Research on attitude compensated algorithm for shipborne dynamic weighing

Shipborne dynamic weighing is fundamental in developing marine fishery resources and oceanographic research. It enables the weighing and sorting of seafood, quantitative baiting, and measurement of research sample weights in marine environments. Therefore, developing shipborne dynamic weighing systems is crucial for the integrated exploitation of marine fishery resources. However, research on shipborne dynamic weighing is limited. To address this issue, the study initially analyzed the impact of ship's attitude information on weighing results. Subsequently, a mathematical model for shipborne dynamic weighing, incorporating compensation factors, was constructed. The compensation factors were determined using the Recursive Least Squares (RLS) method. And then real-time weight estimation was updated using Kalman filtering, effectively mitigating the influence of ship oscillations and swaying on weight measurements. Furthermore, a shipborne dynamic weighing system with a 24-bit analog-to-digital converter (ADC) and STM32F4 processor was developed. The system performance was evaluated by simulating the sail of a ship under different sea conditions on a swing platform. The results demonstrate that the average absolute percentage error of the test meets the requirement of less than 1%, and the standard deviation of the error is less than 1% F. S., which essentially meets the weight measurement requirements of marine dynamic weighing and sorting.