段家河流域泥石流发育的渗流(Percolation)模型

在观察资料的基础上,提出了泥石流发育的渗流(Percolation)模型。由类比得到泥石流爆发的临界值P_c=d/(Z(d-1)),其中d是欧氏空间维数,z是配位数。根据广义Fibonacci数列,得到临界状态时的分形维数D_t(p,q)=In N/2ln,其中p、q是与人类活动、环境因素有关的参数.用以上结果对段家河流域的泥石流的发生作了理论分析。

Signal de-noising method based on wavelet decomposition

A noise reduction method for infrared detector output signal is studied during dynamic calibration of thermocou- pie. Firstly, the deficiency of the classical filter method is analyzed and the application of the wavelet analysis is introduced for signal de-noising during the dynamic testing. Secondly, the theoretical basis of wavelet analysis, the choice of wavelet base and the determination of decomposed series and threshold are analyzed. Finally, the de-noising experiment for infrared detector signal is carried out on the Matlab platform. The results indicate the proposed wavelet de-noising method is effective to remove fixed frequency and high-frequency noise; furthermore, good synchronization is achieved between the de-noised signal and the useful signal components in the original signal, which is of great significance to thermocouple modeling analys- is.

Percolation on networks with dependence links

As a classical model of statistical physics, the percolation theory provides a powerful approach to analyze the network structure and dynamics. Recently, to model the relations among interacting agents beyond the connection of the networked system, the concept of dependence link is proposed to represent the dependence relationship of agents. These studies suggest that the percolation properties of these networks differ greatly from those of the ordinary networks. In particular, unlike the well known continuous transition on the ordinary networks, the percolation transitions on these networks are discontinuous. Moreover, these networks are more fragile for a broader degree distribution, which is opposite to the famous results for the ordinary networks. In this article, we give a summary of the theoretical approaches to study the percolation process on networks with inter- and inner-dependence links, and review the recent advances in this field, focusing on the topology and robustness of such networks.

Research on the nonlinear spherical percolation model with quadratic pressure gradient and its percolation characteristics

For bottom water reservoir and the reservoir with a thick oil formation, there exists partial penetration completion well and when the well products the oil flow in the porous media takes on spherical percolation. The nonlinear spheri-cal flow equation with the quadratic gradient term is deduced in detail based on the mass conservation principle, and then it is found that the linear percolation is the approximation and simplification of nonlinear percolation. The nonlinear spherical percolation physical and mathematical model under different external boundaries is established, considering the ef-fect of wellbore storage. By variable substitu-tion, the flow equation is linearized, then the Laplace space analytic solution under different external boundaries is obtained and the real space solution is also gotten by use of the nu-merical inversion, so the pressure and the pressure derivative bi-logarithmic nonlinear spherical percolation type curves are drawn up at last. The characteristics of the nonlinear spherical percolation are analyzed, and it is found that the new nonlinear percolation type curves are evidently different from linear per-colation type curves in shape and characteris-tics, the pressure curve and pressure derivative curve of nonlinear percolation deviate from those of linear percolation. The theoretical off-set of the pressure and the pressure derivative between the linear and the nonlinear solution are analyzed, and it is also found that the in-fluence of the quadratic pressure gradient is very distinct, especially for the low permeabil-ity and heavy oil reservoirs. The influence of the non-linear term upon the spreading of pressure is very distinct on the process of percolation, and the nonlinear percolation law stands for the actual oil percolation law in res-ervoir, therefore the research on nonlinear per-colation theory should be strengthened and reinforced.

Applications of Wavelet Analysis in Differential Propagation Phase Shift Data De-noising

Using numerical simulation data of the forward differential propagation shift （ΦDP） of polarimetric radar,the principle and performing steps of noise reduction by wavelet analysis are introduced in detail.Profiting from the multiscale analysis,various types of noises can be identified according to their characteristics in different scales,and suppressed in different resolutions by a penalty threshold strategy through which a fixed threshold value is applied,a default threshold strategy through which the threshold value is determined by the noise intensity,or a ΦDP penalty threshold strategy through which a special value is designed for ΦDP de-noising.Then,a hard-or soft-threshold function,depending on the de-noising purpose,is selected to reconstruct the signal.Combining the three noise suppression strategies and the two signal reconstruction functions,and without loss of generality,two schemes are presented to verify the de-noising effect by dbN wavelets：（1） the penalty threshold strategy with the soft threshold function scheme （PSS）; （2） the ΦDP penalty threshold strategy with the soft threshold function scheme （PPSS）.Furthermore,the wavelet de-noising is compared with the mean,median,Kalman,and finite impulse response （FIR） methods with simulation data and two actual cases.The results suggest that both of the two schemes perform well,especially when ΦDP data are simultaneously polluted by various scales and types of noises.A slight difference is that the PSS method can retain more detail,and the PPSS can smooth the signal more successfully.

