Wavelet Analysis in the Signal Processing

The conceptions of mother wavelet and complete wavelet system are introtuced.Their digital features are described in detail.The definitions of con ti n nons, discrete, and dyadic discrete wavelet transforms are given,and their inverse transforms are deduced with reference to thevector expressions in R2 space.     

Suppression of Periodic Narrowband Interferences in Cable Partial Discharge Detections

There are background noises and interferences in the signal acquired,due to partial discharge(PD) detection system covers a broad frequency band.To suppress periodic narrowband signal which is a quite serious interference in PD measurement,the existing suppression method is introduced,the new method of wavelet packet transform is mainly studied to de-noise the periodic narrowband in XLPE cable PD detection system,which is based on the db4 basic wavelet using soft threshold.The results of the experiment show that wavelet packet transform is effective in restraining the periodic narrowband interferences to extract the PD pulses in XLPE cable PD monitoring system.     

A New Method of Diesel Engine Fuel System Fault Diagnosis

A method of diesel engine fuel system fault diagnosis based on wavelet transform and fuzzy C-means clustering is presented. Five characteristic parameters of reflecting fault state are distilled with wavelet transform of pressure wave of high-pressure oil pipe of diesel. The theory and generic approach of fuzzy C-means clustering algorithm (FCM) is given, and the validity of evaluating fuzzy clustering making use of partition coefficient, partition entropy and parting coefficient is pointed out. Identification of fault mode can be completed utilizing standard fault character modes established by FCM algorithm, and calculating and comparing the similarity degree between this standard mode and sample. The arithmetic is applied to all kinds of typical faults diagnose in the diesel engine fuel system. Measuring results indicate that the precision of fault diagnosis is increased with the analysis of wavelet and FCM.     

强化杨木单板的傅立叶红外光谱分析

通过热压聚合方法,利用苯乙烯和甲基丙烯酸甲酯对杨木进行强化试验,结果表明:聚合温度是主要影响因素,而聚合时间和引发剂、促聚剂的添加数量等因素是次要影响因素;聚合温度x与单体转化率y高度线性相关,线性回归方程为y=0.107x-0.036 7;最优制备工艺为:聚合温度80℃,聚合时间6h,环烷酸钴、氯化锌以及引发剂AIBN所占混合树脂掖比分别为2%、6%、3%;最大转化率为64.50%。傅立叶变换红外光谱分析结果表明,强化杨木单板中含有大量的苯环聚合物,羰基官能团大量增加。     

超声波辅助碱法提取酒糟中纤维素和半纤维素

为了获取酒糟中优质的纤维素和半纤维素组分,采用超声波辅助碱提法进行同步提取。以酒糟为原料,以纤维素得率和半纤维素得率为指标,研究KOH溶液质量分数、浸提温度和超声波时间等因素对纤维素和半纤维素提取效果的影响,通过正交试验优化了提取条件。结果表明,在KOH溶液质量分数为7.5%,浸提温度为55℃,超声波时间为10 min条件下,酒糟中纤维素和半纤维素得率分别为38.72%和26.34%,说明采用超声波辅助碱法分离纤维素和半纤维素的工艺是可行的。傅里叶变换红外光谱分析表明,该工艺所提取的纤维素和半纤维素组分为预期产物,符合其结构特征。     

对偶Lp 混合质心体的广义B u s e m a n n - P e t t y问题

首先考虑了Rn中凸体K的i-曲率函数fi(K,.)和Lp-曲率函数fp(K,.)的综合推广,引进了Rn中凸体K的Lp-混合曲率函数fp,i(K,.)的概念,然后研究了对偶Lp-混合质心体Γ-p,iKΓ-p,iL是否必定蕴含Wi(K)≤Wi(L)的类似Busemann-Petty问题,获得了一些相应的结果.     

小波变换的木材纹理在线分选

以180幅木材样本图片为对象,研究以小波变换方法提取特征参数,分析几种小波基的特点和性质,最终以对称性为依据,选择使用sym4小波对图像进行二级小波分解,可以得到一级水平细节HL1、垂直细节LH1、对角细节HH1,二级的近似LL2、水平细节HL2、垂直细节LH2、对角细节HH2共7个子图,提取整幅图像的熵和每个子图小波系数的均值及标准差作为特征参数。将木材纹理按照直纹、抛物线和乱纹3种纹理的分类标准,以BP神经网络作为分类器进行了木材纹理分类的验证,并与灰度共生矩阵的方法进行了对比。试验表明:采用小波变换的方法对木材纹理特征进行描述,不但提高了分类的准确率,重要的是缩短了运算时间,可以达到在线监测的要求。     

栽培与野生黄花蒿中化学组分的FTIR表征及青蒿素含量比较分析

本研究运用FTIR技术,对栽培和野生黄花蒿不同部位化学成分的红外光谱特征进行指认,并比较分析两者不同部位青蒿素含量差异。结果显示：酰胺、芳香类物质均以栽培黄花蒿茎和叶片中多;可溶性多糖和糖苷类物质,栽培与野生黄花蒿茎中含量相近,但是,叶片中含量以栽培黄花蒿高;纤维素类物质,栽培茎少于野生茎,而两种黄花蒿叶片的纤维素含量相近。与青蒿素标准品比较,栽培和野生黄花蒿不同部位青蒿素含量有一定差异,其中栽培叶最高,其次是野生叶,栽培茎的含量最低。所以,运用FTIR技术可以快速判断栽培和野生型黄花蒿主要化学成分的差异,本研究对黄花蒿的引种驯化和良种选育工作有一定指导意义。     

A floating threshold quantization algorithm to suppressmixing interferences in partial discharge

Due to the obvious difference of energy distribution frequencies from partial discharge (PD) signal and its mixing interferences (white noise and narrow brand), we uses the characteristic that node decomposition coefficients of wavelet packet transform can effectively show the energy change of signals to build up a floating threshold quantization algorithm (FTQA) varying with the noise energy of PD decomposition coefficients. It makes the node thresholds under the optimal base various with the noise strength in decomposition coefficients to self adaptively reality the choice of optimal threshold to finely partition PD decomposition coefficients. For simulated and real PD signals with mixing interferences, the conditional global threshold quantization algorithm (GTQA) and the proposed floating threshold quantization algorithm are employed to suppress the mixing interferences in PD signals and compared, and the results show that the proposed algorithm has the stronger suppression ability to mixing interference on PD signal and keeps perfect PD waveform via suppression.     

Simulation of nonstationary stochastic earthquake ground motion based on orthogonal Hilbert spectrum

A new method is proposed for the simulation of nonstationary stochastic earthquake ground motion based on orthogonal Hilbert-Huang transform (OHHT) spectra of its sample observations. Orthogonal EMD method is introduced to treat with IMF. OHHT avoids leakage of energy compared with conventional HHT, and it can be used for analysis of nonstationary signal. The average of the Hilbert spectra over the samples is defined as the Hilbert spectrum of the earthquake motion process and used as the target in the simulation of the process. Random Phase is also introduced to simulate nonstationary earthquake. The statistic characteristics function of stochastic process is given in the paper. Simulations of two earthquake ground motion are carried out. The results show that the samples can accurately reflect amplitude and frequency nonstationary of records. Samples and record of same earthquake ground motion process have same statistic characteristics.