Published

4 months ago

October 24, 2025

Alice Rush

Weather Guard Lightning Tech

Sensing360’s Fiber Optics Catch Gearbox Failures Early

Eric van Genuchten, COO and Co-founder of Sensing360, explains how fiber optic technology is changing gearbox monitoring by catching failures that standard vibration sensors miss. The company’s system uses light-based sensors mounted directly onto planetary gearboxes to measure tiny steel deformations and load changes, providing early warning for the 10% of catastrophic failures current monitoring can’t detect.

Sign up now for Uptime Tech News, our weekly email update on all things wind technology. This episode is sponsored by Weather Guard Lightning Tech. Learn more about Weather Guard’s StrikeTape Wind Turbine LPS retrofit. Follow the show on Facebook, YouTube, Twitter, Linkedin and visit Weather Guard on the web. And subscribe to Rosemary Barnes’ YouTube channel here. Have a question we can answer on the show? Email us!

Welcome to Uptime Spotlight, shining light on wind. Energy’s brightest innovators. This is the Progress Powering. Tomorrow

I am here with Eric van Genuchten. Uh, so Eric is the COO and Co-founder of Sensing 360. Um, and they are bringing optics, um, to monitoring for gearbox, other rotational equipment. Uh, we’re gonna talk a little bit about what that means for the wind industry today, implementation retrofits, uh, from the factory, all kinds of good stuff.

So, Eric, can you give us a little bit of a, of your background? What’s, what makes you an expert in the space?

Eric van Genuchten: Uh, that’s a good question. So basically my background is. Uh, I studied physics when I was much younger than I’m now, so, uh, I’m not gonna disclose when, but, uh, I’ve been working since roughly 20 years and I have a background in SKF in the [00:01:00] bearing, uh, uh, manufacturing space.

And basically I’ve been working within SKF as condition monitoring, uh, solution developer. So I’ve been in condition monitoring for almost 15 years now. And from SKF, where we developed, uh, condition monitoring systems for all kind of applications, but also wind of course, we went towards, um, load sensing of barrens to be very specific to help our large customers.

And for that we used, uh, fiber sensing. And, uh, eight years ago, seven and a half years ago, uh, I started with two colleagues. I started sensing 360. Which is the 360 is of course the rotation, but we are using five optical sand or optics, uh, for rotating equipment, mainly bearings, large bearings, gear boxes.

And uh, we have been focusing a lot on wind, uh, the last five years, uh, mainly on the planetary gearbox because that’s a challenging part from the rotating, uh, [00:02:00] system to monitor. So that’s where we, uh, think we can add some value.

Joel Saxum: So I know like, uh, I, I wanna share this with the users too. Our listeners here too, because I came across your technology man, three, four or five years ago or something, uh, over in Europe.

I, I think it was, we were in Copenhagen, wind, Europe and Copenhagen. Um, and I remember seeing you guys in like the startup space and I walked over and you had like, basically what looked to be, um, a stainless steel bearing race on the, on the table. With your sensor package on it and a live readout. And I looked at it and I went to pick it up and I was like, this is interesting.

And when I picked it up, just my hand on it, I looked at the screen and I could see all the deflections happening on the screen from just me grabbing this. And I mean, it was, I mean, you remember what the product thing there was? It was probably four millimeters thick of stainless steel. Like that’s not, I’m not squishing that thing with my hand, but you could see it.

Eric van Genuchten: Yeah, no, a lot of people checked if we had a camera around it to see if they were mimicking the move. But basically, [00:03:00] if you ring about it, it’s, it’s this, this product still, we still have it, it’s still operational. And this is the, the, the type of bearing a small, relatively small one for, for let’s say, um, wind.

But it’s, uh, 22 kilotons of bearing and you can still see the pinching of your arms. So, uh, indeed. And that’s basically what we do. We, we, we integrate our sensors in steel and make, uh, I don’t say stupid steel smart, or if you put it around, we made rotating equipment smarter if you rephrase it vaguely, basically.

Joel Saxum: I like that. I like that. So, um, you know, in the wind industry, if you’re, if you talk about the past, the past was. Uh, when blades were shorter, of course now everybody’s worried about blades, blades, blades. That’s what we hear all the time. But when blades were shorter and more robust, the problem was gear boxes.

It was, what are we doing about this rotating equipment? We’re having failures. This is a, this is a regular thing. Um, we’ve gotten a little bit past that, um, with. Better bearing [00:04:00] technology, more iterations of gear boxes, different things of this sort. But there’s still issues out there. Um, and, but this is your mission statement, right?

So can you describe the problem of basically what you guys see in the field and what you’re trying to solve?

Eric van Genuchten: Yeah, so the problem in the field where we see gearbox specific and also what has been accomplished with several OEMs, because we, we like to work with customers because that basically brings the real problems outside is, is still.

And it’s, it’s valid for all slowly rotating equipment, but it’s still, uh, if it’s slowly rotating, there’s a lot, a lot of energy to do the classical, more classical vibration monitoring. So you have a challenge to predict failures, and that’s what we are still, uh, focusing on eliminating failure. So let’s say in a bare main bearing, they get 99% of the failures by vibration monitoring.

In the high speed shop bearing, they get the same amount, but in the. Gear In the gearbox, they get 90%, so there’s still 10% of fillers they cannot detect. And [00:05:00] planetary gearbox fillers are pretty catastrophic. They are, let’s say, huge replacements, cranes downtime. So, um, yeah, we, we want to predict it better.

And secondly, um. Like all rotating parts basically. Do you translate the rotation to It’s the fixed world and it’s, it’s as we say, I used to say the bearing is not, the victim is not the cause, but the victim of a failure. Um, it is, you can derive almost all your running conditions from that single point of, uh, measurement.

So operation conditions, misbalance unbalance where, so you can make predictions about, this is my. Yeah, statement prediction about this is the drive line. And of course, as you mentioned, a wind turbine is not only a drive line, the weakest link kind of defines the total life, but the drive line is an essential part of it.

