CN103150856A - Fire flame video monitoring and early warning system and fire flame detection method - Google Patents
Fire flame video monitoring and early warning system and fire flame detection method Download PDFInfo
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Abstract
The invention discloses a fire flame video monitoring and early warning system and a fire flame detection method. The fire flame video monitoring and early warning system comprises a network video CCD (Charge Coupled Device) camera, a video management module, a fire flame detection subsystem and an early warning subsystem. The fire flame detection method performs information integration of the static and dynamic features of fire flames and provides a fire judgment algorithm based on a neural network and D-S (Dempster-Shafer) evidence judgment, the algorithm can provide three early warning threshold values according to the magnitude of a fire, and the three early warning threshold values correspond to three levels of early warning modes, i.e. on-scene sound and light warning, remote short message warning and network warning. The invention provides the fire flame video monitoring system which monitors early small fire sources and judges the fire flame level on the basis of multi-feature information integration, and has the advantages of strong anti-interference capability, high space adaptability, high fire early warning accuracy and low false warning rate.
Description
Technical field
The invention belongs to public safety field, relate to the fire monitoring early warning system, be specifically related to a kind of fire disaster flame video monitor and early warning system and fire disaster flame detection method.
Background technology
Fire is the major hidden danger that threatens human survival, and especially in recent years, the fire that takes place frequently has caused great Loss of Life and property to people.According to statistics, China was total to 125402 of breaking out of fires in 2011, caused 1106 people dead, 19.8 hundred million yuan of direct economic losses.The wildfire that in June, 2011, Shanghai occured causes 58 people dead, 1.58 hundred million yuan of direct economic losses.Find in time the fire source and in time take effective fire protection to put out incipient flame, can greatly reduce various losses.
Fire detector has approximately experienced from the development course of heat detector → ion smoke detector → optical detector of fire smoke → air-sensitive detector → infrared eye → video detector as the core component of fire early-warning system.Be mainly used in indoor fire detection among a small circle as the temperature-sensitive of traditional fire detector, sense cigarette, air-sensitive class detector, have that the space applicability is limited, information reliability is poor, be subject to the shortcoming such as external interference.And infrared eye is expensive, has limited its usable range.Video detector is a kind of take the fire detector of image processing techniques as the basis, utilize camera supervised monitoring point sight, by the video information that catches is processed, analyzed, and then realize the detection of fire disaster flame and the early warning of fire, antijamming capability is stronger, and the space applicability is strong.In the video fire hazard early warning technology, the fire disaster flame detection method is core, although domestic expert was carrying out certain research and development to the video fire hazard flame detecting method in recent years, proven technique rarely has application, and corresponding product also seldom emerges.
Summary of the invention
The object of the invention is to: a kind of fire disaster flame video monitor and early warning system and fire disaster flame detection method are provided, it is the fire disaster flame video frequency monitoring system of the trickle burning things which may cause a fire disaster of monitoring during Initial Stage of Fire, and the differentiation of fire disaster flame rank is carried out in fusion based on multicharacteristic information, antijamming capability is strong, the space applicability is strong, the fire alarm accuracy is high, and rate of false alarm is low.
Technical solution of the present invention is: fire disaster flame video monitor and early warning system adopts the distributed system architecture of Internet of Things to dispose, and is comprised of Internet video CCD camera, video management module, fire disaster flame detection subsystem and early warning subsystem; Described Internet video CCD camera is responsible for completing imaging, supports the WiFi wireless transmission, supports simultaneously TCP/IP network remote image transmitting, and has the detection of dynamic recording function; Described video management module adopts the generic video administration module; Described fire disaster flame detection subsystem is obtained the realtime graphic of Internet video CCD camera by image pick-up card, after processing the acquisition image with digital image processing techniques, whether call the fire disaster flame discriminating program, providing has the judgement of condition of a fire conclusion, if there is the condition of a fire to provide other judgement conclusion of condition of a fire level; Described early warning subsystem adopts three grades of modes of warnings, i.e. on-the-spot acousto-optic early warning, remote short messages breath early warning and Network Warning; When the one-level condition of a fire occured, the voice guard and the warning light that are arranged in the monitoring point in monitored district were responsible for realizing on-the-spot acousto-optic early warning, and alarm command is independently assigned by the monitoring site control module; When finding the secondary condition of a fire by Java Servlet real time access early warning database and in the monitoring point, the Android handset server ceases early warning to specifying the person liable to send the early warning short message to realize remote short messages; Wireless transmission is utilized the WiFi technology, and encrypted transmission is adopted in the transmission of early warning data, guarantees the security of data; When the condition of a fire of passing on when the fire disaster flame detection system reaches Senior Three level, jump out warning window and picture, realize network alarming, and it is live to transmit on-the-spot fire.
