Filter design for dynamic weight measurement

Weighing is an indispensable part of industrial production systems. In this sense, dynamic weighing systems are used as a method of increasing the industrial production rate. Since the weight signal from the dynamic weighing systems is a noisy signal, weights of the products cannot be determined directly using this signal. Therefore, it is necessary to filter the weight signal in order to precisely determine the weights of the products. Within the scope of this study, a filter design practice was performed for cancellation of noise from the weight measurement signal which was used to weigh 12 eggs with dynamic weighing system. For filter design, adaptive LMS filter and fixed window filters (Blackman, Hamming, Von Hann, Rectangular) were used. The obtained filter results have been compared on a graphic. A simple stabilization procedure was applied to the filter results in order to obtain the stabilized weight values of the eggs. Additionally, the stable weight values obtained at the end of the stabilization process are compared with each other and with the static weight value of 12 eggs. With this application, it is aimed to perform filtering application with suitable FIR filters and adaptive LMS filter in MATLAB environment for use in dynamic weighing systems and signal processing applications and researches.