基于最大重叠离散小波变换的油中颗粒污染物特征信号提取  

Feature Signal Extraction for Particle Pollutants in Oil Based on Maximal Overlap Discrete Wavelet Transform

作　　者：彭娟[1] 李川[1] 

机构地区：[1]重庆工商大学废油资源化技术与装备教育部工程研究中心,重庆400067

出　　处：《重庆工商大学学报（自然科学版）》2013年第6期24-28,共5页Journal of Chongqing Technology and Business University:Natural Science Edition

基　　金：教育部科学技术研究重点项目(212143);重庆市自然科学基金(2010BB4261);重庆市教委科学技术研究项目(KJ120720;KJ120727);重庆工商大学研究生创新型科研项目(YJSCXX201203712)

摘　　要：油液中的金属颗粒物是液压系统重要的健康指标,利用颗粒污染物的相关参数,实现对故障的诊断,可以提前预防事故的发生;介绍了基于最大重叠离散小波变换的油中颗粒污染物特征信号提取技术,并分别使用仿真信号和真实信号对该方法进行了验证,以期能够以此提高油液中颗粒污染物监测精度。Metal particles in oil are an important healthy indicator for hydraulic systems. Accident prevention can be achieved by using particle-related parameters to diagnose system faults. In this paper, a feature signal extraction technique for the particles contaminants in oil using maximal overlap discrete wavelet transform is presented. Both simulated and real signals are employed to evaluate the proposed approach, in order to improve measurement precision of the metal particles in the oil.

关 键 词：油中颗粒物 最大重叠离散小波变换 信号处理 

分 类 号：TN701[电子电信—电路与系统]