Aircraft structural testing: The challenges and the solutions

Static and fatigue tests are some of the most challenging campaigns that test engineers can run on an aircraft – at least in terms of the scale and complexity of the testing process.
So it’s no wonder that so many test engineers are always on the hunt for ways to optimise this vital stage of the testing process.
So what does it take to do aircraft structural testing as quickly, accurately, and painlessly as possible?
Let’s take a look at the biggest opportunities for optimisation – and how the right technology can help you make the most of them.
 

Static and fatigue testing for the aerospace industry takes time, there’s no way around it.
But when your testing period spans months or years, small daily time savings can make a real difference. Added together, they could mean you get to wrap up testing ahead of schedule – or even just make sure your team gets home on time.
But how can efficient data acquisition (DAQ) technology accelerate static and fatigue testing for aircraft?
The best solutions will:

• Cover all relevant sensor types so you can easily scale up. In static and fatigue testing the most important sensors are strain gauges. However, to conduct a full assessment of the test article, other quantities need to be taken as well, like force, temperature, pressure, and displacement. The perfect data acquisition system is capable of conducting all measurements you need.
• Make it easy to check things are running smoothly while you’re on the move. You shouldn’t have to run back to your computer 50 times a day to check that your sensors are working as they should. The best solutions allow you to verify functionality through an app on a phone or tablet, so you can easily check that you’re collecting the data you need.
• Parameterise sensors automatically through transducer electronic data sheets (TEDS) or similar technologies, rather than forcing you to manually transfer values from the sensor data sheet or calibration certificate into your software. This saves time, but also reduces the chances that typos or other forms of human error will interfere with the accuracy of your data.
• Optimise interfaces and the overall user experience of the DAQ system to make data collection as smooth and easy as possible. If you get to test the hardware and software before you buy, think about how easy it will be to use it on a daily basis. Does it have a dark and a light mode, since you’ll probably be using it for long periods of the day and night? Does it use easily understandable error messages to help you get to the source of the problem fast when something goes wrong? These small touches can make a big difference.
• Allow you to adapt the software interface and automate key actions with custom Python scripts, so you can extend the software functionality to your team’s needs and processes.
  

Understanding the impact of fatigue on an aircraft means integrating data collected from a huge number of sources.
And if you want a complete and useful picture of the aircraft’s durability, you’ll need every one of those data sources to be perfectly synchronised, so you can easily track how the aircraft responds to your stimuli over time.
That means perfectly synchronising data from hundreds – or even thousands – of strain gauges. Plus there’s all the data that test engineers now glean from techniques like digital or thermal image correlation. To get the most accurate picture, you’ll want this synchronisation to be accurate to within a millisecond, at the very least.
The challenge is that running these tests means using equipment from a potentially huge range of vendors, all of whom might have different standards for synchronising data. Not to mention the amount of time and stress involved in running around constantly checking that your sensors are aligned.
The best DAQ solutions can remove this stress almost entirely, making it easy to synchronise data points across a wide range of data sources. They’ll help by:

• Making it easy to integrate external data sources with your DAQ system. Look for a solution that is open for data from the sources you use most often, easily matching up, for example, sensor readings with digital images so you can see exactly what was happening when the reading was taken.
• Allowing you to feed data seamlessly into simulation software, so you can update your aircraft’s FEM, validate numerical models, and pass insights on to other members of your team with ease.
   

When this much time, money, and effort has gone into building a prototype and conducting testing, you can’t afford to doubt the accuracy of your data or the reliability of your DAQ solution. Not to mention that, at the end of all this testing, the safety of future passengers is on the line.
So it’s no wonder that reliability is one of the biggest things that test engineers worry about when it comes to choosing a DAQ solution.

You want something that you can plug in, switch on, and trust to run smoothly until your tests are finished. But the best DAQ solutions don’t just make your static and fatigue tests more accurate – they go above and beyond to make sure your data is collected accurately and easily, and stored securely.

The best solutions will offer: 

• Robust, reliable sensors, built with high-quality components, so you can rely on them to collect accurate values under almost any circumstance. These sensors won’t be affected by temperature or other environmental influences, giving you more accurate results and making it easier to replicate the results of earlier tests.
• A good balance between accuracy, speed, and cost. More accuracy often means more expensive hardware and slower testing, so it’s important to choose a level of accuracy that’s appropriate for the test you’re running. A test in the wind tunnel with a scaled model, for example, requires much higher accuracy than a fatigue test. Look for a DAQ solution that’s built with static and fatigue testing in mind, so you can collect data at the accuracy that you need, without slowing down testing or blowing your budget unnecessarily.
• Redundancies and fail-safes – No one likes losing data, but missing values or sensor failures can be particularly catastrophic in this kind of aircraft testing. Look for a solution that offers two forms of data recall – one from your hardware and one from your software – so that you can more easily extract your data if something goes wrong. Make sure you check how the hardware is networked too – avoid solutions with a single point of failure, where one failing cable can bring down all of your other hardware.