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Reference: Duhaney, J., T.M. Khoshgoftaar, I. Cardei, B. Alhalabi, J.C. Sloan, 2010: Applications of data fusion in monitoring inaccessible ocean machinery. Proceedings, 16th International ISSAT on Reliability and Quality in Design, 5-7 August, 2010, International Society of Science and Applied Technologies. ISBN: 978-0-9763486-6-5.
Abstract: Machine condition monitoring (MCM) enables real time health assessment, prognostics, and advisory generation by interpreting data from sensors installed on the machine being monitored. To effectively utilize measurements for determining the health of individual components, macro-components and the overall system, these measurements must somehow be combined or integrated to form a holistic picture. The process used to perform this combination is called sensor data fusion. While research on data fusion techniques spans across many domains, not much work has been done in data fusion for MCM in unmanned systems. This paper addresses this need by providing the intuition behind a mathematical model and process for data fusion in ocean machinery.