Detection of Signal Integrity Issues in Vibration Monitoring Using One-Class Support Vector Machine

This paper presents an analysis of the common signal integrity issues in vibration monitoring caused by sensor saturation and signal distortion, or sensor loosening and detachment, and the development of a method of detecting the occurrence of vibration signal integrity issues using a one-class supp...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of Vibration Engineering & Technologies 2024-12, Vol.12 (Suppl 1), p.601-611
Hauptverfasser: Kannan, Vigneshwar, Dao, Dzung Viet, Li, Huaizhong
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:This paper presents an analysis of the common signal integrity issues in vibration monitoring caused by sensor saturation and signal distortion, or sensor loosening and detachment, and the development of a method of detecting the occurrence of vibration signal integrity issues using a one-class support vector machine. For this, vibration signals with distortions due to sensor saturation and/or sensor detachment are analysed to determine parameters sensitive to common integrity issues. These features are then extracted from training data of good quality vibration signals. Principal Component Analysis is used to dimensionally reduce the parameters which are then used in the training of the one-class support vector machine. The proposed method was validated on trained and untrained health conditions. Additionally, model sensitivity was also tested on trained health conditions with varying defect sizes. The method successfully detected all signal integrity issues tested proving to be an effective pre-processing step in condition monitoring systems for increased reliability and accuracy.
ISSN:2523-3920
2523-3939
DOI:10.1007/s42417-024-01435-8