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Open AccessArticle

A Fault Feature Extraction Method for the Fluid Pressure Signal of Hydraulic Pumps Based on Autogram

1
College of Mechanical Engineering, North China University of Science and Technology, Tangshan 063210, China
2
National Research Center of Pumps, Jiangsu University, Zhenjiang 212013, China
*
Authors to whom correspondence should be addressed.
Processes 2019, 7(10), 695; https://doi.org/10.3390/pr7100695
Received: 23 July 2019 / Revised: 9 September 2019 / Accepted: 11 September 2019 / Published: 3 October 2019
(This article belongs to the Special Issue Smart Flow Control Processes in Micro Scale)
Center spring wear faults in hydraulic pumps can cause fluid pressure fluctuations at the outlet, and the fault feature information on fluctuations is often contaminated by different types of fluid flow interferences. Aiming to resolve the above problems, a fluid pressure signal method for hydraulic pumps based on Autogram was applied to extract the fault feature information. Firstly, maximal overlap discrete wavelet packet transform (MODWPT) was adopted to decompose the contaminated fault pressure signal of center spring wear. Secondly, based on the squared envelope of each node, three kinds of kurtosis of unbiased autocorrelation (AC) were computed in order to describe the fault feature information comprehensively. These are known as standard Autogram, upper Autogram and lower Autogram. Then a node corresponding to the biggest kurtosis value was selected as a data source for further spectrum analysis. Lastly, the data source was processed by threshold values, and then the fault could be diagnosed based on the fluid pressure signal. View Full-Text
Keywords: hydraulic pump; feature extraction; fluid pressure; Autogram; kurtosis hydraulic pump; feature extraction; fluid pressure; Autogram; kurtosis
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MDPI and ACS Style

Zheng, Z.; Li, X.; Zhu, Y. A Fault Feature Extraction Method for the Fluid Pressure Signal of Hydraulic Pumps Based on Autogram. Processes 2019, 7, 695.

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