CN115294718A - Fire early warning system based on multisource data fusion - Google Patents
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B17/00—Fire alarms; Alarms responsive to explosion
- G08B17/06—Electric actuation of the alarm, e.g. using a thermally-operated switch
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B17/00—Fire alarms; Alarms responsive to explosion
- G08B17/10—Actuation by presence of smoke or gases, e.g. automatic alarm devices for analysing flowing fluid materials by the use of optical means
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B17/00—Fire alarms; Alarms responsive to explosion
- G08B17/12—Actuation by presence of radiation or particles, e.g. of infrared radiation or of ions
- G08B17/125—Actuation by presence of radiation or particles, e.g. of infrared radiation or of ions by using a video camera to detect fire or smoke
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B25/00—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems
- G08B25/01—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems characterised by the transmission medium
- G08B25/08—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems characterised by the transmission medium using communication transmission lines
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Abstract
The invention relates to the field of fire monitoring, in particular to a fire early warning system based on multi-source data fusion, which comprises temperature sensing nodes, smoke sensing nodes, flame sensing nodes and surrounding environment access nodes which are arranged in a monitoring area, wherein each sensing node transmits data to a sink node in a dynamic routing and multi-hop transmission mode, the sink node is communicated with a PC (personal computer) through a GPRS (general packet radio service) technology, and the PC is used for fusing fire parameters fed back by each sensing node to realize monitoring and early warning of fire in a corresponding area and obtain the type, the coverage area and a surrounding environment dynamic feedback graph of the fire in the current area. The invention can quickly find fire or fire safety hidden danger in the monitoring area and realize comprehensive visualization of the field situation.
Description
Technical Field
The invention relates to the field of fire monitoring, in particular to a fire early warning system based on multi-source data fusion.
Background
With the development of economic construction in China, various fire hazards are increased year by year. Once a fire occurs, the serious consequences of group death and disastrous economic loss are easily caused. The fire early warning aims to accurately discover hidden fire hazards as early as possible and give an alarm in time so as to take corresponding measures to control the occurrence and development of fire. At present, the automatic fire alarm system in China basically relies on a single sensor to monitor fire information, such as temperature alarm, smoke alarm and fire alarm, the obtained fire characteristics are few in types, greatly influenced by factors such as environment and the like, the reliability is low, and false alarm are easy to occur. Moreover, most of the fire alarm systems adopt a threshold alarm mode, and only after a fire breaks out, the fire alarm systems can stimulate response and do not have an early warning function, so that the original purpose of the original design is violated.
Disclosure of Invention
Aiming at the problems, the invention provides a fire early warning system based on multi-source data fusion, which can quickly find fire or fire safety hidden dangers existing in a monitoring area and realize comprehensive visualization of field conditions.
In order to achieve the purpose, the invention adopts the technical scheme that:
a fire early warning system based on multi-source data fusion comprises temperature sensing nodes, smoke sensing nodes, fire sensing nodes and surrounding environment access nodes which are arranged in a monitoring area, wherein each sensing node transmits data to a gathering node in a dynamic routing and multi-hop transmission mode, the gathering node is communicated with a PC (personal computer) through the GPRS technology, and the PC is used for fusing fire parameters fed back by each sensing node, monitoring and early warning of fire in a corresponding area are realized, and the type, the coverage area and a surrounding environment dynamic feedback graph of the fire in the current area are obtained.
Furthermore, the temperature sensing node adopts a dual-spectrum video collector for realizing the sensing of the temperature of the current area and realizing the positioning of the flame in cooperation with the flame sensing node.
Furthermore, the smoke sensing node comprises an ion smoke detector, a smoke type identification model and an electrochemical gas sensor group, and when the ion smoke detector monitors smoke, the electrochemical gas sensor group works to monitor gas components in the current environment; the smoke type identification model acquires the smoke type through identification of a smoke generation source, the color of the smoke and the coverage range of the smoke in the smoke image by means of a smoke image acquired by a visual sensor of a flame sensing node and/or a camera erected in a current area.
