Fault location and isolation in the power distribution system are the core links to ensure the reliability of power supply, and the traditional methods have problems such as insufficient positioning accuracy and slow isolation response in complex power grid structures. The introduction of intelligent sensing technology provides a new path for distribution network fault handling, and with the help of multi-source sensor data collection and deep integration of machine learning algorithms, the goal of accurate capture and rapid research and judgment of fault signals can be achieved. At the fault location level, a technical system including signal feature extraction, type recognition, multi-terminal fusion and single-phase grounding high-sensitivity positioning is constructed, and at the isolation level, adaptive criterion and distributed collaborative isolation scheme are proposed, which combines network reconstruction and multi-level protection coordination to improve power supply reliability. The simulation results show that the proposed method has better positioning accuracy and isolation speed, and has strong practical value in engineering applications.
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