CN113256928A - Fire detection method based on image recognition and temperature determination algorithm - Google Patents
Fire detection method based on image recognition and temperature determination algorithm Download PDFInfo
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- G—PHYSICS
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- 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
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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
Abstract
The invention discloses a fire detection method based on image recognition and temperature judgment algorithms, and relates to the technical field of fire fighting. The fire detector comprises a color image module, a near-infrared image module, an infrared thermal imaging module, a light supplementing lamp and an algorithm processing unit; the color image module is connected with the light supplementing lamp, and the color image module, the near-infrared image module and the infrared thermal imaging module are connected with the algorithm processing unit; the algorithm processing unit judges the fire by adopting a multiple judgment algorithm; the multiple judgment algorithms comprise a high-temperature abnormity judgment algorithm, a flame judgment fire algorithm and a smoke judgment fire algorithm. The user can adopt the mode that three kinds of detection methods of smoke detection, flame detection and high temperature anomaly detection coexist simultaneously to detect, and can also be self-defined. The invention can detect the fire source in different stages when fire occurs.
Description
Technical Field
The invention belongs to the technical field of fire fighting, and particularly relates to a fire detection method based on image recognition and a temperature judgment algorithm.
Background
At present, a fire detector based on an image recognition technology has the technical core that an 850nm-1000nm near infrared band imaging technology is used, a detection method and a scheme have a single false alarm rate and are particularly serious outdoors, an alarm cannot be given out in heating and fuming stages in coal, petrochemical industry and tobacco and wine manufacturing places, particularly, the detection cannot be carried out in natural and cloudy states of coal, and the early detection and early warning cannot be achieved by the existing technology of firstly heating and then detonating when a fire disaster occurs in the petrochemical industry. There are the following disadvantages:
1) the single false alarm rate of the detection wave band is high;
2) high temperature objects and cloudy objects cannot be detected; (e.g., coal natural, chemical raw material high temperature heating)
3) The detection stage is single, the high temperature and the fuming stage cannot be detected, and only open fire can be detected.
Disclosure of Invention
The invention aims to provide a fire detection method based on an image recognition and temperature judgment algorithm, and solves the problems that the existing product cannot detect high-temperature abnormal cloudy objects, cannot detect smoke function and has a high outdoor false alarm rate. The detection method can detect smoke, flame and temperature, and can detect fire sources in different stages when a fire breaks out.
In order to solve the technical problems, the invention is realized by the following technical scheme:
the invention relates to a fire detection method based on image recognition and temperature judgment algorithms.A fire detector adopted by the method comprises a color image module, a near-infrared image module, an infrared thermal imaging module, a light supplementing lamp and an algorithm processing unit; the color image module is connected with the light supplementing lamp, and the color image module, the near-infrared image module and the infrared thermal imaging module are connected with the algorithm processing unit;
the signal output by the color image module, the signal output by the near-infrared image module and the output signal of the infrared thermal imaging module are accessed into the algorithm processing unit to judge the fire by adopting a multiple judgment algorithm;
the multiple judgment algorithms comprise a high-temperature abnormity judgment algorithm, a flame judgment fire algorithm and a smoke judgment fire algorithm;
furthermore, the fire detector is a three-band fire detector, and adopts 850nm-1000nm near infrared band imaging technology, 8um-14um band infrared thermal imaging temperature measurement technology and 650nm visible light image identification technology; and identifying the three band images and carrying out composite operation with a temperature measurement technology to carry out fire detection judgment.
Furthermore, the color image module comprises an imaging device, an optical lens and a lens mounting base, and the interface signal adopts a standard signal source mipi format;
the near-infrared image module comprises an imaging device, an optical lens, a near-infrared optical filter and a lens mounting base, and an interface signal adopts a standard signal source mipi format;
the infrared thermal imaging module comprises an optical lens and an installation base, and the output image format is BT656 and temperature data.
Furthermore, the algorithm processing unit adopts an artificial intelligence chip;
the artificial intelligence core is manufactured by Shenzhen Shanxi semiconductor limited company, Ruizi microelectronic limited company or Beijing Junzhen integrated circuit limited company.
Further, the high-temperature abnormality determination: and the high-temperature abnormity judgment algorithm judges according to the highest temperature point, the number of pixel points occupied by the high temperature and the highest temperature rise rate.
