Industrial Process Tomography - Platform II grant funded by EPSRC

FACULTY OF ENGINEERING

 

Colloid Vibration Potential Imaging

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.

a reconstructed cross-sectional slice and a 3D view of the scanned Aspirin tablet
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).

a reconstructed cross-sectional slice and a 3D view of the scanned Aspirin tablet a reconstructed cross-sectional slice and a 3D view of the scanned Aspirin tablet
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.

a reconstructed cross-sectional slice and a 3D view of the scanned Aspirin tablet
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.

a reconstructed cross-sectional slice and a 3D view of the scanned Aspirin tablet
Figure 5: Data fusion operations

 

Author Information: Brian Hoyle, Institute of Particle Science and Engineering, School of Process, Environmental and Materials Engineering, Email: b.s.hoyle@leeds.ac.uk

References:

  1. 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.

  2. 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.

  3. Nahvi M and Hoyle B S, (2009) “Electrical Impedance Spectroscopy Sensing for Industrial Processes”, IEEE Sensors Journal, 9 (12), pp1808-1816.

  4. Nahvi M and Hoyle B S, (2009), “Data Fusion for Electrical  Spectro-tomography”, IEEE Imaging Systems and Techniques Conference, Shenzen, China, pp229-234.