Development of an edge computing device by integrating deep learning model for flame tomographic reconstruction

点击翻译按钮获取中文摘要

Due to increasingly tight environment legislation, optical imaging techniques for combustion diagnostics are becoming prevalent in industrial environments for improved combustion efficiency and reduced pollutant emissions.Volumetric tomography (VT) which is one of these techniques is an effective methodused for combustion monitoring and diagnostics as it provides authentic 3D information for combustion diagnostics. The development of VT has helped in understanding of complex combustion processes such as flame ignition and combustion instability. Also, the unique features of VT include non-intrusiveness and easy implementation, which has made such an optical imaging technique suitable for the spatial and temporal monitoring and diagnostics of combustion systems.There are various reconstruction approaches suitable for volumetric image reconstruction (Fig 1). They include analytic reconstruction which is based on the mathematical inversion, iterative reconstruction based on numerical inversion and deep learning-based image reconstruction.