Roller bearing acoustic signature extraction by wavelet packet transform, applications in fault detection and size estimation

By F. Hemmati, W. Orfali, M. Gadala. 2016

156 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Mechanical Engineering, Mechanics of Materials

View Paper: https://www.semanticscholar.org/paper/49d1337441decf74f94b81500256d90daf3e4282

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Control and Systems Engineering

1. David He
2. Miao He

In Mechanical Engineering

1. David He
2. Miao He

In Mechanics of Materials

1. David He
2. Miao He

Citations in the corpus

• Deep Learning Based Approach for Bearing Fault Diagnosis (2017, methodology): “[3] proposed a new algorithm by using wavelet packet transform to optimize the ratio of kurtosis and Shannon entropy for diagnosing local defects on bearings under various working conditions.”