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On the Implementation of Neural Network Concept to Optimize Thermal Spray Deposition Process

机译:关于神经网络概念的实施以优化热喷涂沉积工艺

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摘要

Numerous processing parameters, up to fifty, characterize the plasma spray deposition process. A better quality control of the resulting deposits induces a better understanding of their effects on coating formation mechanisms. Numerical models can help to provide such an understanding. From a mathematical point of view, d.c. plasma spray deposition process is assimilated to a nonlinear problem in regards to its variables (operating parameters, environment, etc.). This paper develops a global approach based on an implicit describing of the mechanisms implementing Artificial Neural Networks (ANNs). The global concept and the protocols to implement are presented and developed for an example related to d.c. plasma spray process.
机译:多达50个处理参数代表了等离子喷涂沉积过程的特征。对生成的沉积物进行更好的质量控制,可以更好地理解其对涂层形成机理的影响。数值模型可以帮助提供这种理解。从数学角度来看,直流电就其变量(操作参数,环境等)而言,等离子喷涂沉积过程被等同于非线性问题。本文基于对实现人工神经网络(ANN)的机制的隐式描述,开发了一种全局方法。提出并开发了与dc相关的示例的全局概念和要实现的协议。等离子喷涂工艺。

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