{'fraction_non_alphanumeric': 0.02243211334120425, 'fraction_numerical': 0.0023612750885478157, 'mean_word_length': 5.057142857142857, '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}}
Novel TQWT Algorithm for Structural Damage Identification

In this paper tunable Q-factor wavelet transform is implemented into damage identification. Fixed – Fixed beam damage identification problem is demonstrated. Translation and Rotational mode shapes are used as an input signal, the TQWT algorithm depends Q-factor and asymptotic redundancy, when it matches with the oscillatory behavior of the input signal it is tuned. This method decomposes a signal into a high-Q-factor and low-Q-factor component, and it can be used to differentiate the damaged and undamaged mode shapes of the beam structure. TQWT coefficient is used as damage index to locate and quantify the damage. Proposed method evaluated experimentally and results shows TQWT algorithm has a potential to detect even a small damage (10% stiffness loss) present in the structure.