CN108378450B - Method for realizing intelligent fire-fighting helmet for sensing explosion accident and predicting risk - Google Patents

Method for realizing intelligent fire-fighting helmet for sensing explosion accident and predicting risk Download PDF

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Publication number
CN108378450B
CN108378450B CN201810191027.1A CN201810191027A CN108378450B CN 108378450 B CN108378450 B CN 108378450B CN 201810191027 A CN201810191027 A CN 201810191027A CN 108378450 B CN108378450 B CN 108378450B
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fire
data
risk
temperature
explosion
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CN108378450A (en
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刘晅亚
陈彦菲
宋晓峰
黄建建
张英豪
陈晔
李晶晶
朱红亚
于年灏
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Tianjin Fire Research Institute of MEM
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Tianjin Fire Research Institute of MEM
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    • A—HUMAN NECESSITIES
    • A42—HEADWEAR
    • A42B—HATS; HEAD COVERINGS
    • A42B3/00—Helmets; Helmet covers ; Other protective head coverings
    • A42B3/04—Parts, details or accessories of helmets
    • A42B3/18—Face protection devices
    • A42B3/20—Face guards, e.g. for ice hockey
    • A—HUMAN NECESSITIES
    • A42—HEADWEAR
    • A42B—HATS; HEAD COVERINGS
    • A42B3/00—Helmets; Helmet covers ; Other protective head coverings
    • A42B3/04—Parts, details or accessories of helmets
    • A42B3/0406—Accessories for helmets
    • A—HUMAN NECESSITIES
    • A42—HEADWEAR
    • A42B—HATS; HEAD COVERINGS
    • A42B3/00—Helmets; Helmet covers ; Other protective head coverings
    • A42B3/04—Parts, details or accessories of helmets
    • A42B3/0406—Accessories for helmets
    • A42B3/0433—Detecting, signalling or lighting devices
    • A—HUMAN NECESSITIES
    • A42—HEADWEAR
    • A42B—HATS; HEAD COVERINGS
    • A42B3/00—Helmets; Helmet covers ; Other protective head coverings
    • A42B3/04—Parts, details or accessories of helmets
    • A42B3/0406—Accessories for helmets
    • A42B3/0433—Detecting, signalling or lighting devices
    • A42B3/046—Means for detecting hazards or accidents
    • A—HUMAN NECESSITIES
    • A42—HEADWEAR
    • A42B—HATS; HEAD COVERINGS
    • A42B3/00—Helmets; Helmet covers ; Other protective head coverings
    • A42B3/04—Parts, details or accessories of helmets
    • A42B3/06—Impact-absorbing shells, e.g. of crash helmets
    • A—HUMAN NECESSITIES
    • A42—HEADWEAR
    • A42B—HATS; HEAD COVERINGS
    • A42B3/00—Helmets; Helmet covers ; Other protective head coverings
    • A42B3/04—Parts, details or accessories of helmets
    • A42B3/30—Mounting radio sets or communication systems
    • G—PHYSICS
    • G02—OPTICS
    • G02B—OPTICAL ELEMENTS, SYSTEMS OR APPARATUS
    • G02B27/00—Optical systems or apparatus not provided for by any of the groups G02B1/00 - G02B26/00, G02B30/00
    • G02B27/01—Head-up displays
    • G02B27/017—Head mounted
    • G02B27/0172—Head mounted characterised by optical features
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
    • G08B21/02—Alarms for ensuring the safety of persons
    • G08B21/12—Alarms for ensuring the safety of persons responsive to undesired emission of substances, e.g. pollution alarms
    • G08B21/14—Toxic gas alarms
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
    • G08B21/02—Alarms for ensuring the safety of persons
    • G08B21/12—Alarms for ensuring the safety of persons responsive to undesired emission of substances, e.g. pollution alarms
    • G08B21/16—Combustible gas alarms

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  • Physics & Mathematics (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Toxicology (AREA)
  • Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Environmental & Geological Engineering (AREA)
  • Business, Economics & Management (AREA)
  • Emergency Management (AREA)
  • Combustion & Propulsion (AREA)
  • Chemical & Material Sciences (AREA)
  • Optics & Photonics (AREA)
  • Alarm Systems (AREA)

Abstract

The invention relates to a method for realizing an intelligent fire-fighting helmet for sensing explosion accidents and predicting risks, which comprises a fire-fighting helmet, a remote combustible gas detector, a thermal imaging camera module, a head-mounted near-to-eye display module, a positioning instrument, a data communication transmission module, an embedded core board, an earphone, a base station and a fire-fighting command center. According to the invention, a firefighter positioning technology is combined with a building information model and live-action thermal image information, and information projection and display are carried out through the head-mounted near-to-eye display module, so that the real-time position of the firefighter in a building can be displayed for the firefighter, and the environment explosion risk and the risk thereof can be predicted in real time. When a firefighter enters an unknown environment place, the potential fire explosion accident risk can be rapidly and effectively predicted, and the rapid perception and information communication of the firefighter on the fire accident scene can be realized through an advanced video and thermal imaging technology and an indoor positioning and communication transmission technology, so that the fire fighting rescue science level and capability of the firefighter are improved.

Description

Method for realizing intelligent fire-fighting helmet for sensing explosion accident and predicting risk
Technical Field
The invention relates to an intelligent fire-fighting helmet realizing method for sensing explosion accidents and predicting risks, which is used for detecting fire fields of firefighters, predicting and early warning explosion accidents in fire rescue sites, can provide support for fire-fighting rescue site safety disposal decisions of firefighters, and can also provide support for a site command center to deeply understand fire field conditions and conduct scientific decision command.
Background
In the process of entering a building space to carry out fire-extinguishing rescue, firefighters often have insufficient knowledge of risks of secondary fire and explosion accidents possibly occurring in fire scene information, so that firefighters bear huge risks in the fire-extinguishing rescue process. In the case of fire rescue in buildings or confined spaces, there are also a number of incidents that occur as a result of secondary deflagrations occurring as a result of firefighters being surprised into an unknown space. At present, in the aspect of intelligent fire helmets, equipment such as thermal imaging, gas detection alarm, communication intercom and the like is often integrated with products in the prior art, but gas detection mainly adopts an air suction type gas detector, detection analysis of gas concentration at the position of a firefighter cannot be realized, detection of the environment at the remote position of the firefighter cannot be realized, firefighters cannot quickly master fire scene environment, building facility layout and related information, prediction and early warning of environmental fire explosion risks cannot be realized, comprehensive intelligent analysis and judgment of fire information at an accident scene cannot be realized, visual fire scene information and accident risk early warning display are performed on the firefighter, and functions such as navigation and guidance of firefighter rescue paths are not realized.
Disclosure of Invention
In view of the state of the prior art, the invention provides a realization method and a use method of an intelligent fire-fighting helmet for sensing explosion accidents and predicting risks, which combines a firefighter positioning technology with Building Information Model (BIM) and live-action thermal image information, performs information projection and display through a head-mounted near-to-eye display module, can display the real-time position of the firefighter in a building, and predicts the environment explosion risks and risks of the firefighter in real time.
According to the intelligent fire-fighting helmet, the potential fire explosion accident risk can be rapidly and effectively predicted when a firefighter enters an unknown environment place, and the firefighter can rapidly sense and communicate information on the fire accident scene through an advanced video and thermal imaging technology and an indoor positioning and communication transmission technology, so that the fire-fighting rescue science level and capability of the firefighter are improved.
