摘要
针对曲线光顺问题,提出了集合经验模态分解、游程检测法重构以及奇异谱分析降噪三者相结合的一种曲线光顺算法。算法首先将空间离散数字曲线上的x,y,z三个变量视为3个一维数字信号;然后对每个变量的数字信号序列分别进行集合经验模态分解;进而分别对每个变量分解后的所有分量使用游程检测法,将其重构为高频、低频分量;随后通过使用奇异谱分析对重构后的高频分量进行降噪;最终将降噪后的高频分量与低频分量重构,得到光顺后的曲线。通过试验表明,所提算法的光顺效果优于EMD法和曲率法,所提算法、EMD法和曲率法的平均曲率分别为0.0893,0.0919,0.1112。
Aiming at the curve smoothing,a curve smoothing algorithm based on empirical mode decomposition,run test refactoring and singular spectrum analysis noise reduction was proposed.Three variables x,y and z on the spatial discrete digital curve were regarded as three one-dimensional digital signals.Ensemble Empirical Mode Decomposition(EEMD)decomposition was carried out for each variable s digital signal sequence.Then,the runs test method was used to reconstruct all components of each variable into low-frequency components and high-frequency components.Singular Spectrum Analysis(SSA)was used to reduce the noise of the reconstructed high frequency components.The high frequency and low frequency components after noise reduction were reconstructed to obtain the curve after smoothing.Experiments showed that the smoothing effect of this algorithm was better than that of Empirical Mode Decomposition(EMD)method and curvature method.The average curvature of the proposed algorithm,EMD method and curvature method were 0.0893,0.0919 and 0.1112 respectively.
作者
吴易泽
张旭
WU Yize;ZHANG Xu(School of Mechanical and Automotive Engineering,Shanghai University of Engineering Science,Shanghai 201620,China)
出处
《计算机集成制造系统》
EI
CSCD
北大核心
2020年第12期3258-3267,共10页
Computer Integrated Manufacturing Systems
关键词
集合经验模态分解
游程检测法
奇异谱分析
曲线光顺算法
ensemble empirical mode decomposition
runs test method
singular spectrum analysis
curve fairness algorithm
