# Prediction Method of Swirling Flame Lean Blowout Based on Flame Image Morphological Features
## 3 Prediction Method Based on Flame Image Morphological Features
### Extraction of Flame Morphological Features  
During the oscillation process of the lean premixed flame, the flame area, and chemiluminescence intensity will change significantly. At the same time, the back-and-forth jump of the flame from the standing state to the floating state, the wrinkling of the flame edge, and the local extinguish phenomenon inside the flame are all image features that can be observed from the flame image and reflect the combustion state of the lean premixed flame. Therefore, the frequency and degree of the occurrence of the phenomena mentioned before can be captured by the feature extraction of the flame image so as to obtain the details and progress of the reacting flow process in the lean premixed combustion system. As a result, the subsequent prediction process of the flame blowout state of the lean premixed flame will have strong explainability. Based on the image features mentioned above, we design the experimental image processing process shown in Figure 3 and extract the required features. First, we use the threshold method to zero the pixel with a value below half to remove the background noise. Then, the image is low-pass filtered through a fast Fourier transform to convert the dot-like distribution of pixels in the area with weak light intensity into a cloud map. After that, the value range is adjusted and then the threshold truncation treatment is done again to strip out the flame area. For the obtained flame contour image, the position of the lower edge of the flame \(h\) is found by searching for the lowest point of the flame contour. The flame area \(S\) is obtained by directly summing the normalized pixel values. The flame edge extraction is carried out by using the Canny edge detection algorithm [38], where the high  
Figure 2: A flow chart of the prediction method. \(x(t)\) is the extracted morphological feature vector at the \(t\) moment, \(X(t;k)\) is the combined morphological feature vector with the information of the \(k\) length time series, and \(y(t)\) is the corresponding blowout state. and low thresholds of the \"strong\" edge are 200 and 130, and the high and low thresholds of the \"weak\" edge are 130 and 20, respectively. Finally, the normalized pixel results of the obtained \"strong\" and \"weak\" edges are summed to obtain the length of the flame \"weak\" edge \(L\) and the difference between the length of flame \"weak\" and \"strong\" edges \(d\). These extracted features are related to the typical phenomena that occur during the oscillation of the lean premixed flame as mentioned before. Specifically, the area and average light intensity of the flame can reflect the intensity of the overall combustion process; the position of the lower edge of the flame can reflect whether the swirling flame is standing or rising; and the \"weak\" edge length of the flame reflects the wrinkle of the flame edge, which in turn characterizes the degree of the flame stretch and strain rate. The difference in the length of the \"strong\" and \"weak\" edges of the flame are the embodiment of the local extinguish phenomenon inside the flame surface, which corresponds to the degree of local combustion instability. Therefore, the feature extraction of the high-frequency flame images can obtain essential information that reflects the multi-physics process of swirl combustion. In Figures 4 and 5, the morphological feature extraction and the extracted feature values of some images during the reignition process and extinguish process are exhibited. Figure 4: Morphological feature extraction results from images during reignition process. Figure 3: Experimental image processing process and corresponding features acquired. It can be seen from Figures 4 and 5 that during the extinguishing process and the reignition process, the characteristics of the flame area, flame edge length, and other characteristics undergo distinctive changes.