Back to Search
Start Over
Method for filtering proportional valve-frequency-response test data containing impulsive noise
Method for filtering proportional valve-frequency-response test data containing impulsive noise
- Source :
- Advances in Mechanical Engineering, Vol 11 (2019)
- Publication Year :
- 2019
- Publisher :
- SAGE Publishing, 2019.
-
Abstract
- Impulsive noise, generated by inverters and other equipment used in the field, tends to easily enter test channels in scenarios where continuous frequency conversion signals are employed to test the frequency response of electrohydraulic proportional valves. Interference caused by such noise reduces the signal-to-response ratio of response signals, thereby influencing the accuracy of the frequency response of proportional valves. To address this concern, in this article, an integrated filtering method that combines ensemble empirical mode decomposition with median filtering is proposed. The proposed method first preprocesses the response signals of the systems and subsequently obtains frequency-response diagrams using fast Fourier transforms. Simulation results demonstrate that the proposed method reduces the root mean square error associated with the amplitude–frequency characteristic curves of the proportional directional valve considered from 2.1 to 0.3, whereas that associated with phase–frequency characteristic curves is reduced from 78.0 to 1.4 with signal-to-noise ratios in the high-frequency band being of the order of –20 dB. Experimental results also reveal that the proposed method reduces the root mean square error of the amplitude–frequency characteristic curves of the proportional directional valve by 52.5% and that of the phase–frequency characteristic curves by 71.2%.
- Subjects :
- Mechanical engineering and machinery
TJ1-1570
Subjects
Details
- Language :
- English
- ISSN :
- 16878140
- Volume :
- 11
- Database :
- Directory of Open Access Journals
- Journal :
- Advances in Mechanical Engineering
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.381764c7fce48a1b8e1ef0981525bc6
- Document Type :
- article
- Full Text :
- https://doi.org/10.1177/1687814019836298