The present invention also proposes a kind of fire disaster flame detection method, Static and dynamic feature to fire disaster flame is carried out information fusion, provide a kind of fire based on neural network and the judgement of D-S evidence and differentiate algorithm, this algorithm can provide three threshold value of warning according to condition of a fire size, and three the corresponding on-the-spot sound and light alarms of threshold value of warning, long-range short messages are reported to the police and these three other modes of warnings of level of network alarming; Specific as follows:
Step 1: described Internet video CCD camera is completed field imaging, and the digital picture at the scene that image pick-up card acquisition Internet video CCD camera transmits utilizes digital image processing techniques to carry out pre-service to this digital picture;
Step 2: utilize gray scale thresholding technology by the motion feature of the variation detection of fires flame of the gray scale thresholding of two two field pictures before and after comparing; The area change feature whether the growth detection fire disaster flame is arranged by two two field picture flame area before and after comparing; Flame detection color characteristic in the HIS color space; Realize differentiation to naturally light and daylight lamp monochrome information background interference by the circularity feature of extracting fire disaster flame; Extract the wedge angle number of fire disaster flame, the wedge angle number that utilizes fire disaster flame along with the characteristics that present irregular rule burning time with the variation of the wedge angle number of fire disaster flame as one of Fire Criterion; Fire disaster flame burning initial stage predominant frequency is in 12Hz, and the variation of surrounding environment is not remarkable to frequency influence, therefore extracts the blinking characteristics of fire disaster flame as one of Fire Criterion;
Step 3: gather the fire disaster flame data sample of monitoring point, select in advance weights and the threshold value of the fire disaster flame data sample of monitoring point being trained these four kinds of fire disaster flame features of flicker frequency feature of the wedge angle number of the circularity feature that obtains to comprise fire disaster flame color characteristic, fire disaster flame, fire disaster flame and fire disaster flame;
Step 4: utilize formula (1) to obtain the fire disaster flame threshold value of warning:
In formula:
Be
iIndividual fire disaster flame feature output,
,
H 0Expression is without fire disaster flame,
H 1Expression has fire disaster flame;
,
m i (H
0) and
m i (
H 1) be
iThe detection probability of individual fire disaster flame feature and probability of miscarriage of justice;
Step 5: utilize above-mentioned detected real-time threshold value and empirical value to realize that relatively fire disaster flame detects and early warning in real time.
Advantage of the present invention is:
1, adopt the distributed system architecture of Internet of Things to dispose, the space applicability is strong, both can be used for warehouse, indoor fire monitoring and the early warning among a small circle of laboratory class, also can be used for the monitoring of forest class large-range fire disaster and early warning.
2, Adoption Network video CCD camera obtains the monitoring point image, utilizes digital image processing techniques to make early warning system that higher antijamming capability and networked Characteristics be arranged, and to compare cost performance higher with infrared fire hazard monitoring system.
3, the Static and dynamic feature of fire disaster flame is carried out information fusion, provide a kind of fire based on neural network and the judgement of D-S evidence and differentiate algorithm, the early warning of energy Quick, False Rate is lower.
4, adopt three grades of fire disaster flame early warning subsystems, can realize that early warning system is intelligent by flame real-time according to the scene, scientific and reasonable and manpower, financial resources when dispatching in an orderly manner fire and occuring.
Description of drawings
Fig. 1 is fire disaster flame video monitor and early warning system structural representation of the present invention.
Fig. 2 is fire disaster flame image detection process flow diagram.
