波导小衰减分析及测量的一种简易方法

推导了矩形波导主模传输小衰减最小时,频率和波导尺寸及截止波长的关系;研究了波导小衰减变化的规律性;提出了利用两个相同的标准冷负载和一个标准精密可变波导衰减器,通过测量Y因子与标准衰减L_a的定标曲线,从而确定波导小衰减的一种简易方法;给出了测量实例,实测值同理论值吻合很好。

去嵌入法测量小衰减器件有效效率误差分析

首先分析了网络分析仪测量误差的来源和类别,然后定义了用以表征小衰减器件衰减量的有效效率的概念,为了准确得到小衰减器件有效效率测量值,利用网络分析仪的去嵌入选件,将被测小衰减器件当做一个插入直通适配器的误差项,通过两次简单的直通校准和一次简单计算实现双端口、小衰减器件有效效率的快速测量,在此基础上,进一步提出了该方法的误差分析模型,通过对模型的误差分析推导出误差表达式以及修正方法。本文提出的小衰减器件有效值测量及误差修正方法简单方便,对进一步提高该类器件测量精度和测量效率具有很好的借鉴意义。

Ground roll wave suppression based on wavelet frequency division and radial trace transform

Ground roll waves interfere with seismic data. The suppression of ground roll waves based on the division of wavelet frequencies considers the low-frequency characteristics of ground roll waves. However, this method will not be effective when the ground roll wave and the effective signal have the same frequency bands because of overlapping. The radial trace transform （RTT） considers the apparent velocity difference between the effective signal and the ground roll wave to suppress the latter, but affects the low-frequency components of the former. This study proposes a ground roll wave suppression method by combining the wavelet frequency division and the RTT based on the difference between the ground roll wave velocity and the effective signal and their energy difference in the wavelet domain, thus making full use of the advantages of both methods. First, we decompose the seismic data into different frequency bands through wavelet transform. Second, the RTT and low-cut filtering are applied to the low-frequency band, where the ground roll waves are appearing. Third, we reconstruct the seismic record without ground roll waves by using the inverse RTT and the remaining frequency bands. The proposed method not only improves the ground roll wave suppression, but also protects the signal integrity. The numerical simulation and real seismic data processing results suggest that the proposed method has a strong ability to denoise while preserving the amplitude.

River channel flood forecasting method of coupling wavelet neural network with autoregressive model

Based on analyzing the limitations of the commonly used back-propagation neural network （BPNN）, a wavelet neural network （WNN） is adopted as the nonlinear river channel flood forecasting method replacing the BPNN. The WNN has the characteristics of fast convergence and improved capability of nonlinear approximation. For the purpose of adapting the timevarying characteristics of flood routing, the WNN is coupled with an AR real-time correction model. The AR model is utilized to calculate the forecast error. The coefficients of the AR real-time correction model are dynamically updated by an adaptive fading factor recursive least square（RLS） method. The application of the flood forecasting method in the cross section of Xijiang River at Gaoyao shows its effectiveness.

Amplitude phase control for electro-hydraulic servo system based on normalized least-mean-square adaptive filtering algorithm

The electro-hydraulic servo system was studied to cancel the amplitude attenuation and phase delay of its sinusoidal response,by developing a network using normalized least-mean-square (LMS) adaptive filtering algorithm.The command input was corrected by weights to generate the desired input for the algorithm,and the feedback was brought into the feedback correction,whose output was the weighted feedback.The weights of the normalized LMS adaptive filtering algorithm were updated on-line according to the estimation error between the desired input and the weighted feedback.Thus,the updated weights were copied to the input correction.The estimation error was forced to zero by the normalized LMS adaptive filtering algorithm such that the weighted feedback was equal to the desired input,making the feedback track the command.The above concept was used as a basis for the development of amplitude phase control.The method has good real-time performance without estimating the system model.The simulation and experiment results show that the proposed amplitude phase control can efficiently cancel the amplitude attenuation and phase delay with high precision.

Periodical attenuation of Al(OH)_3 particles from seed precipitation in seeded sodium aluminate solution

Periodical attenuation of particles,which interferes seriously the normal alumina production,exists in Bayer process.In order to solve this problem,the rule of periodical attenuation of Al(OH) 3 particles was investigated by laboratory experiments under simulated industrial conditions.The results show that at higher temperature the variation period of particle size is shortened,while prolongs with more solid content.Particle size fluctuation amplitude reduces with the temperature rising but increases with the solid content increasing.Particle size distribution becomes more uniform by replenishing fine seeds,enabling the periodical fluctuation of Al(OH)3 particle size to be attenuated.Combining properly the additives with controlling the seed size is able to reduce the amplitude of periodical fluctuation and shorten the attenuation time.With unbalance of particle size distribution,the particles gradually become bigger,even inducing the decrease of the specific surface area of seeds,which is the major reason causing explosive attenuation of Al(OH)3 particles in seed precipitation process.

Multiple subtraction method based on a non-causal matching filter

The filter operator used in normal multichannel matching filter is physically realizable. This filter operator only delays seismic data in the filtering process. A non- causal multichannel matching filter based on a least squares criterion is proposed to resolve the problem in which predicted multiple model data is later than real data. The differences between causal and non-causal multichannel matching filters are compared using a synthetic shot gather, which demonstrates the validity of the non-causal matching filter. In addition, a variable length sliding window which changes with offset and layer velocity is proposed to solve the count of events increasing with increasing offset in a fixed length sliding window. This variable length sliding window is also introduced into the modified and expanded multichannel matching filter. This method is applied to the Pluto1.5 synthetic data set. The benefits of the non-causal filter operator and variable length sliding window are demonstrated by the good multiple attenuation result.

B→ X8γ, X8l＋l- Decays and Constraints on Mass Insertion Parameters in MSSM

In this paper, we study the upper bounds on the mass insertion parameters （δAB^q）ij in the minimal super symmetric standard model. We found that the information from the measured branching ratio of B→ X8γ, X8l＋l- decay can help us to improve the upper bounds on the mass insertions parameters （δAB^u,d）3j,i3 Some regions allowed by the data of Br（B→ X8γ） are excluded by the requirement of an SM-like C7γ （rnb） imposedby the data of Br（B→ X8γ, X8l＋l- ）.

Seislet transform denoising based on total variation minimization

Attenuation of noise is a persistent problem in seismic exploration. The authors use conventional denoising method to remove noise which may cause vibration near the discontinuity called pseudo-Gibbs artifact.In order to remove the artifact,the study proposed a method combining the seislet transform and total variation minimization. Firstly,the data are converted into the seislet transform domain. Secondly,the hard threshold was used for eliminating the noise and keep useful signal,which is the initial input for the next step. Finally,total variation minimization dealed with denoised data to recover boundary information and further eliminated the noise. Synthetic data examples show that the method has feasibility in eliminating random noise and protecting detailed signal,and also shows better results than the classic f-x deconvolution. The field data example also shows effective in practice. It can remove the noise and preserve the discontinuity signal at the same time.