基于图像处理的变电站中隔离开关的状态研究

State Evaluation of Isolating Switch in Transformer Substation Based on Image Processing

摘要:

随着图像处理技术的不断发展,本文利用图像处理技术分析变电站中隔离开关的状态。蚁群算法(Ant Colony Algorithm,ACA)使用的广泛性,很多学者将其应用到图像处理中。本文将蚁群算法应用于变电站设备区域图像分割中,从某个或某些像素点出发,提取出变电站的隔离开关信息,然后对其进一步的图像处理,分析隔离开关的状态。但是,蚁群算法在运算过程中,易出现过早收敛于局部最优解及运算时间过长的缺点。为了使蚁群算法收敛于全局最优解及加快收敛速度,本文针对传统的蚁群算法模型对其信息浓度更新规则改进及参数的改进。通过仿真对比分析改进后的蚁群算法对于图像分割效果更好。

Abstract:

With the development of image processing technology, this article uses image processing technology analysis isolating switch in substation. The image processing method based on Ant Colony Algorithm is a new type of image processing technology. The ant colony algorithm is applied to image segmentation of substation equipment area, from one or some of the pixels, extracted isolating switch information of substation, then isolating switch for image processing, analysis the state of isolation switch. However, the Ant Colony Algorithm in the process of operation, easy prematurely convergence to local optimal solution, and its computation time is too long. In order to solve the shortcomings of Ant Colony Algorithm, This paper improves the traditional Ant Colony Algorithm model to improve update rules of information concentrations and parameter. The improved Ant Colony Algorithm is better for image segmentation by comparing simulation analysis.