Level estimation of column side ballast tank of semisubmersible crane vessel based on multi-sensor robust cubature Kalman fusion

被引：0

作者：

Xiao Y.-F. ^{[1
]}

Guo Y.-H. ^{[1
]}

Gao H.-B. ^{[1
]}

Hu Y. ^{[1
]}

机构：

[1] Key Laboratory of High Performance Ship Technology of Ministry of Education, School of Energy and Power Engineering, Wuhan University of Technology, Wuhan

来源：

Chuan Bo Li Xue/Journal of Ship Mechanics | 2023年 / 27卷 / 01期

关键词：

Column side ballast tank; Cubature Kalman filter; Level estimation; Multi-sensor fusion; Robustness; Semi-submersible crane vessel;

D O I：

10.3969/j.issn.1007-7294.2023.01.007

中图分类号：

学科分类号：

摘要：

In the level measurement of the column side ballast tank of a semi-submersible crane vessel, the observation outliers may occur and the reliability of the system output is reduced due to sensor failure or external interference. To solve this problem, a level estimation algorithm based on multi-sensor robust cubature Kalman fusion (MSRCKF) was proposed in this paper. Inspired by the idea of the Huber equivalent weight function, an adaptive factor was introduced to suppress the influence of observational outliers on the cubature Kalman filter, and the MSRCKF algorithm was derived through matrix transformation based on extended information filtering, which is approximately equivalent to the centralized fusion. The simulation results show that the MSRCKF algorithm can effectively improve the reliability and stability of the level estimation system in case of sensor failure. © 2023, Editorial Board of Journal of Ship Mechanics. All right reserved.

引用

页码：70 / 80

页数：10

共 20 条

[1]

Xu Xin, Li Xin, Yang Jianmin, Numerical simulation and model test of floating crane operation of semi-submersible crane vessel, Journal of Ship Mechanics, 18, 7, pp. 799-808, (2014)

[2]

Zhang Jianhua, Hu Kun, Liu Changbo, Numerical simulation of the process of submarine blowing off the main ballast tank with high-pressure air, Journal of Ship Mechanics, 19, 4, pp. 363-368, (2015)

[3]

Liu Hui, Pu Jinyun, Li Qixiu, Wu Xiangjun, Experimental research on submarine high pressure air blowing main ballast tank system, Journal of Harbin Engineering University, 34, 1, pp. 34-39, (2013)

[4]

Jin Tao, Liu Hui, Wang Jingqi, Yang Feng, Recovery maneuvering of submarine in case of cabin flooding, Journal of Ship Mechanics, 14, 1, pp. 34-43, (2010)

[5]

Huang Chao, He Yanping, Zhang Weijing, Et al., Research on multiplex ballast system design for large floating crane, Shipbuilding of China, 54, 2, pp. 97-104, (2013)

[6]

Masazade E, Fardad M, Varshney P K., Sparsity-promoting extended Kalman filtering for target tracking in wireless sensor networks, IEEE Signal Processing Letters, 19, 12, pp. 845-848, (2012)

[7]

Zhan Ronghui, Wan Jianwei, Iterated unscented Kalman filter for passive target tracking, IEEE Transactions on Aerospace and Electronic Systems, 43, 3, pp. 1155-1163, (2007)

[8]

Arasaratnam I, Haykin S., Cubature Kalman filters, IEEE Transactions on Automatic Control, 54, 6, pp. 1254-1269, (2009)

[9]

Olfati-Saber R., Distributed Kalman filter with embedded consensus filters, Proc of the 44th IEEE Conf on Decision and Control and the European Control, pp. 8179-8184, (2005)

[10]

Olfati-Saber R, Shamma J S., Consensus filters for sensor networks and distributed sensor fusion, Proc of the 44th IEEE Conf on Decision and Control and the European Control, pp. 6698-6703, (2005)

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