Fred.Olsen Renewables

Fred. Olsen Renewables is a leading developer, owner, and operator of renewable energy assets, primarily onshore wind. With 12 wind farms and 342 turbines across the UK, Norway, and Sweden, the company has an installed capacity of 804.9 MW.

Backed by a heritage of innovation dating back to 1848 Fred. Olsen Renewables combines long-term operational thinking with a strong commitment to sustainability and asset performance.

Target

By adopting Dhalion autonomous drone system, Fred. Olsen Renewables transitioned from outsourced inspections to a fully in-house inspection and repair management model in Scandinavia, gaining full data ownership, faster decision-making, and a single source of data for blade condition and repair management.

Challenges they were facing

Delayed and incomplete reporting, often limited to summary PDFs without access to raw data.

Dependency on external logistics, causing scheduling delays and lost inspection days.

Limited insight, lacking visibility into the true condition of their turbines + Repair data scattered across reports and files

The process

Fred. Olsen Renewables initially engaged Perceptual Robotics to validate data quality and workflow. Following this proof of concept, they brought inspections in-house by acquiring two Dhalion Eve systems for their teams in Sweden and Norway.

Inspections and repairs can now be managed through Perceptual Robotics’ web platform, centralising inspection data, damage tracking, and repair actions all accessible to internal teams and suppliers.

The results

Over the past two years, several severe blade cracks have been identified early through regular in-house inspections, including Category 5 crack damages.

In one case, a 30 cm crack was monitored through frequent inspection and found to increase the size considerably within one year. Early detection enabled immediate action, preventing major escalation and unplanned downtime,

In conclusion

By internalising inspections the loop between inspection, analysis, and repair has been closed.

The shift has reduced downtime, lowered costs, improved data consistency and the level of safety, and strengthened accountability -positioning Fred. Olsen Renewables not just as an operator, but as a leader in proactive, data-driven blade management.

Download the full details in our Case Studies page (link).

The post New Case Study: How Fred.Olsen Renewables adopted Dhalion appeared first on Perceptual Robotics.

Listening to operators who need answers fast, not weeks later.
Listening to asset managers balancing inspection quality with cost, downtime, and risk.
Listening to teams who don’t want more data, but clearer decisions.

That’s what led us to focus on on-site wind turbine inspection capability, giving operators more control and reducing reliance on third-party mobilisation. It’s why we built a comprehensive classification framework, the Dhalion Guidelines for blade damages. And it’s why we introduced repair prioritisation logic, helping teams decide what needs fixing now versus what can safely wait, based on economic impact.

We’ve also learned that insight only creates value if it fits into existing workflows. Features like consistent blade damage categorisation, clear reporting structures, and actionable insights came directly from real operational constraints: weather windows in the wind farm, skills scarcity, and the pressure to do more with fewer resources and reducing friction rather than adding complexity.

Progress doesn’t always show up as big announcements. Often, it looks like quieter improvements that compound over time, shaped by a deepening understanding of the market.

That’s the journey we’re on, so join us and share your thoughts on what should be next! You can see more about our technology here

#windenergy #blades #bladerepair #droneinspection #UAV #perceptualrobotics #robotics #artificialintelligence #renewableenergy #innovation #drone #energy #offshorewind #offshorewindenergy #operations

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On Tuesday 17th, the focus will be on Wind & Renewable Energy at one of Finland’s most significant annual forums. With more than 9,000 MW installed in the country, representing over 34.9% of total installed capacity and, according to ENTSO-E, placing Finland first in Europe by percentage of installed capacity, this is an event our Eve and Dot drones simply cannot miss.

Whether you would like to learn more about our in-house (Eve)  or service-devoted (Dot) solutions, or simply stop by for a coffee, do reach out to Kaspars at the event and discover what the Dhalion system can do for you.

#windenergy #blades #bladerepair #droneinspection #UAV #perceptualrobotics #robotics #artificialintelligence #renewableenergy #innovation #drone #energy #offshorewind #offshorewindenergy #operations

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We began using the Bladena Standards, and have now transitioned into a more comprehensive framework: the Dhalion Guidelines.

Compared to previous classifications, the Dhalion Guidelines include:

• A wider range of damage types to ensure we capture the variability in all blade types and materials.
• Visual references to support accurate identification to provide consistency between Blade Experts.
• Depth: We now take into account the depth of the damages (e.g. surface, outer/inner layer, through etc) alongside the type to classify with the appropriate severity and next action for a damage.
• Damage classification: We have expanded on the damage classification tables that objectively define the severity of a damage based on key clear parameters like type, location, size, depth.

While these are defined in the guidelines they are also built in our AI system directly allowing any blade expert using our system to follow the guideline easily.

These guidelines are available to all our customers and can be shared on request. Contact us

#windenergy #blades #bladerepair #droneinspection #UAV #perceptualrobotics #robotics #artificialintelligence #renewableenergy #innovation #drone #energy #offshorewind #offshorewindenergy #operations

The post Blade Damage Assessment: Introducing the New Dhalion Guidelines appeared first on Perceptual Robotics.

