CN115713833A - Flame detection method and device based on area characteristics and storage medium - Google Patents
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Abstract
The invention relates to the technical field of carbon fiber production detection, in particular to a flame detection method, flame detection equipment and a flame detection storage medium based on area characteristics, which comprise the following steps: image acquisition, namely photographing in an oxidation furnace to obtain an initial image; image processing, namely performing high-frequency feature extraction on the initial image to obtain a plurality of first areas; area screening, namely judging the color of the edge of each first area, and judging the first area as a suspected area when the edge of the first area is red; and (3) determining the fire, observing the area characteristics of the suspected area, judging the suspected area as a flame area if the area of the suspected area is increased along with time, and giving an alarm. In the invention, if the area of the suspected area is increased along with the time, the area can be judged to be a flame area, so that an alarm is given.
Description
Technical Field
The invention relates to the technical field of carbon fiber production detection, in particular to a flame detection method and device based on area characteristics and a storage medium.
Background
The PAN-based carbon fiber has the characteristics of high specific strength, high specific modulus, high temperature resistance, fatigue resistance, creep resistance, electric conduction, heat insulation, small thermal expansion coefficient and the like, is a novel carbon material with comprehensive excellent performance, and is widely applied to industries such as aviation, aerospace, automobiles, chemical engineering, buildings, sports goods and the like.
The oxidation carbonization process of the PAN-based carbon fiber comprises the steps of pre-oxidation, low-temperature carbonization, high-temperature carbonization, surface treatment, sizing, drying and the like. The pre-oxidation is an important intermediate process, linear molecular chains of the PAN precursor gradually form a heat-resistant trapezoidal structure in the process, the PAN precursor needs to pass through a plurality of oxidation furnaces with gradually increased temperatures in an oxidation furnace cluster, main reactions in the pre-oxidation process are cyclization, oxidation and dehydrogenation, all are exothermic reactions, heat storage and overheating can be caused inside fibers, the temperature in the oxidation furnace is high, and the ignition phenomenon is easily caused due to the fact that the local temperature is too high.
When the internal fire of oxidation furnace, because the high temperature of oxidation furnace itself, take place the detonation phenomenon in the oxidation furnace very easily, it may only be short for a few seconds time to stretch to whole oxidation furnace from starting to fire to the intensity of a fire, and because the silk bundle need pass through a plurality of oxidation furnaces, once one of them oxidation furnace is on fire, the intensity of a fire will be scurried into other oxidation furnaces along the silk bundle very fast, thereby cause the phenomenon of on fire of a plurality of oxidation furnaces, cause very big hidden danger to producers' life safety, also very big increase manufacturing cost.
In the prior art, the flame in the oxidation furnace is usually detected by a PT100 type platinum thermal resistor, and when the flame is sensed to be higher than a set fire early warning value, a fire signal is sent out. However, although the PT100 type platinum thermistor has high measurement accuracy, it is a conventional slow temperature measuring device, and when the flame in the furnace causes the temperature of the PT100 type platinum thermistor to exceed a predetermined fire value and send a fire alarm signal, the process is expected to take more than 3 seconds, and at this time, it is often too late to take fire extinguishing measures, and the flame in the oxidation furnace has spread to the whole oxidation furnace. Therefore, how to identify the fire condition more quickly and accurately becomes a difficult problem for carbon fiber production enterprises.
The information disclosed in this background section is only for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person skilled in the art.
Disclosure of Invention
The invention provides a flame detection method, flame detection equipment and a flame detection storage medium based on area characteristics, so that the problems in the background art are effectively solved.
In order to achieve the purpose, the invention adopts the technical scheme that: a flame detection method based on area characteristics comprises the following steps:
image acquisition, namely taking a picture of the inside of the oxidation furnace to obtain an initial image;
image processing, namely performing high-frequency feature extraction on the initial image to obtain a plurality of first areas;
area screening, namely judging the color of the edge of each first area, and judging the first area as a suspected area when the edge of the first area is red;
and determining the fire, observing the area characteristics of the suspected area, judging the suspected area as a flame area if the area of the suspected area is increased along with time, and giving an alarm.
