基于机器视觉的高压电缆故障自动检测方法
Automatic Detection Method for High-Voltage Cable Fault Based on Machine Vision
张曦 1周光尧 1董静1
作者信息
- 1. 济南轨道交通集团有限公司,山东济南 250000
- 折叠
摘要
现有方法易受图形特征参数变化的影响,检测的故障IMF分量相关系数与实际系数不一致.为解决该问题,基于机器视觉设计了一种全新的高压电缆故障自动检测方法.该方法利用机器视觉生成高压电缆故障自动检测中心,提取高压电缆故障自动检测特征参数,从而完成高压电缆故障的自动检测.结果表明,设计方法检测的故障IMF分量相关系数与实际较为拟合,故障自动检测准确率均高于94.1%,证明该方法检测效果较好、准确性高.
Abstract
The existing methods are easily affected by changes in graphic feature parameters,and the correlation coefficients of the detected fault IMF components are inconsistent with the actual coefficients.To solve this problem,a new automatic detection method for high-voltage cable faults is designed based on machine vision.This method utilizes machine vision to generate an automatic detection center for high-voltage cable faults,extracts feature parameters for automatic detection of high-voltage cable faults,and thus completes automatic detection of high-voltage cable faults.The results show that the correlation coefficient of the IMF component detected by the design method fits well with the actual situation,and the accuracy of automatic fault detection is higher than 94.1%,proving that the design method has good detection effect and high accuracy.
关键词
机器视觉/高压电缆/故障/自动检测Key words
machine vision/high-voltage cable/fault/automatic detection引用本文复制引用
出版年
2024
NETL
NSTL
万方数据