Knowledge-based diagnosis of drill conditions

One major bottleneck in the automation of the drilling process by robots in the aerospace industry is drill condition monitoring. This paper describes a system approach to solve this problem through the advancement of new machine design, sensor instrumentation, metal-cutting research, and intelligent software development. All drill failures can be detected and distinguished: chisel edge wear, flank wear, crater wear, margin wear, corner wear, breakage, asymmetry, lip height difference, and chipping at lips. However, in the real manufacturing environment, different workpiece materials, drill size, drill geometry, drill material, cutting speed, feed rate, etc. will change the criteria for judging the drill condition. The knowledge base used for diagnosing the drill failures requires a huge data bank and prior exhaustive testing. A self-learning scheme is therefore introduced to the machine in order to acquire the threshold history needed for automatic diagnosis by using the same new tool under the same drilling conditions.     

库岸滑坡稳定可靠性分析中若干规律的探讨

采用可靠性分析的Monte-Carlo法，对中岸滑坡稳定可靠性分析中的有关规律进行了探讨。指出了影响滑坡体稳定的有关因素及其变异性对破坏概率的影响。     

精轧油膜轴承密封失效机理的初步分析

对油膜轴承密封出现的进水、漏油现象作了大量的调查、测量和统计分析，找出了产生质量事故的根本原因，提出了解决措施。     

Fault-accommodation with intelligent sensors

Optimal sensor fault-accommodation is considered for faults modelled by an increase in measurement noise. This noise is taken to be bounded and its probabilistic properties unknown. It is assumed that intelligent (e.g. self-validating) instrumentation is in use and estimates of the noise bounds are available. The fault-tolerant controller is designed to optimize a noise rejection and a nominal reference tracking index and leads to a mixed norm minimization problem (l₁/l₂). We exploit known results and a particular feedback configuration to show that it is possible to optimize simultaneously without a trade-off the two performance indices. The results are applied to systems where the presence of auxiliary measurements allows for an optimal fault-accommodation strategy. Using properties of the optimal solution, we define a factorization for the optimal controller alternative to the Youla parametrization, leading to an algorithm which is optimal, transparent and efficient.     

Macha爆炸机故障维修十一例

随着Macha遥爆系统在地震勘探中使用年限的增加，该系统在工作中时常出现各种各样的故障，本文根据其日常检修记录，分析总结了Macha系统常见的十一例故障，并从故障的现象、分析、排除三个方面对各个故障进行了详细的介绍。     

Forecasting of Turkey's net electricity energy consumption on sectoral bases

In this study forecast of Turkey's net electricity energy consumption on sectoral basis until 2020 is explored. Artificial neural networks (ANN) is preferred as forecasting tool. The reasons behind choosing ANN are the ability of ANN to forecast future values of more than one variable at the same time and to model the nonlinear relation in the data structure. Founded forecast results by ANN are compared with official forecasts.     

模拟退火算法用于蒸汽吞吐井生产能力的预测

模拟退火算法是一种利用统计力学观点求解优化问题全局最优解的方法,是目前解决优化问题的一种比较先进的方法。本文应用模拟退火算法对蒸汽吞吐注采参数进行优化设计,并确定出了6个吞吐周期的最优周期产油量和周期注蒸汽量,较实际周期产油量和实际周期注汽量均有明显增加。将各周期的优化累积产油量和优化累积注汽量画在累积产油量与累积注汽量的双对数坐标中,得出累积注汽量和累积采油量关系曲线(简称注采关系曲线)。将该注采关系曲线外推估算了该井未来周期的累积产油量和累积注汽量,从而达到对蒸汽吞吐井生产能力的预测。     

疏松砂岩地层出砂对套管损坏的研究

以东濮凹陷文明寨油田历年井况调查的套管损坏资料为依据，在对出砂油井套管损坏形态、层位与射孔状况、岩石性质等因素进行综合分析基础上，对疏松砂岩出砂、上覆岩层坍塌等主要方面导致的套管受力变形进行研究，为探讨防治措施提供依据。     

梯级-关联算法在多泥沙河流含沙量预报中的应用

本文借助历史加成法处理样本数据，并分别利用梯级-关联算法(CC)和误差反馈传播算法(BP)建立模型对黄河下游夹河滩水文站汛期含沙量进行预报。传统BP网络需要预先设定网络结构，预报过程虽利用了神经网络的内插特性，但其样本的处理方式和网络构建方式使得运算效率较低；CC算法仅要求初始网络含有输入层和输出层，通过运算不断向网络增加隐含节点，从而最大限度的减少了在网络构建过程中的主观因素。本文比较了当预报的峰值超出训练样本取值范围时两种算法的表现，结果显示：当预报的峰值为训练样本峰值的2.45倍时，二者均能实现较为准确的预报，BP网络在预报精度上要略高于CC网络，但CC网络在运算速度上要明显快于BP网络。     

DIN-100MnCrW4模具钢开裂原因分析

对DIN－100MnCrW4模具钢开裂原因进行了分析。结果表明，模具钢 属淬火开裂，主要原因是材料内部组织不均匀所致。