Research on Extract Method of Rotating Machinery Based on Birgé-Massart Threshold
Flue gas generator set is a kind of large high-speed rotating machinery in petrochemical industry.The operational status monitoring in order to ensure safe and stable operation of the flue gas generator set needs to resolve problem in the extraction of state feature weak information under large amount of background noise.To this end,the research is on noise suppression algorithms on the basis of Birgé-Massart penalty function strategy to obtain signal wavelet transform modulus maximum of threshold.Obtain the threshold through Penalization Strategy Provided by Birgé-Massart; construct different modulus maximum vertex neighborhood on different wavelet transform decomposition scales to influence the search process of modulus maximum point; obtain the appropriate modulus maximum points sequence on various wavelet decomposition scales; highlight state feature information; finally use Mallat staggered projection to reconstruct signals.In order to validate the effectiveness of the algorithm,it was compared with four kinds of threshold noise suppression methods namely Rigrsure,Sqtwolog,Heursure,Minimaxi,and the results show that this algorithm has a better signal to noise ratio and mean-square error.
feature extraction modulus maximum punishment strategies
Xiaoli Xu Zhanglei Jiang Guoxin Wu Yunbo Zuo
School of Mechanical and Vehicle Engineering,Beijing Institute of Technology,Beijing 100081,china;Ke School of Mechanical and Vehicle Engineering,Beijing Institute of Technology,Beijing 100081,china Key Laboratory of Modern Measurement & Control Technology,Ministry of Education,Beijing Information
国际会议
南京
英文
1-4
2013-08-20（万方平台首次上网日期，不代表论文的发表时间）