Uh, so it’s still a complex system to monitor. It currents [00:06:00] current vibration monitoring, and we, we add basically load and strain sensing towards it. Therefore we do better predictions.

Joel Saxum: Yeah, because I mean, the answer here is, or the, the, what we’re trying to arrive at is we want to have early prediction of what would be a failure, right?

Because we want the up tower repair. We want the 20, 30, 40, $50,000 repair versus the. 300,000, $400,000 repair where you’re replacing gear boxes or planetary or all kinds of things of that sort. Um, so the tech, the technology that you guys have, of course you’re using fiber optics, which we can, you can arrive at, uh, a much more finite measurement.

Can you explain how that works? I guess let’s take the first, the, the, the first side of it. Let’s explain how it works, if it’s integrated, say from an OEM standpoint. Yeah.

Eric van Genuchten: So

Joel Saxum: if it’s

Eric van Genuchten: integrated from an OE EM standpoint, and we’re working with two. Two of them, and there’s not that many. So basically when you integrate it, you put it directly on the outside of the, the ring gear, so the freely accessible site, uh, [00:07:00] uh, part of the system, and it’s directly put on the outside.

And as you mentioned, you can integrate more very sensitive sensors. And due to the fact that you have more sensors and that they’re so sensitive, you can distinguish between temperature, uh, loading, uh, misbalance, so you have more information than just one. Basic string gauge. Uh, so we integrated on the outside.

Then basically when the planets are rolling, so you have the planets and you have the sun, the planets are rotating. It presses basically the steel way. And we measure that. And that measurement can be done, integrated at the OEM. And then, uh, you get a, a smart gearbox basically, which measures, uh, torque and load sharing and used for prediction, even as you mentioned.

To prevent the, the, the, the small opt tower repairs or to actually to prevent the big non-op tower repairs, but do the small opt towers, repairs, and even winning time if you have to replace it anyways, the whole logistics saves a lot of money and time if you know it six months upfront instead of two [00:08:00] weeks.

Joel Saxum: So speaking of OEMs though, right, because of course weather guard here, we’re an aftermarket product company and we speak with OEMs about integrating from the factory level and, and those kind of things quite regularly, uh, as well as operators, right? You’re starting to see operators put aftermarket solutions that they’ve deemed to be good in their turbine supply agreements are in their turbine RFPs.

Hey, hey. OEMs, we want this. Um, you guys are working directly with OEMs. That’s a tough thing to do. Congrats on that. Right? Um, so what are they using it for? What I mean, of course we know sensing, right? But if it’s, it’s an advanced thing. It’s not on every turbine. Why, why your system? Why, why are they using it?

Eric van Genuchten: The main reasons, the two main reasons to use it maybe have to make three reasons to use it, is the. The main reason is that there’s now a trend towards journal bearings. They’re cheaper, they’re essentially longer life. So in the planets there’s and different type of bearings which are not possible to monitor with vibration sensing.

And we are able to monitor by looking at the, the load changes [00:09:00] over time. That’s the main reason. Extra condition monitor, better condition monitor. And secondly, I think gearbox OEMs will also want to extend their. Let’s say piece of the puzzle or piece of the cake, they want to be become more important so they become more digital.

I think you have seen the platforms by By 360 or Thrive, and they want to do the digitalization, but in the end to to, to provide extended warranty because that’s what their customers are asking for, and. You can give extended warranty if you know what happens with your system. And that’s why they use it.

They use it for the real operation and usage monitoring of their gearbox.

Joel Saxum: Well, I think that, that, that makes sense, right? If you’re trying to extend a warranty period, or like, I guess for, uh, a gearbox manufacturer, they get to sell an extra bit of warranty, right? So they’re happy with that. Um, but you were getting closer and closer to, and, and I know this, this.

Term always kind of bothers me. It’s like when people say, oh, this is ai, eh, it’s not always ai. Sometimes it’s machine learning, sometimes it’s algorithms, whatnot. But when we get closer to [00:10:00] that term of a digital twin, you guys are, are making progress towards getting the industry at that level for slowly rotating equipment, fast rot or quick rotating equipment.

Is, is that part of the, the, the marketing sales pitch from Sensing 360? Is the digital twin or what does it look like?

Eric van Genuchten: Yeah, so it’s input for the digital twin. So basically we provide information for data teams to make a digital twin. And it’s nice that you say that because I mentioned already we measure torque or loading, and 20% more loading on a gearbox or on a bearing is half of your life and the other way around, 20% less loading.

Double your life. So if you have a digital twin, the crucial part is what is actually the operating, uh, to do any yeah. Scenario planning or maintenance planning. So we provide the information for the digital twinning. We don’t make the digital twins. Um, we might, we grow, but at this point

Joel Saxum: I like, well, I like the idea, [00:11:00] right?

Because when, where you hear a lot of times like, oh, this, this turbine has this issue. Let’s, let’s de-rate it. We’ll de-rate it for this amount of time or this, this part of its life, or, or even if we’re into a lifetime extension scenario, we’re gonna de-rate it for the rest of its life. That happens. It’s happening around the world.

So, uh, but actually having knowledge and having, um, information and data, hard data, and I, I, I stress this with everybody, uh, and it’s not just a wind industry problem, right? It’s a, it’s an industry problem. Quantitative data versus qualitative data. Uh, but I stress quantitative data. So now you, you have the ability to produce that, hey, you’re reducing loads by 17% or 22%, whatever that may be, and the lifetime extension could look like this.

Um, that’s an important part of the, of furthering the wind industry, is we get to aging assets, especially here now in this, in the states as we see this last one big, beautiful bill thing changing our ability to do. [00:12:00] PTC repo driven Repowers, right? Which was like, ah, run this thing hard for 10 years. ’cause at year 11 we’re gonna repower.

That’s not a reality anymore. Over here in the United States, you know, who knows what could happen in four more years or eight more years. But right now we’re switching operational strategies, o and m thought processes to. How can we get a lifetime extension out of this? So, so let’s speak on that a little bit.

You know, you guys are integrating from the factory. Great. Now. Fantastic. However, retrofit, what does retrofit look like?