The invention adopts the technical proposal for realizing the aim that: an intelligent fire-fighting helmet for sensing explosion accidents and predicting risks and early warning comprises a fire-fighting helmet, a remote combustible gas detector, a thermal imaging camera module, a head-mounted near-to-eye display module, a positioning instrument, a data communication transmission module, an embedded core board, headphones, a base station and a fire-fighting command center;
The fire-fighting helmet comprises a helmet shell, a helmet hoop, a helmet support, a buffer layer, a mask and a cape; the lower extreme of helmet cap shell is the cap and holds in the palm, and the lower extreme of cap holds in the palm is the cape, and the front end of helmet cap shell is the face guard, is equipped with cap hoop and buffer layer, its characterized in that respectively in helmet cap shell: the helmet comprises a helmet shell, a helmet head-mounted near-to-eye display module, a far-distance combustible gas detector, a thermal imaging camera module, a positioning instrument, a data communication transmission module and an embedded core plate, wherein the inner surface of the helmet shell is provided with a layer of silica gel honeycomb damping layer, the damping layer is arranged below the silica gel honeycomb damping layer, two earphones are symmetrically arranged on two side walls in the helmet shell, the head-mounted near-to-eye display module is arranged on one side of the inner surface of the helmet shell, the far-distance combustible gas detector, the thermal imaging camera module, the positioning instrument, the data communication transmission module and the embedded core plate are respectively arranged on the inner top surface of the helmet shell, and a lens of the thermal imaging camera module and a sensor of the far-distance combustible gas detector are respectively extended out of the helmet shell and are arranged right in front of the helmet shell;
the embedded type core board consists of a CPU, an MIPI interface, a USB interface I, a USB interface II, an SDIO interface, a serial communication interface and an SD card, wherein the CPU is respectively connected with the MIPI interface, the USB interface I, the USB interface II, the SDIO interface and the serial communication interface, and the SD card is inserted into the SDIO interface;
The data communication transmission module consists of a wireless processor CPU, a radio frequency module and a built-in antenna, and the radio frequency module is respectively connected with the wireless processor CPU and the built-in antenna;
the thermal imaging camera module consists of a camera chip, a video module and a thermal imaging sensor, and the camera chip is respectively connected with the video module and the thermal imaging sensor;
the remote combustible gas detector is formed by connecting a laser/infrared gas detection module and an interface chip I;
the head-mounted near-to-eye display module consists of an LCOS module, a display chip and a prism, wherein the display chip is respectively connected with the LCOS module and the prism;
the positioning instrument consists of a gyroscope, a wireless module and an interface chip II, wherein the gyroscope and the wireless module are respectively connected with the interface chip II;
the circuit connection is that the MIPI interface of the embedded core board is connected with the display chip of the head-mounted near-to-eye display module, the USB interface I is connected with the wireless processor CPU of the data communication transmission module, the USB interface II and the serial communication interface are respectively connected with the camera chip of the thermal imaging camera module, the serial communication interface is respectively connected with the interface chip II of the positioning instrument and the interface chip I of the remote flammable gas detector, the data communication transmission module sends or receives signals of the base station through the built-in antenna, and the base station is connected with the fire command center;
The remote combustible gas detector can detect the concentration of combustible harmful gas within the range of not less than 30m away from the firefighter through the laser/infrared gas detection module;
the thermal imaging camera module detects rescue environment and the temperature distribution condition of articles thereof through the video module and the thermal imaging sensor;
the head-mounted near-to-eye display module projects real-time images, thermal images, BIM information, personnel position information and explosion risk early warning information to the retina of the human eye through the prism;
the locator determines and transmits the position information of the firefighter;
the data communication transmission module is communicated with the fire control command center through the base station;
the embedded core board realizes comprehensive processing and transmission of combustible gas concentration data, thermal imaging temperature data, personnel position information, explosion accident risk prediction and early warning information.
A method for realizing an intelligent fire-fighting helmet for sensing explosion accidents and predicting risks is characterized by comprising the following steps:
the fire-fighting helmet is worn on the head of a fire fighter, the helmet support is used for fixing the face of the fire fighter, the tightness of the helmet hoops in the helmet shell can be adjusted according to the head size of the person, the silica gel honeycomb damping layer is used for protecting the head of the person wearing the helmet, the impact force of external force on the head of the person wearing the helmet caused by impact is reduced, the comfort and the safety of wearing the helmet are further improved by the damping layer, the earphones on the two sides in the helmet shell are arranged on the two ears of the fire fighter, the headset connected with the earphones is arranged in front of the mouth of the fire fighter, the mask is worn in front of the face of the fire fighter to provide safety protection, the head-wearing near-eye display module on the inner face of the mask is arranged in front of the eyes of the fire fighter to enable the cape to be buckled on the shoulder, and the neck of the fire fighter to be protected by the cape;
Before a fire fighter enters a rescue building, the fire control command center transmits building BIM information model data to a fire control helmet embedded core board through a network, and the embedded core board stores the BIM data into an SD card through an SDIO interface, so that the data volume transmitted through the network after the fire fighter enters the building is reduced, and the real-time exchange response speed of on-site information is improved;
the positioning instrument regularly transmits positioning information data to the embedded core board through the serial port communication interface, the embedded core board receives the data and then transmits the positioning information to the fire control command center through the built-in antenna of the data communication transmission module, the base station combines the positioning data and BIM (building information model) of a building according to the positioning data, the position and direction information of fire fighters and the harmful gas detection data and the thermal imaging data of the front end, the dangerous degree of each area is displayed in a three-dimensional map mode, the dangerous degree is displayed through the embedded core board and the head-mounted near-to-eye display module, meanwhile, the base station transmits the information to the fire control command center, and a fire control command center control terminal computer invokes the building BIM information to generate a three-dimensional map comprising building model information, accident scene blasting dangerous distribution and firefighter position information content, and the three-dimensional map is displayed on a command center display screen;
When navigation is needed, a fire fighter can carry out voice communication with a fire command center, the fire command center can assist fire fighters in setting rescue destinations and selecting optimal rescue planning paths, meanwhile, the fire command center sends navigation path information to an embedded core board through a base station and a data communication transmission module, the embedded core board calls BIM information stored in an SD card to generate a three-dimensional map, marks the navigation paths and sends the navigation paths to a head-mounted near-to-eye display module for display through an MIPI interface;
the remote combustible gas detector detects the concentration of gas or combustible vapor at the rescue accident site in real time, and the types of gas which can be detected remotely comprise methane, propane, ethylene, ethanol or CO flammable and explosive dangerous gas;
the remote flammable gas detector sends the dangerous gas concentration data detected in real time to the embedded type core board through the serial port communication interface, the embedded type core board CPU integrates and analyzes the received concentration data of the gas and the environmental thermal image data, a preset explosion risk calculation model and a preset method are adopted for quick prediction and evaluation, the explosion risk level of a corresponding area is calculated and analyzed, the risk level of an explosion accident and a dangerous early warning prompt of the area to be entered are provided for firefighters, and the dangerous early warning prompt is projected and displayed by the head-mounted near-to-eye display module in a color block labeling mode, so that firefighters can see the displayed area temperature, the inflammable and explosive gas components and concentration distribution, the explosion accident risk level and the early warning prompt content;
Analyzing the collected dangerous gas concentration and environmental temperature data by adopting a preset explosion risk calculation model and method, calculating a risk value of a detection area, and identifying the dangerous gas concentration and environmental temperature data as a safe area by green when the risk value R is less than 1; when the risk value 2 is more than R and is more than or equal to 1, prompting as IV explosion risk early warning, and marking the area by blue; when the risk value 3 is more than R and is more than or equal to 2, prompting to be III explosion risk early warning, and marking the region with yellow; when the risk value is 4 & gtR & gtor more than 3, the warning is II risk early warning, and the area is marked with orange; when the risk value R is more than or equal to 4, prompting to be I-level risk early warning, and marking the region by dark red; the base station calculates real-time risk results of different areas of the scene according to dangerous gas concentration, environmental thermal images and temperature information data acquired on the scene, sends the dangerous areas and the safe areas which are divided after analysis and calculation back to the embedded core board, and displays the dangerous display contents of the different areas through the head-mounted near-to-eye display module, and meanwhile, the embedded core board sends images, temperatures and dangerous gas concentration data to the fire control command center through the built-in antenna of the data communication transmission module, and the fire control command center can make relevant rescue treatment decisions according to the scene detection data and risk analysis results, returns command decision instructions to the embedded core board in real time and performs projection display through the head-mounted near-to-eye display module;
The thermal imaging camera module sends the field image with the superimposed temperature data and the temperature data to the embedded core board, the USB interface transmits video data with the superimposed temperature data and the video synthesized by the camera chip, the video data is compressed by using the H.264 standard, the serial communication interface transmits the temperature lattice data acquired by the thermal imaging sensor, the CPU of the embedded core board receives the video data and then decodes and displays the video data to the head-mounted near-to-eye display module, a fire fighter can know the environmental temperature distribution condition, and the combustible gas detection data, the thermal imaging data and the fire fighter position information collected by the embedded core board are transmitted to the command center through the data communication transmission module by the base station in a wireless manner;
the base station can intensively display the data acquired by each firefighter, analyzes the data acquired by the front end through a deep learning algorithm, and is used for the decision-making of a firefighting command center and a front-end firefighter.
