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Online Estimation of Soil Grain Diameter during Dredging of Hopper Dredger Using Continuous-Discrete Feedback Particle Filter.
- Source :
- Sensors & Materials; 2019, Vol. 31 Issue 3, Part 3, p953-968, 16p
- Publication Year :
- 2019
-
Abstract
- The trailing suction hopper dredger (TSHD) is a ship that excavates sediments from the sea bottom while sailing. Soil properties have a strong effect on the dredging process. The parameter with the greatest importance is the real-time soil grain diameter dm. This, however, cannot be directly measured by available sensors. In this paper, an alternative method is proposed to solve this problem. A new estimation method is developed on the basis of an existing sedimentation model and measuring system data. The loading process with several grain diameters is simulated to perform a sensitivity analysis of soil type. Simulation results show that the dredging efficiency is strongly affected by fine soil. This soil-related estimation problem is solved with a continuous-discrete feedback particle filter (CD-FPF), which is a recently developed filter for a CD time system. For comparison, a bootstrap particle filter (BPF) is also used to simulate the steplike changes in dm in both the no-overflow and constantvolume loading phases. The results show that the CD-FPF outperforms the BPF in terms of accuracy and applicability. Thus, it is recommended to be applied in the estimator of artificial intelligence (AI) dredging systems. [ABSTRACT FROM AUTHOR]
- Subjects :
- DREDGES
MONTE Carlo method
OCEAN bottom
DREDGING
ARTIFICIAL intelligence
Subjects
Details
- Language :
- English
- ISSN :
- 09144935
- Volume :
- 31
- Issue :
- 3, Part 3
- Database :
- Complementary Index
- Journal :
- Sensors & Materials
- Publication Type :
- Academic Journal
- Accession number :
- 135675048
- Full Text :
- https://doi.org/10.18494/SAM.2019.2220