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Machine fault diagnosis collects massive amounts of vibration data about complex mechanical systems. Performing feature detection from these data sets has already led to a major challenge. Compressive sensing theory is a new sampling framework that provides an alternative to the well-known Shannon sampling theory. This theory enables the recovery of sparse or compressible signals from a small set...
Machine fault diagnosis collects massive amounts of vibration data about complex mechanical systems. Analyses of the information contained in these data sets have already led to a major challenge. Compressed sensing (CS) theory is a new sampling framework that provides an alternative to the well-known Shannon sampling theory. This theory enables the recovery of sparse or compressible signals from...
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