The beneficial effects of the invention are as follows: the invention provides an intelligent fire-fighting helmet with intelligent sensing, information communication processing and visual display functions at a fire accident scene, which can detect combustible, toxic and harmful gases within 30 meters away from a firefighter, rapidly predicts the explosion accident risk at the accident scene, and can perform risk early warning prompt, and belongs to integrated digital intelligent individual equipment.
The invention adopts a laser/infrared spectrum gas concentration detector, a thermal imaging camera module, an indoor gyroscope positioning device, a head-mounted near-to-eye micro-display module and a wireless networking information communication transmission technology, is integrally applied to a full-protection or face-mask type fire-fighting helmet, can intelligently sense and judge information such as fire scene environment temperature, environment information position, flammable and toxic harmful gas concentration in a fire scene, accident scene explosion accident risk and the like for a fire fighter in a fire accident scene, so as to fully master fire hazard and explosion accident risk of the fire fighter before the fire fighter enters an unknown fire scene environment, and also provides fire scene real-time information and rescue command basis for accident scene fire-fighting and rescue command. The helmet meets the related requirements of GA44, has interconnection and intercommunication with a fire-fighting command vehicle on the fire-fighting rescue site, can provide a site fire-fighting command for firefighters, rescue site environment geographic information and building BIM information, and can provide prediction and early warning judgment on the risk of fire and explosion accidents on the accident site according to measurement and analysis on the ambient temperature and the surrounding combustible GAs concentration distribution on the accident site, so that multi-information data support is provided for safe, scientific and effective rescue of firefighters.
The invention combines BIM and a positioning instrument, displays the building information model of the current position on the intelligent fire-fighting helmet worn by the fire fighter, comprises the position of the corresponding facility, and plans all possible paths and optimal travelling paths between the current position and the destination, so as to be beneficial to the fire fighter to make optimal selection and judgment on site.
(1) And detecting the concentration of combustible gas and toxic and harmful gas within the range of 30m by utilizing a laser/infrared spectrum detection technology, determining the risk of secondary explosion accidents in the area to be entered, and carrying out effective early warning.
(2) The risk of explosion accidents on the rescue scene is prompted to pay attention to by the aid of a head-mounted near-to-eye display module and voice prompt, and the fire fighters can rapidly evaluate the dangerous degree of the area.
(3) The projection imaging of the building area BIM information on the helmet mask is realized by using the virtual imaging projection technology, the wireless communication transmission technology and the support of the central server, so that firefighters can better solve the detailed information of the building at the position and can carry out navigation guidance for rescue of the firefighters.
(4) And displaying the temperature distribution condition of each area of the site by adopting an augmented reality mode through the combination of a virtual imaging projection technology and a thermal imaging technology.
(5) The thermal imaging image is combined with a visual algorithm based on deep learning of the center platform, so that a safe area and a dangerous area of a fire scene can be vividly described, and temperature dangerous grades can be divided.
(6) And dividing the comprehensive dangerous grade by combining different combustible gas concentrations, gas ignition temperature and thermal imaging temperature data.
(7) And integrating a plurality of firefighter data through the center platform to form comprehensive condition analysis data, and sending the comprehensive condition analysis data to a virtual imaging projection system of each firefighter, so that the firefighters can know the real-time overall condition of the fire scene.
(8) The front-end firefighter can be instructed to execute the command center command in the mode of an indoor navigation map by combining the firefighter indoor positioning data with BIM data.
(9) The inner damping layer of the helmet adopts the design of a silica gel honeycomb damping structure, so that the strength of the intelligent fire-fighting helmet is effectively improved, and the weight of the firefighter helmet is reduced.
The invention can be used as a firefighter integrated digital individual device, and can be widely applied to firefighter fire-extinguishing rescue treatment and auxiliary decision-making command.
Drawings
FIG. 1 is a schematic diagram of the structure of the present invention;
FIG. 2 is a schematic view of a silica gel honeycomb damper layer disposed on the inner face of a helmet shell according to the present invention;
FIG. 3 is a block diagram of a circuit connection of the present invention;
FIG. 4 is a flow chart of the analysis and display of the risk of explosion accident of the present invention;
FIG. 5 is a flow chart of a smart helmet data call display;
FIG. 6 is a flow chart of a gas detection process of the present invention;
FIG. 7 is a flow chart of a thermal imaging image display of the present invention;
FIG. 8 is a mathematical model fitting curve of the environmental temperature risk RT of the explosion risk analysis of the present invention;
fig. 9 is a graph of a mathematical model fit of the explosion risk analysis thermal radiation risk RH of the present invention.
Detailed Description
As shown in fig. 1 to 7, the intelligent fire-fighting helmet for sensing explosion accidents and predicting risk and early warning comprises a fire-fighting helmet 1, a remote combustible gas detector 2, a thermal imaging camera module 3, a head-mounted near-to-eye display module 4, a positioning instrument 5, a data communication transmission module 6, an embedded core board 7, an earphone 8, a base station 9 and a fire-fighting command center 10.
The fire-fighting helmet 1 comprises a helmet shell 1-1, a helmet hoop 1-2, a helmet support 1-3, a buffer layer 1-4, a face shield 1-5 and a cape 1-6.
The lower end of a helmet shell 1-1 is a helmet support 1-3, the lower end of the helmet support 1-3 is a cape 1-6, the front end of the helmet shell 1-1 is a face mask 1-5, a helmet hoop 1-2 is arranged in the helmet shell 1-1, a layer of silica gel honeycomb shock-absorbing layer 1-7 is adhered to the inner surface of the helmet shell 1-1, a layer of buffer layer 1-4 is arranged below the layer of silica gel honeycomb shock-absorbing layer 1-7, two earphones 8 are symmetrically arranged on two side walls in the helmet shell 1-1, a head-wearing near-to-eye display module 4 is arranged on one side of the inner surface of the face mask 1-5, a remote flammable gas detector 2, a thermal imaging camera module 3, a positioning instrument 5, a data communication transmission module 6 and an embedded core plate 7 are respectively arranged on the inner top surface of the helmet shell 1-1, and a lens of the thermal imaging camera module 3 and a sensor of the remote flammable gas detector 2 are respectively extended out of the helmet shell 1-1 and are arranged right in front of the helmet shell 1-1.
The embedded core board 7 is composed of a CPU, an MIPI interface, a USB interface I, a USB interface II, an SDIO interface, a serial communication interface and an SD card, wherein the CPU is respectively connected with the MIPI interface, the USB interface I, the USB interface II, the SDIO interface and the serial communication interface, and the SD card is inserted into the SDIO interface.
