摘要
为了向煤矿作业者提供可穿戴式井下安全告警设备,提出了一种基于可编程片上系统的智能腰带。讨论了利用小波软阈值降噪算法及3次样条插值,对瓦斯和氧气浓度测量值中的噪声和环境误差进行修正的措施。并研究了使用附加应力/移轴辅助参数的支持向量机判决模型对作业者的意外跌倒进行甄别的方法。详细阐述了系统的设计方案及具体实现方法。实验中分别对静态与动态环境下瓦斯与氧气检测效果、不同行为性状下的跌倒检测误检率与敏感度进行了测试。实验结果表明,该智能腰带可较为准确地对煤矿井下瓦斯、氧气参数及作业者意外跌倒进行检测告警。
A smart belt for wearable coal mine safety is presented in this paper.The random noise and nonlinear error in gas and oxygen measurement results are reduced by Wavelet Threshold algorithm and Cubic Spline Interpolation respectively.Support Vector Machine method with plantar stress and axis-shifting is introduced for fall detection.The specific configuration of this smart belt is discussed.Related experiments show the smart belt can monitor coal mine gas and oxygen parameters and fall detection with high precision.
出处
《电子测量技术》
2014年第9期98-103,共6页
Electronic Measurement Technology
基金
国家自然科学基金(11102038
61221249)资助项目
