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Near real-time tracking of dynamic properties for standalone structural health monitoring systems

机译:独立结构健康监测系统的动态特性近实时跟踪

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Automated modal parameter identification of civil engineering structures has been analyzed in a previous paper. An original algorithm, named LEONIDA, working in frequency domain, has been presented and a number of test cases have been discussed in order to point out advantages and drawbacks. It has been demonstrated that LEONIDA represents a promising and reliable tool, in particular for modal testing. Conversely, integration of such a procedure into a fully automated structural health monitoring (SHM) system has shown that it can be used as modal information engine, but length of record durations, amount of computational burden and response time lead to recognize that serious drawbacks and limitations exist for a class of applications, such as continuous monitoring of structures in seismically prone areas.In fact, a fast assessment of relevant structure health conditions in the early post-earthquake phase is becoming of interest in different European areas. In such a context, the statistical treatment of measured dynamic properties could be certainly useful, but it requires the collection of an extensive amount of local and global data in a short time.As a consequence, availability of reliable, robust and fairly fast data processing procedures for modal tracking is fundamental whenever really effective and useful SHM systems are adopted to support civil protection activities during seismic sequences. This applies mainly to strategic structures, whose health conditions must be rapidly assessed after any seismic event, in order to securely manage rescue operations.In the present paper, the main issues related to a fast, robust and reliable modal tracking for emergency management are outlined. Then, an automated modal tracking strategy for SHM applications in earthquake prone regions is described. It is based on the knowledge of the experimental mode shapes and a revised concept of spatial filtering. Results of sample applications of the proposed procedure refer to simulated data and to real measurements collected by a SHM system. The latter are representative of operational conditions and of the transient response due to the ground motion induced by the recent L'Aquila earthquake mainshock. Discussion of results will point out advantages and limitations of the data processing strategy.
机译:在先前的论文中已经分析了土木工程结构的自动模态参数识别。提出了一种名为LEONIDA的原始算法,该算法在频域中工作,并讨论了许多测试案例,以指出优缺点。事实证明,LEONIDA是一种有前途且可靠的工具,尤其是在模态测试中。相反,将这样的程序集成到全自动的结构健康监测(SHM)系统中表明,它可以用作模式信息引擎,但是记录持续时间的长度,计算量和响应时间导致人们认识到严重的缺陷和在诸如地震多发地区对建筑物进行连续监测等一类应用方面存在局限性。事实上,在欧洲不同地区,地震后早期对相关建筑物健康状况的快速评估已成为人们关注的问题。在这种情况下,对测得的动态特性进行统计处理固然有用,但需要在短时间内收集大量的本地和全局数据,因此,需要可靠,强大且相当快速的数据处理能力只要采用真正有效和有用的SHM系统来支持地震序列中的民防活动,模态跟踪程序就必不可少。这主要适用于战略结构,为了安全地管理救援行动,必须在任何地震事件后对其健康状况进行快速评估。本文概述了与快速,稳健和可靠的应急管理模式跟踪有关的主要问题。 。然后,描述了地震易发地区SHM应用的自动模式跟踪策略。它基于对实验模式形状的了解和对空间滤波的修订概念。拟议程序的样本应用结果涉及到模拟数据以及SHM系统收集的实际测量结果。后者代表了操作条件以及由于最近的拉奎拉地震主震引起的地面运动引起的瞬态响应。对结果的讨论将指出数据处理策略的优点和局限性。

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