Cointegration: a novel approach for the removal of environmental trends in structural health monitoring data
Cointegration: a novel approach for the removal of environmental trends in structural health monitoring data
复制标题
DOI：
10.1098/rspa.2011.0023
复制
发表时间：
2011-09-08
影响因子：
3.5
通讯作者：
Chen, Qian
中科院分区：
文献类型：
--
作者：
Cross, Elizabeth J.;Worden, Keith;Chen, Qian
在结构健康监测（SHM）技术可以可靠地实施在实验室条件以外的结构，监测功能的环境变化的问题必须首先得到解决。受到变化的环境或操作条件的结构通常会表现出固有的非平稳动态和准静态响应，这可以掩盖任何变化所造成的损害的发生。目前的工作介绍了协整的概念，非平稳时间序列的分析工具，作为一个有前途的新方法，用于处理监测功能的环境变化的问题。如果来自SHM系统的两个或多个监测变量被协整，那么它们的一些线性组合将是清除原始数据集中共同趋势的平稳残差。从协整过程中创建的平稳残差可以用作损伤敏感的功能，是独立的正常的环境和操作条件。
Before structural health monitoring (SHM) technologies can be reliably implemented on structures outside laboratory conditions, the problem of environmental variability in monitored features must be first addressed. Structures that are subjected to changing environmental or operational conditions will often exhibit inherently non-stationary dynamic and quasi-static responses, which can mask any changes caused by the occurrence of damage. The current work introduces the concept of cointegration, a tool for the analysis of non-stationary time series, as a promising new approach for dealing with the problem of environmental variation in monitored features. If two or more monitored variables from an SHM system are cointegrated, then some linear combination of them will be a stationary residual purged of the common trends in the original dataset. The stationary residual created from the cointegration procedure can be used as a damage-sensitive feature that is independent of the normal environmental and operational conditions.