伺服机构性能评估指标体系构建及优化研究

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英文篇名：Research on Construction and Optimization of Performance Evaluation Index System of Servo Mechanism 作者：贺友 ; 何华锋 ; 徐永壮 ; 戴嘉琪 ; 何耀民 英文作者：HE You;HE Hua-feng;XU Yong-zhuang;DAI Jia-qi;HE Yao-min;Rocket Force University of Engineering; 关键词：性能评估 ; 指标体系 ; 主成分分析 ; 系统聚类 ; 伺服机构 ; 类平均法 英文关键词：performance evaluation;;index system;;principal component analysis(PCA);;system clustering;;servo mechanism;;cluster average method 中文刊名：XDFJ 英文刊名：Modern Defence Technology 机构：火箭军工程大学; 出版日期：2018-12-18 09:55 出版单位：现代防御技术 年：2019 期：v.47;No.270 语种：中文; 页：XDFJ201902004 页数：7 CN：02 ISSN：11-3019/TJ 分类号：21-27

摘要

利用某型导弹电动伺服机构弹上实测数据,对25个动、静态特性指标进行主成分分析;通过比较最短距离法等6种方法的实际聚类效果,选择类平均法完成系统聚类。根据主成分分析结果,5个主成分能够表征25个指标量;进一步的聚类结果表明,由平方误差准则求得最优聚类数为8,由相关指数法筛选出8个指标,这为指标体系的优化提供可能,为后续改进测试方法和改善性能评估方案打下初步的基础。
        Based on the measured data of an electric servo mechanism of a certain missile,the principal component analysis of 25 dynamic and static characteristic indexes is carried out. By comparing the actual clustering effect of six methods,such as the shortest distance method,the cluster average method is selected to complete the system clustering. According to the results of principal component analysis( PCA),5 principal components can represent 25 indexes. Further clustering results show that the optimal clustering number is 8 by square error criterion,and 8 indexes are selected by correlation index method. This provides the possibility for the optimization of the indicator system,and lays a preliminary foundation for the subsequent improvement of test methods and performance evaluation schemes.

引文

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