GE Vernova’s new AI-powered autonomous software to transform energy asset inspections

image is Cloud Computing

The solution uses image capture devices and artificial intelligence/machine learning (AI/ML) algorithms to automate traditionally manual processes. Picture used for illustrative purpose.

GE Vernova has announced a cloud-based computer vision software solution designed to transform how energy companies inspect and monitor their assets. Autonomous Inspection could bring 20% O&M savings and also help geographically dispersed assets, such as solar and wind farms, which pose annual inspection challenges.

The solution uses image capture devices and artificial intelligence/machine learning (AI/ML) algorithms to automate traditionally manual processes. GE Vernova says this helps make them faster, safer, and more cost-effective - crucial aspects when it comes to accelerating progress on digitalisation and the energy transition.

Software synergy

The company - a global leader in electrification, decarbonisation, and energy solutions - explained how the new software integrates with select applications within its Asset Performance Management (APM). This existing suite of software and services is designed to help asset performance and operations and maintenance (O&M) efficiency across equipment, plant, and an entire fleet.

Autonomous Inspection is designed to be industry-agnostic and can help users in energy generation and other industries access and act on visual data and insights within APM applications to improve asset and operational outcomes.

Enhancing technology

Linda Rae, General Manager of GE Vernova’s Power & Energy Resources Software business, explained that digitalising operations had helped customers in quality, safety, and performance improvements, as well as emission management.

“In the energy industry, computer vision is not just about seeing, it’s about foresight,” she said. “Autonomous Inspection is the eyes of our APM suite and is powered by AI technology that turns images into rich data that can help power insights to transform how we safeguard, optimise, and propel the future of energy.”

Enabling progress

GE Vernova said that despite significant digital progress within the energy industry, traditional manual asset inspection processes could often slow momentum, pose challenges, be resource intensive, prone to safety risks and errors, and difficult to scale.

The company said they were also becoming unsustainable amid a rapidly changing energy landscape with decentralisation of assets due to renewables sources, workforce availability challenges, and tougher generation requirements.

Autonomous Inspection is designed to support and contribute to the energy industry digital transformation in multiple ways, such as accelerating operational excellence by removing bottlenecks like manual-intensive and siloed inspection workflows through automation.

Bringing savings

The software can also help with safety and compliance, as workers currently need to perform inspections at elevated heights or near heated equipment that pose personal safety risk, as well as reduce travel.

GE Vernova said it could assist energy firm in their performance goals while transforming as they look to meet profitability goals while adapting to energy transition needs. John Villali, Senior Research Director for IDC Energy Insights, IDC, suggested at least 20% savings on O&M costs being “realised from leveraging autonomous visual asset inspections”, by helping workers save time and effort and detect defects faster via alerts, enabling earlier action for improving asset uptime.

GE Vernova added that Autonomous Inspection could serve applications in industries outside energy generation and in a range of use cases, including automated gauge reading, corrosion detection and severity classification, plus thermal profiling of equipment.


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