Further, the high-temperature abnormality determination algorithm is as follows:
the algorithm processing unit acquires temperature and imaging signals through the infrared thermal imaging module to perform algorithm analysis and processing, wherein the high-temperature response threshold value is Wd _ F, the high-temperature response threshold value accumulates pixel points Sum _ Wd _ F, the temperature rise rate Wd _ K is higher than the response threshold value Wd _ F, and the ratio of the number of pixel points to the total pixel point is higher than the response threshold value Wd _ Pe;
a) judging whether the highest temperature exceeds a response threshold value Wd _ F or not, and entering b) if the highest temperature exceeds an early warning threshold value;
b) judging whether the accumulated pixel point of the high-temperature response threshold exceeds Sum _ Wd _ F or not, and entering c if the accumulated pixel point of the high-temperature response threshold exceeds the Sum _ Wd _ F; c) judging whether the highest temperature rate is greater than Wd _ K, and if so, entering d);
d) judging whether the ratio of the number of pixels which is higher than the response threshold value Wd _ F to the number of total pixels is higher than Wd _ Pe or not, and outputting a high-temperature early warning signal if the ratio is higher than Wd _ Pe;
further, the flame determination fire algorithm:
a judgment algorithm which is compounded with a near-infrared image recognition algorithm on the basis of a high-temperature abnormity judgment algorithm; the near infrared image module signal is transmitted to the algorithm processing unit through the mipi signal;
e) judging whether the high-temperature abnormal algorithm gives an alarm or not, and if so, entering f);
f) acquiring a near-infrared image module signal, and judging whether the image accords with a fire disaster or not by performing feature determination on the brightness, the sharp angle characteristic, the dispersion and the fluctuation characteristic of the image, and if so, entering g);
g) and respectively identifying the acquired near-infrared image, the thermal imaging image and the color image module video by artificial intelligence fire target identification, and if the images are all reported, outputting a fire alarm signal by the system.
Further, the smoke decision fire algorithm:
the smoke judgment algorithm is an algorithm which is based on a high-temperature abnormity judgment algorithm and is compositely judged by a color image artificial intelligence recognition algorithm;
h) judging whether the high-temperature abnormal algorithm gives an alarm or not, and entering i if the high-temperature abnormal algorithm gives an alarm;
i) judging the current illumination, and if the illumination condition is not met, starting a light supplement lamp;
j) and carrying out artificial intelligent smoke target identification on the obtained color image module video, and if the alarm is given, outputting a fire alarm signal by the system.
A user selects a high-temperature abnormity determination algorithm to perform high-temperature abnormity detection, a flame determination fire algorithm to perform flame detection and a smoke determination fire algorithm to perform smoke detection according to the field use environment, and the three detection modes coexist at the same time or perform custom combination.
The invention has the following beneficial effects:
(1) the present invention follows the following three stages according to the conventional fire occurrence mechanism: a fuming stage, a smoldering fuming stage and an open fire stage; the non-contact type detector of the existing national standard fire detector can not realize the full-stage detection in the fire occurrence mechanism process, and the invention can realize the effect of completely detecting and early warning to realize the extremely early prevention in the initial heating stage, the smoldering stage and the open fire stage of fire occurrence, thereby providing a large amount of time for fire extinguishment and reducing property loss to the maximum extent.
(2) The invention effectively reduces the false alarm rate of the product and improves the fire detection accuracy of the product by adopting multiple composite judgment modes of temperature, image recognition, multiband detection and artificial intelligence algorithm.
(3) The image type fire detector has the advantages of large detection area, small wiring engineering quantity and the like.
Of course, it is not necessary for any product in which the invention is practiced to achieve all of the above-described advantages at the same time.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a system diagram of a detector of the present invention.
Fig. 2 is a high-temperature abnormality determination algorithm of the present invention.
FIG. 3 is a flame determination fire algorithm of the present invention.
FIG. 4 is a smoke fire determination algorithm of the present invention
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention uses 850nm-1000nm near infrared band imaging technology, 8um-14um band thermal imaging technology and temperature measurement technology, 650nm visible light image recognition technology; the three band images are identified and processed, and are subjected to composite operation with a temperature measurement technology to detect and judge the fire, and an artificial intelligence algorithm is introduced as the core of the algorithm.
As shown in fig. 1, the detector mainly comprises: the system comprises a color image module, a near-infrared image module, an infrared thermal forming module (image and temperature part), a light supplementing lamp and an algorithm processing unit.
