Partial oxidation of ethane by in situ generated H2O2

Selective partial oxidation of ethane to ethanol and acetaldehyde by in situ generated H₂O₂ has been achieved under cathodic current passing through a carbon supported Nafion-H catalytic membrane. A correlation between H₂O₂ generation rate and reaction rate has been found.     

旋转变压器信号的标定与解调

针对检波后信号存在直流偏置、幅值不等和相位偏移等问题,采用梯度估计算法,对检波后的包络信号进行离线标定;并设计了基于状态观测器的旋转变压器-数字转换(RDC)算法,对标定后的包络信号进行解调.试验结果表明,梯度估计算法收敛速度快,估计精度高.与反正切法相比,所设计的RDC算法不需通过数值差分即可获得角速度信息,干扰抑制能力强,角位置和角速度估计精度高.     

Maximum quasi-likelihood estimation for the near(2) model

Abstract.  Maximum quasi-likelihood estimation is investigated for the NEAR(2) model, an autoregressive time series model with marginal exponential distributions. In certain regions of the parameter space, simulations indicate that maximum quasi-likelihood estimators perform better than two-stage conditional least squares estimators in terms of the per cent of estimates falling in the parameter space. The problem of out-of-range estimates is shown to be caused by the lack of information in the data rather than the characteristics of the method of estimation.     

基于LS-SVM逆系统的无轴承异步电机解耦控制

无轴承异步电机具有非线性、多变量和强耦合的特点,要实现电机稳定悬浮和旋转运行,必须对其进行非线性动态解耦控制。为了克服逆系统方法精确建模难的局限性,采用基于最小二乘支持向量机(LS-SVM)α阶逆系统方法对无轴承异步电机进行动态解耦控制的研究。首先利用最小二乘支持向量机辨识出无轴承异步电机的逆模型,然后将它串联在原系统前,将无轴承异步电机解耦成四个独立的伪线性子系统-2个径向位移子系统、一个速度子系统和一个磁链子系统。为保证鲁棒性能,最后对解耦后的系统采用非线性内模控制策略。研究表明,LS-SVMα阶逆系统方法能够实现无轴承异步电机径向悬浮力和旋转力之间的动态解耦控制,控制系统具有良好的静态和动态性能。     

基于参数估计的半挂汽车列车稳定性控制研究

车辆参数估计是半挂汽车列车稳定性控制研究的关键,通过递推最小二乘法（RLS）估计整车质量和轮胎侧偏刚度,进而获取挂车横摆转动惯量,将估计的车辆参数应用于稳定性控制系统,修正控制系统参数.基于商用车动力学仿真软件TruckSim建立了某半挂汽车列车的非线性整车仿真模型,在Matlab/Simulink中设计建立了稳定性控制逻辑和参考响应模型,通过TruckSim-Simulink的联合仿真对控制方案进行了验证分析.结果表明,基于名义参数设计的控制系统受载重变化的影响较大,而带有参数估计的控制系统由于能够对控制参数进行修正,可以较好地适应载运工况的变化,受载运工况的影响较小.     

基于PSO-LSSVM的网络流量预测模型

为了提高网络流量的预测精度,考虑到网络流量的长相关、非线性等特性,提出一种粒子群算法优化最小二乘支持向量机参数的网络流量预测模型（PSO-LSSVM）．首先将最小二乘支持向量机参数作为粒子的位置向量,然后利用粒子群算法找到模型的最优参数,最后采用最优参数最小二乘支持向量机建立网络流量预测模型．仿真结果表明,相对于参比模型,PSO-LSSVM能够获得更高的网络流量预测精度,更能准确描述网络流量变化规律．     

基于P系统的粒子群优化算法

为了克服算法早熟收敛问题并提高算法精度, 引入了膜计算理论。将PSO算法与P系统相结合, 提出了一种基于P系统的粒子群优化算法 (P-PSO), 有效地平衡粒子群的全局搜索和局部寻优。采用常用的三个测试函数对新算法进行了实验, 结果表明, 提出的P-PSO算法有效地解决了算法早熟问题, 提高了算法的收敛精度。由此可见, P-PSO算法能够有效改进原有PSO算法的性能。     

Direct partial oxidation of methane over ZSM-5 catalyst: effects of additives

Previously, it was reported that the direct partial oxidation (DPO) of CH₄ with O₂ over HZSM-5 catalysts produces C₅₊ hydrocarbon liquids when the feed contains a propane or propene additive. This work studies additive effects on C₅₊ production in this system by processing a CH₄/C₃H₈ feed with subsequent removal of the C₃ additive and by processing natural gas feed. Results show C₅₊ production is maintained at constant yields for HZSM-5 catalysts having different zeolitic Al contents after removal of the C₃ additive. Mechanistic implications are discussed. Natural gas DPO consistently produced C₅₊ liquids due to the presence of C₂₊ components in the feed. While C₅₊ yields from natural gas DPO are higher than those observed for CH₄/C₃ feeds, increasing feed O₂ concentration, and thus conversion, deleteriously affected C₅₊ selectivity.     

局部表面改性紫铜方柱阵列池沸腾传热特性和机理

以局部表面改性的紫铜直方柱和梯度方柱阵列为研究对象，实验研究了表面润湿性、表面形貌和表面活性剂对池沸腾换热性能和气泡生长特性的影响。实验工质为去离子水，浓度分别为100、200、400、800 mg·L^-1的异丙醇溶液和正庚醇溶液。实验结果表明：方柱阵列表面镀银之后润湿性变差，表面产生的气泡数量减少。向去离子水中添加异丙醇或正庚醇后，在热通量为66.1～202 kW·m^-2时，气泡脱离直径变小、数目减少，而当热通量增至413 kW·m^-2时，活性剂能够有效阻碍气泡合并，故池沸腾传热系数随着浓度增加先减小后增大。上下层宽分别0.5 mm和1 mm、间距为2 mm的梯度方柱阵列结构有助于气泡的合并，但由于促进了固体表面气膜的形成，从而降低了沸腾换热性能。     

Measurement of soybean fatty acids by near-infrared spectroscopy: Linear and nonlinear calibration methods

A key element of successful development of new soybean cultivars is availability of inexpensive and rapid methods for measurement of FA in seeds. Published research demonstrated applicability of NIR spectroscopy for FA profiling in oilseeds. The objectives of this study were to investigate the applicability of NIR spectroscopy for measurement of FA in whole soybeans and compare performance of calibration methods. Equations were developed using partial least squares (PLS), artificial neural networks (ANN), and support vector machines (SVM) regression methods. Validation results demonstrated that (i) equations for total saturates had the highest predictive ability (r ²=0.91–0.94) and were usable for quality assurance applications, (ii) palmitic acid models (r ²=0.80–0.84) were usable for certain research applications, and (iii) equations for stearic (r ²=0.49–0.68), oleic (r ²=0.76–0.81), linoleic (r ²=0.73–0.76), and linolenic (r ²=0.67–0.74) acids could be used for sample screening. The SVM models produced significantly more accurate predictions than those developed with PLS. ANN calibrations were not different from the other two methods. Reduction in the number of calibration samples reduced predictive ability of all equations. The rate of performance degradation of SVM models with sample reduction was the lowest.