Researchers with the US Army Research Laboratory (ARL) and the US Army Aviation and Missile Research, Development and Engineering Center (AMRDEC) have developed and tested networked acoustic emission (AE) sensors capable of detecting airframe damage on conceptual composite UH-60 Black Hawk rotorcraft.
The discovery provides an opening for onboard features capable of alerting flight crew to the state of structural damage, such as matrix cracking and delamination, as they occur. This will give crew a greater opportunity to take corrective actions before failure ensues.
Alternative rotorcraft airframe health monitoring has been the subject of study by ARL for almost two years. This makes a strong case for integrated real-time damage sensing methodologies on future airframe structures. The sensing method can be used to reliably detect and locate the initiation and growth of damage that may occur during service.
“Future Army airframe structures are required to be lighter, safer and ultra-reliable,” said Dr Mulugeta Haile, research aerospace engineer. “To achieve these the army must adopt a combined strategy of implementing advanced structural design methods, improved structural materials and integrated damage sensing and risk prediction capabilities.”
Haile explained that the team turned to acoustic emission tests because other methods such as ultrasonic and radiography require an external energy source in the form of a directed wave: “The external energy has the undesirable effect of interfering with other systems of the aircraft. In addition, other methods are not as good as AE in detecting early damage.”
Acoustic emission sensing detects damage in real time – when it is happening and long before failure. Furthermore, because AE is a passive non-destructive technique for early detection of damage, it does not require an external energy to perform its function. Instead, it relies on the energy that is initiated within the structure, Haile explained.
“The novelty of the current work is that we introduced several new concepts on wave acquisition control and signal processing to recover damage related information in networked acoustic emission sensors,” Haile said.
“The eureka moment was when the sensing network consistently identified and located the initiation and progression of damage during a prolonged fatigue test that lasted over 200,000 cycles – a feat that has never been achieved before.”
The ARL sensing network is composed of several lightweight transducers encapsulated in 3D-printed non-intrusive sensor mounts. Sensors of the network are optimally distributed in multiple zones to maximize coverage as well as probability of damage detection.
The data acquisition process is embedded with a software controllable timing parameter to reject reflections of a direct wave, as well as waves coming from non-damage related events. Meanwhile, the signal processing algorithm is augmented with a layer of adaptive digital filters to minimize effects of signal distortion during location analysis.
November 23, 2017