Modelling of Networked Measuring Systems -- From White-Box Models to Data Based Approaches
CoRR(2023)
摘要
Mathematical modelling is at the core of metrology as it transforms raw
measured data into useful measurement results. A model captures the
relationship between the measurand and all relevant quantities on which the
measurand depends, and is used to design measuring systems, analyse measured
data, make inferences and predictions, and is the basis for evaluating
measurement uncertainties. Traditional modelling approaches are typically
analytical, for example, based on principles of physics. But with the
increasing use of digital technologies, large sensor networks and powerful
computing hardware, these traditional approaches are being replaced more and
more by data-driven methods. This paradigm shift holds true in particular for
the digital future of measurement in all spheres of our lives and the
environment, where data provided by large and complex interconnected systems of
sensors are to be analysed. Additionally, there is a requirement for existing
guidelines and standards in metrology to take the paradigm shift into account.
In this paper we lay the foundation for the development from traditional to
data-driven modelling approaches. We identify key aspects from traditional
modelling approaches and discuss their transformation to data-driven modelling.
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