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AI Use Cases

A collection of over 250 uses for artificial intelligence

A continually updated list exploring how different types of AI are used across various industries and AI disciplines,including generative AI use cases, banking AI use cases, AI use cases in healthcare, AI use cases in government, AI use cases in insurance, and more

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Visual monitoring of wind turbines

Introduction

Wind turbines have become important in today’s world as the world struggles with climate change and other environmental issues. However, the maintenance of these huge structures is a complex and expensive process which at times needs risky manual inspection. This is where Computer Vision Artificial Intelligence (CV AI) comes in. CV AI, a kind of AI that deals with the ability of machines to interpret and interpret visual information, is changing the way wind turbines are managed and inspected and has the following advantages:

Challenges

There are several issues that the energy industry faces when it comes to the visual monitoring of wind turbines. First of all, conventional methods are slow and risky, involving the need for people to ascend the structures. Second, these inspections are qualitative and rely on the judgment of the inspector; two different inspectors may have different opinions. Third, it is impractical to monitor a large number of turbines spread across different locations. Last but not the least, it is imperative to identify the faults at the earliest to avoid severe consequences like catastrophic failure which cannot be done effectively with the help of traditional visual inspection techniques.

AI Solutions

All these challenges are being solved by CV AI. This is because CV AI systems use sophisticated image processing algorithms and machine learning to analyse visual information that is captured using drones and uploaded as images or videos. The AI can also identify anomalies such as cracks, corrosion and icing which at times are even better than human inspectors. Such companies as SkySpecs and BladeEdge have already adopted AI to analyse drone videos and find both visible and hidden problems. In addition, GE Renewable Energy’s Predix platform applies AI to forecast the likelihood of failure of components before it actually occurs with the help of historical data and real-time performance information.

Benefits

There are numerous advantages of employing CV AI in the visual monitoring of wind turbines. Safety is enhanced due to the technology as it minimizes the risks involved in assessing the turbines. It also reduces the time and expenses needed for an inspection and at the same time gives better and more consistent outcomes. The capability to recognize problems in their initial stage helps in avoiding costly and severe consequences like catastrophic failures thus increasing the efficiency of the turbines and its lifetime. In addition, the information gathered can be analyzed to develop improved design and maintenance procedures which will in turn advance the industry.

Return on Investment

The ROI of using CV AI in the visual monitoring of wind turbines can be very high. A study by McKinsey states that AI enabled predictive maintenance has the potential of cutting down the costs of repairing wind turbines by 12%. In addition, longer turbine life, less down time, and better overall operations are key to achieving a high ROI. For instance, SkySpecs, a company that provides inspection services for wind turbines said that they have improved efficiency by 70% while cutting the cost of inspections by 50% for their clients.

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