A Development Strategy for Structural Health Monitoring Applications

P. Cawley
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引用次数: 4

Abstract

Permanently installed structural health monitoring (SHM) systems are now a viable alternative to traditional periodic inspection (nondestructive testing (NDT)). However, their industrial use is limited, and this article reviews the steps required in developing practical SHM systems. The transducers used in SHM are fixed in location, whereas in NDT, they are generally scanned. The aim is to reach similar performance with high temporal frequency, low spatial frequency SHM data to that achievable with conventional high spatial frequency, and low temporal frequency NDT inspections. It is shown that this can be done via change tracking algorithms such as the generalized likelihood ratio (GLR), but this depends on the input data being normally distributed, which can only be achieved if signal changes due to variations in the operating conditions are satisfactorily compensated; there has been much recent progress on this topic, and this is reviewed. Since SHM systems can generate large volumes of data, it is essential to convert the data to actionable information, and this step must be addressed in the SHM system design. It is also essential to validate the performance of installed SHM systems, and a methodology analogous to the model-assisted probability of detection (POD) (MAPOD) scheme used in NDT has been proposed. This uses measurements obtained from the SHM system installed on a typical undamaged structure to capture signal changes due to environmental and other effects and to superpose the signal due to damage growth obtained from finite element predictions. There is a substantial research agenda to support the wider adoption of SHM, and this is discussed in this study.
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结构健康监测应用的发展策略
永久安装的结构健康监测(SHM)系统现在是传统定期检查(无损检测(NDT))的可行替代方案。然而,它们的工业用途是有限的,本文回顾了开发实际SHM系统所需的步骤。在SHM中使用的换能器是固定位置的,而在无损检测中,它们通常是扫描的。目标是在高时间频率、低空间频率的SHM数据下达到与传统高空间频率、低时间频率无损检测相似的性能。研究表明,这可以通过诸如广义似然比(GLR)之类的变化跟踪算法来实现,但这取决于输入数据是正态分布的,这只有在操作条件变化引起的信号变化得到满意补偿的情况下才能实现;最近在这一课题上取得了许多进展,本文对此进行综述。由于SHM系统可以生成大量数据,因此必须将数据转换为可操作的信息,并且必须在SHM系统设计中解决这一步骤。验证安装的SHM系统的性能也很重要,并提出了一种类似于无损检测中使用的模型辅助检测概率(POD) (MAPOD)方案的方法。该方法使用安装在典型未损坏结构上的SHM系统获得的测量数据来捕获由于环境和其他影响而产生的信号变化,并叠加由有限元预测获得的损伤增长信号。有大量的研究议程来支持更广泛地采用SHM,这在本研究中进行了讨论。
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来源期刊
CiteScore
3.80
自引率
9.10%
发文量
25
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