CN117518175A - Method for rapidly finding fire source by infrared Zhou Saolei reaching wide area range - Google Patents
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Abstract
The invention provides a method for rapidly finding a fire source by infrared Zhou Saolei reaching a wide area range, and belongs to the technical field of fire source identification. Comprising the following steps: s1, acquiring monitoring area data; s2, extracting flame appearances and image features of high-temperature hot spots under different distances and different weather by using the monitoring area data; s3, deep learning is carried out by utilizing the image features of the flame model and the high-temperature hot spot, and a database of the flame model and the high-temperature hot spot is established; s4, processing flame appearances and high-temperature point image features under different distances and different weather, and expanding the number of samples of a flame model and a database of high-temperature hot spots; s5, acquiring a monitoring area, and judging whether a fire point is found; s6, calculating the flame area change rate of the ignition point; s7, analyzing whether the ignition point continuously maintains the characteristics of the fire source and accompanies the expansion and movement spreading trend according to the change rate of the flame area, and if so, giving an early warning; solves the problem that the fire source can not be found rapidly.
Description
Technical Field
The invention relates to a method for finding a fire source, in particular to a method for quickly finding the fire source by infrared Zhou Saolei reaching a wide area range, and belongs to the technical field of fire source identification.
Background
In the open field or dense jungle of Liaoku, when the fire phenomenon occurs due to the geographical property reasons, monitoring staff cannot find out in time, if no people find out the occurrence of the fire situation for a long time, the fire situation becomes larger, the fire situation is larger, the fire is more difficult to extinguish, even the fire source cannot be controlled, the property loss which cannot be estimated is caused, if the time for finding out the fire source is shortened, the fire spreading can be controlled at the initial stage of the fire, the fire fighting efficiency is improved, and the loss caused by the fire spreading is reduced. If the fire is not happened or is about to happen, the situation that the fire is likely to happen can be realized, the fire is prevented, and the fire fighting and the fire source monitoring can be well performed.
Disclosure of Invention
The following presents a simplified summary of the invention in order to provide a basic understanding of some aspects of the invention. It should be understood that this summary is not an exhaustive overview of the invention. It is not intended to identify key or critical elements of the invention or to delineate the scope of the invention. Its purpose is to present some concepts in a simplified form as a prelude to the more detailed description that is discussed later.
In view of this, in order to solve the technical problem that the fire source cannot be found rapidly in the prior art, the invention provides a method for finding the fire source rapidly in a wide area range by infrared Zhou Saolei.
Scheme one, a method for rapidly discovering fire sources by infrared Zhou Saolei reaching a wide area range, comprises the following steps:
s1, acquiring monitoring area data by using an infrared panoramic imaging radar;
s2, extracting flame appearances and image features of high-temperature hot spots under different distances and different weather by using the monitoring area data;
s3, deep learning is carried out by utilizing the image features of the flame model and the high-temperature hot spot, and a database of the flame model and the high-temperature hot spot is established;
s4, processing flame appearances and high-temperature point image features under different distances and different weather, and expanding the number of samples of a flame model and a database of high-temperature hot spots;
s5, acquiring a monitoring area, and judging whether a fire point is found;
s6, calculating the flame area change rate of the ignition point;
s7, analyzing whether the ignition point continuously maintains the characteristics of the fire source and accompanies the expansion and movement spreading trend according to the change rate of the flame area, and giving an early warning if the continuously maintains the characteristics of the fire source and accompanies the expansion and movement spreading trend.
Preferably, the method for deep learning by utilizing the flame model and the image features of the high-temperature hot spot comprises the following steps:
s31, establishing a neural network, wherein the weight of the neural network is a membership function in a fuzzy rule;
s32, inputting training samples in a flame model and a database of high-temperature hot spots into a neural network, training the neural network, searching an optimal membership function during training the neural network, continuously modifying the membership, and expressing each membership of input variables by using the membership function of a Gaussian model, wherein the formula is as follows:
wherein x is i C is the variation value of the high-temperature hot spot i Is the center of the membership function; sigma (sigma) i Standard deviation as a gaussian membership function;
s33, extracting the modified membership function and the fuzzy rule from the neural network, and storing the membership function and the fuzzy rule.
Preferably, the method for establishing the flame model and the database of the high-temperature hot spots is as follows: and (3) performing the processes of turning over, denoising and sharpening on the flame appearance and the high-temperature point image characteristics under different distances and different weather conditions.
