Title :
The Application of Vibration Signal Multi-fractal in Fault Diagnosis
Author :
Yu, Yuan ; Baoliang, Li ; Jingshan, Shang ; Shixuan, Yao
Author_Institution :
Sch. of Mech. Eng., Dalian JiaoTong Univ., Dalian, China
Abstract :
Condition monitoring of machines through the analysis of their vibrations has been recognized to be a difficult issue, essentially because of the strong nonlinearity of the vibration signals. In this paper, vibration signal multifractal method was researched. multifractal on time-frequency domain was an energy fractal method and the signal feature extraction was based on the analysis of its energy distributing. The method analyzed signal on time-frequency domain to characterize the distributing of its frequency or energy, and the signal´s feature was extracted by fractal dimension. After the signal was changed to time-frequency domain by Hilbert-Huang transform, general dimension Dq would be calculated from the signal in time-frequency domain by least square method. In the end, examples of emulator and practical application proved that this integrated method was feasible.
Keywords :
Hilbert transforms; acoustic signal processing; condition monitoring; fault diagnosis; feature extraction; fractals; least squares approximations; machinery; vibrations; Hilbert-Huang transform; energy fractal method; fault diagnosis; least square method; machine condition monitoring; signal feature extraction; time-frenquency domain; time-frequency domain; vibration signal multifractal method; Density measurement; Fault diagnosis; Feature extraction; Fractals; Motion measurement; Noise measurement; Nonlinear systems; Signal analysis; Time frequency analysis; Vibrations; Condition monitoring; Hilbert-huang transform; Mulfractal; Nonlinearity; Time-frequency domain;
Conference_Titel :
Future Networks, 2010. ICFN '10. Second International Conference on
Conference_Location :
Sanya, Hainan
Print_ISBN :
978-0-7695-3940-9
Electronic_ISBN :
978-1-4244-5667-3
DOI :
10.1109/ICFN.2010.90
