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Structural monitoring of a tower by means of MEMS-based sensing and enhanced autoregressive models

机译:通过基于MEMS的传感和增强的自回归模型对塔进行结构监测

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摘要

Structural Health Monitoring (SHM) methodologies are taking advantage of the development of new families of MEMS sensors and of the available network technologies. Advanced systems rely on intelligent bus-connected sensing units performing locally data filtering, elaboration and model identification. This paper describes a family of enhanced multivariate autoregressive models that can be used in SHM-oriented identification procedures and the implementation of a new advanced SHM system in the tower of the Engineering School of Bologna University. It describes also the results given by the considered procedure and a comparison of the implemented MEMS-based system with a traditional solution based on piezoelectric seismic accelerometers.
机译:结构健康监测(SHM)方法正在利用MEMS传感器新系列和可用网络技术的发展。先进的系统依靠与智能总线相连的传感单元执行本地数据过滤,细化和模型识别。本文介绍了一系列增强的多元自回归模型,这些模型可用于面向SHM的识别过程以及在博洛尼亚大学工程学院塔楼中实施的新的高级SHM系统。它也描述了所考虑的过程所给出的结果,以及所实施的基于MEMS的系统与基于压电地震加速度计的传统解决方案的比较。

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