Optimisation of Image Processing Parameters for Flame Image Velocimetry (FIV) Measurement in a Single-Cylinder, Small-Bore Optical Diesel Engine 2019-01-0719
High-speed soot luminosity movies are widely used to visualise flame development in optical diesel engines due to its simple setup and relatively low cost. Recent studies demonstrated the high-speed soot luminosity movies are not only effective in showing the overall distribution and temporal evolution of sooting flames but also flow fields within the flame through the application of combustion (or flame) image velocimetry. The present study aims to improve this imaging technique by systematically evaluating key image processing parameters based on high-speed soot luminosity movies obtained from a single-cylinder, small-bore optical diesel engine. The raw luminosity movies are processed in PIVlab – a Matlab-based open-source code widely used for particle image velocimetry (PIV) applications. The images are processed using the Contrast-Limited Adaptive Histogram Equalization (CLAHE) filter before the velocity vectors determined using the multi-pass Discrete Fourier Transform (DFT) approach. In this process, the CLAHE filter size, interrogation window size, and numbers of passes are optimised for minimal interpolation counts. The camera exposure time and frame rate are also evaluated. The results show that the internal flame pattern change, as demonstrated by previous studies, can be used to obtain the flow fields within the flame successfully. The processed images show the development of multiple vortex structures as a result of strong flame-wall and flame-to-flame interactions as well as the significant swirl effects.