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Lookup NU author(s): Dr Hongbin Tang, Dr Wenxian YangORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
Hydraulic systems have been widely used in construction machinery, aeronautics, astronautics, automobiles, shipping and other fields. Piston pumps are power source and core component in the hydraulic system. The detection and assessment of leakage fault in piston pumps is challenging because (1) piston pump is always subjected to varying loads and operates at variable speeds, the conventional condition monitoring methods that rely on instantaneous behavior analysis can hardly give reliable prediction to the actual health state of the piston pump; (2) it is not easy to obtain the typical condition monitoring data that can reflect the change of the piston pump in dynamic behavior when it suffers different severity levels of faults under various loading conditions. In order to tackles these issues, a model-based method for leakage detection of piston pump under variable load condition was proposed in this paper. The liquid-solid coupling model of piston pump is developed and verified at first. Then, with the aid of the model, different severity levels of oil leakage faults are simulated. It is found that outlet pressure signals can better indicate the oil leakage of piston pumps in comparison of the casing vibration signals. Subharmonics‟ will appear in the frequency spectra of outlet pressure signals in the presence of oil leakage fault. Finally, the dynamic responses of the piston pump under different loading and structural health conditions are investigated systematically. The results show that external load can significantly influence the dynamic responses of the piston pump and the gradients of the trend lines of total „sub-harmonic‟ energy of outlet pressure provide correct prediction to the presence and growth of the oil leakage fault. Based on the investigation results, a reliable oil leakage detection and assessment method is proposed.
Author(s): Tang H, Yang W, Wang Z
Publication type: Article
Publication status: Published
Journal: IEEE Access
Year: 2019
Volume: 7
Pages: 99771 - 99781
Online publication date: 24/07/2019
Acceptance date: 15/07/2016
Date deposited: 26/07/2019
ISSN (electronic): 2169-3536
Publisher: IEEE
URL: https://doi.org/10.1109/ACCESS.2019.2930816
DOI: 10.1109/ACCESS.2019.2930816
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