Further, the flame sensing node monitors the flame in the current area based on a visual sensor and a preset flame identification model. The fire identification model can adopt a DSOD (digital differential optical density) Xception coco model, the model adopts a DSOD target detection algorithm, when a certain fire sensing node finds a fire, other fire sensing nodes and cameras around the certain fire sensing node automatically adjust an image acquisition angle to the position of the current fire, wherein the camera meeting the requirements can be automatically accessed into the system, and therefore the calculation of acquiring the fire coverage area is assisted.
Further, the surrounding environment access node is used for accessing combustible materials, dangerous equipment, fire fighting equipment and door and window layout maps in the current area.
Further, the PC is loaded with a data post-processing system, which includes:
the fire type identification module is used for identifying the current fire type based on gas component parameters fed back by the electrochemical gas sensor group;
the fire disaster coverage area calculation module is used for realizing the calculation of the fire disaster coverage area based on the current fire disaster scene image fed back by the fire disaster sensing node and the camera; specifically, firstly, acquiring images of flames collected from different angles, then acquiring depth images of the flames based on a kinect depth sensor, triangulating the acquired current flame depth images, then fusing a layered directional distance field constructed by all the triangulated depth images in a scale space, applying an integral triangulation algorithm to all voxels in the distance field to generate a convex hull covering all the voxels, constructing an equivalent surface by using a Marching Tetrahedra algorithm, thereby completing three-dimensional reconstruction to obtain a three-dimensional flame model, finally placing the three-dimensional flame models in the same three-dimensional coordinate system, realizing splicing of all the three-dimensional flame models to obtain an integral three-dimensional flame model, and measuring the size of the integral three-dimensional flame model to obtain the fire coverage area;
the dynamic feedback graph generating module is used for generating a surrounding environment three-dimensional dynamic feedback graph of each time point according to the obtained flame integral three-dimensional model, the information of the geographic position of the flame, and parameters of combustible, dangerous equipment, fire fighting equipment, door and window layout graphs and the like of the current area accessed by the surrounding environment access node;
and the fire early warning module is used for fusing the fire parameters fed back by each node to obtain a fused fire early warning probability value, and generating a corresponding early warning short message when the obtained probability value is greater than a preset threshold value to realize fire early warning.
Further, different surrounding environments are configured with different temperature safety thresholds, smoke safety thresholds and gas composition safety thresholds, and the read temperature parameters, smoke generation source parameters, smoke color parameters, smoke coverage range parameters and gas composition parameters are subjected to information fusion based on an improved D-S evidence theory data fusion algorithm to obtain fused fire early warning probability values.
The invention has the following beneficial effects:
the fire disaster or fire hazard safety hazard in the monitoring area can be quickly found;
the comprehensive visualization of the fire type, the fire coverage area, the surrounding environment and the like can be realized, and the reasonable formulation of a fire extinguishing scheme is guaranteed;
and a multi-parameter joint monitoring mode can avoid a blind area of fire monitoring as much as possible.
Drawings
Fig. 1 is a system block diagram of a fire early warning system based on multi-source data fusion according to an embodiment of the present invention.
Fig. 2 is a block diagram of a data post-processing system according to an embodiment of the present invention.
Fig. 3 is a schematic diagram of the operation of the fire warning module according to the embodiment of the present invention.
Detailed Description
The present invention will be described in detail with reference to specific examples. The following examples will aid those skilled in the art in further understanding the present invention, but are not intended to limit the invention in any manner. It should be noted that variations and modifications can be made by persons skilled in the art without departing from the spirit of the invention. All falling within the scope of the present invention.
