Spectro-tomography – adding a material dimension to IPT
IPT can help to deliver benefits of increased productivity and quality, and reductions in emissions and waste products through the insight it provides of the relative spatial distribution of materials in a process. This is based upon the sensing of the ‘contrast’ of the process material to a physical excitation, such as an electrical current at a fixed frequency. Multiple estimates can then provide a time sequence of these process states. Such basic forms of IPT are limited by the sensitivity of the process materials to the narrow energy band (frequency in the electrical case). Hence where materials have similar responses they cannot be discriminated (Fig 1) using this approach.
Figure 1 Single ERT frequency (e.g. 50k Hz)
In multi-component processes it is important to be able to identify each component. For example the material in a process reactor (Fig 2) used to manufacture pharmaceutical compounds is likely to have a distinct electrical spectrum (Fig 3).
|Figure 2: A process reactor||Figure 3: A distinct electrical spectrum from the material|
In this project we have used a wideband chirp stimulus (Fig 4) able to excite wide range of responses This results in process response data that can be segmented into frequency bands and yield a set of frequency-banded tomograms (Refs 1,2). Known or modelled component material spectra can then be extracted for each spatial region of interest.
Figure 4 : A wideband chirp stimulus
Data fusion operations (Fig 5) reveal a multi-dimensional view of the process in terms of spatial distribution (in 2D/3D), with superimposed component identification, and dynamic temporal flow (giving 4/5D in total) which could be used for process monitoring and control. Follow-on grant support has been provided by UK EPSRC to develop an industrially testable prototype system with 4 industrial partners.
Figure 5: Data fusion operations
Hoyle B S and Nahvi M, (2008) “Spectro-tomography - an electrical sensing method for integrated estimation of component identification and distribution mapping in industrial processes”, IEEE Sensors Conference, Lecce, Italy, pp807-810.
Nahvi M and Hoyle B S, (2008), “Wideband Electrical Impedance Tomography”, J. Measurement Science and Technology, 19, doi: 10.1088/0957-0233/19/9/094011, 9pp.
Nahvi M and Hoyle B S, (2009) “Electrical Impedance Spectroscopy Sensing for Industrial Processes”, IEEE Sensors Journal, 9 (12), pp1808-1816.
Nahvi M and Hoyle B S, (2009), “Data Fusion for Electrical Spectro-tomography”, IEEE Imaging Systems and Techniques Conference, Shenzen, China, pp229-234.