Spatial and Time-Series 4D Infrared Gas Cloud Imaging Reconstructed from Infrared Images Measured in Multiple Optical Paths

Current gas leak detection systems rely on the human senses and experience. It is necessary to develop remote and wide-range gas leak monitoring systems that enable us to quantitatively estimate the gas concentration distribution and amount of leaked gas. In this research, an infrared camera was used to detect gas leakage. We developed a 4D, i.e., 3D spatial plus time-series, gas cloud imaging system, in which time-series 2D gas image data obtained in multiple optical paths were computed to reconstruct 4D gas cloud data. The 4D imaging of gas clouds was successfully accomplished in a very short computation time by applying the Elastic Net based on L1 and L2 regularization to the Fourier components of the time-series infrared gas images.