基于粗糙集和支持向量机的矿井漏电保护系统故障线检测

Xiaoyan Shi, Longji Zhu
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引用次数: 0

摘要

由于矿山泄漏故障的复杂性和多样性,故障信息具有不确定性。粗糙集理论具有解决不确定性问题的能力,可以及时、准确地确定故障。本文采用粗糙集方法提取泄漏故障信号的属性特征,然后建立决策表。作为支持向量机的训练样本,通过决策规则得到泄漏故障信号与线路检测方法之间的判别准则,从而准确检测出故障线路。测试结果表明,采用粗糙集和支持向量机方法检测故障线路简单、高效,鲁棒性好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fault Line Detection of Leakage Protection System of Mine Based on Rough Sets and Support Vector Machine
For the complexity and multiformity of leakage faults of mine, the fault information has the uncertainty. With the capability of the solving the uncertain problem, Rough Sets theory can determine the fault timely and accurately. The paper adopted Rough Sets to extract the attribute characteristics of leakage fault signal and then to build the decision table. As the training sample of Support Vector Machine, the criterion by decision rules between the leakage fault signals and line detection method to detect fault line accurately can be gotten. The test results show that adopting the Rough Sets and Support Vector Machine to detect fault line is simple, efficient and good robustness.
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