|本期目录/Table of Contents|

[1]朱亚男.轨道衡称重的建模方法与模拟加载仿真研究[J].工业仪表与自动化装置,2016,(03):93-96.
　ZHU Yanan.The modeling method and load simulation research of track scale weighing[J].Industrial Instrumentation & Automation,2016,(03):93-96.
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轨道衡称重的建模方法与模拟加载仿真研究(PDF)

《工业仪表与自动化装置》[ISSN:1000-0682/CN:61-1121/TH]

卷:
期数:
2016年03期
页码:
93-96
栏目:
出版日期:
2016-06-15

文章信息/Info

Title:
The modeling method and load simulation research of track scale weighing
文章编号:
1000-0682(2016)03-0000-00
作者:
朱亚男
（西安铁路职业技术学院 牵引动力系，西安 710014）
Author(s):
ZHU Ya’nan
(Dept. of Traction Power, Xi’an Railway Vocational & Technical Institute, Xi’an 710014, China)
关键词:
轨道衡; 误差补偿; 建模; 优化; 仿真
Keywords:
track scale;  error compensation;  model;  optimization;  simulation
分类号:
TP391.9；U260.72
DOI:
-
文献标志码:
A
摘要:
轨道衡称重结果受多种因素影响误差较大，因此必须采用合理的误差补偿方法对结果进行修正，为方便测试不同误差补偿方法的性能，该文提出一种轨道衡称重的建模方法。通过分析轨道衡实际测量过程提出偏载荷优化问题，进一步推导得出轨道衡称重时允许的载荷加载区域，该区域可作为实际加载过程中的最大偏载位置限制；利用模型设计的模拟加载仿真实验对于不同误差补偿方法的性能优劣进行分析，便于选择出合适的误差补偿方法使轨道衡测量结果更为精确，具有非常重要的现实意义。
Abstract:
The accuracy of track scale weighing results is affected by many factors, which lead to considerable error, so the results have to be corrected by a reasonable error compensation method. In order to test the performance of different error compensation methods, a track scale weighing modeling method was presented. By analyzing the actual measurement process of track scale, the bias load optimization problem was proposed, and further deduced the allowable loading area which is the maximum limit position of bias load. The load simulation designed by the model is capable of reliable analysis the performance of different error compensation methods, which is important to improve the accuracy of track scale weighing results by choose a reasonable error compensation method.

参考文献/References:

[1] 沈立人.大型衡器检测方法探讨[J].衡器,2006 (1):30-35.

[2] 陈昌,王孝良,秦子君.大型衡器系统偏载荷数字化补偿方法的研究[J].大连理工大学学报,1994,34(1):10-107.
[3] Griffen N C．Digital load shift compensation：US，4799558 [P].1989.
[4] 蒋金山,何春雄,潘少华.最优化计算方法[M].广州:华南理工大学出版社,2007.
[5] 朱亚男.基于人工免疫系统的智能融合算法研究及应用[D].长沙:中南大学,2012.
[6] Chen S，Cowan C F N,Grant P M．Orthogonal least squares learning algorithm for radial basis function networks[J]. IEEE Transactions on Neural Networks,1991,2(2):302-309.
[7] Moody J E,Darken C J.Fast learning in networks of locally- tuned processing units[J].Neural Computation.1989,1(2): 281-294.
[8] Karayiannis N B．Reformulated radial basis neural networks trained by gradient descent[J].IEEE Transactions On Neural Networks,1999,10(3):657-671.

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备注/Memo

备注/Memo:
收稿日期：2015-08-10
作者简介：朱亚男（1986），女，甘肃省庆阳市人，硕士，主要研究方向为智能测控，电力电子技术。
更新日期/Last Update: 1900-01-01