Stability Augmentation of a Fishing Vessel using Low Order Single Axis Mechanical Slider Based onKalman Data Estimation Technique.

Abstract

In this paper, we propose a low order mechanical design with a data estimation technique in order to minimize the roll motion of a fishing vessel which is adversely affected by hydrodynamic forces of water waves. To increase the stability of a fishing vessel we introduced a MEMS gyroscope based single axis mechanical slider. The gyro sensor will perform as an angular rate detection component to gain the raw data of the dynamic environment created by water waves. Later it will provide data for the stepper motors which will control the linear slider to find the right position of the weight attached on the top of the slider. To achieve the perfect positioning, Kalman filter is used to manipulate the stored data. The validity and feasibility of this study are evaluated by Three experimental results. At first, real time environmental data have been obtained from the fishing vessel. Then Kalman filter equations are calibrated using those derived data to predict the stability line without operating the mechanical slider. In the last stage, real time data have been collected again and filtered using same algorithm with activation to stabilize the platform. We observed the performances and experienced improvement in the stability of the aforementioned system. Moreover, many of the previous mechanism depend on multiple sensors and associated with costly installation and maintenance, this research implements a low-cost design based on only one mobile sensor.