{'fraction_non_alphanumeric': 0.012422360248447204, 'fraction_numerical': 0.0, 'mean_word_length': 5.159235668789809, '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 Health Monitoring Using the Hilbert-Huang Transform and Beating

In this paper, a combined approach to damage diagnosis of systems is proposed. The intention is to identify the natural frequencies and the presence of damage. In a first step, the basic concept of the Hilbert Huang Transform is presented where the empirical mode decomposition is applied on the signal using a sifting process to obtain intrinsic mode functions exhibiting monocomponent behavior. In the next step, the Hilbert Transform is used to identify the frequencies from the well behaved intrinsic mode functions. Finally, a time domain approach known as beating phenomenon is used to calculate the shift in frequencies and also the presence of damage. Simulations are done on linear and nonlinear structures. Results demonstrate that the proposed methods provide a new and useful tool for damage detection and evaluation of structures especially when the frequency shift is minimal.