Application of Internet of Things Technology in Condition Monitoring and Maintenance of Electrical Equipment

In this study, when discussing the application of Internet of Things technology in electrical equipment condition monitoring and maintenance, machine learning algorithm is mainly introduced to improve the accuracy and efficiency of monitoring. Specifically, the study selected two excellent classifiers - Light Gradient Boosting Machine (LightGBM) and Support Vector Machines (SVM). Using a certain amount of electrical equipment operating data, these classifiers were trained to generate ROC curves that effectively evaluated their performance in distinguishing between normal and faulty operating states of electrical lines. In order to meet the actual operational requirements of the electrical monitoring system, the research also integrates NB-IoT technology for data communication. The introduction of NB-IoT not only enhances the reliability of data transmission, but also optimizes the operation efficiency of the system in the wide area network, making remote monitoring and maintenance possible. The application of this technology significantly improves the overall performance and reliability of the electrical equipment monitoring system, and provides an efficient and economical solution for the condition monitoring and maintenance of electrical equipment.