A Fault Location Algorithm Based on Convolutional Neural Network for Sensor System of Seafloor Observatory Network

CORC > 沈阳自动化研究所 > 中国科学院沈阳自动化研究所 > 海洋信息技术装备中心

	A Fault Location Algorithm Based on Convolutional Neural Network for Sensor System of Seafloor Observatory Network
	Sun K(孙凯)
	2019
会议日期	June 17-20, 2019
会议地点	Marseille, France
关键词	seafloor observatory network data transmission system fault location convolutional neural network
页码	1-5
英文摘要	The seafloor observatory network (SFON) covers an extensive area and consists of many network devices functioning in the abyssal environment, which make patrolling inapplicable to fault location in the marine setting. Moreover, finding faults like degradation of precision or zero drift would be rather difficult if such faults are only located by the warning message from a single sensor. To solve this problem and as per the features of SFON, we propose a fault location algorithm based on the convolutional neural network (CNN) for the data transmission system. This algorithm which takes a holistic perspective and considers the features of network device can monitor all the sensors in a unified and centralized way. The algorithm sets the CNN parameters according to the features of the research object, and normalizes the data of sensors to images. It first qualitatively judges a fault, and then recognizes its source and type. The new algorithm has higher precision on fault recognition than the support vector machine.
产权排序	1
会议录	OCEANS 2019 Marseille
会议录出版者	IEEE
会议录出版地	New York
语种	英语
ISBN号	978-1-7281-1450-7
内容类型	会议论文
源URL	[http://ir.sia.cn/handle/173321/26046]
专题	沈阳自动化研究所_海洋信息技术装备中心
通讯作者	Sun K(孙凯)
作者单位	Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
推荐引用方式 GB/T 7714	Sun K. A Fault Location Algorithm Based on Convolutional Neural Network for Sensor System of Seafloor Observatory Network[C]. 见:. Marseille, France. June 17-20, 2019.