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The Remaining Useful Life Prediction Method of a Hydraulic Pump under Unknown Degradation Model with Limited Data

Authors :
Guo, Fenghe Wu
Jun Tang
Zhanpeng Jiang
Yingbing Sun
Zhen Chen
Baosu
Source :
Sensors; Volume 23; Issue 13; Pages: 5931
Publication Year :
2023
Publisher :
Multidisciplinary Digital Publishing Institute, 2023.

Abstract

This study proposes a remaining useful life (RUL) prediction method using limited degradation data with an unknown degradation model for hydraulic pumps with long service lives and no failure data in turbine control systems. The volumetric efficiency is calculated based on real-time monitoring signal data, and it is used as the degradation indicator. The optimal degradation curve is established using the degradation trajectory model, and the optimal probability distribution model is selected via the K-S test. The above process was repeated to optimize the degradation model and update parameters in different performance degradation stages of the hydraulic pump, providing quantification of the prediction uncertainty and enabling accurate online prediction of the hydraulic pump’s RUL. Finally, an RUL test bench for hydraulic pumps is built for verification. The results show that the proposed method is convenient, efficient, and has low model complexity. The method enables online accurate prediction of the RUL of hydraulic pumps using only limited degradation data, with a prediction accuracy of over 85%, which meets practical application requirements.

Details

Language :
English
ISSN :
14248220
Database :
OpenAIRE
Journal :
Sensors; Volume 23; Issue 13; Pages: 5931
Accession number :
edsair.multidiscipl..6f18fe00707a301d8a6115435380631d
Full Text :
https://doi.org/10.3390/s23135931