Fault diagnosis plays an important role in smart energy meters, but there is a problem of inaccurate fault location. The traditional particle swarm algorithm cannot solve the fault diagnosis problem in the smart energy meter, and the effect is not ideal. With the rapid development of modern power grid technology, the stable and reliable operation of smart energy meters, as an important part of the power system, is essential to ensure the continuity and efficiency of power supply. However, due to environmental factors, aging materials, and external forces, smart energy meters may have various faults, which may lead to power supply interruptions and even safety accidents if not detected and repaired in time. In this context, the use of High-Performance Liquid Chromatography (HPLC) for fault diagnosis of smart energy meters has become an effective means to ensure the safety of the power grid and improve the quality of power services.