CN115394040A - Flame detection method, computer equipment and storage medium - Google Patents
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- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
- G06V10/25—Determination of region of interest [ROI] or a volume of interest [VOI]
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
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- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/56—Extraction of image or video features relating to colour
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- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
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Abstract
The invention relates to the technical field of carbon fiber production detection, in particular to a flame detection method, computer equipment and a storage medium, wherein the method comprises the following steps: acquiring an image, and taking a picture of the inside of the oxidation furnace to obtain a first image; image processing, namely performing high-frequency feature extraction on the first image to obtain a plurality of high-frequency regions; image identification, namely, judging the color of edge pixel points in each high-frequency region, and judging the edge pixel points as suspected flame regions when the proportion of red pixel points in the edge pixel points exceeds a first threshold; and (4) area screening, namely observing the intensity characteristic of the suspected flame area, judging the suspected flame area as the flame area if the intensity characteristic is increased along with the time, and giving an alarm. According to the invention, through image acquisition, image processing, image identification and area screening, the corresponding speed of flame identification is high, flame identification and alarm can be completed within 1 second, and precious time is won for subsequent fire extinguishment.
Description
Technical Field
The invention relates to the technical field of carbon fiber production detection, in particular to a flame detection method, computer equipment 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 and carbonization process of PAN-based carbon fiber comprises the procedures of pre-oxidation, low-temperature carbonization, high-temperature carbonization, surface treatment, sizing, drying and the like. The linear molecular chain of the PAN protofilament gradually forms a heat-resistant trapezoidal structure in the process, the PAN protofilament 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 the fiber, 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 oxidation furnace is on fire, because the high temperature in the oxidation furnace, the phenomenon of detonation takes place in the oxidation furnace very easily, it may only be short several seconds time to spread to whole oxidation furnace from the intensity of a fire to the intensity of a fire, moreover 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 flee 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 temperature in an oxidation furnace is often detected through a PT100 type platinum thermal resistor, and when the temperature is sensed to exceed a set fire early warning value, a fire signal is sent out. However, although the PT100 type platinum thermal resistor has high measurement accuracy, it is a conventional slow temperature measuring device, when the flame in the furnace makes the temperature of the PT100 type platinum thermal resistor exceed the fire predetermined value and send out a fire alarm signal, the process is expected to pass over 3 seconds, at this time, it is not time 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, computer equipment and a storage medium, thereby effectively solving the problems in the background art.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows: a method of flame detection comprising the steps of:
acquiring an image, and taking a picture of the inside of the oxidation furnace to obtain a first image;
image processing, namely performing high-frequency feature extraction on the first image to obtain a plurality of high-frequency regions;
image identification, namely, judging the color of edge pixel points in each high-frequency region, and judging the edge pixel points as suspected flame regions when the proportion of red pixel points in the edge pixel points exceeds a first threshold;
and (4) area screening, namely observing the intensity characteristic of the suspected flame area, judging the suspected flame area as the flame area if the intensity characteristic is increased along with time, and giving an alarm.
Furthermore, in the image processing, the first image is subjected to high-pass filtering to obtain a second image, and then the second image is subjected to threshold segmentation to extract a plurality of high-frequency regions.
Further, the image recognition comprises the following steps:
the method comprises the following steps: extracting the edge points of the high-frequency area and establishing an edge point set
Wherein
Respectively as the coordinates of n edge points;
step two: extracting the R, G and B characteristics of each edge point, and judging the color of each edge point;
step three: if the edge point is red, the initial value of k = k +1 is 0;
step four: and traversing n edge points in the set A, and when k/n is larger than the first threshold value, judging that the high-frequency area is a suspected flame area.
Further, the step two, when determining the color, includes: and when the R value of the edge point is greater than the second threshold value, the R-G value is greater than the third threshold value, and the R-B value is greater than the third threshold value, judging that the edge point is red.
Further, the first threshold is 80%.
Further, the observing the suspected flame area intensity characteristic includes the following steps:
calculating the Euclidean distance between any two pixel points in each suspected flame area;
screening out the longest Euclidean distance in each suspected flame area;
and judging the variation relation of the longest Euclidean distance of each suspected flame area with time.
Further, after the suspected flame area exists in the image, a plurality of frames of pictures are continuously taken, and when the longest Euclidean distance of the suspected flame area in the pictures of the subsequent frames is gradually increased and the change value of the longest Euclidean distance is in nonlinear correlation with time, the picture is judged to be the flame area.
Further, in the subsequent frame of photos, if a plurality of repeated pixel points exist in the suspected flame area and the suspected flame area in the previous frame, the suspected flame area is determined to be the same.
The invention also includes a computer device comprising a camera, a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the camera is in communication with the processor, and the processor executes the computer program to implement the method as described above.
