When I first started as an NDT technician working with aerospace and automotive composite parts back in 2008, I didn’t realize how many small, hidden flaws could sneak into a carbon fiber or fiberglass laminate mid-production. I once watched a parts manufacturer scrap an entire run of aircraft control surfaces because a single internal void, smaller than a pencil eraser, led to a catastrophic failure during stress testing. That moment stuck with me—not just as a lesson in how critical flaws are, but as a reminder that non-destructive testing (NDT) isn’t just a quality check; it’s the difference between a product that works and one that doesn’t. Today, as an NDT supplier focused exclusively on composite materials, I get asked this question all the time: How exactly does NDT detect internal voids in composites, and why does it matter more now than ever? Non-destructive Testing NDT
Let’s start with what internal voids in composites actually are, because that foundation helps make every NDT method make sense. Composites are made of two parts: a reinforcing fiber (carbon, glass, aramid) and a polymer matrix (usually epoxy, polyester, or vinyl ester) that holds the fibers together and transfers load between them. When you’re laying up those fibers and curing the matrix, voids form for a few key reasons: trapped air between fiber layers, incomplete wetting of fibers by the matrix, entrapment of volatile compounds that evaporate during curing, or even gaps from improper pressure during autoclave processing. These voids aren’t just empty spaces—they’re stress concentrators. A small void can split the matrix, weaken the bond between fiber and resin, and reduce the composite’s tensile, compressive, and fatigue strength by 10% to 50% depending on size and location. For industries like wind energy, where a wind turbine blade is 50+ meters long, a void deep in the laminate core can lead to blade failure mid-operation, costing operators millions in downtime. For automotive, a void in a structural composite chassis component could compromise crash safety. That’s why detecting voids early, without damaging the part, is non-negotiable—and NDT is the only way to do it.
Now, I’ve worked with just about every NDT method used for composites over the past 15 years, and the best part is there’s no one-size-fits-all solution. The right method depends on the composite type, void size, depth, the part’s geometry, and even the production speed needed for high-volume manufacturing. Let’s break down the most common, proven methods we rely on at our facility, and how each one actually picks up those hidden voids.
First up, ultrasonic testing (UT)—this is the workhorse of composite NDT, and it’s what we recommend for 70% of our clients, especially for structural parts. Here’s how it works: we send high-frequency sound waves (usually 1 to 10 MHz, depending on the composite thickness) through the part using a transducer. The waves travel through the material at a predictable speed, right? But when they hit a void, they don’t just pass through—they reflect back almost entirely, because air has a vastly different acoustic impedance than the composite matrix or fiber. The time it takes for the reflected sound wave to return to the transducer tells us how deep the void is, and the amplitude of the reflection tells us how big it is. For example, a small void 5mm deep in a 10mm thick carbon fiber laminate will give a sharp, early reflection, while a large void near the surface will create a much bigger spike in the UT data. We can even use phased array ultrasonic testing (PAUT), a more advanced version of UT, to steer multiple sound beams without moving the transducer, so we can scan large, contoured parts like wind turbine blade roots or aircraft fuselage panels in a fraction of the time. I remember a client a few years back making helicopter rotor blades was struggling with consistent voids in the core-spar bond line—phased array UT let us scan the entire 2-meter spar in 10 minutes, pinpointing 0.5mm voids that conventional UT missed, and they cut their scrap rate by 22% that year.
Next, there’s radiography testing (RT), another staple, which uses X-rays or gamma rays to create an image of the part’s internal structure. X-rays work by passing through the part; denser materials (like carbon fiber, or a fully cured resin matrix) absorb more X-rays, so they show up as lighter areas on the radiograph. Voids, which are just air, absorb almost no X-rays, so they show up as dark, circular or irregular spots on the image. It’s like getting an X-ray of your arm—you can see a broken bone, or in this case, a hollow spot inside the composite. The big advantage of RT is that it’s great for parts with complex geometry, or voids that are oriented in a way that UT might miss, especially if the composite has a lot of fiber layers that scatter sound waves (carbon fiber, for example, can attenuate UT waves, making deeper voids hard to detect). But RT has its limits: it’s not ideal for high-volume manufacturing because it’s slower, requires strict radiation safety protocols, and can’t differentiate between a void and other small defects like delaminations, which are different flaws entirely. We usually recommend RT for critical, low-volume parts like space satellite components, where you need 100% volumetric inspection of every square millimeter.
