Mixing Apparatus Mass Flow Tracking in Transient States

A mathematical model acts as an intermediary between the noisy weight sensor signals and the required mass flow rate information. The model processes the interfered measurements through algorithms (such as Kalman filtering) to extract accurate product weight and mass flow rate data without requiring slow mechanical filtering, thus resolving the contradiction between measurement reliability and response speed.

The patent replaces traditional mechanical filtering approaches with a mathematical modeling approach. Instead of using slow mechanical filters that reduce dynamic range, the system employs mathematical models with algorithms (such as Kalman filters) that can process transient state data reliably, thus maintaining both measurement reliability and transient state detection capability.

The system uses feedback from weight measurements combined with mathematical modeling to indirectly determine outlet mass flow rate. The mathematical model continuously adjusts its predictions based on feedback from actual weight measurements, enabling comprehensive product tracking without requiring direct outlet flow measurement that would be subject to the same interference problems.

The system performs preliminary calculations using mathematical models to predict mass flow rates and product weight before actual processing occurs. By pre-calculating expected values and comparing them with actual measurements, the system can identify defective batches early in the process, enabling waste minimization through targeted discarding of only affected final products rather than entire batches.