Author(s)

Wenfei Ning, Huajian Li, Zhiqiang Zhao, Yingjie Xie, Baozhu Jia

Corresponding Author

Baozhu Jia

Abstract

The purpose of this paper is to discuss the research progress and application practice of fault diagnosis and predictive maintenance technology for marine power system. In view of the challenges faced by the safety and reliability of the power system in the current shipbuilding industry, this paper puts forward a variety of fault diagnosis and predictive maintenance methods in order to build an efficient, intelligent and reliable fault diagnosis and maintenance system. In terms of methods, through comparative analysis and case study, this paper expounds in detail the fault diagnosis technology based on signal processing, knowledge reasoning, model analysis and the predictive maintenance technology based on data-driven and physical models. At the same time, according to the advantages and disadvantages of these methods and the scope of application, a multi-level system architecture including data acquisition, processing, fault diagnosis, performance prediction and maintenance decision support is designed. By monitoring all kinds of operation data of ship power system in real time, the system can accurately identify fault types and locations, predict the performance degradation trend of the system, and provide timely decision support for maintenance personnel, thus improving the safety, reliability and economy of ship power system.

Keywords

Ship power system; Fault diagnosis; Predictive maintenance