A robust alternative to correlation networks for identifying fault systems

Autoren Patrick Traxler
Tanja Grill
Pablo Gomez
Editoren
TitelA robust alternative to correlation networks for identifying fault systems
BuchtitelProceedings of the 26th International Workshop on Principles of Diagnosis (DX-15)
Typin Konferenzband
MonatAugust
Jahr2015
Seiten11-18
SCCH ID#1439
Abstract

We study the situation in which many systems relate to each other. We show how to robustly learn relations between systems to conduct fault detection and identification (FDI), i.e. the goal is to identify the faulty systems. Towards this, we present a robust alternative to the sample correlation matrix and show how to randomly search in it for a structure appropriate for FDI. Our method applies to situations in which many systems can be faulty simultaneously and thus our method requires an appropriate degree of redundancy. We present experimental results with data arising in photovoltaics and supporting theoretical results.