Fuzzy handling of measurement errors in instrumentation

This paper focuses on the use of the possibility theory and of the fuzzy subset theory to deal with the uncertainty of the measurements handled in instrumentation systems. Methods are described for building fuzzy subsets from numerical data coming from imprecise “physical” sensors on the one hand, and handling approximate estimations provided by “human” sensors on the other hand. The propagation of the fuzzy representation of acquired measures in further treatments, such as those involved in performance indicators aimed at controlling manufacturing production, is also considered.

[1]  Leonard L Fortuin,et al.  Performance Indicators — Why, Where and How? , 1988 .

[2]  Lotfi A. Zadeh,et al.  Outline of a New Approach to the Analysis of Complex Systems and Decision Processes , 1973, IEEE Trans. Syst. Man Cybern..

[3]  D. Dubois,et al.  FUZZY NUMBERS: AN OVERVIEW , 1993 .

[4]  H. W. Kalfsbeek,et al.  Elicitation, assessment, and pooling of expert judgments using possibility theory , 1995, IEEE Trans. Fuzzy Syst..

[5]  R. C. Michelini,et al.  Assessing measurement uncertainty in quality engineering , 1996, Quality Measurement: The Indispensable Bridge between Theory and Reality (No Measurements? No Science! Joint Conference - 1996: IEEE Instrumentation and Measurement Technology Conference and IMEKO Tec.

[6]  Glenn Shafer,et al.  A Mathematical Theory of Evidence , 2020, A Mathematical Theory of Evidence.

[7]  Ronald R. Yager,et al.  Essentials of fuzzy modeling and control , 1994 .

[8]  D. Dubois,et al.  Fuzzy sets, probability and measurement , 1989 .

[9]  Ronald E. Giachetti,et al.  A parametric representation of fuzzy numbers and their arithmetic operators , 1997, Fuzzy Sets Syst..

[10]  G. Zingales.  The evaluation of uncertainties in industrial measurements for quality , 1996, Quality Measurement: The Indispensable Bridge between Theory and Reality (No Measurements? No Science! Joint Conference - 1996: IEEE Instrumentation and Measurement Technology Conference and IMEKO Tec.

[11]  Maurice G. Kendall,et al.  The advanced theory of statistics , 1945 .

[12]  D. Dubois,et al.  Fuzzy sets and statistical data , 1986 .