4种除草剂对小麦田雀麦(Bromus japonicus)的田间药效试验

Joint Algorithm of Variational Mode Decomposition with Correlation Coefficient Method and its Application in Pipeline Leakage Detection

以北京市大兴区常用冬小麦品种农大211为试验材料,在春季以30 g/L甲基二磺隆、70%氟唑磺隆、10%精噁唑禾草灵和40%三甲苯草酮为试验药剂,对冬小麦麦田杂草雀麦的防治效果进行研究。结果表明:30 g/L甲基二磺隆20 m L/667 m^2、70%氟唑磺隆2 g/667 m^2和10%精噁唑禾草灵水乳剂10 g/667 m^2在药后28 d鲜质量防效达到了90%以上,防治后小麦与对照相比分别增产35.82%、33.69%和59.57%,对千粒质量影响差异显著(P<0.05),对穗粒数没有影响。本次试验中40%三甲苯草酮水分散粒剂40 g/667 m^2防治雀麦与对照相比效果不明显。

Aiming at the problem that it is difficult to select preset scale K and effective IMF component after decomposition in variational mode decomposition algorithm,a new method combined VMD and correlated coefficient is proposed and to be used to detect pipeline leakage signal in this paper. Firstly,the original signal is decomposed into intrinsic mode functions with different time scales. Then,the correlation coefficient method is used to select the preset scale K and the IMF component containing the most abundant fault information. Finally,the signal reconstruction of the selected effective IMF component is implemented. It is shown by the experiments that preset scale K can be chosen precisely and effective IMF component can be obtained through combined algorithm of VMD and correlated coefficient so that the accuracy of pipeline leak detection can be improved.