suggestions through voice broadcast, and visually display the abnormal area and related parameters on the user interface.

4. The busbar system for fire warning and escape assistance using optoelectronic technology as claimed in claim 1, wherein The busbar system further includes an artificial intelligence escape assistance module, which automatically generates the optimal escape route based on the environmental data collected by the sensors, marks the escape direction through voice prompts and LED indicators, and can adjust the escape route in real time according to the dynamic changes of the environment.

5. The bus system for fire warning and escape assistance using optoelectronic technology according to claim 1, wherein, The busbar system further includes a 360-degree visualization module, which collects data through the arrangement of multi-point optoelectronic sensors and generates a 360-degree real-time panoramic image through a stitching algorithm. It uses three-dimensional modeling technology to display the busbar spatial layout and operation parameters, supports free scaling and rotation viewing, and dynamically marks the key states and highlights the abnormal areas through a heat map.

6. The busbar system for fire warning and escape assistance using optoelectronic technology as described in claim 1, wherein, The busbar system further includes a human-computer interaction module, which is used to realize the remote management and real-time display of the busbar system operation state.

7. The busbar system for fire warning and escape assistance using optoelectronic technology as described in claim 1, wherein The operation data collected by the optoelectronic imaging module includes information such as busbar temperature, current, and voltage, so as to realize the comprehensive monitoring of the busbar operation state and capture abnormal phenomena, such as local overheating and arc phenomena.

8. The bus system for fire warning and escape assistance using optoelectronic technology according to claim 3, characterized in that, The deep learning model is LSTM, which is used to accurately analyze the optoelectronic imaging data and other sensor information, effectively evaluate the busbar operation state and give early warnings in time.

9. The busbar system for fire warning and escape assistance using optoelectronic technology according to claim 4, wherein The deep learning algorithm is the Dijkstra algorithm, which is used to quickly generate the optimal escape route to ensure the safe evacuation of personnel in case of emergency.

10. The busbar system for fire warning and escape assistance using optoelectronic technology according to claim 1, characterized in that, The system adopts a modular design, supports long-term stable operation in complex environments such as salt spray, high humidity, and high temperature, is compatible with the existing smart grid platform, and has the functions of energy recovery and emergency power supply expansion.

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