Eric van Genuchten: Retrofit looks the same. I would say. We still integrate it on the outside of the ring gear, even on the outside of the paint by, so something called, we call a sensor strip, which you can.

It takes an hour to install, basically opt tower, and then you have the same data as you have from the five factory installation. Of course, you need to think about, will I do with magnets? Will magnets live for long enough? So there, that’s always, is it acceptable, blah, blah, blah. Um, [00:13:00] but that gives the same load data.

Now, the good thing about a wind turbine is of course, that it runs. It rated power most of the time. So you can derive a calibration while running institute. So you don’t need a whole kinds of, uh, high level simulations or other thought to solve it. But looking at that, we measure for a month as an example, and then you get the, the, the torque levels, the load levels, the, the curtailment stops, the start stops, the, the, the breaks.

And we get all these effect. And every day you make a statement like, I have used this much life according. To the load I had and to the time I was running, and that comes to reduced capacity. Of course, you have to go back to make an estimation about the future, but you basically take a period of three months and you go back and forward with it with the same regime.

She can say, well, based on what we have now, now there six years left in this park. And then you talk about extension. If you have [00:14:00] multiple turbines, you can play with load balancing over the turbines to. Take the hard ones to, to, to, to reduce the air of loads and take the, the, the ones who have, based on the data, seen less load, take them a bit more load so you can kind of maximize energy output.

At least you have the information to do so. I don’t know if, if, if park owners are fully equipped to do it, but that’s one of the, the,

Joel Saxum: the,

Eric van Genuchten: the input parameters you can use to

Joel Saxum: do extension. Well that, that, that leads me to another question here. So sensing 360, of course you guys create the technology, uh, the hardware, the sensors, and you know, a software platform to look at the data.

But are you guys providing those operational insights or is that a part of your business model to say, Hey, you should do this or you should do that? Um, because one of the problems we see in wind and we, and talk about this all the time, is tons of data. We’ve got big data, big data, big data. What do we do with all of it?

And at the same time, you’re seeing. Engineering staffs shrink, uh, you know, some layoffs and things like [00:15:00] this, so they’re losing some internal resources. Is this something that you guys can help people with as well? Yeah, so our,

Eric van Genuchten: so our solution gives a recommendation. So in the end we are, don’t own the park.

So we, well, most of the time not allowed too many control on it, but it makes it, and I like to say it, and of course I would like to say that, but it makes condition monitoring basically one side simpler, and also the information more dedicated. So you need. Less of a degree to analyze it because if you are in the vibration space, looking at vibration spectrum and analysis and making the correct conclusion is still a science.

It’s still quite some, and of course AI is increasing there and we can look at an analogies and, but you still physically need to understand it to make. A good estimation. That is what we, since we have both usage and vibration monitoring, we both have, let’s say more, we have both information at one point.

So we use that to make it simpler. So also run in times are a lot shorter, basically. And secondly, a [00:16:00] statement like you have six years left is a relatively simple statement, but even financial people can translate into what, this is my cost over time. So. Yes, that’s our goal and we give recommendations and advices.

That’s still the case. Um, unless they won’t be to control their park. So I would love to build, build. I would love to build a business model, Joel, with, I get extra production. I get paid for in at least production. I don’t, but I’m not there yet.

Joel Saxum: I like that. Um, okay, so I’m gonna ask a couple questions then, I guess from an operation standpoint.

Say I am. Wind farm owner, X, Y, Z, and I have two parks and one of ’em I’ve been losing some gear boxes in, or I’m getting towards, uh, you know, a lifetime extension type thing. What, what does my journey look like if I call Eric and team and say, Hey, I would like to monitor these things. I, I need more insights of what’s going on in my rotational equipment.

How, what does life look like for me? If I’m trying to implement the solution?

Eric van Genuchten: They never [00:17:00] immediately start buying everything for the whole park. Which is understandable because we are not like, uh, the big, big, huge condition monitor company. So there’s still some, some trust issues, I would say, or, uh, but basically it starts with an assessment.

So basically we have now developed, uh. A two true, um, a suitcase where we will go up, we will put our sensor there with a magnets, with magnets measure for a day or an hour and then say, okay, this is what we can gather. This is the information and this is what we can see. Now we do that on one turbine and preferably three, four, if you have a pocket problems, it’s slightly different because then they know the problems we had in the past we cannot see with our current system.

So. We’re gonna instrument several of them and, and look together at the data. ’cause we have kind of proven that we can pick point teeth breaking, uh, bearing failures in the plan. So we, we have a story. [00:18:00] This is working if we go about lifetime extension. Yeah. That’s still, the proof is still in the pudding, let’s say, or in p the end proof is in the eating of the pudding.

Um. That’s still going together. Look at this data. Okay? We can see now last month with this one GI one wind turbine. We, this is the status and we see you have six years left and then you slowly go to two turbines, four turbines, whatever, turbines. That’s

Joel Saxum: the story, I think. Okay. When I look at the solution from the outside, I think, oh man, this must be difficult.

Um, but it seems like you guys have come with, uh, the hardware solution that’s not right, maging onto the outside of the, the planetary. Pretty f pretty freaking simple. Um, deploy a couple systems on some thing on a couple of different turbines. I, if you are leaving it now, I wanna get a cybersecurity question if you’re leaving it behind.

Um, what does communications and power look like up tower,

Eric van Genuchten: and that’s a good one. So, so basically you, you put on the sensors and you have a small computer [00:19:00] box, which both gets in the light, reach the light out, and does the calculation. Then there is the, the, the, the, the most classical ways to put it directly into the current systems, scatter systems, monitoring systems, which you already have, which have the security there, and also are managed on the security level.

Uh, and the data goes to the customer portal. That is the integration with current systems. Then parts problems, and especially older parks, do not always have condition monitoring systems. Uh, and then you need to indeed, uh, find a either a 4G connection, 5G starlink. There’s, there’s many options. And then there’s a secured connection towards our cloud according to the latest standards.