As shown in fig. 1, an embodiment of the present invention provides a fire early warning system based on multi-source data fusion, including:
the temperature sensing node adopts a double-spectrum video collector and is used for realizing the sensing of the current area temperature and realizing the positioning of the flame in cooperation with the flame sensing node; meanwhile, the device is also used for assisting in realizing the evaluation of the flame size, namely the fire behavior when each visual sensor and the camera cannot acquire flame images;
the smoke sensing node comprises an ion smoke sensing detector, a smoke type identification model and an electrochemical gas sensor group, wherein when the ion smoke sensing detector monitors smoke, the electrochemical gas sensor group works and is used for monitoring gas components in the current environment; the smoke type identification model acquires the smoke type through identification of a smoke generation source, the color of smoke and the coverage range of the smoke in a smoke image by means of a smoke image acquired by a visual sensor of a flame sensing node and/or a camera erected in a current area;
and the flame sensing node realizes the monitoring of the flame in the current area based on the visual sensor and a preset flame identification model. The flame recognition model can adopt a DSOD Xceptance coco model, the model adopts a DSOD target detection algorithm, a coco data set is used for pre-training an Xceptance neural network, then the model is trained by a previously prepared data set, various parameters in the deep neural network are finely adjusted, and finally a proper model for detecting the flame is obtained; when a certain flame sensing node finds a flame, other flame sensing nodes and cameras around the certain flame sensing node automatically adjust an image acquisition angle to the position of the current flame, wherein the cameras meeting the requirements can be automatically accessed into the system, so that the calculation of acquiring the fire covering area is assisted;
the surrounding environment access node is used for accessing combustible materials, dangerous equipment, fire fighting equipment and door and window layout diagrams in the current area;
the data are transmitted to the sink nodes by the sensing nodes in a dynamic routing and multi-hop transmission mode, the sink nodes are communicated with the PC through the GPRS technology, the PC is used for fusing fire parameters fed back by the sensing nodes, monitoring and early warning of fire in the corresponding area are achieved, and the type, the coverage area and the surrounding environment dynamic feedback graph of the fire in the current area are obtained.
As shown in fig. 2, the PC is loaded with a data post-processing system, which includes:
the fire type identification module is used for identifying the current fire type based on gas composition parameters fed back by the electrochemical gas sensor group;
the fire coverage area calculation module is used for realizing the calculation of the fire coverage area based on the current fire scene image fed back by the fire sensing node and the camera; specifically, firstly, acquiring images of flames collected from different angles, then acquiring depth images of the flames based on a kinect depth sensor, triangulating the acquired current depth images of the flames, then fusing all triangulated depth images in a scale space to construct a layered directional distance field, applying an integral triangulation algorithm to all voxels in the distance field to generate a convex hull covering all the voxels, constructing an isosurface by using a Marchang Tetrahedra algorithm, thereby completing three-dimensional reconstruction to obtain a three-dimensional model of the flames, finally placing the three-dimensional models of the flames in the same three-dimensional coordinate system, realizing splicing of the three-dimensional models of the flames to obtain an integral three-dimensional model of the flames, and measuring the size of the integral three-dimensional model of the flames to obtain a fire covering area;
the dynamic feedback graph generating module is used for generating a surrounding environment three-dimensional dynamic feedback graph of each time point according to the obtained flame integral three-dimensional model, the information of the geographic position of the flame, and parameters of combustible, dangerous equipment, fire fighting equipment, door and window layout graphs and the like of the current area accessed by the surrounding environment access node;
the fire early warning module is used for fusing the fire parameters fed back by each node to obtain a fused fire early warning probability value, and generating a corresponding early warning short message when the obtained probability value is greater than a preset threshold value to realize fire early warning; specifically, different surrounding environments are configured with different temperature safety thresholds, smoke safety thresholds and gas component safety thresholds, as shown in fig. 3, information fusion is performed on the read temperature parameters, smoke generation source parameters, smoke color parameters, smoke coverage range parameters and gas component parameters based on an improved D-S evidence theory data fusion algorithm, and a fused fire early warning probability value is obtained.
The foregoing description of specific embodiments of the present invention has been presented. It is to be understood that the present invention is not limited to the specific embodiments described above, and that various changes or modifications may be made by one skilled in the art within the scope of the appended claims without departing from the spirit of the invention. The embodiments and features of the embodiments of the present application may be combined with each other arbitrarily without conflict.
Claims (7)
1. The utility model provides a fire early warning system based on multisource data fusion which characterized in that: the fire disaster early warning system comprises temperature sensing nodes, smoke sensing nodes, fire disaster sensing nodes and surrounding environment access nodes which are arranged in a monitoring area, wherein each sensing node transmits data to a sink node in a dynamic routing and multi-hop transmission mode, the sink node is communicated with a PC (personal computer) through a GPRS (general packet radio service) technology, and the PC is used for fusing fire disaster parameters fed back by each sensing node, realizing monitoring and early warning of fire disasters in a corresponding area and obtaining the type, coverage area and surrounding environment dynamic feedback graph of fire disasters in the current area.
