Wavelet Domain Characterization Localization of Modal Acoustic Emissions inAircraft Aluminum

摘要

As machines age, broadband acoustic emission (AE) signals are emitted fromunknown locations, often due to microscopic material degradation. Not only is the AE source location unknown, but the source mechanism and hence signal characteristics are also unknown. These signals then propagate along multiple, complex geometric paths, in various distorting modes experience mode conversion and wave guide selection, before finally reaching the sensors. In addition to this wave distortion, the signals are corrupted by the noisy and interference-rich environment. If we wish to improve our understanding about the health or state of a mechanical system, we should employ AE analysis methods which can more effectively account for these physical effects. This paper presents a technique for detecting, classifying and localizing these acoustic emissions. Due to the significant uncertainty surrounding these sensed signals, high fidelity, well verified models are uncommon. Starting from wide-band, high-fidelity AE data we have shown that it is possible to determine source location with greater accuracy than is possible by traditional source location techniques. This improvement was achieved by considering the multimode wave nature of the AE events, and by applying wide band signal processing techniques that specifically accounted for the dispersive nature of the signals.