Paper Info
Title
Application of wavelet de-noising method in vibration signal analysis of elevator car
Abstract
During the operation of the elevator, the amplitude of the vibration of the elevator has a direct impact on the degree of comfort when you take the elevator, and the mechanical fault of elevator system will appear through the vibration of the elevator car. So collection and analysis of vibration signal can be used to judge the degree of comfort so as to decide the type of mechanical fault, which can provide the effective evidence for detection of running state and fault diagnosis of elevators. The key point of studying this problem is to de-noise effectively for the vibration signal we have collected; in this way, we can extract fault characteristic information of the signal. From a practical point of view, after collecting vibration signal of a multitude of elevators and conducting a lot of simulation experiments, this paper will demonstrate the wavelet multi-threshold de-noising method works best based on RMS error, SNR and correlation coefficient of honest signal by comparing these three de-noising method: wavelet analysis, wavelet packet analysis and wavelet packet multi-threshold analysis. The practice shows that this method can de-noise effectively and provide reliable signals for detection of running state and fault diagnosis of elevators.
Year
DOI
Venue
2016
10.1109/URAI.2016.7625789
2016 13th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)
Keywords
Field
DocType
wavelet analysis,wavelet packet,threshold,de-noising,fault diagnosis
Noise reduction,Signal processing,Correlation coefficient,Control theory,Network packet,Signal-to-noise ratio,Electronic engineering,Elevator,Vibration,Engineering,Wavelet
Conference
ISSN
ISBN
Citations 
2325-033X
978-1-5090-0822-3
0
PageRank 
References 
Authors
0.34
1
3
Name
Order
Citations
PageRank
Qifeng Fu100.34
Guoqing Chen2225.61
Zibo Song300.34