The data communication transmission module 6 consists of a wireless processor CPU, a radio frequency module and a built-in antenna, and the radio frequency module is respectively connected with the wireless processor CPU and the built-in antenna.
The thermal imaging camera module 3 consists of a camera chip, a video module and a thermal imaging sensor, and the camera chip is respectively connected with the video module and the thermal imaging sensor.
The remote combustible gas detector 2 is formed by connecting a laser/infrared gas detection module and an interface chip I.
The head-mounted near-to-eye display module 4 consists of an LCOS module, a display chip and a prism, wherein the display chip is respectively connected with the LCOS module and the prism.
The locator 5 comprises a gyroscope, a wireless module and an interface chip II, and the gyroscope and the wireless module are respectively connected with the interface chip II.
The circuit connection is that MIPI interface and the display chip of the near-to-eye display module 4 of embedded core board 7 are connected, USB interface I is connected with the wireless processor CPU of data communication transmission module 6, USB interface II and serial communication interface are connected with the chip of making a video recording of thermal imaging module 3 respectively, serial communication interface is connected with interface chip II, the interface chip I of remote combustible gas detector 2 of locater 5 respectively, data communication transmission module 6 sends or receives the signal of basic station 9 through built-in antenna, basic station 9 is connected with fire control command center 10.
The remote combustible gas detector 2 can detect the concentration of the combustible harmful gas within a range of not less than 30m from the firefighter through the laser/infrared gas detection module 3.
The thermal imaging camera module 3 detects the rescue environment and the temperature distribution condition of the articles thereof through the video module and the thermal imaging sensor.
The head-mounted near-to-eye display module 4 projects real-time images, thermal images, BIM information, personnel position information and explosion risk early warning information to the retina of the human eye through a prism.
The locator 5 determines and transmits the location information of the firefighter.
The data communication transmission module 6 communicates with the fire command center 10 through the base station 9.
The embedded core board 7 realizes comprehensive processing and transmission of combustible gas concentration data, thermal imaging temperature data, personnel position information, explosion accident risk prediction and early warning information.
The method for realizing the intelligent fire-fighting helmet for sensing the explosion accident and predicting and early warning risk comprises the following steps:
the fire-fighting helmet 1 is worn on the head of a fire fighter, the face of the person is fixed by the helmet support 1-3, the tightness of the helmet hoop 1-2 in the helmet shell 1-1 can be adjusted according to the head size of the person, the silica gel cellular shock-absorbing layer 1-7 is used for protecting the head of the person wearing the helmet, the impact force of external force on the head of the person wearing the helmet caused by impact of the helmet is reduced, the buffer layer 1-4 further increases the comfort and safety of the person wearing the helmet, the earphones 8 on the two sides in the helmet shell 1-1 are arranged on the two ears of the fire fighter, the headset 8-1 connected with the earphones 8 is arranged in front of the mouth of the fire fighter, the head-wearing near-eye display module 4 on the inner face of the mask 1-5 is arranged in front of the eyes of the fire fighter, the cape 1-6 is buckled on the shoulder, and the neck of the fire fighter is protected by the cape 1-6.
Before a fire fighter enters a rescue building, the fire control command center 10 transmits building BIM information model data to the embedded core board 7 of the fire control helmet 1 through a network, and the embedded core board 7 stores the BIM data into the SD card through the SDIO interface, so that the data volume transmitted through the network after the fire fighter enters the building is reduced, and the real-time exchange response speed of on-site information is improved.
The positioning instrument 5 sends positioning information data to the embedded core board 7 at regular time through the serial port communication interface, the embedded core board 7 receives the data and then sends the positioning information to the fire control command center 10 through the built-in antenna of the data communication transmission module 6, the base station 9 combines the positioning data and BIM (building information model) of a building according to the position and direction information of fire fighters and the harmful gas detection data and thermal imaging data of the front end, the dangerous degree of each area is displayed in a three-dimensional map mode, meanwhile, the base station 9 sends the information to the fire control command center 10, the fire control command center 10 controls a terminal computer to call the building BIM information, and a three-dimensional map comprising building model information, accident scene blasting danger distribution, firefighter position information and the like is generated and displayed on a command center display screen.
When navigation is needed, a fire fighter can carry out voice communication with the fire control command center 10, the fire control command center 10 can assist fire fighters in setting rescue destinations and selecting optimal rescue planning paths, meanwhile, the fire control command center 10 sends navigation path information to the embedded core board 7 through the base station 9 and the data communication transmission module 6, the embedded core board 7 calls BIM information stored by the SD card to generate a three-dimensional map, marks the navigation paths and sends the navigation paths to the head-mounted near-to-eye display module 4 for display through the MIPI interface.
The remote combustible gas detector 2 detects the concentration of gas or combustible vapor at the rescue accident site in real time, and the types of gas which can be detected remotely comprise flammable and explosive dangerous gases such as methane, propane, ethylene, ethanol or CO.
The remote flammable gas detector 2 sends the dangerous gas concentration data detected in real time to the embedded core board 7 through the serial port communication interface, the embedded core board 7 CPU integrates and analyzes the received concentration data of the gas and the environmental thermal image data, the explosion risk level of the corresponding area is calculated and analyzed by adopting a preset explosion risk calculation model and method, the risk level and the dangerous early warning prompt of explosion accidents which are about to enter the area are provided for firefighters, the head-mounted near-to-eye display module 4 is used for projection display in a color block labeling mode, and firefighters can see the displayed area temperature, the flammable and explosive gas components and concentration distribution, the explosion accident risk level and the early warning prompt content.
Analyzing the collected dangerous gas concentration and environmental temperature data by adopting a preset explosion risk calculation model and method, calculating a risk value of a detection area, and identifying the dangerous gas concentration and environmental temperature data as a safe area by green when the risk value R is less than 1; when the risk value 2 is more than R and is more than or equal to 1, prompting as IV explosion risk early warning, and marking the area by blue; when the risk value 3 is more than R and is more than or equal to 2, prompting to be III explosion risk early warning, and marking the region with yellow; when the risk value is 4 & gtR & gtor more than 3, the warning is II risk early warning, and the area is marked with orange; when the risk value R is more than or equal to 4, prompting to be I-level risk early warning, and marking the region by dark red; the base station 9 calculates real-time risk results of different areas of the scene according to dangerous gas concentration, environmental thermal images and temperature information data acquired on the scene, sends the dangerous areas and the safe areas which are divided after analysis and calculation back to the embedded core board 7, and displays the dangerous display contents of the different areas through the head-mounted near-to-eye display module 4, meanwhile, the embedded core board 7 sends images, temperatures and dangerous gas concentration data to the fire control command center 10 through the built-in antenna of the data communication transmission module 6, the fire control command center 10 can make relevant rescue treatment decisions according to the scene detection data and risk analysis results, and returns command decision instructions to the embedded core board 7 in real time, and the command decision instructions are projected and displayed through the head-mounted near-to-eye display module 4.
The thermal imaging camera module 3 sends the field image and the temperature data of the superimposed temperature data to the embedded core board 7, the USB interface transmits the video data of the superimposed temperature data and the video data synthesized by the camera chip, the video data is compressed by using the H.264 standard, the serial communication interface transmits the temperature dot matrix data acquired by the thermal imaging sensor, the CPU of the embedded core board 7 decodes and displays the video data to the head-mounted near-to-eye display module 4 after receiving the video data, a fire fighter can know the environmental temperature distribution condition, the combustible gas detection data, the thermal imaging data and the fire fighter position information collected by the embedded core board 7 are transmitted to the command center through the data communication transmission module 6 by the base station 9 in a wireless mode, the base station 9 can intensively display the data collected by each firefighter, and the data collected at the front end are analyzed by the deep learning algorithm for the fire fighter decision making of the fire fighter command center 10 and the front end.