Uh, it depends per company. Indeed. What are the demands of your securing systems? But we have for. We know that there was, um, a huge hack, uh, at Nordic and, and, and so they have improved their security levels and we meet those. So that’s basically, [00:20:00] uh, currently there, but it, it’ll remain a, an ongoing, um, work evolution of what a secure what’s not.

Joel Saxum: Yeah. It’s continued to change all the time and, and I think you’re, you’re starting to see people. Get more stringent, right? We’ve, I’ve even had things where I’ve dealt with clients sending ’em an email and they’re like, whoa, whoa, whoa. We have to look at your email processes. Like, what? This is a bit ridiculous.

Um, but let, lemme go to another question. So this is a big one. Um, you’re working, so you’re, I wanna give a little track record for the company you’re working with OEMs. Uh, so you’re integrating things from the factory. Again, kudos on that, that’s difficult to do. You’re doing retrofits, uh, multiple different styles of gear boxes, uh, for different manufacturers.

How many, how many wind farms are you guys on? Or how many, uh. Turbines you guys on out in the field? I hope to,

Eric van Genuchten: to reach the 50 by the end of the year, but we’re currently at three, five turbines.

Joel Saxum: Yeah. Kudos to you guys. I think that, I mean, it’s a difficult place. It’s a, that’s a difficult hurdle to cross, right?

From a startup with a [00:21:00] bunch of really smart technology and smart people, uh, creating a product, getting it into the market, and then starting to expand the fact that you’ve done it with OEMs already. Again, difficult. Uh, so, so good work on that. Uh, Eric, um, what other message would you like to get across to the wind industry about, um.

About their gear boxes, what do they need to be doing? What’s the, what’s the best practices from Eric seat?

Eric van Genuchten: So there’s a statement from one of our earlier cooperators, which was Siemens, Gaza, uh, and he said it would be ridiculous with the increase of complexity and value of a gearbox to not instrument them with fiber optic sensing, which is a statement of course I would like to bring out.

And basically it is if you start integrating a couple of hundred euros of sensors in a gearbox, which is. The half a million, I have no idea. But in those ranges and failures are up to two tons, why not do that? And digital twins and AI start with making the physical, [00:22:00] physical digitally. So basically you still need the feed of data towards all these models to optimize an ai.

And if you, for me, it’s just we have more computing power and therefore the same equations we had 60 years ago are now actually. Being used, which wiser, but you need to make the physical, digital, and then you can start making all these great models. So I would say for me it’s a no brainer. And of course I will say that, but it’s also what our customers say.

And for the long term, this, it’s ridiculous not to do it.

Joel Saxum: We’ve talked about gear boxes, planter gear boxes, being able to sense the load changes on ’em. Slow rotating equipment. Okay. We’ve talked to a lot of people that test these things, uh, and they’re doing hybrid testing simply because it’s so difficult to test, say bearing pitch bearings, uh, rotor bearings, these kind of things because they are slower speed.

Can your technology be used, uh, for, for those types of applications as well?

Eric van Genuchten: Yeah, so that’s where we are currently also in the development roadmap. On, on, on the, the [00:23:00] large, slowly rotating parts. Pitch bearings in marine, you see more of them, the ones which keep the cranes on place, et cetera, slowing bearings, they’re nicely, but basically those are hard to monitor because there’s not enough energy to do vibration or to do sound measurements.

And by changing, loading or changing, uh, response of the outing. ’cause that’s what we are measuring the deformation. Uh, you can see cracks, you can see uneven loading, you can see other issues. So we are able to predict failures much earlier than, than what’s now ongoing, so that we are extending our, uh. Now I talk about a dream extending.

If you have one optical part in it, you can do the blades, you can do the pitch bearings. The the main bearing, the, the, the, the, the, the, the gearbox, the generator, probably the jaw, the pole fully optical monitoring. That is for, for me, it’s the long term goal to go

Joel Saxum: there. I, um, I’m gonna, uh, send some, some [00:24:00] thought energy to a specific OEM here in the states that needs helps with pitch bearings.

Call Eric and his team to get a project going so we can see the failure modes and these things before we start keep cracking hubs out in the field. Uh, but Eric, I I really want to thank you for the time today. Um, if anybody has any questions about fiber optic, sensing, slow rotating equipment, gearbox is all the above.

Eric and team are fantastic. How can, how can the listeners reach out to you?

Eric van Genuchten: On my site, there’s even my direct number still as a contact, so that’s why I’m ENS three sixty.com. You can look at contact and my number is there still. So that’s the perks of being a small company. And LinkedIn. We are pretty active on LinkedIn, getting active on YouTube, but mainly a VR site.

That’s how we are easiest to contact. Or you can do the simple one, eric@sensingthreesixty.com. That also helps.

Joel Saxum: Perfect. Uh, thanks

Eric van Genuchten: again Eric. Thank you. Thanks for having [00:25:00] me.

https://weatherguardwind.com/sensing-360-gearbox/

Renewable Energy

Wind Industry Operations: In Wind’s Next Chapter, Operations take center stage

Published

9 hours ago

February 26, 2026

Alice Rush

Weather Guard Lightning Tech

Wind Industry Operations: In Wind’s Next Chapter, Operations take center stage

This exclusive article originally appeared in PES Wind 4 – 2025 with the title, Operations take center stage in wind’s next chapter. It was written by Allen Hall and other members of the WeatherGuard Lightning Tech team.

As aging fleets, shrinking margins, and new policies reshape the wind sector, wind energy operations are in the spotlight. The industry’s next chapter will be defined not by capacity growth, but by operational excellence, where integrated, predictive maintenance turns data into decisions and reliability into profit.

Wind farm operations are undergoing a fundamental transformation. After hosting hundreds of conversations on the Uptime Wind Energy Podcast, I’ve witnessed a clear pattern: the most successful operators are abandoning reactive maintenance in favor of integrated, predictive strategies. This shift isn’t just about adopting new technologies; it’s about fundamentally rethinking how we manage aging assets in an era of tightening margins and expanding responsibilities.

