Biblio
The relative permittivity (also known as dielectric constant) is one of the physical properties that characterize a substance. The measurement of its magnitude can be useful in the analysis of several fluids, playing an important role in many industrial processes. This paper presents a method for measuring the relative permittivity of fluids, with the possibility of real-time monitoring. The method comprises the immersion of a capacitive sensor inside a tank or duct, in order to have the inspected substance as its dielectric. An electronic circuit is responsible for exciting this sensor, which will have its capacitance measured through a quick analysis of two analog signals outputted by the circuit. The developed capacitance meter presents a novel topology derived from the well-known Howland current source. One of its main advantages is the capacitance-selective behavior, which allows the system to overcome the effects of parasitic resistive and inductive elements on its readings. In addition to an adjustable current output that suits different impedance magnitudes, it exhibits a steady oscillating behavior, thus allowing continuous operation without any form of external control. This paper presents experimental results obtained from the proposed system and compares them to measurements made with proven and calibrated equipment. Two initial capacitance measurements performed with the system for evaluating the sensor's characteristics exhibited relative errors of approximately 0.07% and 0.53% in comparison to an accurate workbench LCR meter.
Interconnect opens are known to be one of the predominant defects in nanoscale technologies. Automatic test pattern generation for open faults is challenging, because of their rather unstable behavior and the numerous electrical parameters which need to be considered. Thus, most approaches try to avoid accurate modeling of all constraints like the influence of the aggressors on the open net and use simplified fault models in order to detect as many faults as possible or make assumptions which decrease both complexity and accuracy. Yet, this leads to the problem that not only generated tests may be invalidated but also the localization of a specific fault may fail - in case such a model is used as basis for diagnosis. Furthermore, most of the models do not consider the problem of oscillating behavior, caused by feedback introduced by coupling capacitances, which occurs in almost all designs. In [1], the Robust Enhanced Aggressor Victim Model (REAV) and in [2] an extension to address the problem of oscillating behavior were introduced. The resulting model does not only consider the influence of all aggressors accurately but also guarantees robustness against oscillating behavior as well as process variations affecting the thresholds of gates driven by an open interconnect. In this work we present the first diagnostic classification algorithm for this model. This algorithm considers all constraints enforced by the REAV model accurately - and hence handles unknown values as well as oscillating behavior. In addition, it allows to distinguish faults at the same interconnect and thus reducing the area that has to be considered for physical failure analysis. Experimental results show the high efficiency of the new method handling circuits with up to 500,000 non-equivalent faults and considerably increasing the diagnostic resolution.