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Research on Dynamic Measurement Method of Flow Rate in Tea Processing

机译:茶叶加工中流量动态测量方法的研究

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摘要

Tea flow rate is a key indicator in tea production and processing. Due to the small real−time flow of tea leaves on the production line, the noise caused by the transmission system is greater than or close to the real signal of tea leaves. This issue may affect the dynamic measurement accuracy of tea flow. Therefore, a variational mode decomposition combined with a wavelet threshold (VMD−WT) denoising method is proposed to improve the accuracy of tea flow measurement. The denoising method of the tea flow signal based on VMD−WT is established, and the results are compared with WT, VMD, empirical mode decomposition (EMD), and empirical mode decomposition combined with wavelet threshold (EMD−WT). In addition, the dynamic measurement of different tea flow in tea processing is carried out. The result shows that the main noise of tea flow measurement comes from mechanical vibration. The VMD−WT method can effectively remove the noise in the tea dynamic weighing signal, and the denoising performance is better than WT, VMD, EMD, and EMD−WT methods. The average cumulative measurement accuracy of the tea flow signal based on the VMD−WT algorithm is 0.88%, which is 55% higher than that before denoising. This study provides an effective method for dynamic and accurate measurement of tea flow and offers technical support for digital control of the tea processing.
机译:茶叶流速是茶叶生产和加工中的关键指标。由于生产线上茶叶的实时流量较小,传输系统引起的噪声大于或接近茶叶的真实信号。此问题可能会影响茶叶流的动态测量精度。因此,提出了一种变分模态分解结合小波阈值 (VMD−WT) 的去噪方法,以提高茶叶流测量的精度。建立了基于VMD−WT的茶流信号去噪方法,并将结果与WT、VMD、经验模态分解(EMD)和经验模态分解结合小波阈值(EMD−WT)进行了比较。此外,还对茶叶加工中不同的茶叶流量进行了动态测量。结果表明,茶叶流量测量的主要噪声来自机械振动。VMD−WT 方法可以有效去除茶叶动态称量信号中的噪声,去噪性能优于 WT、VMD、EMD 和 EMD−WT 方法。基于 VMD−WT 算法的茶流信号平均累积测量精度为 0.88%,比去噪前提高了 55%。本研究为茶叶流动的动态准确测量提供了一种有效的方法,为茶叶加工的数字化控制提供了技术支持。

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