基于自适应滤波器的皮带机动态称重信号处理方法  

A Signal Processing Method for Dynamic Weighing of Belt Conveyor Based on Adaptive Filter

作　　者：刘圣煌 LIU Shenghuang(National Energy Tianjin Port Co.LTD,Tianjin 300450,China)

机构地区：[1]国能(天津)港务有限责任公司,天津300450

出　　处：《人工智能科学与工程》2024年第1期51-58,共8页Journal of Southwest China Normal University(Natural Science Edition)

基　　金：河南省科技开放合作项目“豫北天敌昆虫资源开发与利用”(172106000056)。

摘　　要：针对目前皮带机动态称重系统的称重信号存在噪声或干扰的问题,提出了一种改进自适应噪声消除(IANC)的称重信号处理方法。建立了皮带机动态称重系统动态响应过程的数学模型。设计了结合卡尔曼和最小均方的算法(KF-LMS),提升了ANC噪声消除的性能。实验阶段,通过模拟和搭建实验平台对所提方法进行测试。结果表明,与LMS,NLMS,SLMS等算法相比,所提的KF-LMS算法在皮带机动态称重信号处理中具有良好性能,具备较高的可靠性和称重精度。实验结果验证了所提方法的有效性和实用性,该模型具有广阔的应用前景。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 designed 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 precision.The experimental results have verified the effectiveness and practicality of the proposed method,and the method has broad application prospects.

关 键 词：皮带机 动态称重系统 信号处理 自适应噪声消除 卡尔曼滤波 最小均方 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]