Korea Southern Power is pushing to establish an artificial intelligence (AI)-based predictive diagnosis system for civil engineering facilities at its power plants.
Korea Southern Power announced on the 2nd that it held a Workshop on Establishing an AI-Based Predictive Diagnosis System for Civil Engineering Facilities at its Busan headquarters on the 1st, with company-wide facility maintenance personnel and representatives of specialized safety diagnosis firms in attendance.
Companies specializing in detailed safety diagnosis, AI video analysis, drones and LiDAR, artificial intelligence of things (AIoT)-based solutions, and smart measurement participated in the workshop and explored ways to apply smart safety diagnosis technologies in the field.
The workshop also featured key programs, including training to strengthen expertise in facility safety inspections; the sharing of AI- and IoT-based inspection technologies and application cases; the detection of abnormal signs using drone and video data; and an introduction to an intelligent risk-alert system based on smart sensors.
In particular, participants examined from various angles the feasibility of applying an AI-based safety management system in the field, including the early detection of abnormal signs and prediction of potential risks through real-time data analysis. They also discussed customized implementation plans for each site.
Korea Southern Power plans to rigorously verify the field applicability of each technology, pilot smart safety diagnosis technologies optimized for power plant environments at some sites by the end of this year, and consider expanding them company-wide from next year.
Seoseongjae, vice president of technology and safety at Korea Southern Power, said, “Using this workshop as an opportunity, we will continue identifying smart safety diagnosis technologies optimized for power plant facilities and complete a prevention-centered safety management system that proactively manages risk factors.”
This article has been translated by GripLabs Mingo AI.
