A High-Resolution Frequency Estimation Method for Three-Phase Induction Machine Fault Detection

By Shahin Hedayati Kia, Humberto Henao, Gérard-André Capolino. IEEE transactions on industrial electronics (1982. Print), 2007

334 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/ddd544d3139cf89f0c1e3fce2fcdfaab5c4025c9

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. Mohamed El Hachemi Benbouzid
2. Vincent Choqueuse
3. El Houssin El Bouchikhi
4. Javier A. Rosero
5. A. Espinosa
6. Luís Romeral
7. Mahesh Krishnamurthy
8. Yao Da

In Mechanical Engineering

1. Mohamed El Hachemi Benbouzid
2. Vincent Choqueuse
3. El Houssin El Bouchikhi
4. Mahesh Krishnamurthy
5. Yao Da
6. Xiaodong Shi

Citations in the corpus

• Induction machine faults detection using stator current parametric spectral estimation (2015, methodology): “In [33], the MUSIC algorithm and a zooming method were combined to reduce the computational cost of the spectral estimator.”
• Fault Detection in Induction Machines Using Power Spectral Density in Wavelet Decomposition (2008, methodology): “To overcome this drawback, the multiple-signal-classification method with an algorithm with zooming in a specific frequency range is proposed in [13] to”
• Advances in Diagnostic Techniques for Induction Machines (2008, methodology): “[66], the MUSIC and zooming methods are conjugated to improve the diagnosis by detecting a large number of frequencies in a given bandwidth.”