Role of Signal Processing, Modeling and Decision Making in the Diagnosis of Rolling Element Bearing Defect: A Review
Source abstract
Abstract
A significant development in condition monitoring techniques has been observed over the years. The scope of condition monitoring has been shifted from defect identification to its measurement, which was later on extended to automatic prediction of defect. This development is possible because of advancement in the area of signal processing. A number of signal processing and decision making techniques are available each having their own merits and demerits. A specific technique can be most appropriate for a given task, however, it may not be suitable or efficient for a different task. This paper reviewed recent and traditional research, and development in area of defect diagnosis, defect modelling, defect measurement and prognostics. Also it highlights the merit and demerit of various signal processing techniques. This paper is written with the objective to serve as guide map for those who work in the field of condition monitoring.
Source: openaire · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Machine Fault Diagnosis Techniques · Gear and Bearing Dynamics Analysis · Advanced machining processes and optimization
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (100+)
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