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| 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。本文着重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。 |
| 关键词: 油中颗粒物，特征，最大重叠离散小波变换，提取，信号处理 |
| DOI： |
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| Extracting oil particle feature using maximal overlap discrete wavelet transform |
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PENG Juan, LI Chuan
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| Abstract: |
| Metal particle in oil is an important healthy index for hydraulic systems. Accident prevention can be achieved using particle parameters to diagnose system faults. In this paper, a feature extraction technique for oil particle contaminants using maximal overlap discrete wavelet transform is presented. Both simulated and real signals are employed to evaluate the proposed approach, which is helpful to improve the measurement precision of the metal particle in the oil. |
| Key words: Oil particle, Feature, Maximal overlap discrete wavelet transform, Extraction, Signal processing. |
