CN110070692A - A kind of intelligent vision fire-fighting monitoring system and method - Google Patents
A kind of intelligent vision fire-fighting monitoring system and method Download PDFInfo
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- CN110070692A CN110070692A CN201910359576.XA CN201910359576A CN110070692A CN 110070692 A CN110070692 A CN 110070692A CN 201910359576 A CN201910359576 A CN 201910359576A CN 110070692 A CN110070692 A CN 110070692A
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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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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
- H04N7/181—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a plurality of remote sources
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Abstract
The invention discloses a kind of intelligent vision fire-fighting monitoring system and methods, including embedded microprocessor, camera module, communication module, voice alarm module, power module, Keysheet module, alarm bell module, algorithm process directly can be carried out to the image of camera module acquisition by embedded microprocessor, it obtains the fire behaviors information such as smoke condition, fire location, intensity of a fire size, the function to fire alarm is completed by voice alarm module；Utilize communication module, establish fire-fighting Transmission system, wireless transmission method is used between each node, by treated, fire behavior information carries out real-time Transmission, wired electric signal is avoided to be influenced by fire and transmit and be obstructed, realize the quick transmission of the signals such as alarm, monitoring, control, the present invention is influenced small, adaptable by ring, is effectively evacuated and fire extinguishing provides effective means to realize in heavy construction.
Description
Technical field
The present invention relates to monitoring and fire-fighting domain, especially a kind of intelligent vision fire-fighting monitoring system and methods.
Background technique
In China, with the rapid development of scale of urbanization, heavy construction (such as: market, Commercial Complex, office building,
Residential building, large storehouse, workshop) as land resource effective means in short supply is solved, it continues to bring out like the mushrooms after rain.Due to
All kinds of heavy constructions are with the number of plies is more, vertical pipe well is more, construction material is many kinds of, electrical equipment is more, furniture category is inflammable
The features such as article is more, once fire occurs, fire spreading speed is fast, easily causes large area stereo burning, arduous task of putting out a fire,
Risk is big, also aerial ladder, giant frequent occurrence, to its phenomenon beyond one's ability to help；In addition, personnel are close in heavy construction
Collection, exit passageway are complicated, and ordinary person lacks fire disaster escaping self-saving ability in addition, and when fire occurs, place channel is unsmooth, no
Easily evacuation, some materials can also discharge the poisonous gas such as hydrogen cyanide in burning, further increase evacuation and fighting difficulty, easily make
Dead group's wound in groups.Therefore, in the case where various fire prevention conditions are substantially the same, skyscraper has bigger fire risk,
A kind of research of the intelligent fire monitor suitable for heavy construction is of great significance with application.
Fire is generally to be caused by part is dim, experienced smog, the process that flame is spread again, if in-site installation can
The auto fire-detection system leaned on, so that it may detect smog or flame early and and alarm, can effectively reduce or avoid
Fire damage.Currently,
Fire source probing generallys use sensor Detection Techniques, such as sense cigarette type, compound, temperature sensing sensor type etc..It is such
Technology is to identify whether it is fire source by certain the same or certain characteristic of sensor detection flame.But traditional detection means are difficult
To be suitable for large-space clean factory building.The sense cigarette and temperature sensitive type fire of widely used ceiling installation are visited in general small space buildings
Survey device, maxi-mum height at 12 meters hereinafter, fire smoke and temperature signal can comparatively fast reach ceiling, detector within a short period of time
It can alarm.And in large space place, due to the randomness that the finiteness and fire of detector quantity occur, cause to detect
Device apart from fire location generally farther out, and due to the partition of top of space heat expansion air act on so that fire signal is difficult to reach
Top detector, to be difficult to realize incipient fire alarm.Other than scale is big, detection environment in large space generally compared with
Difference, there are numerous noise jammings, such as dust, electromagnetism, light and vibration, and larger detection noise is caused even to make detector failure.
