Improved finite difference method for pressure distribution of aerostatic bearing

An improved finite difference method （FDM）is described to solve existing problems such as low efficiency and poor convergence performance in the traditional method adopted to derive the pressure distribution of aerostatic bearings. A detailed theoretical analysis of the pressure distribution of the orifice-compensated aerostatic journal bearing is presented. The nonlinear dimensionless Reynolds equation of the aerostatic journal bearing is solved by the finite difference method. Based on the principle of flow equilibrium, a new iterative algorithm named the variable step size successive approximation method is presented to adjust the pressure at the orifice in the iterative process and enhance the efficiency and convergence performance of the algorithm. A general program is developed to analyze the pressure distribution of the aerostatic journal bearing by Matlab tool. The results show that the improved finite difference method is highly effective, reliable, stable, and convergent. Even when very thin gas film thicknesses （less than 2 Win）are considered, the improved calculation method still yields a result and converges fast.

Identifying influential nodes in social networks via community structure and influence distribution difference

This paper aims to effectively solve the problem of the influence maximization in social networks.For this purpose,an influence maximization method that can identify influential nodes via the community structure and the influence distribution difference is proposed.Firstly,the network embedding-based community detection approach is developed,by which the social network is divided into several high-quality communities.Secondly,the solution of influence maximization is composed of the candidate stage and the greedy stage.The candidate stage is to select candidate nodes from the interior and the boundary of each community using a heuristic algorithm,and the greedy stage is to determine seed nodes with the largest marginal influence increment from the candidate set through the sub-modular property-based Greedy algorithm.Finally,experimental results demonstrate the superiority of the proposed method compared with existing methods,from which one can further find that our work can achieve a good tradeoff between the influence spread and the running time.

Fiber Migration and Distribution of Twist at Different Radial Positions of Rotor Yarn-by Hi-Scope Video Microscope System

This paper describes systematic measurement of fiber migration and distribution pattern of twist at different radial positions of rotor spun yarn mixed tracer fiber by Hi-Scope Video Microscope System. The positions of tracer fibers were measured in three dimensions accurately, and the migration index and the twist distribution at different radial positions of rotor yarn were calculated and analyzed. This research result serves to provide useful references for further study on the structural mechanics of rotor spun yarn.

基于WVD/ATDM的铝合金板孔损伤位置与区域识别

为识别铝合金板孔损伤位置及区域,以Lamb波为研究基础,提出基于魏格纳-威利分布(WVD,WignerVille distribution)和到达时间差值法(ATDM,arrival time difference method)的损伤识别技术。首先,采集实验铝合金板健康和有损模型的Lamb信号,对其差值信号进行WVD分析,准确提取损伤反射信号到达时间;其次,通过ATDM建立各传感器间的距离差值关系,确定孔损伤位置中心并预测最大损伤半径,从而实现对孔损伤关键指标的识别;最后,通过数值模拟进一步验证该方法,结果表明,基于WVD/ATDM的损伤识别技术不仅能准确识别出孔损伤位置,而且能够有效地识别损伤区域面积。

Application of Transfer Learningin Mechanical Equipment Intelligent Diagnosis:Literature Review

Accelerating the process of intelligent manufacturing and the demand for new industrial productivity,the operating conditions of machinery and equipment have become ever more severe.As an important link to ensure the stable operation of the production process,the condition monitoring and fault diagnosis of equipment have become equally important.The fault diagnosis of equipment in actual production is often challenged by variable working conditions,large differences in data distribution,and lack of labeled samples,etc.Traditional fault diagnosis methods are often difficult to achieve ideal results in these complex environments.Transfer learning(TL)as an emerging technology can effectively utilize existing knowledge and data to improve the diagnostic performance.Firstly,this paper analyzes the trend of mechanical equipment fault diagnosis and explains the basic concept of TL.Then TL based on parameters,TL based on features,TL based on instances and domain adaptive(DA)methods are summarized and analyzed in terms of existing TL methods.Finally,the problems faced in the current TL research are summarized and the future development trend is pointed out.This review aims to help researchers in related fields understand the latest progress of TL and promote the application and development of TL in mechanical equipment diagnosis.

