Information Fusion of Infrared Images and Acoustic Signals for Bearing Fault Diagnosis of Rotating Machinery - Surveillance, Vibrations, Shock and Noise Access content directly
Conference Papers Year : 2023

Information Fusion of Infrared Images and Acoustic Signals for Bearing Fault Diagnosis of Rotating Machinery

Abstract

To minimize the operation and maintenance costs of rotating machinery, damaging conditions should be detected in the early stages. In recent years, infrared (IR) imaging and acoustic-based condition monitoring methods have gained attention for this purpose. To solve the problems when one single type of data, either acrostic signals or IR images, cannot be individually used to assess the severity of faults in rotating machinery, in this paper we proposed an information fusion method to improve the utilization of multisource sensor systems. Fusing the extracted information from both sources is performed with the aid of a fuzzy inference system. The effectiveness of the proposed techniques is demonstrated through the data that has been captured by an inspection mobile robot for monitoring conveyor belt idlers at a mining site
Fichier principal
Vignette du fichier
SURVISHNO_2023_EDITED_1.pdf (447.17 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-04165899 , version 1 (19-07-2023)

Identifiers

  • HAL Id : hal-04165899 , version 1

Cite

Mohammad Siami, Hamid Shiri, Tomasz Barszcz, Jacek Wodecki, Radoslaw Zimroz. Information Fusion of Infrared Images and Acoustic Signals for Bearing Fault Diagnosis of Rotating Machinery. Surveillance, Vibrations, Shock and Noise, Institut Supérieur de l'Aéronautique et de l'Espace [ISAE-SUPAERO], Jul 2023, Toulouse, France. ⟨hal-04165899⟩

Collections

SURVISHNO2023
63 View
44 Download

Share

Gmail Facebook X LinkedIn More