Data Driven Framework for Prognostics

• Other Authors: Varadarajan, Gayathri (Author)
• Format: Dissertation
• Language: English
• Published: 2010
• Subjects: Computer Science; Database; Data management system; Prognostics
• Online Access: http://hdl.handle.net/2286/R.I.8595

abstract: Prognostics and health management (PHM) is a method that permits the reliability of a system to be evaluated in its actual application conditions. This work involved developing a robust system to determine the advent of failure. Using the data from the PHM experiment, a model was developed to estimate the prognostic features and build a condition based system based on measured prognostics. To enable prognostics, a framework was developed to extract load parameters required for damage assessment from irregular time-load data. As a part of the methodology, a database engine was built to maintain and monitor the experimental data. This framework helps in significant reduction of the time-load data without compromising features that are essential for damage estimation. A failure precursor based approach was used for remaining life prognostics. The developed system has a throughput of 4MB/sec with 90% latency within 100msec. This work hence provides an overview on Prognostic framework survey, Prognostics Framework architecture and design approach with a robust system implementation. === Dissertation/Thesis === M.S. Computer Science 2010