The method for determining the explosion risk level comprises the following steps:
the method comprises the steps of comprehensively calculating the possibility of accident occurrence, the frequency of personnel exposure to dangerous environments and the angle of the consequences possibly caused by the accident occurrence, comparing the comprehensive calculation with threshold values, determining the influence of three factors of combustible gas concentration C, temperature T and heat radiation H in a related building area on human bodies, giving different scores, multiplying the three scores, and determining the dangerous grade of the area.
The accident area explosion risk level calculation model formula is as follows:
R=f(C 0 ,T,H)=Max(RC,RT,RH) ×K
=Max QUOTE
wherein:
RC is the dangerous value of the concentration of the combustible gas, is dimensionless, and is equal to C in percentage by weight 0 /（LEL 25 *0.25）；
RC= C 0 /（LEL 25 *0.25 Indicating the possibility of a fire explosion accident due to the concentration of the combustible gas.
The explosion limit is a general term of the explosion lower limit and the explosion upper limit, the concentration of the combustible gas in the air can only explode between the explosion lower limit and the explosion upper limit, and the alarm concentration is generally set below 25% of the explosion lower limit LEL when the explosion risk early warning is carried out by the concentration of the explosive gas at present;
C 0 is the volume concentration of the combustible gas.
LEL 25 The lower explosion limit of the combustible gas at normal temperature and normal pressure can be obtained by consulting physicochemical properties;
RT is a temperature hazard value, a dimensionless value and RT= | 0.7063e 0.0152*T -1|*K1*K2；
RT =| 0.7063e 0.0152*T -1| (T is more than or equal to 0 ℃) indicates that the human body is subjected to convection due to high temperature of environment, smoke temperature and heatThe high temperature can threaten the life of rescue workers in the accident environment, and the hot air generated by the flame can cause burn, heat collapse, dehydration and unsmooth breathing of human bodies.
Regarding the influence of the temperature of the flue gas on the human body, comprehensive literature shows that: the temperature exceeds 45 degrees, so that normal thinking and behaviors of a human body can be influenced; when the temperature is 60-65 ℃, people can endure for a period of time, and the evacuation behavior is not affected; after 95 degrees, the skin tolerance temperature drops sharply; the limit temperature of human survival is 130 ℃, and beyond the temperature, the blood pressure can be reduced, capillary vessels are damaged, so that blood cannot circulate, and the central nerve of the brain is seriously damaged to die; according to the standard definition of GB14200-2008 high temperature operation grading, more than 25 degrees of operation is defined as high temperature operation in production labor, so that 25 degrees can be set as a more comfortable state of a human body, 60 degrees is a safety threshold, and 130 degrees is a highest risk threshold; the human body can act for a long time at low temperature, and the high-temperature acting time is short; therefore, by combining RT definition, an exponential function is adopted to take (25, 0), (60, 1) and (130,4) for curve fitting, so that an environment temperature risk RT mathematical model fitting curve of FIG. 8 is obtained, meanwhile (95,2) is used as an auxiliary point for verification, and the temperature risk RT can be rapidly determined according to the temperature value of the region acquired by corresponding thermal imaging through the fitting curve.
The fire officer and soldier can improve the high temperature tolerance and the degree of wear protective clothing after certain fire-fighting and rescue training, so that the life threat caused by high temperature is reduced; referring to the ICI Monder method and the requirement of road chemistry on compensation coefficients, defining K1 as a protection coefficient, and if rescue workers wear common protective clothing, setting the coefficient to be 0.90; the fire-fighting suit for firefighters is worn, and the fire-resistant temperature is generally within 200 ℃ and the coefficient is 0.67; the fire-resistant temperature of the high-temperature protective clothing is generally about 800-1000 ℃ and the coefficient is 0.2; and defining K2 as a training coefficient, wherein the coefficient is 0.95 if firefighting rescue personnel are trained and experienced.
T is the ambient temperature;
k1 is a protection coefficient;
k2 is a human training coefficient;
RH is a thermal radiation risk value, dimensionless, rh=0.1571×h+0.0952;
rh=0.1571×h+0.0952, which represents irreversible damage to the human body due to the intensity of thermal radiation. According to the related literature study, the ambient heat radiation flux reaches 37.5 KW/m 2 1% of people within 10s die, and 100% die after 1min; up to 25 KW/m 2 100% of people die after burn within 10s and 1min; up to 12.5 KW/m 2 1% of personnel die after being lightly injured within 10s and 1min; up to 6.3KW/m 2 Personnel can stay for 1min without radiation shielding measures; up to 4 KW/m 2 Pain felt over 20 s; therefore, 5 KW/m is adopted 2 As a safety threshold, 25 is used as a highest risk critical value to perform curve fitting with (0, 0), (5, 1) and (25,4) by adopting a linear relation, so as to obtain a mathematical model fitting curve of the thermal radiation risk RH in fig. 9, and the environmental thermal radiation risk value can be determined by measuring the thermal radiation flux in the environment by using the fitting curve, and when rh=1, the formula after fitting is h=5.63, and the personnel is not at life risk.
H is the heat radiation flux in the environment KW/m 2 ；
K is an influence coefficient and represents the influence of temperature on the limit of explosive gas;
the explosion limit test is usually performed at standard temperature and pressure, and in the practical application process, the explosion limit is easily affected by the initial temperature and pressure, and the pressure of the detection environment is generally basically equal to the normal pressure state, so that the influence of the initial temperature on the explosion limit of the combustible gas, namely the coefficient K, is considered.
Since the initial ambient temperature affects the chemical reaction rate, the temperature affects the explosion limit with a general rule that the lower explosion limit decreases and the upper explosion limit increases with increasing temperature, according to the correction formula for the lower explosion limit of the general range given by zabetake et al:
LEL（T）=[1-0.000721 (T-25)]*LEL 25
simplifying the definition of temperature influence coefficients:
K=1/[1-0.000721*(T-25)]；
Max is a big function;
risk classification is carried out, and judgment is carried out according to the comprehensive risk score R;
according to the establishment process of RC, RH and RT functions, when the independent risk value is taken to be 4, the personnel face the death risk, and when the independent risk value is taken to be 0, the personnel are in absolute safety, and because the influences of temperature, heat radiation and combustible gas limit on the personnel risk exist in parallel, the maximum value is taken according to the high and low of the risk value;
if R is more than or equal to 4, I grade red early warning is performed, and personnel are at high death risk;
if R is more than 4 and is more than or equal to 3, II is an orange warning, and personnel face a moderate death risk;
if R is more than 3 and is more than or equal to 2, III yellow warning is carried out, and personnel face a slight death risk;
if R is more than 2 and is more than or equal to 1, IV is blue, early warning is carried out, and personnel potentially face death risk in the environment for a long time;
if 1 is more than R, the environment is green and safe, and the personnel have no death risk in the environment for a long time.
The BIM data implementation method comprises the following steps:
BIM data related processes are divided into BIM data processing processes and intelligent helmet data calling and displaying processes, and BIM data needs to be preprocessed because:
the BIM data contains building detail information, and the complete BIM data of a building is about hundreds of G, so that a large amount of processing time is required for directly calling the level data when fire fighters enter the building.
The storage standard IFC standard of BIM data is only a framework standard, and each family has its own refinement format, so that unified processing is required to call when required.
The fire department can build a city building fire-fighting BIM database according to the needs, and mainly comprises building unit model information, fire-fighting facility data information and the like.
When a fire fighter enters a fire accident scene, the building BIM data can be displayed on the intelligent fire helmet; the specific flow is as follows:
the first step, the command center BIM processing server downloads the fire-fighting special BIM data of the building from the fire-fighting BIM database.
And calibrating the fire position by staff of the command center according to the alarm display coordinates.
And thirdly, after the fire fighter enters, the intelligent helmet is connected to the BIM information processing server through the base station, and the current position of the fire fighter is sent to the BIM information processing server.