Further, since traditional probe algorithm is mostly based on simple threshold value or Trend Algorithm, degree of intelligence is not high, visits if improving fire
The sensitivity of survey is then easy to happen wrong report, and reduces sensitivity and be then easy to happen alarm delay or fail to report, it is difficult to effectively solve report
Contradiction between alert accuracy and timeliness.Since space scale is big, if continuing to use traditional detection means, need more
Detector could effectively cover space exploration, economic benefit is undesirable.
Heavy construction fire detection there are aiming at the problem that, people have jumped out the beam of temperature-sensitive, the sense conventional detections means such as cigarette
It ties up, and uses video camera (head) as detector, acquire the video image information in heavy construction in real time, and be based on video image
The technological development such as processing, pattern-recognition fire-fighting monitoring system, Direct Recognition can go out fire information from image sequence, go forward side by side
The linkages processing such as row alarm, fighting.The advantage that this detection method based on video image has investigative range wide, Simple System
System composition be mostly video camera power-up brain form, it is common such as: several video cameras are connected with a computer terminal, pass through cable
Real-time transmission monitoring screen, by staff to determine whether fire occurs, type, degree and the place that fire occurs.But
All there are several fire emphasis monitor areas, now taken the photograph by several on each layer of skyscraper or each region of heavy construction
The mode that camera connects a computer terminal is unable to satisfy the demand of a large amount of monitoring points while monitoring.Moreover, artificial judgment monitors
Whether regional fire occurs, and is easily influenced by staff's subjectivity situation, is difficult to accomplish 24 hours discovery fire behaviors in time.Also have
More complicated fire-fighting monitoring system is made of video camera, transmission device and server, operating mode are as follows: video camera acquisition is existing
Image is uploaded to server by cable network by field picture, by server operation image Processing Algorithm obtain fire condition into
Row alarm.Its defect: one, multi-channel video transmits, improper wireless transmission higher to network bandwidth requirement, generally uses wired biography
Defeated medium, and wired transmissions medium is easily damaged when fire generation, is caused image transmitting to fail, is fallen into entire monitoring system
It paralyses and fails；Two, multi-point monitoring occasion this for heavy construction, multiple paths of video images processing causes server to calculate in real time
It measures excessive.This is also visualization fire-fighting monitoring system using the main reason for cannot being widely popularized.
Summary of the invention
The invention aims to solve wrong report big by such environmental effects, easy existing in the prior art, fire letter
The technical problems such as transmission, cable bad, cost height, the complex process of breath, providing one kind can be intelligent, locates in embedded systems
Reason is influenced small, adaptable intelligent vision fire-fighting monitoring system and method by ring.
In order to achieve the above objectives, the present invention is implemented according to following technical scheme:
A kind of intelligent vision fire-fighting monitoring system, including embedded microprocessor, camera module, communication module, voice
Alarm module, power module, Keysheet module, alarm bell module, in which:
The output end of the camera module and the input terminal of embedded microprocessor connect, and camera module is for sending out
Live image is provided and is sent to embedded microprocessor when existing fire hazard or generation fire；
The embedded microprocessor, the image for acquiring to camera module carry out live extraction and algorithm analysis,
Smokescope, fire location, intensity of a fire size are obtained, i.e., when smokescope reaches early warning value, then being considered as has fire hazard, works as cigarette
When mistiness degree reaches alarming value, then being considered as has fire；
The output end of the Keysheet module and the input terminal of embedded microprocessor connect, and Keysheet module is set as input
Standby, for configuring the network ip address, the location of in the environment of embedded microprocessor, and setting smokescope is pre-
Alert value and alarming value and live image pass back to the time interval at the local end PC；
The serial ports of the communication module and embedded microprocessor connection, communication module using wireless network transmissions be used to
The information at scene and image are passed back to this according to the time of setting when finding fire hazard by local PC client information transmitting
The ground end PC；When finding fire, fire behavior, fire source, ignition point and live image are passed back into the local end PC in real time, make correlation
Personnel can timely understand fire information, quickly to deal with；
The input terminal of the voice alarm module and the output end of embedded microprocessor connect, and voice alarm module is used for
When smokescope reaches early warning value, voice broadcast is carried out, reminds relevant staff to be checked to handle in time, simultaneously
The local end PC is also alarmed, and related personnel's processing is waited；When smokescope reaches alarming value, carries out continual voice and broadcast
Report reminds the processing of staff and withdrawing for irrelevant personnel, guarantees effective evacuation of personnel in building；
The input terminal of the alarm bell module and the output end of embedded microprocessor connect, and alarm bell module is used to that fire to occur
When calamity, there is prompting function to people, so that people can quickly withdraw, prevents danger, replace with voice alarm module and broadcast
Out；
The output end of the power module and the power interface of embedded microprocessor connect, for being embedded micro process
Device power supply.
