Abstract: The operation status of the power distribution equipment in the pump station is directly related to the stability and economy of the power supply system. However, traditional maintenance techniques have defect such as fixed maintenance cycles, insufficient fault prediction capabilities, and low efficiency in allocating maintenance resources. Therefore, an intelligent maintenance technology based on adaptive particle swarm optimization algorithm is proposed. This article uses a multidimensional sensor network to collect real-time operating parameters such as voltage and current, and introduces an inertia weight dynamic adjustment strategy and a learning adaptive update mechanism in the traditional particle swarm optimization algorithm, effectively improving the global search ability and convergence accuracy. The experimental results show that the proposed technology can reduces equipment failure rate and maintenance costs, which provides an important foundation for intelligent operation and maintenance management of water pump station distribution systems.