Fourthly, the BIM information processing server transmits the processed vectorized BIM data (generally tens of kilobytes to hundreds of kilobytes) of the position to the intelligent fire-fighting helmet through the base station according to the position information of the fire fighter, and a vector data interpretation program contained in the intelligent fire-fighting helmet displays the data to the head-mounted near-to-eye display module 4 for display; the transmitted BIM data includes the following information:
a) Building information of the current position and information of surrounding fire-fighting facilities;
b) Marking the ignition position;
c) A safe traffic space path from the current location to the destination;
d) Optimal path to surrounding fire facilities.
And fifthly, after the fire fighter moves, updating the position information to the BIM information processing server, and jumping to the third step.
Sixth, fire fighters find that the fire condition is inconsistent with the sign, and can communicate with staff of the command center through voice intercom, and jump to the second step.
The laser/infrared gas detection module has the following processing flow:
the laser/infrared gas detection module can remotely detect the gas concentration, the detectable range is not less than 30 meters, and the embedded core board realizes the gas concentration detection of the surrounding environment by calling the function of the laser/infrared gas detection module, and the specific flow is as follows:
the first step, the embedded core board 7 sends an instruction to the laser/infrared gas detection module through the serial communication interface, and the laser/infrared gas detection module is required to start a gas detection function.
And the second step of laser/infrared gas detection module starts to detect surrounding gas components and concentration, and sends detection results to the embedded core board 7 through the serial communication interface after detection is completed.
And thirdly, after receiving the data, the embedded core board 7 analyzes the data according to the agreed protocol of the two parties to obtain the concentration of each gas.
Fourth step, the embedded core plate 7 calculates the risk level by comparing with a preset concentration risk level table.
Fifthly, if the dangerous level is larger than the set value, alarming is carried out through sound and the head-mounted near-to-eye display module.
And sixthly, if the detection needs to be continued, jumping to the first step.
The implementation method of the thermal imaging camera module comprises the following steps:
first, the embedded core board 7 starts the thermal imaging camera module 3 through the USB interface II.
And after the second step of starting the thermal imaging camera module 3, obtaining the ambient temperature and the image through a thermal imaging sensor, and processing the image into an image conforming to the fire control temperature marking standard.
And thirdly, the thermal imaging camera module sends data to the USB drive of the embedded core board 7 through the USB interface II.
And fourthly, calling the Android MediaPlayer plug-in by the application program to send the data from the USB driver to the display card driver.
And fifthly, the display card driver sends data to the head-mounted near-to-eye display module 4 through the chip hardware and the MIPI interface.
And sixthly, the head-mounted near-to-eye display module 4 displays the thermal imaging image through a prism.

Claims (5)

1. The intelligent fire-fighting helmet system for sensing and early warning of explosion accidents comprises a fire-fighting helmet (1), a remote combustible gas detector (2), a thermal imaging camera module (3), a head-mounted near-to-eye display module (4), a positioning instrument (5), a data communication transmission module (6), an embedded core board (7), an earphone (8), a base station (9) and a fire-fighting command center (10);
the fire-fighting helmet (1) comprises a helmet shell (1-1), a helmet hoop (1-2), a helmet support (1-3), a buffer layer (1-4), a face mask (1-5) and a cape (1-6); the lower extreme of helmet cap shell (1-1) is cap support (1-3), and the lower extreme of cap support (1-3) is cape (1-6), and the front end of helmet cap shell (1-1) is face guard (1-5), is equipped with cap hoop (1-2) and buffer layer (1-4) respectively in helmet cap shell (1-1), its characterized in that: the helmet comprises a helmet shell (1-1), wherein a silica gel honeycomb damping layer (1-7) is arranged on the inner surface of the helmet shell (1-1), a buffer layer (1-4) is arranged below the silica gel honeycomb damping layer (1-7), two earphones (8) are symmetrically arranged on two side walls in the helmet shell (1-1), a head-mounted near-to-eye display module (4) is arranged on one side of the inner surface of a face mask (1-5), a remote combustible gas detector (2), a thermal imaging camera module (3), a positioning instrument (5), a data communication transmission module (6) and an embedded core plate (7) are respectively arranged on the inner top surface of the helmet shell (1-1), and a lens of the thermal imaging camera module (3) and a sensor of the remote combustible gas detector (2) extend out of the helmet shell (1-1) respectively and are arranged right in front of the helmet shell (1-1);
The embedded core board (7) consists of a CPU, an MIPI interface, a USB interface I, a USB interface II, an SDIO interface, a serial communication interface and an SD card, wherein the CPU is respectively connected with the MIPI interface, the USB interface I, the USB interface II, the SDIO interface and the serial communication interface, and the SD card is inserted into the SDIO interface;
the data communication transmission module (6) consists of a wireless processor CPU, a radio frequency module and a built-in antenna, and the radio frequency module is respectively connected with the wireless processor CPU and the built-in antenna;
the thermal imaging camera module (3) consists of a camera chip, a video module and a thermal imaging sensor, and the camera chip is respectively connected with the video module and the thermal imaging sensor;
the remote combustible gas detector (2) is formed by connecting a laser/infrared gas detection module and an interface chip I;
the head-mounted near-to-eye display module (4) consists of an LCOS module, a display chip and a prism, and the display chip is respectively connected with the LCOS module and the prism;
the positioning instrument (5) consists of a gyroscope, a wireless module and an interface chip II, and the gyroscope and the wireless module are respectively connected with the interface chip II;
the circuit connection is that an MIPI interface of an embedded core board (7) is connected with a display chip of a head-mounted near-to-eye display module (4), a USB interface I is connected with a wireless processor CPU of a data communication transmission module (6), a USB interface II and a serial communication interface are respectively connected with a camera chip of a thermal imaging camera module (3), the serial communication interface is respectively connected with an interface chip II of a positioning instrument (5) and an interface chip I of a remote combustible gas detector (2), the data communication transmission module (6) sends or receives signals of a base station (9) through an internal antenna, and the base station (9) is connected with a fire command center (10);
The remote combustible gas detector (2) detects the concentration of combustible harmful gas within the range of not less than 30m away from the firefighter through the laser/infrared gas detection module;
the thermal imaging camera module (3) detects rescue environment and temperature distribution conditions of articles thereof through the video module and the thermal imaging sensor;
the head-mounted near-to-eye display module (4) projects real-time images, thermal images, BIM information, personnel position information and explosion risk early warning information to the retina of the human eye through a prism;
the positioning instrument (5) determines and transmits the position information of the firefighter;
the data communication transmission module (6) is communicated with the fire control command center (10) through the base station (9);
the embedded core board (7) realizes comprehensive processing and transmission of combustible gas concentration data, thermal imaging temperature data, personnel position information, explosion accident risk prediction and early warning information.
