SVM-Based Bearing Anomaly Identification with Self-Tuning Network-Fuzzy Robust Proportional Multi Integral and Smart Autoregressive Model

SVM-Based Bearing Anomaly Identification with Self-Tuning Network-Fuzzy Robust Proportional Multi Integral and Smart Autoregressive Model

In this paper, the combination of an indirect self-tuning observer, smart signal modeling, and machine learning-based classification is proposed for rolling element bearing (REB) anomaly identification. The proposed scheme has three main stages. In the first stage, the original signal is resampled,...

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Bibliographic Details
Main Authors: Shahnaz TayebiHaghighi, Insoo Koo
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Applied Sciences
Subjects:
rotating machine
rolling element bearing
indirect self-tuning observer
machine learning–based classification technique
autoregressive with external uncertainties
machine learning–based regression
Online Access:https://www.mdpi.com/2076-3417/11/6/2784

Internet

https://www.mdpi.com/2076-3417/11/6/2784

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