Fig. 3 is many features fire disaster flame detection method schematic diagram.
Embodiment
Below in conjunction with description of drawings technical solution of the present invention.
As shown in Figure 1, fire disaster flame video monitor and early warning system adopts the distributed system architecture of Internet of Things to dispose, and is comprised of Internet video CCD camera, video management module, fire disaster flame detection subsystem and early warning subsystem; Described Internet video CCD camera is responsible for completing imaging, supports the WiFi wireless transmission, supports simultaneously TCP/IP network remote image transmitting, and has the detection of dynamic recording function; Described video management module adopts the generic video administration module; Described fire disaster flame detection subsystem is obtained the realtime graphic of Internet video CCD camera by image pick-up card, after processing the acquisition image with digital image processing techniques, whether call the fire disaster flame discriminating program, providing has the judgement of condition of a fire conclusion, if there is the condition of a fire to provide other judgement conclusion of condition of a fire level; Described early warning subsystem adopts three grades of modes of warnings, i.e. on-the-spot acousto-optic early warning, remote short messages breath early warning and Network Warning; When the one-level condition of a fire occured, the voice guard and the warning light that are arranged in the monitoring point in monitored district were responsible for realizing on-the-spot acousto-optic early warning, and alarm command is independently assigned by the monitoring site control module; When finding the secondary condition of a fire by Java Servlet real time access early warning database and in the monitoring point, the Android handset server ceases early warning to specifying the person liable to send the early warning short message to realize remote short messages; Wireless transmission is utilized the WiFi technology, and encrypted transmission is adopted in the transmission of early warning data, guarantees the security of data; When the condition of a fire of passing on when the fire disaster flame detection system reaches Senior Three level, jump out warning window and picture, realize network alarming, and it is live to transmit on-the-spot fire.
As shown in Fig. 2,3, the fire disaster flame detection method is that the Static and dynamic feature of fire disaster flame is carried out information fusion, provide a kind of fire based on neural network and the judgement of D-S evidence and differentiate algorithm, this algorithm can provide three threshold value of warning according to condition of a fire size, and three the corresponding on-the-spot sound and light alarms of threshold value of warning, long-range short messages are reported to the police and these three other modes of warnings of level of network alarming; Specific as follows:
Step 1: described Internet video CCD camera is completed field imaging, and the digital picture at the scene that image pick-up card acquisition Internet video CCD camera transmits utilizes digital image processing techniques to carry out pre-service to this digital picture;
Step 2: utilize gray scale thresholding technology by the motion feature of the variation detection of fires flame of the gray scale thresholding of two two field pictures before and after comparing; The area change feature whether the growth detection fire disaster flame is arranged by two two field picture flame area before and after comparing; Flame detection color characteristic in the HIS color space; Realize differentiation to naturally light and daylight lamp monochrome information background interference by the circularity feature of extracting fire disaster flame; Extract the wedge angle number of fire disaster flame, the wedge angle number that utilizes fire disaster flame along with the characteristics that present irregular rule burning time with the variation of the wedge angle number of fire disaster flame as one of Fire Criterion; Fire disaster flame burning initial stage predominant frequency is in 12Hz, and the variation of surrounding environment is not remarkable to frequency influence, therefore extracts the blinking characteristics of fire disaster flame as one of Fire Criterion;
Step 3: gather the fire disaster flame data sample of monitoring point, select in advance weights and the threshold value of the fire disaster flame data sample of monitoring point being trained these four kinds of fire disaster flame features of flicker frequency feature of the wedge angle number of the circularity feature that obtains to comprise fire disaster flame color characteristic, fire disaster flame, fire disaster flame and fire disaster flame;
Step 4: utilize formula (1) to obtain the fire disaster flame threshold value of warning:
In formula:
Be
iIndividual fire disaster flame feature output,
,
H 0Expression is without fire disaster flame,
H 1Expression has fire disaster flame;
,
m i (H
0) and
m i (
H 1) be
iThe detection probability of individual fire disaster flame feature and probability of miscarriage of justice;
Step 5: utilize above-mentioned detected real-time threshold value and empirical value to realize that relatively fire disaster flame detects and early warning in real time.
