An air respirator smart switching module, mask system

Abstract

The application discloses an air respirator intelligent switching module, comprising a switching head main body, wherein a breathing machine switching interface is arranged on the switching head main body, and a filter canister interface and an oxygen interface are arranged on both sides of the switching head main body, and the application further comprises an air respirator intelligent mask system, comprising a mask body installed at the breathing machine switching interface, wherein a sensor module, an anti-noise communication module and an augmented reality display module are installed on the mask body. The breathing machine mask provided with double gas paths can not only perform rescue work in a complex environment through integration of multiple sensors, but also can monitor the state of a rescuer in real time and command the rescue work, so that the rescue efficiency is further improved, the life safety of the rescuer is further ensured, and the danger of fire rescue is further reduced.

Description

Technical Field

[0001] This utility model relates to the field of fire rescue technology, and in particular to an intelligent adapter module for an air respirator and a mask system. Background Technology

[0002] Fire scenes are complex environments with a variety of gases in the air. Wearing oxygen masks is one of the most important measures to protect firefighters, especially in oxygen-deficient environments. It can prevent the risk of suffocation and ensure that firefighters can enter the fire scene to complete rescue missions. It is an indispensable core piece of equipment for fire rescue.

[0003] Traditional fire-fighting breathing apparatus masks have limited functionality and lack intelligent monitoring and multi-scenario adaptability. Firefighters face risks such as oxygen deficiency, high temperatures, poisoning, and physical exhaustion in fire scenes. Furthermore, the interfaces of breathing apparatus and filter canisters are not interchangeable, requiring firefighters to carry only one before entering the fire scene and switch back and forth. To address these issues, we have proposed an intelligent air breathing apparatus adapter module and mask system. Utility Model Content

[0004] This application provides an intelligent adapter module for an air respirator and a mask system, which solves the problem that breathing masks are not adaptable to complex environments during fire rescue and cannot be used to guide firefighters.

[0005] This application provides an intelligent adapter module for an air respirator, including an adapter body. The adapter body is provided with a respirator adapter interface. A filter canister interface and an oxygen interface are distributed on both sides of the adapter body. A one-way valve is installed in the filter canister interface. A filter canister interface cover is installed on the filter canister interface by a first fixing screw. A quick-release cover is installed on the oxygen interface by a second fixing screw.

[0006] Preferably, a first sealing ring is provided between the one-way valve and the inner wall of the filter canister interface.

[0007] Preferably, a second sealing ring is provided at the connection between the ventilator adapter and the mask.

[0008] An intelligent face mask system for an air respirator includes a face mask body installed on an intelligent adapter module of the air respirator, and the face mask body is equipped with a sensor module, an anti-noise communication module, and an augmented reality display module.

[0009] Preferably, the thin-film temperature sensor, MEMS gas sensor, and triaxial accelerometer / gyroscope, the multi-parameter life monitoring module, the non-contact photoelectric sensor, the thin-film temperature sensor, the MEMS gas sensor, and the triaxial accelerometer / gyroscope are all integrated on the mask body.

[0010] Preferably, the noise-resistant communication module includes a bone conduction microphone and a directional speaker.

[0011] Preferably, the augmented reality display module includes a micro OLED transparent display screen and a laser projection unit.

[0012] Preferably, it also includes a cloud-based decision-making module, which includes a fire scene 3D modeling module, a reinforcement learning decision-making module, and a risk prediction module.

[0013] Preferably, it also includes a multi-level alarm protocol, which includes setting a second-level warning.

[0014] A method for using an air respirator smart mask includes the following steps:

[0015] Dynamic thermodynamic diffusion simulation is generated by combining BIM building information model with thermal imaging data;

[0016] Optimize fire suppression path planning using Q-learning algorithm;

[0017] LSTM neural network analysis of physiological data temporal characteristics can provide early warning of hypoxia / poisoning risk.

[0018] Firefighters entered the fire scene wearing intelligent self-contained breathing apparatus and face shield systems.

[0019] The photoelectric sensor monitors heart rate at a sampling rate of 100Hz, the MEMS gas sensor detects CO concentration, and the HUD projects the movement route while simultaneously providing voice announcements.