1) Color image module: the method comprises the following steps of forming a Sony imaging device, an optical lens, a lens mounting base and the like, wherein an interface signal adopts a standard signal source mipi format;
2) near-infrared image module: the method comprises the following steps of forming a Sony imaging device, an optical lens, a near infrared filter, a lens mounting base and the like, wherein an interface signal adopts a standard signal source mipi format;
3) infrared thermal imaging module: mainly comprises an optical lens, a mounting base and an output image format of BT656 and temperature data;
4) an algorithm processing unit: adopting an artificial intelligence chip (such as Shenzhen Shansi semiconductor Limited, Ruizhou microelectronic Limited, Beijing Junzhen integrated circuit Limited), connecting the color image module signal, the near-infrared image module signal and the infrared thermal imaging module into the algorithm processing unit, judging the fire by adopting a multiple condition judgment mode, and abandoning the traditional algorithm modeling mode algorithm; adopting an artificial intelligent recognition algorithm and a multiple judgment algorithm to judge the fire;
5) principle of algorithm
1) And (4) judging the high-temperature abnormity, as shown in figure 2.
High-temperature anomaly determination algorithm: judging by methods such as the highest temperature point, the number of pixel points occupied by the high temperature, the highest temperature rise rate and the like as main parameters; the algorithm processing unit obtains the temperature and the imaging signal through the infrared thermal imaging module to perform algorithm analysis and processing.
The following is assumed:
the high temperature response threshold is Wd _ F; accumulating pixel points Sum _ Wd _ F by a high-temperature response threshold value; temperature rise rate Wd _ K; (ii) a The number of pixel points higher than the response threshold Wd _ F is greater than the response threshold Wd _ Pe;
a) judging whether the highest temperature exceeds a response threshold value is Wd _ F, and entering a next algorithm if the highest temperature exceeds the response threshold value;
b) judging whether the high-temperature response threshold value accumulated pixel point exceeds Sum _ Wd _ F or not, and entering the next algorithm if the high-temperature response threshold value accumulated pixel point exceeds the Sum _ Wd _ F and the early warning;
c) judging whether the highest temperature rate is greater than Wd _ K or not, and entering an early warning algorithm if the highest temperature rate is greater than Wd _ K;
d) judging whether the ratio of the number of pixels which is higher than the response threshold value Wd _ F to the number of total pixels is higher than Wd _ Pe or not, and outputting a high-temperature early warning signal if the ratio is higher than Wd _ Pe;
2) flame algorithm determination, as shown in fig. 3.
The fire disaster judgment algorithm is as follows: a high-temperature anomaly judgment algorithm and a near-infrared image recognition and identification algorithm are compounded to form a judgment algorithm; the near infrared image acquisition is carried out by transmitting a mipi signal to an algorithm processing unit
a) Judging whether the high-temperature abnormal algorithm gives an alarm or not, and entering the next algorithm if the alarm is given;
b) acquiring a near-infrared image signal, carrying out characteristic judgment on the brightness, the sharp angle characteristic, the dispersion and the fluctuation characteristic of the image to judge whether the image accords with the fire, and entering a next-stage algorithm if the image accords with the fire
c) And respectively identifying the acquired near-infrared image, the thermal imaging image and the color image module video by artificial intelligence fire target identification, and if the images are all reported to the police, outputting a fire alarm signal by the system.
3) Smoke algorithm decision, fig. 4.
The smoke decision algorithm is as follows: an algorithm for composite judgment based on a high-temperature anomaly judgment algorithm and a color image artificial intelligence recognition algorithm;
a) judging whether the high-temperature abnormal algorithm gives an alarm or not, and entering the next algorithm if the alarm is given;
b) judging the current illumination, and if the illumination condition is not met, starting a light supplement lamp;
c) and carrying out artificial intelligent smoke target identification on the obtained color image module video, and if the alarm is given, outputting a fire alarm signal by the system.
In the description herein, references to the description of "one embodiment," "an example," "a specific example" or the like are intended to mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The preferred embodiments of the invention disclosed above are intended to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise embodiments disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims (9)
1. A fire detection method based on image recognition and temperature judgment algorithm is characterized in that: the adopted fire detector comprises a color image module, a near-infrared image module, an infrared thermal imaging module, a light supplementing lamp and an algorithm processing unit; the color image module is connected with the light supplementing lamp, and the color image module, the near-infrared image module and the infrared thermal imaging module are connected with the algorithm processing unit;
the signal output by the color image module, the signal output by the near-infrared image module and the output signal of the infrared thermal imaging module are accessed into the algorithm processing unit to judge the fire by adopting a multiple judgment algorithm;
the multiple judgment algorithms comprise a high-temperature abnormity judgment algorithm, a flame judgment fire algorithm and a smoke judgment fire algorithm.
