一种可替代漂珠的低密度材料

漂珠低密度水泥浆由于密度低、强度高、体系稳定而在油田低压易漏层及低压油气层长封固段固井作业中获得了广泛的应用。但近年来,由于漂珠的产量越来越少,油田低成本要求急需开发代替漂珠的新型减轻材料,以满足配制低密度水泥浆的需求。开发了BCL-10S低密度混合减轻材料,其物化性能与漂珠相当,用它作减轻剂配制的低密度水泥浆性能与用漂珠作减轻剂配制的低密度水泥浆性能相媲美,并已经在长庆油田获得了应用。     

人工颅骨用复合材料中微量甲基丙烯酸甲酯的气相色谱法测定

采用氢气焰离子化检测器(FID),以正丁醇为外标物,PEG-20M为固定相,甲醇作为溶剂,气相色谱法测定复合材料人工颅骨中微量MMA的含量。其相对标准偏差<0.022,平均回收率(n=4)为98.0％～99.1％。此方法操作简便,用于实际样品分析可得到满意的结果。     

人工神经网络预测煤的发热量

应用人工神经网络处理部分广东地区煤质分析数据,建立网络模型,预测出煤的发热量,经实测值与预测值比较,在一定的煤种范围内预测值与实测值比较接近。     

人工智能的原理及应用

介绍了人工智能的发展，并对改进的神经网络专家系统的优越性做了介绍，指出了神经网络专家系统广阔的应用前景及实现。     

人工神经网络理论及其应用

简要介绍了人工神经网络的发展过程和基本理论，从神经网络具有自学习功能、联想存储功能和高速寻找优化解的能力三个方面论述了其特点和优越性，详细阐述了在模式识别、信号处理、自动控制、人工智能、自适应的人机接口、优化计算、通信以及其它方面的应用，探讨和分析了其发展前景。     

半合成发动机油基础油调配的仿真研究

采用矿物油、聚α-烯烃、多元醇酯和高压加氢BS光亮油调配半合成发动机油基础油,并测定不同配比下基础油的油膜强度、摩擦系数和粘度指数,通过双隐层BP神经网络对基础油调配进行仿真研究,建立了半合成发动机油基础油调配配方优化模型,经过优化训练后,最终得出综合性能优良的配方组合。按49.9957∶4.3693∶42.4578∶3.1772的配比调配基础油,可以使基础油的油膜强度、摩擦系数和粘度指数分别达到56 kg,0.065和112,经实验后仿真结果与实验结果(56 kg;0.065598;112)极其吻合。     

Range of the Applicability of the Wilkins Method to the Investigation of the Dynamic Stress-Strain State of Anisotropic Elastic Axisymmetric Shells

The exactness and stability of the Wilkins method in the investigation of the stress-strain state of axisymmetric anisotropic elastic shells, including thick-walled ones, have been studied for different values of artificial viscosity, pulse load rise and fall time, and different deformation process durations. A comparison of numerical calculations, performed by means of an application software package developed by V. A. Romashchenko on the basis of the Wilkins method, with experimental results, known numerical data, and with calculations using the computation kernel LS-DYNA 3D has been carried out.     

Boole函数的线性可分性(Ⅰ)——n-维超立方体的基本理论

Boole函数的线性可分性是前向人工神经网络理论中的一个比较困难的问题之一。目前仅对变量数n≤7的某些问题给予讨论。当n≥8时,尚无判别Boole函数线性可分的一般准则,更无线性可分Boole函数的计数公式。基于此,本文详细地研究了与Boole函数线性可分性有关的n-维超立方体的基本理论,包括n-维超立方体的基本性质、超立方体中的平行线、子超立方体的计数等,并给出了构造n-维超立方体图的一种新方法。     

人工关节试验机电液力伺服控制系统迭代学习控制策略仿真

本文首先介绍了人工关节试验机电液力伺服控制系统的构成，并分析了其静特性。针对力系统的特性，本文提出了一种闭环比例型一阶给定超前迭代学习控制算法，并对其控制效果进行了仿真研究。研究结果表明，采用迭代学习控制算法可以有效地提高力系统的跟随精度。     

Effects of modeling means on properties of monitoring models of spot welding quality

Analyzing and modeling the relation between monitoring information during welding and quality information of the joints is the foundation of monitoring resistance spot welding quality. According to the means of modeling, the known models can be divided into three large categories: single linear regression models, multiple linear regression models and multiple non-linear models. By modeling the relations between dynamic resistance information and welding quality parameters with different means, this paper analyzes effects of modeling means on performances of monitoring models of resistance spot welding quality. From the test results, the following conclusions can be drawn: By comparison with two other kinds of models, artificial neural network (ANN) model can describe non-linear and high coupling relationship between monitoring information and quality information more reasonably, improve performance of monitoring model remarkably, and make the estimated values of welding quality parameters more accurate and reliable.