作　　者： ; ; ; ; ; ; ;

机构地区： 华中科技大学能源与动力工程学院煤燃烧国家重点实验室

出　　处： 《化工学报》 2002年第12期1276-1280,共5页

摘　　要： 利用小波分解、滤波、重构对热重信号进行去噪处理,消除实验中由于各种因素产生的噪声,得到了较为满意的热重实验数据.该方法与其他处理方法相比,得到的处理信号不失真且去噪效果明显.比较发现小波去噪的结果与阈值选取相关,通过分析确定合适的阈值选取规则,使得处理后的信号能满足以后分析的需要.研究表明选择的阈值可广泛应用于不同煤种的热重实验数据处理. By using wavelet decomposition, filtering and reconstructing, noise signal could be deleted from thermogravimetry signal. It can help researchers to gain true parameters about kinetic characteristics. Different process methods were compared and several rules of threshold selection for wavelet noise removal were studied. Some parameters of processed signal curve were calculated by different threshold selection rules. By utilizing this information, the characteristics of this processed signal by different threshold selection rules were confirmed. Power-spectrum analysis was used to change the time-varying information into frequency distribution information. Quantitative comparison of signals could be made. Wavelet transform is an effective and accurate method, which can be used in thermogravimetry signal processing.

关 键 词： 小波分析 热重实验 数据处理 去噪 信号处理 定量分析

领　　域： [理学] [理学] [电子电信] [电子电信]