基于高光谱成像技术和 IPCA-SVM 模型的硅橡胶绝缘子老化状态像素级评估方法

IF 7.5 1区计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Expert Systems with Applications Pub Date : 2024-11-17 DOI:10.1016/j.eswa.2024.125788

Yihan Fan , Yujun Guo, Yang Liu , Song Xiao , Junbo Zhou, Guoqiang Gao , Xueqin Zhang , Guangning Wu

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引用次数: 0

摘要

酸性环境是导致硅橡胶绝缘子老化和失效的一个重要因素。如何有效评估绝缘子的老化状态，防止输电事故的发生，一直是电网亟待解决的关键问题。因此，本文采用了高光谱成像（HSI）技术，分别在可见光和近红外区域捕捉硅橡胶在六种老化状态下的光谱线数据。为了减少数据冗余，本文引入了遗传算法（GA）和波段加权来改进传统的主成分分析法（PCA），并使用总体准确率（OA）和 Kappa 与其他 12 种特征提取或降维方法进行了性能比较。提出的改进型主成分分析-支持向量机（IPCA-SVM）模型有效地减少了高光谱原始数据中的无关信息，准确率超过 93%，与所有波段数据相比，OA 提高了 8.26%。最后，IPCA-SVM 模型被用于硅橡胶绝缘子表面老化状态的像素级评估，证明了其可靠性。该方法有效地表征了复合绝缘子的老化状态，为电网的安全稳定运行提供了坚实的基础。

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A pixel-level assessment method of the aging status of silicone rubber insulators based on hyperspectral imaging technology and IPCA-SVM model

Acidic environments are a significant factor in the aging and failure of silicone rubber insulators. Addressing the effective assessment of insulators’ aging state to prevent power transmission accidents has been a critical and urgent issue for the power grid. Therefore, hyperspectral imaging (HSI) technology was employed in this paper, capturing spectral line data of silicone rubber in six aging states in both visible and near-infrared regions, respectively. To reduce data redundancy, genetic algorithm (GA) and band weighting were introduced to improve traditional principal component analysis (PCA), with performance compared using overall accuracy (OA) and Kappa, against 12 other feature extraction or dimensionality reduction methods. The improved principal component analysis − support vector machine (IPCA-SVM) model proposed effectively minimizes irrelevant information in hyperspectral original data, exceeding 93% accuracy and improving OA by 8.26% compared to all bands data. Finally, the IPCA-SVM model was used for pixel-level assessment of the surface aging state of silicone rubber insulators, demonstrating its reliability. This method effectively characterizes the aging state of composite insulators, providing a solid foundation for the safe and stable operation of power grids.

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来源期刊

Expert Systems with Applications 工程技术-工程：电子与电气

CiteScore

13.80

自引率

10.60%

发文量

2045

审稿时长

8.7 months

期刊介绍： Expert Systems With Applications is an international journal dedicated to the exchange of information on expert and intelligent systems used globally in industry, government, and universities. The journal emphasizes original papers covering the design, development, testing, implementation, and management of these systems, offering practical guidelines. It spans various sectors such as finance, engineering, marketing, law, project management, information management, medicine, and more. The journal also welcomes papers on multi-agent systems, knowledge management, neural networks, knowledge discovery, data mining, and other related areas, excluding applications to military/defense systems.