0

Full Content is available to subscribers

Subscribe/Learn More  >

Development of an Intelligent Rotating Machinery Diagnostics Programme

[+] Author Affiliations
Blaž Suhač, Jože Vižintin

University of Ljubljana, Ljubljana, Slovenia

Pavle Boškoski

University Ss. Cyril & Methodius Skopje, Skopje, Macedonia

Dani Juričić

Jožef Stefan Institute, Ljubljana, Slovenia

Paper No. ESDA2008-59190, pp. 561-567; 7 pages
doi:10.1115/ESDA2008-59190
From:
  • ASME 2008 9th Biennial Conference on Engineering Systems Design and Analysis
  • Volume 2: Automotive Systems; Bioengineering and Biomedical Technology; Computational Mechanics; Controls; Dynamical Systems
  • Haifa, Israel, July 7–9, 2008
  • Conference Sponsors: International
  • ISBN: 978-0-7918-4836-4 | eISBN: 0-7918-3827-7
  • Copyright © 2008 by ASME

abstract

Rotating machines are one of the most wide spread items of equimpnet in the industrial plants; hence the reliable operation is of great practical importance. Analyses show that when a run-to-failure philosophy is adopted in rotating machinery maintenance, their downtime is usually three to four times longer comparing to a periodic or proactive maintenance approach. A successful proactive maintenance program requires an integration of several diagnostic procedures into an intelligent data processing system. Such a system allows detection of a broad range of faults in an early stage. The main aim of this paper is to present current results of our development of an intelligent rotating machinery diagnostics program for detecting a broad range of faults from signals which can be measured non-destructively and on-line. The main motivation is to develop computationally efficient algorithm that can be implemented on a standard (low-cost) platform. In that respect we have developed a test rotating machine equipped with accelerometers, temperature sensors and sensors for lubricating oil characterization. In this paper we focus on gear-box faults and a feature extraction procedure based on non-parametric statistical concepts as suggested and demonstrated on experimental data.

Copyright © 2008 by ASME
Topics: Machinery

Figures

Tables

Interactive Graphics

Video

Country-Specific Mortality and Growth Failure in Infancy and Yound Children and Association With Material Stature

Use interactive graphics and maps to view and sort country-specific infant and early dhildhood mortality and growth failure data and their association with maternal

NOTE:
Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In