Open AccessWavelet Leaders Based Vibration Signals Multifractal Features of Plunger Pump in Truck Crane
Author(s) -
Wenliao Du,
Yang Cui,
Ansheng Li,
Liangwen Wang
Publication year - 2013
Publication title -
advances in mechanical engineering/advances in mechanical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.318
H-Index - 40
eISSN - 1687-8140
pISSN - 1687-8132
DOI - 10.1155/2013/676404
Subject(s) - multifractal system , wavelet , signal (programming language) , vibration , computer science , noise (video) , wavelet transform , acoustics , process (computing) , artificial intelligence , algorithm , engineering , pattern recognition (psychology) , mathematics , fractal , mathematical analysis , physics , image (mathematics) , programming language , operating system
Vibration signal of plunger pump in truck crane is a typical nonlinear, nonstationary signal, and the multifractal features are a powerful tool for depicting the geometry features of such signals. The wavelet-leaders based multifractal features extraction method is an attractive tool, which has solid theoretical mathematical support and a simplified calculation procedure. The wavelet-leaders based multifractal features extraction method is compared for the original signal and the denoised signal, and the statistical performance of the obtained features is also introduced based on block bootstrap technology. The effectiveness of the wavelet leaders based method is first verified for a traditional multifractal signal. Then, the application of the proposed method to the pump vibration signals of three working conditions of truck crane: lifting, rotating, and luffing is discussed. The result shows that the geometry features of vibration signals can be obtained with wavelet leaders multifractal analysis method, and the denoising process improves the multifractal features