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Identification of dynamic loads on structural component with artificial neural networks

机译:用人工神经网络识别结构部件的动态载荷

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Enhancing structural components by implementing sensors offers great potential regarding condition monitoring for lifetime analysis, predictive maintenance and automatic adaptation to environmental conditions. This article describes an approach to determining the operational forces applied to the front suspension arm of a car using strain gauges. Since suspension arms are components with free-form surfaces, an analytical calculation of applied forces by means of measured strains is not feasible. Hence, artificial neural networks are applied to approximate the functional relationship. The results reveal how artificial neural networks can be applied to identify load conditions on structural components and, therefore, deliver essential data for condition monitoring.
机译:通过实施传感器增强结构部件,对终身分析,预测性维护和环境条件的自动适应的状态监测提供了很大的潜力。本文介绍了使用应变仪确定施加到汽车的前悬架臂的操作力的方法。由于悬浮臂是具有自由形状表面的组分,因此通过测量的菌株的施加力的分析计算是不可行的。因此,应用人工神经网络以近似于功能关系。结果揭示了人工神经网络如何应用于识别结构部件上的负载条件,因此为条件监测提供必要的数据。

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