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,因此能夠將變化微弱的漂移特征從信號噪聲和其他干擾中有效地檢測出來. 此外,對于采集序列中常見的“野點”數據,提出一種改進的中位值濾波算法(MMF) 予以消除. 仿真計算結果證明了該算法的有效性.
關鍵詞: 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