v Condition assessment of electro-mechanical actuators for aerospace using relative density-ratio estimation · Mirko Mazzoleni

Condition assessment of electro-mechanical actuators for aerospace using relative density-ratio estimation

Abstract

This paper faces the problem of developing an effective Condition Monitoring algorithm (CM) for Electro-Mechanical Actuators (EMA) in aerospace applications. In this view, a test campaign has been carried out in order to progressively bring the EMA near to failure, by means of a test bench suitably developed. Various indicators have been computed from measured data, for a set of the EMA’s working regimes. The statistical distribution of the computed features is assessed and tracked over time. We propose an online statistical approach, based on density estimation techniques, in order to detect potential changes in the data distribution. The discovered changes are then interpreted as a modification of the EMA’s health state, leading to a first building block for a complete condition assessment strategy. [Paper, Code]

Reference

M. Mazzoleni, M. Scandella, Y. Maccarana, F. Previdi, G. Pispola, N. Porzi, "Condition assessment of electro-mechanical actuators for aerospace using relative density-ratio estimation", 18th IFAC Symposium on System Identification (SYSID), Stockholm, Sweden, 2018, doi: 10.1016/j.ifacol.2018.09.070 , ISSN: 2405-8963, pp. 957 - 962.

Bibtex

@article{MAZZOLENI2018957,
title = "Condition assessment of electro-mechanical actuators for aerospace using relative density-ratio estimation",
journal = "IFAC-PapersOnLine",
volume = "51",
number = "15",
pages = "957 - 962",
year = "2018",
note = "18th IFAC Symposium on System Identification SYSID 2018",
issn = "2405-8963",
doi = "https://doi.org/10.1016/j.ifacol.2018.09.070",
author = "M. Mazzoleni and M. Scandella and Y. Maccarana and F. Previdi and G. Pispola and N. Porzi",
keywords = "Condition monitoring, Change-point detection, Kernel methods, Time-series"
}