利用神经网络对电解槽工艺条件进行仿真

Alena N. Ilyushina, O. A. Beliaevskii, I. M. Novozhilov
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引用次数: 0

摘要

电解池运行参数的测量是一项耗时的任务。由于存在大量的外部因素,测量精度仍然很低。为了消除这个缺点,论文的作者建议在细胞上放置更多的无线传感器,从这些传感器获取的数据进入神经网络。作者在MatLab中创建了用于进一步分析的网络。配置的系统使监视和预测单元的技术状态成为可能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Simulation of the Technical Condition of the Electrolyzer Using Neural Networks
Measuring parameters of an operating electrolysis cell is a time-consuming task. The measurement accuracy remains quite low due to the presence of a huge number of external factors. To eliminate this shortcoming, the authors of the paper propose to place a larger number of wireless sensors on the cell, the data from which comes into the neural network. Authors created the network for further analysis in MatLab. The configured system makes it possible to monitor and predict the technical state of the cell.
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