A Novel Wavelet Packet Transform-Fuzzy Pattern Recognition-Based Method for Leakage Fault Diagnosis of Sail Slewing Hydraulic System

Abstract

When the wind direction changes, rotating the sail to keep it at the optimal angle of attack can effectively utilize offshore wind resources to improve the ship’s energy efficiency. The hydraulic system usually drives the slewing of the sail onboard. The functioning, as well as the safety of hydraulic system will be directly affected in case of leakage failure occurs. Therefore, the leakage fault diagnosis is essential to improve the sail-assisted effect as well as the reliability of the sail slewing system. In this paper, a novel wavelet packet transform (WPT)–fuzzy pattern recognition (FPR) based leakage fault diagnosis method is proposed. In order to analyze the different leakage fault features of the hydraulic system, a simulation model is established, and its effectiveness is verified by the hydraulic testbed. Then, the sensitive feature of flow and pressure signal for different leakage faults is extracted by a WPT-based method. On this basis, an FPR-based leakage fault diagnosis method is proposed. The diagnosis results show that the proposed method has an accuracy of 94% for nine leakage fault modes. This work contributes to realizing the greenization of the shipping industry by improving the utilization rate of offshore wind resources.

Keywords

• sail-assisted technology
• slewing hydraulic system
• leakage fault diagnosis
• wavelet packet transform
• fuzzy pattern recognition