The instrumented Indentation Test is based on simultaneous recording of force and indentation depth, obtained during test cycle. The force-depth curve, describing the indentation pattern, is typically formed by two parts having the "zero-point" in common, i.e. the first contact point between the indenter and the surface of test piece. The zero-point determination is a crucial aspect for Martens Hardness evaluation, so that relevant ISO standard suggests to estimate it by extrapolation of polynomial fitted functions. In this paper a new model, based on a segmented function, is proposed. This approach implies the use of maximum likelihood estimator for parameters determination. The corresponding uncertainty is provided through the covariance matrix of the regression model.
Zero-Point in the evaluation of Martens Hardness uncertainty / Barbato, Giulio; Brondino, Gabriele; Galetto, Maurizio; Vicario, Grazia. - In: VDI-BERICHTE. - ISSN 0083-5560. - 1685:(2002), pp. 113-118. (Intervento presentato al convegno Joint international conference IMEKO TC3/TC5/TC20 / proceedings of the International Conference on Force, Mass, Torque, Hardness and Civil Engineering Metrology in the age globalization tenutosi a Tagung Celle, Germany nel September 24-26).
Zero-Point in the evaluation of Martens Hardness uncertainty
BARBATO, Giulio;BRONDINO, Gabriele;GALETTO, Maurizio;VICARIO, GRAZIA
2002
Abstract
The instrumented Indentation Test is based on simultaneous recording of force and indentation depth, obtained during test cycle. The force-depth curve, describing the indentation pattern, is typically formed by two parts having the "zero-point" in common, i.e. the first contact point between the indenter and the surface of test piece. The zero-point determination is a crucial aspect for Martens Hardness evaluation, so that relevant ISO standard suggests to estimate it by extrapolation of polynomial fitted functions. In this paper a new model, based on a segmented function, is proposed. This approach implies the use of maximum likelihood estimator for parameters determination. The corresponding uncertainty is provided through the covariance matrix of the regression model.Pubblicazioni consigliate
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https://hdl.handle.net/11583/1646411
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