Further, the observing the area characteristics of the suspected area includes the following steps:
when the suspected area exists in the shot image, continuously shooting a plurality of frames of photos;
performing the image processing and the region screening on the pictures of the subsequent frames to obtain a plurality of suspected regions;
comparing the suspected area in each subsequent frame with the position of the suspected area in the previous frame in the image;
and if the position of the suspected area in the previous frame is close to the position of the suspected area in the image, judging that the suspected area is the same as the suspected area in the previous frame.
Further, the step of, if the position of the suspected area in the previous frame is close to the position of the suspected area in the image, including:
respectively establishing a set of coordinates of pixel points in each suspected area in the image;
comparing the suspected area pixel point coordinate set in each subsequent frame with the suspected area pixel point coordinate set in the previous frame;
and if repeated pixel point coordinates in the suspected area pixel point coordinate set in the next frame and the suspected area pixel point coordinate set in the previous frame exceed a first threshold value, judging that the two suspected areas are the same suspected area.
Further, the first threshold is 80% of pixel coordinates in the suspected area pixel coordinate set of the previous frame.
Further, the step of, if the area of the suspected area increases with time, including:
counting the number of pixels in the pixel coordinate set in the suspected area in the previous and next frames;
and if the number of the pixel points in the same suspected area in the next frame is increased, determining that the area of the suspected area is increased along with time.
Further, after the area of the suspected area is judged to increase along with time, the suspected area with the area increasing along with time changing linearly is removed, and the suspected area with the area increasing along with time changing nonlinearly is judged as the flame area.
Further, when the color of the edge of each first region is determined, extracting R, G, B values of edge points of the first region, determining the color of the edge points, and when the edge points of the first region that are red exceed a second threshold, determining that the edge of the first region is red.
Further, when the high-frequency feature extraction is performed on the initial image, high-pass filtering is performed on the initial image, and then threshold segmentation is performed to extract a high-frequency region in the initial image, so that a plurality of first regions are obtained.
The invention also includes a flame detection device, comprising a camera and a computer device, wherein the camera is in communication connection with the computer device, the computer device comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, and the processor implements the method when executing the computer program.
The invention also comprises a storage medium having stored thereon a computer program which, when executed by a processor, implements the method as described above.
The beneficial effects of the invention are as follows: according to the method, through image acquisition, image processing, region screening and fire determination, a picture is taken in an oxidation furnace, after an initial image is obtained, high-frequency features in the image are extracted, high frequencies in the image often represent the positions of edges, details and even noise points in the image, after a plurality of first regions are obtained, the color of the edges of the first regions is judged, because a pre-oxidized fiber is burnt, the center of a flame region often appears bright white, and the edges of flames appear red, if the flame region is a flame region, the edges of the flame region are red, if the edges of the first regions are red, the flame region is judged to be a suspected region, and finally, in order to remove interference, the area features of the suspected region are observed.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments or the description of the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the present invention, and it is also possible for those skilled in the art to obtain other drawings based on the drawings without creative efforts.
FIG. 1 is a flow chart of a method of the present invention;
fig. 2 is a schematic structural diagram of a computer device according to 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.
As shown in fig. 1: a flame detection method based on area characteristics comprises the following steps:
image acquisition, namely photographing in an oxidation furnace to obtain an initial image;
image processing, namely performing high-frequency feature extraction on the initial image to obtain a plurality of first areas;
area screening, namely judging the color of the edge of each first area, and judging the first area as a suspected area when the edge of the first area is red;
and (3) determining the fire, observing the area characteristics of the suspected area, judging the suspected area as a flame area if the area of the suspected area is increased along with time, and giving an alarm.
The method comprises the steps of photographing an oxidation furnace through image acquisition, image processing, region screening and fire situation determination, extracting high-frequency features in an image after obtaining an initial image, wherein the high frequency in the image often represents the position of an edge, details and even noise points in the image, after obtaining a plurality of first regions, carrying out color judgment on the edge of the first region, and observing the area features of a suspected region for removing interference, wherein the center of the flame region often presents bright white and the edge of flame presents red.
In this embodiment, observing the area characteristics of the suspected region includes the following steps:
when a suspected area exists in a shot image, continuously shooting a plurality of frames of photos;
carrying out image processing and region screening on the pictures of the subsequent frames to obtain a plurality of suspected regions;
comparing the position of the suspected area in each subsequent frame with the position of the suspected area in the previous frame in the image;
and if the position of the suspected area in the previous frame is close to the position of the suspected area in the image in the previous frame, judging that the suspected area is the same as the suspected area in the previous frame.
