Austria | Germany | France | Sweden | India | USA | China | Singapore
6 Tips for Stress-free Strain Measurement during Fatigue Testing of Aircraft Structures
Tips & Trends | 4 minutes Reading Time |

6 Tips for Stress-free Strain Measurement during Fatigue Testing of Aircraft Structures

Strain is the single most important measurement during aircraft fatigue testing. The accuracy and precision of strain gauge measurements is of the greatest importance to exactly determine the durability and damage tolerance of a structure. The higher a structure is in the ‘pyramid of test’, the higher the test complexity, number of measurement channels, and data produced. On top of that the risk in terms of time delay and cost associated to a test program increases more than proportional with the increase in test complexity. Here are six tips to help you choose the right data acquisition system for your fatigue test:

1.    Measure Strain, not Temperature

Fatigue tests can run for several weeks up to several months. Often during day and night. Variations in ambient temperature are amongst the most common causes of measurement error when using quarter-bridge strain gauges. A temperature-related resistance change as small as 0.1 % could result in an elongation of 500 µm/m. Because you want to avoid that your strain measurement turns into a temperature measurement, Gantner Instruments recommends paying special attention to the stability of the internal completion resistor. All too often low stability resistors are used to save cost. This either results in unwanted errors or forcing you to program complex temperature correction curves in software.

The Q.series data acquisition system comes with internal completion resistors that have a Temperature Coefficient of Resistance (TCR) of 0.05 ppm/K. A temperature drift of 10 K will result in a measurement error of only 0.025 %. Using a resistor with a higher TCR will increase the error accordingly. For example, a TCR of 0.5 ppm/K will result in a substantial measurement error of 0.25 %.

2.    No Measurement Error with long Cable Runs

Due to the size of the test specimen, long cables runs are sometimes unavoidable. The resistance of bridge wires that connect a gauge into a Wheatstone bridge attenuates the bridge output, or “desensitizes” the gauge. As the attenuation is a function of the length of the bridge wires, it will have greater effect with increasing cable length. With traditional instrumentation, a manual shunt calibration process must be performed prior to starting the measurement. The shunt calibration process determines the lead wire resistance and subsequent correction factor. Although widely applied, this method does not compensate for changes in lead wire resistance during the actual measurement, for example due to ambient temperature fluctuations.

The Q.series data acquisition system features an OCS (Online Compensation Signal) reference stage that automatically corrects for measurement errors due to lead wire resistance, even during the measurement itself. No need for manual shunt calibration and thus also eliminating operator errors.

3.    Eliminate Data Skew

Data skew in a multi-channel, distributed data acquisition system is one of those major uncertainties during a test program. Aircraft test articles are extremely expensive. So, when a failure occurs, measurement data is analyzed closely to understand precisely the test article’s failure characteristics. If the measurement data is not tightly synchronized it can bring ambiguity into the analysis. Especially with high-channel count systems the jitter from channel to channel can lead to significant errors. A jitter of only 500 µs will result in a measurement error of 0.6% at 2 Hz cycle frequency.

The Q.series data acquisition system has a built-in, hardware-based synchronization between the modules. No need for additional sync cables between measurement modules or racks. Even when the system is distributed over long distances we ensure precise time synchronization with a maximum jitter of 1 µs. If you see a phase shift, you can rule out time synchronization as the problem. There is no ambiguity.

4.    Keep your Data available when you need it most

It is a test engineer’s worst nightmare – the loss of measurement data due to accidental overwrite or deletion, database corruption, or even IT infrastructure failures. Because data is the heart of a test program, it’s the task of the test engineer to implement a data backup and recovery plan. Using multiple parallel data storage paths your data is automatically replicated or triplicated in real time, ensuring continuous data availability.

To be really certain that you do not miss a single sample, our Q.series system has 3 levels of redundancy for assured data availability. Measurement data can be broadcasted in parallel to an online database as well as to an FTP backup server. Both data ports are continuously monitored. If a broadcast fails, the Q.series system will automatically start logging data to its local disk.

5.    Avoid Data Overload

Typically fatigue test campaigns go on for months, if not years. Data is collected from 1000 or more strain gauges. Sample rates might vary from 25 Hz to 5000 Hz for failure analysis. Terabytes of measurement data is recorded. Recent analysis has shown that close to 40% of the recorded data has no significant relevance, but is stored because of the limitation of the data acquisition system. Having too much data slows down data processing, analysis and decision-making. This is valuable time, especially when you are under pressure of completing an unexpected failure analysis.

The Q.series allows you to create up to 20 data loggers. Each data loggers can be configured to record a different data set at a different logging rate. You can choose between different logger types, either continuoustriggered or event-based logging. For example, a supervisory control system can be used to trigger a logging action with a pre- and post-trigger time. In parallel it is possible to configure a logger that continuously records data to a circular data buffer. File name, size, destination, and protection level are fully configurable for each data logger.

6.    Reliable Interoperability

Without interoperability lights will not work with the switches, sensors cannot be read by your measurement system, and test equipment cannot use the networks around them. The times of monolithic systems supplied by one vendor are over. A wide variety of different control and measurement techniques are used today. Safe and reliable interoperability between specialized test and measurement devices is vital for test lab efficiency. For example, the ability to predict or quickly detect structural failures with data collected from various systems is of major importance during a test program. Reliable interoperability between test and measurement systems is vital for direct processing, analyzing and reporting of test data.

The Q.series data acquisition system supports various fieldbus standards, software protocols and stream processing platforms. Drivers are available to integrate the Q.series DAQ system with commonly used software tools, like LabVIEW™, MATLAB® and DIAdem®. The Q.series system comes with a Plugin Management System that allows for creating and deploying custom communication protocols and device drivers, for example to implement custom interfaces to a servo control system. In addition, various external time sources are supported, like IRIG-B, that can be used to accurately synchronize with ancillary systems, like a high-speed camera.

6 Tips for Stress-free Strain Measurement during Fatigue Testing of Aircraft Structures

More articles

Success Stories

SEDS Colossus Static Fire System Test Stand Unveiling

The SEDS-Students for the Exploration and Development of Space-organization at the University of California San Diego, recently held a launch gathering to unveil the final design and build of their Colossus static fire system test stand.

Tips & Trends

Long term Volcano Monitoring – A field study

Monitoring volcano activity is an important issue in the mitigation of natural hazards. Recently, most fatal issues occurred on volcanoes with low-energy and moderate activity, making them attractive touristic places (e.g., the 2014 Mount Ontake eruption in Japan). For these types of volcanoes, monitoring involves multiphysics measurements on dense networks. Distributed networks of sensors must be easily adapted to the volcano’s evolving state and the appearance of new active areas like fumaroles or high heat flux in the soil.

News & Events presents Gantner Edge computing devices and at InteractiveWest

Our Edge computing devices and our new was presented by our partners Christian Lutz and Jodok Batlogg (founders of

News & Events

Cloud-based Railway Bridge Monitoring with Solar Powered Q.series DAQ

For a large railway operator, Gantner Instruments continuously monitors a railway bridge using displacement transducers to detect deflection in bridge support elements.