Title :
Fractal Fault Diagnosis of Rotor System Based on Morphological De-nosing
Author :
Du, Bi-qiang ; Tang, Gui-ji ; Wang, Song-ling
Abstract :
As an experimental tool for analyzing movement of chaos, we intend to introduce the correlation dimension for analyzing vibration signals of rotor system in this paper. For noise corruption existing in field-measured vibration signal, morphological filter is also introduced for de-noising the vibration signal. The analysis and comparison between the correlation dimensions of the noised and de-noised vibration signals of rotor system at different states are done. The result shows that reflecting the system´s characteristic with the correlation dimension of noised signal is largely unreliable, so the field-measured signal must be de-noised prior to the correlation dimension calculation. The favorable de-noising effect by morphological filter is also showed. The correlation dimension of de-noised vibration signals can reflect and distinguish the actual state of rotor effectively. As a character to classify the fault type and state of rotor in fault diagnosis, the correlation dimension after de-noising is feasible.
Keywords :
Chaos; Fault diagnosis; Fractals; Geometry; Image analysis; Noise reduction; Nonlinear filters; Signal analysis; Signal processing; Vibrations; Rotor system; correlation dimension; fault Diagnosis; fractal; morphological filter;
Conference_Titel :
Image and Signal Processing, 2008. CISP '08. Congress on
Conference_Location :
Sanya, China
Print_ISBN :
978-0-7695-3119-9
DOI :
10.1109/CISP.2008.28