{'fraction_non_alphanumeric': 0.017964071856287425, 'fraction_numerical': 0.0026613439787092482, 'mean_word_length': 5.345991561181434, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Structural damage assessment with antiresonances versus mode shapes using parallel genetic algorithms

Antiresonances have become an attractive alternative in structural damage assessment. They can be identified easier and more accurately than mode shapes, and still providing the same information. Antiresonances are derived from point frequency response functions (FRFs) or from transfer FRFs. However, antiresonances from transfer FRFs are very sensitive to small structural changes, and the matching between numerical and experimental antiresonances is affected. This problem is solved if antiresonances from point FRFs are used. However, it implies an experimental procedure that differs from a common modal testing, which may become not practical or too expensive. This paper proposes a damage detection method able to deal with transfer antiresonances. The inverse problem is handled by a Parallel Genetic Algorithm. In this case, a perfect match between the antiresonances is not required because the optimization is not gradient based. Moreover, the matching can change at each step and the optimization is not affected. The algorithm is verified with two experimental cases: an exhaust system of a car with a single fatigue crack and a tridimensional space frame structure with single and multiple damage scenarios. Results are compared with the ones obtained using mode shapes. Damage detected is consistent with the experimental damage in both cases. Copyright © 2010 John Wiley & Sons, Ltd.