椭圆齿轮传动的非零变位方法探索

针对椭圆齿轮传动提出了一种非零变位的方法。在传动比函数保持不变的前提下,使传动中心距略微改变(给定一个相对变动量),则会产生变位的效果。变位后的齿轮节曲线仍然是一对共轭的椭圆,其离心率与变位前椭圆节曲线的离心率相同,而大小的相对变动量等于中心距的相对变动量。变位前后节曲线共轭点处的切线、法线的斜率不变,但二者位置发生变化,因此,造成共轭点产生了切向分离和法向分离。切向分离现象是椭圆齿轮传动所特有的,其分离量应作为生成齿条的切向变位量。法向分离现象则类似于圆形齿轮变位时的中心距变动,成为生成齿条的法向变位量。经齿廓曲线图形仿真证实,这种非零变位能够有效地消除根切现象、增大齿厚,从而提高轮齿的强度。

Radial mixing and segregation of granular bed bi-dispersed both in particle size and density within horizontal rotating drum

Taking simultaneous variations in both particle volume and density into account, the radial mixing and segregation of binary granular bed in a rotating drum half loaded were investigated by a 3D discrete element method. Then, based on the competition theory of condensation and percolation, radial segregation due to differences in particle volume and/or density was analyzed. The results show that if either percolation effect induced by volume difference or condensation effect induced by density difference dominates in the active layer of moving bed, separation will occur. Controlling the volume ratio or density ratio of the two types of particles can achieve an equilibrium state between percolation and condensation, and then homogenous mixture can be obtained. When the percolation balances with the condensation, the relationship between volume ratioand density ratiopresents nearly a power function. Scaling up a rotating drum will not affect the mixing degree of the granular bed so long as the volume ratio and density ratio are predefined.

Soft measurement for component content based on adaptive model of Pr/Nd color features

For measurement of component content in the extraction and separation process of praseodymium/neodymium(Pr/Nd), a soft measurement method was proposed based on modeling of ion color features, which is suitable for fast estimation of component content in production field. Feature analysis on images of the solution is conducted,which are captured from Pr/Nd extraction/separation field. H/S components in the HSI color space are selected as model inputs, so as to establish the least squares support vector machine(LSSVM) model for Nd(Pr) content,while the model parameters are determined with the GA algorithm. To improve the adaptability of the model,the adaptive iteration algorithm is used to correct parameters of the LSSVM model, on the basis of model correction strategy and new sample data. Using the field data collected from rare earth extraction production, predictive methods for component content and comparisons are given. The results indicate that the proposed method presents good adaptability and high prediction precision, so it is applicable to the fast detection of element content in the rare earth extraction.

Brain-Computer Interface Design Using Signal Powers Extracted During Motor Imagery Tasks

Accurate classification of EEG left and right hand motor imagery is an important issue in brain-computer interface. Firstly, discrete wavelet transform method was used to decompose the average power of C3 electrode and C4 electrode in left-right hands imagery movement during some periods of time. The reconstructed signal of approximation coefficient A6 on the 6al level was selected to build up a feature signal. Secondly, the performances by Fisher Linear Discriminant Analysis with two different threshold calculation ways and Support Vector Machine methods were compared. The final classification results showed that false classification rate by Support Vector Machine was lower and gained an ideal classification results.

高三物理复习备考建议——抓住典型问题,突破复习难点

高三学生时间紧、任务重,复习会出现措手不及之感,本文从老师的指导与学生的行为两个方面谈高考备考复习建议。