Diagnosability Index and Its Application to Bearing Fault Diagnosis
Author:
Publisher
Springer Singapore
Link
http://link.springer.com/content/pdf/10.1007/978-981-15-5701-9_29
Reference17 articles.
1. Smith WA, Randall RB (2015) Rolling element bearing diagnostics using the Case Western Reserve University data: a benchmark study. Mech Syst Signal Process 64–65:100–131
2. Antoni J, Randall RB (2006) The spectral kurtosis: application to the vibratory surveillance and diagnostics of rotating machines. Mech Syst Signal Process 20(2):308–331
3. Antoni J (2016) The infogram: entropic evidence of the signature of repetitive transients. Mech Syst Signal Process 74:73–94
4. Tse PW, Wang D (2013) The design of a new sparsogram for fast bearing fault diagnosis: Part 1 of the two related manuscripts that have a joint title as “Two automatic vibration-based fault diagnostic methods using the novel sparsity measurement—Parts 1 and 2”. Mech Syst Signal Process 40(2):499–519
5. Tse PW, Wang D (2013) The automatic selection of an optimal wavelet filter and its enhancement by the new sparsogram for bearing fault detection: Part 2 of the two related manuscripts that have a joint title as “Two automatic vibration-based fault diagnostic methods using the novel sparsity measurement—Parts 1 and 2”. Mech Syst Signal Process 40(2):520–544
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