The fire disaster flame early warning system is divided into perception terminal, data collection and analysis layer and three parts of terminal application platform, perception terminal comprises by The Cloud Terrace and is arranged on high resolution CCD video camera, voice guard and warning light in the monitoring point in monitored district, the data collection and analysis layer comprises video frequency collection card, Mysql database and the Android handset server in the computing machine that is arranged on each monitoring point, and terminal application platform is to have being connected to the Internet and having the computing machine of public network IP address of data processing function; Ccd video camera is responsible for completing sight imaging in the monitoring point, image pick-up card gathers image that ccd video camera becomes, by the video management module, the digital picture that reads is carried out pre-service successively, each feature extraction utilizes multicharacteristic information blending algorithm output early warning information; Adopt three grades of modes of warnings according to condition of a fire size, comprise on-the-spot acousto-optic early warning, long-range short message early warning and Network Warning; During Initial Stage of Fire, alarm command is independently assigned or is assigned by Surveillance center by the monitoring site control module, the voice guard and the warning light that are arranged in the monitoring point in monitored district are responsible for realizing on-the-spot acousto-optic early warning, select to start simple and easy fire protection and eliminate the condition of a fire, or can hear that the person liable of alarm song adopts manual type to eliminate the condition of a fire near being positioned at the monitoring point; If the condition of a fire does not weaken, start long-range short message modes of warning, when the Android handset server is found the condition of a fire by Java Servlet real time access early warning database and in the monitoring point, to specifying the person liable to send the early warning short message, this moment, on-the-spot sound and light alarm was still effective; Specify the person liable to the site disposal condition of a fire, if the intensity of a fire is still uncontrollable, start network alarming this moment, jump out warning window and picture, transmit simultaneously the far-end video information, select to be reported to the police or automatic 110 warnings of system by the staff 110 of Surveillance center, employ the fire extinguishing of public fire protection facility.
Claims (2)
1. fire disaster flame video preprocessor alarm system, it is characterized in that: fire disaster flame video monitor and early warning system adopts the distributed system architecture of Internet of Things to dispose, and is comprised of Internet video CCD camera, video management module, fire disaster flame detection subsystem and early warning subsystem; Described Internet video CCD camera is responsible for completing imaging, supports the WiFi wireless transmission, supports simultaneously TCP/IP network remote image transmitting, and has the detection of dynamic recording function; Described video management module adopts the generic video administration module; Described fire disaster flame detection subsystem is obtained the realtime graphic of Internet video CCD camera by image pick-up card, after processing the acquisition image with digital image processing techniques, whether call the fire disaster flame discriminating program, providing has the judgement of condition of a fire conclusion, if there is the condition of a fire to provide other judgement conclusion of condition of a fire level; Described early warning subsystem adopts three grades of modes of warnings, i.e. on-the-spot acousto-optic early warning, remote short messages breath early warning and Network Warning; When the one-level condition of a fire occured, the voice guard and the warning light that are arranged in the monitoring point in monitored district were responsible for realizing on-the-spot acousto-optic early warning, and alarm command is independently assigned by the monitoring site control module; When finding the secondary condition of a fire by Java Servlet real time access early warning database and in the monitoring point, the Android handset server ceases early warning to specifying the person liable to send the early warning short message to realize remote short messages; Wireless transmission is utilized the WiFi technology, and encrypted transmission is adopted in the transmission of early warning data, guarantees the security of data; When the condition of a fire of passing on when the fire disaster flame detection system reaches Senior Three level, jump out warning window and picture, realize network alarming, and it is live to transmit on-the-spot fire.
