From Periodic Inspections to Continuous Monitoring in Nuclear & Hydro Power with Eagle Edge LoRa

Location: Europe
Application: Nuclear & Hydro Power

EXECUTIVE SUMMARY

A major energy provider needed to improve the availability and reliability of its nuclear power plants and hydro power stations by replacing periodic, subcontracted data collection with an automatic wireless monitoring system. Due to remote locations and strict regulations, LoRaWAN was the only authorized wireless protocol.

Acoem deployed Eagle Edge LoRa vibration sensors and Edge LoRa gateways in nuclear environments as well as in isolated hydro power plants, with the potential to scale these solutions for large-scale deployment.

The Challenge

The customer relied on subcontracted periodic vibration measurements, which resulted in:

Delayed fault detection and reactive maintenance actions.
High operational costs from manual inspections and site interventions.
Limited visibility over remote or hard-to-access assets.

In nuclear plants, the high cost of wired systems limited monitoring to a few key machines. In hydro facilities, remote locations made site access complex and expensive.
This approach increased operational costs and left maintenance teams with a fragmented view of asset health, a situation incompatible with the reliability targets of modern energy production.

The Solution

Technology Implemented

Eagle Edge Lora wireless vibration sensors
LoRaWan gateway for secure data transmission
Triaxial Vibration and temperature monitoring
Automated diagnostics delivered from the sensor
Remote access to real-time machine health data

Acoem was selected for its proven LoRaWAN compliance, validated performance in demanding environments, scalable architecture, and long-standing expertise in vibration-based condition monitoring for the energy sector.

The Results

Switching from periodic inspections to continuous monitoring has already transformed maintenance operations. Early fault detection now prevents costly unplanned shutdowns, while maintenance schedules are optimized based on actual equipment condition rather than fixed intervals.

This shift has also improved the reliability of measurement data, enabling better planning and coordination of maintenance activities. The successful pilot phase confirmed the system’s robustness and scalability, leading to progressive deployment across multiple nuclear and hydro sites.

The Impact

The project marks a key step toward predictive maintenance 4.0 in the energy sector. Continuous data acquisition and automated diagnostics have set a new benchmark for operational excellence, combining safety, performance, and cost efficiency.
Building on this success, Acoem and its partner plan to extend the Eagle Edge LoRa solution to other critical energy assets and integrate it with next-generation AI algorithms such as Accurex AI for fully automated anomaly detection.