[0020] When a heart rate >160 bpm or CO concentration rises to 80 ppm for 5 consecutive minutes is detected, the HUD projects an evacuation route to instruct firefighters to evacuate.

[0021] As can be seen from the above technical solutions, this application provides an intelligent transfer module for an air respirator and a mask system. The breathing mask of this application adopts a multi-mode air supply system of an air respirator and a filter canister to ensure the breathing safety of firefighters. The main air circuit is connected to a compressed air cylinder, and the backup air circuit is connected to a filter canister. The air supply mode can be automatically or manually switched according to the oxygen concentration and toxic gas detection of the sensor. The filter canister is installed in a detachable mode and can be replaced according to different rescue scenarios. Before entering the fire scene for rescue, a fire scene model is generated based on the BIM building information model and thermal imaging data. Then, the rescue route is planned, and the rescue route and data such as ambient temperature, toxic gas content, remaining oxygen cylinder volume, and the firefighter's blood oxygen concentration and heart rate are displayed on the respirator mask using a miniature OLED transparent display screen and laser projection unit. The above data is transmitted to the command center in real time. When abnormal personnel are encountered during the rescue, they can be marked and a request for coordinated rescue can be made. When a firefighter's physical signs are abnormal, the firefighter can be quickly notified to return and a return route can be planned.

[0022] Compared with the prior art, the beneficial effects of this utility model are:

[0023] 1. This application adopts a dual-gas-path design, with the main gas path connected to a compressed air cylinder and the backup gas path connected to a filter canister (for filtering toxic gases such as CO and H2S). It features a built-in intelligent switching valve that automatically switches the gas supply mode based on environmental sensors (oxygen concentration, toxic gas detection), or supports manual rapid switching. The filter canister adopts a modular design for quick replacement, adapting to different toxic gas scenarios.

[0024] 2. Through a multi-parameter life monitoring module, non-contact photoelectric sensors, thin-film temperature sensors, MEMS gas sensors, and triaxial accelerometers / gyroscopes, the system can monitor firefighters' vital signs and location in real time. In case of abnormalities, it can promptly notify firefighters to take evasive action and assist them in planning rescue or evacuation routes, further improving the safety of fire rescue operations.

[0025] 3. This application enables data communication and linkage with the command center. Firefighters' personal relay devices are connected to upload vital signs, location, and gas cylinder status to the command platform. The command platform monitors the status of all personnel in real time and can quickly dispatch support upon detecting abnormalities.

[0026] In summary, this application, through a ventilator mask with a dual-airflow configuration and the integration of multiple sensors, not only enables rescue operations in complex environments but also allows for real-time monitoring of rescue personnel's status and command of their rescue efforts. This not only further improves rescue efficiency but also enhances the safety of rescue personnel and reduces the inherent dangers of fire rescue operations. Attached Figure Description

[0027] To more clearly illustrate the technical solution of this application, the accompanying drawings used in the implementation examples will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained from these drawings without any creative effort.

[0028] Figure 1 An exploded view of an intelligent adapter module for an air respirator proposed in this utility model;

[0029] Figure 2 This is a first side view of an intelligent adapter module for an air respirator proposed in this utility model;

[0030] Figure 3 This is a second side view of an intelligent adapter module for an air respirator proposed in this utility model;

[0031] Figure 4 This is a schematic diagram of the internal structure of an intelligent adapter module for an air respirator proposed in this utility model;

[0032] Figure 5 This is a schematic diagram of the external structure of an intelligent adapter module for an air respirator proposed in this utility model.

[0033] In the diagram: 1. Adapter body, 2. First fixing screw, 3. Filter canister interface cover, 4. First sealing ring, 5. One-way valve, 6. Quick release cover, 7. Second sealing ring, 8. Second fixing screw, 9. Ventilator adapter, 10. Filter canister interface, 11. Oxygen interface. Detailed Implementation

[0034] To enable those skilled in the art to better understand the technical solutions in this application, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings.

