Lightweight Multi-System Multivariate Interconnection and Divergence Discovery

arXiv:2404.08453v1 Announce Type: new
Abstract: Identifying outlier behavior among sensors and subsystems is essential for discovering faults and facilitating diagnostics in large systems. At the same time, exploring large systems with numerous multivariate data sets is challenging. This study presents a lightweight interconnection and divergence discovery mechanism (LIDD) to identify abnormal behavior in multi-system environments. The approach employs a multivariate analysis technique that first estimates the similarity heatmaps among the sensors for each system and then applies information retrieval algorithms …

abstract arxiv behavior cs.lg cs.sy data data sets diagnostics discovery divergence eess.sy identify multivariate outlier sensors study systems type