HCL : DL based defect detection on wind turbine
Reducing the Levelized Cost of Energy (LCoE) remains the priority in the development of the wind energy sector. In the last decades, both the size and capacity of wind turbines have increased by virtue of technological developments in wind energy field. This situation resulted in an increasing focus on topics such as wind turbine fault detection. The Operation and Maintenance (O&M) costs account for 20 - 25% of the total LCoE. The aim of our technologies is to achieve more effective operation, inspection and maintenance of wind turbines with minimal human interference. This solution uses drone technology to capture images and DNN to find out defects present. The model is optimized using Intel® Distribution of OpenVINO™ and New Intel® Xeon® Scalable Processors to give faster inference.
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- Optimized inference
This solution utilizes the power of Intel® Distribution of OpenVINO™ toolkit to get highspeed inference.
- Detection of small-scale defects
The DNN model is capable of detecting small structural defects.