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L. Pitolli

Publications and source records attributed to L. Pitolli.

3 recordsLinked to original sources

Statistical properties of acoustic emission signals from metal cutting processes

Acoustic Emission (AE) data from single point turning machining are analysed in this paper in order to gain a greater insight of the signal statistical properties for Tool Condition Monitoring (TCM) applications. A statistical analysis of the time series data amplitude and root mean square (RMS) value at various tool wear levels are performed, �nding that ageing features can be revealed in all cases from the observed experimental histograms. In particular, AE data amplitudes are shown to be distributed with a power-law behaviour above a cross-over value. An analytic model for the RMS values probability density function (pdf) is obtained resorting to the Jaynes' maximum entropy principle (MEp); novel technique of constraining the modelling function under few fractional moments, instead of a greater amount of ordinary moments, leads to well-tailored functions for experimental histograms.

physics.data-an

A statistical analysis of acoustic emission signals for tool condition monitoring (TCM)

The statistical properties of acoustic emission signals for tool condition monitoring (TCM) applications in mechanical lathe machining are analyzed in this paper. Time series data and root mean square (RMS) values at various tool wear levels are shown to exhibit features that can be put into relation with ageing in both cases. In particular, the histograms of raw data show power-law distributions above a cross-over value, in which newer cutting tools exhibit more numerous larger events compared with more worn-out ones. For practical purposes, statistics based on RMS values are more feasible, and the analysis of these also reveals discriminating age-related features. The assumption that experimental RMS histograms follow a Beta (b) distribution has also been tested. The residuals of the modeling b functions indicate that the search for a more appropriate fitting function for the experimental distribution is desirable.

physics.data-an

In-situ acoustic-based analysis system for physical and chemical properties of the lower Martian atmosphere

The Environmental Acoustic Reconnaissance and Sounding experiment (EARS), is composed of two parts: the Environmental Acoustic Reconnaissance (EAR) instrument and the Environmental Acoustic Sounding Experiment (EASE). They are distinct, but have the common objective of characterizing the acoustic environment of Mars. The principal goal of the EAR instrument is "listening" to Mars. This could be a most significant experiment if one thinks of everyday life experience where hearing is possibly the most important sense after sight. Not only will this contribute to opening up this important area of planetary exploration, which has been essentially ignored up until now, but will also bring the general public closer in contact with our most proximate planet. EASE is directed at characterizing acoustic propagation parameters, specifically sound velocity and absorption, and will provide information regarding important physical and chemical parameters of the lower Martian atmosphere; in particular, water vapor content, specific heat capacity, heat conductivity and shear viscosity, which will provide specific constraints in determining its composition. This would enable one to gain a deeper understanding of Mars and its analogues on Earth. Furthermore, the knowledge of the physical and chemical parameters of the Martian atmosphere, which influence its circulation, will improve the comprehension of its climate now and in the past, so as to gain insight on the possibility of the past presence of life on Mars. These aspect are considered strategic in the contest of its exploration, as is clearly indicated in NASA's four main objectives on "Long Term Mars Exploration Program" (http://marsweb.jpl.nasa.gov/mer/science).

physics.space-ph