摘要
阶跃信号包含重要的故障信息,基于拟合误差的区间半分定性趋势提取方法能有效的自动提取过程数据趋势,但当过程运行状态发生激烈变化,重要参数中包含阶跃信号时,却存在时间窗分隔不恰当,趋势提取不准甚至错误等问题。文章通过增加阶跃信号识别预处理过程,实现了阶跃信号和非阶跃信号数据趋势的分段提取,并给出了一种定性趋势提取效果判别方法。实例验证表明该方法能有效地解决阶跃信号趋势提取问题。
Step signals comprise the important fault information.A polynomial-fit based interval-halving algorithm in qualitative trend analysis can automatically identify the qualitative shapes of process data trends.When the parameter data comprise step signals,the interval-halving algorithm has some problems such as being hard to partition the window size felicitously,inaccurate of trend extraction.This paper improves the interval-halving algorithm for trend extraction.Data are divided into two parts by data preprocessing,one comprises step signals only and the other comprises non-step signals.The method that discriminates the effectiveness of interval-halving algorithm is also given.The simulation results show that the improved algorithm is correct.
出处
《仪表技术》
2011年第2期57-60,62,共5页
Instrumentation Technology
基金
重庆市自然科学基金资助项目(2007BB2101)
关键词
阶跃信号
定性趋势分析
区间半分
数据预处理
step signal
qualitative trend analysis
interval-halving algorithm
data preprocessing
