Extracting turbulence parameters of smoke via video analysis

Turbulence can be observed in almost all the smoke videos, so turbulence parameters can be extracted as features of smoke in the video smoke detection system. A video-based turbulence parameter measuring method is proposed in this paper. Turbulence can be regarded as a series of irregular flow states with instantaneous velocity fluctuations. First, the instantaneous turbulent velocity field is obtained from the real-time video using an optical flow method, and based on the velocity field information, the turbulence kinetic energy (TKE) and dissipation rate are calculated using large eddy simulation and sub-grid scale (SGS) models. Three different methods, Smagorinsky model, gradient model, and dimensional analysis, are used to obtain the dissipation rate. The results obtained using different methods are compared. The dissipation rate estimated using the SGS models shows high consistency and that estimated by the dimensional analysis has a similar distribution, which shows that the choice of the SGS model is not important for the dissipation rate estimation. Then the TKE is calculated, and the processed images show that each plume structure has its own life cycle and the rising velocity of each plume structure is steady. This method is efficient for the plume turbulence measurement, and it provides benefits to the experimental study of fire plumes. Furthermore, the measured parameters can be analyzed for video-based fire detection. It is a useful method in both scientific research and industrial development.