2. The fire early warning system based on multi-source data fusion of claim 1, wherein: the temperature sensing node adopts a dual-spectrum video collector and is used for sensing the temperature of the current area and realizing the positioning of the flame in cooperation with the flame sensing node.
3. The fire early warning system based on multi-source data fusion of claim 1, wherein: the smoke sensing node comprises an ion smoke detector, a smoke type identification model and an electrochemical gas sensor group, and when the ion smoke detector monitors smoke, the electrochemical gas sensor group works to monitor gas components in the current environment; the smoke type identification model acquires the smoke type through identification of a smoke generation source, the color of the smoke and the coverage range of the smoke in the smoke image by means of a smoke image acquired by a visual sensor of a flame sensing node and/or a camera erected in a current area.
4. The fire early warning system based on multi-source data fusion of claim 1, wherein: the flame sensing node realizes the monitoring of the flame in the current area based on a visual sensor and a preset flame identification model. The fire identification model can adopt a DSOD (digital differential optical density) Xception coco model, the model adopts a DSOD target detection algorithm, when a certain fire sensing node finds a fire, other fire sensing nodes and cameras around the certain fire sensing node automatically adjust an image acquisition angle to the position of the current fire, wherein the camera meeting the requirements can be automatically accessed into the system, and therefore the calculation of acquiring the fire coverage area is assisted.
5. The fire early warning system based on multi-source data fusion of claim 1, wherein: and the surrounding environment access node is used for accessing combustible materials, dangerous equipment, fire fighting equipment and door and window layout maps in the current area.
6. The fire early warning system based on multi-source data fusion of claim 1, wherein: the PC is loaded with a data post-processing system, comprising:
the fire type identification module is used for identifying the current fire type based on gas composition parameters fed back by the electrochemical gas sensor group;
the fire coverage area calculation module is used for realizing the calculation of the fire coverage area based on the current fire scene image fed back by the fire sensing node and the camera; specifically, firstly, acquiring images of flames collected from different angles, then acquiring depth images of the flames based on a kinect depth sensor, triangulating the acquired current depth images of the flames, then fusing all triangulated depth images in a scale space to construct a layered directional distance field, applying an integral triangulation algorithm to all voxels in the distance field to generate a convex hull covering all the voxels, constructing an isosurface by using a Marchang Tetrahedra algorithm, thereby completing three-dimensional reconstruction to obtain a three-dimensional model of the flames, finally placing the three-dimensional models of the flames in the same three-dimensional coordinate system, realizing splicing of the three-dimensional models of the flames to obtain an integral three-dimensional model of the flames, and measuring the size of the integral three-dimensional model of the flames to obtain a fire covering area;
the dynamic feedback graph generating module is used for generating a three-dimensional dynamic feedback graph of the surrounding environment of each time point according to the obtained three-dimensional model of the whole flame, the information of the geographic position of the flame, and the layout graphs of combustible, dangerous equipment, fire fighting equipment and doors and windows of the current area accessed by the surrounding environment access node;
and the fire early warning module is used for fusing the fire parameters fed back by the nodes to obtain a fused fire early warning probability value, and generating a corresponding early warning short message when the obtained probability value is greater than a preset threshold value to realize fire early warning.
7. The fire early warning system based on multi-source data fusion of claim 6, wherein: different surrounding environments are configured with different temperature safety thresholds, smoke safety thresholds and gas composition safety thresholds, and the read temperature parameters, smoke generation source parameters, smoke color parameters, smoke coverage range parameters and gas composition parameters are subjected to information fusion based on an improved D-S evidence theory data fusion algorithm to obtain a fused fire early warning probability value.
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Cited By (1)
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| CN117370751A (en) * | 2023-09-13 | 2024-01-09 | 浙江天禹信息科技有限公司 | Cross-validation hydrologic data elasticity monitoring method and system |
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