In Structural Health Monitoring, there are usually many strain sensors installed in different places of a single structure. The raw measurement of a strain sensor is generally a mixed response caused by different excitations such as moving vehicle loads, ambient temperature, etc. Monitoring data collected by different strain sensors are usually correlated with each other, correlation structures of responses caused by different excitations for different sensor pairs are quite diverse and complex. In Structural Health Monitoring, quantitatively describing and modeling complicated dependence structures of strain data is very important in many applications. In this article, copulas are exploited to characterize dependence structures and construct joint distributions of monitoring strain data. The constructed joint distribution is also applied in missing data imputation.
Comments: 8 Pages.
Unique-IP document downloads: 28 times
Vixra.org is a pre-print repository rather than a journal. Articles hosted may not yet have been verified by peer-review and should be treated as preliminary. In particular, anything that appears to include financial or legal advice or proposed medical treatments should be treated with due caution. Vixra.org will not be responsible for any consequences of actions that result from any form of use of any documents on this website.
Add your own feedback and questions here:
You are equally welcome to be positive or negative about any paper but please be polite. If you are being critical you must mention at least one specific error, otherwise your comment will be deleted as unhelpful.