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Title: Machinery fault diagnosis by wavelet analysis
Authors: Liu, Bao.
Keywords: DRNTU::Engineering::Mechanical engineering::Machine design and construction
Issue Date: 2000
Abstract: Many machines generate nonstationary dynamic signals. The featured components of such signals, such as spikes and transients, are usually localized both in time and in frequency. Since these features often carry rich information about the condition of the machines, enhancing and extracting them are of particular importance in machinery fault diagnosis.
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:MAE Theses

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