BIL00/17/Polen - BoF- BIL00/17/Polen
From 11-12-2000 to 10-12-2003
Description
This research project is concerned with the problem of imaging shallowly buried objects. The primary application that will be addressed is that of land mine detection. The research effort differs from previous studies not only in its use of Electrical Impedance Tomography (EIT) as a rather unconventional imaging modality, but equally well in its consistent emphasis on tomographic imaging. When compared to the more common methods, based on single soundings, this should lead to a significant higher detection confidence. Up to now, tomographic imaging has only raised moderate interest in subsurface imaging, mainly due to its high computational demands. Therefore, the main contribution of this study will be the development of 0computational efficient and numerical reliable algorithms. Although this project will concentrate on Electrical Impedance Tomography for the detection and imaging of shallowly buried objects, it should be emphasized that the detection probability and the rejection of false alarms, may be envisaged to be too low for most applications if EIT is used as a stand-alone technique. The current research should instead be seen as part of more global activities (e.g. VUB-ETRO research on humanitarian demining) aiming at the design of multisensor probes and the use of data fusion, integrating measurements coming from various sensors and being based on different physical principles. The non-invasive detection and localization of shallowly buried objects using electromagnetic principles has attracted significant interest in recent years. Among its many promising application domains we only cite here the localization of utility constructions such as vessels and pipes, and the detection of land mines. It is the latter subject which will be the primary application motivating this research proposal. It should be kept in mind, however, that most of the results that will be obtained in this project could equally well be applied to many other, perhaps commercially more attractive, applications of subsurface imaging. The specific performance requirements for the mine detection application are approximately 30 cm of penetration and 1 cm of resolution. In recent years, the world's attention has been brutally drawn on the immense social implications of the global land mine problem. Often underestimated, however, is its devastating impact on the local economy of the affected, mostly developing, countries. Efficient detection and remediation technologies are therefore urgently requested. Metal detectors, based on electromagnetic induction, are considered today as the more mature sensing modality for mine detection. There are, however, several limitations to its application. As the metal detection principle is largely restricted to detection solely, it does mostly not allow for discrimination between mines and other metallic debris. Furthermore, as land mines are made more and more from non-metallic materials such as plastic and only retain a minor amount of metal residue in their detonator, the efficacy of metal detectors necessarily must diminish. In Electrical Impedance Tomography, the problem is to find a spatially varying conductivity distribution in a closed domain from electrostatic measurements collected at its boundary. Specifically, it is assumed that known current excitation patterns are imposed on the boundary and the resulting boundary voltages are collected. The physical phenomenon of electrical conduction through an isotropical conductive material in a bounded region is modeled by a second order elliptic Poisson equation with a variable coefficient corresponding to the conductivity of the medium. The applied current excitation patterns are typically modeled as Neumann boundary conditions while the voltage measurements are represented as Dirichlet data. The linear operator that relates the excitation pattern to the boundary measurements is referred to as the Neumann-to-Dirichlet map. This Neumann-to-Dirichlet map depends nonlinearly on the conductivity. The inverse conductivity problem then is to determine the parameters of a partial differential equation given the knowledge of the Neumann-to-Dirichlet map associated with it. When the conductivity is sufficiently smooth and the full Neumann-to-Dirichlet map is available then it is known that the conductivity distribution can be recovered exactly. The mathematical reassuring facts that both piecewise analytic and smooth conductivities can be distinguished by boundary measurements made with infinite precision have been proven rigorously. However, the inverse problem is in general very unstable. Since its inception in the beginning of the 80's, EIT research has traditionally been firmly rooted in the domain of biomedical imaging. More recently, however, EIT concepts also have been applied with much success in various other application domains. In particular the use of EIT in geophysics, to map subsurface liquid flows during natural or man-induced processes and to map geological structures, has been a source of inspiration for the research proposed in this project. A complete overview of these applications would be outside the scope of this description, suffices it to cite among the most notable examples, the on-line detection of leaks in underground storage tanks and the monitoring of in-situ ground remediation processes. The result of such a reconstruction is a 2 or 3 dimensional map of the electrical impedance distribution in the underground obtained from a series of voltage and current measurements, using a set of buried electrodes. Geophysical EIT surveys are typically realized from a number of electrode arrays that are lowered in so-called bore holes, to measure the impedance distribution between these boreholes. When a sufficient number of such measurements are assembled, a complete tomographic image of the underground impedance distribution can be reconstructed. It is clear that such invasive measurement configurations, although exhibiting clearly the highest sensitivity, can not be adopted for the application envisaged here. Instead the surface electrode configurations that will be utilized here, have to resemble much more those used in biomedical applications. However, this is not the only distictive characteristic setting apart the shallow subsurface sampling application studied here, from the more common geophysical applications of EIT. Spatial resolutions in geophysical surveying typically are in the 1 meter range, while depths of a few tens of meters are probed. This is to be contrasted with the original biomedical application of EIT were resolutions of a few millimeter are attempted. Therefore, the application of EIT to shallow subsurface imaging, studied in this project, can be regarded as combining the resolution and penetration depth of biomedical EIT imaging with the measurement conditions of geophysical surveying. In the past, the majority of theoretical developments were on the use of encircling electrode configurations. Comparatively little work has been reported on the use of planar electrode configurations for underground probing. Wexler was one of the first to apply EIT to the detection of unexploded ordnances buried in the ground using a rectangular array of electrodes. The results were shown to be rather disappointing. In particular, the detection of unexploded ordnances apparently requires probing depths that exceed the penetration depth of electrical currents in most circumstances. Kotre also applied a rectangular array of electrodes for underground probing and concluded that such an electrode grid should preferentially be treated as a set of parallel linear arrays. The feasibility of EIT-based techniques for the problem of mine detection was illustrated by Worth et al. using a rectangular array of electrodes.Team
- Bart De Moor, Promoter
Financing
Funding: KU Leuven - Internal Funding KU Leuven
Events
2/09/2024:
PhD defense - Martijn Oldenhof
Machine Learning for Advanced Chemical Analysis and Structure Recognition in Drug Discovery
3/09/2024:
Meet the Jury Igor Tetko on Advanced Machine Learning in Drug Discovery
12/09/2024:
Multimodal analysis of cell-free DNA for sensitive cancer detection in low-coverage and low-sample settings
Seminar by Antoine Passemiers
News
STADIUS Alumni Herman Verrelst – new CEO of Biocartis
08 June 2017
Herman Verrelst, the founder of KU Leuven spin-off Cartagenia, who has been working in Silicon Valley, US for the last few years will be returning to Belgium to follow the steps of Rudi Pauwels as CEO of the Belgian diagnostic company, Biocartis.
Supporting healthcare policymaking via machine learning – batteries included!
29 May 2017
STADIUS takes the lead in the data analytics efforts in an ambitious European Project MIDAS.
Marc Claesen gives an interview about his PhD for the magazine of the Faculty of Engineering Sciences "Geniaal"
10 February 2017
Did you know that in Belgium approximately one third of type 2 diabetes patients are unaware of their condition?
Joos Vandewalle is nieuwe voorzitter KVAB
09 October 2016
Op 5 oktober 2016 heeft de Algemene Vergadering van de Academie KVAB Joos Vandewalle verkozen tot voorzitter van de KVAB.