Using dijital filter in motion weighing

Weighing is a method that we frequently use in all areas of our lives from past to present. Weighing devices, which can be designed in accordance with usage conditions and needs, are developing day by day with technology. In this study, the weighing process of objects with different weights was observed in the moving area and the estimation algorithm was developed. Measured in weighing operation, unstable conditions and moving area. Due to this situation, low frequency signals, namely noise signals, can be added to the measured signals and give misleading results. In order to overcome this problem, an estimation algorithm has been developed using the Kalman filter. In this algorithm, filtering is also done with FIR filter. More accurate results were obtained by presenting the filtered data to the KF estimation algorithm. The developed prediction algorithm works recursively on the noise-containing data stream. The estimation result was obtained by minimizing the error and performing filtering at each step with KF.