2. A fire detection method based on image recognition and temperature determination algorithm as claimed in claim 1, characterized in that: the fire detector is a three-band fire detector, and adopts 850nm-1000nm near infrared band imaging technology, 8um-14um band infrared thermal imaging temperature measurement technology and 650nm visible light image identification technology; and identifying the three band images and carrying out composite operation with a temperature measurement technology to carry out fire detection judgment.
3. A fire detection method based on image recognition and temperature determination algorithm as claimed in claim 1, characterized in that:
the color image module comprises an imaging device, an optical lens and a lens mounting base, and an interface signal adopts a standard signal source mipi format;
the near-infrared image module comprises an imaging device, an optical lens, a near-infrared optical filter and a lens mounting base, and an interface signal adopts a standard signal source mipi format;
the infrared thermal imaging module comprises an optical lens and an installation base, and the output image format is BT656 and temperature data.
4. A fire detection method based on image recognition and temperature determination algorithm as claimed in claim 1, characterized in that: the algorithm processing unit adopts an artificial intelligence chip;
the artificial intelligence core is manufactured by Shenzhen Shanxi semiconductor limited company, Ruizi microelectronic limited company or Beijing Junzhen integrated circuit limited company.
5. A fire detection method based on image recognition and temperature determination algorithm as claimed in claim 1, characterized in that:
the high-temperature abnormality determination: and the high-temperature abnormity judgment algorithm judges according to the highest temperature point, the number of pixel points occupied by the high temperature and the highest temperature rise rate.
6. The fire detection method based on image recognition and temperature determination algorithm according to claim 5, wherein:
the high-temperature anomaly determination algorithm is as follows:
the algorithm processing unit acquires temperature and imaging signals through the infrared thermal imaging module to perform algorithm analysis and processing, wherein the high-temperature response threshold value is Wd _ F, the high-temperature response threshold value accumulates pixel points Sum _ Wd _ F, the temperature rise rate Wd _ K is higher than the response threshold value Wd _ F, and the ratio of the number of pixel points to the total pixel point is higher than the response threshold value Wd _ Pe;
a) judging whether the highest temperature exceeds a response threshold value Wd _ F or not, and entering b) if the highest temperature exceeds an early warning threshold value;
b) judging whether the accumulated pixel point of the high-temperature response threshold exceeds Sum _ Wd _ F or not, and entering c if the accumulated pixel point of the high-temperature response threshold exceeds the Sum _ Wd _ F;
c) judging whether the highest temperature rate is greater than Wd _ K, and if so, entering d);
d) and judging whether the ratio of the pixel point number of the pixels higher than the response threshold value Wd _ F to the total pixel point number is higher than Wd _ Pe, and if so, outputting a high-temperature early warning signal.
7. A fire detection method based on image recognition and temperature determination algorithm according to claim 1 or 6, characterized in that:
the flame determination fire algorithm comprises the following steps:
a judgment algorithm which is compounded with a near-infrared image recognition algorithm on the basis of a high-temperature abnormity judgment algorithm; the near infrared image module signal is transmitted to the algorithm processing unit through the mipi signal;
e) judging whether the high-temperature abnormal algorithm gives an alarm or not, and if so, entering f);
f) acquiring a near-infrared image module signal, and judging whether the image accords with a fire disaster or not by performing feature determination on the brightness, the sharp angle characteristic, the dispersion and the fluctuation characteristic of the image, and if so, entering g);
g) and respectively identifying the acquired near-infrared image, the thermal imaging image and the color image module video by artificial intelligence fire target identification, and if the images are all reported, outputting a fire alarm signal by the system.
8. A fire detection method based on image recognition and temperature determination algorithm according to claim 1 or 6, characterized in that:
the smoke fire judgment algorithm comprises the following steps:
the smoke judgment algorithm is an algorithm which is based on a high-temperature abnormity judgment algorithm and is compositely judged by a color image artificial intelligence recognition algorithm;
h) judging whether the high-temperature abnormal algorithm gives an alarm or not, and entering i if the high-temperature abnormal algorithm gives an alarm;
i) judging the current illumination, and if the illumination condition is not met, starting a light supplement lamp;
j) and carrying out artificial intelligent smoke target identification on the obtained color image module video, and if the alarm is given, outputting a fire alarm signal by the system.
9. A fire detection method based on image recognition and temperature determination algorithm as claimed in claim 1, characterized in that:
a user selects a high-temperature abnormity determination algorithm to perform high-temperature abnormity detection, a flame determination fire algorithm to perform flame detection and a smoke determination fire algorithm to perform smoke detection according to the field use environment, and the three detection modes coexist at the same time or perform custom combination.
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