A physics-informed feature weighting method for bearing fault diagnostics
Intelligent bearing diagnostics has gained popularity over the last few years. However, most
of the diagnostic methods are developed under the assumption that training and test data
sets are collected under the same working conditions. This assumption is rare in practical
scenarios because rotating machinery usually works under wide ranges of rotational speeds
and loads. As bearings work under complex and time-varying operating conditions, the test
data might come from a data distribution outside the training distribution. Purely data-driven …
of the diagnostic methods are developed under the assumption that training and test data
sets are collected under the same working conditions. This assumption is rare in practical
scenarios because rotating machinery usually works under wide ranges of rotational speeds
and loads. As bearings work under complex and time-varying operating conditions, the test
data might come from a data distribution outside the training distribution. Purely data-driven …
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