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 invention has the beneficial effects that: the method comprises the steps of extracting high-frequency characteristics from a first image through image acquisition, image processing, image identification and area screening, wherein the high frequency in the image often represents the position of an edge, details or even a noise point in the image, after a high-frequency area is obtained, color judgment is carried out on edge pixel points in the high-frequency area, when pre-oxidized fibers are burnt, the center of a flame area often appears bright white, the edge of flame appears red, when the proportion of the red pixel points in the edge pixel points in the high-frequency area exceeds a certain proportion, the flame area is judged to be a suspected flame area, because the intensity of flame is increased in the burning process of the flame, the intensity characteristics of the suspected flame area are observed, if the intensity characteristics are increased along with time, the flame area is judged to be the flame area, and an alarm is given out.
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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 description of the embodiments or 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 for those skilled in the art, other drawings can be obtained according to 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 method of flame detection comprising the steps of:
acquiring an image, and taking a picture of the inside of the oxidation furnace to obtain a first image;
image processing, namely performing high-frequency feature extraction on the first image to obtain a plurality of high-frequency regions;
image identification, namely, judging the color of edge pixel points in each high-frequency region, and judging the edge pixel points as suspected flame regions when the proportion of red pixel points in the edge pixel points exceeds a first threshold;
and (4) area screening, namely observing the intensity characteristic of the suspected flame area, judging the suspected flame area as the flame area if the intensity characteristic is increased along with the time, and giving an alarm.
The method comprises the steps of extracting high-frequency features from a first image through image acquisition, image processing, image identification and region screening, wherein the high frequency in the image often represents the position of an edge, details and even noise points in the image, after a high-frequency region is obtained, color judgment is carried out on edge pixel points in the high-frequency region, when pre-oxidized fibers are burnt, the center of a flame region often appears bright white, the edge of flame appears red, when the proportion of the red pixel points in the edge pixel points in the high-frequency region exceeds a certain proportion, the flame region is judged to be a suspected flame region, and because the intensity of flame is increased in the burning process of the flame, the intensity features of the suspected flame region are observed, if the intensity features are increased along with time, the flame region is judged to be the flame region, and an alarm is given out.
In this embodiment, in the image processing, the first image is first subjected to high-pass filtering to obtain the second image, and then the second image is subjected to threshold segmentation to extract a plurality of high-frequency regions.
When the oxidation furnace works, the furnace is usually in a dark state, only a pre-oxidation wire in the oxidation furnace penetrates through the oxidation furnace, and the detection background is single, so that after a first image is shot, high-pass filtering is carried out on the first 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.
The image recognition comprises the following steps:
the method comprises the following steps: extracting edge points of the high-frequency area and establishing an edge point set
Wherein
Respectively are the coordinates of n edge points;
step two: extracting the R, G and B characteristics of each edge point, and judging the color of each edge point;
step three: if the edge point is red, k = k +1, k is 0;
step four: and traversing n edge points in the set A, and when k/n is greater than a first threshold value, judging that the high-frequency area is a suspected flame area, wherein the first threshold value is 80%.
After the high-frequency area is screened out, extracting edge points of the high-frequency area according to flame features, then extracting R, G and B features of each edge point to judge the color of the edge point, counting after judging that one edge point is red, and further, k = k +1, the initial value of k is 0, after traversing each edge point in the set, obtaining the number of all red edge points, dividing the number by the total value of all edge points of the high-frequency area to obtain the proportion of red pixel points in the edge point, if the proportion is high, for example, the proportion exceeds 80%, most edges of the high-frequency area are red, and the flame features are preliminarily met, so that the flame area is judged to be the meaning flame area.
Preferably, in the second step, the determining the color includes: and when the R value of the edge point is greater than the second threshold value, the R-G value is greater than the third threshold value, and the R-B value is greater than the third threshold value, judging that the edge point is red.
When a pixel point is red, the component value of R is larger, and the component value of R is much larger than the values of the other two components G and B, so that whether the pixel point is red or not is judged according to the R value of the pixel point and the difference values of R, G and B.
In this embodiment, observing the intensity characteristics of the suspected flame area includes the following steps:
calculating the Euclidean distance between any two pixel points in each suspected flame area;
screening the longest Euclidean distance in each suspected flame area;
and judging the variation relation of the longest Euclidean distance of each suspected flame area with time.
In a fire scene, the flame height is generally used to represent the flame intensity, in this embodiment, the euclidean distance is used to measure the height of an area, and since the image captured by the camera in the image processing is a two-dimensional frame image, a formula for calculating the euclidean distance in two dimensions and a formula for calculating the linear distance between two points are used.
After the suspected flame area exists in the image, a plurality of frames of pictures are continuously shot, and when the longest Euclidean distance of the suspected flame area in the pictures of the subsequent frames is gradually increased and the change value of the longest Euclidean distance is in nonlinear correlation with time, the suspected flame area is judged.
