為了提高氣體傳感器漂移故障檢測的靈敏度,采用了一種基于多分辨分析理論的在線小波
分解算法(OLMS) . 與傳統(tǒng)的小波分解算法不同的是,OLMS 算法具有較好的實(shí)時性,適于在線使用. 采用該算法可以將傳感器輸出信號中發(fā)生在不同的時間尺度上的“事件”分離開,因此能夠?qū)⒆兓⑷醯钠铺卣鲝男盘栐肼暫推渌蓴_中有效地檢測出來. 此外,對于采集序列中常見的“野點(diǎn)”數(shù)據(jù),提出一種改進(jìn)的中位值濾波算法(MMF) 予以消除. 仿真計(jì)算結(jié)果證明了該算法的有效性.
關(guān)鍵詞: 在線小波變換;傳感器漂移;中位值濾波
Abstract : In order to improve the sensitivity of drift detection for gas sensors , an on2line wavelet de2 composition algorithm (OLMS) is applied. Unlike the t raditional wavelet decomposition algorithm , OLMS is adaptively used on2line. Applying this algorithm , the sensor signal can be decomposed into multi scales. This makes the drift features separated sensitively f rom the noises or other event s. More2 over , a modified median filtering method is proposed to eliminate the outliers in the collected data suc2 cessfully. Detail description of the algorithm is given and it s superior performances are illust rated by simulation.
Keywords : on2line w avelet decom position ; sensor drif t ; median f il ter