Further, the power module includes external power supply and lithium battery.
In addition, the present invention also provides a kind of intelligent vision fire-fightings to monitor that method, specific steps are as shown in Figure 2:
S1, activation system；
S2, system detect automatically, each system parameter initialization, and receive the early warning value of the smokescope of Keysheet module input
And alarming value, and the passback local end PC time interval；
S3, camera module carry out Image Acquisition to environment；
The image of acquisition is carried out image preprocessing by S4, embedded microprocessor；
The image that S5, embedded microprocessor obtain image preprocessing carries out dynamic detection；
Image after dynamic detection is carried out feature identification by S6, embedded microprocessor；
S7, judge whether the absolute value of the difference of region area is greater than set up threshold value by embedded microprocessor, and examine
It surveys and whether there is smog, judging result is greater than threshold value, that is, there is smog, smokescope reaches early warning value, and then voice alarm module has
The carry out voice broadcast of time interval reminds relevant staff to handle in time, and in real time returns field condition and image
To the local end PC；Smokescope reaches alarming value then continual progress voice broadcast and the alarm bell that sounds, and reminds related work
The processing of personnel and withdrawing for irrelevant personnel, and field condition and image are passed back into the local end PC in real time；Judging result
Less than threshold value, then smog is not present, then returns to S3.
Further, specific step is as follows by the S4:
S401, the template for creating image preprocessing；
S402, the template of the step S401 image preprocessing created is intersected with the image of acquisition, its element is stored in number
In group；
S403, pixel sequence is carried out to the element among array；
S404, using element value intermediate in array as institute's intersection graph as the value of regional center point；
All elements in S405, one frame image of traversal, judge whether that traversal is completed, are judged as YES, execute S5, judge
Otherwise to return to S402.
Further, specific step is as follows by the S5:
S501, Gauss model is defined；
S502, Gauss model parameter initialization；
S503, pixel is read to forms；
S504, judge whether pixel matches, be judged as YES, execute S507, be judged as and otherwise execute S505；
S505, Gauss model is re-established, and by its parameter initialization, executes S506；
S506, instead of impossible initial Gaussian model, execute S502；
S507, the Gauss model for being included into definition execute S508；
S508, judge whether to read and complete, be judged as YES, execute S6, be judged as and otherwise execute S501.
Further, specific step is as follows by the S6:
S601, the geometrical characteristic for observing smog, can be gradually to bleeding around, above area greatly below during rising
It is small, execute S602；
Highs and lows in S602, calculating target area, obtain the span of target area, execute S603；
S603, target area is divided into three regions from the bottom up, in the area region in each region pixel number come
It indicates, then subtracts each other its area.
Compared with prior art, the image that the present invention can directly to camera module acquisition by embedded microprocessor
Algorithm process is carried out, obtains the fire behaviors information such as smoke condition, fire location, intensity of a fire size, passes through voice alarm module completion pair
The function of fire alarm；Using communication module, fire-fighting Transmission system is established, wireless transmission method is used between each node, will locate
Fire behavior information after reason carries out real-time Transmission, and wired electric signal is avoided to be influenced by fire and transmit and be obstructed, and realizes alarm, prison
Depending on, control etc. signals quick transmission, the present invention influenced by ring it is small, adaptable, for realize heavy construction in effectively evacuation and
Fire extinguishing provides effective means.
Detailed description of the invention
Fig. 1 is embedded system composition figure of the invention；
Fig. 2 is control method flow chart of the invention.