Preferably, the method for acquiring the monitoring area and judging whether the ignition point is found is as follows: and acquiring monitoring area data by using an infrared panoramic imaging radar, comparing the monitoring area data with sample data of a flame model and a database of high-temperature hot spots, and judging that the ignition point is found when the similarity of the feature comparison reaches 85%.
Preferably, the method for changing the flame area rate is as follows:
the area growth rate of the flame hot spot area is calculated to express the area growth rate of the fire source, and the pixel change rate in the image area is used to express the area growth rate of the flame hot spot area, specifically: let Y be the total pixel value of the target region at time t, the total pixel value of the target region in the ith frame can be Y i The total pixel value of the i+1th frame is Y i+1 And the area of the region of the ith frame is S i The (i+1) th frame area is Si+1 The area change rate of the flame in the successive video frames is:
wherein DeltaB represents the change rate of flame area, and the time range is t i To t i+1 In the interval period, j represents the j-th frame, and i+j represents the i+j-th frame.
Preferably, the method for analyzing whether the ignition point continuously maintains the characteristic of the fire source and accompanies the expansion and the movement spreading trend according to the change rate of the flame area, and if the characteristic of the fire source continuously maintains and accompanies the expansion and the movement spreading trend, the method for making the early warning comprises the following steps: setting a flame area change rate threshold, judging that the flame source characteristics are continuously maintained and the flame source characteristics are accompanied by expansion and movement and spreading trend when the flame area change rate is larger than the set threshold, making early warning, and not making early warning when the flame area change rate is smaller than the set threshold.
The second scheme is an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the method for quickly discovering fire sources in a wide area range by using the infrared Zhou Saolei of the first scheme when executing the computer program.
A third aspect is a computer readable storage medium having a computer program stored thereon, the computer program when executed by a processor implementing a method for quickly discovering a fire source over a wide area by infrared Zhou Saolei as set forth in the first aspect.
The beneficial effects of the invention are as follows: according to the invention, the built infrared panoramic imaging radar video monitoring mode is used for rapidly scanning the hot spot in the wide area range, and the radar is used for rapidly judging and alarming the fire source in the coverage area in the circumferential scanning process, so that the fire source is rapidly discovered, the fire condition is rapidly controlled, and the loss is reduced.
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The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention and do not constitute a limitation on the invention. In the drawings:
FIG. 1 is a flow chart of a method for rapidly discovering fire sources over a wide area by infrared Zhou Saolei.
Detailed Description
In order to make the technical solutions and advantages of the embodiments of the present invention more apparent, the following detailed description of exemplary embodiments of the present invention is provided in conjunction with the accompanying drawings, and it is apparent that the described embodiments are only some embodiments of the present invention and not exhaustive of all embodiments. It should be noted that, without conflict, the embodiments of the present invention and features of the embodiments may be combined with each other.
Example 1, the present embodiment is described with reference to fig. 1, which is a method for rapidly discovering a fire source by infrared Zhou Saolei in a wide area, comprising the steps of:
s1, acquiring monitoring area data by using an infrared panoramic imaging radar;
an infrared panoramic imaging radar is erected in a monitoring area, the monitoring range of the infrared panoramic imaging radar can be covered at a radius of about 10km for code scanning, and the frequency is 1Hz; if the monitoring of the area beyond 10km is required, a plurality of infrared panoramic imaging radars can be erected in the monitoring area;
s2, extracting flame appearances and image features of high-temperature hot spots under different distances and different weather by using the monitoring area data;
by extracting the flame appearance and the image characteristics of the high-temperature hot spot under different distances and different weather, the characteristics of the flame appearance and the high-temperature hot spot under different distances and different weather near the ignition point or in the ignition process can be obtained, and the possibility of finding the ignition point can be predicted according to the characteristic comparison of the different characteristics and the real-time data of the monitoring area.
The method for extracting the flame appearance and the image features of the high-temperature hot spot under different distances and different weather by the monitoring area data comprises the following steps: manually extracting, namely, circling the flame position on the image by a worker, wherein the flame position comprises images of all fire source areas; or artificial intelligence extraction;
s3, deep learning is carried out by utilizing the image features of the flame model and the high-temperature hot spot, and a database of the flame model and the high-temperature hot spot is established;
the method for deep learning by utilizing the flame model and the image features of the high-temperature hot spot comprises the following steps:
s31, identifying a high-temperature hot spot based on a fuzzy neural network, and firstly, establishing the neural network, wherein the weight of the neural network is a membership function in a fuzzy rule;
s32, inputting training samples in a flame model and a database of high-temperature hot spots into a neural network, training the neural network, searching an optimal membership function during training the neural network, continuously modifying the membership, and expressing each membership of input variables by using the membership function of a Gaussian model, wherein the formula is as follows:
wherein x is i C is the variation value of the high-temperature hot spot i Is the center of the membership function; sigma (sigma) i Standard deviation as a gaussian membership function;
s33, extracting a membership function and a fuzzy rule after modification from the neural network, and storing the membership function and the fuzzy rule so as to be used as fuzzy reasoning under the operation site environment; when the ignition point is actually found on site, the acquired high-temperature ignition point characteristics of the flame are input as input signals, and the data are calculated according to the network structure trained before, so that the most accurate output can be obtained.