The distance between any two points in each suspected flame area is calculated, because the edge points are extracted in image recognition, the distance between every two edge points in the set A can be calculated here to find out the maximum value of the Euclidean distance, if the longest Euclidean distance of one suspected flame area increases along with the increase of time, the area is in an expanded state, and the expansion of the area and the time are in a nonlinear relation according to the characteristics of flame combustion, so that when the longest Euclidean distance of one suspected flame area is judged to be increased along with the increase of time and to be in a nonlinear relation, the flame area can be judged to be one flame area, and the suspected flame area in the linear relation is removed, so that the interference is prevented, the recognition accuracy is increased, the misjudgment is prevented, and the production cost is increased.
When the relationship between the longest euclidean distance and the time is judged, because the camera is used for taking a picture of one frame and one frame, and the number of frames taken by the camera is generally fixed, the change of the time can be judged according to the number of frames of the picture, and the pictures of the previous frame and the next frame are mutually independent, so that after the suspected flame area is judged in the picture of the previous frame, the same suspected flame area needs to be found out from the picture of the next frame, otherwise, the intensity characteristics in time cannot be compared, when the same suspected flame area is judged, the change is small according to the short time interval and the small change of each frame, the same suspected flame area in the pictures of the previous frame and the next frame has small difference and possibly contains most repeated pixel point coordinates, so that in the pictures of the subsequent frames, a plurality of repeated pixel points exist in the suspected flame area and the suspected flame area of the previous frame, the same suspected flame area is judged, and the longest euclidean distance is monitored according to the time.
In the embodiment, flame can be accurately identified only according to the change of the suspected flame area in a plurality of frames before and after, the detection time of the flame can be controlled to be greatly reduced to reach the millisecond level by the identification processing of the image, and valuable time is provided for the subsequent fire extinguishment and personnel protection of the flame.
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 camera, 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 explicitly defined otherwise.
In the present invention, unless otherwise explicitly stated or limited, the terms "mounted," "connected," "fixed," and the like are to be construed broadly, e.g., as being permanently connected, detachably connected, or integral; can be mechanically or electrically connected; either directly or indirectly through intervening media, either internally or in any other relationship. 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 technologies, which are well 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 out in the method of 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 the program, when executed, 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 method of flame detection, comprising the steps of:
acquiring an image, and taking a picture of the inside of the oxidation furnace to obtain a first image;
image processing, namely performing high-frequency feature extraction on the first image to obtain a plurality of high-frequency regions;
image recognition, namely performing color judgment on edge pixel points of each high-frequency region, and judging the edge pixel points as suspected flame regions when the proportion of red pixel points in the edge pixel points exceeds a first threshold value;
and (4) area screening, namely observing the intensity characteristic of the suspected flame area, judging the suspected flame area as the flame area if the intensity characteristic is increased along with time, and giving an alarm.
2. The flame detection method according to claim 1, wherein in the image processing, the first image is high-pass filtered to obtain a second image, and then the second image is subjected to threshold segmentation to extract a plurality of high-frequency regions.
3. The flame detection method according to claim 1, wherein the image recognition comprises the steps of:
the method comprises the following steps: extracting the edge points of the high-frequency area and establishing an edge point set
Wherein
Respectively are the coordinates of n edge points;
step two: extracting the R, G and B characteristics of each edge point, and judging the color of each edge point;
step three: if the edge point is red, k = k +1, k is 0;
step four: and traversing n edge points in the set A, and when k/n is larger than the first threshold value, judging that the high-frequency area is a suspected flame area.
4. The flame detection method according to claim 3, wherein the second step of determining the color of the flame includes: and when the R value of the edge point is greater than the second threshold value, the R-G value is greater than the third threshold value, and the R-B value is greater than the third threshold value, judging that the edge point is red.
5. The flame detection method of claim 3, wherein the first threshold is 80%.
6. The flame detection method of claim 1, wherein the observing the suspected flame region intensity characteristic comprises:
calculating the Euclidean distance between any two pixel points in each suspected flame area;
screening out the longest Euclidean distance in each suspected flame area;
and judging the variation relation of the longest Euclidean distance of each suspected flame area with respect to time.
7. The flame detection method according to claim 6, wherein after the suspected flame area is determined to exist in the image, a plurality of frames of photographs are continuously taken, and when the longest Euclidean distance of the suspected flame area in the photographs of the subsequent frames is gradually increased and the change value of the longest Euclidean distance is non-linearly related to time, the suspected flame area is determined to be the flame area.
8. The flame detection method according to claim 7, wherein in a subsequent frame of photograph, if there are a plurality of repeated pixel points in the suspected flame area and the suspected flame area in a previous frame, it is determined that the suspected flame area is the same.
9. A computer device comprising a camera, a memory, a processor, and a computer program stored on the memory and executable on the processor, the camera being communicatively connected to the processor, the processor implementing the method of any one of claims 1-8 when executing the computer program.
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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| CN117593588A (en) * | 2023-12-14 | 2024-02-23 | 小黄蜂智能科技(广东)有限公司 | Intelligent identification method and device for flame image |
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