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Abstract：
To better address mechanical behavior, it is necessary to make use of modern tools through which it is possible to run predictions, simulate scenarios, and optimize decisions. sources integration. This will increase the capability of detecting material modifications that forerun damage and/or to forecast the stage in the future when very likely fatigue is initiating and propagating cracks. Early warning outcomes obtained by the synergetic implementation of NDE-based protocols for studying mechanical and fatigue and fracture behavior will enhance the preparedness toward economically sustainable future damage control scenarios. Specifically, these early warning outcomes will be developed in the form of retopologized models to be used coupled with FEA. This paper presents the first stage of calibration and the combination of a system of different sensors (photogrammetry, laser scanning and strain gages) for the creation of volumetric models suitable for the prediction of failure of FEA software. The test objects were two components of car suspension to which strain gauges were attached to measure its deformation under cyclic loading. The calibration of the methodology was carried out using models obtained from photogrammetry and experimental strain gauge measurements.
摘要：
为了更好地解决机械性能，有必要利用现代工具进行预测，模拟场景，优化决策。源整合。这将增加检测材料修改的能力，这些材料修改预示着损坏和/或预测将来很可能发生疲劳并扩展裂纹的阶段。通过协同实施基于NDE的协议来研究机械，疲劳和断裂行为而获得的预警结果将增强对经济上可持续的未来损害控制方案的准备。具体来说,这些预警结果将以重新拓扑模型的形式开发，并与FEA结合使用。本文介绍了校准的第一阶段和不同传感器系统的组合(摄影测量，激光扫描和应变计），用于创建适用于FEA软件故障预测的体积模型。测试对象是汽车悬架的两个组件，其上安装了应变仪以测量其在循环载荷下的变形。方法的校准是使用从摄影测量法和实验应变仪测量获得的模型进行的。