The evidence was overwhelming at this year’s SkySpecs Customer Forum, where representatives from over 75% of US installed wind capacity gathered to share experiences and strategies. The consensus was clear: those who integrate monitoring, inspection, and repair into a cohesive operational strategy are achieving dramatic improvements in reliability and profitability.

Takeaway: These options have been available to wind energy operations for years; now, adoption is critical.

Why traditional approaches to wind farm operations are failing

Today’s wind operators face an unprecedented convergence of challenges. Fleets installed during the 2010-2015 boom are aging in unexpected ways, revealing design vulnerabilities no one anticipated. Meanwhile, the support infrastructure is crumbling; spare parts have become scarce, OEM support is limited, and insurance companies are tightening coverage just when operators need them most.

The situation is particularly acute following recent policy changes. The One Big Beautiful Bill in the United States has fundamentally altered the economic landscape. PTC farming is no longer viable; turbines must run longer and more reliably than ever before. Engineering teams, already stretched thin, are being asked to manage not just wind assets but solar and battery storage as well. The old playbook simply doesn’t work anymore.

Consider the scope of just one challenge: polyester blade failures. During our podcast conversation with Edo Kuipers of We4Ce, we learned that an estimated 30,000 to 40,000 blades worldwide are experiencing root bushing issues. ‘After a while, blades are simply flying off,’ Kuipers explained. The financial impact of a single blade failure can exceed €300,000 when you factor in replacement costs, lost production, and crane mobilization. Yet innovative repair solutions, like the one developed by We4Ce and CNC Onsite, can address the same problem for €40,000 if caught early. This pattern repeats across every major component. Gearbox failures that once required complete replacement can now be predicted months in advance. Lightning damage that previously caused catastrophic failures can be prevented with inexpensive upgrades and real-time monitoring. All these solutions are based on the principle that predicted maintenance is better than an expensive surprise.

Seeing problems before they happeny, and potential risks

The transformation begins with visibility. Modern monitoring systems reveal problems that traditional methods miss entirely. Eric van Genuchten of Sensing360 shared an eye-opening statistic on our podcast: ‘In planetary gearbox failures, they get 90%, so there’s still 10% of failures they cannot detect.’ That missing 10% represents the catastrophic failures that destroy budgets and production targets. Advanced monitoring technologies are filling these gaps. Sensing360’s fiber optic sensors, for example, detect minute deformations in steel components, revealing load imbalances and fatigue progression invisible to traditional monitoring. ‘We integrate our sensors in steel and make rotating equipment smarter,’ van Genuchten explained.

Other companies are deploying acoustic systems to identify blade delamination, oil analysis for gearbox health, and electrical signature analysis for generator issues. Each technology adds a piece to the puzzle, but the real value comes from integration. The impact of load monitoring alone can be transformative.

As van Genuchten explained, ‘Twenty percent more loading on a gearbox or on a bearing is half of your life. The other way around, twenty percent less loading is double your life.’ With proper monitoring, operators can optimize load distribution across their fleet, extending component life while maximizing production.

But monitoring without action is just expensive data collection. The most successful operators are those who’ve learned to translate sensor data into operational decisions. This requires not just technology but organizational change, breaking down silos between monitoring, maintenance, and management teams.

In Wind Energy Operations, Early intervention makes the million-dollar difference

The economics of early intervention are compelling across every component type. The blade root bushing example from We4Ce illustrates this perfectly. With their solution, early detection means replacing just 24-30 bushings in about 24 hours of drilling work. Wait, and you’re looking at 60+ bushings and 60 hours of work. Early detection doesn’t just prevent catastrophic failure; it makes repairs faster, cheaper, and more reliable.

This principle extends throughout the turbine. Early-stage bearing damage can be addressed through targeted lubrication or minor adjustments. Incipient electrical issues can be resolved with cleaning or connection tightening. Small blade surface cracks can be repaired in a few hours before they propagate into structural damage requiring weeks of work.

Leading operators are implementing tiered response protocols based on monitoring data. Critical issues trigger immediate intervention. Developing problems are scheduled for the next maintenance window. Minor issues are monitored and addressed during routine service. This systematic approach reduces both emergency repairs and unnecessary maintenance, optimizing resource allocation across the fleet.

Turning information into action

While monitoring generates data, platforms like SkySpecs’ Horizon transform that data into operational intelligence. Josh Goryl, SkySpecs’ Chief Revenue Officer, explained their evolution at the recent Customer Forum: ‘I think where we can help our customers is getting all that data into one place.

The game-changer is integration across data types. The company is working to combine performance data with CMS data to provide valuable insights into turbine health. This approach has been informed by operators across the world, who’ve discovered that integrated platforms deliver insights that siloed data can’t.

The platform approach also addresses the reality of shrinking engineering teams managing expanding portfolios. As Goryl noted, many wind engineers are now responsible for solar and battery storage assets as well. One platform managing multiple technologies through a unified interface becomes essential for operational efficiency.

The Integration Imperative for Wind Farm Operations

The most successful operators aren’t just adopting individual technologies; they’re integrating monitoring, inspection, and repair into a seamless operational system. This integration operates at multiple levels.

At the technical level, data from various monitoring systems feeds into unified platforms that provide comprehensive asset visibility. These platforms don’t just display data; they analyze patterns, predict failures, and generate work orders.

At the organizational level, integration means breaking down barriers between departments. This cross-functional collaboration transforms O&M from a cost center into a value driver. Building your improvement roadmap For operators ready to enhance their O&M approach, the path forward involves several key steps:

Assessing the Current State of your Wind Energy Operations

Document your maintenance costs, failure rates, and downtime patterns. Identify which problems consume the most resources and which assets are most critical to your wind farm operations.

Start with targeted pilots Rather than attempting wholesale transformation, begin with focused initiatives targeting your biggest pain points. Whether it’s blade monitoring, gearbox sensors, or repair innovations, starting with your largest issue will help you see the biggest benefit.

• Invest in integration, not just technology: the most sophisticated monitoring system is worthless if its data isn’t acted upon. Ensure your organization has the processes and culture to transform data into decisions – this is the first step to profitability in your wind farm operations.

