A Signal Processing Method for Dynamic Weighing of Belt Conveyor Based on Adaptive Filter
Aiming at the problem of noise and interference in the weighing signal of the current belt conveyor dynamic weighing system,an improved adaptive noise cancellation(IANC)weighing signal processing method was proposed in this work.A mathematical model for the dynamic response process of the belt conveyor dynamic weighing system was established.We de-signed a combination of Kalman filter and least mean square(KF-LMS)algorithm to improve the performance of ANC noise cancellation.In the experimental stage,the proposed method was tested through simulation and an experimental platform.The results show that the proposed KF-LMS method outperforms algorithms such as LMS,NLMS,and SLMS in the dynamic weighing signal processing of belt conveyor systems,showcasing excellent performance,higher reliability,and weighing preci-sion.The experimental results have verified the effectiveness and practicality of the proposed method,and the method has broad application prospects.
belt conveyordynamic weighing systemsignal processingadaptive noise cancellationKalman filteringmini-mum mean square
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