基于MATLAB的上海光源光束线运行状态分析与预警

孙皓; 龚培荣

doi:10.11889/j.0253-3219.2016.hjs.39.070104

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基于MATLAB的上海光源光束线运行状态分析与预警

同步辐射技术及应用 | 更新时间：2021-05-24

- 基于MATLAB的上海光源光束线运行状态分析与预警
- Analysis of beamline running state and forewarning by using MATLAB in SSRF
- 核技术 2016年39卷第7期文章编号：070104
- 作者机构：
  
  1.中国科学院上海应用物理研究所张江园区上海 201204;
  2.中国科学院大学北京 100049
- 作者简介：
  
  [ "孙皓,女,1989年出生,2012年毕业于南京航空航天大学,现为硕士研究生,主要研究领域为数据处理与分析", "SUN Hao, female, born in 1989, graduated from Nanjing University of Aeronautics and Astronautics in 2012, master student, focusing on data processing and analysis" ]
  龚培荣,E-mail:gongpeirong@sinap.ac.cn GONG Peirong, E-mail: gongpeirong@sinap.ac.cn
- 基金信息：
  
  国家自然科学基金(U1232115)
- DOI：10.11889/j.0253-3219.2016.hjs.39.070104
  中图分类号： TN911.7
- 收稿日期：2016-03-14，
  
  修回日期：2016-04-18，
  
  纸质出版日期：2016-07
- 稿件说明：
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孙皓, 龚培荣. 基于MATLAB的上海光源光束线运行状态分析与预警[J]. 核技术, 2016,39(7):070104

Hao SUN, Peirong GONG. Analysis of beamline running state and forewarning by using MATLAB in SSRF[J]. Nuclear techniques, 2016, 39(7): 070104
孙皓, 龚培荣. 基于MATLAB的上海光源光束线运行状态分析与预警[J]. 核技术, 2016,39(7):070104 DOI： 10.11889/j.0253-3219.2016.hjs.39.070104.

Hao SUN, Peirong GONG. Analysis of beamline running state and forewarning by using MATLAB in SSRF[J]. Nuclear techniques, 2016, 39(7): 070104 DOI： 10.11889/j.0253-3219.2016.hjs.39.070104.

摘要

随着上海光源（Shanghai Synchrotron Radiation Facility

SSRF）新建光束线站数量的增加，其运行状态的参数记录每年都在成倍地增长，光束线站建设之初实施的运行数据处理方法已不能满足用户不断增长的需求。为此，采用MATLAB连接光束线的Archive数据库，发展了一种新的光束线运行数据的处理方法，本文通过对两条光束线单色器温度信号的数据分析，说明了MATLAB神经网络可根据数据的变化情况给出相应信号的预警提示，利用MATLAB强大的数据功能，还可有效地提高光束线站设备运行数据的分析处理能力。

Abstract

Background

With the increasing number of beamlines in Shanghai Synchrotron Radiation Facility (SSRF)

the amount of the parameter records of the running state grows exponentially year by year

while the data processing method implemented at the beginning of the construction of beamlines could not meet new user requirements.

Purpose

This study aims to solve this problem by using MATLAB. Methods: The fault pattern recognition system with strong nonlinear mapping ability was developed by using MATLAB

and the neural network was adopted to analyze the running data

which could get the result we want and give pre-warning information

via

the connection between the MATLAB and Archive database.

Results

Analysis result of the two temperatures record data of the monochrometer at BL13W and BL17U beamlines demonstrated the efficiency of this method.

Conclusion

MATLAB can be used to improve analytical ability of running data and successfully identify pre-warning for each beamline in SSRF.

关键词

Keywords

references

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