Condition monitoring and classification of rotating machinery using wavelets and hidden Markov models

By Qiang Miao, V. Makis. 2007

138 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/704b2a7b4e873d8437ed26bb9a2601d84c0b036d

How researchers see this paper

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

In Analytical Chemistry

1. Michael G. Pecht
2. Jing Tian
3. Michael H. Azarian
4. Carlos Morillo
5. Kwok Leung Tsui
6. Dong Wang
7. Qiang Miao

In Control and Systems Engineering

1. Michael G. Pecht
2. Dong Wang
3. Kwok Leung Tsui
4. Jing Tian
5. Michael H. Azarian
6. Carlos Morillo
7. Qiang Miao
8. Hee-Jun Kang

Citations in the corpus

• Stochastic modelling and analysis of degradation for highly reliable products (2015, unknown): “Miao andMakis [97] used wavelet”
• Motor Bearing Fault Detection Using Spectral Kurtosis-Based Feature Extraction Coupled With K-Nearest Neighbor Distance Analysis (2016, methodology): “WPT has been found to have an aliasing problem near the border of the frequency bands, and there is no general rule to choose mother wavelets [19], [37], [38].”
• Prognostics and Health Management: A Review of Vibration Based Bearing and Gear Health Indicators (2018, background): “[82] Y. Zhan and V. Makis, ‘‘A robust diagnostic model for gearboxes subject to vibration monitoring,’’ J. Sound Vibrat., vol. 290, nos.”