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Development of Virtual Visual Sensor Applications for Wood Structural Health Monitoring

机译:用于木材结构健康监测的虚拟视觉传感器应用程序的开发

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Inspection techniques for wood structures are typically based on visual observations of degradation, and often limited to localized observable surface damage on the structure, rather than holistic non-destructive evaluations. Hidden deterioration and overall impacts of distributed damage may not be included in the assessment. This research evaluates the implementation of Eulerian-based virtual visual sensors (VVS), applying commercially available digital video cameras, to characterize dynamic structural response of wood structures. Natural vibration frequencies are determined by monitoring the intensity value of a single fixed pixel coordinate over a few seconds of a video of structural vibration and then applying a fast Fourier transform to estimate signal frequencies. Changes in stiffness and mass of materials and structural systems that may relate to deterioration are reflected in the natural frequencies. The end goal is development and application of VVS to wood structures to obtain information relevant to objective structural health monitoring (SHM). In this development phase, the effects of moisture content and simulated damage on natural frequencies are observed on simply supported beams of dimensional lumber. Initial applications are also made to an in-place U.S. Forest Service pedestrian bridge. Results show comparable accuracy in determining vibrational frequencies with VVS and a commercially available transverse vibration measurement system, successful observation of vibrational frequencies in a timber bridge, and beneficial use of naturally occurring color gradients in wood structures in laboratory and field tests. Moisture content and simulated damage have measurable effects on natural frequencies. Eulerian-based VVS show potential as a tool for cost-effective SHM of wood structures, especially for quick, global screening of structures, with subsequent visual inspection and other means of evaluation.
机译:木质结构的检查技术通常基于对退化的视觉观察,通常仅限于对结构进行局部可观察的表面损伤,而不是整体的非破坏性评估。评估中可能不包括隐性恶化和分布式破坏的整体影响。这项研究评估了基于欧拉的虚拟视觉传感器(VVS)的实现,应用了市售的数码摄像机来表征木结构的动态结构响应。通过在结构振动视频的几秒钟内监视单个固定像素坐标的强度值,然后应用快速傅立叶变换来估计信号频率,来确定自然振动频率。可能与退化有关的材料和结构系统的刚度和质量变化会在固有频率中反映出来。最终目标是开发VVS并将其应用于木结构,以获得与客观结构健康监测(SHM)有关的信息。在此开发阶段,在简单支撑的尺寸木材梁上观察到了水分含量和模拟损伤对自然频率的影响。最初的应用还用于就地美国森林服务局的行人天桥。结果表明,使用VVS和市售的横向振动测量系统确定振动频率时,具有相当的精度,可以成功观察木桥中的振动频率,并且可以在实验室和现场测试中有益地利用木材结构中自然发生的颜色梯度。水分含量和模拟损伤对自然频率有可测量的影响。基于欧拉的VVS具有潜力,可作为具有成本效益的木结构SHM的工具,尤其是对结构进行快速,全面的筛查以及随后的目视检查和其他评估手段。

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