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Traditional asset inspection and vegetation management is costly and complex, not to mention time consuming. The need to improve risk management and productivity is driving much of the digital transformation seen in utilities today. With the right technology, the utility can mitigate threats and strengthen its grid through improved vegetation management and asset inspection workflows.
GE Digital’s Visual Intelligence platform is a cloud-based solution powered by artificial intelligence (AI) that ingests any kind of visual data to provide a holistic picture of the grid. Using machine learning (ML) allows for the optimal blend of image types (RGB, LiDAR, Hyperspectral, Multispectral, FLIR) to drive the highest value through core vegetation management and asset inspection use cases.
Maintenance, inspection, and asset management are the largest OPEX budget lines in most utilities. Shrinking this is the fastest way to add dollars to the bottom line. Significantly reducing the need for manual quality review and allowing data aggregation and incorporation into existing workflows, the visual intelligence platform supports:
Leveraging new remote sensing technology, surveying methods, and AI-driven asset condition assessment solutions, utilities have a clear path away from legacy inspection and risk management programs. Avoiding human bottlenecks with the benefits of data insights, the utility can identify problems early, detect asset damage or failure, provide enhanced public and worker safety, and help extend the lifespan of aging assets.
Data abounds today. Let’s take the example of a utility power line. To ensure asset reliability, the business sends up an unmanned drone to take images of an overhead cable corridor. It gets more than 5,000 2D images back. All for a single project section.
Rather than having to manually review each individual image, one-by-one, the utility’s asset manager can use the visual intelligence platform to create a high accuracy 3D representation of the section under review. The AI-engine in the platform can also overlay legacy data about the corridor. Then, it provides a color-coded risk analysis for vegetation management considering distance and position related to the power line, transmission line voltage, and value of asset.
The 3D view, integrated with a digital twin, can make risk assessment easier to process and visualize. Yet the 3D representation isn’t useful to the crews contracted to trim trees along the actual corridor. So, the platform can also translate the risk analysis back into a 2D map with an associated, prioritized task list in the utility’s workforce management software.
Using historic data, along with imported weather data, the utility can model vegetation growth for a particular transmission line area over the next six months or even further into the future.
Anticipating potential risk requires the utility to be accurately informed. With AI supporting its efforts, it is possible to:
The platform isn’t only offering benefits in risk analysis. The cloud-based technology also lets crew members in the field view necessary images onsite for comparison purposes. Plus, they have the ability to annotate the 2D or 3D inspection images from a tablet or smart device. This develops global awareness and improves decision making end-to-end in the asset management process.
There is a better way to plan and analyze; watch our demo to experience AI-based vegetation management.
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