We stand for equal rights for all – regardless of gender, race, sexual orientation, age, nationality, or any other distinction.

While progress has been made in some parts of the world, equality is far from universal. That’s why we choose to speak up today and act every day, by empowering women in our company and honoring female scientists through our drone systems.

Because equality isn’t a one-day statement. It’s continuous work toward a future where everyone is heard and has equal opportunity.

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Our systems deliver fast, accurate post-repair assessments, helping operators and even repair companies  to:

• Check repair quality and ensure standards are met

• Spot remaining or secondary damage in the repair early

• Minimise downtime

• Enhance safety for people and equipment

• Support documentation and compliance

A repair isn’t complete until it’s been validated and is appropriately monitored. By combining high-resolution drone inspections, AI analysis, and actionable insights, which include the Repair Module for Repair Management, as well as the Repair Now Ratio and the possibility to upload any pdf to a specific turbine or damage,  we ensure that every repair is not just done, but done right and monitored as needed. 

In industries where downtime is costly and safety is critical, accountability and post-repair inspections are essential.

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Across the most recent confidence surveys, including two involving experienced blade specialists reviewing data at specialist-portal level, the feedback shows consistent strengths:

• High confidence in report clarity and completeness, with scores clustering in the upper range, supporting efficient technical review and decision-making.
  • Strong confidence in damage detection and classification for the most common blade damage types, particularly erosion and open bond lines, which are critical drivers for maintenance planning.
  • Positive confidence in repair prioritisation recommendations, especially among Blade Experts working with detailed damage data.
  • Consistent confidence in repair decision support, indicating that our outputs are considered reliable inputs rather than black-box results.

Importantly, surveys of Blade Experts reflect feedback from highly experienced structural and materials specialists, using the Specialist part of the portal. While surveys on the End User Portal reflect the feedback from Repair and Asset Owner companies with experience in Repair and Cost management. Their combined input confirms that AI-supported inspections can be trusted not only at Blade Expert level, but also at Operator level.

The surveys also provide clear guidance on where to continue improving: notably expanded damage classification options, reinforcing the value of continuous feedback in strengthening confidence further.

We see this ongoing dialogue with users as essential: confidence is not claimed, it is earned, inspection by inspection, dataset by dataset.

The post Building confidence in AI-driven wind blade damage assessment appeared first on Perceptual Robotics.

Our solutions are currently deployed on:

• DJI Matrice 300 & 350 RTK, supporting complex, mission-critical inspection workflows, including tower inspections

• DJI Mavic 3 (E/T) & Matrice 4/ 4T, enabling rapid, efficient on-site inspections with minimal setup

Behind the scenes, our teams work closely on evolving our systems in step with DJI’s platform updates. This ensures consistent performance, validated workflows, and long-term value for operators.

It also allows you to use an automated inspection service regardless if you are using your old existing drone or the newest ones.

Looking ahead, support for the upcoming DJI M400 is already in development, and will allow our customers to transition smoothly to next-generation platforms without rethinking their inspection stack.

When the industry leader evolves, our solutions evolve with it.

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• Ada – after Ada Lovelace, pioneer of early computing
• Bea – honouring Beatrice Shilling and Beatrice Hicks, trailblazers in aeronautical and space engineering
  
• Dot – inspired by Dorothy Vaughan, Dorothy Spicer and Dorothy Buchanan, leaders in mathematics, aviation and civil engineering
  
• Eve – named after Evelyn Boyd Granville, mathematician, computing pioneer and STEM advocate

And we’re not stopping there.

We’re already working on Flo, our newest development in wind turbine drone inspections named after Florence Violet McKenzie – Australia’s first female electrical engineer and a pioneer in radio communication. In 1939 she founded the Women’s Emergency Signalling Corps, training over 12,000 servicemen and 3,000 women in Morse code and wireless telegraphy at her own expense. Her life’s work was about equipping people with the capabilities they need, which is exactly what Flo will be designed to do: put professional-grade inspection capability directly in the hands of asset owners and service providers in the easiest way possible and with the minimum field equipment required.

Stay tuned and follow our page to be the first one to know👀.

Today we celebrate the women whose legacy continues to power innovation.

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Unexpected damage, extreme weather, or urgent operational concerns don’t follow planning cycles. That’s why we’re set up to mobilise fast.

With same-week deployment, Perceptual Robotics supports operators with rapid-response inspections that help teams:

• Assess damage quickly after incidents
• Reduce turbine downtime and uncertainty
• Make informed decisions on repair or continued operation
• Avoid unnecessary delays and lost production

Our inspection teams and AI-driven analysis are designed to deliver clear insights, fast, so you can act when it matters most, not weeks later.

Because in emergency situations, speed isn’t a luxury. It’s essential.

With our team of pilots and our trusted network of partners, we can cover a wide range of locations. For urgent inspections, there is always a qualified operator nearby to support you.

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