2. An implementation method of the intelligent fire-fighting helmet system for sensing explosion accidents and predicting risks and early warning by adopting the method disclosed in claim 1 is characterized in that:
the fire-fighting helmet (1) is worn on the head of a fire fighter, the helmet support (1-3) is used for fixing the face of the fire fighter, the tightness of the helmet hoop (1-2) in the helmet shell (1-1) is adjusted according to the head size of the person, the silica gel honeycomb shock-absorbing layer (1-7) is used for protecting the head of the person wearing the helmet, the impact force of external force on the head of the person wearing the helmet caused by impact is reduced, the buffer layer (1-4) further increases the comfort and safety of wearing the helmet, the earphones (8) on the two sides in the helmet shell (1-1) are arranged on the two ears of the fire fighter, the headset (8-1) connected with the earphones (8) are arranged in front of the fire fighter's mouth, the face mask (1-5) is worn in front of the fire fighter's face to provide safety protection, the head-wearing near-eye display module (4) on the inner face of the mask (1-5) is arranged in front of the eyes of the fire fighter, the cape (1-6) is buckled on the shoulders, and the neck of the fire fighter is protected;
Before a fire fighter enters a rescue building, a fire control command center (10) transmits building BIM information model data to an embedded core board (7) of a fire control helmet (1) through a network, the embedded core board (7) stores BIM data into an SD card through an SDIO interface so as to reduce the data volume transmitted by the fire fighter through the network after entering the building and improve the real-time exchange response speed of on-site information;
the positioning instrument (5) sends positioning information data to the embedded core board (7) at regular time through the serial port communication interface, the embedded core board (7) receives the data and then sends the positioning information to the fire control command center (10) through the built-in antenna of the data communication transmission module (6), the base station (9) combines the position and direction information of fire fighters and the harmful gas detection data and the thermal imaging data of the front end according to the positioning data and the BIM (building information model) of the building, the dangerous degree of each area is displayed in a three-dimensional map mode, the dangerous degree of each area is displayed through the embedded core board (7) and the head-mounted near-to-eye display module (4), meanwhile, the base station (9) sends the information to the fire control command center (10), and the fire control command center (10) controls a terminal computer to call building BIM information to generate a three-dimensional map comprising building model information, accident scene explosion dangerous distribution and firefighter position information content, and the three-dimensional map is displayed on a command center display screen;
When navigation is needed, a fire fighter carries out voice communication with a fire command center (10), the fire command center (10) assists fire fighters to set rescue destinations and select optimal rescue planning paths, meanwhile, the fire command center (10) sends navigation path information to an embedded core board (7) through a base station (9) and a data communication transmission module (6), the embedded core board (7) calls BIM information stored by an SD card to generate a three-dimensional map, marks the navigation paths and sends the navigation paths to a head-mounted near-to-eye display module (4) for display through an MIPI interface;
the remote combustible gas detector (2) detects the concentration of gas or combustible steam at the rescue accident site in real time, and the types of gas which can be detected remotely comprise methane, propane, ethylene, ethanol or CO flammable and explosive dangerous gases;
the remote flammable gas detector (2) sends the dangerous gas concentration data detected in real time to the embedded core board (7) through the serial communication interface, the CPU of the embedded core board (7) integrates and analyzes the received concentration data of the gas and the environmental thermal image data, a preset explosion risk calculation model and a preset method are adopted for quick prediction and evaluation, the explosion risk level of a corresponding area is calculated and analyzed, the risk level of an explosion accident and a dangerous early warning prompt of a region to be entered are provided for a firefighter, and the dangerous explosion risk level and the dangerous early warning prompt are projected and displayed by the head-mounted near-to-eye display module (4) in a color block labeling mode, so that a firefighter can see the displayed temperature, flammable and explosive gas components and concentration distribution, the explosion accident risk level and early warning prompt content;
Analyzing the collected dangerous gas concentration and environmental temperature data by adopting a preset explosion risk calculation model and method, calculating a risk value of a detection area, and identifying the dangerous gas concentration and environmental temperature data as a safe area by green when the risk value R is less than 1; when the risk value 2 is more than R and is more than or equal to 1, prompting as IV explosion risk early warning, and marking the area by blue; when the risk value 3 is more than R and is more than or equal to 2, prompting to be III explosion risk early warning, and marking the region with yellow; when the risk value is 4 & gtR & gtor more than 3, the warning is II risk early warning, and the area is marked with orange; when the risk value R is more than or equal to 4, prompting to be I-level risk early warning, and marking the region by dark red; the base station (9) calculates real-time risk results of different areas of the scene according to dangerous gas concentration, environmental thermal images and temperature information data acquired on the scene, sends the dangerous areas and the safe areas which are separated after analysis and calculation back to the embedded core board (7) and displays the dangerous display contents of the different areas through the head-mounted near-to-eye display module (4), meanwhile, the embedded core board (7) sends images, temperatures and dangerous gas concentration data to the fire control command center (10) through the built-in antenna of the data communication transmission module (6), and the fire control command center (10) makes relevant rescue treatment decisions according to the scene detection data and the risk analysis results, returns a command decision to the embedded core board (7) in real time and performs projection display through the head-mounted near-to-eye display module (4);
The thermal imaging camera module (3) sends the field image and the temperature data of the superimposed temperature data to the embedded core board (7), the USB interface transmits the video data superimposed by the video and the temperature data synthesized by the camera chip, the video data is compressed by using the H.264 standard, the serial communication interface transmits the temperature dot matrix data acquired by the thermal imaging sensor, the CPU of the embedded core board (7) decodes and displays the video data to the head-mounted near-to-eye display module (4) after receiving the video data, a fire fighter can know the environmental temperature distribution condition, and the combustible gas detection data, the thermal imaging data and the fire fighter position information collected by the embedded core board (7) are transmitted to the command center through the data communication transmission module (6) in a wireless manner by the base station (9);
the base station (9) displays the data collected by each firefighter in a centralized way, analyzes the data collected by the front end through a deep learning algorithm, and is used for a fire command center (10) and a front-end fire fighter to decide;
the method for determining the explosion risk level comprises the following steps:
the method comprises the steps of comprehensively calculating the angles of the frequent degree of accident occurrence, personnel exposure to dangerous environments and the consequences caused by accident occurrence, comparing the angles with threshold values respectively, determining the influence of three factors of combustible gas concentration C, temperature T and heat radiation H in a related building area on human bodies, giving different scores, multiplying the scores, and determining the dangerous grade of the area, wherein the calculation model formula of the accident area explosion risk grade is as follows:
Wherein:
RC is the dangerous value of the concentration of the combustible gas, is dimensionless, and is equal to C in percentage by weight 0 /(LEL 25 *0.25)；
RC＝C 0 /(LEL 25 *0.25 Indicating the possibility of a fire explosion accident due to the concentration of the combustible gas;
the explosion limit is a general term of the explosion lower limit and the explosion upper limit, the concentration of the combustible gas in the air can only explode between the explosion lower limit and the explosion upper limit, and the alarm concentration is generally set below 25% of the explosion lower limit LEL when the explosion risk early warning is carried out by the concentration of the explosive gas at present;
C 0 is the volume concentration of the combustible gas;
LEL 25 the lower explosion limit of the combustible gas at normal temperature and normal pressure is shown and is obtained by consulting physicochemical properties;
RT is a temperature hazard value, a dimensionless value and RT= |0.7063e 0.0152*T -1|*K1*K2；
RT＝|0.7063e 0.0152*T -1| (T is more than or equal to 0 ℃) represents a relative risk value of heat convection to human bodies due to high environmental temperature, flue gas temperature, and the high temperature threatens lives of rescue workers in accident environments, and hot air generated by flame can cause human body burns, heat collapse, dehydration and unsmooth breathing;
