Abstract: The present disclosure pertains to detection of anomalous conditions in a variety of types of systems. In one embodiment, a system may be configured to identify anomalous conditions in a stream of measurements. The system may include a communications interface configured to receive a stream of measurements. An archive subsystem may maintain a data archive comprising a statistical representation of the stream of measurements. A pre-processing subsystem may divide the stream of measurements into a plurality of data windows. The plurality of data windows may be analyzed by an analysis subsystem configured to generate a plurality of normalized representations based on the data archive. The plurality of normalized representations may be grouped into a plurality of ranges. An anomaly detection subsystem may perform a comparison of the plurality of normalized representations to at least one threshold and may determine that the comparison indicates an anomalous condition.

Abstract: The present disclosure pertains to detection of anomalous conditions in a variety of types of systems. In one embodiment, a system may be configured to identify anomalous conditions in a stream of measurements. The system may include a communications interface configured to receive a stream of measurements. An archive subsystem may maintain a data archive comprising a statistical representation of the stream of measurements. A pre-processing subsystem may divide the stream of measurements into a plurality of data windows. The plurality of data windows may be analyzed by an analysis subsystem configured to generate a plurality of normalized representations based on the data archive. The plurality of normalized representations may be grouped into a plurality of ranges. An anomaly detection subsystem may perform a comparison of the plurality of normalized representations to at least one threshold and may determine that the comparison indicates an anomalous condition.