A Review on Fault Diagnosis Technology of Key Components in Cold Ironing System

Kai Ding, Chen Yao, Yifan Li, Qinglong Hao, Yaqiong Lv and Zengrui Huang
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Kai Ding: State Grid Hubei Electric Power Company Limited Research Institute, Wuhan 430000, China
Chen Yao: No. 2 Institute of Water Transportation, Anhui Transport Survey and Design Institute Co., Ltd., Hefei 230011, China
Yifan Li: School of Transportation and Logistics Engineering, Wuhan University of Technology, Wuhan 430000, China
Qinglong Hao: School of Transportation and Logistics Engineering, Wuhan University of Technology, Wuhan 430000, China
Yaqiong Lv: School of Transportation and Logistics Engineering, Wuhan University of Technology, Wuhan 430000, China
Zengrui Huang: State Grid Hubei Electric Power Company Limited Research Institute, Wuhan 430000, China

Sustainability, 2022, vol. 14, issue 10, 1-28

Abstract: Nowadays, cold ironing technology has been demonstrated to be an effective solution to deal with the environmental and social problems brought by port ship emissions and relevant effects. The working states of cold ironing equipment, especially the key components such as circuit breakers, transformers and frequency converters, have a significant effect on the safety and reliability of the whole system. However, due to the harsh working environment of cold ironing equipment, they are prone to a high risk of failure. In this respect, fault diagnosis methods can play a significant role in detecting potential failure in time and guarantee the safe and reliable operation of the cold ironing system. In recent years, research on the fault diagnosis of a cold ironing system has been rapidly growing, and this paper aims to present a comprehensive review of this literature, with an emphasis on the fault diagnosis technology applied to the key components in a cold ironing system. This review classifies the literature according to the type of key component, and, for each special type of component, the fault diagnosis methods are further categorized and analyzed. This paper provides useful references for professionals and researchers working on the fault diagnosis of a cold ironing system and points out valuable research directions in the future.

Keywords: cold ironing system; fault diagnosis; key component (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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