Study On Poplar Water Stress Acoustic Emission Detection System

Water stress is the most common environmental threat that affects plant growth. In plants, there is a physiological regulatory mechanism to adapt to soil water stress in order to survive in a bad growth environment. This provides the signal and basis for the detecting of water deficit. Researching the poplar water stress acoustic emission signal (hereafter referred to as "AE signal") is of great significance to irrigate poplar reasonably. In order to lay a foundation for getting poplar water deficit information accurately, detecting water stress automatically and irrigating reasonably, the purpose of this study is to establish a set of poplar water stress AE signal processing and analysis method based on wavelet analysis, and completely record original AE signal by developing the poplar water stress AE signal detection system, then preliminarily studies poplar water stress AE signal generation rhythm.Based on theoretical research, this study proposes a signal-noise separation method for poplar water stress AE signal based on wavelet analysis. Through researching different de-noising methods and comparing corresponding signal noise ratio (SNR), the study analyzes a more suitable de-noising method under the same condition for poplar water stress AE signal. Secondly, the wavelet feature spectrum analysis method is used to make a comparative study between poplar and broussonetia. On this basis, the study confirms energy distribution situations in each frequency band for their water stress AE signals by using the wavelet energy spectrum coefficient analysis method. The results show that both the methods can effectively extract the features of AE signal, which is an effective method of analyzing poplar water stress AE signal. In addition, with the functions such as signal noise reduction and feature extraction, a poplar water stress AE signal processing platform is constructed by MATLAB and LabVIEW, together with a hardware system, to make the water stress AE signal process easier, more convenient, and more integrated. Moreover, AE signal parameters extraction platform developed by Visual Basic makes AE signal parametric analysis easier. Finally, the hybrid variety of black poplar and cathay poplar are used to test and analyze the AE signal. The experimental results show that poplar water stress AE signal is relatively steady in the daily variation mode. Furthermore, it has almost the same water regime assessment as the traditional water stress detecting index. It can be concluded it is reasonable to regard AE signal as a detecting index for poplar water stress.In this study, acoustic emission detection and signal processing techniques are applied to the specific research of poplar water stress. It provides a new index for studying poplar drought-resistant, which has significant and far-reaching importance for how to breed quality trees under severe water shortage condition and save more freshwater resources.