Research on De-noising Method of Plant Electric Signal Based on EMD and Wavelet Threshold

被引:0
|
作者
Liu, Zilu [1 ]
Bing, Zhigang [1 ]
Tian, Liguo [1 ]
Li, Meng [1 ]
Sun, Yu [1 ]
Wang, Yusong [1 ]
机构
[1] Tianjin Univ Technol & Educ, Tianjin Key Lab Informat Sensing & Intelligent Co, Tianjin, Peoples R China
基金
中国国家自然科学基金;
关键词
empirical mode decomposition; plant electrical signal; improved wavelet threshold function;
D O I
10.1109/ICCAR52225.2021.9463480
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Plant electrical signal is a complex non-stationary signal, which can reflect the growth state of plants and the changes in the surrounding environment. There will be a lot of noise in the acquisition process. The Kalman filter and wavelet domain de-noising used in the current research have certain limitations. In order to solve this problem, this article takes the Liliaceae herb Aloe as the research object and adopts self-built signal acquisition. The system extracts the electrical signal of aloe, and combines the empirical mode decomposition (EMD) and improved wavelet threshold function to de-noise the collected signal. The results show that the method can effectively separate the interference signals in the aloe electrical signal, use the improved wavelet threshold method to remove the interference signals, and retain the effective information in the aloe electrical signals as much as possible, which has certainly practical significance for the analysis and feature extraction of the plant electrical signals, lay the foundation for the next step of exploring the relationship between plant electrical signals and growth status.
引用
收藏
页码:271 / 274
页数:4
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