Study of on-line monitoring and fault diagnosis system for a naval transformer

  Objectives  The ship transformer is the key to the safe, stable and reliable operation of a large ship integrated power system, so serious faults must be avoided.

  Methods  Based on the Advanced RISC Machine(ARM), a transformer status online monitoring and fault diagnosis system was constructed. Anti-interference and data processing are used to ensure real-time, reliable and accurate acquisition of operational status data. Diagnostic system data analysis is used to accurately predict and identify fault types and trigger alarm, thereby ensuring timely action of the system to prevent faults from spread. Screen display is used to improve the dispatcher's ability to accurately grasp the operating status of the transformer.

  Results  Multisim simulation modeling analysis and field operation test results show that the system can accurately collect the operating status data of the transformer, determine the type of transformer fault, and feedback it to the centralized control center in real time to formulate a reasonable control strategy and planning and scheduling scheme, thereby ensuring the normal operation of the ship integrated power system.

  Conclusions  The research results can provide reference for on-line monitoring and fault diagnosis of ship transformers.