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ELECTRICAL CAPACITANCE TOMOGRAPHY FOR CONDUCTIVE MATERIALS

Wael Deabes

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Paperback / softback
26 May 2011
RRP: $126.87
$102.00
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Lost Foam Casting is a simple and reliable casting process for producing tiny and complex metal components. The real time monitoring of the metal characteristics while replacing the foam pattern is important to minimize the related defects. Electrical Capacitance Tomography is developed to obtain images describing the profile of grounded metal inside the foam pattern. A new capacitance measuring circuit has been designed and analyzed for measuring the mutual capacitance between electrodes. Theoretical analysis has been given to illustrate the behavior of the measuring stage, taking into account the non-ideal characteristic of the current feedback amplifierer. Fuzzy inference systems have been used as a nonlinear inverse solver. It has been applied to either speed up the traditional iteration image reconstruction techniques or as a stand alone direct nonlinear solution for the inverse problem. A fuzzy mathematical model providing the relationship between pixels in images and the ECT sensor measurements has been designed.

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RRP: $126.87
$102.00
Ships in 3-5 business days
Hurry up! Current stock:

ELECTRICAL CAPACITANCE TOMOGRAPHY FOR CONDUCTIVE MATERIALS

RRP: $126.87
$102.00

Description

Lost Foam Casting is a simple and reliable casting process for producing tiny and complex metal components. The real time monitoring of the metal characteristics while replacing the foam pattern is important to minimize the related defects. Electrical Capacitance Tomography is developed to obtain images describing the profile of grounded metal inside the foam pattern. A new capacitance measuring circuit has been designed and analyzed for measuring the mutual capacitance between electrodes. Theoretical analysis has been given to illustrate the behavior of the measuring stage, taking into account the non-ideal characteristic of the current feedback amplifierer. Fuzzy inference systems have been used as a nonlinear inverse solver. It has been applied to either speed up the traditional iteration image reconstruction techniques or as a stand alone direct nonlinear solution for the inverse problem. A fuzzy mathematical model providing the relationship between pixels in images and the ECT sensor measurements has been designed.

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