1,721,098 research outputs found
Laminar material characterization by ultrasonic wide-band measurements of Lamb waves disperison curves
No full textA measurement technique to obtain dispersion curves for guided acoustic modes in laminated plate-like materials is described. The measurement is performed by means of two angled ultrasonic longitudinal transducers positioned on the plate surface with dry contact coupling, in a pitch catch configuration. Dry contact coupling ensures higher signal to noise ratios than immersion techniques. The excitation signal of the transmitting transducer is a wide band pulse. Thus all the frequencies contained in the pulse-band are simultaneously used to excite the guided modes
Guided acoustic propagation modelling for platelike multilayered structures.
No full textIn this paper a simulation model is presented for acoustic guided wave propagation, which was developed from a technique widely reported inthe literature as the 'transfer matrix method'. This model describes the phenomenon of ultrasonic guided wave propagation in stacks of anisotropic laminae in an extremely synthetic form and under a large variety of boundary conditions. Acoustic guided wave propagation is a powerful tool for Non Destructive Testing (NDT) of plate-like structures (e.g. composites or films deposited on substrates) because the dispersive nature of the propagation modes gives a signature of the actual material state. Thus the model presented in this paper can be effectively used in NDT applications
Guided acoustic wave propagation for porcelain coating characterization
No full textIn this paper a measurement technique to obtain dispersion curves for guided acoustic modes in porcelain-coated steel is described. The measurement is performed with two angled ultrasonic longitudinal transducers in a pitch catch configuration by employing an immersion technique. Phase velocities for the guided modes are selected through the variation of the angle formed by the transmitter beam with the surface normal vector. The excitation signal of the transmitting transducer is a narrow band pulse. For each phase velocity, the guided mode frequencies are recovered by evaluating the frequency minima of the reflection coefficient
Shadow images for subtle defect detection in ceramic materials
No full textThe integrity of ceramic material is assessed by means of an high frequency (50 MHz) large bandwidth ultrasonic technique. C-mode images are produced which represent both the amplitude and spectral centroid of the sample back-surface echoes. The comparison of the two image kinds ensures a better evaluation of the defect shape, because it hilights the filtering effect of the flaw on the forward propagating ultrasonic wave
Analysis of a grid anti-islanding impedance detection system in presence of uniform distributed noise
No full textThe incomplete knowledge of the power distribution grid status and
in particular the impossibility to constantly monitor the number of subjects
(feeder) able to inject current autonomously at a known time can represent a
hazardous condition for the main utility provider operators’ safety. Whenever
an unexpected islanding condition is induced on the utility grid, every subject
injecting power on the grid should stop such injection switching to a safety shut
down condition. Due to the presence of multi injecting sources on the utility
grid it is possible that one or more feeders do not recognise such event and
continue to supply energy to a portion of the utility grid, keeping the main
provider operators unaware of such condition. Such situation is the islanding
condition. The present work aims, starting from a previous paper Fort et al.
(2010) at assessing the robustness of an anti-islanding detection system in
presence of a uniform distributed noise sources on the grid. The anti islanding
detection system is based on the injection of an interharmonic component on
the grid. The single phase case is considered. In this paper it is considered the
optimum tradeoff between the harmonic distortion injection of a component
which is required to be both meaningful from a signal to noise ratio standpoint
and low enough not to affect the overall grid THD. The aim of this paper is to
prove that such device will constitute a low cost, stand alone, and reliable
automatic detection system for grid disconnection detection, to be supplied in
conjunction with devices like the photovoltaic (PV) inverters in order to
minimise their islanding non-detection zone
Valutazione della robustezza dei sistemi di rilevamento delle condizioni di isola rispetto al rumore
No full textSurface State Models For Conductance Response Of Metal Oxide Gas Sensors During Thermal Transients
No full textIn the last decades a large amount of research work has been devoted to understanding
the sensing mechanism of metal oxide gas conductometric sensors
(Wang et al. 1995; Barsan and Weimar 2001, 2003; Korotcenkov 2008; Moseley et
al. 2008; Pokhrel et al. 2008; Barsan et al. 2010, 2011; Yamazoe and Shimanoe
2010; Hübner et al. 2011a). Many results have been obtained with special reference
to the most often used oxides such as, e.g., SnO2 (Barsan and Weimar 2001;
Barsan et al. 2011) and WO3 (Guérin et al. 2006; Bendahan et al. 2007). Indeed,
it can be stated that for these materials the sensing principle is understood in its
essential features. Nevertheless, even for these materials that have been applied in
gas sensors for more than 20 years, and that are the basis of some successful and widespread commercial products, some aspects are still under study, and it can be
affi rmed that an exhaustive knowledge of their behavior has not yet been achieved.
