A copula is a function that joins multivariate distribution functions to their margins (i.e. marginal distribution functions). Copulas are widely used in finance and economics for time series analysis and approaches based on them have found application in engineering as well, typically in civil and reliability engineering. In this paper, two data-driven prognostic algorithms based on copula application to power systems are proposed. The first is related to the estimation of the Remaining Useful Life (RUL) of a product, and the second aims at evaluating the performance and predict the behavior of an energy-consuming load. Obtained results are encouraging and candidate this approach as a useful method in Prognostics and Health Management (PHM) and energy monitoring applications.

Prognostic and Health Management using Copula Correlation: a Power System application

L. Cristaldi;M. Alice;E. Ragaini
2020-01-01

Abstract

A copula is a function that joins multivariate distribution functions to their margins (i.e. marginal distribution functions). Copulas are widely used in finance and economics for time series analysis and approaches based on them have found application in engineering as well, typically in civil and reliability engineering. In this paper, two data-driven prognostic algorithms based on copula application to power systems are proposed. The first is related to the estimation of the Remaining Useful Life (RUL) of a product, and the second aims at evaluating the performance and predict the behavior of an energy-consuming load. Obtained results are encouraging and candidate this approach as a useful method in Prognostics and Health Management (PHM) and energy monitoring applications.
2020
17th IMEKO TC 10 and EUROLAB Virtual Conference “Global Trends in Testing, Diagnostics & Inspection for 2030”
health condition (HC), Remaining Useful Life (RUL), Copula correlation, marginal distributions, load modelling, pseudo-random load curves
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1150257
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