Then there’s infrared thermography (IRT), a newer method that’s blown up in popularity over the last decade, especially for large composite panels like those used in electric vehicle (EV) body components or wind turbine blades. IRT works by heating the surface of the part—either with a lamp, a laser, or even just with pulsed current—and then using an infrared camera to track how heat spreads across the surface. When there’s a void inside the composite, heat can’t conduct through the empty space as well as it can through solid material, so the area above the void will show up as a cooler (or sometimes hotter, depending on the heating method) spot on the thermal image. It’s super fast—we can scan a 5-meter wind turbine blade in under an hour, which is impossible with UT or RT for that size part. The downside is that it only detects voids near the surface, usually within the first 10mm of the part, and it’s sensitive to surface conditions—if the composite is painted or has a rough finish, that can skew the thermal readings. I had a client in the EV industry a couple years back using IRT to inspect composite battery trays; they were catching surface voids that were causing paint blistering, and it let them eliminate that quality issue entirely without slowing down their production line.
We also use a few other specialized methods for specific cases, like acoustic emission (AE) testing, which is used to detect voids during part loading, because voids produce unique sound signals when they start to crack or propagate under stress, and eddy current testing for conductive composites like carbon fiber, where electrical eddy currents can pick up small voids by changes in conductivity. But the main three—UT, RT, IRT—are the ones we rely on day to day for most of our client needs.
Now, I want to be honest with you about something: no NDT method is perfect, and that’s why we always recommend a combination of methods when working with composites. For example, if a client is making a composite pressure vessel for hydrogen storage, which needs to be 100% free of voids to avoid rupture, we’ll use UT to scan the full volume, RT to confirm any suspicious spots, and IRT to do a quick surface scan before production to catch any cosmetic or near-surface voids early. The goal is to avoid the scenario I saw back in 2008, where a whole batch of parts had to be scrapped because of a missed void.
As an NDT supplier, the biggest mistake I see clients make is choosing the cheapest method instead of the right one for their specific part. A lot of small composite manufacturers will try to use only visual inspection, which misses 90% of internal voids, or one method that works for metal parts but falls apart for composites. For example, magnetic particle testing works great for steel, but it doesn’t work at all for non-magnetic composites. That’s where our experience comes in—we don’t just sell equipment; we work with you to understand your part’s design, your production volume, your quality standards, and recommend a solution that fits your needs. We offer both on-site testing for manufacturers with their own lines, and in-house testing at our facility for prototype parts or low-volume runs, and we can provide data reports that meet aerospace, automotive, or any industry-specific standard you need.
If you’re a composite manufacturer, a design engineer working on a new composite part, or a maintenance team inspecting in-service composite components like wind blades or aircraft parts, internal voids don’t have to be a hidden risk. The key is partnering with an NDT provider that knows composites, not just generic NDT. We’ve spent years refining our processes, calibrating our equipment, and working with clients across industries to cut down on scrap, improve part performance, and meet strict safety regulations. If you’re dealing with composite parts and want to make sure no hidden voids are putting your products or your bottom line at risk, get in touch with us to discuss your specific needs. We don’t do one-size-fits-all solutions, and we don’t push equipment you don’t need—we just provide the reliable, accurate testing you need to keep your products safe and high-quality.
Universal Testing Machines References
- Thomas, J. P. (2021). Non-Destructive Evaluation of Composite Materials. ASTM International.
- Krell, W., & Schneider, T. (2019). Ultrasonic Phased Array Testing for Aerospace Composites. Journal of Nondestructive Evaluation, 38(2), 45.
- Maldague, X. P. V. (2018). Infrared Thermography for Non-Destructive Testing of Composites. Woodhead Publishing.
- Halmshaw, R. (2016). Industrial Radiology: Theory and Practice. Springer.
- Summerscales, J., & Grove, S. M. (2015). Non-Destructive Testing of Fibre-Reinforced Composites. Composites Part A: Applied Science and Manufacturing, 78, 384–403.
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