LG Uplus Analyzes Industrial Sites with AI and Big Data... Predicts Timing of Anomalies

Diagnosing Underground Geothermal Pipeline Leaks with Subsurface Sensors... Detecting Gas Leaks via Ultrasonic Measurement

LG Uplus employees examining a geothermal measurement device used in the hot water pipe anomaly diagnosis solution. Photo by LG Uplus

[Asia Economy Reporter Oh Su-yeon] LG Uplus announced on the 17th that it has developed predictive maintenance and anomaly diagnosis solutions such as 'Hot Water Pipe Anomaly Diagnosis,' 'Gas Pipe Anomaly Diagnosis,' and 'Trend Anomaly Prediction' by analyzing various information from industrial sites using artificial intelligence and big data technologies to innovate the business-to-business (B2B) customer experience.

The Hot Water Pipe Anomaly Diagnosis solution installs geothermal measurement devices on the ground surface around the heat transport pipes and periodically measures vibration, geothermal heat, and tilt. If leakage occurs in the heat transport pipe due to excavation work or aging, it immediately notifies the operator.

This solution enhances the accuracy of algorithms diagnosing rupture, impact, and sensor failure by utilizing external information such as the environment around the buried pipes, depth, and temperature, reflecting seasonal underground temperature changes. Power companies supplying hot water can use this to prevent accidents.

Additionally, LG Uplus developed a smart factory equipment predictive maintenance solution based on artificial intelligence (AI) and big data-powered intelligent Internet of Things (AIoT) technology. The 'Gas Pipe Anomaly Diagnosis Solution' detects gas leaks by measuring the intensity of ultrasonic waves in the 30~40 kHz band generated when gas is released. It enables early detection of micro-leaks in gas pipes at refineries and chemical plants operating numerous pipelines.

By analyzing data collected from smart factory sensors as time series and using the 'Trend Anomaly Prediction Algorithm' to analyze upward or downward trends, it is possible to predict the occurrence of anomalies in advance even before reaching critical thresholds.

Furthermore, LG Uplus developed a predictive maintenance solution using AI and big data to monitor the status of machine tools and detect anomalies. Having developed this AI and big data-based anomaly diagnosis technology, LG Uplus plans to continue discovering and developing AIoT solutions that respond to various hazardous environments in industrial sites.

Jeon Young-seo, CTO and Head of Corporate Service Development Lab at LG Uplus, said, "We are striving to create new customer value from data collected from various IoT sensors and equipment," adding, "In the future, we will secure not only anomaly diagnosis technology but also predictive maintenance and forecasting technologies in various industrial fields such as smart factories and industrial IoT to provide customers with more valuable information and services."

This content was produced with the assistance of AI translation services.