Application of the blind source separation method to feature extraction of machine sound signals

As the result of vibration emission in air, a machine sound signal carries important information about the working condition of machinery. But in practice, the sound signal is typically received with a very low signal-to-noise ratio. To obtain features of the original sound signal, uncorrelated sound signals must be removed and the wavelet coefficients related to fault condition must be retrieved. In this paper, the blind source separation technique is used to recover the wavelet coefficients of a monitored source from complex observed signals. Since in the proposed blind source separation (BSS) algorithms it is generally assumed that the number of sources is known, the Gerschgorin disk estimator method is introduced to determine the number of sound sources before applying the BSS method. This method can estimate the number of sound sources under non-Gaussian and non-white noise conditions. Then, the partial singular value analysis method is used to select these significant observations for BSS analysis. This method ensures that signals are separated with the smallest distortion. Afterwards, the time-frequency separation algorithm, converted to a suitable BSS algorithm for the separation of a non-stationary signal, is introduced. The transfer channel between observations and sources and the wavelet coefficients of the source signals can be blindly identified via this algorithm. The reconstructed wavelet coefficients can be used for diagnosis. Finally, the separation results obtained from the observed signals recorded in a semi-anechoic chamber demonstrate the effectiveness of the presented methods .     

A parametric interpolator with confined chord errors, acceleration and deceleration for NC machining

Parametric interpolation has many advantages over linear interpolation in machining curves. Real time parametric interpolation research so far has addressed achieving a uniform feed rate, confined chord errors and jerk limited trajectory planning. However, simultaneous consideration of confined chord errors that respect the acceleration and deceleration capabilities of the machine has not been attempted. In this paper, the offline detection of feed rate sensitive corners is proposed. The velocity profile in these zones is planned so that chord errors are satisfied while simultaneously accommodating the machine's acceleration and deceleration limits. Outside the zone of the feed rate sensitive corners, the feed rate is planned using the Taylor approximation. Simulation results indicate that the offline detection of feed rate sensitive corners improves parametric interpolation. For real time interpolation, the parametric curve information can be augmented with the detected feed rate sensitive corners that are stored in 2×2 matrices.     

The effect of support morphology on the reaction of oxidative dehydrogenation of ethane to ethylene at short contact times

The oxidative dehydrogenation of ethane is carried out in short contact time reactors over Pt and LaMnO₃ based catalysts supported on a large number of different ceramic substrates (45, 60 and 80 ppi foam monoliths and 200, 400, 600, 900 and 1200 cpsi honeycomb monoliths). Experimental results, obtained under the same conditions at varying the C₂H₆/O₂ ratio, showed that the highest performance in terms of ethylene selectivity and yield is always attained on LaMnO₃ catalysts. Furthermore, the results are significantly influenced by the morphology and cell density of the support, with 45 and 60 ppi foams and 400 and 600 cpsi honeycombs giving the best performance. The experimental results are explained by means of geometrical and fluid dynamic considerations on the support, and by means of a 2D mathematical model, which clearly indicates an optimal intermediate cell density for maximising ethylene selectivity and yield.     

On the number of broadcast schemes in networks

Broadcasting is the process of spreading one piece of information among a group of individuals connected by an interconnection network. In this paper we give exact lower and upper bounds for the number of broadcast schemes in arbitrary networks. Also, we give the exact value for complete bipartite graphs and an upper bound for regular networks. Based on the counting method we describe a new random algorithm for broadcasting in networks.     

Composite group vector space method for estimating melting and boiling point of pure organic compound

Composition Group Vector Space (CGVS) method for estimating melting and boiling point T _m , T _b of organic compound has been proposed, and the principle of this method has been elucidated. The models for estimating T _m , T _b have been established and the numerical values of relative parameters have been presented. The average percentage deviations of T _m , T _b estimation are 7.53 and 1.58, respectively, which show that the present method demonstrates significant improvement in applicability to predict the above properties, compared to conventional group methods.     

面向对象机器翻译知识库IMT—KB的设计与实现

机器翻译知识库是机译系统的重要组成部分,针对传统机译知识库的不足之处,本文提出一种面向对象的机译知识体系结构,同时给出这种具有层次性和模块性机译知识库的存储组织和管理机制。     

反转矢量透射反馈求解光电混合全加器

提出了利用反转矢量透射反馈算法研制偏振编码光电混合全加器，该加法器可以实现两输入的光学算术运算，研制成的各单元器件可用于其它各种光计算机系统中。     

Efficient prolog programming

This paper presents some basic programming strategies for Prolog programmers. The strategies are based on knowledge about the operational behaviour of the Warren Abstract Machine (WAM). The aim is to provide simple principles for making programs both faster and less space-consuming. The programming hints given are mostly local, i.e. only a single clause or procedure need be considered at a time.     

Estimating areal means and variances of forest attributes using the k-Nearest Neighbors technique and satellite imagery

The k-Nearest Neighbor (k-NN) technique has become extremely popular for a variety of forest inventory mapping and estimation applications. Much of this popularity may be attributed to the non-parametric, multivariate features of the technique, its intuitiveness, and its ease of use. When used with satellite imagery and forest inventory plot data, the technique has been shown to produce useful estimates of many forest attributes including forest/non-forest, volume, and basal area. However, variance estimators for quantifying the uncertainty of means or sums of k-NN pixel-level predictions for areas of interest (AOI) consisting of multiple pixels have not been reported. The primary objectives of the study were to derive variance estimators for AOI estimates obtained from k-NN predictions and to compare precision estimates resulting from different approaches to k-NN prediction and different interpretations of those predictions. The approaches were illustrated by estimating proportion forest area, tree volume per unit area, tree basal area per unit area, and tree density per unit area for 10-km AOIs. Estimates obtained using k-NN approaches and traditional inventory approaches were compared and found to be similar. Further, variance estimates based on different interpretations of k-NN predictions were similar. The results facilitate small area estimation and simultaneous and consistent mapping and estimation of multiple forest attributes.