Your browser doesn't support javascript.
loading
Gearbox tooth cut fault diagnostics using acoustic emission and vibration sensors--a comparative study.
Qu, Yongzhi; He, David; Yoon, Jae; Van Hecke, Brandon; Bechhoefer, Eric; Zhu, Junda.
Affiliation
  • Qu Y; Department of Mechanical and Industrial Engineering, University of Illinois at Chicago, Chicago, IL 60607, USA. yqu5@uic.edu.
  • He D; Department of Mechanical and Industrial Engineering, University of Illinois at Chicago, Chicago, IL 60607, USA. davidhe@uic.edu.
  • Yoon J; Department of Mechanical and Industrial Engineering, University of Illinois at Chicago, Chicago, IL 60607, USA. jyoon52@uic.edu.
  • Van Hecke B; Department of Mechanical and Industrial Engineering, University of Illinois at Chicago, Chicago, IL 60607, USA. bvanhe2@uic.edu.
  • Bechhoefer E; Department of Mechanical and Industrial Engineering, University of Illinois at Chicago, Chicago, IL 60607, USA. eric@gpms-vt.com.
  • Zhu J; Department of Mechanical and Industrial Engineering, University of Illinois at Chicago, Chicago, IL 60607, USA. jz@renewablenrgsystems.com.
Sensors (Basel) ; 14(1): 1372-93, 2014 Jan 14.
Article in En | MEDLINE | ID: mdl-24424467
In recent years, acoustic emission (AE) sensors and AE-based techniques have been developed and tested for gearbox fault diagnosis. In general, AE-based techniques require much higher sampling rates than vibration analysis-based techniques for gearbox fault diagnosis. Therefore, it is questionable whether an AE-based technique would give a better or at least the same performance as the vibration analysis-based techniques using the same sampling rate. To answer the question, this paper presents a comparative study for gearbox tooth damage level diagnostics using AE and vibration measurements, the first known attempt to compare the gearbox fault diagnostic performance of AE- and vibration analysis-based approaches using the same sampling rate. Partial tooth cut faults are seeded in a gearbox test rig and experimentally tested in a laboratory. Results have shown that the AE-based approach has the potential to differentiate gear tooth damage levels in comparison with the vibration-based approach. While vibration signals are easily affected by mechanical resonance, the AE signals show more stable performance.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Tooth Diseases / Vibration / Acoustics Type of study: Diagnostic_studies Limits: Humans Language: En Journal: Sensors (Basel) Year: 2014 Document type: Article Affiliation country: United States Country of publication: Switzerland

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Tooth Diseases / Vibration / Acoustics Type of study: Diagnostic_studies Limits: Humans Language: En Journal: Sensors (Basel) Year: 2014 Document type: Article Affiliation country: United States Country of publication: Switzerland