Build partnerships, not just contracts: look for technology providers and service companies willing to share knowledge, not just deliver services. The goal is building capability, not dependency.

• Measure and iterate: track the impact of each initiative on your key performance indicators. Use lessons learned to refine your approach and guide future investments.

The competitive advantage

The wind industry has reached an inflection point. With increasingly large and complex turbines, monitoring needs to adapt with it. The era of flying blind is over.

In an industry where margins continue to compress and competition intensifies, operational excellence has become a key differentiator. Those who master the integration of monitoring, inspection, and repair will thrive. Those who cling to reactive maintenance face escalating costs and declining competitiveness.

The technology exists. The business case is proven. The early adopters are already reaping the benefits. The question isn’t whether to transform your O&M approach, but how quickly you can adapt to this new reality. In the race to operational excellence, the winners will be those who act decisively to embrace the efficiency revolution reshaping wind operations.

Unless otherwise noted, images here are from We4C Rotorblade Specialist.

Wind Industry Operations: In Wind's Next Chapter, Operations take center stage

Contact us for help understanding your lightning damage, future risks, and how to get more uptime from your equipment.

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Wind Industry Operations: In Wind’s Next Chapter, Operations take center stage

Renewable Energy

BladeBUG Tackles Serial Blade Defects with Robotics

Published

12 hours ago

February 26, 2026

Alice Rush

Weather Guard Lightning Tech

BladeBUG Tackles Serial Blade Defects with Robotics

Chris Cieslak, CEO of BladeBug, joins the show to discuss how their walking robot is making ultrasonic blade inspections faster and more accessible. They cover new horizontal scanning capabilities for lay down yards, blade root inspections for bushing defects, and plans to expand into North America in 2026.

Sign up now for Uptime Tech News, our weekly newsletter on all things wind technology. This episode is sponsored by Weather Guard Lightning Tech. Learn more about Weather Guard’s StrikeTape Wind Turbine LPS retrofit. Follow the show on YouTube, Linkedin and visit Weather Guard on the web. And subscribe to Rosemary’s “Engineering with Rosie” YouTube channel here. Have a question we can answer on the show? Email us!

Welcome to Uptime Spotlight, shining Light on Wind. Energy’s brightest innovators. This is the Progress Powering Tomorrow.

Allen Hall: Chris, welcome back to the show.

Chris Cieslak: It’s great to be back. Thank you very much for having me on again.

Allen Hall: It’s great to see you in person, and a lot has been happening at Blade Bugs since the last time I saw Blade Bug in person. Yeah, the robot. It looks a lot different and it has really new capabilities.

Chris Cieslak: So we’ve continued to develop our ultrasonic, non-destructive testing capabilities of the blade bug robot.

Um, but what we’ve now added to its capabilities is to do horizontal blade scans as well. So we’re able to do blades that are in lay down yards or blades that have come down for inspections as well as up tower. So we can do up tower, down tower inspections. We’re trying to capture. I guess the opportunity to inspect blades after transportation when they get delivered to site, to look [00:01:00] for any transport damage or anything that might have been missed in the factory inspections.

And then we can do subsequent installation inspections as well to make sure there’s no mishandling damage on those blades. So yeah, we’ve been just refining what we can do with the NDT side of things and improving its capabilities

Joel Saxum: was that need driven from like market response and people say, Hey, we need, we need.

We like the blade blood product. We like what you’re doing, but we need it here. Or do you guys just say like, Hey, this is the next, this is the next thing we can do. Why not?

Chris Cieslak: It was very much market response. We had a lot of inquiries this year from, um, OEMs, blade manufacturers across the board with issues within their blades that need to be inspected on the ground, up the tap, any which way they can.

There there was no, um, rhyme or reason, which was better, but the fact that he wanted to improve the ability of it horizontally has led the. Sort of modifications that you’ve seen and now we’re doing like down tower, right? Blade scans. Yeah. A really fast breed. So

Joel Saxum: I think the, the important thing there is too is that because of the way the robot is built [00:02:00] now, when you see NDT in a factory, it’s this robot rolls along this perfectly flat concrete floor and it does this and it does that.

But the way the robot is built, if a blade is sitting in a chair trailing edge up, or if it’s flap wise, any which way the robot can adapt to, right? And the idea is. We, we looked at it today and kind of the new cage and the new things you have around it with all the different encoders and for the heads and everything is you can collect data however is needed.

If it’s rasterized, if there’s a vector, if there’s a line, if we go down a bond line, if we need to scan a two foot wide path down the middle of the top of the spa cap, we can do all those different things and all kinds of orientations. That’s a fantastic capability.

Chris Cieslak: Yeah, absolutely. And it, that’s again for the market needs.

So we are able to scan maybe a meter wide in one sort of cord wise. Pass of that probe whilst walking in the span-wise direction. So we’re able to do that raster scan at various spacing. So if you’ve got a defect that you wanna find that maximum 20 mil, we’ll just have a 20 mil step [00:03:00] size between each scan.

If you’ve got a bigger tolerance, we can have 50 mil, a hundred mil it, it’s so tuneable and it removes any of the variability that you get from a human to human operator doing that scanning. And this is all about. Repeatable, consistent high quality data that you can then use to make real informed decisions about the state of those blades and act upon it.

So this is not about, um, an alternative to humans. It’s just a better, it’s just an evolution of how humans do it. We can just do it really quick and it’s probably, we, we say it’s like six times faster than a human, but actually we’re 10 times faster. We don’t need to do any of the mapping out of the blade, but it’s all encoded all that data.

We know where the robot is as we walk. That’s all captured. And then you end up with really. Consistent data. It doesn’t matter who’s operating a robot, the robot will have those settings preset and you just walk down the blade, get that data, and then our subject matter experts, they’re offline, you know, they are in their offices, warm, cozy offices, reviewing data from multiple sources of robots.

And it’s about, you know, improving that [00:04:00] efficiency of getting that report out to the customer and letting ’em know what’s wrong with their blades, actually,

Allen Hall: because that’s always been the drawback of, with NDT. Is that I think the engineers have always wanted to go do it. There’s been crush core transportation damage, which is sometimes hard to see.