regarding the influence of the temperature of the flue gas on the human body, comprehensive literature shows that: the temperature exceeds 45 degrees, so that normal thinking and behaviors of a human body can be influenced; when the temperature is 60-65 ℃, people bear for a period of time, and the evacuation behavior is not affected; after 95 degrees, the skin tolerance temperature drops sharply; the limit temperature of human survival is 130 ℃, and beyond the temperature, the blood pressure is reduced, capillary vessels are destroyed, so that blood cannot circulate, and the central nerve of the brain is seriously destroyed to die; according to the standard definition of GB14200-2008 high temperature operation grading, more than 25 degrees of operation is defined as high temperature operation in production labor, so 25 degrees are set as a more comfortable state of a human body, 60 degrees are set as a safety threshold, and 130 degrees are set as the highest risk threshold; the human body acts for a long time at low temperature, and the high-temperature acting time is shorter; therefore, by combining RC definition, curve fitting is performed by adopting an exponential function to perform curve fitting, and meanwhile (95,2) is used as an auxiliary point for verification, and through the fitted curve, a temperature dangerous value RT is rapidly determined corresponding to a temperature value of a region acquired by thermal imaging;
The fire officer and the soldier can improve the high-temperature tolerance to a certain extent through certain fire-fighting and rescue training and wearing protective clothing, so that the life threat caused by high temperature to the firemen is reduced; referring to the ICI Monder method and the requirement of the road chemistry on the compensation coefficient, defining K1 as a protection coefficient, and if a rescue worker wears common protective clothing, the coefficient is 0.90; the fire-fighting suit for firefighters is worn, and the fire-resistant temperature is generally within 200 ℃ and the coefficient is 0.67; the fire-resistant temperature of the high-temperature protective clothing is generally about 800-1000 ℃ and the coefficient is 0.2; defining K2 as a training coefficient, wherein if firefighting rescue personnel are trained, the training coefficient is 0.95;
t is the ambient temperature;
k1 is a protection coefficient;
k2 is a human training coefficient;
RH is a thermal radiation risk value, dimensionless, rh=0.1571×h+0.0952;
rh=0.1571×h+0.0952, representing irreversible damage to human body due to heat radiation intensity; according to the related literature researches, the ambient heat radiation flux reaches 37.5KW/m 2 1% of people within 10s die, and 100% die after 1 min; up to 25KW/m 2 100% of people die after burn within 10s and 1 min; up to 12.5KW/m 2 1% of personnel die after being lightly injured within 10s and 1 min; up to 6.3KW/m 2 Personnel stay for 1min without radiation shielding measures; up to 4KW/m 2 Pain felt over 20 s; therefore, 5KW/m is adopted 2 As a safety threshold, 25 is used as a highest risk critical value to carry out curve fitting by adopting a linear relation in (0, 0), (5, 1) and (25,4), the heat radiation risk value of the environment is determined by measuring the heat radiation flux of the environment by using the fitting curve, and when RH=1, H=5.63 is the formula after fitting, and personnel are not in danger of life;
h is the heat radiation flux in the environment KW/m 2 ；
K is an influence coefficient and represents the influence of temperature on the limit of explosive gas;
the explosion limit test is usually carried out under standard temperature and pressure, and in the practical application process, the explosion limit is easily influenced by the initial temperature and pressure, and the pressure of the detection environment is generally equal to the normal pressure state, so the influence of the initial temperature on the explosion limit of the combustible gas, namely the coefficient K, is mainly considered;
since the initial ambient temperature affects the chemical reaction rate, the temperature affects the explosion limit with a general rule that the lower explosion limit decreases and the upper explosion limit increases with increasing temperature, according to the correction formula for the lower explosion limit of the general range given by zabetake et al:
LEL(T)＝[1-0.000721(T-25)]*LEL 25
simplifying the definition of temperature influence coefficients:
K＝1/[1-0.000721*(T-25)]；
Max is a big function;
risk classification is carried out, and judgment is carried out according to the comprehensive risk score R;
according to the establishment process of RC, RH and RT functions, when the independent risk value is taken to be 4, the personnel face the death risk, and when the independent risk value is taken to be 0, the personnel are in absolute safety, and because the influences of temperature, heat radiation and combustible gas limit on the personnel risk exist in parallel, the maximum value is taken according to the high and low of the risk value;
if R is more than or equal to 4, I grade red early warning is performed, and personnel are at high death risk;
if R is more than 4 and is more than or equal to 3, II is an orange warning, and personnel face a moderate death risk;
if R is more than 3 and is more than or equal to 2, III yellow warning is carried out, and personnel face a slight death risk;
if R is more than 2 and is more than or equal to 1, IV is blue, early warning is carried out, and personnel potentially face death risk in the environment for a long time;
if 1 is more than R, the environment is green and safe, and the personnel have no death risk in the environment for a long time.
3. The method for realizing the intelligent fire-fighting helmet system for sensing explosion accidents and predicting risk according to claim 2, wherein the method for realizing BIM data is as follows:
BIM data related flow is divided into BIM data processing flow and intelligent helmet data calling and displaying flow, BIM data are preprocessed:
the BIM data comprises detailed information of a building, the whole BIM data of a building is about hundreds of G, and a large amount of processing time is required for directly calling the level data when a fire fighter enters the building;
The storage standard IFC standard of BIM data is only a frame standard, and each family has a refined format, so that unified processing is needed to be called when needed;
the fire department establishes a city building fire-fighting BIM database according to the need, and mainly comprises building unit model information and fire-fighting facility data information content;
when a fire fighter enters a fire accident scene, the building BIM data is displayed on the intelligent fire helmet; the specific flow is as follows:
firstly, a command center BIM information processing server downloads fire-fighting special BIM data of a building from a fire-fighting BIM database; secondly, staff in the command center marks the fire position according to the alarm display coordinates;
thirdly, after a fire fighter enters, the intelligent helmet is connected to the BIM information processing server through the base station, and the current position of the fire fighter is sent to the BIM information processing server;
fourthly, the BIM information processing server displays the processed vectorized BIM data of the position of the fire fighter to tens of kilobytes to hundreds of kilobytes according to the position information of the fire fighter, the vectorized BIM data are transmitted to the intelligent fire fighting helmet through the base station, and a vector data interpretation program contained in the intelligent fire fighting helmet displays the data to a head-mounted near-to-eye display module (4) for display; the transmitted BIM data includes the following information:
a) Building information of the current position and information of surrounding fire-fighting facilities;
b) Marking the ignition position;
c) A safe traffic space path from the current location to the destination;
d) Optimal path to surrounding fire facilities;
fifthly, after the fire fighter moves, updating the position information to the BIM information processing server, and jumping to the third step;
sixth, fire fighters find that the fire condition is inconsistent with the sign, communicate with staff of the command center through voice intercom, and jump to the second step.
4. The method for realizing the intelligent fire-fighting helmet system for sensing explosion accidents and predicting risk according to claim 2, wherein the processing flow of the laser/infrared gas detection module is as follows:
the laser/infrared gas detection module can remotely detect the gas concentration, the detection range is not less than 30 meters, and the embedded core board realizes the gas concentration detection of the surrounding environment by calling the functions of the laser/infrared gas detection module, and the specific flow is as follows: the first step, the embedded core board (7) sends an instruction to the laser/infrared gas detection module through the serial communication interface, and the laser/infrared gas detection module is required to start a gas detection function;
The second step of starting to detect surrounding gas components and concentration by the laser/infrared gas detection module, and sending detection results to the embedded core board (7) through the serial communication interface after detection is completed;
thirdly, after receiving the data, the embedded core board (7) analyzes the data according to the protocol agreed by the two parties to obtain the concentration of each gas;
fourthly, calculating by the embedded core board (7) through a comparison table with a preset concentration risk level to obtain a risk level;
fifthly, if the danger level is greater than the set value, alarming through sound and the head-mounted near-to-eye display module;
and sixthly, if the detection needs to be continued, jumping to the first step.
5. The method for realizing the intelligent fire-fighting helmet system for sensing explosion accidents and predicting risk and early warning according to claim 2 is characterized in that the method for realizing the thermal imaging camera module is as follows:
firstly, starting a thermal imaging camera module (3) by an embedded core board (7) through a USB interface II;
after the second step of floating and thermal imaging camera module (3) is started, obtaining the surrounding temperature and the image through a thermal imaging sensor, and processing the image into an image which accords with the fire control temperature marking standard;
thirdly, the thermal imaging camera module sends data to a USB driver of the embedded core board (7) through a USB interface II;
Fourth step, calling the Android MediaPlayer plug-in by the application program to send data from the USB driver to the display card driver;
fifthly, the display card drives to send data to the head-mounted near-to-eye display module (4) through the chip hardware and the MIPI interface;
and step six, a head-mounted near-to-eye display module (4) displays the thermal imaging image through a prism.
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