POINT - Perception Of wINd Turbines (POINT)

The POINT project aims to explore the potential of robotics and AI in the wind energy sector by employing drones as tools to perform autonomous perception on the difficult to access, internal structure of the blades of wind turbines.

Background

POINT - Perception Of wINd Turbines (POINT)

Inspection of wind turbine blades is a critical task which allows the assessment of the actual condition of wind turbines —both recurrent as part of maintenance activities and as asset assessment “snapshots” (e.g. at end-of-warranty).

Background

Visual inspection for surface imperfections in wind turbine blades from the outside is currently widely used. Today, they are primarily carried out with a camera or other inspection device, either manually or using a “sewer crawler”. This is time-consuming, uncomfortable and dangerous due to narrow, confined spaces.

The main benefit of adopting autonomous drone systems as tools that perform inspections, is the ability to acquire accurate and repeatable results. This is the first time an autonomous perception system operating inside the blades of wind turbines is proposed and, therefore, it constitutes an innovative and novel solution which will benefit the industry.

Purpose / Vision

Using a drone with autonomous navigation an high precision positioning opens up a new range of possibilities to access actual blade condition —and thereby avoiding fatal failures and optimizing operation and uptime— in a fast, simple, in-expensive and secure manner.

The project will generate new knowledge and technology for the industry that can help both OEMs and drone / robot / software / AI companies - to develop new services within the fast-growing aftermarket within the wind industry.

Milestones include:

The project will commence with the identification of the specific use case
A workshop will be held focusing on the companies, their needs and the end-users.
Development of a drone with perception sensors, and stable flight in the GNSS-denied environments
Development of software for autonomous perception of internal structures
To validate the performance of the system, both a dataset acquisition campaign and a demonstration will be performed.

Expected Results

POINT will start from TRL3 and reach TRL5, within the scope of the demonstration. The process of the project development and demonstration will benefit the industry. The end users will experience robot operation in an area that has always been man-led.

POINT will lead to a method for performing more regular, more accurate, more repeatable, faster inspections and will greatly reduce the downtime and increase the lifetime of the wind turbines making them more cost effective, benefiting the Green Transition. While allowing the easier integration of measurements and inspection results in digitalized systems and increase of the accuracy and repeatability in the inspection procedure.

The consortium will identify the main research and development directions which are required to transition to a valuable service. The project constitutes a great opportunity for SMEs as there is an abundance of market to be serviced.

POINT will be the steppingstone to a larger scale research and innovation activity (i.e., a fully autonomous drone-based system to acquire accurate measurements and perform inspections of the structure inside the blades of wind turbines) acquiring new funding either by IFD (Grand Solutions) or the EC Horizon program.