摘要
介绍了高压输电线自动巡检机器人实时在线断股检测与诊断系统。根据高压输电线断股引起的辐射场变化和机器人运行环境状况,选择合适的传感器,并对传感器信号调理和采集电路进行高可靠性设计。描述了检测信号分析过程。针对断股信号的非平稳性质和小波基的时频特征,选用db4小波基对断股信号进行了6层小波分解。通过引入小波能量熵的概念,较好地解决了单纯采用小波变换带来的分解信息量大、故障特征值数目多、提取需要人工干预、难以实现在线检测和诊断等问题,使其能够利用较小规模的反向传播(BP)网络就可实现对铝绞导线断股损伤的在线精确诊断。系统实验进一步表明了该断股检测和诊断系统的可行性及有效性。
A real-time on-line broken strand detection and diagnosis system is introduced for high-voltage transmission line automatic inspection robots. Based on the radiation field changes caused by the transmission line strand breaking and the operating environments of the robot, an appropriate sensor is selected with fine tuned sensor signals and highly reliable collecting circuits. Then, the signal analysis process is described in detail. Given the instable nature of broken strand signal and the time-frequency characteristics of wavelet base, the broken signal is decomposed into six level wavelets using db4 wavelet base. By introducing the concept of entropy energy wavelet, the problems caused by simply adopting wavelet transform, such as over-abundant information and eigenvalues, and hard to inspect online are solved. A small BP network can realize on-line precised diagnosis on the strand breaking problem. Experimental results show the feasibility and effectiveness of the proposed system.
出处
《电力系统自动化》
EI
CSCD
北大核心
2008年第14期77-81,107,共6页
Automation of Electric Power Systems
基金
国家高技术研究发展计划(863计划)资助项目(2002AA420110-4)~~
关键词
高压输电线
小波能量熵
断股在线检测
high voltage power transmission line
wavelet energy entropy
on-line detection of broken strand
作者简介
周风余（1969-），男，通信作者，博士，副教授，主要研究方向：特种机器人的研究开发和利用、检测技术、计算机控制系统等。E-mail：zhoufengyu@sdu．edu．cn
李贻斌（1960-），男，教授，博士生导师，主要研究方向：机器人技术、智能控制等。
李峰（1982-），男，硕士研究生，主要研究方向：计算机控制系统。
