Spectro-tomography interpretation for integrated sensing of process component identification and distribution

New developments are described that augment the recently introduced electrical sensing technology of industrial process tomography (applicable to a wide range of industrial processes) with methods for the identification of materials in the contrast-sensed distribution. Advances are set in the context of current technology, where results are typically limited intrinsically by single frequency excitation. Previous extensions to the platform technology have provided a spectroscopic dimension, using wideband excitation and associated detection technique, to deliver a raw spectro-tomogram dataset. Two methods and test results are described which add the capability to interpret this raw dataset to identify process components: a simply implemented look-up table (LUT) method able to identify known and distinct 'spectral fingerprints'; and a more computationally intensive model-fitting method that can tolerate components that are similar in their spectrographic response.