[0035] See Figure 1-5An intelligent adapter module for an air respirator includes an adapter body 1, which is used for the conversion connection of a respirator mask. The material is high-temperature nylon. Specifically, the adapter body 1 is provided with a respirator adapter interface 9 for connecting to the respirator mask. For specific connection details, please refer to existing technology. The adapter body 1 has a filter canister interface 10 and an oxygen interface 11 distributed on both sides. This application adopts a dual-air supply method to ensure the breathing safety of rescue personnel. The oxygen interface 11 connects to a compressed air cylinder, and the filter canister interface 10 connects to a filter canister, mainly for filtering toxic gases such as CO and H2S. The adapter body 1 has a built-in switching valve that automatically switches the supply based on the oxygen concentration and toxic gas detection of an environmental sensor. The device features a gas mode, or supports manual and quick switching, and the filter canister adopts a modular design for rapid replacement, adapting to different toxic gas scenarios to meet various rescue environments. A one-way valve 5 is installed inside the filter canister interface 10, effectively preventing the entry of toxic gases when the filter canister interface 10 is in use. A filter canister interface cover 3 is installed on the filter canister interface 10 via a first fixing screw 2, which can be used to seal the interface when not in use. Similarly, a quick-release cover 6 is installed on the oxygen interface 11 via a second fixing screw 8, which can be used to seal the oxygen interface 11 when not in use. This application presents a lightweight, highly reliable, multi-scenario adaptable breathing mask that improves firefighter safety and fire rescue efficiency.

[0036] In this application, a first sealing ring 4 is provided between the one-way valve 5 and the inner wall of the filter canister interface 10, and a second sealing ring 7 is provided at the connection between the ventilator adapter 9 and the mask. Both the first sealing ring 4 and the second sealing ring 7 are made of military-grade sealing ring material, such as fluororubber, and have high fatigue resistance after simulation verification by the switching mechanism.

[0037] This application also includes an intelligent face mask system for an air respirator, comprising a face mask body installed on an intelligent adapter module of the air respirator. The face mask body is made of high-temperature resistant polyether ether ketone (PEEK) material, and a sensor module, an anti-noise communication module, and an augmented reality display module are installed on the face mask body.

[0038] The sensor module includes a non-contact photoelectric sensor, which uses a dual-wavelength reflective measurement with a wavelength of 660nm-940nm and an accuracy of ±2bpm for heart rate detection. In actual use, the heart rate is monitored at a sampling rate of 100Hz. When the heart rate is detected to be >160bpm for 5 consecutive minutes, the edge computing unit marks it as "fatigue state" and promptly notifies firefighters to evacuate.

[0039] Thin-film temperature sensor with a range of 0-150℃ and a resolution of 0.1℃ is used to monitor ambient temperature and notify firefighters to evacuate in time if the ambient temperature affects their personal safety.

[0040] MEMS gas sensors can detect CO, O2, and HCN gases with a sensitivity of 1 ppm. In specific rescue operations, if the CO concentration is detected to rise to 80 ppm, it can notify firefighters to evacuate in time.

[0041] The three-axis accelerometer / gyroscope monitors motion posture and can detect the movement status of firefighters during rescue operations. It can promptly detect whether firefighters are in a normal state of motion and can detect and inquire about their current status immediately after a fall, which helps the command center to issue instructions.

[0042] Non-contact photoelectric sensors, thin-film temperature sensors, MEMS gas sensors, and triaxial accelerometers / gyroscopes are all integrated on the mask body. This application uses flexible circuit boards and miniaturized sensors, making the device lightweight, capable of life monitoring and environmental monitoring, and easy to carry.

[0043] In this application, the noise-resistant communication module includes a bone conduction microphone and a directional speaker. Since the ambient noise in the fire scene exceeds 100dB and the voice recognition rate of traditional microphones is less than 50%, a bone conduction microphone with a frequency response of 100-6000Hz and a signal-to-noise ratio of ≥60dB is used during communication. For the speaker, a directional speaker is selected, which supports beamforming noise reduction technology, has a frequency response of 100-6000Hz, and a signal-to-noise ratio of ≥60dB. During transmission, an echo cancellation algorithm (AEC) is used to achieve full-duplex communication, which has low latency and high clarity.

[0044] Furthermore, to improve the reliability of the transmission, i.e., in case the speaker malfunctions or fails to operate normally, this application also includes an augmented reality display module, including a micro-OLED transparent display screen with a resolution of 1280×720 and a brightness of 1000 cd / m². 2 The laser projection unit uses HUD projection technology, which not only provides voice prompts but also displays instructions on a micro OLED transparent screen and projects the action route, further ensuring safety on the fire scene.

