自适应信号识别在煤界面检测中的应用

G. L. Mowrey
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引用次数: 1

摘要

介绍了两种与矿机振动相关的煤岩界面探测(CID)方法,以及如何使用自适应信号识别(ASD)技术处理这些信号。在这些CID方法中,监测地层(顶板、煤层、底板)或采矿机振动产生的复杂信号,这些信号根据所使用的采矿机的类型而变化。然后使用先进的ASD技术对这些信号进行分析。正是这种先进的信号分析将这种方法与先前的研究区分开来。ASD系统最初使用从感兴趣条件下测量的已知信号中提取的特征数据库进行训练。随后,它使用该数据库来确定未知信号是否属于给定条件。假设ASD系统对这些信号进行了正确的分类,这样的系统就有可能控制采矿机,使其始终留在煤炭系统中。
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Adaptive signal discrimination as applied to coal interface detection
A description is given of two coal-rock interface detector (CID) methods associated with vibrations generated by mining machines and how adaptive signal discrimination (ASD) technology is being used to process these signals. In these CID methods, strata (roof, coal seam, floor) or mining machine vibrations are monitored for the complex signals generated, which vary according to the type of mining machine being used. These signals are then analyzed using sophisticated state-of-the-art ASD technology. It is this advanced signal analysis that distinguishes this approach from those of prior research. The ASD system is initially trained using a database of features extracted from known signals measured under conditions of interest. Subsequently, it uses this database to determine if unknown signals belong to a given condition. Assuming that the ASD system classifies these signals correctly, such a system could have the potential for controlling a mining machine so that it always remains in the coal system.<>
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