Embedded Shape Memory Alloy Particles for the Self-Sensing of Fatigue Crack Growth in an Aluminum Alloy

Future aerospace vehicles will be built using novel materials for mission conditions that are difficult to replicate in a laboratory. Structural health monitoring and condition-based maintenance will be critical to ensure the reliability of such vehicles. A multi-functional aluminum alloy containing embedded shape memory alloy (SMA) particles to detect fatigue crack growth is proposed. The regions of intensified strain near the tip of a growing fatigue crack cause the SMA particles to undergo a solid-to-solid phase transformation from austenite to martensite, releasing a detectable and identifiable acoustic emission (AE) signal that can be used to locate the crack in the affected component.;This study investigates the AE response of two SMA systems, Ni-Ti, and Co-Ni-Al. Tensile (Ni-Ti) and compressive (Co-Ni-Al) tests were conducted to study the strain-induced transformation response in both of the alloy systems. It was found that the critical stress for transformation in both SMA systems was easily identified by a burst of AE activity during both transformation and reverse transformation. AE signals from these experiments were collected for use as training data for a Bayesian classifier to be used to identify transformation signals in a Al7050 matrix with embedded SMA particles.;The Al/SMA composite was made by vacuum hot pressing SMA powder between aluminum plates. The effect of hot pressing temperature and subsequent heat treatments (solutionizing and peak aging) on the SMA particles was studied. It was found that, at the temperatures required, Co-Ni-Al developed a second phase that restricted the transformation from austenite to martensite, thus rendering it ineffective as a candidate for the embedded particles. Conversely, Ni-Ti did survive the embedding process and it was found that the solutionizing heat treatment applied after hot pressing was the main driver in determining the final transformation temperatures for the Ni-Ti particles. The effect of hot pressing on the transformation temperatures was negated upon solutionizing and peak aging occurred at a sufficiently low temperature to as not affect the properties of the Ni-Ti.;Strain-induced transformation was confirmed in the Ni-Ti particles by digital image correlation (DIC) using an environmental scanning electron microscope (ESEM). Specimens were fatigue pre-cracked until a crack was produced and observed to be approaching a particle that could be monitored on the surface, at which point it was put into the ESEM for DIC under tensile loading. Acoustic emission activity was observed during this experiment. In order to distinguish AE signals arising due to phase transformation in the particles from those due to crack extension in the matrix, a Bayesian classifier was constructed based on frequency parameters calculated using the Hilbert-Huang transform (HHT). Using this classifier, AE signals consistent with those arising from phase transformation in bulk Ni-Ti were identified during phase transformation in the particles as observed with DIC.;In addition to tensile crack growth in the ESEM, a fatigue crack was grown through a specimen with particles interspersed along the specimen center line. Several low amplitude AE events were observed as the crack grew through the aluminum. As the fatigue crack passed through the line of particles AE events increased dramatically in rate of occurance and amplitude. Amplitudes were 6-10 times higher as the crack passed near the particles. These AE events were also shown to be consistent with Ni-Ti phase transformation.;A successful proof-of-concept was demonstrated for an aluminum alloy with embedded particles that emit an identifiable and repeatable AE signal in the presence of a fatigue crack, allowing for quick diagnosis of fatigue crack damage in this material.