利用Kohonen特征映射监测同步发电机运行状态

Workshop on Neural Network Applications and Tools Pub Date : 1993-09-13 DOI:10.1109/NNAT.1993.586058

H. Jiang, J. Penman

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引用次数: 9

摘要

本文阐述了利用无监督学习的神经网络对同步发电机运行状态进行自动监控的方法。结果表明，如果明智地选择网络的大小，那么就有可能一致且明确地识别出此类机器中的一系列非典型条件。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Using Kohonen Feature Maps To Monitor The Condition Of Synchronous Generators

This paper illustrates the way in which a neural network, employing unsupervised learning, can be used for the automatic surveillance of the operational condition of synchronous generators. Results show that, if the size of the network is chosen judiciously, then it is possible to cosistently, and unambiguously identifi a range of atypical conditions in such machines.

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Workshop on Neural Network Applications and Tools

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