[0045] Furthermore, this application also includes a cloud-based decision-making module, which includes a fire scene 3D modeling module. Before entering the fire scene, it generates a dynamic thermodynamic diffusion simulation by integrating BIM building information model and thermal imaging data, thereby realizing dynamic fire scene modeling and rescue strategy optimization. A reinforcement learning decision-making module optimizes fire extinguishing path planning by utilizing temperature gradient, structural stress, and remaining gas cylinder volume, thereby improving rescue efficiency. A risk prediction module provides early warning of hypoxia / poisoning risks through sensor data and the time-series characteristics of firefighters' physiological data, further reducing the danger of rescue.

[0046] Furthermore, this application also includes a multi-level alarm protocol, which includes setting a second-level warning, wherein:

[0047] Level 1 alarm (voice prompt): When CO concentration > 50 ppm, the "Recommend activating water curtain isolation" command is triggered;

[0048] Level 2 alarm (vibration + visual warning): When heart rate consistently >150 bpm and body temperature >39°C, the movement route will be forcibly locked and emergency oxygen supply will be activated. This improves safety during rescue operations.

[0049] This application discloses a method for using a smart face mask for an air respirator, comprising the following steps:

[0050] By combining BIM building information modeling with thermal imaging data, dynamic thermodynamic diffusion simulations are generated to help the command center accurately grasp the dynamics of the fire scene. Furthermore, the temperature at each fire location can be revised using sensors carried by firefighters, making the model more accurate.

[0051] The Q-learning algorithm is used to optimize fire extinguishing route planning. When planning the route, it is necessary to plan according to temperature gradient, structural stress, and remaining gas cylinder capacity, and leave 5%-8% of the gas cylinder capacity as a reserve to ensure rescue safety.

[0052] By analyzing the temporal characteristics of physiological data using an LSTM neural network, early warnings of hypoxia / poisoning risks are provided. Calculations are performed using existing physiological parameters. Timely feedback is provided when gas cylinders are insufficient, firefighters' heart rates are too high, temperatures are too high, or the surrounding toxic gas levels exceed safe limits.

[0053] After planning the route, firefighters put on air-breathing respirators and smart mask systems to enter the fire scene and carry out rescue work according to the route instructions;

[0054] The photoelectric sensor monitors heart rate at a sampling rate of 100Hz, the MEMS gas sensor detects CO concentration, and the HUD projects the movement route while simultaneously broadcasting voice instructions to firefighters, thereby monitoring their vital signs and environmental information.

[0055] When a heart rate >160 bpm or CO concentration rises to 80 ppm for 5 consecutive minutes is detected, the HUD projects an evacuation route to instruct firefighters to evacuate and avoid personal injury to firefighters.

[0056] Example 1: Firefighters wearing masks enter the fire scene. After the system is activated:

[0057] 1. The non-contact photoelectric sensor monitors heart rate at a sampling rate of 100Hz. When a heart rate >160bpm is detected for 5 consecutive minutes, the edge computing unit marks it as "fatigue state".

[0058] 2. The MEMS gas sensor detected that the CO concentration rose to 80ppm. The cloud decision module called the building BIM model and combined it with airflow simulation to generate an avoidance path.

[0059] 3. The laser projection unit HUD projects arrows indicating "Evacuate to * → 10m" while simultaneously broadcasting a voice message: "Carbon monoxide levels detected. Evacuation along the marked route is recommended." At the same time, the command center makes real-time corrections to the evacuation route to ensure its safety.

[0060] Example 2: Under conditions of multiple rescuers

[0061] 1. Upload the remaining gas cylinder quantity at each node to the cloud-based decision-making module;

[0062] 2. The cloud-based decision-making module calculates the optimal supply scheduling plan and sends the instruction via the bone conduction microphone: "*personnel proceed to **personnel's location to hand over the gas cylinder";

[0063] 3. The vibration module of the air respirator mask indicates that the operator has entered standby mode.

