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Linear Classification of System Poles for Structural Damage Detection using Piezoelectric Active Sensors

机译:用压电活性传感器进行结构损伤检测系统极线的线性分类

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The identification of damage in structural systems, including characterization of damage location and severity, is of extreme interest to the structural engineering profession. To date, many damage detection methods have been proposed that utilize global structural response measurements in the time and frequency domains to hypothesize the existence of structural damage. The accuracy and robustness of current damage detection methodologies could be improved through the use of active sensors. Active sensors, such as piezoelectric pads, impart low-energy acoustic excitations into structural elements and can record the corresponding system behavior. In this study, a novel methodology utilizing the input-output behavior of actively sensed structural elements is proposed. The poles of ARX time-series models describing modal frequencies and damping ratios are plotted upon the discrete-time complex plane and Perceptron linear classifiers employed to determine if poles of the structural element in an unknown state (damaged or undamaged) can be separated with those of the undamaged structure. If poles of the unknown state are separable from those of the undamaged state, the system is diagnosed as damaged. A simple cantilevered aluminum plate damaged by hack saw cuts is actively sensed by piezoelectric pads to show the efficacy of the proposed damage detection methodology. Furthermore, the number of misclassified poles and the final value of the Perceptron criterion function can be shown to be correlated to the severity of the damage.
机译:识别结构系统的损坏,包括损害地区的表征和严重程度,对结构工程专业具有极大的兴趣。迄今为止,已经提出了许多损伤检测方法,其利用时间和频率域中的全局结构响应测量测量来假设结构损伤的存在。通过使用有源传感器可以提高电流损坏检测方法的准确性和稳健性。活性传感器,例如压电焊盘,将低能量声激发赋成结构元件,并且可以记录相应的系统行为。在本研究中,提出了一种利用主动感测结构元件的输入输出行为的新方法。描述了描述模态频率和阻尼比的ARX时间序列模型的极点在离散时间复杂的平面上绘制,并且用于确定结构元素的磁极在未知状态(损坏或未损坏)的情况下可以与那些分开没有损坏的结构。如果未知状态的极可分离未损坏状态,则系统被诊断为损坏。由黑客锯切割损坏的简单悬臂式铝板被压电垫主动感测,以显示所提出的损伤检测方法的功效。此外,错误分类的极点的数量和Perceptron标准功能的最终值可以被认为与损坏的严重程度相关。

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