The fuzzy neural network based on the Takagi-Surgeon model realizes the feature layer fusion of the ignition point high-temperature point detection and early warning method;
s4, processing flame appearances and high-temperature point image features under different distances and different weather, and expanding the number of samples of a flame model and a database of high-temperature hot spots;
the method for establishing the flame model and the database of the high-temperature hot spots comprises the following steps: the method comprises the steps of performing overturning, denoising and sharpening on flame appearances and high-temperature point image features under different distances and different weather;
s5, acquiring a monitoring area, and judging whether a fire point is found;
the method for acquiring the monitoring area and judging whether the ignition point is found is as follows: acquiring monitoring area data by using an infrared panoramic imaging radar, comparing the monitoring area data with sample data of a flame model and a database of high-temperature hot spots, and judging that a fire point is found when the similarity of the feature comparison reaches 85%;
s6, calculating the flame area change rate of the ignition point;
the method for the flame area change rate comprises the following steps:
the area growth rate of the flame hot spot area is calculated to express the area growth rate of the fire source, and the pixel change rate in the image area is used to express the area growth rate of the flame hot spot area, specifically: let Y be the total pixel value of the target region at time t, the total pixel value of the target region in the ith frame can be Y i The total pixel value of the i+1th frame is Y i+1 And the area of the region of the ith frame is S i The (i+1) th frame area is Si+1 The area change rate of the flame in the successive video frames is:
wherein DeltaB represents the change rate of flame area, and the time range is t i To t i+1 In the interval period, j represents the j-th frame, and i+j represents the i+j-th frame.
S7, analyzing whether the ignition point continuously maintains the characteristics of the fire source and accompanies the expansion and movement spreading trend according to the change rate of the flame area, and giving an early warning if the continuously maintains the characteristics of the fire source and accompanies the expansion and movement spreading trend, wherein the method comprises the following steps: setting a flame area change rate threshold, judging that the flame source characteristics are continuously maintained and the flame source characteristics are accompanied by expansion and movement and spreading trend when the flame area change rate is larger than the set threshold, making early warning, and not making early warning when the flame area change rate is smaller than the set threshold.
When the conditions of continuously keeping the characteristics of the fire source and accompanied with the expansion and movement and spreading trend occur, the position and the distance of the ignition point are recorded and stored while early warning is carried out.
In embodiment 2, the computer device of the present invention may be a device including a processor and a memory, for example, a single chip microcomputer including a central processing unit. And the processor is used for executing the computer program stored in the memory to realize the method for quickly finding the fire source by the infrared Zhou Saolei in a wide area range.
The processor may be a central processing unit (Central Processing Unit, CPU), other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program (such as a sound playing function, an image playing function, etc.) required for at least one function, and the like; the storage data area may store data (such as audio data, phonebook, etc.) created according to the use of the handset, etc. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as a hard disk, memory, plug-in hard disk, smart Media Card (SMC), secure Digital (SD) Card, flash Card (Flash Card), at least one disk storage device, flash memory device, or other volatile solid-state storage device.
Embodiment 3, a computer-readable storage medium embodiment.
The computer readable storage medium of the present invention may be any form of storage medium that is read by a processor of a computer device, including but not limited to a nonvolatile memory, a volatile memory, a ferroelectric memory, etc., on which a computer program is stored, and when the processor of the computer device reads and executes the computer program stored in the memory, the steps of a traffic congestion state prediction method described above may be implemented.
The computer program comprises computer program code which may be in source code form, object code form, executable file or in some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth. It should be noted that the computer readable medium contains content that can be appropriately scaled according to the requirements of jurisdictions in which such content is subject to legislation and patent practice, such as in certain jurisdictions in which such content is subject to legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunication signals.
While the invention has been described with respect to a limited number of embodiments, those skilled in the art, having benefit of the above description, will appreciate that other embodiments are contemplated within the scope of the invention as described herein. Furthermore, it should be noted that the language used in the specification has been principally selected for readability and instructional purposes, and may not have been selected to delineate or circumscribe the inventive subject matter. Accordingly, many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the appended claims. The disclosure of the present invention is intended to be illustrative, but not limiting, of the scope of the invention, which is defined by the appended claims.