Implicit finite difference method for fractional percolation equation with Dirichlet and fractional boundary conditions

An implicit finite difference method is developed for a one-dimensional frac- tional percolation equation （FPE） with the Dirichlet and fractional boundary conditions. The stability and convergence are discussed for two special cases, i.e., a continued seep- age flow with a monotone percolation coefficient and a seepage flow with the fractional Neumann boundary condition. The accuracy and efficiency of the method are checked with two numerical examples.

Percolation Model of Graphite-modified Asphalt Concrete

The addition of graphite powder in conventional asphalt mixture can produced asp halt concrete with excellent electrical performance. Percolation theor y was employed to discuss the relation between the conductivity and graphite con tent of graphite-modified asphalt concrete. It was found that the results of pe rcolation model are consistent with experimental values. The percolation thresho ld of graphite-modified asphalt concrete is 10.94% graphite content account for the total volume of the binder phase consisting of asphalt and graphite. The cr itical exponent is 3.16, beyond the range of 1.6-2.1 for the standard lattice c ontinuous percolation problem. Its reason is that the tunnel conduction mec hanism originates near the critical percent content, which causes this system to be not universal. Tunnel mechanism is demonstrated by the nonlinear voltage-cu rrent characteristic near percolation threshold.The percolation model is able to well predict the formation and development of conductive network in graphite- modified asphalt concrete.

A Novel Method for Preparing Polyurethane Based Conductive Composites with Low Percolation Threshold

A novel method for preparing conductive carbon black fllled polymer composites with low percolation threshold from polyurethane emulsion are reported in this paper. The experimental results indicate that with a rise in carbon black concentration the insulator-conductor transition in the emulsion blended composites occurs at 0.8-1.4vol%. In contrast, the solution blended composites exhibit drastic increase in conductivity at conducting filler fraction as high as 12.3-13.3vol%. It is demonstrated that the composites microstructure rather than chemical structure of the matrix polymer predominantly determines the electrical conduction performance of the composites.

Research on fiber optic gyro signal de-noising based on wavelet packet soft-threshold

Gyro＇s drift is not only the main drift error which influences gyro＇s precision but also the primary factor that affects gyro＇s reliability. Reducing zero drift and random drift is a key problem to the output of a gyro signal. A three-layer de-nosing threshold algorithm is proposed based on the wavelet decomposition to dispose the signal which is collected from a running fiber optic gyro （FOG）. The coefficients are obtained from the three-layer wavelet packet decomposition. By setting the high frequency part which is greater than wavelet packet threshold as zero, then reconstructing the nodes which have been filtered out noise and interruption, the soft threshold function is constructed by the coefficients of the third nodes. Compared wavelet packet de-noise with forced de-noising method, the proposed method is more effective. Simulation results show that the random drift compensation is enhanced by 13.1%, and reduces zero drift by 0.052 6°/h.

Research on percolation model and criticality of seismicity

Making use of modern nonlinear physics theory and earthquake focus theory, combined with seismicity characteristics, the percolation model of earthquake activity is given in this paper. We take the seismogenic process of alarge earthquake as a phase transition process of percolation and apply the renormalization method to phase transition of percolation. The critical property of the system, which is like percolation probability exponential andcorrelative length exponential, etc, can be calculated under the fixed point as which in the renormalization transformation infinite correlative length in percolation phase transition is taken. The percolation phase transition process of two large earthquakes, which are Haicheng and Tangshan event occurred in 1975 and 1976 respectively, hasbeen discussed by means of seismicity data before and after two shocks.

Analysis on nonlinear effect of unsteady percolation in the inhomogeneous shale gas reservoir

The nonlinear effects of unsteady multi-scale shale gas percolation,such as desorption,slippage,diffusion,pressure-dependent viscosity,and compressibility,are investigated by numerical simulation.A new general mathematical model of the problem is built,in which the Gaussian distribution is used to describe the inhomogeneous intrinsic permeability.Based on the Boltzmann transformation,an efficient semi-analytical method is proposed.The problem is then converted into a nonlinear equation in an integral form for the pressure field,and a related explicit iteration scheme is constructed by numerical discretization.The validation examples show that the proposed method has good convergence,and the simulation results also agree well with the results obtained from both numerical and actual data of two vertical fractured test wells in the literature.Desorption,slippage,and diffusion have significant influence on shale gas flows.The accuracy of the usual technique that the product of viscosity and compressibility is approximated as its value at the average formation pressure is examined.

