Next Generation AI-Powered Damage Detection & Predictive Risk Software Platform for Commercial Wind Industry
AirFusion, developers of leading AI-powered damage detection and risk prediction software solutions, today announced AirFusion Wind, a cloud-based workflow and AI-based analysis platform to identify and classify wind turbine asset damage. The platform delivers faster, more accurate analysis of wind turbine inspection data, enabling proactive, predictive maintenance that significantly reduces the risks of catastrophic failure, excessive downtime and performance-based revenue loss. AirFusion Wind rapidly transforms pixel-based inspection imagery from drones, ground-based sensors and other image capture tools, into data that can be used across the Enterprise to reduce costs and increase earnings.
AirFusion’s patent-pending sensor fusion technology in combination with an advanced convolutional neural network (cnn) AI technology core, leverages terabytes of specialized images in a unique training set built around vertical-specific heuristics and deep learning techniques from wind experts around the world. The ‘self-learning’ AI system continually ingests new sensor images and related data to optimize overall accuracy. AirFusion Wind provides consistent detection and analysis for Wind operators that scales across the enterprise. Clients have global access to inspection data and analytics tools to quickly create and save customized, dynamic reports that easily integrate into corporate ERP, Industrial IoT, CMMS or other enterprise data systems.
The commercial wind ecosystem, while growing, is also facing numerous challenges; an aging infrastructure that despite condition issues, requires 95% plus uptime and maximum generative efficiency, downward price pressure across energy markets, the requirement for inspections to deliver better and instantly actionable data, and the transition to drone-based inspections with more and better quality data increases the time and costs required for human-centric inspection reporting and analysis. Add to this, downward price pressure from energy operators on overall maintenance and operations budgets (to accommodate for energy pricing pressure) and you have the perfect storm: unaided, 100% human-centric analysis is economically unsustainable.
“Only AI-based solutions will be powerful enough to handle the demand, scale, and complexities of autonomous wind turbine inspections,” said Dennis Chateauneuf, President and CEO at AirFusion. “AirFusion Wind’s unique technology combination of image recognition, patent-pending sensor fusion technology, and AI provide the consistency to provide highly accurate inspections, and the scalability required by our customers. With AirFusion Wind, inspection data analysis is reduced from hours to minutes enabling prognostics and prescriptive maintenance that dramatically reduce operational costs.”
AirFusion Wind monitors turbine conditions, identifies damage and asset degradation, streamlines inspection workflows and reporting for smarter more reliable infrastructure monitoring. Technically advanced customer friendly analysis tools help customers get better, more accurate answers from the data they collect while reducing their cost per report. Using AI-based machine learning, accuracy is dramatically increased and the time for human-based data analysis is reduced by up to 95%.
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