Specific embodiment
To make the objectives, technical solutions, and advantages of the present invention more comprehensible, with reference to embodiments, to the present invention into
Row is further to be described in detail.Described herein the specific embodiments are only for explaining the present invention, is not used to limit invention.
As shown in Figure 1, a kind of intelligent vision fire-fighting monitoring system of the present embodiment, including embedded microprocessor, camera shooting
Head module, communication module, voice alarm module, power module, Keysheet module, alarm bell module, in which:
The output end of the camera module and the input terminal of embedded microprocessor connect, and camera module is for sending out
Live image is provided and is sent to embedded microprocessor when existing fire hazard or generation fire；
The embedded microprocessor, the image for acquiring to camera module carry out live extraction and algorithm analysis,
Smokescope, fire location, intensity of a fire size are obtained, i.e., when smokescope reaches early warning value, then being considered as has fire hazard, works as cigarette
When mistiness degree reaches alarming value, then being considered as has fire；
The output end of the Keysheet module and the input terminal of embedded microprocessor connect, and Keysheet module is set as input
Standby, for configuring the network ip address, the location of in the environment of embedded microprocessor, and setting smokescope is pre-
Alert value and alarming value and live image pass back to the time interval at the local end PC；
The serial ports of the communication module and embedded microprocessor connection, communication module using wireless network transmissions be used to
The information at scene and image are passed back to this according to the time of setting when finding fire hazard by local PC client information transmitting
The ground end PC；When finding fire, fire behavior, fire source, ignition point and live image are passed back into the local end PC in real time, make correlation
Personnel can timely understand fire information, quickly to deal with；
The input terminal of the voice alarm module and the output end of embedded microprocessor connect, and voice alarm module is used for
When smokescope reaches early warning value, voice broadcast is carried out, reminds relevant staff to be checked to handle in time, simultaneously
The local end PC is also alarmed, and related personnel's processing is waited；When smokescope reaches alarming value, carries out continual voice and broadcast
Report reminds the processing of staff and withdrawing for irrelevant personnel, guarantees effective evacuation of personnel in building；
The input terminal of the alarm bell module and the output end of embedded microprocessor connect, and alarm bell module is used to that fire to occur
When calamity, there is prompting function to people, so that people can quickly withdraw, prevents danger, replace with voice alarm module and broadcast
Out；
The output end of the power module and the power interface of embedded microprocessor connect, for being embedded micro process
Device power supply.Power module includes that external power supply and lithium battery use external power supply under normal circumstances.Outside power-off or
When fire occurs, cause external power supply that cannot use, then use lithium battery power supply, but protecting equipment under any circumstance can be just
Normal work.
When carrying out fire-fighting monitoring using above-mentioned intelligent vision fire-fighting monitoring system, detailed process is as follows:
S1, activation system；
S2, system detect automatically, each system parameter initialization, and receive the early warning value of the smokescope of Keysheet module input
And alarming value, and the passback local end PC time interval；
S3, camera module carry out Image Acquisition to environment；
The image of acquisition is carried out image preprocessing by S4, embedded microprocessor:
S401, the template for creating image preprocessing；
S402, the template of the step S401 image preprocessing created is intersected with the image of acquisition, its element is stored in number
In group；
S403, pixel sequence is carried out to the element among array；
S404, using element value intermediate in array as institute's intersection graph as the value of regional center point；
All elements in S405, one frame image of traversal, judge whether that traversal is completed, are judged as YES, execute S5, judge
Otherwise to return to S402；
The image that S5, embedded microprocessor obtain image preprocessing carries out dynamic detection:
S501, Gauss model is defined；
S502, Gauss model parameter initialization；
S503, pixel is read to forms；
S504, judge whether pixel matches, be judged as YES, execute S507, be judged as and otherwise execute S505；
S505, Gauss model is re-established, and by its parameter initialization, executes S506；
S506, instead of impossible initial Gaussian model, execute S502；
S507, the Gauss model for being included into definition execute S508；
S508, judge whether to read and complete, be judged as YES, execute S6, be judged as and otherwise execute S501；
Image after dynamic detection is carried out feature identification by S6, embedded microprocessor:
S601, the geometrical characteristic for observing smog, can be gradually to bleeding around, above area greatly below during rising
It is small, execute S602；
Highs and lows in S602, calculating target area, obtain the span of target area, execute S603；
S603, target area is divided into three regions from the bottom up, in the area region in each region pixel number come
It indicates, then subtracts each other its area；
S7, judge whether the absolute value of the difference of region area is greater than set up threshold value by embedded microprocessor, and examine
It surveys and whether there is smog, judging result is greater than threshold value, that is, there is smog, smokescope reaches early warning value, and then voice alarm module has
The carry out voice broadcast of time interval reminds relevant staff to handle in time, and in real time returns field condition and image
To the local end PC；Smokescope reaches alarming value then continual progress voice broadcast and the alarm bell that sounds, and reminds related work
The processing of personnel and withdrawing for irrelevant personnel, and field condition and image are passed back into the local end PC in real time；Judging result
Less than threshold value, then smog is not present, then returns to S3.
