CAJ | 학술논문

目前煤矿井采用的瓦斯浓度监控设备一般为有线设备。而少数的无线设备一般采用均值法或利用高斯分布或其他一些算法对采集到的瓦斯浓度数据进行处理，在瓦斯气体分散的情况下误差较大，存在安全隐患。针对此类问题，本文提出了应用量子粒子群算法（QPSO）优化采集到的一定数量的瓦斯浓度数据，提高了数据精度，降低了误差，在一定程度上提高了安全指标，具有普遍的应用意义。
목전매광정채용적와사농도감공설비일반위유선설비。이소수적무선설비일반채용균치법혹이용고사분포혹기타일사산법대채집도적와사농도수거진행처리，재와사기체분산적정황하오차교대，존재안전은환。침대차류문제，본문제출료응용양자입자군산법（QPSO）우화채집도적일정수량적와사농도수거，제고료수거정도，강저료오차，재일정정도상제고료안전지표，구유보편적응용의의。
Currently the gas density monitoring equipment that used in minegas is generally wired. And the small number of wireless devices usually use the average method or Gaussian distribution or some other algorithm to process the collected gas density data. In the case of gas dispersion, the error is great and it exists security risk. For such problems, this paper presents quantum particle swarm optimization （QPSO） to optimize a number of collected gas density data. It improves the data accuracy, reduces the error, to some extent, improves the safety indicators, and it has general application significance.