CORRELATION AND ANNOTATION OF TIME SERIES DATA SEQUENCES TO EXTRACTED OR EXISTING DISCRETE DATA

• Main Authors: INTERRANTE, John A, COURTNEY, Brian Scott, MATHUR, Sunil, AGGOUR, Kareem Sherif, BOWMAN, Ward Linnscott, WILLIAMS, Jenny Marie Weisenberg
• Format: Patent
• Language: English; French; German
• Published: 25.11.2020
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; CONTROL OR REGULATING SYSTEMS IN GENERAL; CONTROLLING; COUNTING; ELECTRIC COMMUNICATION TECHNIQUE; ELECTRICITY; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS; PHYSICS; REGULATING; TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION

A system for predicting events by associating time series data with other types of non-time series data can include a processor configured to receive a data stream including time series data transmitted from a sensor configured to measure an operating parameter of a component being monitored. The processor identifies sequences of interest in the time series data having predictive value. The processor compares the real-time data stream to a set of known historical patterns that act as effective leading indicators of different alarms and events. The processor extracts any identified sequences of interest from the time series data as an extracted event. The processor quantifies the relationship between the data of the extracted event and the known historical pattern by calculating a confidence level to denote a probability of occurrence of the event by comparing how closely the new time series data matches the data patterns associated with known events.