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Application of frame energy based DCT moments for the damage diagnosis in steel plates using FLNN

机译:基于框架能量的DCT矩在FLNN诊断钢板损伤中的应用

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This paper discusses the application of frame energy based Discrete Cosine Transformation (DCT) moment features for the detection of damages in steel plates. A simple experimental model is devised to suspend the steel plates in a free-free condition. Experimental modal analysis methods are analyzed and protocols are formed to capture vibration signals from the steel plate using accelerometers when subjected to external impulse. Algorithms based on frame energy based DCT moment feature extraction are developed and prominent features are extracted. A Functional Link Neural Network (FLNN) is modeled to classify the condition of the steel plate. The output of the network model is validated using Falhman testing criterion and the results are compared.
机译:本文讨论了基于框架能量的离散余弦变换(DCT)矩特征在钢板损伤检测中的应用。设计了一个简单的实验模型,以自由状态悬挂钢板。分析了实验模​​态分析方法,并形成了协议,以在受到外部冲击时使用加速度计捕获来自钢板的振动信号。提出了基于帧能量的DCT矩特征提取算法,并提取了显着特征。对功能链接神经网络(FLNN)进行建模以对钢板的状况进行分类。使用Falhman测试准则验证网络模型的输出,并比较结果。

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