IMPACT OF UPLIFT OF TIBETAN PLATEAU AND CHANGE OF LAND-OCEAN DISTRIBUTION ON CLIMATE OVER ASIA

Using an improved CCM1/NCAR climate dynamic model and a combination distribution of land-ocean-vegetation during 40-50 MaBP,a series of numerical experiments representing different stages of the Tibetan Plateau uplifting and different land-ocean distributions are designed to discuss the influence of the Plateau uplifting and land-ocean distribution variation on Asian climate change.It is shown that Tibetan Plateau uplifting can firstly increase the precipitation in China during the period from initial uplift to half height of modern Tibetan Plateau and then decrease the rainfall during the time from the half height to the present plateau.At the same time. the uplifting can reduce surface air temperature over China.Besides.the effects of the uplift and land-ocean distribution change on the variation of winter and summer Asian monsoon circulation are also discussed.

High accuracy in automatic detection of atrial fibrillation for Holter monitoring

Atrial fibrillation(AF) has been considered as a growing epidemiological problem in the world,with a substantial impact on morbidity and mortality.Ambulatory electrocardiography(e.g.,Holter) monitoring is commonly used for AF diagnosis and therapy and the automated detection of AF is of great significance due to the vast amount of information provided.This study presents a combined method to achieve high accuracy in AF detection.Firstly,we detected the suspected transitions between AF and sinus rhythm using the delta RR interval distribution difference curve,which were then classified by a combination analysis of P wave and RR interval.The MIT-BIH AF database was used for algorithm validation and a high sensitivity and a high specificity(98.2% and 97.5%,respectively) were achieved.Further,we developed a dataset of 24-h paroxysmal AF Holter recordings(n=45) to evaluate the performance in clinical practice,which yielded satisfactory accuracy(sensitivity=96.3%,specificity=96.8%).

Changes of Precipitation Intensity Spectra in Different Regions of China's Mainland During 1961-2006

The spectral characteristics of precipitation intensity during warm and cold years are compared in six regions of China based on precipitation data at 404 meteorological stations during 1961-2006.In all of the studied regions except North China,with the increasing temperature,a decreasing trend is observed in light precipitation and the number of light precipitation days,while an increasing trend appears in heavy precipitation and the heavy precipitation days.Although changes in precipitation days in North China are similar to the changes in the other five regions,heavy precipitation decreases with the increasing temperature in this region.These results indicate that in most parts of China,the amount of precipitation and number of precipitation days have shifted towards heavy precipitation under the background of a warming climate;however,the responses of precipitation distributions to global warming differ from place to place.The number of light precipitation days decreases in the warm and humid regions of China（Jianghuai region,South China,and Southwest China）,while the increasing amplitude of heavy precipitation and the number of heavy precipitation days are greater in the warm and humid regions of China than that in the northern regions（North China,Northwest China,and Northeast China）.In addition,changes are much more obvious in winter than in summer,indicating that the changes in the precipitation frequency are more affected by the increasing temperature during winter than summer.The shape and scale parameters of the Γ distribution of daily precipitation at most stations of China have increased under the background of global warming.The scale parameter changes are smaller than the shape parameter changes in all regions except Northwest China.This suggests that daily precipitation shifts toward heavy precipitation in China under the warming climate.The number of extreme precipitation events increases slightly,indicating that changes in the Γ distribution fitting parameters reflect changes in the regional precipitation distribution structure.

Steganalysis of stochastic modulation steganography

Stochastic modulation steganography embeds secret message within the cover image by adding stego-noise with a specific probabilistic distribution. No method is known to be applicable to the estimation of stochastic modulation steganography. By analyzing the distributions of the horizontal pixel difference of images before and after stochastic modulation embedding, we present a new steganalytic approach to accurately estimate the length of secret message in stochastic modulation steganography. The pro- posed method first establishes a model describing the statistical relationship among the differences of the cover image, stego-image and stego-noise. In the case of stegoimage-only steganalysis, rough estimate of the distributional parameters of the cover image＇s pixel difference is obtained with the use of the provided stego-image. And grid search and Chi-square goodness of fit test are exploited to estimate the length of the secret message embedded with stochastic modulation steganography. The experimental results demonstrate that our new approach is effective for steganalyzing stochastic modulation steganography and accurately estimating the length of the secret message.