Geotechnical engineering blasting:a new modal aliasing cancellation methodology of vibration signal de-noising

In the present study of peak particle velocity(PPV)and frequency,an improved algorithm(principal empirical mode decomposition,PEMD)based on principal component analysis(PCA)and empirical mode decomposition(EMD)is proposed,with the goal of addressing poor filtering de-noising effects caused by the occurrences of modal aliasing phenomena in EMD blasting vibration signal decomposition processes.Test results showed that frequency of intrinsic mode function(IMF)components decomposed by PEMD gradually decreases and that the main frequency is unique,which eliminates the phenomenon of modal aliasing.In the simulation experiment,the signal-to-noise(SNR)and root mean square errors(RMSE)ratio of the signal de-noised by PEMD are the largest when compared to EMD and ensemble empirical mode decomposition(EEMD).The main frequency of the de-noising signal through PEMD is 75 Hz,which is closest to the frequency of the noiseless simulation signal.In geotechnical engineering blasting experiments,compared to EMD and EEMD,the signal de-noised by PEMD has the lowest level of distortion,and the frequency band is distributed in a range of 0-64 Hz,which is closest to the frequency band of the blasting vibration signal.In addition,the proportion of noise energy was the lowest,at 1.8%.

Continuum percolation of porous media via random packing of overlapping cube-like particles

The pore configuration in porous medium is assumed to be the randomly distributed cube-like particles which can overlap each other in the periodic cubic domain, and the impact of particle characteristics on the percolation property of these cube-like particle packing systems is analyzed.Firstly, by combining the percolation models and finite-size scaling analysis, three numerical parameters(i.e., percolation transition width △L, local percolation threshold ψ_c(L), and correlation length exponent v) for the cube-like particle systems with shape parameter s in[1.0, +∞] are derived successively. Then, based on the relation between the percolation thresholdψ_c in infinite space and the local percolation threshold ψ_c(L), the corresponding ψ_c with s in[1.0, +∞] are further determined. It is shown from the study that the characteristics of cube-like particles have significant influence on the global percolation threshold ψ_c of the particle packing systems. As the parameter s increases from 1.0 to +∞, the percolation threshold ψ_c will go down persistently. When the surface of cube-like particles is cubical and spherical, respectively, the minimum and maximum thresholds ψ_c,min and ψ_c,max are obtained.

Moving horizon based wavelet de-noising method of dual-observed geomagnetic signal for nonlinear high spin projectile roll positioning

Phase-frequency characte ristics of approximate sinusoidal geomagnetic signals can be used fo r projectile roll positioning and other high-precision trajectory correction applications.The sinusoidal geomagnetic signal deforms in the exposed and magnetically contaminated environment.In order to preciously recognize the roll information and effectively separate the noise component from the original geomagnetic sequence,based on the error source analysis,we propose a moving horizon based wavelet de-noising method for the dual-observed geomagnetic signal filtering where the captured rough roll frequency value provides reasonable wavelet decomposition and reconstruction level selection basis for sampled sequence;a moving horizon window guarantees real-time performance and non-cumulative calculation amount.The complete geomagnetic data in full ballistic range and three intercepted paragraphs are used for performance assessment.The positioning performance of the moving horizon wavelet de-noising method is compared with the band-pass filter.The results show that both noise reduction techniques improve the positioning accuracy while the wavelet de-noising method is always better than the band-pass filter.These results suggest that the proposed moving horizon based wavelet de-noising method of the dual-observed geomagnetic signal is more applicable for various launch conditions with better positioning performance.

