In this paper, the use of the Principal Direction Divisive Partitioning (PDDP) method for unsupervised learning is discussed and analyzed with a focus on fault detection applications. Specifically, a geometric limit of the standard algorithm is highlighted by means of a simulation example and a modified version of PDDP is introduced. Such a method is shown to correcly perform data clustering also when the standard algorithm fails. The modified strategy is based on the use of a Chi-squared statistical test and offers more guarantees in terms of detection of a wrong functioning of the system. The proposed algorithm is finally experimentally tested on a fault detection application for aerospace electro-mechanical actuators, for which a comparison with k-means and fuzzy kmeans approaches is also provided.
(2014). Fault detection via modified Principal Direction Divisive Partitioning and application to aerospace electro-mechanical actuators [conference presentation - intervento a convegno]. Retrieved from http://hdl.handle.net/10446/32426
Fault detection via modified Principal Direction Divisive Partitioning and application to aerospace electro-mechanical actuators
MAZZOLENI, Mirko;FORMENTIN, Simone;PREVIDI, Fabio;
2014-12-01
Abstract
In this paper, the use of the Principal Direction Divisive Partitioning (PDDP) method for unsupervised learning is discussed and analyzed with a focus on fault detection applications. Specifically, a geometric limit of the standard algorithm is highlighted by means of a simulation example and a modified version of PDDP is introduced. Such a method is shown to correcly perform data clustering also when the standard algorithm fails. The modified strategy is based on the use of a Chi-squared statistical test and offers more guarantees in terms of detection of a wrong functioning of the system. The proposed algorithm is finally experimentally tested on a fault detection application for aerospace electro-mechanical actuators, for which a comparison with k-means and fuzzy kmeans approaches is also provided.File | Dimensione del file | Formato | |
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2014 IEEE CDC - FDI PDDP.pdf
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