Maximizing Incipient Fault Signatures of Rotating Machines Using Wavelet Entropy and Cyclic Logarithmic Envelope Spectrum
Author:
Affiliation:
1. School of Electrical Engineering, University of Ulsan, Ulsan, South Korea
Publisher
Informa UK Limited
Subject
Electrical and Electronic Engineering
Link
https://www.tandfonline.com/doi/pdf/10.1080/02564602.2016.1179135
Reference38 articles.
1. A Joint Kurtosis-Based Adaptive Bandstop Filtering and Iterative Autocorrelation Approach to Bearing Fault Detection
2. Rolling element bearing fault diagnosis based on the combination of genetic algorithms and fast kurtogram
3. Detection and diagnosis of incipient bearing failure in helicopter gearboxes
4. Vibration monitoring of rolling element bearings by the high-frequency resonance technique — a review
5. Differential Diagnosis of Gear and Bearing Faults
Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. A Wavelet Entropy-Based Approach to Select Structure Element of Morphological Filter for Bearing Fault Detection;SN Computer Science;2022-12-17
2. Underdetermined Source Separation of Bearing Faults Based on Optimized Intrinsic Characteristic-Scale Decomposition and Local Non-Negative Matrix Factorization;IEEE Access;2019
3. The Entropy Algorithm and Its Variants in the Fault Diagnosis of Rotating Machinery: A Review;IEEE Access;2018
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