Method for recognition of flame pulsation frequency under action of sound field

Abstract

This invention discloses a method for identifying the pulsation frequency of a flame under the influence of an acoustic field. The method is validated using a back-diffusion flame as an example, identifying the pulsation frequency of the back-diffusion flame under different acoustic parameters. The method involves acquiring continuously changing flame images under different operating conditions using a non-invasive optical diagnostic system, binarizing the images to divide them into flame and non-flame regions, and calculating the overlap rate of each image relative to the first flame image. Analysis shows that the flame pulsation frequency can be determined by observing changes in the overlap rate. Experimental verification demonstrates that this method can accurately determine the flame pulsation frequency under different acoustic parameters.

Description

Technical Field

[0001] This invention belongs to the field of combustion technology, specifically relating to a method for identifying the frequency of flame pulsation under the influence of a sound field. Background Technology

[0002] The pollutants produced by the incomplete combustion of fossil fuels not only damage the climate but also pose serious threats to human health. Therefore, there is an urgent need for new combustion technologies to improve combustion efficiency and reduce pollutant emissions. Based on these requirements, the coupling of sound waves and flames has attracted widespread attention in recent years.

[0003] The addition of a sound field can influence flame behavior, including flame morphology, flame structure, chemical reaction rates, and the diffusion rates of fuel and oxidizer. Due to the periodic nature of sound waves, their interaction with a flame causes flame pulsation. However, due to physiological limitations, high-frequency flame pulsations are not visible to the naked eye. Therefore, this invention utilizes a high-speed camera combined with optical diagnostic methods to accurately capture the pulsation characteristics of the flame. Exploring the relationship between flame pulsation frequency and sound wave frequency helps deepen our understanding of flame behavior under the influence of a sound field. Summary of the Invention

[0004] The purpose of this invention is to provide a method for identifying the frequency of flame pulsation under the influence of a sound field. This is of great significance for the study of flame behavior dynamics under the influence of a sound field.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0006] A method for identifying the frequency of flame pulsation under the influence of a sound field, the method comprising the following steps:

[0007] Step 1: Use a camera to capture images of the flame as it changes continuously under different acoustic parameters;

[0008] Step 2: Use image processing software to convert the flame image into a grayscale image;

[0009] Step 3: Convert the grayscale image into a two-dimensional numerical matrix. The value of each element in the matrix represents the grayscale value of the corresponding pixel in the image, and its value ranges from 0 to 255.

[0010] Step 4: Set a grayscale threshold. Pixels with a grayscale value higher than the threshold are considered flames and their grayscale value is reset to 255. Pixels with a grayscale value lower than the threshold are considered non-flames and their grayscale value is reset to 0.

[0011] Step 5: Count the total number of pixels in the flame region after binarization of the first image, and record the two-dimensional position of the flame region in the image;

[0012] Step 6: Calculate the total number of pixels in the flame in the subsequent images that appear in the two-dimensional position recorded in the first image, calculate the overlap rate of the subsequent images relative to the first image, and analyze the variation pattern of the overlap rate.

[0013] Furthermore, the camera in step 1 is a high-speed camera.

[0014] Furthermore, the shooting frame rate in step 1 is set to an integer multiple of the sound wave frequency.

[0015] Furthermore, the camera in step 1 was in a fixed position during the experiment, and there were no other external light sources around it.

[0016] Furthermore, in step 1, the flame and sound field are in a fixed position, and there are no external sound sources around.

[0017] Furthermore, in step 4, the grayscale threshold is set to 40. Pixels with a grayscale value greater than 40 are considered flames, while pixels with a grayscale value less than 40 are considered non-flames.

[0018] Furthermore, in step 5, the total number of pixels is denoted as m1.

[0019] Furthermore, in step 6, the total number of pixels in the nth image where the flame appears at the two-dimensional position recorded in the first image is denoted as m. n .

[0020] Furthermore, in step 6, the flame overlap rate R of the subsequent nth image relative to the first image is defined as:

[0021]

[0022] Compared with the prior art, the present invention has the following advantages:

[0023] (1) The method of the present invention transforms the pulsation law of the flame into the two-dimensional position change law of the flame image, which simplifies the problem and is easy to operate;

[0024] (2) The present invention has clear judgment indicators and can accurately collect changes in flame pulsation frequency;

[0025] (3) This invention combines optical diagnosis with image post-processing, which has high precision and can capture flame pulsations that cannot be observed by the naked eye, which helps to understand the flame behavior characteristics under acoustic interference.

[0026] The present invention will now be further described with reference to the accompanying drawings. Attached Figure Description

[0027] Figure 1This is a grayscale image converted from continuous flame images captured by a high-speed camera under 200Hz acoustic interference.

[0028] Figure 2 This is the binarized image.

[0029] Figure 3 This is a graph showing the change in continuous grayscale image and overlap rate of a flame under 200Hz acoustic interference.

[0030] Figure 4 This is a graph showing the change in continuous grayscale image and overlap rate of a flame under 240Hz acoustic interference.

[0031] Figure 5 This is a graph showing the change in continuous grayscale image and overlap rate of a flame under 300Hz acoustic interference. Detailed Implementation

[0032] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the invention.

[0033] The present invention will be further described using an ethylene back-diffusion flame under sinusoidal acoustic interference as an example.