The limitation that technical solution of the present invention is not limited to the above specific embodiments, it is all to do according to the technique and scheme of the present invention
Technology deformation out, falls within the scope of protection of the present invention.
Claims (6)
1. a kind of intelligent vision fire-fighting monitoring system, which is characterized in that including embedded microprocessor, camera module, communication
Module, voice alarm module, power module, Keysheet module, alarm bell module, in which:
The output end of the camera module and the input terminal of embedded microprocessor connect, and camera module is used in discovery fire
Live image is provided and is sent to embedded microprocessor when calamity hidden danger or generation fire；
The embedded microprocessor, the image for acquiring to camera module carry out live extraction and algorithm analysis, obtain
Smokescope, fire location, intensity of a fire size, i.e., when smokescope reaches early warning value, then being considered as has fire hazard, when smog is dense
When degree reaches alarming value, then being considered as has fire；
The output end of the Keysheet module and the input terminal of embedded microprocessor connect, and Keysheet module is used as input equipment
In the network ip address of configuration embedded microprocessor, in the environment location, and the early warning value of setting smokescope
And alarming value and live image pass back to the time interval at the local end PC；
The connection of the serial ports of the communication module and embedded microprocessor, communication module are used to and local using wireless network transmissions
The information at scene and image are passed back to local PC according to the time of setting when finding fire hazard by the transmitting of PC client information
End；When finding fire, fire behavior, fire source, ignition point and live image are passed back into the local end PC in real time, make related personnel
Fire information can be understood, timely quickly to deal with；
The input terminal of the voice alarm module and the output end of embedded microprocessor connect, and voice alarm module is used in cigarette
When mistiness degree reaches early warning value, voice broadcast is carried out, relevant staff is reminded to be checked to handle in time, while is local
PC also alarms at end, waits related personnel's processing；When smokescope reaches alarming value, continual voice broadcast is carried out,
The processing of staff and withdrawing for irrelevant personnel are reminded, guarantees effective evacuation of personnel in building；
The input terminal of the alarm bell module and the output end of embedded microprocessor connect, and alarm bell module is used to that fire to occur
When, there is prompting function to people, so that people can quickly withdraw, prevents danger, replace broadcast with voice alarm module；
The output end of the power module and the power interface of embedded microprocessor connect, for supplying for embedded microprocessor
Electricity.
2. intelligent vision fire-fighting monitoring system according to claim 1, it is characterised in that: the power module includes external
Power supply and lithium battery.
3. a kind of intelligent vision fire-fighting monitors method, which is characterized in that disappeared using a kind of intelligent vision as described in claim 1
Anti- monitoring system is monitored, the specific steps are as follows:
S1, activation system；
S2, system detect automatically, each system parameter initialization, and receive the early warning value and report of the smokescope of Keysheet module input
Alert value, and the passback local end PC time interval；
S3, camera module carry out Image Acquisition to environment；
The image of acquisition is carried out image preprocessing by S4, embedded microprocessor；
The image that S5, embedded microprocessor obtain image preprocessing carries out dynamic detection；
Image after dynamic detection is carried out feature identification by S6, embedded microprocessor；
S7, judge whether the absolute value of the difference of region area is greater than set up threshold value by embedded microprocessor, and detection is
No judging result is greater than threshold value there are smog, that is, there is smog, smokescope reaches early warning value then voice alarm module having time
The carry out voice broadcast at interval reminds relevant staff to handle in time, and field condition and image are passed back to this in real time
The ground end PC；Smokescope reaches alarming value then continual progress voice broadcast and the alarm bell that sounds, and reminds relevant staff
Processing and irrelevant personnel withdraw, and in real time field condition and image are passed back into the local end PC；Judging result is less than
Threshold value is then not present smog, then returns to S3.
