The large-scale integration of renewable distributed generations into the distribution network is a necessary process to achieve carbon neutrality, but the potential stability hazards brought in need to be treated seriously. It is of great significance to effectively screen the weak links in the low-voltage distribution network via data analysis, and carry out targeted optimization and improvement. Therefore, a health status assessment method for low-voltage distribution network based on edge computing is proposed in this paper. In the method, 5+1 indices are selected for the assessment of low-voltage distribution network, which are performed normalization processing before application. The subjective and objective weights of each evaluation index are obtained by the order relation analysis method and the variation coefficient method which simulate the expert knowledge respectively. The subjective weight and objective weight are optimized by Lagrange optimal multiplier method, and the comprehensive weight and evaluation function of each index are obtained. The health status of low-voltage distribution network is reasonably quantified the value of evaluation function. The proposed method is performed by edge computing in the smart terminals on site to relieve computing pressure for communication and main station systems. The evolution and analysis results of 8 low-voltage transformer stations in Zibo City prove the effectiveness and objectiveness of the proposed method, which can be implemented in practical power systems.