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Damage location in an isotropic plate using a vector of novelty indices

机译:使用新奇指数向量的各向同性板中的损伤位置

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This paper presents a novel approach to detecting and localising structural defects based on a novelty detection method, outlier analysis (OA), and a multi-layer perceptron (MLP) neural network. In order to assess the effectiveness of the approach, a thin rectangular plate with isotropic behaviour was evaluated experimentally. The scope of this present work also comprises an investigation of the scattering effect of an ultrasonic guided wave on the tested plate under both damaged and undamaged conditions. The wave propagation is sequentially transmitted and captured by 8 PZT patches bonded on the plate, forming a sensor network on the tested isotropic rectangular structure. An in-house 8 channel multiplexer is incorporated in this small scale and low-cost 'structural health monitoring' (SHM) system to effectively swap the PZTs role from sensor to actuator and vice-versa. The 'real-time damage demonstrator' software is primarily developed to acquire and store the waveform responses. These sets of scattering waveform responses representing normal and damage conditions are transformed into a set of novelty indices that ultimately determine the true conditions of the tested structure. The acquired novelty indices representing the available sensor paths are used as the inputs for the neural network incorporating the MLP architecture to compute and predict the damage location in the x and y location on the tested isotopic plate.
机译:本文提出了一种基于新颖性检测方法,离群分析(OA)和多层感知器(MLP)神经网络的检测和定位结构缺陷的新颖方法。为了评估该方法的有效性,对具有各向同性行为的矩形矩形薄板进行了实验评估。本工作的范围还包括在损坏和未损坏条件下研究超声波在被测板上的散射效果。波的传播通过结合在板上的8个PZT贴片依次传输和捕获,在经过测试的各向同性矩形结构上形成传感器网络。这种小型,低成本的“结构健康监控”(SHM)系统中集成了一个内部8通道多路复用器,可有效地将PZT的角色从传感器转换为执行器,反之亦然。 “实时损伤演示器”软件主要用于获取和存储波形响应。这些代表正常和破坏条件的散射波形响应集被转换为一组新颖性指标,这些指标最终确定了测试结构的真实条件。所获得的代表可用传感器路径的新颖性指数用作结合MLP架构的神经网络的输入,以计算和预测受测同位素板上x和y位置的损坏位置。

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