2. fire disaster flame detection method, it is characterized in that: the fire disaster flame detection method is that the Static and dynamic feature of fire disaster flame is carried out information fusion, provide a kind of fire based on neural network and the judgement of D-S evidence and differentiate algorithm, this algorithm can provide three threshold value of warning according to condition of a fire size, and three the corresponding on-the-spot sound and light alarms of threshold value of warning, long-range short messages are reported to the police and these three other modes of warnings of level of network alarming; Specific as follows:
Step 1: described Internet video CCD camera is completed field imaging, and the digital picture at the scene that image pick-up card acquisition Internet video CCD camera transmits utilizes digital image processing techniques to carry out pre-service to this digital picture;
Step 2: utilize gray scale thresholding technology by the motion feature of the variation detection of fires flame of the gray scale thresholding of two two field pictures before and after comparing; The area change feature whether the growth detection fire disaster flame is arranged by two two field picture flame area before and after comparing; Flame detection color characteristic in the HIS color space; Realize differentiation to naturally light and daylight lamp monochrome information background interference by the circularity feature of extracting fire disaster flame; Extract the wedge angle number of fire disaster flame, the wedge angle number that utilizes fire disaster flame along with the characteristics that present irregular rule burning time with the variation of the wedge angle number of fire disaster flame as one of Fire Criterion; Fire disaster flame burning initial stage predominant frequency is in 12Hz, and the variation of surrounding environment is not remarkable to frequency influence, therefore extracts the blinking characteristics of fire disaster flame as one of Fire Criterion;
Step 3: gather the fire disaster flame data sample of monitoring point, select in advance weights and the threshold value of the fire disaster flame data sample of monitoring point being trained these four kinds of fire disaster flame features of flicker frequency feature of the wedge angle number of the circularity feature that obtains to comprise fire disaster flame color characteristic, fire disaster flame, fire disaster flame and fire disaster flame;
Step 4: utilize formula (1) to obtain the fire disaster flame threshold value of warning:
In formula:
Be
iIndividual fire disaster flame feature output,
,
H 0Expression is without fire disaster flame,
H 1Expression has fire disaster flame;
,
m i (H
0) and
m i (
H 1) be
iThe detection probability of individual fire disaster flame feature and probability of miscarriage of justice;
Step 5: utilize above-mentioned detected real-time threshold value and empirical value to realize that relatively fire disaster flame detects and early warning in real time.
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| CN106060480A (en) * | 2016-07-13 | 2016-10-26 | 北京中凯润邦科技发展有限责任公司 | Fusion monitoring system for early warning video information flow |
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Families Citing this family (1)
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101334924A (en) * | 2007-06-29 | 2008-12-31 | 丁国锋 | Fire hazard probe system and its fire hazard detection method |
| US20090315722A1 (en) * | 2008-06-20 | 2009-12-24 | Billy Hou | Multi-wavelength video image fire detecting system |
| KR101148799B1 (en) * | 2011-09-21 | 2012-05-24 | 주식회사 창성에이스산업 | Infrared thermal image fire detector and fire detection method using the same |
| CN102682565A (en) * | 2012-03-23 | 2012-09-19 | 合肥博构元丰信息技术有限公司 | Fire protection and security integrated intelligent video monitoring system suitable for open space |
| CN102784451A (en) * | 2012-08-06 | 2012-11-21 | 西安硅光电子科技有限公司 | Automatic positioning flame detection system for three-dimensional space |
-
2013
- 2013-02-28 CN CN201310062843.XA patent/CN103150856B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101334924A (en) * | 2007-06-29 | 2008-12-31 | 丁国锋 | Fire hazard probe system and its fire hazard detection method |
| US20090315722A1 (en) * | 2008-06-20 | 2009-12-24 | Billy Hou | Multi-wavelength video image fire detecting system |
| KR101148799B1 (en) * | 2011-09-21 | 2012-05-24 | 주식회사 창성에이스산업 | Infrared thermal image fire detector and fire detection method using the same |
| CN102682565A (en) * | 2012-03-23 | 2012-09-19 | 合肥博构元丰信息技术有限公司 | Fire protection and security integrated intelligent video monitoring system suitable for open space |
| CN102784451A (en) * | 2012-08-06 | 2012-11-21 | 西安硅光电子科技有限公司 | Automatic positioning flame detection system for three-dimensional space |
Non-Patent Citations (1)
| Title |
|---|
| 蒋佳佳等: "智能火灾两级报警与联动控制系统的设计", 《传感技术学报》, vol. 23, no. 3, 31 March 2010 (2010-03-31) * |
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