Claims (8)
1. A method for rapidly discovering fire sources by infrared Zhou Saolei in a wide area range, which is characterized by comprising the following steps:
s1, acquiring monitoring area data by using an infrared panoramic imaging radar;
s2, extracting flame appearances and image features of high-temperature hot spots under different distances and different weather by using the monitoring area data;
s3, deep learning is carried out by utilizing the image features of the flame model and the high-temperature hot spot, and a database of the flame model and the high-temperature hot spot is established;
s4, processing flame appearances and high-temperature point image features under different distances and different weather, and expanding the number of samples of a flame model and a database of high-temperature hot spots;
s5, acquiring a monitoring area, and judging whether a fire point is found;
s6, calculating the flame area change rate of the ignition point;
s7, analyzing whether the ignition point continuously maintains the characteristics of the fire source and accompanies the expansion and movement spreading trend according to the change rate of the flame area, and giving an early warning if the continuously maintains the characteristics of the fire source and accompanies the expansion and movement spreading trend.
2. The method for quickly finding a fire source in a wide area range by using infrared Zhou Saolei as set forth in claim 1, wherein the method for deep learning by using the flame model and the image features of the high-temperature hot spot is as follows:
s31, establishing a neural network, wherein the weight of the neural network is a membership function in a fuzzy rule;
s32, inputting training samples in a flame model and a database of high-temperature hot spots into a neural network, training the neural network, searching an optimal membership function during training the neural network, continuously modifying the membership, and expressing each membership of input variables by using the membership function of a Gaussian model, wherein the formula is as follows:
wherein x is i C is the variation value of the high-temperature hot spot i Is the center of the membership function; sigma (sigma) i Standard deviation as a gaussian membership function;
s33, extracting the modified membership function and the fuzzy rule from the neural network, and storing the membership function and the fuzzy rule.
3. The method for quickly finding fire sources in a wide area range by infrared Zhou Saolei according to claim 2, wherein the method for establishing a flame model and a database of high-temperature hot spots is as follows: and (3) performing the processes of turning over, denoising and sharpening on the flame appearance and the high-temperature point image characteristics under different distances and different weather conditions.
4. A method for rapidly detecting a fire source over a wide area by infrared Zhou Saolei as claimed in claim 3, wherein the method for acquiring the monitored area and determining whether a fire is detected is as follows: and acquiring monitoring area data by using an infrared panoramic imaging radar, comparing the monitoring area data with sample data of a flame model and a database of high-temperature hot spots, and judging that the ignition point is found when the similarity of the feature comparison reaches 85%.
5. The method for rapidly detecting fire sources over a wide area by infrared Zhou Saolei as claimed in claim 4, wherein the method for changing the flame area is as follows:
calculating the area growth rate of the flame hot spot area to express the area growth rate of the fire source by usingThe pixel change rate in the image area represents the area growth rate of the flame hot spot area, specifically: let Y be the total pixel value of the target region at time t, the total pixel value of the target region in the ith frame can be Y i The total pixel value of the i+1th frame is Y i+1 And the area of the region of the ith frame is S i The (i+1) th frame area is Si+1 The area change rate of the flame in the successive video frames is:
wherein DeltaB represents the change rate of flame area, and the time range is t i To t i+1 In the interval period, j represents the j-th frame, and i+j represents the i+j-th frame.
6. The method for rapidly detecting a fire source in a wide area by using infrared Zhou Saolei according to claim 5, wherein the method for analyzing whether the fire point continuously maintains the fire source characteristic and accompanies the expanding and moving spread trend according to the flame area change rate, and if the fire point continuously maintains the fire source characteristic and accompanies the expanding and moving spread trend, the method for making an early warning is as follows: setting a flame area change rate threshold, judging that the flame source characteristics are continuously maintained and the flame source characteristics are accompanied by expansion and movement and spreading trend when the flame area change rate is larger than the set threshold, making early warning, and not making early warning when the flame area change rate is smaller than the set threshold.
7. An electronic device comprising a memory and a processor, the memory storing a computer program, the processor implementing the steps of a method of rapidly discovering a fire source over a wide area for infrared Zhou Saolei as claimed in any one of claims 1 to 6 when the computer program is executed.
8. A computer readable storage medium, having stored thereon a computer program which when executed by a processor implements a method of rapidly discovering a fire source over a wide area by infrared Zhou Saolei as claimed in any one of claims 1 to 6.
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