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Status Accepted
journal_subject Part A
Article Type Regular Paper (More than 4 pages)
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Article Title Extract Method of Flue Gas Generator Set State Feature Weak Information Based on Birgé-Massart Threshold
Keywords Flue Gas Generator Set, Weak Information Extraction, Modulus Maximum, Punishment Strategies
Abstract Flue gas generator set is a kind of large high-speed rotating machinery in petrochemical industry, which function is transfer the energy in catalytic cracking regeneration flue gas into mechanical energy. 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. Apply the algorithm to extract state features weak information of vibration signals collected on the Industrial scene, the results show that the signals after processing has good smoothness while retaining the mutation point and can be used for state feature information extraction of exhaust gas generator set.
First Name Middle Name Last Name E-Mail Corresponding
Xiaoli Xu Yes
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