… Anomaly Detection approach for MPFM that considers the aforementioned constraints and
allows equipping the instrument with self-diagnosis … efficient Anomaly Detection tools and (ii) …

… • Anomaly detection: Our goal is to detect anomalies in the network in real time. The detection
should be automatic and unsupervised. The proposed solution should learn from previous …

… detect when and where a problem occurs in the network. On the other hand, most network-level
diagnosis tools can effectively detect … a new anomaly detection and diagnosis method by …

… to detect and diagnose previously unknown benign sensor … alternative techniques for anomaly
detection in SSME data … a very straightforward method for anomaly detection, based upon …

… The presence of an anomaly is confirmed for a given confidence level. The efficacy of the
proposed anomaly detection architecture is illustrated with test data acquired from components …

Several methods of the modern intelligent anomaly detection and fault diagnosis have been
developed to provide more efficient solutions. However, lacking of fault samples, the training …

… In this paper, anomaly detection aims to detect the transition point from the useful life period
to the wear-out period, and fault prognosis tries to predict the RUL in the wear-out period. To …

… diagnostic analytics, anomaly detection, which aims to detect data patterns that deviate
significantly from normal operation behaviour, is implemented to perform fault detection. Its …

… by detecting and diagnosing large-scale traffic anomalies in a … clearly suggest that anomaly
detection and diagnosis based on … of traffic anomalies, particularly in the studied scenario. …

… for detection of the incipient faults and anticipation of their impact on the future behavior
of the system using fault diagnosis … developments within Fault Detection and Diagnosis (FDD) …