Fault Diagnosis of Motor in Frequency Domain Signal by Stacked De-noising Auto-encoder

With the rapid development of mechanical equipment,mechanical health monitoring field has entered the era of big data.Deep learning has made a great achievement in the processing of large data of image and speech due to the powerful modeling capabilities,this also brings influence to the mechanical fault diagnosis field.Therefore,according to the characteristics of motor vibration signals(nonstationary and difficult to deal with)and mechanical‘big data’,combined with deep learning,a motor fault diagnosis method based on stacked de-noising auto-encoder is proposed.The frequency domain signals obtained by the Fourier transform are used as input to the network.This method can extract features adaptively and unsupervised,and get rid of the dependence of traditional machine learning methods on human extraction features.A supervised fine tuning of the model is then carried out by backpropagation.The Asynchronous motor in Drivetrain Dynamics Simulator system was taken as the research object,the effectiveness of the proposed method was verified by a large number of data,and research on visualization of network output,the results shown that the SDAE method is more efficient and more intelligent.

Carbon materials with quasi-graphene layers:The dielectric,percolation properties and the electronic transport mechanism

We investigate the dielectric properties of multi-walled carbon nanotubes（MWCNTs） and graphite filling in SiO2 with the filling concentration of 2-20 wt.% in the frequency range of 10 ^2-10^ 7 Hz.MWCNTs and graphite have general electrical properties and percolation phenomena owing to their quasi-structure made up of graphene layers.Both permittivity ε and conductivity σ exhibit jumps around the percolation threshold.Variations of dielectric properties of the composites are in agreement with the percolation theory.All the percolation phenomena are determined by hopping and migrating electrons,which are attributed to the special electronic transport mechanism of the fillers in the composites.However,the twin-percolation phenomenon exists when the concentration of MWCNTs is between 5-10 wt.% and 15-20 wt.% in the MWCNTs/SiO2 composites,while in the graphite/SiO2 composites,there is only one percolation phenomenon in the graphite concentration of 10-15 wt.%.The unique twin-percolation phenomenon of MWCNTs/SiO2 is described and attributed to the electronic transfer mechanism,especially the network effect of MWCNTs in the composites.The network formation plays an essential role in determining the second percolation threshold of MWCNTs/SiO2.

Research on Percolation Network and Physical Properties of Graphite/Antimony Composites

The microstructure, friction and wear behaviour of graphite preform and graphite/antimony composites are analysed based on the percolation theory of hydrodynamics to investigate the relationship between the percolation net- work and physical properties of graphite/antimony composites. The result shows that there are two important factors to enhance friction and wear behaviour of graphite/antimony composites at high temperature: 1) the formation of the pore network in the preform, which is called the first percolation and 2) the optimization of infiltration method in the process of infiltrating antimony, which is called the second percolation. By adding some pyrolysate and controlling the roasting process, perfect net pores and sub-micron percolation microstructure may be formed in the graphite preform. By con- trolling the infiltration process, the saturation of molten antimony infiltrating into perfect pores can be optimized.

Application of RLS adaptive filteringin signal de-noising

In view of the problem that noises are prone to be mixed in the signals,an adaptive signal de-noising system based on reursive least squares （RLS） algorithm is introduced.The principle of adaptive filtering and the process flow of RLS algorithm are described.Through example simulation,simulation figures of the adaptive de-noising system are obtained.By analysis and comparison,it can be proved that RLS adaptive filtering is capable of eliminating the noises and obtaining useful signals in a relatively good manner.Therefore,the validity of this method and the rationality of this system are demonstrated.

Percolation analysis of large-scale wireless balloon networks

Recent advancements in wireless technology have tested Wireless Balloon Networks (WBNs) as an ideal solution for the provision of internet facilities in deprived and challenging areas. A few high profile companies, such as Google, Space Data Inc., etc., have already made news by initiating projects based on high-altitude WBNs in order to provide internet facilities in remote areas. Unfortunately, the technical details have mainly been kept confidential so far. In this paper, we attempt to analyze the percolation properties of large-scale WBNs, considering both homogenous and heterogenous wireless nodes. In order to do so, we modeled a WBN as a large-scale random network where the path-loss models of homogenous and heterogenous WBNs were reduced to GDM (Gilbert's Disk Model) and RGDM (Random Gilbert's Disk Model), respectively. The bounds of the critical density regime were derived for both percolation models. Additionally, this paper implemented an experimental test bed for the WBN percolation model. Consequently, the findings of this research may prove crucial in estimating critical network properties.

Technology of signal de-noising and singularity elimination based on wavelet transform

Based on wavelet transform theory,a method for signal de-noising and singularity detection and elimination is proposed,which can reduce the noises and express local singularity.Each singularity can also be detected and located through the local modulus maxima of wavelet transform.Simulation experiments are conducted with MATLAB software.The experimental results demonstrate that the method proposed in this paper is effective and feasible.