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Smart structures health monitoring using artificial neural network

机译:使用人工神经网络的智能结构健康监测

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This paper presents a non-model based technique to detect and locate structural damage with the use of artificial neural networks. This method utilizes high frequency structural excitation (typically greater than 30 kHz) through a surface bonded piezoelectric sensor/actuator to detect changes in structural point impedance due to the presence of damage. Two sets of artificial neural networks were developed in order to detect, locate and characterize structural damage by examining changes in the measured impedance curves. A simulation beam model was developed to verify the propose method. An experiment was successfully performed in detecting damage on a 4-bay structure with bolted-joints, where the bolts were progressively released.
机译:本文提出了一种基于非模型的技术,利用人工神经网络来检测和定位结构损伤。该方法利用通过表面结合的压电传感器/执行器的高频结构激励(通常大于30 kHz)来检测由于损坏的存在而导致的结构点阻抗的变化。开发了两组人工神经网络,以便通过检查所测阻抗曲线的变化来检测,定位和表征结构损伤。仿真梁模型被开发来验证所提出的方法。成功地进行了一项试验,以检测螺栓连接在4托架结构上的损坏,并逐步释放螺栓。

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