You can maybe see a little bit of a wobble on the blade service, but you’re not sure what’s underneath. Bond line’s always an issue for engineering, but the cost to take a person, fly them out to look at a spot on a blade is really expensive, especially someone who is qualified. Yeah, so the, the difference now with play bug is you can have the technology to do the scan.

Much faster and do a lot of blades, which is what the de market demand is right now to do a lot of blades simultaneously and get the same level of data by the review, by the same expert just sitting somewhere else.

Chris Cieslak: Absolutely.

Joel Saxum: I think that the quality of data is a, it’s something to touch on here because when you send someone out to the field, it’s like if, if, if I go, if I go to the wall here and you go to the wall here and we both take a paintbrush, we paint a little bit [00:05:00] different, you’re probably gonna be better.

You’re gonna be able to reach higher spots than I can.

Allen Hall: This is true.

Joel Saxum: That’s true. It’s the same thing with like an NDT process. Now you’re taking the variability of the technician out of it as well. So the data quality collection at the source, that’s what played bug ducts.

Allen Hall: Yeah,

Joel Saxum: that’s the robotic processes.

That is making sure that if I scan this, whatever it may be, LM 48.7 and I do another one and another one and another one, I’m gonna get a consistent set of quality data and then it’s goes to analysis. We can make real decisions off.

Allen Hall: Well, I, I think in today’s world now, especially with transportation damage and warranties, that they’re trying to pick up a lot of things at two years in that they could have picked up free installation.

Yeah. Or lifting of the blades. That world is changing very rapidly. I think a lot of operators are getting smarter about this, but they haven’t thought about where do we go find the tool.

Speaker: Yeah.

Allen Hall: And, and I know Joel knows that, Hey, it, it’s Chris at Blade Bug. You need to call him and get to the technology.

But I think for a lot of [00:06:00] operators around the world, they haven’t thought about the cost They’re paying the warranty costs, they’re paying the insurance costs they’re paying because they don’t have the set of data. And it’s not tremendously expensive to go do. But now the capability is here. What is the market saying?

Is it, is it coming back to you now and saying, okay, let’s go. We gotta, we gotta mobilize. We need 10 of these blade bugs out here to go, go take a scan. Where, where, where are we at today?

Chris Cieslak: We’ve hads. Validation this year that this is needed. And it’s a case of we just need to be around for when they come back round for that because the, the issues that we’re looking for, you know, it solves the problem of these new big 80 a hundred meter plus blades that have issues, which shouldn’t.

Frankly exist like process manufacturer issues, but they are there. They need to be investigated. If you’re an asset only, you wanna know that. Do I have a blade that’s likely to fail compared to one which is, which is okay? And sort of focus on that and not essentially remove any uncertainty or worry that you have about your assets.

’cause you can see other [00:07:00] turbine blades falling. Um, so we are trying to solve that problem. But at the same time, end of warranty claims, if you’re gonna be taken over these blades and doing the maintenance yourself, you wanna know that what you are being given. It hasn’t gotten any nasties lurking inside that’s gonna bite you.

Joel Saxum: Yeah.

Chris Cieslak: Very expensively in a few years down the line. And so you wanna be able to, you know, tick a box, go, actually these are fine. Well actually these are problems. I, you need to give me some money so I can perform remedial work on these blades. And then you end of life, you know, how hard have they lived?

Can you do an assessment to go, actually you can sweat these assets for longer. So we, we kind of see ourselves being, you know, useful right now for the new blades, but actually throughout the value chain of a life of a blade. People need to start seeing that NDT ultrasonic being one of them. We are working on other forms of NDT as well, but there are ways of using it to just really remove a lot of uncertainty and potential risk for that.

You’re gonna end up paying through the, you know, through the, the roof wall because you’ve underestimated something or you’ve missed something, which you could have captured with a, with a quick inspection.

Joel Saxum: To [00:08:00] me, NDT has been floating around there, but it just hasn’t been as accessible or easy. The knowledge hasn’t been there about it, but the what it can do for an operator.

In de-risking their fleet is amazing. They just need to understand it and know it. But you guys with the robotic technology to me, are bringing NDT to the masses

Chris Cieslak: Yeah.

Joel Saxum: In a way that hasn’t been able to be done, done before

Chris Cieslak: that. And that that’s, we, we are trying to really just be able to roll it out at a way that you’re not limited to those limited experts in the composite NDT world.

So we wanna work with them, with the C-N-C-C-I-C NDTs of this world because they are the expertise in composite. So being able to interpret those, those scams. Is not a quick thing to become proficient at. So we are like, okay, let’s work with these people, but let’s give them the best quality data, consistent data that we possibly can and let’s remove those barriers of those limited people so we can roll it out to the masses.

Yeah, and we are that sort of next level of information where it isn’t just seen as like a nice to have, it’s like an essential to have, but just how [00:09:00] we see it now. It’s not NDT is no longer like, it’s the last thing that we would look at. It should be just part of the drones. It should inspection, be part of the internal crawlers regimes.

Yeah, it’s just part of it. ’cause there isn’t one type of inspection that ticks all the boxes. There isn’t silver bullet of NDT. And so it’s just making sure that you use the right system for the right inspection type. And so it’s complementary to drones, it’s complimentary to the internal drones, uh, crawlers.

It’s just the next level to give you certainty. Remove any, you know, if you see something indicated on a a on a photograph. That doesn’t tell you the true picture of what’s going on with the structure. So this is really about, okay, I’ve got an indication of something there. Let’s find out what that really is.

And then with that information you can go, right, I know a repair schedule is gonna take this long. The downtime of that turbine’s gonna be this long and you can plan it in. ’cause everyone’s already got limited budgets, which I think why NDT hasn’t taken off as it should have done because nobody’s got money for more inspections.

