ISSN 0914-4935
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Sensors and Materials
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Online Estimation of Soil Grain Diameter during Dredging of Hopper Dredger by Continuous-discrete Feedback Particle Filter

Zhen Su, Zhao-Xu Zhou, Meng-Hong Yu, Wei Yuan, and Jing-Qi Fu

(Received November 23, 2018; Accepted February 18, 2019)

Keywords: hopper dredge, soil grain diameter, measuring system, mathematical model, estimation, feedback particle filter, online measurement, sensor

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 step like changes in dm in both no-overflow and constant-volume 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.

Corresponding author: Jing-Qi Fu




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