China Mechanical Engineering ›› 2012, Vol. 23 ›› Issue (21): 2594-2596.

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Temperature Data Processing for Breakout Prediction Based on Wavelet Analysis

Zhang Benguo1;Li Qiang1;Wang Ge1;Sun Lifeng2;Zhang Zhike3   

  1. 1.Yanshan University,Qinhuangdao,Hebei,066004
    2.Hebei University of Science and Technology,Shijiazhuang,050018
    3.Handan Iron and Steel Co.,Ltd.,Handan,Hebei,056015
  • Online:2012-11-10 Published:2012-11-15
  • Supported by:
    Hebei Provincial S&T Research and Development Program of China(No. 07212119D)

基于小波分析的漏钢预报温度数据处理

张本国1;李强1;王葛1;孙丽凤2;张志克3   

  1. 1. 燕山大学,秦皇岛,066004
    2.河北科技大学,石家庄,050018
    3.邯郸钢铁集团公司,邯郸,056015
  • 基金资助:
    河北省科学技术研究与发展计划资助项目(07212119D)
    Hebei Provincial S&T Research and Development Program of China(No. 07212119D)

Abstract:

A wavelet-based de-noising method was introduced into the breakout prediction system in the continuous casting process to conduct the noise reduction. Temperature data collected by thermocouples was multi-scale decomposed. The threshold was applied to the wavelet coefficients, the temperature signals were reconstructed and the temperature date were de-noised. The trend of the temperature changing can be well shown by the de-noised data results.

Key words: breakout prediction, wavelet analysis, signal de-noise, data processing

摘要:

将小波分析引入到连铸过程漏钢预报系统中,对热电偶所采集的温度数据进行降噪处理。通过对连铸现场采集的温度数据进行多尺度小波分解,并对小波分解系数作相应的阈值处理,最后重建温度信号,去除了温度数据中的噪声。结果表明,经过小波分析降噪后的温度数据能更好地反应测温点的温度变化趋势。

关键词: 漏钢预报, 小波分析, 信号降噪, 数据处理

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