Autonomous, self-driving robot equipped with multi-camera-system, 3D-microphone-array and LIDAR-laserscanning revolutionizes transformer monitoring
Transformers are central components of the energy infrastructure, hence their availability is an integral factor of security of supply. Continuous monitoring and predictive maintenance are therefore an important factor in increasing the longevity of these infrastructure elements. Although transformers are extremely durable and stable, undetected changes can lead to unplanned outages, therefore high repair costs, and long downtimes.
For this reason, a multi-sensor platform for the lifecycle-monitoring of transformers was designed and implemented in the X-AMINOR project. Models for inspection, diagnosis and condition assessment were developed based on the collected sensor data. This continuous monitoring enables the detection of rare and unusual changes of the transformer, which cannot currently be identified using standard methods and sensors for transformer diagnostics.
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