Fault Diagnosis Method for Temperature Rise of Tulip Contact in High Voltage Switchgear Based on Digital Twin Technology

The temperature rise fault of tulip contacts in high-voltage switchgear significantly compromise the electrical and insulation performance of power equipment, leading to potential safety hazards. Thus, it is crucial to evaluate the operating state of tulip contacts and visualize their three-dimensional field information in real time to ensure the stable operation of power system. Firstly, the conduction bridge model of tulip contact is simulated using finite element simulation software. A dimensionality reduction model is then constructed to simulate temperature rise under various operating conditions by combining data dimensionality reduction techniques with the K-nearest neighbor algorithm. Additionally, an RBF surrogate model for tulip contacts is built based on multiple sets of dimensionality reduction data. Secondly, the time-domain characteristics of temperature rise and discharge information during the operation of the tulip contact are integrated using an adaptive fuzzy neural network (ANFIS). This fusion process aims to obtain the state indices and level that accurately characterize the operating status of the contact, enabling fault diagnosis. Finally, to collect the status information of tulip contact, a data acquisition system is employed. By combining the Surrogate model and fault evaluation algorithm, three-dimensional field cloud image rendering and fault diagnosis of contacts are carried out to realize the online simulation of virtual contact model and the construction of digital twin system. The findings of this study provide valuable insights for the condition monitoring and maintenance of tulip contact in high-voltage switchgear. They can serve as a useful reference for ensuring the safe and efficient operation of power equipment.