Since the area characteristics need to be observed to determine the relationship between the area and the time, the camera takes pictures one frame by one frame, and the frame rate of the camera is generally fixed, the time change can be determined according to the number of the pictures, and the pictures of the previous and next frames are independent from each other, so that the same suspected area in the pictures of the previous and next frames needs to be found out, and the change of the suspected area in the previous and next frames is observed to obtain the change of the area with the time.
When judging whether the suspected areas in the pictures of the previous and next frames are the same or not, judging according to the positions of the suspected areas in the pictures, wherein the time interval of each frame is short, so that the suspected areas in the previous and next frames do not change greatly, and when judging whether the positions of the suspected areas in the previous and next frames in the pictures are close to each other or not, the method comprises the following steps:
respectively establishing a set of coordinates of pixel points in each suspected area in the image;
comparing the suspected area pixel point coordinate set in each subsequent frame with the suspected area pixel point coordinate set in the previous frame;
and if repeated pixel point coordinates in a suspected area pixel point coordinate set in the next frame and a suspected area pixel point coordinate set in the previous frame exceed a first threshold value, judging that the two suspected areas are the same suspected area.
By judging the coordinates of the pixel points of the suspected areas in the previous and next frames, if the coordinates of the pixel points in the two suspected areas are repeated, the positions of most of the pixel points in the two suspected areas are the same, and therefore the two suspected areas can be judged to be the same suspected area at different time.
As a preferred example of the foregoing embodiment, the first threshold is 80% of pixel coordinates in the suspected area pixel coordinate set of the previous frame.
In this embodiment, if the area of the suspected area increases with time, the method includes:
counting the number of pixels in a pixel coordinate set in a suspected area in the previous frame and the later frame;
and if the number of the pixel points in the same suspected area in the next frame is increased, determining that the area of the suspected area is increased along with time.
And after judging that the area of the suspected area is increased along with time, removing the suspected area of which the area is increased along with time and changing linearly, and judging the suspected area of which the area is increased along with time and changing nonlinearly as a flame area.
Because the combustion process of the flame in the oxidation furnace is deflagration, the flame can be rapidly expanded in a short time and is reflected in the area characteristic, the area of the flame is increased along with the time, but the increasing process is in a nonlinear relation with the time, through the characteristic, the interference can be further removed, the identification accuracy is ensured, the suspected area with the area increasing along with the time and linear change is removed, the suspected area with the nonlinear change is judged as the flame area, and therefore an alarm signal is sent out, and precious time is provided for subsequent fire extinguishment and personnel evacuation.
In this embodiment, when performing color determination on the edge of each first region, extracting R, G, B values of edge points of the first region, determining the color of the edge points, and when the edge point of the first region that is red exceeds the second threshold, determining that the edge of the first region is red.
The edge color of the first area can be judged by R, G, B values of the edge points, if the R value of one edge point is very high and is much higher than the G value and the B value, the edge point reflects a red feature, and when the number of the red edge points in the edge points of the first area is larger, the edge of the first area is red as a whole, so that the suspected area is judged.
As a preferred example of the above embodiment, when performing high-frequency feature extraction on the initial image, high-pass filtering is performed on the initial image, and then threshold segmentation is performed to extract high-frequency regions in the initial image, so as to obtain a plurality of first regions.
Because the oxidation furnace is in a darker state when in work, and only the pre-oxidized fiber in the oxidation furnace passes through the oxidation furnace, the detection background is single, so after an initial image is shot, high-pass filtering is carried out on the initial image, high-frequency signals in the image are amplified and enhanced, the flame characteristics are more obvious, namely, the image is sharpened to a certain degree, the flame area is more prominent conveniently, and subsequent identification is facilitated.
Also included in this embodiment is a flame detection device comprising a camera and a computer device, the camera and the computer device being communicatively coupled.
In this embodiment, only a plurality of frames of photos before and after need, can carry out accurate discernment to the flame region to shorten the time that the condition of a fire detected to the millisecond level, and discernment accuracy is high.
Please refer to fig. 2, which illustrates a schematic structural diagram of a computer device according to an embodiment of the present application. The embodiment of the present application provides a computer device 400, including: a processor 410 and a memory 420, the memory 420 storing a computer program executable by the processor 410, the computer program performing the method as above when executed by the processor 410.