[0064] Example 3, 1. The Huawei Tianji module detected that the firefighter's blood oxygen saturation dropped sharply from 98% to 88% (lasting for 10 seconds), triggering the emergency data channel;

[0065] 2. The raw data was encrypted with AES-256 and transmitted to the DeepSeek cloud. The Fire-3 model, combined with the fire heat map, determined that it was a toxic gas leak in a concealed space.

[0066] 3. The system performs the following actions:

[0067] The HUD flashes red to warn of "Evacuate immediately";

[0068] Use the TinyFire model to generate the shortest purification path;

[0069] The self-organizing network module sends a collaborative rescue request (including location coordinates and remaining gas cylinder balance) to teammates.

[0070] Example 4: In a multi-firefighter collaborative scenario, the DeepSeek model dynamically adjusts task allocation based on the group physiological load data uploaded by the Tianji module.

[0071] When the average heart rate of 3 team members is detected to be >140 bpm, the system will automatically dispatch substitute team members to take over the attack mission.

[0072] Oxygen supply priority is intelligently allocated based on individual differences in blood oxygen levels (error rate <5%).

[0073] As can be seen from the above technical solution, the breathing mask of this application adopts a multi-mode air supply system of air respirator and filter canister to ensure the breathing safety of firefighters. The main air circuit is connected to the compressed air cylinder, and the backup air circuit is connected to the filter canister. The air supply mode can be automatically or manually switched according to the oxygen concentration and toxic gas detection of the sensor. The filter canister is installed in a detachable mode and can be replaced according to different rescue scenarios. Before entering the fire scene for rescue, a fire scene model is generated based on the BIM building information model and thermal imaging data. Then, the rescue route is planned, and the rescue route and surrounding temperature, toxic gas content, oxygen cylinder remaining amount and the firefighter's own blood oxygen concentration and heart rate are displayed on the breathing mask using a miniature OLED transparent display screen and laser projection unit. The above data is transmitted to the command center in real time. When abnormal personnel are encountered during the rescue, they can be marked and a request for coordinated rescue can be made. When a firefighter's physical signs are abnormal, the firefighter can be quickly notified to return and a return route can be planned.

[0074] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the application disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope of this application is indicated by the claims.

[0075] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The embodiments of this application described above do not constitute a limitation on the scope of protection of this application.

Claims

1. An air respirator smart adapter module comprising an adapter main body (1), characterized in that: The adapter body (1) is provided with a ventilator adapter interface (9). The adapter body (1) is provided with a filter canister interface (10) and an oxygen interface (11) on both sides. A one-way valve (5) is installed in the filter canister interface (10). A filter canister interface cover (3) is installed on the filter canister interface (10) by a first fixing screw (2). A quick-release cover (6) is installed on the oxygen interface (11) by a second fixing screw (8).

2. The intelligent adapter module for an air respirator according to claim 1, characterized in that, A first sealing ring (4) is provided between the one-way valve (5) and the inner wall of the filter canister interface (10).

3. The intelligent adapter module for an air respirator according to claim 1, characterized in that, A second sealing ring (7) is provided at the connection between the ventilator adapter (9) and the mask.

4. An intelligent face mask system for an air respirator, comprising a face mask body mounted on an intelligent adapter module of an air respirator, characterized in that: The mask body is equipped with a sensor module, an anti-noise communication module, and an augmented reality display module.

5. The intelligent face mask system for an air respirator according to claim 4, characterized in that, The sensor module includes a non-contact photoelectric sensor, a thin-film temperature sensor, a MEMS gas sensor, and a triaxial accelerometer / gyroscope, all of which are integrated on the mask body.

6. The intelligent face mask system for an air respirator according to claim 5, characterized in that, The noise-resistant communication module includes a bone conduction microphone and a directional speaker.

7. The intelligent face mask system for an air respirator according to claim 5, characterized in that, The augmented reality display module includes a micro OLED transparent display screen and a laser projection unit.

8. The intelligent face mask system for an air respirator according to claim 4, characterized in that, It also includes a cloud-based decision-making module, which comprises a fire scene 3D modeling module, a reinforcement learning decision-making module, and a risk prediction module.

9. The intelligent face mask system for an air respirator according to claim 4, characterized in that, It also includes a multi-level alarm protocol, which includes setting a second-level warning.

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