4. intelligent vision fire-fighting according to claim 3 monitors method, it is characterised in that: specific step is as follows by the S4:
S401, the template for creating image preprocessing；
S402, the template of the step S401 image preprocessing created is intersected with the image of acquisition, its element is stored in array；
S403, pixel sequence is carried out to the element among array；
S404, using element value intermediate in array as institute's intersection graph as the value of regional center point；
All elements in S405, one frame image of traversal, judge whether that traversal is completed, are judged as YES, execute S5, be judged as NO
Then return to S402.
5. intelligent vision fire-fighting according to claim 4 monitors method, it is characterised in that: the specific steps of the S5 are such as
Under:
S501, Gauss model is defined；
S502, Gauss model parameter initialization；
S503, pixel is read to forms；
S504, judge whether pixel matches, be judged as YES, execute S507, be judged as and otherwise execute S505；
S505, Gauss model is re-established, and by its parameter initialization, executes S506；
S506, instead of impossible initial Gaussian model, execute S502；
S507, the Gauss model for being included into definition execute S508；
S508, judge whether to read and complete, be judged as YES, execute S6, be judged as and otherwise execute S501.
6. intelligent vision fire-fighting according to claim 5 monitors method, it is characterised in that: the specific steps of the S6 are such as
Under:
S601, the geometrical characteristic for observing smog, can be big small below above area gradually to bleeding around during rising,
Execute S602；
Highs and lows in S602, calculating target area, obtain the span of target area, execute S603；
S603, target area being divided into three regions from the bottom up, pixel number indicates in the area region in each region,
Then its area is subtracted each other.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112183475A (en) * | 2020-10-28 | 2021-01-05 | 镇江启创信息技术有限公司 | Electrical potential safety hazard identification system based on machine vision |
| CN113726014A (en) * | 2021-09-01 | 2021-11-30 | 广东省珩祥安全科技有限公司 | Power utilization monitoring method and system based on circuit breaker |
| CN114038147A (en) * | 2021-06-16 | 2022-02-11 | 武汉光阴南北网络技术咨询中心 | Fire rescue communication method, electronic device and storage medium |
| CN115147993A (en) * | 2022-09-05 | 2022-10-04 | 无锡卓信信息科技股份有限公司 | Fire early warning system for closed place and system data processing method thereof |
-
2019
- 2019-04-30 CN CN201910359576.XA patent/CN110070692A/en active Pending
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112183475A (en) * | 2020-10-28 | 2021-01-05 | 镇江启创信息技术有限公司 | Electrical potential safety hazard identification system based on machine vision |
| CN114038147A (en) * | 2021-06-16 | 2022-02-11 | 武汉光阴南北网络技术咨询中心 | Fire rescue communication method, electronic device and storage medium |
| CN114038147B (en) * | 2021-06-16 | 2023-11-14 | 武汉光阴南北网络技术咨询中心 | Fire rescue communication method, electronic equipment and storage medium |
| CN113726014A (en) * | 2021-09-01 | 2021-11-30 | 广东省珩祥安全科技有限公司 | Power utilization monitoring method and system based on circuit breaker |
| CN113726014B (en) * | 2021-09-01 | 2022-07-12 | 广东省珩祥安全科技有限公司 | Power utilization monitoring method and system based on circuit breaker |
| CN115147993A (en) * | 2022-09-05 | 2022-10-04 | 无锡卓信信息科技股份有限公司 | Fire early warning system for closed place and system data processing method thereof |
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