Development of a smart mass flow sensor based on adaptive notch filtering and frequency domain identification

A popular method for measuring mass flows of granular materials is to register the induced force on a circular chute. When properly designed, an accurate, friction independent and linear flow measurement is achieved, ready to install in agricultural machinery or process lines. Since this type of sensor is strongly subject to wear and is installed in inaccessible places, it is important to know when it provides wrong measurements without interrupting the process. In this study, an off-line frequency domain procedure is designed to estimate wear on the chute suspension based on normal grain flow variations without extra excitation devices. The uncertainty bounds on the dynamic parameters are iteratively estimated based on a non-linear transformation between the parameter and pole/zero space. As an alternative, a robust and stable method is presented to track the resonance frequency of the mechanical sensor and paddle rate of a feeding elevator on-line.