Due to this lack of knowledge, and to the absence of a reliable and simple
sensor input–output relationship, at present, sensor-based measurement systems
are mainly designed on the basis of experimental characterization and still
suffer from some unsolved problems, such as drift and heavy sensitivity to operating
conditions.
In this context it is clear how the development of a dynamic model for metal
oxide gas sensors would be of the utmost utility from many points of view. First,
the availability of a simulation tool, able to predict with suffi cient accuracy the
sensor behavior, would enable us to replace experimental tuning with simulations,
and could signifi cantly speed up sensor-based system development and guarantee
better performance. Moreover, and perhaps most important, comparison of the
model outputs with experimental data could greatly help us to understand the
behavior of metal oxide sensors, because it would allow us to explore the relevance
of the different mechanisms involved in sensing, to validate some commonly accepted
assumptions, or to assess their validity ranges. Computational modeling is,
in fact, a powerful tool to gain information about the behavior of complex systems
which is diffi cult or impossible to obtain by direct measurements and observations.
Sensor models have to incorporate all the phenomena that contribute to the
sensing mechanism and these, in the case of metal oxide conductometric sensors,
are very complex in that they comprise chemical solid–gas reactions and physical
phenomena related to electronic conduction. Especially the fi rst are very diffi cult
to observe and often remain the subject of hypotheses that are diffi cult to assess
with independent measurements.
It must be underlined, also, that the chemical-physical behavior of the sensor
depends, of course, on the material—its composition as well as bulk and surface
structure—but also heavily on the crystal bulk and surface defect population, and
fi nally on the sensor micro- and macrostructure. All these aspects are crucial to
the electronic conduction in the sensors (Korotcenkov et al. 2007), and should be
taken into account when building a computational model.
In detail, a sensor model has to describe, fi rst, the interaction of the target
gases with the sensing material, resulting from both the surface chemical reactions
and the possible gas diffusion in it. It must be stressed that, for resistive
sensors, only reactions involving electron exchange between the sensing material
and the gas can be sensed, even if other possible reactions (absorption, adsorption
or desorption), though not sensed directly, affect the sensor response. Note
that the sensor response also depends on the interactions between different gases
(target gases and other gases) that take place on the surface. Among important
interfering gases, the effect of water vapor has to be taken into account; in fact,
water vapor is always present in normal environments in very large concentrations
(tens of thousands of parts per million) and heavily affects the response of binary oxides (Hübner et al. 2001b; Henderson 2002; Korotcenkov et al. 2007;
Gaman et al. 2008). The reaction of water with oxide surfaces has long been studied
but is not yet completely understood.
The second contribution to the sensor response is the mechanism that causes
a variation of the sensor resistance in relationship to the quantity of adsorbed
gas. Different mechanisms can occur in different fi lm microstructures (Wang et
al. 1995; Brynzari et al. 1999; Korotcenkov 2007, 2008; Rettig and Moos 2008;
Yamazoe and Shimanoe 2008a; Shaalan et al. 2011). In particular, for many metal
oxides, used in the temperature range 200–400°C, the electronic conduction, and
hence the resistance value, is mainly determined by the surface chemical reactions,
which are responsible for the creation of some “extrinsic” surface energy
states. The presence of adsorbates affects the resistance in a way that depends
on the metal oxide fi lm microstructure. For poorly sintered porous fi lms, for instance,
the most relevant phenomenon responsible for the sensor response is the
surface electric fi eld, which is established in the surface region where free carriers
are trapped by the adsorbed molecules.
In this chapter, some research carried out in the fi eld of simulation based
on surface chemical reactions of the dynamic response of resistive metal oxide
sensors is summarized, and the different points of view and assumptions are discussed.
The models presented in the literature have proven to well describe some
devices under particular operating conditions, but different points of view are
often chosen by the researchers. Particular attention will be devoted in this work
to SnO2 sensors interacting with mixtures of oxygen (O2) and carbon monoxide
(CO), and a possible approach followed by the authors of this review for modeling
their behavior will be briefl y described. This approach leads to the development
of a gray-box model that, starting from a physical-chemical description of
the surface reactions, provides a compact description of the sensor behavior in
dry O2, and in the presence of both O2 and CO (Fort et al. 2006a, 2006b, 2006c,
2007, 2010; Bicelli et al. 2009) The effect of water vapor is also accounted for
(Fort et al. 2011a). The model explains the sensor dynamics by means of oxygen
adsorption and ionization processes, and of CO direct adsorption and reaction
with the ionized adsorbed oxygen, as suggested also by many other researchers.
The model applies to large-grained thick-fi lm sensors or to nanowires (quasi-onedimensional)
bundles. All the developed models take into account sensor operation
under dynamic thermal conditions
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