Abstract
Fault Diagnosis is a process of detecting and isolating faults in a system. On demanding for safety and high reliability systems make it important for some reasons such as economical and environmental incentives. Especially embedded technology and IT technology combined with precise sensing techniques has been doing well developed and applied to fault diagnosis and prognosis in industrial systems like as automotive, ship, heavy industry and aerospace as well. This paper, as an empirical application of diesel engine, presents a method how to get raw data from physical systems, what to consider for successful implementation and which theoretic mathematical models should be applied. In a sense of system level Adaptive Filtering (we call Modified Kalman Filter) and a unit of part level Hidden Markov Process was developed and applied.
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