Estimation in degradation models with explanatory variables.

V Bagdonavicius; M S Nikulin

doi:10.1023/a:1009629311100

Home/Archive/PubMed

PubMed · 11280850

Estimation in degradation models with explanatory variables.

V Bagdonavicius·M S Nikulin

View original source ↗Export metadata ↓

Abstract

Influence of covariates on degradation is modelled. Models which include dependence of the intensity of the process of traumatic events on the degradation level are also discussed. Estimation of reliability and degradation characteristics from data with covariates is considered in dynamic environments.

Explore related subjects

Equipment Failure Models, Statistical Stochastic Processes Journal Article

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

V Bagdonavicius, M S Nikulin. 2001. Estimation in degradation models with explanatory variables.. https://doi.org/10.1023/a%3A1009629311100

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2007

Tip cooling effect and failure mechanism of field-emitting carbon nanotubes.

The cooling effect accompanying field electron emission has been considered for a single carbon nanotube (CNT) used as a field emission (FE) electron source. An improved model for the failure mechanism of field emitting CNTs has been proposed and validated. Our model predicts a maximum temperature (T-max) located at an interior point rather than the tip of the CNTs, and the failure of the CNT emitters tends to take place at the T-max point, inducing a segment by segment breakdown process. A combination of Joule heating and electrostatic force effect is proposed responsible for initiating the failure of the field emitting CNT and validated by in situ FE observation.

Equipment Failure↗

PubMed2007

A solution to one cause of accidental cuff deflation.

Explore the source record for details and available documents.

Equipment Failure↗

PubMed2006

[Importance of an initial check-up for diagnostic radiology apparatus management].

The management of apparatus for diagnostic imaging is an important job for radiological technologists. In the last 10 years we have encountered 2227 malfunctions in 3652 days. We detected 163 cases at the initial check-up, which accounted for 7.3% of total cases. By performing an initial check-up, we detected one malfunction every 21 days and were able to keep the effects of mishaps to a minimum, prevent accidents, and obtain stable-quality images.

Equipment Failure↗