@article{tang_online_2008,
	title = {Online fault diagnosis and prevention expert system for dredgers},
	volume = {34},
	issn = {0957-4174},
	url = {http://www.sciencedirect.com/science/article/pii/S0957417406003022},
	doi = {10.1016/j.eswa.2006.09.032},
	abstract = {Faults during dredging process often caused serious damages on dredging system. High maintenance costs and prolonged fault recovering process often make dredging production and profit low. An online fault diagnosis and prevention expert system that is aimed to prevent fault occurrence and to quicken the recovering process is introduced in this paper. For the complexity of fault judging and prevention process and frequently varying dynamics of dredging operations, hybrid structure and inference process are adopted in the expert system. ANNs are introduced to adapt the varying system dynamics and to predict system state. Designed expert application is also featured by online fault prevention and recovering decisions. Preliminary test has been carried out in actual engineering project and results of performance evaluation experiment are also introduced.},
	language = {en},
	number = {1},
	urldate = {2020-05-06},
	journal = {Expert Systems with Applications},
	author = {Tang, Jian-Zhong and Wang, Qing-Feng},
	month = jan,
	year = {2008},
	keywords = {Dredging, Expert system applications, Expert systems, Fault diagnosis, Fault prevention},
	pages = {511--521},
}

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