Contribution to prediction of soft and hard failure occurrence in combustion engine using oil tribo data

When assessing technical systems, one can apply different condition indicators. If one takes into account indirect diagnostic indicators, lubricant seems to be a very good source of different information. Where the oil is part of a system, it is possible to get the information about the oil condition as well as the system itself. In this article the authors focus on the system of piston combustion engine and tribodiagnostic data. The indirect diagnostic information is the concentration level of contaminating particles in the oil. One observes specific particles of oil contamination - soot which is formed in the operation as a by-product during fuel combustion. The soot contaminates the oil significantly and the soot concentration shows under what conditions the system was operated. It also indicates that the system condition gradually deteriorates. There is a statistically very interesting set of data from the operation of heavy off-road vehicles. The recorded soot operation data depend on a few operation values: kilometres [km], days [day] and moto-hours [Mh]. Modelling a soft and a hard failure which might occur the moment the concentration reaches its critical value is performed with selected stochastic diffusion processes, namely the Wiener process with drift and the Ornstein-Uhlnbeck process. The main aim and contribution of this article is to estimate and study the distribution of the first hitting time of a critical threshold and to determine the moment when the soft and hard failure occur in a vehicle. The authors also try to estimate the engine useful residual life. They are aware, however, that there are numerous possibilities of using these results.

• Record URL:
  • https://doi.org/10.1016/j.engfailanal.2017.04.018
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S135063071630992X
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/13506307
• Supplemental Notes:
  • © 2017 Elsevier Ltd. Abstract reprinted with permission of Elsevier.
• Authors:
  • Vališ, David
  • Žák, Libor
• Publication Date: 2017-12

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: pp 583-598
• Serial:
  • Engineering Failure Analysis
  • Volume: 82
  • Publisher: Elsevier
  • ISSN: 1350-6307
  • Serial URL: https://www.sciencedirect.com/journal/engineering-failure-analysis

Subject/Index Terms

• TRT Terms: Degradation failures; Engine oils; Failure analysis; Internal combustion engines; Service life
• Uncontrolled Terms: Engine failure; Soot
• Subject Areas: Highways; Vehicles and Equipment;

Filing Info

• Accession Number: 01677971
• Record Type: Publication
• Files: TRIS
• Created Date: Aug 18 2018 10:05PM