The embodiment of the present application also provides a storage medium 430, where the storage medium 430 stores a computer program, and the computer program is executed by the processor 410 to perform the method as above.
The storage medium 430 may be implemented by any type of volatile or nonvolatile storage device or combination thereof, such as a Static Random Access Memory (SRAM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), an Erasable Programmable Read-Only Memory (EPROM), a Programmable Read-Only Memory (PROM), a Read-Only Memory (ROM), a magnetic Memory, a flash Memory, a magnetic disk or an optical disk.
In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implying any number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. The meaning of "plurality" is two or more unless specifically limited otherwise.
In the present invention, unless otherwise expressly stated or limited, the terms "mounted," "connected," "secured," and the like are to be construed broadly and can, for example, be fixedly connected, detachably connected, or integrally formed; can be mechanically or electrically connected; they may be directly connected or indirectly connected through intervening media, or may be connected through the use of two elements or the interaction of two elements. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
In the description of the specification, reference to the description of "one embodiment," "some embodiments," "an example," "a specific example," or "some examples" or the like means 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 are not necessarily intended to 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. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and alternate implementations are included within the scope of the preferred embodiment of the present invention in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present invention.
The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc. Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.
Claims (10)
1. A flame detection method based on area characteristics is characterized by comprising the following steps:
image acquisition, namely taking a picture of the inside of the oxidation furnace to obtain an initial image;
image processing, namely performing high-frequency feature extraction on the initial image to obtain a plurality of first areas;
area screening, namely judging the color of the edge of each first area, and judging the first area as a suspected area when the edge of the first area is red;
and determining the fire, observing the area characteristics of the suspected area, judging the suspected area as a flame area if the area of the suspected area is increased along with time, and giving an alarm.
2. The area signature-based flame detection method of claim 1, wherein the observing the area signature of the suspected region comprises:
when the suspected area exists in the shot image, continuously shooting a plurality of frames of photos;
performing the image processing and the region screening on the pictures of the subsequent frames to obtain a plurality of suspected regions;
comparing the suspected area in each subsequent frame with the position of the suspected area in the previous frame in the image;
and if the position of the suspected area in the previous frame is close to the position of the suspected area in the image, judging that the suspected area is the same as the suspected area in the previous frame.
3. The area-based feature flame detection method of claim 2, wherein the step of, if the suspected area in the previous frame is close to the position of the suspected area in the image, comprises:
respectively establishing a set of coordinates of pixel points in each suspected area in the image;
comparing the suspected area pixel point coordinate set in each subsequent frame with the suspected area pixel point coordinate set in the previous frame;
and if repeated pixel point coordinates in the suspected area pixel point coordinate set in the next frame and the suspected area pixel point coordinate set in the previous frame exceed a first threshold value, judging that the two suspected areas are the same suspected area.
4. The area feature based flame detection method of claim 3, wherein the first threshold is 80% of the pixel coordinates in the suspected region pixel coordinate set of the previous frame.
5. The area-based feature flame detection method of claim 3, wherein the step of, if the area of the suspected region increases with time, comprises:
counting the number of pixels in the coordinate sets of the pixels in the suspected areas in the previous and next frames;
and if the number of the pixel points in the same suspected area in the next frame is increased, determining that the area of the suspected area is increased along with time.
6. The area-feature-based flame detection method according to claim 5, wherein, after determining that the area of the suspected region increases with time, the suspected region whose area increases linearly with time is removed, and the suspected region whose area increases non-linearly with time is determined as the flame region.
7. The area-feature-based flame detection method according to claim 1, wherein when determining the color of the edge of each of the first regions, extracting R, G, B values of edge points of the first region, determining the color of the edge points, and when the edge points of the first region that are red exceed a second threshold, determining that the edge of the first region is red.
8. The area feature-based flame detection method according to claim 1, wherein when the high-frequency feature extraction is performed on the initial image, high-pass filtering is performed on the initial image, and then a threshold segmentation is performed to extract a high-frequency region in the initial image, so as to obtain a plurality of first regions.
9. A flame detection device comprising a camera and a computer device, the camera and the computer device being communicatively connected, the computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, when executing the computer program, implementing the method of any one of claims 1-8.
10. A storage medium on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1-8.
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