Special interpretation of formal measurement scales for the case of multiple heterogeneous properties

Muravyov, Sergey V.; Savolainen, Vesa

doi:10.1016/s0263-2241(00)00040-3

Cited by 12 publications

(4 citation statements)

References 19 publications

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“…We may thus conclude that, seemingly, even in the case of derived quantities, measurability implies that it is possible to establish a scale in such a way as to respect empirical relations. The difference is that in the case of fundamental measurement such a scale is directly constructed on the basis of empirical relations, whilst in the case of derived quantities, it is obtained thanks to the functional relation with other quantities, but the final result seems to be, in some regards, equivalent [22].…”

Section: Derived Quantitiesmentioning

confidence: 99%

Measurability

Rossi

2007

Measurement

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We discuss measurability, intended as the fundamental problem of assessing what can be measured. We review some of the main ideas that have been historically proposed on this subject, including the positions of Helmoltz, Campbell and Stevens, the representational viewpoint and some criticism of it.Then we propose an approach that attempts to combine scientific rigour with openness to innovation and we discuss its applicability to both fundamental and derived quantities, in virtually any scientific domain.Such an approach may be particularly suited for addressing the measurement of quantities related to human perception.

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Section: Derived Quantitiesmentioning

confidence: 99%

Measurability

Rossi

2007

Measurement

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“…. 1 x n , that is, the quantity value corresponding to the whole object equals to the sum of quantity values corresponding to its parts (IUPAC, 1997;Muravyov and Savolainen, 2001;Muravyov and Ramamoorthy, 2016). Examples of additive quantities are mass, length, DC voltage, etc.…”

Section: Introductionmentioning

confidence: 99%

Accuracy enhancement of measurand estimate on the base of additive combined measurements

Muravyov

2020

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Purpose The paper aims to develop a method for improving the accuracy of smart sensors (deemed as digital measuring instruments) by organizing combined measurements and processing their results by the parametric adjustment method at heterogeneous dispersion of the random error of the applied regression model. Design/methodology/approach When carrying out combined measurements, the problem of joint processing of measurement results of functionally related quantities must be solved. The function type can be known in advance or obtained experimentally. The number of combined measurements exceeds the number of unknown measured quantities. The redundant measurements can improve the accuracy of estimates of measured values but lead to inconsistency of the measurement results. The problem of inconsistency is solved by the parametric adjustment method, which is rather widely used mainly in the field of geodetic measurements, wherein the parametric equations are linear and the measured quantities are additive. Findings The proposed method allows to reduce the uncertainty of type B of a measurement result, caused by the maximum permissible error of a digital measuring instrument, by 1.2–4 times in comparison with the direct estimation method. Originality/value A compact description of the parametric adjustment method in matrix form is given. Recommendations are given on shaping a sensitivity matrix of functions for the proposed method. The geometric interpretation of the proposed method is considered. The results of the proposed method experimental testing are given when evaluating resistance values.

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“…We will follow an interdisciplinary approach, considering both general metrological principles [32,35], results from the formal theory of measurement [25][26][27][28][29][30][31][32][33][34] and facts and model from psychoacoustics [15][16][17][18].…”

Section: Introductionmentioning

confidence: 99%

“…More recently, there has been increased interest from scientists active in the physical and engineering area in the formal theory of measurement [28][29][30][31][32][33], and the topic of measurement of quantities related to human perception has been raised again [31,32,34,49].…”

Section: Introductionmentioning

confidence: 99%

Panel or jury testing methods in a metrological perspective

Rossi¹,

Crenna²,

Panero³

2005

Metrologia

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Panel or jury testing is a widely used technique in the measurement of quantities related to human perception. However, despite both scientific and applied interests, the confidence of potential users of this technique is less than in more familiar physical and engineering measurements. This lack of confidence arises mainly due to the lack of standardization and of internationally recognized metrological references for panel testing.Here we discuss some methodological aspects of panel testing, including the construction of the reference scale, the definition and realization of a measuring system based on a previously established scale, its calibration and related uncertainty evaluation. We provide illustrative examples concerning the measurement of the quality of sound (acceptability) of machinery used for the automatic sorting of post, presenting experimental results from tests performed in our laboratory, which seem encouraging.Finally, we propose some possible actions for standardization and for the promotion of a metrological approach.

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Special interpretation of formal measurement scales for the case of multiple heterogeneous properties

Cited by 12 publications

References 19 publications

Measurability

Measurability

Accuracy enhancement of measurand estimate on the base of additive combined measurements

Panel or jury testing methods in a metrological perspective

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