研究了一种用于三维滑坡模型试验数据处理的新方法:首先用“3σ准则”检测奇异数据,然后用时间序列中的自适应滤波法对检测出奇异数据的时刻进行预测,并用预测值替换奇异值,最后用五点三次平滑法对噪声干扰较弱的波动数据进行平滑处理。把该方法运用到三维滑坡模型试验数据处理中,处理结果显示该方法能够有效剔除奇异数据和去除毛刺现象,同时不改变原始数据的正常变化趋势。
Abstract
A novel method of data processing for three-dimensional landslide model test is proposed. First, “3σ criteria” is adopted to detect singular data. In subsequence, self-adaptive filtering method of time series is employed to predict the moment of singular data, and the singular values are replaced by the predicted values. Finally the cubical smoothing algorithm with five-point approximation is used to process the fluctuation data subjected to noise interference. The method is applied to the data processing for three-dimensional landslide model test, and the results show that this method could remove singular data and glitches effectively without altering the normal trend of the original data.
关键词
3σ准则 /
时间序列 /
自适应滤波法 /
五点三次平滑法
Key words
3σ criteria /
time series /
self-adaptive filtering method /
cubical smoothing algorithm with five-point approximation
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参考文献
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基金
国家重点基础研究发展计划(973计划)资助项目(2011CB013505);2013年三峡大学土木与建筑学院优秀硕士论文培优基金项目(PY201305);2013年三峡大学硕士学位论文培优基金项目(2013PY017)
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