煤与瓦斯突出信号挖掘方法研究

发布时间：2018-06-20 06:21

本文选题：煤与瓦斯突出 + 信号挖掘　；参考：《工矿自动化》2015年06期

【摘要】：针对传统关联聚类算法因难以捕捉异常信号非线性随机变化而造成采煤作业中特征信号检测不准确的问题,提出一种基于特征关联挖掘算法的煤与瓦斯突出信号挖掘方法。该方法利用小波变换提取煤矿井下作业区状态信号特征,为煤与瓦斯突出信号挖掘提供依据;计算煤矿井下作业区状态信号特征之间的关联度,实现煤与瓦斯突出特征信号挖掘。实验结果表明,该方法可提高煤与瓦斯突出信号挖掘的准确性。
[Abstract]:In order to solve the problem of inaccurate detection of characteristic signals in coal mining operation because of the difficulty in capturing the nonlinear random variation of abnormal signals in traditional association clustering algorithm, a method of mining coal and gas outburst signal based on characteristic association mining algorithm is proposed. The coal and gas outburst signal mining provides the basis, calculates the correlation degree between the characteristics of the state signal in the coal mine operation area, and realizes the coal and gas outburst characteristic signal mining. The experimental results show that this method can improve the accuracy of coal and gas outburst signal mining.
【作者单位】：平顶山学院计算机科学与技术学院;
【基金】：河南省重点科技攻关项目(142102210225)
【分类号】：TD713.2

【参考文献】