Reliability Improvement Technology of Insulation Monitoring and Grounding System for Electrical Equipment in Water Plants

Traditional technologies in water plants can hardly meet the high-reliability requirements of smart water plants. Combining the Internet of Things, edge computing and new grounding material technologies, this paper proposes a comprehensive improvement scheme integrating multi-source sensing, intelligent diagnosis and adaptive grounding optimization. An insulation prediction model based on the pulse current method and long short-term memory neural network is constructed. The optimized design combining composite grounding bodies with deep well grounding and soil resistivity dynamic adjustment technology is adopted. The effectiveness of the scheme is verified by a control experiment. Experimental results show that the scheme increases the insulation defect detection rate from 73.3% to 93.3%, restricts the grounding resistance fluctuation from ±14.1% to within ±5.0%, reduces the equipment failure rate from 22.7% to 4.5%, and cuts the operation and maintenance cost by 30%. The technical scheme solves the pain points of traditional monitoring and grounding systems, and provides reliable technical support for the safe and stable operation of electrical systems in water plants.