Fatigue crack growth during the service of aging aircrafts has become an important issue and the monitoring of such cracks in hot spots is desirable. A structural health monitoring system using an acoustic emission technique under development for monitoring safety of such structures is described in this paper. A “continuous sensor” formed by connecting multiple sensor nodes in series arrangement to form a single channel sensor is proposed to monitor acoustic emission signals. This paper describes the work in progress on developing sensors, instrumentation, and measurement technique applicable to on-board monitoring of fatigue cracks in 7075-T6 aluminum lap joints. The traditional AE sensors as well as bonded nodes of continuous sensors described above were used to monitor acoustic emission signals emanating from crack growth in aluminum 7075 T6 specimens. It was possible to differentiate the signals due to crack growth from noise signals arising from fretting as well as RF pickup. The sensitivity of the bonded sensor under development was comparable to commercial high sensitivity resonant frequency AE sensors. The relationship between acoustic emission parameters and the crack growth rate in the aluminum specimens is examined.
Since today's aging fleet is intended to far exceed their proposed design life, monitoring the structural integrity of those aircraft has become a priority issue for today's Air Force. One of the most critical structural problems is corrosion. In fact the KC-135 now costs $1.2 billion a year to repair corrosion. In this paper, we plan to show the use of Lamb waves to detect material loss in thin plates representative of aircraft skins. To do this we will use embedded transducers called Piezoelectric Wafer Active Sensor (PWAS) in a pitch-catch configuration. The sensors were placed on a grid pattern. Material loss through corrosion was simulated by removing the material mechanically with an abrasive tool. Thus, simulated corrosion pits of various depths and area coverage were made. Three-count tone burst wave packets were used. The Lamb wave packets were sent in a pitch-catch mode from one transmitter PWAS to the other PWAS in the grid acting as receivers. The Lamb wave mode used in these experiments was A1, since this was found to be more sensitive to changes due to material loss. At the frequencies considered in our experiments, the A1 waves are highly dispersive. It was found that, as the Lamb wave travels through simulated corrosion damage, the signal changes. The observed changes were in the signal wavelength (due to change in the dispersive properties of the medium) and in signal amplitude (due to redistribution of energy in the wave packet). This change in signal can be correlated to the magnitude of damage. To achieve this, we have used several approaches: (a) direct correlation between the sent and the received signals; (b) wavelet transform of the signal followed by correlation of the wavelet coefficients time-frequency maps; (c) Hilbert transform of the signal to produce the signal envelope and comparison of the resulting envelope signals (d) neural network correlation between the sent and received signals. It was found that these methods work well together in a complementary way.