摘要
传统广播电视发射机故障诊断方法的信号幅值变化较小,诊断准确率低.为解决该问题,文中提出了一种基于VMD与小波变换的方法来提取信号信息,并通过排列熵来量化VMD分解后的信号的噪声水平,应用RET线性时频分布方法进行故障诊断.实验结果表明,在检测时间达到4 s时,信号的时域波形复杂,整体幅值显著增加,幅值在[-10,10]之间,从而识别出此处为故障;当信噪比在[-2,6]范围内时,不同样本的诊断准确率范围为98%~99%,能更精确地诊断出发射机中的故障.
The traditional fault diagnosis methods for broadcasting and television transmitters have small changes in signal amplitude and low diagnostic accuracy.In order to solve this problem,a method based on VMD and wavelet transform is proposed to extract signal information,and the noise level of the decomposed signal is quantified by permutation entropy.The experimental results show that when the detection time reaches 4s,the time-domain waveform of the signal is complex,the overall amplitude increases significantly,and the amplitude is between[-10,10],so that the fault is identified here;when the signal to noise ratio is within the range of[-2,6],the diagnostic accuracy of different samples is between 98%and 99%,which can more accurately diagnose the fault in the transmitter.
作者
卢炜
LU Wei(Ganzhou,Jiangxi Province,852 Units,Ganzhou,Jiangxi 341000,China)
出处
《移动信息》
2025年第2期82-84,共3页
Mobile Information
关键词
VMD
小波变换
广播电视
发射机
VMD
Wavelet transform
Radio and television
Transmitter
