Hull behavior control system and marine vessel

Patent metadata

Field	Value
Publication number	US-11987340-B2
Application number	US-202117348870-A
Country	US
Kind code	B2
Filing date	Jun 16, 2021
Priority date	Jun 17, 2020
Publication date	May 21, 2024
Grant date	May 21, 2024

Abstract

A hull behavior control system for controlling behavior of a hull of a marine vessel includes a memory and at least one controller coupled to the memory. The at least one controller is configured or programmed to control a steering that changes the traveling direction of the marine vessel, obtain a water surface shape around the marine vessel, estimate movement of a wave based on the water surface shape, and when it is determined that the hull rides the wave whose movement has been estimated, control the steering so as to reduce an influence of the wave on the hull.

First claim

What is claimed is:

1. A hull behavior control system for controlling behavior of a hull of a marine vessel including a steering that changes a traveling direction of the marine vessel, the hull behavior control system comprising:
a memory; and
at least one controller coupled to the memory and configured or programmed to:
control the steering that changes the traveling direction of the marine vessel;
obtain a water surface shape around the marine vessel;
estimate movement of a wave based on the water surface shape;
upon determining that the hull rides the wave whose movement has been estimated, control the steering so as to reduce an influence of the wave on the hull; and
upon determining that the hull rides a crest of the wave whose movement has been estimated, control the steering so that the hull avoids the crest of the wave.

2. The hull behavior control system according to claim 1 , wherein the at least one controller is configured or programmed to:
upon determining that the hull rides the crest of the wave whose movement has been estimated, control the steering so that the hull moves away from the crest of the wave.

3. The hull behavior control system according to claim 1 , wherein the water surface shape is a three-dimensional water surface shape; and
the at least one controller is configured or programmed to:
extract the wave from undulation information of the three-dimensional water surface shape; and
estimate movement of the extracted wave.

4. The hull behavior control system according to claim 3 , wherein the at least one controller is configured or programmed to:
delete information equal to or below an average water level from the undulation information; and
extract the wave by fitting a curved surface function to the undulation information from which the information equal to or below the average water level has been deleted.

5. The hull behavior control system according to claim 3 , wherein the at least one controller is configured or programmed to estimate the movement of the extracted wave by tracking the crest of the wave.

6. The hull behavior control system according to claim 1 , wherein the at least one controller is configured or programmed to use a Kalman filter to estimate the movement of the wave.

7. The hull behavior control system according to claim 1 , wherein
the at least one controller is configured or programmed to:
input a water surface image obtained by the at least one controller into a first machine learning model that has been trained; and
estimate the movement of the wave based on a water surface shape output from the first machine learning model; and

the first machine learning model is generated by machine learning using training data including water surface images associated with respective water surface shapes.

8. The hull behavior control system according to claim 1 , wherein the at least one controller is configured or programmed to determine whether or not the hull rides the wave whose movement has been estimated based on at least a relative speed between the wave whose movement has been estimated and the marine vessel, and a traveling direction of the wave whose movement has been estimated.

9. The hull behavior control system according to claim 1 , wherein
the at least one controller is configured or programmed to:
input, into a second machine learning model that has been trained, at least a relative speed between the wave whose movement has been estimated and the marine vessel, and a traveling direction of the wave whose movement has been estimated; and
determine whether or not the hull rides the wave whose movement has been estimated using an output of the second learned model; and

the second machine learning model is generated by machine learning using training data including at least relative speeds between the wave and the marine vessel and traveling directions of the wave, associated with respective collision possibilities between the marine vessel and the wave.

10. The hull behavior control system according to claim 1 , wherein the at least one controller is configured or programmed to, upon determining that the hull rides the wave whose movement has been estimated, use a cost map to set an optimum route to reduce the influence of the wave on the behavior of the hull.

11. The hull behavior control system according to claim 10 , wherein the cost map uses costs including a deviation amount from a straight water route of the marine vessel to a destination, vertical acceleration of the hull due to the wave whose movement has been estimated, and a roll angle generated in the hull.

12. The hull behavior control system according to claim 1 , wherein
the at least one controller is configured or programmed to:
input, into a third machine learning model that has been trained, a deviation amount from a straight water route of the marine vessel to a destination, vertical acceleration of the hull due to the wave whose movement has been estimated, and a roll angle generated in the hull; and
set an optimum route to reduce the influence of the wave on the behavior of the hull using an output of the third learned model; and

the third machine learning model is generated by machine learning using training data including deviation amounts from the straight water route of the marine vessel to the destination, vertical accelerations of the hull due to the wave, and the roll angles generated in the hull, associated with respective optimum routes.

13. A marine vessel comprising:
the hull;
the steering to change the traveling direction of the marine vessel; and
the hull behavior control system according to claim 1 .

Assignees

• Yamaha Motor Co Ltd

Inventors

• Kadota Ritsu
• Koyanagi Tomoyoshi
• Moromi Shuichi
• Miyano Sadao

Classifications

• G06N3/0464

  Convolutional networks [CNN, ConvNet] · CPC title

• G06N3/09

  Supervised learning · CPC title

• B63H25/04 Primary

  automatic, e.g. reacting to compass · CPC title

• B63B79/15

  for monitoring environmental variables, e.g. wave height or weather data · CPC title

• B63B79/20

  using models or simulation, e.g. statistical models or stochastic models · CPC title