Employs UAS With Infrared Technology To Capture Images Of Solar Panels To Be Analyzed By AI

Tokyo, Japan-based V-Cube Robotics will soon begin offering a solar power plant inspection package service that uses UAS called ‘SOLAR CHECK.’

The UAS, which are equipped with infrared thermography cameras, autonomously fly around a facility, imaging the solar panels. These images are then analyzed using artificial intelligence, which, according to VStar, dramatically improves the efficiency of inspection, making it possible to discover discrepancies and report on the results of an inspection in a short amount of time.

To match the positions of the plant’s solar panels, the SOLAR CHECK UAS’ flight path is set ahead of time. It then autonomously flies along that path, and uses its on-board thermography camera to image the panels from the air.

The saved panel images are uploaded into the cloud, and using deep learning, they are automatically analyzed to find discrepancies such as hotspots.

A report on the results of the inspection is created by the service, and it shows the abnormal panels and where the discrepancy occurred.

Some of the initial preparations for the service include configuring the system as required for operation, test imaging and training, which is performed by V-cube Robotics after a customer applies for the service. V-cube says that from the second inspection on, the customer can perform the inspections themselves with an easy operation.

SOLAR CHECK uses “advanced image analysis technology” that employs deep learning and other forms of AI offered by a company called Datasection Inc., to provide extremely accurate analyses. One of the strengths of Datasection, according to V-cube, is its technology that processes large volumes of images instantly utilizing MLFlow, which is a platform that Datasection developed independently.

The company used this technology in the development of an algorithm tailored to detect discrepancies in solar panels specifically for the SOLAR CHECK service. It then developed this into a framework that “improves detection accuracy using an AI algorithm that gets smarter the more it runs,” and that includes several deep networks, in addition to existing image processing.

(Image provided with V-cube Robotics news release)

FMI: www.vcube.com