Rapid detection and classification of PC + ABS meter box materials based on laser-induced breakdown spectroscopy - Xia, Yunfeng; Liang, Qishuai; Xia, Zhongchen; Yang, Jie; Ye, Jiang (Frontiers in Physics, 2025)
Polycarbonate + Acrylonitrile-Butadiene-Styrene (PC + ABS) is a typical non-metallic material used for electric meter enclosures, characterized by its corrosion resistance, excellent insulation properties, and lightweight nature, making it widely applicable in power supply systems. However, prolonged exposure to outdoor environments often leads to performance degradation, which can affect normal usage. Therefore, developing rapid detection technologies to timely identify and rectify potential faults is particularly important. This not only ensures the stable operation of the power grid but also enhances the overall performance and efficiency of the power system. This study employs Laser-Induced Breakdown Spectroscopy (LIBS) technology and proposes a method for the rapid detection of PC + ABS materials by optimizing testing system parameters. The research utilizes LIBS data to classify different formulations of PC + ABS based on Support Vector Machine (SVM) and Self-Organizing Map (SOM) neural networks. The results indicate that the classification accuracy of SVM reached 98.4%, while the unsupervised classification through the SOM neural network maintained approximately 90% consistency among the three different samples. This method achieves rapid detection and classification of PC + ABS electric meter enclosures, providing new theoretical and practical foundations for enhancing the safety and stable operation of the power grid system.