Fault identification and accommodation for incipient and abrupt faults

Parlangeli, Gianfranco; Pacella, D.; Corradini, Maria Letizia

doi:10.1109/cdc.2007.4434480

Cited by 1 publication

(1 citation statement)

References 17 publications

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“…The incipient faults (drifts) are parameterized by a slope, allowing for different shapes (logarithmic, constant or exponential), reflecting different possible malfunctions. We didn't consider combinations of faults into a single pattern, as the aforementioned fault types are the most common ones (Luo, 2006), and the most studied along the literature as well (Zhang, Polycarpou, & Parisini, 2000) (Zhang, Polycarpou, & Parisini, 2002) (Parlangeli, Pacella, & Corradini, 2007) (Serdio, Lughofer, Pichler, Buchegger, & Efendic, 2014.a) (Serdio, Lughofer, Pichler, Buchegger, & Efendic, 2014b) (Serdio et al, 2015).…”

Section: Custom Faultmentioning

confidence: 99%

A Fault Detection and Isolation Software Framework for Repeatable and Comparable Experimentation

Serdio

Lughofer

2016

PHME_CONF

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There is an extensive literature available about condition monitoring relying on multi-dimensional data-driven system models and mappings, including proposal of new methods and algorithms,comparison of state-of-the-art methods, and stateof- the-art revisions. But, when practitioners start to implement their own software to carry out their research, there is a lack of articles in the literature with detailed documentation about how to design a framework for repeatable and comparable experimentation. We propose a design for repeatable and comparable experimentation on the field of Data-Driven Residual-Based Fault Detection and Isolation. The framework has already been used for several experiments, with successful results, eliciting features such as (i) decreasing of developing times, (ii) facilitating of configuration management, and (iii) facilitating of collection and comparison of results.

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