A Review of Hydraulic Cylinder Faults, Diagnostics, and Prognostics
- Authors
- Kumar, Prashant; Park, Sechang; Zhang, Yongli; Jo, Soo-Ho; Kim, Heung Soo; Kim, Taejin
- Issue Date
- Sep-2024
- Publisher
- 한국정밀공학회
- Keywords
- Hydraulic cylinders; Faut detection; Fault prognosis; Artificial intelligence
- Citation
- International Journal of Precision Engineering and Manufacturing-Green Technology, v.11, no.5, pp 1637 - 1661
- Pages
- 25
- Indexed
- SCIE
SCOPUS
KCI
- Journal Title
- International Journal of Precision Engineering and Manufacturing-Green Technology
- Volume
- 11
- Number
- 5
- Start Page
- 1637
- End Page
- 1661
- URI
- https://scholarworks.dongguk.edu/handle/sw.dongguk/22191
- DOI
- 10.1007/s40684-024-00639-3
- ISSN
- 2288-6206
2198-0810
- Abstract
- Hydraulic cylinders are typical actuators that are used in many industries, including manufacturing and construction machinery. Due to the wide application of cylinders, cylinder failures could increase maintenance costs, reduce productivity, and raise safety issues. Therefore, estimating and predicting the condition of cylinders is necessary for cost reduction and safety. This paper reviews various methods that have been proposed to estimate and predict cylinder failures. The paper first investigates the types of failures that can occur in cylinders and their causes. The failures include internal leakage, external leakage, and seal wear. The sensors used to identify each type of failure are then introduced. Since the failure information of the cylinder is implicitly embedded in the measured data, different diagnostics methods for isolating the failure information have been developed for each sensor. The diagnostic methods vary from traditional feature engineering to recent artificial intelligence-based methods. The prognostics that provide the remaining useful life of the cylinder are then reviewed. Finally, the paper discusses the challenges associated with the fault prognosis of hydraulic cylinders and future prospects.
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Collections - College of Engineering > Department of Mechanical, Robotics and Energy Engineering > 1. Journal Articles

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