井下人员违规进入无源监测方法

Passive monitoring method for underground personnel violation entry

  • 摘要: 针对现有井下人员违规进入监测方法存在实用性差、稳定性差、准确度低等问题,提出了一种基于WiFi网络信道状态信息的井下人员违规进入无源监测方法。该方法分为训练阶段和测试阶段:在训练阶段,分别采集有人进入、无人进入场景下信道状态信息数据,并对采集的数据进行离群点剔除和滤波等数据预处理,再将预处理后的数据构造成特征值,通过构造特征值建立判别模型;在测试阶段,将采集的数据预处理后构成特征值,再将特征值输入到训练阶段建立的判别模型中,实现人员是否违规进入判识。实验结果表明,该方法准确率达99.31%。

     

    Abstract: In view of problems of poor practicability, poor stability and low accuracy of existing monitoring methods for underground personnel violation entry, a passive monitoring method for underground personnel violation entry based on channel state information of WiFi network was proposed. The method includes training phase and testing phase. In the training phase, channel state information data under conditions of somebody entry and nobody entry is collected respectively, and the collected data is preprocessed through outlier elimination and filtering. Then the preprocessed data is constructed into eigenvalue to establish discrimination model. In the testing phase, the collected data is preprocessed to construct eigenvalue, which is input into the discrimination model established in the training phase, so as to realize judgment of personnel violation entry. The experimental results show that accuracy of the method is 99.31%.

     

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