首页> 外文会议>Thermosense: thermal infrared applications XXXVI >Estimating non-metallic coating thickness using artificial neural network modeled time-resolved thermography: capacity and constraints

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Estimating non-metallic coating thickness using artificial neural network modeled time-resolved thermography: capacity and constraints

机译：使用人工神经网络模拟时间分辨热成像法估算非金属涂层厚度：容量和约束

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Current studies suggest that thermography-based measurements may provide a feasible solution for measuring the thickness of non-metallic coatings. The focus of this research was to build an artificial neural network model to predict coating thickness using active thermography and thickness samples that have not previously been seen by the model. Best results (7.5% error) were achieved when using an ANN model with the derivative of a temperature increment's real part Laplace transform over the real axis as the input, the gradient descent with momentum back-propagation training algorithm, and 20 hidden nodes.

机译：当前的研究表明，基于热成像的测量可能为测量非金属涂层的厚度提供可行的解决方案。这项研究的重点是建立一个人工神经网络模型，以使用主动热成像技术和该模型先前未发现的厚度样本来预测涂层厚度。当使用ANN模型并以温度增量的实部在实轴上的拉普拉斯变换的导数作为输入，具有动量反向传播训练算法的梯度下降以及20个隐藏节点时，可获得最佳结果（7.5％误差）。

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来源
《Thermosense: thermal infrared applications XXXVI》|2014年|91050K.1-91050K.9|共9页
会议地点 Baltimore MD(US)
作者
Hongjin Wang; Sheng-Jen Hsieh;
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作者单位

Department of Mechanical Engineering, Texas AM University, College Station, TX USA 77843-3367;

Department of Mechanical Engineering, Texas AM University, College Station, TX USA 77843-3367,Department of Engineering Technology and Industrial Distribution Texas AM University, College Station, TX USA 77843-3367;

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正文语种 eng
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关键词
NDT; non-metallic coating thickness; thermography; artificial neural networks;

机译：无损检测；非金属涂层厚度热成像人工神经网络;

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1. Non-metallic coating thickness prediction using artificial neural network and support vector machine with time resolved thermography [J] . Wang Hongjin, Hsieh Sheng-Jen, Peng Bo, Infrared physics and technology . 2016,第Null期

机译：基于时间分辨热成像的人工神经网络和支持向量机的非金属涂层厚度预测
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3. Experimental Investigation and Artificial Neural Network Modeling of Warm Galvanization and Hardened Chromium Coatings Thickness Effects on Fatigue Life of AISI 1045 Carbon Steel [J] . Kazem Reza Kashyzadeh, Erfan Maleki Journal of Failure Analysis and Prevention . 2017,第6期

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Estimating non-metallic coating thickness using artificial neural network modeled time-resolved thermography: capacity and constraints

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