Research on confirmation of basic technological parameters of tension levellers based on neural network and genetic algorithm

Confirmation of basic technological parameters of tension levellers is the most important factor of leveling strip. Up to now, most factories have used experts' experience to decide these parameters, without any established rule to follow. For better quality of strip, a valid method is needed to decide technological parameters precisely and reasonably. In this paper, a method is used based on neural network and genetic algorithm. Neural network has a good ability to extract rules from work process of tension levellers. Then using neural network, which has learned from a lot of working samples, to be the evaluation of fitness, genetic algorithm could easily find the best or better technological parameters. At the end of this paper, examinations are given to show the effect of this method.     

基于嵌入式技术的舰船电子水平仪设计

随着船舶工业的技术进步,高精度的船载仪器被越来越多的应用到舰船领域。其中,卫星雷达、武器制导等先进技术对舰船稳定性要求很高,受海浪载荷作用下,舰船的振动和摇摆都会降低这些船载设备的精度。针对这一问题,本文研究了一种基于嵌入式技术的舰船电子水平仪控制系统,利用嵌入式芯片DSP处理水平仪的三自由度位置信号,并控制机械传动结构补偿舰船运动导致的水平仪误差,具有重要的实际应用价值。     

采用电子水平仪检定0级平板平面度的误差分析

本文通过误差分析与计算，论证了采用分度值为0．005mm／m的电子水平仪能够满足0级平板平面度检定准确度要求，这对于保证0级平板检定质量有着重要意义。