Bearing fault detection of induction motor using wavelet and Support Vector Machines (SVMs)

By P. Konar, P. Chattopadhyay. Applied Soft Computing, 2011

477 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/80049985b4fce9825b29e2d3d4faf6cd92658b4c

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. Boyuan Yang
2. Ruonan Liu
3. Enrico Zio
4. Yihao Xue
5. Gaoliang Peng
6. Mengjie Huang
7. Hongyan Tao
8. Yong Guan

In Mechanical Engineering

1. Enrico Zio
2. Gaoliang Peng
3. Hongyan Tao
4. Yong Guan
5. Zhujun Zhang
6. Ran Zhang
7. Yuanhang Chen
8. Lifeng Wu

Citations in the corpus

• Transfer Learning With Neural Networks for Bearing Fault Diagnosis in Changing Working Conditions (2017, methodology): “Machine learning algorithms and classifiers with signal processing methods are commonly used in traditional data driven fault diagnosis models [4]–[6].”
• Artificial intelligence for fault diagnosis of rotating machinery: A review (2018, methodology): “Along with continuous wavelet transform (CWT), SVM is used for bearing fault detection of induction motors [61].”
• A New Deep Learning Model for Fault Diagnosis with Good Anti-Noise and Domain Adaptation Ability on Raw Vibration Signals (2017, methodology): “In [16], continuous wavelet transform was used to overcome the shortcomings of the traditionally used Fourier transform, like not being able to tell when a particular event took place, and then SVM is used as the classifier to analyze frame vibrations.”
• Deep Transfer Learning for Bearing Fault Diagnosis: A Systematic Review Since 2016 (2023, background): “machine [32], k-nearest neighbor [33], artificial neural net-”
• Wavelets for fault diagnosis of rotary machines: A review with applications (2014, unknown): “Konar and Chattopadhyay proposed a hybrid CWT-Support Vector Machine (SVM) approach for bearing fault detection in induction motor [54].”