Machine Fault Diagnosis and Prognosis: The State of The Art
International Journal of Fluid Machinery and Systems
Machine fault diagnostic and prognostic techniques have been the considerable subjects of condition-based maintenance system in the recent time due to the potential advantages that could be gained from reducing downtime, decreasing maintenance costs, and increasing machine availability. For the past few years, research on machine fault diagnosis and prognosis has been developing rapidly. These publications covered in the wide range of statistical approaches to model-based approaches. With the
... m of synthesizing and providing the information of these researches for researcher's community, this paper attempts to summarize and classify the recent published techniques in diagnosis and prognosis of rotating machinery. Furthermore, it also discusses the opportunities as well as the challenges for conducting advance research in the field of machine prognosis. conducted by Prof. Kim Youn-jea. (Paper number R08030) Corresponding author: Bo-Suk Yang, Professor, firstname.lastname@example.org Knowledge-Based Approaches Knowledge-based system (KBS) or expert system (ES) for fault diagnosis is performed based upon the evaluation of on-line monitored data according to a rule set which is determined by expert knowledge. This knowledge includes the locations of input and output process variables, patterns of abnormal process conditions, fault symptom, operational constraints, and performance criteria. The operators and engineers' intelligence related to the specific process systems can be implemented into this approach.