The invention discloses a low-
voltage power grid residual current monitoring and
early warning system and method based on an
intelligent network, and belongs to the field of
safety monitoring. The method comprises the steps that a residual
current sensor is installed to monitor current change, and current fluctuation is intelligently analyzed; establishing a
machine learning model based on historical data, and training normal fluctuation characteristics of the residual current; the sudden change of the current is judged through a
time sequence anomaly detection algorithm, and a new
data optimization model is regularly utilized; the residual current fluctuation is graded, when the current deviation reaches a threshold value, the
system automatically sends a notification of the corresponding grade according to the early warning grade, the position of a fault node is automatically judged through the geographic position of a sensor and a
network topology structure, and a fault section is judged in combination with
power grid topology data; after early warning is triggered, the
system performs
statistical analysis on abnormal current data, and the
system automatically optimizes the acquisition frequency and the early warning threshold according to the real-time current data and the
fault probability. According to the invention, through monitoring and intelligent early warning, the safety and response speed of the
power grid are significantly improved.