建筑业中应用机器人的前景

机器人技术是当代高科技的产物,代表了机电一体化的最高成就。为了跟踪世界高科技发展目标,促进机器人技术在我国建筑工程领域的开发和应用,本文综述了我国工业机器人的发展及现状,研究了建筑工程机器人的特点,提出了发展我国建筑工程机器人的设想和建议。     

试谈高炉冷却壁的检漏及维护

高炉冷却壁的检漏及维护，是炼铁工作者十分关心的问题，本文针对邯钢高炉具体情况，探讨了高炉冷却壁漏水的原因，检漏方法，漏水冷却壁的维护及预防措施。     

深基坑土钉支护的有限元分析

本文阐述了土钉支护的发展简史，针对济南济享大厦土钉支护开挖深基坑进行有限元分析并取得较准确的结果，说明在深基坑土钉支护设计中应注意的问题．     

电加工机床故障分析及检修实例

机床故障的判断都是有规律可循的。维修一台有故障的机床时不要急于动手，应做到一观、二查、三电，即先观察故障现象，做到心中有数；其次，询问操作者；最后检查相应的电路图，根据故障现象排除无关联部分，缩小检修范围，找出故障部分进行维修。有时，故障现象并不是直观反映在故障部位，要透过现象抓住实质，对症下药。下面举例说明。１．慢走丝机床CUT１００D（１）故障信息。１０４。（２）故障现象。机床回零点时，向U轴负方向移动机床至极限－３０．５mm处时机床仍然不停（手压行程开关向U轴正方向移动时，机床只能回到零点），…     

In situ particle size measurements using a two-color laser scattering technique

We have developed a technique using light scattered from individual particles in the near-forward direction to measure particle size in the range of 10-200 microm. This technique uses the Mie scattering theory to relate the measured light intensity to particle size based on calibration techniques employing pinholes and water droplets of known size. We have applied a unique two-color optical arrangement to minimize the edge effect which can cause incorrect size measurements for particles that pass through the edge of the laser beam focal volume. In this paper we describe our experimental technique and the results of size measurements obtained with this technique for water droplets and pulverized coal particles.     

Efficient Implementation of the Fuzzy c-Means Clustering Algorithms

This paper reports the results of a numerical comparison of two versions of the fuzzy c-means (FCM) clustering algorithms. In particular, we propose and exemplify an approximate fuzzy c-means (AFCM) implementation based upon replacing the necessary ``exact' variates in the FCM equation with integer-valued or real-valued estimates. This approximation enables AFCM to exploit a lookup table approach for computing Euclidean distances and for exponentiation. The net effect of the proposed implementation is that CPU time during each iteration is reduced to approximately one sixth of the time required for a literal implementation of the algorithm, while apparently preserving the overall quality of terminal clusters produced. The two implementations are tested numerically on a nine-band digital image, and a pseudocode subroutine is given for the convenience of applications-oriented readers. Our results suggest that AFCM may be used to accelerate FCM processing whenever the feature space is comprised of tuples having a finite number of integer-valued coordinates.