文章基本信息

标题：Oil metal particles Detection Algorithm Based on Wavelet Transform
本地全文：下载
作者：Wei Shang ; Wei Shang ; Yanshan Wang 等
期刊名称：MATEC Web of Conferences
电子版ISSN：2261-236X
出版年度：2017
卷号：100
页码：1-7
DOI：10.1051/matecconf/201710002001
语种：English
出版社：EDP Sciences
摘要：In order to observe the real-time abrasion status of the aero-engine, we need to monitor the lubrication system online. As the aero-engine operating time and running state changes, the concentration, composition, size and other parameters of the metal debris can show different changes. They can be used as an important indicator to reflect the state of the aero-engine fault. However, due to the influence of electromagnetic, vibration disturbance and random noise signal introduced by the processing unit itself, the metal particles signal tend to comprise noise. Oil metal particles detection algorithm based on wavelet transform, utilizes the optimized localized nature in time domain and frequency domain of wavelet transform and the characteristics of multi-resolution analysis, combined with the signal characteristics in actual aero-engine condition to realize noise reduction and detection, while validating the algorithm using real experimental data. The result shows that noise can be effectively decreased and signal characteristics can be detected correctly.
关键词：Sensor;metal debris;wavelet transform;variance iterative estimation;feature extraction