DocumentCode :
3579198
Title :
Signal Singularity Detection Based on the Hermitian Wavelet for Fault Diagnosis
Author :
Jian Chen ; Wen Li ; Qingdong Li ; Peng Li ; Chengbin Lian ; Zhang Ren
Author_Institution :
Sci. & Technol. on Aircraft Control Lab., Beijing Univ. of Aeronaut. & Astronaut., Beijing, China
fYear :
2014
Firstpage :
116
Lastpage :
118
Abstract :
On Big Data analysis for fault diagnosis, health monitoring & fault tolerance of rockets and spacecrafts in aerospace industry, as the local anomaly induced signals tend to have singularity, this paper presents a guideline to employ the time-scale amplitude and phase diagrams based on the Hermitian wavelet transform to identify signal singularities. Firstly, the principle of signal singularity detection based on wavelet transform is formulated. Secondly, the definitions, characteristics, and expressions of the Hermitian wavelet transform is studied. Finally, simulations are carried out to verify the proposed algorithms.
Keywords :
condition monitoring; fault diagnosis; signal detection; wavelet transforms; Hermitian wavelet transform; aerospace industry; data analysis; fault diagnosis; fault tolerance; health monitoring; local anomaly-induced signals; rockets; signal singularity detection; signal singularity identification; spacecrafts; time-scale amplitude-phase diagram; Big data; Continuous wavelet transforms; Fault diagnosis; Wavelet analysis; Wavelet domain; amplitude diagram; hermitian wavelet; phase diagram; signal singularity; time-scale analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cloud Computing and Big Data (CCBD), 2014 International Conference on
Type :
conf
DOI :
10.1109/CCBD.2014.33
Filename :
7062881
Link To Document :
بازگشت