Right. Even though there is a money saving to be had long term, everyone is fighting [00:10:00] fires and you know, they’ve really got a limited inspection budget. Drone prices or drone inspections have come down. It’s sort, sort of rise to the bottom. But with that next value add to really add certainty to what you’re trying to inspect without, you know, you go to do a day repair and it ends up being three months or something like, well

Allen Hall: that’s the lightning,

Joel Saxum: right?

Allen Hall: Yeah. Lightning is the, the one case where every time you start to scarf. The exterior of the blade, you’re not sure how deep that’s going and how expensive it is. Yeah, and it always amazes me when we talk to a customer and they’re started like, well, you know, it’s gonna be a foot wide scarf, and now we’re into 10 meters and now we’re on the inside.

Yeah. And the outside. Why did you not do an NDT? It seems like money well spent Yeah. To do, especially if you have a, a quantity of them. And I think the quantity is a key now because in the US there’s 75,000 turbines worldwide, several hundred thousand turbines. The number of turbines is there. The number of problems is there.

It makes more financial sense today than ever because drone [00:11:00]information has come down on cost. And the internal rovers though expensive has also come down on cost. NDT has also come down where it’s now available to the masses. Yeah. But it has been such a mental barrier. That barrier has to go away. If we’re going going to keep blades in operation for 25, 30 years, I

Joel Saxum: mean, we’re seeing no

Allen Hall: way you can do it

Joel Saxum: otherwise.

We’re seeing serial defects. But the only way that you can inspect and or control them is with NDT now.

Allen Hall: Sure.

Joel Saxum: And if we would’ve been on this years ago, we wouldn’t have so many, what is our term? Blade liberations liberating

Chris Cieslak: blades.

Joel Saxum: Right, right.

Allen Hall: What about blade route? Can the robot get around the blade route and see for the bushings and the insert issues?

Chris Cieslak: Yeah, so the robot can, we can walk circumferentially around that blade route and we can look for issues which are affecting thousands of blades. Especially in North America. Yeah.

Allen Hall: Oh yeah.

Chris Cieslak: So that is an area that is. You know, we are lucky that we’ve got, um, a warehouse full of blade samples or route down to tip, and we were able to sort of calibrate, verify, prove everything in our facility to [00:12:00] then take out to the field because that is just, you know, NDT of bushings is great, whether it’s ultrasonic or whether we’re using like CMS, uh, type systems as well.

But we can really just say, okay, this is the area where the problem is. This needs to be resolved. And then, you know, we go to some of the companies that can resolve those issues with it. And this is really about played by being part of a group of technologies working together to give overall solutions

Allen Hall: because the robot’s not that big.

It could be taken up tower relatively easily, put on the root of the blade, told to walk around it. You gotta scan now, you know. It’s a lot easier than trying to put a technician on ropes out there for sure.

Chris Cieslak: Yeah.

Allen Hall: And the speed up it.

Joel Saxum: So let’s talk about execution then for a second. When that goes to the field from you, someone says, Chris needs some help, what does it look like?

How does it work?

Chris Cieslak: Once we get a call out, um, we’ll do a site assessment. We’ve got all our rams, everything in place. You know, we’ve been on turbines. We know the process of getting out there. We’re all GWO qualified and go to site and do their work. Um, for us, we can [00:13:00] turn up on site, unload the van, the robot is on a blade in less than an hour.

Ready to inspect? Yep. Typically half an hour. You know, if we’ve been on that same turbine a number of times, it’s somewhere just like clockwork. You know, muscle memory comes in, you’ve got all those processes down, um, and then it’s just scanning. Our robot operator just presses a button and we just watch it perform scans.

And as I said, you know, we are not necessarily the NDT experts. We obviously are very mindful of NDT and know what scans look like. But if there’s any issues, we have a styling, we dial in remote to our supplement expert, they can actually remotely take control, change the settings, parameters.

Allen Hall: Wow.

Chris Cieslak: And so they’re virtually present and that’s one of the beauties, you know, you don’t need to have people on site.

You can have our general, um, robot techs to do the work, but you still have that comfort of knowing that the data is being overlooked if need be by those experts.

Joel Saxum: The next level, um, commercial evolution would be being able to lease the kit to someone and or have ISPs do it for [00:14:00] you guys kinda globally, or what is the thought

Chris Cieslak: there?

Absolutely. So. Yeah, so we to, to really roll this out, we just wanna have people operate in the robots as if it’s like a drone. So drone inspection companies are a classic company that we see perfectly aligned with. You’ve got the sky specs of this world, you know, you’ve got drone operator, they do a scan, they can find something, put the robot up there and get that next level of information always straight away and feed that into their systems to give that insight into that customer.

Um, you know, be it an OEM who’s got a small service team, they can all be trained up. You’ve got general turbine technicians. They’ve all got G We working at height. That’s all you need to operate the bay by road, but you don’t need to have the RAA level qualified people, which are in short supply anyway.

Let them do the jobs that we are not gonna solve. They can do the big repairs we are taking away, you know, another problem for them, but giving them insights that make their job easier and more successful by removing any of those surprises when they’re gonna do that work.

Allen Hall: So what’s the plans for 2026 then?

Chris Cieslak: 2026 for us is to pick up where 2025 should have ended. [00:15:00] So we were, we were meant to be in the States. Yeah. On some projects that got postponed until 26. So it’s really, for us North America is, um, what we’re really, as you said, there’s seven, 5,000 turbines there, but there’s also a lot of, um, turbines with known issues that we can help determine which blades are affected.

And that involves blades on the ground, that involves blades, uh, that are flying. So. For us, we wanna get out to the states as soon as possible, so we’re working with some of the OEMs and, and essentially some of the asset owners.

Allen Hall: Chris, it’s so great to meet you in person and talk about the latest that’s happening.

Thank you. With Blade Bug, if people need to get ahold of you or Blade Bug, how do they do that?

Chris Cieslak: I, I would say LinkedIn is probably the best place to find myself and also Blade Bug and contact us, um, through that.

Allen Hall: Alright, great. Thanks Chris for joining us and we will see you at the next. So hopefully in America, come to America sometime.

We’d love to see you there.

Chris Cieslak: Thank you very [00:16:00] much.