Characterizing human activity induced impulse and slip-pulse excitations through structural vibration
Characterizing human activity induced impulse and slip-pulse excitations through structural vibration
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DOI：
10.1016/j.jsv.2017.10.034
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发表时间：
2018-02
影响因子：
4.7
通讯作者：
Shijia Pan;Mostafa Mirshekari;Jonathon Fagert;C. G. Ramirez;Albert Jin Chung;C. C. Hu-C.;John Paul Shen;Pei Zhang;H. Noh
中科院分区：
文献类型：
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作者：
Shijia Pan;Mostafa Mirshekari;Jonathon Fagert;C. G. Ramirez;Albert Jin Chung;C. C. Hu-C.;John Paul Shen;Pei Zhang;H. Noh
许多人类活动对周围各种物体的结构产生激励，导致结构振动。准确的振动激励源检测和表征使人类活动信息推断成为可能，从而为各种智能建筑应用提供人类活动监控。通过利用结构振动，我们可以实现稀疏和非侵入性的传感，而不是基于压力和视觉的方法。基于振动源的表征方法有很多，但由于结构的频散和衰减效应，这些方法要么集中在一种激励类型上，要么性能有限。在这篇文章中，我们提出了我们的方法来描述人类活动在多个结构上引起的两种主要类型的激励(脉冲和滑移脉冲)。该系统通过了解波的物理特性及其传播规律，在不需要大规模标注训练数据的情况下，实现对不同结构的精确激励跟踪。具体来说，我们的算法考虑了脉冲产生的表面波和滑移脉冲产生的体波的特性，以处理不同类型的激励在不同结构上发生时的色散和衰减效应。然后，我们通过多个场景对算法进行了评估。与不考虑波浪特性的现有方法相比，我们的方法在脉冲定位精度上提高了6倍，在滑移脉冲轨迹长度估计上提高了3倍。
Many human activities induce excitations on ambient structures with various objects, causing the structures to vibrate. Accurate vibration excitation source detection and characterization enable human activity information inference, hence allowing human activity monitoring for various smart building applications. By utilizing structural vibrations, we can achieve sparse and non-intrusive sensing, unlike pressure- and vision-based methods. Many approaches have been presented on vibration-based source characterization, and they often either focus on one excitation type or have limited performance due to the dispersion and attenuation effects of the structures. In this paper, we present our method to characterize two main types of excitations induced by human activities (impulse and slip-pulse) on multiple structures. By understanding the physical properties of waves and their propagation, the system can achieve accurate excitation tracking on different structures without large-scale labeled training data. Specifically, our algorithm takes properties of surface waves generated by impulse and of body waves generated by slip-pulse into account to handle the dispersion and attenuation effects when different types of excitations happen on various structures. We then evaluate the algorithm through multiple scenarios. Our method achieves up to a six times improvement in impulse localization accuracy and a three times improvement in slip-pulse trajectory length estimation compared to existing methods that do not take wave properties into account.