[0034] A method for identifying the frequency of flame pulsation under the influence of a sound field, the specific steps of which are as follows:

[0035] Step 1: In an environment without external light source, use a high-speed camera with a fixed position and shooting parameters to capture images of the pulsating flame under sound field interference.

[0036] Step 2: Use image processing software to convert the captured flame image into a grayscale image, such as... Figure 1 As shown.

[0037] Step 3: Convert the grayscale image into a two-dimensional numerical matrix. The value of each element in the matrix represents the grayscale value of the corresponding pixel in the image, and its value ranges from 0 to 255.

[0038] Step 4: Set a grayscale threshold. Pixels with a grayscale value higher than this threshold are considered flames and their grayscale value is reset to 255. Pixels with a grayscale value lower than this threshold are considered non-flames and their grayscale value is reset to 0. Here, the grayscale threshold is set to 40. The binarized image is as follows. Figure 2 As shown;

[0039] Step 5: Count the total number of pixels in the flame region after binarization of the first image, and record the two-dimensional position of the flame region in the image;

[0040] Step 6: Calculate the total number of pixels in the two-dimensional position of the flame in the subsequent images recorded in the first image, calculate the overlap rate of the subsequent images relative to the first image, analyze the variation law of the overlap rate, and calculate the overlap rate by formula (1).

[0041]

[0042] Where R is the overlap ratio, m1 is the total number of pixels in the flame region of the first binarized image, and m n This represents the number of pixels in the nth binarized image that overlap with the flame region in the first binarized image. For comparison, sinusoidal sound waves with frequencies of 200Hz, 240Hz, and 300Hz were selected, and the frame rate of the high-speed camera was set to 1200 frames per second to ensure that the sampling frequency is exactly an integer multiple of the sound wave signal frequency. Figure 3 , 4 Figures 5 and 6 show the changes in flame images and overlap rates at the three frequencies mentioned above. It can be observed that the overlap rate fluctuates regularly within a certain range. The periods of change in flame overlap rate under the action of 200Hz, 240Hz, and 300Hz sound waves are 6 / 1200 seconds, 5 / 1200 seconds, and 4 / 1200 seconds, respectively. This coincides with the period of the sound waves, indicating that the flame pulsation frequency under the action of sound waves is consistent with the sound wave frequency.

[0043] This invention uses a non-invasive optical diagnostic system to acquire continuously changing flame images under different operating conditions. The images are binarized, dividing them into flame and non-flame regions. The overlap rate of each image with respect to the first flame image is calculated. By observing changes in the overlap rate, the flame pulsation frequency is determined. This method can accurately determine the flame pulsation frequency under different acoustic parameters.

[0044] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for identifying the frequency of flame pulsation under the influence of a sound field, characterized in that, The method includes the following steps: Step 1: Use a camera to capture images of the flame as it changes continuously under different acoustic parameters; Step 2: Use image processing software to convert the flame image into a grayscale image; Step 3: Convert the grayscale image into a two-dimensional numerical matrix. The value of each element in the matrix represents the grayscale value of the corresponding pixel in the image, and its value ranges from 0 to 255. Step 4: Set a grayscale threshold. Pixels with a grayscale value higher than the threshold are considered flames and their grayscale value is reset to 255. Pixels with a grayscale value lower than the threshold are considered non-flames and their grayscale value is reset to 0. Step 5: Count the total number of pixels in the flame region after binarization of the first image, and record the two-dimensional position of the flame region in the image; Step 6: Calculate the total number of pixels in the flame in the subsequent images that appear in the two-dimensional position recorded in the first image, calculate the overlap rate of the subsequent images relative to the first image, and analyze the variation pattern of the overlap rate.

2. The method for identifying the frequency of flame pulsation under the action of a sound field according to claim 1, characterized in that, The camera in step 1 is a high-speed video camera.

3. The method for identifying the frequency of flame pulsation under the action of a sound field according to claim 1, characterized in that, The acoustic parameter is the sound wave frequency.

4. The method for identifying the frequency of flame pulsation under the action of a sound field according to claim 3, characterized in that, In step 1, the shooting frame rate is set to an integer multiple of the sound wave frequency.

5. The method for identifying the frequency of flame pulsation under the action of a sound field according to claim 1, characterized in that, The camera in step 1 was in a fixed position during the experiment, and there were no other external light sources around it.

6. The method for identifying the frequency of flame pulsation under the action of a sound field according to claim 1, characterized in that, In step 1, the flame and sound field are in a fixed position and there are no external sound sources around.

7. The method for identifying the frequency of flame pulsation under the action of a sound field according to claim 1, characterized in that, In step 4, the grayscale threshold is set to 40. Pixels with a grayscale value greater than 40 are considered flames, while pixels with a grayscale value less than 40 are considered non-flames.

8. The method for identifying the frequency of flame pulsation under the action of a sound field according to claim 1, characterized in that, In step 5, the total number of pixels is denoted as m1.

9. The method for identifying the frequency of flame pulsation under the action of a sound field according to claim 1, characterized in that, In step 6, the total number of pixels in the nth image where the flame appears at the two-dimensional position recorded in the first image is denoted as m. n .

10. The method for identifying the frequency of flame pulsation under the action of a sound field according to claim 1, characterized in that, In step 6, the flame overlap rate R of the subsequent nth image relative to the first image is defined as:

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