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Smart structures health monitoring using artificial neural network

机译:使用人工神经网络智能结构健康监测

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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:本文介绍了一种基于非模型的技术来检测和定位人工神经网络的结构损坏。该方法通过表面粘合的压电传感器/致动器利用高频结构激发(通常大于30 kHz),以通过存在损坏而检测结构点阻抗的变化。通过检查测量阻抗曲线的变化来开发两组人工神经网络以检测,定位和表征结构损坏。开发了模拟光束模型以验证提出的方法。成功进行了实验,在用螺栓接头检测到4个托架结构的损坏时进行,其中螺栓逐渐释放。

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