用模糊方法识别信号趋势

Proceedings 11th International Conference on Tools with Artificial Intelligence Pub Date : 1999-11-08 DOI:10.1109/TAI.1999.809813

Xin Wang, T. Wei, J. Reifman, L. Tsoukalas

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引用次数: 5

摘要

介绍了一种基于模糊逻辑的在线信号趋势识别方法。虽然信号趋势识别由于噪声的存在而变得复杂，但模糊逻辑可以帮助捕获在线信号的重要特征，并将输入的电厂信号分为增加、减少和稳态趋势三类。为了验证该方法，开发了名为PROTREN的代码，并使用植物数据进行了测试。结果表明，该代码能够准确地检测瞬态，可靠地识别趋势，并且不会将稳态信号误认为瞬态信号。

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Signal trend identification with fuzzy methods

A fuzzy logic-based methodology for online signal trend identification is introduced. Although signal trend identification is complicated by the presence of noise, fuzzy logic can help capture important features of online signals and classify incoming power plant signals into increasing, decreasing and steady-state trend categories. In order to verify the methodology, a code named PROTREN is developed and tested using plant data. The results indicate that the code is capable of detecting transients accurately, identifying trends reliably, and not misinterpreting a steady-state signal as a transient one.

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Proceedings 11th International Conference on Tools with Artificial Intelligence

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