An Absolute Displacement Measurement Method and Its Application in Ship Motion Measurement

In order to perform multi-degree-of-freedom motion measurements of marine machinery, such as ship-borne mechanical platforms, in an absolute environment without a reference, absolute measurement methods using acceleration sensors and tilt gyroscopes are typically employed. However, the influence of wave forces on ship-borne mechanical platforms can cause coupling between different degrees of freedom, resulting in significant measurement disturbances that make efficient computation and real-time analysis challenging. To address these challenges, a correction method for the motion measurement of the ship-borne mechanical platform based on multi-sensor fusion is proposed by analyzing the influence of the inclination angle of the ship-borne mechanical platform on the sensor measurement based on the working principles of the acceleration sensor and angle sensor. In this article, we first analyzed the influence of the inclination angle on the integral effect in the heave direction. Then, we proposed a configuration using four groups of acceleration sensors to correct the integral effect. Finally, the optimal inclination angle is determined through Kalman filtering based on the measured values of the angle sensors and estimated values from the acceleration sensor sets. Experiments have proved that the average error of the corrected heave displacement signal is 25.34 mm, which is better than the integral displacement signal of a single acceleration sensor. At the same time, we use the acceleration sensor to calculate the roll angle and pitch angle of the ship-borne mechanical platform and combine it with the angle sensor signal to perform Kalman filtering. This filters out the errors caused by the shaking and instability of the mechanical platform and can more accurately estimate the true inclination of the platform. Therefore, this method can enhance the precision and accuracy of ship-borne mechanical platform motion signal acquisition, providing more valuable experimental data for research in marine engineering and related fields.

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Visual-Inertial Fusion-Based Five-Degree-of-Freedom Motion Measurement System for Vessel-Mounted Cranes

Yu,

Cheng,

Xia

et al. 2024

Machines

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Vessel-mounted cranes operate in complex marine environments, where precise measurement of cargo positions and attitudes is a key technological challenge to ensure operational stability and safety. This study introduces an integrated measurement system that combines vision and inertial sensing technologies, utilizing a stereo camera and two inertial measurement units (IMUs) to capture cargo motion in five degrees of freedom (DOF). By merging data from the stereo camera and IMUs, the system accurately determines the cargo’s position and attitude relative to the camera. The specific methodology is introduced as follows: First, the YOLO model is adopted to identify targets in the image and generate bounding boxes. Then, using the principle of binocular disparity, the depth within the bounding box is calculated to determine the target’s three-dimensional position in the camera coordinate system. Simultaneously, the IMU measures the attitude of the cargo, and a Kalman filter is applied to fuse the data from the two sensors. Experimental results indicate that the system’s measurement errors in the x, y, and z directions are less than 2.58%, 3.35%, and 3.37%, respectively, while errors in the roll and pitch directions are 3.87% and 5.02%. These results demonstrate that the designed measurement system effectively provides the necessary motion information in 5-DOF for vessel-mounted crane control, offering new approaches for pose detection of marine cranes and cargoes.

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An Absolute Displacement Measurement Method and Its Application in Ship Motion Measurement

Cited by 3 publications

References 31 publications

Application of Indoor Motion Measurement Technology based on SLAM Algorithm in Underground Engineering

Application of Indoor Motion Measurement Technology based on SLAM Algorithm in Underground Engineering

A Correction Method for the Motion Measurement of the Ship-Borne Mechanical Platform Based on Multi-Sensor Fusion

Visual-Inertial Fusion-Based Five-Degree-of-Freedom Motion Measurement System for Vessel-Mounted Cranes

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