Extraction of Machinery Health Index for CBM
Condition-based Maintenance (CBM) is widely accepted as a powerful technique for optimal maintenance decision-making. Generally, this objective is realized by extracting the health index using machinery health monitoring system from different kinds of informative sources (vibrations, acoustic emissions, etc). The study summarized in this paper proposed a novel scheme for the extraction of machinery health index, which is based on the wavelet modulus maxima. This approach takes advantage of high sensitivity to non-stationary signatures. Specifically, modulus maxima distribution, a measure of the existence of singularity points, is the feature that is utilized to depict the presence of machinery fault and determine the degree of damage that occurred. This scheme is validated by real vibration data and the results presented herein show this approach to be an effective way in the extraction of machinery health index.
condition-based maintenance health index wavelet modulus maxima.
MIAO Qiang HUANG Hongzhong FAN Xianfeng XIONG Jingqi YANG Bo
School of Mechatronice Engineering, University of Electronic Science and Technology of China, China
国际会议
The First International Conference on Maintenance Engineering(首届维修工程国际学术会议)
成都
英文
235-241
2006-10-15（万方平台首次上网日期，不代表论文的发表时间）