独立分量分析在输电塔防盗监测系统中的应用

Application of ICA on Transmission Tower Theftproof Monitoring System

在电磁干扰下检测出因不良企图引起的铁塔振动信号,防止塔材被盗事件的发生,对保障电网安全运行有着重要意义。文中介绍了一种基于独立分量分析(ICA)的输电塔防盗监测系统。ICA方法能够在没有源信号和传输通道参数先验知识的情况下,按照统计独立的原则,通过选择判据和优化算法将信号分解成若干独立的源成分,适合于该系统中非平稳振动信号的提取。系统在硬件方面采取了相应的抗干扰措施,有效降低了电磁等干扰。采用负熵的FastICA方法和探查性投影追踪信号处理算法快速地对铁塔盗窃中产生的振动信号进行了较好的提取和分离,结合自适应阈值脉冲提取算法,有效地提取振动脉冲成分,降低了噪声干扰。实验结果表明该系统能够较好地检测出铁塔盗窃中产生的振动信号。

An anti-theft monitoring system for transmission tower based on Independent Component Analysis （ICA） is presented to examine the vibration signals hidden in the electromagnetic interference signal to prevent the high incidences of transmission tower from being stolen. It is of great importance to guarantee the security of power systems operation. The monitoring system using the ICA algorithm is to find underlying factors or components from multivariate statistical data with the help of the dimension reduction methods available to extract the non-stationary vibration signals. The anti interference measures are adopted in the hardware of the system so as to reduce the electromagnetic interference effectively. Moreover, the vibration signals are extracted and separated successfully by use of the Negentropy based FastICA method and the Exploratory Projection Pursuit （EPP） method. The vibration pulse is also extracted efficaciously by using the adaptive threshold pulse extraction method to suppress the interference signals to a certain extent. Tests results on the spot demonstrate the system is effective in checking the vibration signals.