- Laser Sensor Can Detect Damage to Military Assets
WASHINGTON, D.C., Aug. 31, 2016 — A distributed feedback fiber laser sensor has detected acoustic emission signatures associated with cracks in riveted lap joints, demonstrating that it has the potential to uncover structural damage in U.S. Navy assets before the damage reaches critical levels.
Developed by researchers at the U.S. Naval Research Laboratory (NRL), the laser sensor consists of a single fiber, similar in width to a human hair, which is integrated into a shallow groove formed in the lap joint. The sensor has a small system footprint and can be multiplexed.
Crack detection in riveted lap joints with fiber laser acoustic emission sensors: The initiation and growth of cracks between rivets in a lap joint is shown at top left. A fiber laser sensor, at top right, adhered to the structures, measures the acoustic emission signals generated by the cracks, and software records them as acoustic events (AE). A typical AE is shown at lower right. The amplitude of the AEs as a function of time is shown at lower left. Large increases in AE amplitude are seen when the cracks grow. Courtesy of U.S. Naval Research Laboratory.
To test the technology, researchers installed the laser sensors into a series of riveted aluminum lap joints and measured acoustic emission over a bandwidth of 0.5 MHz generated during a two-hour accelerated fatigue test. They took equivalent measurements with an electrical sensor.
The embedded laser sensors demonstrated acoustic sensitivity comparable to or greater than that achieved by existing electrical sensors. The laser sensors were able to detect low-level acoustic events generated by periodic fretting from the riveted joint, in addition to acoustic emissions from crack formation. Time-lapse imagery of the lap joint revealed that the observed fracture correlated with the signals measured. In addition to crack detection, the fiber laser sensor also showed the ability to measure compromising impacts.
“Our research team has demonstrated the ability of this fiber laser technology to detect acoustic emission at ultrasonic frequencies from cracks generated in a simulated fatigue environment,” said Geoffrey Cranch, research physicist. “The novel part of this work is the fiber laser technology and how it is being applied.”
Acoustic signals from cracks can also be measured using piezoelectric sensors, and this technology has driven the existing work on failure prediction. However, the piezoelectric technology is not practical for many applications due to its large size and limited multiplexing capability.
The fiber laser sensor system has now been expanded to multiplex many sensors onto a single fiber. Efforts are underway to interpret the acoustic emission data to calculate metrics such as probability of failure. Future enhancements may include implementing phased array beam forming techniques to facilitate crack location.
The fiber laser sensor also has the potential to integrate with existing fiber optic strain and temperature sensing systems. Integrating the sensor with these systems would provide a multiparameter sensing capability that could meet the operational safety requirements for an SHM system at significantly lower cost.
“An automated, in-situ structural health monitoring (SHM) system, capable of monitoring key structural parameters such as temperature, strain, impacts and cracks, and capable of reliably detecting damage well before reaching a critical level is needed to increase safety and readiness while lowering operational cost of Navy platforms” said Cranch. “At present, none of the services are using in-situ technologies to manage the structural health of their assets.”
Cranch added that the laser sensor technology may have possible applications beyond the military.
“Our focus is on Navy platforms, such as aircraft, ships and submarines, but the technology could also be used on civilian aircraft,” he said. “Applications to bridges and buildings are also possible if there are critical parts prone to fatigue and failure that would benefit from continuous monitoring.”
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