[2] Masaryk Univ, Dept Math & Stat, Brno, Czech Republic
来源:
2013 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING AND ENGINEERING MANAGEMENT (IEEM 2013)
|
2013年
关键词:
Field data assessment;
off-line diagnostics;
first hitting time;
residual life;
maintenance optimization;
PREDICTIVE MAINTENANCE;
RELIABILITY;
DISTRIBUTIONS;
SYSTEMS;
RISK;
D O I:
暂无
中图分类号:
T [工业技术];
学科分类号:
08 ;
摘要:
The aim of the article is to estimate a system technical life. When estimating a residual technical life statistically, a big amount of tribo-diagnostic data is used. This data serves as the initial source of information. It includes the information about particles contained in oil which testify to oil condition as well as system condition. We focus on the particles which we consider to be interesting. This kind of information has good technical and analytical potential which has not been explored well yet. By modelling the occurrence of particles in oil we expect to find out when a more adequate moment for performing preventive maintenance might come. The way of modelling is based on the specific characteristics of diffusion processes, namely the Wiener process. Following the modelling results we could in fact set the principles of "CBM- Condition Based Maintenance". However, the possibilities are much wider, since we can also plan operation and mission. All these steps result in inevitable cost saving.