基于智能手机高光谱相机确定硅橡胶绝缘子的老化状态

Lincong Chen, Xiaolin Chen, Xinran Li, Xiaotao Fu, Ruien Zhang, Tianci Wang
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引用次数: 0

摘要

在电力工业中,硅橡胶复合绝缘子应用广泛。本文介绍了一套现场判断硅橡胶复合绝缘子老化程度的方法,包括我们的手持式小型低成本高光谱相机和分类算法。高光谱相机具有结构紧凑、工作性能稳定、光谱探测范围宽(400nm-1000nm)等优点。将高光谱相机连接到智能移动终端后,我们还通过自己开发的APP,完成了光谱数据的可视化,可以将硅橡胶复合绝缘子样品的实时光谱显示在智能终端的屏幕上。此外,我们基于支持向量机(SVM)、KNN(K-NearestNeighbor)和决策树三种算法建立了复合绝缘子老化预测模型。结果表明,支持向量机模型效果最好。该模型的预测精度为96.09%。说明该模型对复合绝缘子的老化程度预测具有较高的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Determine the aging status of silicone rubber insulators base on smartphone hyperspectral cameras
In the power industry, silicone rubber composite insulators are widely used. This article introduces a set of methods for judging the aging degree of silicone rubber composite insulators on site, including our handheld compact and low-cost hyperspectral camera and classification algorithm. The hyperspectral camera has the advantages of compactness, stable working performance, and Broad spectral detection range (400nm-1000nm). After connecting the hyperspectral camera to the smart mobile terminal,We also through the APP we developed, which completes the visualization of spectral data, can display the real-time spectral of the silicone rubber composite insulator sample on the screen of the smart terminal. In addition, we build a composite insulator aging prediction model based on the three algorithms of SVM(support vector machines), KNN(K-NearestNeighbor) and decision tree. The results show that the SVM model has the best effect. And the prediction accuracy of this model is 96.09%. it means that the model has high feasibility for predicting the aging degree of composite insulators.
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