Low temperature delamination of plastic encapsulated microcircuits

Plastic encapsulated microcircuits (PEMs) are increasingly being used in applications requiring operation at temperatures lower than the manufacturer’s recommended minimum temperature, which is 0°C for commercial grade components and −40°C for industrial and automotive grade components. To characterize the susceptibility of PEMs to delamination at these extreme low temperatures, packages with different geometries, encapsulated in both biphenyl and novolac molding compounds, were subjected to up to 500 thermal cycles with minimum temperatures in the range −40 to −65°C in both the moisture saturated and baked conditions. Scanning acoustic microscopy revealed there was a negligible increase in delamination at the die-to-encapsulant interface after thermal cycling for the 84 lead PQFPs encapsulated in novolac and for both 84 lead PQFPs and 14 lead PDIPs encapsulated in biphenyl molding compound. Only the 14 lead novolac PDIPs exhibited increased delamination. Moisture exposure had a significant effect on the creation of additional delamination.     

数字散斑干涉技术及应用

介绍了数字散斑干涉技术在位移、应变、振动和医学诊断等领域中的应用和国内外发展状况。提出了一种新的应用领域—数字散斑干涉技术在语音识别中的应用,并对该方法作了介绍,讨论了它的特点。     

法国产CT4型横拼双金属专用真空电子束焊机原理与构造

试述法国TECHMETA公司产的CT4型横拼双金属专用真空电子束焊机原理与构造，其中主要阐述电子枪控制电路板的原理。     

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.     

储层敏感性快速预测软件在大港油田的研究与应用

在储层特征分析，室内实验，机理研究的基础上，利用人工神经BP网络建立预测模型，并编制了预测储层5种敏感性的软件，该软件受人为因素干扰小，所需参数少，准确度高，综合符合率大于80％现场应用结果表明，该技术能为制定保护油气层技术措施提供较可靠的依据，能提高油田滚动开发效益，改善老油田的开发效果，该软件对BP算法进行了改进，（1）从两方面入手使网络摆脱平坦区，一是对输入数据进行归一化处理，使O1的取值在[0,1]之间，二是一旦网络陷入平坦区域，局部极小，使连接权值Wkj,Wji和阈值Qk,Qj同时缩小一个因子，λ＞1，可使Ok(1-Ok)脱离零值，离开平坦区；（2）加速收敛，方法有自动调整学习因子，添加动量项以及对权值进行批处理，用BP算法预测储层潜在敏感性，首先应确定影响储层敏感性的主要因素，然后根据这些因素有针对性地收集有关资料并进行处理，再根据敏感性预测的要求，设计相应的网络结构进行训练，最后对训练好的网络进行.检验。     

连续工作型电子装备战备完好性预计

从战略完好性的实际内涵出发，考虑到装备实际工作中可能处于不同的工作状态，因而其战略完好性模型也应有所有同。对于处于连续工作状态的电子装备，即使工作中发生故障，只要执行下次任务前能修好，就不影响装备的战略完好性。基于此，得出了电子装备处于连续工作状态下的战略完好性预计模型，并在对应的条件下对此模型的得出进行了缜密的推理。     

根据人工裂缝特征优化油井压裂地质方案

近年来大庆油田外围地区地质储量得到动用，每年依靠压裂投产的井逐渐增多，由达西定律可知，在油层厚度一定的情况下，措施井的渗透率是影响产量的关键参数，油井压裂可以改善油井周围地层渗透性，消除近井地带油层污染，从而提高油井产能，而人工压裂的成功与否主要取决于裂缝的导流能力和裂缝的几何形态，为此，根据台105地区地质特征，结合低渗透油田开发实际，本着经济有效的开发原则，从人工裂缝特征，方位对开发效果的影响等方面，论述了优化油井压裂地质方案技术的方法，改善了低渗透油田的开发效果。     

电子衡器特殊故障的分析及处理

因为电子衡器在安装与调试过程中出现的较为特殊的故障，难以找出正确的起因与处理方法，所以介绍了如何保证电子衡器的正常使用和计量准确性的工作体会。     

Quantitative analysis of Ni effect on CCT diagrams of novel air-cooled bainite steels using artificial neural network models

The quantitative effect of Ni content on continuous cooling transformation （CCT） diagrams of novel air-cooled bainite steels was analyzed using artificial neural network models. The results showed that Ni may retard the high- and medium-temperature transformation and martensite transformation. The results conform to the materials science theories.     

Integration framework for intelligent manufacturing processes

In this article, we describe a new approach to applying distributed artificial intelligence techniques to manufacturing processes. The construction of intelligent systems is one of the most important techniques among artificial intelligence research. Our goal is to develop an integrated intelligent system for real time manufacturing processes. An integrated intelligent system is a large knowledge integration environment that consists of several symbolic reasoning systems (expert systems) and numerical computation packages. These software programs are controlled by a meta-system which manages the selection, operation and communication of these programs. A meta-system can be implemented in different language environments and applied to many disciplines. This new architecture can serve as a universal configuration to develop high performance intelligent systems for many complicated industrial applications in real world domains.To whom all correspondence should be addressed.