Gearbox Fault Identification Model Using an Adaptive Noise Canceling Technique, Heterogeneous Feature Extraction, and Distance Ratio Principal Component Analysis

Gearbox Fault Identification Model Using an Adaptive Noise Canceling Technique, Heterogeneous Feature Extraction, and Distance Ratio Principal Component Analysis

Using an adaptive noise canceling technique (ANCT) and distance ratio principal component analysis (DRPCA), this paper proposes a new fault diagnostic model for multi-degree tooth-cut failures (MTCF) in a gearbox operating at inconsistent speeds. To account for background and disturbance noise in th...

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Bibliographic Details
Main Authors: Cong Dai Nguyen, Cheol Hong Kim, Jong-Myon Kim
Format: Article
Language:English
Published: MDPI AG 2022-05-01
Series:Sensors
Subjects:
fault diagnosis
feature extraction
gearbox fault identification
adaptive noise canceling technique
principal component analysis
support vector machine
Online Access:https://www.mdpi.com/1424-8220/22/11/4091

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